Particulate matter in a lockdown home: evaluation, calibration, results and health risk from an IoT enabled low-cost sensor network for residential air quality monitoring

Exposure to atmospheric particulate matter is associated with a wide array of health impacts. Whilst ambient air pollution exposure is widely discussed both within the scientific literature and media, indoor exposure to pollutants has received less attention. However, humans spend a large amount of time in indoor environments, which increased significantly during the Covid-19 pandemic. This paper tests the application of a low-cost Internet of Things (IoT) enabled indoor sensor network to provide a relative assessment of variations in PM in a lockdown home. The paper validates the low cost, IoT approach via sensor corrections and testing before assessing particulate concentrations for a ∼7 week period within a typical suburban home in the UK. With the caveat that data from low-cost sensors are at best indicative, it was found that particulate matter concentrations in multiple rooms exceeded both 2021 and 2005 WHO Global Air Quality Guidelines, when extrapolated to annual exposure levels, despite relatively low ambient concentrations. Concentrations peaked at 488 μg m−3 (PM2.5) when cooking was occurring within the home. © 2023 RSC.

An Automated Approach for Screening COVID-19 from Thermal Images Using Convolutional Neural Network

The world has seen the disastrous effect caused by COVID-19 on humankind. The rapidity of COVID-19 transmission, re-infections, post-COVID-19 symptoms, and the emergence of new COVID-19 strands have disrupted the global healthcare systems. Consequently, screening for COVID-19 cases has become of the utmost importance. As temperature and mask checks help significantly to prevent the rapid spread of COVID-19, automating this process in public places has become indispensable. In this work, we propose an end-to-end approach for mask detection followed by temperature for efficient screening. The proposed model achieved 93.5%, 96.7%, and 97.7% precision, recall, and mAP when trained on the thermal surveillance dataset and tested on a lightning dataset consisting of images with varying intensities. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

COVID-19 and post-COVID effect in India: A critical analysis

India is in the second position in terms of population and the third-worstaffected country in the world in the total number of confirmed COVID- 19 cases. COVID-19 was marked by low case fatality rates and strong recovery rates in India, as well as an increase in public-private partnerships in the health sector. Technological advancements have aided in the containment of this epidemic. The virus's growth rate was halted by an early lockdown policy, however, super events are increasing infection rates due to the breakdown of COVID protocol behavior. This COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It contributes to worldwide healthcare issues and overstretched healthcare resources. As the people recovering from this disease, it is of utmost importance to establish knowledge of healthcare issues surrounding them. COVID-19 is a multi-organ disease and there are reports of permanent and prolonged effects of this disease. So it is very important to understand COVID-19, the post-COVID effect and the status of the administration and individuals dealing with this situation. The present chapter discusses the knowledge regarding COVID-19, various post-COVID-19 symptoms reported all over the world, especially in India in terms of professional status, financial status, mental status and status of the government and people dealing with this pandemic situation. © 2022 Nova Science Publishers, Inc..

Assessing Patient Reported Quality of Care and Safety in Mohs Surgery During the COVID-19 Pandemic

COVID-19 has greatly impacted patients’ ability to receive medical care. Early on during the pandemic, skin cancer diagnosis and treatment were often delayed due to fear of viral spread. In certain locales, executive orders have prevented physicians from performing procedures that were not immediately lifesaving. This study aims to assess patient-reported quality of care and sense of safety while receiving Mohs micrographic surgery (MMS) during the pandemic. The intent of this study is to identify patient-specific factors that influence concerns and feelings of safety, and thus guide future safety measures. A telephone survey was administered to assess patient concerns about treatment delay, feelings of safety, and satisfaction. A retrospective chart review was performed to collect demographics, comorbidities, tumor characteristics, etc. A total of 144 patients (102 male, 42 female;average 71.9 years old) completed the study. Overall, patients felt safe and satisfied, with 75.7% reporting 10/10 safety (average 9.5/10) and 84% reporting 10/10 satisfaction (average 9.7/10). Patients had more notable levels of concern regarding pandemic-related treatment delays (median 2/10), compared to the risk of contracting COVID during their visit (median 1/10). Concerns regarding treatment delay included an increase in cancer size, spread, pain, and scarring. This study demonstrates that high levels of patient feelings of safety and satisfaction can be obtained with MMS during the pandemic. As the pandemic continues, it is imperative that patients can receive high quality and timely care without compromising safety. Outpatient dermatologic surgery can continue without jeopardizing patients' overall feeling of safety and satisfaction. © 2022 THE AUTHORS.

