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                <text>Carbon Dots from Natural Sources for Biomedical Applications</text>
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                <text>bioimaging; carbon dots; chemiluminescence; drug delivery; nanomedicine; photodynamic therapy; photothermal therapy; toxicity</text>
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                <text>Carbon dots (CD), a class of 0D nanomaterials, have gained much research attention over the years due to their uniqueness in properties such as tunable photoluminescence, biocompatibility, low toxicity, water-solubility, and chemical stability. Converting inexpensive biomass to valuable materials highlights the synthesis and applications of biomass-derived CDs. This review summarizes the research and development related to the synthesis, properties, and applications of biomass-derived CDs, furnishing a comprehensive list of biomass-derived CDs with their properties and potential applications. This review's discussions and references span the properties that equip CDs for their diverse biomedical applications, such as bioimaging, sensing, drug delivery, phototherapy, and nanomedicine.  2022 Wiley-VCH GmbH.</text>
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                <text>Ayiloor Rajesh G., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; John V.L., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Pookunnath Santhosh A., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India; Krishnan Nair Ambika A., Centre for Neuroscience, Department of Biotechnology, Cochin University of Science and Technology (CUSAT), Kerala, Kochi, 682022, India; Thavarool Puthiyedath V., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Karnataka, Bangalore, 560029, India</text>
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                <text>The quest for finding the right candidate for their post has made the recruiters employ several methods since the beginning of corporate job recruitment. Apart from the skills and the quality of interview, a thing that matters the most and forms the basis of selection is the candidate's resume. Recruiters and companies have a tough time dealing with the several thousands resumes of the candidates which apply, as manually scanning them and finding the right selection can be tough most of the time. In this paper, Natural Language Processing(NLP) methods have been integrated with ontologies to improve the pace and quality of the recruitment process by proposing an automatic resume parser model. The resume of a candidate, along with his LinkedIn and GitHub profiles are weighted and using the Greywolf algorithm, the global maxima of the most deserving and qualified candidate are found and are recommended with a high accuracy of 96.13%.  2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0)</text>
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                <text>Ayush Kumar A., National Institute of Technology, Tiruchirappalli, India; Deepak G., Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, India; Sheeba Priyadarshini J., CHRIST (Deemed to be University), Bangalore, India</text>
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                <text>As the area of computational intelligence evolves, the dimensionality of any sort of data gets expanded. To solve this issue, Rough Set Theory (RST) has been successfully used for finding reducts as it requires only supplied data and no additional information. This paper investigates a novel search strategy for minimal attribute reduction based on rough sets and Ant Lion Optimization (ALO). ALO is a nature-inspired algorithm that mimics the hunting mechanism of ant lions, and this is inspired to find the minimum reducts. Datasets from the UCI repository are used in this paper. The experimental results show that the features selected by the proposed method are well classified with reasonable accuracy.  2020 IEEE.</text>
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                <text>The selection of an algorithm to tackle a certain problem is a vital undertaking that necessitates both time and knowledge. Non-functional needs, such as the size, quality, and nature of the data, must frequently be taken into account. To develop a generalized machine learning model for any domain, the most relevant features must be chosen because noisy and irrelevant characteristics degrade data mining performance. However, the selection of the dominating features is still dependent on the search technique. When there are a high number of input features, stochastic optimization can be applied to the search space. In this research, the authors investigate the ant lion optimization (ALO), a natureinspired algorithm that mimics the hunting process of ant lions and is further stimulated to identify the smallest reducts. They also investigate rough set-based ant lion optimizer for feature selection. The actual results reveal that the ant lion-based rough set reduct selects a better feature subset and classifies them more accurately.  2022 Information Resources Management Association. All rights reserved.</text>
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                <text>Azar A.T., College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi Arabia, Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt; Nizar Banu P.K., Department of Computer Science, CHRIST (Deemed to Be University), Bangalore, India</text>
