International Journal of Advanced Research and Multidisciplinary Trends (IJARMT)
The International Journal of Advanced Research and Multidisciplinary Trends (IJARMT) is a peer-reviewed-refereed, open-access journal dedicated to publishing high-quality research across a broad spectrum of academic disciplines. Established in 2024, the journal aims to provide a platform for scholars, researchers, and professionals from various fields to share their innovative findings and contribute to global knowledge. Journal particulars: Title: International Journal of Advanced Research and Multidisciplinary Trends (IJARMT) ISSN: 3048-9458 Impact Factor: 7.2 Frequency: Quarterly (4 issues per year) Publisher: Publication and Advance Research Welfare Society Publication Place: Hisar, Haryana Publisher Email: ijarmtjournal@gmail.com Editor-in-Chief: Dr. Anjali Khokhar Copyright: Remain Journal Starting Year: 2024 Main Subject: Multidisciplinary Language: English & Hindi Publication Format: Online (Open Access) Website: https://ijarmt.com UGC Approved Journal : as per New UGC Rules
Publication and Advance Research Welfare Society
पर्यावरण प्रदूषण के क्षेत्र में गुरु जंभेश्वर का योगदानः एक अध्ययन
गुरु जम्भेश्वर जी, जिन्हें जम्भोजी के नाम से भी जाना जाता है, का जन्म 1451 ईस्वी में नागौर जिले के पीपासर में पंवार गोत्र के एक दूरदराज के राजस्थानी राजपूत परिवार में हुआ था । उनके पिता का नाम लोहाट जी पंवार और माता का नाम हंसा बाई था। जम्भोजी ने 27 साल जंगल में अकेले बैठकर, ध्यान करते हुए बिताए । उन्होंने 1485 में राजस्थान के बीकानेर जिले के नोखा के पास धोरा गांव में बिश्नोई संप्रदाय की स्थापना की। उनकी शिक्षाएं काव्य रूप में थीं, जिन्हें शब्दवाणी के नाम से जाना जाता है। उनकी शिक्षाएं 29 सिद्धांतों और 120 शब्दों में शामिल हैं । उनतीस सिद्धांतों में से आठ पर्यावरण, जैव विविधता, पारिस्थितिकी की सुरक्षा के लिए सख्त दिशानिर्देश हैं और साथ ही वे अच्छी पशुपालन और जीवित चीजों के प्रति दया की भावना को प्रेरित करते हैं। ये सिद्धांत जानवरों को मारने, हरे पेड़ काटने, बैलों की नसबंदी पर सख्ती से रोक लगाते हैं, और सभी जीवों के संरक्षण को प्रेरित करते हैं। जम्भोजी ने अपने दिमाग का इस्तेमाल किया और पर्यावरण संरक्षण के आंदोलन को धार्मिक दर्शन में बदल दिया। वर्तमान समय में जब दुनिया पर्यावरणीय संकट का सामना कर रही है, तो जम्भोजी की शिक्षाएं बहुत महत्वपूर्ण साबित होती हैं।
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भू राजस्व के विशेष संदर्भ में भू राजस्व व्यवस्था का उदय और विकासः एक अध्ययन
प्राचीन भारत में एक सुव्यवस्थित भू राजस्व प्रथा विद्यमान थी जो राज्य की आय का प्रमुख स्त्रोत थी। इस अध्ययन का उदेश्य भारत में भू राजस्व के उदय और विकास की जांच करना है। वैदिक काल में, जमीन को ज्यादातर समुदाय की सम्पति समझी जाती थी, जबकि राजा उसके रक्षक के तौर पर काम करता था। इस सुरक्षा और प्रशासनिक कार्यों के बदले में, राजा खेती की उपज का एक हिस्सा इकट्ठा करता था, जिसे आमतौर पर भाग कहा जाता है। अर्थशास्त्र में कहा गया है कि भू राजस्व उपज का लगभग छठा हिस्सा कर के तौर पर लिया जाना चाहिए । इसी तरह, मनुस्मृति भी राजा को खेती की उपज का एक हिस्सा राजस्व के तौर पर लेने का अधिकार देती है। भू राजस्व व्यवस्था का विकास राजनितिक अधिकार , प्रशासनिक संगठन और खेती की पैदावार से करीब से जुड़ा था। इसने न सिर्फ राज्य की आर्थिक नींव का काम किया, बल्कि पुराने भारत के खेती के ढांचे और ग्रामीण समाज को बनाने में भी अहम भूमिका निभाई।
THE IMPACT OF ADMINISTRATIVE TRIBUNALS ON INDIAN GOVERNANCE
Administrative tribunals in India are quasi-judicial bodies created to provide speedy, expert, and relatively inexpensive adjudication of disputes arising primarily from the expanding administrative state. Constitutionally anchored in Articles 323A and 323B and implemented through the Administrative Tribunals Act, 1985, they were intended to reduce judicial backlog, professionalize adjudication in specialized areas such as service law and taxation, and enhance administrative accountability. This paper analyzes the origin, structure, functioning, and impact of administrative tribunals—particularly the Central Administrative Tribunal (CAT) and State Administrative Tribunals (SATs)—on Indian governance, drawing on doctrinal developments, empirical assessments, and critical scholarship. It argues that tribunals have made a significant but uneven contribution to efficiency and access to justice, while also generating enduring concerns about independence, constitutionalism, and institutional design.
Dietary Patterns and Vitamin B12–Folate Axis in Gestational Diabetes Mellitus: A Comparative Analysis
Introduction: Gestational Diabetes Mellitus (GDM) is a common metabolic disorder that occurs during pregnancy. GDM has been related to adverse maternal and child health. Dietary patterns and levels of micronutrients such as vitamin B12 and folate have been identified as key modifiable risk factors for GDM. However, there has been little research on the combined impact of these factors, particularly in Indian women. Methodology: A comparative cross-sectional study design was followed among a sample of 200 pregnant women, comprising 100 GDM and 100 non-GDM pregnant women. The study participants were recruited from the districts of Kurukshetra and Karnal. Data collection was conducted based on socio-demographic variables, dietary intake by the use of a 24-hour recall method and food frequency method, and biochemical variables such as vitamin B12 and folate levels. Results: The GDM subjects had significantly higher energy, carbohydrate, and fat intakes, whereas they had lower folate and vitamin B12 intakes. The GDM subjects also had lower fruit, dairy product, and green leafy vegetable intakes, whereas they had higher cereal and sweet food intakes. The prevalence of vitamin B12 and folate deficiencies was higher in GDM women. High BMI, lower vitamin B12, lower folate, higher carbohydrate, and lower fruit intakes were significant predictors of GDM, as confirmed by logistic regression analysis. Discussion: The findings of the study, therefore, suggest that dietary imbalance, as well as deficiencies of various micronutrients, contribute to the development of GDM. The interaction of vitamin B12 and folate levels may affect metabolic pathways, leading to insulin resistance. Nutritional imbalance, therefore, adds to the risk of developing GDM. Conclusion: It is observed that there is a strong association between dietary habits, micronutrients, and GDM risk. Improvement of dietary quality and adequate intake of vitamin B12 and folate may be helpful in reducing the burden of GDM. Nutritional interventions and screening of micronutrients should be undertaken to improve maternal and fetal outcomes.
Opportunities and Challenges of Hollow Core Fiber Deployment in India
As the telecommunications backbone of India rapidly scales to support expansive 5G/6G rollouts, high-frequency financial trading networks, and the explosive growth of AI-driven hyperscale data centers, our reliance on conventional single-mode fiber (SMF) faces physical limitations. Hollow Core Fiber (HCF), which guides light through an air-filled or vacuum core rather than solid silica glass, represents a paradigm shift in optical networking. This paper evaluates HCF's technical maturity, assessing its strategic opportunities for operations in India against formidable deployment barriers, such as a 50-100x cost premium, highly specialized splicing requirements, and a high terrestrial disruption environment. A phased deployment strategy tailored to the Indian telecom landscape is outlined.
सरस्वती नदी बेसिन की सभ्यतागत: एक विश्लेषण
प्रस्तुत शोध-पत्र सरस्वती नदी बेसिन की सभ्यतागत एवं सांस्कृतिक विरासत का ऐतिहासिक, पुरातात्विक एवं वैज्ञानिक दृष्टिकोण से विश्लेषण प्रस्तुत करता है। सरस्वती नदी भारतीय सभ्यता की उत्पति, विकास और सांस्कृतिक निरन्तरता में केन्द्रीय भूमिका निभाने वाली नदी रही है। वैदिक साहित्य में इसे ‘‘नदितमा’’, ‘‘अंबितमे’’ और ‘‘देवीतमे’’ जैसे विश्लेषणों से संबोधित किया गया है, जो इसके भौगोलिक, धार्मिक और सांस्कृतिक महत्व को स्पष्ट करते हैं। सरस्वती नदी बेसिन सिंधु-सरस्वती (हड़प्पा) सभ्यता का प्रमुख क्षेत्र रहा है , जहाँ सुव्यवस्थित नगर योजना, उन्नत जल निकासी प्रणाली, कृषि-आधारित अर्थव्यवस्था, शिल्प एवं व्यापार के प्रमाण प्राप्त होते हैं। राखी गढ़ी, कालीबंगा, बनवाली, फरमाना एवं अन्य पुरातात्विक स्थल इस क्षेत्र की विकसित सामाजिक-आर्थिक संरचना को रेखांकित करते हैं। आधुनिक वैज्ञानिक अनुसंधानों - विशेषतः उपग्रह चित्रण, भू-वैज्ञानिक सर्वेक्षण एवं पेलियों-चैनल अध्ययन से यह सिद्ध हुआ है की सरस्वती नदी का विस्तार प्रवाह क्षेत्र था, जो वर्तमान घग्गर-हकरा नदी प्रणाली से संबद्ध रहा है। इस प्रकार यह शोध-पत्र सरस्वती नदी बेसिन को भारतीय सभ्यता की एक मूलभूत सांस्कृतिक धरोहर के रूप में स्थापित करता है।
CSR AS A DRIVER OF BRAND VALUE: EVIDENCE FROM INDIAN CORPORATES LISTED ON THE BOMBAY STOCK EXCHANGE
Corporate Social Responsibility (CSR) is now a key component of modern business strategy, as it considers both the business side and the company's overall growth. More and more businesses are realising that corporate social responsibility (CSR) is important for promoting ethical business practices and long-term growth. CSR is essential because it ensures that businesses do the right thing, contribute to the economy's growth, and make the world a better place. This helps meet the needs of stakeholders and also fosters trust and a positive reputation. The Companies Act of 2013 in India stipulates that businesses must allocate a particular portion of their profits to corporate social responsibility (CSR). This makes it very important. This way, business goals can be more aligned with national goals, such as healthcare, education, and environmental sustainability. The findings indicate that businesses that engage in CSR not only enhance their public image but also experience growth advantages, including increased revenue, improved risk management, and elevated employee retention rates. The article also discusses the challenges and limitations of implementing CSR programs. It emphasizes the importance of CSR aligning with the company's primary objectives and the need for collaboration among all stakeholders. The report concludes with guidance for businesses on how to leverage CSR for long-term success while meeting their financial needs, social obligations, and brand value.
The Impact Of Artificial Intelligence On Financial Reporting Accuracy And Fraud Detection: Evidence From Indian Banking Companies
Artificial Intelligence (AI) is a revolutionary technology in the banking industry that has dramatically affected financial reporting systems and fraud detection systems. This study analyzes the effect of AI on the accuracy of financial reporting and efficiency in fraud detection in Indian banking firms through a quantitative research methodology. A structured questionnaire was used to gather primary data on 80 banking professionals and conduct an analysis based on the statistical methods, including mean, standard deviation, weighted scores, correlation analysis, and ranking. The results indicate that AI is beneficial to financial reporting, by improving data consistency, error reduction, and enabling real-time processing, and enhancing fraud detection, using methods like pattern recognition, anomaly detection, and predictive analytics. The research also establishes some of the challenges such as expensive implementation, privacy of the data, and skills gaps, which influence the adoption of AI. In spite of these difficulties, the findings suggest that AI is critical in enhancing transparency, efficiency, and risk management in the banking systems. The research offers viable information to financial institutions and policymakers to facilitate the successful implementation of AI in the banking industry.
A Deep Learning Framework for Multi-Class Lung Disease Classification Using Chest X-Ray Images
Lung diseases are among the leading causes of mortality worldwide, and early detection plays a crucial role in effective treatment and diagnosis. Chest X-ray (CXR) imaging is one of the most widely used and cost-effective diagnostic tools for detecting lung abnormalities. However, manual analysis of large volumes of medical images can be time-consuming and prone to human error. To address this challenge, this study proposes a deep learning-based architecture for multi-class lung disease classification using chest X-ray images. The dataset used in this study is collected from the Kaggle repository and includes labeled images belonging to different lung disease categories such as pneumonia, tuberculosis, COVID-19, and normal cases. The proposed framework begins with image preprocessing techniques including grayscale conversion, resizing, normalization, and noise filtering to improve image quality and standardize the dataset. Subsequently, Region of Interest (ROI) extraction is performed to isolate the lung region and eliminate irrelevant background information, thereby enhancing feature learning. The processed dataset is divided into training and testing subsets using a 70:30 ratio. Several deep learning models including VGG16, VGG19, InceptionV3, ResNet50, and DenseNet201 are implemented for feature extraction and classification of lung diseases. These convolutional neural network architectures learn hierarchical features from the chest X-ray images through convolutional layers, pooling layers, and fully connected layers. The performance of the proposed system is evaluated using various statistical metrics such as Accuracy, Precision, Sensitivity (Recall), F1-score, Kappa statistic, and Confusion Matrix. The experimental results demonstrate that deep learning models can effectively classify multiple lung diseases from chest X-ray images and assist in automated medical diagnosis. The proposed framework provides an efficient and reliable computer-aided diagnostic system that can support healthcare professionals in early detection and decision-making for lung disease diagnosis.
भारत विभाजन का पंजाब (हरियाणा) की ग्रामीण अर्थव्यवस्था पर प्रभाव।
1947 का भारत विभाजन भारतीय इतिहास की एक अत्यंत महत्वपूर्ण और दुखद घटना थी, जिसने देश की सामाजिक, आर्थिक और राजनीतिक संरचना को गहराई से प्रभावित किया। इसका प्रभाव केवल राष्ट्रीय स्तर तक सीमित नहीं रहा, बल्कि क्षेत्रीय स्तर पर भी इसके व्यापक परिणाम देखने को मिले। हरियाणा, जो उस समय अविभाजित पंजाब का हिस्सा था, विभाजन की इस प्रक्रिया से विशेष रूप से प्रभावित हुआ। विभाजन के परिणामस्वरूप बड़े पैमाने पर जनसंख्या का विस्थापन हुआ, जिसमें पश्चिमी पंजाब से आए शरणार्थियों ने हरियाणा के ग्रामीण क्षेत्रों में आकर बसावट की। इस अचानक जनसंख्या परिवर्तन ने ग्रामीण अर्थव्यवस्था की संरचना को पूरी तरह बदल दिया। इस शोध पत्र का मुख्य उद्देश्य 1947 के भारत विभाजन के परिणामस्वरूप हरियाणा की ग्रामीण अर्थव्यवस्था में हुए परिवर्तनों का विश्लेषण करना है। अध्ययन में द्वितीयक स्रोतों जैसे ऐतिहासिक ग्रंथों, शोध लेखों, सरकारी रिपोर्टों तथा जनगणना आंकड़ों का उपयोग किया गया है। शोध का स्वरूप वर्णनात्मक एवं विश्लेषणात्मक है, जिसके माध्यम से विभाजन के आर्थिक प्रभावों को विभिन्न आयामों में समझने का प्रयास किया गया है। अध्ययन से यह स्पष्ट होता है कि विभाजन के कारण भूमि स्वामित्व के प्रतिरूप में महत्वपूर्ण परिवर्तन हुए, क्योंकि पाकिस्तान जाने वाले लोगों की भूमि का पुनर्वितरण शरणार्थियों के बीच किया गया। इसके अतिरिक्त, प्रारंभिक वर्षों में कृषि उत्पादन में अस्थिरता देखने को मिली, किंतु समय के साथ नई कृषि तकनीकों और श्रम शक्ति के आगमन से इसमें सुधार हुआ। ग्रामीण क्षेत्रों में श्रम संरचना, उत्पादन प्रणाली और सामाजिक संबंधों में भी बदलाव आए, जिससे एक नई ग्रामीण अर्थव्यवस्था का निर्माण हुआ।
Role of E-Commerce in Promoting Bastar Handicrafts: A Quantitative Study.
The rapid expansion of the digital economy has significantly transformed traditional modes of trade and commerce, offering new avenues for the promotion of indigenous industries. In this context, the present study investigates the role of e-commerce in promoting Bastar handicrafts through a quantitative analytical framework. The primary objective is to examine the impact of e-commerce adoption on market reach and sales performance, as well as to analyze the challenges hindering its effective utilization among artisans.The study is based on primary data collected from 200 respondents, including artisans and handicraft vendors, using a structured questionnaire. Statistical analysis was conducted using SPSS, employing inferential tools such as the Chi-square test and Pearson’s correlation coefficient. The results reveal a statistically significant association between e-commerce adoption and enhanced sales performance (χ² = 77.00, p < 0.05), indicating that digital platforms substantially improve market accessibility and economic outcomes. Furthermore, correlation analysis demonstrates a moderate negative relationship (r = -0.52) between adoption and prevailing challenges, suggesting that factors such as limited technical knowledge, inadequate infrastructure, and logistical constraints impede the effective integration of e-commerce.The findings underscore the dualistic nature of e-commerce as both an enabler of economic growth and a domain constrained by structural barriers. The study concludes that while e-commerce possesses significant potential to enhance the visibility and sustainability of Bastar handicrafts, targeted interventions focusing on digital literacy, infrastructural development, and policy support are essential to ensure inclusive participation.
