International Journal of Innovations in Science, Engineering And Management
IJISEM International Journal of Innovations in Science, Engineering And Management A Peer-reviewed Scholarly Indexed Quarterly Journal International Journal of Innovations in Science, Engineering, and Management (IJISEM) is an open-access publication overseen by IJISEM Journals. It is dedicated to fostering the interests of emerging and promising writers. IJISEM endeavors to transcend geographical boundaries by welcoming contributions from professionals and academics worldwide, not limited to India. We thus adopted the term International as our motto and used it in the title of our journal. We are dedicated to fostering innovation and excellence across scientific, engineering, and management disciplines through our commitment to sharing knowledge. The publication focuses on research and intellectual viewpoints in order to achieve this goal. Realistic analysis, interdisciplinary/applied/methodological, empirical evidence production and utilization, critical viewpoint development and policy building work are all welcome in achieving this goal. IJISEM aims to provide a platform for doctoral researchers to showcase their investigations and disseminate their research findings and knowledge to a wider audience. IJISEM International Journal of Innovations in Science, Engineering and Management Title IJISEM International Journal of Innovations in Science, Engineering And Management Frequency Quarterly (July, October, January and April) ISSN 2583 – 7117 Publication Format Online Chief Editor Dr. Rajesh Gupta Publisher Yogesh Sharma, M.Tech (Industrial Design) Subject Multidisciplinary Published by IJISEM Journals Starting Year 2022 E-Mail editor@ijisem.com Mobile No (+91) 70893666889 Mobile No (+91) 9981622288 Publishing Body AG Publishing House Language Multiple Languages Copyright AG Publishing House Website http://www.ijisem.com/ Address IJISEM Journals 57-First Floor, Susheela Bhawan, Priyadarshini Phase-3, near Meenakshi Planet City, Bagmugaliya, Bhopal, Madhya Pradesh 462043
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FOX NUT (MAKHANA): Bihar’s Superfood with Global Potential - A Multidimensional Analysis of Nutritional Value, Economic Prospects and Sustainable Commercialization
Makhana the popped kernel of Euryale ferox Salisb. Makhana has transformed from a local wetland crop of Bihar into an strategic and important functional food, export commodity and asset for rural development. This study shall build a multi-faceted empirical understanding of makhana through combining nutritional biochemistry, agricultural economics and export competitiveness, value-chain efficiency and sustainability. The paper creates an analytical dataset from secondary sources, including Government of Bihar production estimates tied to various government policies, evidence from ICAR-RCER value chains, PMFME/NIFTEM technical documentation and peer-reviewed food-science research as well as policy announcements in 2025, and uses descriptive statistics, CAGR estimation, correlation analysis, multiple regression, time-series projections and SWOT analysis. The nutrition comparison indicates that makhana is not a traditional high fat nut – rather it is a low fat, carbohydrate rich, low glycemic snack with significant protein and mineral content. The economic analysis shows robust growth in area, production, and market visibility, with the area expanding from the APEDA dashboard midpoint estimate of 2020 (7.3 Lakhs Ha) to 2025 expectation (14.5 Lakhs Ha), and the production rising from 2020 midpoint (0.5 Lakhs Ha) to 2025 expectation (1.5 Lakhs Ha) and the export volume steeply rising from 2020 (6.7 Killed MT) to 2024 (25.1 Killed MT) before narrowing down slightly in 2025 (Jan-Oct) estimate. The positive effects of production volume and processing capacity and market expansion on the export performance index constructed here are the strongest, evidence pointing toward regression that GI branding embraces quality signalling and origin differentiation to strengthen commercialization. The study posits that addressing the constraints of productivity growth along with institutional/policy interventions like mechanised processing, export grade quality system, FPO aggregation, gender inclusive interventions and product innovations like healthy snacks, nutraceuticals and functional foods will be crucial for Bihar's potential to rise as a global hub for makhana.
Copyright (c) 2026 Vikash Kumar Singh https://creativecommons.org/licenses/by-sa/4.0
ESG Practices and SME Performance: A PLS-SEM Analysis of Financial Forecasting and Sustainable Practices
SMEs are quickly adopting ESG practices to boost organisational performance, deepen their sustainability commitment and increase their capacity to make wise financial decisions. The aim of this research is to analyse the impact of environmental, social and governance practices on financial projections, standards of sustainability, and SMEs. Partial Least Squares Structural Equation Modelling (PLS-SEM) was conducted using ADANCO using data from 230 SME owners in Odisha. People were given the questionnaire. The model has seven components: SMEs’ performance, environmental, social, governance, financial predictions and sustainable methods . The measurement model was shown to be accurate and valid with adequate Average Variance Extracted (AVE) values and significant explanatory power (R2 values over 0.88 for all endogenous constructs). The structural model illustrates that ESG activities are substantially beneficial for environmental, social and governance practices. The structural model also revealed that ESG practices might enhance financial predictions and sustainability. Financial projections and sustainable methods boost the performance of SMEs, which demonstrates the strategic value of incorporating environmental, social and governance principles into the operations of a firm. The results demonstrate that ESG-led financial planning and sustainability initiatives are important to long-term competitiveness, resilience and company development. This study offers practical recommendations for SMEs and policymakers.
