Education 4.0: Classification of Student Adaptability Level in E-Education

In India, online education is an important part of the educational system, but it grew even more popular during the Covid 19 epidemic since schools and universities were closed after March 2020. Students benefit from online instructions since they may record lectures and watch them as many times as necessary to grasp the material. However, the application of this technology in the sphere of education presents obstacles and ethical issues. Artificial Intelligence's prospects, advantages, and problems in education is be examined in this research. Several researches have shown that pupils might be hindered by online education, despite its widespread appeal and effectiveness. This study examines whether or not students are accepting of technology in the classroom. This article uses machine learning algorithms to classify the adaptability level of pupils. To predict the amount of student adoption of Industry 4.0 capabilities, we used a variety of machine learning techniques. With 93% classification accuracy, neural network and random forest techniques were shown to be the most effective. © 2022 IEEE.

A multi-modal bone suppression, lung segmentation, and classification approach for accurate COVID-19 detection using chest radiographs

The high transmission rate of COVID-19 and the lack of quick, robust, and intelligent systems for its detection have become a point of concern for the public, Government, and health experts worldwide. The study of radiological images is one of the fastest ways to comprehend the infectious spread and diagnose a patient. However, it is difficult to differentiate COVID-19 from other pneumonic infections. The purpose of this research is to provide an automatic, precise, reliable, robust, and intelligent assisting system ‘Covid Scanner’ for mass screening of COVID-19, Non-COVID Viral Pneumonia, and Bacterial Pneumonia from healthy chest radiographs. To train the proposed system, the authors of this research prepared novel a dataset called, “COVID-Pneumonia CXR”. The system is a coherent integration of bone suppression, lung segmentation, and the proposed classifier, ‘EXP-Net’. The system reported an AUC of 96.58% on the validation dataset and 96.48% on the testing dataset comprising chest radiographs. The results from the ablation study prove the efficacy and generalizability of the proposed integrated pipeline of models. To prove the system's reliability, the feature heatmaps visualized in the lung region were validated by radiology experts. Moreover, a comparison with the state-of-the-art models and existing approaches shows that the proposed system finds clearer demarcation between the highly similar chest radiographs of COVID-19 and Non-COVID viral pneumonia. The copyright of “Covid Scanner” is protected with registration number SW-13625/2020. The code for the models used in this research is publicly available at: https://github.com/Ankit-Misra/multi_modal_covid_detection/.

Emerging real time analytics based health start-ups: opportunities during covid-19

Indian population has potential threat of communicable and non-communicable diseases. The low preventive health measure is a cause of major loss to the economy. Integration of the cloud platform with remote wearable sensors not only helps the health stakeholders to capture the patient vitals but also perform predictive analysis during COVID-19. Raising timely alarms through Internet of Medical Things and Artificial Intelligence has wide application in preventive care through real time analytics. However, Health Merchandise Startups using artificial intelligence and machine learning for timely device delivery face delay in making themselves available and affordable for Remote patients of Tier II and III. This study takes a health service provider perspective and seeks to study problem situation systemically by using a casual loop model. Finally, analysis of the feedback loops is done to be able to come out with suitable strategies for COVID-19 patients of Remote locations. © MEDIC SCIENTIFIC, All rights reserved.

Emergency responses of Indian smart cities during the COVID-19 pandemic

This paper presents the current status of Indian smart cities and examines their preparedness and response to the COVID-19 outbreak. The study focuses on implemented & ongoing projects under the Smart City Mission of the Government of India, which have contributed significantly to controlling the pandemic along with other channels. The study finds that modern cities in both developed and developing countries were not well-prepared to deal with the emergency situations and struggled in providing a satisfactory response during the pandemic. The analysis of primary and secondary data has shown that digital surveillance and movement control through integrated control command centers (ICCC) were the most useful projects in monitoring the COVID-19 cases. However, the lack of technology integration in smart cities hinders the effective usage of implemented projects. Thus, the study recommends integrated network-based applications that include healthcare, essential services, mobility, and movement across smart cities in India. The proposed framework is expected to provide the much-needed alignment at the policy, objective, and implementation levels of smart city framework designs. © 2022 Urban Affairs Association.