Healthcare case study: COVID19 detection, prevention measures, and prediction using machine learning & deep learning algorithms

In healthcare, COVID19 has been spreading in multiple forms across the entire world. Coronavirus, or COVID19, belongs to a large group of viruses that are the causes for mild respiratory tract infections in humans, varying from the common cold, or can be more severe like Severe Acute Respiratory Syndrome (SARS) and Middle Eastern Respiratory Syndrome (MERS). This work aims to provide information about symptoms of coronavirus, its detection, and its prevention. In this study, we proposed a model for predicting results. Predictions are made using patients' symptoms of having Covid19 or not by applying various machine learning and deep learning algorithms. The effectiveness of the proposed model is experimentally evaluated on patients' symptoms using 5000 rows of a data set. Many cases are highlighted as a group of problems related to the COVID19 pandemic and point out promising results. © 2022 Scrivener Publishing LLC.

Detection of COVID-19 from X-Ray Images using Deep Neural Networks

In Dec 2019, Coronavirus has first shown in China and since then there is a big rise in the number of these cases. On March 28, 2020, WHO (World Health Organization) tweeted and proclaimed it's an epidemic. The test kits are relatively less likely to be checked by collecting blood samples because they are easily infectious, and collecting blood samples are very time taking. But it's important to get a quick and simpler way to validate the covid-19. Lungs are getting very badly affected by the Coronavirus and it increases in lungs gradually so we have to come up with the Convolutional Neural Network (CNN). This detects Corona virus utilising X-Rays of the Chest within about few seconds. To diagnose Coronavirus from X-ray Image dataset using different Convolutional Neural Network methodologies like Mobile Net, Inception, Exception, VGG. However, the findings obtained are based on the VGG16, VGG19 model. Apply the models to the X-ray dataset this was obtained from the Kaggle source. This dataset included 100 X-ray images of the lungs(chest) of the Patients with CORONA VIRUS, and 100 X-ray images of the lungs(chest) of People who are healthy. Python language is being used to execute the COVID19 dataset and Google Collaboratory is used for coding purposes. The focus of this research is to see how successful automatically detecting COVID-19 from chest X-rays using Convolutional Neural Networks. This study shows that to detecting COVID-19, VGG16 performs better than other method. The accuracy is 96.15% using VGG16 method. The excellent achievement of these models has the potential to rapidly better the COVID-19 diagnosis performance and speed. Although, A bigger dataset of chest X-ray pictures (COVID-19 positive) are necessary while using deep transfer learning to achieve consistent, accurate and better results to detecting COVID-19 diseases. © 2021 IEEE.

Dilated CNN for Crowd Count

In the current scenario of the COVID-19 pandemic estimating the count of number of people present in public places at a particular time has become a significant task. Crowd count is attracting a lot of researchers from the computer vision and deep learning field. It has been found that to achieve this objective computer vision techniques such as deep learning, machine learning, etc. outperform traditional ways of estimating crowd count that uses handcrafted features such as Histogram of gradients, Haar, Scale Invariant Feature Transform and gives better results with higher accuracy. The paper studies the effect of dilation on convolution layers in estimating the crowd count. We have also done a comparative analysis of the developed model with different dilation rates on the ShanghaiTech dataset (part A and part B). The model is trained with images containing occluded and restricted visibility of heads. The model outputs the result with substantial accuracy in estimating the headcount in images of the dense crowd in a sensibly less amount of time. © 2021 IEEE.

COVID-19 Outbreaks Challenges to Global Supply Chain Management and Demand Forecasting on SCM Using Autoregressive Models

Global-SCM (Global-supply-chain-management) is characterised as the distribution of goods and services to maximise profit and reduce waste within the global network of a transnational business. The goal of this chapter is to provide information on the challenges faced by global supply chain management as a result of the Covid-19 pandemic, and to suggest solutions to these challenges through machine learning and artificial intelligence. The work presented in this research constitutes a contribution to modelling and forecasting the demand in a retail sales company, by using time series approach. Our work shows how the historical data of retail items could be utilized to forecast future demands and how these forecasts affect the supply chain management. The historical demand information was used for forecasting future demands using several autoregressive integrated moving average models like AR, MA, ARMA, ARIMA, and SARIMA. By comparing their Akaike's Information Criterion (AIC) values we get to know that ARIMA model is best suited for demand forecasting of the current retail item sale data. The result from the proposed work so obtained proves that the proposed model could be utilized for demand forecasting to meet the future demands in the retail sales item company. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Does India Need Vaccine Federalism?

