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                <text>Keratin as a sustainable biopolymer for waste water treatment</text>
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                <text>Biopolymer; Dyes; Heavy metals; Keratin; Oil; Waste water</text>
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                <text>Keratin is one of the most abundant natural polymers with potential application in various fields but is usually seen discarded as waste generated from poultry farms along roadsides and landfills. These are indeed the cheapest source of keratin protein which could be used for various applications. Owing to the structural properties, keratinous materials are now being exploited in wastewater treatment systems as adsorbents. The rich amino acid content having hydroxyl, carboxyl and amino groups has been found to be beneficial in removing contaminants from waste waters like heavy metals and dyes. Research based on this idea has received peak attention to a point where formulations of different adsorbent materials like nanofibre, biofilms and biocomposite from keratinous raw materials are now available for commercial use. This review summarises the application of keratin as an efficient adsorbent for waste water treatment providing an insight into its structure, forms of keratin used for treatments and mechanism of adsorption of different components in waste water.  2022 World Research Association. All rights reserved.</text>
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                <text>Stanly L.M.; Umesh M.</text>
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                <text>Research Journal of Chemistry and Environment, Vol-26, No. 9, pp. 157-166.</text>
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                <text>2022-01-01</text>
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                <text>&lt;a href="https://doi.org/10.25303/2609rjce1570166" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.25303/2609rjce1570166&lt;/a&gt;
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                <text>ISSN: 9720626</text>
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                <text>Stanly L.M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Umesh M., Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bangalore, India</text>
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                <text>Kernel granulometric texture analysis and light res-aspp-unet classification for covid-19 detection</text>
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                <text>Convolutional neural network; COVID-19; Deep residual learning; Granulo metrics texture analysis; Principal component analysis; X-ray</text>
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                <text>This research article proposes an automatic frame work for detecting COVID -19 at the early stage using chest X-ray image. It is an undeniable fact that coronovirus is a serious disease but the early detection of the virus present in human bodies can save lives. In recent times, there are somany research solutions that have been presented for early detection, but there is still a lack in need of right and even rich technology for its early detection. The proposed deep learning model analysis the pixels of every image and adjudges the presence of virus. The classifier is designed in such a way so that, it automatically detects the virus present in lungs using chest image. This approach uses an image texture analysis technique called granulometric mathematical model. Selected features are heuristically processed for optimization using novel multi scaling deep learning called light weight residual-atrous spatial pyramid pooling (LightRES-ASPP-Unet) Unet model. The proposed deep LightRES-ASPPUnet technique has a higher level of contracting solution by extracting major level of image features. Moreover, the corona virus has been detected using high resolution output. In the framework, atrous spatial pyramid pooling (ASPP) method is employed at its bottom level for incorporating the deep multi scale features in to the discriminative mode. The architectural working starts from the selecting the features from the image using granulometric mathematical model and the selected features are optimized using LightRESASPP- Unet. ASPP in the analysis of images has performed better than the existing Unet model. The proposed algorithm has achieved 99.6% of accuracy in detecting the virus at its early stage.  2022 Tech Science Press. All rights reserved.</text>
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                <text>Devipriya A.; Prabu P.; Venkatachalam K.; Ibrahim A.Z.</text>
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                <text>Computers, Materials and Continua, Vol-71, No. 1, pp. 651-666.</text>
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                <text>&lt;a href="https://doi.org/10.32604/cmc.2022.020820" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.32604/cmc.2022.020820&lt;/a&gt;
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                <text>All Open Access; Gold Open Access</text>
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                <text>ISSN: 15462218</text>
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                <text>Devipriya A., Department of Computer Science and Engineering, KPR Institute of Engineering and Technology, Coimbatore, 641407, India; Prabu P., Department of Computer Science, CHRIST (Deemed to be University), Bangalore, 560029, India; Venkatachalam K., Department of Applied Cybernetics, Faculty of Science, University of Hradec Kralove, Hradec Kralove, 50003, Czech Republic; Ibrahim A.Z., Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, KSA.P.o.Box: 84428, Riyadh, 11671, Saudi Arabia</text>
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                <text>KESMR: A Knowledge Enrichment Semantic Model For Recommending Microblogs</text>
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                <text>Algorithm; Semantic Heterogeneity; Semantic Web; Statistical Techniques; Web 3.0</text>
