Volume 14 Issue 8

This review paper explores the critical aspects of pre-processing, feature extraction, feature selection, and classification in fake news detection on Twitter. Pre-processing involves cleaning text data by removing unwanted elements and normalizing the text. Feature extraction transforms raw text into analysable formats, identifying significant aspects to distinguish between fake and real news. Feature selection focuses on identifying relevant features to reduce dimensionality and noise. Various classification techniques are evaluated for their effectiveness, demonstrating the potential of machine learning in achieving high accuracy. The paper also examines Twitter's role in rapid information dissemination and the challenges posed by fake news. It reviews content-based methods like text analysis, user-based methods such as behaviour and network analysis, hybrid methods integrating multiple features, and the use of external knowledge through fact-checking and knowledge graphs. Addressing the challenges of high information volume, rapid spread, and evasion techniques, the paper concludes that effective fake news detection on Twitter requires advanced analytical techniques and real-time monitoring to manage and mitigate misinformation.

The manufacture of ordinary Portland cement produces a lot of CO2s in the atmosphere. The production of cement emits approximately 5% of worlds carbon. Carbon dioxide emissions from the cement industry are a major environmental concern, which is increasing day by day searching for an alternative replacement for cement has become very important. Self-compacting concrete (SCC) offers advantages in complex formwork and congested reinforcement, but its reliance on Portland cement raises environmental concerns. Geopolymer concrete is an eco-friendly construction material that utilizes industrial by-products such as fly ash, ground granulated blast furnace slag, rice husk ash, and metakaolin as binders. Recycling these waste materials for construction offers a sustainable solution to environmental concerns and presents a cost-effective building alternative. This review explores the potential of integrating the self-compacting properties of SCC with the sustainability of GPC by using slag sand as a fine aggregate. It examines key aspects such as workability, mechanical strength, durability, and microstructure of SCC-GPC incorporating slag sand. Additionally, it highlights the challenges, existing research gaps, and future research directions in this area. Developing new construction materials from industrial waste contributes to a more sustainable future by providing an environmentally friendly and resource-efficient alternative in the construction industry. The literature on geopolymer concrete which is based various industrial wastes such as fly ash, copper slag etc… replaced by natural resource in geopolymer concrete This study provides a review of research era in the field of Self compacting Geo polymer concrete

This study examines the underperformance of local construction contractors in Monrovia, Liberia, identifying critical factors and proposing solutions to enhance their operational effectiveness. It addresses the preference of clients for international firms due to dissatisfaction with local contractors. A mixed-methods approach was used, incorporating interviews with industry professionals and quantitative analysis using the Relative Importance Index (RII) to rank performance criteria. Questionnaires, employing a modified Likert scale, were distributed to 40 respondents, including employees, contractors, managers, engineers, and clients. Data were analyzed using RII and Pareto analysis. Key factors negatively affecting the work quality of local contractors include bribery and corruption, a lack of collaboration between designers and contractors, and inadequate monitoring and feedback. Significant issues involve poor project management, mismanagement of funds, inadequate equipment, limited access to finance, intense competition from international firms, and political influences. Pareto analysis highlighted underestimation, late delivery, scope mismanagement, and lack of operational funds as key influencers of performance. Limited to Liberian-owned construction companies in Monrovia, findings may have limited generalizability. However, it provides a framework for understanding challenges faced by local contractors in similar developing countries. Recommendations include enhancing project management practices, fostering better communication, improving access to finance and technology, and promoting transparency and meritocracy in contract awards. The study suggests implementing Total Quality Management (TQM) to enhance organizational performance. This research provides valuable insights into the specific challenges faced by local Liberian contractors, offering a comprehensive analysis and actionable solutions that contribute to the advancement of construction management knowledge in developing countries.

Abstract: Innovation management in multinational organizations requires navigating complex cultural landscapes to foster creativity, collaboration, and competitive advantage. This research explores cross-cultural perspectives on innovation management, emphasizing how cultural values, norms, and practices influence innovation processes in global firms. Drawing on a comprehensive review of literature, the study examines the interplay between cultural dimensions—such as individualism, power distance, and uncertainty avoidance—and innovation outcomes. It highlights strategies for aligning diverse cultural frameworks with organizational goals to enhance innovation performance. The discussion integrates empirical data, including tables and graphs, to illustrate cultural impacts on innovation metrics like patent filings and R&D investment. Findings suggest that culturally sensitive leadership, adaptive knowledge management, and inclusive team structures are critical for success. The study concludes that multinational organizations must prioritize cultural competence to optimize innovation, offering suggestions for implementing cross-cultural training, leveraging digital tools for collaboration, and fostering open innovation ecosystems. By addressing cultural barriers and capitalizing on diversity, organizations can unlock innovation potential in global markets. This research contributes to the growing discourse on managing innovation in culturally diverse settings, providing actionable insights for practitioners and scholars.

Abstrak : River in Indonesia has suffered a high pollution, it might cause the river has dirty and dark color. Pollutants are come from industrial, agriculture, and house hold waste, particularly for unmanageble municipal solid waste (MSW) enter into the river bodies. Water quality modeling has been used as a support tool for water resources management. The Streeter-Phelps equations are used to solve the algorithm  of  river water quality simulation. The equations were solved using matlab pragramme.  Organic pollutant is called biological oxygen demand (BOD) or chemical oxygen demand (COD). Naturally, rivers are able to neutralize BOD it’s self, because of the activities of microorganisms in body river. Equilibrium concentration between  DO and BOD is  very important to make the degradation reaction continue along the  river bodies. Interaction between DO and BOD is one of  the indicator  of quality of river water.

Abstract— Urban economic progress is increasingly dominated by the coming together of smart technologies and automation. This research investigates the degree to which automation has contributed towards triggering economic changes in three of India's smart cities: Sambhajinagar, Pune, and Nagpur. From a reading of pathfinder projects, techno-innovation, and socio-economic effects, this research establishes the relationship between green urban development and automation. The study highlights the optimism of automation to raise efficiency, promote innovation, and stimulate inclusive growth overcoming hurdles like job displacement and infrastructure readiness.

Abstract: The growing prevalence of mental health issues underscores the need for innovative and effective monitoring systems. Traditional approaches to mental health assessment often rely on self-reported data and clinical evaluations, which can be limited in scope and frequency. Recent advancements in machine learning offer promising alternatives for real-time, scalable, and objective mental health monitoring. Among these advancements, text-based analysis using sentiment analysis and emotion detection has emerged as a powerful tool for understanding and managing mental health. Despite significant progress in sentiment analysis, existing models frequently encounter limitations in addressing the complex and nuanced nature of emotional expression across diverse cultural contexts. Standard models often fail to capture the full spectrum of emotional experiences due to their limited cultural adaptability and inability to handle dynamic emotional states effectively. Natural Language Processing (NLP) refers to a collection of methods for identifying, reading, extracting and untimely transforming large collections of language. In this work, we aim to give an overview of how NLP has successfully been applied thus far in Mental Health Monitoring system. We conduct a literature search on PubMed, Scopus Web of Science and Google Scholar for scientific articles published between 2007and 2024. We use both quantitative and qualitative methods to screen papers and provide insights into the inclusion and exclusion criteria. We outline our approach for article selection and provide an overview of our findings. This is followed by a more detailed insight into selected article. Overall, 2000 articles were screened for the suitability of this review, where we review 69 articles in depth. Finally, we discuss future avenues of research and outline challenges in existing work.

Abstract: In an increasingly competitive global marketplace, the agricultural sector faces significant challenges in differentiating its products and capturing consumer attention. Branding, traditionally associated with manufactured goods, is gaining prominence as a crucial strategy for agricultural producers and distributors. This paper explores the evolving role of branding in agricultural products, examining its impact at various stages of the supply chain, from the farm to the retail shelf. We delve into the benefits of branding, including price premiums, enhanced consumer trust, and improved market access. Furthermore, we analyze the challenges associated with building strong agricultural brands, considering factors such as product variability, traceability, and the need for authentic storytelling. Finally, we discuss strategies for successful branding in the agricultural sector, emphasizing the importance of quality assurance, provenance, sustainability, and effective communication.

Abstract: The increasing global demand for energy, coupled with inefficient waste management practices, presents significant environmental and sustainability challenges, particularly in developing countries. This study addresses these issues by investigating the production, characterization, and optimization of fuel nuggets derived from agricultural waste materials specifically, palm kernel shells (PKS), corn cobs (CC), and plastic straws (PS The methodology involved using a face-centered central composite design (FCCCD) to optimize the blending ratios of PKS, CC, and PS. Fuel nuggets were fabricated through a process of grinding, mixing, and compressing the biomass materials at high pressure and temperature. The experimental data were analyzed using Design-Expert software to develop quadratic models, with statistical validation performed through Analysis of Variance (ANOVA). The results demonstrated that higher proportions of PKS significantly enhanced the calorific value (up to 24.12 MJ/kg), reduced ash content (as low as 0.90%), and increased bulk density (1.63 g/cm³). CC contributed to lowering moisture content (as low as 2.87%) and increasing volatile matter, which improved ignition properties. The optimal blend achieved a combustion efficiency of up to 93.88%. The models showed high reliability, with adjusted R² values above 0.98 across all response variables. In conclusion, the study confirms that fuel nuggets produced from agricultural waste are a viable, sustainable alternative to traditional fossil fuels. These nuggets offer high energy output, low emissions, and significant environmental benefits by reducing agricultural waste and deforestation. It is recommended that future research explore additional biomass materials and assess the commercial scalability of this technology to promote broader adoption in energy-deficient regions Cite this paper as: Egbo Benedict; Momoh, KO; (2025). Characterization and Optimization of Fuel Nugget from Waste Materials

Abstract: 5-Hydroxymethylfurfural (HMF) is a vital renewable organic compound found useful as a platform chemical in bio-refining, polymer precursors and other chemical intermediates. HMF is produced via acid-catalyzed dehydration of diverse carbohydrates. The study aimed to investigate the effect of different acid types: sulphuric (H2SO4), hydrochloric (HCl) and nitric (HNO3), at acid concentrations (0.25-0.75 moldm-3) and time (15-60 minutes) on HMF production. UV-Visible spectrophotometric and high-performance liquid chromatographic (HPLC) were the two analytical techniques employed to evaluate HMF production in all conditions of analysis. It was observed that the catalytic action of the acids towards HMF formation is in the following decreasing trend HCl > HNO3 > H2SO4. The highest HMF produced (0.255 mg/l) was achieved at 0.75 moldm-3 HCl at 60 minutes hydrolysis time. Increasing acid concentration and time was found to increase HMF production with HCl. However, the yield decreased after 45 minutes hydrolysis time for HNO3 and H2SO4 hydrolyzed samples. Therefore, the knowledge obtained from this work will help in designing HMF production process for optimum industrial production.

Abstract— This paper presents an autonomous robot that detects and collects litter in real time. The robot is designed for use in resource-limited urban environments in developing countries. Its main purpose is to automate the process of collecting waste and sorting it for recycling. It is made up of a combination of object detection using a raspberry pi camera module, autonomous navigation with ultrasonic sensors to measure the distance from obstacles, a YOLOv11 model to detect litter in real time and a custom robotic arm to collect the litter and sort it. Test results showed a detection accuracy of 87.87 %, with reliable navigation and collection performance. The system provides a practical and easy to scale solution for improving and supporting waste management in urban areas.

Abstract: Coal and natural gas are the primary fossil fuel sources that currently supply the majority of the world's energy needs. However, the World Energy Forum projects that these fossil-based resources could be depleted in less than a century. Consequently, the development of renewable alternatives to conventional diesel has become increasingly important. These alternatives must be technically feasible, economically and technologically competitive, environmentally acceptable, and readily available. Among the available options, biodiesel stands out as the most viable replacement for petroleum-based diesel fuel. In this study, transesterification was employed to produce biodiesel, as it is considered the most efficient and environmentally friendly method among existing production techniques. The feedstock used was African oil bean seed oil, from which Fatty Acid Methyl Esters (FAME), commonly known as biodiesel, were derived. To optimize biodiesel yield, five key process parameters were considered: Catalyst concentration: 0.775 wt% Methanol-to-oil molar ratio: 6.2:1, Agitation speed: 255 rpm, Reaction temperature: 60°C, Reaction time: 60 seconds At these optimal conditions, the biodiesel yield reached 99.75%. The produced biodiesel was subsequently tested and characterized according to ASTM standards, and all measured properties fell within the specified standard limits.

Abstract: In simple terms, the exchange rate represents the value of one nation’s currency in relation to another. It determines how much of one currency be exchanged for another and plays a crucial role in international trade and finance. Often referred to as the foreign exchange rate or forex rate, it influences economic stability, trade competitiveness, and investment flows between countries. Exchange rates are determined in the forex market, a global marketplace where various participants engage in continuous currency trading, operating 24 hours a day except on weekends. The spot exchange rate represents the current value at which currencies are exchanged. In contrast, the forward exchange rate is an agreed-upon rate set today for a transaction that will be executed on a future date. In both developed and developing nations, various stakeholders such as foreign exchange investors, exporters, importers, banks, businesses, financial institutions, and travelers base their decisions on exchange rate fluctuations. Changes in exchange rates affect the value of international reserves, influence the competitiveness of exports and imports, determines the cost of repaying foreign debts, and impact travel expenses by altering the purchasing power of a currency. Therefore, fluctuations in exchange rates greatly influence the business cycle, trade dynamics, and capital movements within an economy. Understanding these changes is vital for analyzing financial trends and evaluating shifts in economic policy.

Abstract: In recent years, the growing awareness of nutrition and personalized health care has driven the need for intelligent diet planning systems. This paper presents the design and implementation of a web-based Diet Recommendation System using the Django framework. The system accepts user inputs such as Body Mass Index (BMI), age, and specific health goals—including weight loss, muscle gain, or maintenance—to generate a personalized diet plan [1]. The backend features an admin-controlled nutrition database containing categorized food items with detailed macronutrient information. Based on the user profile, the system intelligently maps appropriate meal options [3] and suggests a balanced diet that aligns with the user's goals. The platform also allows scalability to include real-time nutritional analytics, food logging, and PDF report generation [2]. By leveraging Django’s modular architecture and relational database capabilities, the system ensures flexibility, security, and ease of use. This project demonstrates the potential for technology to assist in promoting healthier lifestyles through intelligent dietary planning.

Abstract Purpose: This paper is to examine the potential of crowdfunding for financial inclusion and alternative finance. Design/methodology/approach: This paper uses the historical data and current trends as a mixed method. Findings: Conceptual platforms, mobile integration and localized strategies. Research limitations/implications: Infrastructure and tech barrier, Regulatory challenges and trust and culture. Originality/value: 98% original by Turnitin check. Crowdfunding has proved to be an effective instrument of financial inclusion, particularly in developing countries, where it is practically impossible for underbanked and unbanked members of the society to access standard banking services. This paper investigates the potential of crowdfunding platforms as a mechanism for financial inclusion and for enabling individuals and small firms to access capital. We examine the role of crowdfunding as a driver of financial inclusion and discuss its significance in promoting entrepreneurship, economic growth and social change. Based on a common review of case studies in different developing contexts, we find the main challenges and opportunities of crowdfunding from a financial inclusion perspective. The authors contribute to the literature by sharing knowledge about how crowdfunding can be an effective financial inclusion tool, and they provide some recommendations for policy makers, platform operators and the stakeholders needed to improve its reach and effectiveness.

Abstract: In recent years, human resource management has undergone a major shift, with many organizations adopting digital platforms to manage people-related functions more efficiently. This study looks into how electronic Human Resource Management (e-HRM) practices have not only digitized traditional HR activities but also paved the way for newer technologies—particularly Artificial Intelligence (AI) and Emotional Intelligence (EI)—to take root. Through a careful review of academic literature published between 2004 and 2024, the paper explores how AI tools, when embedded within e-HRM systems, streamline everyday tasks such as hiring, training, payroll, and performance tracking. More importantly, it discusses how AI is beginning to learn and mimic human emotions through tools like chatbots, facial recognition software, and natural language processing. These emotion-aware systems help HR departments connect with employees in more meaningful ways, especially in remote or hybrid work settings. By combining operational efficiency with emotional insight, e-HRM is becoming a powerful tool for creating sustainable and human-centered workplaces. The study offers a fresh perspective on how HR is evolving in the age of smart technologies, emphasizing the need for a balanced approach that values both speed and sensitivity.

Abstract: The rapid growth of Over-The-Top (OTT) platforms in India has transformed entertainment consumption patterns. Series have received considerable attention and viewer engagement across platforms such as Disney+ Hotstar, Amazon Prime Video, Sony LIV, ZEE5 and Netflix. This article explores viewer perception regarding these five popular web series using primary data collected through a structured questionnaire. The aim is to identify viewer preferences, emotional connections, satisfaction levels, and expectations from web content in India.

Abstract: This systematic review examined the influence of transformational leadership, workplace incivility, and emotional intelligence on employee work engagement. The study was motivated by the growing recognition of engagement as a key driver of organizational performance and employee well-being. The objective was to synthesize existing empirical evidence on how these three factors shape engagement levels in diverse workplace settings. The review followed the PRISMA 2020 guidelines and analyzed peer-reviewed studies published between 2010 and 2024. Databases such as Scopus, Web of Science, PsycINFO, and Google Scholar were searched, and relevant studies were screened based on predefined eligibility criteria. A narrative synthesis approach was adopted to integrate findings from quantitative, qualitative, and mixed-methods research. The findings revealed that transformational leadership consistently enhanced work engagement by fostering inspiration, trust, and psychological safety. Workplace incivility, on the other hand, significantly undermined engagement by increasing stress and reducing employees' emotional investment in their work. Emotional intelligence emerged as a critical personal resource, helping employees sustain engagement by managing stress and maintaining positive workplace relationships. Despite these insights, limitations such as cross-sectional designs and self-report biases were noted. The study highlighted the importance of positive leadership, respectful workplace interactions, and emotional competence in promoting employee engagement. Organizations were recommended to invest in leadership development programs, implement policies to reduce incivility, and incorporate emotional intelligence training into employee well-being initiatives. Future research should explore longitudinal and cross-cultural studies to strengthen causal inferences and broaden practical applicability.

Abstract: Inventory forecasting practices are pivotal for FMCG manufacturing firms in Kenya’s competitive market in order to improve their operational performance. The fast-moving consumer manufacturing firms have been experiencing performance challenges that affect their daily operations through increased production costs, increased lead-time, poor customer satisfaction. The study sought to determine the relationship between inventory forecasting practices and performance of fast-moving consumer manufacturing firms in Kilifi County, Kenya. The study targeted 11 Fast-moving consumer manufacturing firms in Kilifi County, Kenya as unit of analysis while procurement officers, logistic officers, transport officers, distribution officers and warehouse officers were the unit of observation. The target population was 2922 and therefore the sample size of 351 respondents was determined using Yamane 1967 sampling formula. The study adopted stratified random sampling. The research was anchored on two theories Systems Theory and the Theory of Economic Order quantity (EOQ). The study used descriptive research design, the study targeted 351 respondents comprising of procurement officers, logistic officers, transport officers, ware-housing officers. Primary data was collected through structured questionnaires. Data was analysed using SPSS version 31 where descriptive statistics such as means, standard deviation, frequencies and percentages were used. Correlation analysis was done to test the strength and direction of linear relationship between variables. Multiple regression analysis was conducted to determine the relationship between independent and dependent variables.   A pilot test was conducted with 10% of the sample size and it showed strong reliability (Cronbach’s alpha = 0.795) The pilot test results revealed that the data collection instruments used in the study were both valid and reliable. Inventory forecasting demonstrated a strong positive relationship with performance. The study concluded that effective inventory forecasting plays a key role in boosting the performance of FMCG manufacturing firms in Kilifi County.

Abstract: This study investigates how exposure to Artificial Intelligence (AI) influences women entrepreneurs’ business strategies, performance, and innovation potential. Adopting a mixed-methods design—a combination of quantitative surveys and qualitative interviews—this paper examines adoption levels of GenAI tools among women-led ventures, associated barriers (e.g., technology literacy, bias, privacy concerns), and business outcomes. Data sources include academic literature, industry reports (e.g., Nasscom‑BCG), and government-backed initiatives in India. Results indicate that despite high interest (e.g., women constitute ~30% of GenAI enrolments in India), adoption remains limited by structural and cultural impediments. However, where applied, AI adoption correlates with scaling faster, improved decision-making, and enhanced access to networks. Recommendations include targeted AI upskilling initiatives, ecosystem support, and policy interventions to reduce gendered digital divides.

Abstract: The performance of radio signals propagating through the lower atmospheric layers is influenced by their refractive conditions. To ensure that the effects of propagation do not compromise the strength of signals transmitted, link budgets must be carefully designed. The International Telecommunication Union (ITU) model is the globally accepted standard for estimating radio refractivity. However, due to climate variability, researchers have reported overestimations and underestimations of radio refractivity by the ITU model in tropical climates. In response, this study introduces a novel modeling approach by developing a new empirical model for estimating radio refractivity and generating contour maps to enhance existing link budgets in Nigeria. Ten years of atmospheric parameter data from twelve locations across different climatic regions of Nigeria were obtained from the Center for Atmospheric Research (CAR), Anyigba, Nigeria. Using these data, a new refractivity model was developed and statistically validated with R-squared and Root Mean Squared Error (RMSE) metrics. Subsequently, refractivity contour maps for Nigeria were created using Surfer 16 software. The analysis revealed that the proposed model achieved R-squared and RMSE values of 0.99 and 0.27, respectively. Additionally, annual refractivity contour maps indicated a progressive increase in refractivity values from the northern (dry) regions of Nigeria to the southern (coastal) region. The study also demonstrated that refractivity values vary across climatic regions. Thus, this work can be employed for the quick and precise link budgets estimation in the design and planning of radio links in Nigeria and other regions with comparable climatic conditions.

Abstract: This study evaluates the ten-year development impact of budget expenditure in Tanzania's public investments, using audit reports by the Controller and Auditor General (CAG) as the primary source of information. Although budgetary expenditures on development projects have increased significantly from FY 2014 right up to FY 2023/24, translating such investments into tangible public services and infrastructures has been inconsistent. Through the analysis of audit trends, this paper reveals persistent shortcomings in terms of underspending, unsupported spending, poor implementation of audit recommendations, and value-for-money. These are systemic problems and indicate deep-rooted shortcomings in financial controls, procurement management, and institutional accountability. The study also considers the evolving governance context, primarily the goal of the newly published Tanzania Development Vision 2050, which underscores the need for efficient, transparent, and accountable public finances management. The suggestions involve the institutionalization of results-based budgeting, strengthening of audit enforcement arrangements, integration of value-for-money guidelines, and stakeholder engagement innovation beyond existing Citizen Report formats. The findings are beneficial to policymakers, development practitioners, researchers, and citizens who desire to link public expenditure to more effective delivery of services and national development targets. Such linking of budget expenditure and development impact is indispensable for Tanzania to achieve inclusive and sustainable development, concludes the paper.

Abstract: In technical analysis, traders use various indicators to help make buy and sell decisions. One such indicator is the moving average, which helps smooth out daily price movements to help establish a trend in price by creating a constantly updated average price. By calculating the moving average, the impacts of random, short-term fluctuations on the price of a stock over a specified time frame are mitigated. Simple moving averages use a simple arithmetic average of prices over some timespan, which exponential moving averages place greater weight on more recent prices than older ones over the time period. Moving average are calculated to identify the trend direction of a stock or to determine its support and resistance levels. It is a trend-following or lagging indicator because it is based on past prices.

Abstract: In Educational Data Mining (EDM), ensuring accurate and fair student placement prediction is essential for fostering equal opportunities and minimizing biases that may disadvantage certain student groups. This study develops a bias mitigation and explainability framework to enhance fairness and transparency in predictive modeling. Recognizing that data bias can skew prediction outcomes, the study explores various bias mitigation techniques, including re-sampling, re-weighting, and adversarial debiasing, to balance the dataset and ensure equitable representation across student groups. Deep Learning (DL) models are deployed on both the original and bias-mitigated datasets to analyze differences in placement predictions. The results reveal significant disparities in prediction outcomes, highlighting that bias mitigation enhances both predictive accuracy and fairness. Additionally, the integration of explainability techniques, such as SHAP (Shapley Additive Explanations) values, provides insights into feature contributions, promoting transparency and trust in AI-driven decisions. This study underscores the critical importance of addressing bias in EDM and advocates for the integration of bias mitigation and explainability methods to ensure fair and equitable placement predictions. By doing so, it contributes to the development of ethical, accountable, and transparent AI systems in education, supporting data-driven, unbiased decision-making in student placement processes.

Abstract: This study examines how lighting and circulation systems influence user comfort, security, accessibility, and community engagement in the University of Lagos community center. Using survey responses from 120 stakeholders, including visitors, staff, facility managers, and design experts, the research evaluates the effectiveness of existing infrastructure. Findings indicate that while most users rate these systems favourably, challenges remain, particularly in hallway and outdoor lighting, congestion in key areas, and limited accessibility for individuals with mobility impairments. Statistical analysis confirms that improved lighting enhances perceived security, while well-structured circulation facilitates navigation and social interaction. Additionally, respondents strongly support sustainable, technology-driven solutions such as motion-sensor lighting, smart signage, and solar-powered illumination. Based on these insights, targeted improvements are recommended to optimize lighting, circulation, and sustainability, ensuring a more inclusive and efficient community center.

Abstract: This study examines the role of green roofs in urban air filtration, specifically their ability to mitigate airborne pollutants in Lagos, Nigeria. As urban air quality continues to decline due to rapid development, traffic congestion, and industrial emissions, nature-based solutions such as green roofs have gained attention for their environmental benefits. The research employs a quantitative approach, using structured closed-ended questionnaires administered to 196 ecological experts, architects, urban planners, and sustainability professionals. Cochran’s formula for an infinite population was used to determine the sample size, ensuring statistical significance at a 7% margin of error. Data were analyzed using advanced SPSS techniques, including descriptive statistics and inferential testing, aligned with three primary objectives: evaluating pollutant reduction, assessing the impact of plant diversity and roof design on filtration efficiency, and exploring the integration of green roofs into urban sustainability strategies. The findings show moderate agreement on the effectiveness of green roofs in reducing particulate matter and gaseous pollutants, with more substantial support for their role within broader environmental policy frameworks. The study concludes that while green roofs hold considerable promise for urban air management, their implementation in Lagos requires targeted policies, design standards, professional training, and public engagement to realize their potential fully.