A phase III, randomized, multicenter, double-blind study to compare efficacy and safety of EG12014 (EirGenix trastuzumab) with Herceptin® as neoadjuvant treatment in combination with anthracycline/paclitaxel-based systemic therapy in patients with HER2-positive early breast cancer-a multinational phase III study conducted during the COVID-19 pandemic

Amplification and/or overexpression of HER2 in breast cancer (BCa) patients is associated with aggressive disease and poor prognosis. Herceptin® (trastuzumab), a monoclonal antibody targeting HER2, has an established role in the treatment of HER2 positive BCa. Addition of trastuzumab to anthracycline-and taxane-based neoadjuvant treatment in women with HER2-positive BCa has resulted in improvements in pathological complete response (pCR, a strong predictor for long-term clinical outcome), event-free survival (EFS) and overall survival (OS). This study is designed to compare efficacy (pCR) and safety between the originator Herceptin and the proposed trastuzumab biosimilar EG12014. The study is conducted during the COVID-19 pandemic (last patient in: March 2020, last patient last visit: planned Jan 2022) in Belarus, Chile, Colombia, Georgia, India, Russia, South Africa, South Korea, Taiwan, and the Ukraine. Methods: Neoadjuvant phase: 807 patients were randomized (1:1) into 2 arms receiving epirubicin (90 mg/m 2) and cyclophosphamide (600 mg/m2) every 3 weeks for 4 cycles, followed by EG12014 (arm 1) or Herceptin (arm 2) (both at loading dose: 8 mg/kg and maintenance dose: 6 mg/kg) and paclitaxel (175 mg/m2) every 3 weeks Sfor 4 cycles. Subsequently, the patients underwent surgery, and primary endpoint (pCR [ypT0/is ypN0]) was assessed. Adjuvant phase: After surgery, the patients received EG12014 or Herceptin (both at loading dose: 8 mg/kg and maintenance dose: 6 mg/kg) to complete 12 months of overall trastuzumab treatment. COVID-19 infections in the study population were not expected to affect primary endpoint analysis;thus, no sensitivity analysis was performed regarding COVID-19 status (symptomatic/asymptomatic). Differences between the 2 arms regarding delays in study treatments and procedures due to COVID-19 were assessed. Results (at interim data base lock, blinded as study is ongoing): Study population: the mean age was 50 years, the majority were white Europeans with tumor stage II, estrogen receptor positive and progesterone receptor negative. The median time from date of first diagnosis was 0.5 months. Primary endpoint pCR (ypT0/is ypN0) was reached with relative risk ratio (RR) for the full analysis set: 0.992 (90% CI 0.880 to 1.118) between the 2 treatment arms. Secondary pCR endpoints (defined as ypT0 ypN0 and ypT0/is) were also reached, with RR between the treatment arms: 0.917 and 0.992, respectively. Objective clinical response prior to surgery was similar for the 2 treatment arms: 83.8% and 83.6%, respectively. EFS, OS, safety endpoints (e.g., adverse events [most frequently reported: alopecia], serious adverse events, and deaths), and toxicity assessments, supported similarity between EG12014 and Herceptin. Sixty-two patients (7.7%) were infected with COVID-19;the infections were equally distributed between the 2 treatment arms. COVID-19 did not cause any discontinuations or deaths in the study. Among all reported COVID-19 events, 13 (21%) were asymptomatic, 11 (18%) were graded as 3 (severe), and 1 (1.6%) was graded as grade 4 (life threatening). Conclusion: EG12014 has shown equivalent efficacy to Herceptin in regard to clinical response (pCR) and has also demonstrated a similar safety profile. The impact of the COVID-19 pandemic has been comparable between the two treatment arms. The influence of the pandemic on this clinical study has been relatively low considering timing and the participating countries.

