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                <text>Investigations on the Design, Performance and Effect of Feed Mechanisms, Defected Ground Structures and Materials for Optimized Microstrip Antenna Array  </text>
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                <text>Microstrip antenna exhibiting low-profle features such as and#64258;exible, lightweight and newlinelow production cost attracts majority of communication industries working the lower newlinepart of the microwave spectrum ranging from 1 GHz to 6 GHz. Also, the microwave integrated circuit technology enables the integration of feed systems and other microwave integrated circuits on the same substrate where the antenna is printed. However, single antenna topologies feature a number of drawbacks, including low gain, poor directivity, narrow bandwidth and limited coverage being low in profle. In the perspective of miniaturization, developments in wireless communication have had a signifcant impact on antenna or array design based on the gain, bandwidth and directivity requirements for specifc wireless applications. As a result, usage of single antenna is not considered appropriate for diversity reception, long-distance communication, signal-to-interference as well as signal-to-noise ratio maximization, and direction of arrival determination, interference rejection, and high power applications. A high-gain broadband antenna or array may be the good choice for outdoor line-of-sight access points to increase signal strength and coverage range. To meet these requirements the antenna designers either can use conventional antennas or rely on miniaturized antennas. When antenna arrays are built using such small antennas to enhance the above said parameters, suitable and compact feed networks are required to ft within the given space of the overall transmitter-receiver geometry. This research work addresses the challenges faced by antenna researchers in newlineminiaturization, maintenance of gain-bandwidth and high-directivity narrow-beam newlineradiation of microstrip antenna arrays, through an investigation made on the design, new mathematical modelling of feed mechanisms for arrays, their inand#64258;uence on 1D and 2D uniform and non-uniform arrays, and the performance enhancement by amalgamating proposed arrays with defected ground structures and metasurfaces.</text>
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                <text>Emotional Intelligence is a set of qualities and competencies that captures a broad collection of individual skills and dispositions, usually referred to as soft skills or inter and intra-personal skills, that are outside the traditional areas of specific knowledge, general intelligence, and technical or professional skills. Emotions are an intrinsic part of our biological makeup, and every morning they march into the office with us and influence our behavior.</text>
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                <text>Emotional needs of women post-rescue from sex trafficking in India</text>
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                <text>emotional needs; sex trafficking; sexual exploitation; survivor</text>
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                <text>Sex trafficking has persisted a social crime that maintains its status despite being unlawful. Since it prevails, there is a need to investigate it to understand the effects and consequences of the same on the survivors. The current study aims to understand the emotional needs of survivors post-rescue from sex trafficking living in aftercare homes in India and to look into survivors suggestions post-rescue to NGOs, society, family, government and police. It included ten survivors from sex trafficking, ages between 18 to 24years old. They are emerging adults who have experienced sex trafficking for at least one year, regardless of whether trafficking happened in childhood, adolescence or early adulthood, rescued one to five years ago. The researcher used a phenomenological approach. Thematic analysis was employed to identify themes within the data collected from the participants. Findings revealed that survivors had got a better life after the rescue, and they need acceptance, respect, understanding, and they need to develop trust on people around them. They still have many challenges post-rescue such as lack of education and job opportunities. They need guidance to start a new life. Mostly, sex trafficking survivors need safety and protection.  2019,  2019 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.</text>
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                <text>da Silva I.M.; Sathiyaseelan A.</text>
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                <text>Cogent Psychology, Vol-6, No. 1</text>
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                <text>Cogent OA</text>
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                <text>&lt;a href="https://doi.org/10.1080/23311908.2019.1631584" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1080/23311908.2019.1631584&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067825884&amp;amp;doi=10.1080%2F23311908.2019.1631584&amp;amp;partnerID=40&amp;amp;md5=a20ded7d22180d0a3e847b9227b30b19" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067825884&amp;amp;doi=10.1080%2f23311908.2019.1631584&amp;amp;partnerID=40&amp;amp;md5=a20ded7d22180d0a3e847b9227b30b19&lt;/a&gt;</text>
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              <elementText elementTextId="132548">
                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 23311908</text>
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                <text>da Silva I.M., Department of Psychology, Christ (Deemed to be University), Bangalore, India; Sathiyaseelan A., Department of Psychology, Christ (Deemed to be University), Bangalore, India</text>
