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                <text>Perera A.P., Christ University, Department of Electrical and Electronics Engineering, Bangalore, India; Alex A.J., Christ University, Department of Electrical and Electronics Engineering, Bangalore, India; Bhushan S., Christ University, Department of Electrical and Electronics Engineering, Bangalore, India</text>
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                <text>Singha S., Kristu Jayanti College (Autonomous), India; Singha R., Christ University, India; Natal M.S., Amity University, Noida, India; Ruben V.M., Christ University, India; Haokip A.D., Christ King High School, India</text>
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                <text>The Climate Change Crisis and Its Impact on Mental Health, pp. 213-226.</text>
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                <text>Kulkarni S., CHRIST University, Karnataka, Bengaluru, India; Kaveramma C.C.N., CHRIST University, Karnataka, Bengaluru, India; Jayadurga R., CHRIST University, Karnataka, Bengaluru, India</text>
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                <text>Real-time sign language is a basic means of communication for hearing-impaired people. There is a substantial communication barrier between sign language users and those who cannot comprehend sign language. Indian Sign Language (ISL) is built to ease the social challenge between hearing-impaired people and individuals who are unable to understand sign language using TensorFlow featuring Indian languages for smoother communication. The study aims to build a proficient real-time sign language translator using TensorFlow to detect hand signals in real-time video streams. Integration of TensorFlow enables real-time gesture detection, demonstrating how technology can bring about real progress when it comes to improving communication with persons who cannot hear. The application is trained on a specialized dataset comprising different Indian sign language signals, pre-processed to improve gesture recognition focusing on fast and accurate sign language recognition and translation. The objective is to develop a model that can recognize and translate hand gestures into text in Indian languages. This approach uses TensorFlow object detection API to recognize body gestures from real-time videos. The model is trained on a unique dataset of diverse Indian languages that is pre-processed for better recognition accuracy. Techniques like transfer learning are employed to fine-tune the model by integrating CNN for gesture recognition. The detected outputs are after-ward transformed into Indian languages. The systems accuracy may be restricted because of the quality and variety of different Indian languages across the country. The findings indicate that the model can accurately translate the collection of sign languages into text highlighting the potential of TensorFlow Object Detection for real-time sign language.  The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.</text>
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                <text>Inorganic nanomaterials of different chemical compositions and morphologies have been applied in cosmetic products due to their size- and shape-dependent properties which can improve the performance of the products. This chapter discusses the application of inorganic nanoparticles in cosmetic products with an emphasis on the characteristic features of nanoparticles suitable for cosmetic applications. In particular, applications of inorganic nanoparticles as UV filters and antimicrobial materials are discussed in detail with a basic overview of the fundamental scientific basis related to these applications. Types of nanoparticles used in commercial cosmetic products are enlisted, reflecting the range of applications and property modifications. Applications of inorganic nanoparticles in cosmetic formulations as active components and nanocarriers are also discussed along with relevant examples.  Springer Nature Switzerland AG 2019.</text>
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                <text>Nanocosmetics: From Ideas to Products, pp. 29-46.</text>
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                <text>Vinod T.P., Department of Chemistry, CHRIST (Deemed to be University), Hosur Road, Bangalore, 560029, India; Jelinek R., Department of Chemistry, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel, Ilse Katz Institute for Nanotechnology, Ben-Gurion University of the Negev, Beer Sheva, 84105, Israel</text>
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                <text>Inpatient complaining behaviour: A study on the overt and covert behaviour of inpatients in Indian hospitals</text>
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                <text>Consumer dissatisfaction and complaining behaviour have always been a topic of discussion in educational institutes and industries alike. Whereas dissatisfaction with product purchases and subsequent returns or associated consumer responses is very common, the same in the service sector has been quite different. In India, it is not only the patient who decides, which healthcare service to opt for, because Indians are culturally embedded in a system of collective consumption where other family members or relatives or friends also influence their decision-making. This paper is an exploratory study done to comprehend the chosen behavioural responses of dissatisfied inpatients in India through a questionnaire survey. The survey followed a retrospective recall technique in which the recall window was fixed at six months. The sampling technique followed was probability sampling. The data collection tool was structured and self-administered questionnaire administered in the sampled nine districts of Kerala. A good number of respondents attributed their overt complaining behaviour to lack of cordiality of doctors, nurses or the attending staff and lack of proper care and concern from doctors or nurses. Post complaining, service recovery was found to be satisfactory for most of the complainers.  2020, Kamala-Raj Enterprises. All rights reserved.</text>
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                <text>Khadir F.; Swamynathan R.</text>