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                <text>Analysis of day-to-day weather patterns is critical and essential in daily life. Although traditional methods exist, in modern times, we have developed realistic and reliable methods to provide better insights and understanding of complex weather patterns for various surges, especially in these times of global warming. Implementing clustering and topological data analysis in this analysis has looked into a vast understanding of how regions with similar characteristics behave when weather changes occur due to heat, pressure, or wind-related phenomena. The classification model developed using Mapper analysis has produced 95.8% accuracy, concluding that weather follows a transient weather pattern due to various resources and how stagnant conditions affect transient weather patterns, causing rise in sub-clusters. Thus, fitting and interpreting newer models helps us understand weather analysis and classification.  2024, IGI Global. All rights reserved.</text>
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                <text>Ethics, Machine Learning, and Python in Geospatial Analysis, pp. 279-303.</text>
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                <text>Tightened-normal-tightened (TNT) sampling scheme is one of the most frequently used sampling schemes for making decisions about the finished product lots by examining certain samples from the lots. TNT sampling scheme includes two attribute sampling plans, one for tightened inspection and other for normal inspection along with switching rules. This paper introduces a procedure for TNT by incorporating two single sampling plans (SSP) under the conditions of intervened Poisson distribution (IPD) for the lots which may have a possibility of someintervention during the production process. The paper also assesses the performance of the proposed scheme procedure through its operating characteristic curves. Also, the unity value table is provided for certain parameters of specified producer's risk and consumer's risk for shop floor conditions. Further, the efficiency of proposed TNT scheme over the individual SSP under the conditions of IPD is demonstrated with illustrations.  2019 University of the Punjab.</text>
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                <text>Pakistan Journal of Statistics and Operation Research, Vol-15, No. 1, pp. 129-140.</text>
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                <text>Azarudheen S., Department of Statistics, CHRIST, India; Veerakumari K.P., Department of Statistics, Bharathiar University, India</text>
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                <text>Patent Number: 202141042517, Applicant: Dr.V. Muthukumaran.&#13;
The medical industry attains the highest priority among all the other industrial sectors as people expect high-quality treatment and timely execution of medical procedures regardless of cost. The biomedical imaging and its contributory aspects have taken the medical industry to another level, even though it has yet to fulfil the social expectations but still consume the maximum budget. In many of the interpretation of the case of medical images being performed by the medical expertise or a doctor has got certain limitations due to many factors as a normal human eye cannot distinguish variations which exist among the different interpreters and an image can have many sorts of internal complexities among the arrangement of pixel entities where visual interpretation simply may not provide insightful information and result in fatigue.</text>
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                <text>The objective of this study was to explore the lived experiences of food insecurity amongst Bronx residents. Applying a community-based participatory research approach, we conducted a qualitative study, entailing 38 interviews with food pantry recipients, 4 key informant interviews with social service administrators, and two focus groups with 12 food pantry staff and social service providers in New York City (NYC). Applying a precarity framework, we identified three themes: (1) unaffordability of living expenses in NYC; (2) financial hardships during the COVID-19 pandemic; and (3) institutional and technological barriers to food access. We identified the following subthemes under theme one: rising food costs and high cost of living. Under theme two, we identified four subthemes: (a) large household size driving poverty for Bronx families; (b) vulnerabilities to food insecurity among older adults; (c) budgeting for reduced incomes during the COVID-19 pandemic; and (d) managing unstable employment. Under the third theme, we identified three subthemes: (a) lack of access to healthy, culturally appropriate foods; (b) need for wider service availability; (c) and not having smartphones for telehealth. Study findings demonstrate how precarity impacts the lived experiences of food insecurity and financial hardship for residents of the South Bronx during the COVID-19 pandemic.  2024 Association for the Study of Food and Society (ASFS).</text>
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                <text>Azhar S., Graduate School of Social Service, Fordham University, United States; Ross A.M., School of Social Policy and Practice, University of Pennsylvania, United States; Acharya A., Department of Economics, Christ University, Bangalore, India; Lerner R., Graduate School of Social Service, Fordham University, United States; Tripathi S., Department of Social Work, Binghamton University, State University of New York, Binghamton, NY, United States; Keller E., Fordham College at Rose Hill, Fordham University, United States; Weed J., Bronx Works, New York, NY, United States; Acevedo G., Graduate School of Social Service, Fordham University, United States</text>
