ABSTRACT
The study proposes a novel deep learning-based model for early and accurate detection of the Tomato Flu virus, also known as tomato fever, which has recently emerged in children under the age of five in the Indian state of Kerala. The model utilizes a deep learning method to classify skin pictures and check whether a person is suffering from the virus or not, with an accuracy of 100% and a validation loss of 0.2463. Additionally, an API is developed for easy integration into various web/app frameworks. The authors highlight the importance of careful management of rare viral diseases, especially in the context of the ongoing COVID-19 pandemic. © 2023 Bharati Vidyapeeth, New Delhi.
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As tourism research focuses on experience, memorable tourism experience (MTE) is gaining importance among academia and destination managers. However, only limited studies have examined the antecedents and consequences of MTE. Therefore, this study will investigate human emotions with their underlying factors in influencing MTE to cater to revisit intention in tourists. For this study, CFA-SEM is applied to a sample of 1120 tourists from central India to access the empirical relationships. The empirically validated model confirmed the significant relationships among human emotions, MTE, and revisit intention. Results suggested that human emotions significantly influence MTE, which is reflected as revisit intention in tourists. Findings also confirmed the moderating role of the perceived risk of COVID-19 further, exploring the health-linked effects on tourism. This study will help the researchers and destination managers make more informed decisions and strategies to make tourism destinations more sustainable by incorporating human emotions as a significant factor in influencing the tourism experience. The findings will also help destination managers in making tourism more risk-averse.
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Due to the fast advancement of Internet technology, the popularity of Online Social Networks (OSN) over the Internet is increasing day by day. In the modern world, people are using OSN to communicate with others around the world who may or may not know each other. OSN has become the most convenient means to transmit media (news/content) and gather or spread information in the world. The posts (contents) on OSN affect and impact people, and minds at least for some time. These contents are important because they play a crucial role in taking the decision. The posts which are available on the OSN may be information or just misinformation. The misinformation may be a type of fake news or rumour. This is very difficult for people to differentiate whether the posts are information or rumour. Therefore, the development of techniques that can prevent the transmission of false information or rumours that might harm society in any way is critical. In this paper, a model is developed based on the epidemic approach, for examining and controlling fake information dissemination in OSN. The proposed model illustrates how different misinformation debunking measures impact and how misinformation spreads among different groups. In this article, we explain that the proposed model will be able to recognize and eradicate fake news from OSN. The model is written as a system of differential equations. Its equilibrium and stability are also carefully examined. The basic reproduction number $(R_{0})$ is calculated, which is an important parameter in the study of message propagation in OSN. If $R_{0} < 1$ , the propagation of rumor in the OSN will be minimal;nevertheless, if $R_{0} > 1$ , the fake information/rumor will continue in OSN. The effects of disinformation of rumours in OSN in the real world are explored. In addition, the model covers the fake information/rumour dissemination control mechanism. The comparative study shows that the proposed model provides a better mechanism to prevent the dissemination of fake information in OSN in comparison to other previous models Extensive theoretical study and computation analysis have also been used to validate the proposed model © 2013 IEEE.
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Krishikosh, a digital repository, is a collection of online resources. It is a large collection of Indian resources in agriculture and allied sectors which is both institutional and discipline wise of Indian National Agricultural Research and Education System (NARES). A large collection of thesis, old and valuable books, institutional publications, technical bulletins, project reports, lectures, preprints, reprints, records, etc. is available in Krishikosh (https://krishikosh.egranth. ac.in/) . The repository has been designed using open source software with efficient Integrated Content Management System (ICMS), configured to meet the user requirements of a reliable digital repository. It is a customized digital repository platform where users can upload and manage their content in compliance with the open access policy of the Indian Council of Agricultural Research. This is a unique platform for sharing the intellectual outputs of the agricultural fraternity hosted by the ICAR-Indian Agricultural Research Institute, (IARI), New Delhi. At present over 2,01,000 items are available on the krishikosh platform which includes students research work (>150,000 theses), old and valuable documents since 1948 in all major subjects of Agricultural and allied disciplines. The Krishikosh analytics shows over 1,87,23,710 hits on the website from 175 countries since 2017. The top ten countries visiting this digital platform were India, United States ofAmerica, Sudan, China, Russia, Ethiopia, Iran, Philippines, Nigeria and Indonesia. Google analytics, during the COVID 19 lockdown period (April-May 2020) indicates a monthly average hit of 6,93,295 indicating higher users on the Krishikosh repository during this time.