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                <text>Studies on Ethno-Medicine, Vol-14, No. 45689, pp. 30-40.</text>
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                <text>ISSN: 9735070</text>
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                <text>Khadir F., School of Business Studies and Social Sciences, Christ University, Bengaluru, Karnataka, India; Swamynathan R., School of Business, Manipal Academy of Higher Education, Dubai International Academic City, Dubai, United Arab Emirates</text>
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                <text>Inphase and outphase concentration modulation on the onset of magneto-convection and mass transfer in weak electrically conducting micropolar fluids</text>
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                <text>Mathew A.; Jagannath M.; Pranesh S.</text>
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                <text>AIP Conference Proceedings, Vol-2080</text>
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                <text>American Institute of Physics Inc.</text>
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                <text>Mathew A., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560029, India; Jagannath M., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560029, India; Pranesh S., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, Karnataka, 560029, India</text>
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                <text>Masonry is one of the commonly used construction technology both in urban and rural areas. In this paper the in-plane behaviour of masonry walls is analytically studied considering existing closed form equations. Previous studies have proven that the lateral load behaviour mainly depends on the aspect ratios (h/L) as well as the axial loads. From this analysis the governing failure is determined and the lateral load versus lateral deflection curve is plotted for various percentages of axial loads. This graph gives the ductility of the wall. This concept is further applied to a simple masonry structure and the push over curve is plotted.  2020, Springer Nature Switzerland AG.</text>
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                <text>Sivadas A., Adi Shankara Institute of Engineering and Technology, Ernakulam, India; Kavya K.N., Adi Shankara Institute of Engineering and Technology, Ernakulam, India; Prakash P., Adi Shankara Institute of Engineering and Technology, Ernakulam, India; Sharma S., Adi Shankara Institute of Engineering and Technology, Ernakulam, India; Kollerathu J.A., Department of Civil Engineering, Faculty of Engineering, Christ (Deemed to be) University, Bengaluru, India</text>
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                <text>Inquiry into reverse logistics and a decision model</text>
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                <text>A process in which a product is moving in reverse along the supply chain network is called as reverse logistics. The objective of reverse logistics is to recapture the value of the final product. Reverse logistics is gaining ground because of its importance in managing a closed loop supply chain. Companies across the world are showing concern about environmental degradation and are realising the need for sustainable development. Many countries have already passed legal regulations. Good reverse logistics process indicates lot of reuse, recycling and reducing the material consumed, thereby ensuring sustainability. Improving reverse logistics will result in increase in sales up by 10%, a reduction in the supply chain costs by 25% to 40%. In retail sector the profit margins are less and strengthening reverse logistics can increase the profit margins. This paper attempts to inquire into the reverse logistics area and come out with the prioritised variables impacting the different reverse logistics disposition decision. The paper attempts to propose a conceptual model for reverse logistics disposition decision. Copyright  2019 Inderscience Enterprises Ltd.</text>
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                <text>International Journal of Logistics Systems and Management, Vol-33, No. 3, pp. 353-382.</text>
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                <text>ISSN: 17427967</text>
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                <text>Padmanabh B., Institute of Management, Christ University, Bangalore, India; Jeevananda S., Institute of Management, Christ University, Bangalore, India</text>
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                <text>International Journal Logistics Systems And Management, Vol.33, Issue 3, pp.353-382, ISSN No: 1742-7967.</text>
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                <text>Cloud computing is a high network infrastructure where users, owners, third users, authorized users, and customers can access and store their information quickly. The use of cloud computing has realized the rapid increase of information in every field and the need for a centralized location for processing efficiently. This cloud is nowadays highly affected by internal threats of the user. Sensitive applications such as banking, hospital, and business are more likely affected by real user threats. An intruder is presented as a user and set as a member of the network. After becoming an insider in the network, they will try to attack or steal sensitive data during information sharing or conversation. The major issue in today's technological development is identifying the insider threat in the cloud network. When data are lost, compromising cloud users is difficult. Privacy and security are not ensured, and then, the usage of the cloud is not trusted. Several solutions are available for the external security of the cloud network. However, insider or internal threats need to be addressed. In this research work, we focus on a solution for identifying an insider attack using the artificial intelligence technique. An insider attack is possible by using nodes of weak users systems. They will log in using a weak user id, connect to a network, and pretend to be a trusted