Advantages and Applications of Transforming Empirical Model Input Space with Dimensional Models

Model-based calibration of steady-state engine operation is commonly performed with highly parameterized empirical models that are accurate but not very robust, particularly when predicting highly nonlinear responses such as diesel smoke emissions. To address this problem, and to boost the accuracy of more robust non-parametric methods to the same level, GT-Power was used to transform the empirical model input space into multiple input spaces that simplified the input-output relationship and improved the accuracy and robustness of smoke predictions made by three commonly used empirical modeling methods: Multivariate Regression, Neural Networks and the k-Nearest Neighbor method. The availability of multiple input spaces allowed the development of two committee techniques: a 'Simple Committee' technique that used averaged predictions from a set of 10 pre-selected input spaces chosen by the training data and the "Minimum Variance Committee" technique where the input spaces for each prediction were chosen on the basis of disagreement between the three modeling methods. This latter technique equalized the performance of the three modeling methods. The successively increasing improvements resulting from the use of a single best transformed input space (Best Combination Technique), Simple Committee Technique and Minimum Variance Committee Technique were verified with hypothesis testing. The transformed input spaces were also shown to improve outlier detection and to improve k-Nearest Neighbor performance when predicting dynamic emissions with steady-state training data. An unexpected finding was that the benefits of input space transformation were unaffected by changes in the hardware or the calibration of the underlying GT-Power model.

Abandoned Coal Mine Drainage and Its Remediation: Impacts on Stream Ecosystem Structure and Function

The effects of abandoned mine drainage (AMD) on streams and responses to remediation efforts were studied using three streams (AMD-impacted, remediated, reference) in both the anthracite and the bituminous coal mining regions of Pennsylvania (USA). Response variables included ecosystem function as well as water chemistry and macroinvertebrate community composition. The bituminous AMD stream was extremely acidic with high dissolved metals concentrations, a prolific mid-summer growth of the filamentous alga, Mougeotia, and .10-fold more chlorophyll than the reference stream. The anthracite AMD stream had a higher pH, substrata coated with iron hydroxide(s), and negligible chlorophyll. Macroinvertebrate communities in the AMD streams were different from the reference streams, the remediated streams, and each other. Relative to the reference stream, the AMD stream(s) had (1) greater gross primary productivity (GPP) in the bituminous region and undetectable GPP in the anthracite region, (2) greater ecosystem respiration in both regions, (3) greatly reduced ammonium uptake and nitrification in both regions, (4) lower nitrate uptake in the bituminous (but not the anthracite) region, (5) more rapid phosphorus removal from the water column in both regions, (6) activities of phosphorus-acquiring, nitrogenacquiring, and hydrolytic-carbon-acquiring enzymes that indicated extreme phosphorus limitation in both regions, and (7) slower oak and maple leaf decomposition in the bituminous region and slower oak decomposition in the anthracite region. Remediation brought chlorophyll concentrations and GPP nearer to values for respective reference streams, depressed ecosystem respiration, restored ammonium uptake, and partially restored nitrification in the bituminous (but not the anthracite) region, reduced nitrate uptake to an undetectable level, restored phosphorus uptake to near normal rates, and brought enzyme activities more in line with the reference stream in the bituminous (but not the anthracite) region. Denitrification was not detected in any stream. Water chemistry and macroinvertebrate community structure analyses capture the impact of AMD at the local reach scale, but functional measures revealed that AMD has ramifications that can cascade to downstream reaches and perhaps to receiving estuaries.

Use of a State-Level Pharmaceutical Assistance Program Among Urban and Rural Elders

A number of state-level pharmaceutical assistance programs have been established as a result of the growing recognition of the role of pharmaceuticals in the long-term care of the elderly. However, existing research does not provide a coherent expectation for patterns of use by rural and urban elderly. The data for this analysis are drawn from a larger study of the Pennsylvania Pharmaceutical Assistance Contract for the Elderly (PACE). PACE provides prescription medicines for elderly who meet income requirements. The research project was designed to assess the characteristics of PACE program participants and non-participants on a wide range of issues. Chi-square analysis and regression models were used to assess the association between rural and urban residence and access to the PACE Program. The results indicate that rural/urban status of the elderly is not a significant predictor of the use of PACE. Other traditional variables (e.g., health self-rating and physician visits) did predict difference in the pattern of use.