Volume 14 Issue 7

Abstract: The digital era has revolutionized the way organizations communicate, collaborate, and innovate. With the proliferation of remote work, cloud-based platforms, artificial intelligence (AI), and natural language processing (NLP), digital communication strategies have become critical to organizational success. This paper provides an in-depth analysis of advanced digital communication strategies, focusing on the comparative effectiveness of synchronous and asynchronous tools, the transformative role of cloud collaboration platforms such as Google Workspace, Microsoft 365, and Notion, the integration of AI and chatbots, the importance of digital fluency and etiquette, and the identification of communication gaps through global surveys. The findings reveal that asynchronous communication enhances productivity and work-life balance, while AI-powered tools significantly reduce miscommunication and streamline workflows. However, disparities in digital fluency and access remain, particularly among deskless and frontline workers. The paper concludes with actionable recommendations for organizations seeking to optimize their digital communication landscape in an era of rapid technological change.

Abstract—Advanced forensic approaches are required to handle digital crimes because they need to provide transparent methods that foster trust and enable interpretable evidence in judicial investigations. The current black-box machine learning models deployed in traditional digital forensics tools accomplish their tasks effectively yet fail to meet legal standards for admission in court because they lack proper explainability. This study creates an Explainable Artificial Intelligence (XAI) system for digital forensics to improve flagging events as legal evidence by establishing high levels of trust and transparency. A digital evidence system employs interpretable machine learning models together with investigative analysis techniques for the detection and classification of computer-based irregularities which generate clear explanations of the observed anomalies. The system employs three techniques including SHAP (Shapley Additive Explanations) alongside LIME (Local Interpretable Model-agnostic Explanations) and counterfactual reasoning to deliver understandable explanations about forensic findings thus enhancing investigation clarity for law enforcement agents and attorneys as well as stakeholder professionals. The system performs successfully on actual digital forensic datasets thus boosting investigation speed while minimizing wrong alerts and improving forensic decision explanations. The system must demonstrate GDPR and digital evidence admission framework compliance to maintain legal and ethical correctness for usage in court procedures. Forensic digital investigations need explainable Artificial Intelligence as an essential integration for creating reliable and legally sound practices.

Abstract: In today’s digital world, access to information is essential for personal growth, education, and empowerment. However, government censorship continues to limit this access, and women are often among those most affected. This study explores how censorship impacts women's ability to obtain important information—especially on issues like education, health, and gender rights. By analyzing different cases worldwide, this research highlights the inequalities created by censorship and the ways it restricts women’s voices in media and public spaces. Through a combination of surveys and academic research, the study examines how censorship operates, whether through direct restrictions, biased media representation, or online harassment. The findings show that censorship can deepen gender inequalities, silence critical discussions, and even impact women’s mental well-being. The study also emphasizes the role of social media, where women journalists and activists face online violence, leading to self-censorship and reduced participation in public discourse. To address these challenges, the research suggests policy changes that promote freedom of information and gender-inclusive media representation. It also highlights the need for better legal protections and awareness campaigns to ensure women can freely access and share information. Ultimately, this study advocates for a world where information is available to all, empowering women to make informed choices and actively participate in society.

Abstract: Digital technology has profoundly influenced higher education, reshaping traditional teaching and learning paradigms. This review paper synthesizes existing literature to examine the transformative impact of digital technology adoption in higher education. It explores various dimensions of this impact, including work practices, learning outcomes, institutional dynamics, and the roles of educators and students. Additionally, the paper discusses challenges and opportunities associated with digital technology integration, such as accessibility, digital literacy, and privacy concerns. Drawing from diverse research sources, this review provides insights into the evolving landscape regarding higher learning in the era of digitalization and offers recommendations for future research and practice. This paper is descriptive in nature. Additionally, the paper discusses the role of digitalization in fostering economic growth, development, and sustainable practices. By shedding light on the multifaceted nature of digitalization, this abstract seeks to foster a deeper understanding of its implications and opportunities in an increasingly digital world.

Abstract: This review article examines the current state and future prospects of systems for storing thermal energy in concentrated solar power (CSP) plants. CSP technology has drawn a lot of interest as a renewable energy source, but its intermittent nature necessitates efficient energy storage solutions. The paper provides a comprehensive overview of various TES technologies, including thermochemical, latent, and sensible storage methods, analyzing their performance, cost-effectiveness, and scalability. Key challenges such as material degradation, heat transfer efficiency, and system integration are discussed. Recent advancements in novel storage materials, heat transfer fluids, and system designs are evaluated, with a focus on their potential to enhance overall plant efficiency and reduce levelized cost of electricity. The review also explores emerging trends, such as high-temperature storage systems and hybrid configurations, assessing their potential impact on the future of CSP technology. Finally, the paper identifies critical research gaps and provides recommendations for future developments to improve the viability and competitiveness of CSP plants with integrated systems for TES.

Abstract: This study provides an overview of design methodologies for thermal energy storage systems and examines the key factors in concentrating solar power (CSP) facilities at various levels of hierarchy. A crucial component for enhancing power plant dispatchability is thermal energy storage. While numerous reviews have focused on storage media, few have addressed the design of storage systems and how power plants incorporate them. In addition to analyzing the thermal and energy efficiency of various storage systems integrated into power plants, this research looks at the designs of thermal energy storage systems that have been published in the literature. Additionally, this work summarizes these systems economic components and important published research.

Abstract: Food is the basic need for human life and agriculture is an activity that allows meeting that demand. Man has been improving his agrarian activity by adding domestication of animals and to supplement his food supply by the flesh of animals and plants that he raises. Adoption of agriculture resulted in reducing the amount of energy man had to spend in obtaining a unit of food. He began to develop better efficiency in tapping the solar energy cycle than the hunting and gathering (Cook,1975). Hubert (1969) equates evolution of human culture with his increasing ability to control and manipulate energy of which agriculture has been the most significant development. Growth of agriculture also led to an era of higher rate of growth and increase in population density. And though it is doubtful to establish the geographical conditions in which agriculture Revolution found its root (Saur,1952) there is no dying the fact that it provided mankind a more sedate way of living that later flourished in the river valleys. Most the ancient civilizations stand testimony to it and where agricultural operation could be carried out more conveniently. However, irrational and excessive use of environmental resources attributed mainly to increasing growth of population is believed to have led to the decline in the carrying capacity and demise of many old civilizations. People sought areas where there would be better productivity and better opportunities for resource use hence food security. Expansion of agricultural activities and ancient migration of people may largely be attributed to this fact.

Abstract: This study explores the eco-friendly extraction of natural pH indicators from locally available plant materials such as rose petals. The extract was tested for effectiveness in acid-base titration and compared with the synthetic indicator phenolphthalein. The natural indicator showed visible color changes and proved to be a viable alternative in rural laboratories where cost-effective and safe chemicals are needed.

Abstract: The study examines the Effect of Bank Specific Variables on the Profitability of listed deposit money banks in Nigeria during the period 2014-2024. Proxies used to measure bank specific variables are bank size and liquidity ratio, while profitability (ROA) was the dependent variable. Panel data was used to analyse the data sourced from the individual financial reports of the listed deposit money banks in Nigeria. The sample adopted ten (10) listed deposit money banks out of the fifteen (15) deposit money banks traded in the Nigerian exchange group (NGX). The study employed panel regression model to estimate the key relationship between bank specific variables and profitability. The result showed that bank size has insignificant effect on profitability of listed deposit money banks in Nigeria, while liquidity has significant effect on profitability of listed deposit money banks in Nigeria. The study recommended that considering the fact that bank size has no significant effect on profitability of listed deposit money banks in Nigeria, managers of deposit money banks should concentrate on providing quality service to their customers instead of embarking on expansion which has no effect on earnings. The study also recommended that managers of deposit money banks should manage their liquid asset efficiently, in order to meet up their day to day financial obligations which will increase profitability.

Abstract: Fintech services helping in overall financial inclusion of the economy in both direct and indirect manner. Fintech is an umbrella term including all technically enabled financial services This paper has the objective of knowing about the role of Fintech in expanding the real meaning of Financial Inclusion in the district . Further through this paper an attempt has been made to analyse the role of users of Fintech in various aspect along with prevailing reasons for unwillingness to use fintech. Methodology of the paper is both descriptive and analytical in nature. Population of the study is definite in nature and hence sample size was selected as per kerjcie and Morgan table (Krejci & morgan,1970). 382 numbers of Responses were collected with a help of self developed questionnaire. Collected data has been analysed with simple arithmetic tools representation of data . Findings of the study came out with some interesting facts . Awareness level  regarding Fintech in Majuli district is in a very low level. Along with some other factors associated with it like various types of risk .There is need of promotion of more awareness in the field of Fintech, so government agencies /NGOs in collaboration with banks can organize some programme to spread awareness about fintech emphasizing more on the risk combating measures which is always attached with the concept of safe practice of Fintech.

Abstract—The D-ATIS system is a crucial communication tool providing pilots with continuous and accurate aeronautical information, such as weather updates, runway details, and other essential notices. This initiative seeks to reduce the workload of air traffic controllers by automating information dissemination and ensuring timely updates of critical data. The system design encompasses several components: The Weather Data Acquisition, the Information Processing Unit, the Voice Synthesis Module, and the Broadcasting Equipment. The implementation plan involves a step-by-step approach which is to conduct an assessment to determine the specific requirements of the airport and its stakeholders, procuring the necessary equipment, ensuring compliance with international aviation standards, installing and integrating the system components with the existing airport communication infrastructure and performing a comprehensive testing and calibration to ensure accurate functionality. This proposal outlines a reliable and effective solution that meets the needs of modern aviation, ensuring continuous, accurate, and timely information dissemination to pilots. Furthermore, the paper proposes a cheaper and easier-to-maintain technology as compared to the systems already on the market.

Abstract: This study aims to describe the form of empathic communication between parents and children in final-year students. The psychological and social conditions of final-year students enter the adult development stage, but they still require parental involvement. They still need acceptance, empathy, support, and parental attachment. In the final years of college, students experience unique psychological and social development. Psychologically, they face various challenges and pressures, both academic and personal. However, on the other hand, they also experience significant emotional growth and maturity. This type of research uses qualitative descriptive methods with in-depth interviews as a data collection technique. There are three pairs of informants with purposive sampling techniques. Data were analyzed using interactive analysis involving the relationship between data collection, data presentation, and verification/conclusions. The research findings show that each parent informant shows a unique but effective empathic communication approach in providing emotional support, including NH with humor and practical support, DA with a motivational approach and value reconnection, and SA with a redefinition of success and unconditional acceptance. This proves that empathetic communication from parents is a very valuable resource and has a significant impact on student well-being and academic success. Efforts to improve empathetic communication skills in families can contribute to mental health and positive educational experiences for students facing the challenges of writing a final assignment.

Abstract: This study addresses the critical issue of power losses in Nigeria's electricity distribution networks, which contribute to energy poverty and high electricity costs. By modeling the Enugu distribution network and integrating distributed energy resources, specifically a hybrid system comprising solar PV, diesel generators, and battery storage, the research evaluates the impact on power losses. Load flow analysis reveals that the integration of distributed energy resources significantly reduces both active and reactive power losses, with a notable 36% decrease in reactive power loss for a key transformer. Notably, the reactive power loss in a key transformer (T10) decreased by 36%, from 201.4 kvar to 128.8 kvar, while active power loss in the same transformer dropped from 10.1 kW to 6.4 kW. Other branches, such as Line604, also showed reduced losses, with active power loss decreasing from 50.9 kW to 49.5 kW. These findings demonstrate the potential of distributed energy resources to improve the efficiency and reliability of power distribution networks, supporting Nigeria's objectives for universal energy access and sustainable development.

Abstract:  The pharmaceutical landscape is undergoing a transformative revolution through the integration of automation and robotics, which offer significant improvements in precision, efficiency, and patient care. This research aims to highlight the transformative impact of these technologies and guide key stakeholders, including researchers, pharmacists, industry professionals, and policymakers, toward informed investment and effective implementation strategies. A descriptive review methodology was employed to explore the historical evolution, classifications, and practical applications of robotic systems, with a focus on Cartesian, SCARA, and articulated robots. The study draws on current literature, regulatory frameworks, and case-based evidence to analyze their adoption and operational dynamics in pharmaceutical premises. Despite challenges such as high initial investment and workforce displacement, the overall findings reflect a net positive contribution to pharmaceutical quality, safety, and global competitiveness. The paper concludes by advocating for strategic adoption, continuous innovation, and regulatory alignment to unlock the full potential of these technologies in modern pharmaceutical practice.

Abstract: Rural tourism in India has emerged as a powerful vehicle for preserving and promoting the country's rich cultural heritage. With an increasing interest in authentic, immersive experiences, rural tourism allows visitors to explore India's traditional lifestyles, crafts, festivals, and landscapes. This paper examines the impact of rural tourism on India's cultural heritage, focusing on how it helps preserve indigenous practices, enhances community engagement, and contributes to sustainable development in rural areas. By fostering awareness and appreciation for local traditions, rural tourism creates economic opportunities for rural populations while ensuring the protection of cultural landmarks and practices. However, the rapid commercialization of rural tourism also presents challenges, including cultural commodification and the potential loss of authenticity. This study highlights both the positive outcomes and the possible risks, advocating for a balanced approach to rural tourism development that prioritizes cultural conservation, local involvement, and responsible tourism practices. Ultimately, rural tourism in India holds the potential to bridge the gap between tradition and modernity, offering a path towards preserving cultural identity while embracing global connectivity.

Abstract: This systematic review examines the relationship between corporate governance practices and financial performance across East African firms. Despite growing interest in governance reforms in Kenya, Uganda, Tanzania, Rwanda, and Ethiopia, empirical evidence remains fragmented and context-dependent, with limited synthesis of regional findings. The main aim of the study is to examine the impact of corporate governance practices on the financial performance of firms in the East African Region. The paper systematically reviewed 19 peer-reviewed studies published between 2014-2024 that examined governance-performance relationships in East African corporations. Using narrative synthesis methodology, the study analysed the effects of board composition, ownership structure, audit committees, and regulatory compliance on financial performance measures including return on assets (ROA), return on equity (ROE), and market valuation metrics. Results indicate positive associations between board independence and financial performance in Kenya and Uganda, with studies showing correlation coefficients ranging from 0.416 to 0.65. However, ownership concentration effects vary significantly, with family-owned enterprises demonstrating different governance dynamics compared to publicly listed companies. Foreign and institutional ownership generally correlate with improved financial discipline, while concentrated family ownership often limits transparency and performance. Audit committee effectiveness shows positive impacts in Tanzania and Uganda, though implementation challenges persist. Regulatory enforcement varies substantially across countries, with Kenya's Capital Markets Authority showing stronger compliance mechanisms than other regional regulators, limiting the overall effectiveness of governance reforms. The findings suggest that institutional context, cultural norms, and enforcement capacity significantly mediate governance-performance relationships in East Africa, requiring region-specific approaches rather than universal governance best practices. This review contributes to understanding governance effectiveness in emerging African markets and identifies critical gaps for future empirical research. The study concluded that sound corporate governance contributes positively to firm performance, particularly by enhancing transparency, accountability, and managerial discipline.

Abstract: Lighting design plays a pivotal role in shaping workplace environments, influencing both the productivity and well-being of employees. This study examines the impact of lighting design on employee efficiency within the Nigerian Stock Exchange (NSE) building. The research aims to understand how lighting conditions affect employee performance, well-being, and overall satisfaction, contributing to the increasing body of knowledge on sustainable and human-centred workplace designs. Quantitative analysis was employed; data collection and analysis were guided through the use of structured questionnaires. Findings reveal that optimum lighting, characterized by balanced brightness, suitable colour temperature, and little glare, significantly enhances employee productivity and reduces visual exhaustion. However, poor lighting conditions were connected to reduced focus, increased stress levels, and lower job satisfaction. Based on the findings, this research suggested viable lighting design strategies suitable for corporate environments, particularly in the circumstances of high-pressure industries. These recommendations aim to foster safer and efficient workplaces that align with sustainable architectural practices.

