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Conducting field research in Taiwan can be challenging because of the abundance of steep slopes. This study aimed to establish an automatic interpretation procedure applicable to exploring images of large-scale slope land taken using UAVs. The proposed method was compared with traditional field surveying and manual image interpretation techniques to determine the advantages and disadvantages of the proposed procedure in terms of efficiency. The object-based image analysis (OBIA) and texture features were first combined and the random forest (RF) classifier was then employed to interpret crop types. This study selected three sites of slope land and plains for experimentation. The obtained results indicated that the overall accuracy of the proposed classification method exceeded 91%, and the Kappa value was approximately 0.9 for all sites. In addition, interpretation of the proposed method was more efficient than that of the two traditional methods. [ABSTRACT FROM AUTHOR]

This research introduces the following to establish a Taiwan Weighted stock index (TAIEX) prediction model: intervention analysis integrated into the ARIMA-GARCH model, error correction model (ECM), intervention analysis integrated into the transfer function model, the simple average combination forecasting model, and the minimum error combination forecasting model. The results show that intervention analysis integrated into the transfer function model yields a more accurate prediction model than ECM and intervention analysis integrated into the ARIMA-GARCH model. The minimum error combination forecasting model can improve prediction accuracy much better than non-combination models and also maintain robustness. Intervention analysis integrated into the transfer function model shows that the TAIEX is affected by external factors, the INDU, the exchange rate, and the consumer price index; therefore, facing the different issues of the TAIEX, the government could pursue some macroeconomic policies to reach the goals of policies. [ABSTRACT FROM AUTHOR]

Two sampling sites in central Taiwan, at Hungkuang University (HKU) and Tunghai University (THU), were chosen to contrast the content of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere from November 2000 to April 2001. PAHs that arise from incomplete combustion of organic materials, especially fossil fuels, are the major toxic pollutants in central Taiwan. This study aimed to analyse PAHs, by using a PS-1 sampler and a gas chromatograph/mass selective detector (GC/MSD), and to identify the major sources of PAHs. At the HKU sampling site, the primary emission sources are probably vehicles and coal burning, and vehicular emissions are the primary contributor at the THU sampling site. [ABSTRACT FROM AUTHOR]

In this research, a real-time nowcasting system for regional landslide-hazard assessment under extreme-rainfall conditions was established by integrating a real-time rainfall data retrieving system, a landslide-susceptibility analysis program (TRISHAL), and a real-time display system to show the stability of regional slopes in real time and provide an alert index under rainstorm conditions for disaster prevention and mitigation. The regional hydrogeological parameters were calibrated using a reverse-optimization analysis based on an RGA (Real-coded Genetic Algorithm) of the optimization techniques and an improved version of the TRIGRS (Transient Rainfall Infiltration and Grid-based Regional Slope-Stability) model. The 2009 landslide event in the Xiaolin area of Taiwan, associated with Typhoon Morakot, was used to test the real-time regional landslide-susceptibility system. The system-testing results showed that the system configuration was feasible for practical applications concerning disaster prevention and mitigation. [ABSTRACT FROM AUTHOR]

The understanding for the impact of petrochemical pollutants exposure on renal functions is limited. Our study examined the associations between renal functions and pollutants exposure in adult residents living in the vicinity of a petrochemical industry. We recruited 2069 adult residents near a big petrochemical complex in Taiwan in 2009–2012, and they were categorized into high exposure (HE) and low exposure (LE) groups based on their address to source by 10 km radius. Study subjects were measured the urinary levels of arsenic, cadmium, mercury, thallium, and 1-hydroxypyrene (1-OHP). The estimated glomerular filtration rate (eGFR) was calculated using the Taiwanese Chronic Kidney Disease Epidemiology Collaboration equation, and the chronic kidney disease (CKD) prevalence and risks were defined according to KDIGO 2012 guidelines. Adjusted generalized linear and logistic regression models were applied to evaluate the associations between petrochemical exposure and renal functions. Subjects in the HE areas had significantly lower eGFR, higher CKD prevalence, and higher levels of urinary arsenic, cadmium, mercury, thallium and 1-OHP. The closer to complex and high exposure group of study subjects were significantly associated with the decrease in eGFR, higher ORs for CKD and high-intermediate risk of CKD. In addition, the study subjects who had two-fold urinary arsenic and 1-OHP levels were significantly with decreased 0.68 and 0.49 ml/min/1.73 m2 of eGFR, respectively. Residing closer and higher arsenic and polycyclic aromatic hydrocarbon exposure were associated with the renal impairment and risks of CKD among the residential population near the petrochemical industry. Image 1 • Renal effect and risks of CKD among residents near the petrochemical industry. • Residential exposure from petrochemical complex observed by biomonitoring. • Higher arsenic and PAHs exposure associated with adverse renal function. [ABSTRACT FROM AUTHOR]

Background: Evidence shows a high incidence of insulin resistance, inflammation and dyslipidemia in adult obesity. The aim of this study was to assess the relevance of inflammatory markers, circulating lipids, and insulin sensitivity in overweight/obese children., Methods: We enrolled 45 male children (aged 6 to 13 years, lean control = 16, obese = 19, overweight = 10) in this study. The plasma total cholesterol, HDL cholesterol, triglyceride, glucose and insulin levels, the circulating levels of inflammatory factors, such as TNF-α, IL-6, and MCP-1, and the high-sensitive CRP level were determined using quantitative colorimetric sandwich ELISA kits., Results: Compared with the lean control subjects, the obese subjects had obvious insulin resistance, abnormal lipid profiles, and low-grade inflammation. The overweight subjects only exhibited significant insulin resistance and low-grade inflammation. Both TNF-α and leptin levels were higher in the overweight/obese subjects. A concurrent correlation analysis showed that body mass index (BMI) percentile and fasting insulin were positively correlated with insulin resistance, lipid profiles, and inflammatory markers but negatively correlated with adiponectin. A factor analysis identified three domains that explained 74.08% of the total variance among the obese children (factor 1: lipid, 46.05%; factor 2: obesity-inflammation, 15.38%; factor 3: insulin sensitivity domains, 12.65%)., Conclusions: Our findings suggest that lipid, obesity-inflammation, and insulin sensitivity domains predominantly exist among obese children. These factors might be applied to predict the outcomes of cardiovascular diseases in the future.