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                <text>Kavitha, Rose; Gour, Shivashish; Srinivasa, G.; Arvind, Tripti</text>
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                <text>Building a sustainable brand in textile industry</text>
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                <text>Asian Textile Journal;Volume;34;Issue;3;pp.31-35</text>
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                <text>Kavitha R., Dept of Management, New horizon College, Bengaluru, 560 103, India, School of Business and Management, Christ University, Bengaluru, 560 029, India; Gour S., Dept of Management, New horizon College, Bengaluru, 560 103, India, School of Business and Management, Christ University, Bengaluru, 560 029, India; Srinivasa G., Dept of Management, New horizon College, Bengaluru, 560 103, India, School of Business and Management, Christ University, Bengaluru, 560 029, India; Arvind T., Dept of Management, New horizon College, Bengaluru, 560 103, India, School of Business and Management, Christ University, Bengaluru, 560 029, India</text>
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                <text>The textile industry is at a pivotal moment where integrating sustainability into brand strategies is not merely an ethical obligation but a competitive necessity. This study highlights three key approaches-adoption of circular economy principles, implementation of blockchain technology for supply chain transparency, and the use of innovative, sustainable materials-that are shaping the future of sustainable brand development in the textile sector.</text>
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                <text>G P S Kwatra</text>
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                <text>ISSN: 9713425;</text>
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                <text>Kavitha, S.; Vinay, M.; Joby, Sona; Ribu, P.B.</text>
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                <text>Automated Classification of Medicinal Plants Using Lightweight Deep Learning and Transfer Learning</text>
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                <text>SN Computer Science;Volume;7;Issue;3;Article No.;263;</text>
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                <text>Kavitha S., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Vinay M., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Joby S., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Ribu P.B., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India</text>
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                <text>The identification of medicinal plants plays a pivotal role in traditional medicine, biodiversity conservation, and rural healthcare. Conventional manual identification methods are often time-consuming and error-prone, particularly when differentiating between morphologically similar species or plants at varying growth stages. Recent developments in deep learning, especially convolutional neural networks (CNNs) with transfer learning, have emerged as robust solutions for image-based classification tasks, offering efficiency and high accuracy with limited computational resources. The proposed framework employs a carefully structured deep learning pipeline integrating advanced preprocessing, lightweight architecture design, and domain-adaptive transfer learning. A large real-world dataset of 20,109 medicinal leaf images across 99 classes was standardized through resizing, normalization, and categorical encoding, followed by targeted data augmentation and class-weight balancing to address inter-class similarity and dataset imbalance. A key methodological novelty lies in the use of MobileNetV3 with an optimized transfer-learning strategy, leveraging its inverted residual blocks, Squeeze-and-Excite modules, and hard-swish activation to enhance texture-, venation-, and contour-based feature extraction in plant leaves. Unlike existing plant-recognition studies that rely on heavier CNNs, our approach introduces a computationally efficient, low-latency model specifically tailored for mobile and embedded deployment. Experimental results demonstrate that the proposed MobileNetV3-based model achieved a classification accuracy of 92.88%, with macro- and weighted-average F1-scores of 0.85 and 0.86, respectively. Precision and recall values across most classes ranged between 0.80 and 0.95, confirming the models reliability in differentiating species.  The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2026.</text>
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                <text>Biodiversity informatics; Deep learning; Feature extraction; Healthcare technology; Medicinal plants; Plant identification; Smart agriculture tools</text>
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                <text>ISSN: 2662995X;</text>
