An Interdisciplinary Model-Based Study on Emerging Infectious Disease: The Curse of Twenty-First Century

In this article, we present a epidemiological model to analyze the impact of the emerging disease COVID-19. When an infectious disease like coronavirus suddenly emerges out of the blue, little is known about it. As time passes we get equipped with better information and knowledge. Some of the common tactics generally adopted to fight off the disease include awareness, isolation, lockdown, treatment and vaccination. Media also plays a pivotal role in spreading these information to general population. Here, we consider a changing population with immigration during an outbreak. We apply some of the above said measures to the population and study the effect of them in combating the disease. The effect of media is also examined. Both analytical and numerical simulations help us in establishing our findings. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.

Interactive Communication Robot Handling Crowd Management and Content Delivery in Museums Employing Crowd Counting

Through the last decade, and particularly after the Covid period (2020 - 2022), crowd counting and localization have attracted much attention of AI researchers due to its potential applicability in crowd monitoring and control, public safety, space design, interactive content delivery etc. Once delivery objectives for a system are envisaged and the premises are fixed, we can always construct manifold technology architecture that delivers the set goals. However, in the Indian context a solution of choice needs to be optimized on frugality and ease of adaptability. In this paper we report an economic and replicable application of crowd counting and interactive content delivery in museums through unbiased knowledge systems embedded in robotic museum assistants. We intend to demonstrate a robotic system that can deliver any gallery content to groups of visitors keeping special focus on the exhibits that are popular choices. Crowd counting is used here to enable the content presentation to a group of choice in an interactive way. There are some market-ready solutions available for interactive gallery demonstration by moveable robots but they require not only huge capital investment but are also of limited use within controlled environments. Our proposed design is to multiplex an existing infrastructure of surveillance system as a smart crowd counting and gallery demonstration system along with crowd management with minimum additional hardware infusion. © 2023 IEEE.

A Hand Gesture-Based Contact-less Interface for Electronic Health Records

Clinical data monitoring and storing are essential components of continuous and preventive healthcare systems. Data such as blood pressure, pulse rate, temperature, etc., can be recorded by the hospital staff daily for in-patient subjects. The usual way of noting them down is to check different parameters using various medical instruments and write it on paper with the corresponding patient's details (e.g., name, patient-id, or government identity card number). However, after the outbreak of COVID-19, there is a set of World Health Organization (WHO) guidelines to behave in public places. Ordinary people and professionals feel hesitant to touch any media even if they have some protection such as gloves and sanitizer. In this crisis, there is a natural demand for contact-less activities instead of touch-based traditional ways. Gesture-based activities might be one of the low-cost alternatives to some sensor-based systems. This paper uses a profound learning-based finger point gesture to capture writing in the air and realize it on the screen through a predictive model. Here, the proposed framework has been demonstrated as a proof of concept to record blood pressure data for multiple patients without touching any electronic screen or paper. The proposed architecture is developed based on the gesture recognition and metric learning, which have been used to recognize different digits trained from the MNIST digit dataset. The mean test accuracy is reached 99.47% on the same dataset. © 2022 IEEE.

Screening for COVID-19 among Workers Attending Medical Examinations Under Occupational Health Service of an Open Cast Iron Ore Mine in Jharkhand: A Cross-Sectional Study

Introduction: The world is going through an unprecedented phase of COVID-19. Safe and healthy workplace are integral part of Occupational Health. Unsafe work practices anywhere are a constant threat, both for our health and sustainable business of an organization. Screening involves testing asymptomatic individuals who do not have known or suspected exposure to COVID-19. There is no screening strategy to exclude anyone contagious entering workplace. Objective(s): Workplace-based testing for COVID-19 and thus help to prevent or reduce further transmission. Methodology: A cross-sectional study was conducted through screening for COVID-19 by Rapid Antigen Test (RAT) or RTPCR test (TrueNat) of 860 workers who appeared for initial and periodical medical examinations (IME / PME) under Occupational Health Service of a mine hospital in Jharkhand. Study period: December 2020 to April 2021. Chi-Square test was used for statistical analysis. Result(s): Study revealed, mean age of employees 32.09+/-8.42 years. Total 28 (3%) workers were tested COVID-19 positive, mostly asymptomatic (64%). Among COVID positive cases, 16 (57%) were in age group of 21-30 years and 25 (89%) were male. Among the symptomatic cases (n=10), 50% presented with generalized weakness. 20% workers presented with fever, 20% with cough and 10% workers had sore throat. Generalized weakness was significantly associated (p< 0.05) with COVID positive cases (x2=8.944, p=0.003). Conclusion(s): Screening is important part of health check-up to maintain safety in workplace, especially in time of pandemic. Most of the affected persons were asymptomatic and would have been caused of more positive cases at workplace, community at large. Our study emphasized the need for implementation of population-based screening programs at shop floors to prevent spread of COVID-19 among the mining workers.

