• Journal of Korean Society of Forest Science
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• v.86 no.4
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• pp.435-442
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• 1997

The research was carried out to investigate the contamination of stream water by the acid mine drainage originated from the abandoned coal mines and coal waste rock in Keumsan, Chungnam. The pH, sulfate and chemical compositions in the stream water were analyzed. At the polluted sites, the pH of stream water was the strong acid, ranging from 3.46 to 4.29. The pH shows negative correlations with sulfate, manganese, copper, zinc, iron and magnesium concentrations. Sulfate concentrations of the polluted stream water, 236.73-310.53mg/l, had 10 times more than those of the non-polluted stream water. The concentrations of heavy metals, Mn and Fe, in the polluted water were 0.56 - 0.83mg/l and 5.89 - 10.58mg/l, respectively. The Mn concentrations were 20 times higher than those of the non-polluted stream water. Compared with those in the non-polluted stream water, the Mg and Ca concentrations in the polluted stream water were high because of leaching from rock and soil to water by the acidifications. Calculated AMDI(Acid Mine Drainage Index) values are low in the polluted stream water, relative to those of the non-polluted water.

• Structural Engineering and Mechanics
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• v.88 no.3
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• pp.239-249
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• 2023

The Radial Point Interpolation Method (RPIM) has been proposed to overcome the difficulties associated with the use of the Radial Basis Functions (RBFs). The RPIM has the following properties: Simple implementation in terms of boundary conditions as in the Finite Element Method (FEM). A less expensive CPU time compared to other collocation meshless methods such as the Moving Least Square (MLS) collocation method. In this work, we propose an adaptive high-order numerical algorithm based on RPIM to simulate the thermoviscoplastic behavior of a material mixing observed in the Friction Stir Welding (FSW) process. The proposed adaptive meshfree RPIM algorithm adapts well to the geometric and physical data by choosing a good shape parameter with a good precision. Our numerical approach combines the RPIM and the Asymptotic Numerical Method (ANM). A numerical procedure is also proposed in this work to automatically determine an improved shape parameter for the RBFs. The efficiency of the proposed algorithm is analyzed in comparison with an iterative algorithm.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.9
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• pp.4031-4035
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• 2015

Background: Breast cancer is one of the most feared diseases among women and it could induce the development of psychological disorders like anxiety and depression. An assessment was here performed of the status and to determine contributory factors. Materials and Methods: A cross-sectional study was conducted among breast cancer patients at University Kebangsaan Malaysia Medical Center (UKMMC), Kuala Lumpur. A total of 205 patients who were diagnosed between 2007 until 2010 were interviewed using the questionnaires of Hospital Anxiety and Depression (HADS). The associated factors investigated concerned socio-demographics, socio economic background and the cancer status. Descriptive analysis, chi-squared tests and logistic regression were used for the statistical test analysis. Results: The prevalence of anxiety was 31.7% (n=65) and of depression was 22.0% (n=45) among the breast cancer patients. Age group (p= 0.032), monthly income (p=0.015) and number of visits per month (p=0.007) were significantly associated with anxiety. For depression, marital status (p=0.012), accompanying person (p=0.041), financial support (p-0.007) and felt burden (p=0.038) were significantly associated. In binary logistic regression, those in the younger age group were low monthly income were 2 times more likely to be associated with anxiety. Having less financial support and being single were 3 and 4 times more likely to be associated with depression. Conclusions: In management of breast cancer patients, more care or support should be given to the young and low socio economic status as they are at high risk of anxiety and depression.