A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

MULTIPLE MODEL EVALUATION ABSENT THE GOLD STANDARD VIA MODEL COMBINATION

We describe a method for evaluating an ensemble of predictive models given a sample of observations comprising the model predictions and the outcome event measured with error. Our formulation allows us to simultaneously estimate measurement error parameters, true outcome — aka the gold standard — and a relative weighting of the predictive scores. We describe conditions necessary to estimate the gold standard and for these estimates to be calibrated and detail how our approach is related to, but distinct from, standard model combination techniques. We apply our approach to data from a study to evaluate a collection of BRCA1/BRCA2 gene mutation prediction scores. In this example, genotype is measured with error by one or more genetic assays. We estimate true genotype for each individual in the dataset, operating characteristics of the commonly used genotyping procedures and a relative weighting of the scores. Finally, we compare the scores against the gold standard genotype and find that Mendelian scores are, on average, the more refined and better calibrated of those considered and that the comparison is sensitive to measurement error in the gold standard.

A Mechanistic Latent Variable Model for Estimating Drug Concentrations in the Male Genital Tract

The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

Molecular interaction between perthiolated [beta]-cyclodextrin (CD) and the guests molecules adamantaneacetic acid (AD) and ferroceneacetic acid (FC); and the effect of the interaction on the electron transition of CD anchored particles

The molecular interactions between the host molecule, perthiolated beta-cyclodextrin (CD), and the guest molecules, adamantaneacetic acid (AD) and ferroceneacetic acid (FC), have been inestigated theoretically in both the gas and aqueous phases. The major computations have been carried out at the theoretical levels, RHF/6-31G and B3LYP/6- 31G. MP2 electronic energies were also computed based at the geometries optimized by both the RHF and B3LYP methods in the gas phase to establish a better estimate of the correlation effect. The solvent phase computations were completed at the RHF/6-31G and B3LYP/6-31G levels using the PCM model. The most stable structures optimized in gas phase by both the RHF and B3LYP methods were used for the computations in solution. A method to systematically manipulate the relative position and orientation between the interacting molecules is proposed. In the gas phase, six trials with different host-guest relative positions and orientations were completed successfully with the B3LYP method for both the CD-AD and CD-FC complexes. Only four trials were completed with RHF method. In the gas phase, the best results from the RHF method gives for the association Gibbs free energy (ΔG°) values equal to -32.21kj/mol for CD-AD and -25.73kj/mol for CD-FC. And the best results from the B3LYP method have ΔG° equal to -47.57kj/mol for CD-AD and -41.09kj/mol for CD-FC. The MP2 correction significantly lowers ΔG° based on the geometries from both methods. For the RHF structure, the MP2 computations lowered ΔG° to -60.64kj/mol for CD-AD and -54.10 for CD-FC. For the structure from the B3LYP method, it was reduced to -59.87 kj/mol for CD-AD and -54.84 kj/mol for CDFC. The RHF solvent phase calculations yielded following results: ΔG°(aq) equals 107.2kj/mol for CD-AD and 111.4kj/mol for CD-FC. Compared with the results from the RHF method, the B3LYP method provided clearly better solvent phase results with ΔG° (aq) equal to 38.64kj/mol for CD-AD and 39.61kj/mol for CD-FC. These results qualitatively explain the experimental observations. However quantitatively they are in poor agreement with the experimental values available in the literature and those recently published by Liu et al. And the reason is believed to be omission of hydrophobic contribution to the association. Determining the global geometrical minima for these very large systems was very difficult and computationally time consuming, but after a very thorough search, these were identified. A relevant result of this search is that when the complexes, CD-AD and CD-FC, are formed, the AD and FC molecules are only partially embedded inside the CD cavity. The totally embedded complexes were found to have significantly higher energies. The semiempirical method, ZINDO, was employed to investigate the effect of complexation on the first electronic excitation of CD anchored to a metal nano-particle. The computational results revealed that after complexation to FC, the transition intensity declines to about 25% of the original value, and after complexation with AD, the intensity drops almost 50%. The tighter binding and transition intensity of CD-AD qualitatively agrees with the experimental result that the addition of AD to a solution of CD and FC restores the fluorescence of CD that was quenched by the addition of FC. A method to evaluate the “hydrophobic force” effect is proposed for future work.

Numerical solutions of elliptic inverse problems via the equation error method

To estimate a parameter in an elliptic boundary value problem, the method of equation error chooses the value that minimizes the error in the PDE and boundary condition (the solution of the BVP having been replaced by a measurement). The estimated parameter converges to the exact value as the measured data converge to the exact value, provided Tikhonov regularization is used to control the instability inherent in the problem. The error in the estimated solution can be bounded in an appropriate quotient norm; estimates can be derived for both the underlying (infinite-dimensional) problem and a finite-element discretization that can be implemented in a practical algorithm. Numerical experiments demonstrate the efficacy and limitations of the method.