Abstract: The study designed, developed, and implemented a Decision Support System (DSS) that integrates Time Series Analysis and Forecasting techniques to enhance decision-making and loan disbursement efficiency within the financial sector. A quantitative research approach was utilized, employing the Rapid Application Development (RAD) model for building the system, alongside the Knowledge Discovery in Databases (KDD) process for data mining activities. Classification algorithms enabled the DSS component, while historical data were analyzed through time series methods for forecasting purposes. The classification model recorded an accuracy of 92.3%, while the forecasting component performed consistently well, with a Mean Absolute Percentage Error (MAPE) of 6.4%. System performance and user satisfaction were assessed using the ISO/IEC 25010:2011 quality model, producing an overall weighted mean score of 4.26, reflecting a high level of user acceptance. The integration of classification and forecasting within the DSS contributed to improved efficiency of loan processing, more accurate decision outcomes, and enhanced operational procedures. To ensure the system's continued effectiveness and scalability, the study recommends ongoing model updates and retraining, improvements in system security, and the adoption of a scalable infrastructure capable of handling growing data volumes and user activity.

Abstract: This study presents an integrated renewable energy solution for simultaneous desalination and green hydrogen production, optimized for water-stressed coastal regions with high solar potential. The system combines mechanical vapor compression (MVC) desalination (1.5 m³/h capacity) with photovoltaic power (247 kWp) and electrolytic hydrogen storage (8.1 kg/day), enabling 24/7 operation in Mediterranean climates like Tunisia [1].

Abstract: This study investigates the impact of abiotic stress, particularly drought, on seed germination in drought-adapted plant species native to the arid regions of India, such as Rajasthan and Gujarat. The research aims to understand how water-deficit conditions affect germination dynamics and early seedling development. Laboratory experiments simulated drought conditions using varying concentrations of polyethylene glycol (PEG-6000) to induce osmotic stress. Selected plant species were evaluated for germination percentage, mean germination time, seedling vigor, and biochemical markers including proline accumulation and antioxidant activity. Results revealed significant interspecies variation in drought tolerance, with certain native species demonstrating robust germination performance even under high stress. The findings highlight the adaptive mechanisms of these species and underscore their potential role in sustainable agriculture and ecosystem restoration in water-scarce environments. This research contributes to the development of drought-resilient crops and supports strategic planning for agriculture in regions increasingly affected by climate variability.

Abstract: This study examines how Zimbabwe can harness its diaspora for economic transformation through innovative policy frameworks addressing barriers, opportunities, and entrepreneurship development. Using qualitative desk review methodology and comparative analysis of global best practices, the study analyses Zimbabwe's diaspora investment potential in the post COVID-19 economic context. The research reveals that Zimbabwe's diaspora remittances of US$1.9 billion (January-September 2024), representing 25% of foreign currency earnings, constitute only the consumption-oriented portion of available diaspora financial capacity. Comparative analysis with successful models from India, Philippines, and Nigeria demonstrates potential annual diaspora investments of US$3.8-5.7 billion under appropriate policy frameworks, representing transformational economic impact beyond current informal investment levels of $200-300 million annually. Key findings identify systemic barriers including regulatory complexity, foreign exchange constraints, institutional weaknesses, and limited formal investment channels that deter productive diaspora engagement. However, the study reveals significant opportunities across five high-potential sectors: agribusiness (US$800M-US$1.2B), renewable energy (US$1.5B-US$2.0B), fintech (US$300M-US$500M), manufacturing (US$1.0B-US$1.5B), and real estate (US$800M-US$1.0B). The research proposes an innovative four-pillar policy framework encompassing institutional governance, digital innovation integration, sectoral investment facilitation, and comprehensive risk mitigation mechanisms. Central innovations include blockchain-based diaspora bonds, AI-powered investment matching systems, and cryptocurrency remittance channels that address traditional barriers while creating new engagement opportunities. Implementation projections suggest potential creation of 50,000-75,000 direct jobs over five years with GDP growth contribution of 2.5-3.0 percentage points annually. The framework is envisaged to transform Zimbabwe's diaspora relationship from passive remittance reception to active investment partnership, facilitating technology transfer, market access, and institutional capacity building. This research contributes the first comprehensive Zimbabwe-specific diaspora investment framework while providing actionable policy innovations for similar developing economies seeking to optimise diaspora engagement for sustainable economic transformation and entrepreneurship development.

Abstract: The growing demand for functional beverages has led to the exploration of plant-based ingredients with health-promoting properties. This study aimed to formulate and evaluate a natural functional beverage using guava leaves (Psidium guajava), barley seeds (Hordeum vulgare), ginger (Zingiber officinale) and cinnamon (Cinnamomum spp.). Three variations of the beverage were prepared by altering the quantities of guava leaves and barley seeds, while maintaining constant levels of cinnamon, ginger, and water. Sensory evaluation was conducted using a 7-point hedonic scale, and the best-performing variation was selected based on statistical analysis. Nutritional composition, vitamin, mineral content, antioxidant potential and microbial safety of the optimized beverage were assessed using standard AOAC methods and in vitro antioxidant assays (DPPH, ABTS, and FRAP). The results showed that the detox drink was low in calories (12 kcal/100 g) and contained beneficial nutrients including dietary fiber (1.14 g/100 g), potassium (24 mg/100 g), vitamin E (1.7 mg/100 mg) and vitamin K (4.8 mg/100 mg). The beverage also exhibited strong antioxidant activity particularly in the FRAP (2700.2 mg/100 g) and ABTS (2500.7 mg/100 g) assays. One-way ANOVA revealed a significant difference in sensory attributes among the formulations (F = 7.81, p = 0.0093), indicating the influence of ingredient concentration on consumer acceptability. Microbiological evaluation confirmed the product's safety, with negligible counts of aerobic bacteria, yeast, and mold, and the absence of pathogens. Overall, the formulated functional beverage demonstrated promising potential as a safe, palatable, and health-enhancing functional beverage.

Abstract: Kappa and Scott Pi statistics are agreement measures that are used to measure the level of agreement between two raters. The academic performance of students used is the Cumulative Grade Point Average (CGPA) of year one and the final year.  Year One is classified as rater one and that of the final year is classified as rater two. The Analysis was done to see the consistency in the students’ performance, if the level of agreement is high, i.e. if there is agreement between their first-year result and that of the final year.  A comparison of the Kappa Estimates and that of the Scot Pi was also done to determine the most efficient measure between the two. Kappa Agreement outperforms the Scot pi measures in terms of precision and efficiency. Also, there is no agreement between the Year One Performance and that of the Final Year

Abstract: Audit independence is paramount for corporate accountability and market confidence, particularly in rapidly evolving emerging economies. This study examines its practical application within Kenya's telecommunications sector, using Safaricom PLC – contributing approximately 7% to Kenya's GDP – as a prominent case to illustrate the challenges and implications. Despite Safaricom's robust governance, its prolonged 14-year auditor tenure with PwC Kenya, and KES 167 million in non-audit fees (approaching the 30% local threshold), raised significant concerns about familiarity and self-review threats. This research addresses a notable knowledge gap in understanding these specific challenges within emerging market telecommunications. Employing a detailed case study approach spanning Safaricom's audit relationship from 2009 to 2024, the study analyzed quantitative independence indicators, qualitative changes in audit reports, and stakeholder perceptions. The 2024 auditor transition to EY served as a valuable natural experiment. Findings reveal a strong negative correlation (r=−0.73, p<0.05) between prolonged auditor tenure and audit independence, with the Independence Index decreasing by 2.847 points for each additional year of tenure (p=0.002). This manifested as a 40% decline in management letter issues during PwC's final five years. The transition to EY resulted in an immediate 104% increase in audit fees and a significant rise in management letter issues (from 2 to 8), alongside an increase in investor confidence (from 23.1 to 67.8).

Abstract: Chandigarh's recognition as India's second cleanest city in 2016 was a moment of pride, but its subsequent decline in ranking underscores the urgent challenges in urban waste management. The situation at the Dadu Majra garbage dump site exemplifies this crisis, where waste accumulation is both a visible and systemic issue. This reflects deeper flaws, including inadequate facilities for clean water, sanitation, and electricity in areas surrounding the landfill. The health risks faced by waste pickers further highlight the human cost of poor waste management. Prolonged exposure to hazardous materials leads to respiratory issues, skin infections, and frequent injuries. The absence of protective gear, combined with limited access to healthcare, exacerbates the dangers of this occupation. These issues not only impact individual lives but also point to broader gaps in public health and urban planning. Chandigarh has the potential to reclaim its status as a model city for cleanliness and sustainability with a focused and inclusive effort.

Abstract: The rapid growth of data in smart cities driven by interconnected systems like traffic monitoring, surveillance, and environmental sensing demands efficient and sustainable data management solutions. The aim of this study is to evaluate the effect of policy-based cache control on the performance and sustainability of the storage systems within smart city infrastructures. Synthetic workloads simulating urban data pattern were generated to evaluate system behavior under realistic conditions. Important performance metrics including cache-hit rate, latency, throughput, and energy consumption were analyzed across three different scenarios; namely, no cache, traditional LRU and proposed policy-based control. The findings show that the policy-based approach had an 85% cache hit rate, reduced latency to 70 ms, and improved throughput of 220 MB/s, while decreasing daily energy consumption of 95 kWh. These results shows clear benefits in both performances and energy efficiency. The study concludes that policy-based caching has a strong potential to enhance responsiveness of urban data infrastructure and sustainability. Its relevance to SDG 11 (Sustainable Cities and Communities) lies in its ability to support intelligent and low-impact technological systems, which promote resilient and smart urban growth.

Abstract: Sustainable development is compromised by corruption in small and medium-sized businesses (SMEs). The operational realities of SME were overlooked by current anti-corruption initiatives, which concentrate on extensive corporate governance and public sector reforms. Due to their restricted budget, lack of internal controls, and intimate ties to local authorities, these emerging companies, which were essential drivers of economic growth and job creation, were disproportionately vulnerable to petty bribery, extortion and procurement fraud. The goal of the research was to scrutinise disruptive technologies, new business models, and creative governance practices that SMEs may use to get around the drawbacks of conventional anti-corruption tactics.  The methodology of the mixed approach was used. Probability and non-probability sampling methods were used in the investigation.  SMEs were left susceptible and unable to contribute to long-term development objectives like good governance, and decreased inequality, due to a lack of easily accessible, reasonably priced, and user-friendly anti-corruption technologies that were suited to their particular requirements. The study fills an information vacuum about creative strategies that can enable SMEs to reduce the dangers of corruption, enhance transparency, and encourage moral corporate conduct. According to the study's findings, disruptive innovation was seen as a catalyst for anti-corruption efforts. In order to promote holistic development in SMEs, the study suggested utilizing technology and systemic change.

Abstract: The incorporation of social media into educational broadcasting has profoundly altered traditional paradigms of instructional content delivery, especially in the Global South. This paper critically examines the intersection between digital communication platforms and broadcast education, focusing on how tools such as blogs, podcasts, virtual classrooms, and social networking applications have redefined pedagogical practices in Nigeria. Anchored in the Uses and Gratifications Theory and Media Convergence Theory, the study interrogates the transformative impact of social media on the accessibility, participatory dynamics, and learner autonomy within educational broadcasting. By tracing the evolution of educational broadcasting in Nigeria, the paper situates current developments within a historical and socio-technological context, highlighting the ongoing shift from unidirectional to dialogic modes of knowledge dissemination. The communicative affordances of social media including real-time interactivity, collaborative learning, and multimodal content engagement are presented as pivotal innovations shaping contemporary learning ecosystems. Furthermore, the study reflects on the implications of this convergence for educational policy, curriculum innovation, and digital literacy enhancement in African contexts. The paper concludes that when strategically deployed, social media can serve as an equalizing force, enabling inclusive, decentralized, and learner-driven educational experiences aligned with 21st-century imperatives.

Abstract: This study investigates the impact of generational diversity on employees' work behaviour in selected commercial banks in Abeokuta, Nigeria. A descriptive research design was adopted, with structured questionnaires used to gather information from 162 employees across six banks. Three primary research objectives were addressed: exploring the influence of generational diversity on work behaviour; investigating the role of employee motivation on work behaviour across different generational cohorts; and examining the role of communication styles in work behaviour amongst multi-generational workers. Multiple linear regression analysis revealed that the strongest positive influences on work behaviour were exerted by employee motivation (β = 0.43, p < 0.001), communication styles (β = 0.38, p < 0.001), and perception of leadership (β = 0.34, p < 0.001). However, generational diversity did not have a statistically significant direct impact on work behaviour (β = 0.07, p = 0.245). The study concludes that whilst generational variation exists in Nigerian banks, the influence of generational diversity on employee behaviour is moderated by adequate motivation mechanisms and effective communication systems. These findings contribute to understanding human resource dynamics in emerging economies and offer practical implications for human resource management in multi-generational banking contexts.

Abstract: This study investigates the impact of generational diversity on employees' work behaviour in selected commercial banks in Abeokuta, Nigeria. A descriptive research design was adopted, with structured questionnaires used to gather information from 162 employees across six banks. Three primary research objectives were addressed: exploring the influence of generational diversity on work behaviour; investigating the role of employee motivation on work behaviour across different generational cohorts; and examining the role of communication styles in work behaviour amongst multi-generational workers. Multiple linear regression analysis revealed that the strongest positive influences on work behaviour were exerted by employee motivation (β = 0.43, p < 0.001), communication styles (β = 0.38, p < 0.001), and perception of leadership (β = 0.34, p < 0.001). However, generational diversity did not have a statistically significant direct impact on work behaviour (β = 0.07, p = 0.245). The study concludes that whilst generational variation exists in Nigerian banks, the influence of generational diversity on employee behaviour is moderated by adequate motivation mechanisms and effective communication systems. These findings contribute to understanding human resource dynamics in emerging economies and offer practical implications for human resource management in multi-generational banking contexts.

Abstract: This study explores the adverbial effect of colors—how colors indirectly shape human actions, expressions, and perceptions—through the lived experiences of Bachelor of Technology and Livelihood Education (BTLED) students. Anchored in qualitative insights, the research identifies three central themes: color’s influence on decision-making, interpersonal relationships, and personal philosophies. Findings reveal that students associate colors with aesthetic choices and consumer behavior, illustrating how personal beliefs about color affect lifestyle decisions. Moreover, colors were perceived to subtly impact social interactions, emotional connections, and group dynamics, suggesting that shared color preferences foster attraction and cohesion. In shaping self-concept and worldview, colors were found to play a vital role in enhancing self-expression and identity. The study introduces Carale’s Model of the Adverbial Effect of Colors, which identifies four interrelated elements—experiences, assumptions, conception, and concrete actions—that illustrate how individual perceptions of color evolve into behavioral manifestations. Supported by existing literature in psychology, philosophy, and design, the research underscores the wide-reaching implications of color perception in educational and business contexts. Recommendations include integrating color awareness into pedagogy, product branding, and social interactions to promote engagement, identity, and inclusivity.

Abstract: The substantial impact of artificial intelligence (AI) on business and services sector performance is examined in this review article, along with how AI fosters innovation in the rapidly evolving digital landscape. Drawing from a thorough review of the literature, we investigate the development of artificial intelligence in the business world across time, highlighting important breakthroughs and turning points. Examining the substantial impact of artificial intelligence (AI) on business performance is the aim of this study, with a focus on how AI may increase productivity, efficiency, cut expenses, and maximize resources.

Abstract: The rising prevalence of antimicrobial resistance has prompted an increased interest in natural remedies such as plant-based antimicrobials. Among these, Daucus carota (carrot) is recognized for its potential antibacterial and antifungal properties. This study investigated the antibacterial activity of Daucus carota extracts against Escherichia coli isolated from urine specimens. Furthermore, the study evaluated the antimicrobial susceptibility of these pathogens using carrot extracts that quantifies the major phytochemical constituents of the carrot rhizome. The antimicrobial susceptibility testing was carried out using the in-vitro method, wherein varying concentrations of carrot extracts (aqueous extracts of carrot) were applied to the test pathogen. Zones of inhibition were measured to assess the sensitivity of the pathogen Escherichia coli. The results revealed that carrot extracts exhibited significant antibacterial activity as (7mm, 5mm, 10mm, 1mm, 8mm) against tested pathogen. The phytochemical analysis revealed that carrot contains high levels of bioactive compounds, including flavonoids, alkaloids, tannins, saponins, resins, steroids, glycosides and phenolic compounds through phytochemical analysis. These compounds maybe responsible for the observed antimicrobial properties. The findings suggest that carrot extracts possess notable antimicrobial properties, particularly against bacteria responsible for urinary tract infections. This suggests that Daucus carota can be used as a natural alternative to ineffective synthetic antibiotics for treating infections caused by multidrug-resistant pathogens.