node. Then, they can easily attack and hack information as an insider, and identifying them is very difficult. These types of attacks need intelligent solutions. A machine learning approach is widely used for security issues. To date, the existing lags can classify the attackers accurately. This information hijacking process is very absurd, which motivates young researchers to provide a solution for internal threats. In our proposed work, we track the attackers using a user interaction behavior pattern and deep learning technique. The usage of mouse movements and clicks and keystrokes of the real user is stored in a database. The deep belief neural network is designed using a restricted Boltzmann machine (RBM) so that the layer of RBM communicates with the previous and subsequent layers. The result is evaluated using a Cooja simulator based on the cloud environment. The accuracy and F-measure are highly improved compared with when using the existing long short-term memory and support vector machine.  2022 CRL Publishing. All rights reserved.</text>
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                <text>Anakath A.S.; Kannadasan R.; Joseph N.P.; Boominathan P.; Sreekanth G.R.</text>
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                <text>Computer Systems Science and Engineering, Vol-41, No. 2, pp. 479-492.</text>
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                <text>&lt;a href="https://doi.org/10.32604/csse.2022.019940" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.32604/csse.2022.019940&lt;/a&gt;
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                <text>All Open Access; Hybrid Gold Open Access</text>
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                <text>Anakath A.S., School of Computing, E.G.S. Pillay Engineering College, Tamilnadu, Nagapattinam, 611002, India; Kannadasan R., Department of Software Systems, School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology University, Tamilnadu, Vellore, 632014, India; Joseph N.P., Department of Computer Science, CHRIST(Deemed to be University), Bengaluru, 560029, India; Boominathan P., Department of Information Security, School of Computer Science and Engineering (SCOPE), Vellore Institute of Technology University, Tamilnadu, Vellore, 632014, India; Sreekanth G.R., Department of Computer Science and Engineering, Kongu Engineering College, Tamilnadu, Erode, 638060, India</text>
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                <text>Insight into the effects of waste vegetable oil on self-healing behavior of bitumen binder</text>
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          <element elementId="49">
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                <text>Bitumen; Molecular dynamics; Self-healing behavior; Waste vegetable oil</text>
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                <text>The application of waste vegetable oil (WVO) in bitumen has been the subject of research for years, however, the self-healing behavior of WVO modified bitumen (WMB) has not been adequately reported. In this research, molecular dynamics (MD) simulations and laboratory experiments were performed to reveal the effects of WVO on the self-healing behavior of bitumen. Models of base bitumen and WMB were constructed. Further, dynamic calculations were carried out for the self-healing models of base bitumen and WMB both with 10 microcracks. The energy properties, conformation and density of bitumen during the self-healing process were analyzed. Meanwhile, the effects of WVO on the fractional free volume (FFV) of bitumen, the distribution of bitumen components and the mobility of bitumen molecules were investigated. Finally, the modified fatigue-healing-fatigue (FHF) test was conducted to verify the effects of WVO on the self-healing efficiency of bitumen. Results show that Van der Waals forces drive the mobility of bitumen molecules. Along with the disappearance of the central microcrack, the density of the self-healing system gradually increases and finally reaches that of the bulk bitumen. WVO with superior mobility capacity increases the FFV of bitumen and converts asphaltene large aggregated structure into small aggregated structure, which facilitates the mobility of the bitumen during the self-healing process. Thus, the addition of WVO contributes to the self-healing efficiency of the bitumen. The modified FHF test also verified that the self-healing efficiency of bitumen is improved with the presence of WVO. These findings provide further insight into the self-healing behaviors of WMB.  2022</text>
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                <text>Xu N.; Wang H.; Chen Y.; Hossiney N.; Ma Z.; Wang H.</text>
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              <elementText elementTextId="98701">
                <text>Construction and Building Materials, Vol-363</text>
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              <elementText elementTextId="98702">
                <text>Elsevier Ltd</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.conbuildmat.2022.129888" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.conbuildmat.2022.129888&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143308132&amp;amp;doi=10.1016%2Fj.conbuildmat.2022.129888&amp;amp;partnerID=40&amp;amp;md5=48e7332f87a078520f94d3a1df05ce00" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85143308132&amp;amp;doi=10.1016%2fj.conbuildmat.2022.129888&amp;amp;partnerID=40&amp;amp;md5=48e7332f87a078520f94d3a1df05ce00&lt;/a&gt;</text>
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              <elementText elementTextId="98705">
                <text>Restricted Access</text>
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            </elementTextContainer>
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            <description>A related resource</description>
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              <elementText elementTextId="98706">
                <text>ISSN: 9500618; CODEN: CBUME</text>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="98708">
                <text>English</text>
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              <elementText elementTextId="98710">