Copyright (c) 2026 Subrat Kumar Rout, Suresh Kumar Sahoo, Vishal Sood https://creativecommons.org/licenses/by-sa/4.0
ग्रामीण विकास में महिला सरपंचों के नेतृत्व एवं योगदान का समाजशास्त्रीय अध्ययन: अशोकनगर जनपद पंचायत, मध्य प्रदेश के विशेष संदर्भ में”
भारत में 73वें संविधान संशोधन अधिनियम, 1992 के लागू होने के पश्चात पंचायती राज संस्थाओं में महिलाओं की सहभागिता को संवैधानिक आधार प्राप्त हुआ, जिससे ग्रामीण स्थानीय स्वशासन में महिलाओं की भागीदारी और नेतृत्व को नई दिशा मिली। प्रस्तुत अध्ययन में मध्य प्रदेश के अशोकनगर तहसील के जनपद पंचायत अशोकनगर के संदर्भ में पंचायती राज व्यवस्था में निर्वाचित महिला प्रतिनिधियों की भूमिका, उत्तरदायित्व, निर्णय-निर्माण की क्षमता, नेतृत्व शैली तथा ग्रामीण विकास में उनके योगदान का समाजशास्त्रीय विश्लेषण किया गया है। इस अध्ययन में महिलाओं की राजनीतिक सहभागिता को प्रभावित करने वाले सामाजिक, आर्थिक, शैक्षिक एवं सांस्कृतिक कारकों का परीक्षण किया गया है। साथ ही यह भी विश्लेषण किया गया है कि आरक्षण व्यवस्था ने महिलाओं के सशक्तिकरण, आत्मविश्वास, सामाजिक प्रतिष्ठा तथा स्थानीय शासन में उनकी प्रभावशीलता को किस सीमा तक बढ़ाया है। अध्ययन में महिला प्रतिनिधियों के समक्ष आने वाली प्रमुख चुनौतियों का भी विवेचन किया गया है। प्रस्तुत शोध में प्राथमिक एवं द्वितीयक दोनों प्रकार के तथ्यों का उपयोग किया गया है। प्राथमिक तथ्यों के संकलन हेतु संरचित साक्षात्कार अनुसूची तथा प्रत्यक्ष अवलोकन का उपयोग किया गया है, जबकि द्वितीयक तथ्यों के लिए पुस्तकों, शोध-पत्रों, सरकारी प्रतिवेदनों तथा अन्य प्रासंगिक स्रोतों का उपयोग किया गया है। अध्ययन के माध्यम से पंचायती राज संस्थाओं में महिला प्रतिनिधियों की वास्तविक भूमिका, नेतृत्व क्षमता, निर्णयात्मक सहभागिता तथा ग्रामीण विकास में उनके योगदान का मूल्यांकन किया गया है।
Copyright (c) 2026 गंगीता शर्मा, सुनीता बाणकर https://creativecommons.org/licenses/by-sa/4.0
Adoption and Use of Generative AI Tools among College Students in Kashmir: Implications for Academic Libraries and Information Services
Higher education has seen a significant shift towards using Generative Artificial Intelligence (GenAI), which has revolutionized student learning and behavior by significantly improving their ability to engage with information. The effects of Generative AI tools on academic libraries are investigated in a study conducted among undergraduate college students in Kashmir. Google Forms was employed to implement a questionnaire that provided measurable research findings. In the study, undergraduate students from degree colleges in Kashmir were observed to adopt and use Generative AI tools. The analysis of 172 valid responses was carried out using descriptive statistics, with the data being analysed using frequencies and percentages, and then presented in tables and figures. The results show that many students are familiar with Generative AI tools and ChatGPT is the most popular plateform. Most of the students use Generative AI mainly for learning new concepts, studying to clear exams and doing homework. Additionally, students indicate that Generative AI can be beneficial in terms of improving learning efficiency and reducing time-wasting. Also, most respondents believed that academic libraries should be a key factor in improving literacy on AI by providing instruction and knowledge about the responsible and ethical use of Generative AI technologies. The study suggests that academic libraries should enhance their AI literacy programmes and user education programmes to address the growing presence of Generative AI in student academic activities. The outcomes provide valuable information for librarians, teachers, and policy makers on how to make the use of Generative AI more responsibly in higher education.
Copyright (c) 2026 Shakir Ahmad Dar, Fajar ul Islam Malla https://creativecommons.org/licenses/by-sa/4.0
Corporate Governance and Post-M&A Performance in the Banking Industry: A Study
Corporate governance in the banking sector is essential for the success of mergers and acquisitions (M&A) since it significantly influences post-M&A performance. This research analysed the impact of corporate governance rules on post-merger and acquisition (M&A) performance, along with the key governance domains influencing financial stability and operational success. The research used quantitative methods and regression analysis to investigate governance frameworks and performance metrics after mergers and acquisitions. The results were gathered from 385 respondents of the questionnaire. The study identified a significant positive correlation between governance quality and performance after mergers and acquisitions. The research revealed that leadership, decision-making, risk management, compliance, and transparency were essential. The research demonstrated that exemplary governance enhances financial performance, operational efficiency, and stakeholder confidence. The research emphasized the need of systematic governance during integration. This research aims to enhance theoretical and practical understanding of the impact of corporate governance frameworks on banking mergers and acquisitions. It synthesizes many governance theories, including Agency Theory and Stakeholder Theory, together with their practical implications to enhance the understanding of governance methodologies. The suggestions of the study will enhance governance in mergers and acquisitions for banking executives and practitioners. The study's authors advocate for enhancing governance procedures and examining the long-term impacts of governance on integration success. The study demonstrated that effective corporate governance maintains performance after mergers and acquisitions.