Abstract— This study focuses on ensuring the static stability of model missile rockets, which is crucial for maintaining a zero angle of attack and returning to equilibrium when disturbed by external forces such as wind or model inconsistencies. The objective is to develop and compare methods for determining the center of pressure and assessing static stability to simplify the design process for reliable launches of exhibition and sports model rockets. The methodology includes a simplified method that approximates the center of pressure as the center of the rocket's two-dimensional silhouette, suitable for small angles of attack (15-20°), a graphical method that has been developed and compared to various methods for estimating the center of pressure and assessing static stability and has been validated using SolidWorks Flow simulation.  The results show that static stability is achieved by placing the center of gravity in front of the center of pressure. The simplified and practical plane figure method yields an error of 15-28%, which is suitable for demonstration rockets, while the analytical method achieves high accuracy with an error of 0-0.34%, which is ideal for competitive sports models. The graphical method provides moderate accuracy with an error of 3-12%. Validation with SolidWorks confirms the reliability of these techniques. The proposed methods streamline the design process for both demonstration and sports model rockets, ensuring the analytical method recommended for high-performance models in international competitions and the possibility of further refinement in future research. Conclusion. The proposed method for ensuring static stability of a model rocket makes it possible to simplify the design process of both demonstration and sports models of rockets for reliable demonstration launches.

Abstract: This paper evaluated the effectiveness of a proposed overpass in total crossing time and pedestrian perceived safety at unsignalized crosswalks in Olivarez Plaza Mall in Brgy. Batong Malake, Los Baños. This study employed the Mann-Whitney U Test to compare the total crossing time of an actual unsignalized crosswalk and a simulated overpass, revealing that the unsignalized crosswalk had a shorter total crossing time. The Shapiro-Wilk R test was utilized to determine whether the data sets were normally distributed and to support the use of a non-parametric test further. Pedestrians’ perceived safety was determined using the 5-point Likert Scale, with Cronbach’s Alpha to measure the consistency of the questions. The study uses the Jamovi Data analysis software to accurately compute the data and ensure correct and precise data calculation. The results show that the one-week period produces negative mean differences, indicating that total crossing time in the crosswalk is faster than a simulated overpass. Shapiro-Wilk R test implied that the calculated p value of < 0.05 defines the group of data as not normally distributed, requiring the use of the Mann-Whitney U Test. The reliability test revealed that the value resulted in 0.910, which is interpreted as excellent. The findings highlight that a proposed overpass should be further enhanced for efficient crossing and provide the perception of pedestrians on their safety when crossing in an unsignalized crosswalk or an overpass.

Abstract Objective: The purpose of this study is to determine and examine the main factors that affect consumers' use of credit cards, with an emphasis on perceived convenience, ease of use, security, and special benefits. Methodology: We used a quantitative exploratory design and gave structured questionnaires to a stratified sample of 348 credit card users. We used a five-point Likert scale to measure the answers. Regression and structural equation modeling (SEM) were used to look at the relationships between the variables in the data analysis. The fit indices and factor analysis showed that the conceptual model was valid. Findings and Implications: The findings show that increased credit card use is substantially correlated with unique benefits and a strong sense of security. Convenience has a positive impact on user preference, while perceived ease of use is a crucial mediator between perceived usefulness and actual use. These results underline how crucial it is to create credit card services with an emphasis on security, rewards, and ease of use. By concentrating on these elements, financial institutions can increase user engagement and trust, which will ultimately promote more frequent and responsible usage.

Abstract- Object identification in computer vision enables systems to interpret real-world images by recognizing, localizing, and classifying objects within them. This task becomes complex when multiple objects are present in a single image, requiring advanced methods to simultaneously reduce training time and computational cost. Traditional approaches relied on feature extraction techniques using color, shape, and texture information, often supported by classifiers like support vector machines. However, limitations in processing power and insufficient datasets hindered progress until the emergence of multicore processors and GPUs around 2010. These technological advancements, along with large annotated datasets like ImageNet, have enabled deep learning models to significantly improve object recognition capabilities. Despite these improvements, developing efficient algorithms for resource-constrained environments remains a challenge, highlighting the complexity of replicating human-like visual recognition in machines.

Abstract - The rapid growth of mobile technologies has expanded the functionality of smartphones, with Android emerging as the dominant platform due to its open ecosystem and massive user base exceeding 2 billion. However, this popularity has also made Android a primary target for cybercriminals, particularly in the distribution of mobile malware. Since 2009, mobile malware has escalated significantly, with a notable rise in new variants in 2017, fueled by profit-driven attackers and underground markets. Advanced evasion techniques such as obfuscation, logic bombs, and runtime payload dropping have made malware detection increasingly difficult. This thesis focuses on analyzing modern Android trojans—specifically, banking trojans that steal user credentials via fake login interfaces. Using both static reverse engineering and dynamic behavioral analysis in emulated environments, the study examines 2,380 samples across 20 trojan (sub)families. The research identifies common traits and evolutionary patterns among these threats, providing valuable insights into their increasing sophistication and the growing challenge they pose to existing mobile security solutions.

Abstract: This study explores the use of Vitis vinifera (grape branch stem powder) as an eco-friendly and cost-effective biosorbent for the removal of Zn (II) ions from aqueous solutions. With the increasing concern over heavy metal pollution, especially zinc contamination from industrial activities, the development of sustainable remediation strategies has become essential. The objective of this work is to evaluate the adsorption capacity of grape branch stem powder for zinc ions and investigate the influence of various operational parameters on the adsorption process. The biosorbent was prepared by washing, drying, grinding, and sieving grape branches to obtain a fine powder, which was stored in airtight containers. Batch adsorption experiments were performed by varying key parameters such as pH, contact time, adsorbent dosage, initial metal ion concentration, and temperature to determine optimal conditions for maximum zinc removal. Zinc ion concentrations before and after adsorption were measured using Atomic Absorption Spectrophotometry (AAS). Characterization of the biosorbent before and after adsorption was carried out using FTIR, SEM, and EDX to understand surface morphology, functional groups, and elemental composition. The study concludes that Vitis vinifera branch stem powder shows significant potential as a natural biosorbent for zinc.

Abstract: The researcher conducted research on the development of a website-based MERDEKA syntax  on the learning process of students at SMPN 2 Kersamanah. This study aims to find out about: 1) how the ADDIE model with the MERDEKA syntax based on Websites can be applied to science subjects, 2) improving Science Literacy Competency (SLC) on the subject of the reproductive system of science subjects. The type of research used is Research and Development (R&D), and the research model uses ADDIE, namely Analysis, Design, Develop (Borg and Gall stages), Implementation, and Evaluate. The population in this study was 242 students in grade IX and a sample of 63 people. The data collection techniques used were non-test and test, the data obtained was analyzed by rating grade, and quantitative data was analyzed by linearity, normality, heteroscedasticity, and regression test. Product validation is carried out by 4 experts. Validated products are implemented on the research subjects. From the regression test  , a linear equation Ŷ=107.970-0.298X was produced, then the hypothesis was tested to see the significance of tcal = -1.315 > ttable = 1.296 where H0 was rejected and H1 was accepted. This means that there is an influence of the website-based MERDEKA syntax on SLC. To see how much influence the X variable has, look at the R Square value  of 0.028, meaning that the website-based MERDEKA syntax  has an effect on the increase in SLC by 2.8%. So that the website-based MERDEKA syntax product  is suitable for use and development in learning.

Abstract: Educators frequently contend with significant psychological and emotional pressures, yet the buffering role of social and institutional support systems remains underexplored. This study examines how relationships with colleagues, school administrators, and the broader community influence educators’ well-being. It explores the multilayered interactions among personal, professional, and institutional environments that affect teacher resilience and satisfaction. Data were collected through qualitative interviews with educators from various secondary schools. The findings indicate that supportive peer relationships and responsive leadership play a critical role in reducing burnout and enhancing job satisfaction. In contrast, environments characterized by a lack of collaboration and empathy tend to intensify stress and feelings of isolation. This study contributes to ongoing discussions surrounding teacher retention and mental health by highlighting the importance of systemic support. It concludes that collective care and institutional responsiveness are essential to sustaining educator well-being. The study recommends school-wide initiatives that promote peer mentorship, encourage open dialogue with administrators, and foster stronger community engagement.

Abstract—Diagnosing Autism Spectrum Disorder (ASD) is challenging due to its complexity and the diverse symptoms it presents. In this study, we focus on applying machine learning techniques, specifically the Random Forest algorithm, for identifying ASD. Utilizing a comprehensive dataset that encompasses both behavioral and demographic information, we perform thorough preprocessing, feature selection, and model evaluation. The study examines the Random Forest classifier's effectiveness in differentiating between individuals with and without ASD. The results are encouraging and highlight the algorithm's predictive capabilities. By concentrating solely on this method, we gain insights into its strengths and limitations, which are critical for enhancing ASD diagnostic processes. This research underscores the potential of Random Forest in advancing early ASD detection and improving intervention strategies in clinical practice.

Abstract: Introduction- Upper back pain & neck pain is increasingly common among college students due to sedentary lifestyles, poor posture, and excessive screen time. Early identification of disability levels is essential to prevent long-term musculoskeletal problems. The aim and objective - To determine the prevalence of upper back pain including neck pain among college-going students using the Neck Disability Index (NDI) and to explore its association with lifestyle factors. Need of study – The Need of study is to investigate the Prevalence of upper back pain including neck pain among college going students. Methodology &Outcome measures - A cross-sectional observational study was conducted among 60 college students. The NDI questionnaire was used to assess the level of neck-related functional disability. Participants with vertebral artery insufficiency, spinal trauma, deformity, radiating pain, or a history of neck surgery were excluded. Results - Out of 60 participants, 29 (48.3%) reported varying degrees of neck-related disability, while 31 (51.7%) reported no disability. The NDI demonstrated high reliability and internal consistency for this population. Trends suggested a possible association between disability and prolonged screen time or poor posture. Conclusion- The study reveals a high prevalence of upper back pain & neck pain - related disability among college students. These findings highlight the need for early preventive strategies, including posture education and lifestyle modification, to reduce the burden of musculoskeletal disorders in young adults.

Abstract - Depression is a widespread mental health condition marked by ongoing sadness, reduced interest in activities, and emotional detachment. Unlike normal mood changes, it significantly impacts daily life, relationships, and productivity. This study presents a new, more reliable approach for identifying depression, which was tested using the Mental Screen Inventory. The method showed improved accuracy over existing techniques. The findings offer valuable insights for mental health professionals and researchers aiming to better understand and manage depression.

Abstract: The research titled “Bridging the Gap between Artificial Intelligence and Multiple Intelligence” explores how human intelligence, traditionally seen as unique, has inspired the development of Artificial Intelligence (AI). Initially focused on Natural Intelligence, the study later expanded to include Multiple Intelligence (MI), recognizing Natural Intelligence as a subset of MI. The objective is to build a conceptual bridge between human and artificial intelligence. In this discusses the basics of both intelligences and how human intelligence is influenced by expressions, emotions, and environment. reviews existing literature to support the study. delves deeper into the bridge concept, exploring the transfer of knowledge from humans to machines, with coding examples provided. outlines the hardware and software necessary for AI development. The research aims to enhance both human and artificial intelligence by leveraging each other’s strengths.

Abstract - This research addresses key security and privacy challenges in IoT by proposing a multi-layered security framework. It includes formal verification of IoT protocols using the Scyther tool for secure communication, a hybrid intrusion detection system using LSTM and Deep Reinforcement Learning, and an ensemble model combining CNNs with a Quantum Neural Network to improve detection accuracy. Additionally, a blockchain-based system with Improved PCA and a GRU–Deep Belief Network classifier enhances accuracy and reduces false positives. Experiments demonstrate strong performance, with detection accuracy up to 97.26% and improved reliability through blockchain integration.

Abstract: Assigning predetermined categories to text documents according to their content is known as text classification, and it is a fundamental task in natural language processing (NLP). With an emphasis on the extensively researched Reuters dataset, this paper provides a thorough examination and application of text classification using neural networks. A strong standard for assessing classification algorithms is provided by the Reuters dataset, which consists of a collection of brief newswires divided into 46 unique and mutually exclusive subjects. To address this challenge, we use a neural network-based architecture constructed with TensorFlow and Keras. The approach entails one-hot encoding of the target labels after preprocessing the textual material using tokenization and vectorization techniques. To improve generalization and avoid overfitting, dropout regularization layers are added to a feedforward neural network in the suggested model architecture. To guarantee effective and precise learning, the training procedure makes use of the Adam optimizer with categorical cross-entropy as the loss function. Our tests demonstrate the neural network's capacity to successfully categorize the Reuters news wires by assessing the model's performance in terms of accuracy and other pertinent metrics. The findings show that a reliable solution for text categorization challenges can be obtained by combining neural networks with sophisticated optimization approaches. In addition to demonstrating deep learning's ability to handle multi-class text categorization, this study acts as a guide for further investigation and applications in related fields.

Avena sativa is a promising crop valued for its nutritional benefits, adaptability and rapid growth. The rapidly increasing global salinisation threatens more than 10% of arable land, lowering the average yield of major crops. To examine the impact of salinity on seed germination and seedling development in six Avena genotypes (JHO Kent, JHO 822, JHO 851, JHO 2009-1, JHO 2010-1, and JHO 2012-2) subjected to different salinity levels (EC 4, EC 8, EC 12, EC 16 dS/m), including distilled water. The seeds were germinated in petri plates. The germination and seedling vigour were significantly affected by increasing salinity, with notable declines observed at EC 12 and EC 16. Among the genotypes, JHO 822 and JHO 2009-1 displayed the highest salinity tolerance. JHO 822 achieved 90% germination in distilled water at EC 12 and exhibited superior radicle (19 cm) and plumule (20.76 cm) lengths. Similarly, JHO 2009-1 retained 85% germination at EC 16 and exhibited strong seedling growth, with maximum radicle and plumule lengths. JHO Kent, JHO 851, and JHO 2012-2 showed moderate salinity tolerance, attaining germination rates above 75% at EC 16 but with reduced seedling growth metrics. In contrast, JHO 2010-1 demonstrated the lowest resilience, with germination declining to 40% and minimal radicle and plumule development at EC 16. Across all genotypes, lower salinity levels (EC 4 and EC 8) supported optimal germination and growth. Thus, the study highlights substantial genotypic variability in salinity tolerance, with JHO 822 and JHO 2009-1 emerging as promising genotypes for cultivation in saline environments.

The lack of distinct symptoms makes it difficult to detect thyroid illnesses, such as hypothyroidism, hyperthyroidism, and thyroid nodules, which impact millions of individuals globally. The key to successful treatment and management is early and precise identification. The goal of this research is to automate and improve the accuracy of thyroid illness identification using a deep learning-based technique. The system learns intricate patterns from medical data to categorize different thyroid disorders, making use of state-of-the-art neural network designs including Convolutional Neural Networks (CNNs) for image-based analysis and Deep Neural Networks (DNNs) for structured clinical data. Thyroid ultrasound pictures and patient records are two examples of publicly accessible datasets used to train and verify the model. The findings show that the suggested approach is very accurate, sensitive, and specific, which makes it a great tool for helping doctors diagnose thyroid problems quickly. This study demonstrates how deep learning has the ability to revolutionize conventional medical diagnosis and enhance patient care.

Abstract- Failure, in general, refers to a situation where the system's performance is significantly impaired, usually dropping below a preset level, such as 80% of its nominal power output. This degradation is caused by a variety of factors, including physical damage, manufacturing defects, and environmental factors. The ability of the PV system to continuously generate electricity over its anticipated lifespan, even in the face of changing environmental conditions, is referred to as reliability. This includes weather resistance, performance, and the system's capacity to continue operating without significant malfunctions. A new method for examining the failure and dependability rate of a solar PV module was examined in this study. The method includes a reliability model called linear degradation model. A PV reliability model was designed based on degradation. On evaluating the model, it was applied to a practical case based on state-of- the-art parameter of crystalline silicon PV technology. This model uses time-dependent power variability and measured degradation rates to produce reliable data, including relevant and tenable power warranties. Examining the reliability and failure of the monocrystalline DSP 210 and polycrystalline SPP 280W PV modules was part of the strategy. With monocrystalline DSP 210, the computed power was 191.134 watts, whereas with polycrystalline DSP 210, it was 267.8 watts. Comparing them to the calculated power for the same model demonstrates their relative reliability. The cells' dependability indicates that they are reliant on the amount of solar radiation present during a specific time of day. Analytical tests and testing revealed that the panels' failure rate was significantly higher in some months than their reliability rate. The bright sunlight over those months was the cause of that.

