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                <text>Generalisation of the rainbow neighbourhood number and k-jump colouring of a graph</text>
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                <text>K-jump colouring; K-rainbow neighbourhood; K-rainbow neighbourhood number</text>
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                <text>In this paper, the notions of rainbow neighbourhood and rainbow neigh-bourhood number of a graph are generalised and further to these general-isations, the notion of a proper k-jump colouring of a graph is also intro-duced. The generalisations follow from the understanding that a closed k-neighbourhood of a vertex v ? V (G) denoted, Nk [v] is the set, Nk [v] = {u: d(v, u) ? k, k ? N and k ? diam(G)}. If the closed k-neighbourhood Nk [v] contains at least one of each colour of the chromatic colour set, we say that v yields a k-rainbow neighbourhood.  2020, Eszterhazy Karoly College. All rights reserved.</text>
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          <element elementId="39">
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                <text>Kok J.; Naduvath S.; Mphako-Banda E.G.</text>
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                <text>Annales Mathematicae et Informaticae, Vol-52, pp. 147-158.</text>
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                <text>Eszterhazy Karoly College</text>
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                <text>2020-01-01</text>
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                <text>&lt;a href="https://doi.org/10.33039/ami.2020.02.003" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.33039/ami.2020.02.003&lt;/a&gt;
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                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>ISSN: 17875021</text>
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                <text>Kok J., Department of Mathematics, CHRIST (Deemed to be University), Bangalore, 560029, India; Naduvath S., Department of Mathematics, CHRIST (Deemed to be University), Bangalore, 560029, India; Mphako-Banda E.G., School of Mathematical Sciences, University of Witswatersrand Johannesburg, South Africa</text>
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                <text>Generalized p-Transmuted Neutrosophic Distributions: Theory and its Applications</text>
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              <elementText elementTextId="87369">
                <text>Empirical study; Generalized p-transmuted distributions; Life time distributions; Neutrosophic distribution</text>
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                <text>The study of neutrosophy offers a fresh approach for handling uncertain data with adaptability. This article explores the application of neutrosophic probability distribution in constructing a transmuted neutrosophic framework. Specifically, it introduces a generalized transmuted neutrosophic distribution. Building upon this generalization, quadratic and cubic transmuted distributions are developed and examined alongside certain lifetime distributions serving as foundational neutrosophic models. Additionally, an empirical investigation is conducted to assess the practicality and versatility of these distributions in real-world contexts.  2024, American Scientific Publishing Group (ASPG). All rights reserved.</text>
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              <elementText elementTextId="87371">
                <text>Jabarali A.K.; Mohana K.; Devanayan D.W.P.; Krishnaprasad; Sandhya D.; Pradeep Kumar S.V.</text>
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                <text>International Journal of Neutrosophic Science, Vol-24, No. 3, pp. 201-219.</text>
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                <text>2024-01-01</text>
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                <text>&lt;a href="https://doi.org/10.54216/IJNS.240318" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.54216/IJNS.240318&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197210633&amp;amp;doi=10.54216%2FIJNS.240318&amp;amp;partnerID=40&amp;amp;md5=285157de2aaef19db2e7b1eaaac1415b" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197210633&amp;amp;doi=10.54216%2fIJNS.240318&amp;amp;partnerID=40&amp;amp;md5=285157de2aaef19db2e7b1eaaac1415b&lt;/a&gt;</text>
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                <text>ISSN: 26926148</text>
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                <text>Jabarali A.K., Department of Statistics, Madras Christian College, Chengalpattu, Tamilnadu, East Tambaram, 600 059, India; Mohana K., Department of Mathematics, Nirmala College for Women, Red Fields, Tamilnadu, Coimbatore, 641 015, India; Devanayan D.W.P., CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India; Krishnaprasad, CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India; Sandhya D., CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India; Pradeep Kumar S.V., CHRIST (Deemed to be University), Karnataka, Bangalore, 560 029, India</text>
