Enhancing Prediction Efficacy with High-Dimensional Input Via Structural Mixture Modeling of Local Linear Mappings

Regression is a widely used statistical tool to discover associations between variables. Estimated relationships can be further utilized for predicting new observations. Obtaining reliable prediction outcomes is a challenging task. When building a regression model, several difficulties such as high dimensionality in predictors, non-linearity of the associations and outliers could reduce the quality of results. Furthermore, the prediction error increases if the newly acquired data is not processed carefully. In this dissertation, we aim at improving prediction performance by enhancing the model robustness at the training stage and duly handling the query data at the testing stage. We propose two methods to build robust models. One focuses on adopting a parsimonious model to limit the number of parameters and a refinement technique to enhance model robustness. We design the procedure to be carried out on parallel systems and further extend their ability to handle complex and large-scale datasets. The other method restricts the parameter space to avoid the singularity issue and takes up trimming techniques to limit the influence of outlying observations. We build both approaches by using the mixture-modeling principle to accommodate data heterogeneity without uncontrollably increasing model complexity. The proposed procedures for suitably choosing tuning parameters further enhance the ability to determine the sizes of the models according to the richness of the available data. Both methods show their ability to improve prediction performance, compared to existing approaches, in applications such as magnetic resonance vascular fingerprinting and source separation in single-channel polyphonic music, among others. To evaluate model robustness, we develop an efficient approach to generating adversarial samples, which could induce large prediction errors yet are difficult to detect visually. Finally, we propose a preprocessing system to detect and repair different kinds of abnormal testing samples for prediction efficacy, when testing samples are either corrupted or adversarially perturbed.PHDStatisticsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149938/1/timtu_1.pd

Bounds of Efficiency at Maximum Power for Normal-, Sub- and Super-Dissipative Carnot-Like Heat Engines

The Carnot-like heat engines are classified into three types (normal-, sub- and super-dissipative) according to relations between the minimum irreversible entropy production in the "isothermal" processes and the time for completing those processes. The efficiencies at maximum power of normal-, sub- and super-dissipative Carnot-like heat engines are proved to be bounded between $\eta_C/2$ and $\eta_C/(2-\eta_C)$, $\eta_C /2$ and $\eta_C$, 0 and $\eta_C/(2-\eta_C)$, respectively. These bounds are also shared by linear, sub- and super-linear irreversible Carnot-like engines [Tu and Wang, Europhys. Lett. 98, 40001 (2012)] although the dissipative engines and the irreversible ones are inequivalent to each other.Comment: 1 figur

catena-Poly[[bis­[2-(2-pyrid­yl)-1-H-imidazole-κ2 N 2,N 3]cadmium]-μ-benzene-1,3-dicarboxyl­ato-κ2 O 1:O 3]

In the title coordinaltion polymer, [Cd(C8H4O4)(C8H7N3)2]n, the CdII atom, lying on a twofold rotation axis, is six-coordinated by two carboxyl­ate O atoms from two benzene-1,3-dicarboxyl­ate (m-BDC) ligands and four N atoms from two chelating 2-(2-pyrid­yl)imidazole mol­ecules, forming a slightly distorted octa­hedral geometry. The m-BDC ligand is located over a twofold rotation axis. The CdII atoms are bridged by the m-BDC ligands, leading to a wave-shaped chain structure along [010]. N—H⋯O hydrogen bonds connect the chains

THE ACUTE EFFECT OF UPPER EXTREMITY PLYOMETRIC TRAINING

The purpose of this study was to probe the acute effect of the performance of upper extremity muscle groups after the plyometric training intervention. The participants were 13 healthy male college students. The force transducers (300kg, 200 Hz) and EMG sensor (1000 Hz) were taken to diagnose the acute effects of strength and muscle activation done by upper extremity pre and post plyometric training (load :24kg, 12 repetiiion times Iset, 3 set), and pair t-test was taken to test the significance(a=.05). The result showed that the strength after the upper extremity plyometric training intervention obviously had decreased 8% (

ELEMENTARY SCHOOL BOYS’ SOCCER KICK SKILL ANALYSIS

The purpose of this study is aimed to analyze elementary school boys’ kicking skills on the perspective of motor skills. The data is collected by Vicon Motion Analysis System (250Hz). The parameters include the compare of the instant joint angles and the time proportion during the process of the kicking toward the different kick performance groups. The participants are 36 elementary boy soccer players (age: 11.7±0.3 yrs; height: 1.42±0.13 m; weight: 37.5±13.0 kg). The subjects were divided to two groups according to the instance kicking ball speed. The result indicated that the high ball speed group players have greater extremity joint angles than the low ball speed group. No difference was found on the time proportion during the process of the kicking. We suggest that the learning of kicking skill can start with the lower speed in the beginner stage

Metabolic labelling of cholesteryl glucosides in Helicobacter pylori reveals how the uptake of human lipids enhances bacterial virulence.

Helicobacter pylori infects approximately half of the human population and is the main cause of various gastric diseases. This pathogen is auxotrophic for cholesterol, which it converts upon uptake to various cholesteryl α-glucoside derivatives, including cholesteryl 6'-acyl and 6'-phosphatidyl α-glucosides (CAGs and CPGs). Owing to a lack of sensitive analytical methods, it is not known if CAGs and CPGs play distinct physiological roles or how the acyl chain component affects function. Herein we established a metabolite-labelling method for characterising these derivatives qualitatively and quantitatively with a femtomolar detection limit. The development generated an MS/MS database of CGds, allowing for profiling of all the cholesterol-derived metabolites. The subsequent analysis led to the unprecedented information that these bacteria acquire phospholipids from the membrane of epithelial cells for CAG biosynthesis. The resulting increase in longer or/and unsaturated CAG acyl chains helps to promote lipid raft formation and thus delivery of the virulence factor CagA into the host cell, supporting the idea that the host/pathogen interplay enhances bacterial virulence. These findings demonstrate an important connection between the chain length of CAGs and the bacterial pathogenicity