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                <text>Exploring Meaningfullness of Life among Survivors of Sex Trafficking in India  </text>
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                <text>Psychology</text>
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                <text>Sex trafficking is a form of human trafficking which is considered a contemporary form of slavery. It is made up of victims (supply), buyers (demand), and traffickers (distributors). Sex trafficking is a billion dollars industry. It generates more profit than any other industry in the world, illicit or otherwise. It is estimated that one woman or child is commercialized to be a sex slave every hour. The present study aimed to explore the meaningfulness of life among survivors of sex trafficking in India. It is a two-phase research design where the researcher has collected quantitative data first, and qualitative data was collected during the second phase. The qualitative phase comprises data from 126 subjects 
They were divided into two groups. Group 1, survivors rescued within two years (N=63), and group 2, survivors post two years after the rescue (N=63). Group 1 (M=15.58) scored lower on the meaningfulness of life compared to group 2 (M=23.15). Group 1 (M=16.80) is less satisfied with life compared to group 2 (M=22.65). Group 1 (M=61.09) has a lower quality of life compared to group (M=77.49). Group 1 tends to have lesser positive emotions and more negative emotions compared to group 2. There was a moderate positive correlation between the current meaning in life and satisfaction with life, r=.42, n=126, p&amp;lt;.001. There was a negative moderate correlation between the current meaning in life and negative emotions r=-49, n=126, p&amp;lt;.001, and there was a strong, positive vii correlation between current meaning in life and positive emotions, r=.53, n=126, p&amp;lt;.001. Results from the qualitative phase, which comprises data from 20 participants show that survivors' life in slavery was meaningless and marked by torture and rape. The meaningfulness of life for participants in the current study depends on a new identity, acceptance, education, spirituality, and respect. Those who have children found the meaningfulness of life in motherhood. Participants reported not being fully satisfied with their life and they described what they need to increase their life satisfaction. First is livelihood, that is food and shelter over their heads, good health, and dreams/goals fulfillment that for most of them is to get an education and/or professional training. Survivors reported having more negative emotions than positive emotions. Physical health problems found among participants were headache, gastritis, cough, and fever. Psychological health symptoms found among them were depression, anxiety, isolation, crying spells, and fatigue. Survivors have a limited social life because they distrust almost all people. The environment was found to be unsafe for girls and women and they ask for protection for themselves and for all females in the country. </text>
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                <text>Da Silva, Irani Machado </text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>Author's Submission</text>
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            <description>An entity responsible for making the resource available</description>
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                <text>Christ(Deemed to be University)</text>
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            <name>Date</name>
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              <elementText elementTextId="68812">
                <text>S, Anuradha.</text>
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            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="68813">
                <text>Open Access</text>
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            <description>A language of the resource</description>
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              <elementText elementTextId="68815">
                <text>English</text>
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            <description>The nature or genre of the resource</description>
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                <text>PhD</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="68817">
                <text>&lt;a href="http://hdl.handle.net/10603/478098" target="_blank" rel="noreferrer noopener"&gt;http://hdl.handle.net/10603/478098&lt;/a&gt;</text>
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              <description>A name given to the resource</description>
              <elementTextContainer>
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                  <text>Faculty Publications</text>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="275825">
                <text>Dabbir, Rupesh; Logeshwaran, J.</text>
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            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="275826">
                <text>Integrating Big Data Management with Machine Learning in Cloud Environments</text>
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          </element>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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                <text>01-01-2025</text>
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              <elementText elementTextId="275828">
                <text>2025 International Conference on Networks and Cryptology, NETCRYPT 2025;pp.443-447</text>
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            <description>An unambiguous reference to the resource within a given context</description>