Abstract: This study examined how artificial intelligence (AI) techniques affect the creation of user-friendly mobile application interfaces. This study examined the effectiveness of incorporating accessibility standards into AI-generated user interfaces. There were two stages to the research. In the first phase, an AI tool was chosen, and by providing various prompts, various interfaces for a mobile application for food delivery were developed. In the second step, experts and users (older persons) assessed the AI-generated interfaces to see how the accessibility features were implemented. The outcome led to the selection of a certain interface, which was then manually constructed using guidelines to incorporate all the accessibility aspects. Once more, users and specialists participated in the testing to gauge the existence of accessibility. Using this procedure, the effectiveness of both manual and AI-generated user interfaces in integrating accessibility elements was assessed. All of these measurements' results showed that manually created interfaces had more accessibility features than AI-generated ones. To create efficient AI-generated interfaces with accessibility features, more research must be done on the subject and better models and prompts are required to support the functioning.

Abstract: The extensive usage of social media has radically transformed communication habits among teenagers. Though these sites provide avenues for self-expression, peer interaction, and information exchange, they are also linked to a myriad of mental health issues. This paper discusses the two-sided effect of social media on the mental health of teenagers, examining both its positive and negative influences. Grounded in psychological theory and empirical research, the paper discusses how processes such as social comparison, fear of missing out (FOMO), and reduced face-to-face interaction contribute to mental health outcomes. The paper also discusses how negative effects of social media can be mitigated, focusing on digital literacy, media usage patterns, and supportive environments.

Abstract: This article explores the transformative role of digital transformation in fostering sustainable business growth amid rapid technological advancements. It emphasizes how integrating cutting-edge technologies such as artificial intelligence (AI), cloud computing, IoT, and blockchain, alongside innovation and entrepreneurial strategies, creates resilient, adaptive organizations capable of competitive advantage. The paper highlights empirical evidence demonstrating that digital infrastructure, strategic AI deployment, and active participation in innovation ecosystems significantly enhance operational efficiency, market responsiveness, and customer engagement. It underscores the importance of agile leadership, responsible innovation, and inclusive entrepreneurship in driving long-term value while addressing challenges like cybersecurity, digital skill shortages, and organizational resistance. Additionally, the study discusses the critical need for adaptive digital governance and ethical considerations to navigate regulatory complexities and safeguard societal interests. By synthesizing global industry data, econometric models, and case studies, the article presents a comprehensive framework for leveraging digital tools responsibly to promote sustainable development, environmental efficiency, and social inclusiveness. Ultimately, it advocates for a strategic, holistic approach that aligns digital transformation with environmental and social objectives, ensuring that technological progress contributes to resilient, equitable, and future-ready enterprises in the evolving global economy. This forward-looking perspective not only prepares organizations for future challenges but also fosters inclusive, innovation-led economic growth, addressing timely and globally relevant challenges.

Abstract: Comparative research was conducted to find out differences among combat and non-combat female athletes in terms of their aggression and adjustment. The sample consisted of six hundred, Combat Sports Female Athletes (N-300) & Non-Combat Sports Female Athletes (N=300) participants from Tonk District of Rajasthan.  Dr. G.P. Mathur and Dr. R.K. Bhatnagar (2004) (QA) and Bell’s Adjustment Inventory (Student Form) by Dr. R.K. Ojha (2006) was used for the present research to assess the level of aggression and adjustment among the female athletes respectively. It was hypothesized that there would be no difference among combat and non-combat female athletes in terms of their aggression and adjustment. ‘Z’ test results (Z=1.8139, p<.01) reject the null hypothesis and states that aggression among combat and non-combat female athletes are different. In terms of adjustment (Family, Health, Social & Emotional), results show an insignificant difference among combat and non-combat female athletes (Z= -0.245, -0.36, 0.27, 0.390 p<.01). Thus, result supports the null hypothesis in terms of adjustment.  

Abstract: Women's Economic Empowerment (WEE) and Financial Inclusion (FI) initiatives in Zimbabwe have proliferated significantly between 2020 and 2025, yet persistent gender disparities challenge their transformative potential. This systematic review critically examines whether these initiatives genuinely break down barriers to women's economic participation or inadvertently reinforce existing inequalities when analyzed through a feminist lens. Following PRISMA guidelines, we systematically reviewed 47 peer-reviewed articles, policy documents, and grey literature spanning 2020-2025, focusing on WEE and FI initiatives targeting women in Zimbabwe. Our analysis employed feminist theoretical frameworks, particularly intersectionality and post-colonial feminism, to interrogate how these initiatives engage with structural gender power relations. Key findings reveal substantial progress in women's formal financial inclusion, rising from 69% in 2014 to 83% in 2022, with the gender gap in financial access effectively closed. However, deeper analysis exposes concerning patterns: women's share of total bank loans declined by 2.7 percentage points despite absolute increases, 91.6% of employed women remain in informal work, and persistent collateral requirements exclude many from meaningful credit access. The review identifies critical policy gaps including inadequate attention to unpaid care work, limited operationalization of gender-responsive budgeting, and insufficient challenge to patriarchal structures underlying economic exclusion. While initiatives demonstrate instrumental gains in access, they fall short of achieving transformative empowerment that fundamentally alters gender power relations. Our feminist analysis reveals that current approaches often integrate women into existing unequal economic systems rather than challenging structural inequalities. The study recommends a paradigm shift toward transformative policies that address root causes of gender inequality, strengthen intersectional approaches recognizing diverse women's experiences, and institutionalize feminist economic principles in policy design. These findings contribute to scholarly understanding of WEE and FI effectiveness while providing evidence-based recommendations for achieving genuinely inclusive economic growth in Zimbabwe and similar contexts.

Abstract: The increasing global demand for energy, coupled with growing concerns about climate change and environmental degradation, underscores the urgent need for sustainable energy strategies. This research explores the role of renewable energy technologies—such as solar, wind, hydro, and bioenergy—in mitigating environmental impacts associated with fossil fuel consumption. It critically examines the environmental benefits of clean energy systems, including reductions in greenhouse gas emissions, air and water pollution, and habitat destruction. The study also identifies key challenges to the widespread adoption of renewable energy, including technological limitations, economic barriers, and policy constraints. Through a multidisciplinary approach combining energy modeling, environmental analysis, and policy review, the research highlights the potential of integrated energy-environmental planning. The findings suggest that a coordinated policy framework, investment in green technologies, and public awareness are essential to transition towards a low-carbon, environmentally resilient future. The study provides recommendations for policymakers, industry leaders, and stakeholders to support the development of an inclusive and sustainable energy ecosystem.

Abstract: Although human error is still the most critical of vulnerabilities, it has been estimated to contribute to more than 90% of all data breaches in the contemporary world of dynamic cyber security. The traditional security awareness training programs not have been sufficient in reaching out to the users owing to old-fashioned event such as static presentations and generic quizzes. This research instead proposes a novel Security Awareness Training System for improved engagement, retention, and promptness to reality threats. It employs adaptive learning procedures, interactive simulations such as phishing attacks, social engineering scenarios, and gamification to present an innovative and personalized training experience. With AI analytics undergirding the system, individual user activities are assessed, contents fitted against risk profiles, and real-time feedback sustained to reinforce secure practices. It was an evaluation mixed-method quantitative such as reduction, pre-post training assessment scores, and others-phishing susceptibility, qualitative user feedback-to measure effectiveness. Preliminary results suggest actual improvements in participants' security hygiene, 40% decrease in phishing click-through rates. They retained better knowledge over the long term than just with the old training methods. Moreover, the scalable architecture of the system allows most IT infrastructures in organizations, small or large, to easily adapt it to their environments. The research clearly illustrates weaknesses in existing training paradigms while providing a data-driven, user-centered framework facilitating entities' future cybersecurity education initiatives.  

Abstract Purpose: This study investigated the effectiveness of economic support programs on student participation in schooling in public secondary schools in Meru County, Kenya. The research examined how bursaries, scholarships, work-study programs, and alternative fee payment modes influence student engagement in educational activities. Methodology: A mixed-methods approach was adopted, combining descriptive and correlational research designs. The study sampled 331 respondents from 1,903 participants, including 13 principals, 12 Parent Association chairpersons, 147 class teachers, 144 student leaders, and 3 Constituency Development Fund managers. Data was collected through semi-structured interviews, self-report questionnaires, and focus group discussions. Quantitative data was analyzed using descriptive statistics (frequencies and percentages) and inferential statistics (Chi-square tests), while qualitative data underwent thematic analysis. Results: Descriptive findings revealed that only 33.06% of class teachers and 24.36% of student leaders confirmed readily accessible economic support programs in their schools. Chi-square analysis (χ² = 12.909, p < 0.001) demonstrated that economic support programs significantly influence student participation in schooling. The Contingency Coefficient measure indicated that 28.4% of the total variance in student participation could be attributed to economic support programs. Conclusions and Recommendations: Economic support programs are effective in facilitating student participation in schooling; however, their accessibility remains critically low in public secondary schools. The study recommends enhanced implementation of economic support initiatives, improved coordination between stakeholders, and diversification of funding sources to ensure sustainable access to these programs.

Abstract- Tobacco smoking is one of the most important public health problems and while global smoking prevalence has fallen, it is still common in many countries and causes a significant health burden worldwide. More than 8 million deaths per year were directly attributable to tobacco use or from exposure to tobacco smoke, and at least 1 billion people are expected to die from tobacco use in the 21st century. Exercise has been shown in studies to have a preventive role against smoking, as well as a positive effect in prevention and cessation interventions.

Abstract: Indian cinema has evolved into a diverse ecosystem encompassing various regional industries, including Bollywood, Tollywood, Kollywood, Mollywood, and Gollywood, and others, each contributing to the cultural tapestry of the nation. Hirsch (1972) observed that “Films or movies are cultural goods defined as ‘non-material goods’ directed at public consumers for whom they generally serve an aesthetic or expressive, rather than utilitarian function”.  The objectives of the research are to explore key factors that shape audience preferences for Gujarati films over other films. And another one to investigate variations in audience preferences for Gujarati films that vary across the demographic groups, and the frequency of watching Gujarati films. The research paper aims to explore the nuanced dynamics of changing audience preferences in Gujarati films, examining the factors driving these shifts, the impact on filmmaking trends, and the implications for the industry's future. The changing audience preferences in Gujarati films have had a profound impact on filmmaking trends, influencing every aspect of the creative process, from scriptwriting and casting to production design and marketing strategies. Filmmakers are constantly innovating and adapting to meet the evolving demands of audiences, striving to strike a balance between artistic integrity and commercial viability.

Abstract: The exponential growth of the Internet interconnections has led to a significant growth of cyber-attack incidents often with disastrous and grievous consequences. Malware is the primary choice of weapon to carry out malicious intents in the cyberspace, either by exploitation into existing vulnerabilities or utilization of unique characteristics of emerging technologies. The development of more innovative and effective malware defense mechanisms has been regarded as an urgent requirement in the cyber security community. To assist in achieving this goal, we first present an overview of the most exploited vulnerabilities in existing hardware, software, and network layers. This is followed by critiques of existing state-of-the-art mitigation techniques as why they do or don’t work. We then discuss new attack patterns in emerging technologies such as social media, cloud computing, smartphone technology, and critical infrastructure. Finally, we describe our speculative observations on future research directions.

Abstract: The principle of "As Low as Reasonably Practicable" (ALARP) has long served as a foundational tool in health, safety, and environmental (HSE) decision-making, particularly in high-risk industries. Grounded in cost–benefit logic, ALARP seeks to minimize risks unless further reduction would require disproportionate effort relative to benefit. This critical review analyzed the ethical strengths and weaknesses of ALARP through the lenses of utilitarianism, deontological duty, process integrity, and distributive justice. Drawing on recent literature and professional experience, the study identified that while ALARP promotes optimization, accountability, and continuous improvement, it also suffers from ethical limitations such as subjectivity, commodification of life and environment, lack of transparency, and potential injustice towards marginalized or vulnerable populations. The researchers argued that ALARP’s heavy reliance on cost–benefit analysis risks monetizing human life and environment and sidelining stakeholders consent especially in contexts where residual risks affect vulnerable groups or where the groups with potential exposure to the risk are not part of the decision makers. Recommendations include embedding ethical scrutiny, procedural fairness, and stakeholder participation into ALARP-based decisions, especially where AI or algorithmic systems are involved, to ensure morally sound and equitable HSE practices in an increasingly automated world.

The banking industry is an important engine of economic growth and financial stability in India, with the Nifty Bank Index being a major gauge for assessing banking stock performance. Investors need to understand market trends and investment strategy in order to maximize returns while minimizing risks in this fast-changing sector. The study concentrates on significant financial indicators like market capitalization, P/E ratio, return on equity (ROE), dividend yield, and earnings per share (EPS) to study the investment prospects of top banking stocks like HDFC Bank, ICICI Bank, SBI, Kotak Mahindra Bank, and more. The research identifies that large-cap banks offer stability, mid-cap banks offer growth potential, and undervalued banks with low P/E ratios offer good investment opportunities. Also, income-oriented investors are attracted to dividend-paying banks, and aggressive investors are drawn to high-growth banks. This research concludes that investment choices in the Nifty Bank sector must be based on financial performance, market trends, and personal risk appetite to attain sustainable returns in the changing financial environment.

 In many educational institutions, the process of assigning roommates is often conducted randomly, leading to potential conflicts and dissatisfaction among students. This document introduces "Roommate Matcher," a system designed to improve the roommate assignment process in Ghanaian schools by matching students based on compatibility. Roommate Matcher aims to address the issues arising from random room assignments, such as conflicts, stress, and poor academic performance, by utilizing a structured approach to pair students with similar habits and preferences. This study explores the purpose, scope, research questions, technologies used, and realistic applications of Roommate Matcher, specifically tailored to the context of Ghanaian schools.

The increasing difficulty of library operations and growing student populations in educational institutions calls for innovative and efficient management systems. Manual library systems are not only time consuming but prone to human errors, misplacement of books, and mismanagement of borrowing records. The Library Book Tracking System project aims to address these difficulties of library along with student growth. For manual library systems, they are often time consuming, prone to errors, and can lead to misplacement of books and mismanagement of book records. The system is a software application that will be designed to digitize daily library activities, thereby improving accountability, traceability, and overall service delivery for library lovers. This project outlines a solution that allows users to check book availability, borrow and return books, and track library records in real-time. The system's design is scalable, featuring robust security, user access controls, and reporting tools to provide real time analytics for informed decision-making in the future. This report details the system's objectives, design, architecture, implementation, and benefits, offering a comprehensive framework for deploying Library Book Tracking System in academic settings.

Groundwater plays a critical role in supplying clean water for domestic, agricultural, and industrial uses. However, its quality is highly susceptible to contamination from nearby objectionable vectors, such as septic tanks, landfills, and industrial waste sites. A fundamental factor influencing the risk and extent of contamination is the velocity of groundwater. Groundwater velocity is influenced by aquifer properties such as permeability, porosity, hydraulic gradient, and the nature of subsurface materials. Understanding this velocity is essential for assessing contamination risks and for estimating safe distances between boreholes and potential sources of pollution. The determination of safe distances requires a clear grasp of gcontaminant travel times, which are directly affected by groundwater flow velocity. Faster groundwater velocities reduce the time available for natural attenuation processes (like dilution, filtration, and chemical breakdown) and increase the risk of rapid contaminant transport to boreholes. Conversely, slower velocities may allow for sufficient natural purification before reaching a borehole, provided the distance is adequate. This paper highlights the critical place of groundwater velocity in risk assessments and regulatory frameworks for borehole siting .It emphasizes the need for site-specific velocity determination through field measurements  or modeling and proposes methodologies for calculating minimum separation distances to safeguard groundwater supplies. A deeper understanding of groundwater dynamics not only protects public health but also enhances sustainable management of groundwater resources in the face of increasing anthropogenic pressures. The average seepage velocity in the study area is 0.4562 m/days while the highest and the lowest are respectively 0.9599 and 0.15483. This implies that areas bothering Isingwu-Ibeku and Ibeku –Fmc Umuahia axis which are above the average are pruned to faster contamination than the ones around Nkpa1-Nkpa2 and Ibeku-Amachara axis. To safeguard boreholes in these areas therefore more reassuring work has to be done by building strong concrete or impassable walls against the objectionable vectors.

