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During this COVID-19 outbreak, diagnostic tests were crucial in controlling its spread. This pandemic, which was caused by the SARS-CoV-2 virus, has created an urgent need for rapid diagnostic testing to enable efficient treatment and control of COVID-19. Many institutes and companies are trying to develop effective methods for detecting COVID-19. The essential indicative instrument presently utilized is reverse transcription-polymerase chain response (RT-PCR), which can have great affectability. Tragically, execution costs, time is taken, and false-negative results have limited the use of RT-PCR. Lateral flow assays (LFAs) are a type of diagnostic test that is clinically sensitive enough, might bridge various inadequacies in the present RT-PCR system, especially in low-and middle-income countries. In basic hospitals and laboratories, AuNP-LFA is a viable technique for diagnosing COVID-19, especially in emergency settings where a large number of samples must be examined quickly. This review summarizes the different diagnostic approaches for detecting the SARS-COV-2. This review thus provides guidelines for the scientists and technicians engaged in detecting SARS-COV-2. An accurate and sensitive detection system would enormously benefit in controlling this pandemic. © 2022 by the authors.
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COVID pandemic hit the farming community harder with its nature of infection and also with various restrictions imposed during the first and second lockdown in 2020 and 2021. The present study was conducted during the year 2021 to study the psychological distress experienced by the farmers in wake of COVID-19 in two surrounding districts of Hyderabad, Telangana namely Rangareddy and Vikarabad. Data was collected from 240 farmers from July to September, 2021 just after second wave of COVID-19. Non-specific psychological distress due to pandemic was measured by the Kessler 10 (K10) scale which is a well validated and widely used scale to measure distress. The findings of the study showed that about 76 per cent of the farmers experienced high to very high level of psychological distress during the second wave of COVID 19. This was attributed to the fact that these districts were dependent on Hyderabad for sale of its produce which was badly affected by pandemic leading to distress. The results further revealed that majority of farmers (85%) involved in full time farming were experiencing very high distress while only 15 per cent farmers having service in addition to farming were in the same category. This highlights the need of providing alternate livelihood strategies for farmers to tide over uncertain circumstances.
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The COVID-19 Pandemic is considered as the worst situation for human beings;it affected people's lives worldwide. Due to this pandemic, the respective government authority announced the lockdown to break the coronavirus chain. The lockdown impacted people's mental health, leading to many psychological issues as well as hampered students' academics. In this chapter we have studied the impacts on students' academics due to lockdown effect. The data has been collected via a google form questionnaire circulated to various educational institutes. Further, we have developed a novel machine learning classifier model called Naïve Bayes-Support Vector Machine for analyzing the data, which utilizes the properties of both classifiers by using a deep learning framework. We have used natural language processing (TextBlob, Stanza and Vader) libraries to label the dataset and applied in the proposed NBSVM method and other machine learning models and classified the sentiments into two categories (Positive vs Negative). We also applied the natural language processing libraries used a topic-modelling technique called Latent Dirichlet Allocation to know the essential topics words of both classes from students' feedback data. The study revealed 83% and 86% accuracy for unigram and bigram, respectively, whereas the precision was 79% and recall 81%. According to NLP libraries' result, approximately 71% of the feedback's sentiment is negative, and only 16% of feedbacks are positive. The proposed model shown that (Naïve Bayes-Support Vector Machine) outperforms the other variants of the Naïve Bayes and support vector machine. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Background: COVID-19 pandemic had multiple associated actions from government and consequences for public. NIMHANS Bangalore had initiated a national helpline for psychosocial support for people affected by COVID pandemic. Large number of individuals contacted the helpline for seeking various kinds of help. This paper reports the temporal patterns of help seeking behavior in a population exposed to COVID-19 pandemic and associated adversities. Objectives: The aim of the study was to identify meaningful patterns in help seeking behavior of population affected by the biological disaster to improve our understanding population level behavioral patterns. This could also provide insight useful for health policy and administration. Methods: Distribution analysis of 316,134 calls received during the period of 28th March 2020 – 31st December 2020 on two temporal factors. We used Microsoft excel for the analysis of data. Results: Temporal distribution shows a sudden spike (forming a J curve) in the first four weeks of starting the helpline, this was followed by sharp decline for next four weeks and finally showing a slow decline with fluctuating patterns over next 32 weeks. Pattern of data on hourly rates of calls shows a maximum number of help seeking calls during 10am-8pm, and least numbers of calls during 12am-5am. Conclusions: The descriptive analysis of temporal patterns in help seeking behaviours drawn from this large dataset of national helpline provide insights and reference for health administrators and policy makers in effective planning and efficient utilization of scarce mental health resources. © 2023 DMICS.
