The composition of chemicals and anti-osteogenic properties in the volatile extracts from Homalomena gigantea rhizome.

In this study, the anti-osteogenic properties of the volatile oil extracted from Homalomena gigantea rhizome using ethyl acetate (EtOAc) and methanol (MeOH) were examined. Gas chromatography-mass spectrometry (GC-MS) was employed for the identification of volatile components. Following this, bioassays were performed to evaluate their effects on osteogenesis, encompassing parameters like cell viability, osteoblast differentiation, collagen synthesis and mineralization. The GC-MS analysis revealed 19 compounds in the EtOAc extract and 36 compounds in the MeOH extract. In the MeOH extract, major constituents included bis(2-ethylhexyl) terephthalate (13.83%), linalool (9.58%), palmitic acid (6.55%) and stearic acid (4.29%). The EtOAc extract contained bis(2-ethylhexyl) terephthalate (16.64%), palmitic acid (5.60%) and stearic acid (3.11%) as the predominant components. Both the EtOAc and MeOH extracts of H. gigantea exhibited promising potential for further investigation in anti-osteoporosis research. These findings contribute to the exploration of natural compounds with potential anti-osteoporotic properties, expanding our understanding of their therapeutic potential.

Multi-air pollution risk assessment in Southeast Asia region using integrated remote sensing and socio-economic data products.

Air pollution has massive impacts on human life and poor air quality results in three million deaths annually. Air pollution can result from natural causes, including volcanic eruptions and extreme droughts, or human activities, including motor vehicle emissions, industry, and the burning of farmland and forests. Emission sources emit multiple pollutant types with diverse characteristics and impacts. However, there has been little research on the risk of multiple air pollutants; thus, it is difficult to identify multi-pollutant mitigation processes, particularly in Southeast Asia, where air pollution moves dynamically across national borders. In this study, the main objective was to develop a multi-air pollution risk index product for CO, NO2, and SO2 based on Sentinel-5P remote sensing data from 2019 to 2020. The risk index was developed by integrating hazard, vulnerability, and exposure analyses. Hazard analysis considers air pollution data from remote sensing, vulnerability analysis considers the air pollution sources, and exposure analysis considers the population density. The novelty of this study lies in its development of a multi-risk model that considers the weights obtained from the relationship between the hazard and vulnerability parameters. The highest air pollution risk index values were observed in urban areas, with a high exposure index that originates from pollution caused by human activity. Multi-risk analysis of the three air pollutants revealed that Singapore, Vietnam, and the Philippines had the largest percentages of high-risk areas, while Indonesia had the largest total high-risk area (4361 km2). Using the findings of this study, the patterns and characteristics of the risk distribution of multiple air pollutants in Southeast Asia can be identified, which can be used to mitigate multi-pollutant sources, particularly with respect to supporting the clean air targets in the Sustainable Development Goals.

Identifying Factors Influencing Productivity of Older Workers in Service Sector: A Case Study in Pilot Companies in Thailand.

Productivity has posed issues for global countries in terms of promoting older employment due to an emergence of questions regarding production efficiency. Individual characteristics result in varying production efficiencies, which in turn provide different levels of productivity. Taking this concern into account, we are here to examine the characteristics of older workers who provide high productivity in order to seek recommendations for fostering decent work for them. We utilized the dataset collected from the pilot service companies in Thailand who participated in a national initiative program for employing older people. A total of 204 older workers and their characters were then observed. Those characters were analyzed by the Generalized Ordered Logit Regression (gologit) model. Empirical findings indicate that allocating work that is related to communication and coordination to older workers would enhance odd ratio of their productivity by as much as 4.79 times compared to general tasks. Furthermore, employing older individuals on a part-time basis tends to generate higher-level productivity than full-time employment. We also found that gender and age differences have no significant effect on productivity in the service sector as people age, and factors related to types of employment, education, health, and financial status are also a precise determinant for the productivity of older workers. This would suggest that the work design for the older workers must be in line with the aforementioned determinants. In addition, the government initiatives utilizing key findings from this study to boost older workers' productivity should give priority on tax incentives, promoting and advocating for employment equality, and vocationalization programs.