Abstract: Cervical spondylosis (CS) is a degenerative disorder affecting the cervical spine, with increasing prevalence globally due to sedentary lifestyles and prolonged screen exposure. This review synthesizes findings from recent literature (primarily the last five years) on the epidemiology, risk factors, diagnosis, and management of CS. A significant rise in neck pain among young adults and students, especially due to poor posture and excessive digital device use, has been documented.[1-4] Various psychosocial, ergonomic, and demographic factors contribute to CS.[5-8] Diagnostic advances and a multidisciplinary approach incorporating physical therapy, ergonomics, and surgical interventions have shown promising outcomes.[9-12] Public health strategies focusing on education, early intervention, and workplace ergonomics are critical to mitigating the burden of CS.[6,11]

Abstract: The textile industry generates effluents with high concentrations of hazardous heavy metals, posing serious environmental threats if discharged untreated.  In this study, an attempt was made by phytoremediation potential of Salvinia molesta, a free – floating aquatic macrophyte, for removing heavy metals from textile wastewater.  Experiments were conducted with effluent concentrations of (25%, 50%, 75%, and 100%) and the remediation performance was assessed over 28 days ( for every 7 days).  The heavy metals such as Chromium (Cr), Copper (Cu), and Zinc (Zn), which are found in sample were analyzed using Atomic Absorption Spectrophotometer (AAS).  Tanks containing Salvinia molesta showed a Cr removal rate (55.7%), Cu removal rate (48.25%), and Zn removal rate (30.50%). A one way ANOVA table was used for statistical analysis to compare the average concentrations (p<0.05) for  heavy metals in the effluent and removal efficiencies.  This study shows an effective biological approach to treating textile industry effluent with Salvinia molesta, providing a sustainable solution to minimize the risks to its improper disposal.

Abstract: Non-biodegradable waste in Nigeria include: plastic, synthetic rubbers, e-waste, glass polyethene, scrap metals like aluminum, zinc, iron, electronic devices, computer parts, batteries, medical waste. But the most poorly managed of these wastes are plastic, e-waste, and scrap metals. Inadequate management of these wastes lead to land and water pollution; increased the risk of excessive flooding from clog drains, atmospheric carbonization, land degradation. Legislative intervention was made to enhance management of nonbiodegradable waste In Nigeria. Inspect of these laws and policies, non-biodegradable wastes are poorly managed due to lack of adequate funding, corruption, and poor infrastructural development. This paper finds that nonbiodegradable are not properly managed, thus, usually dumped in open drains, bushes, streets, walkways and litter outside homes. The paper also finds that the most prevalent method of Management of waste in Nigeria including policy is by burning, dumping in open drain and landfills, recycling is still in its infancy.

Abstract: This study traces the evolution of the Task-Technology Fit (TTF) model from its initial formulation by Goodhue and Thompson (1995) to its enrichment through other major theoretical frameworks, including Davis’s (1989) Technology Acceptance Model (TAM), Ajzen’s (1991) Theory of Planned Behaviour (TPB), DeLone and McLean’s (1992) Information Systems Success Model (ISSM), and Venkatesh et al.’s (2003) Unified Theory of Acceptance and Use of Technology (UTAUT). The TTF model highlights the importance of the alignment between tasks and technological functionalities as a key determinant of individual performance and technology adoption. Successive adaptations have incorporated dimensions such as system quality, information quality, user satisfaction, and social norms, thereby enhancing the understanding of the mechanisms underlying effective technology use. Taken together, these combined models offer a more comprehensive approach to evaluating and predicting the adoption, use, and impact of information systems in various organizational contexts. Overall, this body of work underscores that, while task–technology fit is essential, it must be considered within a broader framework that integrates human, social, and organizational factors to ensure the success of information systems.

Abstract: Lex Forensica Integrata is a pioneering jurisprudential doctrine that unifies three distinct but interconnected pillars of justice — Traditional Law, Modern Law, and Forensic Science. Traditional law provides the moral and customary framework; modern law offers codified statutes and constitutional safeguards; and forensic science ensures empirical validation through evidence-based methods. By integrating these domains, this theory seeks to create a justice system that is ethically grounded, procedurally sound, and scientifically accurate. The approach addresses the historical tension between normative justice and factual truth, proposing a model where legal determinations are reinforced by scientific validation without compromising cultural values or constitutional guarantees. This doctrine can be adopted globally, with necessary jurisdiction-specific adaptations, to improve judicial accuracy, public trust, and cross-border criminal justice collaboration.

Abstract: The Sustainable Development Goals lay out a uniquely ambitious and comprehensive agenda for global development by 2030. NITI Aayog is the nodal institution for achieving SDGs in the country, leading the 2030 Agenda with the spirit of cooperative and competitive federalism. The Sustainable Development Goals (SDGs) aim to transform our world. They are a call to action to end poverty and inequality, protect the planet, and ensure that all people enjoy health, justice, and prosperity. SDG 5 strives for gender equality and empowerment of all women and girls. It is predicated on ending all forms of discrimination against women and girls and eliminating all forms of violence against women and girls including harmful practices such as child, early, and forced marriages. Unsustainable production and consumption patterns are gendered, with women suffering disproportionately from resource scarcity and natural disasters resulting from climate change. Article 23 - Equality between women and men. Equality between women and men must be ensured in all areas, including employment, work, and pay. The principle of equality shall not prevent the maintenance or adoption of measures providing for specific advantages in Favor of the under-represented sex. The state shall not discriminate against any citizen on grounds only of religion, race, caste, sex, or place of birth. Article 14 embodies the general principles of equality before the law and equal protection of laws. Article 15(1) and (2) prohibits the state from discriminating against any citizen only based on any one or more of the aspects such as religion, race, caste, sex, place of birth, or any of them. No citizen shall be subjected to any disability, liability, restriction, or condition on grounds only of religion, race, case, sex, or place of birth. Gender equality is a fundamental human right and a keystone for achieving sustainable development. In India, the advancement of gender equality has made significant progress on one hand but on the other hand, it has persistent challenges. A vision for India's sustainable development represents a transformative roadmap for India's growth and development by the centenary of its independence. This ambitious vision aims to build a nation that is economically robust, socially inclusive, and environmentally sustainable.

Abstract: The integration of artificial intelligence (AI) into clinical ultrasound imaging presents profound opportunities for advancing diagnostic accuracy, streamlining workflow efficiency, and ultimately improving patient outcomes. This comprehensive review synthesizes contemporary literature and industry frameworks to evaluate current advances, practical use cases, observed performance, and inherent limitations of Google Cloud's Vertex AI when applied to clinical ultrasound imaging studies.1 The platform's capabilities are not merely incremental; they represent a potential paradigm shift in how clinical ultrasound diagnostics are approached and executed. This fundamental change can lead to reduced human variability in interpretation, optimized resource allocation within healthcare systems, and faster patient diagnoses, though it also implicitly raises questions about associated regulatory, ethical, and integration challenges that warrant careful consideration.

Abstract: This study investigates how digital tools can enhance supply chain resilience among small and medium enterprises (SMEs) in Zimbabwe. The research employs a comprehensive desk review methodology, analysing recent publications from Zimbabwean and international repositories to examine the relationship between digital technology adoption and supply chain resilience. Zimbabwe's SME sector faces significant challenges including limited access to financing, infrastructure constraints, and supply chain disruptions exacerbated by global crises such as COVID-19. The study reveals that Fourth Industrial Revolution (4IR) technologies including artificial intelligence, Internet of Things (IoT), blockchain, enterprise resource planning systems, and e-commerce platforms offer substantial opportunities for enhancing supply chain visibility, flexibility, and responsiveness. However, adoption rates remain low due to high implementation costs, limited digital literacy, and inadequate ICT infrastructure. Key findings indicate that personal innovativeness, education levels, ICT literacy, security concerns, and ease of use significantly influence digital tool adoption among Zimbabwean SMEs. The research demonstrates that SMEs implementing digital tools exhibit improved supply chain performance, enhanced risk management capabilities, and greater operational efficiency. Digital transformation enables real-time tracking, predictive analytics, automated processes, and improved stakeholder collaboration. The study concludes that coordinated efforts involving government support, private sector investment, and capacity building initiatives are essential for successful digital transformation. Recommendations include developing affordable digital solutions, improving ICT infrastructure, enhancing digital literacy programs, and creating supportive regulatory frameworks. This research contributes valuable insights into leveraging digital technologies for building resilient supply chains in developing economies, particularly within the African context.

Abstract: Water is essential for human survival. According to the World Health Organization (WHO), approximately 36% of urban populations and 65% of rural populations in India lack access to safe drinking water. Water is primarily used for domestic purposes, especially for drinking. The present study shows that Bottled Water has become a necessity in people’s lives due to the poor quality of the municipal water supply. However, based on the results obtained from the study, we can conclude that in all three mineral water brands, the amount of dissolved oxygen and alkalinity increased over time. The amount of dissolved carbon dioxide decreases as the storage time increases.

Abstract: Combining ability for seed yield and its component characters was studied in sesame by using line x tester mating design. The experimental material included eight lines, four testers and 32 hybrids obtained by crossing eight lines with each of the four testers. The analysis of variance for all the nine characters under study was highly significant which specified wide variability amid parents and hybrids for these traits. The greater degree of SCA variance than GCA variance indicated the role of non-additive genes meant for all the nine characters studied.  DORG 37-11, CT-51 and IC 129908 among lines and Phule Til-1 as well as RT-125 among testers were found to be good general combiners for seed yield per plant. Seed yield per plant was maximum for CT-50(14.26 g) among lines and RT-125(14.52g) among testers. Selection of parents based on per se performance as well as gca effects together showed that the parent IC 129908 can be adjudged as the best parent and can be included in further breeding programmes.

Abstract: Construction waste continues to be a serious global concern, placing pressure on natural resources, energy use, and landfill capacity. In many cases, this waste stems from issues like poor design, inefficient planning, and outdated procurement practices. This study was driven by the growing need to explore how modern digital tools particularly Building Information Modeling (BIM) can play a role in reducing waste on construction sites. Although BIM is widely recognised for its capabilities in 3D modelling, scheduling, and simulation, its actual impact on reducing construction waste in specific local contexts remains less understood. Focusing on construction projects in Kuching, Sarawak, the study set out to identify what factors most contribute to waste and how BIM can help address them. An online survey was distributed to industry professionals, and the responses were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Among five main factors examined environmental awareness, procurement procedures, document preparation, planning and management, and project design the analysis revealed that procurement procedures and project design had the strongest positive impact on improving cost estimates and building performance when supported by BIM. These findings highlight the potential of BIM not just as a design tool but as a practical solution to reduce waste and improve efficiency. This study offers useful insights for construction stakeholders aiming to adopt more sustainable and data-driven practices.

Abstract: Micro plastics, which are plastic particles smaller than 5 m, they are widely recognized as contaminants in marine environments, pose great threats to marine life and ecosystems, and have gathered much information in scientific literature. Examples of these particles are breakdown products of large plastics, synthetic materials, and even personal hygiene products. Marine organisms consume microplastics directly or indirectly from plankton to large crustaceans and mammals, leading to physical issues, chemical contamination, and altered eating habits. Consuming microplastics may cause internal harm, change digestion processes, and introduce toxins into the food chain. Additionally, microplastics serve as carriers for harmful chemicals, including persistent organic pollutants, thus highlighting the effects of these chemicals on marine organisms. Long-term exposure to micro plastic particles is linked with altered reproductive success, reduced growth rates, and loss of biodiversity in marine ecosystems. The ingestion of microplastics by marine organisms has been extensively reported across multiple trophic levels, including zooplankton, bivalves, crustaceans, fish, seabirds, and marine mammals. Research indicates that many species mistake microplastics for food due to their size, color, and movement, leading to unintentional consumption. For instance, copepods and other zooplankton have been observed ingesting microplastics suspended in the water column, which negatively impacts their feeding efficiency and energy intake. In bivalves like mussels and oysters, both laboratory and field studies have documented the accumulation of microplastics in digestive tissues, resulting in inflammation, reduced filtration capacity, and weakened immune function. The diverse distribution of micro plastic particles is not only a threat to marine biodiversity but also raises questions about the sustainability of marine resources. Addressing the effects of micro plastics on marine life requires comprehensive global efforts, including policy regulation, pollution reduction, and enhanced waste management practices. Standardized methodologies for sampling, detection, and toxicity assessment are urgently needed to enable consistent comparisons across studies and geographic regions. Enhancing microplastic detection techniques and developing reliable biomonitoring tools are crucial steps toward accurately measuring exposure levels and evaluating associated risks. Additionally, future research should prioritize the development and assessment of mitigation strategies, such as biodegradable material alternatives, more efficient waste management systems, and effective policy measures aimed at reducing plastic pollution at its source. This review explores recent research on the biological and ecological impacts of microplastic pollution on marine organisms. The ingestion of microplastics can cause physical harm, including digestive blockages, reduced nutrient uptake, stunted growth, and reproductive disturbances. Furthermore, microplastics serve as carriers for toxic chemicals and pathogens, leading to bioaccumulation and disrupting marine food webs. Particularly at risk are filter feeders, benthic species, and coral reef communities. Although awareness of these issues is increasing, significant gaps remain in understanding the long-term and population-level consequences of micro plastic exposure. It also provides a basic view on the types and effects of micro plastics on specific species and other health concerns.  

Abstract: An underutilized agro-industrial waste, mango seed kernel starch (MSKS), was extracted from Mangifera indica seeds and characterized for its physicochemical properties, including amylose content, swelling power, and thermal stability. The extracted starch exhibited a moderate amylose content (31.4%), which is favorable for film formation because it can form strong, continuous networks. The widespread environmental impact of synthetic plastics has prompted the search for sustainable alternatives, with biodegradable polymers emerging as a promising solution. The films were prepared by blending MSKS with polyvinyl acetate (PVAc) at varying ratios (20:80 to 80:20) to enhance mechanical properties and processability. The blends were analyzed using Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD), and thermogravimetric analysis (TGA). FTIR confirmed successful polymer blending, while SEM revealed homogeneous film surfaces with minimal cracks. XRD indicated a semi-crystalline structure, and TGA demonstrated thermal stability up to 350°C, with decomposition primarily occurring between 200–350°C. The research highlights the potential of MSKS as an economical, environmentally friendly substitute for traditional plastics, reducing pollution and promoting sustainable packaging solutions. Future work should concentrate on life cycle assessments (LCA) and industrial-scale production to validate commercial feasibility. The study emphasizes the sustainability and economic viability of MSKS-based films, highlighting waste valorization, reduced carbon footprint, and inherent biodegradability; however, challenges like processing costs and scalability require further optimization. The findings are in line with global efforts to promote circular economy principles and comply with strict regulations like the EU’s Packaging and Packaging Waste Regulation (PPWR).

Abstract: The Neo-banking sector is expanding rapidly due to the increasing penetration of the internet and smartphones, supportive government initiatives for digital payments (like UPI), and a large unbanked or underbanked population. The study is aimed at analyzing the awareness, challenges and satisfaction level on Neo- Banking Services. The study is exploratory and is based on primary data collected from 100 samples from Mysuru city of Karnataka. SPSS version 21 was used for data analysis and interpretation. The study found that there is a significance difference in factors with respect to awareness, challenges and satisfaction level among respondents. The factors on awareness, challenges and satisfaction level have been identified. Therefore, this study would assist millennials in acquiring the required knowledge to make savings and investment decisions in future in order to reach the desired economic growth.

Abstract: Catching arson has numerous constituents and is all about effectively establishing the scene, the cause, and how it occurred. This all-encompassing look highlights the evolution of crime scene tactics, analytical instruments, and management practices involved in managing arson investigations. The approach increasingly presents different technologies that can be utilized for fire scene documentation, including digital forensics and fire pattern analysis, as well as the significance of forensic chemistry in identifying accelerants. It also discusses evidence collection, preservation, and chain of custody methods considered best practices for maintaining the integrity of findings for use in litigation. The paper highlights how fire science and law enforcement skills are exploited with new analytical tools to make arson investigation an interdisciplinary field in precision and efficiency. It demonstrates how, through this analysis, ongoing development in the field may be noted and further recommendations made for improvement of investigatory outcomes concerning arson cases.

Abstract: The growing need for sustainable composting technologies requires efficient mechanical systems capable of producing consistent, high-quality outputs. This study evaluates the performance of a 220 V, 2200 W induction motor-based compost mixer through three tests: (1) a homogeneity mixture test assessing physical and chemical uniformity; (2) a dispensing efficiency test measuring accuracy and repeatability; and (3) an ampere rating test monitoring current draw under varying loads. Compost samples were analyzed for moisture content, bulk density, pH, and nutrient levels, while current measurements were taken at no load, 3 kg, 4 kg, and 5 kg using descriptive statistics. Results showed highly uniform compost with minimal variability in key parameters, confirming effective blending. Dispensing efficiency ranged from 93.0% to 95.4%, indicating precise and reliable material discharge. Ampere ratings remained stable, averaging 2.29 A (no load) to 2.51 A (5 kg), suggesting efficient power use across loads. These findings demonstrate the mixer’s reliability for controlled compost processing and potential suitability for small- to medium-scale operations. Further work should assess long-term performance, adaptability to varied compost materials, and integration of sensors for automated monitoring. This research contributes to advancing smart, energy-efficient composting systems for agricultural and environmental applications.

Abstract: Frequency division is a key application of flip-flops, particularly in wideband frequency synthesizers based on phase-locked loops (PLLs). In such systems, the high-frequency output from the voltage-controlled oscillator (VCO) is typically fed directly into a prescaler, also known as an N/N+1 counter, which serves as a critical building block. As semiconductor technology continues to scale down, both the channel length and supply voltage are significantly reduced. Consequently, the prescaler must operate reliably at higher frequencies and under lower voltage conditions.

Abstract: This paper explores the relationship between anthropometric, physical, and physiological variables and competitive yoga performance. The study involved 25 yoga players aged 10 to 15 from the Delhi-NCR region. The findings indicate a substantial positive association between flexibility and yoga performance, while an insignificant link was observed between sit-ups, push-ups, balance, and yoga performance. The regression equation derived for the study was as follows: Yoga Performance = 29.157 + 1.075 (Flexibility)- 0.856 (Fat%) + (Respiratory rate). The reliability of the regression equation is supported by the R2 value of 647. Therefore, it might be concluded that the variables Flexibility, Fat %, and Respiratory rate significantly explain the variation in the Yoga performance. This study provides valuable insights into the physical aspects of yoga and its impact on performance, which can be useful for athletes and yoga practitioners alike.

Abstract: As campaign is ongoing and efforts are put in place to increase the Nigeria total oil production rate above 1.75 million BOPD, it is expedient to carry out the petrophysical re-evaluation of some of the fields in order to understand the reservoir behaviour and possibly optimize production. In this work, all the hydrocarbon bearing reservoirs were mapped and correlated across the three (3) wells and the petrophysics were evaluated accordingly. This work reveals that there is decrease in the Net to Gross (NTG), porosity and the water saturation (Sw) with increase in depth. The decrease in the NTG of this field may be due to the frequent intercalation of the shale. The closer we approach the Akata Formation the more shaly the sand becomes. We can infer that the decrease in the porosity with increase in depth in this field is due to compaction as a result of the load of the overburden. The anomalies in the trend may likely be the resultant effect of the mud in the invasion zones. The NTG ranges between 0.43 and 0.98, Porosity ranges between 0.17 and 0.28 and the Sw ranges between 0.12 and 040. Three (3) reservoirs were selected for volumetric re-evaluation based on their NTG and porosity values. The B3 reservoir at the depth of 8243ft has the lowest volume Stock Tank Oil Initially in Place (STOIIP) with about 14.31MMBO while the C1 reservoir had the highest volume with a STOIIP of about 14.71MMBO.

Abstract: One of the fundamental topics in Physics but found uninteresting by students is light. This birthed the need for a strategy to aid its teaching and learning, which this study focused on by determining the effect of project-based learning on academic achievement of secondary school physics students in light topics in Oyo metropolis. Guided by two research questions and two hypotheses, the study adopted a pre-test, post-test 2 X 2 quasi-experimental research design, consisting of two experimental groups and two control groups. The population of the study was 3751 Senior Secondary 2 (SS2) physics students in Oyo metropolis. A sample of 145 SS2 Physics students from four intact classes participated in the study via multi-stage and purposive sampling techniques: Experimental group (Urban, N=48, Rural, N=33) and Control Group (Urban N=37 Rural N=27) from the four selected schools. Data were collected using a validated Light Topic Achievement Test (LTAT) (KR-20=0.86). Research questions were answered using frequency counts and standard deviation, while ANCOVA was employed to test the hypotheses. The findings showed a significant effect of project-based learning strategy on the academic achievement of Physics students (F (1;142) =13.24, P=0.00 < 0.05); and a significant interaction effect of project-based learning strategy on academic achievement of secondary school physics students on the bases of school location (F(1; 142) = 36.05), P=0.00 < 0.05. The study concluded that project-based learning strategy was effective in teaching Light topics; and for teaching all school locations. It was recommended that physics educators should adopt Project-based learning strategy to enhance academic achievement in Light topics and at any school location. 

Abstract: Hydrological fluxes and temperature dynamics are emerging as key drivers of hydro- climatology variability across sub-Saharan Africa. As climate change intensifies, these factors exert growing influence on the frequency, intensity and spatial-temporal distribution of hydro climate extremes such as flood and drought. Understanding their complex interactions is critical for improving predictive capabilities and informing adaptive strategies for improved agricultural production, water resources management, climate risk mitigation and resilience across the region. In this study, hydrological and temperature variables from Global Land Data Assimilation System(GLDAS) were optimized using Principal Component Analysis(PCA)  thereafter their Anomalies were computed and generated for spatial trend averages of changes to be visualized and investigated, furthermore Decomposition Analysis Technique integrated with Empirical Orthogonal Function (EOF) was implemented on PCA to unravel the significant influence of hydrological fluxes and temperature on the hydro-climatology variability across the region. Results of the spatial-Temporal distribution of these variabilities were depicted in respective interpret-able maps. Study recommends that the Regional Climate and hydrological monitoring networks should be expanded and modernized and secondly, Promoting the development of a coupled hydrological-climate modeling that can better simulate the interaction between hydrological fluxes, temperature dynamics and extreme events such as flood and drought.

Abstract—Accurate demand forecasting is important in the biscuit manufacturing business to optimize inventory management, maintain operational efficiency and reduce costs. Currently, the scenario subjected company has produced over 50 products under different brand names as well as SKUs. To get demand forecasting, they rely on the manual methods conducted by the sales and administration and marketing departments. These manual methods are performed using tools like excel, they are prone to errors, data duplication, and inefficiencies which are leading to unreliable forecasts and dependencies on individuals. To address these challenges, this project aims to develop predictive analytics forecasting models. To build this model, machine learning techniques will be employed such as Random Forest, Time series and Regression which will be used to analyze historical sales data to identify the trends and patterns, capture complex relationships and find external factors influencing demand. Model creation will enhance the accuracy of demand, inventory management, and improve the decision-making process of the company. The future outcome of this project, the company will be able to meet customer demands in a better manner, reduce inventory costs, and maintain a competitive edge in the market.

Abstract: This study looks at the mechanical properties and microstructural aspects of Al-Mg-Si alloy matrix composites that are reinforced with Groundnut Shell Ash (GNSA), Palm Kernel Shell Ash (PKSA), Avocado Pear Seed Ash (APSA), and aluminium oxide (Al2O₃) particles.  The composites were fabricated using stir casting and analyzed for porosity, hardness, tensile properties, and fracture behaviour.  The percentage porosities increased for all reinforcements, with APSA showing the highest (31.1% increase) and PKSA the lowest (18.1% increase), while all values stayed within the acceptable limit for cast aluminium.  Significant enhancements in hardness were observed, particularly in GNSA-reinforced composites (43.1% increase), confirming improved wear resistance.  Al2O₃ exhibited the most significant improvement in ultimate tensile strength (39.2% increase), succeeded by PKSA (30.0% increase), demonstrating successful reinforcement.  The specific strength reached its zenith with Al2O₃ reinforcement (60.1% increase), underscoring its exceptional load-bearing capability.  In contrast, ductility, shown by strain to fracture, decreased in Al2O₃ (57.98% decrease) but dramatically increased with GNSA (80.8% increase) and APSA (69.8% increase), demonstrating enhanced energy absorption in agro-based composites.  Fracture toughness significantly diminished in all samples, especially in APSA (274.3% decrease) and Al2O₃ (136.6% decrease), indicating increased brittleness due to the reinforcements.  SEM examination demonstrated uniformly distributed particles throughout all matrices, reducing clustering and enhancing consistent mechanical performance.  Agro-waste reinforcements exhibited commendable efficacy in improving mechanical properties while minimizing environmental impact; however, compromises in toughness should be acknowledged in design considerations.

Abstract: With an emphasis on their sources, detection, and possible effects on the environment and human health, this paper investigates the existence of Naturally Occurring Radioactive Materials (NORM) in petrol and diesel fuels. Crude oil contains NORM, mainly uranium, thorium, and their decay products, such as radium, which can concentrate during the refining process. Gamma spectroscopy and other detection techniques are essential for keeping an eye on these substances. Along with regulatory measures and safety standards to mitigate these risks and ensure safety, the review also discusses the environmental concerns, worker risks, and refining processes that concentrate NORM.

Abstract: This study investigates the evolving landscape of ransomware attacks and critically evaluates the effectiveness of current countermeasures. Drawing on a thematic analysis of secondary data from global case studies, cybersecurity reports, and academic literature, the research highlights the commodification of ransomware through Ransomware-as-a-Service (RaaS). It identifies key attack vectors, including phishing, Remote Desktop Protocol (RDP) exploitation, and unpatched vulnerabilities, while examining the increasing sophistication of extortion tactics such as double and triple extortion. Organisational responses are assessed, distinguishing proactive defenders with layered security infrastructures from reactive institutions hampered by limited preparedness, particularly in under-resourced regions. Findings indicate that resilience depends on comprehensive strategies that integrate technological safeguards, user education, and policy-level interventions. This study concludes that ransomware is no longer merely a technical threat but a systemic challenge requiring coordinated action across sectors and jurisdictions. Practical recommendations are offered to support scalable, context-aware defences and foster cybersecurity maturity.

