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Background: Health care providers worldwide are rapidly adopting electronic medical record (EMR) systems, replacing paper record-keeping systems. Despite numerous benefits to EMRs, the environmental emissions associated with medical record-keeping are unknown. Given the need for urgent climate action, understanding the carbon footprint of EMRs will assist in decarbonizing their adoption and use., Objective: We aimed to estimate and compare the environmental emissions associated with paper medical record-keeping and its replacement EMR system at a high-volume eye care facility in southern India., Methods: We conducted the life cycle assessment methodology per the ISO (International Organization for Standardization) 14040 standard, with primary data supplied by the eye care facility. Data on the paper record-keeping system include the production, use, and disposal of paper and writing utensils in 2016. The EMR system was adopted at this location in 2018. Data on the EMR system include the allocated production and disposal of capital equipment (such as computers and routers); the production, use, and disposal of consumable goods like paper and writing utensils; and the electricity required to run the EMR system. We excluded built infrastructure and cooling loads (eg. buildings and ventilation) from both systems. We used sensitivity analyses to model the effects of practice variation and data uncertainty and Monte Carlo assessments to statistically compare the 2 systems, with and without renewable electricity sources., Results: This location's EMR system was found to emit substantially more greenhouse gases (GHGs) than their paper medical record system (195,000 kg carbon dioxide equivalents [CO 2 e] per year or 0.361 kg CO 2 e per patient visit compared with 20,800 kg CO 2 e per year or 0.037 kg CO 2 e per patient). However, sensitivity analyses show that the effect of electricity sources is a major factor in determining which record-keeping system emits fewer GHGs. If the study hospital sourced all electricity from renewable sources such as solar or wind power rather than the Indian electric grid, their EMR emissions would drop to 24,900 kg CO 2 e (0.046 kg CO 2 e per patient), a level comparable to the paper record-keeping system. Energy-efficient EMR equipment (such as computers and monitors) is the next largest factor impacting emissions, followed by equipment life spans. Multimedia Appendix 1 includes other emissions impact categories., Conclusions: The climate-changing emissions associated with an EMR system are heavily dependent on the sources of electricity. With a decarbonized electricity source, the EMR system's GHG emissions are on par with paper medical record-keeping, and decarbonized grids would likely have a much broader benefit to society. Though we found that the EMR system produced more emissions than a paper record-keeping system, this study does not account for potential expanded environmental gains from EMRs, including expanding access to care while reducing patient travel and operational efficiencies that can reduce unnecessary or redundant care., (©Cordelia Kwon, Lernik Essayei, Michael Spencer, Tom Etheridge, Rengaraj Venkatesh, Natrajan Vengadesan, Cassandra L Thiel. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 06.02.2024.)

Purpose: This study aims to examine the effectiveness of the Central Board of Secondary Education (CBSE)-based English textbooks and question papers in developing second-language higher-order thinking skills (HOTS). Design/methodology/approach: Descriptive analysis establishes a causal relationship between learning objectives and second language (L2) writing proficiency. Content analysis is used to compare and analyze tabulated data for textbooks and question papers for the English language by the National Council of Educational Research and Training (NCERT) and CBSE. This method categorizes the materials and their assessments under HOTS and lower-order thinking skills to ascertain the relationship between learning objectives and L2 writing proficiency. Findings: The study highlights teaching material and assessment shortcomings and their alignment with learning outcomes to enhance students' writing skills. It underscores the need for HOTS-focused materials, discussing their impact on writing skills. The study also explores how textbook-question paper mismatch hampers Bloom's taxonomy-based cognitive skills. Practical implications: This research illuminates the efficacy of teaching and learning English as a second language (ESL) writing skills to improve the quality of education, which has real-world implications. The study highlights flaws in the educational system in India and suggests curricular and pedagogical changes. Originality/value: The research examines NCERT and CBSE ESL textbooks and question papers to align teaching and assessment methods. The results aim to improve education through ESL writers' HOTS.

The pulp and paper industry is critical to global industrial and economic development. Recently, India's pulp and paper industries have been facing severe competitive challenges. The challenges have impaired the environmental performance and resulted in the closure of several operations. Assessment and prediction of the performance of the Indian pulp and paper industry using various parameters is a critical task for researchers. This study proposes a framework for performance assessment and prediction based on Data Envelopment Analysis (DEA), Artificial Neural Networks, and Deep Learning (DL) to assist industry administration and decision-making. We presented a case study based on eight industries to demonstrate the methodology's applicability. This study analyses and predicts industry performance based on sample data observations over 30 years. The result suggests the DEA-DL-based efficiency prediction has an overall MSE of 0.08 compared with the actual efficiency. Furthermore, the efficiency rankings are compared between the three techniques. The results suggest that the integrated DEA-DL method is primarily accurate in most scenarios with the actual values. The findings of this study provide a comprehensive analysis of environmental performance for policymakers. [ABSTRACT FROM AUTHOR]

Aim and Objectives: Although inclusive education of children with intellectual disability is currently an accepted practice, it is often challenged by negative attitude of schoolteachers. We undertook two surveillance studies aimed at Study A - identifying knowledge and teachers' attitudes towards children with intellectual disability and practices of inclusive education in a semi-urban school of South India. Study B -Determining the effect of educational intervention towards attitudes on inclusive education. Method: Knowledge, Attitude and Practice surveillance questionnaires (KAP and ATPD) were given to ninety-six consenting schoolteachers in Study A and twenty schoolteachers in Study B and analyzed. Results: In Study A, the overall attitude mean indicated a favorable attitude towards the children with intellectual disability. The mean overall attitude score was 77.1 (SD: 9.58), with a normal distribution. Forty to fifty percent were aware of intellectual disability and attributed them to biological causes. Ninety-two percent agreed on the need for education and stepwise training for a child with an intellectual disability. In real-life practice, results of classroom management were inaccurate. In Study B, knowledge, attitudes and practices towards inclusive education improved with educational intervention with a positive change of 7.19% on the ATDP scale. Conclusion: These findings suggest a generally positive attitude towards intellectual disability and inclusive education. Comprehensive training programs improve knowledge and attitudes towards inclusive education.