Spatio-temporal variation in air quality and unexpected pollution levels during the lamp event over the Indo-Gangetic Plain in the first wave of the COVID-19 pandemic†

This study focuses on spatio-temporal variation in air quality caused by the nationwide lamp event of nine minutes named as the "#9 pm 9 min event” during the historic lockdown in the first wave of the COVID-19 pandemic across India in the year 2020. Due to the Janta curfew (March 22, 2020) and the lockdown (from March 25 to May 31, 2020), the concentration of pollutants like fine particulate matter (PM2.5), trace gases such as nitrogen dioxide (NO2), sulphur dioxide (SO2), and carbon monoxide (CO), and volatile organic compounds (VOCs), namely benzene and toluene reduced significantly in the six most polluted cities, i.e., Agra, Ghaziabad, Lucknow, Meerut, Noida and Varanasi in the Indo-Gangetic Plain (IGP), while the concentration of ozone increased. A maximum decline in PM2.5 concentrations was observed in Noida (43%), followed by Ghaziabad (39%), Lucknow (33%), Meerut (25%), Agra (23%) and Varanasi (5%) during phase-1 (P1) of lockdown in comparison with the period before lockdown. Similar to PM2.5, other pollutants also decreased at all sites under consideration. This event (lamp event, #9 pm 9 min event) offered an exclusive opportunity to study the effects of burning oil lamps or candles in an open environment with minimum industrial and vehicular emissions. The decline in pollution levels reversed in the wake of the lamp event, which resulted in a sharp increase in pollutant concentrations, except for ozone levels. PM2.5 mass concentrations were significantly correlated with benzene (0.7) and CO (0.7), whereas toluene was moderately correlated with benzene (0.5). Principal component analysis (PCA) also revealed that increases in the concentrations of PM2.5, NO2, CO, benzene and toluene were largely due to oil-based emissions. The study points out that future policy initiatives should take into account the changes in air quality which were seen during the lamp event. These changes have reinforced the necessity for comprehensive action across all emission sectors to achieve significant air quality improvements. It is also advised that people should strictly follow the guidelines issued by the government during such events. © 2023 The Author(s).

Ethical and Sustainable Perceptions on Cloud Kitchen Business- A Study of Consumers and Stakeholders during the Covid-19 Pandemic

Cloud kitchen has evolved as a popular means to meet the growing demand of home-delivered food during the pandemic. The purpose of this research is to gauge the perception of consumers as well as stakeholders about the ethical correctness of cloud kitchen models of business and whether the cloud kitchen model is sustainable or not. The manuscript is primary and quantitative in nature. The data was collected during the period of pandemic from the respondents living in Delhi and Kolkata. The research focuses on the Utility, Rights, Fairness and Care constructs of ethics to gauge the perception of respondents about cloud kitchen business including its sustainability and challenges. The analysis was done running ANOVA and binomial distribution. The consumers as well as stakeholders and employees appear to be positively responding on the question of the cloud kitchen model being ethically correct on the 4 constructs and they seem to agree that Cloud Kitchens are sustainable. Very little existing literature is available on the ethical and sustainability aspects of cloud kitchen model with Utility, Rights, Fairness and Care constructs. Thus, it is the first paper of its kind and is expected to add to the existing body of literature. ©Copyright IJHTS.

Enhancing compliance rate of hand hygiene before and after Covid-19: An interference analysis in Abu Dhabi, UAE hospitals