This paper focuses on the identification of the key determinants of the interstate differences in the incidence of COVID-19. It finds that it is best to have a dynamic, transparent, and explicit formula for the interstate allocation of vaccines under conditions of deficient supply. This is ideally handled by an objective expert body. © 2022 Economic and Political Weekly. All rights reserved.

Does India Need Vaccine Federalism?

In the context of interstate distribution of COVID-19 vaccines in India, an erstwhile excess supply situation got quickly converted into a deficient supply situation soon after the eligibility criterion was extended from persons 60 years and above to persons aged 45 years and above and subsequently to persons 18 years and above. The vaccine supply situation may come under further pressure once the eligibility age is extended further to lower age groups covering children. The states have frequently complained about the inadequate supply of vaccines and have asked for a more transparent mechanism for their interstate allocations (Phadke et al 2021). At present, the interstate distribution is being handled by the Union Ministry of Health and Family Welfare. Any objective basis of the algorithm or methodology presently being used for this interstate distribution has not been shared with the wider public, and the complaint of the states regarding non-transparency in handling of interstate distribution of vaccines seems justified. Given the supply shortages, the initiative by the Government of India to augment vaccine supplies by granting approval to vaccines already approved by regulatory authorities in the United States (US), the European Union (EU), the United Kingdom (UK), and Japan subject to certain conditions is a welcome move.

Valorization of By-Products from Food Processing Through Sustainable Green Approaches

The food processing sector is a very prominent section of the international market and increased up to approximately $4.5 trillion by 2024 (Businesswire in Global food processing market report, 2019: trends, forecasts, and competitive analysis (2013–2024), 2019 [1]). The increasing demand for healthy fruits and vegetables, organic processed foods, nutraceuticals and functional foods, seafood with packaged food products like ready-to-eat, and frozen processed foods is expected to drive the market growth after pandemic COVID-19 incidence. During processing and handling of horticultural crops, generate large volumes of wastes annually and become a major concern to the whole world. Fruits and vegetables have many bioactive compounds (polyphenols, flavonoids, organic acids, aroma, and flavoring agents, etc.) which have a positive impact on human health because of anti-inflammation, anti-allergic, anti-cancer, anti-atherogenic, and antioxidants properties, depending upon extraction their methods from wastes, efficacy, and bioavailability to the body. Applications of conventional (soxhlet, maceration, percolation, hydro-distillation) and green techniques (solid-phase, supercritical, accelerated solvent, microwave, and ultrasound extractions) for the valorization of horticultural wastes’ conversion in many bioactive components are followed by the potentiality, scalability, and sustainability of the extraction process and highlight the concept of the circular economy as “Waste to Wealth.” © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Future of work: a systematic literature review and evolution of themes

Purpose: Concerned with the rising social, economic and technological disruption in the world, the impact of the technological disruption had a significant impact on the future of work and it has been tremendously increased in past five years. Further, with the rising uncertainties and COVID-19 in the picture, the trends suggested by earlier literature might not hold. The purpose of this paper is to understand the evolution of technology in the workplace in the past five years, how does it stand during COVID-19, will the trend continue in light of disruption caused by COVID-19, the impact of COVID-19 on the future of work. Design/methodology/approach: The paper uses bibliometric techniques to identify the conceptual and intellectual structure of the studies. The programming language named after authors Robert and Ross (R) software and Biblioshiny were used to identify the structures and the themes underlying those structures, which further helped in forecasting the trends of the studies. Findings: The paper shows the drastic evolution of the studies in past few years and different technologies implemented at the workplace in the same period. It further identified the influential papers, authors, journals in the area with an emphasis on the various collaboration network among authors and countries. It also paints a picture of the impact of COVID-19 on the future of work. The paper finally concluded with future directions for the emerging trends and themes in the area in aftermath of COVID-19. Originality/value: This paper takes the microscopic view of the studies carried out in the past five years as during the past five years, the studies related to this topic have grown tremendously and accordingly many trends have been identified but with the COVID-19 pandemic in the picture, the trend is likely to get accelerated. This paper takes this view and identifies the trends in the future by identifying the themes based on periods and at different levels – organizational, managerial, individual. © 2021, Emerald Publishing Limited.

