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The COVID-19 pandemic has caused significant global morbidity and mortality. As the vaccination was rolled out with prioritization on healthcare workers (HCWs), it was desirable to generate evidence on effectiveness of vaccine in prevailing real-life situation for policy planning. The objective of the study was to evaluate the safety, effectiveness and immunogenicity of COVID-19 vaccination among HCWs in a tertiary care hospital.This prospective observational study was undertaken on the safety, immunogenicity and effectiveness of the ChAdOx1 nCoV- 19 coronavirus vaccine (Recombinant) during the national vaccine roll out in January-March 2021, in a tertiary care hospital, New Delhi, India.The vaccine was found to be safe, with local pain, fever and headache as the most common adverse events of milder nature which generally lasted for two days. The adverse events following vaccination were lower in the second dose as compared to the first dose. The vaccine was immunogenic, with seropositivity, which was 51 per cent before vaccination, increasing to 77 per cent after single dose and 98 per cent after two doses. Subgroup analysis indicated that those with the past history of COVID-19 attained seropositivity of 98 per cent even with single dose. The incidence of reverse transcription (RT)-PCR positive COVID-19 was significantly lower among vaccinated (11.7%) as compared to unvaccinated (22.2%). Seven cases of moderate COVID-19 needing hospitalization were seen in the unvaccinated and only one such in the vaccinated group. The difference was significant between the fully vaccinated (10.8%) and the partially vaccinated (12.7%). The hazard of COVID-19 infection was higher among male, age50 yr and clinical role in the hospital. After adjustment for these factors, the hazard of COVID-19 infection among unvaccinated was 2.09 as compared to fully vaccinated. Vaccine effectiveness was 52.2 per cent in HCWs.ChAdOx1 nCoV-19 coronavirus vaccine (Recombinant) was safe, immunogenic as well as showed effectiveness against the COVID-19 disease (CTRI/2021/01/030582).

Background Seroprevalence studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can provide information on the target populations for vaccination. We aimed to evaluate the seroprevalence among healthcare workers (HCWs) at our tertiary care institution and to identify parameters that may affect it. Method We assessed seroprevalence of SARS-CoV-2 by the chemiluminescence immunoassay test among 3258 HCW in our hospital and evaluated as per gender, age, their previous Covid-19 diagnosis, role in hospital and type/risk of exposure. Results Of 3258 participants, 46.2% (95% CI 44.4%– 47.9%) were positive for SARS-CoV-2 IgG antibodies (i.e. IgG ≥15 AU/ml). Higher seroprevalence was seen in non-clinical HCWs (50.2%) than in clinical HCWs (41.4%, p=0.0001). Furthermore, people with a history of Covid-19 were found to have significantly higher antibody levels (p=0.0001). Among the HCWs, doctors and nurses had lower relative risk (RR) of acquiring Covid-19 infection (RR=0.82; 95% CI 0.76–0.89) compared to non-clinical HCWs. Conclusion Seroprevalence in HCWs at our hospital was 46.2%. Clinical HCWs had lower seroprevalence compared to non-clinical HCWs. Previous history of Covid-19 almost doubled the seropositivity, particularly in those with current infection.

Seborrheic dermatitis (SD) is a common disorder of the skin, which is dermatologically manifested by erythematous patches covered by yellow-grey scales. It mostly appears on the face, scalp, upper chest, and back. Half of the adult population is estimated to be affected by seborrheic dermatitis of the scalp. Although its prevalence is very high, the etiology has not been very well known. Numerous intrinsic and external environmental factors such as excessive sebum secretions, fungal colonization of the surface of the skin, genetic susceptibility, and dynamics, among others, can result in the development of the disease. Unani medicine is familiar with this disease under the entity named ‘Tasherul Raas/Huzaz’. Various herbal and mineral-origin drugs have been declared in the Unani classical literature for the treatment of SD. In the present paper, topical Unani drugs particularly beneficial for scalp seborrheic dermatitis are discussed.

