Volume 13 | Issue 1

 Abstract

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Cardiovascular disease, QRISK2, Primary prevention, Cardiovascular risk score, Coronary Heart Disease.

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Automated GMAW, Submerged-arc-welded pipes, Robotic welding optimization, Weld quality enhancement

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Abstract: Universal Design (UD) aims to create environments that are accessible, usable, and inclusive for people of all abilities. This research investigates the role of ramps in embodying the seven principles of Universal Design, demonstrating how ramps can transcend their traditional role as mechanical solutions to enhance usability, safety, and aesthetic appeal. The research begins by defining the seven principles of Universal Design--Equitable Use, Flexibility in Use, Simple and Intuitive Use, Perceptible Information, Tolerance for Error, Low Physical Effort, and Size and Space for Approach and Use--and explores how ramps can be designed to address these principles. Case studies of notable buildings such as the Ed Roberts Campus, Guggenheim Museum of Modern Art, Enabling Village by Woha, Akshay Pratishthan School, Amar Jyothi Charitable Trust, and Disha Resource Centre for Multiple Disabilities illustrate practical applications of these principles in real-world architectural contexts. The research highlights innovative approaches to ramp design, emphasizing their potential to function as design elements, integrate with landscaping, and convey cultural significance. By examining these aspects, the research underscores the importance of incorporating ramps thoughtfully into architectural design, not only to ensure accessibility but also to enhance the overall user experience and aesthetic value of spaces. The findings advocate for a broader perspective on ramp design, encouraging architects and designers to view ramps as integral components of inclusive design rather than purely functional elements. This approach fosters a more comprehensive understanding of Universal Design and promotes environments that are genuinely accessible and welcoming to all.

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Universal Design principles, Equitable use, Accessibility in architecture, Seamless ramp integration

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Photorespiration, often considered an energy-costly process, plays a crucial role in plant metabolism, particularly under environmental stress conditions. This paper examines the significance of photorespiration in regulating plant responses to abiotic stresses such as drought, heat, salinity, and nutrient deficiency. Through its involvement in maintaining cellular homeostasis and mitigating oxidative damage, photorespiration enables plants to adapt to adverse environments. The process interacts closely with key metabolic pathways, including the TCA cycle and carbon metabolism, influencing nitrogen balance and energy utilization. While photorespiration generates reactive oxygen species (ROS) as byproducts, it also activates protective mechanisms to prevent cellular damage, highlighting its dual role in stress adaptation. Advances in genetic and biotechnological approaches have demonstrated the potential of modifying photorespiratory pathways to improve stress resilience in crops. By engineering Rubisco efficiency and targeting enzymes involved in photorespiration, scientists aim to reduce energy costs and enhance plant tolerance to stress. This review underscores the protective and adaptive roles of photorespiration, challenging its traditional perception as a purely wasteful process. The findings emphasize the need for further research on molecular mechanisms, metabolic interactions, and innovative biotechnological strategies to optimize photorespiration. Such efforts hold promise for improving agricultural productivity and crop resilience, particularly in the context of climate change and resource scarcity.

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Photorespiration, Plant stress response, Metabolic adaptation, Reactive oxygen species (ROS), Crop resilience

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Abstract Pharmacovigilance is a science aimed at ensuring the safety of medicines by detecting, assessing, and preventing adverse drug reactions (ADRs). This article explores the evolution and objectives of pharmacovigilance, emphasizing its importance in modern healthcare. It also highlights parallels with Ayurvedic teachings, which stress the responsible use of medicines and the risks of improper administration. The article offers a comprehensive perspective on the shared goal of both systems, safeguarding public health through vigilance and informed medicine use.

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Keywords: Pharmacovigilance, Ayurveda, Adverse Drug Reactions, Drug Safety etc

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This research paper explores the profound impact of digital banking services on retail customer loyalty, with a focus on three pivotal determinants: service quality, transaction security, and service personalization. As digital banking continues to evolve, comprehending the intricacies of how these dimensions influence customer loyalty is vital for sustaining competitive advantage in the financial sector. A survey encompassing 400 retail banking customers was conducted to extract nuanced insights regarding their perceptions and interactions with digital banking platforms. Utilizing both descriptive and inferential statistical methods, including ANOVA, the study rigorously examines the correlations between digital banking attributes and customer loyalty.