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                <text>Evaluation of phytoconstituents of Triticum aestivum grass extracts on nutritional attributes, antioxidant, and antimicrobial activities against food pathogens with molecular in silico investigation</text>
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                <text>carbohydrates; diphenyl-1-picryl-hydrazyl; gas columnmass spectroscopy; proteins; Pseudomonas aeruginosa; Staphylococcus aureus</text>
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                <text>The plant-based medicine and diet is gaining importance in recent days. The consumption of Triticum aestivum grass in the form of juice and tablets is increasing among common people. The present study elaborates on the nutritional, antioxidant, and antimicrobial potential of a nongenetically modified type of T. aestivum grass, along with the evidence of molecular docking studies. The T. aestivum grass extracts like decoction, aqueous, ethanol, and chloroform were subjected to preliminary phytochemical tests, quantitative estimation, antioxidant analysis, and antimicrobial activity determination. The ethanolic extract that had good antioxidant and antimicrobial potential was subjected to gas columnmass spectroscopy (GCMS) analysis and the compounds identified were docked against the antioxidant and antimicrobial receptors. The decoction and aqueous extracts performed well in preliminary qualitative tests with the presence of most of the phytochemicals tested. The decoction, aqueous, and ethanolic extracts possessed good concentrations of the phytochemicals. The decoction had about 210.839.16 and 154.160.33mg/g of carbohydrates and proteins, respectively, while the aqueous extract had about 10.910.08mg/g of amino acids and the ethanolic extract had about 52.51.4mg/g of phenolic content, which were the highest concentration of the phytochemicals observed among the extracts. Along with phytochemical potential, good antioxidant potential in the DPPH and ABTS by decoction as well as ethanolic extract with nearly 40 and 90% inhibition, respectively, and in FRAP by aqueous extract with maximum OD value. The ethanolic extract exhibited the best inhibition potential against the Staphylococcus aureus about 281mm, Pseudomonas aeruginosa with 202mm, Bacillus cereus at 201mm by the ethanolic extract at 200?g concentration, and Aspergillus fumigatus and A. niger at 150mm by the aqueous extract at 200?g concentration. The GCMS analysis revealed the presence of terpenoids, alkaloids, and phenols, which on docking had highest binding capacity toward the antioxidant and antimicrobial receptors.  2023 The Authors. Food Frontiers published by John Wiley &amp;amp; Sons Australia, Ltd and Nanchang University, Northwest University, Jiangsu University, Zhejiang University, Fujian Agriculture and Forestry University.</text>
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              <elementText elementTextId="95381">
                <text>Kaviya M.; Balamuralikrishnan B.; Sangeetha T.; Senthilkumar N.; Malaisamy A.; Sivasamy M.; Poorni L.; Pushparaj K.; Arun M.; Anand A.V.</text>
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                <text>Food Frontiers, Vol-4, No. 2, pp. 831-848.</text>
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              <elementText elementTextId="95383">
                <text>John Wiley and Sons Inc</text>
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                <text>&lt;a href="https://doi.org/10.1002/fft2.233" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1002/fft2.233&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85157983994&amp;amp;doi=10.1002%2Ffft2.233&amp;amp;partnerID=40&amp;amp;md5=2a68fedd40afeae4218bfbacb781054e" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85157983994&amp;amp;doi=10.1002%2ffft2.233&amp;amp;partnerID=40&amp;amp;md5=2a68fedd40afeae4218bfbacb781054e&lt;/a&gt;</text>
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 26438429</text>
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                <text>Kaviya M., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India; Balamuralikrishnan B., Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, South Korea; Sangeetha T., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India; Senthilkumar N., Department of Bioprospecting of Forest Resources, Institute of Forest Genetics and Tree Breeding (IFGTB), Forest Campus, Tamil Nadu, Coimbatore, India; Malaisamy A., Transcription Regulation Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India; Sivasamy M., Division of Crops Improvement, Indian Council of Agricultural Research (ICAR) - Indian Agricultural Research Institute, Regional Station, Wellington, Tamil Nadu, Nilgiris, India; Poorni L., Department of Biochemistry, Vivekanandha College of Arts and Sciences for Women, Tamil Nadu, Namakkal, India; Pushparaj K., Department of Zoology, School of Biosciences, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, Coimbatore, India; Arun M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India; Anand A.V., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India</text>