Abstract Background: Drug discovery and development face critical data silos and collaboration barriers across pharmaceutical institutions, research centers, and healthcare organizations. While deep learning models demonstrate exceptional potential for accelerating drug discovery through pattern recognition in molecular data, genomic sequences, and clinical records, current approaches require centralized data aggregation that violates privacy regulations, compromises intellectual property, and limits cross-institutional collaboration essential for breakthrough therapeutic development. Objective: This systematic review evaluates the effectiveness and implementation challenges of multi-institution AI security frameworks in federated drug design systems, examining how privacy-preserving collaborative learning can overcome traditional data sharing barriers while maintaining competitive advantages and regulatory compliance. Methods: We conducted a comprehensive systematic review following PRISMA guidelines across PubMed, Scopus, IEEE Xplore, SpringerLink, Web of Science, and Google Scholar databases from 2015-2025. Search terms included "multi-institution AI security,""federated drug design systems,""privacy-preserving pharmaceutical AI," and "secure collaborative drug discovery." Articles were evaluated for technical security mechanisms, implementation effectiveness, scalability metrics, and practical deployment considerations. Data extraction focused on security performance quantification, privacy preservation guarantees, and real-world validation outcomes. Results: Analysis of 105 selected studies reveals that multi-institutional federated learning frameworks achieve superior security effectiveness (92%) compared to traditional centralized approaches (72%), cloud-based hybrid systems (65%), and conventional distributed architectures (58%). Privacy-preserving federated learning with differential privacy (ε ≤ 0.1) and homomorphic encryption enables secure knowledge sharing across pharmaceutical institutions while preventing model inversion attacks and membership inference vulnerabilities. Industry-scale implementations, exemplified by the MELLODDY consortium involving ten pharmaceutical companies with 2.6+ billion confidential molecular data points, demonstrate successful cross-pharma collaboration without compromising proprietary information. Federated distillation approaches show 15-25% improvement in drug-target prediction accuracy while expanding applicability domains by up to 9.7% compared to single-institution models. Conclusions: Multi-institution AI security frameworks represent a transformative paradigm for pharmaceutical research, enabling unprecedented collaboration while preserving competitive advantages and ensuring regulatory compliance with HIPAA, GDPR, and emerging AI governance requirements. The integration of differential privacy, secure multi-party computation, and federated distillation creates robust defense mechanisms against adversarial attacks while accelerating drug discovery timelines. These findings establish multi-institutional federated learning as an essential infrastructure for next-generation pharmaceutical research, offering a validated pathway to overcome data fragmentation barriers that currently limit therapeutic innovation and patient benefit. Clinical Implications: Implementation of secure federated drug design systems could reduce drug development timelines by 20-30% through enhanced data diversity and improved model generalization, ultimately accelerating life-saving therapeutic delivery to patients while maintaining the highest standards of data protection and intellectual property security.

Abstract: Suitcases Packed with memories, languages stitched into accents, recipes whispered across generations - this is the living archive of diaspora. This article provides an extensive and affirmative examination of Kashmiri identity within diasporic literature, focusing on memory as a mechanism for cultural preservation in Rahul Pandita’s “Our Moon Has Blood Clots” (2013), the intricate interplay of moral complexity and identity negotiation in Mirza Waheed’s  “The Collaborator” (2011), and the dynamics of identity, hybridity, and belonging in Siddhartha Gigoo’s “The Garden of Solitude” (2011) as critically analyzed by Saikat Ghosh. It integrates the salad bowl metaphor, representing cultural coexistence, and diaspora consciousness, embodying an enduring connection to the homeland. This study celebrates the resilience, cultural pride, and communal strength embedded in these narratives, offering a detailed and accessible analysis that reflects the transformative power of Kashmiri diasporic literature.

Abstract: This case study narrates the journey of Milli Al-Ameen College in Kolkata, a minority institution for girls that persevered to secure NAAC accreditation despite severe financial constraints, outdated infrastructure, and a student population composed largely of first-generation learners. Based on college documents and personal experiences, the research shows how committed leadership and practical, locally tailored solutions helped the college turn obstacles into opportunities for progress. By involving the community, protecting local culture, and giving students practical skills, the college not only met the requirements for accreditation but also improved the quality of teaching and helped students build confidence. This study shows that when accreditation is approached with dedication and a strategic plan, it can bring lasting, positive change instead of becoming a burden. The lessons from this case can guide other colleges with limited resources to see accreditation as a chance to grow and improve.

Abstract: This paper presents a case study of mental health and happiness among non-teaching employees of public universities in West Bengal. Drawing on empirical research and the accompanying data set (N = 328), the study employs the Mental Health Continuum—Short Form (MHC-SF) and the Oxford Happiness Questionnaire (OHQ) to describe levels of well-being, test group differences, and examine the association between happiness and mental health. Descriptive statistics and inferential tests (independent-samples t tests, one-way ANOVA, and Pearson correlation) were run on the full sample. Findings show: (a) average OHQ scores correspond to a per-item mean of 4.11 (on a 1–6 scale), while MHC-SF scores correspond to 2.90 per item (0–5 scale); (b) women report significantly higher happiness than men; men report higher (but not significantly higher) mental health; (c) employment nature, education, work experience, and age groups exhibit statistically significant differences; and (d) happiness and mental health are weakly, negatively correlated (r = −.13, p = .023). The paper discusses institutional explanations and outlines management-oriented interventions for Indian universities. The data set is provided as supplementary material to ensure transparency.

Abstract: Piracy was presented in the past as an international challenge, but thanks to military interventions and naval patrols mainly in the recent time, which has ameliorated the impact of pirates operations. The paper depicts the frequency of piracy and the rates of which the operations of pirates were disrupted by assessing the impact of piracy off the Coast of Somalia through social, economic, environmental and moral factors. Both primary and secondary methods of data collection were applied. The primary method entails information generated by the researcher through semi structured interviews. The secondary data were obtained from establishment such as European Union (EU) Naval Force Somalia Operation Atlanta and others from 2008 to 2024. The available data were further analysed and subjected to statistical method using spearman rank order correlation methods, since the available data were non parametric type (without unit of measurement). The results of finding shows that there is a very strong positive relationship between frequency of piracy and the rates of which activities of pirates were disrupted with (r = 0.95). This implies that the frequency of piracy and the rates of which operations of pirates were disrupted contributed maximally to the reduction of maritime security threats from year 2012 to 2024 in particular, but the reverse is the case in year 2011 in particular. Therefore, information sharing should be invigorated among the security experts on time, but not just focusing on intelligence gathering alone. Similarly, Central Intelligence Agency (CIA) presence should be felt at all Africa nations and off the Coast of Somalia in particular. For example, CIA operation centre should introduced to Somalia environment. Finally, capacity building should be encouraged continually in order to enhance the performance of security personnel during military operations but prevention is better than the cure. Then, to prevent pirates operations to a larger extent, international actors should apply more resources to support study/research of this nature.

Abstract:  Poverty is a serious a national challenge in Nigerian communities. This study explores the impact of sustainable procurement practices by FCT’s, Departments, and Agencies (MDAs) on poverty reduction, driven by the need to align procurement strategies with broader socio-economic development goals. The study applied  a mixed-methods approach  combining quantitative and qualitative research approaches. Data were collected using quantitative survey question which were distributed to 320 respondents and semi-structured interviews conducted with 30 key stakeholders across MDAs in FCT. The study applied  descriptive statistics, and ANOVA to analyze the data. The ANOVA results  gave a p-value of 0356, which is less than   0.05 and thus the null hypothesis was rejected, while the alternative hypothesis was accepted. Key findings of the indicate that while sustainable procurement is not yet fully integrated into most MDAs in the FCT, it is recognized as a potential tool for poverty reduction through job creation, meeting critical needs of communities and facilitates local economic growth and development. In conclusion, the study highlights the need for more robust policies, enhanced capacity-building initiatives, and stronger leadership commitment to embed sustainability into procurement processes. Key recommendations include increasing training for procurement professionals, improving policy frameworks to explicitly incorporate sustainability and poverty reduction objectives, and addressing financial barriers through alternative financing mechanisms. These study contributes to more effective integration of sustainable procurement practices, ultimately enhancing their role in poverty reduction in Nigeria.

Abstract: The growing incident of various diseases globally underscores the urgent need for innovative healthcare solutions. This study focused on developing an improved machine learning-based system for predicting multiple diseases. By evaluating the probability of illnesses using patient data, the primary goal is to aid medical professionals in the early diagnosis and personalized management of conditions such as cancer, diabetes, and cardiovascular diseases. The approach employs supervised learning algorithms to analyze medical datasets and provide accurate disease predictions. Several methods, including decision trees, support vector machines, and neural networks, were explored to identify the optimal model based on accuracy and computational efficiency. The system was trained and validated using diverse medical datasets that were preprocessed to address noise and missing values. The architecture of the system was elaborated, detailing steps such as data preparation, model training, and interpretation of results. The performance of the system was rigorously evaluated using key metrics like accuracy, precision, recall, and F1-score. Findings from this study indicate that this approach can serve as a valuable tool in clinical decision-making, delivering highly accurate predictions for various diseases. This work highlights the potential of machine learning to enhance diagnostic processes, leading to faster and more effective treatments. Future efforts will focus on incorporating real-time data for dynamic updates and extending the system's functionality to predict a broader range of diseases.

Abstract: This research examines the transformative effects of artificial intelligence technologies on contemporary employment structures through both systematic literature analysis and empirical data collection. Using a mixed-methods approach combining bibliometric analysis (n=847 papers), survey data from 2,350 workers across 15 industries, and longitudinal employment statistics from 12 countries (2019-2024), this study quantifies AI's impact on global labor markets. Statistical analysis reveals that routine-intensive occupations face a 67% higher displacement risk (p<0.001) compared to creative and interpersonal roles. Industry-specific regression models demonstrate manufacturing (β=-0.43, CI: -0.52 to -0.34) and administrative services (β=-0.38, CI: -0.47 to -0.29) show significant negative employment correlations with AI adoption rates. Conversely, healthcare (β=0.29, CI: 0.21 to 0.37) and education (β=0.22, CI: 0.15 to 0.29) sectors demonstrate positive employment growth correlations. The study provides quantified evidence for 2.3 million net job creation potential by 2030, with 78% confidence intervals, while identifying critical skill gaps affecting 34% of current workforce positions.

Abstract— Digital transformation in Indonesia is accelerating, driven by a 600% surge in QRIS digital payment usage in Q1 2025 and major investments such as Microsoft’s USD 1.7 billion commitment to AI and cloud infrastructure. This study aims to map research themes, identify gaps, and explore policy implications for achieving inclusive and sustainable digital transformation, both in Indonesia and comparable developing economies. Using a Systematic Literature Review (SLR) based on the PRISMA method, we searched the Elsevier database (2020–2025) with the keyword “digital transformation”, applied inclusion/exclusion criteria for relevance and quality, and screened down from 581 to 164 peer-reviewed articles. Bibliometric analysis was conducted using VOSviewer with keyword co-occurrence mapping, generating network, overlay, and density visualizations. Findings reveal dominant clusters around digital literacy, digital financial inclusion, and innovation, alongside emerging themes such as agroecology and digital public service evaluation. Barriers including low literacy, infrastructure gaps, and rigid regulations most strongly affect sectors like education, health, and public administration. Policy implications highlight the need for targeted literacy programs, investment in rural infrastructure, and cross-sector collaboration to leverage emerging areas like AI and green technologies. This study contributes to the regional discourse on digital development by offering a thematic roadmap for future research and policy action.

Abstract: This study examines the effect of the Commercial Agriculture Credit Scheme (CACS) on poverty alleviation in South-East Nigeria, focusing on its contributions to food security and self-employment. CACS is a federal government initiative designed to accelerate the development of the agricultural sector thgh credit facilities. Using a mixed-methods approach, the study collected and analyzed both quantitative and qualitative data from CACS beneficiaries. Findings reveal that access to CACS significantly improved food security through increased agricultural output, diversification of food production, and the creation of income-generating opportunities. The scheme also contributed to self-employment, particularly among rural youth. The study further shows that the adoption of xeriscaping principles has enhanced farming efficiency in water-scarce areas, further strengthening food production systems. The study concludes that CACS has significantly contributed in reducing poverty in South-East Nigeria by supporting agricultural activities that boost food security and employment. It recommends expanding the scheme’s coverage and providing agro-based training, with increased awareness of xeriscaping techniques to maximize the impact of the programme across the region and Nigeria in general.

Abstract: Medical diagnostic and therapeutic procedures involving X-rays have become integral to modern healthcare, enabling clinicians to make accurate diagnoses and provide targeted treatments for various medical conditions. However, the use of X-rays poses potential health risks to both patients and healthcare workers due to exposure to ionizing radiation. Shielding materials are essential to mitigate these risks by effectively attenuating radiation. This study aims to evaluate the current usage of X-ray shielding materials and the extent to which they align with the recommended global standards set by the International Commission on Radiological Protection (ICRP). The goal is to enhance the safety of patients and healthcare workers by ensuring the proper use of shielding materials in hospitals. By comparing current practices with global standards, the research seeks to identify gaps in radiological protection—crucial for minimizing harmful radiation exposure and safeguarding the health of individuals in medical facilities. Additionally, the study aims to highlight areas for improvement to ultimately enhance radiation safety practices. A total of 109 respondents from 46 healthcare facilities participated in the study. These respondents included radiologists, radiology technicians, and radiology assistants working in hospitals with functional radiology departments utilizing X-ray machines within the study area. The study employed a descriptive cross-sectional research design to systematically collect and analyze data from randomly selected hospitals in the Enugu metropolis, using structured questionnaires. For each facility, the modal score was used. Privately owned facilities made up 70% of the total, followed by faith-based (13%) and government-owned facilities (13%), with only 4% owned by corporate organizations. In terms of healthcare levels, secondary health facilities constituted the largest proportion (33%), followed by primary health facilities (30%), specialist facilities (26%), and tertiary health facilities (11%). The findings reveal significant variation in compliance with the recommended global standards, with compliance levels ranging from high to medium and low across different facility types and ownership categories. Factors influencing compliance were also identified. Private-for-profit facilities demonstrated the highest level of adherence, with 82% of their facilities achieving high compliance. Faith-based and corporate organizations each accounted for 7% of the high compliance group, while government-owned facilities lagged behind, contributing only 4% to the high compliance category.

Abstract: Visual acuity is a crucial aspect of eye health, significantly influencing overall quality of life. Vision impairment is a significant global health issue, impacting an estimated 2.2 billion individuals. A substantial proportion of these cases, roughly 1 billion, could be prevented or treated with proper care. India has made notable progress in reducing blindness through targeted initiatives, with its National Program for Control of Blindness and Visual Impairment contributing to a decline in blindness prevalence. According to global health research, around 33.6 million people worldwide are blind, and 206 million experience moderate to severe visual impairment. This study aimed to investigate the impact of yogic practices on visual acuity among school children. A group of 60 students, comprising 33 females (55%) and 27 males (45%) aged 10-19 years, participated in the study. The participants were engaged in yogic practices and underwent ocular vision tests using Snellen's Chart before and after the yogic intervention. The data collection process involved Snellen's Chart tests to determine visual acuity, and paired sample t-tests were calculated using SYSTAT 13 to identify significant changes between pre-test and post-test values. The results revealed a significant decline in visual acuity for both eyes, as indicated by the p-values. Furthermore, a notable decrease was observed in the mean values of the post-test. These findings suggest that incorporating yogic practices into school curricula may have a positive impact on visual health among children. By promoting eye health and addressing vision problems early on, schools can play a vital role in ensuring the overall development and well-being of their students. The study results highlight the potential benefits of incorporating yogic practices into school curricula thus promoting visual health and overall well-being among children.

Abstract:  In an era marked by pervasive loneliness despite widespread digital connectivity, AI-powered virtual families emerge as a novel solution to combat emotional isolation. These sophisticated digital companions, built on advanced natural language processing, adaptive memory systems, and emotional algorithms, offer personalized, emotionally intelligent interactions that adapt to users’ routines and moods. Designed to provide companionship rather than replace human bonds, virtual families serve as a digital hearth, offering comfort and connection to individuals such as the elderly, international students, or those grieving. While critics question the authenticity of synthetic bonds, the potential of these AI companions to deliver meaningful emotional support highlights a reimagined approach to companionship in the digital age. This paper explores the rise of virtual families, their technological foundations, their role in addressing emotional voids, and the challenges and future prospects of this innovative technology.

Abstract: The widespread adoption of unmanned aerial vehicle (UAV) across diverse sectors has increased the risk of collisions and heightened the urgency for robust collision avoidance mechanisms, especially in multi-UAV operations. This comprehensive review synthesizes recent advancements in conflict resolution and sensor fusion techniques for multi-UAV systems, highlighting their principles, applications, advantages, and limitations. An analysis of fifteen peer-reviewed papers published between 2020 and 2024 reveals the increasing adoption of decentralized architectures, model predictive control, geometric methods, and deep learning-integrated sensor fusion for dynamic obstacle detection and avoidance. These approaches enable UAVs to operate autonomously in uncertain and complex environments by improving conditional awareness and response times. Furthermore, the review highlights application domains such as precision agriculture, disaster response, and urban navigation. Eventually, limitations regarding sensor calibration, computational demands, and environmental variability are also discussed. Future research directions emphasize the need for hybrid decision frameworks, real-time processing, and AI-enhanced multi-sensor integration to support fully autonomous and cooperative UAV operations.

Abstract: Artificial Intelligence (AI) is currently transforming contemporary business at a very fast pace, and one of the most drastically affected domains is digital marketing. This research paper, "The Role of Artificial Intelligence in Transforming Digital Marketing Strategies," considers the manner in which AI technologies like machine learning, natural language processing, computer vision, predictive analytics, and chatbots are transforming marketing practices.  Based on a mixed-method methodology, the research integrates primary data through survey responses of 140 participants with secondary sources such as academic journals, industry reports, and case studies. The results show that AI technologies significantly augment customer personalization, customer engagement, and marketing effectiveness. Predictive analytics allows for more precise forecasts of consumer behavior, and AI-driven chatbots enhance responsiveness and cost savings in customer services.  But the study also outlines issues of data privacy, ethics, transparency in algorithms, and consumer trust. These factors point to the importance of accountable AI deployment. The research concludes that AI is not only an enabling tool but also a primary strategic tool in digital marketing. Businesses embracing AI-led strategies can reap long-term competitive benefits through better targeting, automation, and customer satisfaction. In the future, the paper recommends further research into topics like hybrid intelligence, real-time personalization, and the fusion of AI with upcoming technologies like augmented reality (AR), virtual reality (VR), and the Internet of Things (IoT).

Abstract: This study examines the relationship between work-life balance, family responsibilities, and job satisfaction among Muslim female teachers in Surathkal, Dakshina Kannada.  It highlights how cultural, religious, and social contexts influence their dual roles as professionals and caregivers. Most respondents, early-career married women with master’s degrees, reported a generally positive work-life balance. However, many experienced stresses, guilt over unmet family expectations, and felt unsupported by institutional systems. Over 60% of participants reported challenges in observing religious practices during working hours, while domestic responsibilities frequently interfered with their professional duties. Nevertheless, the teachers showed remarkable perseverance and remained deeply committed to both their careers and religious values. The study reveals gaps in institutional support and recommends flexible schedules, religious accommodations, on-site childcare, and wellness programs. These changes can foster a more inclusive and supportive work environment.

Abstract: Generic medicines are affordable alternatives to branded medicines, as they offer the same quality and effectiveness. They play a vital role in making healthcare accessible to all, especially for economically disadvantaged communities. By reducing treatment costs without compromising therapeutic value, generic medicines contribute significantly to public health sustainability. This study aims to assess the knowledge, attitude, and perception of the general public regarding generic medicines in Mangaluru city. The study was conducted on 100 individuals from urban and semi-urban regions of Mangaluru city. Data was collected using a structured questionnaire. The study revealed that public awareness of generic medicines is relatively low, primarily due to uncertainty regarding their quality and safety. The findings of the study highlight the need to raise awareness in rural areas to promote greater acceptance and use of generic medicines. Participants felt that guidance from healthcare professionals and government-led awareness campaigns could play a crucial role in building trust in generic medicines. The study recommends strengthening health campaigns and encouraging healthcare professionals to prescribe generic medicines to improve their availability and acceptance. The study emphasises the importance of enhancing public perception and knowledge of generic medicines to achieve better health outcomes and reduce healthcare costs in Mangaluru.

Abstract: This study, titled “Utilization of Free Time among Students Aged 18–22: A Behavioural Study,” explores how college students in the Dakshina Kannada (DK) district engage in various leisure activities during their free time and how these activities relate to their behavioural patterns and perceptions of productivity. The objectives of the research are threefold: to identify common free-time activities, analyse behavioural patterns linked with free time, and evaluate students’ perceptions regarding the value of such time. Using a structured questionnaire, data were collected from a sample of students aged 18–22, and analysed through statistical tools including chi-square tests and ANOVA. The findings indicate that there is a significant difference in the frequency of leisure activities among students, suggesting diverse preferences in how free time is utilized. However, no significant association was found between behavioural traits (such as time management and stress levels) and types of leisure activities. Further, no notable gender- or year-wise differences were observed in the perception of productive free-time use. The study concludes that while students engage differently in specific activities, their overall attitudes toward free time and its value remain relatively consistent across academic levels and gender. These insights can help educational institutions and policymakers design student-centric initiatives that promote balanced and purposeful use of leisure time.

Abstract: In the era of digital transformation, financial transactions are rapidly shifting from traditional cash-based systems to digital platforms. This study investigates the adoption of digital wallets in Mangalore, an emerging Smart City, focusing on their usage patterns, influencing factors, and key barriers. Primary data was collected from 300 respondents across various demographic groups using a structured questionnaire. Descriptive statistics, paired-samples t-tests, and multiple regression analyses were employed to assess digital wallet usage compared to cash transactions, the impact of demographic and technological factors, and the perceived barriers to adoption. Results indicate that digital wallet usage is significantly higher than cash for routine financial activities. Adoption is strongly influenced by age, education level, smartphone access, and perceived ease of use, while security concerns, technical issues, and digital illiteracy remain significant obstacles. These findings highlight the growing acceptance of cashless payments in Mangalore but underscore the need for improved digital literacy, enhanced security measures, and supportive infrastructure. The study provides insights for policymakers, financial institutions, and technology providers to strengthen digital payment ecosystems in urban India.

Abstract: This paper is about the optimization of a small circular loop antenna using a Genetic Algorithm (GA) to significantly enhance its radiation efficiency for operation at 38.22MHz. Traditional small loop antennas are known for their poor radiation characteristics due to extremely low radiation resistance and high conductor losses, rendering them unsuitable for practical RF communication without a complex matching network. This research applies a Genetic Algorithm implemented in MATLAB to optimize two critical design parameters: the loop radius and the wire radius (thickness). An analytical electromagnetic model was developed to compute radiation resistance, conductor loss resistance (accounting for skin effect and radiation efficiency. The objective function was designed to maximize efficiency by minimizing its negative value. Results from the GA were analysed using convergence plots and two-dimensional contour maps, revealing the efficiency distribution across the design space. The optimized antenna achieved a loop radius of 0.02458m and a wire radius of 0.0099m, leading to a dramatic improvement in radiation efficiency from 0.02% (traditional design) to 99.4%. Additionally, gain and bandwidth performance were significantly improved, making the antenna suitable for terrestrial RF applications. The study demonstrates that evolutionary optimization techniques like GA can overcome the inherent limitations of traditional small loop antennas, by intelligently navigating the design space, the Genetic Algorithm identified configurations that would be difficult to obtain through manual tuning. These findings highlight the practical potential of computational intelligence in modern antenna design particularly for compact efficient and broadband systems in wireless and communication technologies.

Abstract: With the proliferation of 5G networks, emergency services have the opportunity to leverage high-speed, low-latency communication systems. However, the reliability of 5G under crisis conditions remains a critical concern. This study investigates the reliability of 5G networks in emergency scenarios, evaluates the performance and limitations of current infrastructure, and explores mechanisms to enhance resilience and responsiveness. Using both simulation and real-world deployment data, we analyze failure modes, latency behaviors, and redundancy strategies. Our findings provide guidelines for network providers and emergency response organizations to optimize 5G deployment for mission-critical applications and shows the ways to enhance the performance parameters for 5G Network Reliability.

Abstract-Sarcasm detection is a critical research area in Natural Language Sarcasm detection plays a pivotal role in advancing Natural Language Processing (NLP), influencing sentiment analysis, emotion recognition, and conversational AI. Effective models rely on diverse, well-annotated datasets that capture subtle linguistic and contextual cues. This review analyzes 46 research papers and categorizes sarcasm detection datasets into three types: text-based, visual-textual, and audio-visual. The findings highlight the growing importance of multimodal datasets for improving recognition in domains such as social media, news, and dialogues. However, current resources—particularly in audio sarcasm—often overlook critical aspects like prosody, emotional tone, and speaker variability. To address these gaps, the review emphasizes the need for naturalistic conversational data that integrates varied accents, emotional nuances, and dynamic contexts. By advancing dataset design toward real-world dialogue, sarcasm detection models can achieve greater accuracy and robustness, enhancing practical applications including healthcare chatbots, e-commerce reviews, and virtual assistants.

Abstract: Generation Z is entering India's workforce with fresh expectations especially when it comes to flexibility and work-life balance. This study aimed to understand how young professionals in Mangaluru feel about workplace flexibility, and how those feelings affect their job satisfaction. To dig deeper, we conducted a survey among people working in education, IT/ITES, healthcare, and finance. The feedback was pretty consistent: most respondents preferred flexible options like adjustable hours, remote work, and even shared roles. These choices seemed to boost their sense of independence, trust in leadership, and mental well-being. Still, it wasn’t all smooth sailing. Many workplaces haven’t quite caught up. Some policies like compressed workweeks or access to extended leave—were either poorly implemented or not clearly communicated. A surprising number of people didn’t even know if their organization offered mental health support. In short, Gen Z is ready for a more flexible future. But many organisations still have work to do. More awareness, better communication, and broader studies could help close the gap and create workplaces that truly meet the needs of this generation.