                <text>Xu N., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Wang H., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Chen Y., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Hossiney N., Department of Civil Engineering, CHRIST University, Kumbalgodu, Karnataka, Bengaluru, 560074, India; Ma Z., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China; Wang H., School of Highway, Chang'an University, South Erhuan Middle Section, Shaanxi Province, Xi'an City, 710064, China</text>
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                <elementText elementTextId="51377">
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="182131">
                <text>Insights into Artificial Neural Network techniques, and its Application in Steganography</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="182132">
                <text>Convolution Neural Networks; Deep Steganography; Feed forward; LSTM; Optimization Algorithms; Recurrent Neural network</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="41">
            <name>Description</name>
            <description>An account of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="182133">
                <text>Deep Steganography is a data concealment technology that uses artificial intelligence (AI) to automate the process of hiding and extracting information through layers of training. It enables for the automated generation of a cover depending on the concealed message. Previously, the technique depended on the existing cover to hide data, which limited the number of Steganographic characteristics available. Artificial intelligence and deep learning techniques have been used to steganography recently and the results are satisfactory. Although neural networks have demonstrated their ability to imitate human talents, it is still too early to draw comparisons between people and them. To improve their capabilities, neural networks are being employed in a number of disciplines, including steganography. Recurrent Neural Networks (RNN) is a widely used technology that automatically creates Stego-text regardless of payload volume. The features are extracted using a convolution neural network (CNN) based on the image. Perceptron, Multi-Layer Perceptron (MLP), Feed Forward Neural Network, Long Short Term Memory (LSTM) networks, and others are examples of this. In this research, we looked at all of the neural network approaches for Steganographic purposes in depth. This article also discusses the problems that each technology faces, as well as potential solutions.  2021 Institute of Physics Publishing. All rights reserved.</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="39">
            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
            <elementTextContainer>
              <elementText elementTextId="182134">
                <text>Gurunath R.; Samanta D.</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="48">
            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
            <elementTextContainer>
              <elementText elementTextId="182135">
                <text>Journal of Physics: Conference Series, Vol-2089, No. 1</text>
              </elementText>
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          <element elementId="45">
            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="182136">
                <text>IOP Publishing Ltd</text>
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            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="182137">
                <text>2021-01-01</text>
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              <elementText elementTextId="182138">
                <text>&lt;a href="https://doi.org/10.1088/1742-6596/2089/1/012043" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1088/1742-6596/2089/1/012043&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121519081&amp;amp;doi=10.1088%2F1742-6596%2F2089%2F1%2F012043&amp;amp;partnerID=40&amp;amp;md5=a940899a4d0d8d0d4623fd48aeb5708a" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121519081&amp;amp;doi=10.1088%2f1742-6596%2f2089%2f1%2f012043&amp;amp;partnerID=40&amp;amp;md5=a940899a4d0d8d0d4623fd48aeb5708a&lt;/a&gt;</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="182139">
                <text>All Open Access; Gold Open Access</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <description>A related resource</description>
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              <elementText elementTextId="182140">
                <text>ISSN: 17426588</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <name>Format</name>
            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="182141">
                <text>Online</text>
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            </elementTextContainer>
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            <name>Language</name>
            <description>A language of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="182142">
                <text>English</text>
              </elementText>
            </elementTextContainer>
          </element>
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            <elementTextContainer>
              <elementText elementTextId="182144">
                <text>Gurunath R., Department of Computer Science, CHRIST University, Bangalore, India; Samanta D., Department of Computer Science, CHRIST University, Bangalore, India</text>
              </elementText>
            </elementTextContainer>
          </element>
        </elementContainer>
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  <item itemId="18033" public="1" featured="0">
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          <elementContainer>
            <element elementId="50">
              <name>Title</name>
              <description>A name given to the resource</description>
              <elementTextContainer>
                <elementText elementTextId="44496">
                  <text>Book Chapter</text>
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              </elementTextContainer>
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      <name>Book Chapter</name>