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SARS-CoV-2 is a public pandemic health concern globally. Nasopharyngeal and oropharyngeal swab samples are used for Covid-19 viral detection. Sample collection procedure was tedious and uncomfortable and unsuitable for biochemical and CBC analysis in swab samples. Biochemistry and CBC tests are key determinant in management of Covid-19 patients. We developed a LAMP test to detect viral RNA in blood samples. LAMP is required four specific primers targeting the internal transcribed S-region and loop primers for viral RNA amplification. RNA was extracted from blood samples by TRIzol method. LAMP reaction was performed at 60⯰C for 1 hour and amplicons were visualized in HNB dye. No cross-reactivity was seen with HBV, HCV, and HIV infected sample. Out of 40 blood samples, 33 samples were positive for LAMP and Q-PCR analysis, one sample was positive for LAMP and negative for Q-PCR, two samples were negative for LAMP but positive for Q-PCR, and four blood samples were negative for LAMP and Q-PCR. LAMP method has an accuracy of 92.50%, with sensitivity and specificity of 94.28% and 80%, respectively. Thus, LAMP diagnostic test has proved reliable, fast, inexpensive and can be useful for detection where the limited resources available.â¢LAMP method is a potential tool for detection of SARS-CoV-2.â¢Blood samples are the key determinant for routine diagnostics as well as molecular diagnostics.â¢LAMP assay is an appropriate diagnostics method which offers greater simplicity, low cost, sensitivity, and specificity than other methods in molecular diagnostics.
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For densely populated developing countries, such as India, where due to a lack of general and public awareness, limited data collection and compilation facilities, and inherent limitations of the available diagnostic test, accurate modeling of the pandemic is more challenging. Thus, a realistic model for predictions is required in order to formulate more effective strategic policies to control the COVID-19 pandemic using limited available resources. In this article, we propose a time-varying epidemiological model with two classes of compartments, reported and unreported, and consider influential latent factors, for example, undetectable infections, the false-negative rate of testing, testing hesitancy, vaccination efficacy, dual contact dynamics, and the possibility of reinfection in recovered as well as vaccinated individuals. For simulation purposes, we consider the COVID-19 data of India from March 13, 2020, to January 20, 2022. Furthermore, we provide a sensitivity analysis of various latent factors and predictions for the third wave in India. Simulated results suggest that India is able to control COVID-19 for the first time after the second wave, as observed from the trajectory of effective reproduction number. Moreover, for unseen or coming variants of virus for which vaccine efficacy is low, the available vaccine requires a high vaccination rate to control future waves.
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COVID-19 pandemic can be considered as an economic and health crisis of uncertain magnitude and duration. Frequent lockdowns, salary cuts, and losses of jobs and lives have spurred changes in human behaviour. Today customers are experiencing a transformation in their perceptions towards a life insurance product. The common attitude to treat life insurance as an optional investment instrument has been shifted towards a mandatory risk protection instrument. Thus the demand for a life insurance product is increasing by leaps and bounds and undoubtedly competition among insurance providers at the same time. This article seeks to examine the features that should form part of a life insurance product to attract customers in Indiaduring the COVID-19 pandemic. Data for the study were collected for 159 respondents from October 2020 to December 2020 from Delhi and NCR region. The data were analyzed using Principal Component Analysisafter walking through a maze of articles relating to normal times and crisis times. There is testable evidence to show a paradigm shift in the outlook of customers regarding a life insurance product. Thus, the article also paves the path for future research in the direction of customers behaviour for a life insurance product.
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Artificial Intelligence (AI) is refers to an innovative technique which generally deals with the machines. AI re use do decrease or minimize the errors and defects in any field. It is a widely separated technique which is used in many fields and especially in pharama sector it is growing day by day to set the new goals and achieved the new and difficult tasks. AI is also used in the detection, diagnosis, prevention and treatment of covid-19. In the crises of covid- 19 or pandemic of covid the AI technology is used as a very potent and powerful weapon. The AI technology needs some work & time to make and innovative and bright future in health care sector. This article provides a brief overview about the technique of AI it's applications, use of AI technique as a potent weapon in covid pandemic problems associated with AI and last but not the least feature of AI in healthcare. © 2022 University of Stockholm. All rights reserved.
