Volume 14 | Issue 2 |

 Abstract

Ayurveda is the ancient health science which has glorious past and bright future. It comprises many dimensions about health of human being. Ayurveda is a science of life. The main aim of Ayurveda is to maintain health in healthy persons and cures diseases in diseased persons. The life style of the people of modern era has changed due to rapid urbanization. Due to changed work expectations for better life style, stress is causing increased incidence of acute and chronic disorders. Ardhavabhedaka is one of the chronic illness, which is wide spread in the population with varying severity. Many chronic diseases which cannot be treated properly by other medical sciences, or there are side effects of the medicine or recurrence of the disease, those diseases were well treated by Ayurveda principles and medicines. Ayurveda has a variety of natural medication in the treatment of Ardhavabhedaka. Very elaborative treatment has been given in Ayurvedic Samhitas; especially Panchakarma offers significant relief in this disease. Ardhavabhedaka is best treated with Panchakarma like Shiro Virechana, Kaya Virechana, Nadisveda, Niruha and Anuvasana, Basti, Upanaha and Shiro Basti. Nasa is nearest root to alleviate the disease of head. Ayurvedic therapeutics especially Nasya karma has attracted considerable glamour for providing safe and effective remedies in the treatment of Ardhavabhedaka.

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 Keywords

Ayurveda, Ardhavabhedak, Migraine, Panchkarma

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Artificial Intelligence (AI) is disruptive in forensic science; it leads to precision, effectiveness, and authenticity of criminal investigation. Although classical forensic approaches are efficient, they are faced with many barriers, such as human mistakes and limited time. Using AI algorithms (i.e. machine learning, predictive analytics, facial recognition, and natural language processing), forensic scientists will make efficient use of data of large volume and can search for patterns and reconstruct crime scenes. AI in digital forensics helps analyze images, videos, electronic records, and communications, while in biometrics it helps analyze fingerprints as well as DNA and facial recognition data. Tools that utilize AI also contribute towards the improvement of the investigative process by reducing human bias, whilst improving evidence in courts, ensuring accountability in the law. However, bringing AI into criminal justice includes ethical considerations about algorithmic bias, data privacy and the admissibility of evidence--regulatory oversight and standardization will be required to control all these considerations. Focusing this section on the latest state-of-the-art of AI in forensic science, the article discusses current examples which are providing concrete examples of how AI fits in the modern forensic landscape, and it deals with how it fits the intricate investigations and challenges associated with legal structures, validation ethics and ethical challenges (in particular, validating the data). If forensic science can adopt responsible methodologies to use AI technology, forensic science will see improved accuracy in investigations, faster resolution of cases and better decision making that can be supported by decision making that is a fundamental shift towards technologically enabled crime investigation.

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Artificial Intelligence, Forensic Science, Crime Investigation, Digital Forensics, Legal Accountability, Machine Learning, Evidence Analysis, Ethical Concerns

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Multimorbidity has become a characteristic problem of modern adult health care practise, especially in ageing societies and resource-limited health care. Polypharmacy, complicated pharmacological regimens, and increased susceptibility to adverse drug events, nonadherence, and functional impairment are often observed in the coexistence of a variety of chronic conditions. The article explores these issues: the patterns of multimorbidity and therapeutic complexity in adult medical practise will be studied using an integrative review of clinical, epidemiological, and systems-level evidence. Basing the analysis on primary and tertiary care, the findings have identified general disease clusters, the prescribing behaviour and the multidimensional predisposing factors that shape multimorbidity, such as behavioural risk factors, mental health issues, occupational exposures, social vulnerability and ageing. The review also addresses the clinical issues of guided care in complicated patients, focusing on the complexity of medication regimen, its suitability, and related morbidity and mortality risks. There is a special focus on vulnerable groups of people like older adults, women in occupations with high risks, tribal populations, and individuals with substance use and psychiatric conditions, which report disproportionate burden of therapy and worse outcomes. Other innovations addressed in the article, such as precision medicine, artificial intelligence, digital health tools, rehabilitation strategies, and patient empowerment models, are a set of potential outcome facilitators of more personalised and integrated care. On the whole, the synthesis highlights the necessity to no longer focus on disease-based models but rather on complexity-informed, patient-centred, and systems-integrated models of care as a way to effectively address multimorbidity and therapeutic complexity in adult medical practise.