Abstract: The journey of higher education, particularly at the postgraduate level, is a critical phase where students sharpen their expertise, enhance research abilities, and prepare to contribute meaningfully to their academic and professional domains. During this stage, they often grapple with multiple challenges such as rigorous coursework, research responsibilities, and institutional expectations. This study focuses on understanding the influence of AI tools on the academic performance of postgraduate students in Mangalore Taluk. Specifically, it examines the level of awareness, frequency of usage, and perceived impact of AI tools among these students. It also seeks to understand the correlation between AI tool usage and academic outcomes, as well as the effectiveness of such tools in facilitating learning and skill development. Using a random sampling method, data were collected from 72 postgraduate students through both primary and secondary sources. The findings indicate that while AI tools may not directly boost academic grades, they do significantly enhance students’ comprehension and learning experiences, as observed by faculty members. Most students find AI tools user-friendly and supportive in building academic and professional skills. However, they emphasize that AI should complement, not replace, conventional teaching practices. Key challenges identified include technical difficulties, insufficient training, limited institutional support, and concerns regarding academic integrity and over-reliance on AI. Overall, the study highlights the growing relevance of AI in postgraduate education and underscores the need for balanced integration, ensuring that students benefit from these technologies while maintaining academic standards and ethical practices.

Abstract: This study, titled "Students' Perception of Academics and Hobbies: A Study with Reference to Udupi District", explores the dynamic interplay between academic responsibilities and personal hobbies in the lives of students. Recognizing that education shapes intellectual, emotional, and social development, and that hobbies contribute to creativity, stress relief, and personal fulfillment, the study aims to assess how students perceive, prioritize, and balance these two important aspects. Using data collected primarily from students in the Udupi district, the study examines their attitudes toward academic success, the impact of academic pressure, the role and types of hobbies pursued, time spent on hobbies, and institutional support for co-curricular engagement. The findings reveal that while academic success is highly valued, a majority of students actively engage in hobbies, with dancing being the most popular and relaxing activity. However, time spent on hobbies is generally limited due to academic demands. Most students believe that hobbies positively influence their academic performance and personal growth, and many express interest in pursuing careers aligned with their passions. Although institutions show some support for hobbies, there remains a need for more structured encouragement and integration of hobbies into the educational framework. The study concludes that a balanced approach to academics and hobbies leads to holistic student development. It calls for educational institutions to foster environments that promote both academic excellence and creative exploration, ensuring students are not only knowledgeable but also emotionally and personally fulfilled.

Abstract— This project is about using deep learning to find and identify different diseases in pomegranate fruits. The main goal is to help farmers catch diseases early and protect their crops to get better harvests. We used a dataset of around 2,000 pictures of pomegranates. These images were divided into five groups: Healthy, Alternaria, Anthracnose, Bacterial Blight, and Cercospora. Before training, we prepared the images by resizing them, normalizing the colors, and adding some changes to make the model learn better (this is called data augmentation). We trained two models: one was a simple CNN (Convolutional Neural Network) that we made ourselves, and the other was a pre-trained DenseNet121 model that we fine-tuned. Both models were trained for 20 rounds (called epochs). The DenseNet121 model did better, getting 94.2% accuracy on the validation set, while the custom CNN got 87.5%. We also made a web application using Flask, where users can upload images of pomegranates and get real-time results. The app tells whether the fruit is healthy or has a disease, gives tips on how to deal with the disease, and shows an estimate of how much crop might be lost.

Abstract: This project explores how smart meteorological technologies such as automated weather stations, AI-powered forecasting systems, and sensor-based climate monitoring are influencing Ghana’s capacity for accurate climate observation and disaster management. It assesses the role of these systems in improving forecasting precision, agricultural planning, and early warning strategies. Through mixed-method data collection and comparative analysis, the project examines both the benefits and limitations of integrating smart technologies into Ghana’s meteorological infrastructure. Findings aim to offer evidence-based recommendations for national policy frameworks and investment priorities in sustainable climate technology.

Abstract: Carbon dioxide is widely reported as the most important anthropogenic greenhouse gas, it accounts for the greatest portion of the global warming. CO2 capture and utilization (CCU) are one of the leading technologies to capture and utilize CO2. In this connection, a spray tower is used to study the capture of CO2 from flue gas using NaOH solutions as the absorbing medium. The absorption efficiency of CO2 by the spray tower is compared using different molarity of absorbents, such as NaOH solutions, at varying flow rates and with different fuels (cow dung, wood stick & charcoal with kerosene) for generating flue gas in the controlled environment. The spray tower absorption process demonstrates good performance in CO2 capture. When using a 2 Molar concentration of NaOH solution and a flow rate of 200ml/min, the coconut shell as fuel and NaOH solution as the solvent shows excellent performance in the spray tower, reducing the inlet concentration of 894 ppm to an outlet concentration of 215ppm, with an efficiency of 76%. The absorbed CO2 in the rich solution from the spray tower is utilized for growing algae, with the aqueous absorbent solution flowing continuously through the spray tower and algae bioreactor. The absorption of CO2 by micro algae helps to reduce the energy consumption of CCU technology, resulting in savings in electric power and capital expenses. The overall CO2 removal efficiency of the spray tower, using NaOH as the absorbing solution is 76%. This process contributes to the reduction of CO2 emissions in the atmosphere and aids in mitigating global warming.

Abstract: This article critically investigates the evolving intersection between artificial intelligence (AI) and media convergence in the 21st century, with a focus on how intelligent technologies are reshaping media production, distribution, and audience interaction. Synthesizing insights from recent empirical and conceptual studies, the paper highlights the transformative roles of machine learning, natural language processing (NLP), and generative algorithms in contemporary media ecosystems. It identifies four thematic trajectories: AI-enabled content personalization, algorithmic journalism, ethical dilemmas involving bias and misinformation, and the rising call for regulatory interventions. The review demonstrates that while AI optimizes operational efficiency and enhances user engagement, it simultaneously introduces complex challenges to editorial autonomy and professional standards. The study advocates for hybrid frameworks that prioritize human-AI collaboration in journalism, ensuring ethical accountability, transparency, and the protection of democratic values.

Abstract: This project is about making a smart web system that helps people know if they are at risk of getting five common diseases. These diseases are heart disease, cancer, liver disease, diabetes, and chronic bronchitis. The system uses artificial intelligence (AI) to look at personal health information like age, smoking and drinking habits, sleep routine, how much exercise a person does, and what symptoms they have. Before training the models, the data was cleaned and changed using encoding and scaling so the AI could understand it better. Two machine learning models, Random Forest and Support Vector Machine (SVM), were trained to predict the risk of these diseases. The Random Forest model gave a very high accuracy of 96.8%, while SVM gave 95.3%. These models were added into a Flask-based web app, and MongoDB was used to save real-time user data and predictions. This system helps people take care of their health early. In the future, more diseases will be added, and it will be tested with real users.

Abstract: We create an integrated production-distribution model to address a failing two-tier supply chain. The supplier's production batch size is limited to an integer multiple of the discrete delivery lot amount for the buyer. Cost functions for suppliers, buyers, and the complete supply chain have been established. This leads to determining optimal policies for both individuals and the integrated supply chain. We provide a method for making optimum supply chain decisions while minimising overall system costs. Our technique is presented with a numerical example.   

Abstract: The pace of urbanization is increasing rapidly around the world, reaching a critical point in 2007. Nigeria is one of the nations recognized for its swift urban growth, which is significantly altering its built environment. However, the role of architects in promoting the sustainability of this built environment remains unclear. This study examines urbanization, the built environment, sustainability, and the global emphasis on ensuring every urban development is sustainable. Despite the complex and challenging demands of urbanization, Nigeria, like many other developing countries, faces overwhelming developmental pressures. These pressure seen compass the need for sufficient housing, infrastructure, utilities, and various services. While these challenges may evoke feelings of despair and hopelessness, they also present opportunities for  innovative solutions that support a sustainable urban built environment. Consequently, these issues illustrate the sustainable urban paradox faced by architects. The cortical insights suggest that the work of professionals in the built environment, particularly that of architects, must adopt sustainable practices to secure a viable urban built environment for current and future generations. In summary, this study has confirmed the architect's crucial role in fostering a sustainable built environment in Nigeria. Additionally, it has provided insights into the processes that lead to architectural interventions. Lastly, the study highlights the importance of collaborative efforts among design professionals, allied built environment sectors, and policy makers to facilitate the implementation of sustainable practices within Nigeria's urban built environment.

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Abstract: Small and Medium Enterprises are not merely components of the business world, but rather the fundamental engines of economic development, growth, job creation, and innovation. Consequently, their performance has become increasingly critical and timely, particularly in the context of developing nations. This study examines how contemporary service automation, Internet of Things technology, and digital marketing influence the performance of small and medium-sized enterprises (SMEs) in Ogun State, Nigeria. It emphasises the vital role SMEs play in economic development. We employed a quantitative research design and collected data from 107 supermarket firms. The study identified associations between four types of technology and SME performance. Positive associations were found for service automation (β = 0.966, p < 0.001) and digital marketing (β = 0.440, p < 0.001), whilst one negative and significant association concerning IoT was discovered (β = -0.577, p < 0.001). The combined model explains 71.1% of the variation in SME performance. The study serves the dual purpose of enriching existing insights within the framework of the current body of knowledge and helping inform SME sector industries on how they should consider the use of available technology for performance improvement.

Abstract— Quality of Experience (QoE) has become a central metric for evaluating user satisfaction in telecommunication networks, yet most research has focused on LTE, GSM, and UMTS, leaving IEEE 802.11 WLANs still the backbone of global connectivity less explored from a QoE perspective. This paper presents a comprehensive review of QoE in WLANs, integrating technical, regulatory, and business viewpoints. We examine QoE models and their interplay with IEEE 802.11 standards (802.11n/ac/ax/be), and analyze application-level QoE for video streaming, VoIP, online gaming, live event broadcasting, AR/VR, and web browsing. The mapping between Quality of Service (QoS) metrics and user-perceived QoE is discussed, along with methodologies for measurement, simulation, and testbed evaluation. Special attention is given to challenges arising in dense, moderate, and home deployments. Building on this analysis, we propose a priority-aware framework that links QoS indicators, subjective user perception, and contextual application importance (e.g., emergency announcements, interactive gaming, or live sports streaming). We introduce mathematical models for embedding QoE into WLAN operations and identify open challenges, including ML-driven prediction, privacy-preserving telemetry, and QoE-aware scheduling. Our study concludes with recommendations to guide future research and industry practices toward user-centric WLAN design.

Abstract: A key element of sustainable city design is urban transportation infrastructure, which tackles issues including air pollution, traffic jams, and the fast urbanization of cities. This paper offers a thorough analysis of Mysuru City, India's Trin Trin Public Bicycle Sharing System (PBSS), evaluating its potential to promote sustainable urban mobility. Using a mixed-methods approach, the study assesses the system's operational efficacy and spatial accessibility by combining Geographic Information System (GIS) approaches with user survey analysis. Network and proximity assessments based on GIS quantify how well-connected and integrated docking stations are with important urban features, such as transit hubs, neighbourhoods, and job centers. At the same time, performance bottlenecks and user perceptions are identified by analysing user demographics, usage patterns, and satisfaction levels obtained from primary survey data. The results show how the PBSS may significantly improve last-mile connectivity and encourage non-motorized transportation (NMT). They also highlight important issues, such as poor intermodal integration with public transportation, spatial gaps in station coverage, and user safety concerns, especially at night. The study's strategic recommendations for station site optimization, enhancing digital and physical connectivity with other modes of transportation, and putting safety measures in place to boost user engagement are presented in the conclusion. Finally, by highlighting the critical role that evidence-based planning plays in creating strong and efficient PBSS frameworks, this study provides policymakers in Mysuru and other cities with practical advice on how to match their transportation systems with more general sustainability objectives.

Abstract: This conceptual dissertation elaborates on and refines the Micro-Dissatisfaction Accumulation Model (MDAM), a theoretical framework that redefines the significance of frustration in the integration of artificial intelligence into teacher education. Unlike traditional models that focus on ease of use and seamless integration, MDAM contends that small, recurring micro-frustrations act as cognitive triggers for creativity, innovation, and pedagogical evolution. The dissertation is divided into six structured chapters, synthesizing existing literature on technology adoption, frustration tolerance, cognitive dissonance, and creativity to propose a five-stage process: micro-irritation encounters, frustration accumulation, threshold breakthroughs, creative reconfiguration, and conceptual solidification. Applications in real teaching scenarios reveal how minor AI-related frustrations can stimulate assumption examination, systemic thinking, and identity reconstruction among educators. This framework has profound implications for teacher education programs, professional development, AI tool design, and institutional leadership. The study concludes that educational contexts should not seek to eliminate all frustrations but should strategically manage them to enhance resilience, creativity, and sustainable pedagogical change.

Abstract: Timely identification of plant diseases is crucial for safeguarding crop yields and ensuring effective disease management. In this research, we perform a comparative study of multiple deep learning models for classifying rice leaf diseases using the Rice Leaf Dataset. The classification phase involves evaluating LeafNet, a Modified LeafNet, MobileNetV2, Xception, NasNetMobile, and an ensemble model combining LeafNet with NasNetMobile. For leaf abnormality detection, we employ object detection architectures from the YOLO family, including YOLOV5x6, YOLOV5s6, YOLOV8n, and YOLOV9n. The primary objective is to enhance accuracy in both disease classification and abnormality detection, thereby supporting precision agriculture practices. Through extensive experimentation, we identify the models that deliver superior performance in their respective tasks. The findings highlight the value of advanced machine learning approaches in modern agriculture, enabling early intervention, efficient disease control, and optimized resource use in rice production.

Abstract: Dengue fever, a mosquito-borne viral infection caused by the DENV virus, has been spreading rapidly across tropical and subtropical regions, posing a major public health concern and contributing to significant global mortality. Accurate identification of dengue cases remains challenging, making it essential to adopt reliable and efficient diagnostic approaches. This study explores an automated method for detecting dengue from peripheral blood smear (PBS) images using deep learning (DL) techniques, which have gained prominence in computer-assisted diagnosis of various medical conditions. The research utilizes the “Dengue Disease using Blood Smears” dataset and applies multiple classification models, including ResNet50, MobileNets, MobileNetV3-Small, MobileNetV3-Large, and a hybrid ensemble of Xception and MobileNet. For object detection, members of the YOLO family—YOLOV5x6, YOLOV5s6, YOLOV8n, and YOLOV9n—are employed. Experimental results reveal that the Xception–MobileNet ensemble yields the highest classification accuracy, while YOLO-based models effectively localize abnormalities in PBS images. These findings highlight the potential of DL-based approaches to enhance dengue diagnosis, offering a promising direction for improving public health surveillance and outcomes.

Abstract: This empirical study investigates high school teachers’ perceptions of the need for professional communication training for contemporary high school students, focusing on the DK District of Karnataka. A sample of 204 teachers participated by responding to a structured questionnaire based on a 5-point Likert scale assessing their awareness, attitudes, willingness to support communication training, and perceived challenges. Descriptive statistics showed that teachers generally hold positive attitudes toward the integration of communication skills in the curriculum. One-sample t-test results revealed statistically significant support for communication training, with p-values less than 0.05, confirming teachers’ recognition of its importance for students’ academic success, career readiness, and holistic development. However, respondents also identified significant barriers, including inadequate training opportunities, limited resources, and insufficient institutional backing. The study underscores the urgent need for targeted professional development programs and systemic support to enhance the effective implementation of communication training in high schools within the DK District and similar contexts.

Abstract: Artificial Intelligence (AI) is radically transforming the digital marketing landscape by enabling brands to analyze data at scale, personalize experiences, and optimize campaigns with unmatched efficiency. This paper explores the multifaceted impact of AI on digital marketing, covering its applications, benefits, challenges, ethical considerations, and future trajectory. With detailed insights into leading AI tools used in 2025, their explanations, advantages, and a comparative analysis, this comprehensive overview serves marketers, researchers, and industry professionals seeking to enhance customer engagement, drive ROI, and maintain a competitive edge in the digital era.

Purpose: The purpose of this paper is to examine the role of Grama Panchayats in facilitating and improving primary healthcare services in rural areas of Mangalore. The study aims to assess their involvement in healthcare services, implementation, and to identify the challenges and opportunities they face in the healthcare delivery system. Design/ Methodology/ Approach: The study uses both primary and secondary data. The primary data has used the survey method with the help of questionnaires. The questionnaire consisted of 24 questions which were distributed to the residents of Grama Panchayat. For this article, the secondary data is collected from different sources like Google Scholar, Shodhganga etc. Findings: The findings indicate that Grama Panchayats play a critical role in the delivery of primary healthcare services by facilitating awareness programs, monitoring health facilities, and supporting infrastructural development. The study also finds that there is active community participation and satisfaction among the respondents. Originality or Value: This paper is one of the first focused studies to explore the role of Grama Panchayats facilitating healthcare services in rural areas in Mangalore. It provides insights into their contributions, limitations, and potential strategies for improving rural health governance.

Abstract: The leather industry is a significant contributor to India’s economy, providing employment to over 4 million people and serving as a major export sector. Despite its potential, the industry faces numerous challenges that hinder its growth and global competitiveness. This study explores the key problems faced by leather manufacturers in India, including environmental compliance issues, shortage of quality raw materials, outdated technology, inadequate infrastructure, and limited access to skilled labor. Additionally, rising global competition, regulatory hurdles, and lack of innovation further strain the industry's development. The objective of this study is to systematically identify these challenges, analyze their impact on the sector, and propose strategic recommendations for sustainable growth. By examining both internal and external factors, the study aims to provide a comprehensive understanding of the structural and operational difficulties confronting Indian leather manufacturers, with the goal of informing policymakers, industry stakeholders, and investors.

Abstract: For a lot of students in India, especially those from families that don’t have much money or support, scholarships aren’t just helpful they’re necessary. Without them, many would probably drop out or maybe not even start college. That’s the reality. But here’s the thing: not all colleges are the same when it comes to giving access to these scholarships. Some colleges get money from the government. They’re called aided colleges. Others don’t they mostly run on fees paid by students. Those are the unaided ones. Now, in a place like Surathkal in Karnataka, you’ll find both kinds. And from what students say, the difference in how scholarships work between the two is pretty clear. In aided colleges, there’s usually someone who knows how the system works. They help students apply and make sure forms are filled out. But in unaided ones? It’s often confusing. Not enough help, too much paperwork, and students don’t even know where to begin sometimes. There are schemes like the Post-Matric Scholarship from the government. Great idea on paper. But whether it really helps or not that depends on the college. Some research says scholarships improve results and keep students from dropping out. Sure, but only when students can actually access them easily. Many students in unaided colleges still struggle, even though these schemes are technically available to them. And weirdly enough, not a lot of studies have focused on this at a local level. That’s why this research is being done. It’ll look at students in both aided and unaided colleges in Surathkal. The goal is to understand how scholarships affect things like motivation, performance, and whether students stick around. Also, to figure out what’s standing in the way. Maybe then, the system can be made fairer for everyone.

Abstract: The growth of the animal protein industry in India has contributed to the generation of employment, particularly in coastal regions like Mangalore. Mukka Proteins Ltd., a leading company in this sector, has played a key role in this development. This study explores the socio-economic conditions and occupational challenges of the employees working in Mukka Proteins Ltd. The research focuses on aspects such as income level, education, job security, working conditions, and access to welfare facilities. The data collected has been used to understand the daily life and work-related issues faced by the workforce. The findings show that while some employees benefit from stable income and company-provided facilities, others face challenges such as long working hours, occupational stress, and lack of opportunities for career growth. This research aims to highlight these concerns and provide practical suggestions for improving employee welfare and work satisfaction. The results may be useful for both the management of Mukka Proteins and policymakers in understanding employee needs and enhancing work environments in similar industries.

Abstract: Tourism along the coast can be a mixed bag. On the one hand, it creates jobs and brings money into the region. But at the same time, it often leads to damage, both to the environment and to the local way of life. In and around Mangalore, especially near beaches like Panambur, Tannirbhavi and Someshwara, the rise in visitors has changed things quite a bit. This study looked into how those changes are playing out for the people who live there. More specifically, it asked whether tourism that claims to be “sustainable” is actually improving life for locals. It also explored how involved the community really is and whether things like roads, facilities and investment make a difference. To find out, we collected responses from 200 people living close to those beach areas. They were asked about a few things, like whether they felt included in tourism decisions, what they thought about efforts to protect the environment, and how satisfied they were with local infrastructure. Based on what they said, a pattern started to emerge. People were generally more satisfied when tourism businesses made a real effort to be eco-friendly. This included managing waste properly, protecting marine life, using clean energy, and giving jobs to locals instead of bringing in outside workers. But there was something else too. The people who felt like they had a voice in how tourism was handled were noticeably happier. It might be because when people are part of the process, they feel respected and more connected to what’s happening around them. On the other hand, in areas where infrastructure was weak or where there was little investment, the benefits of sustainable practices didn’t feel as strong. The positive efforts were there, but they couldn’t fully take root without proper support systems in place. In the end, this points to something simple but important. If tourism is going to work over the long term in coastal places like Mangalore, it can’t just focus on being environmentally friendly. It has to genuinely involve the people who live there and make sure there is proper investment in infrastructure and development so that everyone benefits.

Abstract: The study titled "A Study on the Common Education Calendar and Its Impact on Student Employability in D.K. District, Karnataka" aims to explore how the standardization of academic schedules influences the development of employability skills among students. The research specifically examines whether the common education calendar facilitates systematic academic planning, supports the acquisition of essential employability skills, and aligns effectively with industry expectations. Data was collected from students across various institutions in D.K. District through a structured questionnaire, with a total of 268 distributed and 250 valid responses analysed. Statistical tools, including descriptive analysis and one-sample t-tests, were employed to interpret the data. The findings reveal that while the common education calendar significantly aids in academic and placement planning, it also imposes scheduling constraints that limit students’ participation in industry training and certification programs. Moreover, the calendar’s direct impact on the development of employability skills like communication, teamwork, and time management is found to be statistically insignificant. The study concludes that the current common education calendar, though beneficial in standardizing academic timelines, requires structural adjustments to better support holistic employability development. Recommendations are proposed to introduce flexible industry-integrated learning periods and skill development interventions within the academic calendar.

Abstract: Chitosan (CS)-based antibacterial hydrogels, often enhanced with inorganic nanoparticles, antibacterial agents, or CS derivatives, are gaining attention for their potential in wound healing, drug delivery, and environmental cleanup. These materials offer excellent biocompatibility, improved antibacterial efficacy, and controlled release capabilities. Research has shown that CS composites with metal oxides such as SnO₂, CuO, Ag, NiO, MgO, and Fe₃O₄ exhibit enhanced antibacterial, antifungal, photocatalytic, and adsorption properties. However, challenges like solubility issues and potential toxicity need to be addressed. Ongoing research is focused on optimizing these composites to improve both performance and safety for biomedical and environmental applications.

Abstract: The Recent online shopping era hit a massive sales attack on sales and services of apprel product in India. Most of the buyers are preferring online apparel product rather than visiting physical shopping.  The sales and services In India, vengeance purchasing was obvious, as in the US and Europe. Since there was no age limit, they could buy everything they wanted, including clothes, and relive the pre-pandemic days. Many stocked their cupboards with favorite clothes. One of the biggest changes in the previous 15 months has been huge retailers acquiring numerous little brands/retailers. It occurred worldwide and in India.In March 2022, Reliance ( Govt.trade report-2023) Retail Ventures (RRV) bought Clovia, a leading lingerie brand, for US $125 million or Rs 950 Crores from Purple Panda Fashions. However, organized merchants entering the Indian market must be aware of its distinctive retail position. Millions of unorganized shops have dominated Indian retail, catering to consumers who are used to convenience and closeness. India's customer mindset has been formed by unorganized retail. Retail constituted 39% of India's GDP in 2005, while just 6% of the organized ( Khale 1989 ) industry is retail. These counter-stores and street sellers may appear modest in a retail sector eventually dominated by Pantaloon and Reliance. The present study focused on Hyderabad online Apparel shoppers buying behaviour and their relation with loyalty issues in this regard.

Abstract: Phytoremediation, the use of plants to remediate contaminated environments, has gained significant attention as an eco-friendly and sustainable approach to address soil and water pollution. This review focuses on the integration of green chemistry principles within phytoremediation practices to enhance their effectiveness and environmental safety. By harnessing the natural abilities of plants to absorb, stabilize, and degrade pollutants, innovative strategies such as the use of plant co-cultivation, genetic engineering, and the application of green solvents are being explored. Recent advancements in bioremediation techniques leveraging nanotechnology also showcase how green chemistry can optimize phytoremediation processes through the enhancement of plant growth and pollutant uptake. This paper discusses various contaminants, including heavy metals, organic pollutants, and emerging contaminants, while reviewing case studies that successfully implemented green chemistry principles in phytoremediation. Challenges such as the limited uptake efficiency of certain plant species and the need for improved understanding of plant-microbe interactions are critically analyzed. Future perspectives on integrating green chemistry with phytoremediation efforts offer promising pathways for developing more sustainable and effective remediation strategies. Overall, this review underscores the vital role of green chemistry in advancing phytoremediation technologies to mitigate environmental pollution.

Abstract Purpose: The purpose of this paper is to examine the challenges and opportunities for youths in employment, with reference to Dakshina Kannada district. Youth face several challenges in securing employment, such as a mismatch between education and industry needs, limited job opportunities, and a lack of practical experience. So, the main purpose of this study is to critically examine these issues and advise strategies to improve youth employability. Design/ Methodology/ Approach: Primary data was collected using a structured questionnaire consisting of multiple-choice question from youths of Dakshina Kannada and secondary data was collected from academic literature, scholarly journals, research articles, and government reports, to support the findings. Findings: The paper reveals that although a large number of respondents are highly educated, they still face barriers to employment, including economic limitations, limited job opportunities, lack of experience, and skills mismatch. The findings indicate a growing awareness and participation in skill development programs, preference for government jobs. Despite education being foundation for employment, there is still a gap between the academic education and job market demand. Originality or Value: This paper provides a contribution in analyzing youth employment challenges and opportunities with main focus to Dakshina Kannada district. This research suggests valuable insights into youth employment dynamics and offers strategic guidance for development stakeholders, educators, and policy-makers in the region.

Abstract: This work investigates the environmentally sustainable production techniques for Zinc (Zn) and Iron (Fe) nanoparticles with a focus on their use as Nano-fertilizers to improve plant growth. Using nanotechnology, which is defined as the manipulation of matter at the nanoscale (1-100 nanometers), will achieve maximum efficiency in terms of nutrient delivery through agricultural practices. The study produced Zn and Fe nanoparticles using cow manure extract in the green synthesis method. Characterization was confirmed through UV-Vis and photoluminescence spectroscopy to achieve nanoparticles. The Nano-fertilizers were applied to chilly and tomato plants, leading to significant increases in chlorophyll content and other parameters like flowers, fruits, leaves, fruit size, clearly showing the potential to improve plant growth and yield.

