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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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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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 Keywords

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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 Keywords

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

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Creative Commons Attribution 4.0 and The Open Definition