Abstract:
Agricultural marketing reforms in India have been pivotal in reshaping the economic landscape of farming communities. This study evaluates the impact of key reforms APMC amendments, e-NAM integration, MSP-based procurement, and the Paddy Procurement Automation System (P-PAS) on farmers in Khurda district of Odisha. A mixed-method approach employing primary data from 120 farmers surveyed across three blocks of Khurda and secondary data from OSAMB, OSCSC, and GoI databases was adopted for the period 2018–2024. The hypothesis tested was that post-reform mechanisms have significantly improved farmers' price realisation and market access. Results indicate that Odisha's paddy procurement grew from 49 lakh MT in 2017–18 to 74.92 lakh MT in 2024–25, while MSP rose from ₹1,750 to ₹2,300 per quintal. However, in Khurda district, only 42.5% of farmers were aware of e-NAM, and intermediary dominance remained a significant constraint. The study concludes that reforms have produced partial but uneven outcomes, with structural gaps in e-governance adoption, infrastructure, and awareness requiring targeted policy intervention.
Area: Department of Business Management
Author: Sabyasachi Ray1, Dr. Puja Kumari2
DOI: MJAP/05/0599
Abstract:
Climate change has significantly reshaped the dynamics of groundwater in the Upper Ganga Plain, and the Meerut district of Uttar Pradesh is an interesting place to study urban-rural differentials, as it is a place of intensive sugarcane agriculture alongside the rapid urbanisation. This paper examines the relationship between changes in rainfall, temperature and anthropogenic pressure, and their comparison and contrast in terms of groundwater depletion and contamination in the urban and rural blocks of Meerut. A compilation and analysis of secondary data were based on descriptive and comparative statistical methods, which covered 2003-2025 period and included Central Ground Water Board (CGWB), India Meteorological Department (IMD), GRACE satellite and peer-reviewed literature in the context of the study. The hypothesis is that urban blocks in Meerut have a considerable difference in ground water depletion and contamination in comparison with rural blocks of the same climatic stress. The findings indicate that urban Meerut experiences a depletion of 0.12-0.33 m/year with high levels of nitrate and fluoride surplus and rural blocks with relatively low declines with moderation by the canal recharge. Increasing temperature (+0.6 C decadal) and unpredictable intensity of monsoon have added pressure. The paper concludes that artificial recharge, crop diversification, and demand-side pricing should be integrated and block specific to achieve climate-resilient water security in Meerut.
Area: Environmental Science
Author: Ayush Tyagi1, Dr. Priyanshu Srivastava2, Dr. Amit Kumar Sharma3
DOI: MJAP/05/0567
Abstract:
VijaydanDetha (1926-2013) is a unique author in contemporary Indian literature, having served over fifty years of his life to retell the oral traditions of rural Rajasthan, in his own language, Rajasthani, into literary short fiction. His fourteen-volume Bataan riPhulwari (Garden of Tales, 19601975) collected and repackaged over eight hundred tales based on village storytelling, bardic and feminine narratives of his native Borunda. In this paper, I will discuss Detha as a place where oral tradition is not only transcripted, but intertextually rewritten, creating a unique narrative form of modernity that does not require the rejection of folklore or the sentimentalizing of folklore. Based on the theorization of intertextuality provided by Julia Kristeva, the re-conceptualization of the text and the author used by Roland Barthes, and the process of cognitive and stylistic alteration which comes with the transition to literacy as developed by Walter J. Ong, this paper contends that the stories of Detha provide a dialogic negotiation between the primary orality and print-based literary modernity. By critically reading Detha'sDuvidha (The Dilemma) and Chouboli, DohariZindagi (Two Lives), and Rijak ki Maryada (The Dignity of Labour), the paper demonstrates that the use of nonsense rhymes, framing, references to the hunkara of the listener and the use of inconclusive conclusions, are intertextual traces that enable Detha to challenge The results imply that the work of Detha provides a useful corrective to the Euro-modern theories of authorship and reductive ideas of Indian folklore, suggesting instead a stratified narrative modernity based in the communal and the communal communing with itself.