Adaptable Critical Patient Caring system is a key concern for hospitals in developing countries like Bangladesh. Most of the hospital in Bangladesh lack serving proper health service due to unavailability of appropriate, easy and scalable smart systems. The aim of this project is to build an adequate system for hospitals to serve critical patients with a real-time feedback method. In this paper, we propose a generic architecture, associated terminology and a classificatory model for observing critical patient's health condition with machine learning and IBM cloud computing as Platform as a service (PaaS). Machine Learning (ML) based health prediction of the patients is the key concept of this research. IBM Cloud, IBM Watson studio is the platform for this research to store and maintain our data and ml models. For our ml models, we have chosen the following Base Predictors: Naive Bayes, Logistic Regression, KNeighbors Classifier, Decision Tree Classifier, Random Forest Classifier, Gradient Boosting Classifier, and MLP Classifier. For improving the accuracy of the model, the bagging method of ensemble learning has been used. The following algorithms are used for ensemble learning: Bagging Random Forest, Bagging Extra Trees, Bagging KNeighbors, Bagging SVC, and Bagging Ridge. We have developed a mobile application named “Critical Patient Management System - CPMS” for real-time data and information view. The system architecture is designed in such a way that the ml models can train and deploy in a real-time interval by retrieving the data from IBM Cloud and the cloud information can also be accessed through CPMS in a requested time interval. To help the doctors, the ml models will predict the condition of a patient. If the prediction based on the condition gets worse, the CPMS will send an SMS to the duty doctor and nurse for getting immediate attention to the patient. Combining with the ml models and mobile application, the project may serve as a smart healthcare solution for the hospitals.

For different purposes, a service robot that can be controlled remotely will play a significant role in the expansion of robotics automation systems. In the developing countries like Bangladesh, everyone is concerned about safety from both natural and human-made situations like Disposal of Bombs, rescuing objects from dangerous places, a useful assistant for handicapped people. In this paper, we propose to make a Robotic Car (RC) which helps to enter an environment of higher risks, grab and move to an appropriate place. For developing this generic model, Raspberry Pi 3 Model B+ is used as the central control unit for the robot. Six Degree of Freedom (DOF) Arm is used to compute as the main factor for grabbing the objects. Radio Frequency (RF) transmitter is the remote handheld controller for the RC. Also, a raspberry pi 0.6MP camera is integrated for live video streaming. The live streaming will provide the actual scenario of the environment to operate, control and navigate the RC. This robot also carries some important sensors like a Gas sensor, Ultrasonic Sonar Sensor and 3-Axis Digital Compass to bring out the scientific task of the robot. This prototype can be both used for educational and research purpose. The performance of the robot can be measured by the transmission of the video streaming, control system success rate for RF controller, outcomes of the sensors and the accuracy of the 6 DOF Arm.

Recommender Systems (RSs) have become an essential part of most e-commerce sites nowadays. Though there are several studies conducted on RSs, a hybrid recommender system for the real state search engine to find appropriate rental apartment taking users preferences into account is still due. To address this problem, a hybrid recommender system is proposed in this paper constructed by two of the most popular recommendation approaches — Collaborative Filtering (CF), Content-Based Recommender (CBR). CF-based methods use the ratings given to items by users as the sole source of information for learning to make a recommendation. However, these ratings are often very sparse in applications like a search engine, causing CF-based methods to degrade accuracy and performance. To reduce this sparsity problem in the CF method, the Cosine Similarity Score (CSS) between the user and predicted apartment, based on their Feature Vectors (FV) from the CBR module is utilized. Improved and optimized Singular Value Decomposition (SVD) with Bias-Matrix Factorization (MF) of the CF model and CSS with FV of CBR constructs this hybrid recommender. The proposed recommender was evaluated using the Statistical Cross-Validation consisting of Leave-One-Out Validation (LOOCV). Experimental results show that it significantly outperformed a benchmark random recommender in terms of precision and recall. In addition, a graphical analysis of the relationships between the accuracy and error minimization is presented to provide further evidence for the potentiality of this hybrid recommender system in this area.

Halela (Terminalia chebula Retz, Family: Combretaceae) is one of the drugs worthwhile to be used in Unani medicine due to its extraordinary therapeutic efficacy. Globally the species is distributed in the Indo-Malesia region and Sri Lanka. Within India, it is distributed in the sub-Himalayan tracts to West Bengal and Assam. Halela is one of the drugs of choice to be used in Saudawi/ chronic diseases (diseases with the dominance of black bile) in Unani medicine. Halela proposed to promotes digestion, absorption, elimination, rejuvenation, and elimination of black bile from the body (khilt sauda, a humour responsible to produce aging and a culprit for chronic diseases). Various scientific studies have also evidenced its beneficial effects. In this paper, a review of three different varieties of halela which have been used in Unani medicine for centuries has been specified with special reference of Unani as well as other pieces of literatures.