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                <text>Study on heat transfer and pressure drop in tube-in-tube helical heat exchanger</text>
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                <text>Dean number; Friction factor; Heat exchanger; Nusselt number</text>
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                <text>The present work aims to investigate the effect of different configurations of the tube-in-tube helically coiled heat exchanger. Commercial CFD codes were used to predict the fluid flow and heat transfer in a tube-in-tube helical heat exchanger. The model of different configurations of the inner tube has been simulated by varying the Dean number. The numerical results are verified and found to be in good agreement with reported data in the literature. Nusselt Number and friction factor are evaluated for different angular positions. The use of geometry E increases the Nusselt number and friction factor by 19.05% and 16% respectively at a Dean number of 4000 as compared with a circular tube as compared with the circular tube.  2021 Tamkang University. All rights reserved.</text>
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                <text>Sreenivasalu Reddy N.; Vishwanath K.C.; Satheesha V.; Thejaraju R.; Karthik Raj N.; Manoj M.; Goutham H.; Manjunatha B.S.</text>
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                <text>Journal of Applied Science and Engineering, Vol-24, No. 4, pp. 635-642.</text>
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                <text>Tamkang University</text>
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                <text>&lt;a href="https://doi.org/10.6180/jase.202108_24(4).0019" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.6180/jase.202108_24(4).0019&lt;/a&gt;
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                <text>ISSN: 27089967</text>
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                <text>Sreenivasalu Reddy N., Department of Mechanical Engineering, Rajarajeswari College of Engineering, Affiliated to Visvesvaraya Technological University, Bangalore, Belagavi, Karnataka, 560074, India; Vishwanath K.C., Department of Mechanical Engineering, Rajarajeswari College of Engineering, Affiliated to Visvesvaraya Technological University, Bangalore, Belagavi, Karnataka, 560074, India; Satheesha V., Department of Mechanical Engineering, Rajarajeswari College of Engineering, Affiliated to Visvesvaraya Technological University, Bangalore, Belagavi, Karnataka, 560074, India; Thejaraju R., Department of Mechanical and Automobile Engineering, CHRIST Deemed to Be University, Bangalore, 560074, India; Karthik Raj N., Department of Mechanical Engineering, Rajarajeswari College of Engineering, Affiliated to Visvesvaraya Technological University, Bangalore, Belagavi, Karnataka, 560074, India; Manoj M., Department of Mechanical Engineering, Rajarajeswari College of Engineering, Affiliated to Visvesvaraya Technological University, Bangalore, Belagavi, Karnataka, 560074, India; Goutham H., Department of Mechanical Engineering, Rajarajeswari College of Engineering, Affiliated to Visvesvaraya Technological University, Bangalore, Belagavi, Karnataka, 560074, India; Manjunatha B.S., Department of Mechanical Engineering, Rajarajeswari College of Engineering, Affiliated to Visvesvaraya Technological University, Bangalore, Belagavi, Karnataka, 560074, India</text>
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                <text>AN ANALYSIS ON THE PORTRAYAL OF INDIA BY NATIONAL GEOGRAPHIC MAGAZINE</text>
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                <text>Sreenivasan Deepthi </text>
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                <text>The research is an analysis on how the magazine ??National Geographic has portrayed India over the years and whether or how it has changed. National Geographic being an all American historical magazine might have its own ways of portraying particular nations. India being known for festivals, colors, superstition and snake charmers has always been portrayed countless number of times as only the above mentioned stereotypical explanation. May it be in movies, cartoons, books, etc., National Geographic being a credible magazine has never failed to bring forth to the world all historical aspects of any country. Bollywood, Spicy food, Religion etc. has been a hot topic for both Nat Geo magazine and television. The researcher wishes to find out if the magazine has portrayed India differently over the years.</text>
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                <text>The research is an analysis on how the magazine National Geographic has portrayed India over the years and whether or how it has changed. National Geographic being an all American historical magazine might have its own ways of portraying particular nations. India being known for festivals, colors, superstition and snake charmers has always been portrayed countless number of times as only the above mentioned stereotypical explanation. May it be in movies, cartoons, books, etc., National Geographic being a credible magazine has never failed to bring forth to the world all historical aspects of any country. Bollywood, Spicy food, Religion etc. has been a hot topic for both Nat Geo magazine and television. The researcher wishes to find out if the magazine has portrayed India differently over the years.</text>