Modulating the granularity of category formation by global cortical states

The unsupervised categorization of sensory stimuli is typically attributed to feedforward processing in a hierarchy of cortical areas. This purely sensory-driven view of cortical processing, however, ignores any internal modulation, e.g., by top-down attentional signals or neuromodulator release. To isolate the role of internal signaling on category formation, we consider an unbroken continuum of stimuli without intrinsic category boundaries. We show that a competitive network, shaped by recurrent inhibition and endowed with Hebbian and homeostatic synaptic plasticity, can enforce stimulus categorization. The degree of competition is internally controlled by the neuronal gain and the strength of inhibition. Strong competition leads to the formation of many attracting network states, each being evoked by a distinct subset of stimuli and representing a category. Weak competition allows more neurons to be co-active, resulting in fewer but larger categories. We conclude that the granularity of cortical category formation, i.e., the number and size of emerging categories, is not simply determined by the richness of the stimulus environment, but rather by some global internal signal modulating the network dynamics. The model also explains the salient non-additivity of visual object representation observed in the monkey inferotemporal (IT) cortex. Furthermore, it offers an explanation of a previously observed, demand-dependent modulation of IT activity on a stimulus categorization task and of categorization-related cognitive deficits in schizophrenic patients.

Analytical investigation of squeeze film dampers

Squeeze film damping effects naturally occur if structures are subjected to loading situations such that a very thin film of fluid is trapped within structural joints, interfaces, etc. An accurate estimate of squeeze film effects is important to predict the performance of dynamic structures. Starting from linear Reynolds equation which governs the fluid behavior coupled with structure domain which is modeled by Kirchhoff plate equation, the effects of nondimensional parameters on the damped natural frequencies are presented using boundary characteristic orthogonal functions. For this purpose, the nondimensional coupled partial differential equations are obtained using Rayleigh-Ritz method and the weak formulation, are solved using polynomial and sinusoidal boundary characteristic orthogonal functions for structure and fluid domain respectively. In order to implement present approach to the complex geometries, a two dimensional isoparametric coupled finite element is developed based on Reissner-Mindlin plate theory and linearized Reynolds equation. The coupling between fluid and structure is handled by considering the pressure forces and structural surface velocities on the boundaries. The effects of the driving parameters on the frequency response functions are investigated. As the next logical step, an analytical method for solution of squeeze film damping based upon Green’s function to the nonlinear Reynolds equation considering elastic plate is studied. This allows calculating modal damping and stiffness force rapidly for various boundary conditions. The nonlinear Reynolds equation is divided into multiple linear non-homogeneous Helmholtz equations, which then can be solvable using the presented approach. Approximate mode shapes of a rectangular elastic plate are used, enabling calculation of damping ratio and frequency shift as well as complex resistant pressure. Moreover, the theoretical results are correlated and compared with experimental results both in the literature and in-house experimental procedures including comparison against viscoelastic dampers.

Discrete element methods for asphalt concrete : development and application of user-defined microstructural models and a viscoelastic micromechanical model

As an important Civil Engineering material, asphalt concrete (AC) is commonly used to build road surfaces, airports, and parking lots. With traditional laboratory tests and theoretical equations, it is a challenge to fully understand such a random composite material. Based on the discrete element method (DEM), this research seeks to develop and implement computer models as research approaches for improving understandings of AC microstructure-based mechanics. In this research, three categories of approaches were developed or employed to simulate microstructures of AC materials, namely the randomly-generated models, the idealized models, and image-based models. The image-based models were recommended for accurately predicting AC performance, while the other models were recommended as research tools to obtain deep insight into the AC microstructure-based mechanics. A viscoelastic micromechanical model was developed to capture viscoelastic interactions within the AC microstructure. Four types of constitutive models were built to address the four categories of interactions within an AC specimen. Each of the constitutive models consists of three parts which represent three different interaction behaviors: a stiffness model (force-displace relation), a bonding model (shear and tensile strengths), and a slip model (frictional property). Three techniques were developed to reduce the computational time for AC viscoelastic simulations. It was found that the computational time was significantly reduced to days or hours from years or months for typical three-dimensional models. Dynamic modulus and creep stiffness tests were simulated and methodologies were developed to determine the viscoelastic parameters. It was found that the DE models could successfully predict dynamic modulus, phase angles, and creep stiffness in a wide range of frequencies, temperatures, and time spans. Mineral aggregate morphology characteristics (sphericity, orientation, and angularity) were studied to investigate their impacts on AC creep stiffness. It was found that aggregate characteristics significantly impact creep stiffness. Pavement responses and pavement-vehicle interactions were investigated by simulating pavement sections under a rolling wheel. It was found that wheel acceleration, steadily moving, and deceleration significantly impact contact forces. Additionally, summary and recommendations were provided in the last chapter and part of computer programming codes wree provided in the appendixes.

