Association of Interleukin-6 (IL-6) and High-Density Lipoprotein Cholesterol (HDL-C) with Disease Severity of Coronavirus Disease 2019 (COVID-19)

Introduction: IL-6 is the key molecule of cytokine storm in COVID-19. Dyslipidemia is a common complication in patients with Coronavirus disease 2019 (COVID-19), but the association of dyslipidemia with the severity of COVID-19 is still unclear. In this study, we aimed to investigate the biochemical alterations of High-Density Lipoprotein Cholesterol (HDL-C), and Interleukin-6 (IL-6) in COVID-19 patients and their relationships with the disease severity. Material(s) and Method(s): We conducted a retrospective single-institutional study of 99 consecutive confirmed cases of COVID-19. Serum IL-6 and HDL-C concentrations, demographic and clinical profile were collected during hospital stay. Duration of study was from September 2020 to August 2021. Descriptive statistics were applied to summarize the demographic data. Results are reported as mean with standard deviation. Receiver operating characteristic curve (ROC) analysis was used to compare biochemical markers. Result(s): Serum HDL-C levels had a significant positive correlation with SpO2 with correlation coefficient r = 0.589. Serum IL-6 had a negative correlation with SpO2 with correlation coefficient r =-0.632. The AUC for IL6 and HDL-C in predicting COVID severity is 0.982 and 0.985 respectively. Conclusion(s): HDL-C is decreased and IL-6 is increased with the disease severity.Copyright © 2023, Dr Yashwant Research Labs Pvt Ltd. All rights reserved.

Social Distance Alerting System Using Machine Learning

The increase into the Corona virus pandemic led to a higher death rate globally. The best way to prevent getting sick is to keep yourself physically or socially far. Our project provides an approach for physical isolation revealing using machine knowledge toward indicate the necessary space to be maintained to decrease the collision of the corona virus contagious widespread spread. By analyzing a videotape provide for from the camera, the detect apparatus be fashioned in the direction of notify individuals toward maintain a out of harm's way aloofness on or after one an additional. The open-source person recognition pretrained model, YOLO3 algorithm, was utilized to recognize people using the video frame from the camera as input. YOLO3 has the benefit of mortal a lot quicker than further algorithms, at a halt maintain exactness and meets the real-time requirements for person detection. In order to calculate distance from the 2D plane, the video frames are afterwards transformed into top-down views. Estimated distance between individuals and any non-compliant pair of individuals within the display is indicate by means of a red colour edge and stripe, the moderate distance is represented with orange colour and the safe distance is represented by green colour frame. The suggested technique was examined lying on a pre record videotape as well as on the live video feed of persons walking on the road. Additionally an alarm sound is provided to notify the persons. The outcome show that the planned strategy is ready toward sees the societal separation trial among many populaces withinthe videotape. © 2022 IEEE.

Influence of metal oxide catalyst on co-pyrolysis of biomass and COVID-19 waste.

The disposal of waste generated by the COVID-19 pandemic is still a challenge to the government in most countries. The present study shines its light on the catalytic effect of metal oxide on converting COVID-19 waste i.e. used face masks into valuable products through co-pyrolysis. The co-pyrolysis trial was carried out for a mixture of waste face mask (WFM) and Moringa oleifera (MO) biomass at a constant temperature of 450°C for 15 min of resident time. This investigation focuses on studying the catalytic effect of calcium oxide (CaO) on the by-products of the pyrolysis process. From the FT-IR studies, it is observed that the CaO catalyst assisted to reduce oxygen as well as sulphur and carboxylic acids in the bio-oil due to its strong basic nature. The FE-SEM images suggest the increase in porous structure with catalytic pyrolysis (CP) char compared to non-catalytic pyrolysis (NCP) char. The catalytic activity of CaO increased the alcoholic content with a reduction in aldehydes and ketones in the bio-oil. The addition of WFM to the biomass with CaO catalyst pyrolysis (CP) delivered a higher oil yield of 52% compared to non-catalytic pyrolysis (NCP).