      <description>Faculty Publications- Book Chapter</description>
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    <elementSetContainer>
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        <elementContainer>
          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="148530">
                <text>Insights into the performance of farmer producer companies: An exploratory analysis in kerala, india</text>
              </elementText>
            </elementTextContainer>
          </element>
          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
            <elementTextContainer>
              <elementText elementTextId="148531">
                <text>Agricultural cooperatives; Farmer producer companies (FPCs); FPC in Kerala; Smallholder farmers; Sustainable agriculture</text>
              </elementText>
            </elementTextContainer>
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          <element elementId="41">
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            <description>An account of the resource</description>
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              <elementText elementTextId="148532">
                <text>India faces challenges in farmers well-being due to small land holdings and the absence of an organized agricultural market system, prompting the introduc-tion of initiatives such as the promotion of Farmer Producer Organizations (FPOs) to fortify the agricultural market. However, ambiguity remains over the functioning of such initiatives. This study aims to tackle the aforementioned issue by collecting and analyzing data on the operations of 400 registered Farmer Producer Companies (FPCs) in the state of Kerala, India. The analysis focuses on key indicators such as the age of the FPC, paid-up capital, and activity status (whether active or struck-off). A primary survey has also been conducted, both telephonic and face-to-face inter-views, based on convenience, using a semi-structured questionnaire. Both farmers and representatives from FPCs are interviewed. The issues discussed are marketing assistance, input sales, type of services offered, managerial capacities, etc. The study finds that not all registered FPCs effectively improve the welfare of farmers. The most common service FPCs provide is marketing, which helps increase product sales through collective bargaining power and access to higher-paying markets. FPCs that engage in contract farming, sell through supermarkets, or explore inter-state or inter-national markets are more successful in increasing farmers revenues than those that only use traditional market chains. However, it is important to note that FPCs face several challenges, including a lack of infrastructure and support, limited access to credit, and a lack of skilled and trained staff. These essential factors must be addressed for FPCs to achieve their full potential.  The Author(s).</text>
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              <elementText elementTextId="148533">
                <text>Augustine D.; Roy N.S.</text>
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            <elementTextContainer>
              <elementText elementTextId="148534">
                <text>Studies in Systems, Decision and Control, Vol-525, pp. 749-766.</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
            <elementTextContainer>
              <elementText elementTextId="148535">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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              <elementText elementTextId="148536">
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                <text>&lt;a href="https://doi.org/10.1007/978-3-031-54383-8_58" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-031-54383-8_58&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200564278&amp;amp;doi=10.1007%2F978-3-031-54383-8_58&amp;amp;partnerID=40&amp;amp;md5=8f352e863067f439ce8aeaa27b42a1da" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200564278&amp;amp;doi=10.1007%2f978-3-031-54383-8_58&amp;amp;partnerID=40&amp;amp;md5=8f352e863067f439ce8aeaa27b42a1da&lt;/a&gt;</text>
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            <description>Information about rights held in and over the resource</description>
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              <elementText elementTextId="148538">
                <text>Restricted Access</text>
              </elementText>
            </elementTextContainer>
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              <elementText elementTextId="148539">
                <text>ISSN: 21984182</text>
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            </elementTextContainer>
          </element>
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            <description>The file format, physical medium, or dimensions of the resource</description>
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              <elementText elementTextId="148541">
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            <elementTextContainer>
              <elementText elementTextId="148543">
                <text>Augustine D., Department of Economics, Christ (Deemed to Be University), Bangalore, India; Roy N.S., Department of Economics, Christ (Deemed to Be University), Bangalore, India</text>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
            <elementTextContainer>
              <elementText elementTextId="92896">
                <text>Insights into the plant growth promotion properties of bacterial endophytes isolated from Alternanthera philoxeroides and Eichhornia crassipes from Bellandur lake, India</text>