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                <text>In today's world, there's an enormous amount of information available on the Internet. Because of this, it's become really important to come up with better and smarter ways to search for things online. The old-fashioned methods, like just matching certain words or using statistics, don't work so well anymore. They often suggest web pages that are irrelevant. As the Semantic Web keeps getting bigger, it needs algorithms for the best fit. In this paper, a way to measure how different the words used for web search. This helps in suggesting the most relevant web pages. A special algorithm that can change its settings. Our proposed method demonstrates 94% accuracy.   2023 IEEE.</text>
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                <text>Ranjan H.; Mishra S.; Al-Khasawneh M.A.; Singhal M.; Sharma V.; Alkhayyat A.</text>
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                <text>2023 10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and Computer Engineering, UPCON 2023, pp. 669-674.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>&lt;a href="https://doi.org/10.1109/UPCON59197.2023.10434773" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/UPCON59197.2023.10434773&lt;/a&gt;
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                <text>ISBN: 979-835038247-1</text>
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                <text>Ranjan H., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Mishra S., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Al-Khasawneh M.A., School of Computing, Skyline University College, University City Sharjah, Sharjah, 1797, United Arab Emirates; Singhal M., Kalinga Institute of Industrial Technology, Deemed to Be University, India; Sharma V., Department of Computational Sciences Christ (Deemed to Be University), Delhi, India; Alkhayyat A., College of Technical Engineering, The Islamic University, Najaf, Iraq</text>
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                <text>Key challenges in developing and executing higher education learners' learning outcomes</text>
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                <text>This chapter examines higher education institutions' complex obstacles in developing and implementing effective learning outcomes. It emphasizes the need for outcomes that include subject-specific and general skills, meet students' diverse requirements, align with market demands, and incorporate emerging technologies. To facilitate student success in the 21st century, institutions must address these. It examines multidisciplinary programs, technology integration, faculty training, and student participation in outcome formation. It proposes enhancing outcomes through emerging technologies, social and emotional learning, global citizenship education, and entrepreneurship education, emphasizing student-centred approaches. Effective learning outcomes are essential for fostering student success in a constantly changing environment. Case studies from India, the United Kingdom, and the United States provide insights, emphasizing India and lessons from the US and UK experiences.  2024, IGI Global. All rights reserved.</text>
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                <text>Increasing digital disruption is driving the necessity for Omni-Channel Retailing, compelling the integration of online and offline channels. The line between online and physical retailing is blurring as retailers intend to deliver a unified experience anytime anywhere, than a mere channel specific experience. As customer expectation for seamless experience intensifies, and retailers organizational, operational and technical barriers persist, it would be vital to formulate a suitable strategy towards e levating Omni-Channel Retail Experience. Though prior studies have observed the need for realigning the strategy around blended advantages of multiple channels, there is a limited understanding with regards to Omni-Channel Capabilities influencing customer experience elements. Besides, it is challenging to adopt all the capabilities within a competitive timeframe. Thus, the importance of prioritizing these capabilities remains fairly underexplored. This research aims to close this gap by ascertaining key Omni-Channel Dimensions and Capabilities influencing experiential aspects, pertaining to Apparel and Fashion retail, which is a leading category in India. The research first employs a qualitative study to corroborate the appropriateness of the Omni-Channel constructs identified from literature review, in the context of Indian retail market, followed by a quantitative study to validate their influence on Omni- Channel Retail Experience. The research determines key capabilities and dimensions from a retailers perspective that underpin key experience elements. The findings established new knowledge in terms of top priority capabilities towards Omni- Channel adoption, and accordingly designed a novel framework termed Capability Priority Framework as a plausible approach to elevate Omni-Channel Retail Experience. The framework is an original contribution of this research serving as an accelerator for retailers to build and reinforce key Omni-Channel capabilities. The research provides a novel perspective of extending The Dialectic Theory of retailing to a modern context such as Omni-Channel. It serves as a basis for organized retailers in India to realign their strategy towards Omni-Channel adoption, as they embark on this path. Finally, it adds to the knowledge base on Omni-Channel, providing a conceptual background towards strategic retailing and further research in this domain.</text>