Area: Department of English
Author: Dr. Naveen Kumar Vishwakarma
DOI: MJAP/05/0566
Abstract:
The annual agricultural loss of agricultural products in developing countries is between 30-40% which is mainly caused by lack of cold storage facilities. The current review paper is a meta-analysis of solar-powered evaporative cooling systems that are applied to the preservation of agricultural products. The article focuses on the development of low-cost cold storage technologies, in particular the solar evaporative cooling systems (SECS) which integrate renewable energy and passive cooling. This study critically analyzes 30 peer-reviewed publications published 2010-2024 to determine different design configurations, cooling performance parameters, cost-effectiveness, and practical implementations. The review of literature points to such key performance indices as coefficient of performance (COP) of 0.65-4.5, 10-25C lower temperature than ambient and preserving relative humidity levels of 85-95%. The critical analysis shows that systems involving photovoltaic panels, which have direct/indirect evaporative cooling, show better performance than isolated systems. This paper will discuss the storage of thermal energy, the psychometric phenomenon, and the criteria of material choice to achieve the optimal performance. Results have shown that these systems have the capacity of extending the shelf life of fruits and vegetables by 200-400 percent with less energy consumption of 60-80 percent than the conventional refrigeration. The paper has addressed implementation issues such as water quality standards, climate-based flexibility and maintenance standards. The future research directions include the integration of the Internet-of-Things, the development of new desiccant materials and multi-stage cooling system designs to achieve higher efficiency in the agricultural setting of the tropical and subtropical areas.
Area: Department of Mechanical Engineering
Author: Pankaj Suresh Singh Bais1, Mr. Ritesh Khaterkar2, Dr. S. S. Pawar3
DOI: MJAP/05/0565
Abstract:
The burden of mental health disorders, especially anxiety and depression, on the population in India is immense and increasing with 197.3 million people identified to be living with mental disorders in 2017. Although there has been progress in pharmacotherapy, there is still a gap of 70-92 percent in treatment, and thus, complementary, culturally aligned interventions are critically needed. The paper will analyze the Sattvik diet a classic Ayurvedic food system of pure, non-processed foods such as whole grains, fruits, nuts, legumes, and medicinal herbs as an adjunctive method of treating anxiety and depression. The systematic review method was applied, which was based on peer-reviewed articles published between 2015 and 2025 and found in PubMed, Google Scholar, and MEDLINE. The hypothesis was that frequent Sattvik dietary compliance is a significant factor in lowering the level of anxiety and severity of depression mediated by the gut brain axis, biosynthesis of tryptophan-serotonin and anti-inflammatory pathways. Cross-sectional, interventional, and meta-analytic studies provide evidence that Sattvik dietary components change the gut microbiome composition, increase serotonin synthesis, and reduce cortisol levels, which provide observable effects in GAD-7 and PHQ-9 scores. The Sattvik diet is a safe, affordable and culturally-based complementary approach to mental health management in India.
Area: Department of Yogic Science
Author: Aparna Vishwash1, Dr. Sarika Shukla2
DOI: MJAP/05/0564
Abstract:
Artificial Intelligence has emerged as a transformative force in contemporary data-driven economies, fundamentally altering the scale, speed, and sophistication with which personal data is collected, processed, and monetised. This paper undertakes a doctrinal and comparative legal analysis of the adequacy of existing personal data protection frameworks principally India's Digital Personal Data Protection Act, 2023 and the European Union's General Data Protection Regulation, 2016 in governing AI-driven data processing. Through critical examination of the structural features of AI systems, including algorithmic opacity, automated decision-making, mass profiling, and cross-border data flows, the paper identifies systemic inadequacies in consent-based legal architectures that were substantially conceived in a pre-AI regulatory paradigm. Drawing upon landmark judicial pronouncements including Justice K.S. Puttaswamy v. Union of India, Google Spain v. AEPD, and Schrems II, as well as peer-reviewed scholarship and institutional reports, the paper demonstrates that current frameworks particularly India's DPDP Act lack enforceable protections against algorithmic discrimination, autonomous decision-making, and surveillance capitalism. The paper further undertakes a comparative evaluation of the India–EU regulatory divide, exposing gaps in India's legislative architecture including the absence of provisions equivalent to Article 22 of the GDPR. Based on this critical analysis, the paper advances concrete, non-generic reform proposals encompassing AI-specific regulatory legislation, algorithmic transparency mandates, an independent AI regulatory authority, and mandatory ethical compliance audits. The paper concludes that effective data protection in the AI era demands a fundamental reorientation from consent-centric models towards accountability-based governance frameworks that place individual fundamental rights at the normative centre of regulatory design.