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          <element elementId="50">
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                <text>Generalized Ricci soliton and paracontact geometry</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="114252">
                <text>Generalized Ricci soliton; K-Paracontact manifold; Paracontact metric manifold; ParaSasakian manifold</text>
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              <elementText elementTextId="114253">
                <text>In the present paper, we study generalized Ricci soliton in the framework of paracontact metric manifolds. First, we prove that if the metric of a paracontact metric manifold M with Q?= ?Q is a generalized Ricci soliton (g,X) and if X? 0 is pointwise collinear to ?, then M is K-paracontact and ?-Einstein. Next, we consider closed generalized Ricci soliton on K-paracontact manifold and prove that it is Einstein provided ?(?+ 2 n?) ? 1. Next, we study K-paracontact metric as gradient generalized almost Ricci soliton and in this case we prove that (i) the scalar curvature r is constant and is equal to - 2 n(2 n+ 1) ; (ii) the squared norm of Ricci operator is constant and is equal to 4 n2(2 n+ 1) , provided ??? - 1.  2021, Instituto de Matemica e Estattica da Universidade de S Paulo.</text>
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              <elementText elementTextId="114254">
                <text>Naik D.M.; Venkatesha V.; Kumara H.A.</text>
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                <text>Sao Paulo Journal of Mathematical Sciences, Vol-15, No. 2, pp. 916-927.</text>
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              <elementText elementTextId="114256">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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              <elementText elementTextId="114257">
                <text>2021-01-01</text>
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                <text>&lt;a href="https://doi.org/10.1007/s40863-021-00260-1" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/s40863-021-00260-1&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112061697&amp;amp;doi=10.1007%2Fs40863-021-00260-1&amp;amp;partnerID=40&amp;amp;md5=03ab1788a60faffcd5c901e76e419533" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112061697&amp;amp;doi=10.1007%2fs40863-021-00260-1&amp;amp;partnerID=40&amp;amp;md5=03ab1788a60faffcd5c901e76e419533&lt;/a&gt;</text>
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                <text>ISSN: 19826907</text>
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              <elementText elementTextId="114262">
                <text>English</text>
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                <text>Naik D.M., Department of Mathematics, CHRIST (Deemed to be University), Bengaluru, Karnataka, India; Venkatesha V., Department of Mathematics, Kuvempu University, Shankaraghatta, 577-451, Karnataka, India; Kumara H.A., Department of Mathematics, Kuvempu University, Shankaraghatta, 577-451, Karnataka, India</text>
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                <text>Generalized Ricci solitons on Riemannian manifolds admitting concurrent-recurrent vector field</text>
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          <element elementId="49">
            <name>Subject</name>
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              <elementText elementTextId="106922">
                <text>Conformal vector field; Generalized Ricci soliton; Gradient generalized Ricci soliton</text>
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                <text>Let (M,g) be a Riemannian manifold admitting a concurrent-recurrent vector field ?. We prove that if the metric g is a generalized Ricci soliton such that the potential field V is a conformal vector field, then M is Einstein. Next we show that if the metric of M is a gradient generalized Ricci soliton, then either of these three occurs: (i) ?? is invariant along gradient of potential function; (ii) M is Einstein; (iii) the potential vector field is pointwise collinear to concurrent-recurrent vector field ?. Finally, we investigate gradient generalized Ricci soliton on a Riemannian manifold (M,g) admitting a unit parallel vector field, and in this case we show that if g is a non-steady gradient generalized Ricci soliton, then the Ricci tensor satisfies Ric=-??{g-?????}, where ?? is the canonical 1-form associated to ?.  2022, The Author(s), under exclusive licence to The Forum DAnalystes.</text>