The present study investigates the algal diversity and physico-chemical parameters in Shikdi Stream and Dogda Stream in the Rohru region of Shimla District, Himachal Pradesh, India. Algal samples were collected during three seasons: post-monsoon, winter, and spring, and a total of 21 algal genera were identified across Bacillariophyceae, Chlorophyceae, and Cyanophyceae. Bacillariophyceae exhibited the highest seasonal stability, indicating broad ecological tolerance, whereas Chlorophyceae and Cyanophyceae displayed notable seasonal variability. Physico-chemical analyses revealed seasonal patterns: water temperature dropped in winter and peaked in spring; pH remained slightly alkaline throughout; and both total dissolved solids (TDS) and electrical conductivity (EC) were highest post-monsoon and decreased in spring, particularly in Dogda stream. Shikdi stream consistently recorded higher TDS, EC, hardness, and alkalinity, suggesting greater mineral input, possibly due to geological or anthropogenic factors. The correlation between environmental parameters and algal distribution underscores the influence of temperature, nutrient availability, and water chemistry on stream algal communities. These findings enhance the understanding of freshwater algal ecology and may inform stream monitoring, conservation, and watershed management strategies in the region.

This paper investigates the design, implementation, and evaluation of resilient machine learning models capable of handling dynamic data streams in enterprise applications where data patterns continuously evolve due to shifting user behavior, market conditions, and external disruptions. Recognizing the limitations of static batch-learning models in non-stationary environments, this research explores a range of adaptive approaches, including online learning, ensemble methods, adaptive windowing, and continual learning techniques, each integrated with drift detection mechanisms and memory retention strategies to combat concept drift and catastrophic forgetting. Using real-world enterprise datasets and simulated streaming scenarios, the study benchmarks these models against static baselines, demonstrating significant improvements in prequential accuracy, drift adaptation speed, and knowledge retention while maintaining fairness and explainability through integrated monitoring and interpretability tools. A pilot deployment further validates the practical feasibility and operational benefits of resilient learning pipelines, highlighting gains in prediction quality and system reliability in use cases such as fraud detection, recommendation systems, and predictive maintenance. The findings emphasize that resilience is not merely an algorithmic challenge but requires holistic integration with scalable architectures, robust MLOps practices, and ethical governance to ensure sustainable and trustworthy AI systems in rapidly changing enterprise environments.

Anti-angiogenic therapy, a traditional strategy in cancer treatment, functions by restricting the formation of new blood vessels, thereby cutting off the supply of oxygen and nutrients to tumor cells. It primarily targets the vascular endothelial growth factor (VEGF) pathway, helping to suppress angiogenesis and improve the outcomes of immunotherapy. The development of novel anti-angiogenic agents is crucial for advancing cancer therapy, and in silico tools have become essential for accelerating the drug discovery process. In this study, ten 1,3,4-oxadiazole derivatives of substituted benzoyl chloride were evaluated for their drug-likeness and pharmacokinetic properties using the Swiss ADME web tool. Key physicochemical descriptors—including molecular weight, topological polar surface area, hydrogen bonding capacity, lipophilicity, and molecular flexibility were assessed alongside drug-likeness filters such as Lipinski, Veber, and Muegge rules. All derivatives demonstrated favorable profiles, with minimal violations, no PAINS alerts, and moderate bioavailability scores (0.55). Despite minor alerts under Brenk and lead-likeness criteria, the compounds exhibited acceptable synthetic accessibility, suggesting good potential for further development. These findings highlight the utility of SwissADME in guiding the early-stage evaluation of drug-like properties, supporting the continued investigation of 1,3,4-oxadiazole scaffolds as promising candidates for anti-angiogenesis therapy.

Abstract: The logistics and supply chain ecosystem encompasses a network of interconnected entities that must work collaboratively to enhance operational efficiency and reduce overall costs. This study explores the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in modern supply chain and logistics management. It examines the integration of advanced ML techniques across various supply chain functions such as demand and supply forecasting, pricing strategy formulation, and text analytics. By leveraging these technologies, organizations can streamline processes, mitigate risks, reduce operational costs, and enhance profitability. The research further emphasizes the practical implications of adopting AI and ML, presenting real-world applications that demonstrate their potential in driving data-driven decision-making and achieving competitive advantage in the logistics domain.

Abstract- Failure, in general, refers to a situation where the system's performance is significantly impaired, usually dropping below a preset level, such as 80% of its nominal power output. This degradation is caused by a variety of factors, including physical damage, manufacturing defects, and environmental factors. The ability of the PV system to continuously generate electricity over its anticipated lifespan, even in the face of changing environmental conditions, is referred to as reliability. This includes weather resistance, performance, and the system's capacity to continue operating without significant malfunctions. A new method for examining the failure and dependability rate of a solar PV module was examined in this study. The method includes a reliability model called linear degradation model. A PV reliability model was designed based on degradation. On evaluating the model, it was applied to a practical case based on state-of- the-art parameter of crystalline silicon PV technology. This model uses time-dependent power variability and measured degradation rates to produce reliable data, including relevant and tenable power warranties. Examining the reliability and failure of the monocrystalline DSP 210 and polycrystalline SPP 280W PV modules was part of the strategy. With monocrystalline DSP 210, the computed power was 191.134 watts, whereas with polycrystalline DSP 210, it was 267.8 watts. Comparing them to the calculated power for the same model demonstrates their relative reliability. The cells' dependability indicates that they are reliant on the amount of solar radiation present during a specific time of day. Analytical tests and testing revealed that the panels' failure rate was significantly higher in some months than their reliability rate. The bright sunlight over those months was the cause of that.

Abstract: The performance of public hospitals in Kenya have been marred with a lot of issues ranging from poor services to the patients, delayed supplier payments and constant labour unrest. Complaints have arisen from the manner in which procurement of goods and services are handled leading to inefficiencies in various departments including in the clinical medicine. Patients have been equally suffering in grief due to poor service delivery. Public hospitals have inadequate facilities and are characterized by dilapidated facilities, insufficient drugs, and inadequate human capital as well as obsolete infrastructural facilities. The general objective of the study was to determine the effect of E-Tendering on performance in public hospitals in Kakamega County, Kenya. The study was founded on diffusion of innovation theory. The study applied descriptive survey research design. The study utilized a sample size of 204 which was derived at after the calculation from a population of 416 using Yamane 1967 formula. Questionnaire was used to collect data. Validity was determined through discussion with the supervisor and experts in the field while reliability was also determined by pilot study with a focus on internal consistency. This was measured using the Cronbach alpha coefficient. The measures of central tendency and correlational analysis were also used in data analysis. The study found out that E-Tendering had a significant influence on the performance of public hospitals in Kakamega County, Kenya.

Abstract: This study investigates the evolving role of trust as a central pillar in contemporary cybersecurity strategies within global payment systems. Employing a qualitative meta-analytical approach and multi-case comparative analysis, the research explores how trust influences the design, adoption, and regulation of three major payment innovations: mobile money platforms in sub-Saharan Africa, cryptocurrency ecosystems, and central bank digital currencies (CBDCs) in Nigeria, China, and Sweden. Data were drawn from empirical studies and institutional reports, analysed using thematic content analysis. The findings reveal that technical security alone is insufficient for user engagement; instead, institutional credibility, regulatory assurance, and positive user experience significantly drive trust. In low-resource settings, such as Africa, platforms like M-Pesa gain user confidence through reliability and accessibility. In contrast, in cryptocurrency markets, systemic failures like FTX erode trust despite blockchain transparency. For CBDCs, adoption depends largely on public confidence in state institutions and their data protection practices. The study concludes that the future of cybersecurity must shift from reactive threat mitigation to proactive trust-building, emphasising trust-by-design, digital literacy, regulatory transparency, and international cyber norms. Trust is not a secondary outcome of secure systems—it is the strategic foundation upon which they must be built.

Abstract -Smartphones have become essential tools in modern life, evolving beyond communication to support a variety of cognitive, emotional, and social activities. This study investigates their dual role—as both tools and subjects of research—by examining their influence on human behavior. While smartphones offer benefits like instant information access, memory aids, and enhanced connectivity, they also raise concerns about attention span, emotional regulation, and dependency. This research aims to provide a balanced view of their impact on attention, working memory, and mental health.

Abstract: Blockchain technology has emerged as a revolutionary tool in securing financial data by offering decentralization, transparency, and immutability. This paper explores how blockchain enhances data security in financial systems, preventing fraud, cyberattacks, and unauthorized access. It also examines its applications in banking, insurance, and regulatory compliance while addressing challenges like scalability and regulatory uncertainty. Through a survey-based approach, this study aims to understand industry adoption trends and stakeholders’ perceptions of blockchain in financial security. 

Abstract— This paper examines the integration of skylights in sustainable architectural design, focusing on the case of The El Guadual Children Centre, located in Villa Rica, Cauca, Colombia. The project exemplifies sustainable design principles and community-centered architecture that is also awarded by LEED Platinum-certified building. Two main issues have been identified: lacking information on the daylight performance via computer simulation and limited analysis on the impact of skylight proposals to the daylight performance. The primary objectives for this research are to evaluate and simulate the existing daylighting performance of the building by using the selected computer software. Furthermore, this research aims to investigate and quantify the impact of the proposed skylight on the daylight performance. Via integration by two simulation tools which are LightStanza and Rhino 7, the study analyses the building's baseline daylighting performance and assesses the improvements after the integration of skylights. Comparative analysis is done to evaluate key metrics of illuminance levels before and after the installation of the skylights. The results clearly show that integrating skylights provides considerably better daylight distribution, reduces the reliance on electric lighting, and consequently leads to energy efficiency.

Abstract: AWS Security Groups and NACL, namely Network Access Control List act as a safeguard to protect the network and manage the incoming and outgoing data flow say traffic or data stream based on the specified rules and allow only authorized users to access the resources. There is a basic variance between security groups and NACLs in that security groups are actually a virtual firewall for EC2 instances, whereas NACLs work for subnets. The chapter highlights the security groups & NACL working, limitations and significance of integrating both.

Abstract: The study assessed the patterns of generation and composition of wastewater in Abuja Municipal Area Council (AMAC), Federal Capital Territory, Abuja. This study is a response to Sustainable Development Goals 6 and 11, which addresses the provision of clean water, safe sanitation and the development of sustainable communities and cities. The study aims to determine the patterns of wastewater generation and composition in AMAC. The research methodology includes qualitative, quantitative and experimental examination. Thirty-six (36) samples of influents/effluents were collected and subjected to laboratory analysis to determine the compositions of the various parameters for both seasons (wet and dry) and the quality of treatment at the Wupa treatment plant in AMAC. The analysis returned r values of 0.995 and 0.882 for dry and wet seasons, respectively. These r values show significant variations between the influent and effluent samples. Specifically, there were substantial variations in the concentration of wastewater parameters such as turbidity, total suspended solids, oil and grease, dissolved oxygen, chemical oxygen demand, ammonia, nitrate, biological oxygen demand and total coliform. In contrast, the variations in the concentration of other parameters remain largely insignificant. The assessment further indicated that wastewater treatment for both seasons at the plant conformed to the World Health Organization standards for effluent discharge. The study established the poor state of wastewater facilities and the need to develop a more sustainable framework for providing and maintaining wastewater facilities in AMAC. The study, therefore, recommended the adoption of a closed-system efficiency model for the management of wastewater in the Federal Capital Territory, Abuja.

Abstract: Since the victim and perpetrator do not need to be in close proximity to one another, virtual sexual offenses have been on the rise for decades. Technology, on the other hand, is making these offenses easier through a variety of platforms, as the current study notes. People of all ages use social media sites like Facebook, Instagram, and others, which can have both beneficial and detrimental effects. Furthermore, shedding more light on the drawbacks of virtual platforms, it is noted that there are many different ways that criminals target their victims and continue to abuse them. Ordinary people who are assaulted experience psychological effects and many traumas. The case study cited in this research provides a brief idea respectively. The paper compares real-world experiences and virtual world assumptions in online activities, highlighting minor loopholes used by criminals. Victims experience traumatic issues in virtual sexual offenses, similar to real-life assaults. Medical diagnoses show a thin line between mental impacts and real-life assaults. The paper emphasizes the need for law enforcement agencies to consider legal impacts and equip their teams to resolve crimes effectively. Strict regulations, education, and technological solutions are needed to combat virtual sexual offenses, including content bans, respectful relationships, outreach programs, AI tools, and mental health impacts.

In the present competitive environment where the customer possess  tremendous alternatives  for selecting brands among consumer goods  , it is a  challenging task for a marketer to attract and retain customers . The marketer of  FMCG products, uses market penetration strategy to position their product brands  in the mind of the customer. With the emergence of multinational companies and wave of economic reforms in 1990’s both the  national and international companies focused  to tap the potential market Rural market..The government initiatives towards rural development led to the attraction of  corporate house in India and around the world as the major  lucrative market. Big  FMCG companies and regional companies compete with one another to garner a a lion’s share in the rural market. Various social  and economic factors influence the rural consumers to go for FMCG. The present study focuses on the market penetration of FMCG in rural market in Prayagraj District of Uttar Pradesh .The objective of the present study is to explore  the factors influencing the rural customer preference towards FMCG and to analyze the impact of loaded factors on the satisfaction of rural consumers towards FMCG. Primary data was collected from 175 respondentsin rural areas of Prayagraj district . The focus of the study is limited to the Personal care products offered by the FMCG. 

Turbidity is one of the most important parameter for assessing the health of river ecosystems in mountainous regions. In the Himalayan foothills, seasonal and anthropogenic disturbances frequently leads to elevated turbidity levels, negatively impact aquatic habitats and human water usage. The Gaula River, which flows through Nainital district of Uttarakhand, plays a vital role in regional hydrology and supports both ecological and domestic functions. Despite its importance, limited research focusing on turbidity variation and spatial distribution along its course exists. This study examine monthly turbidity data from three monitoring sites—Amritpur (upstream), Ranibagh (midstream), and Kathgodam (downstream)—from March 2019 to February 2020. Descriptive statistical technique is used to evaluate temporal and spatial patterns in turbidity. Findings shows turbidity level peaked during the monsoon, especially in July (mean: 113 NTU), indicating significant sediment influx likely driven by rainfall and upstream erosions. Post-monsoon and winter months observed lower turbidity values, with November been the least turbid (mean: 0.9 NTU). Among sites, Kathgodam records the highest turbidity, suggesting strong influence of urbanization and sediment transport dynamics downstream. Amritpur, located in a less disturbed forested zones, displays more stable turbidity except during monsoon peaks. These finding reflect a dynamic sediment regime controlled by climate and land uses patterns. The study reveals periods of concerns and highlights the downstream zone needing focused management. Data from these studies can serve as baseline for future assessments, planning, and hydrological model efforts. In addition, the research underscores need for integrated watershed strategies to minimize sediment input, especially in urbanizing stretches.

Water is dire essential for the sustenance of life. Of late, owing to population explosion, industrial expansion and agriculture development have utilising water resources excessively.  The merciless exploitation of both surface and ground water there is looming water scarcity.  Thus it is the need of the hour to manage water resources by using prudently and managing optimally. Conservation of water, minimizing wastage and ensuring its more equitable distribution through integrated water resources development and management is the main aim of National Water Mission. Community engagement and participation can contribute to sustainable water management through rainwater harvesting. The present paper appraises the quantity, driving factors of water woes, major issues of water resources, water resources management and strategies. It also provides an analytical overview of the emerging water resources management issue in India and to comprehend the gravity of the current water situation

Abstract—Mobile Ad Hoc Networks (MANETs) are prone to frequent topology changes and scalability issues due to their decentralized and mobile nature. As network size and node mobility increase, traditional routing protocols become inefficient, leading to degraded network performance. This paper introduces a novel AI-driven approach to route optimization that enables MANETs to self-adjust to dynamic conditions. The proposed method leverages machine learning algorithms to analyze real-time mobility patterns and link quality, allowing for predictive route selection and rapid reconfiguration. By dynamically adapting to varying network states, the system significantly enhances scalability, reduces latency, and improves packet delivery. Experimental results demonstrate that the AI-based model consistently outperforms conventional routing protocols under diverse network scenarios, making it a promising solution for future mobile and mission-critical applications.

Abstract: New dietary habits, current trends in production and consumption have significant health, environmental, and social implications. The European Union is addressing diseases typical of the modern era, including obesity, osteoporosis, cancer, diabetes, allergies, and dental issues. Developed nations are also confronting challenges associated with aging populations, high-calorie foods, and unbalanced diets. This paper discusses the potential of nutraceuticals, functional foods, and food supplements in alleviating health issues, particularly in the gastrointestinal (GI) tract. Specific members of gut microflora (e.g., probiotic/protective strains) contribute to the health of the host through their roles in nutritional, immunological, and physiological functions. The potential mechanisms by which nutraceuticals, functional foods, and food supplements may influence a host's health are also emphasized in this document. The development of innovative functional cell models of the GI tract and analytical tools that facilitate testing in controlled experiments are greatly needed for gut research.