Copyright (c) 2026 Pratibha Jena, Vishal Sood https://creativecommons.org/licenses/by-sa/4.0
Evolution of Algorithmic Trading Research: A Systematic Literature Review and Identification of Future Research Directions
Algorithmic trading has transformed modern financial markets through the integration of advanced computational techniques, quantitative models, and automated execution systems. The rapid growth of electronic trading platforms, increasing market data availability, and significant advancements in artificial intelligence (AI), machine learning (ML), deep learning (DL), and high-frequency trading (HFT) have stimulated extensive academic and industry research over the past two decades. Despite this expanding body of literature, existing studies remain fragmented across diverse research themes, methodologies, financial markets, and asset classes, creating a need for a comprehensive synthesis of current knowledge and identification of future research opportunities. This paper presents a comprehensive literature review of algorithmic trading research published with a special emphasize between 2000 and 2026. The review systematically examines the evolution of algorithmic trading, major algorithmic trading strategies, theoretical foundations, data sources, research methodologies, and performance evaluation metrics employed in prior studies. The review further categorizes existing research into key thematic areas, including trend-following strategies, statistical arbitrage, market making, portfolio optimization, high-frequency trading, sentiment-based trading, and cryptocurrency algorithmic trading. The analysis identifies several significant research gaps that continue to limit the practical implementation and academic advancement of algorithmic trading. Based on these findings, the paper proposes a comprehensive future research agenda emphasizing hybrid AI-driven trading frameworks. By synthesizing existing knowledge and identifying critical research gaps, this review provides a valuable reference for researchers, practitioners, financial institutions, and policymakers seeking to advance the theory and practice of algorithmic trading.
Copyright (c) 2026 Tuhin Mukherjee, Anirban Sarkar https://creativecommons.org/licenses/by-sa/4.0
Experimental Investigation of Adhesion Mechanisms and Curing Behaviour of Coated Polymer Substrates in Hybrid Printing Systems
The adhesion and curing behaviour of coated plastic substrates in hybrid printing processes are crucial for ensuring high-quality, durable prints specially for flexible packaging applications. This paper aims to optimize substrate performance by investigating ink adhesion and curing efficiency under controlled printing conditions in hybrid printing presses with the combination of Flexo and Gravure Printing processes. The research systematically evaluates the influence of coating formulations, curing parameters and substrate surface characteristics on overall print quality. To achieve this, biaxially oriented polyethylene terephthalate (BOPET) films (both coated and uncoated) are subjected to experimental trials assessing ink-substrate interactions. Key measurement methods included surface energy evaluations using ARCOTEST dyne solutions and adhesion strength assessments through Scotch Tape tests. Additionally, UV and electron beam (EB) curing techniques are employed to study polymerization dynamics, ink anchoring behaviour and overall stability of cured prints. By analysing these parameters, the study provides insights into optimizing hybrid printing technologies, advancing substrate engineering and enhancing durability for packaging applications.
Copyright (c) 2026 Shubham, Arohit Goyat, Satish https://creativecommons.org/licenses/by-sa/4.0
Light weight Intelligence-TinyML based Energy Usage Prediction for Resource-Constrained IoT Edges Nodes
The extensive deployment of battery-powered and resource-constrained edge devices makes energy efficiency a major challenge in Internet of Things (IoT) systems. Accurate energy prediction is important to enable intelligent energy management. However, traditional machine learning models are usually computationally expensive and unsuitable for micro-controller based platforms. In this paper, we present a TinyML-based energy prediction framework for low-power IoT edge devices. The proposed approach employs lightweight machine learning models which are optimized for ultra-low memory and computation footprints, but still retain acceptable prediction accuracy. We collect energy consumption data from a real IoT testbed, and train and evaluate several TinyML compatible models. The experimental results show that the proposed TinyML-based predictor can provide reliable energy estimation with low inference latency and low memory overhead, and thus can be deployed on resource-constrained IoT devices. This work lays a fundamental foundation for intelligent and adaptive energy management in future IoT systems.
Copyright (c) 2026 Sandeep Kumar Rawat, Neha Tuli https://creativecommons.org/licenses/by-sa/4.0
Recent Studies on Chemical Degradation of Microplastics: A Review
The microplastic (MP) is a persistent contaminant that is commonly found in water, soil, sediments and air, and is less than 5 mm in size. This review aims to present the summary of recent studies concerning their chemical degradation, which include oxidative, photochemical, hydrolysis, advanced oxidation processes and free-radical. It also discusses the factors that determine the degradation efficiency: polymer composition, pH, crystallinity, catalysts, UV intensity and dose of oxidants. Recent technologies such as Fenton and photo-Fenton oxidation, ozonation, hydrogen peroxide treatment, persulfate activation, photocatalysis and electrochemical oxidation are discussed and compared on the basis of species generated, applicable polymers, advantages, and disadvantages. These methods can speed up the chain scission and partial mineralisation, but some challenges are still left unsolved: incomplete degradation, toxicity of intermediates, recovery of catalysts, energy demand and scale-up. The use of recyclable catalysts, real-environment validation, standardised assessment methods, and integration with biological treatment to realize sustainable microplastic remediation at practical scales with minimal secondary pollution should be emphasised in future research.
Copyright (c) 2026 Madhu Dubey Swarnkar https://creativecommons.org/licenses/by-sa/4.0
Adversarial Machine Learning in Cybersecurity: A Survey of Attacks, Defenses, and Robustness Evaluation
The rise of artificial intelligence (AI) and machine learning (ML) in cybersecurity has made Adversarial Machine Learning (AML) a key field of research. Though ML-based systems are more effective in intrusion detection, malware analysis, spam filtering and authentication, they are also susceptible to adversarial attacks that modify input samples, modify ML models or alter training data. The review explores the key adversarial attack classes: poisoning, evasion, model extraction, model inversion, and membership inference and also white-box, black-box, and grey-box threat models. It also provides an introduction to important defence methods like adversarial training, feature squeezing, defensive distillation, robust optimisation, detection-based methods, and ensemble learning. In addition, robustness evaluation metrics, benchmark datasets and attack assessment techniques to measure model robustness are highlighted. Lastly, the emerging trends are discussed in order to find future research directions in the field of creating trustworthy and resilient AI-based cybersecurity systems, such as Explainable AI, Federated Learning, Large Language Models, Autonomous Cyber defence, and Regulatory structures.