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                <text>Increasing digital disruption is driving the necessity for Omni-Channel Retailing, compelling the integration of online and offline channels. The line between online and physical retailing is blurring as retailers intend to deliver a unified experience anytime anywhere, than a mere channel specific experience. As customer expectation for seamless experience intensifies, and retailers’ organizational, operational and technical barriers persist, it would be vital to formulate a suitable strategy towards elevating Omni-Channel Retail Experience. Though prior studies have observed the need for realigning the strategy around blended advantages of multiple channels, there is a limited understanding with regards to Omni-Channel Capabilities influencing customer experience elements. Besides, it is challenging to adopt all the capabilities within a competitive timeframe. Thus, the importance of prioritizing these capabilities remains fairly underexplored. This research aims to close this gap by ascertaining key Omni-Channel Dimensions and Capabilities influencing experiential aspects, pertaining to Apparel and Fashion retail, which is a leading category in India. The research first employs a qualitative study to corroborate the appropriateness of the Omni-Channel constructs identified from literature review, in the context of Indian retail market, followed by a quantitative study to validate their influence on Omni�Channel Retail Experience. The research determines key capabilities and dimensions from a retailers’ perspective that underpin key experience elements.</text>
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                <text>The present pandemic situation has led to the rise in the number of financially distressed companies in the Indian business ecosystem. Stakeholders, especially shareholders, unsecured and trade creditors who do not enjoy lien on company assets, should be extra cautious about the financial status of a company before making any investment or lending decision. The present study attempts to suggest the key indicators of corporate financial status after analysing 12 ratios from the financial statements of 162 sample companies for five financial years. The suggested key indicators can assist the shareholders and creditors in differentiating a financially distressed company from a financially sound company in the Indian industrial sector.  2021 SCMS Group of Educational Institutions. All rights reserved.</text>
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                <text>ISSN: 9733167</text>
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                <text>Shetty S.H., Department of Commerce, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India; Vincent T.N., Department of Commerce, CHRIST (Deemed to be University), Hosur Road, Bengaluru, 560029, India</text>
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                <text>In todays scenario, efficient data processing is a fundamental and vital issue for almost every scientific, academic, or business organization. To tackle this issue, organizations end up installing and managing database systems to satisfy different processing needs. In case of adopting a traditional solution, the organization needs to purchase the necessary hardware, deploy database products, establish network connectivity, and hire professional people who run the system. But this solution is getting impractical and expensive as the database systems and problems become larger and complicated (El-Khoury et al., 2009). Again, traditional solution entails different costs from the perspective of the investments involved. These concerns are handled efficiently to a great extent by the fast developing technology that goes by the name, cloud computing..  2014 by Taylor &amp;amp; Francis Group, LLC.</text>
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                <text>The highly mobile nature of VANET implies that the nodes involved are constantly disconnecting and reconnecting as they switch between access points or move out of the range of their access points. In such scenarios, seamless connectivity is essential, especially when emergency services are involved. Handoff is a process in wireless communication that takes care of the switching process that happens between access points whenever a mobile device moves from one point to another. In a dynamic scenario involving vehicular nodes, this switching needs to take place between a mobile node or a fixed access point (known as RSUs), as quickly as possible. To this end, this research work proposes a novel handoff method known as the Kho Kho Model - which is loosely based on the traditional Indian sport of the same name. The model groups together nodes that are moving in the same direction, thereby effectively reducing the amount of processing required to perform handoff for a set of nodes. The use of ANN have helped to improve handoff since it can help in making decisions quickly by making use of multiple parameters including signal strength, noise, direction, and others. To improve the efficiency of the proposed handoff model, RBFNN has been used in this research. The proposed model was implemented using NS-3 simulator. The results have shown that the proposed method has a slightly better improvement in the overall NRO, a reduced average delay and reduced jitter compared to the existing handoff method employed by the IEEE 802.11p standard.   2023 IEEE.</text>
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                <text>Kidney Abnormalities Detection and Classification Using CNN-based Feature Extraction</text>
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                <text>The presents of noises degrade the quality of ultrasound images and diminishes the disease diagnosis accuracy. Thus, an effective automatic stone and cyst detection system is beneficial to both the medical practitioners and patients. In this paper, an automatic detection and classification system for kidney stone and cyst image is proposed. The Gaussian filtering and Contrast Limited Adaptive Histogram Equalization (CLHE) techniques are applied to improve the quality of the images. In the next step, segmentation has been done based on the entropy of the image. The gamma correction technique has been applied to improve the overall brightness and an optimal global threshold value is selected to extract the region. The CNN model has attained much attention in medical image recognition and classification. In this paper, the pre-trained model ResNet-50 is utilized as a feature-extractor and Support Vector Machine as classifier to categorize the normal, cyst and stone images. The CNN model is analyzed with various other classification models such as k-nearest neighbor, decision tree and Nae Bayes. The results demonstrate that the ResNet-50 with supervised classification algorithm SVM is an optimal solution for analyzing kidney diseases.   2022 IEEE.</text>
