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                <text>Current Trends in Technology and Science, Vol-3 (2), pp. 65-68. ISSN-2279-0535</text>
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                <text>Nachamai M</text>
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                <text>family caregiving; low resource settings; Motor Neuron Disease; psychosocial care; social context</text>
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                <text>Motor Neuron Disease (MND) leads to significant psychosocial distress for the person with the illness and caregivers. Psychosocial factors influence the management and quality of life to a significant degree. Objective: To develop individualised psychosocial intervention program for people with MND and their families in India. Methods: People with MND and healthcare staff were constructively involved in co-designing the intervention program in four phases adapted from the MRC framework: 1. A detailed need assessment phase where 30 participants shared their perceptions of psychosocial needs 2. Developing the intervention module (synthesis of narrative review, identified needs); 3. Feasibility testing of the intervention program among seven participants; 4. Feedback from participants on the feasibility (acceptance, practicality adaptation). The study adopted an exploratory research design. Results: Intervention program of nine sessions, addressing psychosocial challenges through the different stages of progression of the illness and ways to handle the challenges, specific to the low resource settings, was developed and was found to be feasible. People with MND and families who participated in the feasibility study shared the perceived benefit through feedback interviews. Conclusion: MND has changing needs and challenges. Intervention programme was found to be feasible to be implemented among larger group to establish efficacy.  The Author(s) 2022.</text>
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                <text>Thomas P.T.; Warrier M.G.; Arun S.; Bhuvaneshwari B.; Vengalil S.; Nashi S.; Preethish-Kumar V.; Polavarapu K.; Rajaram P.; Nalini A.</text>
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                <text>Chronic Illness, Vol-19, No. 2, pp. 458-471.</text>
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                <text>&lt;a href="https://doi.org/10.1177/17423953221097076" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1177/17423953221097076&lt;/a&gt;
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                <text>Thomas P.T., Department of Psychiatric Social Work, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Warrier M.G., Department of Psychology, CHRIST (Deemed to be University), Bangalore, India; Arun S., Department of Counselling Psychology, Montfort College, Bangalore, India; Bhuvaneshwari B., Department of Psychiatry, St Johns Medical college and hospital, Bangalore, India; Vengalil S., Department of Neurology, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Nashi S., Department of Neurology, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Preethish-Kumar V., Department of Neurology, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Polavarapu K., Department of Neurology, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Rajaram P., Department of Psychiatric Social Work, National Institute of Mental Health and Neuro Sciences, Bangalore, India; Nalini A., Department of Neurology, National Institute of Mental Health and Neuro Sciences, Bangalore, India</text>
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                <text>The malignant bone tumor osteosarcoma. Any bone is at risk, but lengthy bones like the limbs are more vulnerable. Although the precise cause of this malignant growth is uncertain, experts concur that it is caused by changes to deoxyribonucleic acid (DNA) inside the bones. This can cause the breakdown of good tissue and the growth of aberrant, pathological bone. Osteosarcoma has a 76% cure rate if detected early and treated before it spreads to other parts of the body. An X-ray is the primary tool for detecting bone tumors. Bone X-rays and other imaging tests can help detect osteosarcoma. A biopsy should be performed for an accurate diagnosis. This is a time-consuming and tedious task that might be greatly reduced with the help of appropriate tools. Data preprocessing, segmentation, feature extraction, and model training are the four main pillars of the proposed approach. Unwanted noises can be filtered out with some preprocessing. Low-spatial-frequency and high-spatial-frequency components are separated using segmentation. The proposed approach employed Tumor Border Clarity, Joint Distance, Tumor Texture, and other features for feature extraction. Let's move on to A-Residual CNN model training. The success percentage of the proposed approach was 96.39 percent.  2023 IEEE.</text>
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                <text>Prasad B.M.G.; Bikash Acharjee P.; Guntakala S.; Sharma D.; Divya N.; Patil H.</text>
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                <text>International Conference on Sustainable Communication Networks and Application, ICSCNA 2023 - Proceedings, pp. 1431-1436.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/ICSCNA58489.2023.10370651" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICSCNA58489.2023.10370651&lt;/a&gt;
