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This article has been withdrawn: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal).This article has been withdrawn as part of the withdrawal of the Proceedings of the International Conference on Emerging Trends in Materials Science, Technology and Engineering (ICMSTE2K21). Subsequent to acceptance of these Proceedings papers by the responsible Guest Editors, Dr S. Sakthivel, Dr S. Karthikeyan and Dr I. A. Palani, several serious concerns arose regarding the integrity and veracity of the conference organisation and peer-review process. After a thorough investigation, the peer-review process was confirmed to fall beneath the high standards expected by Materials Today: Proceedings.The veracity of the conference also remains subject to serious doubt and therefore the entire Proceedings has been withdrawn in order to correct the scholarly record.
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The COVID-19 outbreak resulted in multiple waves of infections that have been associated with different SARS-CoV-2 variants. Studies have reported differential impact of the variants on respiratory health of patients. We explore whether acoustic signals, collected from COVID-19 subjects, show computationally distinguishable acoustic patterns suggesting a possibility to predict the underlying virus variant. We analyze the Coswara dataset which is collected from three subject pools, namely, i) healthy, ii) COVID-19 subjects recorded during the delta variant dominant period, and iii) data from COVID-19 subjects recorded during the omicron surge. Our findings suggest that multiple sound categories, such as cough, breathing, and speech, indicate significant acoustic feature differences when comparing COVID-19 subjects with omicron and delta variants. The classification areas-under-the-curve are significantly above chance for differentiating subjects infected by omicron from those infected by delta. Using a score fusion from multiple sound categories, we obtained an area-under-the-curve of 89% and 52.4% sensitivity at 95% specificity. Additionally, a hierarchical three class approach was used to classify the acoustic data into healthy and COVID-19 positive, and further COVID-19 subjects into delta and omicron variants providing high level of 3-class classification accuracy. These results suggest new ways for designing sound based COVID-19 diagnosis approaches. Copyright © 2022 ISCA.
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The COVID-19 pandemic has accelerated research on design of alternative, quick and effective COVID-19 diagnosis approaches. In this paper, we describe the Coswara tool, a website application designed to enable COVID-19 detection by analysing respiratory sound samples and health symptoms. A user using this service can log into a website using any device connected to the internet, provide there current health symptom information and record few sound sampled corresponding to breathing, cough, and speech. Within a minute of analysis of this information on a cloud server the website tool will output a COVID-19 probability score to the user. As the COVID-19 pandemic continues to demand massive and scalable population level testing, we hypothesize that the proposed tool provides a potential solution towards this. Copyright © 2022 ISCA.
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Introduction: Patients with pre-existing comorbidities and immunosuppression due to lymphoma and its treatments, are at greater risk for SARS-CoV-2 infection and severe manifestation of COVID-19. Patients treated with anti CD 20 monoclonal antibody such as rituximab for non-Hodgkin-lymphoma, which induces rapid B cell depletion and possibly impacting the clinical course of COVID- 19 in terms of prolonged hospital stay and higher mortality. Case report: Here, we describe a case series of three male patients already COVID RTPCR positive admitted at our institute aged >60 years, all treated with rituximab for non-Hodgkin-lymphoma. All patients had increased inflammatory markers, bilateral ground-glass opacities on chest CT and required intensive care in view of progressive hypoxemia and respiratory distress, treated with broad-spectrum antibiotics, antifungals, corticosteroids, anticoagulants, injection remdesivir, Tab barcitinib, and other supportive treatment. One patient also received IVIG. Initially, all patients required high oxygen support followed by non-invasive ventilation and finally invasive mechanical ventilatory support in view of increased ventilatory need with Fio2 100%. Despite best intensive care, all patients showed progressive deterioration with refractory hypoxemia and refractory hypotension and succumbed. Discussion: All three patients had prolonged COVID RT PCR positive varies from one month to maximum 5 months and showed mortality. High in-hospital mortality related to severe COVID-19 among patients with lymphoma has been reported in several countries. The risk of early death for patients with severe COVID-19 and lymphoma increases with age and relapsed lymphoma disease. Lack of an efficient antibody production caused by B cell depletion might explain the protracted course, moderate symptoms as lack of antibody producing B cell may have prevented activation of the complement system. Conclusion: The incidence, risk factors, and outcome of prolonged forms of COVID-19 for patients with lymphoma are still poorly assessed. Relapsed/refractory lymphoma and recent administration of anti CD20 therapy are risk factors for prolonged in-hospital stay and death for lymphoma patients hospitalized for COVID-19. These findings may contribute to guide the management of lymphoma during the pandemic.