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                <text>Optimal Allocation of Renewable Sources with Battery and Capacitors in Radial Feeders for Reliable Power Supply Using Pathfinder Algorithm</text>
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                <text>Distribution network; Energy storage system; Islanding mode; Multi-objective optimization; Pathfinder algorithm; Renewable energy</text>
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                <text>Allocating renewable energy systems (RESs) in an electrical distribution system (EDS) is crucial to achieving various objectives. However, their intermittency presents several challenges. In this connection, an efficient meta-heuristic pathfinder algorithm (PFA) is employed to determine the optimal location and size of photovoltaic (PV) and wind turbine (WT) systems, along with energy storage systems (ESS) and capacitor banks (CB) for both grid and islanding modes of operations. An objective function was formulated for loss reduction, greenhouse gas (GHG) emissions, and voltage profile improvement. The simulation results for the IEEE 33-bus EDS system are shown for two cases: grid-connected and islanding. The computational effectiveness of the PFA was compared with that reported in the literature. The PFA results showed an outstanding ability to resolve difficult optimisation problems. In addition, the optimal size of the RES when the network operates in the grid-connected mode can significantly improve the performance. The real power losses and GHG emissions were reduced by 48.49 % and 67.75% with PV systems and the other, respectively, whereas WT systems they are reduced to 69.68 % and 67.85 %, respectively. However, a combination of ESS, CB, and PV/WT can render the EDN sustainable for the islanding mode of operations.  The Author(s).</text>
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                <text>Sreenivasulu Reddy D.; Janamala V.</text>
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                <text>Journal of Solar Energy Research, Vol-8, No. 4, pp. 1651-1662.</text>
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                <text>University of Tehran</text>
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                <text>&lt;a href="https://doi.org/10.22059/jser.2023.358718.1299" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.22059/jser.2023.358718.1299&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179326345&amp;amp;doi=10.22059%2Fjser.2023.358718.1299&amp;amp;partnerID=40&amp;amp;md5=2eeb88ee50509fa2a9cff0db17134a82" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85179326345&amp;amp;doi=10.22059%2fjser.2023.358718.1299&amp;amp;partnerID=40&amp;amp;md5=2eeb88ee50509fa2a9cff0db17134a82&lt;/a&gt;</text>
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                <text>ISSN: 25883097</text>
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                <text>Sreenivasulu Reddy D., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Karnataka, Bangalore, 560074, India</text>
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                <text>A novel and simple meta-heuristic optimization technique viz., political optimizer (PO) is proposed in this paper to identify the size and optimal location of solar photovoltaic (SPV) system. The main objective is to minimize the distribution loss and is solved using proposed PO. The computational efficiency of PO is compared with the literature, and its superiority is highlighted in terms of global solution at initial stage. The physical requirements of SPV system via soft open points (SOPs) among multiple laterals are solved considering radiality constraints in second stage. The proposed concept of interoperable-photovoltaic (I-PV) system has been applied on standard IEEE 69-bus system and has shown the effectiveness in performance enhancement of the system.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Sreenivasulu Reddy D., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to be University), KA, Bangalore, 560074, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to be University), KA, Bangalore, 560074, India</text>
