Unusual association of orbital tumour and rhino-orbital-cerebral mucormycosis.

In developing tropical countries, rhino-orbital-cerebral mucormycosis has been a cause of severe morbidity and mortality during the COVID-19 pandemic. Classically, it develops as an aggressive angioinvasive destruction of nasal, orbital and cerebral involvement. Blindness is a major disabling complication. The association of mucor in cancer is linked with immunosuppression caused by radiation and/or chemotherapy. In this case report, we tried to explore the diverse possibilities of neck swelling, nasal discharge, ocular swelling and dimness of vision in a teenage boy. Rhabdomyosarcoma is a rare tumour of the soft tissue, connective tissue or bone. This type of unusual association or coexistence of rhabdomyosarcoma with mucormycetes is rarely seen in literature.

Wind of change brought by COVID-19: Exploring the response and the new normal from the perspectives of Indian flexpatriates

Drawing from the positive organizational change theory, this paper aims to explore how Indian flexpatriates responded to the change brought by the pandemic of COVID-19 and what is the new normal according to them. Thematic analysis of 19 in-depth interviews with flexpatriates from the IT industry revealed four explicit phases of change process ? reflection, communication, collaboration, and transformation. Further, the analysis brought out four tenets of the new normal. First, it is time to blend physical and virtual work;second, the ?personal? touch of Indians in international assignments is irreplaceable;third, working from home amidst the entire household being housebound is the new normal;and last, international travel will resume soon with some changed protocols. This is the first qualitative study combining the issue of global talent management with Indian flexpatriates vis-à-vis the impact of COVID-19, the findings of which expand the positive organizational change theory and have important implications.

Classifying COVID-19 and Viral Pneumonia Lung Infections through Deep Convolutional Neural Network Model using Chest X-Ray Images.

Context: Automated detection of COVID-19 in real time can greatly help clinicians to handle increasing number of cases for preliminary screening. Deep CNN models trained with sufficiently large datasets may become best candidates to meet the purpose. Aims: This study aims for automated detection and classification of COVID-19 and viral pneumonia diseases by applying deep CNN model using chest X-ray images. The proposed model performs multiclass classification to meet the purpose. Settings and Design: The proposed model is built on top of VGG16 architecture with pretrained ImageNet weights. The model was fine-tuned using additional custom layers to deliver better performance specific to the target. Subjects and Methods: A total of 15,153 samples are used in this work. These samples include chest X-ray images of COVID-19, viral pneumonia, and normal cases. The entire dataset was split into train and test sets, with a ratio of 80:20 before training the model. To enhance important image features, image preprocessing and augmentation were applied before feeding the image batches to the model. Statistical Analysis Used: Performance of the model is evaluated through accuracy, precision, recall, and F1 score performance metrics. The results produced by the model are also compared with other recent leading studies. Results: The proposed model has achieved a classification accuracy of 98% with 98% precision, 96% recall, and 97% F1 score on the test dataset for multiclass classification. The area under receiver operating characteristic curve score was 0.99 for all three cases of multiclass classification. Conclusions: The proposed classification model may be highly useful for the preliminary diagnosis of COVID-19 and viral pneumonia cases, especially during heavy workloads and large quantities.

An epidemiological study and trend analysis of laboratory confirmed COVID-19 cases among children in North India.

Background: The role of children in transmitting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is difficult to ascertain and the consequences remain unclear. This is necessary for public health or infection control purposes. The objective of this study was to describe the epidemiological, month-wise trends and clinical characteristics of coronavirus disease 2019 (COVID-19) infection among children in a tertiary care hospital. Materials and Methods: A cross-sectional study was performed on all pediatric samples of suspected cases of SARS-CoV-2 infection. The samples were received from the adjoining districts and our Institution in the Department of Microbiology from June to November 2020. Cases were then confirmed by real-time reverse transcriptase-polymerase chain reaction. Results: Of the total 62,030 pediatric samples tested, 847 (1.3%) were SARS-CoV-2 positive. The majority of positive cases were between the ages of 11-15 years. The median age of confirmed patients was 14 years. The male to female ratio was 1.5:1. Infants represented 1.6% of the positive cases. About 62.1% of all positive cases were asymptomatic. Childhood cases increased from June 2020 and peaked in September 2020 before declining. Conclusion: Children of all ages appeared susceptible to COVID-19 and accounted for a very small proportion of confirmed cases. Mostly, children were found to be asymptomatic. Young children can be important transmitters of SARS-CoV-2 infection in the general population. This population can be important for targeting immunization efforts throughout a rapidly evolving situation. Our findings provide further evidence of the distribution of infection in children and the transmission of SARS-CoV-2.

ROLE OF TELEMATICS IN MOTOR INSURANCE: A WAY FORWARD

Telematics or Usage Based Insurance (UBI) is one of the fastest growing concepts in the motor insurance segment. In India, traditional risk rating methods are still used, which are not capable of analysing the risk accurately and telematics can help to solve this issue. India is far behind other countries, which use telematics. This paper seeks to study the Role of Telematics in Motor Insurance and the perception of customers towards it. Further, the way forward for this technology is also discussed. For this research, the benefits and shortcomings of telematics have been analysed. Also, a survey was conducted and respondents opinion as to the installation/ usage of telematics device was asked. A Logistic Regression test was then done to complete our analysis. The findings present that most of the people in India are willing to have telematics devices installed if their privacy concerns are taken care of.

Clinical correlation of severe acute respiratory syndrome-coronavirus-2 cases in selected districts of Uttar Pradesh: A cross-sectional hospital-based study.

BACKGROUND: The novel coronavirus (CoV) has resulted in a global pandemic despite drastic measures to avoid contagious spread. On April 3, 2020, there were around 1 million reported cases and 51,515 deaths due to CoV disease 2019. The disease presents with flu-like symptoms such as fever, dry cough, and fatigue. India being a resource-limited country, it is very important to differentiate the suspected cases clinically. AIM: The aim was to know the correlation of various clinical features of severe acute respiratory syndrome CoV 2 (SARS-CoV-2)-infected cases in selected districts of UP. SETTING AND DESIGN: This was a retrospective cross-sectional hospital-based study. MATERIALS AND METHODS: This was a retrospective cross-sectional study performed on 1243 suspected cases of SARS-CoV-2 infection from March 25, 2020 to April 17, 2020 in the department of microbiology of our institute to know the incidence of SARS-CoV-2 infection in selected districts of Uttar Pradesh. These cases were analyzed to see the association of various clinical symptoms with SARS-CoV-2 infection. For statistical analysis, Pearson's Chi-square test was performed using SPSS version 23. RESULTS: Out of total suspected cases, 4.5% were positive. Travel history was present in 80.4% of positive cases. About 83.9% had fever, 28.6% had shortness of breath, 35.7% had dry cough, 17.9% had either Type I or II diabetes mellitus, 12.5% had chronic kidney disease, and 7.1% had obstructive pulmonary diseases. CONCLUSION: Negative clinical history is very important in ruling out the suspected cases who came out to be free from the infection.