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Multimorbidity; Therapeutic complexity; Polypharmacy; Adult medical practice; Medication regimen complexity; Ageing; Mental health comorbidity; Patient-centred care; Digital health; Precision medicine

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The mobile phone market in India has undergone a profound transformation with the rapid growth of e-commerce platforms and increasing consumer reliance on digital channels for information search and purchasing. Mobile phones, being high-involvement and technology-intensive products, exhibit complex consumer decision-making patterns influenced by price sensitivity, trust, perceived risk, convenience, warranty assurance, and after-sales service expectations. While online platforms offer competitive pricing, convenience, and extensive product information, offline retail outlets continue to attract consumers through physical inspection, immediate possession, personalized assistance, and localized service support. The present study examines the changing consumer purchase behaviour in the mobile phone market through a comparative analysis of online and offline buyers in Madhya Pradesh. Using primary data collected from consumers across selected urban and semi-urban districts, the study investigates differences in behavioural drivers such as price sensitivity, trust, convenience orientation, delivery preference, warranty perception, and after-sales service expectations. A quantitative research design is adopted, employing descriptive statistics, independent sample t-tests, chi-square analysis, factor analysis, and logistic regression to identify determinants of channel choice. The findings reveal statistically significant behavioural differences between online and offline buyers. Online buyers demonstrate higher price sensitivity and convenience orientation, whereas offline buyers exhibit stronger trust, preference for physical verification, clearer warranty perception, and higher after-sales service expectations. The study contributes region-specific empirical evidence from Madhya Pradesh and offers strategic insights for retailers, e-commerce platforms, and policymakers to design channel-appropriate marketing and consumer protection strategies.

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Consumer Purchase Behaviour, Mobile Phone Market, Online Buying, Offline Buying, Price Sensitivity, Trust, Omnichannel Retailing, Madhya Pradesh

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Abstract This study investigates the impact of institutional agricultural credit on farm productivity in Madhya Pradesh using district-level panel data for the period 2014-2024. Institutional agricultural credit has been a major policy instrument in India for promoting rural development and enhancing farm income. However, empirical evidence at the district level remains limited. The study employs descriptive statistics, correlation analysis, and panel regression modelling to examine the relationship between credit disbursement and agricultural productivity while controlling for irrigation coverage, rainfall variability, and fertilizer usage. The findings indicate that institutional credit has a statistically significant positive impact on farm productivity. However, rising non-performing assets (NPAs) and regional disparities moderate this effect. The study contributes to agricultural finance literature by providing district-level empirical evidence and policy recommendations for strengthening credit delivery mechanisms in Madhya Pradesh.

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Institutional Credit, Agricultural Productivity, District-Level Analysis, Rural Banking, Panel Regression

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Shanku Maharaj's travel writings transcend the boundaries of conventional travelogues, evolving into a unique blend of literature, philosophy, and cultural documentation. With nearly fifty Himalayan-centered works, his narratives capture not only the grandeur and peril of mountain landscapes but also the human spirit encountered along the way. His journeys were driven not by religious merit but by an irrepressible desire to see, know, and connect with people across diverse terrains. Through vivid descriptions of nature's transformations, compassionate portrayals of mountain folk, and reflections on unity beyond caste, class, and creed, Maharaj's works embody both scholarly rigor and lyrical beauty. His accounts of places such as Gangotri, Yamunotri, Siniolchu, Ladakh, and Meghalaya reveal a deep engagement with history, geography, and human relationships, while his meticulous documentation of mountaineering records underscores his commitment to preserving knowledge. Ultimately, Shanku Maharaj's travel literature stands as a testament to the transformative power of journeying--where landscapes become living experiences, strangers become kin, and the pursuit of beauty and humanity becomes inseparable.

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Shanku Maharaj, Himalayan Travel Literature, Philosophical Vision, Human Compassion, Nature and Landscape, Pilgrimage and Culture.

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Biological motifs consist of short conserved sequence patterns that serve essential regulatory and structural functions throughout DNA/RNA/protein molecules. The growing genomic data requires developers to solve the essential problem of motif identification and classification in computational genomics. The detection of position-specific conservation between multiple sequences proves difficult for traditional alignment based methods. The Profile Hidden Markov Model (PHMM) framework provides improved motif conservation representation through position dependent emission and transition probabilities to address the limitations. Current PHMM based studies use frequency calculations with weak sequence weighting methods that decrease model accuracy when motif sequences have different lengths. We develop a statistical PHMM model to analyze eukaryotic regulatory DNA motifs using a multiple sequence alignment of a few canonical motifs. The method uses Henikoff & Henikoff (1994) position-based sequence weighting together with Laplace pseudocounts to enhance probability estimation accuracy. To assess motif similarity, the Viterbi algorithm enables log-odds scoring. The results show that PHMMs successfully identify regulatory elements and provide statistical evidence for motif detection.