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                <text>The presence of macrophytes such as Alternanthera philoxeroides and Eichhornia crassipes in Bellandur Lake, India, has been observed despite the high pollution levels. Our research aims to explore the potential role of endophytes in promoting the growth of these macrophytes in such heavily contaminated environments. In current study, we isolated 20 endophytic bacteria from various parts of A. philoxeroides (12) and E. crassipes (8) plants, including shoots, roots, leaves, and flowers. We found that a significant proportion of endophytes from A. philoxeroides (42 %) and E. crassipes (25 %) produced more than 100 g/mL of indole acetic acid (IAA). Similarly, the majority of the isolates possessed other plant growth promoting traits like ammonia production, nitrogen fixation, phosphate and potassium solubilization, siderophore production, and ACC deaminase production. Many of these isolates demonstrated extracellular enzyme production and halotolerance properties. We identified Acinetobacter soli ON529869 and Bacillus licheniformis ON506048 as the most effective plant growth promoters among the isolates, which also displayed antifungal properties against Fusarium solani and Cladosporium tenuissimum in vitro. Furthermore, greenhouse trials using these two endophytes revealed their significant plant growth promotion abilities in Amaranthus viridis. The pigment indices were evaluated using CI-710 Leaf Spectrometer. In conclusion, our findings provide compelling evidence for exploring the endophytic microbiomes of macrophytes in polluted areas for sustainable agriculture and bioprospecting of unique traits. This research could lead to the discovery of new and valuable resources for agricultural practices and other applications. 2023 SAAB</text>
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                <text>Philip I.; Sarojini S.; Biswas S.; Jayaram S.</text>
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                <text>South African Journal of Botany, Vol-162, pp. 588-603.</text>
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                <text>Elsevier B.V.</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.sajb.2023.09.028" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.sajb.2023.09.028&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173153207&amp;amp;doi=10.1016%2Fj.sajb.2023.09.028&amp;amp;partnerID=40&amp;amp;md5=70aa0a7a6cfaf2dfe28169ef11a7fb1f" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173153207&amp;amp;doi=10.1016%2fj.sajb.2023.09.028&amp;amp;partnerID=40&amp;amp;md5=70aa0a7a6cfaf2dfe28169ef11a7fb1f&lt;/a&gt;</text>
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                <text>ISSN: 2546299; CODEN: SAJBD| LS; 2023-2024; Vol-2; 0548-0562</text>
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                <text>Philip I., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India; Sarojini S., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India; Biswas S., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India; Jayaram S., Department of Life Sciences, CHRIST (Deemed to be University), Bangalore, 560029, India</text>
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                <text>Shrikumar, M.; Kurien, Georgy P.; Saha, Saibal Kumar</text>
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                <text>Insights into the Publication Trends of Pharmaceutical Reverse Supply Chain Using Data Mining Approach</text>
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                <text>Lecture Notes in Networks and Systems;Volume;1865 LNNS;pp.286-296</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-3-032-19185-4_24" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-032-19185-4_24&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105039578780?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105039578780?origin=resultslist&lt;/a&gt;</text>
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                <text>Shrikumar M., Christ University, Bangalore, India; Kurien G.P., Christ University, Bangalore, India; Saha S.K., Xavier Business School, St. Xaviers University, Kolkata, India</text>
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                <text>Due to the non-profitable nature of reverse supply chain of pharmaceutical products, researchers and companies have not shown much interest in this field. Due to stringent regulatory compliances pharmaceutical companies and hospitals are mandated for proper disposal of pharmaceutical wastes. This research aims to highlight the publication trends of pharmaceutical reverse supply chain using data mining approach. The metadata of published literature was extracted from Scopus and analysis was done for the title and abstracts of the articles. It was found that there is limited published literature on this topic. Co-occurrence map of text-based data, time graph of co-occurrence map of text, trigrams word cloud, keywords plus word cloud and unigrams word cloud were formed to get insights into the publication trend. A model had been proposed from the consumers end for pharmaceutical reverse supply chain.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>data mining; end of life; end of use; pharmaceutical; reverse supply chain</text>
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              <elementText elementTextId="265587">
                <text>Springer Science and Business Media Deutschland GmbH</text>
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                <text>ISSN: 23673370; ISBN: 978-303219184-7;</text>
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              <elementText elementTextId="265591">
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              <elementText elementTextId="208299">
                <text>Mathew, Sandra; Sunajadevi, Kalathiparambil Rajendra Pai; Varghese, Arun; Pinheiro, Dephan; Saravanakumar, B.</text>
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                <text>Insights into the synergistic effect of V3S4 decorated Ti3C2 MXene as an electrode for asymmetric supercapacitor</text>
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              <elementText elementTextId="208302">
                <text>Journal of Physics and Chemistry of Solids;Volume;207;Issue;;Article No.;112958;</text>
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                <text>&lt;a href="https://doi.org/10.1016/j.jpcs.2025.112958" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1016/j.jpcs.2025.112958&lt;/a&gt; &lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/pages/publications/105008442501?origin=resultslist" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/pages/publications/105008442501?origin=resultslist&lt;/a&gt;</text>