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                <text>Background: A generalized model of mathematical nature is considered to address the viscoelastic flow problem using fractional derivatives. Control/freedom of the flow mechanism is achieved with these derivatives. In simulations of industrial interest, more variations are available with fractional derivatives when compared with ordinary derivatives. Relaxation times are incorporated to handle the abrupt changes in the flow domain. Fluid flow is carried out under the influence of thermal radiations and when a heat source or sink is present. Chemical reactions of the first order are observed in the mathematical modeling of the flow. Methods: Flow is induced with the movement of the lower surface while applying force on the x-plane. Simulations of the governing mathematical problem are computed with the combination of finite element and finite difference algorithms. Significant Findings: It is noted that velocity, temperature, and concentration change with the variation of fractional order derivatives which was not possible with the classical derivatives. Moreover, with greater relaxation times, velocity, temperature, and concentration remained at a lower level. The modeled mechanism can be considered to avoid costly trials in chemical and polymer casting industries.  2023 Elsevier B.V.</text>
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                <text>Shoaib Anwar M., Department of Mathematics, University of Jhang, Jhang, 35200, Pakistan; Alam M.M., Department of Basic Medical Sciences, College of Applied Medical Science, King Khalid University, Abha, 61421, Saudi Arabia; Khan M.A., Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University, P.O. Box-65892, Riyadh, 11566, Saudi Arabia; Abouzied A.S., Department of Pharmaceutical Chemistry, College of Pharmacy, University of Hail, Hail, 81442, Saudi Arabia, Department of Pharmaceutical Chemistry, National Organization for Drug Control and Research (NODCAR), Giza, 12553, Egypt; Hussain Z., Department of Mathematics, University of Baltistan, Skardu, Pakistan; Puneeth V., Department of Computational Science, CHRIST (Deemed to be University), Ghaziabad, 201003, India</text>
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                <text>In India, one in 500 people (Balaji, 2019) are diagnosed with ASD. Around 40 non-governmental organizations cater to Autism Spectrum Disorder (ASD) children; out of that, a few organizations focus on adults providing them vocational training to make them employable. One such exercise was initiated by SAP Labs India, a leading software company, and Enable India, an Indian NGO where they developed a focused training program for people with ASD and placed them in vital technical jobs in SAP Labs India (Karwa, 2016). First, we peek into the lifestyles of a few successful neurodiverse rock stars in India and their journey from becoming aware of their profile to establishing a career and becoming a role model to other people with ASD. Second, we present the autism landscape in India. Third, we explore the organizations that have hired people with ASD, their policies connected to neurodiversity, and the organizations that give training and support. Fourth, we present the potentials and the challenges people with ASD face. Fifth and final, we cover the role of different stakeholders to foster support and up-skill people with ASD for better community development.  2022 by Emerald Publishing Limited. All rights reserved.</text>
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                <text>Generation A: Perspectives on Special Populations and International Research on Autism in the Workplace, pp. 179-198.</text>
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                <text>Annamalai S., School of Business and Management, CHRIST (Deemed to be University), BGR Campus, Bangalore, India; Niranjan L.R., School of Business and Management, CHRIST (Deemed to be University), BGR Campus, Bangalore, India</text>
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                <text>The efficiency of any cryptosystem not only depends on the speed of the encryption and decryption processes but also on its ability to produce different ciphertexts for the same plaintext. RSA, the public key cryptosystem, is the most famous and widely accepted cryptosystem, but it has some security vulnerabilities because it produces the same ciphertext for identical plaintexts occurring in several places. To enhance the security of RSA, magic square-based encoding models have been proposed in the literature. Although magic square-based encoding models have been proposed, they are static. Thus, this paper introduces a dynamic-based magic square with RSA, where encryption and decryption are performed using numbers generated from the magic square instead of ASCII values. Unlike the static magic square, the proposed dynamic magic square allows users to specify the starting and ending numbers in any position rather than fixed positions. In the proposed dynamic magic square generation, different 4 4 magic square templates are created, and 16 16 magic squares are generated from them. Experimental results clearly demonstrate the improved security of RSA.  The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.</text>