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                <text>Dietary Plants, Spices, and Fruits in Curbing SARS-CoV-2 Virulence</text>
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                <text>Patients with coronavirus disease 2019 (COVID-19) infection can suffer from a variety of neurological disorders; therefore, there is a demand to investigate specific treatments. As a part of this endeavor, academic databases related to clinical, neuropathological, and immunological biomarkers were examined for searching promising drugs to treat neurological disorders in the COVID-19 group. Also, the neuroprotective potential of herbs for patients with post-COVID-19 has been evaluated using PubMed, MEDLINE, Scopus, EMBASE, Google Scholar, EBSCO, Web of Science, Cochrane Library, WHO database, and ClinicalTrials.gov. The terms used for the Boolean search were Indian herbs and neuroprotective potential, post-COVID-19 symptoms, and so on. Based on our knowledge, nervous system immunity is an inherent characteristic of the nervous system because it is highly immunologically active. It was found that patients infected with COVID-19 often experience neurological symptoms such as muscle pain, headaches, confusion, dizziness, and loss of smell and taste. The most commonly used herbs for neurological disorders are Bacopa monnieri, Mucuna pruriens, Withania somnifera, Acorus calamus, Phyllanthus emblica, Blumea balsamifera, Asparagus racemosus, Cannabis sativa, Convolvulus prostratus, Swertia chirata, Vitex negundo, Nyctanthes arbor-tristis Linn, Centella asiatica, Curcuma longa, Ocimum tenuiflorum. It is widely recognized that herbal drugs have the potential for treating neurological diseases such as Parkinsons, Alzheimers, and cerebrovascular diseases in COVID-19 patients. However, clinical trials are still limited. The suitability of drugs depends on the investigation of biomarkers and pathobiological mechanisms. Thus, it is necessary to use modern scientific approaches and technologies to conduct comprehensive mechanistic studies to understand the therapeutic potential of herbs for neurological disorders associated with the SARS-CoV-2 infection.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.</text>
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                <text>Kaviya M.; Geofferina I.P.; Poornima P.; Rajan A.P.; Balamuralikrishnan B.; Arun M.; Al-Dhabi N.A.; Arasu M.V.; Karthika P.; Kallidass S.; Ramya S.; Anand A.V.</text>
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                <text>Ethnopharmacology and Drug Discovery for COVID-19: Anti-SARS-CoV-2 Agents from Herbal Medicines and Natural Products, pp. 265-316.</text>
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                <text>Kaviya M., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India; Geofferina I.P., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India; Poornima P., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India; Rajan A.P., Department of Bio-Medical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Tamil Nadu, Vellore, India; Balamuralikrishnan B., Department of Food Science and Biotechnology, Sejong University, Seoul, South Korea; Arun M., Department of Life Sciences, CHRIST Deemed to be University, Bengaluru, India; Al-Dhabi N.A., Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia; Arasu M.V., Department of Botany and Microbiology, College of Science, King Saud University, Riyadh, Saudi Arabia; Karthika P., Department of Zoology, Avinashilingam Institute for Home Science and Higher Education for Women, Tamil Nadu, Coimbatore, India; Kallidass S., Department of Animal Science, Manonmaniam Sundaranar University, Tamil Nadu, Tirunelveli, India; Ramya S., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India; Anand A.V., Department of Human Genetics and Molecular Biology, Bharathiar University, Tamil Nadu, Coimbatore, India</text>
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                <text>Kaviya P K - 1940088</text>
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                <text>The bacterium Mycobacterium tuberculosis is responsible for causing the disease newlinetuberculosis in mammals, which is regarded as one of the oldest diseases haunting the human race. The only available tuberculosis vaccine Bacillus Calmette-Guerine (BCG), is effective against childhood tuberculosis but is regarded as having low efficacy in conferring protection in the case of tuberculosis in adults. A comparison of the M. tuberculosis H37Rv strain and clinical isolates from Kerala had earlier revealed that the clinical strains have a distinctive 4.5 kb genomic sequence that is lacking from the H37Rv strain in the RD7 region. The RD7 is a distinctive genomic region that is absent in M. tuberculosis H37Rv and Mycobacterium bovis BCG