Hand hygiene (HH) is a crucial factor for reducing Healthcare Associated Infections (HAIs) in the hospital setting. The current analysis was created to create an intervention methodology to enhance hand hygiene compliance among hospital personnel in a healthcare setting. Covid-19 disease epidemic has additional stressed the need for world-wide development in hand hygiene compliance by the healthcare personnel. Healthcare Associated Infections have been a hot issue for several time periods and Healthcare Associated Infections are the most common adverse results due to the delivery of medical care and treatment. There is unanimity that hand hygiene is the extremely successful way to avoid healthcare associated infections. As healthcare systems fluctuate widely, prevention approaches must be designed appropriately. Hand hygiene, however, remains relevant in all settings, and World Health Organization (WHO) is strongly endorsing alcohol-based hand rubs to interrupt transmission. Nevertheless, very minimal compliance rate amongst the healthcare staff have been reported worldwide. Infected surfaces, especially those that are touched repeatedly by the patient's surroundings, act as reservoirs for pathogens and cause towards pathogen transmission. Therefore, healthcare disinfection requires a thorough approach whereby several strategies may be applied together, risk-based methodologies, to decrease the possibility of HAIs for the patients. In this paper more than 200 articles have been studied from 2016 to 2021 time period and various surveys have been conducted to analyze hand hygiene intervention and studied the various factors involving the patient's situation, medication management behavior of several units, and the type of healthcare employees during and before the Covid-19 pandemic. Based on this study, we evaluated overall hand hygiene compliance rate including the intake of hand wash liquid agent, alcohol-based hand rub (ABHR), the paper wipes, medical waste consumption and personal protective equipment's (gloves, masks etc.) before and after Covid-19 intervention to improve the hand hygiene compliance rate in Abu Dhabi hospitals. © 2023 Author(s).

Yoga and Physical Exercises as Immunogenic Fortifiers for Coronavirus Vaccine Responses

Background and aim: Coronavirus has emerged as a pandemic leading to pneumonia and death in susceptible populations, especially in immunocompromised hosts and the elderly. Though national governance and drug firms work in cohesion to develop vaccines, the fear and anxiety towards misconceptions about vaccine efficacy and adverse effects lead to underutilization of the vaccines. Though known for its immunogenic responses against infections, conservative lifestyle modifications such as Yoga and physical exercise's synergistic effects with coronavirus vaccine's immunogenic response remains unknown. Methods: We administered a systematic search on the contemporary evidence investigating the immune responses of physical activity or Yoga in three databases: PubMed, Embase and Web of Science. In the present review, we reviewed the empirical evidence that explored the role of Yoga and physical exercise as an immunity booster and extrapolated their effects against coronavirus infection. Results: We found sixteen articles emphasizing physical activity to augment immune responses towards Coronavirus. Discussion and Conclusion: Considering the contemporary evidence, complementary therapies such as Yoga or physical activity are speculated to improve the influenza vaccines' immune responses. We recommend that Yoga and physical exercises be affordable, practical and effective strategies that could be advocated along with vaccination doses. We hope the present review may help readers and policymakers explore complementary therapies that could be administered as adjuncts to vaccine-mediated immunity in combating the deadly pandemic. © 2023 by authors, all rights reserved.

Prognostic Value of Elevated Lipase in Pancreatitis versus Non Pancreatitis Hyperlipasemia (NPHL) due to Non-Malignant Causes

Introduction: While elevated lipase is typically used to diagnose acute pancreatitis, it has also been associated with other critical disease states including sepsis, COVID-19, bowel obstruction, and trauma. In this study we compared outcomes of patients with elevated lipase who had pancreatitis and NPHL. Method(s): Retrospective analysis was performed on all patients who presented to the Emergency Department between February 2016 and August 2020 with lipase >= 3x the upper limit of normal. Patient demographics and past medical history, including active cancer, were noted. Patient outcomes were followed through November 2021. If applicable, dates of death were also documented. Result(s): 414 total patients were included in this study. Upon initial evaluation, 305/414 (74%) were diagnosed with acute pancreatitis (AP) and 109/414 had NPHL. The age (54 617 vs. 58 618, p=0.0220), Sex (male 164/305 vs. 49/109, p=0.1194), and BMI (28.9 67.4 vs. 25.8 64.6, p=0.0066) were compared between the AP and NPHL groups. The serum lipase in the AP and NPHL group were respectively 1471 61070 vs. 605 6555 (p< 0.0001). The most common causes of NPHL were sepsis (10/109;9%) renal failure (7/109;6%), GI bleed (5/109;4%), and bowel obstruction (5/109;4%). The NPHL group had higher rate of malignancy (29/105;28%) compared to those with AP (35/305;11%, p< 0.0001). NPHL patients without malignancy had a higher mortality rate (63/80;80%) compared to those without malignancy in the AP group (17/270;6.3%, p< 0.0001). The most common malignancy in patients with AP was breast (6/35;17%, vs. 3/29;10%, p=0.4943). In NPHL, the most common malignancies were pancreatic (4/29;14%, vs. 3/35;9%, p=0.6920) and bowel malignancies (4/29;14%, vs. 4/35, 11% p51.0000). Conclusion(s): Patients with NPHL without malignancy have higher mortality than those with pancreatitis despite lower serum lipase levels. A limitation of our study is the difference between age and BMI of AP versus NPHL patients. Whether this impacts the prognostic relevance of NPHL on survival need to be explored in future studies.