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                <text>&lt;a href="https://doi.org/10.1109/NETCRYPT65877.2025.11102667" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/NETCRYPT65877.2025.11102667&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105015469770?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105015469770?origin=resultslist&lt;/a&gt;</text>
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                <text>Dabbir R., Google LLC, San Jose, CA, United States; Logeshwaran J., Christ University, Department of Computer Science, Karnataka, Bengaluru, 560029, India</text>
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            <description>An account of the resource</description>
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              <elementText elementTextId="275831">
                <text>In past years, the consideration of cloud environments for big data management and machine learning techniques has increased exponentially. However, the massive amount of data that is made by companies and Internet of Things (IoT) devices has presented the industry with a challenge in storage. In addition, conventional data management methods are unable to manage the complexity, diversity, and volume of this big data. Consequently, cloud environments integrate big data management and machine learning techniques. Combining big data management through cloud environments equipped with machine learning has multiple benefits. First, it is an efficient way to process and analyze large datasets in a distributed and scalable manner. Second, it helps businesses to provide insights and make time to make datadriven decisions. Thirdly, it enables the system to learn from data on an ongoing basis, which helps improve the quality and accuracy of the data. Now, this integration also enhances the overall performance of cloud systems as data management tasks are automated, minimizing manual efforts. Utilizing Big Data Management and Machine Learning Techniques in Cloud Environment to Address the Drawbacks of Conventional Data Management Approaches and Exploit the Value of Big Data These two technologies, when integrated, will allow the enterprise to manage significant amounts of data and derive important insights to arrive at better decisions. Cloud environments provide the automation and scalability required to push this integration further and change considerable data use in businesses.   2025 IEEE.</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="275832">
                <text>Automation; Cloud Systems; Complexity; Conventional Data; Diversity; Internet Of Things</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="275833">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <elementText elementTextId="275834">
                <text>ISBN: 979-833152605-4;</text>
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            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="275835">
                <text>English</text>
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                <text>Conference paper</text>
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          <element elementId="47">
            <name>Rights</name>
            <description>Information about rights held in and over the resource</description>
            <elementTextContainer>
              <elementText elementTextId="275837">
                <text>Restricted Access; Hardcopy may be available in the library</text>
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      <description>Faculty Publications -Articles</description>
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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Barbell-shaped giant radio galaxy with ? 100 kpc kink in the jet</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="102875">
                <text>Galaxies: active; Galaxies: clusters: general; Galaxies: clusters: intracluster medium; Galaxies: jets; Instabilities; Radio continuum: galaxies</text>
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            <description>An account of the resource</description>
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              <elementText elementTextId="102876">
                <text>We present for the first time a study of peculiar giant radio galaxy (GRG) J223301+131502 using deep multi-frequency radio observations from GMRT (323, 612, and 1300 MHz) and LOFAR (144 MHz) along with optical spectroscopic observations with the WHT 4.2m optical telescope. Our observations have firmly established its redshift of 0.09956 and unveiled its exceptional jet structure extending more than ? 200 kpc leading to a peculiar kink structure of ? 100 kpc. We measure the overall size of this GRG to be ? 1.83 Mpc; it exhibits lobes without any prominent hotspots and closely resembles a barbell. Our deep low-frequency radio maps clearly reveal the steep-spectrum diffuse emission from the lobes of the GRG. The magnetic field strength of ? 5 ?G and spectral ages between about 110 to 200 mega years for the radio lobes were estimated using radio data from LOFAR 144 MHz observations and GMRT 323 and 612 MHz observations. We discuss the possible causes leading to the formation of the observed kink feature for the GRG, which include precession of the jet axis, development of instabilities and magnetic reconnection. Despite its enormous size, the Barbell GRG is found to be residing in a low-mass (M200 ? 1014 M) galaxy cluster. This GRG with two-sided large-scale jets with a kink and diffuse outer lobes residing in a cluster environment, provides an opportunity to explore the structure and growth of GRGs in different environments.   2022 EDP Sciences. All rights reserved.</text>
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                <text>Astronomy and Astrophysics, Vol-668</text>