STUDY OF PROFESSIONAL COMPETENCY OF YOUNG AGE AND MIDDLE AGE PROFESSIONALS IN RELATION TO THEIR PHYSICAL ACTIVITY
This study aimed to investigate the connection between young and middle-aged professional’s professional competency and physical activity. Purposive sampling was used to select 60 full-time professionals, who were then divided into two age groups: young (ages 25–35) and middle-aged (ages 36–45). The study used a comparative and correlational design. Physical activity levels were measured using the International Physical Activity Questionnaire (IPAQ), burnout was measured using the Maslach Burnout Inventory (MBI), and professional competency was assessed using the Professionalization Scale. There were no discernible differences in burnout or professional competency between the age groups, according to statistical analysis. Additionally, there were no discernible relationships between professional competency, burnout, and physical activity. Professionals who engaged in a lot of physical activity had marginally higher competency scores, but the differences were not statistically significant. These results imply that professional competency may not be determined solely by age or level of physical activity. Additional influencing factors like job roles, mental health, and organizational environment should be investigated in future research.
A Relationship between Psychological Well-Being and Functional Fitness of Senior Citizens
Purpose: The purpose of the present study was to examine the relationship between psychological well-being and functional fitness among senior citizens. With the increasing ageing population, maintaining both physical capability and mental health has become essential for improving the quality of life in old age. The study aimed to determine whether functional fitness is associated with psychological well-being among senior citizens. Methods: The study employed a descriptive correlational research design. A sample of 120 senior citizens aged 60 years and above was selected from urban and rural areas of Haryana using a random sampling technique. Functional fitness was measured using the Senior Fitness Test developed by Rikli and Jones (2001), and psychological well-being was assessed using Ryff’s Psychological Well-Being Scale (1989). Mean, standard deviation, and Pearson’s Product Moment Correlation were used for statistical analysis. Results: The results of the study indicated a positive and significant relationship between functional fitness and psychological well-being among senior citizens. Individuals with higher functional fitness scores tended to report higher levels of psychological well-being. Conclusion: The study concluded that better functional fitness is associated with improved psychological well-being among senior citizens. Enhancing functional fitness through suitable activities and health programs may contribute to better mental health and overall well-being in later life.
“Barriers to Effective Agricultural Credit Delivery: A Study of Public Sector Banks in Haryana”
This study examines the barriers affecting the effective delivery of agricultural credit by public sector banks in Haryana and their implications for agricultural development. Agriculture, being a critical sector of the Indian economy, relies heavily on timely and adequate access to institutional credit for sustaining productivity and ensuring farmers’ income stability. Despite various government initiatives and financial inclusion programs, several operational and structural challenges continue to hinder the accessibility and efficiency of agricultural credit. The study adopts a quantitative research approach based on primary data collected from 588 farmers through a structured questionnaire. Statistical tools, including descriptive analysis and multiple regression, are employed to identify key factors influencing credit delivery. The findings reveal that documentation delays, loan processing time, collateral requirements, awareness gaps, and high interest rates are the most significant constraints affecting farmers’ access to credit. The regression results further indicate that these variables collectively explain a substantial proportion of the variation in agricultural development outcomes. The study concludes that while public sector banks play a crucial role in agricultural financing, their effectiveness is limited by procedural inefficiencies and inadequate support systems. It suggests the need for simplifying processes, improving awareness programs, enhancing institutional responsiveness, and leveraging technology to strengthen credit delivery mechanisms and promote sustainable agricultural development in Haryana.
परशुराम शुक्ल की बाल कहानियों में अभिव्यक्त समाज और संस्कृति
साहित्य समाज का दर्पण है, समाज में जो घटित होता है, उसका प्रतिबिम्ब साहित्य में दिखाई देता है। जीवन की वास्तविकता को साहित्यकार सदैव लिखता रहा है। हमारी वर्तमान पीढ़ी को भविष्य में आने वाली पीढ़ी से जोड़ने की कड़ी बच्चे होते हैं। बाल-साहित्य, हिंदी साहित्य की एक सशक्त विद्या है। बाल-साहित्य बच्चों को केंद्र में रखकर लिखा जाने वाला साहित्य है। यह साहित्य प्राचीन काल से लेकर आधुनिक काल तक निरन्तर लिखा जा रहा है। स्वतन्त्रता से पूर्व बाल-साहित्य को दोयम दर्जे का साहित्य समझकर बड़े-बड़े साहित्यकार इसे लिखने से कतराते थे, लेकिन वर्तमान में बाल-साहित्य को बड़े से बड़ा लेखक भी लिखकर अपने को गौरवान्वित अनुभव करता है। वर्तमान में अनेक साहित्यकार बाल-साहित्य लिख रहे हैं। कुसुम डोमाल, प्रमाश मनु, हरिकृष्ण देवसरे, सुरेन्द्र विक्रम, मनोज कुमार आदि इन बाल-साहित्यकारों में एक प्रमुख नाम डॉ॰ परशुराम शुक्ल का भी है।
दुर्ग जिले (छत्तीसगढ़) के जल संसाधनों का बहुआयामी विश्लेषण
यह शोध पत्र छत्तीसगढ़ के दुर्ग जिले के सतही और भू-जल संसाधनों की वर्तमान स्थिति का मूल्यांकन करता है। शिवनाथ नदी बेसिन पर आधारित यह क्षेत्र औद्योगिक और कृषि प्रधान है। अध्ययन में पाया गया कि पिछले दशक में औसत वर्षा 1084 { mm} रही है, लेकिन तीव्र शहरीकरण के कारण भू-जल स्तर में 0.5 m/year} की गिरावट दर्ज की गई है।
Bridging the Employability Gap: The Importance of English Communication Skills for Engineering Graduates
The employability of engineering graduates has become a significant concern in the modern job market, where technical proficiency alone is no longer sufficient. This study explores the critical role of English communication skills in enhancing the employability of engineering graduates. In a globalized and competitive professional environment, employers increasingly seek candidates who possess not only technical knowledge but also the ability to communicate effectively in English. The research is based on secondary data collected from academic journals, industry reports, and previous studies focusing on employability and communication skills. The findings indicate that a lack of proficiency in English communication is one of the primary barriers preventing engineering graduates from securing employment, despite having strong technical backgrounds. Skills such as verbal communication, written communication, presentation ability, and interpersonal interaction significantly influence hiring decisions. The study also highlights that engineering curricula often emphasize technical training while neglecting soft skills development, thereby widening the employability gap. Furthermore, the research suggests that integrating communication skill training into engineering education can substantially improve job readiness. It emphasizes the need for structured language programs, industry-academia collaboration, and practical exposure through presentations and group discussions. The study concludes that English communication skills are not merely supplementary but essential for professional success, making them a key factor in bridging the employability gap among engineering graduates.
Exploring the Role of Yoga, Meditation, Spirituality and Sports in Mental Health
The issue of mental health has become rather pressing in today’s world, with stress, anxiety, and depression rates increasing steadily. The paper analyzes ways in which yoga, meditation, spirituality, and sports can be used jointly as holistic tools to enhance mental well-being. Using literature review and theoretical approaches from various disciplines, the paper develops a conceptual framework incorporating all four factors mentioned above and exploring their impacts individually and collectively on psychological state. Based on a descriptive and analytical method, the study is conducted by analyzing secondary data through correlation, regression, and Structural Equation Modeling (SEM).
Dr Anil Kumar Bhardwaj, Sushant Jha, Ms. Manisha Chouhan, Dr. Samir Thakur
LC–MS/MS-BASED APPROACHES FOR METABOLITE IDENTIFICATION AND QUANTIFICATION OF VONOPRAZAN: A COMPREHENSIVE REVIEW
Vonoprazan is a potassium-competitive acid blocker (P‑CAB) that has rapidly emerged as an alternative to proton pump inhibitors for the management of acid‑related disorders and Helicobacter pylori eradication therapy. Its extensive hepatic metabolism via cytochrome P450 (CYP) enzymes and sulfotransferases generates several major metabolites, including M‑I, M‑II, M‑III, and the sulfate conjugate M‑IV‑Sul, which have important implications for efficacy, safety, and drug–drug interaction (DDI) risk. Liquid chromatography–tandem mass spectrometry (LC–MS/MS) has become the method of choice for quantitative determination of vonoprazan and its metabolites in biological matrices and for structural elucidation in in vitro and in vivo metabolism studies. This review summarizes LC–MS/MS-based bioanalytical and metabolite identification approaches applied to vonoprazan, covering method development and validation in plasma, urine, liver microsomes and hepatocytes, strategies for simultaneous quantification of parent drug and multiple metabolites, and applications in pharmacokinetic, bioequivalence and DDI studies. Particular emphasis is placed on multiple‑reaction monitoring (MRM) methods, sample preparation workflows, regulatory validation parameters, and emerging trends such as green analytical chemistry and stable‑isotope internal standards. Finally, current gaps and future directions are discussed, including the need for more comprehensive metabolite profiling in humans, standardized reporting of metabolite exposure, and integration of LC–MS/MS data into mechanistic modeling frameworks.
RECENTLY APPROVED ANTIDIABETIC DRUGS BY FDA AND METABOLITE CHARACTERIZATION STUDIES USING LC/MS: A COMPREHENSIVE REVIEW
Type 2 diabetes mellitus (T2DM) represents a significant global health burden, with over 38 million Americans currently affected. The FDA has approved nearly 60 antidiabetic agents, with continuous expansion of therapeutic options including glucagon-like peptide-1 receptor agonists (GLP-1 RAs), sodium-glucose cotransporter-2 inhibitors (SGLT2i), and novel co-agonists. This review synthesizes recent FDA approvals in antidiabetic therapeutics (2023-2025), with particular emphasis on GLP-1 RAs, SGLT2 inhibitors, and emerging combination therapies. Additionally, this paper comprehensively discusses the role of liquid chromatography-mass spectrometry (LC/MS) in metabolite identification and characterization studies, including FDA compliance protocols and method validation guidelines. The review highlights key regulatory considerations, including GLP status, bioanalytical method validation parameters, and metabolite profiling strategies relevant to drug development. This work synthesizes current literature, regulatory guidance, and clinical data to provide a comprehensive understanding of modern antidiabetic drug development and metabolite assessment methodologies.
Psychosocial Influences on Compulsive Facebook Habits: Personality Meets Self-Perception
Background: An increasing number of people are seeing the detrimental effects of Facebook use on their mental health and ability to interact socially, a phenomenon known as problematic Facebook use (PFU). Perceived social acceptability, self-efficacy, self-esteem, and personality characteristics are major factors in determining whether Facebook usage is excessive or maladaptive, according to previous studies. Method: This research followed the standard procedure for meta-analyses by conducting a systematic review. via the use of predetermined search terms, relevant studies were located via databases including Medline, Scopus, Web of Science, and ScienceDirect. A total of 124 studies were considered after screening and eligibility evaluation. Using standardised methods and evaluation tools, data extraction and quality assessment were carried out. Results: According to the results, PFU is favourably correlated with narcissism, impulsivity, loneliness, and high levels of neuroticism, and negatively correlated with attributes like emotional stability and conscientiousness. Some of the characteristics that mediate the relationship between problematic use and low self-esteem and self-efficacy include social comparison, the need for external validation, and the fear of missing out (FoMO). People are more likely to participate in excessive online conversations when they believe they are socially acceptable to do so. Conclusion: A number of interrelated psychological and personality traits contribute to PFU's complexity. Those who are already emotionally and socially vulnerable may resort to this unhealthy coping method. In order to improve mental health and decrease harmful social media usage, it is important to address these variables via tailored treatments.
Phytochemical Profiling and In Vitro Anti-Inflammatory Potential of Stachytarpheta indica (L.) Vahl Leaf Extracts
Medicinal plants represent a valuable source of bioactive compounds with therapeutic relevance, particularly in the management of inflammatory disorders. This study investigated the phytochemical profile and in vitro anti-inflammatory activity of aqueous and methanolic leaf extracts of Stachytarpheta indica (L.) Vahl. Leaves were collected from Bhopal, authenticated botanically, and extracted using infusion (aqueous) and Soxhlet (methanolic) methods. Qualitative phytochemical screening revealed notable solvent-specific variation, with aqueous extracts containing tannins, saponins, glycosides, phenolics, flavonoids, alkaloids, and terpenoids, whereas methanolic extracts lacked tannins, saponins, and glycosides. Total phenolic content (TPC) was higher in the aqueous extract (0.0753 mg GAE/mL) compared to the methanolic extract (0.0718 mg GAE/mL), while total flavonoid content (TFC) was greater in the methanolic extract (0.4068 µg QE/mg) than the aqueous fraction (0.287 µg QE/mg). Anti-inflammatory potential assessed by the heat-induced protein denaturation assay demonstrated significant inhibition by the aqueous extract (42.16%) relative to the methanolic extract (6.32%), with aspirin showing 79.1% inhibition. The enhanced activity of the aqueous extract correlates with elevated phenolic-tannin presence and their known protein-stabilizing effects. Overall, the findings highlight S. indica as a promising source of natural anti-inflammatory agents and support the relevance of aqueous preparations in traditional medicine.
A Comparative Study of Body Composition among Middle-Aged Adults of Patiala
The current research was done to compare the body composition variables of middle-aged adults living in Patiala city. Body composition is one of the primary factors that predetermine overall health, which has an impact on physical fitness, metabolic efficiency and risk of disease. The variables were analyzed such as protein level, percentage of body water, percentage of fat, waist-hip ratio, height and skeletal mass. One hundred participants (50 men and 50 women) aged between 35 and 50 years were chosen by a simple random sampling method. A Bioelectrical Impedance Analyzer (BIA), tape and stadiometer were used to collect data. The data was analyzed using statistical methods which included mean, standard deviation and independent t-test. The results indicated that there were very significant variations in fat percentage, skeletal mass, and waist-hip ratio among the male and female respondents. The research sheds light on the essence of a balanced body composition in the healthy state and offers practical information to fitness professionals and health practitioners.
Design and Simulation of Non-isolated Bidirectional DC-DC Converter for Vehicle Application
This paper presents the design and simulation of a non-isolated bidirectional DC–DC converter for electric vehicle (EV) applications, focusing on efficient energy transfer between the battery and DC bus. The proposed system integrates a battery energy storage unit with a bidirectional converter that operates in both buck mode (charging) and boost mode (discharging) to support vehicle operation and regenerative energy management. The model is developed and analyzed in MATLAB/Simulink using appropriate control strategies based on pulse width modulation (PWM). The performance of the system is evaluated under different operating conditions, including varying state of charge (SOC) levels, battery charging and discharging characteristics, DC link voltage stability, and load current response. The results demonstrate that the converter ensures smooth and efficient bidirectional power flow, with stable DC link voltage and minimal ripple. The SOC analysis confirms effective charging at lower levels and controlled charging near full capacity, preventing overcharging and enhancing battery life. During discharging, the system provides a consistent and reliable power supply to the load. the proposed non-isolated bidirectional DC–DC converter exhibits high efficiency, reliable operation, and effective energy management, making it suitable for electric vehicle applications, include battery management systems, regenerative braking, and auxiliary power support.
Development of a Grid-Connected PV–DFIG Hybrid Renewable Energy System with Advanced Control Strategies
This study presents the design and simulation of a hybrid renewable energy system developed in MATLAB/Simulink to enhance fault protection and ensure reliable power delivery. The proposed system integrates solar photovoltaic (PV) and wind energy sources to achieve efficient and stable power generation under varying environmental conditions. The solar subsystem is modeled using a PV array coupled with Maximum Power Point Tracking (MPPT) algorithms such as Hill Climbing Search (HCS) and Perturb and Observe (P&O) to maximize energy extraction. The wind subsystem is implemented using both Permanent Magnet Synchronous Generator (PMSG) and Doubly Fed Induction Generator (DFIG) configurations for improved performance and flexibility. The generated power from both renewable sources is processed through power electronic converters and combined via a common DC-link, which acts as an energy buffer to maintain voltage stability and facilitate power balancing. The DC-link output is supplied to a DC/AC inverter that delivers controlled AC power to an asynchronous or synchronous motor. This motor is mechanically coupled to a generator, forming a Motor–Generator Pair (MGP) system that provides electrical isolation between renewable sources and the grid. This configuration enhances system protection by mitigating the impact of grid disturbances such as voltage sags, swells, and short circuits. Furthermore, the system incorporates advanced control strategies, including DC-link voltage regulation and a Fractional Order PID (FOPID) controller to improve dynamic response, stability, and robustness. In the DFIG-based configuration, the stator is directly connected to the grid, while the rotor is interfaced through a back-to-back converter consisting of a Rotor Side Converter (RSC) and Grid Side Converter (GSC), enabling independent control of active and reactive power along with DC-link voltage regulation. Additional components such as filters, measurement units, and fault control mechanisms are included to ensure power quality, accurate monitoring, and effective disturbance mitigation. Simulation results demonstrate that the proposed hybrid system significantly improves reliability, power quality, and fault tolerance, making it suitable for modern grid-connected renewable energy applications.
Grid Connected Hybrid Energy Storage Structure with Renewable Energy Sources
This study presents the design and analysis of a hybrid renewable energy system integrating multiple energy sources such as solar photovoltaic (PV), wind, and hydroelectric power along with advanced energy storage technologies including battery, hydrogen storage, and supercapacitor. The system is supported by a power conversion unit and controlled using an intelligent energy management system (EMS) to ensure efficient power flow and system stability. The proposed model utilizes converters and bidirectional energy flow to interact with the grid, enabling optimal utilization of generated and stored energy. A cooling system is also incorporated to maintain safe operating conditions of storage components. The system is analyzed under varying conditions to evaluate its performance in terms of reliability, efficiency, and stability. The results demonstrate that the proposed hybrid system effectively balances energy generation and consumption, reduces dependency on conventional sources, and ensures continuous power supply.