Opportunities And Threats In Digital Education

COVID-19 pandemic has caused havoc worldwide. India is also facing challenging circumstances as the figure of infected/positive cases is rising day by day. This study deals with the development of education: Post COVID-19. This paper will help to understand "Digital Education: Opportunities and Threats". The Corona virus has exposed emerging vulnerabilities in learning systems all over the world. A lot of relevant literature was explored to confine the essence of continued learning during these exceptional times. Educational organizations all over the world are moving towards online/Digital learning. This paper also proposes digital education as an urgent need in this lock downs times and social distancing due to COVID-19 pandemic. It also provides a powerful stage for further research. The use of digital technology in education is experiencing a tremendous boom in education sector with cost effectiveness. Although it is unclear whether technology will plug all of the holes in the Indian Education system but it seems that technology is playing a major role in education interventions. Due to advancements in technology, accessibility of low-priced laptops/mobiles, wireless equipments, and related communications setups signs both opportunities and challenges for learning organizations and their faculty and students. Digital Education has potential that can produce knowledge workers. The government has analyzed that ICT sector has important role in education due to that many programmes such as NEOR, NMEICT, NKN, Eklavya, NPTEL, and NROER has been launched. Digital Education has bring success in the field of education but still there area number of challenges in most of Indian institutes like shortage of quality teachers, deprived quality of research, and deprived quality of training etc. Digital Education is overall very beneficial for the students of country like India.Copyright © 2020 Ubiquity Press. All rights reserved.

Impact of Green Finance on National Economic Growth During the COVID-19 Pandemic

This study explores the impact of green financing on economic growth during the COVID-19 pandemic. Using data from 30 countries, we find that green financing has a positive impact on economic growth. This finding has both theoretical and practical implications. © 2022, Asia-Pacific Applied Economics Association. All rights reserved.

Diagnostic Approaches for Covid-19: Present Status and Future Prospects

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.

Recent Updates on Bacterial Secondary Metabolites to Overcome Antibiotic Resistance in Gram-Negative Superbugs: Encouragement or Discontinuation?

The rapid spread of COVID-19 has dramatically changed our perspective about how we should be well prepared for upcoming health disasters in the future. Like COVID-19, the world does not seem prepared to fight the slow-moving pandemic, i.e., antimicrobial resistance (AMR). At present, more than 7, 00, 000 people per year across the globe succumb to drug-resistant infections. According to several reports, if we fail to respond, AMR could lead to the loss of ten million lives and trillions of money by 2050. Among the different pathogens affecting human health, the World Health Organization (WHO) has recently announced a priority list of drug-resistant bacteria to pave the way for the development of new antibiotics. Gram-negative bacteria such as Escherichia coli, Klebsiella pneumoniae, Acinetobacter baumannii, and Pseudomonas aeruginosa are the most notorious ones and are responsible for the majority of healthcare-associated infections. These pathogens come under the critical threat category because they express resistance to all of the current antibiotics. The modern combinatorial chemistry approaches and chemical genomics have been unsuccessful to provide enough new antibiotics. In stark contrast to this, natural products have been gifted with remarkable chemical diversity and biological activity. Our modern antibiotic armamentarium was built from microbes' natural products, especially Streptomyces spp. and Bacillus spp. isolated in the golden era. Today, the antibiotic discovery pipeline has almost dried up, in part due to the rediscovery of already known compounds from bacteria, and no new classes emerged from bacteria until recently. These novel natural antibacterial agents from bacteria resurged a spark in the exploitation of bacteria to find new chemical entities. This chapter mainly focuses on natural antimicrobials and adjuvants isolated from the bacterial domain in the last two decades, i.e., from 2001 to 2020, and their status to fight drug-resistant Gram-negative superbugs. We have also described briefly the discovery of synthetic compounds based on natural scaffolds. In conclusion, the bacterial natural products comprise a goldmine to fight superbugs, and future research should be focused on exploring new antimicrobials from bacterial diversity. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2022.

