Volume 3 | Issue 2 |

 Abstract

This study examines the impact of government health expenditure on women and child health outcomes in India during 2005-2015 on the basis of maternal and child health indicators. With the use of secondary data and econometric analysis the relationship between health expenditure and key health indicators have been done. The results reveal highly significant negative correlations between health expenditure and mortality indicators (MMR: r=-0.983, p<0.01; IMR: r=-0.991, p<0.01) and strong positive correlations with service coverage indicators (Institutional Delivery: r=0.994, p<0.01; Full Immunization: r=0.995, p<0.01). Regression analysis demonstrates that every Rs. 1000 crore increase in health expenditure reduces MMR by 0.80 per 100,000 live births and IMR by 0.18 per 1,000 live births. The study shows significant interstate differences with best performing states such as Kerala and Tamil Nadu, spend 4-5 times more per capita on health than Empowered Action Group (EAG) states. The findings highlight the vital role of long-term expenditure on health infrastructure development particularly in underperforming states for improving the equitable improvements in health of women and children.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Government Health Expenditure, Women and Child Health & Econometric Analysis

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Geopolymer concrete (GPC) has emerged as a promising sustainable alternative to conventional Portland cement concrete (PCC), offering a potential reduction in the construction industry's substantial greenhouse gas emissions. PCC production is a major contributor to CO2, and GPC, utilizing industrial by-products like fly ash and ground granulated blast furnace slag (GGBFS), presents a compelling solution. This review examines GPC, focusing on its strength, durability, and workability. GPC uses geopolymers as the binding agent--inorganic aluminosilicate materials synthesized through alkali activation of source materials. This geopolymerization process involves dissolving aluminosilicate precursors in a highly alkaline solution, forming a three-dimensional polymeric network. The use of industrial by-products like fly ash and GGBFS aligns with sustainable practices. GPC has demonstrated the potential for comparable or superior mechanical properties, particularly compressive strength, compared to PCC, especially with optimized mix designs and curing conditions. Research on the microstructure development of alkali-activated fly ash provides insights into strength development. GPC also offers potential durability improvements, notably in aggressive chemical environments like sulfate attack. However, challenges remain, including workability concerns. Optimizing mix design parameters, such as the SiO2/Na2O ratio of the alkali activator, is crucial for achieving desired workability without sacrificing other properties. Long-term durability in diverse environments requires further investigation, extending beyond sulfate resistance to include freeze-thaw cycles and chloride exposure. This review synthesizes research on GPC's strength (compressive, tensile, flexural), exploring the influence of source materials, alkali activators, curing conditions, and mix design. It also addresses durability aspects (chemical resistance, freeze-thaw, elevated temperature) and workability challenges. By synthesizing existing knowledge, this review aims to provide a comprehensive overview of GPC, contributing to the advancement and wider application of this sustainable construction material.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Geopolymer Concrete (GPC), Strength, Durability, Workability, Fly Ash, Ground Granulated Blast Furnace Slag (GGBFS), Compressive Strength, Sustainability, Mix Design

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Retrieving Information from Special EHR of Multiple Systems of Medicine by Applying Naïve Bayes, BayesNet, PART, JRip and OneR Classification Algorithms

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Retrieving Information from Special EHR of Multiple Systems of Medicine by Applying Naïve Bayes, BayesNet, PART, JRip and OneR Classification Algorithms

  License

Creative Commons Attribution 4.0 and The Open Definition