Abstract: The research was conducted in July-August 2024, located in Gurgur Pematangsintar, Siantar Simarimbun District with an altitude of 390 meters above sea level. The purpose of the research was to determine the response of growth and production of lettuce (Lactuca sativa L.) due to the concentration of GDM liquid organic fertilizer (LOF) and NPK Mutiara. The study used a factorial Randomized Block Design (RBD) with two factors. The first factor was the administration of the GDM LOF dose (G) consisting of 4 levels, namely G0 = Control, G1 = 10cc/plot, G2 = 20cc/plot and G3 = 30cc/plot. The second factor was Mutiara NPK (N) consisting of 4 levels N0 = Control, N1 = 100g/plot, N2 = 200g/plot and N3 = 300g/plot. The parameters observed were plant height (cm), number of leaves (strands), net weight per plant (g) and net weight per plot (kg). The results showed that the GDM LOF and NPK Mutiara fertilizer treatments significantly affected plant height, leaf number, net weight per sample, and net weight per plot. GDM LOF treatment at a dose of 30cc/plot was the best dose, and NPK Mutiara treatment at 300g/plot was the best. However, the interaction between GDM LOF and NPK fertilizer showed no significant effect on plant height, leaf number, net weight per sample, or net weight per plot.

Abstract: This study explores the impact of diversity and inclusion (D&I) on organizational culture in contemporary workplaces. As global organizations embrace multiculturalism and gender equity, D&I initiatives have become integral to strategic management. The research investigates how D&I policies influence employee engagement, innovation, and cohesion, and whether they create a measurable shift in organizational behavior and values.

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Abstract: The integration of Internet of Things (IoT) and Big Data analytics is revolutionizing agriculture by enabling data-driven decision-making and precision farming. This paper presents a comprehensive implementation framework for IoT and Big Data in agriculture, focusing on real-time data collection, advanced analytics, and actionable insights. The proposed system architecture comprises four layers: sensing, communication, data processing, and application, which work together to optimize resource use, enhance crop yields, and improve farm management. IoT devices such as soil moisture sensors, drones, and smart irrigation systems collect vast amounts of data, while Big Data analytics processes this information to provide predictive insights and recommendations. A case study demonstrates the practical benefits of this framework, showing a 20% increase in crop yield and a 30% reduction in water usage. However, challenges such as high implementation costs, technical complexity, and farmer adoption remain. Future enhancements, including the integration of AI, blockchain, and 5G, are discussed to address these challenges and further advance smart farming. This paper highlights the transformative potential of IoT and Big Data in agriculture, offering a roadmap for researchers, policymakers, and farmers to harness these technologies for sustainable and efficient farming practices.

Abstract: Conservation Agriculture (CA) is increasingly promoted as a sustainable farming approach with the potential to enhance productivity while improving environmental and social outcomes. However, adoption outcomes are often assessed through narrow lenses, overlooking the complex trade-offs among ecological, economic, and social dimensions. This review critically synthesizes existing studies using a multicriteria framework that balances soil organic carbon (SOC) dynamics, crop yield performance, input efficiency, and social equity considerations. The evidence is explored from diverse agroecological settings, highlighting variations in SOC sequestration, yield stability, and labour and resource distribution under CA practices. The study reveals that while CA can improve soil health and reduce input dependency, the benefits are highly context-dependent, and adoption may exacerbate existing inequities, particularly among women and resource-poor farmers. Methodologically tools used for multicriteria analysis in agriculture, such as Analytic Hierarchy Process (AHP) and weighted scoring systems, and a conceptual model for integrated and equity-sensitive evaluations are discussed. The conclusion with recommendations for participatory research and policy design to ensure CA initiatives support not just environmental sustainability, but also equitable rural development is made in this study.

Abstract: Education is inevitable for socio-economic development as it enhances skills and knowledge of the workforce, promotes economic growth and fosters human capital and social mobility. it encourages individuals for higher knowledge and skills which is required for better employment opportunities and higher earnings which ultimately lead to enhance overall living standards. Moreover, education also plays a very important role in social development by increasing awareness in social issues encouraging critical thinking and fostering civic engagement. Thus, education performs the role of a catalyst for socio-economic development by equipping individuals with the advanced knowledge which is needed to thrive in a competitive world and contribute to a more just, developed and prosperous society. 

Abstract- A fire incident is a catastrophe that may result in property damage, fatalities, or long-term disability for the affected person. Gas tanks, chemical factories, nuclear power facilities, and other large-scale fire industries are among the businesses that experience major fire mishaps that can have very catastrophic repercussions. Such accidents have claimed the lives of thousands of people. As a result, the concept is improved to use a robotic vehicle to manage fire. Robotics is advancing at a rapid pace, and more and more, people are using robots for safety-related purposes. In the course of a typical day, fire incidents occur often, and firefighters occasionally face extreme difficulty rescuing lives.

Abstract – This paper assesses the effectiveness of the Internetwork E-Office Transaction Management System in modern office operations based on ISO/IEC 25010 quality standards. The system improves functionality, usability, and maintainability through centralized office tasks and automated processes with high scores. The research is quantitative-descriptive-evaluative in nature. It highlights areas of strength, such as reliability and security, and weaknesses in performance efficiency and non-repudiation in security. Data was visualized through heatmaps, bar charts, and radar charts using tools such as Python. Overall, the study puts emphasis on how the system has the potential to increase efficiency in operation and offers actionable insights that will be used to correct the identified weaknesses for continued excellence in managing transactions in an e-office.

Abstract: This study comparatively investigated the sorption of sodium laureate, sodium palmitate and sodium oleate on barite in aqueous solution taking into consideration the effect of molecular architecture (hydrocarbon chain length and degree of unsaturation) on the sorption mechanism. The effects of initial concentration, pH, adsorbent dosages, temperature and contact time for each of the adsorbates were investigated and the results obtained were analyzed using Langmuir and Freundlich isotherms and Pseudo first and Second orders. Adsorption of sodium laureate, sodium palmitate and sodium oleate on barite increases with increase in contact time, pH, temperature and initial concentration while increase in adsorbent dosage decreases spontaneously in all cases. Values of the correlation coefficients, shows that Langmuir isotherm is best for describing the adsorption of sodium laureate and sodium oleate onto barite in aqueous solution as compared to the Freundlich isotherm. For sodium palmitate, the Freundlich isotherm is best for describing the adsorption. From the R2 values of pseudo-first and pseudo-second orders, it can be observed that pseudo-second order is the best fit kinetic model for describing the adsorption of all three soap molecules on barite. Specifically, in terms of correlation, Napalmitate>Naoleate>Nalaureate. The adsorption capacity qe values for the pseudo-second order are 1.02, 2.05 and 1.13 for each of the soap similar to the K2 respectively. It has been confirmed in this study that molecular architecture of fatty acids (specifically sodium laureate, palmitate and oleate) significantly influences their adsorption behavior on barite surfaces in aqueous solutions. Chain length promotes stronger hydrophobic interaction, while unsaturation introduces (cis-double bonds) structural kinks that reduce packing density. Palmitic acid, due to its long, saturated chain, exhibits the highest adsorption affinity and stability, while oleic acid offers a balance of surface activity and molecular flexibility. Lauric acid, though more soluble, demonstrates lower adsorption potential due to its short chain and weaker interactions. The positive change in  showed that the reactions were endothermic and the increasing randomness of soap molecules is driven by the positive values of  with the highest form of randomness in pamitate>oleate>laureate. The values of the standard free energy are beyond 0 and -20 kJ/mol, asserting that the adsorption is physico-chemical sorption mechanism, reflecting the influence of physico-chemical interactions between the soap molecules and barite. This can also be asserted to the molecular architecture which favours the adsorption of the three acids in order of palmitate>oleate>laureate due to the influence of chain length and degree of saturation. The finding of this study underlines the importance of understanding the interaction between different surfactants and barite surfaces, which can have implication in mineral.

Abstract: Lichens contribute significantly in ecosystem health and biodiversity. This investigation explores the range and dispersion of lichens in the study area, with a focus on their habitat preferences and environmental adaptations. Comprehensive field surveys were conducted to document lichen species, followed by taxonomic identification using morphological, anatomical, and chemical techniques. Preliminary results reveal a rich diversity of lichen species across varying habitats, including soil, rock, and tree substrates. 15 lichen species were identified within the study area, encompassing 13 genera and distributed among 8 families.  Some of the lichen species present in the study sites are Cladonia cartilaginea Müll. Arg., Lecanora helva Stizenb., Physcia dilatata Nyl., thus showing variation in growth forms in the area. Parmeliaceae was the dominant family with 4 members followed by Cladoniaceae, Lecanoraceae and Physciaceae with 2 members each.

Abstract: This project examines the effects of different educational environment use of technology on the learning outcomes of students. Education has been made more accessible and adaptable with the help of digital interfaces, web-based material, and smart classroom equipment. The study explores different technology tools and their effects on the development of abilities, motivation, and academic achievements. To give a balanced picture, data are collected from various sources such as students, teachers, and policy briefs. Future policy and teaching strategy developments are intended to be guided by the findings.

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Abstract: The Government of Kenya is transitioning from the 8-4-4 system to the Competency Based Education (CBE) to develop a knowledge-based society capable of competing in the global job market. This study examined Board of Management (BOM) strategies for implementing CBE in Junior Secondary Schools within Webuye West sub-county, focusing on staff recruitment effectiveness, infrastructure development adequacy, and financial resource mobilization strategies. Grounded in Change Management theory. The study adopted a descriptive survey research design. The target population was 4565 respondents and 55 schools. Fowler’s formula was used to determine the appropriate sample size for each group. These included 48 BOM members, 48 headteachers, 110 teachers, and 353 students. Data collection involved questionnaires, interview guides and document analysis. Validity was established through supervisor appraisal and content validity measures, while reliability was confirmed using test-retest techniques with Pearson Correlation Coefficient computation. Both quantitative and qualitative data were analyzed using descriptive and inferential statistics, including linear regression, achieving a 97.9% response rate. Staff Recruitment significantly influenced CBE implementation (β = 0.379, p = 0.000), explaining 46.1% of variance in outcomes. It was concluded; that BOM strategies positively impact CBE implementation, with effectiveness significantly enhanced by supportive government policies. Based on the findings and conclusions, the study recommended that there is need for strengthening recruitment and professional development practices. This research provides critical guidance for educational policymakers, school administrators, and stakeholders involved in curriculum reform implementation across similar contexts.

Abstract: Digital Public Infrastructure (DPI) has resulted in a change at the population level. Inclusion is the main aim of the DPI. The ONDC serves as a Digital Public Infrastructure for online businesses. The traditional system of Digital Commerce is dominated by a closed network, wherein network participants can interact only in a constrained environment. A closed network limits access, as opposed to an Open network. It remains expensive for small business owners and establishes a confined environment for Data exchange and communication. The goal of the ONDC is to remove this restriction and to create a free environment. The study’s main objective is to look at the prospects that ONDC offers in India's numerous economic sectors. The study uses secondary data. The study's findings, viewed through a sectoral lens, demonstrate ONDC's potential to transform a number of industries, including food delivery and mobility. ONDC has the potential to revolutionize the way different sectors interact with businesses and consumers by fostering interoperability, transparency, and inclusivity. ONDC creates the foundation for a more vibrant and open ecosystem by promoting innovation and inclusivity. ONDC is providing different opportunities to various sectors, and it is continuously evolving.

Abstract: The rapid growth of mobile data traffic, fueled by a variety of user applications and diverse service needs, has created significant challenges for managing traffic efficiently in next-generation wireless networks. Typically, traditional models for traffic classification and prediction function as separate tasks, which leads to a heavier computational load and less efficient inference. This paper introduces a cohesive solution that employs multi-task learning (MTL) at the mobile edge, allowing for simultaneous traffic classification and prediction in a way that is both resource-efficient and context-aware. The proposed edge-based MTL architecture utilizes shared representations through deep neural networks, facilitating the joint learning of related tasks. This approach not only boosts task performance by leveraging the connections between tasks but also greatly reduces latency and bandwidth usage by processing data closer to its source. By implementing the model on edge servers situated near base stations, we effectively eliminate the need to send data to centralized clouds, achieving real-time intelligence. Comprehensive experiments conducted on real-world mobile traffic datasets show that our model achieves impressive classification accuracy while keeping prediction error rates low. Additionally, when compared to traditional single-task learning models, our edge-based MTL method enhances generalization, shortens training time, and supports adaptive learning in dynamic mobile environments. This research lays the groundwork for a promising framework for intelligent traffic management in 5G and beyond, fostering efficient resource allocation, network slicing, and quality of service (QoS) guarantees across various traffic scenarios.

High-temperature superconductors (HTSCs) exhibit unconventional normal state electrical resistivity, diverging from standard Fermi-liquid behaviour. Resonance scattering is a major contributing factor to this anomalous resistivity, where charge carriers strongly interact with collective excitations like spin fluctuations or impurity-induced localized states. This mechanism is particularly relevant for cuprates, where strong electron correlations and a complex energy landscape result in non-trivial temperature dependence of resistivity. This behaviour often manifests as a linear behaviour over a wide range. We discuss the microscopic origins of resonance scattering, its impact on the transport properties of HTSCs, and its role in understanding the crossover between the normal and superconducting states. We also examine experimental signatures and theoretical models that describe this phenomenon, highlighting.

Abstract: This study investigates how the Technology Acceptance Model (TAM) and its extensions can explain and predict the adoption of digital services offered by Non‑Banking Financial Companies (NBFCs) in India. Central to TAM are two key user perceptions: Perceived Usefulness (PU)—the belief that a technology enhances performance or convenience—and Perceived Ease of Use (PEOU)—the belief that using the system is effort‑free. These constructs drive Behavioral Intention (BI), which precedes actual use. To contextualize TAM within the NBFC sector—which primarily serves underserved and financially vulnerable populations—this research incorporates additional factors such as Trust, Perceived Risk, Subjective Norms, and Facilitating Conditions. Trust captures users’ beliefs in institutional reliability and data protection; Perceived Risk reflects fears of privacy breaches or hidden charges; Subjective Norms cover the influence of family or social circles; and Facilitating Conditions include factors such as smartphone access, digital literacy, and support systems. Based on these constructs, we formulate a conceptual framework in which PU, PEOU, Trust, Risk, and Social Influence affect BI, and BI in turn predicts actual usage behavior. Facilitating Conditions are postulated to moderate the translation from intention to action. Empirically, the framework is validated using a structured survey administered to a representative sample of 400–500 NBFC customers across urban and rural India. Measures are adapted from validated TAM studies and extended-fintech acceptance research. Structural Equation Modeling (SEM) is leveraged to test measurement reliability and the hypothesized relationships. Findings are expected to show that PU and Trust are strong positive predictors of BI, PEOU influences PU and intention, and that Perceived Risk exerts a negative effect. Subjective Norms and Facilitating Conditions are also anticipated to play significant roles. The research explores how demographic moderators—such as age, education, and digital literacy—shape these relationships. This study contributes to theory by adapting extended TAM to the unique context of NBFC customers in India, offering a nuanced understanding of digital financial adoption. Practically, it offers actionable insights for NBFCs and regulators seeking to enhance adoption and financial inclusion—emphasizing user‑friendly design, transparent policies, trust‑building mechanisms, and supportive digital ecosystems.

Abstract: In conventional punching machines, the time required for job setting, marking, and punching operations is relatively high, leading to increased labor cost and reduced efficiency. To overcome these limitations, a Geneva mechanism-based automatic punching machine is proposed, which significantly reduces setup time, labor involvement, and maintenance requirements. This project focuses on the design and fabrication of an automated roll punching machine using the Geneva mechanism, specifically tailored for continuous punching on paper or fabric rolls. The aim is to introduce low-cost automation in industrial applications, particularly in processes requiring repetitive punching tasks. The major components utilized in this system include a DC motor, cam arrangement, chain drive, Geneva wheel mechanism, and punching tool. The setup includes two rollers to move the paper or fabric sheet during operation. A DC motor drives the cam, which features a pin that periodically engages the Geneva wheel. The Geneva wheel, in turn, is connected to a chain drive system that moves the rollers, feeding the material for the punching operation. An IR sensor is incorporated into the system to detect the presence of paper or fabric before each punch cycle. This addition prevents dry runs, ensuring that the punching tool only operates when material is properly in place, thus increasing operational reliability, reducing wear and tear, and avoiding damage to the punch. This prototype is suitable for mass production scenarios and represents a step toward intelligent automation in material handling and processing systems.