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                <text>ISBN: 979-835031398-7</text>
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                <text>Prasad B.M.G., Ravindra College of Engineering for Women (RCEW, Autonomous), Department of Cse, Andhra Pradesh, Kurnool, 518452, India; Bikash Acharjee P., Christ University, Pune, India; Guntakala S., K.B.N College, Department of Mca, Andhra Pradesh, Vijayawada, India; Sharma D., Institute of Pharmacy, Assam Don Bosco University, Tapesi, Assam, India; Divya N., Prince Shri Venkateshwara Padmavathy Engineering College, Department of Civil Engineering, Tamilnadu, Chennai, India; Patil H., Symbiosis Institute of Technology, Symbiosis International (Deemed University), Maharashtra, Pune, India</text>
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                <text>An Innovative Method for Brain Stroke Prediction based on Parallel RELM Model</text>
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                <text>Brain Stroke Prediction; Extreme learning machine (ELM); Recursive Feature Elimination (RFE)</text>
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                <text>Strokes occur when blood supply to the brain is suddenly cut off or severely impaired. Stroke victims may experience cell death as a result of oxygen and food shortages. The effectiveness of various predictive data mining algorithms in illness prediction has been the subject of numerous studies. The three stages that make up this suggested method are feature selection, model training, and preprocessing. Missing value management, numeric value conversion, imbalanced dataset handling, and data scaling are all components of data preparation. The chi-square and RFE methods are utilized in feature selection. The former assesses feature correlation, while the latter recursively seeks for ever-smaller feature sets to choose features. The whole time the model was being trained, a Parallel RELM was used. This new method outperforms both ELM and RELM, achieving an average accuracy of 95.84%.   2024 IEEE.</text>
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                <text>Kavitha K.; Devi V.J.; Alam M.S.; Sindhu V.; Gandhewar N.; Kalra G.</text>
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                <text>4th International Conference on Sustainable Expert Systems, ICSES 2024 - Proceedings, pp. 1637-1643.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>Kavitha K., Gmr Institute of Technology, Department of CSE-AI&amp;amp;ML, Andhra Pradesh, Razam, India; Devi V.J., Aditya Institute of Technology and Management, Department of Information Technology, Andhra Pradesh, Tekkali, India; Alam M.S., College of Engineering and Computer Science, Jazan University, Department of Computer Science, Jizan, Saudi Arabia; Sindhu V., Christ University, Department of Computer Science, Karnataka, Bangalore, India; Gandhewar N., Shri Ramdeobaba College of Engineering and Management, Department of Aiml, Nagpur, India; Kalra G., Maharishi Markandeshwar (Deemed to be University), Department of Mechanical Engineering, Mullana, Ambala, India</text>
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                <text>Acharjee P.B., CHRIST University, Pune, India; Magadum A.A., Department of MCA, MIT-ADT University, Maharastra, Pune, India; Thejovathi M., Department of Computer Science and Engineering, Acharya Nagarjuna University, Guntur, India; Jain R., School of Arts &amp;amp; Humanities, IIMT University, Meerut, India; Umarani K., School of Arts &amp;amp; Humanities, IIMT University, Meerut, India; Nishant N., Department of Computer Science and Engineering, School of Engineering, Babu Banarasi Das University, Lucknow, India</text>
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                <text>This strategy highlights the benefits of utilizing cutting-edge IT to back up company goals and genuinely assist in changing internal procedures by implementing an ERP-appropriate solution. Any organization, no matter how big or little, can benefit from an enterprise resource planning (ERP) system, which is an integrated suite of tools designed to streamline and improve internal business operations. Staying true to this approach will ensure that you get the greatest results while training the model, selecting features, and doing preprocessing. In order to use dense vector embedding for preparing the raw system logs, ERP system logs are typically represented by a combination of alphanumeric characters. While selecting features, SIM uses Particle Swarm Optimization (PSO) to create uniform product configurations. Using a Tree-MLP, the model was trained. This new strategy outperforms the old one, including Decision Tree and MLP. A 94.30% improvement in accuracy was achieved after implementing the technique.   2024 IEEE.</text>