Copyright (c) 2026 Ujjwal Deshmukh https://creativecommons.org/licenses/by-sa/4.0
Human Resource Development Practices and Their Influence on Employee Performance
Human Resource Development (HRD) practices have emerged as a strategic tool for building the ability of employees and boost the performance of the organization. This review aims at highlighting the impact of HRD practices on employee performance by summarizing the recent empirical studies and conceptual literature. It covers the history of the evolution of HRD, its key components – training and development, performance appraisal, career development, succession planning and leadership development, and how these are linked to the effectiveness of employees. The review also identifies areas where HRD has recently improved as well as some key dimensions of employee performance, including AI-driven performance management, technology enhanced learning, personalized development plans, coaching and mentoring, and psychological safety. The reviewed literature clearly shows that the effectiveness of HRD practices strongly leads to enhancing employee competencies, engagement, motivation, and the effectiveness of the organization. The review concludes that the success of strategic HRD efforts in the context of contemporary learning technologies and employee-centred development strategies is vital for maintaining high employee performance and long-term company success.
Copyright (c) 2026 Kratika Baddpalli, Sushil Singh https://creativecommons.org/licenses/by-sa/4.0
Digital Banking Experience and Retail Customer Loyalty in Emerging Indian Cities: An Integrative Review with Implications for Ayodhya
India's digital banking market has moved from adoption-led growth to an experience-led phase in which loyalty depends on reliable, secure, accessible, and transparent service. This integrative review synthesizes verified research and official evidence through July 2026 and reinterprets an earlier Ayodhya survey without presenting its cross-sectional associations as causal or mediational proof. The evidence indicates that reliability and ease create functional value; security, privacy, and transparency build trust; and relevant, controllable personalization strengthens satisfaction. Trust, perceived value, and satisfaction therefore transmit the effects of digital experience to continued use, reduced switching, relationship expansion, and advocacy. Age, digital literacy, usage intensity, bank type, and urban-peri-urban location may modify these relationships. For Ayodhya and comparable emerging cities, banks should prioritize clear transaction status, visible safeguards, rapid human-assisted recovery, multilingual access, and explainable artificial intelligence (AI). A stratified, multi-wave study using validated measures and bootstrapped structural equation modeling is proposed for empirical validation.
Copyright (c) 2026 Amit Yadava, Saurabh Yadav, Anurag Tiwari, Rashi Singh, Rana Rohit Singh https://creativecommons.org/licenses/by-sa/4.0
An Empirical Study on Contract Farming in India
Contract farming in India has been gaining momentum as one of the modes of agricultural productivity in recent years. The activity of contractual farming includes the practice of maintaining agreement among farmers with their buyers. These buyers often comprise corporate companies and businesses that are interested in marketing the agricultural production. Contract farming had been evaluated as a means of combining farming and agricultural production with marketing the farm products through contractual agreement among the contracting corporations and the farmers. Contract farming has been adopted in India’s agricultural sector as a solution for promoting high-value crops, technology and others. The trend of contract farming is often adopted for increasing awareness towards the higher quality crops, given that such activities could satiate the demands from both the corporations and businesses focused on marketing farm products and the farmers. There are several marginal and small category farmers in India with poor resources that often could be mitigated through contract farming by benefiting through contractual agreements and market access and so on. There are several states that take part in contract farming in India, along with the fact that there are legal regulations such as the APMC Act 2003 that secure regulation and government support for contract farming be effective and benefiting practices among the agriculture and corporate sectors. However, there are certain challenges to availing fruitful and effective benefits of contract farming. This includes the potential of mistreatment of the farmers from the corporate companies and contractors. This includes the possibility of the farmers to be facing the threats of losing their contracts with the private business, particularly the small and marginal sized farmers. Moreover there could also be issues in the progressive achievement of interests of both the corporates and the farmers, due to the market and profit-oriented nature of these contracts that are extended by corporations to the farmers. The following study is an empirical overview on contract farming in India, its functioning, impact, regulatory implementations, challenges and potential benefits.
Copyright (c) 2026 Deepa Singh, Praveen Kumar Rai, Anurag Tiwari https://creativecommons.org/licenses/by-sa/4.0
The Impact of Artificial Intelligence on Society: A Comprehensive Review of Opportunities, Challenges, Ethical Issues, and Future Directions
Background: Artificial Intelligence (AI) has rapidly evolved into a transformative technology, significantly influencing healthcare, education, business, governance, and everyday life. While AI enhances efficiency and innovation, it also raises important ethical, social, and economic concerns. Objective: This review critically examines the societal impact of AI by evaluating its opportunities, challenges, ethical issues, and future research directions. Methodology: A qualitative review approach is adopted by synthesizing evidence from peer-reviewed journals, Scopus, Web of Science (WoS), PubMed, policy reports, and other credible secondary sources. The collected literature was analyzed thematically to identify key patterns and emerging trends. Major Findings: The review indicates that AI has significantly improved healthcare services, educational practices, industrial productivity, and decision-making processes. However, challenges such as job displacement, algorithmic bias, privacy concerns, cybersecurity risks, and ethical accountability remain major barriers to its responsible adoption. Research Gap: Existing studies primarily emphasize technological and economic aspects of AI, while comparatively limited attention has been given to its long-term social, psychological, and cultural impacts, particularly in developing countries and marginalized communities. Conclusion: AI offers substantial opportunities for sustainable societal development when supported by ethical governance, transparent policies, and responsible innovation. Future research should focus on human-centered AI, inclusive governance frameworks, and interdisciplinary approaches to ensure that AI benefits society in an equitable and sustainable manner.