Area: Faculty of Legal Studies
Author: Ruby Agarwal1, Prof. Kalpana Devi2
DOI: MJAP/05/0563
Abstract:
This paper examines AI-powered educational systems and their influence on personalized learning and student involvement. The rapid integration of artificial intelligence in educational environments has created transformative possibilities for tailoring instruction to individual learner profiles. The primary objective is to analyze how AI-driven tools including intelligent tutoring systems and adaptive learning platforms affect student engagement and personalized learning outcomes across higher and secondary education. Employing a descriptive-analytical research design, this study synthesizes secondary data from peer-reviewed literature published between 2016 and 2024. The hypothesis posits that AI-powered systems significantly enhance student engagement and personalized learning outcomes compared to conventional pedagogical approaches. Results indicate that students in AI-enhanced environments demonstrate up to 54% higher test scores, 30% improved learning outcomes, and 75% higher motivation levels than peers in traditional classrooms. Discussion confirms that adaptive feedback loops, real-time analytics, and individualized content delivery are the primary mechanisms through which AI drives learner engagement. The paper concludes that AI, when ethically and strategically implemented, holds strong potential to democratize quality education globally, including within India's vast and diverse educational ecosystem.
Area: Department of Education
Author: Manoj Kumar1, Dr. Renu Singh2
DOI: MJAP/05/0562
Abstract:
The undertrial prisoner crisis in India represents one of the most glaring structural failures of its criminal justice system a system that purports to uphold the rule of law while systematically violating the constitutional rights of its most vulnerable constituents. Undertrial prisoners, defined as persons detained in judicial custody pending investigation, inquiry, or trial, constitute approximately 75.8% of India's total prison population, according to the National Crime Records Bureau's Prison Statistics India 2022. This paper undertakes a critical doctrinal and socio-legal analysis of the undertrial prisoner's status within the Indian criminal justice framework, interrogating the normative gap between constitutional guarantees and ground realities. Drawing upon landmark judicial pronouncements, empirical prison data, legislative developments including the Bharatiya Nagarik Suraksha Sanhita (BNSS) 2023, and comparative international standards, the paper argues that prolonged undertrial detention is not merely an administrative failure but a structural injustice entrenched in poverty, caste discrimination, and systemic legal apathy. The paper further offers targeted reform recommendations aimed at transforming India's bail jurisprudence and custodial governance toward a rights-respecting paradigm.
Area: Department of Law
Author: Pankaj Kumar1, Dr. Nagendra Kumar Sharma2
DOI: MJAP/05/0561
Abstract:
The agricultural sector of India, which provides about 46.1 percent of the national working population and almost 16 percent of the GDP, is still characterized by small and marginal farmers which occupy 86.1 percent of the total operated holdings. These farmers experience chronic threats of disjointed farmlands, low access to the market, increasing costs of inputs, as well as information asymmetry, which reduced their income and bargaining power. This paper will be seeking to explore how agri-startups and Farmer Producer Organizations (FPOs) can synergize to promote better market access and value realization by the smallholder farmers in India. The study aims at determining the growth pattern and performance of FPOs and agri-startups and also determining the effect of these on the market integration and income improvement of farmers. Descriptive-analytical research design was followed and secondary data were used, such as NABARD, SFAC, Ministry of Agriculture, and published research. The hypothesis states that joint working of FPOs and agri-startups would greatly enhance the market participation and price realization of farmers. Findings show that the membership of FPOs has a positive effect on the net returns, and electronic platforms such as e-NAM have incorporated more than 1.78 crore farmers into the transparent market system. The paper finds that, institutional empowerment of FPOs through technology-based interventions of agri-startups can form a sound ecosystem in empowering smallholders and in marketing sustainable agricultural produce.