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&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145252585&amp;amp;doi=10.1051%2F0004-6361%2F202243182&amp;amp;partnerID=40&amp;amp;md5=832b248d232100752a6f24df220927bb" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85145252585&amp;amp;doi=10.1051%2f0004-6361%2f202243182&amp;amp;partnerID=40&amp;amp;md5=832b248d232100752a6f24df220927bb&lt;/a&gt;</text>
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                <text>Dabhade P., Observatoire de Paris, Lerma, Colle de France, Cnrs, Psl University, Sorbonne University, Paris, 75014, France; Shimwell T.W., Astron, Netherlands Institute for Radio Astronomy, Postbus 2, AA Dwingeloo, 7990, Netherlands, Leiden Observatory, Leiden University, PO Box 9513, RA Leiden, 2300, Netherlands; Bagchi J., Inter-University Centre for Astronomy and Astrophysics (IUCAA), Pune, 411007, India, Department of Physics and Electronics, Christ (Deemed to Be University), Bengaluru, 560029, India; Saikia D.J., Inter-University Centre for Astronomy and Astrophysics (IUCAA), Pune, 411007, India, Department of Physics, Tezpur University, Tezpur, 784028, India; Combes F., Observatoire de Paris, Lerma, Colle de France, Cnrs, Psl University, Sorbonne University, Paris, 75014, France; Gaikwad M., Max-Planck-Institut f Radioastronomie, Auf dem Hugel 69, Bonn, 53121, Germany; Rtgering H.J.A., Leiden Observatory, Leiden University, PO Box 9513, RA Leiden, 2300, Netherlands; Mohapatra A., Inter-University Centre for Astronomy and Astrophysics (IUCAA), Pune, 411007, India; Ishwara-Chandra C.H., National Centre for Radio Astrophysics, Tifr, Post Bag 3, Ganeshkhind, Pune, 411007, India; Intema H.T., Leiden Observatory, Leiden University, PO Box 9513, RA Leiden, 2300, Netherlands; Raychaudhury S., Inter-University Centre for Astronomy and Astrophysics (IUCAA), Pune, 411007, India, School of Physics and Astronomy, University of Birmingham, Birmingham, B15 2TT, United Kingdom</text>
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                <text>Dabla, Pradeep K.; Upreti, Kamal; Singh, Divakar; Singh, Anju; Puri, Vinod; Stanciu, Adina E.; Serdarevic, Nafija; Gruson, Damien</text>
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                <text>Anti-epileptic medication induced disturbed calcium-vitamin D metabolism: A behavioral analysis using association rule mining technique</text>
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                <text>World Journal of Experimental Medicine;Volume;15;Issue;3;Article No.;104799;</text>
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                <text>Dabla P.K., Department of Biochemistry, Govind Ballabh Pant Institute of Postgraduate Medical Education and Research, Associated Maulana Azad Medical College, Delhi, New Delhi, 110002, India; Upreti K., Department of Computer Science, CHRIST (Deemed to be University), Ghaziabad, 201003, India; Singh D., Barkatullah University Institute of Technology, Barkatullah University, Bhopal, 462026, India; Singh A., Department of Computer Science and Engineering, Lakshmi Narain College of Technology Kalchuri Nagar, Bhopal, 462022, India; Puri V., Department of Neurology, Govind Ballabh Pant Institute of Postgraduate Medical Education and Research, Associated Maulana Azad Medical College, Delhi, New Delhi, 110002, India; Stanciu A.E., Department of Carcinogenesis and Molecular Biology, Institute of Oncology Bucharest, Bucharest, 022328, Romania, Faculty of Biology, University of Bucharest, Bucharest, 050095, Romania; Serdarevic N., Institute for Clinical Chemistry and Biochemistry, University of Sarajevo Clinics Center, Sarajevo, 71000, Bosnia and Herzegovina; Gruson D., Department of Clinical Biochemistry, Department of Laboratory Medicine, Cliniques Universitaires Saint-Luc and Universit Brussels, 1200, Belgium</text>
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                <text>BACKGROUND There is a lack of study on vitamin D and calcium levels in epileptic patients receiving therapy, despite the growing recognition of the importance of bone health in individuals with epilepsy. Associations one statistical method for finding correlations between variables in big datasets is called association rule mining (ARM). This technique finds patterns of common items or events in the data set, including associations. Through the analysis of patient data, including demographics, genetic information, and reactions with previous treatments, ARM can identify harmful drug reactions, possible novel combinations of medicines, and trends which connect particular individual features to treatment outcomes. AIM To investigate the evidence on the effects of anti-epileptic drugs (AEDs) on calcium metabolism and supple-menting with vitamin D to help lower the likelihood of bone-related issues using ARM technique. METHODS ARM technique was used to analyze patients behavior on calcium metabolism, vitamin D and anti-epileptic medicines. Epileptic sufferers of both sexes who attended neurological outpatient and in patient department clinics were recruited for the study. There were three patient groups: Group 1 received one AED, group 2 received two AEDs, and group 3 received more than two AEDs. The researchers analyzed the alkaline phosphatase, ionized calcium, total calcium, phosphorus, vitamin D levels, or parathyroid hormone values. RESULTS A total of 150 patients, aged 12 years to 60 years, were studied, with 50 in each group (1, 2, and 3). 60% were men, this gender imbalance may affect the studys findings, as women have different bone metabolism dynamics influenced by hormonal variations, including menopause. The results may not fully capture the distinct effects of AEDs on female patients. A greater equal distribution of women should be the goal of future studies in order to offer a complete comprehension of the metabolic alterations brought on by AEDs. 86 patients had generalized epilepsy, 64 partial. 42% of patients had AEDs for &amp;gt; 5 years. Polytherapy reduced calcium and vitamin D levels compared to mono and dual therapy. Polytherapy elevated alkaline phosphatase and phosphorus levels. CONCLUSION ARM revealed the possible effects of variables like age, gender, and polytherapy on parathyroid hormone levels in individuals taking antiepileptic medication.  The Author(s) 2025.</text>