Copyright (c) 2026 Sunil Kumar Mehta, Priya Rani Neti https://creativecommons.org/licenses/by-sa/4.0
Evaluating the Effectiveness of Government Schemes in Promoting Women Entrepreneurship in India: Evidence from Startup India, Stand-Up India, and Pradhan Mantri MUDRA Yojana
Women entrepreneurship in India is very significant in promoting inclusive economic growth and sustainable development. The object of the present study was to have understanding about the effect of three Government of India Initiatives namely Startup India, Stand-Up India and Pradhan Mantri MUDRA Yojana (PMMY) on Women entrepreneurship development. A conceptual framework was proposed that was integrated with financial accessibility, institutional support quality and digital and skill readiness as mediator variables and education, rural/urban location, family support and prior business experience as moderator variables. The survey design adopted was quantitative, cross sectional study and 400 women entrepreneurs were surveyed using structured questionnaire. The data were analysed by descriptive statistics and Structural Equation Modeling (SEM). The findings indicated that among the four factors government schemes, digital and skill readiness have been confirmed as the very top, followed by financial accessibility and then the quality of the institution have played significant role in development of women entrepreneurship. The moderating variables also impacted the effectiveness of the government interventions. The study not only has unique contributions to entrepreneurship literature with significant theoretical approaches as brought together and also impact to policy formulation for enhancing financial inclusion, institutional facilitation, digital capacity enhancement but also strength of rural entrepreneurship support. The results have important policy implications for the policymakers, financial institutions and entrepreneurship promotion agencies to foster sustainable women’s entrepreneurship in India.
Copyright (c) 2026 Shweta Mehra https://creativecommons.org/licenses/by-sa/4.0
Current Perspectives on Active Release Technique and Myofascial Release Technique in Housewives with Lateral Epicondylitis
Lateral epicondylitis is a frequently occurring overuse musculoskeletal condition caused by repetitive use of the wrist, lifting and gripping actions at home, which are commonly performed by housewives. Persistent pain, weaker grip strength and loss of upper-limb function considerably limit daily living abilities and quality of life. Conservative physiotherapy is still the primary approach to treatment and manual therapy techniques like Active Release Technique (ART) and Myofascial Release Technique (MFR) are becoming more and more important. The present review was an attempt to present the available evidence on the efficacy of ART and MFR on pain relief and functional performance in housewives having lateral epicondylitis. Pathophysiology of pain and functional impairment, principles and mechanisms of ART and MFR, clinical applications and recent clinical studies are discussed. There is some evidence that both methods are effective in reducing pain, improving grip strength and improving functional outcomes, especially combined with therapeutic exercises. But more high-quality, randomized controlled trials, specifically directed at housewives are required to develop standard treatment protocols.
Copyright (c) 2026 Shriya Payasi https://creativecommons.org/licenses/by-sa/4.0
Physiotherapy Interventions Combining Continuous Passive Motion and Maitland Mobilization for Patellar Fracture Rehabilitation
A common issue following patellar fractures is postoperative pain, joint stiffness, quadriceps weakness, and limited knee range of motion (ROM), all of which may contribute to a suboptimal functional recovery. Early physiotherapy is thus crucial to regain movement and avoid chronic disability. This review aims to provide an overview of current evidence regarding physiotherapy interventions using Maitland Mobilization and passive machine-driven movement (such as Continuous Passive Motion [CPM]) in the treatment of patellar fracture. Review covers rehabilitation challenges, mechanisms and clinical application of CPM, principles of Maitland Mobilization and how this can be integrated with therapeutic exercises. From published clinical studies, CPM appears to encourage early joint motion, reduce joint stiffness and aid to the recovery of ROM, whilst Maitland Mobilization increases accessory joint mobility and helps to relieve pain using graded manual techniques. These interventions are combined with strengthening and stretching exercises and gait training to form a comprehensive rehabilitation approach which improves knee function and functional independence. But more rigorous RCTs are needed to establish standardized REPs and to identify long-term clinical outcomes.
Copyright (c) 2026 Mridula Mahidhar https://creativecommons.org/licenses/by-sa/4.0
Smart Bioremediation: Role Of Artificial Intelligence-Based Monitoring and Control of Aquatic Plant Systems for Wastewater Treatment
Significant technological developments in this field have been made possible by the idea of using wastewater as a replacement for scarce water supplies and to protect the environment, which has produced a wealth of physical data, including chemical, biological, and microbiological information. After looking at this data, wastewater treatment systems become more understandable. Several studies use "machine learning (ML) algorithms" as a proactive approach to tackle issues and forecast how these processing systems will function while using gathered experimental data. This article's objective is to extract the most widely used "machine learning models" from scientific publications in the "Web of Science" database using textual analysis techniques, then examine their applicability and evolution over time. This will provide a comprehensive overview of articles that address the application of artificial intelligence (AI) to address issues in "wastewater treatment technologies", as well as a global scientific follow-up. According to an analysis of research publications, the machine learning models most commonly used in the wastewater treatment domain are "Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), Linear Regression (LR), Adaptive Neuro-Fuzzy Inference System (ANFIS), Decision Tree (DT), and gradient boosting". The findings show that the primary publishers of publications on this study issue are developed countries. Finally, because machine learning requires a large amount of high-quality data, it helps with wastewater treatment. Furthermore, machine learning models' limited interpretability makes it more challenging to comprehend the underlying mechanisms and decisions in wastewater treatment. The AI algorithm for wastewater treatment is also examined in terms of the explainability of data-driven models for transfer learning and reinforcement learning, as well as other significant voids and future prospect. Enhancing energy efficiency, adhering to increasingly strict water quality laws, and optimising resource recovery prospects are just a few of the many issues associated with wastewater treatment. The operational and economic performance of “wastewater treatment plants (WWTPs)” has improved as a result of computational models' growing recognition as effective solutions for solving these difficulties. The paper also covers the use of several "AI algorithms" in "wastewater treatment plants (WWTPs)", such as identifying anomalies, optimising energy utilisation, and forecasting WWTP effluent characteristics and wastewater intakes.