Area: Department of Management
Author: Manoj Kumar Agarwal1, Dr. Reema Singh2
DOI: MJAP/05/0560
Abstract:
The rapid integration of renewable energy sources and the increasing complexity of modern power systems necessitate advanced intelligent energy management solutions. This research investigates machine learning-driven approaches for intelligent energy management and demand prediction in smart grids, with specific focus on the Indian energy sector context. The study employs a comprehensive analysis of deep learning models including Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), Support Vector Regression (SVR), and hybrid architectures for accurate load forecasting and demand prediction. The hypothesis posits that hybrid machine learning models demonstrate superior performance compared to traditional forecasting methods in smart grid applications. Results indicate that hybrid CNN-LSTM models achieve prediction accuracy of 93.38% with RMSE values ranging from 0.56 to 3.99% MAPE across different datasets. The study analyzes data from Indian smart grid implementations showing electricity demand growth of 6.3% annually, with renewable capacity projected to reach 500 GW by 2030. Findings demonstrate that ML-driven energy management systems reduce energy wastage by 12.96% while improving grid stability to 96.25%, thereby validating the hypothesis that advanced machine learning techniques significantly enhance smart grid operational efficiency and sustainability.
Area: Department of Electrical Engineering
Author: Ritik Raj1, Rishikant Garg2
DOI: MJAP/05/0558
Abstract:
Power transmission systems face critical voltage stability challenges due to increasing load demands and integration of renewable energy sources. This research investigates the application of Flexible AC Transmission Systems (FACTS) devices for enhancing voltage stability in transmission networks. The study examines Static VAR Compensator (SVC), Static Synchronous Compensator (STATCOM), Thyristor Controlled Series Capacitor (TCSC), and Unified Power Flow Controller (UPFC) on IEEE 14-bus test system. Continuation Power Flow (CPF) methodology with Newton-Raphson technique was employed to analyze voltage stability margins. Results demonstrate that UPFC provides maximum loading margin improvement of 48.3%, followed by STATCOM (42.7%), SVC (38.5%), and TCSC (35.2%). Voltage profile improvements ranged from 12.4% to 18.6% across critical buses. Statistical analysis reveals significant correlation (r=0.94) between reactive power compensation and voltage stability enhancement. Power loss reduction of 32.8% was achieved with optimal FACTS placement. The research confirms that strategic deployment of FACTS devices substantially improves transmission system voltage stability, reduces losses, and enhances overall power system security.
Area: Department of Electrical Engineering
Author: Mohammad Irfan1, Nikita Khobragade2
DOI: MJAP/05/0557
Abstract:
India's digital banking sector has undergone a rapid and unprecedented transformation, driven by technological innovation, policy reforms, and evolving customer expectations. As of 2024, India hosts approximately 295.5 million digital banking users, placing it ahead of the United States. The Reserve Bank of India's Digital Payments Index (RBI-DPI) reached 493.22 in March 2025, underscoring the deepening penetration of digital payments nationwide. This paper examines how customer-centric leadership strategies shape customer experience within India's digital banking ecosystem. The study objectives are to identify the key leadership strategies enabling digital transformation and to assess their measurable impact on customer experience outcomes. A secondary data-driven, descriptive research design was adopted, utilizing data sourced from RBI reports, Deloitte's Digital Banking Maturity (DBM) study, and peer-reviewed literature published between 2018 and 2025. The hypothesis posits that customer-centric leadership strategies significantly and positively influence customer satisfaction in digital banking. Findings reveal that banks deploying data-driven, agile, and empathy-oriented leadership demonstrate superior customer satisfaction scores. The paper concludes with strategic recommendations for banking leaders aiming to sustain competitive advantage through customer centricity.
Area: Department of Business and Leadership Management
Author: Pragashani Reddy
DOI: MJAP/05/0555
Abstract:
Dynamics and control form the backbone of modern engineering systems, enabling the design, analysis, and operation of complex, interconnected, and autonomous systems. This review presents a comprehensive analysis of the evolution of control methodologies and dynamic modeling techniques from 2000 to 2025. Early studies focused on classical control approaches, including PID, state-space, and robust control, while mid-2010s research emphasized predictive and networked control systems for distributed applications. In recent years, data-driven, intelligent, and hybrid control strategies have emerged, integrating machine learning and adaptive methods with classical frameworks to address nonlinearities, uncertainties, and high-dimensional dynamics. The paper highlights applications across robotics, autonomous vehicles, industrial automation, and smart transportation systems. Key research gaps are identified, including the integration of model-based and data-driven methods, scalability of networked systems, real-time implementation, robustness under uncertainty, and the lack of standardized benchmarking. This review provides insights into trends, challenges, and future directions, guiding researchers toward the development of intelligent, scalable, and resilient control systems for complex engineering applications.