Public Policy Exception In Arbitration Law In India And The United Kingdom: A Comparative Analysis Of Judicial Interpretation And Its Impact On Commercial Certainty
The public policy exception in arbitration law is an important tool in protecting the upholding of basic principles of law, and at the same time creates difficulties in respect of finality and enforcement of arbitral awards. This paper presents a comparative analysis of the interpretation and application of this exception in India and the UK, and in relation to its consequences on commercial certainty. Using statutory provisions, case law, and other pertinent international instruments, the analysis reveals the differences in the approaches taken by the courts in the two jurisdictions. Although historically India adopted a broad and interventionist interpretation, especially by landmark cases which created the concept of patent illegality, recent legislative changes and judicial practice have made this much tighter, more in line with international norms. By contrast, the United Kingdom has always been a restrictive and pro-enforcement jurisdiction, with minimal intervention of the judiciary and finality of arbitral awards. Business certainty, investor trust, and the arbitration landscape as a whole have all been profoundly impacted by these competing approaches, the study finds. In order to preserve the credibility of legal systems and arbitration as an effective means of resolving disputes, it is recommended that the public policy exception be read with a sense of proportion and principle.
A Comparative study of Mental Health among Employed and Unemployed Young Technical Personnel
The Purpose of the present research paper is to highlight the mental health status of employed and unemployed young technical personnel who were recently employed and also on those who remain unemployed. Mental health status was measured by M.M.H.S.I. developed by Kumar and Thakur (1986). t-test was used to find out significant difference. Results obtained by t-test showed that young technical personnel who were employed have better mental health as compared to those who were not employed. Results were interpreted in terms of Indian sociocultural milieu.
Modeling and Simulation of a PV-Based Boost Converter with Maximum Power Point Tracking
This study presents the modeling and simulation of a hybrid renewable energy system integrating solar photovoltaic (PV), wind energy, and battery storage using MATLAB/Simulink. The system is designed with a common DC bus architecture, where the PV array operates under a Maximum Power Point Tracking (MPPT) controller, and the battery is connected through a bidirectional DC–DC converter for energy management. A DC–AC inverter with PWM control converts the DC power into three-phase AC, which is supplied to the load and utility grid through an LC filter.Simulation results demonstrate that the PV system achieves a stable DC voltage of approximately 375 V, while the inverter delivers a constant output power of about 5 kW. The three-phase voltage and current waveforms are balanced and sinusoidal, indicating efficient inverter performance with good power quality. The battery effectively supports the system during fluctuations, and the overall system maintains stability under varying wind speed conditions.The results confirm that the proposed hybrid system provides reliable, efficient, and continuous power supply, making it suitable for grid-connected and standalone renewable energy applications.
Dr. Sunil Kumar Singh, Roshan Vishwakarma, Sandeep Kumar Sonkar, Saroj
शैलेश मटियानी के कथा-साहित्य में मानवीय संवेदनाओं की अभिव्यक्ति
शैलेश मटियानी हिन्दी साहित्य के ऐसे सशक्त कथाकार हैं, जिनकी रचनाओं में मानवीय संवेदना का व्यापक स्वरुप परिलक्षित होता है। उन्होंने समाज के हाशिए पर खड़े,उपेक्षित, शोषित तथा संघर्षशील मनुष्यों के जीवन को अपनी रचनाओं का केन्द्र बनाया, उनकी संवेदना केवल करुणा तक सीमित नहीं है, बल्कि वह मुनष्य के अस्तित्व, उसकी गरिमा, संघर्ष, आशा और जिजीविषा की संवेदना है। मटियानी ने अपने कथा-साहित्य में ग्रामीण, आंचलिक, नगरीय तथा निम्नवर्गीय जीवन के विविध-आयामों को प्रस्तुत किया है। उनके साहित्य में स्त्री, दलित, मजदूर, विस्थापित और अभावग्रस्त वर्ग के जीवनानुभवों का सशक्त चित्रण मिलता है। प्रस्तुत शोध-पत्र में शैलेश मटियानी के साहित्य में निहित संवेदना के विविध पक्षों - मानवीय करुणा, सामाजिक चेतना, स्त्री-संवेदना, लोक-संवदेना,तथा पर्वतीय जीवन बोध का विश्लेषण किया है।
Review on Multi-Level Ensemble and Transfer Learning Approaches for Cybersecurity Anomaly Detection
This review paper critically analyzes and synthesizes existing research to evaluate the performance, limitations, and practical applicability of multi-level ensemble and transfer learning architectures for anomaly detection in cybersecurity systems. The study follows a systematic review approach, focusing on recent and relevant studies related to machine learning-based anomaly detection, ensemble learning methods, and transfer learning techniques applied to various cybersecurity datasets and environments. The selected literature is analyzed based on architectural design, learning models, performance metrics, and implementation challenges rather than proposing or developing a new model.The paper selection criteria include studies published in reputable journals and conferences that focus on cybersecurity anomaly detection using ensemble learning, transfer learning, or hybrid approaches, particularly those addressing real-world datasets and practical deployment scenarios.The findings from the reviewed literature consistently show that multi-level ensemble methods provide higher robustness and better detection accuracy than single-model and single-layer ensemble approaches, especially when dealing with noisy, high-dimensional, and imbalanced cybersecurity data. Transfer learning is found to significantly improve anomaly detection performance in data-scarce environments by enabling knowledge transfer from related domains, reducing training time, and enhancing generalization to unseen and novel attacks, the combined use of ensemble learning and transfer learning demonstrates notable improvements in reducing false positives and enhancing the detection of zero-day attacks and advanced persistent threats (Mukherji et al., 2004). Overall, the review highlights that integrating multi-level ensemble learning with transfer learning is a promising approach for developing adaptive, scalable, and resilient cybersecurity anomaly detection systems. However, challenges such as computational complexity, interpretability, and real-time deployment remain key areas for future research.
Promoting Research And Innovation Through Ai: Global And Indian Perspectives
Artificial Intelligence (AI) has emerged as one of the most transformative forces shaping contemporary research and innovation ecosystems across the world. By enabling advanced data analytics, predictive modelling, automation of routine tasks, and intelligent decision-making, AI has significantly altered how knowledge is generated, validated, and disseminated. This research paper examines the role of AI in promoting research and innovation from a combined global and Indian perspective, highlighting both opportunities and structural challenges. The study adopts a qualitative and analytical approach, drawing upon interdisciplinary literature, policy documents, and real-world case examples to explore how AI enhances research productivity, fosters cross-disciplinary collaboration, and accelerates innovation cycles. At the global level, the paper analyses how leading economies and institutions integrate AI into research infrastructures to address complex societal problems in health, education, climate change, and industrial development. Simultaneously, the Indian context is examined with reference to national initiatives such as the National Education Policy 2020, National Strategy for Artificial Intelligence, and the growing role of academic institutions, startups, and public research organizations. The paper also critically engages with ethical, legal, and social concerns associated with AI-driven research, including data privacy, algorithmic bias, transparency, and academic integrity. By juxtaposing global best practices with India’s evolving research ecosystem, the study identifies gaps, strengths, and future possibilities. It concludes that AI, when governed responsibly and inclusively, can act as a powerful enabler of equitable research and sustainable innovation, provided that human creativity, ethical oversight, and institutional capacity-building remain central to its deployment.
William Golding’s View of Human Nature in Lord of the Flies
William Golding’s Lord of the Flies offers a profound and unsettling exploration of human nature, challenging the optimistic belief that humans are inherently good and guided by reason. This paper argues that Golding presents a fundamentally pessimistic view of humanity, suggesting that evil is an intrinsic part of human nature that emerges when societal constraints are removed. Through the gradual degeneration of a group of schoolboys stranded on an isolated island, Golding reveals how fragile civilization is and how quickly individuals revert to primitive instincts. By analysing key characters—Ralph, Jack, Piggy, and Simon—this study examines the tension between order and chaos, reason and instinct, morality and savagery. It also explores the symbolic significance of the “beast” and the breakdown of social structures. Ultimately, the paper concludes that Golding views human nature as deeply flawed, requiring continuous discipline, ethical awareness, and societal regulation to prevent moral collapse.
GREEN MARKETING AND CONSUMER BUYING BEHAVIOUR: A STUDY ON SUSTAINABILITY-DRIVEN BRAND PREFERENCES
Green marketing has emerged as one of the most significant strategic shifts in contemporary business practice, driven by escalating environmental consciousness and evolving consumer expectations. This paper investigates the relationship between green marketing practices and consumer buying behaviour, with a specific focus on sustainability-driven brand preferences. Drawing on secondary data from multiple global consumer surveys (2023–2025), this study analyses the influence of eco-labeling, sustainable packaging, green advertising, corporate social responsibility (CSR), and eco-branding on purchase intention and brand loyalty. Results confirm a strong positive correlation between green marketing communication and consumer purchase behaviour, with younger demographics—particularly Gen Z and Millennials—demonstrating disproportionately higher sustainability-driven brand preferences. The paper further identifies greenwashing distrust, price premiums, and unclear eco-labeling as primary barriers to green purchasing. Theoretical grounding is provided through the Theory of Planned Behaviour (TPB) and the Green Purchase Intention Model. Findings carry significant implications for marketers, brand managers, and policy architects in India and globally.
शिक्षकांना सूक्ष्म अध्ययन कार्यनीतीची अंमलबजावणी करताना येणाऱ्या आव्हानांचा एक चिकित्सक अभ्यास
21व्या शतकामध्ये प्रत्येक क्षेत्रात वेगाने बदल घडताना दिसत आहेत. त्यात शिक्षण क्षेत्रातही अमुलाग्र बदल घडत आहे. आपल्या जीवनात तंत्रज्ञानाच्या शिरकाव्यामुळे शैक्षणिक पार्श्वभूमी बदलत आहे.आजच्या डिजिटल युगात विद्यार्थ्यांचा एकाग्रतेचा काळ कमी होत चालला आहे.(Nidhi Waldia et al 2013) पारंपारिक आणि दीर्घकालीन चालणाऱ्या अध्ययन अध्यापन पद्धती मधील मर्यादा (MohammedG.S.et al 2018) लक्षात घेता सूक्ष्मअध्ययन कार्यनीती (micro learning strategies) ही एक प्रभावी पद्धती समोर आली आहे. प्रदीर्घ व्याख्यानांपेक्षा त्याच व्याख्यानांचे छोटे घटक (bite sized content ) शिकवणे ही काळाची गरज बनली आहे.(Vivian, J.2018) सूक्ष्म अध्ययन म्हणजे शैक्षणिक माहितीचे अत्यंत छोट्या सुटसुटीत आणि अर्थपूर्ण भागांत (Bite-sized modules) विभाजन करणे. प्रस्तुत संशोधनाचा मुख्य उद्दिष्ट माध्यमिक स्तरावरील शिक्षकांना ही सूक्ष्मअध्ययन कार्यनीती (micro learning strategies) प्रत्यक्ष व्यवहारात वापरत असताना कोणत्या आव्हानांचा सामना करावा लागतो. याचा चिकित्सक अभ्यास करणे हा आहे. प्रस्तुत संशोधनासाठी वर्णनात्मक सर्वेक्षण पद्धती(descriptive survey method) वापरण्यात आली आहे. संशोधकाने निवडक माध्यमिक शिक्षकांकडून प्रश्नावली द्वारे माहिती संकलित केली आहे. संशोधनातून असे निष्पन्न झाले की सूक्ष्म अध्ययन पद्धती लवचिक आणि वेळ वाचवणारी असली तरी तिच्या अंमलबजावणीत अनेक अडथळे आहे. यामध्ये प्रामुख्याने इंटरनेटचा अभाव असणे किंवा इंटरनेट असून वेग कमी असणे, अद्ययावत उपकरणांची कमतरता, शिक्षकांमधील तांत्रिक कौशल्याचे अज्ञान, दैनंदिन कामातून मिळणारा कमी वेळ यांचा समावेश होतो. संशोधनातून असे दिसून आले आहे की अनेक शिक्षकांमध्ये डिजिटल साक्षरतेचा अभाव असल्याने ते नवीन तंत्रज्ञान स्वीकारण्यास मानसिक दृष्ट्या तयार नसतात. सूक्ष्म अध्ययन कार्यनीती यशस्वी होण्यासाठी शाळांनी पायाभूत सुविधा पुरविणे. शासनाने शिक्षकांसाठी विशेष कार्यशाळा आयोजित करणे आवश्यक आहे. हे संशोधन शिक्षकांच्या डिजिटल सक्षमीकरणासाठी आणि विकासासाठी मार्गदर्शक ठरेल. सूक्ष्म अध्ययन राबविताना येणाऱ्या अडचणींवर मात करण्यासाठी उपाय योजना सुचवेल. सदर संशोधनामुळे अध्यापन प्रक्रिया प्रभावी आणि परिणामकारक होण्यास मदत होईल. या दृष्टीने हे संशोधन महत्त्वाचे ठरेल.
सौ. वृंदा महेश पवार, डॉ. अमोल शिवाजी चव्हाण
Secure Agricultural Data Sharing Architecture Using Blockchain, IoT, and Smart Contracts for Climate-Smart Farming
The rapid advancement of digital technologies has significantly transformed modern agricultural systems and introduced new opportunities for achieving sustainable and climate-smart farming practices. Climate change, environmental degradation, water scarcity, soil fertility decline, unpredictable weather conditions, and increasing food demand have intensified the need for intelligent agricultural management systems capable of supporting data-driven decision-making. In this context, agricultural data has become one of the most valuable resources for improving productivity, sustainability, resource optimization, and climate resilience. However, conventional agricultural data management systems suffer from several limitations, including lack of transparency, centralized data control, cybersecurity vulnerabilities, poor interoperability, data manipulation risks, and inadequate stakeholder trust. The present study focuses on the development of a secure agricultural data sharing architecture using Blockchain, Internet of Things (IoT), and smart contracts for climate-smart farming. The proposed framework integrates decentralized blockchain infrastructure with IoT-enabled environmental monitoring systems and automated smart contract mechanisms to establish a secure, transparent, scalable, and intelligent agricultural data ecosystem. IoT devices continuously collect real-time agricultural and environmental data related to soil moisture, temperature, humidity, rainfall, crop conditions, water levels, fertilizer usage, pest detection, and climate variability. Blockchain technology ensures secure, immutable, and tamper-resistant storage of agricultural data, while smart contracts automate data access permissions, transaction validation, resource allocation, insurance claims, and supply chain coordination. The study adopts a mixed-method research design involving both qualitative and quantitative approaches. Primary data were collected through structured questionnaires, interviews, and field observations involving farmers, agricultural officers, climate experts, technology developers, data analysts, and agribusiness stakeholders. The findings reveal that blockchain-enabled agricultural data sharing systems significantly improve transparency, cybersecurity, stakeholder trust, climate monitoring efficiency, and data accessibility. IoT integration enhances real-time environmental monitoring and climate prediction accuracy, while smart contracts improve automation and decentralized governance. The results further indicate that secure agricultural data sharing frameworks contribute to sustainable farming practices, precision agriculture, and climate adaptation strategies. The study contributes to the growing field of Agriculture 4.0 and climate-smart agriculture by proposing an integrated technological framework capable of supporting secure agricultural data ecosystems. The research provides valuable insights for policymakers, researchers, agribusiness firms, agricultural institutions, and technology developers interested in promoting sustainable and intelligent agricultural systems.
Design and implement intelligent automation techniques in web applications for improving operational efficiency, reducing manual intervention, and optimizing real-time decision-making processes
The rapid growth of digital technologies and online services has increased the demand for intelligent web applications capable of improving operational efficiency, reducing manual intervention, and supporting real-time decision-making processes. Traditional web systems often suffer from limited automation, slower response time, lower prediction accuracy, and inefficient resource utilization. To address these challenges, this study proposes and implements intelligent automation techniques in web applications using Artificial Intelligence, Machine Learning, and Deep Learning models. The proposed framework integrates predictive analytics, recommendation systems, Natural Language Processing, chatbot automation, cybersecurity monitoring, and intelligent decision-making mechanisms into a scalable cloud-based web architecture. The system was developed using Machine Learning algorithms such as Decision Tree, Random Forest, Support Vector Machine, and Logistic Regression along with Deep Learning models including Artificial Neural Networks, Convolutional Neural Networks, and Recurrent Neural Networks. Experimental analysis was conducted using real-time web datasets and operational analytics to evaluate the performance of the proposed AI-driven intelligent web system. The experimental results demonstrated significant improvements over traditional web systems across multiple performance metrics. The proposed intelligent system achieved an accuracy of 96.78%, precision of 95.64%, recall of 94.85%, and F1-score of 95.24%, compared to 82.45%, 80.12%, 78.90%, and 79.48% respectively in traditional systems. The Mean Squared Error was reduced from 0.185 to 0.042, confirming improved prediction capability and analytical performance. The AI-driven system also improved operational efficiency through intelligent automation. Response time decreased from 4.8 seconds to 1.6 seconds, while website processing speed improved from 3.9 seconds to 1.3 seconds. Automation efficiency increased from 58.30% to 93.75%, and manual intervention was reduced from 72.50% to 18.40%. User satisfaction improved significantly from 74.20% to 95.10% due to adaptive interfaces, personalized recommendations, and AI-powered chatbot communication. The recommendation system achieved an accuracy of 94.92%, while real-time decision-making accuracy increased to 92.88%. Cyber threat detection improved from 68.25% to 93.40%, demonstrating the effectiveness of Machine Learning-based anomaly detection and intelligent security monitoring. Resource utilization efficiency increased from 61.80% to 90.55%, and system reliability improved from 81.30% to 97.20%. The confusion matrix analysis further validated the superiority of the proposed intelligent automation framework by significantly reducing False Positives and False Negatives while improving classification accuracy and operational reliability. The integration of cloud computing infrastructure enabled scalable deployment, distributed processing, and real-time intelligent automation.