Fiscal consolidation and FRBM in the COVID-19 context: Fifteenth finance commission and beyond

The fiscal consolidation projections provided by the Fifteenth Finance Commission, including its alternative paths, have been rendered out of alignment because of the COVID-19’s deleterious economic impact. The commission has also recommended that the centre’s Fiscal Responsibility and Budget Management Act, 2018 should be reviewed by a high-powered intergovernmental group. The main deficiencies of the FRBM Act, 2018, pertaining to an internal inconsistency between the debt and fiscal deficit targets for both the central and state governments and its weak macro-stabilisation framework should be addressed. The conditions under which the consolidated debt–GDP target may be raised to 70%, divided into 40% and 30% for the central and state governments, which may be combined with fiscal deficit to GDP targets of 4% and 3%, respectively, have been examined. Changes have been suggested in the macro-stabilisation framework, by making a distinction between agricultural and non-agricultural economic cycles. Setting up of a Fiscal and Monetary Policy Coordination Committee for policy coordination and dealing with emergencies and pandemic-kind situations is also relevant for India. © 2021 Economic and Political Weekly. All rights reserved.

A Bibliometric Assessment Of India’S Library And Information Science Research Publications During 2011-2020

The aim of this paper is to conduct a bibliometric study to investigate the research output of library and information science in India. The SCOPUS database was selected to collect data from 2011 to 2020. Collected data was analysed on various parameters such as authorship pattern, year wise contribution of articles, most cited articles, top journals, top authors, document types, etc. The study found that in year 2019 Indian author contributed 471 research papers which 21.8% and highest in 10 years. Again in 2019, double authored article was highest in number with total of 252 articles. In periods of 10 years, about 2159 Indian articles were published with international collaboration. The growth of LIS research has been observed to bincreasing till 2019, but decrease in 2020 possibly due to the Covid pandemic. © 2021, Library Philosophy and Practice. All Rights Reserved.

Impact of recommender algorithms on the sales of e-commerce websites

Purpose: With the current pandemic situation, the world is shifting to online buying and therefore the purpose of this study is to understand how the industry can improve sales based on the product recommendations shown on their online platforms. Design/methodology/approach: This paper has studied content-based filtering using decision trees algorithm and collaborative filtering using K-nearest neighbour algorithm and measured their impact on sales of product of different genres on e-commerce websites and if their recommendation causes a difference in sales.This paper has conducted a field experiment to analyse the customer frequency, change in sales caused by different algorithms and also tried analysing the change in buying preferences of customers in post-pandemic situation and how this paper can improve on the search results by incorporating them in the already used algorithms. Findings: This study indicates that different algorithms cause differences in sales and score over each other depending upon the category of the product sold. It also suggests that post-Covid, the buying frequency and the preferences of consumers have changed significantly. Research limitations/implications: The study is limited to existing users of these sites, it also requires the sites to have a huge database of active users and products. Also, the preferences and likings of Indian subcontinent might not generally apply everywhere else. Originality/value: This study enables better insight into consumer behaviour, thus enabling the data scientists to design better algorithms and help the companies improve their product sales. © 2020, Emerald Publishing Limited.

A review on the covid-19 (Novel coronavirus) – characteristics, evaluation, and treatment

In December 2019, there was a flare-up of the unidentified reason for pneumonia that overwhelmed the vast majority of the world. This infection has a place with β-corona virus, an enormous class of infections common in nature. On the 11th of February 2020, W.H.O named this disease as COVID-19 (Corona virus Disease 2019). This novel corona virus is to be believed to get spread from the bat and later on a human to human transmission. These patients gave indications of extreme pneumonia including fever, weakness, dry cough and respiratory trouble. Still, the exact mechanism of its approach has not been cleared yet. But it’s said to be the same as the previous strain of it like SARS-CoV and MERS-CoV. It has been affirmed that the COVID-19 also uses the cell section receptor i.e.;ACE2 as the SARS-CoV. The COVID-19 said to transmit starting with one then onto the next individual, so it is important to totally intrude on human-to-human transmission. Another method to control the spread is to avoid the diligence of corona viruses on inanimate surfaces because of various kinds of materials it can stay irresistible for 2 hours as long as 9 days. The typical standards are keeping up hydration and sustenance and controlling fever and cough. The typical standards are keeping up hydration and sustenance and controlling fever and cough. But still, the previously used antiviral drugs as well as like antibody and convalescent plasma as a potential therapy were used in the treatment.

Communication and management of public risks (with specific reference to the COVID-19 global pandemic)

We are in the midst of a global pandemic, the COVID-19. With no vaccine against the infection or medicines to treat the infected, the world is struggling to cope up with the increasing infections and casualties. It is recognized by everyone that the only option available to reduce the spread of the infection is to bring in lifestyle changes. Active participation by everyone is mandatory for success of this strategy. It is emphasized that the scientific community can play a very effective role in conveying this message across the entire population.