Plug And Play New Joiners During Pandemic Times: Creating A Sense of Belongingness

COVID-19 has forced several companies to swiftly switch to remote working. The Information Technology (IT) industry responded early by adopting a remote working model. It is now clear that, remote working is here to stay. This model will be an integral part of the working world more than ever. IT organisations have been able to make this migration considerably well in a short span of time. However, it is important to realise that implementation of remote working is a much broader subject. Organizations expect the new joiners to integrate into the organization in a manner similar to a plug and play device. New joiners take time to adapt to a new work environment. Those who joined during the pandemic missed the opportunity to get a first hand experience of their organization due to the remote onboarding. We studied two groups of employees, those who joined in their respective offices in 2019 and those who joined remotely in 2020. We tried to understand and compare the sense of belongingness amongst these two group of employees. The survey approach was adopted for analysis, and a total of 144 employees participated from 27 IT Companies across India. A One Way ANOVA was performed to compare the means and the outcome of the survey. The result was conclusive and corroborated the fact that, the sense of belonging in virtual workers stands low. Some of the significant reasons were due to the lack of regular connect with managers, irregular performance feedback and the dearth of instant recognition for work done. As remote working is going to be a part of future work strategy, it is important to bring the sense of belongingness early on amongst new joiners. Recommendations to address the belongingness gap were provided based on our discussion with a group of HR Managers.

AI Present: Random Interval Query and Face Recognition Attendance System for Classroom using Machine Learning

COVID-19 has triggered a global crisis never been seen before. In numerous sectors of society, the epidemic has produced a huge demand for new problem-solving solutions. Important difficulties have arisen in the field of education and related learning technologies because of the shift from eye to eye to online virtual learning. To battle the spread of COVID-19, several countries have temporarily closed educational institutions. Teachers all across the world have been forced to use internet conferencing as a result of educational institution closures. Online forums' virtual classes are widely considered as the only option to meet face to face in physical classes. In this aspect, teachers face a significant issue in managing student attendance in virtual classes. Student participation is a proportion of their involvement in the study, and it is linked to their active learning. Keeping track of student presence during virtual learning, on the other hand, is a major difficulty. Naming students who appear to be present in classrooms is a simple but time-consuming operation. Due to COVID-19 outbreak and widespread usage of virtual aids, disaster risk management must build a proper tracking system for monitoring student involvement and participation during virtual learning as soon as possible. This research work introduces a novel strategy to solve the significant demand created by the epidemic. Further, the proposed research study introduces the random interval query and face recognition based attendance management system to build a highly efficient and robust learning participation management system (from now on, AI Present). As far as known, no mechanized framework has been developed for following the students' participation and guarantee their involvement during the learning process. © 2022 IEEE.

Modelling and simulation of vaccine distribution: a COVID-19 situation

Ever since the onset of COVID-19, the healthcare fraternity and supply chains have faced severe disruptions like never before in the near past. The higher transmission rate of the virus has spread it worldwide. Vaccination is an inevitable phase to curtail the spread of the pandemic. The present study aims to develop an agent-based model to explain the distribution network of the vaccine. Grey relational analysis has been carried out to rank different states of India based on the critical variables that govern the transmission of the virus. This would help the policymakers rationally distribute the vaccines across different places. Further, sensitivity analysis has been performed with ten scenarios to compare the effects of positive and negative events, word of mouth, and the number of sessions on the distribution of vaccines. Increasing the sessions conducted per day from 163.33 by 40 and 80 increased the proportion vaccinated by 38.32 and 73.89 percentages, respectively. Copyright © 2021 Inderscience Enterprises Ltd.

Healthcare Apps for Post-COVID Era: Trends, Challenges and Potential Opportunities

The use of healthcare apps, e-health or m-health, has grown exponentially during the pandemic time. These apps can be used by people at home, work or on-the-go, which can help with a range of health, wellness and wellbeing tasks seamlessly, integrated with Electronic Health Records (EHRs) of hospital(s) to capture patient information. The data can be accessed by clinicians, patients and attenders anytime and anywhere. One of the major advantages of the healthcare apps has been the reduction of time taken to visit a doctor/clinic/hospital (especially considering the waiting times), medical bills and expenses. To a greater extent, there are many healthcare apps that have improved the accuracy of diagnosis and significantly improved quality of treatment. However, in this paper we have identified 10 challenges and 10 opportunities that can help researchers, developers, policymakers and other stakeholders introspect while building and releasing robust healthcare apps that are very much needed in the post-covid era. © 2022 IEEE.

Employees perception and experience on work from home in it and teaching sectors during COVID-19 with special reference to Coimbatore city

Coronovirus disease has demanded the concept "work from home" (WFH) into an authoritatively instructed, firmly forced law. Organizations in order that energize social distancing and race with time in battling the local spread of the virus now the working from home notion rising from all sectors, from IT sectors to teaching sectors. The work from home concept is new to majority of the employees. As the employees are undergo innovative atmosphere, this research paper aims to figure out the experience of the employees while WFH. This research is undertaken to have an insight on how organizations and individuals experience and perception towards the adaptability of these changes and challenges. Though, the working from home concept decreases the expenditure of the employees, they want to face the fear of unknown, inadequate communication at work, lack of accuracy and direction, interruptions while working from home consequent loss of resources like time and energy etc., which leads to prolonged stress to the employees and crisis in the work. This research found that the employee's readiness to work from home is entirely dependent on the employees comfort, workspace and good internet connectivity. This study efforts out the interest and experience of the workers in employed work from home when compared to operational in office and employee's perception towards it.

