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This study examined the construct and latent factors of social, economic, and environmentally sustainable development and Science & technological progress across 39 economies from 2000 to 2016 using a Confirmatory Factor Analysis (CFA). The linear production function model was used to explore the influence of sustainable development on social-economic development and Science & technological progress using country-wise panel data. The age dependency ratio, education expenditure, female labor force, life expectancy, and gender equality were detected as crucial factors of social development. Further, FDI net inflows, gross capital formation, per capita GDP, total employers, and labor force participation rate were found to be valuable variables for increasing economic development. The use of electricity, renewable energy, and green technology in production activities would be helpful in diminishing CO2 emissions and improving environmental sustainability. High-technology exports, ICT goods exports, and R&D expenditure were perceived as essential drivers of increasing Science & technological progress. Sustainable development, Science & technological progress, environmental technology, and job creation in all sectors appeared to be vital indicators to increase social-economic development. Science & technological progress was positively associated with social-economic development, sustainable development, the share of the industrial sector in GDP, and green technology. It was noticed that factors positively related to economic, social, environmental, Science & technological development seemed beneficial to increasing sustainable development. The global economies should implement integrated policy in the social, economic, Science & technology, and environmental sectors to achieve sustainable development. Otherwise, global economies cannot reach the 17 sustainable development goals of the United Nations by 2030.

Among patients with chronic kidney disease (CKD), the use of recombinant human erythropoietin and its derivatives for the treatment of anemia has been linked to a possibly increased risk of stroke, myocardial infarction, and other adverse events. Several trials have suggested that hypoxia-inducible factor (HIF) prolyl hydroxylase inhibitors (PHIs) are as effective as erythropoiesis-stimulating agents (ESAs) in increasing hemoglobin levels. In this randomized, open-label, phase 3 trial, we assigned patients with CKD who were undergoing dialysis and who had a hemoglobin level of 8.0 to 11.5 g per deciliter to receive an oral HIF-PHI (daprodustat) or an injectable ESA (epoetin alfa if they were receiving hemodialysis or darbepoetin alfa if they were receiving peritoneal dialysis). The two primary outcomes were the mean change in the hemoglobin level from baseline to weeks 28 through 52 (noninferiority margin, -0.75 g per deciliter) and the first occurrence of a major adverse cardiovascular event (a composite of death from any cause, nonfatal myocardial infarction, or nonfatal stroke), with a noninferiority margin of 1.25. A total of 2964 patients underwent randomization. The mean (±SD) baseline hemoglobin level was 10.4±1.0 g per deciliter overall. The mean (±SE) change in the hemoglobin level from baseline to weeks 28 through 52 was 0.28±0.02 g per deciliter in the daprodustat group and 0.10±0.02 g per deciliter in the ESA group (difference, 0.18 g per deciliter; 95% confidence interval [CI], 0.12 to 0.24), which met the prespecified noninferiority margin of -0.75 g per deciliter. During a median follow-up of 2.5 years, a major adverse cardiovascular event occurred in 374 of 1487 patients (25.2%) in the daprodustat group and in 394 of 1477 (26.7%) in the ESA group (hazard ratio, 0.93; 95% CI, 0.81 to 1.07), which also met the prespecified noninferiority margin for daprodustat. The percentages of patients with other adverse events were similar in the two groups. Among

Purpose: This study assesses the impact of climatic and geographical factors on the yield of potato, cotton, groundnut, sesame, linseed, sugarcane, rapeseed & mustard, and sunflower seeds using state-wise panel data in India during 1971-2013. Thereupon, it estimates the expected yield of aforesaid crops in different climate change scenarios. Methods: Cobb-Douglas production function model is used to estimate the regression coefficients of climatic and geographical factors with the yield of aforesaid crops. Results: The empirical result shows that maximum temperature, minimum temperature, rainfall, and precipitation have a significant impact on the yield of potato, groundnut, sesame, linseed, sugarcane, rapeseed & mustard, sunflower seeds. The projected results indicate that yield of sesame, linseed, rapeseed & mustard, potato, and cotton crops may decline by 0.16%, 0.83%, 5.65%, 14.68%, and 23.31% respectively due to one unit change in average maximum and minimum temperature, actual precipitation, and rainfall during crop seasons. Implications: The Agriculture department of the government should encourage farmers to implement crop-specific policies to mitigate the negative impact of climate change in agriculture.    Limitations: Application of fertilizer, quality of seeds, cost of cultivation, farm management practices, irrigated area, demographic factors (e.g., population growth, urbanization, industrialization, etc.), and ecosystem services (e.g., water, soil fertility, and land) have a significant impact on the yield of cash crops. However, these variables were not included to predict the yield of cash crops in this study. Thus, this study acknowledged this limitation and existing researchers can incorporate these variables in further study.

Purpose: This study makes a comparison of the manufacturing sector and its determinants for India and selected Asian countries. It examines the factors affecting the annual turnover of randomly selected 154 firms in seven different industries of the Indian manufacturing sector. Methods: In this study, the firm’s annual turnover is used as a dependent variable. Labor productivity, age, investment on plant & machinery, annual expenditure on marketing, total employees, production technology up-gradation, shortage of skilled workers, skills to improve the process, use of hi-tech tool and technique in production activities, technology transfer abilities, in-house R&D expertise, quality certification, foreign collaboration, waste management capabilities and building capacity of firms are used as independent variables. Regression coefficients of explanatory variables are assessed using linear, log-linear, and non-linear regression models. Results: The study concluded that the firm's annual turnover has a significant association with technological development related variables, labor productivity, age, technology transfer abilities, in-house R&D expertise, quality certification, and waste management practices of firms. Implications: It suggests that Indian policymakers need to adopt a strong IPRs, education, and S&T policy in research institutions. India needs to increase R&D expenditure and researchers in research institutions. Research institutions should collaborate with the existing industries to discover more technologies and innovations for the manufacturing sector. All research organizations must set up technology transfer offices to increase technology transfer and commercialization. Furthermore, India needs to set up hi-tech firms to face global challenges. Originality: It uses primary data of 154 firms which are collected from seven different industries across Indian states. Thus, the study substantially contributes to the existing literature.&