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                <text>Pooja N.G., Nehru Memorial College (Autonomous) Puthanampatti Tiruchirapalli, Affiliated to Bharathidasan University, Tamil Nadu, Tiruchirapalli, India; Mani K., Department of Computer Science, Nehru Memorial College (Autonomous) Puthanampatti Tiruchirapalli, Affiliated to Bharathidasan University, Tamil Nadu, Tiruchirapalli, India; Devi U., Department of Computer Science, Nehru Memorial College (Autonomous) Puthanampatti Tiruchirapalli, Affiliated to Bharathidasan University, Tamil Nadu, Tiruchirapalli, India; Chandar S.K., Department of Computer Science, Christ University, Hosur, Bangalore, India</text>
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                <text>The advent of GenAI has brought about substantial progress and prospects in diverse sectors, including education. We are witnessing significant progress in this field of artificial intelligence, with the emergence of chatbots such as ChatGPT and the proliferation of remarkably realistic AI-generated graphics. Generative AI, as an emerging technology, has the potential to bring significant and transformative improvements to education. Generative AI encourages higher education institutions to embrace and utilize the potential of these technologies to enhance several aspects such as student experience, faculty workload, intellectual property, etc. This chapter has explored the application of generative AI in the context of higher education, in light of its increasing prevalence. Although generative artificial intelligence offers a great deal of promise to improve education, the technology is not entirely devoid of difficulties. The chapter also discusses challenges and strategies related to generative AI in higher education.  2024 by IGI Global.</text>
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                <text>IoT devices are widely used in medical domain for detection of high blood sugar and life threatening disease such as cancer. Breast cancer is one of the most challenging type of cancer which not only affects women but in some cases men also. Deep learning is one of the widely used technology which provides efficient classification of cancerous lumps but it is not useful for IoT devices as the devices lack resources such as storage and computation. For the suitability in IoT devices, in this work, we are compressing UNet, the popular semantic segmentation technique, for the pixel-wise classification of breast cancer. For compressing the deep learning model, we use genetic algorithm which removes the unwanted layers and hidden units in the existing UNet model. We have evaluated the proposed model and compared with the existing model(s) and found that the proposed compression technique suppresses the storage requirement to 77.1%. Additionally, it also improves the inference time by 3.82without compromising the accuracy. We conclude that the primary reason of inference time improvement is the requirement of less number of weight and bias by the proposed model.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.</text>
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                <text>Autism, a pervasive developmental disorder typically characterized by repetitive behaviour, social skills deficit (or a deficit in social communication), speech and language impairments. Our prime focus is to analyze the clinical features and phenotypical behavioural changes using the diagnostic and statistical manual of mental disorders, fourth edition, text revision (DSM IV-TR), and locating the biomarkers associated with specific autistic characters using karyotyping and fluorescence in situ hybridization (FISH) techniques. The prevalence rate of the neurexin 1 (NRXN1) gene polymorphism was also assessed in the current study. The study group involved 196 samples with 98 autistics, and equal age-matched (2) controls based on their birth order and carrier. The participants include 35.2% males (n = 69) and 14.8% females (n = 29). The autistic and control participants were categorized based on their ages as group I (&amp;lt;12 yrs) with n = 62; males n = 41 (20.9%); females n = 21 (10.7%) and group II (?12 yrs)-n = 36; males n = 28 (14.2%); females n = 08 (4.08%). Karyotyping was done for autism participants (n = 98) and the results showed that 90% of autistic participants were either the only child or the first child with a low perception and frequency in both the groups. Subsequently, we carried out the FISH assay on participants (n = 37) with higher DSM-IV TR score (?30). Only 30 FISH tests were negative for subtelomeric deletions with NRXN1 polymorphism genotypic frequency as 62.50%, 25% and 25% for A/A, A/G and G/G genotype respectively. Our study suggests the link between a haplotype with clinical signs of autism for the single nucleotide sequence (SNP rs9636391) and links autistic characters and gene among autistic children according to their birth order, age and gender in India.  2021 Elsevier B.V.</text>
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                <text>Meyyazhagan A.; Balasubramanian B.; Bhotla H.K.; Easwaran M.; Shanmugam S.; Alagamuthu K.K.; Arumugam V.A.; Keshavarao S.; Pappusamy M.</text>
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                <text>Meta Gene, Vol-29</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.mgene.2021.100924" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.mgene.2021.100924&lt;/a&gt;