Impact of #ASCO Twitter impressions on the oncology community

Background: The oncology community is embracing social media (SM) platforms like Twitter to gain exposure to research, to network, and to engage in real-time discussions. The emergence of SM activity around the ASCO annual meetings has dramatically increased over the past 5 years, with factors such as the COVID-19 pandemic further accelerating use of digital platforms. This growth in SM engagement within the oncology community has previously been presented by totaling the quantity of tweets within a given time frame. Here, we explore the impact of specific trends through impression data. Methods: To evaluate activity trends among certain oncology stakeholders, we utilized an SM analytics platform, Symplur, to conduct a content analysis around ASCO conferences (2016-2020) using hashtags (#ASCOyy) as the search criterion. We focused our analysis on trends in impressions, defined by the theoretical maximum number of Twitter users a given tweet could have directly reached in a follower's timeline. We gathered impressions data to quantitatively assess overall ASCO engagement and evaluate topics of interest, and to discover common ASCO themes and reach within specific stakeholder groups. Results: Our results show the largest increase in impressions was during #ASCO20, despite a plateauing effect seen in the actual number of tweets (Table). The cumulative number of impressions for #ASCO16 was 468.2 million compared with approximately 1.12 billion for #ASCO20. Differentiating this result from the number of tweets related to ASCO, there was stabilization in the absolute number from #ASCO17 onward. When compiling impressions by doctors and by patient advocates, a similar trend emerged, with the most impressions captured during #ASCO20 (Table). Conclusions:As SM use continues to expand in the oncology community, stakeholders have turned to their digital voice to express views and opinions. The impact of impressions versus absolute number of tweets will continue to grow with a stakeholder's follower count, thus building on the digital presence in oncology.

A survey on anxiety and depression level among South Indian medical students during the COVID 19 pandemic

The COVID-19 pandemic is being a global Heath crisis. The rate of transmission of the disease is very high. At this time there is no specific vaccine or treat-ment. This widespread outbreak is also associated with psychological distress like depression and anxiety. The effect of COVID 19 on medical students is considerable. The medical students are in a transitory period which could be one of the most stressful times in a person’s life. The aim of this study is to assess the mental health of South Indian medical students during the COVID-19 pandemic and to see if there is any influence of gender on mental health. A cross sectional study was conducted using convenient sampling method. A total of 359 responses were analysed. Anxiety and depression symptoms were assessed based on four point Likert scale. GAD-7 (General Anxiety Disorder-7) scale and CES-D (Center for Epidemiology Studies for Depression) scale is used to assess anxiety and depression symptoms with a small modification respectively. Data analysis was performed using IBM SPSS statistics version 25. Out of 359 participants 50.4% of participants were male and 49.6% of them were females;majority of them (95.3%) were between the age group of 18-21. In total 75.5% and 74.6% of participants showed varying levels of anxiety and depression symptoms respectively. Anxiety and depression symptoms are found to have a mild association with gender. Symptoms are slightly higher among females than males.

Possible preventive measures against the spread of covid-19-a review article

COVID-19 is a current sensational and dangerous threat that affects millions of people across the world. As the day progresses the rate of growth of COVID-19 drastically increases. No vaccine or specific antiviral drug are active against corona, therefore, preventing the exposure to the virus is the base of support against its spread across the world. Despite the implementation of preventive measures, the rate of virus-infected cases progressively increases which stimulates our thought process to raise a question, whether the preventive measures that we follow are effective against the spread of COVID-19 infection. Evidence from previous literature obtained from various online tools implies multiple preventive measures that should be followed and also illustrates their mechanism of action against the active spread of COVID-19 infection. According to the results from the evidence, we can identify the gold standard preventive measure among the described preventive measures. The precautionary measure encompasses both pharmaceutical interventions and non-pharmaceutical interventions among which non-pharmaceutical measures are superior in the prevention of the developing pandemic. Among the non-pharmaceutical interventions, social distancing is the paramount to other measures in the mitigation of the spread of viral infection. © International Journal of Research in Pharmaceutical Sciences.