Detecting COVID-19 Through Lung X-Ray Imaging: An Alternative Using Modified CNN Architecture

The arrival of COVID-19 took the very existence of human race for a toss. In countries like India, where the majority of the population is concentrated in the rural areas and are subject to an affordability and infrastructural constraint, cannot afford sophisticated COVID-19 tests. But, X-Ray is widely obtainable across both the rural and urban belts of our country and comes at an affordable cost, even free at the government hospitals. In the present research paper, we put forward a fusion-based DCGAN and CNN based neural net architecture which will generate synthetic COVID-19 infected lung X-Ray images from our fed data. Here we consider mainly two (2) output classes namely, malignant and benign. The novelty in this paper is that from the original X-Ray Image our model will generate a "predicted” image instantaneously using the DCGAN structure to understand the process of mutation. Also, the model predicts the class of the newly generated "predicted” image, whether it is COVID-19 positive or negative through the proposed CNN architecture. However, the paper that the success of deploying our model depends on the availability of the 5G network as the "predicted” X-Ray image along with the original X-Ray image of a patient needs to be transmitted to a central server from where it needs to be analyzed for further course of treatment as already specified. We have made an attempt to achieve the state of the art accuracy in our CNN model. © 2022 Scrivener Publishing LLC.

Non-profit crisis leadership during the COVID-19 pandemic in India and the United States

During extreme crises, governments' capacity is compromised, and they need support from non-profits, especially to reach the vulnerable and marginalised. Our qualitative study examines leadership response to the COVID-19 pandemic at four US and Indian non-profits;they paused their mission-related activities to focus on crisis leadership tasks. Our key findings reveal the importance of obtaining reliable information, balancing service delivery and stakeholder safety, communication with stakeholders, accepting the new normal and adopting creative solutions. These findings can inform training non-profit leaders on a number of key issues. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

CCN activation of ultrafine biogenic-WSOC under restricted anthropogenic emissions: A study over eastern Himalaya in India

The present study was conducted to investigate the potential of water soluble organic carbon (WSOC) in CCN activation under restricted anthropogenic emissions over a high altitude station, Darjeeling (27.01° N and 88.15° E,∼2200 amsl and covered with huge coniferous forests) in the eastern parts of Himalaya in India. We measured CN, CCN, and ultrafine WSOC (WSOC0.1) during April–May 2020 (COVID-19 lockdown) and compared with the normal period (April–May 2019) to investigate the relative dominance of biogenic over anthropogenic emissions to the aerosol-CCN activation. Though an expected significant decline (53%) in CN concentration was observed, CCN exhibited ∼17% increase during the lockdown period. The activation ratio (AR: CCN/CN) jumped from 0.30 during normal to 0.72 during the lockdown period. The aerosol solubility was also found to be increased during the lockdown period (∼27% decrease in the k- parameter (k)). Lockdown-WSOC was higher (1.62 μg m−3) than the normal-WSOC (1.13 μg m−3) and exhibited better regression with CCN in absence of anthropogenic emissions (Lockdown: R2 = 0.83, p < 0.05;Normal: R2 = 0.40, p < 0.05). Here we hypothesize that under restricted fossil fuel emissions during lockdown (57% decline in NOx), surface ozone was increased by 31%, that in turn favored the photochemical oxidation of biogenic VOCs emitted only from coniferous forest cover to produce huge amount of SOC. The ultrafine "biogenic-only” WSOC (under restricted anthropogenic WSOC during lockdown) participated in CCN activation actively and with higher proficiency compared to the normal period. The study bears immense importance of the role of biogenic emissions in cloud droplet formation over this part of the Himalaya under restricted anthropogenic emissions. The present hypothesis could open a new route of aerosol formation and their CCN activation under high deficiency of anthropogenic emissions. © 2023 Elsevier B.V.