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                <text>Meyyazhagan A., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India, Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India; Balasubramanian B., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India, Department of Food Science and Biotechnology, College of Life Science, Sejong University, Seoul, 05006, South Korea; Bhotla H.K., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India; Easwaran M., Nutritional Improvement of Crops, International Centre for Genetic Engineering and Biotechnology, New Delhi, 110067, India; Shanmugam S., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India, Department of Animal Resource and Science, Dankook University, Cheonan, 31116, South Korea; Alagamuthu K.K., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India, Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Science, Nanjing Normal University, Nanjing, 210023, China; Arumugam V.A., Medical Genetics and Epigenetics Laboratory, Department of Human Genetics and Molecular Biology, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India; Keshavarao S., Human Genetics Laboratory, Department of Zoology, School of Life Sciences, Bharathiar University, 641046, Tamil Nadu, India; Pappusamy M., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India</text>
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                <text>Infertility has haunted mankind from ancient times. In 40 to 50% of the cases resulting in failure to conceive, the cause can be attributed to male infertility. The rates of infertility have risen in the past few decades among both among men and women. The reasons can be attributed to life style changes and environmental pollution apart from genetic causes. Scientists have found out few possible causes of male infertility and there are few treatment measures currently being carried out. The success of these depends on the primary cause of the infertility problem. In the past few decades, a number of genes playing roles in different stages of sperm development and differentiation were functionally analysed. This knowledge coupled with the advancements in stem cell technology and in vitro gametogenesis has led to new frontiers in possible therapeutic measures of male infertility, especially those with genetic causes. The present study focuses on the causes and treatment of male infertility focussing mainly on important genetic regulations and emerging stem cell-based therapeutics.  2021 World Research Association. All rights reserved.</text>
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                <text>Research Journal of Biotechnology, Vol-16, No. 6, pp. 183-189.</text>
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                <text>Suma S., Department of Life Sciences, CHRIST (Deemed to Be University), Bengaluru, 560029, India; Rashmi A., Department of Life Sciences, CHRIST (Deemed to Be University), Bengaluru, 560029, India</text>
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                <text>Genetic correlates of the development of theta event related oscillationsin adolescents and young adults</text>
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                <text>Adolescent; Development; ERO; KCNJ6; P3; Theta</text>
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                <text>The developmental trajectories of theta band (47Hz) event-related oscillations (EROs), a key neurophysiological constituent of the P3 response, were assessed in 2170 adolescents and young adults ages 12 to 25. The theta EROs occurring in the P3 response, important indicators of neurocognitive function, were elicited during the evaluation of task-relevant target stimuli in visual and auditory oddball tasks. Associations between the theta EROs and genotypic variants of 4 KCNJ6 single nucleotide polymorphisms (SNPs) were found to vary with age, sex, scalp location, and task modality. Three of the four KCNJ6 SNPs studied here were found to be significantly associated with the same theta EROs in adults in a previous family genome wide association study. Since measures of the P3 response have been found to be a useful endophenotypes for the study of a number of clinical and behavioral disorders, studies of genetic effects on its development in adolescents and young adults may illuminate neurophysiological factors contributing to the onset of these conditions.  2016 Elsevier B.V.</text>
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                <text>Chorlian D.B.; Rangaswamy M.; Manz N.; Meyers J.L.; Kang S.J.; Kamarajan C.; Pandey A.K.; Wang J.-C.; Wetherill L.; Edenberg H.; Porjesz B.</text>
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                <text>International Journal of Psychophysiology, Vol-115, pp. 24-39.</text>
