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Desi Suantari 한국역학회 2021 Epidemiology and Health Vol.43 No.-
OBJECTIVES: Data are not available in Indonesia to measure the main indicators of zero new infections, zero acquired immune deficiency syndrome (AIDS)-related deaths and zero discrimination. This study aimed to determine factors related to misconceptions about human immunodeficiency virus (HIV) transmission and the stigma against people living with HIV/AIDS (PLWHA) in Indonesia METHODS: This cross-sectional study used secondary data from the 2017 Indonesia Demographic and Health Survey (IDHS). The sample was women and men aged 17-45 years and married (n=3,023). RESULTS: Education and wealth index quintile were significantly related to misconceptions about HIV transmission. Respondents with low levels of education were more likely to have misconceptions about HIV transmission. Respondents who were in the poorest, poorer, middle, and richer quintiles of the wealth index were more likely to have misconceptions about HIV transmission than those in the richest quintile. Educational level, employment status, and wealth index quintile were predictors of stigma against PLWHA. CONCLUSIONS: There are still many Indonesian people with misconceptions about HIV transmission and stigma against PLWHA. Future studies should focus on educational programs or interventions aimed at increasing public knowledge and awareness, promoting compassion towards PLWHA, and emphasizing respect for the rights of PLWHA. These interventions are particularly important for populations who are uneducated and living in poverty.
Estimation of Change in Global Mean Temperature Based on Machine/Deep Learning of Global Data
Desy Caesary,Soo Jin Jang(장수진),Seo Young Song(송서영),Myung Jin Nam(남명진) 한국신재생에너지학회 2021 한국신재생에너지학회 학술대회논문집 Vol.2021 No.7
Continuous increase in anthropogenic CO<SUB>2</SUB> emission can cause rise in global mean temperature (GMT). Many studies have been made to build climate models for the estimation of change in GMT based on several climate factors such as greenhouse gas (GHG) emissions and net ecosystem exchange (NEE). However, the complexity of the climate factors possibly causes uncertainties in climate models leading to an inaccurate estimation of GMT. To overcome the uncertainties, this study applies machine and deep learning (M/DL) methods to the analysis on the relationship links between climate factors and changes in GMT. The pattern learning ability supports more objective analysis on climate models. The input data of climate factors include CO<SUB>2</SUB> and non-CO<SUB>2</SUB> concentration, and NEE global data during 1999~2012, which are currently available. The available data were mostly annual, thus were interpolated to generate more data for the training process of DL. The open-source library of support vector machine (SVM) and artificial neural network (ANN) methods were used. A better-trained model was observed from the ANN with more interpolated data, whereas SVM had difficulty in finding optimal prediction parameters due to the high non-linearity input data.
Geophysical Monitoring on Controlled CO<sub>2</sub> Released Field Experiments: a Review Study
( Desy Caesary ),( Seo Young Song ),( Huieun Yu ),( Myung Jin Nam ) 대한지질공학회 2019 대한지질공학회 학술발표회논문집 Vol.2019 No.2
Geologically sequestrated carbon dioxide (CO<sub>2</sub>) in deep subsurface can leak through leaky well or fault, thus the storage fails. Leaked CO<sub>2</sub> contaminates groundwater when reaching to the atmosphere. Many field experiments of releasing CO<sub>2</sub> into shallow depth in test bed sites, have been made not only to understand impacts of CO<sub>2</sub> in shallow groundwater or atmosphere but also to test monitoring methods for detecting the leaked CO<sub>2</sub>. Among various monitoring methods, geophysical methods have been widely utilized to detect CO<sub>2</sub> plume migration in shallow depth before CO<sub>2</sub>’s reaching to the atmosphere. This study reviews and analyzes geophysical monitoring experiments and results in seven existing field experiment sites. In several fields, geophysical measurements were carried out in time-lapse manners to monitor changes in physical properties of subsurface due to the presence of CO<sub>2</sub> before and during injection, while a couple of fields conducted CO<sub>2</sub> monitoring even after injection has been finished. After the analysis, this study not only summarizes changes in subsurface physical properties such as bulk electrical resistivity, complex resistivity and permittivity, but also analyzes effects of geological conditions on the changes in physical properties; whether the CO<sub>2</sub> injection zone is saturated or vadose zone, contains calcite minerals or clay, precipitation rate, etc. Further, this paper will also introduce tests of geophysical monitoring for shallow CO<sub>2</sub> injection experiment in Korea. This research was supported by KEITI (Project Number: 2018001810002), and partly by KETEP (No. 20194010201920).
Sesquiterpenoids from the Stem Bark of Aglaia grandis
Desi Harneti,Atika Ayu Permatasari,Amallya Anisshabira,Al Arofatus Naini,Nurlelasari,Tri Mayanti,Rani Maharani,Agus Safari,Ace Tatang Hidayat,Kindi Farabi,Unang Supratman,Mohamad Nurul Azmi,Yoshihito 한국생약학회 2022 Natural Product Sciences Vol.28 No.1
Five sesquiterpenoids, 7-epi-eudesm-4(15)-ene,1β,6α-diol (1), 7-epi-eudesm-4(15)-ene,1β,6α-diol (2), saniculamoid D (3), aphanamol I (4), and 4β,10α-dihydroxyaromadendrane (5), were isolated from the stem bark of Aglaia grandis. The compounds’ (1-5) chemical structures were identified by spectroscopic data including, IR, NMR (1H, 13C, DEPT 135°, HMQC, HMBC, 1H-1H COSY), and HRTOFMS, as well as by comparing with the previously reported spectral data. Therefore, this study described the structural elucidation of compounds 1-5 and evaluated their cytotoxic effects against Hela cervical and B16F10 melanoma cells for the first time, but no significant result was discovered.