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                <text>In this paper, the political optimizer (PO), a new and efficient socio-inspired meta-heuristic search algorithm, is proposed for the first time in this research for determining the ideal locations and capacities of photovoltaic (PV) distribution generation (DG) in electrical distribution networks (EDN). A multi-objective function is designed to lower distribution losses and voltage deviation indexes and maximize voltage stability, among other objectives. The computational efficiency of PO when solving the optimal allocation of PV systems in EDN is investigated on an IEEE 33-bus EDN. The results indicate that integrating small DGs at multiple locations has a better EDN performance than integrating a single significant DG in the network. The results also suggest that, as demonstrated by a comparative analysis of PO results and those of other related literature works, PO can deal with complex multi-variable optimization problems.  2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Sreenivasulu Reddy D., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Karnataka, Bengaluru, 560074, India; Janamala V., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Karnataka, Bengaluru, 560074, India; Lahari P.S., Department of Electrical and Electronics Engineering, School of Engineering and Technology, Christ (Deemed to Be University), Karnataka, Bengaluru, 560074, India</text>
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                <text>A Markovian risk model with possible by-claims and dividend barrier</text>
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                <text>by-claims; dividend barrier; Gerber-Shiu function; GSF; Lundberg equation; MAP claim arrivals; phase type claims; risk reserve process</text>
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                <text>A MAP/PH risk model with possible by-claims and a dividend barrier is considered. Along with the main claim, a by-claim also can occur with a certain probability but by-claims are settled only after an inquiry and hence delayed. The model is analysed considering associated Markovian fluid models under the original timeline and an auxiliary timeline. Systems of integro differential equations (IDE) are developed for the Gerber-Shiu function (GSF) and the total dividends paid until ruin. Explicit expressions are obtained for the GSF of the models without and then with the barrier. Expressions are also provided for the moments of the total dividends paid until ruin. A dividends-penalty identity is given. The method is numerically illustrated with a two-phase model and sensitivity analysis of the model is done by varying some of the parameters involved.  2023 Inderscience Enterprises Ltd.. All rights reserved.</text>
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                <text>International Journal of Mathematics in Operational Research, Vol-26, No. 4, pp. 475-501.</text>
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                <text>Sreeshamim P.P., Department of Mathematics, National Institute of Technology, Kerala, Calicut, 673601, India; Jacob M.J., Department of Mathematics, National Institute of Technology, Kerala, Calicut, 673601, India; Dibu A.S., Department of Data Science and Statistics, Christ (Deemed to be University, Bangalore, 560029, India</text>
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                <text>Sreethi, Rebeka R.; Thomas, Rejoice</text>
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                <text>Industry 5.0 represents a transformative shift in industrial practices, merging advanced technologies with human-centered approaches. This evolution emphasizes personalization, ethical considerations, and enhanced consumer experiences in e-commerce. Social media platforms, such as Instagram, TikTok, and Facebook, have revolutionized brand engagement by enabling targeted advertising, community building, and real-time interaction. Women influencers play a crucial role in this new landscape, using their personal brands to drive consumer trust and loyalty. They create authentic content and promote diverse, inclusive narratives. As e-commerce adapts to Industry 5.0, integrating technological advancements with a focus on human values and ethical practices becomes essential for business success and consumer satisfaction.  2025, IGI Global Scientific Publishing. All rights reserved.</text>
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                <text>Sreevidhya K.B., Department of Chemistry, CHRIST University, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560, India; Kanchi S., Department of Chemistry, CHRIST University, Bengaluru, 560029, India, Centre for Renewable Energy and Environmental Sustainability, CHRIST University, Bengaluru, 560, India</text>
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                <text>Melamine is an unauthorized food additive and a highly concerning adulterant in foods that can occur either accidently or intentionally in dairy products, with potential health risks upon exposure to higher concentrations. An ultrasensitive fluorescent probe based on dual emissive RhBx@ZIF-7 was developed to detect melamine. In this study, a fluorescent dye, Rhodamine B (RhB), was successfully encapsulated into the metal-organic framework (MOF) pores of ZIF-7 to form a fluorescent probe (RhB30@ZIF-7), with dual emission properties to enable the detection of melamine at low concentrations. RhB30@ZIF-7 was optimized by varying experimental parameters, including temperature (25 C), pH (7.0), incubation time (10 min), and probe concentration (1 mg mL?1), to enhance its sensitivity and selectivity. The observed fluorescent quenching towards melamine was primarily attributed to the mechanisms of the internal filtering effect (IFE), due to absorption of the excitation wavelength by melamine, causing a turn-off response in the system. The limit of detection (LOD) and limit of quantification (LOQ) were found to be 0.47 ?M and 1.4 ?M, respectively, with an R2 of 0.99. This study reveals the previously unexplored enhanced fluorescence of RhB30@ZIF-7 and elucidates the contribution of the intermolecular interaction between RhB and ZIF-7 to fluorescence sensing, paving the way for food safety monitoring.  2025 RSC.</text>