Bartanvi Punjabi Galap Da Alochanatmk Adhyan
“ਬਰਤਾਨਵੀ ਪੰਜਾਬੀ ਗਲਪ ਦਾ ਆਲੋਚਨਾਤਮਕ ਅਧਿਐਨ” ਇਸ ਖੋਜ ਦਾ ਮੁੱਖ ਉਦੇਸ਼ ਬਰਤਾਨੀਆ ਵਿੱਚ ਰਚੀ ਜਾ ਰਹੀ ਪੰਜਾਬੀ ਛੋਟੀ ਕਹਾਣੀ ਦੀ ਗਹਿਰੀ ਅਤੇ ਵਿਵਸਥਿਤ ਸਮਝ ਵਿਕਸਿਤ ਕਰਨਾ ਹੈ। ਇਸ ਅਧਿਐਨ ਵਿੱਚ ਬਰਤਾਨਵੀ ਪੰਜਾਬੀ ਗਲਪ ਦੇ ਇਤਿਹਾਸਕ ਵਿਕਾਸ, ਇਸ ਦੇ ਪ੍ਰਮੁੱਖ ਵਿਸ਼ਿਆਂ ਅਤੇ ਰਚਨਾਤਮਕ ਵਿਸ਼ੇਸ਼ਤਾਵਾਂ ਦਾ ਵਿਸਤ੍ਰਿਤ ਵਿਸ਼ਲੇਸ਼ਣ ਕੀਤਾ ਗਿਆ ਹੈ। ਪ੍ਰਵਾਸੀ ਜੀਵਨ ਦੇ ਅਨੁਭਵ, ਪਹਿਚਾਣ ਦਾ ਸੰਕਟ, ਸੰਸਕ੍ਰਿਤਿਕ ਦੋਹਰਾਪਣ, ਪੀੜ੍ਹੀ ਅੰਤਰ ਅਤੇ ਬਹੁ-ਸੰਸਕ੍ਰਿਤਿਕ ਸਮਾਜ ਦੇ ਪ੍ਰਭਾਵ ਨੂੰ ਕੇਂਦਰ ਵਿੱਚ ਰੱਖ ਕੇ ਚਰਚਾ ਕੀਤੀ ਗਈ ਹੈ। ਇਸ ਖੋਜ ਵਿੱਚ ਮੁੱਖ ਤੌਰ ‘ਤੇ ਦੂਜੇ ਸਰੋਤਾਂ ਅਤੇ ਚੁਣੀਂਦਾ ਕਹਾਣੀਆਂ ਦੇ ਪਾਠ-ਵਿਸ਼ਲੇਸ਼ਣ ਦੀ ਵਿਧੀ ਵਰਤੀ ਗਈ ਹੈ, ਜਿਸ ਨਾਲ ਗਲਪ ਦੀ ਅੰਦਰੂਨੀ ਬਣਤਰ ਅਤੇ ਅਰਥਧਾਰਾ ਨੂੰ ਸਮਝਣ ਵਿੱਚ ਮਦਦ ਮਿਲਦੀ ਹੈ। ਸਿਧਾਂਤਕ ਆਧਾਰ ਵਜੋਂ ਪ੍ਰਵਾਸੀ ਸਿਧਾਂਤ, ਉਪਨਿਵੇਸ਼ੋੱਤਰ ਦ੍ਰਿਸ਼ਟਿਕੋਣ ਅਤੇ ਸੰਸਕ੍ਰਿਤਿਕ ਮਿਲਾਪ ਦੀ ਧਾਰਨਾ ਨੂੰ ਅਪਣਾਇਆ ਗਿਆ ਹੈ, ਜੋ ਪ੍ਰਵਾਸੀ ਸਾਹਿਤ ਦੀ ਜਟਿਲਤਾ ਨੂੰ ਸਮਝਾਉਂਦੇ ਹਨ। ਇਹ ਅਧਿਐਨ ਦਰਸਾਉਂਦਾ ਹੈ ਕਿ ਬਰਤਾਨਵੀ ਪੰਜਾਬੀ ਗਲਪ ਪੰਜਾਬੀ ਸਾਹਿਤ ਨੂੰ ਵਿਸ਼ਵਿਕ ਪੱਧਰ ‘ਤੇ ਨਵੇਂ ਆਯਾਮ ਦਿੰਦਾ ਹੈ ਅਤੇ ਸੰਸਕ੍ਰਿਤਿਕ ਸੰਵਾਦ ਨੂੰ ਮਜ਼ਬੂਤ ਬਣਾਉਂਦਾ ਹੈ। ਇਸ ਤਰ੍ਹਾਂ, ਇਹ ਖੋਜ ਸਾਹਿਤਕ, ਸਮਾਜਿਕ ਅਤੇ ਸੰਸਕ੍ਰਿਤਿਕ ਦ੍ਰਿਸ਼ਟਿਕੋਣ ਤੋਂ ਇਸਦੀ ਮਹੱਤਤਾ ਨੂੰ ਉਜਾਗਰ ਕਰਦੀ ਹੈ।
The enhance personalized user interaction by incorporating contextual information such as conversational history, user preferences, emotional state, location, and behavioral patterns for adaptive and dynamic communication
This research focuses on enhancing personalized user interaction in intelligent chatbot systems by incorporating contextual information such as conversational history, user preferences, emotional state, location, and behavioral patterns for adaptive and dynamic communication. Traditional chatbot systems often suffer from poor contextual understanding, limited personalization, weak emotional adaptability, and inaccurate response generation, resulting in reduced user satisfaction and inefficient communication. To address these challenges, the proposed framework integrates Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and transformer-based NLP architectures such as BERT and GPT to improve semantic understanding, contextual reasoning, and personalized conversational response generation. The proposed system utilizes contextual memory management, sentiment analysis, behavioral prediction, and location-aware adaptation to create intelligent and human-like communication. Experimental evaluation demonstrates that the proposed Adaptive Context-Aware Hybrid Model significantly outperformed traditional conversational systems. The framework achieved 97.12% accuracy, 96.54% precision, 96.20% recall, and 96.37% F1-score. In addition, the system achieved 97.90% dialogue success rate, 98.10% personalization accuracy, and 98.25% user satisfaction score. The results confirm that integrating contextual computing and transformer-based conversational intelligence significantly improves adaptive communication, emotional understanding, dialogue continuity, and personalized interaction in intelligent chatbot systems.
Pharmacological evaluation of euphorbia hirta l. Leaves for the management of diabetes mellitus
This research utilized in vivo models to investigate the anti-diabetic properties of an extract from Euphorbia hirta leaves in rats that were induced with diabetes using streptozotocin. (Wistar albino rodents). Ethanol was collected, identified, and extracted from fresh leaves of Euphorbia hirta using the Soxhlet method. As per OECD guideline 423, the extract was deemed safe following an acute toxicity test that delivered doses as high as 2000 mg/kg body weight. No negative effects were observed. Animals received streptozotocin (50 mg/kg body weight) to create a diabetic state and were administered extracts of Euphorbia hirta (200 mg/kg and 400 mg/kg, respectively, for 21 days) to induce diabetes. Rats in the extracted group had greater weights than the diabetic control animals and exhibited significant enhancements in their fasting blood glucose levels. Several renal function markers, such as blood urea and serum creatinine, along with liver enzyme levels (SGOT and SGPT), demonstrated significant enhancement. Results from the histology of the pancreatic tissues demonstrated that the islets of Langerhans were more organised, and patients treated with extracts demonstrated partial β-cell regeneration, which was more effective at higher dosages. The results of the current experiment show that Euphorbia hirta has considerable antidiabetic, hypolipidemic, hepatoprotective, and nephroprotective properties and can be used to manage diabetes mellitus.
Regional Disparities In Agricultural Land Use, Cropping Intensity And Irrigation Development In Rajasthan
There are high regional disparities in agricultural development in Rajasthan, with regional differences in the use of land, the supply of irrigation and physical geography. The four indicators used in this study on regional differences in agriculture in Rajasthan are the percentage of land that is actually farmed compared to the total area, the percentage of that land that is farmed twice a year, the percentage of irrigated land compared to the total farmed land compared to the total area farmed. The results indicate a three-fold regional division, with higher agrarian development in the east and south-east (districts of Kota, Baran, Alwar and Bharatpur) due to rich agricultural soils and large-scale regulated irrigation; intermediate advancement in districts in the centre (such as Ajmer, Jaipur and Nagaur) with a transitional character; and lower development in west desert districts (Barmer, Jaisalmer and Churu) and south hilly/tribal districts (Udaipur, Pratapgarh and Sirohi). The analysis finds that the main factor causing differences in agricultural development is irrigation, with the canal-irrigated northwestern districts (Hanumangarh, Ganganagar) showing how human efforts can overcome environmental challenges. Cropping intensity and irrigation efficiencies are seen to be best in the eastern plains and very vast areas in the western and southern Rajasthan still depend on rainfall variability and subsistence agriculture. The paper highlights the relevance of locally based agricultural policies: irrigation in the arid areas, watersheds in tribal regions, and diversification in the well-developed agricultural regions to make it sustainable. The implications of these disparities are wider in terms of rural livelihoods, food security, and balanced socioeconomic development in the state than being limited to agriculture. A future study could be designed to incorporate changes over time, climate Analyse the effects of socio-economic factors, enhanced by GIS and first-hand surveys, to develop a comprehensive outlook on fair and sustainable agricultural development in Rajasthan.
लोक संगीत के संरक्षण एवं प्रचार-प्रसार में सांगीतिक आयोजनों की भूमिका : एक समीक्षात्मक अध्ययन।
लोक संगीत किसी भी समाज की सांस्कृतिक पहचान, परंपरा तथा सामूहिक चेतना का जीवंत प्रतीक होता है। भारतीय लोक संगीत में विविधता, क्षेत्रीयता, सामाजिक जीवन तथा सांस्कृतिक मूल्यों की गहरी छाप दिखाई देती है। बदलते समय, वैश्वीकरण, आधुनिक तकनीक तथा पाश्चात्य संगीत के बढ़ते प्रभाव के कारण लोक संगीत की परंपराएँ धीरे-धीरे प्रभावित हो रही हैं। ऐसे समय में सांगीतिक आयोजन लोक संगीत के संरक्षण एवं प्रचार-प्रसार के महत्वपूर्ण माध्यम के रूप में उभरे हैं। प्रस्तुत शोध पत्र में भोपाल की प्रसिद्ध “ताल कचहरी” के संदर्भ में लोक संगीत के संरक्षण एवं प्रचार-प्रसार में सांगीतिक आयोजनों की भूमिका का समीक्षात्मक अध्ययन किया गया है। ताल कचहरी मध्यप्रदेश की सांस्कृतिक पहचान का एक महत्वपूर्ण मंच है, जहाँ लोक संगीत, लोक नृत्य तथा पारंपरिक वाद्य कलाओं को संरक्षित एवं प्रोत्साहित किया जाता है। इस आयोजन ने न केवल स्थानीय कलाकारों को मंच प्रदान किया है, युवा पीढ़ी को भी लोक संस्कृति से जोड़ने का महत्वपूर्ण कार्य किया है। प्रस्तुत अध्ययन मुख्यतः द्वितीयक स्रोतों जैसे पुस्तकों, शोध पत्रों, सांस्कृतिक रिपोर्टों तथा समाचार पत्रों पर आधारित है। अध्ययन में यह स्पष्ट हुआ कि सांगीतिक आयोजन सांस्कृतिक विरासत के संरक्षण, नई प्रतिभाओं के विकास, सांस्कृतिक पर्यटन को बढ़ावा देने तथा सामाजिक समरसता स्थापित करने में अत्यंत प्रभावी भूमिका निभाते हैं।
कौशल्या धुर्वे, डॉ. वर्षा गोंटिया, डॉ. रवि कुमार पंडोले
A Comparative Analysis Of Polynomial And Non-Polynomial Spline Approximations In Solving Nonlinear Boundary Value Problems
This paper is a comparative study of the use of spline approximation (polynomial and non-polynomial) in solution of nonlinear two-point boundary value problems (TPBVPs). The study points out the drawbacks of classic cubic polynomial splines in dealing with nonlinearities, stiffness, and oscillativeness, and points out the greater flexibility and accuracy of non-polynomial splines, namely exponential and trigonometric formulations. Analytical analysis and numerical examples show that the exponential spline has superior results in nonlinear and stiff and trigonometric spline has superior results in oscillatory systems. The results validate the fact that non-polynomial splines have better convergence rates, lower error, and better computational stability over polynomial ones.
A Study on Digital Financial Behaviour, Behavioural Biases, and Investment Decision-Making specifically in Indore Region
The rapid expansion of digital financial services and fintech platforms has significantly transformed the financial behaviour of households in India. Increasing adoption of digital wallets, mobile banking, Unified Payments Interface (UPI), internet banking, and online investment platforms has changed the saving, spending, and investment patterns of middle-class households. However, despite greater access to financial information and digital financial services, household investment decisions continue to be influenced by behavioural biases and varying levels of financial risk tolerance. Behavioural finance explains that investors do not always behave rationally and are often affected by psychological, emotional, and social factors while making financial decisions. The present study aims to examine the influence of digital financial behaviour, behavioural biases, financial literacy, and risk tolerance on investment decision-making among middle-class households in the Indore region. The study focuses on major behavioural biases such as overconfidence bias, herd behaviour, loss aversion, anchoring bias, and mental accounting, and analyzes how these factors affect household investment preferences. The research further investigates the role of digital financial adoption in shaping investment diversification and participation in modern financial instruments. The study adopts a descriptive and analytical research design based on a quantitative research approach. Primary data are proposed to be collected through a structured questionnaire from middle-class households in the Indore region. Secondary data are collected from research journals, books, RBI reports, financial publications, and academic databases. Statistical tools such as descriptive statistics, reliability analysis, correlation analysis, regression analysis, factor analysis, ANOVA, and hypothesis testing are proposed to analyze the collected data. The findings of the study are expected to reveal that digital financial adoption positively influences financial participation and investment awareness among middle-class households. However, behavioural biases continue to significantly affect investment decisions, particularly in relation to risk perception and investment preferences. The study is also expected to indicate that financially literate households with higher risk tolerance are more likely to participate in market-linked investment avenues such as mutual funds and equity shares, whereas risk-averse households prefer safer investment options such as fixed deposits, insurance, and gold. The study contributes to the growing literature on behavioural finance and digital financial behaviour by providing region-specific insights into household investment behaviour in the Indore region. The findings may assist financial advisors, policymakers, fintech companies, and financial institutions in designing investor-oriented financial products, financial literacy initiatives, and awareness programs that promote rational investment behaviour and long-term financial stability among middle-class households.