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Here, the use of CNN-based technologies is provided with a new method for the detection of fraud during e-exams. This technology will assist providers in identifying any unknown situation during online tests, which are recommended by the majority of governments worldwide owing to the Covid-19 pandemic. Most colleges and students worldwide are severely impacted by their academic programmers, and the universities' role of testing using conventional approaches is a challenge. Thus, the students undergo several of their classes from various kinds of online third-party apps. The universities cannot, however, rely on these service providers for a long time to perform online examinations. Therefore, this work provides a full set-up of computing applications for students who can use them on their own laptops/personal computers with strict university guidance. © 2021
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The Second Diagnosis of COVID-19 using Acoustics (DiCOVA) Challenge aimed at accelerating the research in acoustics based detection of COVID-19, a topic at the intersection of acoustics, signal processing, machine learning, and healthcare. This paper presents the details of the challenge, which was an open call for researchers to analyze a dataset of audio recordings consisting of breathing, cough and speech signals. This data was collected from individuals with and without COVID-19 infection, and the task in the challenge was a two-class classification. The development set audio recordings were collected from 965 (172 COVID-19 positive) individuals, while the evaluation set contained data from 471 individuals (71 COVID-19 positive). The challenge featured four tracks, one associated with each sound category of cough, speech and breathing, and a fourth fusion track. A baseline system was also released to benchmark the participants. In this paper, we present an overview of the challenge, the rationale for the data collection and the baseline system. Further, a performance analysis for the systems submitted by the 21 participating teams in the leaderboard is also presented. © 2022 IEEE
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Purpose: This study aims to identify how ICT appeared as an emergent business strategy and to investigate the impact of ICT adoption factors on the perceived benefits of micro, small and medium enterprises (MSMEs). Design/methodology/approach: A total of 393 responses from Indian small and mid-size enterprises (SMEs) were collected for the final analysis. The study presents the partial least-squares structural equation modeling with the Chi-square test and descriptive analysis as a methodology based on numerous independent variables and one dependent variable. Findings: The findings indicate that ICT adoption during and following the COVID-19 pandemic is constant in nature of the enterprise. Moreover, the results indicate that different adoption of ICT factors influence on perceived benefits of organizational performance of Indian MSMEs that lent good support except for the regulatory framework. Research limitations/implications: The implications of the current research help Indian MSMEs to take investment decisions in various technologies that help the organization. Furthermore, managers and practitioners help the organization in deciding which technology adoption factors are more critical to the betterment of the organization. Originality/value: The study found certain ICT adoption factors that have a significant role in organizational performance in Indian MSMEs. Moreover, during COVID-19, investigate ICTs' role as a business strategy. © 2022, Emerald Publishing Limited.
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The heterogeneous and complex nature of cancer is extensively revealed at molecular, genetic, and tissue microenvironment levels. Currently, co-occurrence of coronavirus disease 2019 (COVID-19) to lung cancer patients and severity of infections by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been understood at preclinical and clinical levels. However, molecular and cellular insights are not discussed in those papers that support the increased COVID-19 severity and comorbidities in several cancer types, including lung cancer patients. Therefore, this perspective highlights the basis of high severity and comorbidities among lung cancer patients infected by COVID-19 with an emphasis on translational aspects.