Comparison of low potassium Euro-Collins solution and standard Euro-Collins solution in an extracorporeal rat heart-lung model

OBJECTIVE: Euro-Collins solution (EC) is routinely used in lung transplantation. The high potassium of EC, however, may damage the vascular endothelium, thereby contributing to postischemic reperfusion injury. To assess the influence of the potassium concentration on lung preservation, we evaluated the effect of a "low potassium Euro-Collins solution" (LPEC), in which the sodium and potassium concentrations were reversed. METHODS: In an extracorporeal rat heart-lung model lungs were preserved with EC and LPEC. The heart-lung blocks (HLB) were perfused with Krebs-Henseleit solution containing washed bovine red blood cells and ventilated with room air. The lungs were perfused via the working right ventricle with deoxygenated perfusate. Oxygenation and pulmonary vascular resistance (PVR) were monitored. After baseline measurements, hearts were arrested with St. Thomas' solution and the lungs were perfused with EC or LPEC, or were not perfused (controls). The HLBs were stored for 5 min or 2 h ischemic time at 4 degrees C. Reperfusion and ventilation was performed for 40 min. At the end of the trial the wet/dry ratio of the lungs was calculated and light microscopic assessment of the degree of edema was performed. RESULTS: After 5 min of ischemia oxygenation was significantly better in both preserved groups compared to the controls. Pulmonary vascular resistance was elevated in all three groups after 30 min reperfusion at both ischemic times. After 2 h of ischemia PVR of the group preserved with LPEC was significantly lower than those of the EC and controls (LPEC-5 min: 184 +/- 65 dynes * sec * cm-5, EC-5 min: 275 +/- 119 dynes * sec * cm * cm-5, LPEC-2 h: 324 +/- 47 dynes * sec * m-5, EC-2 h: 507 +/- 83 dynes * sec * cm-5). Oxygenation after 2 h of ischemia and 30 min reperfusion was significantly better in the LPEC group compared to EC and controls (LPEC: 70 +/- 17 mmHg, EC: 44 +/- 3 mmHg). The wet/dry ratio was significantly lower in the two preserved groups compared to controls (LPEC-5 min: 5.7 +/- 0.7, EC-5 min: 5.8 +/- 1.2, controls-5 min: 7.5 +/- 1.8, LPEC-2 h: 6.7 +/- 0.4, EC: 6.9 +/- 0.4, controls-2 h: 7.3 +/- 0.4). CONCLUSIONS: We thus conclude that LPEC results in better oxygenation and lower PVR in this lung preservation model. A low potassium concentration in lung preservation solutions may help in reducing the incidence of early graft dysfunction following lung transplantation.

Imminent ocean acidification in the Arctic projected with the NCAR global coupled carbon cycle-climate model

Ocean acidification from the uptake of anthropogenic carbon is simulated for the industrial period and IPCC SRES emission scenarios A2 and B1 with a global coupled carbon cycle-climate model. Earlier studies identified seawater saturation state with respect to aragonite, a mineral phase of calcium carbonate, as a key variable governing impacts on corals and other shell-forming organisms. Globally in the A2 scenario, water saturated by more than 300%, considered suitable for coral growth, vanishes by 2070 AD (CO2≈630 ppm), and the ocean volume fraction occupied by saturated water decreases from 42% to 25% over this century. The largest simulated pH changes worldwide occur in Arctic surface waters, where hydrogen ion concentration increases by up to 185% (ΔpH=−0.45). Projected climate change amplifies the decrease in Arctic surface mean saturation and pH by more than 20%, mainly due to freshening and increased carbon uptake in response to sea ice retreat. Modeled saturation compares well with observation-based estimates along an Arctic transect and simulated changes have been corrected for remaining model-data differences in this region. Aragonite undersaturation in Arctic surface waters is projected to occur locally within a decade and to become more widespread as atmospheric CO2 continues to grow. The results imply that surface waters in the Arctic Ocean will become corrosive to aragonite, with potentially large implications for the marine ecosystem, if anthropogenic carbon emissions are not reduced and atmospheric CO2 not kept below 450 ppm.