During the last many years, the air quality of the capital city of India, Delhi had been hazardous. A large number of people have been diagnosed with Asthma and other breathing-related problems. The basic reason behind this has been the high concentration of life-threatening PM2.5 particles dissolved in its atmosphere. A good model, to forecast the concentration level of these dissolved particles, may help to prepare the residents with better prevention and safety strategies in order to save them from many health-related diseases. This work aims to forecast the PM2.5 concentration levels in various regions of Delhi on an hourly basis, by applying time series analysis and regression, based on various atmospheric and surface factors such as wind speed, atmospheric temperature, pressure, etc. The data for the analysis is obtained from various weather monitoring sites, set-up in the city, by the Indian Meteorological Department (IMD). A regression model is proposed, which uses Extra-Trees regression and AdaBoost, for further boosting. Experimentation for comparative study with the recent works is done and results indicate the efficacy of the proposed model.

The novel coronavirus disease is spreading very rapidly across the globe because of its highly contagious nature, and is declared as a pandemic by world health organization (WHO). Scientists are endeavoring to ascertain the drugs for its efficacious treatment. Because, till now, no full-proof drug is available to cure this deadly disease. Therefore, identifying COVID-19 positive people and to quarantine them, can be an effective solution to control its spread. Many machine learning and deep learning techniques are being used quite effectively to classify positive and negative cases. In this work, a deep transfer learning-based model is proposed to classify the COVID-19 cases using chest X-rays or CT scan images of infected persons. The proposed model is based on the ensembling of DenseNet121 and SqueezeNet1.0, which is named as DeQueezeNet. The model can extract the importance of various influential features from the X-ray images, which are effectively used to classify the COVID-19 cases. The performance study of the proposed model depicts its effectiveness in terms of accuracy and precision. A comparative study has also been done with the recently published works and it is observed the performance of the proposed model is significantly better.

Introduction: Uncontrolled population growth in India is recognized as the single most hurdle for the nation's development. Population can only be controlled by effective and compliant methods of contraception. One such method is long acting injectable medroxy progesterone acetate (DMPA) that simplifies compliance. Aims and Objectives: To assess the acceptability and compliance of injection DMPA in rural married women in Sitapur. Methods: The present study was conducted on 150 married women aged 18-45 years who had chosen DMPA as contraceptive at HIMS Sitapur in duration of 2 years. DMPA injection was given within 7days of menstruation, within 7 days post-abortion and after 6 weeks postpartum. Subsequent injections were given at three monthly intervals. All women were followed up for one year after the first injection for pregnancy rate, side-effects, discontinuation and patient satisfaction. Results: It was observed that out of 150 women 72.66% were from age group of 21-30 years and 41.33 % were primipara. Most common side effect was irregular bleeding 58% followed by amenorrhea in 20%. Discontinuation rate was 73.33% after first injection and 18% after second injection. 56% had stopped injection due to side effect 16.66 % women had changed contraception.10% women had planned pregnancy and17.33% women had lost to follow up. Conclusion:Acceptability is very good in rural women because of convenience of dosing, coital independence and privacy. Compliance is low due to side effect but can be increased with counseling and diligent follow up.

Advanced mucinous ovarian cancer is a separate entity and has different biological behaviour. There is a wide range of therapeutic challenges and dilemmas in the management of these patients. The authors present a case of advanced ovarian mucinous cystadenocarcinoma with pseudomyxoma peritonei who had poor response to standard neoadjuvant chemotherapy. This case is highlighted to emphasize the challenges in the decision making for the management of advanced mucinous ovarian cancer.

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