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The COVID-19 pandemic has resulted in a rapid growth of online learning. While majority of the current research focus on different learning management systems, massive open online courses, or even specific softwares like Zoom and Microsoft Teams, the use of artificial-intelligence (AI) based voice assistants (VAs) for the purpose of online education is very rare. In this work we propose, validate, and test a research model that explains the continuance usage of VAs by students for learning purpose during their home quarantine period. We consider novel pandemic-specific psychological factors like loneliness and self-quarantine, together with anthropomorphic factors like voice attractiveness of the VAs for proposing the research model. The factors of satisfaction and continuance usage are borrowed from Expectation Confirmation Theory. Partial Least Squares Structural Equation Modelling is used for testing the proposed model. © 2023 IEEE.
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Ciprofloxacin and ofloxacin belong to a class of antibiotics called Fluoroquinolones (FQs), which have a wide anti-bacterial activity against Gram-positive and Gram-negative bacteria. Since the recent Covid-19 pandemic witnessed a magnanimous rise in the use of antibiotics to prevent secondary bacterial infections, it led to vast production and use of such antibiotics. Ultimately the antibiotics get discharged into the municipal sewer pipes, thereby killing the useful microbial colony. In order to prevent environmental degradation a commercial scale-up of the adsorption of these antibiotics using raw sewage sludge is an absolute necessity. In this study, a continuous adsorption operation is conducted in a packed bed of semi-dried raw sewage sludge to remove the FQs from wastewater. Two transient convective-diffusion models are developed including pseudo-first and second-order kinetics driven depletion terms. The models are optimised using the data collected under various dynamic conditions in order to analyse the performance of the packed bed in terms of bed height, flow rate and initial concentration of the FQs. Damköhler numbers of the FQs are estimated to predict the breakthrough times of both the FQs. The ratios of Damköhler numbers of ciprofloxacin and ofloxacin do not change much with flow rate. In all the experiments, Das << 1 for both the FQs, indicating a faster diffusion process with respect to the rate of pseudo-reaction. Diffusion reaches an ‘equilibrium' well before the reaction achieves pseudo-chemical equilibrium. Ratios of the Damköhler numbers, meant to represent the first-order and second-order convective-diffusion models for ciprofloxacin to ofloxacin is < 1. © 2023 Elsevier Ltd
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We are in the half past of 2022, but still, we are facing the coronavirus pandemic situation. When a patient is hospitalized, only some FDA-approved drugs were administered to cure the patient. In treating coronavirus infection, nitazoxanide, granulocyte-macrophage colony-stimulating factor inhibitors, and various monoclonal antibodies are present. But all the molecules used in the treatment were not so effective in fully curing the patient. So, to break this jinx to develop of newer generation anti-SARS-CoV-2 drug molecules, computational approaches played an essential role. 2D QSAR studies related to anti-SARS-CoV-2 molecule development, some QSAR models observed with good statistical parameters such as R2: 0.748, cross-validated Q2 (LOO): 0.628, external predicted R2: 0.723 and another model suggested with R2: 0.764, Q2: 0.627 and Rm2: 0.610, Q2 (F1): 0.727, Q2 (F1): 0.652, MAE score: 0.127. We developed a new 2D QSAR model with a higher number of molecules and greater statistical parameters. A dataset of 84 anti-SARS-CoV2 molecules was obtained from literature followed by descriptor calculation PADEL software;the QSAR model was generated using the Modelability index, dataset pretreatment, division, MLR equation, validation, and Y randomization test. The model was pIC50 = -1.79268(+/-0.3652) +0.07995(+/-0.03551) naaaC -0.4051(+/-0.09672) nsssN -0.45945(+/-0.11025) SHsOH +1.23189(+/-0.28144) ETA_BetaP with R2 and Q2 values were 0.87028 and 0.70493 with MAE fitness score value: 0.14298. Atoms E-state and electronic features of the molecules directly related to anti-SARS-CoV-2 drug activity. It can be easily concluded that we want to develop a small molecule effective against SARS-CoV-2 disease in the near future.Copyright All © 2023 are reserved by International Journal of Pharmaceutical Sciences and Research.
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Online learning has been a challenge for the students in times of the pandemic. In this context, academic self-concept (ASC) is an important aspect that has been under-researched. We develop a research model in this work based upon the Stimulus Organism Response (SOR) framework for explaining student's ASC, and how it is formed from four unique engagement types and the quality of the online learning systems. Data is collected from a two country study (India and Thailand) across two big public universities specializing in STEM education. A Partial Least Squares Structural Equation Modeling (PLS-SEM) approach is used for the purpose of model building and validation. Results indicate that online system quality affects behavioral, cognitive, and affective engagement dimensions of students, while these three engagement dimensions further significantly affect the student's ASC. Agentic engagement does not have any role in the entire online teaching–learning process. Based on the results, the theoretical and practical implications are discussed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Nanomaterials have played a significant role in effectively combating the global SARS-CoV-2 pandemic that began in December 2019 through the development of vaccines as well as antiviral therapies. These versatile, tunable materials can interact and deliver a broad range of biologically relevant molecules for preventing COVID-19 infection, generating immunity against COVID-19, and treating infected patients. Application of these nanomaterials and nanotechnologies can further be investigated in conjunction with disease models of COVID-19 and this holds immense potential for accelerating vaccine or therapeutic process development further encouraging the elimination of animal model use during preclinical stages. This review examines the existing literature on COVID-19 related nanomaterial applications, including perspective on nanotechnology-based vaccines and therapeutics, and discusses how these tools can be adapted to address new SARS-CoV-2 variants of concern. We also analyze the limitations of current nanomaterial approaches to managing COVID-19 and its variants alongside the challenges posed when implementing this technology. We end by providing avenues for future developments specific to disease modelling in this ever-evolving field.