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                <text>Ahlawat J., Tecnia Institute of Advanced Studies, Department of Management Sciences, New Delhi, India; Sundaresh K., Srm University, School of Law, Chengalpattu, India; Murugan R.T., Kalasalingam Academy of Research and Education, Kalasalingam Business School, Department of Business Administration, Krishnankoil, India; Sawadatkar S., Dr D Y Patil Institute of Technology, Department of Civil Engineering, Pimpri, Pune, India; Mule A.K., Dr. D. Y. Patil Institute of Technology, Department of First Year Engineering, Pimpri, Pune, India; Kiran P.B.N., Christ University, School of Business and Management, Bengaluru, India</text>
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                <text>A heavy-duty vehicle's fuel usage, and thus its carbon dioxide emissions, are significantly impacted by the driver's behavior. The average fuel economy of a car varies by about 28% between drivers. Fuel efficiency can be improved by driver education, monitoring, and feedback. Fuel efficiency-based incentives are one form of feedback that can be provided. The largest challenge for transportation companies implementing such incentive programs is how to accurately evaluate drivers' fuel consumption. The processes of preprocessing, feature extraction, and model training are all utilized in the suggested method. Principal component analysis (PCA) is widely utilized in data science's preprocessing stage. GMM is used for feature extraction. Afterwards, SR-GRU-CNN is used to train the models based on the selected features. When compared to the two most popular alternatives, CNN and SR-GRU, the proposed methodexcels.  2023 IEEE.</text>
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                <text>Bansod P.J., Department of Mechanical Engineering, G H Raisoni College of Engineering &amp;amp;Management, Wagholi, Pune, India; Mohan U., Department of Mechanical Engineering, University of Technology and Applied Sciences, Salalah, Oman; Yadav D.K., Department of Electronics &amp;amp; Communication Engineering, IIMT College of Engineering, Greater Noida, India; Singh Y., India Meteorological Department, Mausam Bhawan, Lodhi Road, New Delhi, India; Sharmila P., Department of Science &amp;amp; Humanities, Prince Shri Venkateshwara Padmavathy Engineering College, Tamil Nadu, Chennai, India; Chauhan A., Department of Life Sciences, School of Sciences, CHRIST (Deemed to be university), Karnataka, Bengaluru, India</text>
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                <text>The House Price Prediction is often employed to forecast housing market shifts. Individual house prices cannot be predicted using HPI alone due to the substantial correlation between housing price and other characteristics like location, area, and population. While several articles have used conventional machine learning methods to predict housing prices, these methods tend to focus on the market as a whole rather than on the performance of individual models. In addition, good data pretreatment methods are intended to be established to boost the precision of machine learning algorithms. The data is normalized and put to use. Features are selected using the correlation coefficient, and LSSVM is employed for model training. The proposed approach outperforms other models such as CNN and SVM.   2023 IEEE.</text>
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                <text>Goel Y.K., Surajmal University, Computer Science Engineering, Uttarakhand,(Udham Singh Nagar), Kichha, India; Swaminathen A.N., Adi Shankara Institute of Engineering and Technology, Civil Department, Kerala, kalad, India; Yadav R., Graphic Era Hill University, Department of Computer Science and Engineering, Dehradun, India; Kanthamma B., Gitam Deemed to Be University, Electrical, Electronics and Communications Engineering (EECE), Andhra Pradesh, Visakhapatnam, India; Kant R., Shoolini University, Cse Department, Himachal Pradesh, Solan, India; Chauhan A., Christ (Deemed to Be University), Department of Life Sciences, Karnataka, Bengaluru, India</text>
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                <text>Anonymity; Cloud computing; Data traceability; Group data sharing; Group signature</text>
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                <text>It is important to provide security and efficient data exchange in cloud infrastructure and achieve traceability and anonymity of data. mean For high levels of safety and performance in one Anonymously, this article addresses the topic It allows data to be exchanged and stored between members of the same group in the cloud. Proposed arrangement creates unique and traceable group data sharing policies using group signatures and special agreements Strategies to accomplish these goals. this Facilitates anonymous communication between systems Public clouds have many users and. Real people following up when needed. Also, the system implements the main agreement programs to make it easier for team members to. Obtain a shared session key for secure data exchange and storage facilities. Basic generation processes a Symmetric Balanced Incomplete Block Theory (SBIBD), significantly reducing the workload of team members a shared session key must be introduced. In cloud computing contexts, the suggested system guarantees efficiency and security for group data sharing, as shown by theoretical analysis and experimental validation.  2024 IEEE.</text>