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Electronic Commerce is the process of doing business through computer networks. He/she sitting on the chair in front of a computer can access all the facilities of the Internet to sell or buy the products. Unlike traditional commerce that is carried out physically with an effort of a person to go & get products, e-commerce has made it easier for a human to reduce physical work and to save time. This was started in the early 1990s and it had taken a great effect in the world of computers. the growth of e-commerce is security. E-commerce is facing many challenges & still there is a lot of security for this. The main advantage of e-commerce over traditional commerce is the user can browse online shops, compare prices, and order merchandise sitting at home on their PC. For increasing the use of e-commerce in developing countries the Business to Business ecommerce is implemented for improving access to global markets for firms in developing countries. For a developing country, advancement in the field of ecommerce is essential. The research strategy shows the importance of e-commerce in developing countries for business applications. © 2022 University of Stockholm. All rights reserved.
ABSTRACT
Krishikosh, a digital repository, is a collection of online resources. It is a large collection of Indian resources in agriculture and allied sectors which is both institutional and discipline wise of Indian National Agricultural Research and Education System (NARES). A large collection of thesis, old and valuable books, institutional publications, technical bulletins, project reports, lectures, preprints, reprints, records, etc. is available in Krishikosh (https://krishikosh.egranth. ac.in/). The repository has been designed using open source software with efficient Integrated Content Management System (ICMS), configured to meet the user requirements of a reliable digital repository. It is a customized digital repository platform where users can upload and manage their content in compliance with the open access policy of the Indian Council of Agricultural Research. This is a unique platform for sharing the intellectual outputs of the agricultural fraternity hosted by the ICAR-Indian Agricultural Research Institute, (IARI), New Delhi. At present over 2,01,000 items are available on the krishikosh platform which includes students research work (>150,000 theses), old and valuable documents since 1948 in all major subjects of Agricultural and allied disciplines. The Krishikosh analytics shows over 1,87,23,710 hits on the website from 175 countries since 2017. The top ten countries visiting this digital platform were India, United States of America, Sudan, China, Russia, Ethiopia, Iran, Philippines, Nigeria and Indonesia. Google analytics, during the COVID 19 lockdown period (April-May 2020) indicates a monthly average hit of 6,93,295 indicating higher users on the Krishikosh repository during this time.
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Purpose Drawing upon the conservation of resource (COR) theory, the purpose of this paper is to explore the mediating role of knowledge hiding in the relationship between job insecurity and two dimensions of thriving at work, i.e. learning and vitality. The study further aims to investigate the moderating role of benevolent leadership in the aforementioned mediating relationship by applying the moderated mediation framework. Design/methodology/approach The sample for the study consisted of employees working in service sector in India. The hypotheses were tested with two wave survey data collected from 365 employees during the COVID-19 pandemic when the Indian Government was lifting phase wise restrictions. Data was analyzed using mediation and moderated mediation analyses on PROCESS v 3.0 macro. Findings Results showed that knowledge hiding mediated the relationship between job insecurity and both dimensions of thriving at work. Further, benevolent leadership was seen to moderate the mediated relationship providing support for the moderated mediation framework. Practical implications The results highlight the significance of providing benevolent leadership training to the managers to help them cope with the anxiety arising out of job insecurity. Further, employees need to be cautioned regarding the deleterious effects of knowledge hiding, which can impede their own learning and vitality. Originality/value To the best of the authors' knowledge, this is the first study to investigate the mediating role of knowledge hiding in the relationship between job insecurity and thriving. Further, the role played by benevolent leadership in mitigating the harmful effects of job insecurity especially during COVID-19 pandemic is a unique contribution of the study.
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From the past year, Online Examination has become popular in all the educational fields due to covid19 and its flexibility. However, the institutions and community confront a big difficulty in terms of proctoring methods, as it is extremely difficult to administer cheating-free online exams. Here we present techniques and tools through which the proctor need not to be present throughout the exam. This is based on neural networks and machine learning. Our AI-based model will be able to detect any unfair means in an examination. Our experiments proved that the proposed system is better than the existing ones. © 2021 IEEE.
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Humanity is going through never seen before health crisis due to the outbreak of novel coronavirus or Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). There are 24.02 million cases and 0.82 million deaths worldwide as of 26th August 2020 due to deadly infection of COVID-19. The disease has been spreading exponentially (R-naught number: 3) and has challenged even the best healthcare infrastructure in the world. With the progression of the disease, the countries shifted the focus from cure to diagnosis and containment to flatten the curve. The review shows that the disease is spreading exponentially while the resources are still limited. We focus upon the probable vectors of the virus, different diagnostic methods with advantages & limitations, and the way forward. This review article covers the different diagnostic methods with more advantages, limitations, and the future sneak-peek into the forthcoming developments for the diagnostic processes such as RT-PCR (Reverse Transcription Polymerase chain reaction).