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Due to the Covid-19 pandemic, people have been forced to move to online spaces to attend classes or meetings and so on. The effectiveness of online classes depends on the engagement level of students. A straightforward way to monitor the engagement is to observe students' facial expressions, eye gazes, head gesticulations, hand movements, and body movements through their video feed. However, video-based engagement detection has limitations, such as being influenced by video backgrounds, lighting conditions, camera angles, unwillingness to open the camera, etc. In this work, we propose a non-intrusive mechanism of estimating engagement level by monitoring the head gesticulations through channel state information (CSI) of WiFi signals. First, we conduct an anonymous survey to investigate whether the head gesticulation pattern is correlated with engagement. We then develop models to recognize head gesticulations through CSI. Later, we plan to correlate the head gesticulation pattern with the instructor's intent to estimate the students' engagement. © 2023 IEEE.
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This article explores the current status of housekeeping-employee retention and efficiency in hotels particularly during COVID-19 in India, then discusses the implications of ergonomic practices on these. Ergonomic practice research in hotel housekeeping has been given enlarged scholarly attention, yet similar research in the Indian context is almost non-existent. Housekeeping work involves considerable physical effort that can lead to discomfort or even injury. This research involved 210 housekeeping employees from five-star hotels through an online survey. The data were interpreted using the partial least square (PLS) software SmartPLS 2.0. The constructs used in the study were working conditions, risk assessment and control, pandemic response plan, employee efficiency and employee retention. Working conditions were found to have a significant positive relationship with employee retention, whereas, risk assessment and control was found to have a positive relationship with employee retention and employee efficiency. Also, the pandemic response plan was found to have a positive relationship with employee efficiency. The pandemic response plan was not found to have a significant positive relationship with employee retention, while working conditions were not found to have a significant positive relationship with employee efficiency either. © by the author, licensee University of Lodz – Lodz University Press, Lodz, Poland.
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Background: COVID-19 disease, a pandemic for more than two years, has major morbidity and mortality related to pulmonary involvement. Chest radiography is the main imaging tool for critically ill patients. As the availability of arterial blood gas analysis is limited in the Level I and II healthcare centres, which are major partners in providing healthcare in resource-limited times, we planned the present study. Objectives: To assess the role of chest radiography in predicting the need for oxygen/ventilator support in critically ill COVID-19 patients. Methods: This hospital-based, retrospective study included 135 patients who needed oxygen/ventilator support and had optimal-quality chest radiographs at admission. All the chest X-rays were evaluated and a severity score was calculated on a predesigned pro forma. Statistical evaluation of the data obtained was done using appropriate tools and methods. Results: Males outnumbered females, with a mean age of 54.35 ± 14.49 years. More than 72% of patients included in our study needed ventilator support while the rest needed oxygen support. There was a significant statistical correlation between the chest radiograph severity score and SPO2 /PaO2 levels in our study. Using a cut-off value >8 for the chest radiograph severity score in predicting the need for ventilator support in a Covid-19 patient, the sensitivity, specificity and accuracy was 85.7%, 92.5% and 89.5%, respectively. Conclusion: Chest radiography remains the mainstay of imaging in critically ill COVID-19 patients when they are on multiple life-support systems. Though arterial blood gas analysis is the gold standard tool for assessing the need for oxygen/ventilator support in these patients, the severity score obtained from the initial chest radiograph at the time of admission may also be used as a screening tool. Chest radiography may predict the need for oxygen/ventilator support, allowing time for patients to be moved to an appropriate-level healthcare centre, thus limiting morbidity and mortality.