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Digital Banking, Customer Loyalty, Service Quality, Transaction Security, Service Personalization

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The researcher is concentrating on different load dynamics on physical variables and how middle distance running and weightlifting training protocols effects on specific physical parameters. A well-thought-out, methodical physical and physiological training program will always result in notable changes in the body. In order to achieve this goal, the investigator has chosen (N=30) women-volunteered elite athletes of each (n=15) of middle distance running and weight lifting athletes age 18 and 22 years. All the volunteered elite athletes were trained by their coaches for about 7 to 9 years. The selected criterion parameters are Speed and explosive power and they were measured by 50-meter dash and standing broad jump. The level of significant is set at 0.05 level of assurance. The study concluded that regular and systematic middle distance running training and weight lifting training significantly brought changes in selected variables as compared to each other training protocols. Further, it is concluded that middle distance running is good for improving speed and weight lifting is good for improving explosive power. In ordered to find out the significant difference 't' ratio is employed.

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middle distance running, weightlifting, speed, explosive power.

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This study explores the construction of collective identities among migrant communities through the lens of Benedict Anderson's concept of imagined communities. Initially formulated to explain the emergence of national identities, Anderson's theory provides a compelling framework for analysing how migrants create and sustain shared identities in host societies. Using a qualitative approach, the research examines cinematic portrayals of migrant experiences, focusing on recent feature films such as The Farewell (2019), Minari (2020), Lion (2016), and In the Heights (2021). These films are analysed to uncover key themes, including shared narratives, cultural rituals, transnationalism, exclusion, and hybrid identities. The findings demonstrate that films serve as cultural texts that visualise the complexities of migrant identity formation. Shared narratives and cultural memory act as unifying forces, while rituals and symbols anchor migrants' sense of belonging. Transnational connections reveal the fluidity of imagined communities, transcending geographic boundaries. Simultaneously, experiences of exclusion and internal tensions within migrant communities challenge the cohesion of these identities. The research highlights how hybrid identities emerge through generational negotiations, blending cultural heritage with adaptation to host societies. By integrating Anderson's theoretical insights with film analysis, this study contributes to an interdisciplinary understanding of migration, identity, and cultural adaptation. It underscores the value of cinema as a medium for examining the lived realities of migrants and the dynamic processes through which they imagine and negotiate collective belonging in an increasingly globalised world.

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Imagined Communities and Migration, Cinematic Narratives of Migration, Diasporic Identity Formation, Cultural Memory in Migrant Communities, Transnational Migration and Identity, Hybrid Cultural Identities, Migration and Exclusion, Rituals and Symbols in Diaspora, Migration and Collective Belonging, Benedict Anderson's Imagined Communities, Film Studies and Migration, Cultural Adaptation in Host Societies, Representation of Migrant Experiences, Globalization and Migrant Communities and Migr

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The growing adoption of Electric Vehicles (EVs) has led to an increasing need for advanced methods to monitor and predict battery performance in real-time. Accurate prediction of battery states, such as State of Charge (SoC) and State of Health (SoH), is critical for enhancing battery longevity, improving energy efficiency, and ensuring the reliability of EVs. This project presents a novel approach that integrates Machine Learning and Digital Twins to predict battery states in EVs using data-driven machine learning techniques. The proposed model utilizes real-time data collected from EV battery systems to create a digital replica, or "digital twin," which simulates the behaviour of the battery over time. The system is trained using machine learning algorithms, including regression and classification models, to predict key battery parameters. An essential feature of this approach is its emphasis on explainability, ensuring that the machine learning model's decisions are interpretable and transparent to users and engineers. This is achieved through the use of interpretable models and feature importance analysis, allowing stakeholders to understand how different factors affect battery performance. The model is implemented in Python using popular machine learning libraries, with real-time data input from EV Battery Management Systems (BMS). Experimental results demonstrate the effectiveness of the approach in accurately predicting battery states while maintaining model transparency. This work provides a promising framework for the development of intelligent, data-driven systems that can optimize the performance and lifespan of EV batteries, ultimately contributing to the sustainability and efficiency of electric mobility.

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Classification, machine learning, quality, semi-supervised learning, web services, Data-Driven Models, Predictive Modelling, Time Series Forecasting, Feature Engineering

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The Indian railway system is one of the largest in the world. However, it faces challenges in updating information about train locations, delays, ticket availability, and platform information. This project aims to improve passenger services using advanced technologies. The system integrates AI-driven chatbots, cloud services (like AWS and Google Cloud), and IoT hardware (ESP32) to provide real-time information. Travelers can get answers from a chatbot or use a web application for a comprehensive view of train and booking information. The project addresses issues like lack of real-time information, disconnected ticketing systems, administrative hurdles, and limited automated support. Enhancing this system will increase efficiency and passenger satisfaction. Key benefits include real-time updates, a unified platform, increased efficiency, scalability, and a user-friendly interface. By using advanced technologies, the overall experience of railway passengers in India will improve.