strain. The 4.5 kb genomic sequence is projected to include 6 potential ORFs by newlineNCBI ORF prediction tool, one of which Novel Hypothetical Protein (NHP2) is anticipated to encode an exported protein with a length of 268 amino acids. Studies demonstrate that Mycobacterium tuberculosis secretory proteins such as the Ag85 complex, the ESAT-6 family protein, and the PE-PPE family proteins were newlineeffective vaccine candidates because they trigger T cells. Here, we present an indepth analysis of the exported protein, which is 268 amino acids long. The putative exported protein with a gene 807 bp long was PCR amplified and cloned in the expression vector pET-32a for expression. The protein was over expressed using Isopropyl D-1-thiogalactopyranoside (IPTG) and was isolated and purified using column chromatography. Bioinformatics studies were conducted to study the characteristics of the expressed protein. A novel putative mycobacterial protein discovered by subtractive hybridization was studied for its potential as a vaccine candidate using cutting-edge computer technologies.</text>
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                <text>Kaviya, P K</text>
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                <text>S, Suma.</text>
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                <text>&lt;a href="http://hdl.handle.net/10603/551690" target="_blank" rel="noreferrer noopener"&gt;http://hdl.handle.net/10603/551690&lt;/a&gt;</text>
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                <text>Machining Characteristics Evaluation of Al7075TiB2 In Situ Composite Using Abrasive Water Jet Machining with Varied Test Parameters</text>
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                <text>Abrasive water jet; Al7075TiB&lt;sub&gt;2&lt;/sub&gt;; In situ process; Surface roughness; VMRR</text>
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                <text>The study delves into the abrasive water jet (AWJ) cutting of an Al7075TiB2 metal matrix composite that was synthesized in situ. The primary goal is to investigate how variations in three key process parameters, namely, stand-off distance (SOD) ranging from 0.5 to 2.5mm, abrasive flow rate (100 to 300gmin), and traverse speed (100 to 500mmmin), affect three critical performance metrics: volumetric material removal rate (VMRR), dimensional accuracy, and surface roughness (SR). The study's findings were represented graphically, highlighting the relationships between these responses and the aforementioned process parameters. Scanning electron microscopy (SEM) was also used to examine the machined surfaces. It was discovered that increasing traverse speed resulted in significant increases in surface roughness, VMRR, and dimensional errors. An increase in the SOD, on the other hand, resulted in an increase in surface roughness, VMRR, and a decrease in dimensional accuracy. Furthermore, increasing the abrasive flow rate resulted in lower surface roughness and dimensional accuracy while achieving a higher VMRR.  2023, The Institution of Engineers (India).</text>
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                <text>Kavya J.T.; Keshavamurthy R.; Ravishankar M.K.; Pradeep Kumar G.S.</text>
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                <text>Journal of The Institution of Engineers (India): Series D</text>
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                <text>&lt;a href="https://doi.org/10.1007/s40033-023-00597-1" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s40033-023-00597-1&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178937550&amp;amp;doi=10.1007%2Fs40033-023-00597-1&amp;amp;partnerID=40&amp;amp;md5=05dc99f4d44f01b177a87907191a98d7" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178937550&amp;amp;doi=10.1007%2fs40033-023-00597-1&amp;amp;partnerID=40&amp;amp;md5=05dc99f4d44f01b177a87907191a98d7&lt;/a&gt;</text>
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                <text>ISSN: 22502122</text>
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                <text>Kavya J.T., Department of Automobile Engineering, Dayananda Sagar College of Engineering, Bangalore, 560111, India; Keshavamurthy R., Department of Mechanical Engineering, Dayananda Sagar College of Engineering, Bangalore, 560111, India; Ravishankar M.K., Department of Automobile Engineering, Malnad College of Engineering, Hassan, 573202, India; Pradeep Kumar G.S., Department of Mechanical and Automobile Engineering, Christ University, Bengaluru, 560074, India</text>
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                <text>Mathematical approach for impact of media awareness on measles disease</text>
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                <text>media awareness; predictor corrector method; SEIR model; stability</text>