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                <text>Pandey M., Christ (Deemed to Be University), School of Business and Management, Bangalore Yeshwanthpur Campus, India; Subramani K., Christ (Deemed to Be University), School of Business and Management, Bangalore Yeshwanthpur Campus, India; Madeswaran A., Christ (Deemed to Be University), School of Business and Management, Bangalore Yeshwanthpur Campus, India; Al-Jawahry H.M., The Islamic University, Najaf, Iraq; Sudhamalla M., Cmr Technical Campus, Department of Ece, Telangana, Hyderabad, India; Misra N., Uttaranchal University, Uttaranchal Institute of Management, Department of Management, Dehradun, 248007, India; Kumar K.K., Saveetha University, Sse, Saveetha Institute of Medical and Technical Science - Simats, Department of Computer Science and Engineering, Chennai, India</text>
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                <text>cellulose; crystallinity; differential scanning calorimetry; electron microscope; Fourier transform infrared spectroscopy; thermogravimetric analysis</text>
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                <text>Cellulose obtained from plants is a bio-polysaccharide and the most abundant organic polymer on earth that has immense household and industrial applications. Hence, the characterization of cellulose is important for determining its appropriate applications. In this article, we review the characterization of cellulose morphology, surface topography using microscopic techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Other physicochemical characteristics like crystallinity, chemical composition, and thermal properties are studied using techniques including X-ray diffraction, Fourier transform infrared, Raman spectroscopy, nuclear magnetic resonance, differential scanning calorimetry, and thermogravimetric analysis. This review may contribute to the development of using cellulose as a low-cost raw material with anticipated physicochemical properties. Highlights: Morphology and surface topography of cellulose structure is characterized using microscopy techniques including optical microscopy, transmission electron microscopy, scanning electron microscopy, and atomic force microscopy. Analytical techniques used for physicochemical characterization of cellulose include X-ray diffraction, Fourier transform infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance spectroscopy, differential scanning calorimetry, and thermogravimetric analysis.  2022 Wiley Periodicals LLC.</text>
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                <text>Chakraborty I.; Rongpipi S.; Govindaraju I.; Rakesh B.; Mal S.S.; Gomez E.W.; Gomez E.D.; Kalita R.D.; Nath Y.; Mazumder N.</text>
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                <text>Microscopy Research and Technique, Vol-85, No. 5, pp. 1990-2015.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122791301&amp;amp;doi=10.1002%2Fjemt.24057&amp;amp;partnerID=40&amp;amp;md5=4f9307fb615a9f2580f08887ba079c4c" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85122791301&amp;amp;doi=10.1002%2fjemt.24057&amp;amp;partnerID=40&amp;amp;md5=4f9307fb615a9f2580f08887ba079c4c&lt;/a&gt;</text>
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              <elementText elementTextId="196843">
                <text>All Open Access; Green Open Access</text>
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                <text>Chakraborty I., Department of Biophysics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, Manipal, 576104, India; Rongpipi S., Department of Chemical Engineering, The Pennsylvania State University, State College, PA, United States; Govindaraju I., Department of Biophysics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, Manipal, 576104, India; Rakesh B., Department of Life Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India; Mal S.S., Department of Chemistry, National Institute of Technology, Karnataka, Mangaluru, 575025, India; Gomez E.W., Department of Chemical Engineering, The Pennsylvania State University, State College, PA, United States, Department of Biomedical Engineering, The Pennsylvania State University, State College, PA, United States; Gomez E.D., Department of Chemical Engineering, The Pennsylvania State University, State College, PA, United States, Department of Materials Science and Engineering, The Pennsylvania State University, State College, PA, United States, Materials Research Institute, The Pennsylvania State University, State College, PA, United States; Kalita R.D., Department of Biotechnology, Royal Global University, Assam, Guwahati, 781035, India; Nath Y., Department of Serology, State Forensic Science Laboratory, Guwahati, India; Mazumder N., Department of Biophysics, Manipal School of Life Sciences, Manipal Academy of Higher Education, Karnataka, Manipal, 576104, India</text>
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                <text>An Insight into Photophysical Investigation of (E)-2-Fluoro-N-(1-(4-Nitrophenyl)Ethylidene)Benzohydrazide through Solvatochromism Approaches and Computational Studies</text>
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                <text>Guggenheim-Debye method; Light harvesting efficiency; Photophysical properties; Schiff base; Solvatochromic method; TD-DFT</text>