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                <text>Mathew S., Department of Chemistry, Christ University, Karnataka, Bengaluru, 560029, India; Sunajadevi K.R.P., Department of Chemistry, Christ University, Karnataka, Bengaluru, 560029, India; Varghese A., Department of Chemistry, Christ University, Karnataka, Bengaluru, 560029, India, Department of Chemistry, Faculty of Engineering and Technology, Jain University, Bangalore, 562112, India; Pinheiro D., Department of Chemistry, Christ University, Karnataka, Bengaluru, 560029, India; Saravanakumar B., Department of Physics, Dr. Mahalingam College of Engineering and Technology, Tamil Nadu, Pollachi, 642003, India</text>
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                <text>As the globe moves toward sustainable energy options, effectively storing and managing energy becomes increasingly crucial. Advanced energy storage technologies can bridge the gap between energy generation and consumption, ensuring a reliable and stable supply even when renewable sources are intermittent. In this context, the rise of two-dimensional layered Ti3C2 MXene as a promising electrode for supercapacitors is particularly noteworthy, owing to its unique physical, chemical, and electrocatalytic attributes. Despite its potential, the immediate collapse and aggregation of MXene layers pose significant obstacles to their widespread usage in energy storage applications. This study explores advanced energy storage technologies using V3S4 coupled Ti3C2 MXene as electrodes in asymmetric supercapacitors. By combining the unique properties of V3S4 and Ti3C2 MXene, new avenues for improving the performance of supercapacitors are being unlocked. The experimental results indicate that the Ti3C2/V3S4 electrode exhibits an enhanced specific capacitance (Csp) of 1323.7 Fg-1 at a current density of 1 Ag-1, with an outstanding capacitance retention of 90.5 % after 2000 cycles. An assembled asymmetric supercapacitor, Ti3C2/V3S4//activated carbon shows superior energy storage efficiency, achieving a Csp of 258.4 Fg-1 at 2 Ag-1. The device exhibits a high energy density of 60.6 Whkg?1 at a power density of 649.2 Wkg-1, while holding onto a capacitance retention rate of 91.1 % over 10,000 cycles.  2025 Elsevier Ltd</text>
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                <text>Asymmetric supercapacitor; Electrocatalyst; Energy storage; Ti&lt;sub&gt;3&lt;/sub&gt;C&lt;sub&gt;2&lt;/sub&gt; MXene; V&lt;sub&gt;3&lt;/sub&gt;S&lt;sub&gt;4&lt;/sub&gt;</text>
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                <text>Insights into thyroid disease: Harnessing machine learning for analysis and classification of multi-label medical data</text>
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                <text>Thyroid disease refers to a wide range of disorders that occur due to dysfunction of the thyroid gland, a small gland located at the base of the neck that produces thyroid hormones. Through the analysis of this comprehensive dataset, we aim to utilize machine learning (ML) techniques for the analysis and classification of thyroid data. Employing ML techniques for thyroid classification has the potential to improve diagnostic accuracy, facilitate timelier interventions, lower expenses, optimize doctor time, and foster a more personalized approach to thyroid care. The objective of this research was to conduct multiclassification, encompassing the broadest array of classes for the target variable. To address the imbalances within the dataset, we employed the Synthetic Oversampling Technique (SMOTE) as a resampling method. Specifically, classes with a minimum of 10 samples were retained, resulting in the inclusion of 19 out of the total 34 classes in the dataset. The importance of SMOTE in addressing class imbalance is examined in this chapter, with an emphasis on how it may be used to enhance classifier model performance. Moreover, we conducted a comparative analysis of Classification Models, including Random Forest, K-Nearest Neighbor, Decision Tree, SVM, Gradient Boosting, Multinomial Naive Bayes, and Logistic Regression, to assess their accuracies. Following the resampling of the dataset, the highest accuracy of 99.99% was achieved with the gradient booster. Additionally, this research incorporated the association rule technique to uncover meaningful relationships within the dataset.  2025 selection and editorial matter, Arun Kumar Rana, Vishnu Sharma, Sanjeev Kumar Rana, and Vijay Shanker Chaudhary; individual chapters, the contributors. All rights reserved.</text>
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              <elementText elementTextId="142054">
                <text>Surendran S.; Salma M.U.</text>
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              <elementText elementTextId="142055">
                <text>Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering, pp. 54-69.</text>
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              <elementText elementTextId="142056">
                <text>CRC Press</text>
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                <text>Surendran S., Christ(Deemed to Be University), Bengaluru, India; Salma M.U., Department of Statistics and Data Science, Christ(Deemed to Be University), Bengaluru, India</text>
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                <text>Insights of Evolving Methods Towards Screening of AI-Enhanced Malware in IoT Environment</text>
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                <text>Artificial Intelligence; detection; Internet of Things; Malware; prevention; Security; Threats</text>
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                <text>Internet-of-Things (IoT) has been encountering a series of potential form of threats since past half decades. Artificial Intelligence (AI), which is frequently seen to be adopted to solve various challenges in IoT operation, has now been adopted even by attackers for their malicious purposes. Of all forms of threats, AI-enhanced malwares are one of the most potential forms of threats which has its extensive effectiveness towards the complete operation of the entire IoT environment. Hence, this manuscript discusses existing detection and prevention approaches evolved in current literatures to understand various taxonomies of solution-based methodologies for circumventing such threats. The paper also contributes towards highlighting the potential open-ended issues that are yet to be addressed.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.</text>