Comparative Study of Molecular Docking, Structural, Electronic, and Fukui Function Studies on Favipiravir and its Newly Designed Derivatives (Potential Inhibitors) for COVID-19 Protease

Favipiravir is an antiviral medication currently being trialed as a COVID-19 treatment. These results motivate us to develop new species (possibly drugs) from favipiravir, perform comparative molecular docking, and reexamine their biological and pharmacological activities. Detailed quantum chemical research on favipiravir and its newly designed derivatives has been carried out with the help of DFT/B3LYP/6–311 + + G (d, p). In the present work, the structure of favipiravir has been modified and 12 new species have been modeled (all species are inherently stable because no virtual frequency is found during the vibration analysis). Reactivity of all species using various descriptors (local) such as Fukui function, local softness, electrophilicity, and global, i.e., electronegativity, hardness, HOMO–LUMO gap, etc. of the same are calculated and discussed. In silico studies such as molecular docking of all species and complete quantum chemistry studies suggest that four of them may mitigate the effects of the COVID-19 protease. © 2023 Wiley-VCH GmbH.

A Novel Machine Learning Classification Model to Analyze the COVID-19 Pandemic's Impact on Academics: Sentiment Analysis Approach

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.

Temporal Patterns of Population Level Help Seeking Behaviours During Covid-19 Pandemic in India: an Exploratory Study

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.

Assess the Burden, Stress and Coping Abilities among Caregivers of Covid-19 Patients

Background: Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered coronavirus. Most people infected with the COVID-19 Virus will experience mild to Moderate respiratory illness and recover without requiring special treatment. Older people and those with underlying medical problems like cardiovascular disease, diabetes, chronic respiratory disease, and cancer are more likely to develop serious illness. The Covid-19 virus spreads primarily through droplets of saliva or discharge from the nose when an infected person coughs or sneezes, so it is important that you also practice respiratory etiquette (for example, by coughing into a flexed elbow). Aim and ObjectivesThis study aim and objectives are to assess the burden, stress coping and their level of significance among caregivers of COVID- 19 patients. Methodology- A descriptive study was done on 60 caregivers of COVID-19 patients in selected hospitals at Meerut. The purposive sampling technique was used. Caregivers burden, stress and coping abilities were assessed by using caregivers burden scale (Zarit-22 interview scale), Kingston caregivers stress scale and modified Jake Sims coping scale respectively, Result-The result showed that mean score for burden, stress and coping with SD for caregivers of COVID-19 patients was 47.00+/-07.008,29.20+/-4.202 and 46. 28+/-7.06 and correlation of patient with COVID-19was (0.273) suggesting a negative significant correlation between the burden, stress and coping abilities 'r' value was less than table value (0.273) with df 58 at (0.05) level of significance. Conclusion(s): there was no significant association between level of burden, stress and coping abilities among caregivers of COVID-19 patients and demographic variables. It is inferred that there is moderate to severe level burden, mild stress & good coping abilities is higher among caregivers of COVID-19 patients.Copyright © 2020 Ubiquity Press. All rights reserved.