Copyright (c) 2026 Aayushi Sharma, Mohammad Faheem https://creativecommons.org/licenses/by-sa/4.0
YOLOv12 - Powered Smart Retail Automation: A Comparative Performance Analysis of Model Variants for Checkout Systems
Automated checkout is increasingly viewed as a transfor-mative solution for improving operational efficiency, reduc-ing revenue loss, and enhancing customer experience in re-tail. While deep-learning-based object detectors offer strong potential for retail automation, deploying them on resource-constrained edge hardware requires a careful evaluation of ac-curacy, computational cost, and storage footprint. This paper presents a YOLOv12-powered smart retail checkout system and reports a comparative evaluation of its Nano (YOLOv12n) and Small (YOLOv12s) variants. A custom dataset of 7,637 annotated images (6,000 train / 909 validation / 728 test) span-ning five grocery categories was used to train and evaluate both models. Results show that YOLOv12n, at only 5.27 MB, matches YOLOv12s (18.06 MB) on mAP@0.5 (99.5%) and achieves higher precision (99.7% vs. 99.3%), while training 24% faster and requiring roughly 71% less storage; YOLOv12s edges ahead only on mAP@50–95 (0.9123 vs. 0.9057), a 0.66% margin. Based on this trade-off, YOLOv12n was selected as the deployment model. The selected model was integrated into a real-time invoicing pipeline that uses a virtual trigger-line (Temporal Crossing Detection) mechanism over a conveyor-belt video feed to prevent duplicate/missed billing, retrieve product information, and automatically gen-erate itemized PDF invoices. The results demonstrate that a lightweight YOLOv12 model can deliver near state-of-the-art detection accuracy while remaining practical for low-cost, edge-based autonomous checkout deployment.
Copyright (c) 2026 Javed Khan, Anushka Nagpal https://creativecommons.org/licenses/by-sa/4.0
A Study on The Integration of Indian Knowledge Systems Philosophy and Spirituality Through Shaktipeeths as Repositories of Cultural Continuity and Holistic Education in The Present Scenario
Introduction: Shaktipeeths refer to the holy areas of the mythical locations where the body members of Goddess Sati hit the ground and have great importance as places of residence of the Divine Feminine, the Adi Shakti of Shaktism. This gives the Indian subcontinent a voice with spiritual and cultural veins. They are not just places of worship; these 51 or 52 pilgrimage sites fall under the jurisdiction of Indian Knowledge Systems (IKS) of spirituality, philosophy and indigenous epistemologies, which have their origins in the ancient narratives. It is due to the fact that Shaktipeeths (sacred sites) evolve as major reservoirs of stability in the current climate of globalization-driven cultural perpetuity and erosion of contemporary education, protecting the wisdom of the entire world against the disruptions caused by urbanization and presenting a locus of integrated education that promotes moral and emotive as well as cognitive growth. Purpose/Objectives: This theoretical paper's main aim is to develop a holistic education model and cultural continuity by using Shaktipeeths, which are supposed to be integrated hubs, through Shakta philosophy, IKS and spirituality to theorize Shaktipeeths. One of the desired objectives is the making of the philosophical-spiritual meeting points on the story preservation, presentation of the system-driven model, making use of the peeth rites to the existing pedagogies and its appraisal of the implications on the cohesiveness of these societies and the strength of identity among them. Methodology: The methodology is based on Shiva-Shakti duality as it synthesizes the secondary sources, the qualitative approaches based on Shakta scriptures, IKS texts and policy frameworks. They are all plotted on such thematic analyses and diagrammatic visualizations with the inputs (philosophy and sadhana), processes (rituals and arts) and outputs (continuity and learning). Results: According to the results, Shaktipeeths would be referred to as living classrooms that bring about the growth of triadics. The model of holistic education also indicates a good fit in the model with a flexible curriculum using modules, which are inspired by pilgrimages to minimize the alienation. Conclusions/Discussions: In short, the paradigm enhances the conference topic by suggesting developing IKS policy-driven centers on the location and empirical confirmations by placing Shaktipeeths as the solutions to the current problems. This broader project envision a Sarvam Shaktimayam society that balances between the tradition and sustainability of the empowered societies.
Copyright (c) 2026 Abhijaat Sahu https://creativecommons.org/licenses/by-sa/4.0
Comparative Assessment of Various Toner Types and Its Impact on Print-Edge Quality in Electrophotographic Printing Presses
Print-Edge sharpness is one of the most important parameters for evaluating print quality in electrophotographic printing because it directly influences image clarity, text readability and the overall visual appearance of printed products. The present study investigates the influence of toner technology and paper substrate on Print-Edge sharpness through a comparative assessment of three commercially available toner types, namely Emulsion Aggregation (EA) toner, Polymerized toner and Pulverized toner. The study was conducted using four commonly used printing substrates: Silk Coated paper, Textured paper, Uncoated paper and NTR paper. Test prints were printed under controlled electrophotographic printing conditions to ensure consistency in machine settings and environmental parameters. Print-Edge sharpness was evaluated and quantified using standard human observer method by measuring the edge definition of printed characters and graphical elements. The comparative analysis examined the interaction between toner characteristics and substrate surface properties, including coating, roughness and absorbency and their influence on edge reproduction. EA toner and Polymerized toner generally produced sharper and more well-defined print edges than Pulverized toner, particularly on coated paper such as Silk Coated Paper. In contrast, textured and uncoated substrates exhibited relatively lower edge sharpness because of their higher surface roughness and greater toner spread. NTR paper showed intermediate performance depending on the toner formulation employed. The findings indicate that both toner technology and substrate characteristics play a critical role in determining Print-Edge sharpness in electrophotographic printing. The study provides valuable insights for selecting suitable toner–paper combinations to optimize print quality and enhance image fidelity in commercial digital printing applications. The outcomes contribute to the understanding of material interactions in electrophotographic printing and provide a scientific basis for improving print quality through appropriate toner and substrate selection.