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                <text>During the recent pandemic caused by COVID-19, media awareness played a crucial role in educating people about social distancing, wearing masks, quarantine, vaccination, and medication. Media awareness brought individual behavioral changes among the people, which in turn helped reduce the infection rate. Motivated by this, we have formulated a mathematical model introducing a media compartment to mitigate measles disease transmission. In this paper, the SEIR model is used to study measles disease in three cases: one with a delay in vaccination, the second with regular vaccination, and the third with the impact of media awareness on the spreading of measles disease. Further, the dynamical behavior of the models is studied in terms of positivity, boundedness, equilibrium, and basic reproduction number (BRN). The sensitivity analysis of the models is conducted, which verifies the importance of the BRN ((Formula presented.)) to be less than one for disease eradication. The numerical study confirms the impact of media awareness on exposed and infected populations.  2023 John Wiley &amp;amp; Sons Ltd.</text>
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                <text>Kavya K.N.; Veeresha P.</text>
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                <text>Mathematical Methods in the Applied Sciences, Vol-47, No. 1, pp. 120-146.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169667479&amp;amp;doi=10.1002%2Fmma.9645&amp;amp;partnerID=40&amp;amp;md5=0501516e1d49e269dab499766958794e" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85169667479&amp;amp;doi=10.1002%2fmma.9645&amp;amp;partnerID=40&amp;amp;md5=0501516e1d49e269dab499766958794e&lt;/a&gt;</text>
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                <text>ISSN: 1704214; CODEN: MMSCD</text>
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                <text>Kavya K.N., Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, India; Veeresha P., Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, India</text>
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                <text>Modelling temperature-dependent malaria transmission vector model considering different levels of immunity in host population</text>
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              <elementText elementTextId="100361">
                <text>host model; Malaria; numerical method; stability; vector model</text>
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                <text>Malaria is spread by female Anopheles mosquitoes, which complete their life cycle by feeding on human blood. Parasites from the mosquito's saliva enter the human bloodstream through a mosquito bite. Thus, the link between humans and mosquitoes to parasites is established. According to WHO statistics, malaria appears widespread in tropical and subtropical locations around the equator, including most of Sub-Saharan Africa, Latin America, and Asia. The most prevalent causes of malaria transmission might be amicable temperature, which aids in the growth of the mosquito life-cycle, and a failure to maintain the local socio-economic condition, which reduces individual immunity. This study proposes the vector-host model to understand the spread of malaria infection. A vector model is used to understand the effects of temperature on the development of egg, larval, pupal, and adult mosquito populations. Furthermore, the role of immunity is being explored using the host model. Numerical simulations support the influence of temperature on disease transmission. The study draws attention to the fact that, along with issues like global warming and climate change, managing the socio-economic conditions of the area (healthcare facilities, environmental improvement) is essential for malaria eradication.  CSP - Cambridge, UK; I&amp;amp;S - Honda, USA, 2023</text>
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                <text>Kavya K.N.; Veeresha P.; Akinyemi L.</text>
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                <text>Mathematics in Engineering, Science and Aerospace, Vol-14, No. 3, pp. 809-833.</text>
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              <elementText elementTextId="100365">
                <text>Cambridge Scientific Publishers</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171476256&amp;amp;partnerID=40&amp;amp;md5=76942a1e22d7ce748df37421d3f15331" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171476256&amp;amp;partnerID=40&amp;amp;md5=76942a1e22d7ce748df37421d3f15331&lt;/a&gt;</text>
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                <text>ISSN: 20413165</text>
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                <text>Kavya K.N., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Veeresha P., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Akinyemi L., Department of Mathematics, Lafayette College, Easton, PA, United States</text>