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Stress and anxiety have been implicated as contributors to many chronic diseases and to decreased quality of life, even with pharmacologic treatment. Efforts are underway to find non-pharmacologic therapies to relieve stress and anxiety, and yoga is one option for which results are promising. The focus of this review is on the results of human trials assessing the role of yoga in improving the signs and symptoms of stress and anxiety. A significant decrease in stress and/or anxiety symptoms when a yoga regimen was implemented;however, many of the studies were also hindered by limitations, such as small study populations, lack of randomization, and lack of a control group. Biochemical and physiological markers of stress and anxiety, but yielded inconsistent support of yoga for relief of stress and anxiety. Evaluation of the current primary literature is suggestive of benefits of yoga in relieving stress and anxiety, but further investigation into this relationship using large, well-defined populations, adequate controls, randomization and long duration should be explored before recommending yoga as a treatment option.
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Purpose: The purpose for writing this article is derived from the misery and chaos prevalent in the world due to the coronavirus pandemic – since late 2019 and still continuing as of December 2020. Design/methodology/approach: A blockchain-based solution to verify the country visit trail and disease and treatment history of the passengers who arrive at the immigration counters located at various national borders and entry points is proposed. A fuzzy inference based suspect identifier system is also presented in this article that could be utilized to make further decisions based on the degree of suspicion observed on a particular passenger. Findings: This paper attempted to put forth a blockchain-based system which consumes the healthcare and visit trail summary of a passenger (appearing for an interview before an immigration officer) and forwards it to a fuzzy inference system to reach to a conclusion that the passenger should be advised to self-quarantine, detained, or should be allowed to enter. Such a system would help to make correct decisions at the immigration counters to check pandemic diseases, like COVID-19, right at the entry points. Research limitations/implications: The implications of this work are manifold. First, the proposed framework works independent of the type of pandemic and is a readymade tool to check the spread of disease through infected human carriers. Second, the proposed framework will keep the mortality rates under check, which would give ample time for the authorities to save the lives of the people with co-morbidities and age vulnerabilities (Vichitvanichphong et al., 2018). Third, it is a general phenomenon to restrict the flights from the country where the first few cases of infection are discovered;however, the infected person, at the same time, might travel through alternative routes. The blockchain-enabled proposed framework ensures the detection of such cases at no other cost. Finally, the solution may appear costly in the first place, but it has the potential to hold back the revenue of the countries that would otherwise be spent on reactive measures. Originality/value: As of now no other study or research article provides the solution to the biggest problem persists in the world in this way. The contribution is original and worth applying. © 2021, Emerald Publishing Limited.
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This paper presents results from a rapid-response industry-academia collaboration for virtual screening of chemical, natural and virtual drug ligands towards identifying potential therapeutics for COVID-19. Compared to resource-intensive traditional approaches of either conducting high- throughput screening in a lab or in-silico molecular dynamics simulations on supercomputers, we have developed an open- source framework that leverages artificial intelligence (AI) to accurately and quickly predict the binding potential of a drug ligand with a target protein. We have trained a novel molecular-highway graph neural network architecture using the entirety of the BindingDB database to predict the probability of a drug ligand binding to a protein target. Our approach achieves a prodigious 98.3% accuracy with its predictions. Through this paper, we disseminate our source code and use the AI model to screen both public (ChEMBL, DrugBank) and proprietary databases. Compared to other AI-based methods, our approach outperforms the state-of-the-art on the following metrics - (i) number of molecules currently undergoing active clinical trials, (ii) number of antiviral drugs correctly identified, (iii) accuracy despite not needing active-site priors, and (iv) ability to screen more compounds in unit time. © 2020 IEEE.
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Introduction: Distributed computing is a field of computer science which deals with the study of distributed systems A system which has communication and coordination with each of its nodes and which interacts with each other to achieve a common target which is to effectively compute the computation. These capabilities are conducive to implementing a systematic and efficient COVID-19 tracking application which can be accessed and worked on by numerous entities. Objective: To provide information about a client-server architecture which is a platform for managing and maintaining container-ized workloads and services that forms a base for automation. Methods: A Kubernetes cluster IS created with a calico pod network along with the main drivers of Kubelet, Kubeadm and Kubectl. Secure Shell (SSH) protocol is used for secured shell and data management and authentication between the client and server. Results: We have performed and distributed our tasks in such a way to show the developers that multiple tasks can be performed at the same time using Kubernetes orchestration platform and used to parallelize multiple tasks. This increases the efficiency of the machine and the performance of the system becomes much faster. Conclusion: A system which has communication and coordination with each of its nodes and which interacts with each other to achieve a common target which is to effectively compute the computation. One such application which helps in the distribution of tasks and helps do the computation is Kubernetes. It is based on a client-server architecture which is a platform for managing and maintaining containerized workloads and services that forms a base for automation. © IJCRR.