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                <text>K shell X-ray intensity ratios, K-Li, K-L, and K-M vacancy transfer probabilities of Ba and Tl following internal conversion process</text>
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                <text>K shell X-rays of barium and thallium following internal conversion decay in Cs137 and Hg203, respectively, were detected using a Si(Li) X-ray detector coupled to PC-based 8k multichannel analyser employing the method suggested earlier by our group. The K shell X-ray intensity ratios and vacancy transfer probabilities for thallium and barium were calculated. The obtained results are compared with theoretical, semiempirical, and others' experimental results obtained via photoionization as well as decay processes. The effects of beta decay and internal conversion on X-ray emission probabilities are discussed.  2014 Published by NRC Research Press.</text>
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              <elementText elementTextId="138244">
                <text>Sreevidya P.V.; Gudennavar S.B.; Joseph D.; Bubbly S.G.</text>
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                <text>Canadian Journal of Physics, Vol-92, No. 11, pp. 1489-1493.</text>
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                <text>Canadian Science Publishing</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-84909619982&amp;amp;doi=10.1139%2Fcjp-2014-0105&amp;amp;partnerID=40&amp;amp;md5=cfe6164b75cdd0a45bf03c5f94caa9f7" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-84909619982&amp;amp;doi=10.1139%2fcjp-2014-0105&amp;amp;partnerID=40&amp;amp;md5=cfe6164b75cdd0a45bf03c5f94caa9f7&lt;/a&gt;</text>
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                <text>ISSN: 84204; CODEN: CJPHA</text>
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                <text>Sreevidya P.V., Department of Physics, Christ University, Bangalore, Karnataka, 560029, India; Gudennavar S.B., Department of Physics, Christ University, Bangalore, Karnataka, 560029, India; Joseph D., Nuclear Physics Division, Bhabha Atomic Research Centre, Trombay, Mumbai, Maharashtra, 400 085, India; Bubbly S.G., Department of Physics, Christ University, Bangalore, Karnataka, 560029, India</text>
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              <elementText elementTextId="268152">
                <text>Sreya, Pampati; Yashaswi, D.; Stephen, R.; Gobinath, R.; Ramkumar, S.</text>
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                <text>Indian Stock Market Prediction Using Neural Networks: A Comparative Analysis</text>
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              <elementText elementTextId="268155">
                <text>Lecture Notes in Networks and Systems;Volume;1469 LNNS;pp.101-112</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-96-7807-5_10" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-96-7807-5_10&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105020263014?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105020263014?origin=resultslist&lt;/a&gt;</text>
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                <text>Sreya P., CHRIST University, Bangalore, India; Yashaswi D., CHRIST University, Bangalore, India; Stephen R., CHRIST University, Bangalore, India; Gobinath R., CHRIST University, Bangalore, India; Ramkumar S., CHRIST University, Bangalore, India</text>
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                <text>Predicting stock prices remains a challenging problem due to the highly dynamic and nonlinear nature of financial markets. Traditional statistical models like ARIMA and GARCH often fail to capture the complexities inherent in stock market data. This paper investigates the use of deep learning techniques, focusing on Convolutional Neural Networks (CNNs) and a hybrid CNN-LSTM ensemble model for stock price prediction in the Indian stock market. The CNN model efficiently extracts temporal patterns from sequential data, while the CNN-LSTM ensemble leverages temporal dependencies for improved long-term prediction accuracy. Historical data from Tata motors, spanning over two decades, was used to train and evaluate the models. Experimental results highlight the CNN-LSTM ensemble's superior performance in capturing volatile trends and long-term dependencies, with a notable decrease in test loss compared to standalone CNN. This study underscores the effectiveness of hybrid deep learning architectures in enhancing prediction reliability, paving the way for more adaptive and robust financial forecasting systems.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026.</text>