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                <text>Mathematical modeling to investigate the influence of vaccination and booster doses on the spread of Omicron</text>
              </elementText>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="82756">
                <text>Basic reproduction number; Omicron; Predictor corrector method; Stability; Vaccination</text>
              </elementText>
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              <elementText elementTextId="82757">
                <text>The emergence of new variants, such as Omicron, has raised concerns regarding the transmission dynamics of COVID-19 and the effectiveness of vaccination strategies. This paper proposes a mathematical model to investigate the impact of vaccination and booster doses on Omicron transmission dynamics, considering various infection compartments. The model incorporates multiple compartments representing different stages of infection, including susceptible individuals, vaccinated individuals, boosted individuals, and those infected with Omicron. The infection dynamics are captured by parameters such as vaccine efficacy, vaccination with booster received efficacy, and infection rate. Using mathematical analysis and numerical simulations, we explore how different vaccination and booster strategies affect the spread of Omicron. The normalized sensitivity analysis method of R0 is investigated to understand the importance of parameters in disease transmission. Furthermore, we assess the influence of infection compartments, such as asymptomatic and symptomatic cases, on overall transmission dynamics.  2023 Elsevier B.V.</text>
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                <text>Kavya K.N.; Veeresha P.; Baskonus H.M.; Alsulami M.</text>
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              <elementText elementTextId="82759">
                <text>Communications in Nonlinear Science and Numerical Simulation, Vol-130</text>
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              <elementText elementTextId="82760">
                <text>Elsevier B.V.</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.cnsns.2023.107755" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.cnsns.2023.107755&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178497716&amp;amp;doi=10.1016%2Fj.cnsns.2023.107755&amp;amp;partnerID=40&amp;amp;md5=fcc0d4e770f99827b6bd02ecf19307bb" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85178497716&amp;amp;doi=10.1016%2fj.cnsns.2023.107755&amp;amp;partnerID=40&amp;amp;md5=fcc0d4e770f99827b6bd02ecf19307bb&lt;/a&gt;</text>
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                <text>ISSN: 10075704</text>
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                <text>Kavya K.N., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Veeresha P., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Baskonus H.M., Department of Mathematics and Science Education, Faculty of Education, Harran University, Sanliurfa, Turkey; Alsulami M., Department of Mathematics, Faculty of Science, King Abdulaziz University, P.O. Box 80203, Jeddah, 21589, Saudi Arabia</text>
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          <element elementId="50">
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              <elementText elementTextId="101896">
                <text>High-affinity binding of celastrol to monomeric ?-synuclein mitigates invitro aggregation</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="101897">
                <text>aggregation; celastrol; Parkinsons disease; phytochemical; ?-Synuclein</text>
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              <elementText elementTextId="101898">
                <text>?-Synuclein (?Syn) aggregation is associated with Parkinsons disease (PD). The region ?Syn36-42 acts as the nucleation 'master controller and ?Syn1-12 as a secondary nucleation site. They drive monomeric ?Syn to aggregation. Small molecules targeting these motifs are promising for disease-modifying therapy. Using computational techniques, we screened thirty phytochemicals for ?Syn binding. The top three compounds were experimentally validated for their binding affinity. Amongst them, celastrol showed high binding affinity. NMR analysis confirmed stable ?Syn-celastrol interactions involving several residues in the N-terminus and NAC regions but not in the C-terminal tail. Importantly, celastrol interacted extensively with the key motifs that drive ?Syn aggregation. Thioflavin-T assay indicated that celastrol reduced ?Syn aggregation. Thus, celastrol holds promise as a potent drug candidate for PD. Communicated by Ramaswamy H. Sarma.  2023 Informa UK Limited, trading as Taylor &amp;amp; Francis Group.</text>
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                <text>Kavya R.; Aouti S.; Jos S.; Prasad T.K.; Kumuda K.N.; Unni S.; Padmanabhan B.; Kamariah N.; Padavattan S.; Mythri R.B.</text>