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                <text>Elsevier B.V.</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007418188&amp;amp;doi=10.1016%2Fj.ijpsycho.2016.11.007&amp;amp;partnerID=40&amp;amp;md5=7e34e9dfc9f5bf36220a648b4ae20980" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85007418188&amp;amp;doi=10.1016%2fj.ijpsycho.2016.11.007&amp;amp;partnerID=40&amp;amp;md5=7e34e9dfc9f5bf36220a648b4ae20980&lt;/a&gt;</text>
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                <text>All Open Access; Green Open Access</text>
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                <text>Chorlian D.B., Henri Begleiter Neurodynamics Laboratory, SUNY Downstate Medical Center, Department of Psychiatry, Brooklyn, NY, United States; Rangaswamy M., Department of Psychology, Christ University, Bangalore, India; Manz N., Department of Physics, College of Wooster, Wooster, OH, United States; Meyers J.L., Henri Begleiter Neurodynamics Laboratory, SUNY Downstate Medical Center, Department of Psychiatry, Brooklyn, NY, United States; Kang S.J., Stratton VA Medical Center, Albany, NY, United States; Kamarajan C., Henri Begleiter Neurodynamics Laboratory, SUNY Downstate Medical Center, Department of Psychiatry, Brooklyn, NY, United States; Pandey A.K., Henri Begleiter Neurodynamics Laboratory, SUNY Downstate Medical Center, Department of Psychiatry, Brooklyn, NY, United States; Wang J.-C., Mount Sinai School of Medicine, New York, NY, United States; Wetherill L., Indiana University School of Medicine, Indianapolis, IN, United States; Edenberg H., Indiana University School of Medicine, Indianapolis, IN, United States; Porjesz B., Henri Begleiter Neurodynamics Laboratory, SUNY Downstate Medical Center, Department of Psychiatry, Brooklyn, NY, United States</text>
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                <text>Genetic Diversity of Garcinia gummi-gutta and Sustainable Utilization</text>
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                <text>The chapter discusses the consequences of using Garcinia gummi-gutta, often known as Malabar Tamarind, sustainably while diving into the complex web of genetic variation inside the crop. Giving a thorough overview, the chapter starts by detailing the botanical and genetic traits of this enigmatic species, revealing the morphological quirks and genetic differences that make it distinct. Examining the range and preferred habitats helps to highlight the ecological niches that are essential to its existence. It delves intently into the complex web of phytochemicals found in various plant parts and explains their range of biological functions. A crucial component of this study is a thorough examination of the techniques used to gauge the genetic diversity of populations of G. gummi-gutta. The assessment of G. gummi-gutta's conservation status indicates that threats to the species genetic richness need to be taken seriously and quickly addressed. The difficulties in attaining sustainable use are examined in detail, offering a comprehensive grasp of the nuances related to overexploitation and conservation initiatives. This study of G. gummi-gutta offers evidence of the complex interplay in the field of botanical resources between genetic diversity, conservation, and sustainable use.  2025 Hosakatte Niranjana Murthy.</text>
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                <text>Scaria S.S.; Joseph K.S.; Dandin V.S.; Shameer P.S.</text>
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                <text>Genetic Diversity of Fruits and Nuts: Sustainable Utilization, pp. 146-158.</text>
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                <text>&lt;a href="https://doi.org/10.1201/9781003492207-9" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1201/9781003492207-9&lt;/a&gt;
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                <text>ISBN: 978-104031239-1; 978-103277911-9</text>
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                <text>Scaria S.S., Department of Life Science, School of Sciences, Christ University, Bangalore, 560029, India; Joseph K.S., Department of Life Science, School of Sciences, Christ University, Bangalore, 560029, India; Dandin V.S., Department of Biology, JSS RSH PU College, Dharwad, 580004, India; Shameer P.S., ICAR- Central Tuber Crops Research Institute, Sreekariyam, Kerala, Thiruvananthapuram, India</text>
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                <text>Lignocellulose biomass is an economically viable and most abundant energy source. The synthesis of renewable energy-based fuel from lignocellulosic biomass is a replacement for fossil fuel. Cellulases are the biocatalysts that hydrolyze the ?-1,4-glycosidic bond in cellulose to release carbohydrate moieties that can be converted to ethanol, butanol, and other compounds. However, little enzymatic activity and product yield, and thermal stability are hurdles in the deconstruction of lignocellulose. Current progress in synthetic and omics technologies has resulted in several works in metabolic and genetic engineering that have paved the way for efficient conversion of lignocellulose to fuel in the last decades. Several works have attempted to apply genetic and metabolic engineering in the synthesis of stable and highly active cellulases at lower cost. This chapter reviews various genetic engineering technologies for enhancing cellulase synthesis and catalytic efficiency.  2024 selection and editorial matter, Reeta Rani Singhania, Anil Kumar Patel, Htor A. Ruiz, Ashok Pandey; individual chapters, the contributors.</text>