Purpose                                                There is growing dependency on technology among students who use the internet regularly. This creates concern regarding cyber security in this digital era. The purpose of this study is to investigate the level of cyber security knowledge and practice among Dakshina Kannada District students. The study investigates how different factors affect knowledge of cyber security among students. Design/Methodology/Approach Primary data was obtained from the students studying in Dakshina Kannada District and secondary data was collected from academic literature, scholarly journals, research articles, and government reports, to support the findings. Findings         According to the findings, although many students are active online users, a sizable portion do not know enough about safe online practices, which highlight awareness gaps among students in Dakshina Kannada District. Originality or Value The report stresses the importance of community-based initiatives, focused awareness campaigns, including cyber security instruction in university curriculum as it plays an important role in creating a safer digital environment in Dakshina Kannada District. The findings provide necessary information to educators, legislators, and advocates for digital safety for building youth cyber resilience.

Abstract: This thesis investigates the dual impact of rapid urbanization and increasing fast food consumption on public health and environmental sustainability in Mangalore. As the city grows due to migration and development, significant lifestyle and dietary changes are occurring, with more people turning to fast food driven by hectic schedules and changing cultural norms. This shift has led to a rise in lifestyle-related diseases such as obesity, diabetes, and cardiovascular problems. Simultaneously, the expansion of fast food outlets contributes to environmental challenges, including increased plastic waste, pollution, and the reduction of green spaces caused by urban sprawl and inadequate waste management. A survey of 300 Mangalore residents found that while fast food is favored for its convenience and taste, traditional home-cooked meals are still preferred by many. The respondents showed considerable awareness of the health and environmental risks associated with fast food and expressed a desire for healthier food options, improved waste disposal, and more sustainable food systems. The study emphasizes the need for a balanced urban development strategy that integrates health and environmental concerns, promoting traditional diets and raising public awareness about the dangers of fast food. It also advocates for eco-friendly business practices and calls for stronger government regulations to oversee the fast food industry and ensure responsible urban growth. These findings aim to guide policymakers, communities, and individuals toward creating a healthier, more sustainable future for Mangalore amid ongoing urban transformation.

Abstract: Electronic trade crime has been a significant setback to the internet economy with the exploitation of weaknesses in the online business exchange. This research study evaluates the development of fraud detection methodology in online retailing and how contemporary automated learning systems have Classic exchange mechanisms based on rule-based. It offers a clear explanation of the general applicability of the methodology, both participant installation categorizer and Xgboost. This enhances the discoverability. This paper examines contemporary literature, covers the symptoms of relative performance, and covers problems, data, and research prospects. The findings explore the opportunities to adjust, evolve, and real-time ML tools in relation to internet fraud. Additionally, the paper has elucidated on the significance of the synthetic and realistic datasets in training the models reliably and there is a need to present a more explanatory solution to be implemented in real e-commerce systems. With the help of this review, this article is going to arbitrate future advances into the intellectual framework of fraud detection.

Abstract: This Research paper investigates the workload dynamics of employees within the hospital sector, a critical industry where human resources play a pivotal role in delivering quality healthcare. The study explores the factors contributing to workload levels, their implications on staff well-being and performance, and strategies for workload optimization. The research identifies that hospital employees, including doctors, nurses, and administrative staff, face diverse challenges such as long working hours, high patient-to-staff ratios, and emotional strain due to the nature of their work. These pressures often result in burnout, reduced job satisfaction, and a potential decline in patient care quality. Through data analysis, interviews, and surveys conducted in multiple hospital settings, the project uncovers key trends and patterns in workload distribution. It highlights the role of organizational policies, technological integration, and resource allocation in either exacerbating or alleviating employee workloads. This study offers actionable recommendations for hospital management, such as implementing robust staffing models, leveraging technology for task efficiency, and fostering employee support programs. By adopting these strategies, hospitals can enhance employee well-being, improve productivity, and ultimately provide better patient care.

Abstract: The global tourism industry is severely transformed by the COVID-19 pandemic. The situations accelerate the need of adoption of Smart Tourism Technologies (STTs) to meet traveler expectations. This study focuseson how STTs facilitate visitor experiences, and post-pandemic preferences of the travelers. It aims to understand the role ofdigital advancements in influence travel choices and satisfaction among tourists. A mixed methods approach i.e.,primary data derived from systematic analysis of various web-based sources such as social media trends, online reviews, and digital travel platforms along with secondary data is used for this study. To analyze the patterns ofthe derived primary data,statistical analysis tools such as descriptive statistics, Chi-square tests and ANOVA are used. The study shows a significant post-pandemic shift among the tourists towards technology, safety, and experience in travel. It is noticed that STTs such as mobile applications, AI-powered recommendations, and virtual/augmented reality are useful for touriststo enhance their personalization, accessibility, and overall satisfaction. Post-pandemic preferences show a strong inclination towards domestic, sustainable, and authentic cultural experiences facilitated by these smart technologies. The findings of this study revealscertain insights for tourism stakeholders by emphasizing strategic investment in digital infrastructure, personalized service delivery, and sustainable tourism initiatives to cater to modern travelers' evolving demands.

Abstract: The rapid expansion of the AI revolution has been propelled by a focus on large-scale pretrained models, which have enabled significant advancements across diverse tasks in computer vision, multimodal applications, and natural language processing. This swift progress has simultaneously heightened concerns regarding data privacy and protection, particularly with the introduction of more stringent legislative measures like the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation (GDPR). To address these challenges, the concept of "unlearning" is crucial. Unlearning refers to the technological process of eliminating specific data or its influence from a trained model, typically when necessitated by data deletion rights or ethical considerations. Unlike simply removing entries from a database, the complex and interconnected nature of learned representations in deep neural networks makes the process of unlearning within AI systems considerably more difficult. This study thoroughly investigates AI unlearning methods and structures for data erasure in trained models, operating within established ethical and legal boundaries. The inquiry begins by discussing the moral and legal justifications for machine unlearning, emphasizing factors such as model functionality, data traceability, and the completeness of the deletion process. Next, i present a classification of existing unlearning techniques, ranging from those less suitable for handling large-scale pretrained models and diverse data types to those better adapted for real-world applications. This category includes techniques such as retraining, model modification, knowledge distillation, approximation unlearning, and certified removal. Following an assessment of unlearning approaches for large pretrained models and varied data modalities, the discussion expands into a detailed examination of their benefits, drawbacks, computational costs, and trade-offs. This includes a focus on concepts like 'influence' (data's impact) and 'deletion' (successful removal). I formalize machine unlearning and establish its theoretical foundation. In my experience, unlearning can be effectively implemented in various contexts, particularly with pretrained models, to minimize accuracy loss while ensuring robust privacy assurances. This capability is enabled by specific methodological frameworks and algorithms. My experimental assessment compares various unlearning methods across a range of datasets and tasks, paying particular attention to the 'remembering' metric, model utility preservation, computational cost, and resilience to data reconstruction attacks. Furthermore, the study integrates technical and regulatory domains by connecting legal requirements to quantifiable machine learning goals and by illuminating moral dilemmas that seek to balance privacy with openness and justice. I clearly highlight significant inconsistencies between current legal requirements and the actual technical potential of unlearning, offering theoretical and technological guidance through multidisciplinary approaches. Despite these achievements, I found that scalable and verifiable unlearning in large pretrained models remains a nascent yet crucial field of study. To ensure adherence to privacy regulations and uphold ethical standards in AI applications, this study lays the groundwork for future research into unified standards, rigorous evaluation processes, and practical unlearning technology deployment. The overarching goal is to foster the sustained development of trustworthy AI systems that uphold personal data rights while simultaneously delivering genuine value and goodwill to society.

Abstract: The work a study on Traditional Knowledge and Grassroots Innovation in Khejur Gur Production in Belphari Forest Fringe Villages, Jhargram District, West Bengal deals with indigenous knowledge and grassroots innovations that help sustain the traditional practice of date palm jaggery production in the forest-adjacent communities. Additionally, through household surveys, semi-structured interviews, and participant observation, the study documents traditional practices such as manual tapping, clay oven processing, and seasonal scheduling while also identifying innovations in terms of heating chambers, sap collection vessels, and storing techniques. Descriptive statistics were used to assess the socio-economic parameters of 80 households, including landsize and income from Gur production, as well as level of education. Cross-tabulation and Chi-square tests showed significant associations between education and the adoption of innovations, and correlation analysis also showed that the number of date palm trees tapped and the seasonal income earned were positively related to each other. Using Likert scale analysis, the perception of producers was captured on irregular market access, lack of forest tenure rights, and limited institutional support, which were later used to develop a “Production Constraint Index”. The producers, however, despite these challenges, remain resilient, thanks to their adaptive strategies, cooperative practices, and interchange of local knowledge. Findings indicate the realization that Khejur Gur production stands as an economic activity along with cultural expression and ecological engagement. The study finds that with policy interventions in support of traditional knowledge systems, better access to technology, and programs for sustainable forest-based livelihood, rural income security as well as cultural preservation could be supported in forest fringe areas.

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Abstract: The family Coccinellidae, belonging to the order Coleoptera, is ecologically and economically significant due to its dual roles as predators and phytophages. This investigation focuses on the diversity and distribution of Coccinellid beetles in the Nashik district of Maharashtra. A total of 160 beetles were documented, representing six predominant predatory species. These species fall under subfamilies including Coccinellinae, Chilocorinae, Coccidulinae, and Epilachninae. Cheilomenes sexmaculata (Fabricius) emerged as the most prevalent species, with 185 individuals observed across multiple host plants throughout the study period. The next most frequently encountered species was Hippodamia convergens, with 180 specimens recorded. Hippodamia variegata was found the dominant species of all the predatory coccinellids with 210 specimens collected from different crops and plants. This species was found throughout the survey period. The 2nd most common species was Illies cincta with 130 species specimens collected on available crops and vegetables. This species also was found throughout the study area.The members of Anegleis cardoni were collected from Cucumber, weeds, alfalfa and grasses. Cryptolaemus montrozieri specimens were found quite rare in district Nashik. All the observed species have been described for the first time from Nashik district. The presence of Cryptolaemus montrozieri was good sign for agriculture because it is fungivorous. Six species exhibited broad temporal and spatial distribution.

Abstract: Contour integration is a powerful method in complex analysis used to evaluate both complex and real integrals, particularly those that are difficult or impossible to compute using elementary calculus. By leveraging the properties of analytic functions, contour integration enables the transformation of seemingly intractable real integrals into more manageable complex integrals. This paper explores the theoretical underpinnings of contour integration, presents key techniques such as the residue theorem and Cauchy’s integral formula, and examines its applications in evaluating complex and real integrals. Special attention is given to the treatment of multivalued functions using branch cuts, the role of Riemann surfaces, and the significance of analytic continuation.

Abstract: This study examines the work pressure experienced by CA Articled Assistants in the Dakshina Kannada District, focusing on key contributing factors and exploring potential solutions, including the integration of Artificial Intelligence (AI) in the accounting profession. The demographic analysis reveals that most articled assistants fall within the 20–25-year age group, with a notable female majority among the respondents. The study identifies tight deadlines, long working hours, lack of proper planning, and multitasking as the primary causes of work pressure. Statistical tests, including the Chi-Square Test, confirm that these factors are significantly associated with increased stress levels. The research also finds that work pressure substantially affects the personal lives and mental well-being of articled assistants, supporting the hypotheses that workload has a significant negative impact on both personal and mental health. Interestingly, the study concludes that there is no significant difference in workload between peak and non-peak seasons, indicating that work pressure persists throughout the year. While respondents recognize the potential of AI to reduce manual tasks and improve efficiency, the current impact of AI on reducing work pressure is minimal due to limited adoption in their present work environment. Nevertheless, articled assistants express optimism about the future positive impact of AI in enhancing work life. The study presents several practical suggestions to mitigate work pressure, including balanced workload distribution, time management training, structured mentorship, realistic deadlines, AI integration, mental health support, and initiatives to promote work-life balance. Overall, the study emphasizes the need for both technological advancements and supportive organizational practices to create a healthier and more productive work environment for articled assistants.

Abstract: In today's digital world, focused on cloud services, keeping forensic data secure and intact is very important. The increasing reliance on cloud and IoT systems has exposed vulnerabilities associated with centralized storage and evidence handling. This paper introduces a decentralized forensic framework called DFA-AOKGE, which incorporates robust authentication mechanisms and optimal key generation encryption to address the limitations of conventional systems. The proposed model utilizes biometric authentication integrated with blockchain for transparent audit trails and implements Enhanced Elliptic Optimization (EEO) for dynamic secret key creation. Additionally, Secure Biometric Verification Mechanisms (SBVM) and multi-key homomorphic encryption ensure end-to-end data protection, even during cloud processing. The architecture supports distributed data collection, reducing single-point failure and improving accountability. This approach overcomes challenges in digital evidence integrity, data leakage prevention, and user trust enhancement. The evaluation of the framework shows it does a good job with secure storage, privacy protection, and system scaling. This makes it a useful contribution to digital forensics.

Abstract: This study examines the evolving career aspirations of undergraduate students in Dakshina Kannada district, shaped by contemporary socio-economic trends and technological advancements. Traditionally, students aspired to secure stable employment in government or private sectors. However, a noticeable shift has occurred, with many young graduates now seeking careers that offer personal growth, autonomy, work-life balance, and a sense of purpose. The growing influence of digital technologies, online work opportunities, and social media platforms has significantly reshaped how students perceive their future careers. Family and peer influences remain strong determinants in shaping career decisions, alongside individual values and external economic factors. Using a descriptive research design, primary data were collected from 100 undergraduate students through structured questionnaires. Secondary data were sourced from academic journals and credible websites to support the findings. The results indicate that 49% of respondents prioritise salary as a key factor in their career choices, while 42% are guided by family expectations. Additionally, 79% reported modifying their career goals in response to current job market trends, and 44% identified limited employment opportunities as a major concern. Notably, 69% of the students have undertaken additional training or skill development programs to enhance their employability. These findings highlight the need for dynamic career guidance, curriculum alignment with industry needs, and greater emphasis on skill-based education to meet the changing aspirations of undergraduate students.

Abstract: Growing environmental concerns have influenced consumer behaviour, increasing interest in sustainable and eco-friendly alternatives. This study examines consumer awareness, attitudes, and adoption of eco-friendly products in and around the city of Mangalore. Using a quantitative method, data was collected from 100 randomly selected individuals through a digital questionnaire. The findings show that although many respondents are aware of eco-friendly products and express environmental concern, this does not consistently lead to sustainable purchasing behaviour. Media platforms effectively raise awareness but have a limited impact on actual consumer action. While consumers value quality, durability, and environmental benefits, practical factors such as cost, brand loyalty, and accessibility often take precedence. The study emphasises the importance of collaborative efforts among producers, policymakers, and communities in promoting responsible consumption. Improving access to sustainable options and strengthening support systems are essential for encouraging long-term, environmentally conscious consumer behaviour.

Abstract: This research paper delves into the financial performance and growth trajectories of Non-Banking Financial Companies (NBFCs) operating in India. NBFCs are integral to the Indian financial landscape, as they cater to the financial needs of segments of the population that are often underserved or unbanked. The study examines a set of financial metrics over a five-year period, using secondary data sourced from Reserve Bank of India (RBI) publications, financial statements, and various company databases. Key financial indicators, including the Current Ratio, Debt-Equity Ratio, Net Profit Margin, Return on Capital Employed, and Return on Net Worth, are analyzed using statistical techniques like ANOVA. The results indicate notable differences in financial performance across various categories of NBFCs. Drawing on these findings, the paper provides recommendations to improve regulatory frameworks, promote digital transformation, and enhance risk management practices.

Abstract: Environmental crimes in the recent past have become a major concern in India as many natural resources, health and sustainable development in the country are at risk. This review article discusses the different types of environmental crimes that take place in India such as illicit felling of trees, wildlife smuggling, pollution and disposal of hazardous wastes. It acknowledged the contextual variables that press these activities like poverty, ignorance and weakness in the application of legal provisions. Although the country has developed and adopted appropriate legal and regulatory instruments for environmental compliance, compliance difficulties including corruption, inadequate resources and institutional capacity impede implementation and enforcement. The article moves on to discuss more of the consequences of environmental crimes to the ecosystems and the communities and thus the approach of a multi disciplinary one that is enforcing more stringent laws, education to the public and proper conservation and management of the resources. This review outlines the extent of ECs in India and makes recommendations that will help policymakers, researchers, and stakeholders to rise to the challenge of fighting these crimes in the interest of environmental protection.

Abstract: This research investigates how lean management influences organisational performance within the educational sector, focusing on three prominent institutions: the University of Lagos, Lagos State University, and Inspire Polytechnic. Implementing lean management principles and techniques has enabled organisations to be more purposeful in delivering goods and services while also minimizing waste. Although lean management originated in the manufacturing industry, there is a wealth of research regarding its application in the service sector. A survey research design was employed, utilizing a structured questionnaire comprising 25 questions as the method of data collection. With a population of 2,243, selecting them from the final year students of each institutions, a total of 743 questionnaires were distributed, with 722 being completed and returned. The participants included both students and staff from these institutions. Furthermore, ordinal logistic regression was employed to analyze the data, and the ordinal regression model tested the hypotheses. Ethical standards, including voluntary participation, confidentiality, thorough briefing, privacy, and safeguarding against harm, were rigorously followed. The findings indicated that the implementation of Value Stream Mapping positively and significantly influences the performance of the institutions. Additionally, it was found that waste reduction has a notable effect on organizational performance. Therefore, it is essential for organizations to manage waste effectively. A key finding was that students expressed concerns about the lengthy wait times for administrative assistance. The researcher also suggested that organizations, particularly in the education sector, should identify the areas within their operations that provide value to the institution and concentrate on them. Furthermore, the time students have to wait should be minimized, and the unnecessary consumption of material resources should be limited.

Abstract: A survey conducted in farmers' fields in Dhadgaon, Nandurbar District, Maharashtra, during the 2024 kharif season assessed the occurrence of major rice pests. Observations were made biweekly from August to November/December. The study identified seven pest species, including Cnaphalocrocis medinalis (leaf folder) and Scirpophaga incertulas (yellow stem borer), as the most abundant and dominant in the paddy fields.

Abstract: This study outlines regional disparities in Karnataka, India, resulting from climate change impacts on vulnerable communities. Using secondary data, the research analyzes socio-economic consequences of climate-induced changes across different regions. Key climate change manifestations include altered rainfall patterns, increased drought frequency, and rising temperatures, leading to significant regional disparities affecting agricultural productivity, water availability, and livelihood security. Coastal, northern, and eastern regions of Karnataka are disproportionately affected, with small-scale farmers, fisher folk, and tribal populations bearing the brunt of these impacts. The study highlights cascading effects on food security, health, education, and overall well-being, including gender-based vulnerabilities. A social work perspective underscores the need for targeted interventions and policy measures. The study proposes a multi-faceted approach, including climate-resilient agricultural practices, sustainable water management, livelihood diversification, and strengthened social protection mechanisms. It emphasizes community-based adaptation strategies and integration of indigenous knowledge in climate change mitigation efforts. This research contributes to literature on sub-national climate change impacts and provides insights for policymakers, social workers, and development practitioners working towards climate resilience and social equity in Karnataka. The findings underscore the urgency of addressing climate-induced regional disparities to ensure sustainable development and social justice for vulnerable communities.

Abstract: This study surveys the ethical dimensions of e-learning, with a focus on equity, privacy and academic integrity. The major objectives of the study are to examine ethical concerns surrounding equitable access and data privacy in the e-learning environment. The study employed a systematic review of literature of peer-reviewed publications from the year 2018 to 2024, retrieved from academic databases including Google Scholar, ERIC and Education Source. The qualitative research design was employed and thematic analysis was used to categorize the patterns and classify findings into three principal ethical extents complemented by empirical surveys and educator perspectives. The analysis indicated that e-learning environments face ethical challenges despite the benefits of enhanced flexibility and accessibility. Equity-related apprehensions rose due to lack of digital access, disparities in income and insufficient infrastructure. Privacy issues were raised due to the storage of sensitive learner data, often without adequate transparency. Academic integrity faced problems of increased occurrences of plagiarism and online cheating, demanding the integration of technological safety measures such as secure online exam platforms, plagiarism detection tools and proctoring systems. The study concluded that addressing these ethical problems necessitates the designing of flawless ethical guidelines, strong privacy protection protocols, strategies for digital inclusion and a strong culture of academic integrity alongside practical institutional policy recommendations. It also concluded that promoting ethical awareness and collective efforts of stakeholders is essential for development of ethically accountable e-learning ecosystems that support the principles of quality and equitable education.

Abstract: The sustainability of agricultural supply chains is increasingly influenced by digital advancements, particularly in developing countries like Nigeria, where agriculture plays a vital role in livelihoods and food security. This research examines the perspectives of various stakeholders on the impact of digital technologies on enhancing the sustainability of agricultural supply chains in Nigeria. A qualitative methodology was employed to gather data through interviews and focus group discussions that included farmers, agritech business owners, policymakers, and financial institutions. Thematic analysis highlighted three main results: (i) digital platforms improve market access, financial inclusion, and the efficiency of supply chains, (ii) collaboration among stakeholders is essential for scaling and integrating digital solutions, and (iii) sustainability benefits are noticeable through reduced post-harvest losses, increased productivity, and stronger climate resilience, although challenges related to inclusivity continue to exist. The study concludes that, although digital innovation has significant transformative potential, obstacles such as infrastructural deficits, the digital divide, and policy gaps are critical challenges. It suggests expanding digital infrastructure, enhancing partnerships among stakeholders, and developing inclusive digital literacy initiatives to promote equitable and sustainable agricultural growth. 

Abstract: The Street Light Fault Detection and Location Identification is an intelligent system designed for automating manual identification of faulted street lights. This paper presents the development and implementation of a novel fault detection method that enables the technician to easily identify the faulty lights. The primary objective of this system is to enhance the efficiency of repairing the defected street lights. The system is equipped with a LDR Sensor (Light Dependent Resistor) which is connected to the Arduino microcontroller which reads the resistance of the LDR module and send the location of the faulted light using a GPS module The system is designed to be adaptive, allowing the electrician to dynamically s adjust its path based on his relevant environment. The algorithm considers factors such as obstacle proximity, amount of defected light ensuring a robust and responsive identification strategy. Additionally, the system incorporates additional mechanism to smartly avoiding power outages for purpose.

Abstract: This study explores the hydrological dynamics of the Meghna-Surma basin in Kishoregonj, Bangladesh, with the objective of analyzing and forecasting river water levels. Using 30 years of daily data (1995–2024) on rainfall, discharge, and water levels, the study first applies statistical regression to examine correlations among the variables. Subsequently, the ARIMA (Autoregressive Integrated Moving Average) model is employed to predict future water level trends up to 2029. Findings reveal a strong correlation between rainfall and discharge, and the ARIMA (4,1,3) model demonstrated satisfactory short-term forecasting performance. The study highlights the practicality of using ARIMA for real-time water level prediction in data-constrained environments. These insights are crucial for flood risk mitigation, agricultural planning, and infrastructure development in river-prone regions of Bangladesh.

Abstract: This study examines the financial performance and asset quality of three District Central Cooperative Banks (DCCBs) in Andhra Pradesh—Chittoor, Krishna, and Srikakulam—over the period 2012–13 to 2022–23. Using key indicators including Outstanding Advances, Collections, Overdues, Gross NPAs, and Net NPAs, trends and growth patterns are analyzed for each institution. Statistical tools such as Mean, Standard Deviation, Coefficient of Variation (CV), Compound Annual Growth Rate (CAGR), and ANOVA are employed to assess inter-bank differences and performance stability. Findings indicate relatively stable and controlled operations at Chittoor DCCB, while Krishna and Srikakulam DCCBs exhibit higher volatility and increasing credit risk, especially evident in their NPA growth. The study underscores the need for targeted improvement in credit monitoring and loan recovery, with policy recommendations offered for sustainable cooperative banking operations.

Abstract: The backbone of modern economies relies heavily on Critical Information Infrastructure (CII). It helps to provide critical services in the energy, finance, telecommunications, health, and transportation sectors. This growing dependences on third-party vendors, software applications, and supply chains, has exposed CII to formidable cyber risks. Recent attacks like SolarWinds, NotPetya, and Colonial Pipeline show how damaging supply chain cyber-attacks can be. They threaten both national security and economic stability. This paper hence presents a general conceptual framework that protects CII against supply chain threats. Anchored on the DSR approach, the paper synthesizes some of the literature on prior cybersecurity frameworks, models of supply chain risk, and resilience strategies. The proposed framework integrates three layers: Risk Identification, Governance and Compliance, and Resilience and Response. These layers introduce AI-driven threat detection, ZTA, secure procurement policy, and automated mechanisms for incident response. A comparison of major cybersecurity frameworks such as NIST CSF, ISO/IEC 27001, C-SCRM, and the EU NIS2 Directive shows important gaps in risk assessment, regulation, and resilience strategies. The study therefore contributes to both the academic fraternity and industry practices through the presentation of a structured, adaptive model in mitigating evolving supply chain cyber risks. Future research on empirical validation, cross-border regulatory harmonization, and real-time risk quantification models will be useful in further enhancing global CII resilience.

Abstract: Mobile phone number recycling, the process of reassigning deactivated numbers to new users after a designated period, is a necessary practice for managing the limited pool of available numbers in the face of growing demand. While efficient for mobile network operators, this process can leave residual links between the recycled number and its previous owner’s digital footprint. These leftover risks can lead to the new owner receiving calls, messages, or notifications intended for the former owner of such mobile numbers, creating issues relating to privacy and security, such as identity theft and fraud. The aim of this work is to review security and regulatory provisions relating to mobile phone recycling, identifying gaps and proffering solutions to further protect privacy in this aspect.

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Abstract: This study analyses trends in rainfall, temperature, and humidity over a 15-year period (2006–2020) to investigate the effects of climate change on Kabul City. The Afghanistan Meteorological Department provided the data used to evaluate long-term trends and spatiotemporal variability. The findings show considerable climatic variability, with monthly rainfall generally rising but noticeably falling during the monsoon season. With the exception of the summer and monsoon seasons, when increases were noted, temperature study shows that monthly maximum temperatures are decreasing for the majority of the months. Trends in humidity indicate a steady yearly increase with noticeable seasonal variations. Two severe drought events (2007–2008 and 2016–2018) and one intermediate rainy spell (2011–2014) are highlighted in the precipitation record, highlighting the insufficiency of water resources to satisfy the demands of Kabul's rapidly expanding urban population. A negative water balance has been exacerbated by over-extraction and inappropriate water usage, which has weakened urban resilience, especially in agriculture, and increased the likelihood of water scarcity. In addition to offering insights to enable adaptation methods in Kabul's urban climate environment, the study highlights the urgency of evidence-based policies for sustainable water resource management.