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Profile Hidden Markov Model, DNA motifs, multiple sequence alignment, sequence weighting, Laplace pseudocounts, Viterbi algorithm, computational genomics

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Financial restructuring has become a strategic requirement for businesses in today's unstable business environment, especially in the Information Technology (IT) sector, which is extremely vulnerable to changes in the global economy, technological disruptions, and competitive pressures. Cost optimization, workforce rationalization, mergers and acquisitions, debt restructuring, and adjustments to compensation structures are all common components of financial restructuring. These actions have a substantial impact on employees' job security, motivation, trust, and general work engagement, even though they are intended to improve the organization's long-term sustainability and financial health. With an emphasis on factors like job satisfaction, employee morale, organizational commitment, perceived job security, and performance, this study investigates how financial restructuring affects workers in the IT industry. A structured questionnaire was used to gather primary data from 380 IT workers in companies affected by restructuring using a quantitative research design. Data analysis was done using statistical tools like regression analysis, correlation analysis, mediation testing, and descriptive statistics. The results show that financial restructuring significantly affects employee attitudes and behavior, with workload and job insecurity serving as the main sources of stress. However, it was discovered that the detrimental effects were lessened by open communication, equitable HR procedures, and employee support systems. The study emphasizes how important human resource management (HRM) is in striking a balance between employee welfare and financial recovery during restructuring initiatives.

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Key Words: Financial restructuring, IT sector, HRM practices, organizational commitment, job security, job satisfaction, and employee morale.

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Abstract: Access to clean and safe water is one of the most critical global challenges due to rapid industrialization, population growth, and increasing water pollution. Conventional water treatment technologies often face limitations in effectively removing emerging contaminants, pathogens, and heavy metals. In this context, nanotechnology has emerged as a promising and innovative approach for enhancing water purification processes. This study explores the application of nanotechnology in achieving clean and sustainable water resources. Nanomaterials, including carbon nanotubes, graphene oxide, metal and metal-oxide nanoparticles, nanocomposites, and nanostructured membranes, possess distinctive physicochemical characteristics such as large surface area, high reactivity, and adjustable surface functionalities. These characteristics significantly improve contaminant removal efficiency through mechanisms such as adsorption, photo catalytic degradation, antimicrobial activity, and membrane filtration. Nanotechnology-based systems have demonstrated superior performance in removing heavy metals, organic pollutants, dyes, microorganisms, and salinity compared to traditional methods. The study also highlights the role of nanotechnology in desalination, wastewater treatment, and point-of-use water purification systems, making it suitable for both urban and rural applications. Additionally, the integration of green synthesis methods and biodegradable nanomaterials promotes environmental sustainability and reduces potential ecological risks. Despite its advantages, challenges related to large-scale implementation, cost, nanoparticle toxicity, and regulatory concerns remain. Addressing these issues through responsible design and risk assessment is essential for practical deployment. Overall, nanotechnology presents a transformative solution for improving water quality and ensuring access to clean water, contributing significantly to public health and sustainable development goals.

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Nanotechnology, Clean Water, Water Purification, Nanomaterials, Carbon Nanotubes, Emerging Contaminants.

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The covid-19 has disrupted and shaken the entire world. Mostly it has affected learning and teaching of educational institutions. India is now witnessing a rapid shift from traditional chalk-talk teaching model to technology driven E- learning model. While E- learning has been increasing exponentially in recent years, India is now experiencing an E-Learning boom since pandemic has emerged. The E- learning experience has posed some challenges and directions for future of online education. The policy makers are now focussing on scaling and ensuring inclusive E- learning solutions with much updated hands on for both teacher and student. Yet it would be simply to assume that e- learning platform is progressing seamlessly like physical classrooms or not. Thus, objective of our study is to analyse the influential role of covid 19 pandemic in Indian education system specifically among student's cohort, significant contribution to E-Learning mode as a resource of learning. This paper also highlighted how E- learning plays a crucial role and panacea for all educational institutions by analysing awareness of students before and after the pandemic has emerged with insight on challenges and opportunities posed by pandemic. The research is based on both Quantitative and Qualitative Approaches. In this research primary survey and secondary data has approached. Primary Data were collected from 150 students and self-administered questionnaire was adopted to analyse information for the study. Analysis has followed descriptive statistics, gap analysis, scatter diagram.

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COVID-19, Indian Education Mode, Online-Learning, Effect of COVID-19 and Challenges.

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