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Cloud computing , Load Managing, Round-robin , Hardware-based load managing, Software-based Load Managing .

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The present study aims to establish that Eliot has created Dunstan Cass through the art of indirect characterisation and that he is a consummate villain who shapes the simple tale of the weaver, giving it such twists and turns that we are struck by the brilliant narrative and descriptive skills of Eliot. Dunstan's villainy surpasses that of all characters and his cool and calculated style makes him one of the best villains ever created by any novelist of the Victorian Age.

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Silas Marner, Dunstan Cass, Godfrey Cass, Wildfire, Guineas, George Eliot, Villain

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Big Data has revolutionized various sectors by enabling advanced analytics and insights. However, the rapid growth of Big Data systems has also introduced significant security and privacy challenges. This paper explores innovative approaches to enhance Big Data security, focusing on privacy preservation and threat mitigation. We present a comprehensive analysis of existing challenges, propose novel solutions, and discuss their practical applications. Additionally, we examine the role of emerging technologies such as artificial intelligence (AI), blockchain, and differential privacy in fortifying Big Data security. Our findings aim to guide researchers and practitioners in developing robust, scalable, and secure Big Data systems.

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Big Data Security, Privacy, Threat Mitigation

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Customer satisfaction is an essential yardstick of the success and sustainability of e-commerce platforms in an increasingly competitive digital marketplace. As an e-commerce business grows, it is increasingly important to understand the predominant elements influencing customer satisfaction, such as improving user experience, fostering trust, and supporting customer loyalty. This paper aims to discover the factors that affect customer satisfaction in e-commerce. The paper reviews the literature to provide insights into the important determinants of customer satisfaction by using secondary data from scholarly articles and academic reports. The finding includes customer satisfaction factors comprising service quality, website usability, product quality, pricing strategies, trust and security, and post-purchase services. This study's findings will contribute to an excellent knowledge of what online consumers are increasingly expecting and provide valuable tips for businesses to improve their offerings. The review identifies existing literature gaps and proposes future research directions to tackle customer preferences' dynamics and e-commerce technological innovations.

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Customer satisfaction, e-commerce platforms, online shopping, service quality, trust and security, consumer behavior.

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The project aims to design and implement an IoT-based temperature and humidity monitoring system for polyhouses using the DHT11 sensor and ESP32 microcontroller. The system collects real-time environmental data and uploads it to the ThinkSpeak cloud platform for remote monitoring and analysis. ThinkSpeak provides powerful data visualization, analytics, and storage capabilities, enabling users to interpret environmental conditions effectively. This approach facilitates efficient climate management, improving crop yield and reducing manual intervention. The methodology involves interfacing the DHT11 sensor with the ESP32, programming the microcontroller using Arduino IDE, and setting up a cloud-based dashboard for data visualization. Results indicate reliable data acquisition and cloud communication, highlighting the potential of IoT in smart agriculture. This study underscores the benefits of integrating IoT technologies in modern farming systems.

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IoT, Polyhouse, DHT11, ESP32, ThinkSpeak, Smart Agriculture.

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Classifying sleep disorders plays a vital role in enhancing the quality of human life, as conditions like sleep apnea can have a profound impact on overall health. Expert-based sleep-stage classification is a complex and error-prone task, often susceptible to human mistakes. The development of robust machine learning algorithms (MLAs) for sleep disorder classification requires the ability to analyse, monitor, and diagnose sleep-related issues accurately. Our model compares deep learning techniques with traditional machine learning algorithms to classify sleep disorders. We propose an optimized approach for sleep disorder classification, evaluating the model using the publicly available Sleep Health and Lifestyle Dataset. Optimization of the algorithms was performed using a genetic algorithm to fine-tune the parameters of various machine learning models. The study includes a comparative analysis of the proposed algorithm against state-of-the-art methods for classifying sleep disorders. The dataset consists of multiple features related to sleep patterns and daily activities. We assessed several machine learning and deep learning techniques. Experimental results show notable differences in the performance of the evaluated algorithms, with the proposed method achieving superior results.