Abstract: Hair fall has been described in Ayurveda by the name of Indralupta roga under the heading of kshudra roga (~minor disease) due to Alpa- Hetu, Lakshana & Chikitsa or shiroroga (~diseases of head & scalp). However, it has been mentioned as Tridoshaja Vikara in Charaka Samhita, Sutra sthana while Vagbhatta has cited it in Shiroroga (~diseases of head and scalp). The Samprapti (~pathogenesis) of Indralupta is the vitiated Tridosha (~Three vitiated factors) and Rakta (~blood) affecting the scalp. Ayurveda offers an effective treatment approach for the management of Indralupta. Indralupta (~Hairfall) is the most common condition in young and old age. In pathophysiology of Indralupta there is involvement of Rasa, Rakta, Mamsa and Asthivaha Srotas. Hair fall is a cosmetic disorder affecting patient psychologically. There are some differences between khalitya & Indralupta. In khalitya, hair loss is gradual and generalised over the scalp but hairs are lost suddenly and patch by patch in Indralupta. When the kapha dosha combines with rakta dhatu it results in degeneration and shutting down completely of hair follicles thus leading to baldness.

Abstract—With the exponential growth of digital data, database security has become a critical concern for orga- nizations across industries. Traditional rule-based intrusion detection methods struggle to detect evolving and sophisticated threats. This research investigates the application of artificial intelligence (AI) and machine learning (ML) to detect anoma- lies in a real-time database. Using access logs, transaction patterns, and user behavior analytics, ML models can identify anomalies and potential security breaches with higher accuracy and adaptability. The proposed approach emphasizes explain- ability, compliance, and adaptability in dynamic database environments.

Abstract: According to Dr. Karl Branting of Mitre, “Artificial Intelligence” or AI can be described as “the field that seeks technology capable of human-like reasoning, perception, and control.” Machine learning is a form of AI that modifies its own programming as it “learns” via exposure to new data. Accordingly, unless otherwise differentiated, my use of “Artificial Intelligence” or “AI” refers to forms of machine learning. Artificial intelligence (AI) has swiftly shifted from the realm of specialized laboratories to the fabric of everyday life, driving applications in healthcare, finance, education, mobility and governance. Its advocates highlight its transformative potential, from productivity gains to novel forms of creativity. Yet the propagation of AI poses risks that are profound, systemic and, in many cases, irreversible. As the Stanford AI Index (2024) warns, “the pace of deployment has far outstripped the pace of governance,” creating a governance gap with real societal consequences. Drawing upon case studies from healthcare, autonomous vehicles, electoral misinformation, labor automation, privacy scandals and environmental costs, this paper argues that the unchecked propagation of AI undermines democracy, deepens inequality, erodes trust in institutions, threatens human dignity and jeopardizes ecological sustainability. Governance frameworks acknowledge systemic risks but remain insufficient to address the accelerating scale and complexity of frontier AI models. The paper concludes with recommendations for targeted moratoria, mandatory auditing, environmental accountability and democratic oversight.

Abstract: This study investigates the role of digital lending platforms in shaping customer satisfaction among clients of Non‑Banking Financial Companies (NBFCs) in Jharkhand, India. As these platforms integrate advanced technologies such as automation, artificial intelligence (AI), and data analytics they streamline loan issuance, reduce paperwork, and enable rapid disbursals, potentially elevating the borrower experience. Research indicates that such technologies can significantly bolster operational efficiency, widen financial inclusion by lowering access barriers, and deliver tailored services, all of which may enhance satisfaction levels among borrowers. However, the rapid proliferation of digital lending also brings serious challenges. Instances of exploitative practices including unauthorized platforms charging exorbitant interest, invasive data harvesting, and aggressive debt recovery have compromised customer trust and safety. Regulatory interventions, such as the Reserve Bank of India’s (RBI) Digital Lending Guidelines and the pilot of the Unified Lending Interface (ULI), aim to restore transparency, protect privacy, and foster fair lending practices. In the context of Jharkhand, an Indian state characterized by varied digital readiness, diverse languages, and socio-economic disparities. This paper examines how these dynamics influence borrower satisfaction. The study synthesizes existing literature, regulatory developments, and local contextual factors to propose a nuanced understanding of how digital lending platforms can both empower and alienate borrowers. It offers practical recommendations for NBFCs and policymakers to balance innovation with inclusivity, trust, and consumer protection.

Abstract: Exercise and fitness are essential to improve women's overall well-being, prevent chronic disease, and enhance mental health. Physical activity maintains weight, strengthens the cardiovascular system, and helps in maintaining bone health, preventing osteoporosis. It also helps in regulating hormones, which relieves symptoms of menstrual irregularities and menopause. Mental health advantages include less stress, anxiety, and depression, with exercise stimulating the release of endorphins, improving mood and cognitive function. Special fitness programs, including strength training, aerobic exercises, and flexibility exercises, address women's special physiological requirements. In addition, exercise during pregnancy can enhance maternal health and facilitate postpartum recovery. Although there are advantages, the barriers of insufficient time, social pressures, and misinformation tend to prevent women from engaging in regular exercise. Knowledge, access, and individualized fitness plans can enable women to take control of their health by being physically active. Inducing healthy lifetime fitness practices is crucial for long-term health and disease prevention. Exercise play important role in overall health of women.

Abstract: Although multiple studies and examinations have investigated the origins and nature of wastes, as well as the potential harmful impacts of improper management and leading global practices, uncertainty still remains regarding what precisely defines waste. How much do we truly understand about what should be classified as waste, and what are the historical backgrounds of waste management? This paper seeks to address these crucial questions by drawing on insights from previous research. A desktop research method was employed, using a descriptive approach to gather data from peer-reviewed sources such as journal publications, environmental organization reports, and books. Findings reveal that the concept of waste is largely subjective a material is only considered waste when the possessor labels it as such. This is particularly significant because one person may view a material as waste, while another may regard the same material as a valuable resource. Therefore, it is argued that there is a pressing need to clearly define what constitutes waste, as this forms the basis for effective regulation.

Abstract: This work examines the efficiency of electrocoagulation (EC) as an eco-friendly and energy-efficient method for treating landfill leachate in the context of urban storm water management. EC was employed using three electrode configurations punched aluminium-steel, plain aluminium-steel, and plain aluminium - aluminium to evaluate their performance in removing key pollutants such as COD, BOD₅, and TSS. The tests were conducted on leachate samples from a landfill in Bangalore, India, by means of a lab-scale electrochemical reactor under constant voltage and varying electrode arrangements. Findings revealed that the punched aluminium - steel combination attained the highest pollutant removal efficiencies (up to 93.3% BOD, 91.8% COD, and 82.9% TSS) while consuming the least energy. The outcomes highlight that optimizing electrode design and spacing significantly enhances EC performance. The study supports integrating electrocoagulation into sustainable urban drainage strategies, emphasizing its role in mitigating leachate contamination and improving water quality in developing cities.

The internet has evolved into a primary necessity for society, including in Indonesia, which has recorded significant growth in users. This study aims to analyze the factors influencing internet package prices, particularly speed and device limitation. The method used is multiple linear regression based on Ordinary Least Squares (OLS) with the assistance of Jamovi software, utilizing secondary data from brochures and advertisements of Internet Service Providers (ISPs) in Tajurhalang District. The analysis shows an R² value of 0.816 with a significant F-test (p < 0.001). However, only device limitation significantly affects price (p < 0.001), while speed does not (p = 0.578). A t-test also indicates a significant price difference between commercial ISPs and RT/RW Net ISPs. The conclusion emphasizes that the dominant factor determining internet package prices is device limitation, with strategic implications for ISPs in designing service packages tailored to consumer needs.

Abstract: Rural India stands at the cusp of a digital transformation in finance, propelled by innovative public infrastructure like the Unified Payments Interface (UPI), Aadhaar-enabled systems, and Business Correspondent (BC) networks. These digital tools are laying the foundation for greater financial inclusion. However, the path forward is not without obstacles: widespread connectivity gaps, limited digital and financial literacy, low trust in digital platforms, growing cybersecurity threats, and a burgeoning unregulated lending sector all pose significant regulatory challenges. Current regulatory frameworks—such as the Payments Infrastructure Development Fund, data protection norms, and pilot systems like the Unified Lending Interface (ULI)—offer promising avenues for mitigating these challenges by promoting secure, interoperable, and inclusive financial ecosystems. A strategic vision that strengthens rural connectivity, empowers local agents (e.g., BC Sakhis), enhances literacy and consumer awareness, fortifies cybersecurity and grievance mechanisms, and enforces oversight of lending platforms—while fostering open-market innovations like ONDC and digital commons—can unlock the full potential of digital finance in rural India. Through coordinated regulation and community-centric approaches, digital financial services can not only permeate underserved regions but also drive resilient and equitable development.

Abstract: We create an integrated production-distribution model to address a failing two-tier supply chain. The supplier's production batch size is limited to an integer multiple of the discrete delivery lot amount for the buyer. Cost functions for suppliers, buyers, and the complete supply chain have been established. This leads to determining optimal policies for both individuals and the integrated supply chain. We provide a method for making optimum supply chain decisions while minimising overall system costs. Our technique is presented with a numerical example.   

Abstract:  This paper analyzes the performance of 6-bit & 12-bit Gray and Inverse Gray (GIG) Codes in Jamming environment.  Gray and Inverse Gray codes are binary orthogonal codes generated by parallel concatenation of Gray and Inverse Gray codes. Direct sequence spread spectrum communication using orthogonal spreading sequences is a common practice for secured data transmission. Performance evaluation over noisy channel conditions is carried out using bit error rate. Along with popular Walsh codes, 12 and 16-length GIG codes are used as spreading sequences and bit error rate analysis is carried out in the presence of Additive white Gaussian noise and Pulsed jammer. GIG Codes perform on par with existing Walsh codes.    

Abstract: Mining and quarrying have a direct impact on the environment. The extraction processes contaminate air and water with sulfur dioxide and other pollutants. The aim of the study is to assess the impacts of quarrying activities on the environment and livelihood of people. The study area, Hatgachha village, is located in Mohammad Bazar block of Birbhum district in West Bengal, India where a part of the Chhota Nagpur plateau is situated. Primary data was collected through questionnaires. Secondary data was collected from 2011 census. Most of the people of the village (76.43%) were schedule tribe. Literacy rate is low (48.84%). Quarrying activities in the study area were perceived to have both positive and negative impacts on the environment and the livelihood of people. The major environmental, socio economic and health problems related to quarrying revealed during this study include, dust pollution, noise pollution, land degradation, vibration, health hazards.

Abstract: Aquatic ecosystems are increasingly threatened by pollutants such as mercury and micro plastics, both of which disrupt food web dynamics. Mercury, a persistent and bio accumulative heavy metal, enters aquatic systems through industrial discharge and atmospheric deposition, accumulating in organisms and biomagnifying across trophic levels. Micro plastics, defined as plastic fragments smaller than 5 mm, are ingested by a wide range of aquatic organisms, impairing feeding, growth, and reproduction. Moreover, micro plastics act as vectors for toxic substances, including heavy metals like mercury, facilitating their transfer through the food chain. The combined presence of mercury and micro plastics poses synergistic risks, intensifying toxic effects and threatening biodiversity, ecosystem services, and human health via seafood consumption. This paper explores the pathways, interactions, and consequences of mercury and micro plastics in aquatic food chains, highlighting the urgent need for integrated pollution management and policy interventions to safeguard aquatic resources and food security.

Abstract: Drowsy driving is a major cause of traffic accidents, especially among truck drivers who work long hours with limited sleep. Although contemporary driver monitoring systems have employed deep learning and computer vision, many depend on obvious signs like eye closure, yawning, or head nodding, which emerge only after considerable fatigue has developed. This research suggests a novel system that utilizes micro-expressions—slight, unintentional facial movements—as initial signs of drowsiness. Micro-expressions are more reliably identified than explicit signals, allowing for earlier intervention to avert accidents. We developed a deep learning model using a specialized dataset aimed at capturing micro-expressions and enhanced it through pre-processing and augmentation methods to boost generalization. The system underwent testing with truck drivers, who experience increased fatigue risks stemming from extended hours, repetitive routes, and substantial vehicle loads. Our findings show more than 95% accuracy, exceeding current methods and validating the system's ability to enhance road safety by detecting fatigue early.

Abstract: Urban flooding has emerged as one of the gravest challenges for Kolkata and Howrah, driven by heavy monsoon rains, silted canals, outdated pumps, and tidal backflow from the Hooghly River. Traditional drainage systems, largely dependent on manual interventions, have proved inadequate in addressing extreme rainfall events. This DPR proposes a Smart Drainage System that integrates IoT-enabled sensors, automated sluice gates, predictive analytics, GIS-based mapping, and SCADA dashboards. A pilot DPR in the Behala–Taratala corridor demonstrates that smart drains can reduce waterlogging duration by up to 80%, prevent tidal ingress, and deliver socio-economic savings of ₹50–80 crores annually when scaled across the metropolitan region. The report outlines system architecture, implementation strategies, comparative benefits, and phased deployment for a climate-resilient future.

Abstract: This study investigated the factors influencing female students' academic success in Physics and looked at gender differences in performance in Navrongo SHS. In order to gain a deeper understanding of performance patterns, the study employed a mixed-method explanatory sequential design, combining qualitative interviews with quantitative data of standardised Physics test scores. According to quantitative findings, although female students outperformed male students by a small margin (0.92) mean difference which was not statistically significant though worth noting. This result implies that performance in physics is not determined by gender. Qualitative results demonstrated how important it is for students to have good study habits, a favourable opinion of physics, active participation in class, teacher support, and peer cooperation to succeed academically. The voices of female students emphasised the value of a welcoming and inclusive classroom where they can thrive in a field that has historically been dominated by men. They also indicated that, peer support, teacher support, fair opportunities, and meaningful engagement were very key to their success in Physics. The study dispels the myth that girls are less likely to pursue physics and confirms that social connections, pedagogical techniques, and individual initiative all play a vital role in female academic success. It comes to the conclusion that encouraging female success in physics calls for teamwork and is typified by inclusive practices, responsive instruction, and ongoing motivation.

Abstract: A multiplier is one of the key hardware blocks in most digital and high performance systems such as FIR filters, digital signal processors and microprocessors etc. Multiplier is such an important element which contributes substantially to the total power consumption of the system. On VLSI level, the area also becomes quite important as more area means more system cost. Speed is a key parameter while designing a multiplier for a specific Application. These three parameters i.e. power, area and speed are always traded off. Speaking of DSP processors, area and speed are the most important factors. But sometimes, increasing speed also increases the power consumption, so there is an upper bound of speed for a given power criteria. Considering the battery operated portable multimedia devices, low power and fast designs of multipliers are more important than area. Generally as we know multiplication goes in two basic steps, Partial product and then addition. Hence in this paper we have first tried to design ripple carry adder and carry select adder and compare their speed and complexity of circuit i.e. the area occupied. While comparing the adders we found out that Ripple Carry Adder had a smaller area while having lesser speed, in contrast to which Carry Select Adders are high speed but posses a larger area. The result is a completely synthesized Efficient 8-by-8 shift and adds multiplier with low power and low area compared to the low power structure called bypass zero, feed a directly (BZ-FAD) TECHNIQUE of shift-and-add multipliers. The simulation result for 8 bit multipliers shows that the proposed low power architecture lowers the total power consumption by 51.11% when compared to the conventional architecture.

Abstract: India’s media and entertainment (M&E) industry appears to be undergoing a paradigm shift related to the rise of digital platforms, changing consumer behavior, and a global thirst for more culturally interesting content. Though the space of traditional television is still expanding, it is the over-the-top, or OTT, space that “is leading a redefinition of how content is created, distributed, and monetized in India” . Utilizing recent statistics and insights from reports by industry associations and market research companies, this study shows that India is emerging as a global powerhouse for content production, especially in the areas of animation, visual effects and post-production services. It explores the socio-economic conditions, such as access to mobile internet, or policy environments that can be seen as driving this change. At the intersection of creativity, technology and business strategy, this paper aims to provide a picture of emerging opportunities and challenges in India’s media space. It highlights the main game-changing trends within the Indian Media and Entertainment (M & E) ecosystem, such as local content, genre-change, technological innovations, and international partnerships .

Abstract: From the initial rise of technology, mobile devices and the widespread use of the internet, which has also given a head start to the spreading of fraudulent cyber-crimes and online scams. With individuals being dependent on mobile devices from simple communication to totally being dependent for various primary purposes such as online shopping, online gaming, online payment and providing personal information on social media platforms more than ever before have given way for criminals to take advantage of this opportunity for their illegal and deceitful activities (“The_Global_Rise_of_Online_Devi,” n.d.). This paper stresses on the rise and evolution of cybercrimes and how it has affected many people with their day to day livelihood. The concept of “going virtual for everything” has been one of the main reasons for the ever increasing cybercrimes and the growth of artificial intelligence has rapidly changed the entire view of cybercrimes. These fraudulent activities aim to deceive and defraud individuals and organizations, resulting in financial loss and identity theft. The impact of online frauds and scams goes beyond financial losses, they can also cause emotional distress and erode trust in online platforms and transactions. The evolution of cybercrimes from the first ever reported cybercrime to the recent crime will be discussed along with the advancements of different cybercrimes including the detection method. It also stresses upon the different methods sorted during the first ever cybercrime that had taken place and the differences of the newly found methods for modern cybercrimes.

Abstract: This study examined the predictive role of active reading experience and classroom engagement in determining academic performance in Physical Science among Grade 11 students.  A total of 300 students from two public. Senior high schools in Bukidnon, Philippines, participated in the study. Standardized survey instruments were used to assess active reading experience (technology use, reading purpose, and physical strategies), classroom engagement (participation, involvement, and preparation), and academic performance. Descriptive findings revealed that students demonstrated high levels of active reading and classroom engagement, particularly in goal-directed reading and application of physical strategies like summarizing and note-taking. Technology-assisted reading strategies were moderately utilized. Correlational analysis indicated a significant relationship between purposeful reading and academic performance, while regression analysis confirmed classroom engagement as a stronger predictor of academic success than active reading experience. These findings highlight the importance of fostering student-centered, reflective, and interactive learning environments in science education. The study contributes to Sustainable Development Goal 4 (Quality Education) by offering evidence-based recommendations to enhance engagement and performance in Physical Science through strategic instructional practices.

Abstract: Artificial Intelligence (AI) is transforming India’s healthcare sector by tackling major challenges such as limited accessibility, workforce shortages, and complex diagnostics. AI-based tools are improving medical imaging, allowing early detection of diseases like cancer and diabetic retinopathy. Indian startups, including SigTuple and Niramai, are using AI to advance pathology and breast cancer screening. AI-driven telemedicine platforms are closing healthcare gaps in rural areas by offering real-time consultations and remote monitoring. Government initiatives such as the National Digital Health Mission (NDHM) are working to unify health records, making data sharing seamless and supporting personalized treatment. In the pharmaceutical sector, AI is speeding up drug discovery and cutting costs significantly. Programs like Ayushman Bharat, along with partnerships with tech leaders such as Google and Microsoft, are boosting AI integration in healthcare delivery. These advancements not only expand access to quality care but also enhance hospital efficiency through automated scheduling and patient management systems. However, concerns over data privacy and algorithmic bias highlight the need for responsible use of AI. Addressing these issues will be crucial to ensure AI’s ethical and sustainable role in strengthening India’s healthcare ecosystem.

Abstract: Council Sync: Event Management System is a digital solution developed to manage events effectively while improving communication between Pangasinan State University Supreme Student Council (SSC) members. This system resolves various issues that arose when using manual event management procedures by resolving scheduling problems and enhancing information sharing and council member collaboration. Event management and execution become more organized through CouncilSync because it integrates essential features such as event creation, media uploads, centralized calendars, event feeds, and email notifications to notify students. The developers implemented a welcoming interface that combines backend Laravel with frontend React and styling functions through Tailwind CSS. The system provides functional reliability and usability as well as efficiency, maintainability, and portability to deliver solutions that fulfill user requirements at a high level of quality. The CouncilSync platform received user feedback, resulting in a 3.35 average weighted mean representing substantial user approval regarding its event management capabilities. CouncilSync gives the SSC an integrated system that delivers an efficient event management platform, which results in reduced scheduling conflicts and higher attendance rates. The system provides email notifications to strengthen communication and coordination among members. The system's successful execution demonstrates that it can enhance event management procedures for student organizations.

Abstract - The Empowerment of women is an important indicator of social development. The UN’s sustainable development goal focuses on empowering women by eliminating gender inequality and discrimination. Female’s involvement in the labour force is a crucial determinant of economic empowerment of females. This paper through extensive data analysis of 33 Indian states / Union territories, examines the impact of Female literacy and dependency ratio on the female Labour Force Participation rates. Female literacy and dependency ratio are both important factors to consider. Enhancing the education of females on one hand helps to push the females into the workforce while the dependency ratio (the ratio of children and elderly in the household) pull the females out of workforce due to care giving responsibilities of females. The findings reveal the crucial role of education in increasing the participation of females in the labour market. The paper provides few policy measures to make the education accessible to females in the country.

Abstract:  The global automotive industry is rapidly transitioning to electric vehicles (EVs), with e-rickshaws playing a crucial role in developing nations due to their affordability and environmental benefits. The shift from traditional lead-acid batteries (LABs) to Lithium Iron Phosphate (LiFePO₄) batteries is vital, but requires a sophisticated Battery Management System (BMS) for optimal performance and safety. One of the major challenges faced by e-rickshaws is ensuring efficient, safe, and reliable battery performance over extended periods. This research focused on designing and testing a smart BMS specifically for swappable LiFePO₄ batteries in e-rickshaws. Objectives included optimizing the BMS for e-rickshaw operations, implementing real-time monitoring and control, integrating IoT features for remote diagnostics, and testing its performance. The methodology involved developing both hardware (LiFePO₄ cells, microcontroller, sensors) and software components (simulation tools like MPS and Victron Connect, advanced algorithms for SoC and SoH). The system's architecture emphasized real-time monitoring and control, ensuring a holistic and interconnected design. The designed smart BMS demonstrated robust performance, evidenced by a tightly controlled output voltage ripple, oscillating minimally between approximately-3mV and +3mV, indicative of superior power regulation. Efficiency analysis revealed a peak of over 97% at a 0.5A output current, which gradually decreased to approximately 93.5% at 3A, showcasing effective energy conversion and minimal power loss (increasing from near 0W to 1W at 3A) across the operational range. Real-time monitoring via the BMV-700 system further validated the accuracy and reliability of the monitoring and control algorithms, consistently showing stable operational parameters, including a constant power output of -191W, a steady current draw of -7.5A, a stable State of Charge at 85%, and a constant battery voltage of 25.46V. This study's successful design and testing of a smart BMS for swappable LiFePO₄ batteries in e-rickshaws significantly advances operational efficiency, enhances safety, and accelerates the adoption of sustainable urban mobility solutions in developing regions.

Abstract: The policy regarding the relocation of secondary school principals has encountered a variety of challenges and hurdles that have complicated its implementation. Therefore, this study sought to assess the impact of secondary school principals delocalization policy on job performance in Wanjohi Sub-County, Nyandarua County, Kenya. The specific objective was to investigate the influence of principal attachment to family and the effect of job performance. The study applied mixed methods approach. Population for this study was 18 public secondary schools in Wanjohi Sub-County, Nyandarua County, Kenya. This study applied purposive sampling techniques which involved the selection of all 18 respondents. The research employed a questionnaire (for quantitative approach) and interviews (qualitative). Quantitative data was analyzed using descriptive statistics such as frequencies, percentages, with the help of Statistical Package for Social Sciences version 24.0 which was displayed using tables and figures. Qualitative data was analyzed, thematically and the findings were presented in a narrative format, allowing for a comprehensive understanding of the themes that emerge from the data. The study found that principal attachment to family had an influence on job satisfaction following principal delocalization. The study concludes that principal attachment to family has significant influence on their job satisfaction when delocalized since strong family ties provide emotional support, stability, and a sense of belonging. The study recommends that schools and the education department need to provide counseling services to help principals manage their emotional and psychological needs during the transition.

Abstract: In the context of secondary school principals, delocalization refers to the practice of transferring principals from one school to another within a sub-county, county or region. Principal delocalization policy has been linked to have an effect on the quality of teaching and pupil performance as a whole. Therefore, this study sought to assess the impact of secondary school principals delocalization policy on job performance in Wanjohi Sub-County, Nyandarua County, Kenya. The specific objective was to investigate the influence of community resistance on job satisfaction following principal delocalization in Nyandarua County. The study applied mixed methods approach. Population for this study was 18 public secondary schools in Wanjohi Sub-County, Nyandarua County, Kenya. This study applied purposive sampling techniques which involved the selection of all 18 respondents. The research employed a questionnaire (for quantitative approach) and interviews (qualitative). Quantitative data was analyzed using descriptive statistics such as frequencies, percentages, with the help of Statistical Package for Social Sciences version 24.0 which was displayed using tables and figures. Qualitative data was analyzed, thematically and the findings were presented in a narrative format, allowing for a comprehensive understanding of the themes that emerge from the data. The study found that community resistance had an influence on job satisfaction following principal delocalization. The study concludes that community resistance to delocalized principals which affect coordination and consequently influence teachers’ job satisfaction under the principal delocalization policy. The study recommends that building partnerships between community members and school leaders can create a more supportive environment that ultimately enhances job satisfaction for educators. Moreover, this study recommends that there should be open communication between school administrations, teachers, and the community.

Abstract: The objective of the study was to examine the influence of school climate characteristics on student’s academic achievements in physics in Science Technology Engineering and Mathematics (STEM) model schools in Nairobi Metropolitan region, Kenya. The study used convergent parallel mixed method design. The target population comprised 11principals, 60 teachers and 1120 students with a sample size of 368. Proportionate stratified sampling and simple random sampling was used to select students while purposive sampling was used to select teachers of physics and principals. Questionnaires, document analysis guide and interview guide were used to collect data. Descriptive statistics (frequencies and percentages) were used to analyze quantitative data. Thematic and content analysis were used for qualitative data analysis. The study found that school climate characteristics influence student’s academic achievements in physics in STEM model schools in Nairobi Metropolitan region, Kenya. Having a positive student-school staff and management relationship motivates students to do better in physics. Also, friendly student-student relationships allow them to help each other in understanding physics concepts. The study recommended that principals should advocate for healthy relationships between the principals and teachers, teachers and students and students and students. The school management through the principals should ensure that enough science and computer laboratories are constructed and equipped with the required teaching and learning material such as overhead projectors, robotics kits, audiovisual materials, cathode ray oscilloscopes and digital cameras.