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              <elementText elementTextId="101900">
                <text>Journal of Biomolecular Structure and Dynamics, Vol-41, No. 22, pp. 12703-12713.</text>
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                <text>Kavya J.T., Department of Automobile Engineering, Dayananda Sagar College of Engineering, Bangalore, 560111, India; Keshavamurthy R., Department of Mechanical Engineering, Dayananda Sagar College of Engineering, Bangalore, 560111, India; Ravishankar M.K., Department of Automobile Engineering, Malnad College of Engineering, Hassan, 573202, India; Pradeep Kumar G.S., Department of Mechanical and Automobile Engineering, Christ University, Bengaluru, 560074, India</text>
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                <text>Rapid urbanization has significantly increased the demand for residential housing, underscoring the need for real estate retailers to comprehend the factors that drive homebuyers' purchasing behavior. This study employs a Structural Equation Modelling (SEM) framework to examine the critical determinants of purchase intention within the residential real estate sector. Key constructs analyzed include housing attributes, financial and economic considerations, location and service quality, environmental concerns, brand image, and information sources. The SEM analysis elucidates the strength and significance of the relationships among these variables, providing a comprehensive understanding of consumer decision-making processes. The findings yield actionable insights for real estate practitioners, offering guidance for the development of targeted marketing strategies, enhanced customer engagement practices, and improved service delivery. By aligning their offerings with buyer expectations, real estate firms can foster stronger client relationships and enhance their competitive positioning in a dynamic housing market.  Authors.</text>
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                <text>This study investigates the association between Brand Image, Attitude Toward Behaviour, and Purchase Intention within the Indian real estate sector. The research employs the Theory of Planned Behaviour (TPB) to examine the impact of brand image on purchase intention, with attitude toward behaviour serving as a mediating role. Data were gathered from 422 respondents. The collected data is inspected using Structural Equation Modeling (SEM hereafter) utilising JMP Software. The findings demonstrate that brand image has a substantial effect on purchase intention, both directly as well as indirectly, via attitude towards behaviour. The results emphasize the need to establish a robust brand image to cultivate favourable consumer perceptions and influence purchasing decisions, providing essential insights for real estate developers in a competitive landscape.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.</text>
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                <text>Kavya N.S., Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru 560029, India; Mishra S.S., Department of Mathematics, School of CS &amp;amp; AI, SR University, Telangana, Warangal, 506371, India; Sahoo P.K., Department of Mathematics, Birla Institute of Technology and Science, Pilani, Hyderabad Campus, Jawahar Nagar, Kapra Mandal, Medchal District, Telangana, 500078, India; Capozziello S., Dipartimento di Fisica E Pancini, Universitdegli Studi di Napoli Federico II, Complesso Universitario di Monte S. Angelo, Via Cinthia Edificio 6, Napoli, I-80126, Italy, Scuola Superiore Meridionale, Via Mezzocannone 4, Napoli, I-80134, Italy, Istituto Nazionale di Fisica Nucleare  Sezione di Napoli, Via Cinthia, Napoli, I-80126, Italy</text>
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                <text>The accelerated expansion of the Universe remains a fundamental challenge in cosmology, motivating model-independent methods to reconstruct its expansion history without relying on specific dark energy models. Cosmography, which employs series expansions of cosmological observables around the present epoch, provides a powerful kinematic framework rooted in the cosmological principle. However, standard Taylor expansions suffer from limited convergence at high redshift, prompting the exploration of alternative expansions. In this work, logarithmic polynomial cosmography is investigated, which expands observables in powers of the logarithm of redshift, thereby enhancing convergence over a broad redshift range while maintaining physical insight. The logarithmic polynomial parameters are constrained using recent datasets, including gravitational-wave standard sirens, DESI DR2, cosmic chronometers, and multiple Type Ia supernova compilations (DES-SN5YR, Union3, Pantheon+SH0ES). The analysis demonstrates the efficacy of the logarithmic approach in accurately modeling the cosmic expansion history, providing an interpretable alternative to traditional cosmographic techniques.  2026 Wiley-VCH GmbH.</text>