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                <text>Madhavan A.; Arun K.B.; Nair B.G.; Singhania R.R.; Raveendran S.; Awasthi M.K.; Pandey A.; Binod P.</text>
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                <text>Biomass Hydrolyzing Enzymes: Basics, Advancements, and Applications, pp. 101-111.</text>
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                <text>ISBN: 978-100385182-0; 978-103237097-2</text>
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                <text>Madhavan A., School of Biotechnology, Amrita Vishwa Vidyapeetham, Kerala, Kollam, India; Arun K.B., Department of Life Sciences, Christ (Deemed to be University), Karnataka, Bengaluru, India; Nair B.G., School of Biotechnology, Amrita Vishwa Vidyapeetham, Kerala, Kollam, India; Singhania R.R., Institute of Aquatic Science and Technology, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan, Centre for Energy and Environmental Sustainability, Uttar Pradesh, Lucknow, India; Raveendran S., Department of Food Technology, T K M Institute of Technology, Kerala, Kollam, India; Awasthi M.K., College of Natural Resources and Environment, Northwest A&amp;amp;F University, Yangling, Shaanxi Province, China; Pandey A., Centre for Energy and Environmental Sustainability, Uttar Pradesh, Lucknow, India, Centre for Innovation and Translational Research, CSIR-Indian Institute of Toxicology Research, Uttar Pradesh, Lucknow, India, Kyung Hee University, Seoul, South Korea, School of Engineering, University of Petroleum and Energy Studies, Dehradun, India; Binod P., Microbial Processes and Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology, Kerala, Thiruvananthapuram, India</text>
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                <text>Genetically modified foods: bibliometric analysis on consumer perception and preference</text>
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                <text>Bibliometric analysis; consumer perception; consumer preferences; future research thrust; GM food; GMOs; industry implications; policy imperatives</text>
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                <text>In this study, we present the bibliometric trends emerging from research outputs on consumer perception and preference for genetically modified (GM) foods and policy prescriptions for enabling the consumption using VOSviewer visualization software. Consumers positive response is largely influenced by the decision of the governments to ban or approve the GM crops cultivation. Similarly, the public support increases when the potential benefits of the technology are well articulated, consumption increases with a price discount, peoples trust on the government and belief in science increases with a positive influence by the media. Europe and the USA are the first region and country, respectively, in terms of the number of active institutions per research output, per-capita GDP publication and citations. We suggest research-, agri-food industries-, and society-oriented policies to be implemented by the stakeholders to ensure the safety of GM foods, encourage consumer-based studies, and increase public awareness toward these food products.  2022 The Author(s). Published with license by Taylor &amp;amp; Francis Group, LLC.</text>
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                <text>Sendhil R.; Nyika J.; Yadav S.; Mackolil J.; Rama Prashat G.; Workie E.; Ragupathy R.; Ramasundaram P.</text>
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                <text>GM Crops and Food, Vol-13, No. 1, pp. 65-85.</text>
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                <text>&lt;a href="https://doi.org/10.1080/21645698.2022.2038525" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/21645698.2022.2038525&lt;/a&gt;
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                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>ISSN: 21645698; PubMed ID: 35400312</text>
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                <text>Sendhil R., ICAR-Indian Institute of Wheat and Barley Research, Karnal, India; Nyika J., Technical University of Kenya, Nairobi, Kenya; Yadav S., ICAR-National Bureau of Plant Genetic Resources, New Delhi, India; Mackolil J., CHRIST (Deemed to be University), Bangalore, India; Rama Prashat G., ICAR-Indian Agricultural Research Institute, New Delhi, India; Workie E., School of Environmental science and Engineering, Shanghai Jiao Tong University, Shanghai, China; Ragupathy R., Lethbridge Research and Development Centre, Agriculture Agri Food Canada, AB, Canada; Ramasundaram P., National Agricultural Higher Education Project, Indian Council of Agricultural Research, New Delhi, India</text>
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