Abstract: The increasing integration of Artificial Intelligence (AI) into education has raised questions about its utilization in academic environments, particularly in STEM fields. This study focused on the utilization of AI-based tools among STEM students at Lagos State University. The research sought to determine the level of awareness, usage patterns, and perceptions of AI tools, with particular attention to whether AI could replace or assist human instructors. The study was guided by three research questions and two hypotheses centered on AI’s impact on research and education. A descriptive survey research design was adopted, with a population comprising STEM students across different academic levels. A sample size of 150 respondents was selected through stratified random sampling. Data were collected using a structured questionnaire, validated with a reliability index of 0.82. The analysis was conducted using descriptive and inferential statistics. The results indicated that 95.1% of the respondents had utilized AI tools, with ChatGPT being the most commonly used. Students generally found AI tools effective in enhancing their research outcomes, but challenges such as technical difficulties and limited access were prevalent. Furthermore, while students acknowledged AI’s potential to assist educators, a majority emphasized that AI should not replace human instructors due to its lack of human empathy and adaptability. The study concluded that AI-based tools are beneficial for research and education, but there is a need for improved access and training. It was recommended that educational institutions invest in AI tools and ensure that students receive adequate training to enhance their research skills while maintaining a balance between AI usage and human-led learning.

Abstract: In this paper, a comparative thermodynamic performance analysis is presented for Evaporative Cooling and Mechanical Chilling, two inlet air cooling techniques for simple cycle gas turbines in tropical environments. While numerous papers in the literature have examined different cooling methods, this study is particularly focused on the evaluation and comparison of the performance of these two widely employed techniques under Nigerian Climatic Conditions. The research employs operating data from a Nigerian gas turbine power station combined with MATLAB-based modeling to simulate the effect of each cooling method. Performance was assessed under two Relative Humidities, 30% and 70%, typical of the country's two major climatic zones. The key parameters assessed are net work output, Thermal Efficiency, and heat rate. The findings indicate that, against common belief, Evaporative Cooling performs more positively in both low- and high-humidity environments. Although Mechanical Chillers achieve ambient-independent cooling performance regardless of the ambient conditions, their advantage is limited to extremely high ambient temperature with high Relative Humidity conditions, where Evaporative Cooling becomes inefficient. In most other situations, Evaporative Cooling performs better in enhancing Gas Turbine performance. These results necessitate the need for a climate-sensitive approach in the selection of Inlet Air Cooling technologies. Rather than adopting a single-fit-all approach, power plant operators are encouraged to align their choice of cooling systems with the prevailing environmental conditions in specific locations. Practical suggestions that can assist in improving overall efficiency and reliability of power generation in Nigeria's different climatic regions are provided by the study. By determining the conditions under which each cooling technology is optimally effective, the paper contributes to more informed decision-making in Gas Gurbine performance enhancement in tropical climates.

Abstract: The assessment of sanitation and wastewater management at Murtala Muhammed International Airport (MMIA), Lagos, was conducted to quantify sewage generation, evaluate effluent quality, and identify the rehabilitation needs of the sewage treatment plant (STP). Passenger and facility usage data indicated an annual sewage output of 1,117,087 cubic meters, equivalent to 255.04 cubic meters per day; when including contributions from service vehicles, the total increased to 275.04 cubic meters per day. Laboratory analyses revealed widespread non-compliance with benchmarks established by LASEPA, NESREA, WHO, and ICAO: treated effluent exceeded permissible limits for colour (854 Pt-Co versus 250), total suspended solids (154 mg/L versus 100), chloride (493 mg/L versus 250), chemical oxygen demand (201 mg/L versus 200), and biochemical oxygen demand (50.25 mg/L versus 20–50), while dissolved oxygen levels were critically low at 0.53 mg/L (versus ≥2). Microbial indicators persisted positive for total and faecal coliforms. Field inspections confirmed that the STP has been largely non-operational for over three years due to critical mechanical failures. The findings indicate severe risks of groundwater contamination, disease transmission, and regulatory violations. It is recommended that immediate rehabilitation, preventive maintenance, and the integration of sanitation strategies into the airport’s master plan be undertaken to restore compliance and resilience, thereby contributing to the achievement of SDG 6.

Abstract: The geologic Coastal Plain Sands is host to large numbers of onshore hydrocarbon exploration and processing activities and receives a greater part of the adverse environmental impact, including soil and groundwater contamination. This study explores the spatial and vertical distribution of hydrocarbon contamination in coastal plain sands typified by the Ogoni area (using indicator parameters of TPH and PAH) to assist with identification and delineation of vulnerable horizons as well as target specific contaminated areas as a remediation strategy. The investigations utilized a combination of Electrical Resistivity Tomography (ERT) and geotechnical boring to delineate hydrocarbon contaminated areas and laboratory testing for determination of concentrations/degrees of contamination. The 2-D ERT tomograph for the different survey lines were concatenated to provide a 3-D view which enabled horizontal slices corresponding to depths of interest to be assessed for possible contamination. The lithologs obtained from boring were further used in lithological modelling to precisely define the 3-D distribution of the contaminated zone. The results indicate that the ultimate distribution of hydrocarbons in the subsoil is influenced by topography, the physical and chemical characteristics of the compounds as well as those of the affected soil such as permeability and water table variation. In addition, climatic factors such as rainfall and temperature have a great influence on the reactions and the movement of the hydrocarbons plume in the subsoil. Because of their low densities, light hydrocarbons tend to spread laterally and are therefore commonly found at the interface of unsaturated-saturated zones while denser hydrocarbons tend to move vertically down through the subsoil into the saturated zone and migrate downward until they are restrained by an impermeable layer. This implies that the top soil in aged spill sites within the coastal plain sand become renovated by natural attenuation over time and tend to exhibit low levels of hydrocarbon contaminations.

Abstract: This study explores the impact of lecturer feedback on student learning in a higher education institution in the Maldives. Recognizing feedback as a cornerstone of formative assessment, the study examines the relationship between feedback quality, timeliness, and student academic performance. A quantitative, cross-sectional survey design was employed, sampling 220 undergraduates studying from 2nd to 6th semester in the institution, using a validated questionnaire. Data were analyzed using regression analysis. The findings reveal a moderate yet significant relationship between quality feedback and student learning, emphasizing its role in enhancing academic performance and fostering engagement. Additionally, a strong relationship was found between timely feedback and learning outcomes, highlighting its importance in enabling students to promptly address areas of improvement. The study concludes that both quality and timely feedback are critical for maximizing learning impact. The implications suggest structured feedback mechanisms and digital platforms for real-time interactions are important to improve feedback delivery. These insights are valuable for educators and policymakers aiming to optimize feedback practices in higher education. In addition to this, the study contributes to the field highlighting the importance of structured feedback mechanisms offering practical insights for educators and policy makers seeking to enhance feedback delivery and effectiveness in higher education.

Abstract: In the modern times income inequality has been a matter of concern depicting the existence of poverty. With this understanding economists focus on breaking the vicious circle of poverty by achieving the equitable distribution of income. Therefore, the policy formulation revolves around the principle of 'redistribution of income'. Philanthropy is one of the tools to fight the inequality. There are various actors involved in philanthropy such as donors, foundations and beneficiaries. This research paper focuses on the sources of social sector funding in India and brings out the details of those involved in the sector. The paper points out the involvement of corporates and key business figures through ‘family philanthropy’. Driving deep into the conceptual understanding of the area of research following are the objectives, To understand the currents trends in philanthropy in India. To analyse the contributions of philanthropists in driving social change. To evaluate the future potentialities to meet the social sector funding gap. Methodology: This study uses a qualitative content analysis method to examine the India Philanthropy Report from 2021 to 2025. The focus is on identifying key themes related to partnerships, funding strategies and stakeholder roles in the philanthropic sector. Relevant data is extracted from each annual report and organized according to predefined analytical categories. Patterns and trends are then compared across the five years to understand changes and continuities.

Abstract: Collegial relationships among Teachers play a key role in influencing teacher work satisfaction, notably in public secondary schools in Kesses Sub-County, Uasin Gishu County, Kenya. The purpose of this study was to find out the influence of collegial relationships on teacher job satisfaction. The study was guided by the following hypothesis; H01: There is no significant relationship between collegial relationships and teacher job satisfaction. Ex post facto research design was adopted. The study was anchored on Herzberg’s two factor theory. Quantitative data was gathered through a structured survey administered to teachers across multiple public secondary schools, while qualitative insights was obtained from in-depth interviews with selected participants. The data collected was analyzed using descriptive statistics, inferential tests, and regression analyses, among others. Results were as follows; collegial relationship, teacher involvement in curriculum development, teaching and learning resources and physical working conditions had a positive and significant effect on teacher job satisfaction of (β=1.204, p=0.000). The study concluded that collegial relationships enhances teacher job satisfaction. The study further concluded that respecting each other at the school affects teachers’ job satisfaction. Trusting each other helps to improve how teachers relate with one another at the school which subsequently affect job satisfaction. Teacher relationships at school being built on mutual trust affects job satisfaction. Teachers’ commitment to one another at the school affects job satisfaction. How teachers relate with their colleagues being influenced by their level of commitment to one another affect job satisfaction. The study recommended that teachers should respect each other at the school and should trust each other so as to improve how they relate with one another at the school. Teacher relationships at school should be built on mutual trust. Teachers should be committed to one another at the school. A further study should be done on other determinants of teacher job satisfactions in Uasin Gishu County and other counties in Kenya. The study will be of benefit to policy makers and it will be instrumental in shaping educational policies and practices that enhance teacher job satisfaction.

Abstract: Emerging technologies have transformed teaching and learning. Technology is now being used in various fields and is in people ‘s everyday lives incorporated The techno- pedagogical activities have become an integral component in all teaching and learning situations. The paper explores issues related to teaching young learners (3-8) years. A case study has been used along with content analysis to draw evidence from a wide range of techno-pedagogical practices. A blended teaching learning model has been used as a yardstick to measure how online tools and resources are used to enhance learning experiences among young learners. The study found out that techno-pedagogy has witnessed a paradigm shift from the traditional chalk and talk but it has its negative side on the part of ECD children’s holistic development. The study established that techno- pedagogy creates digital divides among children, overreliance on screens, depersonalise children’s learning experiences as well as impacting on physical and mental well-being. The study recommends that children limit technology use while focusing on other tasks and turning off devices where digital activity is not necessary.

Abstract—Smart farming app that connects farmers and buyers on a single platform for crop monitoring and product marketing. It uses secure e-commerce technology to enable fair and profitable transactions. The app offers a reliable information system available through mobile and web dashboards. It provides real-time updates on crop growth, harvest schedules, and daily farm activities. To reach its goals, the study used a quantitative and developmental research design. A modified iterative and incremental waterfall model was applied to meet user needs and business goals. The app was developed with specific tools like Android Studio, Gradle, Firebase, SQLite, and JavaScript, all working in a secure client-server setup. The results show that the app effectively monitors crop development and provides secure e-commerce solutions for farmers and buyers.

Abstract: - This work presents the simulation and performance analysis of a hybrid electric vehicle (EV) powered by solar photovoltaic (PV) modules, a lithium-ion battery, and a supercapacitor, supported by a novel power management framework. The study aims to (i) evaluate the operation of a PV–battery–supercapacitor powered EV under dynamic driving cycles and (ii) investigate the effect of hybrid energy sources on system performance. Synthetic but realistic driving data were employed to analyze vehicle speed, DC link voltage, current sharing, state-of-charge (SOC), efficiency, and energy balance. Results show that the battery provides the primary energy supply (~72%), while the PV contributes ~22% and the supercapacitor ~6%, significantly reducing battery stress. The DC link voltage remains stable around 380 V with minimal fluctuation, while powertrain efficiency is maintained at ~85%. The SOC sustainability confirms extended driving range compared to a pure battery EV. The novelty of this work lies in integrating renewable solar generation with energy buffering from supercapacitors, ensuring improved energy sustainability, stable operation, and reduced dependence on charging infrastructure. These findings demonstrate the potential of hybrid energy management strategies for next-generation electric mobility solutions.

Abstract— This paper presents a detailed technical, environmental, and socio-economic feasibility analysis of a floating solar photovoltaic (FSPV) installation on the Maudaha Dam reservoir in Uttar Pradesh, India. Leveraging a comprehensive dataset compiled by the Remote Sensing Applications Centre - Uttar Pradesh (RSAC-UP) 1 and drawing upon available remotely sensed data and GIS Mapping reports, this study validates the Maudaha Dam as a representative model for FSPV deployment in water-stressed, high-insolation regions. The methodology utilizes a decade of satellite imagery Sentinal-2 to determine the minimum submergence area, providing a robust foundation for long-term project viability.1 The analysis confirms a conservative potential installed capacity of approximately 9.9 MW and an estimated annual energy generation of approximately 40 GWh, which can be seamlessly integrated into the local grid via the nearby 132kV Rath substation, located 14.64 km away.1 The project's co-benefits, including significant water conservation through reduced evaporation and the preservation of agricultural land, are quantitatively and qualitatively assessed.1 Findings suggest that FSPV projects on dams like Maudaha can serve as a dual- purpose solution, simultaneously addressing regional energy deficits and bolstering water security, thereby contributing to sustainable development in the Bundelkhand region.

Abstract Background: Testicular cancer (TC) is a significant health concern among young and middle aged men, necessitating early detection through testicular self-examination (TSE). However, awareness gaps regarding TC and TSE persist, highlighting the need for targeted educational interventions. Methods: A national multicenter cross-sectional study was conducted from March 1, 2024, to April 10, 2025, among 377 eligible male participants (aged ≥18 years) across Punjab, Pakistan. Participants were recruited using convenience sampling through an online questionnaire that was made via questions from standardized tool of WHO for Testicular self examination and testicular cancer. Then validated by Chronbach apha. Eligibility criteria included males residing in Pakistan, aged 18 years or older, with the ability to provide informed consent. A minimum sample size of 384 was estimated using OpenEpi at a 95% CI and 5% margin of error; 430 responses were received, of which 377 were analyzed after exclusions. Age-disaggregated and demographic analyses were performed. Associations between demographic factors and awareness/practices of TC and TSE were examined using Chi-square tests. Results: The median age was 22 years (IQR 21–23). Nearly half (49.9%) of the participants had only limited knowledge of TC, while 30% were completely unaware. Awareness of TSE was even lower, with two-thirds of participants (67%) reporting they had never heard of it. Awareness of both TC and TSE was significantly higher among married participants, older adults (>30 years), and those affiliated with healthcare (p < 0.001). Factors influencing non-practice included lack of knowledge (84%) and fear of discovering a lump (68%). Conclusion: The study highlights the need for targeted educational strategies to enhance TC and TSE awareness. Incorporating TC and TSE topics into healthcare curricula and using social media for public health campaigns can significantly improve knowledge and encourage proactive health behaviors. Addressing perceptual biases and focusing on education are essential for better public health outcomes through early detection and management of testicular cancer.

Abstract: This study presents the design and implementation of a smart vehicle status monitoring and reporting system based on Internet of Things (IoT) technology. The system was developed to address the high rate of road accidents caused by undetected vehicle faults such as engine overheating, improper tire pressure, and excessive vibration. Using an ESP8266 NodeMCU microcontroller, the system integrates a temperature sensor, air pressure sensor, and vibration sensor to monitor three critical parameters of vehicle health. Data are processed in real time and transmitted wirelessly via Wi-Fi to the Blynk cloud platform, where they are displayed on a mobile application interface. Testing under simulated operational and fault conditions showed that the system accurately detected abnormal readings within seconds and provided instant notifications to the user. The system achieved an accuracy deviation of less than ±2% for temperature readings, ±1 psi for pressure readings, and negligible error for vibration detection. Its multi-parameter monitoring capability and low-cost design offer a significant improvement over existing single-parameter solution. The results indicate that the proposed system can enhance road safety by enabling vehicle owners to take proactive maintenance measures, thereby reducing accident risks and repair costs. Future enhancements may include integration with GPS for location tracking, adoption of AI-driven fault prediction models, and ruggedization for deployment in diverse automotive environments.

Abstract- A power system state estimation is a key tool for a reliable and efficient management of electrical power. This paper presents based on new state variables a state estimation method for power system with a large number of branches. In this method, the node voltage and the active current and reactive current of branch are chosen as the state variables. Therefore, measurement functions of ampere and voltage are significantly simplified and no measurements transformation is needed in this method. The observability analysis indicates the proposed method can be used in power system with very limited measurements. Numerical tests on power system with the radial and meshed network show the real-time branch current measurements can significantly improve the accuracy and computation speed of estimation results.

Abstract: Violent flare-ups in herder–farmer conflict often appear suddenly, peak sharply, and dissipate unpredictably across communities. This project adapts rogue-wave dynamics—rare, high-amplitude events emerging from modulation instability in nonlinear systems—to explain and predict such outbreak patterns in Delta State. We model incident intensity as a nonlinear wave field coupled to slow-varying socio-environmental drivers (land use, market shocks, rainfall, policing). Using geocoded incident data (2010–2025), we will (i) test whether conflict clusters exhibit rogue-wave signatures, (ii) estimate conditions that precipitate “surge” events, and (iii) simulate targeted early-warning and response strategies. Outputs include an open dataset, a calibrated model, ward-level risk maps, and policy briefs for state actors and community stakeholders. Existing statistical or diffusion models struggle to capture sudden, high-amplitude incident spikes and their rapid spatial spillovers in Delta State. There is a need for a predictive, interpretable framework that identifies instability windows and guides timely prevention.

Abstract: One of the most intricate and little-studied aspects of unconventional warfare is agroterrorism, which is generally defined as the deliberate targeting of agriculture using biological, chemical, digital, or ecological means. Agroterrorism causes economic shocks, disrupts food systems, and undermines confidence in the safety of everyday life, all of which destabilize societies indirectly in contrast to conventional bioterrorism, which aims to cause direct human casualties. As the backbone of human civilization, agriculture supports social stability, trade, employment, and food production. Therefore, its disruption goes beyond the agricultural sphere and poses a serious threat to both national and international security. Theoretically, agroterrorism is an example of the logic of asymmetry, which states that hostile or non-state actors can have low-cost interventions with disproportionately large results.  Ecological warfare theory presents agriculture as a component of a delicate biosphere that can be purposefully weaponized, while systems theory emphasizes how food supply networks are susceptible to cascading failures as intricate and interdependent systems.  In a similar vein, network theory shows how increased trade increases risks by facilitating the quick cross-border spread of contaminants or pathogens.  Beyond the tangible repercussions, agroterrorism's sociopsychological component exacerbates consumer and farming community mistrust, anxiety, and uncertainty, which fosters social unrest. By focusing on universal vulnerabilities and conceptual models rather than region-specific case studies, this article creates a global theoretical framework for comprehending agroterrorism. It makes the case that agroterrorism needs to be at the center of security discussions in the twenty-first century by combining ideas from human security discourses, resilience studies, and international relations. A comprehensive intellectual model that informs global governance, strategic policy, and collective resilience against emerging agricultural threats is urgently needed, as the study acknowledges food as both a weapon and a target.

Abstract: Globally, the fisheries industry produces millions of tonnes of waste each year, consisting of fish heads, bones, skins, viscera, and shells. While this waste is often discarded or used as low-value animal feed, it actually contains many valuable bioactive compounds such as proteins, collagen, chitosan, omega-3 fatty acids, and minerals. In recent years, researchers, entrepreneurs, and fishing communities have begun transforming this waste into useful products for food, nutraceuticals, cosmetics, agriculture, and biodegradable materials. This paper explores how such innovations are being developed, especially in India, where small scale fishers and start-ups are finding affordable solutions to process fish waste into high-value goods. It discusses the challenges of awareness, infrastructure, and market access, and presents the practical solutions being implemented. The results show that these initiatives reduce pollution, generate income, empower women, and contribute to a circular economy in fisheries.

Abstract: With increasing environmental issues and depletion of resources, the idea of a circular economy is perceived as an effective model for conducting businesses sustainably. This paper investigates how businesses can leverage the principles of the circular economy – which are eliminating waste, improving resources, and extending the life of products – to create sustainable value. The paper discusses pro-circular models of doing business such as product-as-a-service, remanufacturing and closed-loop supply chains, which help companies move from linear to circular models. The circular strategies results in case studies from different sectors prove how these approaches enhance environmental performance while creating opportunities for cost cuts, income generation, and customer loyalty. In addition, this paper highlights some of the possible difficulties that businesses may experience with implementing circular practices such as designing new supply chains and changing consumer habits. The results indicate that there is considerable promise in the circular economy in terms of aiding business organisations to become forces of sustainable growth in a manner where profitability goes hand in hand with beneficial environmental consequences. The businesses can focus on minimizing waste, optimizing consumption of available resources, and enhancing creative processes through adoption of circularity which will enable them to lead the transformation agenda towards sustainability.

Abstract: This study examines the impact of the My Personal Teacher (MPT) online learning platform on the interest levels of secondary school students in Lagos State, Nigeria. As e-learning becomes increasingly prevalent, understanding its effect on student engagement is crucial for effective educational practices. This research utilized a descriptive survey design to gather data on student perceptions and experiences with the MPT platform. A comprehensive questionnaire was administered to a sample of 25 students to assess their interest, engagement, and preferences related to online and traditional learning methods. The data was analyzed using simple percentages and descriptive statistics to identify key trends and findings. The results indicate a strong positive correlation between the use of the MPT platform and student interest in online learning. A significant majority of students reported excitement for online classes (92%) and a belief that the online method is effective (96%). Furthermore, a high percentage of students felt that the MPT platform provided them with opportunities to use innovative learning methods (72%) and that they were able to effectively manage their study time (76%). While a majority (56%) expressed a preference for online learning, a notable portion still valued face-to-face interaction with instructors. In conclusion, this study provides evidence that online learning platforms like MPT can significantly enhance student interest and engagement in the learning process. The findings suggest that by offering flexibility, innovative tools, and a student-centered approach, e-learning can be a valuable supplement to traditional education, leading to improved motivation and academic outcomes. The study recommends the continued integration of such platforms in secondary education to foster a more dynamic and engaging learning environment.

Abstract: This paper is devoted to the spectral collocation method using Jacobi polynomials for Generalized Abel’s integral equations (GAIEs). Jacobi polynomials are used to approximate the solution which reduces GAIEs to a system of algebraic equations. To show the theoretical accuracy of the proposed method, convergence analysis has been proved. Also, the error estimate is approximated which shows that the approximation will converge to the exact solution. Two numerical examples are considered to verify and validate the theoretical results. Further, numerical results are compared using some particular cases of Jacobi polynomials.

Abstract: This study examines outage patterns in the Dugbe Business Unit of the Ibadan Electricity Distribution Company (IBEDC) to highlight reliability challenges and operational improvements at the distribution level within a large Nigerian franchise area. It combines quantitative reliability metrics, such as System Interruption Duration Index (SAIDI), System Average Interruption Frequency Index (SAIFI), and Consumer Average Interruption Duration Index (CAIDI), with qualitative data from stakeholder surveys, interviews, and archival records to analyse outage frequency, duration, and restoration performance. The study identifies key technical and operational factors driving outages. From 2021 to 2024, SAIFI decreased from 520 to 390 interruptions per customer, while SAIDI dropped from 2,800 to 2,200 hours per customer; CAIDI increased slightly from 5.38 to 5.64 hours. The year-to-date figures for 2025 show similar trends: 250 SAIFI, 1,500 SAIDI, and 6.00 CAIDI. These patterns suggest that prevention measures have improved more quickly than restoration efforts, resulting in fewer outages and lower total disruption, but with slightly longer average restoration times. Root cause analysis reveals that certain technical factors- such as air-conditioning equipment, capacitors, cabling, conductors, transformers, and low-voltage lines- as well as random drivers, explain a significant portion of outages, with a persistent downstream pattern at one substation. We recommend a dual approach: enhance event prevention through risk-based and condition-based maintenance, along with targeted undergrounding, while also streamlining restoration processes via automation, OMS/SCADA workflows, staging crews, and spare parts, as well as standard switching procedures. Although focused on distribution outages and limited by the preliminary nature of the 2025 year-to-date data, this analysis provides a practical model for improving reliability and governance at the feeder and business-unit levels.

Abstract: Contract farming has emerged as a significant strategy for modernizing agriculture, enhancing productivity, and integrating smallholders into more profitable markets in India. This study examines the evolution, models, benefits, and challenges of contract farming in India. This study employs a descriptive methodology, utilizing existing data and literature from various sources. The findings indicate that contract farming provides farmers with access to inputs, credit, technical advice, and market opportunities, potentially improving their income and product quality. Different models of contract farming exist, including centralized, nucleus estate, multipartite, informal, and intermediary. While offering benefits such as risk sharing and income stability, contract farming faces challenges such as power imbalances, biased contracts, a lack of suitable institutions, and potentially negative impacts on traditional farming practices. The legal and policy framework for contract farming in India has evolved, with key developments including the Model APMC Act (2003) and the Farm Acts of 2020 (later repealed). Farmer-Producer Organizations (FPOs) play an increasingly important role in enhancing the collective bargaining power and market access of small farmers. Case studies reveal both successes and conflicts in contract-farming arrangements. The effectiveness of contract farming depends on factors such as contract design, institutional support, and specific agricultural and economic contexts. The study concludes that while contract farming offers significant potential for agricultural development and improved farmer livelihoods in India, its success depends on addressing power imbalances, ensuring fair contracts, and developing robust institutional and legal frameworks.

