• Steel and Composite Structures
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• 제34권5호
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2011년도 학술발표회
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• Clinical and Experimental Pediatrics
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• 제51권9호
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• pp.964-970
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• 2008

목 적 : 메틸말로닌산뇨증과 프로피오닌산뇨증은 상염색체 열성으로 유전되는 아미노산 대사 이상 질환으로, methylmalonyl-CoA mutase와 propionyl-CoA carboxylse의 결함에 의해 발생하며 최근 유전자형에 대한 연구가 활발히 이루어지고 있다. 저자들은 단일기관에서 경험한 이 질환군의 임상 양상과 유전자형에 대해 조사하고자 하였다. 방 법 : 1993년부터 2007년까지 서울아산병원 소아과에서 유기산뇨증으로 진단된 20례를 대상으로 질병의 종류, 진단시 연령과 임상 양상, 유전자형, 검사 소견, 치료와 예후 등을 후향적으로 분석하였다. 혈장 암모니아, 소변 유기산 분석과 혈장 아미노산을 조사하였고, 유전자분석은 메틸말로닌산뇨증에서는 MUT, MMAA, MMAB 와 MMACHC 유전자를, 프로피오닌산뇨증에서는 PCCA와 PCCB 유전자를 분석하였다. 결 과 : 유기산뇨증으로 진단된 환아는 모두 20명이었으며, 그 중 메틸말로닌산뇨증이 12명(남아 8명, 여아 4명), 프로피오닌산뇨증이 8명(남아 6명, 여아 2명)이었다. 신생아 대사이상 검사로 진단된 환아가 5명이었으며, 6명은 신생아기에 급성 증상으로 발현하였고, 9명은 1개월 이후 발현한 지발형이었다. 신생아기 발현형에서는 6명 중 5명이 구토와 기면을 주증상으로 내원하였으며, 지발형에서는 구토와 기면 이외에도 발달 지연, 보행 장애, 혈소판 감소증 등 다양한 임상 양상을 보였다. 예후로는 메틸말로닌산뇨증 환아 중 2명(17%)이 2세경에 고암모니아혈증과 대사성 산증으로 사망하였으며, 7명(58%)이 정상발달을 보였다. 프로피오닌산뇨증 환아는 1명이 사망하였고, 4명(50%)이 정상 발달을 보이고 있다. 증상의 발현시기에 따라서는 신생아기 발현형에서 6명중에서 2명은 사망, 2명은 정상 발달, 2명은 발달지연을 보이고 있는 것에 비해, 증상 없이 신생아 대사이상 검사로 진단된 환아 중에는 2명(40%)이 정상발달을 보이고 있고, 지발형에서는 7명(63%)이 정상 발달을 보이고 있다. 유전자형은 메틸말로닌산뇨증 전례에서 규명되었으며 10명은 MUT 유전자에서 11종의 서로 다른 돌연변이가 발견되었는데 대부분 nonsense 돌연변이였다. 비타민 B12 반응형 환아 2명에서는 MMACHC 유전자에서 3종의 서로 다른 돌연변이가 발견되었으며 프로피오닌산뇨증에서는 16개 대립유전자 중 14개에서 PCCA와 PCCB 유전자의 돌연변이가 규명되었다. 결 론 : 유기산뇨증은 진단이 지연되면 매우 치명적이나, 조기에 의심하여 진단하고 적절히 치료하면 좋은 예후를 기대할 수 있는 질환이다. 유기산뇨증의 유전자형의 분석은 정확한 진단을 가능하게 할 뿐 아니라 유전상담, 산전 진단 및 표현형의 예측에도 도움이 된다.