Copyright (c) 2026 Bijender, Manish Kaushik, Ankit Boora https://creativecommons.org/licenses/by-sa/4.0
Small Language Models for Phishing Website Detection: A Review of Cost, Performance, and Privacy Trade-Offs
This review investigates Goldenits et al.'s (2025) empirical comparison of fifteen open small language models (SLMs) for phishing website detection, which aimed to evaluate whether locally hosted models can achieve the same accuracy as proprietary large language models (LLMs), without the prohibitive costs or privacy concerns. The authors test each model with a stratified sample of 1,000 labelled websites from a pool of 10,395 websites and measure the accuracy, precision, recall and F1 score of the results. The best local model, llama3.3:70b, achieves an F1 score of 0.893 and recall of 0.948, which is close to, but still lower than, the F1 scores above 0.95 achieved by the largest proprietary systems (Goldenits et al. 2025). This review restates the three research questions posed in this paper, assesses the evidence provided for each of the questions and situates the evidence in the context of the existing literature on cost-aware deployment (Irugalbandara et al. 2024; Kavya & Sumathi, 2024) and LLM-based phishing detection (Koide et al. 2024). It concludes that, besides the number of parameters, the deployability of an SLM depends on its architecture and on the reliability of its output format, which does not depend only on its classification skill.
Copyright (c) 2026 Krithika Mani https://creativecommons.org/licenses/by-sa/4.0
Digital Payment Systems: Their Role in Economic Growth and Associated Criminal Activities
Digital payment systems have revolutionized the financial sector, offering secure, efficient, and real-time electronic transactions worldwide. The financial inclusion has been enhanced, business efficiency, e-commerce, and economic growth have been supported with the fast growth of technology like Unified Payments Interface (UPI), mobile wallets, Internet banking, credit and debit cards and QR code based payments. At the same time, the growing reliance on digital financial services has opened up new avenues for financial crimes via cyber means such as phishing, identity theft, QR-code fraud, OTP fraud, money laundering, malware attacks and account takeover. This review aims to analyse the impact of digital payment on economic development and provide an insight into the new security issues surrounding the use of these digital payments. It also examines the contribution that the regulatory framework, security measures, fraud protection systems, consumer understanding and awareness, and institutional cooperation can play in enhancing the security of payments. In conclusion, the review suggests that sustainable digital payment systems need to combine technological innovation, effective regulation, and cybersecurity awareness.
Copyright (c) 2026 Suhaib Ahmed Quraishy, Abdulla https://creativecommons.org/licenses/by-sa/4.0
प्रस्तुत शोध पत्र मुख्य रूप से योगवसिष्ठ में वर्णित मन का दार्शिनक एवं विश्लेष्णात्मक अध्ययन किया गया है। जिसमे मुख्य रूप से मन का अर्थ, स्थान, कार्य, जीवन्मुक्ति एवं मन का सम्बंध एवं निग्रह के उपाय आदि का वर्णन किया गया है। जिसमे विवेक, वैराग्य, वासनाक्षय, मुक्ति के चार द्वारपाल एवं आत्म विचार को मन की शुधि का प्रमुख साधन माना गया है। इस अध्ययन से यह स्पष्ट होता है कि मन ही दुःख-सुख, बंधन-मोक्ष आदि का मुख्य कारण है। आज के समय में लोग मानसिक अशांति एवं अनियमित सोच से दुखी लोग के लिय योगवसिष्ठ में वर्णित मन की शिक्षा मनुष्य के लिय बहुत लाभ करी सिद्ध होती है।
Copyright (c) 2026 उज्जवल कुमार, अखिलेश कुमार विश्वकर्मा https://creativecommons.org/licenses/by-sa/4.0
Assessment Of The Socio-Economic Empowerment Of Local Communities Through Food Processing Industries: A Case Study Of Khurda District, Odisha
This study investigates the socio-economic empowerment of local communities through Food Processing Industries (FPI) in Khurda District, Odisha. Adopting a quantitative research approach, the study aims to assess the impact of FPI on key socio-economic indicators, including employment opportunities, income generation, access to nutritious food, and community cohesion. 400 respondents were selected using stratified sampling techniques, with data collected through structured questionnaires administered between December 15, 2023, and January 10, 2024. Structural Equation Modeling (SEM) was adopted to analyze the relationships between FPI and socio-economic outcomes. The results reveal significant positive associations between FPI and employment opportunities, income generation, access to nutritious food, and community cohesion. These findings underscore the potential of FPI to drive socio-economic development and enhance the well-being of local communities in Khurda District. The practical implications of the study suggest the importance of fostering an enabling environment for FPI growth, including policy support, infrastructure development, and skill enhancement programs. Furthermore, the study identifies avenues for future research, includinglong-term impact of FPI interventions and comparative analyses across different regions to inform targeted policy interventions for sustainable socio-economic empowerment. Overall, this study contributes to the literature on FPI and community development, offering insights for policymakers, practitioners, and researchers seeking to promote inclusive and sustainable development in Khurda District, Odisha, and beyond.
Copyright (c) 2026 Avilipsa Panda, Aparajita Biswal https://creativecommons.org/licenses/by-sa/4.0
Analytical Study of Insolvency and Bankruptcy Code 2023 with reference to Stakeholders Rights Perspectives
This study is an attempt to explore the working of the Insolvency and Bankruptcy Code (IBC) 2023 and to focus on the stakeholders and to what extend their rights are upheld under IBC. It explores: Why the bankruptcy regime has been shaped the way it is; the conflict between interest of justice of stakeholders and interest of creditors – who are the system's preferred player when according to Indian statute. The nature of the study is descriptive and analytical because evaluations are carried out about the impact of the Code on creditors, debtors, workers, the shareholders and regulators from different dimension such as legislative provision, the case law/empirical evidence. Results come back suggesting that the IBC 2023 provides for a higher recovery rate with an enhanced creditor oversight, but is likely to result in marginalization non-creditor parties. Weights and counterweights in the judgments of the Judges and protection gaps of vulnerable groups still exist. According to the report, a variety of initiatives are needed, including greater scrutiny of the regulators, more transparency for shareholders and more protection for employees. Emphasis on the policy implication to develop an equitable development and achieve financial stability is created and the comparison is made with Indian and Global bankruptcy regime.