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                <text>Convolutional Neural Networks (CNNs); Deep learning; Ensemble model; Long Short-Term Memory (LSTM); Machine learning (ML); Stock price prediction</text>
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                <text>Internet of Things and Cloud Computing Involvement Microsoft Azure Platform</text>
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                <text>Azure AI and M; Azure Analytics Service; Cloud computing; Internet of Things; Microsoft Azure</text>
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                <text>The rapid advancement of cloud technology has resulted in the emergence of many cloud service providers. Microsoft Azure is one among them to provide a flexible cloud computing platform that can scale business to exceptional heights. It offers extensive cloud services and is compatible with a wide range of developer tools, databases, and operating systems. In this paper, a detailed analysis of Microsoft Azure in the cloud computing era is performed. For this reason, the three significant Azure services, namely, the Azure AI (Artificial Intelligence) and Machine Learning (ML) Service, Azure Analytics Service and Internet of Things (Io T) are investigated. The paper briefs on the Azure Cognitive Search and Face Service under AI and ML service and explores this service's architecture and security measures. The proposed study also surveys the Data Lake and Data factory Services under Azure Analytics Service. Subsequently, an overview of Azure Io Tservice, mainly Io THub and Io TCentral, is discussed. Along with Microsoft Azure, other providers in the market are Google Compute Engine and Amazon Web Service. The paper compares and contrasts each cloud service provider based on their computing capability.  2022 IEEE.</text>
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                <text>Sri Bhavaani S., Christ University, India; Saha S.K., Christ University, India; Saha S., Reva University, India; Sharma N.D., Sikkim Manipal Institute of Technology, Sikkim Manipal University, India; Jha A., Sikkim Manipal Institute of Technology, Sikkim Manipal University, India</text>
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                <text>The necessity of sustainable energy sources and storage technologies is emerging due to growing energy demands. Thus, it encourages the need to perform sustainability analysis in terms of energy efficiency. For battery technologies, energy production and recycling holds a significance. In this study, the direct and indirect requirements of various battery technologies including production to transportation. The five battery technologies taken into account for the analysis are Lithium ion, Nickel Metal Hydride, Lead acid, Valve Regulated lead Acid, and Nickel Cadmium. The characteristics analyzed here are cycle life, energy density and energy efficiency. The study also covers the life cycle assessment in an structured way from raw to evaluation of materials, energy flow, installation, usage to end of life.   The Authors, published by EDP Sciences, 2024.</text>
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                <text>Sridevi J., Department of EEE, GRIET, Bachupally, Telangana, Hyderabad, India; Ananthi S., New Prince Shri Bhavani College of Engineering and Technology, Chennai, India; Gokilavani R., Department of Commerce, CHRIST (Deemed to Be University), Bangalore, India; Al-Farouni M., Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University, Najaf, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Al Diwaniyah, Al Diwaniyah, Iraq, Department of Computers Techniques Engineering, College of Technical Engineering, The Islamic University of Babylon, Babylon, Iraq; Ameer S.A., Ahl Al Bayt University, Karbala, Iraq</text>
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                <text>Sridevi, M.; Pandit, Karuna; Tripathis, Abhinav Priyadarshi; Dhaundiyal, Pankaj; Vekariya, Vipul; Gurpur, Shashikala; Lingaraj, K.; Philip, Jim Mathew</text>
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                <text>NEUROSYMBOLIC AI FOR CONTEXT-AWARE RESOURCE MANAGEMENT IN 5G SMART HEALTHCARE NETWORKS</text>
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                <text>Sridevi M., Department of Electrical and Electronics Engineering, Rajalakshmi Engineering College, Tamil Nadu, Chennai, 602 105, India; Pandit K., Department of Information Science and Engineering, NITTE (Deemed to be University), NMAM Institute of Technology, Karnataka, 574 110, India; Tripathis A.P., School of Business and Management, Christ University, NCR Campus, Uttar Pradesh, Bangalore, 201 003, India; Dhaundiyal D., School of Business and Management, Christ University, NCR Campus, Uttar Pradesh, Bangalore, 201 003, India; Vekariya V., Department of Computer Science and Engineering, Parul Institute of Engineering and Technology, Gujarat, 391 760, India; Gurpur S., Symbiosis Centre for Advanced Legal Studies and Research (SCALSAR) Symbiosis Law School, Pune, Symbiosis International (Deemed University), Maharashtra, Pune, 411 014, India; Lingaraj K., Department of Computer Science and Engineering, Rao Bahadur Y. Mahabaleswarappa Engineering College, Karnataka, 583 104, India; Philip J.M., Department of Computer Science and Engineering, Sri Ramakrishna Institute of Technology, Tamil Nadu, Coimbatore, India</text>
