Biomedical subjects

Sheng-Wei Wang

Publications and source records attributed to Sheng-Wei Wang.

7 recordsLinked to original sources

PubMed2006

Spatial analysis of potential carcinogenic risks associated with ingesting arsenic in aquacultural tilapia (Oreochromis mossambicus) in blackfoot disease hyperendemic areas.

This work analyzed spatially potential carcinogenic risks associated with ingesting arsenic (As) contents in aquacultural tilapia (Oreochromis mossambicus) in coastal regions of southwestern Taiwan, where the blackfoot disease prevails. Sequential indicator simulation (SIS) was used to reproduce As exposure distributions in groundwater based on their three-dimensional variability. A target cancer risk (TR) associated with ingesting As in aquacultural tilapia was calculated to evaluate the potential risk to human health. Owing to sparse measured data, Monte Carlo simulation and SIS properly accounted for the uncertainty of assessed parameters. The probabilistic risk assessment formulated suitable strategies under various remedial stages. Aquacultural regions with high risks were mapped to elucidate the safety of groundwater use at different depths. Many TRs determined from the risks at the 75th and 95th percentiles exceed one millionth in the regions, indicating that ingesting tilapia farmed in the highly As-polluted regions poses potential cancer threats to human health. The 75th percentile of TR is considered in formulating a remedial strategy for the aquacultural use of groundwater in the preliminary stage. Additionally, this study suggests reducing the use of groundwater in aquaculture or changing the depths from which groundwater is withdrawn in the areas with high risks of cancer.

Animals↗

PubMed2006

Random sampling-high dimensional model representation (RS-HDMR) and orthogonality of its different order component functions.

High dimensional model representation is under active development as a set of quantitative model assessment and analysis tools for capturing high-dimensional input-output system behavior based on a hierarchy of functions of increasing dimensions. The HDMR component functions are optimally constructed from zeroth order to higher orders step-by-step. This paper extends the definitions of HDMR component functions to systems whose input variables may not be independent. The orthogonality of the higher order terms with respect to the lower order ones guarantees the best improvement in accuracy for the higher order approximations. Therefore, the HDMR component functions are constructed to be mutually orthogonal. The RS-HDMR component functions are efficiently constructed from randomly sampled input-output data. The previous introduction of polynomial approximations for the component functions violates the strictly desirable orthogonality properties. In this paper, new orthonormal polynomial approximation formulas for the RS-HDMR component functions are presented that preserve the orthogonality property. An integrated exposure and dose model as well as ionospheric electron density determined from measured ionosonde data are used as test cases, which show that the new method has better accuracy than the prior one.

Algorithms↗

PubMed2006

Occurrence of arsenic in ground water in the Choushui River alluvial fan, Taiwan.

An investigation of shallow ground water quality revealed that high arsenic (As) concentrations were found in both aquifers and aquitards in the southern Choushui River alluvial fan of Taiwan. A total of 655 geological core samples from 13 drilling wells were collected and analyzed. High As contents were found primarily in aquitards, to a maximum of 590 mg/kg. The contents were correlated with the locations of the marine sequences. Additionally, strong correlations among the As concentrations of core samples, the clay, and the geological age of the Holocene transgression were identified. Most of the As in ground water originated from the aquitard of the marine sequence. The high As content in marine formations with high clay contents may be attributable to the bioaccumulation of As in the sea organisms, which accrued and were deposited in the formation. A preliminary geogenic model of the origin of the high As concentration in the shallow sedimentary basin of the Choushui River alluvial fan of Taiwan is proposed.

Arsenic↗

PubMed2005

Children's residential exposure to chlorpyrifos: application of CPPAES field measurements of chlorpyrifos and TCPy within MENTOR/SHEDS-Pesticides model.

The comprehensive individual field-measurements on non-dietary exposure collected in the Children's-Post-Pesticide-Application-Exposure-Study (CPPAES) were used within MENTOR/SHEDS-Pesticides, a physically based stochastic human exposure and dose model. In this application, however, the model was run deterministically. The MENTOR/SHEDS-Pesticides employed the CPPAES as input variables to simulate the exposure and the dose profiles for seven children over a 2-week post-application period following a routine residential and professional indoor crack-and-crevice chlorpyrifos application. The input variables were obtained from a personal activity diary, microenvironmental measurements and personal biomonitoring data obtained from CPPAES samples collected from the individual children and in their homes. Simulation results were compared with CPPAES field measured values obtained from the children's homes to assess the utility of the different microenvironmental data collected in CPPAES, i.e. indicator toys and wipe samplers to estimate aggregate exposures that can be result from one or more exposure pathways and routes. The final analyses of the database involved comparisons of the actual data obtained from the individual biomarker samples of a urinary metabolite of chlorpyrifos (TCPy) and the values predicted by MENTOR/SHEDS-Pesticides using the CPPAES-derived variables. Because duplicate diet samples were not part of the CPPAES study design, SHEDs-Pesticides simulated dose profiles did not account for the dietary route. The research provided more confidence in the types of data that can be used in the inhalation and dermal contact modules of MENTOR/SHEDS-Pesticides to predict the pesticide dose received by a child. It was determined that we still need additional understanding about: (1) the types of activities and durations of activities that result in non-dietary ingestion of pesticides and (2) the influence of dietary exposures on the levels of TCPy found in the urine.