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                <text>Anti-epileptic drugs; Association rule mining; Epilepsy; HotSpot; Transaction and metabolism</text>
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                <text>Baishideng Publishing Group Inc</text>
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                <text>ISSN: 2220315X;</text>
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              <elementText elementTextId="226748">
                <text>All Open Access; Gold Open Access; Green Open Access</text>
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                <text>Dabral, Anushka; Sivakumar, R.</text>
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                <text>Machine Learning for Mental Health: A Sentiment Analysis Approach for Detecting Depressive Tendencies on LinkedIn During Layoffs Using RoBERTa</text>
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                <text>01-01-2025</text>
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              <elementText elementTextId="268739">
                <text>Smart Innovation, Systems and Technologies;Volume;413 SIST;pp.279-290</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-981-97-7717-4_19" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-97-7717-4_19&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/86000442424?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/86000442424?origin=resultslist&lt;/a&gt;</text>
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                <text>Dabral A., Department of Statistics and Data Science, CHRIST (Deemed to Be University), Bengaluru, India; Sivakumar R., Department of Statistics and Data Science, CHRIST (Deemed to Be University), Bengaluru, India</text>
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                <text>In the present corporate set-up, layoffs are an unfortunate yet common occurrence. Such occurrences lead to loss of job security and can have direconsequences on an individual's mental health, leading to depression. Depression was a global health concern well before the current downsizing came into the picture. These trying times have acted as a catalyst for this illness that affects not just mental health but all aspects of an individuals life. The study investigates the use of sentiment analysis on LinkedIn data to identify and examine depressive tendencies among victims of layoffs. Web-scraped information was taken from LinkedIn profiles of individuals affected directly or indirectly by layoffs. RoBERTa, a transformers model, is used to classify people as depressed or not by evaluating sentiment and emotional cues. A comparison between four machine learning algorithms- Decision Tree, Logistic Regression, SVM, and Nae Bayes is drawn to check their ability to detect depression. The SVM classifier performed best with an accuracy of 95.59% and 83.52% with the CountVectorizer and TF-IDF feature selection methods, respectively. Sentiment analysis aids in this research by examining the melancholic undertones in the words and phrases used in texts authored by people affected by layoffs directly or indirectly. The knowledge gained from this research can significantly affect corporate initiatives, mental health services, and human resource practices during such challenging times.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.</text>
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                <text>Depression; Layoffs; LinkedIn; Machine Learning; RoBERTa; Sentiment Analysis; TF-IDF</text>
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            </elementTextContainer>
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              <elementText elementTextId="268744">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>ISSN: 21903018; ISBN: 978-981977716-7;</text>
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            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="268748">
                <text>Restricted Access; Hardcopy may be available in the library</text>
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                <text>A Scoping review of Deep Reinforcement Learning methods in Visual Navigation</text>
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            <description>The topic of the resource</description>
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                <text>Artificial Intelligence; Deep Learning; Neural Network; Reinforcement Learning</text>
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                <text>Reinforcement Learning (RL) is a subset of Machine Learning that trains an agent to make a series of decisions and take action by interacting directly with the environment. In this approach, the agent learns to attain the goal by the response from its action as rewards or punishment. Recent advances in reinforcement learning combined with deep learning methods have led to breakthrough research in solving many complex problems in the field of Artificial Intelligence. This paper presents recent literature on autonomous visual navigation of robots using Deep Reinforcement Learning (DRL) algorithms and methods. It also describes the algorithms evaluated, the environment used for implementation, and the policy applied to maximize the rewards earned by the agent. The paper concludes with a discussion of the new models created by various authors, their merits over the existing methods, and a briefing on further research.   2023 IEEE.</text>