Shanu Shah, Yash Sharma, Dr. Vijaya Jain, Dr. Sushil Beliya
उच्च शिक्षा के विद्यार्थियों में करियर निर्देशन एवं निर्णय क्षमता का अध्ययन
वर्तमान समय में उच्च शिक्षा प्राप्त कर रहे विद्यार्थियों के समक्ष करियर चयन एक महत्वपूर्ण चुनौती के रूप में उभरकर सामने आया है। उचित करियर निर्देशन के अभाव में अनेक विद्यार्थी अपने भविष्य संबंधी निर्णय लेने में कठिनाई अनुभव करते हैं। प्रस्तुत शोध-पत्र का उद्देश्य उच्च शिक्षा के विद्यार्थियों में करियर निर्देशन की भूमिका तथा उसकी निर्णय क्षमता पर प्रभाव का अध्ययन करना है। यह एक सैद्धांतिक अध्ययन है जिसमें द्वितीयक स्रोतों जैसे शोध-पत्रों, पुस्तकों एवं पत्रिकाओं का उपयोग किया गया है। अध्ययन से ज्ञात हुआ कि प्रभावी करियर निर्देशन विद्यार्थियों में आत्मविश्वास, निर्णय क्षमता तथा लक्ष्य निर्धारण की योग्यता को विकसित करता है। शोध के निष्कर्ष उच्च शिक्षा संस्थानों में व्यवस्थित करियर परामर्श सेवाओं की आवश्यकता को स्पष्ट करते हैं।
औपनिवेशिक भारत में महिला वं राष्ट्रवादी आंदोलन
भारत के स्वतंत्रता संग्राम में महिलाओं की भूमिका अत्यंत महत्वपूर्ण और निर्णायक रही है। ब्रिटिश औपनिवेशिक शासन से स्वतंत्रता प्राप्त करने के संघर्ष की दिशा को आकार देने में महिलाओं ने महत्वपूर्ण योगदान दिया। उन्नीसवीं शताब्दी के उत्तरार्ध से लेकर 1947 तक, भारत भर की महिलाओं ने प्रतिरोध के विभिन्न रूपों में भाग लिया, जिनमें राजनीतिक सक्रियता, क्रांतिकारी गतिविधियाँ और सामाजिक सुधार शामिल थे। यह शोध-पत्र महिलाओं की विविध भूमिकाओं की चर्चा करता है, जिनमें बेगम हजरत महल और भीकाजी कामा जैसी प्रारंभिक अग्रदूत महिलाओं के साथ-साथ सरोजिनी नायडू और कस्तूरबा गांधी जैसी अहिंसक आंदोलनों की प्रभावशाली हस्तियाँ भी सम्मिलित हैं। इसमें महिलाओं की क्रांतिकारी गतिविधियों में भागीदारी, असहयोग आंदोलन और सविनय अवज्ञा आंदोलन जैसे प्रमुख आंदोलनों में उनके नेतृत्व, तथा स्वतंत्रता के बाद भारत पर उनके स्थायी प्रभाव का विश्लेषण किया गया है। महिलाओं द्वारा निभाई गई इस महत्वपूर्ण भूमिका को उजागर करते हुए यह अध्ययन यह सिद्ध करता है कि राजनीतिक और सामाजिक दोनों क्षेत्रों में उनकी भागीदारी ने एक परिवर्तनकारी प्रभाव डाला, जिसने भारत की स्वतंत्रता-यात्रा और उसके बाद के विकास पर स्थायी विरासत छोड़ी।
दौसा जिले में पंचायती राज व्यवस्था और ग्रामीण बुनियादी ढाँचे के विकास का विश्लेषण
यह अध्ययन “ग्रामीण विकास एवं पंचायती राज: राजस्थान के दौसा जिले की ग्राम पंचायतों का समाजशास्त्रीय अध्ययन” शीर्षक से किया गया है, जिसका उद्देश्य यह आकलन करना है कि पंचायती राज व्यवस्था ग्रामीण बुनियादी ढाँचे और समग्र ग्रामीण विकास को किस सीमा तक प्रभावित करती है। यह शोध वर्णनात्मक एवं विश्लेषणात्मक स्वरूप का है और इसमें दौसा जिले के बसवा तथा बांदीकुई पंचायत क्षेत्रों की 10 ग्राम पंचायतों से 200 उत्तरदाताओं का चयन उद्देश्यपूर्ण प्रतिदर्श तकनीक के माध्यम से किया गया। प्राथमिक आंकड़े संरचित प्रश्नावली और व्यक्तिगत साक्षात्कार द्वारा एकत्र किए गए, जबकि द्वितीयक आंकड़ों के लिए शोध-पत्रों, सरकारी प्रतिवेदनों, पंचायती राज मंत्रालय के दस्तावेजों और संबंधित साहित्य का उपयोग किया गया। अध्ययन में वर्णनात्मक सांख्यिकी, पियर्सन सहसंबंध, रैखिक प्रतिगमन तथा संरचनात्मक समीकरण मॉडलिंग जैसी विधियों का उपयोग करके पंचायती राज, ग्रामीण बुनियादी ढाँचा विकास, सामाजिक परिवर्तन, आर्थिक सशक्तिकरण और महिला सशक्तिकरण के बीच संबंधों का परीक्षण किया गया। अध्ययन के निष्कर्ष दर्शाते हैं कि पंचायती राज व्यवस्था ग्रामीण बुनियादी ढाँचे के विकास में सकारात्मक और सांख्यिकीय रूप से सार्थक योगदान देती है। रिग्रेशन विश्लेषण से यह स्पष्ट हुआ कि पंचायतों की सक्रिय भूमिका सड़क, जलापूर्ति, विद्युतीकरण, स्वच्छता और संचार जैसी आधारभूत सुविधाओं के विकास को गति प्रदान करती है। साथ ही, यह व्यवस्था सामाजिक समावेशन, आर्थिक आत्मनिर्भरता और महिला सशक्तिकरण को भी प्रोत्साहित करती है। अध्ययन यह निष्कर्ष प्रस्तुत करता है कि यदि पंचायतों को पर्याप्त वित्तीय, प्रशासनिक और संस्थागत समर्थन दिया जाए, तो वे ग्रामीण विकास के सबसे प्रभावी माध्यम बन सकती हैं। अंततः, यह शोध दौसा जिले के संदर्भ में पंचायती राज को ग्रामीण भारत में सतत, समावेशी और सहभागी विकास की एक सशक्त संस्था के रूप में स्थापित करता है।
Ethical Considerations Of Euthanasia In The Bhagavad Gita
This paper explores the Bhagavad Gita, a revered holy book in Hindu philosophy, and its ethical considerations surrounding euthanasia. The deliberate taking of life to relieve suffering—euthanasia—presents difficult moral dilemmas in a variety of formal and social contexts. The Bhagavad Gita deeply integrates the concept of dharma, or obligation, with spiritual truths and moral principles. The book emphasizes how important it is to fulfil one's responsibilities and maintain a model lifestyle while also realizing that life is temporary and that death is inevitable. Euthanasia raises questions regarding the harmony between compassion, nonviolence (ahimsa), and the preservation of life in this particular situation. Analysing significant passages from the Bhagavad Gita provides insight into different perspectives on suffering, dying, and the moral implications of intervening in everyday life. The Bhagavad Gita's ethical reflections on euthanasia invite thoughtful analysis of the nuances of moral duty, the value of life, and the pursuit of liberation from the grip of human suffering. This paper emphasizes the relevance of ancient wisdom in addressing modern ethical conundrums involving end-of-life care and the decision to pass on.
भारतीय धर्म तथा संस्कृति के स्वरूप को जानने के लिए पुराणों का अनुषीलन अत्यन्त आवश्यक है। पुराण भारतीय साहित्य का गौरव ग्रन्थ है। प्राचीनकाल से ही भारतवर्ष में पुराणों का पठन-पाठन एंव श्रवण मनन होता आया है। सामान्य भारतीय के हृदयतल में ज्ञान, भक्ति, श्रद्धा, वैराग्य, सदाचरण तथा धर्म-परायणता के उत्तम तत्त्वों का संस्कार पुराणों ने ही प्रतिष्ठित किया है। पुराणों के विषय में वेदव्यास ने तो स्कन्दपुराण में यहाँ तक कह दिया कि जो वेदों में नहीं देखा गया, जो स्मृतियों में भी नहीं देखा गया तथा जो दोनों में नहीं देखा गया, वे सब भी पुराणों में सन्निहित है।
A Deep Learning-Based Framework for Smart Home Energy Consumption Forecasting
The global transition toward sustainable energy systems and the proliferation of smart home technologies have made efficient energy management a critical objective. Central to this goal is the accurate forecasting of residential energy consumption, which empowers both consumers and utilities to optimize energy use, reduce costs, and enhance grid stability. This paper proposes a comprehensive, deep learning-based framework for energy consumption forecasting in smart homes, designed to overcome the inherent challenges of highly variable, non-linear, and privacy-sensitive data. The methodology involves a comparative analysis of established forecasting models, including traditional statistical methods like ARIMA and cutting-edge deep learning architectures such as Long Short-Term Memory (LSTM) and Convolutional Neural Network-LSTM (CNN-LSTM) hybrids. The framework incorporates a robust data pipeline, encompassing meticulous data preprocessing, domain-specific feature engineering, and rigorous model evaluation using a multi-metric approach. The analysis synthesizes findings from recent studies, demonstrating that advanced deep learning models consistently outperform traditional methods by effectively capturing complex temporal patterns and dependencies in energy usage data. The report also provides a nuanced examination of the trade-offs between model complexity, computational demands, and predictive accuracy, revealing that simpler models, such as K-Nearest Neighbors (KNN), can be a competitive and robust alternative in data-scarce environments. This research underscores the vital role of predictive analytics in enabling dynamic demand-side management and ensuring the effective integration of renewable energy sources. It also highlights the growing importance of privacy-preserving techniques like Federated Learning to foster a more secure and sustainable energy future.
Aayush Sharma, Kishore S, Mohit Kumar Pathak, Dr. Ankita Awasthi
Investigating Generative Artificial Intelligence Usage And Investment Performance Efficiency Among Retail Investors In Coimbatore District
This paper investigates the level of the Generative Artificial Intelligence (GenAI) application and its effect on the efficiency of retail investors investment performance in Coimbatore District. The research design will be descriptive and analytical and will be built on the primary data obtained in 200 individuals using a structured questionnaire. The results indicate that GenAI has got a massive adoption, especially among younger and technologically savvy investors who use these applications in the stock market analysis, portfolio management, financial news briefing, and making informed decisions. The findings suggest that a large share of investors thinks that they are performing better in their investments, primarily because they have better analytical tools, faster access to information they need, and fewer reliance on the old forms of advisory services. Nonetheless, the paper also emphasizes the fact that GenAI does not always guarantee higher financial returns because there were investors who did not see any significant increase or even decrease in its performance, which might be explained by the excessive use of AI, the lack of understanding, or the volatility of the markets. The discussion also indicates that GenAI represents a strong decision-support system; however, its performance is highly reliant on the user knowledge, experience as well as strategic implementation. On the whole, the research adds to the existing knowledge about the changing role of the AI in retail investment behavior and the necessity to balance the use of the technological tools with effective financial decision-making in terms of achieving the best possible investment results.
G.Flora Shantha Kumari, Dr. P. S. Selva Tharangini
An Efficient Deep Learning Framework for ECG and EEG Signal Classification in Embedded Healthcare Systems
Biomedical signal classification has become an important area of research in modern healthcare because ECG and EEG signals provide valuable information about the functional condition of the heart and the brain. ECG signals are widely used for detecting arrhythmia, abnormal heartbeat, myocardial infarction, and other cardiovascular disorders, while EEG signals are useful for identifying epileptic seizures, brain activity patterns, sleep disorders, and neurological abnormalities. However, manual interpretation of ECG and EEG signals is difficult, time-consuming, and dependent on expert knowledge because these signals are nonlinear, time-varying, and affected by noise and artifacts. To overcome these limitations, this paper presents an efficient deep learning framework for ECG and EEG signal classification in embedded healthcare systems. The proposed framework focuses on automated signal preprocessing, feature learning, classification, and embedded deployment. Deep learning models such as CNN, RNN, LSTM, and hybrid CNN-LSTM are suitable for learning spatial and temporal patterns from biomedical signals. CNN models can extract important waveform features, while LSTM models can learn time-based dependencies in sequential ECG and EEG data. The framework also emphasizes lightweight model design, model optimization, quantization, and pruning so that the trained model can be deployed on embedded healthcare devices with limited memory, processing power, and battery capacity. Integration with wearable ECG and EEG systems, IoT-based healthcare platforms, and edge computing can enable real-time monitoring, faster diagnosis, and immediate alert generation in critical conditions such as arrhythmia and epileptic seizure. This study highlights that deep learning-based ECG and EEG classification can support smart healthcare, remote patient monitoring, telemedicine, and preventive diagnosis. The proposed approach can assist healthcare professionals by reducing manual workload, improving diagnostic consistency, and providing early detection of cardiovascular and neurological abnormalities.
Historical Evolution And Cultural Identity Of The Mankirdias Tribe: A Socio-Anthropological Study
This present study attempts to explore the history, socio-cultural characteristics and the cultural identity of the Mankirdias tribe from a socio-anthropological perspective. The Mankirdias are a PVTG in Odisha and have a unique cultural heritage characterized by forest culture, occupations, belief systems and social practices. The tribe relies on the environment for survival, making use of the forests and the animals, with particular focus on monkey catching, hunting, gathering, and rope making, which has led to a distinctive social structure and cultural identity. The study explores their history, social structure, kinship system, marriage practices, language, traditional stories, beliefs, music, dance, economy and traditional lifestyle. It also delves into the effects of modernization, migration, deforestation, educational backwardness, health problems, and social isolation on the tribal community. It shows that while modernization has opened up avenues for education, employment, and social mobility, it has also led to a decrease in traditional professions and a decline in indigenous knowledge systems, and loss of cultural identity. However, the Mankirdias have been able to maintain an important part of their traditions, rituals, and community values. The study highlights the importance of sustainable development policies, cultural preservation efforts, educational inclusion, healthcare enhancement, and the protection of tribal rights, all of which contribute to the socio-economic development and cultural sustainability of the Mankirdias tribe.
Impact of british colonial rule on agrarian relations in north odisha during the nineteenth and twentieth centuries
The agrarian structure of north Odisha has witnessed a number of changes during the 19th and 20th centuries owing to the colonization of the region by the Britishers. Before the period of colonization, the agrarian economy of the north Odisha region operated through the traditional systems of land ownership, community-based farming practices, and dependence of tribals on forest and nature. The setting up of British rule in the region has led to a number of land revenue policies that resulted in strengthening the role of zamindars and made land a source of private taxable property. This resulted in the weakening of the existing agrarian organizations, indebtedness of the peasantry, and alienation of land. The forest policy followed by the British further aggravated the position of the tribes by limiting their access to forest and practicing shifting cultivation. This exploitative system of agrarian relations created conditions of poverty, inequality, and uncertainty for the villagers, especially during the period of famine and agricultural depression. Gradually, agrarian unrest was integrated into the national struggle of India and played an important role in developing rural political awareness in the region of Odisha. The research explores how the British colonization affected agrarian relations in the North Odisha region.
PORTRAYAL OF MOTHERHOOD IN MODERN LITERATURE
Motherhood has long occupied a privileged place in literary imagination. It has been represented as tenderness, sacrifice, origin, moral authority and emotional continuity, yet modern literature repeatedly questions the simplicity of such representations. This thesis, titled Portrayal of Motherhood in Modern Literature, examines the changing image of the mother in selected modern literary texts and argues that motherhood is not merely a biological function or sentimental ideal but a complex social, cultural and psychological construct. The major finding of the study is that modern literature transforms the mother from an idealized figure into a more complex and human subject. Modern texts do not simply reject motherhood; rather, they challenge the ideological uses of motherhood that demand silence, obedience and self-erasure from women. The mother in modern literature becomes a site where love and power, body and culture, freedom and duty, memory and trauma are brought into conflict. By reading motherhood through feminist and psychoanalytic frameworks, the thesis contributes to a deeper understanding of women's representation in modern literature and highlights the continuing importance of maternal identity in literary and cultural studies.
Religious architecture has always occupied a special place in Indian social and political life. Temples, stupas, mosques, churches, gurudwaras and sacred complexes are not only places of worship; they are also visible expressions of identity, memory, moral order and public culture. In India, the built form of religion has repeatedly interacted with political authority, community organization and ideas of legitimacy. This thesis examines that relationship through a case study of Birla Mandir, Bhopal, popularly known as Lakshmi Narayan Temple. The main argument of the study is that Birla Mandir is not merely a devotional structure but also a symbolic public space. It represents a form of cultural identity that connects religion, philanthropy, urban memory, tourism, public rituals and political culture. The study uses historical, descriptive and analytical methods. It draws on theories of political culture, symbolic politics, secularism, cultural nationalism and the social meaning of architecture. The thesis concludes that religious architecture can contribute to cultural integration and civic participation when it remains open, ethical and socially inclusive; however, it can also become politically contested if reduced to a narrow instrument of mobilization.
Image-Based Deep Learning Approach for Crop Disease Detection: A Schematic Review
Crop diseases significantly affect agricultural productivity, food quality, and economic stability worldwide. Early and accurate detection of plant diseases is essential for reducing crop losses and improving agricultural sustainability. Traditional disease identification methods mainly rely on manual inspection by agricultural experts, which is time-consuming, labor-intensive, and often inaccurate under large-scale farming conditions. In recent years, image-based deep learning techniques have emerged as powerful tools for automated crop disease detection due to their high accuracy, feature extraction capability, and real-time analysis performance. This schematic review presents a comprehensive overview of image-based deep learning approaches used for crop disease detection and classification. The study discusses various deep learning architectures, including Convolutional Neural Networks (CNN), Transfer Learning models, Recurrent Neural Networks (RNN), and hybrid deep learning frameworks applied to plant disease identification using leaf images. The review also highlights different stages involved in disease detection such as image acquisition, preprocessing, segmentation, feature extraction, classification, and performance evaluation. Publicly available datasets, data augmentation techniques, and evaluation metrics such as accuracy, precision, recall, and F1-score are also analyzed. Furthermore, the paper discusses the advantages, limitations, and challenges associated with deep learning-based crop disease detection systems, including dataset imbalance, environmental variations, computational complexity, and real-time deployment issues. The study concludes that image-based deep learning approaches have significant potential for developing intelligent and automated agricultural monitoring systems capable of improving crop health management and sustainable farming practices.
इतिहासलेखन में राव तुलारामः औपनिवेशिक और राष्ट्रवादी दृष्टिकोण का तुलनात्मक अध्ययन
यह विस्तृत शोध-पत्र 1857 के विद्रोह के संदर्भ में राव तुलाराम के इतिहासलेखन का गहन एवं आलोचनात्मक विश्लेषण प्रस्तुत करता है। अध्ययन का मुख्य उद्देश्य यह समझना है कि औपनिवेशिक और राष्ट्रवादी इतिहासकारों द्वारा एक ही ऐतिहासिक व्यक्तित्व को किस प्रकार भिन्न-भिन्न दृष्टिकोणों से प्रस्तुत किया गया है। औपनिवेशिक लेखन में राव तुलाराम को एक क्षेत्रीय विद्रोही और अस्थिरता उत्पन्न करने वाले नेता के रूप में चित्रित किया गया, जबकि राष्ट्रवादी इतिहासकारों ने उन्हें एक वीर, दूरदर्शी और राष्ट्रभक्त नेता के रूप में स्थापित किया। यह शोध इन दोनों दृष्टिकोणों के वैचारिक आधार, स्रोतों के उपयोग, और उनके राजनीतिक उद्देश्यों का विश्लेषण करते हुए यह तर्क प्रस्तुत करता है कि एक संतुलित इतिहासलेखन के लिए बहु-स्रोत और आलोचनात्मक दृष्टिकोण आवश्यक है।
Political Dimensions of Regionalism and Pathways Toward Inclusive Development
Regionalism has become a significant political, social and economic phenomenon affecting governance and development all over the world. It is associated with the aspirations of regions regarding their representation, culture, economic development, and autonomous administration. The present review paper discusses the political dimension of regionalism and its relationship with inclusive development in the international as well as in Indian scenario. The current research explores various dimensions of regionalism like political regionalism, economic regionalism, cultural regionalism, cooperative regionalism, competitive regionalism, separatist regionalism and developmental regionalism. Furthermore, different theories such as Federalism Theory, Identity Politics Theory, Dependency Theory, Decentralization Theory, and New Regionalism Theory are discussed in the research. The research also highlights the historical evolution of regionalism in various regions of the world like Europe, Africa, Latin America, South Asia, and India with respect to linguistic identity, sub-nationalism, regional parties, and demand for autonomy. It is essential to discuss the concept of inclusive development and its importance through social justice approach, human development perspective and participatory governance strategy. Literature findings reveal that regionalism could contribute to balanced regional growth, decentralization and social inclusion in the process of development when it is governed in an effective manner through sound policies. On the other hand, extreme regionalism could lead to challenges like separatism and political fragmentation.