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Objective: NA Background: COVID-19 associated thromboembolism has attained considerable interest in recent times. However, most studies focus on venous and pulmonary embolism only. We present a case of COVID-19 associated massive aortic thrombosis which presented as paraparesis mimicking transverse myelitis. Design/Methods: NA Results: This is a case of 42-year-old female presented with acute onset paraparesis with paraesthesia and back pain. She was provisionally diagnosed as a case of acute transverse myelitis. During evaluation she developed fever with respiratory distress. Her COVID RTPCR came positive, along with HRCT thorax showing evidence of viral pneumonia with severity score 13/25. She was shifted to COVID-19 facility and managed as per standard protocol. After stabilization, a repeat examination revealed discoloration in left lower limb which was also cold to touch. CT angiography revealed a massive thrombus in distal abdominal aorta extending up to left common iliac artery, while MRI Spine was normal. Patient was transferred to vascular surgery department for further management. To best of our knowledge this is first case reporting arterial thrombosis mimicking myelitis in COVID-19. Conclusions: To conclude, COVID-19 patients are susceptible to thrombosis and aortic thrombosis can mimic transverse myelitis in presentation.
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Maize is an important industrial crop where yield and quality enhancement both assume greater importance. Clean production technologies like conservation agriculture and integrated nutrient management hold the key to enhance productivity and quality besides improving soil health and environment. Hence, maize productivity and quality were assessed under a maize-wheat cropping system (MWCS) using four crop-establishment and tillage management practices [FBCT-FBCT (Flat bed-conventional tillage both in maize and wheat); RBCT-RBZT (Raised bed-CT in maize and raised bed-zero tillage in wheat); FBZT-FBZT (FBZT both in maize and wheat); PRBZT-PRBZT (Permanent raised bed-ZT both in maize and wheat], and five P-fertilization practices [P100 (100% soil applied-P); P50 + 2FSP (50% soil applied-P + 2 foliar-sprays of P through 2% DAP both in maize and wheat); P50 + PSB + AM-fungi; P50 + PSB + AMF + 2FSP; and P0 (100% NK with no-P)] in split-plot design replicated-thrice. Double zero-tilled PRBZT-PRBZT system significantly enhanced the maize grain, starch, protein and oil yield by 13.1-19% over conventional FBCT-FBCT. P50 + PSB + AMF + 2FSP, integrating soil applied-P, microbial-inoculants and foliar-P, had significantly higher grain, starch, protein and oil yield by 12.5-17.2% over P100 besides saving 34.7% fertilizer-P both in maize and on cropping-system basis. P50 + PSB + AMF + 2FSP again had significantly higher starch, lysine and tryptophan content by 4.6-10.4% over P100 due to sustained and synchronized P-bioavailability. Higher amylose content (24.1%) was observed in grains under P50 + PSB + AMF + 2FSP, a beneficial trait due to its lower glycemic-index highly required for diabetic patients, where current COVID-19 pandemic further necessitated the use of such dietary ingredients. Double zero-tilled PRBZT-PRBZT reported greater MUFA (oleic acid, 37.1%), MUFA: PUFA ratio and P/S index with 6.9% higher P/S index in corn-oil (an oil quality parameter highly required for heart-health) over RBCT-RBCT. MUFA, MUFA: PUFA ratio and P/S index were also higher under P50 + PSB + AMF + 2FSP; avowing the obvious role of foliar-P and microbial-inoculants in influencing maize fatty acid composition. Overall, double zero-tilled PRBZT-PRBZT with crop residue retention at 6 t/ha per year along with P50 + PSB + AMF + 2FSP while saving 34.7% fertilizer-P in MWCS, may prove beneficial in enhancing maize productivity and quality so as to reinforce the food and nutritional security besides boosting food, corn-oil and starch industry in south-Asia and collateral arid agro-ecologies across the globe.