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                <text>Shahabadkar R.; Nandeeswar S.B.; Soman R.; Sangeetha G.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-1120 LNNS, pp. 694-704.</text>
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                <text>&lt;a href="https://doi.org/10.1007/978-3-031-70518-2_57" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-031-70518-2_57&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210812213&amp;amp;doi=10.1007%2F978-3-031-70518-2_57&amp;amp;partnerID=40&amp;amp;md5=9ad21107c217298867738a5644654d34" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210812213&amp;amp;doi=10.1007%2f978-3-031-70518-2_57&amp;amp;partnerID=40&amp;amp;md5=9ad21107c217298867738a5644654d34&lt;/a&gt;</text>
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              <elementText elementTextId="162482">
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                <text>ISSN: 23673370; ISBN: 978-303170517-5</text>
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                <text>Shahabadkar R., Department of CSE, AMC Engineering College, Karnataka, Bangaluru, 560083, India; Nandeeswar S.B., Department of CSE (AIML), AMC Engineering College, Karnataka, Bengaluru, India; Soman R., Department of CSE, BNM Institute of Technology, Banashankari Stage II, Karnataka, Bangaluru, 560070, India; Sangeetha G., Department of Computer Science, Christ University, Karnataka, Bengaluru, India</text>
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                <text>Insights on bar quenching from a multiwavelength analysis: The case of Messier 95</text>
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          <element elementId="49">
            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="131790">
                <text>Galaxies: evolution; Galaxies: formation; Galaxies: individual: Messier 95; Galaxies: star formation; Ultraviolet: galaxies</text>
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                <text>The physical processes related to the eect of bars in the quenching of star formation in the region between the nuclear/central subkiloparsec region and the ends of the bar (bar region) of spiral galaxies is not fully understood. It is hypothesized that the bar can either stabilize the gas against collapse, inhibiting star formation, or eciently consume all the available gas, leaving no fuel for further star formation.We present a multiwavelength study using the archival data of an early-type barred spiral galaxy, Messier 95, which shows signatures of suppressed star formation in the bar region. Using optical, ultraviolet (UV), infrared, CO, and HI imaging data we study the pattern of star formation progression and stellar/gas distribution, and try to provide insights into the process responsible for the observed pattern. The FUV NUV pixel colour map reveals a cavity devoid of UV flux in the bar region that matches the length of the bar, which is 4.2 kpc. The central nuclear region of the galaxy shows a blue colour clump and along the major axis of the stellar bar the colour progressively becomes redder. Based on a comparison to single stellar population models, we show that the region of galaxy along the major axis of the bar, unlike the region outside the bar, is comprised of stellar populations with ages 350 Myr; there is a star-forming clump in the centre of younger ages of 150 Myr. Interestingly the bar region is also devoid of neutral and molecular hydrogen but has an abundant molecular hydrogen present at the nuclear region of the galaxy. Our results are consistent with a picture in which the stellar bar in Messier 95 is redistributing the gas by funnelling gas inflows to nuclear region, thus making the bar region devoid of fuel for star formation.  ESO 2019.</text>
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                <text>George K.; Joseph P.; Mondal C.; Subramanian S.; Subramaniam A.; Paul K.T.</text>
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              <elementText elementTextId="131793">
                <text>Astronomy and Astrophysics, Vol-621</text>
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                <text>EDP Sciences</text>
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            <name>Date</name>
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                <text>&lt;a href="https://doi.org/10.1051/0004-6361/201834500" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1051/0004-6361/201834500&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059650898&amp;amp;doi=10.1051%2F0004-6361%2F201834500&amp;amp;partnerID=40&amp;amp;md5=aa5d39db7fb93a37f2b75175b4f22a37" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059650898&amp;amp;doi=10.1051%2f0004-6361%2f201834500&amp;amp;partnerID=40&amp;amp;md5=aa5d39db7fb93a37f2b75175b4f22a37&lt;/a&gt;</text>
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              <elementText elementTextId="131797">
                <text>All Open Access; Bronze Open Access; Green Open Access</text>
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                <text>ISSN: 46361; CODEN: AAEJA</text>
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              <elementText elementTextId="131800">
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              <elementText elementTextId="131802">
                <text>George K., Department of Physics, Christ University, Bangalore, India; Joseph P., Department of Physics, Christ University, Bangalore, India, Indian Institute of Astrophysics, Koramangala II Block, Bangalore, India; Mondal C., Indian Institute of Astrophysics, Koramangala II Block, Bangalore, India; Subramanian S., Indian Institute of Astrophysics, Koramangala II Block, Bangalore, India; Subramaniam A., Indian Institute of Astrophysics, Koramangala II Block, Bangalore, India; Paul K.T., Department of Physics, Christ University, Bangalore, India</text>
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