The Experts below are selected from a list of 83382 Experts worldwide ranked by ideXlab platform
Jery R. Stedinger - One of the best experts on this subject based on the ideXlab platform.
-
Artificial Neural Network Models of Watershed Nutrient Loading
Water Resources Management, 2012Co-Authors: Daniel P. Loucks, Jery R. StedingerAbstract:This paper illustrates the use of artificial neural networks (ANNs) as predictors of the nutrient load from a watershed. Accurate prediction of pollutant Loadings has been recognized as important for determining effective water management strategies. This study compares Haith’s Generalized Watershed Loading Function (GWLF) and Arnold’s Soil and Water Assessment Tool (SWAT) to multilayer artificial neural networks for monthly watershed load modeling. The modeling results indicate that calibrated feed-forward ANN models provide prediction which are always essentially as accurate as those obtained with GWLF and the SWAT, and some times much more accurate. With its flexibility and computation efficiency, the ANN should be a useful tool to obtain a quick simulation assessment of nutrient Loading for various management strategies.
-
Artificial Neural Network Models of Watershed Nutrient Loading
Water Resources Management, 2012Co-Authors: Raymond J. Kim, Daniel P. Loucks, Jery R. StedingerAbstract:This paper illustrates the use of artificial neural networks (ANNs) as predictors of the nutrient load from a watershed. Accurate prediction of pollutant Loadings has been recognized as important for determining effective water management strategies. This study compares Haith’s Generalized Watershed Loading Function (GWLF) and Arnold’s Soil and Water Assessment Tool (SWAT) to multilayer artificial neural networks for monthly watershed load modeling. The modeling results indicate that calibrated feed-forward ANN models provide prediction which are always essentially as accurate as those obtained with GWLF and the SWAT, and some times much more accurate. With its flexibility and computation efficiency, the ANN should be a useful tool to obtain a quick simulation assessment of nutrient Loading for various management strategies. Copyright Springer Science+Business Media B.V. 2012
Y. D. Park - One of the best experts on this subject based on the ideXlab platform.
-
A cell culturing system that integrates the cell Loading Function on a single platform and evaluation of the pulsatile pumping effect on cells
Biomedical Microdevices, 2008Co-Authors: H. Park, K. H. Kwon, J. Y. Park, J. Y. Baek, H. R. Song, Y. D. ParkAbstract:In this paper, we present a novel microfluidic system with pulsatile cell storing, cell-delivering and cell culturing Functions on a single PDMS platform. For this purpose, we have integrated two reservoirs, a pulsatile pumping system containing two soft check valves, which were fabricated by in situ photopolymerization, six switch valves, and three cell culture chambers all developed through a simple and rapid fabrication process. The sample volume delivered per stroke was 120 nl and the transported volume was linearly related to the pumping frequency. We have investigated the effect of the pulsatile pneumatic micropumping on the cells during transport. For this purpose, we pumped two types of cell suspensions, one containing human breast adenocarcinoma cells (MCF-7) and the other mesenchymal stem cells (hMSCs) derived from bone marrow. The effect of pulsatile pumping on both cell types was examined by short and long-term culture experiments. Our results showed that the characteristics of both cells were maintained; they were not damaged by the pumping system. Evaluations were carried out by morphological inspection, viability assay and immunophenotyping analysis. The delivered MCF-7 cells and hMSCs spread and proliferated onto the gelatin coated cell culture chamber. This total micro cell culture system can be applied to cell-based high throughput screening and for co-culture of different cells with different volume.
Huiliang Wang - One of the best experts on this subject based on the ideXlab platform.
-
Variations in source apportionments of nutrient load among seasons and hydrological years in a semi-arid watershed: GWLF model results.