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Background: Covid-19, a zoonotic disease caused by Severe Acute Respiratory Syndrome Coronavirus - 2 (SARSCov-2) has emerged as a worldwide infection and has been declared pandemic since March, 2020, by WHO. This has brought about tremendous burden on the health care system of not only the developing or the third world countries but also that of prosperous counties of the world. The recent Covid-19 pandemic has pushed the worldwide scientific and medical community to find a solution with the help of vaccines to control SARS-CoV-2 pandemic. An effective vaccine is one which leads to synthesis of IgG antibodies against SARS-CoV-2, thus aiding the control and decline of the pandemic. Aim: This study aims to evaluate the antibody titres post 1st dose and post 2nd dose Covishield vaccination and reveals the safety and efficacy of ChAdOx1 nCoV-19(Recombinant) Covishield vaccine. Methodology: The levels of IgG antibodies were estimated in 215 subjects (both normal subjects and Covid-19 positive subjects) using Enzyme Linked Immunosorbent Assay (ELISA) Technique. Results: Two hundred & fifteen subjects from Teerthanker Mahaveer Hospital of Moradabad (western Uttar Pradesh) were enrolled for the study. The participants were divided into two different groups. Group I comprised of 215 subjects who received 1st dose of the Covishield vaccine. Group II comprised of 101 subjects who received both the doses of the ChAdOx1 nCoV-19(Recombinant) Covishield vaccine. Levels of IgG were analysed 28 days post 1st dose of ChAdOx1 nCoV-19(Recombinant) Covishield vaccine and post 2 nd dose of ChAdOx1 nCoV-19(Recombinant) Covishield vaccination. After testing serologically for neutralising IgG antibodies, the titre was found to be below the threshold level of 1.1 in 67.40% of the subjects in the study group 1, whereas 32.60% (n=70) were found to be in the seroprotective range (i.e IgG titre > 1.1). Out of the total 101 participants who took both the doses, 39 participants (38.6%) were found to be in the seroprotective range (i.e IgG titre > 1.1). Conclusion: The two doses of Covishield vaccination (4 weeks interval) given to subjects resulted in increase in IgG antibody titre (Neutralising Antibodies) against both spike protein and nucleocapsid protein after 1st dose and 2nd dose and that single dose may suffice for seroprotection in subjects with previous history of COVID-19 who had recovered from the disease.
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The impact of the COVID-19 pandemic accelerates the Industry 4.0 implementation in the various walk of business processes. The tightly and loosely coupled integration among machines and the processes through intelligent software systems and pervasive computing promises a higher level of automation based on real-time prediction-based control systems. Therefore, Industry 4.0 plays a vital role in maintaining a balance between social distancing compliance and production demand. The proposed system introduces a novel model where the agricultural process is considered automated in adherence to Industry 4.0 standards over rural areas complying with the situation of the COVID pandemic. The proposed model offers a sophisticated operation of sustainability and introduces a new analytical model for Industry 4.0. The simulated outcome shows that the proposed system offers a cost-effective solution towards achieving better sustainability in agricultural innovation. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The present study was conducted to assess effectiveness and challenges of tele-dentistry and factors affecting it, during the times of COVID-19 health emergency among dental professionals. It was a cross-sectional questionnaire study conducted among dental professionals which was online. Mean age of Study participants were 32.3±3 years. Majority of study participants major challenges to practice of Tele dentistry during Covid-19 Pandemic was lack of proper infrastructure {(189 (91.3%)}, negative attitude of Dental professionals {(93 (44.9%)}, According to {172 (83.1%)} dental professionals there are many challenges for practicing Tele-dentistry. Dental professionals reported that effectiveness of Tele dentistry during Covid-19 is good but all together challenges were large to practice. Tele dentistry in India due to which its effectiveness decreases and factors effecting its effectiveness barriers were age, average number of patients seen per month before lockdown, and Practice closed due to Covid-19 outbreak.
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The coronavirus disease (COVID-19) outbreak-related lockdowns have shown that the current public distribution systems (PDS) are inefficient, as it does not reach the needy on-time. Considering a vast country like India, where the population is large and unevenly distributed, the PDS is complicated, aiming to reach out to individuals on-time. If the authorities know in prior, the urgency and demand for food supplies, they can efficiently plan food distribution to reach the individuals quickly. In this work, we propose solutions for the said problem through the Internet of Things (IoT) based architectures, which are inspired by our prior works [1] and [2]. The proposed IoT architecture utilizes a wireless device, wireless data network infrastructure, and cloud technology. The wireless device triggers a ticket or notification to the concerned authority, identifying the person in need of food supplies and the overall demand in a geographic area. A case study-based design approach is followed for designing these IoT architectures. © 2020 IEEE.