Search

When Typhoon Meiji made landfall in Taiwan in 2010, sudden and heavy rainfall caused disasters in Yilan, Hualien, and other places quickly. The Suhua Highway on the 9th line of Taiwan was the most serious. It caused a large landslide of 50,000 cubic meters at 115K and lost 500 meters of subgrade and 30 meters of subgrade at 116K, causing severe disasters in the local area. Therefore, it was built on Suhua Highway 115.9K. There is an urgent need for monitoring instruments for the large-scale collapse of slopes. To provide real-time automatic rainfall monitoring information and GPS satellite positioning monitoring displacement information, a real-time information system was established to receive the coordinates of points measured by GPS instruments and automatically calculate displacement and movement velocity. At the same time, the radar rainfall forecast data of the "Severe Weather Monitoring System (QPESUMS)" of the Central Meteorological Administration was introduced, and the ground rainfall was used to observe the rainfall correction influence factors to improve the estimation accuracy of the radar rainfall forecast. Through the local automatic rain gauge information, it displays information such as hourly rainfall and accumulated rainfall, develops warning reference values, integrates with the "Disaster Warning Data Exchange" for an automatic notification system, and builds functional modules in the "Highway Disaster Prevention and Relief Decision Support System". (TRENDS)". Integrate the front-end and back-end software and hardware interfaces to establish a complete information system to provide real-time slope information for road management units in the face of disasters as an auxiliary tool for decision-making. [ABSTRACT FROM AUTHOR]

Polychlorinated biphenyl (PCBs) are persistent organic compounds used between 1930 and 1970 as thermal insulators in electrical equipment such as transformers, electrical condensers, heat exchangers, and hydraulic systems. Currently, this xenobiotic is a potential source of pollution to soil and water resources. This research aimed to isolate and characterize bacteria strains possessing a high potential to degrade PCBs contained in used dielectric oils. The bacteria strains were isolated from a soil sample taken from “Alao” Hydroelectric Power Center. Four culture media were used for the soil sample culturing: Agar for Standard Methods Medium (STD), Phosphorus, Ammonium, and Salts Medium (PAS), Minimum Medium (Mm), and Minimum Medium (Mm) supplemented with 25 µL of oil contaminated with 43,6 ppm of PCBs. The isolation, screening, and stabilization process were carried out using three culture media: STD, PAS, and Mm, each supplemented with 25 µL of oil contaminated with 43,6 ppm of PCBs. Nineteen bacterial colonies were isolated and exposed to a higher concentration of PCBs. Eighteen colonies could tolerate 250 µL of oil contaminated with 500 ppm of PCBs. Once stabilized and purified these bacteria strains, were characterized according to their microscopic and macroscopic characteristics and tolerance to heavy metals. Through biochemical tests, 18 strains were identified belonging to Providencia alcalifaciens, Proteus mirabillis, Providencia rettgeri, Providencia stuartii, Pseudomona alcaligenes, Morganella morganii, and Shigella disenteriae. [ABSTRACT FROM AUTHOR]

Flooding is the most damaging natural hazard in the world. A better understanding of floods is a fundamental element in guiding the development of policies for managing and reducing flood risk. The main objective of this research is to contribute to the improvement of knowledge on flood susceptibility by combining Fuzzy AHP and Multivariate Analysis. Ha Tinh province in Vietnam was selected as the case study in which many floods have occurred in recent years. To accomplish this goal, 14 factors and 1427 flood locations were used to establish the flood susceptibility model. The area under the curve (AUC) was applied to assess the model accuracy. The results showed that rainfall, NDVI, NDBI, density of river, elevation, slope and aspect are the main factors influencing the occurrence of flooding. The models are efficient in analyzing the flood susceptibility in study area with AUC=0.87. Approximately 36% of the study area was recognized as Very High and High flood susceptibility, which focused on the littoral zone and along the river. The results of this research could be used as a scientific platform for better land use planning and sustainable development in areas highly vulnerable to floods. [ABSTRACT FROM AUTHOR]