(RE)THINKING SUFFERING AND MOURNING THROUGH COVID-19 PHOTOGRAPHS IN INDIA

This article offers a close textual and visual analysis of some of the most iconic photographs of the COVID pandemic's second wave in India, to examine how they evoke violence both within and outside the photographic frame, and become sites of critical reflection. The pandemic's second wave witnessed a proliferation of images in social media and online news portals representing mass deaths, corpses floating in rivers, and mass funerals executed in makeshift crematoria. Pointing out how the widely circulated photographs deployed an excess of violence to represent death as a dreaded event external to life, this article contends that the violence in these images not only evoked shock and horror but also interrupted mourning both in the private and the collective realm, furthered through violence in the images and the interruption of familiar mourning rituals for those dead. Deriving from Ariella Azoulay's idea of the ‘civil gaze' to ‘watch' photographs, the article explores how these photographs configure a space of critical reflection and responsibility towards those photographed, which uncovers the crucial biopolitical interfaces between disease, death, the state, and the precarity of citizens. It simultaneously deliberates on the role of the visual and the photographic gaze in foregrounding these intersections. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

Prediction of Unemployment using Machine Learning Approach

Unemployment is a circumstance which arises when people above a specific age are not engaged in any kind of activities which contribute to the economic welfare of the individual and country. Unemployment is becoming a rising concern which is making the daily life of people difficult. Unemployment causes poverty and depression among the citizens. Nowadays there are different opportunities in different sectors. But people are not aware of those opportunities. Different states are there where there is a lack of skilled labour whereas many states are there that have skilled labour but less opportunities. Another reason for unemployment since 2020 is the COVID-19 pandemic. We have selected this topic to spread awareness among the citizens. This work attempts to detect the states of India which are in serious need of increasing employment opportunities. We have applied the concept of Supervised Machine Learning algorithms to detect the states with the lowest employment rate. The data visualization gives a better picture of the trends in unemployment rate over years. There has been a use of different popular algorithms like Logistic Regression, Support Vector Machine, K-nearest neighbors (kNN) Algorithm and Decision Tree. In the end we have tried to find the algorithm which is going to give us more accuracy so that necessary steps can be taken for the employment of the eligible and deserving people. © 2022 IEEE.

iConDet2: An Improved Conjunctivitis Detection Portable Healthcare App Powered by Artificial Intelligence

Conjunctivitis is one of the common and contagious ocular diseases which affects the conjunctiva of the human eye. Both the bacterial and viral types of it can be treated with eye drops and other medicines. It is important to diagnose the disease at its early stage to realise the connection between it and other diseases, especially COVID-19. Mobile applications like iConDet is such a solution that performs well for the initial screening of Conjunctivitis. In this work, we present with iConDet2 which provides an advanced solution than the earlier version of it. It is faster with a higher accuracy level (95%) than the previously released iConDet. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Facial recognition lock technology for social care settings: A qualitative evaluation of implementation of facial recognition locks at two residential care sites.

Background: There is limited literature on security and access for social care settings despite policy highlighting importance, and no published research exploring facial recognition lock technology (FRLT) for potential improvements. This study explored FRLT device implementation, use, barriers and benefits. Methods: One residential care home with 43 older adults and 68 staff members (Site A), and one supported living facility caring for six individuals with mental health issues with 18 staff members (Site B) were provided with FRLT for six months. Nine pre-implementation staff interviews explored existing access and security perceptions. Ten post-implementation staff interviews and one staff focus group were conducted; all were analysed using content analysis to understand, alongside process mapping, the use and impact of the FRLT. Interview participants included site care staff and other visiting healthcare professionals. We additionally report feedback from the technology developers to demonstrate impact of industry-academia collaboration. Results: Pre-implementation interviews highlighted issues with current pin-pad or lock-box systems, including; code sharing; code visibility, ineffective code changes, security issues following high staff turnover, lack of efficiency for visitors including NHS staff and lack of infection control suggesting requirement for innovation and improvement. Pre-implementation interviews showed openness and interest in FRLT, although initial queries were raised around cost effectiveness and staff skills. Following implementation, good levels of adoption were achieved with 72% and 100% (49/68 and 18/18) of staff members uploading their face at the two sites, and 100% of residents at Site B using the system (6/6). Additionally, Site B made a positive procurement decision and continues to discuss wider rollout. Post implementation interviews suggested FRLT was useful and acceptable for improving security and access. Benefits identified included staff/visitor time saving, enhanced security, team ease of access, resident autonomy and fewer shared touch points. Integration was suggested including with fire alarm systems, staff clocking in/out, and Covid monitoring to improve usefulness. The developers have since responded to feedback with design iterations. Conclusion: We identified concerns on security and access in social care settings, which warrant further exploration and research. FRLT could increase resident autonomy and reduce staff burden, particularly considering frequent multi-agency health and care visits.