Copyright (c) 2026 Mahesh Prakash Kolamkar, Sourabh Vasant Ubale https://creativecommons.org/licenses/by-sa/4.0
The Significance of Full Blood Count (FBC) Indicators in Identifying Anemia: An Examination of 100 Cases from Past Records
Anemia impacts roughly 1.62 billion individuals worldwide, marked by decreased red blood cell numbers, hemoglobin levels, or hematocrit values. This backward-looking study assessed the effectiveness of Full Blood Count (FBC) indicators in diagnosing anemia among 100 affected individuals (55 men, 45 women; ages 18–65) at Metro Hospital in Jabalpur. Indicators examined included hemoglobin, hematocrit, red blood cell (RBC) tally, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and red blood cell distribution width (RDW). Anemia was categorized as microcytic (n=40), normocytic (n=30), or macrocytic (n=30). Marked variations were observed in MCV, MCH, MCHC, and RDW among categories (p<0.001). Associations indicated hemoglobin's negative link with MCV (r=-0.35) and RDW (r=-0.25), and positive with MCHC (r=0.51). FBC indicators proved effective for diagnosing and categorizing anemia, with RDW helping to distinguish iron-related deficiencies. Drawbacks include limited participant numbers and the retrospective approach. This research endorses FBC as an initial diagnostic method, guiding informed anemia treatment strategies. The broadened evaluation explores variations by age and gender subgroups, treatment applications, and comparisons with alternative diagnostic approaches, offering a solid base for hematology investigations.
Copyright (c) 2025 Ravita Thakur https://creativecommons.org/licenses/by-sa/4.0
Correlation Between Fasting Blood Glucose and Glycosylated Hemoglobin (HbA1c) in Type 2 Diabetic Patients: A Cross-Sectional Study
Diabetes Mellitus (DM) is a chronic metabolic disorder characterized by hyperglycemia, with Type 2 DM (T2DM) being the most prevalent form. Effective glycemic monitoring is crucial to prevent complications. Glycosylated hemoglobin (HbA1c) reflects long-term glucose control (2-3 months), while fasting blood glucose (FBG) provides short-term insights. Objective: To evaluate the correlation between FBG and HbA1c in T2DM patients. Methods: This cross-sectional study included 50 T2DM patients (aged 35-50 years) at Metro Hospital, Jabalpur. FBG was measured using the Glucose Oxidase-Peroxidase method, and HbA1c via nephelometry. Descriptive statistics and Pearson correlation were performed. Results: Mean FBG was 140.2 ± 30.1 mg/dL, and mean HbA1c was 7.2 ± 1.5%. A strong positive correlation existed between FBG and HbA1c (r = 0.85, p < 0.001). Conclusion: HbA1c strongly correlates with FBG and is a reliable biomarker for long-term glycemic control. Combined monitoring of both parameters is essential for diabetes management.
Constructed Wetlands with Aquatic Plants For Municipal Wastewater Treatment: Design and Efficiency Analysis
The severe pollution of water produced by untreated textile waste makes effective wastewater treatment a particularly urgent environmental challenge in industrial regions like Mumbai and Delhi. This is a method that is a method that is a common industrial text that is a common. To test the efficiency of pollutant removal throughout a ten-day retention period, carefully controlled laboratory-scale studies were carried out. Eichhornia crassipes demonstrated the most efficient removal of "total dissolved solids (TDS)", "electrical conductivity (EC)", salinity (40.20 %), pH (5.12), total hardness (38.2 %), and chlorides (50.5 percent). For instance, Pistia stratiotes and Lemna minor demonstrated exceptional success in the elimination of nitrate (98.76%), ammonium (52%), and the "sodium absorption ratio (48.19%)". This is indicative of the potential for species-specific bioremediation. The findings highlight the variety of affordable, ecologically advantageous, and sustainable nature-based wastewater treatment approaches available in industrial clusters, offering a practical substitute for conventional treatment techniques. A recent study from 2019 to 2021 found that wastewater treatment utilizing a phytoremediation technique, which involves creating artificial wetlands with aquatic vegetation, is a popular and effective method for pollution removal.
Parental Involvement And Neuroeducation: A Pilot Study On Brain Plasticity In Foundational Stage Learners
This research paper discusses the link between parental engagement and neuroeducation from the perspective of brain plasticity in early childhood. The study is a pilot investigation of 30 learners in the foundational stage (ages 3 to 6) based on neuroscientific evidence that early childhood is a period of heightened synaptic proliferation and environmental sensitivity. This study uses a parental involvement questionnaire, adapted from validated instruments, to investigate the relationship between parent-child interactive behaviours and developmental outcomes. These results suggest that active, reciprocal parent-child interactions, especially those that include language-rich conversations, responsive caregiving, and play-based learning, are associated with improved neurodevelopmental outcomes. This paper contributes to the growing literature of neuropedagogical research by providing empirical evidence that parental involvement is a crucial environmental mechanism for the development of brain architecture. This article adds to the expanding pool of neuropedagogical research with empirical evidence that parental involvement is a major environmental mechanism for influencing brain architecture during the foundational stage, with implications for educational policy, teacher preparation, and family engagement strategies.
Copyright (c) 2026 Amit Kauts, Mankiran Virdhi https://creativecommons.org/licenses/by-sa/4.0