Restricting Ordering of Multiplex Gastrointestinal Panel Improves Test Utilization

Background. The multiplex gastrointestinal pathogen panel (GIP) is a convenient and quick diagnostic test for determining the infectious etiology of diarrhea. It identifies several of the most common pathogens associated with gastroenteritis. However, it is expensive, and test results may not impact care, given that several of the pathogens in the panel are managed expectantly. We describe our experience with a diagnostic stewardship initiative to resolve the overuse of this testing method. Methods. We performed a pre/post study of GIPs ordered for inpatients 18 years old and older from December 19, 2018, to December 18, 2020, at Mayo Clinic hospital in Rochester, Minnesota. GIP orders for inpatients were limited to the first 72 hours of hospitalization starting December 19, 2019. Orders after 72 hours were encouraged to be changed to Clostridioides difficile NAAT testing or sent to an infectious disease provider to override on a case-by-case basis. Our hospitals used BioFire® FilmArray® Gastrointestinal Panel (BioFire Diagnostics, Salt Lake City, Utah). Results. A total of 2,641 GIPs were performed during the study period. There were 1,568 GIPs (3.3/100 hospitalizations) in the pre-intervention period compared to 1,073 (2.6/100 hospitalizations) post-intervention, representing a drop of 21.2%. The most common pathogen detected was C. difficile (toxin A/B) (48.8%, n=402), followed by norovirus (17.5%, n=144). The overall test positivity rate was 27.9% (n=736). The test positivity rate decreased 1.8% from 28.6% (n=448) to 26.8% (n=288) after the restriction (p=0.33). The proportion of C. difficile among all pathogens detected increased from 48.5% to 49.7% (p=0.67). Conclusion. Our study showed that restricting the ordering of GIP to the first 72 hours of hospitalization and directing providers to standalone C. difficile NAAT testing resulted in a reduction of GIPs performed. There were marginal changes in the test positivity rate of GIP. A limitation of our study is that the timing of post-intervention coincided with the COVID-19 pandemic, which had unpredictable effects on hospital practice and patient admissions. Ideally, future quality improvement projects should increase the test positivity of pathogens other than C. difficile while lowering the GIP use in diagnosing C. difficile colitis.

Towards Understanding the Psychological Effects of the COVID-19 Pandemic on the Indian Population

This article explains the preliminary results of the analysis of a public survey carried out in India, assessing the psychological effects on people during the second wave of the COVID-19 pandemic. A survey was designed to categorize the population on the basis of various socio-economic demographics and respondents were then asked to fill out the DASS-21 questionnaire to get their levels of severity of anxiety, depression and stress. The dataset obtained was then further analyzed using various classification machine learning models with the level of severity as the target variable and respondent's attributes as independent variables. A Multinomial Logistic Regression was found to give the best results with an AUC score of 0.94 and was thus, used to predict the severity levels of these three categories, to find various insights from this publicly-sourced dataset. Additionally, the significance of the various socio-demographic attributes asked in the survey was analyzed in order to identify key drivers of mental ailments among the general Indian population. Further, a brief description of segmenting the population using K-Means clustering is provided which attempts to identify population groups that belong to similar socio-economic demographics and suffer from similar mental health issues during the pandemic. Thus, high-risk or high-severity groups can be identified and then could be targeted by the government to provide them relief schemes. This paper applies machine learning on a public dataset to explore the various facets of COVID-induced problems in the Indian Society. © 2021 IEEE.

Network Based Framework to Compare Vaccination Strategies

We propose a network based framework to model spread of disease. We study the evolution and control of spread of virus using the standard SIR-like rules while incorporating the various available models for social interaction. The dynamics of the framework has been compared with the real-world data of COVID-19 spread in India. This framework is further used to compare vaccination strategies. © 2021, Springer Nature Switzerland AG.

Effect of Prone Positioning on Oxygen Saturation in COVID-19 Patients in Sri Aurobindo Hospital, Indore