Area: Department of Mechanical Engineering
Author: Rahul Soma Deshmukh1, Siddhant N. Patil2, Shraddha Lohakare3, Mohan T. Patel4, Pragati Patil5
DOI: MJAP/05/0554
Abstract:
The study investigates the mechanical behavior, structural performance, and durability of conventional and modern construction materials, including steel, concrete, timber, fiber-reinforced polymers (FRP), and self-healing concrete. Experimental testing and comparative analysis were conducted to assess tensile strength, compressive strength, ductility, toughness, and environmental durability under standard and extreme loading conditions. Results indicate that steel exhibits superior tensile capacity and ductility, while concrete demonstrates high compressive strength but limited tensile resistance. FRP-reinforced concrete and self-healing concrete offer enhanced durability, energy absorption, and corrosion resistance, making them suitable for resilient and long-lasting structures. Hybrid systems combining traditional and advanced materials demonstrated improved load-bearing capacity and reduced crack propagation. The findings highlight the potential of integrating modern composites and smart materials with conventional systems to achieve safer, more sustainable, and high-performance infrastructure. The study also identifies key research gaps, including long-term performance, multi-hazard resilience, large-scale implementation, and standardization of innovative materials, suggesting directions for future research in structural engineering.
Area: Department of Mechanical Engineering
Author: Rahul Soma Deshmukh1, Siddhant N. Patil2, Shraddha Lohakare3, Mohan T. Patel4, Pragati Patil5
DOI: MJAP/05/0553
Abstract:
Over the past twenty-five years, significant advancements have been achieved in the fields of structural vibrations, acoustic radiation, and fluid–structure interaction (FSI). This review presents a comprehensive assessment of research developments from 2000 to 2025, focusing on methodological evolution, computational innovations, and emerging intelligent control strategies. Early contributions emphasized classical modal analysis, finite element modeling, and partitioned FSI frameworks. Between 2010 and 2020, research expanded toward strongly coupled multi-physics simulations, smart material–based vibration control, and uncertainty quantification in vibro-acoustic systems. Recent developments (2020–2025) demonstrate a paradigm shift toward artificial intelligence (AI)-driven surrogate modeling, physics-informed neural networks, high-performance computing (HPC), and digital twin applications. The review identifies key achievements, including improved numerical stability in monolithic FSI solvers, hybrid finite element–boundary element acoustic methods, and adaptive vibration suppression using smart materials. However, several challenges persist, such as computational cost in high-frequency acoustic simulations, limited interpretability of AI-based models, insufficient experimental validation, and the absence of fully integrated multi-physics digital twin frameworks. The study concludes that future research should focus on hybrid physics–AI methodologies, scalable energy-efficient computational strategies, and robust uncertainty-aware modeling to address the increasing complexity of modern engineering systems.
Area: Department of Mechanical Engineering
Author: Rahul Soma Deshmukh1, Siddhant N. Patil2, Shraddha Lohakare3, Mohan T. Patel4, Pragati Patil5
DOI: MJAP/05/0552
Abstract:
Artificial intelligence integration into power grid fault management is a groundbreaking strategy of improving the reliability of electrical infrastructure and its efficiency of operations. This work explores the use of AI-based techniques in fault detection and localization in sophisticated power grid models, especially the focus on machine learning algorithms, deep neural networks, and smart monitoring systems. The main goals are to compare the effectiveness of different AI methods, determine the accuracy of fault detection in various grid configurations, and determine the difficulties involved in implementing AI in developing countries such as India. The research approach is a system review and a quantitative analysis of secondary sources gathered in form of grid operators, research departments, and international energy organizations. The hypothesis is that AI-powered systems represent much better fault detection and localization resistance than traditional schemes of protection. The findings have revealed that convolutional neural networks have a fault classification accuracy of over 98% whereas the support vector machines have a high fault localization in a transmission line with less than 1.2 errors. A discussion shows that there were significant gains in response time, decrease in outage time, and increased grid stability using AI. The conclusion has made it clear that AI-based solutions provide scalable answers to modernizing the power grid protection infrastructure in a wide range of contexts.
Area: Department of Electrical Engineering
Author: Sweta Sharma1, Mr. Shrikant Namdeo2, Mr. Rishikant Garg3
DOI: MJAP/05/0551