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In the recent COVID-19 pandemic situation, physical distributions of University question papers to the affiliated colleges are very difficult. Though online distributions of question papers are a good alternative, they may be vulnerable in respect of security concerns. Hackers may intervene in the process and question papers may be stolen or altered. In this paper, we used K-out-of-N visual cryptography techniques to secure the question papers in between the transmissions. Before creating the shares, we applied an extra password protection to the original question paper using AES encryption. At the college examination center, end multiple shares are received by the separate stakeholders, who were ultimately combined together to create the decrypted question paper only after having the password provided by the head of the Institution. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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With the detection of Omicron, a new variant of severe acute respiratory syndrome coronavirus-2 in South Africa, a question arises regarding its implication in public health. The infectivity, ability of getting detected by available testing method and effectiveness of existing vaccine against this strain are not known properly. This Omicron variant can impact public health similarly or more than the Delta variant. The research is going on in many countries to get conclusion regarding the impact of the Omicron variant in public health.
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A large amount of migration of labour from the informal industrial or unorganized sector to the agricultural sector has accelerated the problem of downward pressure in Indian economy during the Covid-19 pandemic situation. If these migrant labourers are bound to be absorbed in the agricultural sector, then not only the amount of surplus labour is aggravated, but the extent of efficiency of agricultural sector may be reduced as well, since these migrant labour would be forced to choose agricultural activities and may not be as efficient as workers who are normally employed in the agricultural sector. This chapter measures the extent of the decline in efficiency in the Indian agricultural sector and the consequent loss of output, arising out of the employment of inefficient labour due to Covid-19 problem and also the extent of the casual labour force that can be dispensed with in order to keep the output level unchanged, taking rice production as a case study and considering the data from 16 major rice-producing Indian states for the period 2004-05 to 2020. © 2022 selection and editorial matter, Rajib Bhattacharyya, Ananya Ghosh Dastidar and Soumyen Sikdar;individual chapters, the contributors.
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This paper attempts to describe the outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) via an epidemic model. This virus has dissimilar effects in different countries. The number of new active coronavirus cases is increasing gradually across the globe. India is now in the second stage of COVID-19 spreading, it will be an epidemic very quickly if proper protection is not undertaken based on the database of the transmission of the disease. This paper is using the current data of COVID-19 for the mathematical modeling and its dynamical analysis. We bring in a new representation to appraise and manage the outbreak of infectious disease COVID-19 through SEQIR pandemic model, which is based on the supposition that the infected but undetected by testing individuals are send to quarantine during the incubation period. During the incubation period if any individual be infected by COVID-19, then that confirmed infected individuals are isolated and the necessary treatments are arranged so that they cannot taint the other residents in the community. Dynamics of the SEQIR model is presented by basic reproduction number R 0 and the comprehensive stability analysis. Numerical results are depicted through apt graphical appearances using the data of five states and India.
