This paper examines the effect of climate change and financial development on agricultural production in ASEAN-4, namely Indonesia, Malaysia, the Philippines, and Thailand from 1990 to 2016. Further, we explore the role of renewable energy, institutional quality, and human capital on agricultural production. Since the shocks in one country affect another country, we use second-generation modeling techniques to find out the relationship among the variables. The Westerlund (2007) cointegration tests confirm long-run relationship among the variables. The results from cross-sectionally augmented autoregressive distributed lag (CS-ARDL) model reveal that climate change negatively affects agricultural production; on the other hand, renewable energy, human capital, and institutional quality affect positively agricultural production. Moreover, renewable energy utilization, human capital, and intuitional quality moderates the effect of carbon emission on agricultural production. In addition, a U-shaped relationship exists between financial development and agricultural production, suggesting that financial development improves agricultural production only after reaching a certain threshold. Hence, this study suggests that ASEAN-4 countries must adopt flexible financial and agricultural policies so that farmers would be benefitted and agricultural production can be increased.
This paper empirically examines the effects of energy, natural resources, agriculture, political constraint and regional integration on CO2 emissions in four ASEAN (Association of Southeast Asian Nations) countries of Cambodia, Malaysia, Indonesia and Thailand. We distinguish between renewable and fossil fuel energy consumption to see their individual impacts on CO2 emissions. The study employed a panel data from 1990 to 2019 derived from sources such as World Development Indicators, which were then analysed using Common-Correlated Effect Mean Group (CCEMG) and Augmented Mean Group (AMG) estimates. The findings show that renewable energy consumption has a negative impact on CO2 emissions while fossil fuel energy degrades the environment. The role of natural resources was found to be favourable for environmental quality with the impact of agriculture being found to be detrimental. For regional trade integration, its influence was not significant enough to offset CO2 emission. Furthermore, we discovered that political constraint induces CO2 emission. Based on the result, it is recommended that the selected ASEAN countries promote the use of renewable energy and clean technologies in their manufacturing processes, conserve natural resources, adopt eco-friendly political policies and intensify regional integration to accelerate the achievement of the SDGs.
The application of multiphysics models and soft computing techniques is gaining enormous attention in the construction sector due to the development of various types of concrete. In this research, an improved form of supervised machine learning, i.e., multigene expression programming (MEP), has been used to propose models for the compressive strength (fc'), splitting tensile strength (fSTS), and flexural strength (fFS) of sustainable bagasse ash concrete (BAC). The training and testing of the proposed models have been accomplished by developing a reliable and comprehensive database from published literature. Concrete specimens with varying proportions of sugarcane bagasse ash (BA), as a partial replacement of cement, were prepared, and the developed models were validated by utilizing the results obtained from the tested BAC. Different statistical tests evaluated the accurateness of the models, and the results were cross-validated employing a k-fold algorithm. The modeling results achieve correlation coefficient (R) and Nash-Sutcliffe efficiency (NSE) above 0.8 each with relative root mean squared error (RRMSE) and objective function (OF) less than 10 and 0.2, respectively. The MEP model leads in providing reliable mathematical expression for the estimation of fc', fSTS and fFS of BA concrete, which can reduce the experimental workload in assessing the strength properties. The study's findings indicated that MEP-based modeling integrated with experimental testing of BA concrete and further cross-validation is effective in predicting the strength parameters of BA concrete.
This study aimed to assess the physical activity levels of pediatric patients with acute leukemia undergoing chemotherapy. Thirty-eight pediatric patients and matched controls, aged 3-12 years old, were measured for weight, height, and other anthropometric parameters. Physical activity was assessed using actical accelerometer and activity log book. Patients recorded significantly lower mean total activity counts (26.2±30.2 cpm vs. 192.2±68.8 cpm; p<0.01) and spent more time in sedentary activities (1301±121 min vs. 1020±101 min; p<0.001) compared to controls. They also achieved fewer 1-5-min bouts of moderate-vigorous physical activity (MVPA) compared to controls (1.50±5.95 vs. 37.38±40.36; p<0.001). In conclusion, patients had lower physical activity level and intensity; and simple exercise intervention programs may be needed to minimize the detrimental effects of prolonged sedentary behaviors.
The Malaysian Node of the Human Variome Project (MyHVP) is one of the eighteen official Human Variome Project (HVP) country-specific nodes. Since its inception in 9(th) October 2010, MyHVP has attracted the significant number of Malaysian clinicians and researchers to participate and contribute their data to this project. MyHVP also act as the center of coordination for genotypic and phenotypic variation studies of the Malaysian population. A specialized database was developed to store and manage the data based on genetic variations which also associated with health and disease of Malaysian ethnic groups. This ethnic-specific database is called the Malaysian Node of the Human Variome Project database (MyHVPDb).