Arsenic testing work has been carried out in Uttar Pradesh by UP Jal Nigam during the period 2005-2008. During this period, arsenic testing was performed using field test kits for 150,000 sources employing screening and blanket testing approach. The current paper describes the work of geographical information system (GIS) mapping in Bahraich district. The district has two physiographic units -Uprahar and Tarhar to depict highland and lowland Quarternary alluvial plains. Out of 30,216 India Mark II hand pumps in the district, arsenic testing was performed, by UP Jal Nigam for 13,812 hand pumps, out of which 7190 (52.06%) tested sources show arsenic value > 0 mg/L. Further segregation of data shows that 56.66% of affected sources fall in 10-40 mg/L category and 10.86% sources fall in >50 mg/L category. Village level mapping of affected sources at GIS platform shows arsenic concentration is more in Huzoorpur and Tajwapur blocks which lie in lowland physiographic unit.

Background: Chronic Suppurative Otitis Media (CSOM) is a significant cause of preventable hearing loss. Global emergence of resistant strains is of great concern. The aim of the present study was to assess the accuracy and predictive value of computed tomography in diagnosis of unsafe chronic suppurative otitis media. Methods: Aprospective, analytical study was conducted among 90 patients with complaint of unsafe chronic suppurative otitis media which were randomly selected from outpatient Department of Otorhinolaryngology at Subharti Medical College, Dehradun, Uttarakhand. The patients comprised of both males as well as females and also of different age groups. Results: Out of 90 patients, 61(67.22%) were males followed by 29 (32.22%) females. The minimum age of patient in the study was of 8years and the maximum age of patient in study of 50 years. Maximum number of patients belonged to the age group of 11-20 (50%). The mean age in this study was 23 years. Among study subjects, 32 (35.55%) cases had conductive hearing loss, 11 (12.22%) cases had sensorineural type, 40 (44.44%) had mixed type and 7 (7.77%) had no response. In this study, sensitivity, specificity, positive predictive value, negative predictive value was calculated of computed tomography findings as compared to preoperative findings. The sensitivity of HRCT for mastoid was 100%, visualization malleus was 94.11%, incus was also 62.31%, stapes was 47.22% and facial N dehiscent and intact was 44.82%. Similarly, the specificity of CT scan for mastoid was 83.33%, malleus was 92.85%, incus was 61.90%, stapes erosion was 37.03% and facial N dehiscent was 96.72%. Conclusion: The present study was concluded that computed tomography can accurately image the findings in unsafe chronic suppurative otitis media and represents a major advance in the diagnostic imaging of this disease.

Microbial contamination of handpump (HP) is common in developing countries like India. The WHO recommends sanitary inspection (SI) to assess the risk of water source contamination. In SI, all risks are given equal weightage. However, different mathematical models have shown that risks associated with localised pathways have a relatively higher influence on microbial contamination. This study aims to assess the efficacy of eliminating four risks associated with localised pathways and have shown a higher positive association with microbial contamination of HP than others in bivariate frequency analysis and four binary logistic regressions applied on 324 HPs randomly selected from nine districts of Uttar Pradesh, India. Analysis showed the four risks: (i) HP loose at base: (ii) apron cracked: (iii) apron < 1 m an: (iv) drainage broken have a higher positive association than others. In this study, the above four risks were eliminated from 154 HPs (safe 48 and unsafe 106) through standard civil structures keeping other risks untouched. Post-intervention thermotolerant coliforms (TTC) tests were carried out and unsafe HPs were reduced from 106 to 3. Therefore, managing the four risks associated with localised pathways is highly effective in preventing microbial contamination of HP water.

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The goal of this project is to develop an emotion-based music recommender system that provides personalized music recommendations based on the user's current emotional state. The system incorporates an emotion detector that analyses user’s facial expressions, to determine their current mood. Based on the detected emotion, the system recommends music tracks that match the user's current emotional state