Switching to Hydropower renewable energy to mitigate the effects of the carbon emissions in South and East Asian economies

Energy is the most essential tool for production and distribution of economic goods. It is also considered as crucial input of economic development. The World Energy Committee states that there are several environmental risks linked to energy production from non-renewable sources such as coal, gas, and petroleum etc. One of the associated risks is high per capita carbon emissions. To reduce such risk economy should switch to the renewable energy sources that characterize less or no carbon emission. This paper investigated the dynamics of coal, gas and hydroelectric energy within the framework of the environmental Kuznets curve. The study used the Arellano and Bond (1991) dynamic panel model using the GMM framework developed by the Hansen (1982). The empirical results of the study confirm the environmental Kuznets curve (EKC) hypothesis and that coal and gas are significant contributors to carbon. Results suggest that the hydel energy can play an essential role in mitigating the carbon emissions and improving climate emissions in case of South and East Asian Countries

Switching to Hydropower renewable energy to mitigate the effects of the carbon emissions in South and East Asian economies

Energy is the most essential tool for production and distribution of economic goods. It is also considered as crucial input of economic development. The World Energy Committee states that there are several environmental risks linked to energy production from non-renewable sources such as coal, gas, and petroleum etc. One of the associated risks is high per capita carbon emissions. To reduce such risk economy should switch to the renewable energy sources that characterize less or no carbon emission. This paper investigated the dynamics of coal, gas and hydroelectric energy within the framework of the environmental Kuznets curve. The study used the Arellano and Bond (1991) dynamic panel model using the GMM framework developed by the Hansen (1982). The empirical results of the study confirm the environmental Kuznets curve (EKC) hypothesis and that coal and gas are significant contributors to carbon. Results suggest that the hydel energy can play an essential role in mitigating the carbon emissions and improving climate emissions in case of South and East Asian Countries

The Impact of Recent Financial Recession on the Banking sector of Pakistan

The basic intent of this study is to examine the impact of recent financial crisis on the Pakistan commercial banking sector. This research paper will help to create the awareness about the risk factor which involves in Pakistan investment sector. The current worldwide financial crisis starts from large financial markets like US, UK and Candia. And this crisis becomes a cause of the fall down of well-known names in banking sector. Objective of this study, to establish the practical facts, that either the recant global financial crisis have or have not significant impact on Pakistan banks. The findings of this study will help to develop the assured recommendations which may help to formulate the policies regarding stabilization and crisis management in Pakistan banking sector

Dataset of 130 metagenome-assembled genomes of healthy and diseased broiler chicken caeca from Pakistan

This article presents metagenomic-assembled genomes (MAGs) of prokaryotic organisms originating from chicken caeca. The samples originate from broiler chickens, one group was infected with Newcastle Disease Virus (NDV) and one uninfected control group. There were four birds per group. Both groups were raised on commercially available antibiotic free feed under a semi-controlled setup. The binning step of the samples identified 130 MAGs with ≥50% completion, and ≤10% contamination. The data presented includes sequences in FASTA format, tables of functional annotation of genes, and data from two different approaches for phylogenetic tree construction using these MAGs. Major geochemical cycles at community level including carbon, sulfur, and nitrogen cycles are also presented

Comprehensive comparison of hetero-homogeneous catalysts for fatty acid methyl ester production from non-edible jatropha curcas oil

The synthesis of biodiesel from Jatropha curcas by transesterification is kinetically controlled. It depends on the molar ratio, reaction time, and temperature, as well as the catalyst nature and quantity. The aim of this study was to explore the transesterification of low-cost, inedible J. curcas seed oil utilizing both homogenous (potassium hydroxide; KOH) and heterogenous (calcium oxide; CaO) catalysis. In this effort, two steps were used. First, free fatty acids in J. curcas oil were reduced from 12.4 to less than 1 wt.% with sulfuric acid-catalyzed pretreatment. Transesterification subsequently converted the oil to biodiesel. The yield of fatty acid methyl esters was optimized by varying the reaction time, catalyst load, and methanol-to-oil molar ratio. A maximum yield of 96% was obtained from CaO nanoparticles at a reaction time of 5.5 h with 4 wt.% of the catalyst and an 18:1 methanol-to-oil molar ratio. The optimum conditions for KOH were a molar ratio of methanol to oil of 9:1, 5 wt.% of the catalyst, and a reaction time of 3.5 h, and this returned a yield of 92%. The fuel properties of the optimized biodiesel were within the limits specified in ASTM D6751, the American biodiesel standard. In addition, the 5% blends in petroleum diesel were within the ranges prescribed in ASTM D975, the American diesel fuel standard

Point prevalence survey of antimicrobial use during the COVID-19 pandemic among different hospitals in Pakistan : findings and implications

The COVID-19 pandemic has significantly influenced antimicrobial use in hospitals raising concerns regarding increased antimicrobial resistance (AMR) through their overuse. The objective of this study was to assess patterns of antimicrobial prescribing during the current COVID-19 pandemic among hospitals in Pakistan, including the prevalence of COVID-19. A point prevalence survey (PPS) was performed among 11 different hospitals from November 2020 to January 2021. The study included all hospitalized patients receiving an antibiotic on the day of the PPS. The Global-PPS web-based application was used for data entry and analysis. Out of 1024 hospitalized patients, 662 (64.64%) received antimicrobials. The top three most common indications for antimicrobial use were pneumonia (13.3%), central nervous system infections (10.4%) and gastrointestinal indications (10.4%). Ceftriaxone (26.6%), metronidazole (9.7%) and vancomycin (7.9%) were the top three most commonly prescribed antimicrobials among surveyed patients, with the majority of antibiotics administered empirically (97.9%). Most antimicrobials for surgical prophylaxis were given for more than one day, which is a concern. Overall, a high percentage of antimicrobial use, including broad-spectrums, was seen among the different hospitals in Pakistan during the current COVID-19 pandemic. Multifaceted interventions are needed to enhance rational antimicrobial prescribing including limiting their prescribing post-operatively for surgical prophylaxis

Automated diagnosis and treatment planning in dentistry

This study aims to investigate the perceptions and experiences regarding automated diagnosis and treatment planning in dentistry. The field of automated diagnosis and treatment planning is rapidly evolving, leveraging advanced technologies such as artificial intelligence (AI) and machine learning to enhance patient care and outcomes. However, there is a need to understand the perspectives of dental professionals regarding the adoption and implementation of these automated systems. A questionnaire survey was conducted among 100 dentists from various dental practices to gather data on their familiarity, usage, and perceptions of automated diagnosis and treatment planning. The survey also explored the perceived benefits, challenges, and future implications of automated systems in dental care. Preliminary findings indicate that the majority of dentists in the sample (80%) have some level of familiarity with automated diagnosis and treatment planning. However, only 45% reported actively using such systems in their practice. Among the dentists using automated systems, the most commonly cited benefits include time-saving (60%), enhanced accuracy (55%), and improved treatment planning (50%). Challenges associated with the adoption of automated systems were also identified.&nbsp