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                <text>4th International Conference on Circuits, Control, Communication and Computing, I4C 2022, pp. 359-362.</text>
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                <text>Institute of Electrical and Electronics Engineers Inc.</text>
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                <text>ISBN: 979-835039747-5</text>
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                <text>George M., CHRIST UNIVERSITY, Dept. of Computer Science, Bengaluru, India; Anita H.B., CHRIST UNIVERSITY, Dept. of Computer Science, Bengaluru, India</text>
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                <text>This chapter seeks to examine the figurations and configurations of 'kingship' reflected in different Vedic literary narratives in general and particularly aims at foregrounding how 'kingship' that happens to be one of the oldest forms of political governance, originated in Vedic times and how it became multifaceted with the passage of time. This chapter particularly seeks to employ three epistemological lenses - govern(mentality), sacral (infra)structuralism and planetarity - to lay down how the Vedic notion of 'kingship' underwent 'intensive' changes and how it stood in conformity with varied dimensions of contemporary political ecology. Besides that, this chapter aims at bringing out how Vedic notion of 'kingship' embodies the limits of 'human' by means of performing a liaison between the Almighty and ordinary human beings. Finally, at the end, royal haecceities of Vedic 'kingship' are critically taken up to facilitate readers to grasp the ontological and onticological fluidity of Vedic understanding of 'kingship'.  2024 selection and editorial matter, Nizar Zouidi; individual chapters, the contributors.</text>
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                <text>Ghosal A., Department of English and Cultural Studies, Christ (Deem to be University), BGR Campus, Bengaluru, India</text>
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                <text>Kitchen Waste Derived Porous Nanocarbon Spheres for Metal Free Degradation of Azo Dyes: An Environmental Friendly, Cost Effective Method</text>
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                <text>Azo degradation; Metal free; Oxidant free; Porous nanocarbon spheres</text>
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                <text>A porous nanocarbon spheres (PNCSs) were prepared from kitchen waste and successfully used for the metal and oxidant free degradation of azo compounds. The PNCSs obtained by the pyrolysis of onion peel, at 1000C, were found to be effective catalysts for the reductive degradation of azo dyes in presence of hydrazine hydrate. The reductive cleavage of azo bonds (N=N) was achieved under microwave irradiation. The degradation process was completed in a span of 1040min; the process was monitored by ultravioletvisible spectroscopy. Fourier transform infrared spectroscopy was also used for the illustration of azo degradation. Interestingly, the reductive degradation of azo dyes produced corresponding amines and they were successfully reused for the preparation of fresh azo compounds. The work, therefore, highlights the valorization of largely produced kitchen-wastes to the sustainable PNCSs and it also provides a platform to demonstrate their applicability as highly cost-effective catalysts for bulk scale chemical transformations. Graphical Abstract: [Figure not available: see fulltext.].  2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</text>
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                <text>Supriya S.; Ananthnag G.S.; Maiyalagan T.; Hegde G.</text>
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                <text>Journal of Cluster Science, Vol-34, No. 1, pp. 243-254.</text>
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                <text>ISSN: 10407278</text>
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                <text>Supriya S., Centre for Nano-Materials &amp;amp; Displays, B.M.S. College of Engineering, Bull Temple Road, Karnataka, Bengaluru, 560 019, India, Department of Chemistry, B.M.S. College of Engineering, Bull Temple Road, Karnataka, Bengaluru, 560 019, India; Ananthnag G.S., Department of Chemistry, B.M.S. College of Engineering, Bull Temple Road, Karnataka, Bengaluru, 560 019, India; Maiyalagan T., Department of Chemistry, SRM Institute of Science and Technology, Kattankulathur, 603 203, India; Hegde G., Centre for Advanced Research and Development (CARD), CHRIST (Deemed to be University), Hosur Rd, Bengaluru, 560029, India, Department of Chemistry, CHRIST (Deemed to be University), Hosur Rd, Bengaluru, 560029, India</text>
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                <text>The emergence of Web 3.0 has left very few tag recommendation structures compliant with its complex structure. There is a critical need for newer novel methods with improved accuracy and reduced complexity for tag recommendation, which complies with the Web 3.0 standard. In this paper, we propose KMetaTagger, a knowledge-centric metadata-driven hybrid tag recommendation framework. We consider the CISI dataset as the input, from which we identify the most informative terms by applying the Term Frequency - Inverse Document Frequency (TF-IDF) model. Topic modeling is done by Latent Semantic Indexing (LSI). A heterogeneous information network is formalized. Apart from this, the Metadata generation quantifies the exponential aggregation of real-world knowledge and is classified using Gated recurrent units(GRU). The Color Harmony algorithm filters out the initial feasible solutions into optimal solutions. This advanced solution set is finalized into the tag space. These tags are recommended along with the document keywords. When the suggested KMetaTagger's performance is compared to that of baseline techniques and models, it is found to be far superior.  2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.</text>