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                <text>A fluoro-based Schiff base (E)-2-fluoro-N?-(1-(4-nitrophenyl)ethylidene)benzohydrazide (FNEB) has been synthesized from condensation of 2-fluorobenzohydrazide and 4?-nitroacetophenone catalyzed by glacial acetic acid with ethanol as the solvent. The dipole moment of FNEB in both the electronic states were found using different solvatochromic approaches such as Lippert-Mataga, Bakhshiev, Kawski-Chamma-Viallet, Reichardt and Bilot-Kawski. The experimental ground state dipole moment of FNEB was calculated using Guggenheim-Debye method and theoretical ground state dipole moment using Bilot-Kawski solvatochromic approach. The solvatochromic behavior of the Schiff base in different solvents was studied using absorption and emission spectra. Catalan and Kamlet-Abboud-Taft parameters were used from the multiple linear regression (MLR) analysis in order to study the solute-solvent interaction. The dipole moments were also calculated using Time Dependent-Density Functional Theory (TD-DFT). The chemical stability of FNEB was determined using computational and Cyclic Voltammetry by the use of obtained energy gap between the frontier orbitals. Using the frontier orbitals energy gap, global reactivity parameters were computed. Further, Light Harvesting efficiency was determined to comprehend the photovoltaic property of the Schiff base.  2019, Springer Science+Business Media, LLC, part of Springer Nature.</text>
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                <text>Journal of Fluorescence, Vol-29, No. 4, pp. 1013-1027.</text>
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                <text>Thadathil D.A., Department of Chemistry, Christ (Deemed to be University), Hosur Road, Bengaluru, 560029, Karnataka, India; Varghese S., Department of Chemistry, Christ (Deemed to be University), Hosur Road, Bengaluru, 560029, Karnataka, India; Akshaya K.B., Department of Chemistry, Christ (Deemed to be University), Hosur Road, Bengaluru, 560029, Karnataka, India; Thomas R., Department of Chemistry, St Berchmans College (Autonomous), Changanassery, 686101, Kerala, India; Varghese A., Department of Chemistry, Christ (Deemed to be University), Hosur Road, Bengaluru, 560029, Karnataka, India</text>
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                <text>Industry 4.0 Key Technological Advances and Design Principles in Engineering, Education, Business, and Social Applications, pp. 17-40.</text>
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                <text>Thomas P., CHRIST (Deemed to be University), Bangalore, Karnataka, India; Jose D.V., CHRIST (Deemed to be University), Bangalore, Karnataka, India</text>
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                <text>An insight into the superior performance of ZnO@PEG nanocatalyst for the synthesis of 1,4-dihydropyrano[2,3-c]pyrazoles under ultrasound</text>
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          <element elementId="49">
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              <elementText elementTextId="187015">
                <text>3-c]pyrazol-6-amine Four-component synthesis Multicomponent reaction; 4-dihydropyrano[2; ZnO@PEG nanoparticle Ultrasonic irradiation 1</text>
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                <text>The investigation presents a straightforward synthesis of fifteen 1,4-dihydropyrano[2,3-c]pyrazoles using ZnO@PEG nanocatalyst in ethanol via Multicomponent approach under the influence of ultrasound. The present methodology successively tolerates a variety of functional groups and offers several advantages such as excellent yields without chromatographic purification, milder reaction conditions, shorter reaction times, and the use of an environmentally benign reusable catalyst. Ecstatically, the reaction was successfully scaled to gram level ascertaining the wider applicability of ZnO@PEG nanoparticles in multicomponent reactions.  2019 Elsevier Ltd. All rights reserved.</text>
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              <elementText elementTextId="187017">
                <text>Tabassum S.; Sunaja Devi K.R.; Govindaraju S.</text>
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                <text>Materials Today: Proceedings, Vol-45, pp. 3898-3903.</text>
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                <text>ISSN: 22147853</text>
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                <text>Tabassum S., Department of Chemistry, Surana College, South End Road, Basavanagudi, Bengaluru, 560004, India; Sunaja Devi K.R., Department of Chemistry, CHRIST (Deemed to be University), Bengaluru, 560029, India; Govindaraju S., Department of Sciences and Humanities, School of Engineering and Technology, CHRIST (Deemed to be University), Kumbalagodu, Mysore Road, Bengaluru, 560074, India</text>
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                <text>An Integrated and Optimized Fog Computing enabled Framework to minimize Time Complexity in Smart Grids</text>
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          <element elementId="49">
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              <elementText elementTextId="171908">
                <text>Cloud Computing; Edge Computing; Fog Computing; Smart Grid</text>