COVID-19 impact on Global Network Performance

The outbreak of the Covid-19 pandemic has created a profound impact on every sector of our life. The most significant effect of this global pandemic is "global lockdown.>> The lockdown has brought many changes in our lifestyle. One of the substantial changes in the usage of network connectivity. Many people have started to work from home, the number of online learning other uses like the OTT, social media, etc., have increased. It's observed that internet traffic has significantly increased by 25%-30%. In this paper, the authors have analyzed the global network connectivity performance concerning the changes in usage. They examined various service providers' or companies' feedback to these unprecedented conditions. The authors used secondary research methodology for quantitative analysis to understand the increase in usage. Also, this pandemic is opening up new opportunities for the service provider as this pandemic is accelerating remote working, so the service provider is going for more and more automation which reduces the field headcount and the cost. Also, operators have started to offer new collaboration apps, video conferencing tools, and learning platforms which open up new business opportunities. Many new businesses have begun to transform their business in digital, which also opens up a unique opportunity.

Critical Enablers that Mitigate Supply Chain Disruption: A Perspective from Indian MSMEs

The study attempts to identify the critical enablers that can mitigate supply chain (SC) disruption and model the interconnectedness among them in the context of the Indian Micro, Small and Medium Enterprises (MSMEs). The supply chain in many Indian MSMEs has been seriously affected by the COVID-19 pandemic, bringing forth the need to identify avenues that can mitigate the disruptions. This study conducts a two-stage qualitative interview and a structured interview with MSME owners. Domain experts are associated with the automotive, aerospace and design services industries. Based on their responses, we have identified seven major critical enablers specific in the context of Indian MSMEs. To model the interconnection among these factors, we have used the ISM (Interpretive Structural Modelling) approach. Results suggest that ‘top management support' is the most crucial enabler in the hierarchy. Further, we find that if the supply chain is designed efficiently with redundancy in mind and the culture of the MSME remains conducive, advanced forms of ‘multi-sourcing' and differentiated logistics can be explored to mitigate supply chain disruption. © 2022 XLRI Jamshedpur, School of Business Management & Human Resources.

Does expanded access to primary prophylaxis with G-CSF decrease the burden of febrile neutropenia?

Category: Management/measurement of side-effects of treatment (acute or late), including patient-reported outcome measures (PROMs) Purpose: Guidelines recommend primary prophylaxis (PP) with haematopoietic colony stimulating factors (CSFs) in chemotherapy with a >=20% risk of febrile neutropenia (FN). During the COVID-19 pandemic, guidelines temporarily supported routine use of G-CSF as PP for intermediate risk regimens. Our retrospective real-world data compares hospital admissions for FN during a period of expanded access (June to December 2020) against baseline use (June to December 2019) in a district general UK hospital. Methods and materials: The process measure was the proportion of patients prescribed PP with G-CSF when initiating a new intermediate/low-risk regimen/month. The outcome measure was the monthly rate of hospital admissions for FN in intermediate/low-risk regimens. Statistical process control (SPC) charts and chi-square tests were used for analysis. Result(s): Use of G-CSF as PP showed statistically significant special cause variation on SPC p-charts consistent with policy change. Median PP prescription rate in June to December 2019 was 0.9% (interquartile range (IQR) 0-2.6%) and June to December 2020 was 34.8% (IQR 29%-43%). Monthly G-CSF prescriptions for all indications was a median of 3% (2019) versus 70% (2020). However, the trends in admissions for FN were stable on SPC p-charts with a median monthly event rate of 0.63% in 2019 and 0.66% in 2020. Summary statistics showed 12 events/698 unique patients in 2019 (1.72%) and ten events/618 patients in 2020 (1.62%), (p=0.8). Conclusion(s): Despite significantly increased use of PP with G-CSF for intermediate/low-risk chemotherapy, the burden of hospitalisations for FN remained unchanged and was lower than expected. Copyright © 2022

2-Deoxy-D-Glucose: The Molecule and Its Recent Perspective

D-Glucose, in its normal form, is known to most of us. Interestingly, just by replacing an -OH group with a hydrogen, we get 2-deoxy-D-glucose (2-DG) which has excellent medicinal properties. An interesting observation related to glycolysis led to the use of 2-DG as an anticancer drug. Recently, there has been sufficient evidence to support the efficacy of 2-DG as an anti-Covid medication. © 2022, Indian Academy of Sciences.