Abstract: Bangladesh is recurrently cited as one of the most vulnerable countries to climate change. Many of the anticipated adverse impacts of climate change, such as sea level rise, higher temperatures, enhanced monsoon precipitation, increase in cyclone intensity etc aggravate the existing stresses that already hindered socioeconomic development of the country. Bangladesh’s impressive economic growth was backed by its decades of systematic investments in climate resilience and disasters preparedness. Sea level rise affects the vast coastal areas and flood plain zone of Bangladesh and gradually the situation would be worsened if appropriate measures are not taken timely. Both livelihood options of coastal communities and the natural environment of the coastal zone of the country will be affected adversely by the anticipated sea level rise (50 cm by 2050). On the other hand, the utilization of Unmanned Aerial Vehicles has rapidly evolved over the past decade in different parts of the world involving a variety of fields ranging from agriculture, commercial, coastal monitoring and becoming increasingly used in disaster management or humanitarian aid. Hence, this article aims to explore the prospects of utilization of Unmanned Aerial Vehicles for coastal monitoring in Bangladesh. This study has been initiated by collecting and reviewing primary and secondary data. Mixed-method research methodology has been used which includes both quantitative and qualitative approaches. This study has been conducted under the statistics of inferential analysis consisting t-test, Pearson correlation analysis and regression analysis. It has also considered one-way ANOVA test to examine the significant relationship among the independent and dependent variables. It is evident that applications of Unmanned Aerial Vehicles need to be further explored examining the existing challenges; to focus further on drone assistance for coastal monitoring. It is envisaged that with the sufficient supportive actions and policy measures, the application of Unmanned Aerial Vehicles for coastal monitoring including disaster management in Bangladesh appears to be promising and will improve its effectiveness.

Abstract Background: Congenital heart diseases are group of pathologies that involve the cardiovascular system since birth but their diagnosis might delay years then after. Objective: This thesis focuses on the pattern of these anomalies in two Iraqi cardiac centers. Method: Prospective cross-sectional study involves all the newly diagnosed patient with congenital heart diseases for eight months duration, in (IBN Al-Nafees Cardiovascular Teaching hospital and IRAQI Center of Cardiac Diseases) in Baghdad-Iraq. Results: more than 200 patients involve in the study; Cardiac murmur was the comments presenting clinical finding to seek medical advice, VSD is the most frequent diagnosis.12% of the patient were syndromic with down syndrome was the most common enfaced clinical syndrome. Conclusion: VSD is the most common A cyanotic CHD, While TOF is the most common cyanotic one.

Abstract: This study investigates the molar heat capacities (Cp) of three choline chloride-based deep eutectic solvents (DESs)—Reline, Ethaline, and Glyceline—and their binary mixtures with two structurally distinct alcohols: 1-butanol (linear) and 2-butanol (branched). Cp measurements were carried out under standard pressure using a differential scanning calorimeter (DSC) across a temperature range of 303.2 K to 353.2 K at various compositions. Results show that Cp increases with both temperature and DES concentration. The temperature dependence of pure DESs was well described using a second-order empirical model, with an average absolute deviation (AAD%) of 0.05. The binary mixtures exhibited predominantly negative excess molar heat capacities (Cpᴱ), indicating non-ideal mixing behavior due to altered hydrogen-bonding interactions. The Redlich–Kister polynomial equation effectively correlated the Cpᴱ values with temperature and composition. The comparative analysis of mixtures with linear and branched alcohols highlights the significant impact of molecular structure on thermal behavior, providing valuable insights for designing sustainable solvents for heat-sensitive and green chemical processes.

Food waste processing holds great potential in mitigating global food insecurity. Valorization of food waste is a sustainable practice that also lessens the effects of climate change. Isolation, identification, and characterization of lactic acid bacteria from fermented soya pulp was conducted. The isolated lactic acid bacteria species was utilized as starter culture to produce soy yogurt. This study was performed to identify LAB isolated from fermented soya pulp using 16s rRNA gene sequencing; to ferment soymilk using the LAB isolated from fermented soya pulp and develop soy yogurt; to determine the proximate nutritional composition of the soy yogurt through proximate analysis; and to evaluate the sensory characteristics of the yogurt such as color, aroma, texture, taste, and overall acceptability. The 16s rRNA gene sequencing procedure identified the isolated lactic acid bacteria species as Pediococcus pentosaceus Mees, 1934. Four yogurt samples were formulated using P. pentosaceus and a commercial starter culture. Proximate compositions such as titratable acidity, ash content, crude protein, and crude fat were determined. The soy-based yogurt drinks were similarly high in protein compared with the cow’s milk counterpart. Notably, formulation 1 with the P. pentosaceus as the sole starter culture scored highest in crude protein.  Significant difference in the average ash content between the four samples was observed. Post-hoc analyses using the Bonferroni correction revealed that formulation 1 with the isolated starter culture, P. pentosaceus, had the highest ash content. Sensory evaluation revealed that formulation 2 with both the isolated starter culture and commercial starter gained peak in color, taste, and overall acceptability. There was significant difference in the average aroma and texture scores between the four samples, favoring the cow’s milk yogurt sample for the aroma and the soymilk yogurt with both P. pentosaceus and commercial starter culture for the texture. This study showed the potential of P. pentosaceus as a sole starter culture and in combination with commercial starter culture in producing functional foods from food waste such as soymilk-based yogurt. Refinement and standardization of the yogurt production protocol is recommended to produce the yogurt with better texture and taste. By so doing, product development from food waste can support sustainable food production and mitigate global food insecurity and climate change.

Abstract: Aircraft altitude is a fundamental parameter in aviation, influencing flight safety, efficiency, and operational performance. This study explores the significance of altitude in relation to aircraft type, atmospheric layers, and flight dynamics. It outlines the standardized use of flight levels to maintain organized air traffic and prevent collisions. The paper examines how different aircraft—from commercial airliners to military jets and ultralights—operate at distinct altitude ranges tailored to their design and mission profiles. It also discusses the physical challenges of high-altitude flight, such as low air density, the need for cabin pressurization, and the role of service and absolute ceilings. Key aerodynamic and atmospheric concepts, including density altitude and jet streams, are analyzed for their operational impact. Furthermore, altitude considerations are contrasted between long-haul and short-haul flights, and common high-altitude aviation questions are addressed. The findings emphasize that altitude is not merely a technical metric but a dynamic factor integral to modern flight operations and airspace management.

Abstract: Deepfake technology, driven by Generative Adversarial Networks (GANs) and diffusion models, presents significant political, social, and economic threats. This review consolidates insights from over 30 scholarly contributions on deepfake detection techniques, datasets, evaluation metrics, and ongoing challenges. We examine both traditional methods and modern deep learning strategies, including convolutional neural networks (CNNs), transformers, multimodal architectures, and ensemble frameworks. Key benchmark datasets—DFDC, FaceForensics++, and Deepfake-Eval-2024—are comparatively analyzed. Performance metrics such as accuracy, AUC, F1-score, and Matthew’s correlation coefficient (MCC), along with adversarial robustness, are critically assessed. Identified limitations include poor cross-domain generalization, suboptimal real-time performance, and dataset bias. The review proposes future directions including adaptive detection models, enhanced multimodal fusion, model interpretability, and the need for unified global standards in forensic validation.

Abstract: The development of biotechnology technology in food production poses new challenges in determining the halal status of products, especially for Muslim consumers. This article discusses various modern biotechnology techniques such as genetic engineering, precision fermentation, cell culture, and microbial biotechnology, and their impact on Islamic law and ethics. Using a multidisciplinary approach between science and fiqh, it examines how genetically modified products can be declared halal or haram based on the maqasid principle of sharia, which includes the preservation of religion, soul, mind, offspring and property. It also highlights the importance of MUI fatwa and halal certification institutions to accommodate food biotechnology innovations. This article emphasises the need for science-based halal education and harmonisation of global halal standards so that biotechnology food products can be widely accepted by the world's Muslim communities.

Abstract: This study assessed the influence of entrepreneurial culture of technologyinnovation on customer satisfaction of indigenous oilfield services companies in selected South-South States, Nigeria. The study adopted descriptive cross-sectional survey research design based on specific research objective, question and hypothesis aligned with the research problem. The study used a self-developed five-points Likert scale questionnaire as instrument of data collection from respondents. The study population was 1827 indigenous oilfield services companies in selected South-South States, Nigeria obtained from Nigerian Content Development and Monitoring Board (NCDMB) approved register. The study sample size was 328 obtained using Taro Yamane’s formula for sample size determination and proportionally allocated with Bowley’s formula. Microsoft Excel Software Package version 2016 and International Business Machine Statistical Packages for the Social Sciences (IBMSPSS) version 29 software application tools were used in computing data for descriptive and inferential results. The results showed that entrepreneurial cultureof technology innovation significantly and positively influenced customer satisfactionof indigenous oilfield services companies in selected South-South States, Nigeria. The study concludes that entrepreneurial culture of technology innovation had significant positive influence on customer satisfaction of indigenous oilfield services companies in South-South States, Nigeria.

Abstract: The aim to acquire online is crucial and intriguing in the current climate. It directly influences client purchasing decisions. Consequently, firms employ several marketing strategies to capture customer attention for purchasing decisions. This study presents a model of customer experience and purchase intention in an electronic environment, incorporating the moderating effect of perceived risk. A total of 179 internet users were solicited to contribute data using a distributed questionnaire utilizing a non-probability convenience sampling method. Additionally, multiple regression analysis was employed to evaluate the model of customer experience and online purchase intention, incorporating the sub-dimensions of customer experience: interaction, informativeness, convenience, and trust aspects. Process analysis was employed to assess the moderating effect of perceived risk on the relationship between consumer online experience and purchase intention. The study's results unequivocally demonstrate that trust and convenient influence frequent purchasing in an online context. The perceived risk does not influence the link between consumer perceived experience and purchase intention.

Abstract - A locally developed python programming language algorithm was used in the deduction of optical depth (OD) for solar irradiance measurement at 500nm, 675nm and 875nm solar wavelengths at Ilorin (Long. 8.573°N, Lat. 4.5444°E) Nigeria. Results obtained indicate a positive trend in all three wavelength measurements in January of 2003, 2013, and 2024. The correlation with report of desert encroachment which was measured as about 0-6km per year indicates clearly that OD measurement can be used as a precursor to desert encroachment. Results of measurements made in November, December and January of 2003/2004, 2013/2014 and 2024/2025 give a positive trend in both parameters especially at the 500nm and 675nm wavelengths. Hence the result is quite encouraging being the first of such comparison at the sub-Saharan site.

Abstract: The purpose of the study is to assess the combined impact of eggshell powder (ESP) and fly ash (Class F) and rice husk ash (RHA) as additional cementitious materials in concrete applications. Fly ash is widely used in concrete works due to its ability to improve mortar and concrete properties. The usage of eggshells, a biodegradable waste product from bakeries, fast food establishments, and chick hatcheries, is also examined in this study. It assesses the fly ash-f, RHA, and ESP blended cements' chemical makeup, physical characteristics, consistency, beginning and final setting times, pH level, and compressive strength. The strength property of ESP blended cement mortars is also evaluated. The study also compares the strength properties of ESP concrete mixes and a control mix. The study also assesses the coefficient of water absorption, sorptivity, resistance to chloride ion penetration, and diffusion coefficient. The findings will help determine how much fly ash and rice husk ash should be replaced in concrete. Water permeability decreased by around 56.8%. A drop in chlorine penetration of about 75.55 percent. A decrease in chloride diffusion of about 49% For 28, 56, and 90 days in an acid solution, the rate of deterioration of RA0 cement concrete (control samples) exposed to acid resistance (HCl & H2 SO4) and sulfate resistance was significantly higher than that of RA4 cement concrete (15FA15RHA5ESP). A decrease in corrosion of almost 88.72% (Good corrosion inhabiting)

Abstract: Heart failure (HF) is a major worldwide health concern, with significant morbidity, death, and healthcare expenditures. Traditional therapy sometimes fall short of improving outcomes, particularly in patients with preserved ejection fraction (HFpEF) and concurrent type 2 diabetes mellitus. Sodium-glucose co-transporter 2 (SGLT2) inhibitors, which were first designed for glycaemic management in T2DM, have shown considerable cardiovascular and renal advantages irrespective of glucose reduction. This review examines the evolving role of SGLT2 inhibitors in heart failure care, drawing on key studies such as DAPA-HF, EMPEROR-Reduced, EMPEROR-Preserved, and SOLOIST-WHF. SGLT2 inhibitors, such as dapagliflozin, empagliflozin, and sotagliflozin, have consistently decreased the incidence of cardiovascular mortality and heart failure hospitalisations in patients with reduced and maintained ejection fractions, independent of diabetes status. These medicines enhance myocardial metabolism by improving ketone body utilisation, increasing cardiac efficiency, and decreasing fibrosis and inflammation. They also influence neurohormonal pathways such as the renin-angiotensin-aldosterone system (RAAS), sympathetic nervous system (SNS), anti-diuretic hormone (ADH), and endothelin systems, which help to enhance haemodynamics and fluid balance. Clinical trials have shown benefits in quality of life, symptom load, and renal outcomes, with few adverse events such as hypoglycemia or ketoacidosis. Early usage of SGLT2 inhibitors during heart failure decompensation results in faster symptom alleviation and improved patient outcomes. Finally, SGLT2 inhibitors have emerged as a cornerstone treatment for heart failure, providing advantages to a wide range of individuals. Their inclusion in heart failure recommendations represents a significant change in the management of both HFrEF and HFpEF.

Abstract: Leadership is a critical factor in how individuals work toward achieving organizational objectives. It is widely acknowledged that leaders in Higher Education (HE) face unique challenges and perform distinct roles compared to their counterparts in the corporate world.  As a result, Higher Education is beginning to rethink their traditional approach to managing institution and a call for student to engage in the designing process. Humble leadership is instrumental in reaching these goals. This paper explores the impact of personality traits and humble leadership on team effectiveness, specifically among leaders in Higher Education and examines how the curriculum in UK higher education can be co-created. The study employs a mixed method research design through surveys and focus group, aiming to describe and explain the current state of leadership by evaluating the spectrum of humility and personality traits in this context. A total of 30 respondents were targeted through convenience and purposive sampling techniques, with a response rate of 77%, sufficient for drawing conclusions and generalizing findings. The results indicate that subordinates strongly agree that their leaders demonstrate humility. Furthermore, the study examines the personality traits of these leaders, revealing that those with low levels of neuroticism are less affected by negative feedback or criticism and are better equipped to handle challenges and setbacks with greater adaptability. Spearman’s rho correlation (0.749) shows a strong positive link between student engagement and satisfaction (p = 0.001), indicating higher engagement leads to greater satisfaction. Consequently, the study concludes and recommends that humble leadership and positive personality traits, particularly agreeableness and openness, among university staff significantly contribute to enhanced team effectiveness. Rich qualitative data were collected from the same group of surveyed participants through a focus group session involving three (3) university staff members, two (2) students, and two (2) employability experts. This session was conducted as part of a co-creation process aimed at developing a learning curriculum.  Key themes identified through thematic mapping during the session included skill gaps between what students learn in school and what is required by the industry, technology advancements such as ChatGPT in writing essay, student needs as they are viewed as active participants rather than passive recipients of education, employability among others. Curriculum co-creation between university staff, student and industry voice has become increasingly popular in recent years. The author research indicates that curriculum co-creation has the potential to bring together diverse perspectives and expertise to address complex social issues, generate innovative solutions, and foster mutual learning and knowledge exchange.

Abstract: Smart materials that react to environmental stimuli, such as temperature, pH, light, or electromagnetic fields are transforming cancer treatment by enabling precisely controlled drug release. Nanoparticle-based delivery systems enhance drug solubility, prolong circulation time, and concentrate therapeutics at tumor sites, mitigating damage to healthy tissues. Stimuli-responsive systems triggered by internal or external cues offer spatiotemporal control over release, improving safety and efficacy. This review outlines recent advances in smart nanocarriers for cancer therapy, examines their mechanisms, highlights clinical successes, addresses current challenges, and explores future directions including AI-driven personalization and emerging nanotechnologies.