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              <elementText elementTextId="173701">
                <text>Dafni Rose J.; Suganthi J.; Prabhakarran V.S.; Muthumari S.</text>
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            <name>Source</name>
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              <elementText elementTextId="173702">
                <text>Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications</text>
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            <elementTextContainer>
              <elementText elementTextId="173703">
                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <elementText elementTextId="173704">
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                <text>Dafni Rose J., Computer Science and Engineering St. Joseph's Institute of Technology, Chennai, India; Suganthi J., Christ (Deemed to Be) University, School of Sciences, Bengaluru, India; Prabhakarran V.S., K.R.College of Arts and Science, Department of Computer Science, Kovilpatti, India; Muthumari S., S.S.Duraisamy Nadar Mariammal College, Department of CS and IT, Kovilpatti, India</text>
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                <text>International Journal of Agricultural and Statistical Sciences, Vol-16, No. 2, pp. 647-657.</text>
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                <text>Dagar V., Amity School of Economics (ASE), Amity University, Noida, 201 303, India; Bansal E., Janki Devi Memorial College, University of Delhi, New Delhi, 110 060, India; Murshed M., School of Business and Economics, North South University, Dhaka, 1209, Bangladesh; Mishra V., Department of Economics, Christ University, Bangalore, Karnataka, 560 076, India; Alvarado R., Carrera de Economia, Universidad Nacional de Loja, Loja, 110 150, Ecuador; Kumar A., Dept. of Economics and Public Policy, Central University of Himachal Pradesh, Dharamshala, Kangra, 176 215, India; Anser M.K., School of Public Administration, Xi'an University of Architecture and Technology, Xi'an, Shaanxi, 710 055, China</text>
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                <text>Comparative Study of Graph Theory for Network System</text>
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                <text>The historical background of how graph theory emerged into world and gradually gained importance in different fields of study is very well stated in many books and articles. Some of the most important applications of graph theory can be seen in the field network theory. Its significance can be seen in some of the complex network systems in the field of biological system, ecological system, social systems as well as technological systems. In this paper, the basic concepts of graph theory in terms of network theory have been provided. The various network models like star network model, ring network model, and mesh network model have been presented along with their graphical representation. We have tried to establish the link between the models with the existing concepts in graph theory. Also, many application-based examples that links graph theory with network theory have been looked upon.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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                <text>Dahal R.; Samanta D.; Karuppiah M.; Biswas J.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-492, pp. 73-84.</text>
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                <text>Dahal R., Department of Mathematics, CHRIST University, Bangalore, India; Samanta D., Department of Computer Science, CHRIST University, Bangalore, India; Karuppiah M., Department of Computer Science and Engineering, SRM Institute of Science and Technology, Delhi-NCR Campus, Uttar Pradesh, Ghaziabad, 201204, India; Biswas J., Department of Computer Science, CHRIST University, Bangalore, India</text>
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                <text>Alzheimer's is a progressive brain disorder which is an untreatable, and inoperable and mostly affect the elderly people. There is a new case of Alzheimer's disease being discovered globally in every four seconds. The outcome is fatal, as it results in death. Timely identification of Alzheimer's disease can be beneficial for us to get necessary care and possibly even avert brain tissue damage by the time. Effective automated techniques are required for detecting Alzheimer's disease at very early stage. Researchers use a variety of novel approaches to classify Alzheimer's disease. machine learning, an AI branch use probabilistic technique that allow system to acquire knowledge from huge amount of data. In this paper we represent a analysis report of the work which is done by researcher in this field. Research has achieved quite promising prediction accuracies however they were evaluated the the non-existent datasets from various imaging modalities which makes it difficult to make the fair comparison with the other methods comparison among them. In this paper, we conducted a study on the effectiveness of using human brain MRI scans to detect Alzheimer's disease and ended with a future discussion of Alzheimer's research trends.   2021 IEEE.</text>
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                <text>Dahiya S., Galgotias University, School of Computing Science and Engineering, Greater Noida, India; Vijayalakshmi S., Christ University, Department of Data Science, Lavasa, India; Sabharwal M., Galgotias University, School of Computing Science, Greater Noida, India</text>
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</itemContainer>