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                <text>PATENTABILITY OF BIOTECHNOLOGY INVENTIONS: Indian Ethical Guidelines</text>
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                <text>Advances in technology have made patenting of biotechnology inventions mandatory. The patent law system contains general clauses prohibiting the patenting of inventions contrary to public order or morality. Recent years have brought numerous debates on limiting the possibility of patent protection for biotechnology inventions for ethical reasons. The existing literature examines bioethical justification in terms of the principles of respect for autonomy, non-maleficence, beneficence and justice. The primary purpose of this study is to explore the uncertainty of ethics guidelines provided by the Indian Council of Medical Research (ICMR) and section 3(b) of the Indian Patents Act 1970 and the applicability of the bioethics principles.  2023 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore), ISSN: 0253-7222.</text>
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                <text>Journal of Dharma, Vol-48, No. 1, pp. 125-144.</text>
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                <text>Azyu H.P., School of Law, CHRIST (Deemed to be University, Bangalore, India; Chakraborty A., School of Law, CHRIST (Deemed to be University, Bangalore, India</text>
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                <text>B R., Department of Psychology, CHRIST University, Bengaluru, India; Gopal B., Department of Psychology, CHRIST University, Bengaluru, India</text>
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                <text>In this paper, we describe the green synthesis of silver nanoparticles (AgNPs) using plant extracts, as well as their structural, optical, and antibacterial activities against Escherichia coli and Bacillus velezensis bacteria. For the study, several sections (root, leaves, and seed) of Mucuna pruriens, an immense medicinal herbal used to treat Parkinson's disease, were evaluated. Also, the seeds were grown in-vitro in the modified Murashige and Skoog's medium and the leaf derived callus supplemented by different phytohormones like picloram (pic), thidiazuron (TDZ), 6-benzylaminopurine (BAP) and 2-isopentenyl adenine (2-iP) were selected for this study. This is the first report of distinct callus obtained from M. pruriens and used for green nanoparticle synthesis. The prepared materials were thoroughly evaluated for structural and optical properties using XRD, FTIR, and UV-Visible spectroscopy. During synthesis, the colour changes from colourless to reddish brown, and the existence of an SPR peak in the absorption spectra confirms the formation of AgNPs. The FTIR spectra reveals the presence of phenolic group and alkyl ether groups, which were responsible for the reduction of silver ions during the green synthesis. The aqueous extracts of plant parts and callus obtained from different hormones showed very poor antibacterial activity. However, the green synthesized nanoparticles fabricated by different plant extracts showed good antimicrobial activity towards E. coli and B. velezensis bacteria. amongst the investigated results, highest antimicrobial activity against E. coli (84.8%) and B. velezensis (78.1%) was shown by AgNPs mediated by leaf extracts respectively followed by 0.5 mg/L pic and 2.0 mg/L BAP callus mediated silver nanoparticle solution. According to the findings, green produced AgNPs are promising candidates for antibacterial applications against E. coli and B. velezensis.  2022 SAAB</text>
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                <text>South African Journal of Botany, Vol-148, pp. 251-258.</text>
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                <text>ISSN: 2546299; CODEN: SAJBD</text>
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                <text>B R., Department of Life Sciences, Christ (Deemed to be University), Hosur Road, Bengaluru, 560 029, India; N S., Department of Physics, RV Institute of Technology and Management, Bengaluru, 560 076, India; K J R.K., Department of Chemistry, RV Institute of Technology and Management, Bengaluru, 560 076, India; A M., Department of Physics, Dayananda Sagar College of Engineering, Kumaraswamy Layout, Karnataka, Bangalore, 560 078, India; M R S.K., Department of Physics, RV Institute of Technology and Management, Bengaluru, 560 076, India; N P., Department of Life Sciences, Christ (Deemed to be University), Hosur Road, Bengaluru, 560 029, India</text>
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                <text>B S, Arjun.</text>
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                <text>&lt;a href="https://www.indianjournals.com/ijor.aspx?target=ijor:ijmie&amp;amp;volume=6&amp;amp;issue=2&amp;amp;article=024" target="_blank" title="Return efficiency level approach through DuPont analysis in personal care sector" rel="noreferrer noopener"&gt;https://www.indianjournals.com/ijor.aspx?target=ijor:ijmie&amp;amp;volume=6&amp;amp;issue=2&amp;amp;article=024&lt;/a&gt;</text>
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