Coronavirus Disease 2019 (COVID-19): Current Situation and Therapeutic Options

Coronavirus disease 2019 (COVID-19) is defined as an illness caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). COVID-19 was first reported in the Wuhan, China, in late December, 2019. The World Health Organization (WHO) declared COVID-19 a global emergency on March 11, 2020. COVID-19 was rapidly transmitted and caused infection in 21,294,845 people and 761,779 deaths in more than 213 countries worldwide till August 16, 2020. United States of America (USA), Brazil, India, Russia Federation, Peru, Mexico, Colombia, Spain, France, Italy, Germany, and United Kingdom (UK) stand top COVID-19 affected countries in the world. The high transmission rate of COVID-19 might be due to large viral incubation time (2-14 days) and some modifications in the spike glycoprotein. Currently, effective drugs or vaccines are not developed for the treatment of novel coronavirus. However, few antibiotics like hydroxychloroquine and remdesivir have been currently used for the treatment of COVID-19 infection. Several collaboratives are working together for developing an effective and safe vaccine against COVID-19 and few vaccines are under clinical trial. Scientists are also working on plasma therapy and monoclonal antibodies. Nowadays, plasma therapy is considered the most effective treatment against COVID-19 and some promising results have been achieved. This review focuses on several therapeutic options for COVID-19, such as anti-viral drugs, vaccines, plasma therapy, and monoclonal antibodies. This review also covers the current situations of COVID-19 in the world. This review is about COVID-19, which will be beneficial to researchers for the development of potential treatment against it.Copyright © 2021 Bentham Science Publishers.

Monitoring Engagement in Online Classes Through WiFi CSI

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.

Effects of trigger events on innovation behaviour: insights from the data collected from construction professionals during COVID-19

During the COVID-19 pandemic, several instances of innovation were reported in construction and other sectors, consistent with previously noted spikes in innovation activities during crises and environmental perturbations. Yet the behavioural mechanisms and factors leading to changes in the innovation behaviour of actors under environmental perturbation are not adequately understood. This paper studies such behavioural mechanisms and factors, building on the Excitable Innovation Behaviour Model (EIBM), which explains the voluntary or coercive change in the innovation behaviour of actors in terms of their stable state needs and excited stated needs. The findings build on data collected through an online survey (N = 266) and interviews (N = 14) during the COVID situation. The results show that environmental perturbations can trigger both an increase and decrease in innovation activities. Actors' network dependencies, motivation, and years of experience influence their innovation behaviour. Environmental perturbation triggers accelerated alignment and shared prioritization of the needs of the different stakeholders, resulting in commitment and timely actions towards innovation from each stakeholder. Actors' ability and financial stability at the time of the excitation trigger mediate their innovation behaviour, revealing similarities and differences between EIBM and Fogg's Behavioural Model of persuasion. The grounding of EIBM in behavioural theories makes it potentially generalizable and compatible with other behavioural models and theories on innovation. The underlying state-change mechanisms in EIBM also make it amenable to developing a parametric and computational model of innovation adoption and diffusion. The research insights will inform innovation management strategies, including technology adoption roadmaps in the construction sector. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Legionella Myocarditis Masquerading as Dual Chamber Cardiac Arrhythmia

Background Legionella pneumonia is a rare cause of myocarditis. Case 64-y.o male with CAD and PCI to LAD, DM and HTN presented to ER with mental status changes. On exam he was febrile and hypoxic.Presenting rhythm was Afib with frequent bouts of sustained and non-sustained stable posteroseptal VT treated with amiodarone and mexilitene. With right lung infiltrate on CXR and elevated WBC count, antibiotics were initiated for pneumonia. SARS COV-2 Ag and Influenza A & B was negative. Urine Ag for legionella was positive and was promptly treated with Levofloxacin. Coronary angiogram prior to discharge showed non-obstructive CAD. Decision-making Legionnaires' disease with myocarditis was suspected. Patient underwent CMR with late gadolinium enhancement (LGE) and Rest 82Rb perfusion and 18F-FDG PET/CT with high-fat dietary preparation scan for evaluation of legionella myocarditis. CMR revealed LVEF of 46%, with LGE and PET findings as described in the Figure. He was initiated on solumedrol for ongoing inflammation after completion of antibiotic therapy for Legionella pneumonia. Conclusion Our case highlights a systematic approach to differential diagnosis and use of multimodality imaging in legionella myocarditis presenting with dual chamber arrhythmia. There was good correlation between LGE inflammation/scar location and origin of VT, as well as active inflammation demonstrated by FDG PET imaging. The patient was successfully treated with antibiotics, steroids and anti-arrhythmic drugs. [Formula presented]Copyright © 2023 American College of Cardiology Foundation