रोहतक नगर में पेय जल संकट: एक विष्लेषणात्मक अध्ययन
तेजी से बढ़ता शहर जब पानी के लिए जूझने लगे, तब समस्या केवल जल की नहीं, बल्कि व्यवस्था की बन जाती है। यह अध्ययन हरियाणा के रोहतक नगर में जल-अभाव की वास्तविक स्थिति को समझने का प्रयास करता है। शोध पूर्णतः द्वितीयक आँकड़ों पर आधारित है, जिसमें जनसंख्या वृद्धि, जल आपूर्ति क्षमता, प्रति व्यक्ति जल उपलब्धता तथा आपूर्ति-माँग अंतर का विश्लेषण किया गया है। शोध परिणाम दर्शाते हैं कि यद्यपि नगर में स्थापित जल आपूर्ति क्षमता संख्यात्मक रूप से पर्याप्त प्रतीत होती है, फिर भी वितरण हानि, नहर आधारित निर्भरता, शहरी विस्तार और भू-जल की खराब गुणवत्ता के कारण कार्यात्मक जल-अभाव बना हुआ है।
“Development and Characterization of Polyphenol-Loaded Chitosan Nanoparticles from Coffea arabica and Evaluation of Antioxidant Activity”
Polyphenol nanocarriers from Coffea arabica were processed byionotropic gelation with chitosan to enhance natural polyphenol's therapeutic efficacy. Hydroalcoholic extract Hydroalcoholic extraction was performed and total phenolic content of the extract was found to be 185 mg GAE/g supplement, thus high amount of active phenolic contents were present in the extracts (Folin-Ciocalteu method). Chitosan nanoparticles were fabricated using the ionotropic gelation technique with chitosan and sodium tripolyphosphate (TPP). We designed three different formulations (F1-F3) according to the concentration of the polymers and the cross-linkers. The developed nanoparticles were characterized for entrapment efficiency, particle size, polydispersity index and zeta potential. The entrapped efficiency increased from 72% to 81% in the case of F3 where the maximum encapsulated efficiency was noted. In the optimized formulation, there is a reduction in particle size from 178 nm to 128 nm with higher uniformity and stability. The alysis showed a biphasic nature with sustained release characteristics as long as 24 hours, as seen with the in-vitro release profile. DPPH radical scavenging activity demonstrated that the nanoformulation exhibited higher antioxidant activity than the crude extract, with maximal inhibition at 94.7%. The data clearly elaborates about the effectiveness of nanoencapsulation in improving Coffea arabica polyphenols physicochemical properties as well as antioxidant potential. The nanoformulation prepared can be considered as a new modality to enhance the functional delivery of natural bioactive compounds.
An Analytical Study Of Facial Expression Recognition Using Convolutional Neural Networks For Enhanced Classification Accuracy
Facial Expression Recognition (FER) has become an important field in artificial intelligence and computer vision because of its various applications in intelligent systems, security, healthcare and human–computer interaction (HCI). A quantitative analytical approach was used with facial image datasets which had emotional categories such as Happy, Sad, Angry, Surprise, Fear, Disgust and Neutral. The study comprised steps such as image preprocessing, developing CNN model, evaluating the model and implementation of optimization techniques. Results showed that the proposed CNN model gives maximum accuracy while training (97.2%), while validation (95.8%) and testing (95.1%) accuracy were the highest, which means that it has a better recognition ability. The results from the expression-wise analysis revealed that highest accuracy of recognition was obtained for Happy and Surprise expression while comparatively lower recognition rate was obtained in Fear and Disgust. The results also showed that feature extraction methods, data quality, and optimization techniques like transfer learning and data augmentation greatly improved the classification results. The results of the study show that the optimized CNN based approaches can be used to recognize facial expression with better classification accuracy with an efficient and reliable solution.
Dave Nikhil Yogeshbhai, Dr. Sankarsan Panda
Educational Discontinuity Among Displaced Adolescent Girls In Manipur
The issue of educational discontinuity is now one of the biggest humanitarian and educational challenges in the conflict affected areas of Manipur with regard to adolescent girls. This is the first study to look at how displacement affects the continuity in education, participation in schooling, and access to learning materials for adolescent girls in relief camps and temporary shelters. The research design that was used for the study was mixed methods – descriptive and exploratory research with both primary and secondary data sources. Structured questionnaires and semi-structured interviews were used to gather primary data from the following groups: displaced adolescent girls, teachers, NGO workers and parents. The study indicated that conflict-induced displacement had a significant impact on school attendance, attendance at examinations, study time, and access to learning materials. The most significant drivers of educational interruption of girls in the context of displacement were found to be economic hardship, psychological trauma, insecurity and insufficient education infrastructure. The study also found that higher rates of conflict intensity were associated with higher dropouts and irregular attendance rates, when compared with districts with lower conflict intensity. Lack of adequate digital access, limited counselling services, and gender insensitivity of educational facilities in relief camps further exacerbated educational exclusion. The study showed that temporary learning facilities, psychosocial support, financial assistance, digital inclusion, and inclusive educational rehabilitation policies are needed to ensure uninterrupted education for adolescent girls who are displaced. The study highlighted that continuity of education is crucial to empower, socially include and promote long-term development of displaced adolescent girls in Manipur.
Analytical Study Of Secondary Metabolites In Medicinal Plant Species
Biologically active chemicals with important therapeutic and pharmacological characteristics can be found in medicinal plants. This study set out to examine the secondary metabolites found in a number of medicinal plant species, such as Withania somnifera (Ashwagandha), Curcuma longa (Turmeric), Aloe vera, Azadirachta indica (Neem), and Ocimum sanctum (Tulsi). Various secondary metabolites, including alkaloids, flavonoids, tannins, phenols, terpenoids, saponins, glycosides, and steroids, were identified using qualitative and quantitative phytochemical investigations that utilised standard analytical and spectrophotometric procedures. The findings showed that various plant species have significantly varied metabolite compositions. Withania somnifera revealed a greater alkaloid content linked with key therapeutic activity, while Curcuma longa showed the highest concentration of phenols and flavonoids, indicating considerable antioxidant potential. Medical plants, according to the research, include a wide variety of phytochemical components that have antibacterial, antioxidant, anti-inflammatory, and therapeutic consequences. In addition to demonstrating the significance of medicinal plants as natural sources for pharmaceutical and therapeutic uses, the results provide scientific backing for their traditional use.
Optimization Accuracy of Distributed Denial of Service Attacks in Cybersecurity based on Machine Learning
Distributed Denial of Service (DDoS) attacks remain one of the most disruptive threats in modern cybersecurity, causing severe service outages and financial losses across networked systems. This study presents an optimized machine learning-based framework for the accurate detection and classification of DDoS attacks using four widely adopted algorithms: Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and Extreme Gradient Boosting (XGBoost). The proposed approach emphasizes improving detection accuracy through effective data preprocessing, feature selection, and model tuning techniques. A benchmark network traffic dataset is utilized, where features are normalized and transformed to enhance model performance. Comparative analysis is conducted using key evaluation metrics, including training accuracy, testing accuracy, precision, and recall, to ensure robust and unbiased assessment. Experimental results demonstrate that ensemble-based models, particularly Random Forest and XGBoost, significantly outperform traditional methods such as Logistic Regression and Decision Tree in terms of accuracy and generalization capability. Among all models, XGBoost achieves the highest detection accuracy with improved precision and recall, indicating its effectiveness in handling complex and imbalanced traffic patterns. The findings highlight the importance of optimized machine learning techniques in strengthening intrusion detection systems and mitigating DDoS threats in real-time environments. This research contributes to the development of intelligent, scalable, and efficient cybersecurity solutions capable of enhancing network resilience against evolving attack vectors.
ग्रामीण हरियाणा से शहरी क्षेत्रों की ओर प्रवासन और सामाजिक-आर्थिक परिवर्तनः एक ऐतिहासिक अध्ययन
हरियाणा राज्य की स्थापना 1 नवम्बर 1966 को हुई। राज्य गठन के समय इसकी सामाजिक और आर्थिक संरचना मुख्यतः ग्रामीण तथा कृषि-आधारित थी। हरित क्रांति, सिंचाई सुविधाओं का विस्तार, उच्च उपज वाले बीजों का प्रयोग, कृषि यंत्रीकरण, सड़क एवं विद्युत सुविधाओं का विकास और राष्ट्रीय राजधानी दिल्ली से निकटता ने हरियाणा की अर्थव्यवस्था को नई दिशा प्रदान की। कृषि उत्पादन में वृद्धि के साथ-साथ उद्योग, परिवहन, व्यापार, निर्माण और सेवा क्षेत्रों का विस्तार हुआ। इस बदलती आर्थिक संरचना ने ग्रामीण जनसंख्या, विशेषकर भूमिहीन श्रमिकों, छोटे किसानों, शिक्षित युवाओं और रोजगार की तलाश करने वाले परिवारों को शहरी क्षेत्रों की ओर आकर्षित किया। 1966 से 2000 तक ग्रामीण हरियाणा से शहरों की ओर प्रवासन केवल रोजगार की खोज तक सीमित नहीं रहा, बल्कि इसने ग्रामीण समाज के पारिवारिक संबंधों, कृषि व्यवस्था, आय-स्रोतों, महिलाओं की भूमिका, शिक्षा संबंधी आकांक्षाओं, उपभोग-व्यवहार और सामाजिक गतिशीलता को भी प्रभावित किया। 1991 की जनगणना के अनुसार हरियाणा की कुल जनसंख्या में ग्रामीण जनसंख्या 75.37 प्रतिशत थी, जबकि शहरी जनसंख्या लगभग 24.63 प्रतिशत थी। 1999-2000 के हरियाणा आर्थिक सर्वेक्षण में स्पष्ट किया गया कि राज्य की अर्थव्यवस्था में प्राथमिक क्षेत्र का हिस्सा घट रहा था, जबकि विनिर्माण और सेवा क्षेत्रों का योगदान बढ़ रहा था। यही आर्थिक परिवर्तन ग्रामीण से शहरी प्रवासन की ऐतिहासिक पृष्ठभूमि तैयार करता है। यह शोध-पत्र 1966 से 2000 तक की अवधि में ग्रामीण हरियाणा से शहरी क्षेत्रों की ओर प्रवासन के कारणों, स्वरूप, सामाजिक-आर्थिक प्रभावों और नीतिगत प्रयासों का ऐतिहासिक विश्लेषण प्रस्तुत करता है।
Adjustment of Secondary School Students in Relation to Gender and Types of School
The present study investigates the adjustment of secondary school students in relation to gender and type of school. Adjustment is an important aspect of adolescent development as it influences emotional stability, social relationships, educational performance, and overall personality development. The study aimed to compare emotional, social, educational, and overall adjustment among male and female students as well as government and private school students. The descriptive survey method was employed for conducting the study. A sample of 400 secondary school students from Haryana state was selected through random sampling technique, including students from both government and private schools. The Adjustment Inventory developed by Sinha and Singh (2022 Rewised) was used for collecting data. Statistical techniques such as mean, standard deviation, and t-test were applied for data analysis. The findings of the study revealed that no significant differences existed between male and female students and between government and private school students in emotional, social, and overall adjustment. However, significant differences were found in educational adjustment. Female students were better adjusted educationally than male students, and private school students demonstrated better educational adjustment than government school students. The study highlights the importance of providing supportive educational environments and guidance services to improve adjustment among adolescents.
A bibliometric analysis on training, effectiveness and efficiency
This study presents a bibliometric analysis of academic research on training, effectiveness, and efficiency. The study examines literature obtained from major academic databases such as Scopus and Web of Science, using keywords including “training,” “effectiveness,” “efficiency,” “training effectiveness,” and “training efficiency.” The main objective of the study is to understand how training programs influence employee knowledge, skills, work efficiency, productivity, and overall organizational performance. The reviewed literature indicates that effective training plays a significant role in improving employee motivation, commitment, performance, and long-term organizational success. The bibliometric results show a noticeable increase in publications after 2020, reflecting growing academic interest in digital learning, technological advancement, artificial intelligence, and performance-based training evaluation. Country-wise analysis highlights the United States, China, and India as major contributors to this research area. The document type analysis shows that journal articles are the dominant medium of scholarly communication, followed by conference papers and review articles. The study also reveals that training effectiveness and efficiency are no longer limited to human resource management, but have expanded into education, healthcare, technology, sustainability, and organizational studies. Overall, this study maps the growth, publication trends, major contributors, research domains, and future directions of training-related research.
Comparative Performance Analysis Of Machine Learning And Deep Learning Models For Nse Stock Market Prediction
The ever-changing and unpredictable nature of financial markets makes examination of stock market predictions an attractive topic for research in finance analytics and artificial intelligence. Predicting the NSE stock market using ML/DL methods is the focus of this research. When making predictions, many models were employed, such as decision tree (DT), random forest (RF), Support Vector Machine (SVM), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU). The data set included information on the starting and closing prices as well as the highest and lowest prices, as well as the volume of trades. Before being used for modelling, the data in the database underwent cleaning, normalisation, and feature selection. We used Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and prediction accuracy to measure each model's performance. The experiment's findings demonstrate that when it comes to stock market prediction, deep learning (DL) models perform better than machine learning (ML) models. When compared to other models, the Transformer model provided the most accurate predictions and the smallest discrepancy between the actual and anticipated values, making it the clear winner for effective prediction.
Thanki Rajesh Harilal, Dr. Krushnadeo T. Belerao
Influence of Agricultural Technology Adoption on Sustainable Agricultural Development in Chopra Tehsil, Uttar Dinajpur District, West Bengal
Agriculture remains the principal source of livelihood in Chopra Tehsil of Uttar Dinajpur District, West Bengal. The increasing demand for food security, environmental protection, and economic sustainability has intensified the need for technological innovations in agriculture. The present study investigates the influence of agricultural technology adoption on sustainable agricultural development in the study area. A qualitative research approach was employed, and primary data were collected from 251 farmers through interviews, discussions, and field observations. The study examined the level of technology adoption, perceived benefits, challenges, and the overall contribution of agricultural technologies toward sustainability. The findings revealed that 59.76% of respondents exhibited high to very high levels of agricultural technology adoption. Increased crop productivity (29.48%) emerged as the most significant benefit, followed by improved farm income (24.70%). High initial investment costs (27.49%) and limited access to credit facilities (23.11%) were identified as the major barriers. Furthermore, 66.53% of respondents perceived a high or very high impact of technology adoption on sustainable agricultural development. The study concludes that technological interventions significantly contribute to productivity enhancement, efficient resource utilization, environmental sustainability, and rural livelihood improvement. Policy measures focusing on training, extension services, and financial support are essential for accelerating sustainable agricultural development in Chopra Tehsil.
Effect of Digital Payment Systems on Financial Management Practices.
The widespread adoption of digital payment systems has transformed the financial landscape by facilitating efficient, secure, and transparent transactions. This qualitative study explores the influence of digital payment systems on financial management practices among business organizations. Data were collected through semi-structured interviews with 25 business owners, financial managers, and accounting professionals. Thematic analysis was employed to identify recurring patterns and insights. The findings reveal that digital payment systems significantly improve cash flow monitoring, financial transparency, record management, decision-making efficiency, and business sustainability. However, concerns regarding cybersecurity risks, technological barriers, and digital literacy challenges remain prevalent. The study concludes that digital payment technologies play a vital role in strengthening organizational financial management and promoting sustainable business operations.
समावेशी शिक्षा के प्रति शिक्षकों की अभिवृत्ति एवं चुनौतियों का अध्ययन।
समावेशी शिक्षा वर्तमान वैश्विक शैक्षिक परिदृश्य का एक महत्वपूर्ण आयाम है, जिसका मूल उद्देश्य प्रत्येक शिक्षार्थी को उसकी व्यक्तिगत, सामाजिक, आर्थिक, भाषाई अथवा शारीरिक भिन्नताओं के बावजूद समान शैक्षिक अवसर प्रदान करना है। प्रस्तुत अध्ययन का उद्देश्य समावेशी शिक्षा के प्रति शिक्षकों की अभिवृत्तियों तथा इसके क्रियान्वयन में आने वाली चुनौतियों का विश्लेषण करना है। अध्ययन में मात्रात्मक शोध पद्धति का उपयोग किया गया। 120 शिक्षकों का चयन सरल यादृच्छिक प्रतिचयन विधि द्वारा किया गया। आंकड़ों के संकलन हेतु स्वनिर्मित प्रश्नावली का प्रयोग किया गया। प्राप्त आंकड़ों का विश्लेषण प्रतिशत, माध्य एवं मानक विचलन के माध्यम से किया गया। अध्ययन के निष्कर्षों से ज्ञात हुआ कि अधिकांश शिक्षक समावेशी शिक्षा के प्रति सकारात्मक अभिवृत्ति रखते हैं, किन्तु संसाधनों की कमी, विशेष प्रशिक्षण का अभाव, कक्षा में विद्यार्थियों की अधिक संख्या तथा प्रशासनिक सहयोग की कमी जैसी चुनौतियाँ इसके प्रभावी क्रियान्वयन में बाधक हैं। अध्ययन यह सुझाव देता है कि समावेशी शिक्षा की सफलता के लिए शिक्षकों को निरंतर व्यावसायिक प्रशिक्षण, पर्याप्त संसाधन एवं संस्थागत सहयोग प्रदान किया जाना आवश्यक है।
Determinant Of Childhood Immunization Dropout Rates
Routine childhood immunization is one of the most effective public health interventions for preventing vaccine-preventable diseases, reducing child morbidity and mortality, and strengthening population immunity. However, children who begin vaccination but fail to complete the recommended schedule remain vulnerable to measles, diphtheria, pertussis, tetanus, polio, hepatitis B, Haemophilus influenzae type b, rotavirus and other preventable conditions. Immunization dropout is a sensitive indicator of continuity of care and programme follow-up. The present thesis was undertaken to assess determinants of childhood immunization dropout rates among children aged 12-23 months, with special attention to maternal education, socioeconomic status, birth order, migration, distance from session site, antenatal care, institutional delivery, immunization card retention, caregiver knowledge, reminder systems and health-service barriers. An analytical community-based cross-sectional study approach was used. The study population included caregivers of children aged 12-23 months from selected urban, peri-urban and rural field practice areas. Data were collected using a structured questionnaire, immunization card review, maternal and child protection card verification and health-system assessment. Data were analysed using frequencies, percentages, chi-square tests, odds ratios and multivariable logistic regression. A p value less than 0.05 was considered statistically significant. Among 300 children included in the analysis, 84 children were classified as dropout and 216 children had completed age-appropriate immunization. The overall dropout proportion was 28.0%. Higher dropout was observed among children of mothers with no formal or primary education, low socioeconomic status, higher birth order, rural or peri-urban residence, distance more than 5 km from session site, fewer than four antenatal visits, home delivery, unavailability of MCP card, low caregiver knowledge, absence of ASHA/ANM reminders, vaccine session cancellation, fear of adverse events and recent migration.