Environmental science and pollution research international, 2014Co-Authors: Wangshou Zhang, Huiliang WangAbstract:Quantifying source apportionments of nutrient load and their variations among seasons and hydrological years can provide useful information for watershed nutrient load reduction programs. There are large seasonal and inter-annual variations in nutrient loads and their sources in semi-arid watersheds that have a monsoon climate. The Generalized Watershed Loading Function model was used to simulate monthly nutrient loads from 2004 to 2011 in the Liu River watershed, Northern China. Model results were used to investigate nutrient load contributions from different sources, temporal variations of source apportionments and the differences in the behavior of total nitrogen (TN) and total phosphorus (TP). Examination of source apportionments for different seasons showed that point sources were the main source of TN and TP in the non-flood season, whereas contributions from diffuse sources, such as rural runoff, soil erosion, and urban areas, were much higher in the flood season. Furthermore, results for three typical hydrological years showed that the contribution ratios of nutrient loads from point sources increased as streamflow decreased, while contribution ratios from rural runoff and urban area increased as streamflow increased. Further, there were significant differences between TN and TP sources on different time scales. Our findings suggest that priority actions and management measures should be changed for different time periods and hydrological conditions, and that different strategies should be used to reduce loads of nitrogen and phosphorus effectively.
Masayasu Ohtsu - One of the best experts on this subject based on the ideXlab platform.
-
Strain-space plasticity model for the compressive hardening-softening behaviour of concrete
Construction and Building Materials, 1995Co-Authors: Ahmed M. Farahat, Masashi Kawakami, Masayasu OhtsuAbstract:Abstract Concrete exhibits strong strain-softening behaviour in the post-failure range. To simulate the strains-oftening behaviour in concrete structures, numerous stress-space plasticity models have been proposed. Unfortunately, it is found that the application of the stress-space formulation of plasticity to concrete encounters difficulties in modelling the softening behaviour since it cannot explicitly give a clear distinction of Loading, unLoading and neutral Loading. Strain-space formulation is therefore rational for further progress. Although several strain-space plasticity models are proposed, these models can simulate the strain-softening behaviour of concrete only under low confining pressure and they lack experimental verification since the available test data with softening behaviour are very limited. In this paper, a general form of strain-space plasticity formulations applied to strain-hardening-softening materials under both low and high confining pressure is developed. The strain-space formulation is presented by introducing the Loading Function as well as the plastic potential Function, corresponding to those of Drucker-Prager type in the stress space. Two material parameters of the failure surface are determined from the test data on the compressive meridian. Experimental work is carried out to determine the model parameters. The model simulation is performed not only for the current experimental data but also for most of the available test data to demonstrate the capability of the model. It is found that the model can sufficiently predict the hardening as well as the softening behaviour of concrete under both low and high confining pressure.
Daniel P. Loucks - One of the best experts on this subject based on the ideXlab platform.
-
Artificial Neural Network Models of Watershed Nutrient Loading
Water Resources Management, 2012Co-Authors: Daniel P. Loucks, Jery R. StedingerAbstract:This paper illustrates the use of artificial neural networks (ANNs) as predictors of the nutrient load from a watershed. Accurate prediction of pollutant Loadings has been recognized as important for determining effective water management strategies. This study compares Haith’s Generalized Watershed Loading Function (GWLF) and Arnold’s Soil and Water Assessment Tool (SWAT) to multilayer artificial neural networks for monthly watershed load modeling. The modeling results indicate that calibrated feed-forward ANN models provide prediction which are always essentially as accurate as those obtained with GWLF and the SWAT, and some times much more accurate. With its flexibility and computation efficiency, the ANN should be a useful tool to obtain a quick simulation assessment of nutrient Loading for various management strategies.
-
Artificial Neural Network Models of Watershed Nutrient Loading
Water Resources Management, 2012Co-Authors: Raymond J. Kim, Daniel P. Loucks, Jery R. StedingerAbstract:This paper illustrates the use of artificial neural networks (ANNs) as predictors of the nutrient load from a watershed. Accurate prediction of pollutant Loadings has been recognized as important for determining effective water management strategies. This study compares Haith’s Generalized Watershed Loading Function (GWLF) and Arnold’s Soil and Water Assessment Tool (SWAT) to multilayer artificial neural networks for monthly watershed load modeling. The modeling results indicate that calibrated feed-forward ANN models provide prediction which are always essentially as accurate as those obtained with GWLF and the SWAT, and some times much more accurate. With its flexibility and computation efficiency, the ANN should be a useful tool to obtain a quick simulation assessment of nutrient Loading for various management strategies. Copyright Springer Science+Business Media B.V. 2012