Background: Physiotherapeutic intervention body positioning have been observed to increase oxygen saturation. In COVID-19 patients, we intended to investigate how the prone position worked in conjunction with conventional respiratory physiotherapy. The objective was to determine the effect of prone position along with conventional respiratory physiotherapy on SpO2 of COVID-19 patients in Aurobindo hospital, Indore district. Methods: The Ministry of Health, Government of India, authorized the rules for collecting data from infected patients. In this study, 400 patients between the ages of 20 and 80 years old were recruited from Sri Aurobindo Hospital in the Indore district, all of them had a confirmed diagnosis of COVID-19 and required oxygen treatment. SpO2 data was collected as a baseline. Patients were helped into the prone position after baseline data collection and conventional respiratory physiotherapy. Clinical data was obtained again after using the prone posture in conjunction with conventional respiratory physiotherapy. To demonstrate the various prone variations, a patient information sheet was supplied. At 0 and 60 minutes after the exercise, oxygen saturation was measured. Results: Between April 2020 to June 2020, we assessed SpO2 of 400 Patients pre and post prone position along with conventional respiratory physiotherapy. Prone positioning was feasible. Oxygenation was significantly improved from supine to prone position. The data were processed for mean and standard deviation. It was analyzed that there was difference in pre to post value of mean, from 95.685 to 98.123 with standard deviation from 1.645to 1.445. The result shows significant improvement in SpO2 after applying prone positioning in patients infected with COVID-19. The findings suggest that prone positioning is both possible and beneficial in increasing blood oxygenation in awake COVID-19 patients. Further study is needed to find the technique's potential value in terms of enhancing overall respiratory and global outcomes. Conclusion: The difference between the saturation of the two position was significant.

Bank Competition Using Networks: A Study on an Emerging Economy

Interconnectedness among banks is a key distinguishing feature of the banking system. It helps mitigate liquidity problems but on the other hand, acts as a curse in propagating systemic risk at times of distress. Thus, as banks cannot function in isolation, this study uses the Contemporary Theory of Networks to examine banking competition in India for five distinct economic phases, emphasizing upon the Global Financial Crisis (GFC) and the ongoing COVID-19 pandemic. This paper proposes a Market Power Network Index (MPNI), which uses network parameters to measure banks' market power. This network structure shows a formation of bank clusters that are involved in competition. Specifically, network properties, such as centroid, average path length, the distance of a node from the centroid, the total number of connections in the inter-bank market, and network density, do go on to explain banking competition. It is interesting to note that crisis periods witness a lower level of competition, with GFC bearing the least competition. The ongoing COVID-19 pandemic shows a lower trend, but it is of a higher magnitude than GFC. It was also found that big-sized, profitable, capital adequate, and public banks dominate the banking system. Notably, this study was conducted on a sample of 33 listed Indian banks from April 2008 to December 2020.

Management of hyperglycemia in COVID-19 and post-COVID-19 syndrome - proposed guidelines for India

SARS-CoV-2 virus spread rapidly all over the globe in 2020 and the second wave has taken our nation, India by storm. The pandemic has posed unique challenges in people with metabolic disorders, including diabetes, hypertension, obesity, pulmonary, cardiovascular, kidney and non-alcoholic fatty liver disease. Uncontrolled diabetes, in conjunction with endocrine, inflammatory and metabolic effects of the infection itself has made management of hyperglycemia in COVID-19 infection particularly challenging. Furthermore, the post-COVID-19 syndrome has also emerged as a sequela in COVID-19 survivors, increasing the risk of death, complications and adding further burden on the health care system. With more than a year of experience, we have gained substantial insight;and now provide practical recommendations on the management of hyperglycemia in COVID-19 as well as post COVID-19 syndrome. © 2021 Journal of Association of Physicians of India. All rights reserved.

SARS-CoV-2 infection in a pediatric acute leukemia patient on chemotherapy and concurrent sofosbuvir/velpatasvir for HCV

There are new targets identified by experimental and animal research for treatment of SARS-COV-2 (Severe acute respiratory syndrome-Corona Virus-2) infection. Out of many clinical trials registered, there are ongoing human studies highlighting Sofosbuvir's possible role in the treatment of Covid-19 (Coronavirus Disease 2019). Here we present a case of acute leukemia on directly acting antiviral therapy (DAAs) for HCV infection mitigating SARS-COV-2 infection in a patient undergoing chemotherapy. The child was undergoing chemotherapy, along with directly acting antiviral for acute hepatitis C infection. He initially had features of hypoxia and radiological evidence of covid-19. He had an uneventful course and tested negative ten days after onset of illness. With ongoing trials on Sofosbuvir in covid 19 treatment, our finding, albeit coincidental, points to the possible role even in immune-compromised children.