Arbaj, Dr. Priyanka Tiwari, Sanjeev Sharma
Knowledge, Attitude, and Preventive Practices Regrading Dengue Fever Among Urban Households
Dengue fever is a major mosquito-borne viral disease of public health importance in tropical and subtropical regions. It is transmitted primarily by infected female Aedes mosquitoes and is closely associated with urban and semi-urban environments, household water storage and community-level vector control behaviour.1,2 Although municipal services and clinical management remain important, prevention ultimately depends on household knowledge, risk perception, attitude toward source reduction and regular preventive practices. A community-based cross-sectional study design was used among 200 urban households. Data were collected through a structured questionnaire containing sociodemographic details, household environmental characteristics, knowledge items, attitude statements and preventive practice questions. Scores were classified into good, moderate and poor levels for knowledge and practices, and favourable, neutral and unfavourable levels for attitude. Descriptive statistics, chi-square tests and correlation analysis were applied. Among 200 respondents, 38.0% had good knowledge, 44.0% had moderate knowledge and 18.0% had poor knowledge. A favourable attitude was observed in 57.5% of respondents, while good preventive practices were reported by 36.0%. Covered water storage, weekly drying of containers, use of mosquito repellents and removal of stagnant water were common practices, but gaps remained in larval source identification, daytime biting awareness and sustained community participation.
Pushpendra Deshmukh , Dr. Priyanka Tiwari
Valuation Of Hospital Management Practices In The Prevention And Control Of Gastroenteritis Outbreaks
Gastroenteritis outbreaks in hospitals can produce rapid patient-to-patient and staff-to-patient transmission, disrupt routine services, increase expenditure on isolation and cleaning, and threaten vulnerable groups such as children, elderly patients and immunocompromised patients. Hospital management practices, including surveillance, hand hygiene, environmental cleaning, safe food and water systems, staff training and a defined outbreak response plan, are therefore central to prevention and control. A descriptive cross-sectional evaluative design was planned among healthcare workers and selected hospital service areas. Data were organised through a structured questionnaire, infection control observation checklist, hospital record review checklist and outbreak preparedness assessment tool. Key domains included knowledge of gastroenteritis outbreaks, hand hygiene, environmental cleaning, waste management, food and water safety, reporting systems, training status, isolation practices and emergency preparedness. Descriptive statistics, chi-square tests and domain-wise percentage scoring were used for analysis. The thesis presents a complete analytical framework with tables and figures for a planned sample of 120 healthcare workers. The model findings indicate that 34.2% of participants had good knowledge, 50.8% had moderate knowledge and 15.0% had poor knowledge regarding gastroenteritis outbreaks. Training was associated with better infection control practice. Hand hygiene and reporting practices were found to be comparatively weaker domains than waste segregation and basic PPE use. Preparedness gaps were observed in line listing, specimen referral planning and interdepartmental communication.
Diabetes Disease Analysis of Smart Healthcare System using Data Mining and Machine Learning
Diabetes is one of the most prevalent chronic diseases worldwide and poses significant challenges to healthcare systems due to its increasing incidence and associated complications. Early detection and accurate diagnosis are essential for effective disease management and reducing healthcare costs. This study presents a Diabetes Disease Analysis of Smart Healthcare System using Data Mining and Machine Learning techniques. The proposed framework utilizes healthcare data containing various clinical and physiological parameters such as glucose level, blood pressure, body mass index (BMI), insulin level, age, and family history. Data preprocessing techniques including data cleaning, normalization, and feature selection are applied to improve data quality and model performance. Various machine learning algorithms such as Logistic Regression, Support Vector Machine (SVM), Random Forest, Decision Tree, and XGBoost are employed for diabetes prediction and classification. The performance of these models is evaluated using metrics such as accuracy, precision, recall, F1-score, and confusion matrix. Experimental results demonstrate that ensemble-based approaches achieve superior predictive accuracy compared to conventional classifiers. The integration of data mining and machine learning within a smart healthcare environment enables efficient disease analysis, early risk identification, and decision support for healthcare professionals. The proposed system can assist in proactive diabetes management, improve patient outcomes, and contribute to the development of intelligent healthcare monitoring solutions.
Impact of Socioeconomic Status on Oral Health Seeking Behaviour
Oral health is an integral component of general health, nutrition, communication, self-esteem and quality of life. Oral diseases are common, largely preventable and frequently untreated because symptoms are normalized until pain or functional limitation occurs. Socioeconomic status influences oral health seeking behaviour through income, education, occupation, residence, affordability, health literacy, transport, insurance coverage and perceived need. Individuals from lower socioeconomic groups may postpone dental visits, depend on self-medication or seek care only when pain becomes severe, whereas persons with better resources may be more likely to attend routine or preventive dental services. A community-based analytical cross-sectional design was used. The study population consisted of 300 adults selected from urban and peri-urban communities. Data were collected using a structured questionnaire covering sociodemographic profile, socioeconomic status, oral health awareness, self-reported oral symptoms, dental service utilization, delay in seeking care, perceived barriers and type of facility used. The findings showed that lower socioeconomic status was associated with delayed dental consultation, problem-oriented visits, self-medication and no professional care. Cost of treatment, distance from dental facility, lack of awareness, dental anxiety and absence of insurance coverage were more frequent barriers among lower socioeconomic groups. Preventive or routine dental visits increased with higher education, higher income and better oral health awareness.
Public Health Strategies to Prevent and Reduce The Misuse of Steroids in Bodybuilding Communities
The misuse of anabolic-androgenic steroids (AAS) and other appearance and performance enhancing drugs has expanded from elite sport into recreational gyms, bodybuilding spaces and social media-driven fitness cultures. AAS are medically useful in selected conditions, but non-medical use for muscularity or performance is associated with endocrine, cardiovascular, hepatic, psychiatric and infectious risks. Because bodybuilding communities are shaped by peer norms, trainer influence, product availability, body image pressure and limited trusted health services, the problem requires a public health approach rather than only an anti-doping or punitive approach. A gym-based analytical cross-sectional study framework was used. The study population comprised 300 bodybuilding and strength-training participants from selected fitness centres. A structured questionnaire assessed demographic profile, training history, motivation, peer influence, social media exposure, knowledge, perceived harm, health-seeking behaviour and willingness to use prevention services. Data were tabulated by self-reported lifetime AAS misuse status and analysed using descriptive statistics, chi-square test and odds ratio. A p value less than 0.05 was considered statistically significant. Among 300 participants, 90 were categorized as the self-reported AAS misuse group and 210 as the non-misuse group. Misuse was strongly associated with longer training experience, competition-oriented goals, peer influence, informal trainer advice, high social media exposure, low knowledge of adverse effects, low perceived harm and body image dissatisfaction. The strongest associations were observed for body image dissatisfaction, low perceived harm, informal advice and peer influence.
Chemical Analysis of Packaged Drinking Water
Packaged drinking water is widely consumed because it is convenient, portable and generally perceived to be safer than untreated local water sources. Its safety, however, depends on the quality of source water, treatment efficiency, packaging hygiene, storage conditions and routine chemical monitoring. The present thesis focuses on chemical analysis of packaged drinking water with emphasis on organoleptic, physicochemical and selected chemical parameters relevant to public health and regulatory compliance. A laboratory-based analytical study format was used. Sealed PET bottles and 20 litre jar or can samples were arranged as two comparison groups. Samples were coded, observed for physical acceptability and analysed by standard water-analysis procedures. Results were summarized by mean, standard deviation, independent samples t-test and chi-square analysis for selected quality categories. The thesis-format observation matrix showed that all included sample values remained within the major referenced limits used for interpretation, but 20 litre jar or can samples demonstrated higher mean TDS, hardness, chloride, nitrate and turbidity than sealed PET bottle samples. Statistical comparison supported a significant difference between the two categories for several parameters, indicating that packaged water should not be judged only by visual clarity or sealed appearance.
Generation and Optimization of Ultrafast Terahertz (THZ) Radiation using Femtosecond Lasers
Terahertz radiation occupies the electromagnetic region between the microwave and infrared bands and is widely used in time-domain spectroscopy, material characterization, imaging and ultrafast control experiments. The availability of stable femtosecond laser systems has made it possible to generate coherent single-cycle and few-cycle THz pulses through photoconductive switching, optical rectification, plasma generation and spintronic emission. However, THz output is highly sensitive to pump pulse duration, fluence, repetition rate, focusing geometry, nonlinear medium, antenna structure, phase matching, absorption and detection alignment. An analytical and parameter-sweep based research design was prepared. The optimization framework considered photoconductive antenna emission and nonlinear optical rectification as the principal source pathways, with comparative discussion of air plasma and spintronic sources. Input variables included laser wavelength, pulse duration, pump fluence, beam size, antenna bias, crystal type, crystal thickness, pulse-front tilt, collection optics and detection method. The analysis showed that femtosecond laser pulse duration and pump fluence are dominant parameters for bandwidth and output amplitude, while velocity matching and absorption determine the usable interaction length in optical rectification. Photoconductive antennas are suitable for compact broadband laboratory systems at moderate field strength, whereas tilted pulse-front lithium niobate is advantageous for high-field, lower-frequency single-cycle output.
Mechanical Performance of Hybrid Fiber Reinforced High-Strength Concrete Incorporating Steel, Coir and Palm Fibers
The growing demand for sustainable and high-performance construction materials has encouraged the development of hybrid fiber reinforced concrete incorporating both natural and synthetic fibers. This study investigates the mechanical performance of hybrid fiber reinforced high-strength concrete (HFRHSC) incorporating steel, coir, and palm fibers. An M50 grade concrete mix containing 10% silica fume as a partial cement replacement was developed, and seven different fiber combinations were evaluated. The experimental program included workability, compressive strength, split tensile strength, and flexural strength tests conducted at 28 days. The results indicated that the inclusion of hybrid fibers improved the mechanical properties of high-strength concrete, although workability decreased with increasing fiber content. Among all mixes, the hybrid combination containing 0.5% steel fiber, 0.25% coir fiber, and 0.25% palm fiber (M4) exhibited the best overall performance. The compressive strength increased from 58.2 MPa for the control mix to 71.1 MPa, representing an increase of approximately 22.2%. Similarly, the split tensile strength increased from 4.61 MPa to 6.42 MPa, while the flexural strength improved from 6.12 MPa to 7.91 MPa, corresponding to increases of 39.3% and 29.2%, respectively. The enhanced performance was attributed to the synergistic action of steel fibers providing crack-bridging capability and natural fibers improving energy absorption and crack resistance. The study demonstrates that the combined use of steel, coir, and palm fibers can significantly enhance the mechanical properties of high-strength concrete and offers a sustainable solution for structural applications requiring improved strength and durability.
MICROSTRUCTURAL ANALYSIS AND SUSTAINABILITY ASSESSMENT OF GLASS POWDER BASED GEOPOLYMER PASTE
The present study investigates the microstructural characteristics of geopolymer paste containing Fly Ash (FA), Ground Granulated Blast Furnace Slag (GGBFS), and waste Glass Powder (GP). Glass powder was incorporated at replacement levels of 5%, 10%, 15%, and 20% to evaluate its influence on geopolymer gel formation and matrix densification. Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS) analyses were conducted under ambient and elevated temperature curing conditions. SEM analysis revealed that incorporation of glass powder improved the compactness and homogeneity of geopolymer paste by reducing porosity and microcracks. The geopolymer mix containing 15% glass powder exhibited the densest matrix formation. EDS analysis confirmed increased silicon and calcium-rich geopolymer gel formation with increasing glass powder content. The Si/Al ratio increased from 2.14 for the control mix to 2.87 for the mix containing 15% glass powder, indicating enhanced geopolymerization. The study demonstrates that waste glass powder can be effectively utilized as a sustainable supplementary precursor material for improving the microstructural performance of geopolymer paste while contributing toward sustainable construction and waste management practices.
Comparison of Rehabilitation Protocols After Rotator Cuff Repair Surgery: Case Study
Background: Rotator cuff repair surgery is commonly performed to restore shoulder strength, reduce pain, and improve functional use of the upper limb after symptomatic tendon tear. Postoperative rehabilitation is essential because the repaired tendon must be protected while stiffness, muscle inhibition, scapular dyskinesis, and fear of movement are gradually addressed. Two widely used rehabilitation strategies are an early controlled motion protocol and a delayed protective motion protocol. Early controlled motion emphasizes protected passive range, scapular control, pain-free mobility, and timely progression to active assisted exercise. Delayed protective motion prioritizes tendon healing, sling compliance, inflammation control, and slower progression before active loading. Clinical comparison at the case level is useful because the balance between mobility and protection varies with tear size, tissue quality, pain irritability, patient confidence, and surgical precautions. Presentation of Cases: This comparative case study presents two adults following arthroscopic rotator cuff repair for symptomatic full-thickness supraspinatus-dominant tears. Case A followed an early controlled motion protocol, whereas Case B followed a delayed protective motion protocol. Both patients were medically stable, had surgeon clearance for physiotherapy, and participated in a twelve-week supervised rehabilitation schedule with comparable therapist contact and home instruction. Baseline assessment included pain, active and passive shoulder range of motion, scapular posture, sling tolerance, sleep disturbance, fear of movement, hand-to-mouth ability, overhead activity readiness, and functional use during grooming, dressing, household work, and occupational tasks. Intervention: The early controlled motion case received education, sling use outside exercise periods, pendulum activity, passive flexion and external rotation within repair limits, scapular setting, thoracic mobility, distal joint mobility, gradual active assisted elevation, low-load isometrics, closed-chain proprioceptive drills, and later progressive strengthening. The delayed protective motion case received prolonged sling protection, pain and swelling control, supported positioning, elbow-wrist-hand exercises, gentle scapular retraction, breathing and posture work, delayed passive mobility, cautious active assisted motion, and slower strengthening progression. Progression criteria were based on pain response, range tolerance, repair precautions, movement quality, and ability to complete home exercises safely. Outcome Measures: Recovery was documented using the Numeric Pain Rating Scale, Shoulder Pain and Disability Index, American Shoulder and Elbow Surgeons score, Quick Disabilities of the Arm, Shoulder and Hand score, goniometric range of motion, manual muscle testing, handheld dynamometer screening, scapular observation, sleep tolerance, and a functional activity log developed for this case comparison. Results: Both protocols improved shoulder pain, mobility, strength, and daily function. The early controlled motion case demonstrated faster gains in passive and active range, earlier confidence during grooming and table-level tasks, and quicker reduction in stiffness. The delayed protective motion case demonstrated better early comfort, fewer flare-ups, stronger adherence to tendonprotection precautions, and gradual but steady gains after the immobilization phase. At twelve weeks, both patients improved on impairment and activity-level outcomes. Early controlled motion produced slightly greater improvement in range-dependent activities, while delayed protective rehabilitation produced a steadier pain profile and greater movement security during the early healing period. Conclusion: The comparative findings suggest that early controlled motion may be useful when pain is controlled and stiffness risk is high, whereas delayed protective rehabilitation may be preferable when tissue protection, pain irritability, or apprehension are dominant concerns. Individualized progression is essential after rotator cuff repair. Keywords: Rotator cuff repair, shoulder rehabilitation, early controlled motion, delayed protective protocol, arthroscopic repair, physiotherapy, shoulder function, tendon healing.