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The necessity of rapid and appropriate diagnosis is emphasized by the COVID 19 as a serious danger to world health. The interchange of patient data across health centers addresses the growth of the number of patients and minimizes needless trials. The sharing of medical information helps patient care to accelerate;thus the sharing of health data is a need nowadays. Due to the sharing of information online among healthcare professionals, safety remains a key concern. In a diagnostic method during the COVID-19 pandemic, computer tomography (CT) and X-ray photos play an essential role in the transmission of information to organizations. Steganography techniques of encryption and imaging can be used in order to secure transmission of COVID-19 pictures. This work proposes a novel encryption for COVID-19 diagnostic using the image steganography (EIS-SDT) paradigm for safe data transfer. For the breakdown of images, a discrete multiple-level transformer for EIS-SDT employs the technique for optimizing the pixel selection for MANTA RY Foraging. For secrete image encryption, the EIS-SDT approach employs a dual logistic chaotic map. Additional security for the steganography process is ensured by the implementation of the DLCM-based encryption mechanism. The EIS-SDT model is efficiently performed by thorough simulation results analysis, and the results are analyzed using many assessment parameters. The analysis showed that the EIS-SDT model exceeds existing technology considerably. © 2021 IEEE.
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The entire human life is passing through a very bad and unprecedented phase of the pandemic called COVID-19. It is a chronic disease that occurs because of "severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)". The entire world has witnessed a very bad phase of life which has never happened before on this massive scale. COVID-19 has made the entire human life challenging. Millions of people got affected around the globe and many lost their loving ones while fighting with the deadly disease. The two critical challenges of the pandemic are: there are no known treatments for COVID-19 and secondly, its transmission from one person to another is very prompt. Therefore, to control the deadly spread of the pandemic the countries have adopted complete lockdown for months, people were isolated and quarantined to control the spread of the disease. Several terminologies such as lockdown, quarantine, social-distancing, home isolation, and Corona waves can be heard around. In all these necessary measures to control the virus taken by the government the entire humankind suffered and still suffering from several challenges towards living a normal life. In this entire disaster, information communication technologies (ICTs) have shown a significant contribution in mitigating the effects and challenges caused due to COVID-19. In the present study, efforts have been given on highlighting the role of ICT in overcoming the challenges of life caused due to COVID-19 with the help of studies that took place in the pandemic duration. The study has also shown that how the extensive inclination of the people towards the use of ICTs helped in emerging new business opportunities. The present study is a conceptual study that will help in leading to another study. A research model has been proposed in the study which can be further tested in upcoming studies. The outcomes of the study can be helpful for the decision and policymakers especially those who are working in the area of ICT. The ICT industry can learn many things that can help focus more on the expansion of business opportunities.
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The world is in great chaotic condition due to the outbreak of COVID-19 caused by a novel coronavirus. People are facing havoc in every corner of the world. As it is an actual novel virus, people search everywhere on the internet and other platforms to know much about this lethal virus. This paper examines various aspects of informationseeking behavior and pattern among ordinary people in India through online mode. The data were collected from August to November 2020. This paper also seeks to identify different areas of information need among common people and their problems while searching for desired information. The primary objectives of the paper include examining the users’ activeness towards social media usage, identifying the most preferred information sources by users, and investigating different purposes for seeking information related to COVID-19 by users. © 2021, Library Philosophy and Practice. All Rights Reserved.
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It is well known that angiotensin-converting enzyme 2 (ACE2) is an important host factor responsible for the attachment of severe acute respiratory syndrome coronavirus clad 2 (SARS-CoV-2). ACE2 has been predominantly reported to be present in lungs and nasal mucosa, which is the most common site for the initiation of COVID-19.<sup>1</sup> Apart from lungs, ACE2 is also expressed in heart, blood vessels, kidneys, brain, intestines, etc.<sup>2</sup> Recently various locations of the oral cavity have been found to be associated with differential expression of ACE2 protein, with the tongue being the most common site.<sup>3</sup> Moreover, the salivary glands have also been regarded as a potential source of SARS-CoV-2 infection due to the presence of the ACE2 receptor.<sup>4</sup> However, till date there is no strong scientific evidence that has proved the existence and interaction of ACE2 protein and spike receptor of SARS-CoV-2 on oral mucosal and salivary gland epithelial cells.