PLIGHT OF FEMALE CONSTRUCTION WORKERS OF SURAT CITY

Background: With the rapid increase in construction sector, the number of female construction workers is increased. The problems of women worker is still not addressed adequately by health sector. Aims and objective: The present study is aimed to explore problems of female workers at construction sites in working environment and to document issues like gender bias, living conditions, vulnerability and slackness of health among female working in construction field. Methodology: This was a Cross sectional study conducted in May 2011in which all females working at the randomly selected construction site were enrolled. The pre-designed semi-structured questionnaire was prepared to study the participant’s response. In-depth interview technique was also used to strengthen the findings. Results: Total of 118 female construction workers participated in the study with mean age found to be 22 years with SD of 6 years. Mean daily wages of female was 120 Rs while for male it was 245 Rs which is double than what female getting. Major health complaints were fatigue/weakness (61 %), backache (30 %), cough (17.5 %), fever (17 %), skin itching (10.5 %) and diarrhoea (7 %). They were not even using the government medical facility due to lack of awareness and knowledge about this. No safety measures provided to female as compare to male except at 2 sites where female were provided ‘gloves’. Some (6%) of the working females has abuse of chewing tobacco daily or smoking ‘bidi’. The living condition was merely enough to provide any privacy for female. Conclusion: As migratory and floating population, female working in construction field needs attention. Lack of social security and family support make them a vulnerable group for addiction and violence. Alternate way for providing healthcare for these women should be sort out early

Hybrid Elastic ARM&Cloud HPC Collaborative Platform for generic tasks

Compute-heavy workloads are currently run on Hybrid HPC structures using x86 CPUs and GPUs from Intel, AMD, or NVidia, which have extremely high energy and financial costs. However, thanks to the incredible progress made on CPUs and GPUs based on the ARM architecture and their ubiquity in today’s mobile devices, it’s possible to conceive of a low-cost solution for our world’s data processing needs. Every year ARM-based mobile devices become more powerful, efficient, and come in ever smaller packages with ever growing storage. At the same time, smartphones waste these capabilities at night while they’re charging. This represents billions of idle devices whose processing power is not being utilized. For that reason, the objective of this paper is to evaluate and develop a hybrid, distributed, scalable, and redundant platform that allows for the utilization of these idle devices through a cloud-based administration service. The system would allow for massive improvements in terms of efficiency and cost for com-pute-heavy workload. During the evaluation phase, we were able to establish savings in power and cost significant enough to justify exploring it as a serious alternative to traditional computing architectures.Instituto de Investigación en Informátic

DETERMINANTS OF MENTAL HEALTH STIGMA AMONG PHARMACY STUDENTS IN AUSTRALIA, BELGIUM, ESTONIA, FINLAND, INDIA AND LATVIA

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Pharmacy Education in India: Strategies for a Better Future

In this world of specialization and globalization the pharmacy education in India is suffering from serious backdrops and flaws. There is an urgent need to initiate an academic exercise aimed at attaining revamping of curriculum, keeping in pace with current and emerging trends in the field of pharmacy. Unfortunately all these years, enough emphasis was not laid on strengthening the components of Community Pharmacy, Hospital and Clinical pharmacy, while designing curriculum at diploma and degree levels of teaching. The curriculum followed by almost all universities in India are no were up to the world standards and students are still getting the 20-30 yrs older compounding practical exposure in labs during the graduation level. The article emphasises the concept of innovation ecosystems and quality management. Application of TQM to the educational system improves the present situation. The counseling system which serves to be the gateway of the students for entry into the profession should be brought under the scanner. Introducing specializations at the graduation level will result in professional expertise and excellence. Education is a customer focused industry and every student should be capable of evaluating themselves for continuously improving their quality and professionalism. Teacher focused mastery learning should give away to student focused smart learning. An educational institution should provide the student with a stress-free atmosphere for learning and developing his intellectual capabilities. Every college should have a counseling centre to address the problems of students in their academic and personal life. An emphasis on the concept of quality teacher is included. Revival of the pharmacy education in India is the need of the hour which in turn will pave the way for the up gradation of the pharmacy profession in the country

Revolutionizing physics: a comprehensive survey of machine learning applications

In the context of the 21st century and the fourth industrial revolution, the substantial proliferation of data has established it as a valuable resource, fostering enhanced computational capabilities across scientific disciplines, including physics. The integration of Machine Learning stands as a prominent solution to unravel the intricacies inherent to scientific data. While diverse machine learning algorithms find utility in various branches of physics, there exists a need for a systematic framework for the application of Machine Learning to the field. This review offers a comprehensive exploration of the fundamental principles and algorithms of Machine Learning, with a focus on their implementation within distinct domains of physics. The review delves into the contemporary trends of Machine Learning application in condensed matter physics, biophysics, astrophysics, material science, and addresses emerging challenges. The potential for Machine Learning to revolutionize the comprehension of intricate physical phenomena is underscored. Nevertheless, persisting challenges in the form of more efficient and precise algorithm development are acknowledged within this review

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Comparative Analysis of Digital Elevation Models: A Case Study of Kayadhu Watershedle

In last few years, Digital Elevation Models (DEMs) have established more popular due to their diverse utility and applications in the fields like hydrology, forestry, precision farming, geomorphology etc. DEM is used for characterizing the topography and to derive the stream network, ridge line, thereby to study the landscape within the watershed area. DEMs from satellite imageries like Cartosat -1 is becoming popular with wide applications. The resolution is allowed for comparison is the DEM of ISRO (30m) (cartosat-1). These DEMs were created using different methods and technologies, and they can differ in how they represent the topography of the same area. This study shows that the differences in these DEMs and illustrates how these differences can produce various analytical outcomes when used to study local problems. The primary objective of this study is to compare the accuracy of Cartosat -1 DEM and DEM generated from Google earth. The google earth DEM is generated with the help of ‘Triangulation’ which is SAGA (System for Automated Geoscientific Analyses) tool. For the comparison of both the DEMs, Kayadhu watershed is taken as study area. The comparative analysis of DEM is carried out on the basis of the Stream network and contours of 5m, 10m and 15m interval with their respective lengths. The counts of contours of Cartosat -1 DEM for 5 m, 10 m and 15 m interval was found to be 27794, 27954 and 18184 respectively with contour lengths at that respective interval about 30503.2 km, 12803.7 km and 8421.45 km. The counts of contours of Google Earth DEM for 5 m, 10 m and 15 m interval was found to be 1485, 776 and 492 respectively with contour lengths at that respective interval about 8308.45 km, 4112 km and 2741 km.  From this study the stream counts of Cartosat-1 DEM and Google Earth DEM was found to be 34449 and 52668 with stream length about 432 km and 1134 km respectively.  This study has been carried out in open source environment viz. QGIS, SAGA, GRASS GIS and Google Earth. In this study, the Cartosat -1 DEM and Google earth DEM has minimum to maximum elevation from the mean sea level was found to be 336 m to 481 m and 408.7 m to 549.3m respectively. From the study, it is observed that Cartosat-1 DEM has more accuracy than DEM generated from Google Earth. Therefore, the Cartosat -1 DEM gives clear 3D topography than DEM generated from google earth