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                <text>Ashvanth R.; Deepak G.; Sheeba Priyadarshini J.; Santhanavijayan A.</text>
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                <text>Lecture Notes in Networks and Systems, Vol-646 LNNS, pp. 1-11.</text>
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                <text>Subramanian D.V., Department of Computer Science, Christ University, Bengaluru, India; Chandra J., Department of Computer Science, Christ University, Karnataka, Bengaluru, India; Immanuel V.A., Department of Computer Science, Christ University, Bengaluru, India; Rohini V., Department of Computer Science, Christ University, Karnataka, Bengaluru, India</text>
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                <text>Knot(s) of the umbilical cord have received emphasis because the clinical assessments and sonographic literature show a crucial role in fetal outcomes. The true umbilical cord knot could be a knot in a singleton pregnancy or an entanglement of two umbilical cords in monoamniotic twins. Clinical manifestations are almost silent, which can raise clinical challenges. They worsen outcomes, and the pathology can be easily missed during prenatal visits because ultrasonographers do not pay attention to the cord during an obstetric ultrasound scan. However, most medical centers now have ultrasound machines that improve fetal assessment. The umbilical cord should be routinely evaluated during a fetal assessment, and suspicion of an umbilical cord knot can be more frequently diagnosed and is detected only incidentally. Clinical outcome is usually good but depends on the knot's characteristics and if it is tight or loose. In this review, we discuss pathophysiology, the theories on formation, the main risk factors, ultrasound signs and findings, different opinions in the management, and features of pregnancy outcomes feature.  2024 International Federation of Gynecology and Obstetrics.</text>
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                <text>AlQasem M., Centre of Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy, Department of Obstetrics and Gynecology, Faculty of Medicine, Mutah University, Al-Karak, Jordan; Meyyazhagan A., Centre of Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy, Department of Life Sciences, CHRIST (Deemed to be University), Karnataka, Bengaluru, India, PREIS International School, Firenze, Italy; Tsibizova V., PREIS International School, Firenze, Italy, CEMER, European Centre for Medical Research, Perugia, Italy; Clerici G., Centre of Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy, CEMER, European Centre for Medical Research, Perugia, Italy; Arduini M., Centre of Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy; Khader M., Department of Obstetrics and Gynecology, Faculty of Medicine, Mutah University, Al-Karak, Jordan; M.Alkarabsheh A., Department of Obstetrics and Gynecology, Faculty of Medicine, Mutah University, Al-Karak, Jordan; DiRenzo G.C., Centre of Perinatal and Reproductive Medicine, University of Perugia, Perugia, Italy, PREIS International School, Firenze, Italy, Department of Obstetrics, Gynecology and Perinatology, IE Sechenov First State University, Moscow, Russian Federation</text>
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                <text>Wagh, Rupali Singh</text>
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                <text>Studies have examined the understanding of human gaze in animals. Gaze following in human infants has been successfully demonstrated, showing that infants can follow the eye direction of another though the ability to represent the intentions of gaze behaviour emerges only after the onset of object permanence or a period over eighteen months of age. Comparative studies indicate that gaze following or gazing at humans vary in different species of animals. Wolves for example were observed to look least at human experimenters during a performance task, whereas dogs turned to look more often and monkeys looked to a lesser extent at their experimenters. It is of interest to discuss that gaze following is different from understanding gaze. Dogs have been observed to be successful in gaze following and almost at par with young children. However, the intention of another's gaze is not as clearly understood by dogs as in humans. We (Ittyerah and Gaunet 2009) have shown that the response of dogs to the gaze of their caretakers did not differ between guide dogs of the blind and pet dogs of sighted people. Both groups of dogs seemed to have responded to the head direction of their caretakers during a search task, indicating that the visual status of the caretaker did not affect the dog's understanding of human gaze. Further some breeds of dogs may respond more often to gaze, while larger inter ocular distances in large dogs could facilitate their response to visual cues. Therefore awareness of interactions between breed and physical size could contribute to studying gaze and cognition among dogs.  2012 Nova Science Publishers, Inc.</text>
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                <text>Ittyerah M.</text>
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                <text>Dogs: Biology, Behavior and Health Disorders, pp. 179-187.</text>
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                <text>ISBN: 978-162081546-5; 978-161209653-7</text>
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