Abstract. In today’s rapidly evolving industrial landscape, sustainability is no longer optional, it’s a core driver of innovation and competitiveness. This study examines how India and South Korea, two prominent players in the global electronics industry, are addressing environmental challenges through differing yet complementary strategies. India leans on policy-driven mechanisms such as Corporate Social Responsibility (CSR) and Extended Producer Responsibility (EPR) to promote inclusive and localized sustainability efforts (MeitY, 2021). In contrast, South Korea advances its agenda through cutting-edge technologies, ESG (Environmental, Social, and Governance) compliance, and smart manufacturing systems (KITA, 2020; KICTI, 2021). Using Bangalore and Busan as regional case hubs, the research explores three key dimensions: energy efficiency, e-waste management, and sustainable sourcing. A structured comparative model is applied to assess policy effectiveness, industry engagement, and measurable environmental outcomes. The findings highlight strengths and challenges unique to each country and propose a hybrid approach that blends India’s socially focused strategies with South Korea’s innovation-driven model. Ultimately, the study offers practical insights for policymakers, business leaders, and researchers working toward a more sustainable and resilient electronics sector (Elkington, 1997; UNEP, 2021; Plepys et al., 2019).this nature, given in the addresses, will be deleted by our typesetters.

Abstract: This analytical study investigates Customer Relationship Management (CRM) practices at the State Bank of India (SBI) branch in Darjeeling, West Bengal. The study's objectives are to evaluate CRM strategies, assess their impact on customer satisfaction and loyalty, and identify the challenges encountered during implementation. A combination of primary and secondary data was used, with primary data collected through a structured questionnaire administered to 75 SBI customers using convenience sampling. This study examined several key variables related to CRM, including customer awareness of CRM policies, perceptions of CRM practices, e-CRM strategies, and customer service. Statistical tools such as ANOVA, correlation analysis, multiple regression analysis, and one-sample t-test were used for data analysis. The findings reveal significant differences between customers' demographic profiles and their awareness of CRM policies. Strong positive correlations were found between CRM awareness, perception, and satisfaction. Customer service significantly influences perceptions of CRM practices, and e-CRM strategies have a substantial impact on customer satisfaction. This study underscores the importance of tailored CRM strategies, effective communication, service quality, and digital banking services in enhancing customer relationships and satisfaction. The findings provide valuable insights for SBI and other banks operating in similar contexts to improve CRM practices and customer satisfaction in the banking industry.

Abstract: This analytical study investigates the impact of human resource management (HRM) practices on job satisfaction among employees in the banking sector in Darjeeling City, India. This study aims to identify the predominant HRM practices, assess job satisfaction levels, analyze the relationship between specific HRM practices and job satisfaction, and compare perceptions between public and private sector bank employees. A structured questionnaire was administered to a sample of 60 bank employees, consisting of 30 each from public and private banks in the region. The data were analyzed using frequency tables, percentages, one-sample t-tests, ANOVA, and Chi-square tests. The findings reveal that the majority of employees perceive HRM practices positively, particularly in areas such as compensation, recruitment and selection, training and development, and the work environment. These practices contribute to high levels of job satisfaction, with 70% of respondents reporting that they are very satisfied with their jobs. Hypothesis testing indicates significant HRM practices in the banking sector, significant quantitative measures of these practices, and a significant association between HRM practices and employee job satisfaction. This study highlights the importance of effective HRM strategies in the banking sector for employee retention and satisfaction, while also identifying areas for improvement. The findings provide valuable insights for bank management and HR professionals in Darjeeling City to refine their HRM practices, potentially leading to better retention rates, increased productivity, and improved overall organizational performance in the competitive banking sector in the future.

Abstract: This article investigates the role of capital markets and securities in enhancing the competitiveness, sustainability, and resilience of small and medium‑sized enterprises (SMEs) in Mozambique amid financial, legal, and foreign‑exchange uncertainties. Drawing upon a comprehensive literature review and an exploratory case‑study methodology, the study examines Mozambique’s tiered market structure - comprising the Official, Second, and Third Markets of the Bolsa de Valores de Moçambique - and compares it with analogous SME exchanges in Ghana, Kenya, Nigeria, South Africa, and the European Union. The findings reveal that access to equity and market‑based debt financing can bridge critical funding gaps, bolster firms’ capital structures, and promote governance improvements through mandatory disclosure and audit requirements. Moreover, capital‑market participation encourages risk‑management practices and provides long‑term funding that mitigates insolvency risks associated with high leverage and currency volatility. Comparative evidence underscores the importance of complementary measures - such as listing‑cost subsidies, investor incentives, capacity‑building programs, and regulatory reforms - to stimulate both SME issuers and investor participation. The Mozambican experience, including the successful “incubation” and graduation of SMEs via the Third Market, demonstrates early signs of enhanced financing access and corporate credibility. However, challenges persist in terms of market liquidity, pricing transparency, and sustaining investor interest. The article concludes with policy recommendations to strengthen the regulatory framework, expand investor‑education initiatives, and develop targeted instruments (e.g., SME bonds, fintech platforms) that can further integrate SMEs into Mozambique’s capital markets. These insights offer valuable guidance for policymakers and practitioners aiming to leverage capital‑market development as a strategic tool for SME empowerment in emerging‑market contexts.

Abstract: In order to bridge the gap between the enormous promise of AI and practicality, this article explores the role of AI in emerging nations. Global AI technological advances will have a significant impact on social and economic growth, particularly in areas that involve a variety of opportunities and difficulties. The paper examines how AI is now adopted in poor countries and examines the advantages, disadvantages, and ethical considerations. The study examines methods and approaches for utilizing AI's revolutionary potential in a variety of industries, including medical care, agriculture, and education, through a thorough literature analysis and case studies. The results highlight the value of talent shortages and infrastructural restrictions being addressed through legislative frameworks, public-private partnerships, and capacity building. Research advances our awareness of the potential and challenges associated with adopting artificial intelligence in developing nations, offering guidance to practitioners, policymakers, librarians, and academics as they navigate this rapidly changing technological environment.

Abstract: As the global construction sector moves toward environmentally responsible practices, the specification of sustainable materials in technical documentation has become crucial. In Nigeria, where the construction industry contributes over 60 percent of national capital projects but relies on outdated documentation practices, working drawings play a central role in translating sustainability goals into built form. This study used a quantitative survey of 605 construction professionals across five Nigerian regions to assess the extent and clarity of sustainable material specifications in working drawings. Results show that 78 percent of working drawings either fail to specify sustainable materials or do so vaguely, while only 22 percent provide detailed specifications. In addition, 48 percent of smart systems were introduced post-design as site improvisations, highlighting weak pre-construction coordination. Key challenges include the absence of standard templates (67 percent), insufficient training (54 percent), and outdated annotation practices (58 percent). The findings indicate that sustainable material documentation in Nigeria remains fragmented and inconsistent, undermining green construction goals. This research provides empirical evidence to an under-explored area of construction practice, contributes to knowledge in architectural documentation and construction management, and offers insights for policymakers, industry professionals, and academics seeking to improve standardization, training, and regulatory frameworks.

Abstract: This study investigates the differences in language and communication development among preschool children living in urban and rural areas of Kien Giang province, Vietnam. Through classroom observations, interviews with teachers and parents, and vocabulary–communication skill assessments with children, the findings reveal that urban children generally possess a richer vocabulary, greater fluency of expression, and higher confidence in communication. These advantages stem from more favorable socio-economic conditions, access to modern educational environments, and stronger parental support. In contrast, rural children tend to experience slower language development, a more limited vocabulary, and fewer opportunities for diverse communication due to constraints in learning resources, educational facilities, and the surrounding living environment. The study further indicates that these disparities are influenced by multiple factors, including parental involvement, socio-cultural conditions, and the quality of preschool education in each setting. Based on these findings, the research proposes several solutions to reduce the gap, emphasizing the joint role of families, schools, and local authorities in creating a rich and diverse linguistic environment for preschool children.

Abstract: In the contemporary hyperconnected marketplace, marketing communication has undergone a fundamental transformation from broadcast messaging to relationship-centered dialogue, prioritizing authentic engagement over traditional promotional tactics. This chapter explores the paradigmatic shift from interruption-based advertising to value-driven engagement, examining how successful brands navigate the increasingly complex landscape of multichannel communication while maintaining authenticity and measuring the genuine impact across diverse customer touchpoints. Through a comprehensive analysis of contemporary consumer behavior, emerging technologies, and evolving cultural expectations, this chapter presents a practical roadmap for developing communication strategies that resonate with modern audiences across diverse touchpoints and cultural contexts. Furthermore, the analysis synthesizes insights from behavioral psychology, neuroscience research, and digital anthropology to provide evidence-based guidance for marketing professionals seeking to build sustainable competitive advantages in rapidly evolving communication environments. The chapter emphasizes the critical importance of ethical communication practices, data-driven personalization balanced with privacy considerations, and the strategic integration of human creativity with technological capabilities that enhance rather than replace authentic relationship-building. By focusing on building genuine relationships rather than merely driving transactions, marketing professionals can create sustainable competitive advantages while contributing positively to society and fostering trust in commercial communication that benefits all stakeholders. Moreover, the analysis draws from recent developments in neuroscience, behavioral economics, and digital anthropology to provide evidence-based insights into effective communication design and implementation strategies in contemporary multichannel environments. Consequently, this comprehensive approach enables organizations to develop communication strategies that not only achieve immediate business objectives, but also contribute to long-term brand equity and customer loyalty through authentic value creation.

Abstract: Periyar E.V. Ramasamy, also known as Periyar, had a progressive and forward-thinking perspective on women’s rights. He was a staunch advocate for gender equality and believed that women should have the same rights and opportunities as men. There are many key aspects of Periyar’s perspective on women’s rights. Education was something Periyar believed that women should have equal access to. He argued that education was essential for women to be economically independent and intellectually empowered. One of Periyar’s core beliefs was that women should be able to be independent of men in all ways including financially, socially and intellectually. His legacy continues to inspire movements for women’s rights and empowerment in the region.While Periyar made significant strides in promoting women’s rights and gender equality, it’s important to acknowledge that societal change takes time. His efforts laid the foundation for future generations to continue working towards a more equitable society for women in India.

Abstract: The exponential growth of data-driven research and technological advancement has created an unprecedented demand for accessible, well-organized datasets across educational and research institutions. This project presents the development of a comprehensive web-based platform designed specifically for dataset sharing and collaboration within academic environments. The Academic Data Repository addresses the critical gap in localized, user-friendly data management systems by providing students, educators, and researchers with an intuitive interface for uploading, exploring, reviewing, and downloading diverse datasets. The platform implements a robust authentication system with role-based access control, enabling differentiated functionality for administrators, faculty members, and students. Key features include multi-format dataset support (CSV, Excel, JSON, PDF), automatic Excel-to-CSV conversion, real-time file preview capabilities, and a sophisticated version control system that allows collaborative dataset management. The system incorporates a community-driven review and rating mechanism to ensure dataset quality and relevance, while advanced search and filtering capabilities facilitate efficient dataset discovery. Built using modern web technologies including PHP 8.0+, MySQL 8.0+, HTML5, CSS3, and JavaScript ES6+, the platform emphasizes security, scalability, and user experience. Security measures include bcrypt password hashing, CSRF protection, SQL injection prevention through prepared statements, and comprehensive input validation. This project contributes to the advancement of academic data management by providing an open-source, locally deployable solution that addresses the specific needs of educational institutions in developing regions. By fostering data sharing and collaboration, the platform promotes research transparency, educational resource accessibility, and collaborative learning environments. The successful deployment of this system demonstrates the feasibility of developing sophisticated web applications that combine technical excellence with practical utility in academic settings.

Abstract: This paper is on “Communicating Cybercrime Proliferation in Nigeria Economic Recession since 2015: a case of Enugu State Youths.” The general objective is to ascertain the level of knowledge of respondents towards cybercrime engagements in Enugu state Nigeria. It is a cross-sectional study of 384 respondents. The total population of the study is 1.380,000 across various local governments in Enugu State, Nigeria. The work was anchored on “Social Learning Theory”. The data was collected using questionnaires. The instrument was administered purposely and analyzed using SPSS version 25.0. The results were presented on simple tables and percentages. The data showed respondents’ level of knowledge on cybercrimes was moderate and majority of the respondents believe the inflation rate fluctuations since 2015 in Nigeria necessitated cybercrime engagement intensification by Youths in these regions. Despite the death punishments for cybercrimes culprits globally, many Nigerian youths in this region still engage in various cybercrime activities. The respondent’s adoption of several cybercrimes reflects wealth chase and lack of contentment by young people. The various issues resulting in dependence on cybercrimes as a lifestyle is fueled from greed, unhealthy competition, peer pressure, poor institutional management and all these have attributed prevalence nature of deep cybercrime culture.  Although the social issues constituted to the reason for cybercrime engagements, the consequences and adverse effects of cybercrimes can shortchange youths’ prospects. The work recommends a mailable policy that enshrines crime consequences in school curricular from Primary schools to help curb inherent crime culture in the teeming youths.

Abstract: This study assessed quality characteristics of Profile Aluminium Sheets Industry in North-Central States, Nigeria. This helps in ascertain level of quality implementation acceptable standard by Nigeria Industrial Standard, NIS 488: 2010 (NIS, 2010).  The industry include Eastchase Aluminium Markudi (A2), Altex Aluminium Lokoja (B1), Shelther Aluminium Ilorin (C2), Andy Aluminium Mararaba (D1), Queesway Aluminum Minna (E1). The quality characteristics test conducted on the profile aluminium sheet include coated characteristics, surface charactristics and chemical constituents of the profile. These include impact resistance, MEK double rub, physical requirement and chemical composition. The test was based on NIS 488: 2010 requirement (NIS, 2010). It was observed only Andy Aluminium Mararaba (D1) and Queesway Aluminum Minna (E1) met major requirement. This indicates majority of profile industries in North-Central State, Nigeria yet to full specification requirement of profiling sheets.  

Abstract: Industrialisation is considered a cornerstone of development strategies. This popularity is due to the significant contribution that industries make to economic growth and human welfare. Industrial production provides goods, services and jobs. At the same time, it is a major source of pollution and waste. This scenario is evident in the long-standing presence of International Breweries Limited, the Ilesa plant, and the surrounding communities. It is against this background that this study investigates the effect of industrial activities, most especially emissions, on air quality in communities around International Breweries Limited, Ilesa, Osun State, Nigeria. Using a random systematic sampling technique, researchers conducted a survey of 500 residents within an area of one square kilometre of the industry. The parameters of interest include awareness of industrial activities, perceptions of air quality, health and environmental effects, community responses, and suggestions. Other primary data were collected through field observation and focus group discussions in the study area. The collected data were analysed using descriptive and inferential statistics for principal component analysis. Major findings from the study showed that 91% of the respondents are aware of the operations of the industry in the area, but only 46% are aware that industrial processes can emit substances into the air. 57.6% of the respondents also confirmed changes in the air quality around the industry. Although 12% and 23% of the respondents noticed cough and eye irritation, respectively, among the people around the industry, 75% confirmed that there was no noticeable health issue in the area. During the focus group discussion, the respondents identified noise pollution as the primary impact of the industry. Emissions of carbon monoxide, heaps of factory waste, and road congestion associated with factory noise were the major observations in the industry during the survey. The study concluded that there is air and noise pollution as a result of industrial activities, leading to obvious environmental degradation in the area. Therefore, there is a need for proper environmental control and management to ameliorate the adverse effects of industrial emissions, waste deposits, and noise pollution in the area.

Abstract: This study examined the effects of automobile maintenance management on the quality of passenger service delivery in Ilala Municipality, Dar es Salaam, Tanzania. It explicitly examined three types of public transport services: commuter services, intercity bus services, and tour services. The study was steered by the Resource-Based Theory, Institutional Theory, and Human Capital Theory, which together provided insights into how the resources, organizational practices, and employees competencies affect service delivery. A cross-sectional survey design was adopted, and data were gathered through structured questionnaires managed to 100 defendants, chosen using both simple random and purposive sampling techniques. The composed data were analyzed using SPSS version 30. Correlation and multiple linear regression analyses were used to evaluate relationships and effects amid the study variables. The results revealed that automobile maintenance management plays an important role in ensuring safety, efficiency, and customers’ satisfaction in passenger transport services. Thus, the well-managed vehicle maintenance proved to reduce service interruptions, minimize mechanical failures, enhance operational reliability, and improve the overall insight of service quality among passengers. The study concludes by stressing the importance of maintenance management in the sustainable delivery of commuter, intercity, and tour transport services in Tanzania.

Abstract: This study addresses the philosophy of management via the twin lenses of scientism and technology within organizational contexts. Scientism, characterized by the focus on empirical facts and scientific procedures, has profoundly affected current management practices by fostering objectivity, efficiency, and predictability. Simultaneously, fast technology innovation has altered organizational structures, procedures, and decision-making methodologies. While both scientism and technology offer great instruments for enhancing performance, their dominance can obscure the human, ethical, and contextual components of management. This paper critically evaluates these factors, proposing for a balanced management philosophy that mixes scientific rigor and technical competence with human-centric values and ethical considerations. Such holistic strategy helps firms to stay inventive, adaptive, and socially responsible in a more complicated and digitalized word.

Abstract: Atmospheric pressure is the force per unit area exerted by the weight of the atmosphere. Dew point is the temperature to which air must be cooled to become saturated with water vapor, assuming constant air pressure and water content. In this research, the estimation of atmospheric pressure from dew point was conducted at an experimental site near the Physics/Electronics Unit laboratory at Kwara State Polytechnic, Ilorin, Nigeria. For the field observations, an instrumented Meteorological Weather Smart System was set up at an experimental site near the Physics/Electronics Unit laboratory, Kwara State Polytechnic, Ilorin, for a period of two weeks (20th May - 3rd June, 2022). The atmospheric pressure and dew point measurements from the Weather Smart System were recorded every 10 seconds and averaged over 2 2-minute intervals. The sampled data was then stored in the datalogger storage module. After removing spurious measurement values, the data stored was further reduced to hourly averages using Microcal Origin (version 7.0) data analysis software. In this research, the acquisition of the data was achieved by using Weather Smart datalogger systems (measurement and control module). An RS232 connection to the computer for communication purposes was achieved by using a USB cable. The datalogger is wirelessly connected to all the sensing elements, thereby accepting their respective signals. The transducers' signals were then sampled, digitized, and stored in the internal/expanded memory. The data, which were collated in ASCII format, were then reduced using a data reduction program, MicroCal Origin 7.0 Version. The results showed that the predicted atmospheric pressure,  was compared with the actual measurements,  and remarkably good agreement have been obtained with the MBE = 0.68 hpa; RMSE = 6.67 hpa , and r = 0.55. The parametric equation obtained in this research was found to be:         

Abstract: This report presents the results of research conducted at Auchi, Edo State, Nigeria, to evaluate the effectiveness of UA741-based op-amp configurations in enhancing student learning. The study utilized the instrumentation module developed by Jibunor et al. (2025) in their work titled "Design and Development of an LM741 Instrumentation Module for Enhancing the Teaching of Basic Analog Circuit Principles in Physics and Electrical Engineering" [International Journal of Research and Scientific Innovation (IJRSI), [https://rsisinternational.org/journals/ijrsi/articles/design-and-development-of-an-lm741-instrumentation-module-for-enhancing-the-teaching-of-basic-analog-circuit-principles-in-physics-and-electrical-engineering/]]. Traditional electronics education often struggles to connect theory with practical application, making it hard for students to understand op-amps in circuit design. "This study involved 40 second-year students from the Physics and Electrical Engineering programs, divided into two groups of 20. One group served as the experimental group, assessing the UA741 module through six configurations: voltage follower, inverting amplifier, non-inverting amplifier, summing amplifier, difference amplifier, and integrator, while the other group functioned as the control group. Knowledge tests were given at the end of the lessons, based on Bloom’s taxonomy, covering knowledge, comprehension, application, analysis, synthesis, and evaluation. Results showed that using the UA741 module significantly improved both the quantity and quality of student achievement compared to the traditional "chalk-and-talk" method. Data analysis focused on performance characteristics like voltage gain, waveform shapes, and input-output relationships, confirming expected behaviors. These findings highlight the effectiveness of hands-on experimentation in enhancing student understanding of electrical and electronic concepts, thus improving teaching effectiveness.

Abstract— This study investigates the determinants of hotel room pricing in ASEAN member states using a dataset of 18,215 observations. The research extends the traditional hedonic pricing model by retaining only statistically significant predictors, thereby improving both explanatory accuracy and practical application. The findings highlight five critical determinants of hotel room pricing: hotel class, occupancy rate, room revenue, resort-town or beachfront location, and independence from major chains. Revenue per Available Room (RevPAR) demonstrates the strongest positive association, while independent hotels consistently price lower than chain-affiliated properties, underscoring the influence of brand strength. External geographic factors further enhance pricing power, confirming prior evidence on location-based premiums. In contrast, variables such as hotel size, franchise ownership, and generalized location categories were found to be statistically insignificant, streamlining the model and improving interpretability. Beyond methodological refinement, this research signals a shift in pricing strategy attitudes within the ASEAN hospitality sector. By aligning econometric rigor with industry relevance, the study advances both theory and practice. It demonstrates how robust statistical models can guide managerial decision-making, inform policy, and enrich classroom instruction. As a first step in the integration of econometric approaches into regional hospitality pricing, the framework provides a foundation for more precise, evidence-based strategies across both academic and professional domains.

Abstract: The Skill India initiative, launched in 2015, aims to equip young Indians with skills and knowledge to enhance employability and promote entrepreneurship. This study assesses the effectiveness of Skill India in fostering entrepreneurship within higher education institutions (HEIs). Our findings indicate that the program has significantly contributed to the growth of an entrepreneurial culture in HEIs, evident in increased student participation and successful start-ups. However, challenges such as inadequate funding, limited industry exposure, and the need for a more inclusive approach need to be addressed. This study provides valuable insights into the impact of entrepreneurship development programs on students' entrepreneurial mind-set, knowledge, and skills. This study highlights the potential of Skill India in shaping the entrepreneurial landscape of India's youth. By examining the program's impact on HEIs, we can better understand how to create a supportive ecosystem for entrepreneurship to thrive. The findings of this study can inform policymakers and educators on how to design and implement effective entrepreneurship development programs that cater to the needs of students from diverse backgrounds. Ultimately, this research contributes to the growing body of literature on entrepreneurship education and its role in promoting economic growth and development in India.

Abstract: This study focuses on the empowerment of tribal women in India through diversifying their livelihoods, as there is marginalization which is caused by socioeconomic and cultural barriers. This study seeks to understand how tribal women economic position and general welfare can be improved by looking at various sources of income other than the traditional subsistence activities. The study employs a two-fold approach that involves the combination of quantitative survey with qualitative interviews in different tribal societies in India. The findings indicate that the diversification of sources of income significantly increases the financial independence, decision making of tribal women, and their social status. However, there are still barriers like limited education, credit and market distribution which remain quite significant. In the study, particular policy actions are highlighted in order to help tribal women in education, skill development and improved market relations to maximise the benefits of diversifying their livelihoods as a form of empowerment. This study contributes to the broader debate around gender equalities and sustainable development in underserved communities.

Abstract: A novel NR/PVP/CB semi IPN composite film of different composition were synthesized by solution casting process using glutaraldehyde (GA) as the crosslinking agent. The semi IPN blends were characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetry, differential scanning calorimetry. Swelling kinetics of semi IPN blends in toluene were studied by weighing blends swollen with toluene at various time points. Swelling rate decreases linearly with the incorporation of PVP demonstrated the removal efficiency of toxic insecticide bendiocarb due to the development of entangled networks in the semi-IPN synthesized. It is evident that theoretically calculated Smax values and the equilibrium swelling ratio obtained experimentally are in good agreement. The swelling exponent (n) values of all system were found to be in between 0.47 and 0.58 signifies that diffusion mechanism follows a Fickian mode of transport. The effect of thermal stability on the in cooperation of PVP and carbon black into the natural rubber latex was studied. A notable bendiocarb removal efficiency is seen from the developed semi IPN composites, along with PVP-induced swelling capacity in water medium that enhances pesticide diffusion.

Abstract: Increasingly shifts in education into the digital age has challenged institutions of learning to rethink how learning is delivered especially in different fields including environmental education that demand both theoretical and practical engagement. This study explored how digital transformation can enhance teaching and learning in environmental education in the University of Port Harcourt. Using a descriptive survey method and a sample of 360 respondents comprising lecturers and students, the study examined levels of awareness, perceived benefits, and the challenges encountered in implementing digital tools. The findings revealed a high level of awareness about digital platforms such as Zoom, Google Classroom, and other learning management systems. However, actual usage was limited due to challenges like poor infrastructure, insufficient ICT training, and irregular power supply. Despite these setbacks, respondents acknowledged the value of digital learning in promoting flexibility, engagement, and access to resources. Based on the findings, the study recommends increased investment in digital infrastructure, consistent capacity building, and targeted motivation strategies to bridge the gap between digital awareness and practical implementation. If well harnessed, digital transformation can serve as a powerful tool to enrich environmental education and prepare students for solving real-world ecological problems.

Abstract: This study traces management’s evolution from Frederick W. Taylor’s early 20th‑century scientific management to the contemporary phenomenon of algorithmic management, probing how technological advancements have fundamentally transformed managerial logic and dynamics. Taylorism emphasized optimizing labor through meticulous time‑and‑motion studies, task standardization, top-down control, and managerial oversight, aimed at maximizing economic efficiency and reducing reliance on worker discretion. In contrast, algorithmic management entrusts managerial functions such as monitoring, performance assessment, scheduling, goal‑setting, compensation, and even dismissal to algorithms and automated systems. Enabled by real‑time data collection, predictive analytics, and digital platforms, algorithmic management enables organizations to manage dispersed labor at scale with unprecedented precision. While both approaches share enduring principles like efficiency, standardization, and control, the shift from human supervision to software‑mediated governance introduces distinctive dynamics. Algorithmic systems create triangular visibility regimes rather than traditional hierarchical oversight, often obscuring decision logic and engendering information asymmetries, where employers and increasingly algorithm designers hold more knowledge than workers do. Moreover, the impacts of algorithmic management are complex and dual in nature. Empirical and theoretical literature suggests such systems can simultaneously restrict and enable worker autonomy and value creation shaping workstation design, job demands, well-being, and motivation. This duality underscores that algorithmic management’s consequences are not predetermined by technology but are contingent on sociotechnical design and implementation choices. The paper explores how these shifts play out in contemporary labor contexts - from gig platforms to fulfillment centers where workers are subject to algorithmic surveillance and quantified performance regimes, compelling new forms of worker resistance, adaptation, and negotiation of agency. Integrating Labor Process Theory, the analysis reveals how algorithmic systems reenact power asymmetries and labor control while posing fresh challenges and opportunities for worker autonomy and organizational justice. It argues that as management becomes digitized, practitioners, policymakers, and scholars must critically assess algorithmic design, prioritize ethical implementation, and craft frameworks to preserve worker dignity, transparency, and fairness.