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                <text>Kavya N.S., Center for Mathematical Needs, Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, 560029, India; Swagat Mishra S., Department of Mathematics, Birla Institute of Technology and Science, Pilani, Jawahar Nagar, Kapra Mandal, Medchal District, Telangana, Hyderabad, 500078, India; Sahoo P.K., Department of Mathematics, Birla Institute of Technology and Science, Pilani, Jawahar Nagar, Kapra Mandal, Medchal District, Telangana, Hyderabad, 500078, India</text>
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                <text>The symmetric teleparallel framework brings about the possibility of alleviating cosmological tensions. The current burning issue in cosmological studies is the increase in discrepancies in measurements from several surveys. Here, we have focused on and tensions, which are important factors in describing the evolution of the Universe from primordial perturbation to late-time acceleration. Additionally, the consistency of the sound horizon is verified against the Planck results. The gravity model is constrained using recently obtained data. Implementing gravitational wave data to study late-time acceleration is one of the key features of our study. Since standard sirens show promising results, the implementation of gravitational waves to probe dark energy is an interesting study. Through our work, we introduce this possibility by performing statistical MCMC analysis for late-time cosmological evolution. Also, the and tensions are explored utilizing gravitational wave data alongside other prominent datasets, such as the latest DESI BAO, redshift space distortion, cosmic chronometers, Pantheon+SH0ES, and cosmic microwave background data. With the results obtained, we analyzed the profile of cosmological parameters. Finally, the study presents the tension of the model with observations, which is found to have a much lower magnitude compared to the current trend. Thus, the considered f(Q) model alleviates tension, making it the best candidate for further investigation.  The Author(s) 2025.</text>
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                <text>CMB; DESI DR2; f(Q) gravity; Gravitational wave data; H&lt;sub&gt;0&lt;/sub&gt;; S&lt;sub&gt;8&lt;/sub&gt; tension</text>
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                <text>The Mediating Effect of WorkLife Integration on the Relationship Between Hybrid Work Practice and Work Engagement in the Information Technology Industry</text>
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                <text>South Asian Journal of Human Resources Management;Issue;;Article No.;2.32209372513392e+16;</text>
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                <text>&lt;a href="https://doi.org/10.1177/23220937251339289" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1177/23220937251339289&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105007022332?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105007022332?origin=resultslist&lt;/a&gt;</text>
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                <text>Kavya R., Research Scholar, School of Business and Management, Christ University, Karnataka, Bengaluru, India; Mathew J., Professor and Dean, School of Business and Management, Christ University, Karnataka, Bengaluru, India; Raghavendra A.N., School of Business and Management, Christ University, Karnataka, Bengaluru, India</text>
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                <text>Post-pandemic, hybrid work arrangements have garnered the interest of researchers. The main aim of the study is to explore the influence of hybrid work practices on worklife integration and work engagement among IT industry employees. The job demandsresources (JD-R) model and self-determination theory (SDT) have been used to derive the conceptual model to explain the hybrid work practices which can be essential for a balance between work and life, and engagement at work. Using a mixed method, this research first quantitatively investigated hybrid work practices, worklife integration and work engagement among 253 IT employees in India. The quantitative findings were supplemented by a qualitative methodology involving interviews of five IT employees. Later, data triangulation was performed to cover IT employees different perspectives on hybrid work practices. This research highlights that hybrid work practices constituting conventional workplace, work flexibility, work focus and work communication are positively related to worklife integration and employees work engagement. Hybrid work practices play an elemental role in work-related outcomes; however, due to the complex nature of hybrid work mode, longitudinal studies with a larger sample size should be explored.  The Author(s) 2025.</text>
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