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                <text>Context-aware resource management in 5G Utilising neurosymbolic AI has growing impacts in the next-generation healthcare systems as smart healthcare networks to overcome the crucial issues of optimal service delivery and dynamic resource allocation. The 5G technology is adopted in healthcare networks for real-time processing, low latency, and high reliability that supports a vital application as telemedicine and remote patient monitoring. The resource management process of existing model rapidly fails in complicated, context-dependent situation with dynamic demands. To overcome these limitations, we proposed improved framework that combines a deep learning (DL) models for context extraction and symbolic reasoning process for decision-making. To determine the contextual patterns, the DL component analyses the multi-source data, as patient vitals, network conditions, and device status by utilising Transformer and Graph Neural Networks (GNNs). These data fed into symbolic reasoning module employ a knowledge graph and a rule-based system to dynamically allocate and distribute the resources based on the predetermined healthcare policies and requirements. Experimental results of this study showcase the improvements by attaining a reduction in latency, enhances in resource utilisation efficiency, and improved Quality of Service (QoS) for essential healthcare applications. In 5G-enabled smart healthcare systems, the results ensure a proposed model potential to transforms a resource management and ensure context-aware, versatile, and dependable service delivery for enhanced patient outcomes.  2025, Scibulcom Ltd.. All rights reserved.</text>
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                <text>Purpose: This study aims to gain an understanding of how caring for an ageing population affects caregivers psychological well-being, quality of life and ability to tolerate distress. This study provides valuable insights into the challenges faced by family caregivers and underscores the critical need for comprehensive support systems. Design/methodology/approach: A correlational method and cross-sectional research design was used for the study. For this, a sample of 200 caregivers in the age range of 2560 years who were taking care of the geriatric population above the age of 70 years for a minimum of one year were chosen. Four questionnaires ? Burden Scale for Family Caregivers, Psychological Well-Being Scale, World Health Organizations Quality of Life Scale-BRIEF version and Distress Tolerance Scale were chosen. Correlation and multivariate regression were calculated using statistical package for social sciences (SPSS) 21 and Jamovi 3.4.1. Findings: This study found that there is a negative correlation of caregiver burden with psychological well-being, quality of life and distress tolerance. The sub-domains of self-acceptance, psychological health and tolerance levels were most impacted for the caregivers. Through multivariate regression, it was found that the caregiver burden significantly predicted psychological well-being and quality of life. Research limitations/implications: This study focuses on the English-speaking caregivers which may overlook the diverse linguistic and cultural variations within the broader caregiver community in India and the data collection exclusively targeted family caregivers providing support to geriatric population without chronic illnesses. This restriction could potentially limit the generalizability of the findings to the broader caregiving context. Practical implications: The implications of this research are that for caregivers, this study underscores the importance of tailored support programmes that address the negative impact of caregiver burden on psychological well-being and quality of life. Health-care professionals can use the findings to incorporate mental health assessments and interventions within caregiving contexts, recognizing the interconnected nature of these variables. Policymakers can use the findings to inform policies related to caregiver support and health-care resource allocation. Originality/value: In India, the social norm is that children are expected to take care of their parents when they become old. Taking care of elderly parents can be challenging, even emotionally. As a result, this study will focus on how caregivers psychological well-being, quality of life and ability to tolerate distress are affected. Consequently, promoting the creation of community support groups and workplace mental health programmes which could give caregivers a forum to voice their concerns.  2024, Emerald Publishing Limited.</text>
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                <text>Sridhar A., Department of Psychology, CHRIST (Deemed to be University) Delhi-NCR Campus, Ghaziabad, India; Kuriakose H., Department of Psychology, CHRIST (Deemed to be University) Delhi-NCR Campus, Ghaziabad, India</text>