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Background & objectives: Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a highly infectious virus which causes the severe respiratory disease for human also known as Coronavirus Disease (COVID) emerged in China in December 2019 that spread rapidly all over the world. As there is no proper medicine or vaccine against the virus SARS-CoV-2 or COVID-19 to control the spread of the virus, all the countries are taking many steps as preventive measures, like lockdown, stay-at-home, social distancing, sanitization, use of mask, etc. For almost three months of lockdown many countries are relaxing the lockdown period and the movement of people. The objective of this study is to develop a new mathematical model, called the SEIQRS model in imprecise environment and to find out the essentiality of quarantine, stay-at-home orders, lockdown as precautionary measures to protect the human community. Methods: In this study, after developing the COVID-19 SEIQRS model, the SEIQRS fuzzy model and the SEIQRS interval model are constructed by taking parameters as triangular fuzzy numbers and interval numbers respectively. Solution curves are drawn for two imprecise models by using MATLAB R2014a software package and the sensitivity analysis is also performed with respect to the control parameters. The next generation matrix approach is adopted to calculate the basic reproduction number (R0) from the SEIQRS model to assess the transmissibility of the SARS-CoV-2. Results: The basic reproduction number (R0) is calculated for this model and to get the stability and disease free equilibrium the value of the basic reproduction number must be less than 1. Also, we find the solution curves in different uncertain environments and sensitivity studies show the importance of newly added population (α), rate of spreading asymptomatic infection (β ), rate of developing symptoms of infection (λ ), proportion of infected population in quarantine (γ ). Interpretation & conclusions: Our model shows that quarantine, lockdown are essential to control the spread of the disease as at present there is no such medicine or vaccine to combat COVID-19. Once the virus establishes transmission within the community, it will very difficult to stop the infection. As a measure of public health, healthcare and community preparedness, it would be serious to control any impending outbreak of COVID-19 in the country. © 2022 L&H Scientific Publishing, LLC. All rights reserved
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Introduction: The lockdown was implemented nationally for six weeks, followed by another two weeks of graded lockdown in districts in India as a means to prevent spread of infection. During this period, there was restriction of movement of residents except for those engaged in providing essential services. Aim: To find out sociodemographic profile of patients along with the impact of lockdown and spread of COVID-19 infection post-lockdown. Materials and Methods: A prospective observational study conducted in Bairagarh, a suburban area of Bhopal. The study was conducted for three months. A contact tracing questionnaire was used for data collection. The data was collected by actual visiting the patient’s address. The data collected was compiled and analysed using Microsoft Excel-2020. The patients were instructed to inform the data collector of any postviral symptoms after 15 days of diagnosis to find out any postviral complaints. Percentages and proportions were derived using Epi info-7.0. Results: During the study period of three months, in total 90 patients were interviewed. Almost 85.5% cases were found post-lockdown. Most common age group to be involved was 30-45 years. Males were more commonly infected. Only 14.44% patients who worked during lockdown were infected. Almost 26.6% patients were involved in cloth merchandise business which was closed during lockdown and had a sudden upsurge in business during unlock. In total 47.7% patients were asymptomatic when tested. Relative Risk (RR) of acquiring infection post-lockdown was 1.13. Doubling rate of infection among study population during lockdown was found to be 14.05 days compared to 5.35 days post-lockdown. Almost 80% patients did not have any postviral symptoms. The most common symptom seen was nose block. Conclusion: The lockdown was found to be effective strategy in controlling spread of COVID-19 infection as post-lockdown there was sudden increase in number positive cases.
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This paper presents the current situation and how to minimize its effect in India through a mathematical model of infectious Coronavirus disease (COVID-19). This model consists of six compartments to population classes consisting of susceptible, exposed, home quarantined, government quarantined, infected individuals in treatment, and recovered class. The basic reproduction number is calculated, and the stabilities of the proposed model at the disease-free equilibrium and endemic equilibrium are observed. The next crucial treatment control of the Covid-19 epidemic model is presented in India’s situation. An objective function is considered by incorporating the optimal infected individuals and the cost of necessary treatment. Finally, optimal control is achieved that minimizes our anticipated objective function. Numerical observations are presented utilizing MATLAB software to demonstrate the consistency of present-day representation from a realistic standpoint. © 2021 Pal et al.
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Introduction: Contact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Current clinical and epidemiological data are insufficient to understand the full extent of the transmission potential of the COVID pandemic. The main advantages are that it can identify potentially infected individuals before severe symptoms emerge, and if conducted sufficiently quickly can prevent onward transmission from the secondary cases. Hence the study was undertaken. Methodology: It was a cross-sectional study conducted by the Department of Community Medicine, Bhopal from 9th May to 30th June 2020.
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The COVID-19 pandemic has forced educational institutes worldwide to resort to an "online only" mode of teaching delivery. As a consequence, throughout the globe there has been an increasing trend among the students to use different videoconferencing applications for the purpose of learning online. However, the multimedia quality provided by these different applications provides the key to their success i.e. whether or not the students will be willing to use those for learning online. Consequently, three popular applications (Zoom, Microsoft Teams, and Cisco Webex) are taken up in this work for the purpose of multimedia quality evaluation by using an objective based approach. Results from both the models are in close agreement with each other. Microsoft Teams provides the least experience, whereas those from the others vary depending upon the objective models used. The results obtained are further verified by conducting relevant hypotheses tests. © 2020 ACM.
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Physical closure of educational institutes worldwide due to the COVID-19 pandemic has resulted in the emergence of a new era of video-based learning. The current circumstances are unique that have forced students to use digital technologies for their learning purpose. However, the successful usage of such a system relies on the understanding of the adoption factors, for which an integrated model is proposed based on the Technology Acceptance Model and the Task Technology Fit Model. Additionally, this work considers the moderating effects of gender and digital inequality. Data are collected from 232 students all of whom have taken part in a full-semester video-based online learning course in times of the pandemic. A Partial Least Squares method is used for analyzing the data. Results show that video-based learning positively fits into the student’s perception and their actual use of the system. The effect of individual characteristics is more than the technology characteristics on the task-technology-fit chain. The integrated model can predict 64.6% of the variance in the final dependent variable: actual usage of video-based learning. Further, while the moderating effect of gender is found to be significant, that for digital inequality is non-significant. Finally, the theoretical and practical implications are discussed. © 2020 Taylor & Francis Group, LLC.