Air Pollutants↗

PubMed2005

A source-to-dose assessment of population exposures to fine PM and ozone in Philadelphia, PA, during a summer 1999 episode.

A novel source-to-dose modeling study of population exposures to fine particulate matter (PM(2.5)) and ozone (O(3)) was conducted for urban Philadelphia. The study focused on a 2-week episode, 11-24 July 1999, and employed the new integrated and mechanistically consistent source-to-dose modeling framework of MENTOR/SHEDS (Modeling Environment for Total Risk studies/Stochastic Human Exposure and Dose Simulation). The MENTOR/SHEDS application presented here consists of four components involved in estimating population exposure/dose: (1) calculation of ambient outdoor concentrations using emission-based photochemical modeling, (2) spatiotemporal interpolation for developing census-tract level outdoor concentration fields, (3) calculation of microenvironmental concentrations that match activity patterns of the individuals in the population of each census tract in the study area, and (4) population-based dosimetry modeling. It was found that the 50th percentiles of calculated microenvironmental concentrations of PM(2.5) and O(3) were significantly correlated with census-tract level outdoor concentrations, respectively. However, while the 95th percentiles of O(3) microenvironmental concentrations were strongly correlated with outdoor concentrations, this was not the case for PM(2.5). By further examining the modeled estimates of the 24-h aggregated PM(2.5) and O(3) doses, it was found that indoor PM(2.5) sources dominated the contributions to the total PM(2.5) doses for the upper 5 percentiles, Environmental Tobacco Smoking (ETS) being the most significant source while O(3) doses due to time spent outdoors dominated the contributions to the total O(3) doses for the upper 5 percentiles. The MENTOR/SHEDS system presented in this study is capable of estimating intake dose based on activity level and inhalation rate, thus completing the source-to-dose modeling sequence. The MENTOR/SHEDS system also utilizes a consistent basis of source characterization, exposure factors, and human activity patterns in conducting population exposure assessment of multiple co-occurring air pollutants, and this constitutes a primary distinction from previous studies of population exposure assessment, where different exposure factors and activity patterns would be used for different pollutants. Future work will focus on incorporating the effects of commuting patterns on population exposure/dose assessments as well as on extending the MENTOR/SHEDS applications to seasonal/annual studies and to other areas in the U.S.

Air Pollutants↗

PubMed2003

High-dimensional model representations generated from low order terms--lp-RS-HDMR.

High-dimensional model representation (HDMR) is a general set of quantitative model assessment and analysis tools for improving the efficiency of deducing high dimensional input-output system behavior. RS-HDMR is a particular form of HDMR based on random sampling (RS) of the input variables. The component functions in an HDMR expansion are optimal choices tailored to the n-variate function f(x) being represented over the desired domain of the n-dimensional vector x. The high-order terms (usually larger than second order, or equivalently beyond cooperativity between pairs of variables) in the expansion are often negligible. When it is necessary to go beyond the first and the second order RS-HDMR, this article introduces a modified low-order term product (lp)-RS-HDMR method to approximately represent the high-order RS-HDMR component functions as products of low-order functions. Using this method the high-order truncated RS-HDMR expansions may be constructed without directly computing the original high-order terms. The mathematical foundations of lp-RS-HDMR are presented along with an illustration of its utility in an atmospheric chemical kinetics model.

Journal Article↗

PubMed2003

Correlation method for variance reduction of Monte Carlo integration in RS-HDMR.

The High Dimensional Model Representation (HDMR) technique is a procedure for efficiently representing high-dimensional functions. A practical form of the technique, RS-HDMR, is based on randomly sampling the overall function and utilizing orthonormal polynomial expansions. The determination of expansion coefficients employs Monte Carlo integration, which controls the accuracy of RS-HDMR expansions. In this article, a correlation method is used to reduce the Monte Carlo integration error. The determination of the expansion coefficients becomes an iteration procedure, and the resultant RS-HDMR expansion has much better accuracy than that achieved by direct Monte Carlo integration. For an illustration in four dimensions a few hundred random samples are sufficient to construct an RS-HDMR expansion by the correlation method with an accuracy comparable to that obtained by direct Monte Carlo integration with thousands of samples.

Journal Article↗