Gas Tragedy and COVID-19 Vulnerabilities: An Analysis of Health Infrastructure in Bhopal, India

Cities are thought to be the adobe of all services and amenities. But, the public health emergencies like COVID-19 exposed the lacuna of the city systems worldwide. Although some parts of the cities appear to be well served with public utilities and affluence, there remain many deprived spaces where people are more vulnerable to public health emergencies. Bhopal city (1.79 million;2011) is the capital of Madhya Pradesh State and one of the fast-growing metropolises in India. The city has already experienced the worst gas tragedy, which has demonstrated the stress on the city system;now, COVID-19 has again brought the city to the same door. In this paper, an attempt has been made to analyze the spatial spared of COVID-19 and explore the relationship between the Bhopal gas tragedy and COVID-19 vulnerabilities. The paper also explores the status of available health infrastructure within the city. A review of the draft Bhopal Development Plan-2031 has been done to determine future health infrastructure provisions. Finally, an attempt has been made to find out the role of Bhopal’s Integrated Control and Command Center (ICCC), established under the Smart Cities Mission, in reducing the impact of the COVID-19 pandemic. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Designing of Latent Dirichlet Allocation Based Prediction Model to Detect Midlife Crisis of Losing Jobs due to Prolonged Lockdown for COVID-19

The sudden outbreak of the virus COVID-19 has created a pandemic situation worldwide. Humankind has not experienced such a danger caused by this disease in the past hundred years. Apart from all the health issues, the pandemic has created an immense impact on social life, economics, mental peace, and all aspects of human life. Prolonged quarantine is creating uncertainties;death tolls are creating fear. According to the World Health Organization, this public health emergency is likely to create anxiety, loneliness, depression, fear of losing jobs, being economically unstable, and committing suicide. In our present discussion, we prepare a statistical record using data collected from all over the world to find the intensity of mental disorder caused by this pandemic. Now we aim at finding the polarity of the specified term used by social media users. We aim to formulate a highly efficient mechanism that will detect depressive sentences more accurately. In our work, we try to formulate an optimal mechanism implementing the Latent Dirichlet Allocation approach to modify our findings and prove through a comparative study that depression affects the highest among people age 40−50. We experience that this age group is highly devastated in fear of losing jobs because of to this pandemic. The standard psychiatric symptom of lack of self-dignity and self-confidence that can happen to a human at the middle age is proliferated due to extended lockdown and its after effects. There is much research in sentiment analysis, which shows us the impact of COVID-19 in recent days. Surprisingly, recognizing symptoms of the midlife crisis in the pandemic situation of COVID-19 is yet to achieve. © 2022 Elsevier Inc. All rights reserved.

“The Long Wait for Homecoming”: Looking at the Lives of Oil Field Wives in COVID-19 Times

The migration of Indians to Gulf countries can be traced back to the early twentieth century. With the discovery of oil in the region, Indian laborers began to migrate for a better livelihood, which also served as a valuable source of income for the country. Oil field workers who have migrated from India to the Gulf region are employed in oil rigs located in remote desert areas. They include both skilled as well as unskilled laborers and are employed in high-risk field-based jobs wherein family is not allowed. They work as international commuters and return home on a rotational basis at regular intervals. They constitute transnational families wherein most rely on telecommunication to connect with their family members in India and fulfill their social obligations. The economic, political, and sociocultural impact of migration has been studied by social scientists in substantial detail from the perspective of homeland as well as host land, but not much has been discussed about the experience of wives/spouses of oil field workers who are left behind at home even though their population is fairly large in India. Available data on the social and psychological impact of international migration suggest that such migration histories have both positive and negative impacts on transnational families. The COVID-19 pandemic, which affected the global scenario, did not spare them either. This article is a part of a meso-level study wherein a group of women residing in different parts of India was interviewed regarding their experience as wives of oil field workers in Gulf countries. Their husbands could not return home due to travel bans imposed by the Middle Eastern countries owing to the pandemic. This article attempts to look at significant issues pertaining to family and international migration to Gulf countries in the COVID times. © 2022 SAGE Publications.