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                <text>A distributed computing paradigm known as 'cloud computing'works as a connection between IoT devices and cloud data centres. The environment system model in this work is on basis of clouds and fog and includes smart grids, which we explore. Prior to understanding the use of fog computing in smart grids we discuss about various features of cloud computing and talk about how to manage the connection between fog and cloud computing. Along with the usual performance of low latency, low cost, and high intelligence, the distinctive characteristics and service scenarios are also explored. Based on the outcome of the simulation, it appears that our suggested PSO-SA algorithm outperforms other optimization algorithms. It recorded a least mean response time of 3.86 seconds only. While the model build up delay was 4.6 seconds, the model execution delay was also found to be only 4.9 seconds with PSO-SA method. The improved efficiency of the technique can be credited to the best aspects of particle swarm optimisation (PSO) and a modified inertia weight obtained by simulated annealing.   2023 IEEE.</text>
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                <text>Nag R.; Samantraj A.S.; Mishra S.; Sharma V.</text>
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                <text>Proceedings of International Conference on Contemporary Computing and Informatics, IC3I 2023, pp. 455-459.</text>
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              <elementText elementTextId="171912">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>The need for integrated care for the elderly has grown globally due to ageing populations and the increasing prevalence of chronic health conditions. Many elderly individuals, particularly those in transnational families, face challenges in accessing adequate care and support, as their family members may be dispersed across different countries. This study addresses the role of social work and legal services in supporting elderly individuals in their home countries, focusing on transnational families. The integration of social work practices and legal frameworks is crucial in providing effective care for the elderly in these complex family dynamics. The research explores the challenges faced by elderly individuals and their families, emphasizing the importance of collaboration between social work professionals and legal experts. The study proposes an integrated care model that combines these services to enhance the well-being and rights of elderly individuals in home countries, offering insights into how this model can be applied in transnational family settings.  The Author(s), under exclusive licence to Institute for Social and Economic Change 2026.</text>
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                <text>An integrated framework for digitalization of humanitarian supply chains in post COVID-19 era</text>
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                <text>Digitalization; Humanitarian supply chain; Neutrosophic DEMATEL; Post COVID-19; Principal component analysis</text>
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                <text>Digital Supply Chains (DSCs) are transforming industries across various domains. Digitalization can improve coordination, increase data collection and retention capacities, enhance funding mechanisms, and improve operational performance and resource utilization. However, DSC adoption is constrained by lack of funding, operational complexities, infrastructure issues, etc. Thus, the need emerges to explore the digitalization of the Humanitarian Supply Chain (HSC) and provide solutions that can ease the adoption of DSC. In this study, a framework is created to facilitate the digitalization process of HSC in post COVID-19 era. Nineteen related drivers are identified with the potential to digitalize the HSC. The drivers are identified from the previous literature and finalized with the assistance of HSC stakeholders. A Principal Component Analysis is carried out to discover the most pertinent drivers from the identified list of drivers. A Kappa analysis is adopted to perfect the priority map of the digitalization drivers. Further, the neutrosophic DEMATEL methodology is adopted to prioritize the potential drivers and find their dependency on each other. The results from the study indicate that the most influential drivers fall under the operational and technological categories. However, the social drivers have the potential to play a significant contribution in an effort to HSC digitalization. In addition, the study presents strategies for enhancing funds collection and data management using emerging technologies. These strategies can assist HSC decision-makers in formulating relevant policies and strategic interventions.  2023 Elsevier Ltd</text>
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                <text>Patil A.; Shardeo V.; Dwivedi A.; Paul S.K.</text>
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                <text>International Journal of Disaster Risk Reduction, Vol-87</text>
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                <text>ISSN: 22124209</text>