Abstract: The rapid growth of mobile data traffic, fueled by a variety of user applications and diverse service needs, has created significant challenges for managing traffic efficiently in next-generation wireless networks. Typically, traditional models for traffic classification and prediction function as separate tasks, which leads to a heavier computational load and less efficient inference. This paper introduces a cohesive solution that employs multi-task learning (MTL) at the mobile edge, allowing for simultaneous traffic classification and prediction in a way that is both resource-efficient and context-aware. The proposed edge-based MTL architecture utilizes shared representations through deep neural networks, facilitating the joint learning of related tasks. This approach not only boosts task performance by leveraging the connections between tasks but also greatly reduces latency and bandwidth usage by processing data closer to its source. By implementing the model on edge servers situated near base stations, we effectively eliminate the need to send data to centralized clouds, achieving real-time intelligence. Comprehensive experiments conducted on real-world mobile traffic datasets show that our model achieves impressive classification accuracy while keeping prediction error rates low. Additionally, when compared to traditional single-task learning models, our edge-based MTL method enhances generalization, shortens training time, and supports adaptive learning in dynamic mobile environments. This research lays the groundwork for a promising framework for intelligent traffic management in 5G and beyond, fostering efficient resource allocation, network slicing, and quality of service (QoS) guarantees across various traffic scenarios.

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: This study aimed to explore the moderating role of emotional intelligence between personality traits and mental health issues (depression, anxiety, and stress) among university students in Bangladesh. A total of 302 students (151 males, 151 females) from Gopalganj Science and Technology University participated using a convenience sampling method. A cross-sectional design was employed. Data were collected using the Bangla versions of the Big Five Inventory-10 (BFI-10), the Emotional Intelligence Scale (EIS), and the Depression Anxiety Stress Scale-21 (DASS-21). Correlational analysis revealed that personality traits and EI were significantly associated with mental health variables. Specifically, extraversion, agreeableness, conscientiousness, openness, and EI were negatively correlated with depression, anxiety, and stress, while neuroticism showed positive correlations. Hierarchical regression analyses showed that personality traits significantly predicted depression, anxiety, and stress. Adding EI increased explained variance across all outcomes, and interaction terms revealed that EI significantly moderated the relationships between certain personality traits and mental health. Notably, interactions between EI and conscientiousness, openness, and neuroticism significantly influenced depression; EI with extraversion, agreeableness, conscientiousness, and openness influenced anxiety; and EI with extraversion, conscientiousness, openness, and neuroticism influenced stress. These findings suggest that emotional intelligence serves as a protective factor, buffering the impact of certain personality traits on mental health outcomes. The study highlights the importance of integrating personality and emotional skills into mental health support strategies for young adults.

Abstract: Men, environment and development remained disentwine issues of discussions in academic circles after the advent of industrialization. Cement industry pushed this debate further. The present study takes into consideration the impact ofthe oldest cement plant in Himachal Pradesh, Rajban in Sirmour district into consideration. The main objectives of the present research are: 1. effects of cement plant on the health of the people, 2. influence on human settlements, 3. impact on nearby vegetation. For the purpose of this study, stratified samples of population were collected from three nearby villages during 2021-2023. Also, official websites of government and cement plant was taken into consideration. For few quarries, RTI was also sought from the respective agencies. Information regarding health status and diseases was collected through house to house interviews and medical receipts of various hospitals and dispensaries. Photographs of deserted houses and dusty trees and shrubs were taken during field survey only. The present research derived following conclusions: 1. Exposure to cement dust increased human health risks, 2. Human settlements were affected due to the dust and pollution, 3. Thick layer of dust on plants had resulted into stunted growth of vegetation.

Abstract: Over the past decade, a significant number of infrastructure projects have been implemented across Bangladesh, resulting in a rapid increase in demand for construction materials. In the fiscal year 2017 to 2020 alone, approximately 12.7 million tons of aggregate were consumed by the construction industry, of which only 13% were sourced locally. The rest were imported, leading to variability in concrete performance due to differences in aggregate characteristics. This study investigates the influence of commonly used coarse aggregate types on concrete properties, with a focus on developing sustainable infrastructure. Six widely used coarse aggregate sources Balason, Shebok, Torsha, Dandruff Mine, Pakur Black Stone, and Kothin Shila were selected for analysis. Laboratory tests were conducted to determine the physical, chemical, and petrographic properties of these aggregates, including Aggregate Crushing Value (ACV), Aggregate Impact Value (AIV), Los Angeles Abrasion (LAA), Elongation Index (EI), Flakiness Index (FI), specific gravity, water absorption, and unit weight. Additionally, aggregates were subjected to visual and mechanical preparation including washing, drying, sieving, and shape evaluation using thickness and length gauges. Cement consistency was assessed using Vicat’s apparatus. Concrete mixes with constant gradation and water-cement ratios (0.4) were used to cast cylinders. Tests were conducted to measure compressive strengths. Results revealed that the physical properties of aggregates significantly affect concrete strength, particularly when compressive strength exceeds standard values. Among the samples, Balason aggregate exhibited the highest 28-day compressive strength (267.39 kN), followed by Shebok and Pakur, while Kothin Shila showed the lowest strength (123.10 kN). The findings provide essential guidance for engineers in selecting suitable aggregate sources based on the required concrete strength, contributing to more durable and reliable infrastructure in Bangladesh.

Abstract: Bituminous concrete, often referred to as asphaltic concrete, is one of the most technically refined and high-cost types of flexible pavement layers employed in surface courses. Due to its premium performance requirements, bituminous mixtures are precisely formulated to meet specific standards for strength, stability, and durability. This composition includes well-graded coarse aggregates, fine aggregates, and a mineral filler, all uniformly coated with a bitumen binder. The mineral filler, which passes through a 0.075 mm sieve, plays a crucial role in enhancing the performance of asphalt mixtures. Research shows that Marshall Stability improves with an increase in filler content, and the Asphalt Institute recommends 4 to 8% filler content in asphalt concrete. In Bangladesh, traditional fillers like cement, limestone, and granite powder are neither economically viable nor widely available. As an alternative, this study investigates the use of a 50:50 blend of recycled concrete (R.C.C) waste dust and brick masonry waste combined with natural sand as a cost-effective and sustainable filler. The study evaluates the performance characteristics of bituminous mixtures incorporating this blended filler and compares the results with those of mixes using conventional filler materials such as fine sand and stone dust. The Marshall mix design procedure was utilized to assess the strength and workability of the mixes. The Marshall Stability values obtained for mixtures using fine sand with stone dust and the blended filler (50:50 blend of recycled concrete (R.C.C) waste dust and brick masonry waste) were both of them 2.15 kN respectively, all surpassing the minimum requirement as outlined in the Marshall Design criteria. These findings suggest that the use of recycled R.C.C and brick masonry waste in combination with sand can serve as a promising and economical filler alternative in asphaltic concrete.

Abstract: Field service operations often face scheduling inefficiencies that lead to wasted travel time, underutilized work hours, and decreased productivity (Alp et al., 2024; Yahiaoui et al., 2023). This study examined how V Zone International LLC optimized its technician scheduling and routing to maximize productivity and minimize idle time. Using a case-study approach with operational data from four instances, we analyzed current scheduling practices and identified bottlenecks such as vehicle unavailability and poor coordination (Stein et al., 2024; Gamst et al., 2022). Improved scheduling models based on the Vehicle Routing Problem with Time Windows (VRPTW) were developed to group nearby tasks and sequence visits efficiently (Castañe et al., 2014; Basak & Nguyen, 2023). Simulations compared the status quo with optimized schedules, measuring metrics like tasks completed per day, travel distance/time, and idle time. Results showed that route optimization and task clustering significantly improved technician utilization and reduced costs. For example, optimized scheduling reduced visits from 9 to 3 for 30 installations in one case, saving substantial technician-hours. The study concluded that advanced scheduling strategies could lead to significant productivity and cost savings for V Zone.

Abstract: In today’s competitive business environment, organizations must go beyond financial compensation to retain and motivate their workforce. This case study explores the application of non-monetary motivational strategies within the corporate ecosystem of Bangalore, a major hub of India’s knowledge-based economy. Through an analysis of intrinsic motivational techniques such as public recognition, flexible work practices, career growth pathways, and wellness programs, the study highlights the evolving expectations of employees and the shifting paradigms of organizational behavior. Theoretical grounding is drawn from Herzberg’s Two-Factor Theory (Herzberg, 1968) and Deci and Ryan’s Self-Determination Theory (Deci & Ryan, 1985), both of which emphasize the central role of psychological fulfillment in fostering motivation. Findings suggest that non-cash incentives play a crucial role in enhancing employee satisfaction, reducing turnover, and improving productivity. These approaches are particularly impactful in urban, high-skill settings like Bangalore, where workers increasingly value autonomy, purpose, and well-being over monetary gain alone.

Abstract: The present paper deals with the diversity and taxonomy of Phytopathogenic fungi on families Fabaceae and Caricaceae including addition of two new species of Cladosporium viz, C.caricae-papayae and C.cassicolum causing foliar disease on Caricapapaya (Caricaceae) and Cassiafistula (Fabaceae) respectively.The present species are described,illustrated and compared with closely related species.These novel species are characterized by branched,longer,smooth conidiophores,and smooth. longer conidia.Description and nomenclatural details are deposit in Mycobank(www.Mycobank.org).

Abstract: A strategic model for sustainable growth must revolve around the procedures that constitute circular economy. This economy emphasizes optimizing resource efficiency, reducing the total waste and closed-loop production methodologies. The economic development in India is highly dependent on growth and output of micro-, small- as well as medium Enterprises (MSMEs), yet the circular economy practices are largely not adopted. This paper explores Panipat’s textile MSMEs regarding investigating the awareness levels and adoption of circular economic practices, relating this with their educational levels. It was seen that the entrepreneurs with higher educational levels tend to have higher awareness levels, as well as willingness to implement such practices. The prediction models adopted for this study showed that the likelihood of resorting to circular economy practices depends not only on education levels but also on firm characteristics. Our study explicitly explains that education is a vital enabler for driving sustainable transitions in MSMEs. Concluding the study, we have recommended that targeted training programs, friendly policy frameworks and collaborative channels can play significant roles in enhancing the acceptability of circular economy practices in small-scale enterprises.

Abstract: Mobile money has become a key driver of financial inclusion in Ghana, improving access to financial services for underserved populations since its introduction in 2009. With over 330 million active accounts in sub-Saharan Africa by 2023, mobile money supports everyday transactions like remittances and bill payments [1][2]. Usage is higher in urban areas (72%) than in rural areas (47%) indicating a notable accessibility gap [3][4]. Young adults aged 18-27 form the majority of users, with women representing 52.7% of participants [5]. However, challenges like gender disparities, financial literacy, and economic barriers continue to hinder widespread adoption, especially among women [6][7]. Mobile money has helped increase economic resilience, especially for women by enhancing their ability to engage in financial activities [8]. Nonetheless, concerns over security, regulations and transaction costs remain significant, especially in rural regions [9][10]. These issues highlight the need for policy reforms to ensure equitable benefits across all demographics [11]. The future of mobile money in Ghana depends on technological progress and stakeholder collaboration to improve security and accessibility [12][13].

Abstract: The human body demonstrates an association between mathematical and biological fields, since its structure, proportions, and functions are determined by mathematical concepts.  This research investigates how geometry, ratios, biomechanics, and modeling may be made used of understanding the human body.  Facial proportions, limb lengths, and total body symmetry [6] all adhere to the Golden Ratio, which is required for structural and aesthetic balance.  The connecting patterns of blood vessels, neurons, and the respiratory system are geometric in nature, which increases the efficiency of physiologic processes [3].  The center of gravity serves as vital role in posture and movement, and the skeletal and muscular systems' mechanics follow the laws of leverage, anxiety, stress, and strain [4]. DNA structure and embryonic development are also influenced by the Fibonacci sequence and logarithmic spirals [8]. Mathematical modeling is essential for understanding brain connections, respiratory efficiency, and circulatory dynamics. Modern technologies, such as gait analysis, prosthesis, and medical imaging, emphasize the relevance of mathematics in biomechanics and medicine [2]. This study investigates the complex mathematical structure of the human body in order to emphasize the close relationship between mathematical theories and biological systems.

Abstract: We are entering a new world, and lots of worldwide supply chains are unwell equipped to cope with it. As an end result, so as for Supply chain managers to create price across the company, they need to consciousness on making agencies extra connected and agile as opposed to just cutting fees. Every day, new virtual technology are being developed, and they may be about to upend nearly every element of conventional business techniques. Nearly each industry's top enterprise precedence could be on the middle of the approaching virtual technology. The digitization technique places a variety of strain on companies to trade and affects nearly the entirety in modern-day businesses, such as supply chain management. Consequently, managers must realize the results of digitization on their employer and personnel. The modern state of affairs emphasizes the importance of organizational and people control in virtual modifications. Digitization has an expansion of effects at the economic system as an entire; corporations will face both extensive opportunities and challenges as a result. In state-of-the-art globalized world, digitization isn't a preference but a necessity for all agencies in all sectors. The primary goals of digitization are the business model, products and services, manufacturing tactics, and work. The six methods of large statistics, cloud services, particular identification and show innovation, robotics, sensors and relocation, nanotech and 3-D printing, and it may be the virtual transformation enablers and framework mentioned on this observe. 

Abstract: Blood spatter analysis plays a prominent role in forensic investigations that shed light on the very dynamics of violent crimes. This review discusses the basic principles, techniques, and prospective applications of blood spatter analysis in forensic science. It examines the main factors affecting blood spatter patterns, including the nature of the force applied, the angle of impact, and the character of the surface onto which the blood is deposited. The paper discusses various analytical methods, such as mathematical modelling, chemical techniques, photographic documentation, and the use of specialized software, alongside the challenges faced in interpreting complex blood spatter evidence. Moreover, the review addresses advancements in the field, highlighting technological innovations like 3D reconstruction and the integration of blood spatter analysis with other forensic disciplines. It explains about the recent advances and innovations and the development of new imaging tools to interpret blood spatter; potential advances that are needed. Finally, the paper emphasizes the importance of standardized protocols and the need for continued research to enhance the reliability and accuracy of blood spatter interpretation in criminal investigations.

Abstract— The increasing prevalence of airborne infectious diseases has necessitated the development of intelligent, automated screening systems to ensure public safety in high-risk environments. This paper proposes a deep learning and neural network-based approach for integrated face mask detection and non-contact temperature identification. The system is designed to operate in real-time and is suitable for deployment in public spaces such as transportation terminals, corporate entry points, and commercial facilities. To enhance identification accuracy under mask-wearing conditions, the proposed framework employs a masked facial recognition technique that utilizes convolutional neural networks (CNNs) to analyze visible facial features. In parallel, a contactless infrared temperature sensor enables real-time thermal screening without human intervention. The system architecture is supported by a lightweight, reliable IoT communication protocol for efficient data transmission to a cloud-based platform, enabling remote monitoring through web and mobile applications. Experimental validation demonstrates that the proposed system achieves high accuracy in both mask detection and temperature measurement, outperforming conventional manual methods in terms of speed, reliability, and scalability. The collected data can be further utilized for health analytics and decision support by relevant authorities. This work contributes a cost-effective, scalable solution for enhancing public health safety through automation and intelligent sensing.

Abstract. Plant diseases are a critical barrier to agricultural sustainability, contributing to annual crop losses of 30–40% in some regions. Such diseases arise from diverse pathogens, including fungi, bacteria, and viruses, and can severely degrade crop yield and quality if undetected. Early diagnosis is crucial for timely intervention, reduced pesticide use, and long-term soil health. Traditional approaches, which rely on manual visual inspection of leaves, remain slow, subjective, and impractical for monitoring large or remote farms. In recent years, the convergence of artificial intelligence (AI), computer vision, and image-based analysis has enabled automated disease detection systems that are both scalable and real-time. Classical techniques first employed color, texture, and shape descriptors combined with machine learning models such as Support Vector Machines (SVM), k-Nearest Neighbor (KNN), and Random Forests. These methods achieved moderate success but struggled with variability in lighting, background, and leaf orientation. The introduction of deep learning, particularly Convolutional Neural Networks (CNNs), transformed plant disease detection by allowing end-to-end feature learning directly from raw images. Modern lightweight architectures like MobileNet and EfficientNet further enhance deployability on mobile and edge devices. In parallel, segmentation-assisted and hybrid models improve robustness under complex field conditions. This review consolidates these developments, evaluating methods in terms of accuracy, generalization, computational efficiency, and field-readiness. It also identifies persistent challenges—such as limited annotated datasets and the opaque decision-making of deep models—and highlights future directions in explainable AI, multi-modal sensing, and IoT-integrated precision agriculture.