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Aim/Background: Dietary factors have shown important role in the rapid management of several human ailments including viral infections. Since ancient times, constituents of Nigella sativa seeds have been utilized as food preservatives with significant medicinal benefits in Unani and Ayurveda practices. Nigella sativa (Black seed) has presented significant therapeutic potential against several disorders and known to have numerous biological activities (such as antibacterial, antiviral and anti-inflammatory). Nigella plant has shown significant potential in the reduction of viral load as well as in enhancing immunity. Materials and Methods: Our study enlightens the inhibitory role of phytocompounds of Nigella sativa against various key targets of coronavirus through in silico approaches including molecular docking using several software’s such as AUTO DOCK 4.2 and PATCH DOCK. Results: Thus in this study, we have elucidated the potential of best reported phytocompounds of Nigella sativa as potent inhibitors of COVID-19. We have mainly focused our study towards inhibiting four different targets in CoVs. Molecular docking was performed between 10 potent compounds to identify best potential inhibitor which could inhibit the viral attachment and replication. Nigellone have shown the most significant inhibitory potential (with Binding energy of-5.48) against all the four crucial targets of coronavirus. Conclusion: Further, in vitro experiments are needed to validate the efficacy of Nigellone as a potential lead compound for the management of COVID-19 disease. © 2021, Association of Pharmaceutical Teachers of India. All rights reserved.
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A novel threat to mankind by novel coronavirus infection occurred in December 2019. According to the World Health Organization (WHO) Situation Report-141, 7,039,918 confirmed cases and 404,396 death cases were observed till 9 June 2020 in the different regions of world. Therefore, this article aims to summarize and share the update on the present status of the outbreak and possible treatment options. The present review focuses on latest statistics, diagnostic and preventive measures under study and the future planning of the researchers to discover an effective cure for this threat to the mankind. For carrying out this review, literature searches were performed on Clinicaltrials.gov, official website of WHO,Centers for Disease Control and Prevention, PubMed, Google scholars, etc. Data from these searches was collected and evaluated for getting the available literature on COVID-19 outbreak and drugs under study. The details of history, virology, epidemiology, possible therapeutic options, associated risk factors and preventive measures related to COVID-19 are compiled here in this review. Along with this, some ongoing clinical trials have also been included in this review in order to conclude the efforts of researchers towards controlling this outbreak. The trajectory and severity of this outbreak can't be predicted at present, but immediate actions are required to be taken in order to develop and implement an effective treatment against the global threat. © 2020 This is an Open Access article licensed under a Creative Commons license: Attribution 4.0 International (CC-BY). Published by Oriental Scientific Publishing Company.
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Introduction: A novel threat to mankind occurred in December 2019 which was an outbreak of infection caused by a novel coronavirus (SARS-CoV-2 or 2019-nCoV). The infection was first developed in Wuhan, China, and has affected more than 200 countries around the world till now. Objective: The present study aims to assess the knowledge related to coronavirus disease (COVID-19), risk perception and preventive behaviours among the Pharmacy students in a part of India approximately 3 months after the onset of this outbreak in India. Methods: This survey was conducted from 2nd to 5th of September 2020 with Indian Pharmacy students (1st to 4th year). The knowledge, self-reported preventive behaviours and risk perceptions of COVID-19 were assessed using an online questionnaire. A total of 21 questions were there in the questionnaire in which 14 questions were about knowledge related to COVID-19, 4 items regarding preventive behaviours and 3 about risk perception. Results: A total of 268 participants completed the questionnaire. The participants were under the age group of 15-30 years. A high level of disease-related knowledge was found in the participants (77.66%). On an average 96.1% of participants were practising preventive behaviours. The aggregate score of items in risk perception section was found to be in the moderate range i.e., 5.38 out of 8. A significant negative correlation was obtained between risk perception and preventive behaviours. Conclusion: The trajectory and severity of this outbreak are very high, therefore, effective treatment against this global threat is required to be developed as early as possible. In the present study, a high level of disease-related knowledge and preventive behaviours were observed among the participants with a moderate level of risk perception. © IJCRR.