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                <text>Patil A., Christ University, Bengaluru, India; Shardeo V., Lal Bahadur Shastri Institute of Management, New Delhi, India; Dwivedi A., Jindal Global Business School, O.P. Jindal Global University, Sonipat, India; Paul S.K., UTS Business School, University of Technology Sydney, Sydney, Australia</text>
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                <text>Honnalli, Vivain; Lajwanti, M.; Stephen, S.; Jaheer Mukthar, K.P.</text>
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                <text>Studies in Systems, Decision and Control;Volume;236;pp.767-778</text>
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                <text>Honnalli V., CHRIST (Deemed to be University), Bangalore, India; Lajwanti M., CHRIST (Deemed to be University), Bangalore, India; Stephen S., CHRIST (Deemed to be University), Bangalore, India; Jaheer Mukthar K.P., Kristu Jayanti College, Autonomous, Bangalore, India</text>
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                <text>The CTF model introduces a new approach to team organization, inspired by the atomic structure of carbon. This interdisciplinary model combines organizational psychology, team dynamics research, and chemistry principles. The paper evaluates current team models, such as Belbins team roles, Hackmans model of team effectiveness, and the GRPI model, emphasizing their strengths and weaknesses. CTF expands on these frameworks while addressing their limitations. It consists of a productivity core (similar to protons and neutrons) and critique networks (similar to electrons), connected by Team Cohesion Factors. Unlike previous models that focus on specific aspects, CTF provides a comprehensive structure that integrates leadership, execution, and feedback mechanisms. It balances a hierarchical structure with collaborative input, including internal and external feedback systems. Inspired by the adaptability of carbon, the model is suitable for dynamic environments. Although it shows promise in addressing the limitations of previous models, CTF needs empirical validation. This paper lays out the theoretical basis of CTF, compares it with existing frameworks, explores its potential benefits and limitations, and outlines future research directions.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.</text>
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                <text>Organizational structure; Team dynamics</text>
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                <text>An integrated model to predict students online learning behavior in emerging economies: a hybrid SEMANN approach</text>
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                <text>Artificial neural networks (ANN); Online learning behaviour; Perceived mobility; Perceived ubiquity; Readiness to learn online; Technology acceptance model (TAM); Theory of planned behaviour</text>
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                <text>Purpose: The online learning environment is a function of dynamic market forces constantly restructuring the e-learning landscapes complete ecosystemcape. This study aims to propose an e-learning framework by integrating the Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB) to predict students Online Learning Readiness and Behaviour. Design/methodology/approach: A structured questionnaire was used to collect data from 406 students through a survey. The data were analysed using two-stage structural equation modelling and artificial neural network (ANN). Findings: The studys results revealed that perceived ubiquity (PUB) positively influences perceived ease of use, usefulness and attitude. Similarly, perceived mobility significantly influences perceived ease of use and attitude. Furthermore, attitude, subjective norms, perceived behavioural control and perceived usefulness significantly influence readiness to learn online, which further influences students online learning behaviour. The root-mean-square error (RMSE) values obtained from the ANN analysis indicate the models predictive solid accuracy. Originality/value: The study contributes to the existing literature by proposing an Online Learning Behaviour Model by integrating the TAM and the TPB frameworks in association with two additional constructs, PUB and Perceived Mobility. Secondly, this study proposes a unique triangulation framework of recommendations for learners, educators and policymakers.  2024, Emerald Publishing Limited.</text>
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                <text>Mathur S.; Tewari A.; Vishnoi S.; Agarwal V.</text>
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                <text>Journal of International Education in Business, Vol-18, No. 1, pp. 102-126.</text>
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                <text>ISSN: 2046469X</text>
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                <text>Mathur S., Department of Marketing, Christ University (Deemed to be University), Ghaziabad, India; Tewari A., School of Management, Babu Banarasi Das University, Lucknow, India; Vishnoi S., Department of Marketing, Institute of Management Studies Ghaziabad, Ghaziabad, India; Agarwal V., Department of Marketing, Institute of Management Studies Ghaziabad, Ghaziabad, India</text>
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