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.

Global Search for Minimum Energy (H2O)n Clusters, n = 3−5

The Gaussian-3 (G3) model chemistry method has been used to calculate the relative ΔG° values for all possible conformers of neutral clusters of water, (H2O)n, where n = 3−5. A complete 12-fold conformational search around each hydrogen bond produced 144, 1728, and 20 736 initial starting structures of the water trimer, tetramer, and pentamer. These structures were optimized with PM3, followed by HF/6-31G* optimization, and then with the G3 model chemistry. Only two trimers are present on the G3 potential energy hypersurface. We identified 5 tetramers and 10 pentamers on the potential energy and free-energy hypersurfaces at 298 K. None of these 17 structures were linear; all linear starting models folded into cyclic or three-dimensional structures. The cyclic pentamer is the most stable isomer at 298 K. On the basis of this and previous studies, we expect the cyclic tetramers and pentamers to be the most significant cyclic water clusters in the atmosphere.

Ability of the PM3 Quantum Mechanical Method to Model Intermolecular Hydrogen Bonding between Neutral Molecules

The PM3 semiempirical quantum-mechanical method was found to systematically describe intermolecular hydrogen bonding in small polar molecules. PM3 shows charge transfer from the donor to acceptor molecules on the order of 0.02-0.06 units of charge when strong hydrogen bonds are formed. The PM3 method is predictive; calculated hydrogen bond energies with an absolute magnitude greater than 2 kcal mol-' suggest that the global minimum is a hydrogen bonded complex; absolute energies less than 2 kcal mol-' imply that other van der Waals complexes are more stable. The geometries of the PM3 hydrogen bonded complexes agree with high-resolution spectroscopic observations, gas electron diffraction data, and high-level ab initio calculations. The main limitations in the PM3 method are the underestimation of hydrogen bond lengths by 0.1-0.2 for some systems and the underestimation of reliable experimental hydrogen bond energies by approximately 1-2 kcal mol-l. The PM3 method predicts that ammonia is a good hydrogen bond acceptor and a poor hydrogen donor when interacting with neutral molecules. Electronegativity differences between F, N, and 0 predict that donor strength follows the order F > 0 > N and acceptor strength follows the order N > 0 > F. In the calculations presented in this article, the PM3 method mirrors these electronegativity differences, predicting the F-H- - -N bond to be the strongest and the N-H- - -F bond the weakest. It appears that the PM3 Hamiltonian is able to model hydrogen bonding because of the reduction of two-center repulsive forces brought about by the parameterization of the Gaussian core-core interactions. The ability of the PM3 method to model intermolecular hydrogen bonding means reasonably accurate quantum-mechanical calculations can be applied to small biologic systems.

Teacher resistance to school-based consultation with the school psychologist: An analysis according to school level and model of identification for special education services

Consultation is promoted throughout school psychology literature as a best practice in service delivery. This method has numerous benefits including being able to work with more students at one time, providing practitioners with preventative rather than strictly reactive strategies, and helping school professionals meet state and federal education mandates and initiatives. Despite the benefits of consultation, teachers are sometimes resistant to this process.This research studies variables hypothesized to lead to resistance (Gonzalez, Nelson, Gutkin, & Shwery, 2004) and attempts to distinguish differences between school level (elementary, middle and high school) with respect to the role played by these variables and to determine if the model used to identify students for special education services has an influence on resistance factors. Twenty-sixteachers in elementary and middle schools responded to a demographicquestionnaire and a survey developed by Gonzalez, et al. (2004). This survey measures eight variables related to resistance to consultation. No high school teachers responded to the request to participate. Results of analysis of variance indicated a significant difference in the teaching efficacy subscale with elementary teachers reporting more efficacy in teaching than middle school teachers. Results also indicate a significant difference in classroom managementefficacy with teachers who work in schools that identify students according to a Response to Intervention model reporting higher classroom management efficacy than teachers who work in schools that identify students according to a combined method of refer-test-place/RtI combination model. Implications, limitations and directions for future research are discussed.