Aimed Robot: Autonomous & IoT Controlled Medical Assistance Robot

This paper describes the emerging role of robots in health care and integrated environments with special concerns related to the management and control of the spread of novel coronavirus 2019. The primary use of such robots is to reduce human interaction and ensure cleanliness, fertility, and support in the hospitals and facilities such as isolation. This will lead to a reduction in the life-threatening risk for medical professionals and physicians who have played a significant role in the management of infectious diseases like coronavirus. The purpose of this work is to highlight the importance of medical robots in general and to link their use in the field of medical assistance so that hospital administrators can use the medical robots for different treatment processes. The work involves the design and development of an AUTONOMOUS and IoT CONTROLLED MEDICAL ASSISTANCE ROBOT (AIMED), which is designed as a potential answer for any irresistible ailment, particularly for Coronaviruses Outbreak. AIMED ROBOT is utilized to limit individual to-individual contact and to guarantee cleaning, sanitization and backing in emergency clinics and comparable offices, for example, food and medication conveyance in isolate emergency clinics/offices. Voice communication can also be established between the control room and patient through a wireless network. This data is sent to the doctor and staff using a communication network that helps in monitoring the patient's condition without human interaction. Hand Sanitization, food delivery and waste collection system are also provided in the robot for quarantine zones. This is despite the popularity of telemedicine, which also applies to similar situations. In fact, the recent success of the Korean and Chinese health sectors in gaining effective control of the coronavirus epidemic would not have been possible without the use of state-of-the-art technology. Background(s): In the quick advancement of innovation, there are numerous sorts of robots with different details and capacities. The AIMED Robots are being developed for hospitals to deliver medicines, food and for taking live data from the patient directly. A few issues are confronted in regards to the limitation of explicit places around and inside the clinic because different robots were utilizing landmark recognition. Moreover, the issues faced when the robot is to convey things to any patient from any place should be taken care of. Objective(s): The objective of this work is to highlight the importance of medical robots in general and to link their use in the field of medical assistance so that hospital administrators can use the medical robots for different treatment processes. Method(s): The work involves the design and development of an AUTONOMOUS and IoT CONTROLLED MEDICAL ASSISTANCE ROBOT (AIMED), which is designed as a potential answer for any irresistible ailment particularly for Coronaviruses Outbreak. Result(s): AIMED Robot goes through three testing stages. In the final stage, one complete embedded system is designed by embedding each tested sub-system and then this final embedded system is tested. All the project goals, which were planned as 'Solution to Problem Statement', have been achieved properly. Conclusion(s): This paper provides an overview of the robotics and therapeutic potential of robotics in specific environments with COVID-19 epidemic control. The AIMED robot introduced in this paper is a piece of emergency clinic and care focus computerization framework. Multiple patients are placed for stop-over and doctor's prescription regarding patient health. It can be very useful to counter infectious diseases like SARS, MERS or Covid-19 etc. This work confirms that the introduction of medical robots has significantly increased the safety and quality of health care systems compared to manual systems due to the digitalization of health care.Copyright © 2021 Bentham Science Publishers.

Psychological dimension of COVID 19 on farmers in rainfed regions of India

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.

Mucormycosis infection associated with global COVID-19 pandemic - an institutional histopathological study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) in the recent times have instilled signs of immunosuppression globally which has further precipitated increasing range of opportunistic infections. Mucormycosis is a distressing opportunistic fungal infection with a high incidence and is the third commonest acute invasive infection following candidiasis and aspergillosis. The aim of the present observational study is to delineate the enigmatic histopathological profile between mucormycosis cases seen prior to pandemic (PPM) and pandemic associated mucormycosis (PAM). MATERIAL AND METHODS: Tissue archives of 105 histopathologically diagnosed cases of mucormycosis were included and analysed for demographical details and histopathological parameters like fungal load and localization, granuloma formation, necrosis, inflammatory infiltrate and tissue invasion. RESULTS: 0ut of 105 included cases, 11/105 (10.48%) were reported PPM and 94/105 (89.52%) PAM. Among 94 cases of PAM, 51/94 (54%) cases also showed COVID-19 positivity, while 43/94 (46%) did not. Of all the histological variables, increased fungal load and necrosis were observed in PAM relative to PPM cases. CONCLUSIONS: The histopathological variables like fungal load, necrosis, granuloma formation and tissue invasion, could help the clinician in assessing the clinical status at the time of tissue diagnosis and improve the treatment accordingly.