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Introduction: Orthopaedic surgeons are among the most frequent users of radiation and are often exposed to X-Ray radiation regularly. There is an overall unsatisfactory level of knowledge, attitude, and practices regarding the same among surgeons. This study aimed to assess the practices among orthopaedic surgeons regarding radiation and its hazards in India. Methodology: This questionnaire-based survey was conducted between March and September 2022. The questionnaire broadly assessed the knowledge, awareness, and practices among orthopaedic surgeons regularly exposed to X-ray radiation. The questionnaire consisted of objective and Likert scale questions which were distributed to the respondents electronically using publicly available contact information. A qualitative review of interpretations obtained from the responses and available evidence in the literature was then performed. Results: The response rate for the survey was 36.4%. 65.9% reported using trunk protection all the time during procedures. 57.1% of respondents reported not using thyroid protection during procedures. 92.3% reported not using protective goggles and 100% did not use appropriate gloves. 76.9% were not issued dosimeters, and only 5.5% of those who had been issued one wore it during radiation procedures. 58.2% reported having a dedicated employee to operate the machine. 86.8% of respondents did not have formal training and 81.3% were not aware of institutes offering formal training. Conclusion: There is very high compliance with the use of protection aprons among the respondents however, the use of other apparel like thyroid shields, protection goggles and gloves was poor. The awareness regarding radiation exposure was also poor as most respondents were not issued dosimeters, however, those issued with one were well aware of their exposure. It is imperative to prioritize both surgeons' and patients' safety where radiation exposure is concerned. [ABSTRACT FROM AUTHOR]

AstroSat, India's first UV and X-ray astronomy satellite, has completed over six years of observations while in orbit around the Earth. It has carried out detailed studies of all kinds of objects in the Universe ranging from single stars, stars in clusters, binary stars with compact companions like neutron stars and black holes, star formation in galaxies, supermassive black holes in active nuclei of galaxies, etc. Here, I give a short description of its UV and X-ray telescopes and detectors. Some of the most important results obtained using AstroSat will be described in Part II. [ABSTRACT FROM AUTHOR]

Infectious diseases are highly contagious due to rapid transmission and very challenging to diagnose in the early stage. Artificial Intelligence and Machine Learning now become a strategic weapon in assisting infectious disease prevention, rapid-response in diagnosis, surveillance, and management. In this paper, a bifold COVID_SCREENET architecture is introduced for providing COVID-19 screening solutions using Chest Radiography (CR) images. Transfer learning using nine pre-trained ImageNet models to extract the features of Normal, Pneumonia, and COVID-19 images is adapted in the first fold and classified using baseline Convolutional Neural Network (CNN). A Modified Stacked Ensemble Learning (MSEL) is proposed in the second fold by stacking the top five pre-trained models, and then the predictions resulted. Experimentation is carried out in two folds: In first fold, open-source samples are considered and in second fold 2216 real-time samples collected from Tamilnadu Government Hospitals, India, and the screening results for COVID data is 100% accurate in both the cases. The proposed approach is also validated and blind reviewed with the help of two radiologists at Thanjavur Medical College & Hospitals by collecting 2216 chest X-ray images between the month of April and May. Based on the reports, the measures are calculated for COVID_SCREENET and it showed 100% accuracy in performing multi-class classification. [ABSTRACT FROM AUTHOR]