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Sleep Disorder Classification, Machine Learning Algorithms, Deep Learning, Sleep Apnea, Health Monitoring, Genetic Algorithm Optimization, Automated Diagnosis, Sleep Health Dataset, Feature Extraction, Artificial Neural Networks (ANN), Machine Learning Optimization, Sleep Stage Classification, Predictive Modeling, Health Data Analysis, Precision Medicine, Sleep Disorder Diagnosis, Data-driven Health Solutions, Sleep Pattern Recognition, Supervised Learning

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A corporation uses social responsibility accounting (SRA) as a tool for evaluating how its operations affect society. It is a systematic evaluation of how the company affects its shareholders based on input from stakeholders in financial statement data. It involves methods along with policies for collecting, evaluating, as well as monitoring social, financial, as well as environmental data. Phrase "social responsibility accounting" describes how a company relates to social environment. Information about social performance is currently being made public by many companies to show the public and shareholders their moral and ethical standards. The study focuses on the scope and conceptual aspects of SRA as well as the state of affairs in India currently.

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Social Responsibility Accounting, CSR, Financial, Social, Environmental

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In creative filmmaking, Ramayana has evolved as a captivating subject explored through various cinematic adaptations. However, navigating the delicate balance between innovation and reverence poses a challenge, as audiences swiftly embrace or dismiss films based on their adherence to expectations, which often hold cultural and sentimental values. A comparative analysis was conducted on two Ramayana-themed films, Japanese producer Yugo Sako's "Ramayana: The Legend of Prince Rama" (1991) and Om Raut's adaptation "Adipurush" (2024) by applying the "Diffusion of Innovation theory" of E.M. Rogers to examine the factors influencing the reception of two distinct film adaptations of Ramayana among young audiences. Subjective interviews were conducted with young adult audiences who watched both movies to explore the impact of cultural influences and nostalgia on their decision-making processes. Additionally, the study categorized respondents into the five adopter stages of innovation to derive comprehensive conclusions regarding audience perceptions and preferences regarding cinematic adaptations of the Ramayana. The research concludes that audience perception of sensitive themes is prejudiced, and fixated on childhood nostalgia, thus any bold contemporary experimentation results in cultural shock, filmmakers should understand the audience's pulse associated with mythological epics to avoid commercial failure in the movie-making business.

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Ramayana, Cultural influence, Adipurush, Legend of Prince Rama, Cinema, Innovation

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After facing a long horrible situation of pandemic corona in India, here is originated a new generation of worker and a new role of worker is defined as "Gig-worker" and now it has been proved that, Gig-workers are made most essential part of modern India because in every big or small activity of business, they are contributing their skill and labour in instant manner. And today, we cannot imagine that, instant services will be completed without Gig-workers. But it is unfortunate that, till now no one thought about their rights and protection, which is provided under our Indian constitution. Gig-workers are totally violated in every stage of their life. In their employment, there is no security provided to them, they can be fired in any time without giving any information by their employer. It is great grief that there is no law, no awareness and great lackness of determination of Governments & Employers too.

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Low payment, Lack of benefits, Job insecurity of Gig workers, No employ protection, Lack of worker rights, Poor working conditions & Competition for Gig

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Ficus benghalensis Linn., commonly known as the Banyan tree, is a medicinal plant with diverse pharmacological properties. This review focuses on its antiulcer and hepatoprotective activities, summarizing the phytochemical constituents responsible for these effects, mechanisms of action, and recent research findings. The plant's potential therapeutic applications in gastrointestinal and hepatic disorders make it a valuable candidate for further pharmacological studies.

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Ficus benghalensis, antiulcer activity, hepatoprotective effect, phytochemicals, gastric mucosal protection, oxidative stress, liver detoxification, traditional medicine, Ayurveda, pharmacological properties.

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Introduction: This heterogenous disorder is characterized by excessive androgen production by the ovaries mainly. PCOS is a multifactorial and polygenic condition. The incidence varies between 0.5-4 percent, more common amongst infertile women. It is prevalent in young reproductive age group (20-30%). Polycystic ovary may be seen in about 20% of normal women. HAIR-AN syndrome in patients with PCOS is characterized by hyperandrogenism, insulin resistance and acanthosis nigricans. Internal examination reveals bilateral enlarged cystic ovaries which may not be revealed due to obesity. As per Ayurveda, we can co-relate this condition with mainly Artavadushti. Case Presentation: The patient in this case had complaint of failure to conceive for 11 years and Irregular and delayed menses since a year. She decided to consult a doctor and was diagnosed with PCOS. For the same she visited the OPD of PTSR, ITRA, Jamnagar. Management and Outcome: She was managed with Nitya Virechana with Naracha Choorna, Matrabasti with Sahacharadi Taila and Shatapushpadi Yoga orally. The Ayurvedic management resulted in the patient conceiving within 2 months of treatment.

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Ayurveda, Primary Infertility, Non-Obese PCOS, Matrabasti, Sahacharadi Taila

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