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                <text>To ensure safety, quality, and extended shelf life of perishable food products, food preservation is a critical aspect of food industries. Concerns regarding the potential health risks and loss of nutritional value of food because of traditional methods of preservation such as using chemical additives and high temperatures have set the need for finding alternative methods of preservation, for the betterment of health and the environment. Enzymes have the potential to kill microorganisms. Enzymes such as oxidases, peroxidases, hydrolases, catalases, and others have been extensively studied for their microbicidal activities. However, natural enzymes have shortfalls as they can be easily denatured and cannot be recycled. Nanozymes have gained the limelight in recent years as they can be applied in food industries to overcome the shortfalls of natural enzymes. They embody the highly beneficial properties of both enzymes and nanoparticles at the same time. Due to their enzyme-mimicking properties and versatile applications, nanozymes have become more popular in the last few years. Nanozymes have evolved as a promising alternative for food preservation and the detection of various contaminants in food. However, before the integration of nanozymes into the food industry, several factors such as their stability, biocompatibility, longevity, toxicity, cost-effectiveness, scalability, and regulatory approval need to be addressed. This chapter discusses the concept of nanozymes, its classification, and various applications in food industries specially designed for preservation of food products.  2024 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies.</text>
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                <text>Since ages, catalysts have played a pivotal role in accelerating the production and lowering the cost of a plethora of industrially important commodities. The latest in the scenario are nanocatalysts, which offer a wide array of advantages ranging from improved reaction rates to higher rates of recyclability. However, factors such as stability and support systems must be fine-tuned to achieve maximum efficiency. In accordance with the principle of sustainability, green synthesis methods have propelled the development of a range of nanocatalysts that can be applied in various domains, such as the food industry and biofuel production. Simultaneously, heterogeneous catalysis is gaining more attention globally, primarily due to the ease of recoverability of the nanocatalysts and in this context, magnetically retrievable nanocatalysts are indeed a boon for the green synthesis and sustainable production. Nanocomposites combining plasmonic and catalytic components with noble metal nanoparticles (Au and Ag) and doped semiconductor nanostructures have gained interest in recent years owing to their utility in multiple sectors by virtue of their ability to convert sunlight to chemical energy. The current review describes some methods for the synthesis of such nanocatalysts and their applications in diverse domains. Graphical Abstract: (Figure presented.)  The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.</text>
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                <text>The educational researcher has a wealth of options to apply analytics to extract meaningful insights to improve teaching and learning due to the growing availability of educational data. Teaching analytics, in contrast to learning analytics, examines the quality of the classroom environment and the efficacy of the instructional methods used to improve student learning. To investigate the potential of analytics in the classroom without jeopardizing students' privacy, we suggest a data science strategy that uses simulated data using pseudocode to build test cases for educational endeavors. Hopefully, this method's findings will contribute to creating a teaching outcome model (TOM) that can be used to motivate and evaluate educator performance. In Splunk, the study's simulated methodology was carried out. Splunk is a real-time Big Data dashboard that can gather and analyze massive amounts of machine-generated data. We provide the findings as a set of visual dashboards depicting recurring themes and developments in classroom effectiveness. Our study's overarching goal is to help bolster a culture of data-informed decision-making at academic institutions by applying a scientific method to educational data.  2023 IEEE.</text>
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                <text>Sridhar K., Department of Mechanical Engineering, Lendi Institute of Engineering and Technology, Andhra Pradesh, Vizianagaram, India; Shinde G., Department of Management, H K Institute of Management Studies and Research, Maharashtra, Mumbai, India; Chaurasia A., School of Commerce Finance and Accounting, Christ Demd to Be University Ncr Campus, UP, Gaziabad, India; Rani N.R.A., Department of Civil Engineering, Alliance College of Engineering and Design, Alliance University, India</text>
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