Effectiveness of Cranial base Release and Gong's Mobilization in the Management of Text Neck Syndrome: A Case Study
Background: Text neck syndrome is a postural and movement-related cervical condition commonly associated with prolonged smartphone, laptop, and tablet use. Sustained lower cervical flexion with upper cervical extension increases load on the posterior cervical soft tissues, encourages forward head posture, reduces cervical extension tolerance, and may produce suboccipital pain, headache, upper trapezius tightness, and disability in daily work. Manual therapy is often used when pain, muscle guarding, and joint restriction prevent active correction. Cranial base release is directed toward reducing suboccipital tightness, improving cranio-cervical mobility, calming protective muscle tone, and restoring a more comfortable head-on-neck relationship. Gong's mobilization is a specific mobilization approach directed toward cervical extension mechanics, facet gliding, and correction of forward head posture through a controlled passive movement strategy. Presentation of Case: This case study describes a 26-year-old female office employee and postgraduate student who presented with four months of posterior neck pain, heaviness around the suboccipital region, intermittent frontal headache, reduced cervical extension, and difficulty using a mobile phone and laptop for prolonged periods. She reported eight to ten hours of screen exposure per day, frequent use of a handheld phone with neck flexion, and poor ergonomic awareness during online work. Baseline assessment showed forward head posture, rounded shoulders, tenderness in suboccipital muscles, upper trapezius and levator scapulae tightness, reduced active cervical range of motion, reduced deep neck flexor endurance, and functional limitation in reading, typing, driving, and sleeping. Intervention: The patient received a four-week supervised physiotherapy programme consisting of cranial base release, Gong's mobilization, pain-free cervical mobility training, postural correction, deep neck flexor activation, scapular stabilization, pectoral stretching, ergonomic education, and a home exercise schedule. Treatment was provided five sessions per week, approximately forty minutes per session. Cranial base release was applied initially to decrease guarding and suboccipital overactivity. Gong's mobilization was then used to improve cervical extension, joint glide, and tolerance to upright head position. Exercise and activity modification were progressed according to pain response, movement quality, and functional tolerance. Outcome Measures: Pain was recorded with the Numeric Pain Rating Scale. Cervical disability was assessed with the Neck Disability Index. Cervical range of motion was measured by goniometric and inclinometer-based clinical assessment. Forward head posture was documented through craniovertebral angle observation. Deep neck flexor endurance, muscle tenderness, sleep disturbance, work tolerance, and patient-specific functional activity scores were recorded at baseline, week two, and week four. Results: After four weeks, pain reduced from 7/10 to 2/10, Neck Disability Index improved from 42 percent to 12 percent, craniovertebral angle improved from 40 degrees to 49 degrees, cervical extension increased from 32 degrees to 58 degrees, and deep neck flexor endurance increased from 10 seconds to 31 seconds. The patient reported improved sitting tolerance, less headache frequency, better sleep, reduced upper trapezius tightness, and greater awareness of neutral screen posture. No adverse response was reported during or after treatment. Conclusion: The combined use of cranial base release and Gong's mobilization was associated with reduction of pain and disability, improvement in cervical posture, and better functional tolerance in a patient with text neck syndrome. The findings support the use of manual therapy followed by corrective exercise and ergonomic retraining when suboccipital tightness, forward head posture, and cervical extension limitation are prominent.
Effects of Glute Activation Exercises on Low Back Pain in Office Workers with Gluteal Amnesia: Case Study
Background: Low back pain is highly common among office workers because prolonged sitting, low physical activity, poor lumbopelvic control, and repetitive static postures place sustained mechanical demand on the lumbar spine. Gluteal amnesia refers to delayed, reduced, or poorly coordinated activation of the gluteus maximus and gluteus medius during hip extension, pelvic stabilization, gait, squatting, stair climbing, and sit-to-stand activity. When the gluteal muscles fail to contribute efficiently, the lumbar extensors, hamstrings, tensor fascia lata, and hip flexors may compensate, leading to increased lumbar loading, anterior pelvic tilt, altered hip mechanics, and recurrent pain. Glute activation exercises are used to restore neuromuscular awareness, improve hip extension strategy, enhance pelvic control, and reduce unnecessary lumbar overuse during functional movement. Presentation of Cases: This case study presents two adult office workers with mechanical low back pain and clinical features consistent with gluteal amnesia. Both worked more than seven hours daily in sitting, reported repeated episodes of pain after prolonged computer work, and demonstrated weak or delayed glute activation during prone hip extension, bridge holding, single-leg support, and sit-to- stand assessment. Case A presented with dominant gluteus maximus inhibition, hamstring overactivity, and extension-related lumbar discomfort. Case B presented with gluteus medius weakness, pelvic drop, dynamic knee valgus, and pain during stairs and prolonged standing. Both cases were medically stable and participated in a six-week supervised physiotherapy programme with progressive home practice. Intervention: The intervention included education regarding sitting breaks and neutral spine awareness, low-load glute setting, supine bridge progression, prone hip extension with abdominal bracing, clamshells, side-lying hip abduction, band-resisted lateral walk, quadruped hip extension, hip hinge training, sit-to-stand retraining, step-up control, and work-related movement practice. Exercise intensity was progressed according to pain response, quality of activation, endurance, and ability to avoid lumbar substitution. Both cases were monitored for symptom irritability and fatigue. Outcome Measures: Pain intensity, disability, strength, activation timing, movement control, and work tolerance were documented using the Numeric Pain Rating Scale, Oswestry Disability Index, manual muscle testing of gluteus maximus and medius, prone hip extension observation, single-leg bridge endurance, Trendelenburg assessment, sit-to-stand quality, sitting tolerance record, and a therapist-maintained functional task log. Results: At six weeks both office workers showed reduction in pain, improvement in gluteal strength, better pelvic control, and increased tolerance for sitting and daily activity. Case A improved markedly in hip extension pattern, bridge endurance, and reduction of lumbar extensor dominance. Case B showed stronger improvement in frontal-plane pelvic stability, stair confidence, and single- leg control. Pain decreased from moderate-severe to mild levels in both cases, and disability shifted from moderate limitation to minimal functional restriction. The greatest functional changes were noted in prolonged sitting, rising from a chair, walking after office hours, stair use, and confidence during household activity. Conclusion: Glute activation exercises were associated with meaningful improvement in low back pain, hip muscle performance, and functional tolerance in office workers with gluteal amnesia. The findings support a progressive programme that begins with isolated neuromuscular activation and advances toward task-based hip control.
Multi-level inverters for Renewables and Industrial Drives Applications
The electric power system in a sustainable future will augment the centralized and large grid dependent system of today with distributed smart grid based energy generation system. To achieve this world is increasingly adopting renewable energy sources e.g. solar, wind, tidal and fuel cells. The expanded utilization of power electronic devices has expanded the pressure on power system as it prompts generation of voltage and current harmonics and it additionally builds the reactive current. These days, power electronic devices are utilized by the ventures for some, reasons like variable voltage, variable frequency and current control so as to get accurate controllability, better and higher proficiency, quicker reaction and in particular to make the devices compact in estimate.
Ravi Kumar Prajapati, Anjana Tripathi, Balram Yadav
The Role of Women in Early English Literature
This study examines the role of women in early English literature with special reference to Anglo-Saxon and medieval English texts. It investigates how women are represented as queens, peace-weavers, mothers, wives, saints, temptresses, rulers, rebels, silent figures, and speaking subjects. The study begins with the historical and social background of early England and then analyses major literary traditions, including heroic poetry, religious writing, courtly love, and Chaucerian narrative. Special attention is given to Beowulf, where women such as Wealhtheow, Hildeburh, and Grendel's mother reveal the political and emotional dimensions of heroic society. The study also examines medieval literature, especially Chaucer's Wife of Bath, as a major voice of female experience, authority, and resistance. Through qualitative and textual analysis, the study argues that women are not marginal figures in early English literature. They are central to the construction of social order, moral meaning, kinship, spiritual value, and literary debate. The study further shows that early literature contains both patriarchal limitations and early signs of gender critique. Female characters often appear within restrictive conventions, yet they also expose contradictions in male authority and contribute significantly to the development of English literary tradition.
भिंड जिले के वस्त्र उद्योग में सामाजिक वाणिज्य का उपभोक्ता संतुष्टि पर प्रभाव: जागरूकता, विश्वास एवं अनुमानित लाभों का विश्लेषणात्मक अध्ययन
यहशोधपत्र भिंड जिले के वस्त्र उद्योग में सामाजिक वाणिज्य का उपभोक्ता संतुष्टि पर प्रभाव का अध्ययन करता है। इस अध्ययन में 400 उत्तरदाताओं से संरचित प्रश्नावली के माध्यम से प्राथमिक समंक एकत्र किए गए। अध्ययन के तीन प्रमुख स्वतंत्र चर हैं: सामाजिक वाणिज्य की जागरूकता, प्लेटफार्मों पर विश्वास, तथा अनुमानित लाभ; जबकि आश्रित चर उपभोक्ता संतुष्टि है। विश्वसनीयता विश्लेषण (क्रोनबेक अल्फा: .872 से .953) ने प्रश्नावली की उच्च विश्वसनीयता सिद्ध करती। पियर्सन सहसंबंध विश्लेषण द्वारा सभी छः परिकल्पनाओं का परीक्षण किया गया। परिणामों से स्पष्ट हुआ कि अनुमानित लाभ (r = 0.743), विश्वास (r = 0.715) तथा जागरूकता (r = 0.682) का उपभोक्ता संतुष्टि से महत्वपूर्ण सकारात्मक संबंध है। निष्कर्षतः सामाजिक वाणिज्य प्लेटफार्मों ने भिंड जिले के वस्त्र उपभोक्ताओं के क्रय व्यवहार और संतुष्टि स्तर को सकारात्मक रूप से प्रभावित किया है।
Influencer Role in Marketing: An Indian Perspective
India possesses a unique connection with social media. A significant portion of the population is now online due to affordable data plans, cost-effective smartphones, and platforms that cater to various languages. Digital advertising is often encountered for the first time by many of them. As a result, influencer marketing has grown rapidly because it seamlessly fits into everyday conversations and originates from voices the audience trusts. This paper examines two aspects of influencer marketing strategy, namely (i) what builds trust and (ii) what undermines trust. This paper carries out a survey of 250 social media users belonging to the academic and industry domains and aged between 18 and 35. The aim of this survey-based investigation is to examine how influencers affect purchase decisions, what makes them credible, and how different types perform across India’s diverse market. Further, in order to understand why some influential relationships succeed while others fail, this paper utilizes Source Credibility Theory, Parasocial Interaction Theory, and Congruity Theory. A number of key patterns emerge from the findings that support the effectiveness of influencer marketing. Authenticity is found to be the strongest driver of trust (cited by 76% of respondents), compared to 34% for follower count. Micro-influencers are found to outperform celebrities in terms of trust and engagement, especially in Tier 2 and Tier 3 cities. Notably, a sufficiently high number of respondents (58%) reported making a purchase based on an influencer’s recommendation. Furthermore, the study identifies a number of key barriers to influencing marketing strategy, including poor disclosure practices, fake engagement, excessive promotion, and cultural reversals. In general, Indian influencer marketing is found to be effective due to its alignment with traditional reliance on trusted recommendations. However, this trust is generally fragile in nature. Credibility is found to deteriorate generally when authenticity is substituted with excessive commercialization or disguised advertising. Overall, we conclude in this paper that long-term success depends less on reach and more on trust, and once lost, that trust is hard to rebuild.
DIGITAL TRANSFORMATION AND STRATEGIC MANAGEMENT IN ORGANIZATIONS
The study on “Digital Transformation and Strategic Management in Organizations” examines how the adoption of digital technologies influences strategic decision-making, organizational performance, and competitive advantage. Digital transformation refers to the integration of advanced technologies such as artificial intelligence, cloud computing, big data analytics, and automation into business processes, while strategic management focuses on formulating and implementing long-term organizational strategies. The study highlights that digital transformation has become a key driver of organizational success in the modern business environment. It improves operational efficiency, enhances customer experience, supports data-driven decision-making, and fosters innovation. However, despite high levels of adoption, many organizations fail to fully achieve expected benefits due to challenges such as poor data quality, lack of skilled workforce, high implementation costs, and weak strategic alignment.
STRATEGIC MANAGEMENT OF LITERACY OUTCOMES: IMPLEMENTING THE B.E.S.T. FRAMEWORK TO ENHANCE ENGLISH PROFICIENCY IN DUAL-CURRICULUM PRIMARY EDUCATION
The study on Strategic Management of Literacy Outcomes: Implementing the B.E.S.T. Framework to Enhance English Proficiency in Dual-Curriculum Primary Education focuses on improving English language skills among primary learners through structured instructional strategies. English proficiency is essential in dual-curriculum systems, but learners often face challenges such as limited exposure to English, language barriers, and inconsistent teaching practices. The study uses a descriptive and quantitative research design based on secondary data from educational reports and classroom-based assessments. It analyzes key language skills including reading, writing, speaking, listening, and vocabulary using percentage-based comparative methods. The findings show significant improvement in all English language skills after implementing the B.E.S.T. framework, with speaking and writing showing the highest progress. The framework’s components such as structured teaching, basic skills development, engagement in learning, and continuous assessment contribute effectively to student achievement. Interactive teaching methods like group activities, phonics, storytelling, and digital tools further enhance student participation and learning outcomes. However, challenges such as lack of trained teachers, limited English exposure, and insufficient learning resources still exist. Despite these limitations, the study confirms that the B.E.S.T. framework significantly improves literacy outcomes when supported by proper strategic management. Overall, it concludes that structured educational interventions play a vital role in enhancing English proficiency in dual-curriculum primary education.
Algorithmic Governance And The Transformation Of Administrative Law In The Digital State
The rapid advancement in artificial intelligence, machine learning, and big data technology has dramatically impacted public administration and led to the concept of algorithmic governance. With an increased number of governmental institutions applying algorithms in the process of social service distribution, taxes' collection, police activities, and migration control, etc., more and more efforts have been made by various states to ensure that algorithmic decision-making would become efficient and effective. However, with growing reliance on artificial intelligence, legal and constitutional concerns arise regarding issues of transparency, accountability, fairness, privacy, and adherence to the rule of law. In view of the aforementioned problem, this paper aims at investigating how algorithmic governance affects the core concepts of administrative law and whether the existing legal system is equipped to deal with modern digital challenges. Specifically, using the approach to doctrinal and analytical research of legal problems, the research will examine constitutional rules, administrative law principles, case law, and other legislative acts regarding this issue in India, EU member-states, the United States, and the UK. Among others, such problems as administrative discretion, natural justice, accountability, transparency, equality, privacy, and procedural justice will be analyzed in relation to algorithmic governance. Moreover, certain recent judicial developments concerning the use of algorithms in public administration and the regulation of AI will be discussed within this paper. Therefore, it should be concluded that despite providing many advantages to modern administration, algorithmic governance remains legitimate only when appropriate laws and regulations exist.
शहरी भारत में पारिवारिक संरचना में परिवर्तन और समाजीकरण पर उसका प्रभाव
यह शोध शहरी भारत में पारिवारिक संरचना में हो रहे परिवर्तनों तथा उनके समाजीकरण पर पड़ने वाले प्रभावों का अध्ययन प्रस्तुत करता है। अध्ययन का मुख्य उद्देश्य यह समझना है कि किस प्रकार संयुक्त परिवार से एकल परिवार की ओर बदलाव सामाजिक, नैतिक और भावनात्मक विकास को प्रभावित कर रहा है। इस शोध में वर्णनात्मक एवं विश्लेषणात्मक अनुसंधान डिज़ाइन का उपयोग किया गया है तथा 200 परिवारों से प्राप्त आंकड़ों का विश्लेषण किया गया है। प्राथमिक डेटा प्रश्नावली, साक्षात्कार और सर्वेक्षण के माध्यम से एकत्र किया गया, जबकि द्वितीयक डेटा विभिन्न पुस्तकों, शोध पत्रों और सरकारी रिपोर्टों से प्राप्त किया गया। अध्ययन में Random एवं Stratified Sampling तकनीक का उपयोग किया गया ताकि विभिन्न सामाजिक-आर्थिक वर्गों का प्रतिनिधित्व सुनिश्चित किया जा सके। परिणामों से पता चलता है कि 70% उत्तरदाता एकल परिवार में रहते हैं, जबकि 30% संयुक्त परिवार में। पारिवारिक परिवर्तन के प्रमुख कारणों में रोजगार (35%), आर्थिक कारण (25%), शिक्षा (22.5%) और व्यक्तिगत स्वतंत्रता (17.5%) शामिल हैं। समाजीकरण में विद्यालय (30%) और सोशल मीडिया (27.5%) प्रमुख माध्यम पाए गए। 67.5% उत्तरदाताओं ने बताया कि माता-पिता के पास बच्चों के लिए पर्याप्त समय नहीं है, जिससे बच्चों के व्यवहार में आत्मनिर्भरता बढ़ी (45%), लेकिन अनुशासन में कमी और भावनात्मक दूरी भी देखी गई। पारंपरिक मूल्यों में गिरावट (47.5%) और आधुनिक मूल्यों में वृद्धि (35%) स्पष्ट रूप से दर्ज की गई। निष्कर्षतः यह कहा जा सकता है कि पारिवारिक संरचना में आए परिवर्तन समाजीकरण की प्रक्रिया को गहराई से प्रभावित कर रहे हैं, जिसमें सकारात्मक और नकारात्मक दोनों प्रभाव शामिल हैं।
Resilience Across the Lifespan: Conceptual Developments, Protective Factors, and Future Directions
Resilience has emerged as one of the most influential constructs in contemporary psychology, reflecting the capacity of individuals to adapt successfully despite adversity, stress, and life challenges. Originally conceptualized as an exceptional quality possessed by a select group of individuals, resilience is now understood as a dynamic developmental process shaped by interactions between personal characteristics, social relationships, and environmental resources. The growing interest in resilience research reflects its relevance to mental health promotion, prevention of psychopathology, and enhancement of well-being across the lifespan. The present review examines the conceptual evolution of resilience, explores major protective factors associated with resilient functioning, and discusses resilience across different developmental stages including childhood, adolescence, young adulthood, and later adulthood. The review further highlights the role of resilience within positive psychology and mental health frameworks while identifying important gaps and future directions in resilience research. Existing evidence suggests that resilience is influenced by multiple interacting systems, including cognitive abilities, emotional regulation, social support, family functioning, optimism, and coping skills. Furthermore, resilience appears to contribute significantly to psychological well-being, adaptive functioning, and successful adjustment throughout life. The review concludes that resilience represents a critical target for intervention and mental health promotion efforts and emphasizes the need for culturally sensitive and longitudinal investigations, particularly within developing countries such as India.