Bayesian Analysis of Varying Coefficient Models and Applications

The varying coefficient models have been very important analytic tools to study the dynamic pattern in biomedicine fields. Since nonparametric varying coefficient models make few assumptions on the specification of the model, the 'curse of dimensionality' is an very important issue. Nonparametric Bayesian methods combat the curse of dimensionality through specifying a sparseness-favoring structure. This is accomplished through the Bayesian penalty for model complexity (Jeffreys and Berger, 1992) and is aided through centering on a base Bayesian parametric model. This dissertation presents three novel semiparametric Bayesian methods for the analysis of longitudinal data, diffusion tensor imaging data, and longitudinal circumplex data. In longitudinal data analysis, we propose a semiparametric Bayes approach to allow the impact of the predictors to vary across subjects, which allows flexibly local borrowing of information across subjects. Local hypothesis testing and confidence bands are developed for the identification of time windows for significant predictor impact, adjusting for multiple comparisons. The methods are assessed using simulation studies and applied to a yeast cell-cycle gene expression data set. In analyzing diffusion tensor imaging data, we propose a semiparametric Bayesian local functional model to connect multiple diffusion properties along white matter fiber bundles with a set of covariates of interest. An LPP2 prior facilitates global and local borrowing of information among subjects, while an infinite factor model flexibly represents low-dimensional structure. Local hypothesis testing and confidence bands are developed to identify fiber segments for significant association of covariates with multiple diffusion properties, controlling for multiple comparisons. The method is assessed by a simulation study and illustrated via two fiber tract data sets for neurodevelopment. In analyzing longitudinal circumplex data, we propose a semiparametric Bayesian infinite state-space circumplex model to capture the dynamic transition pattern of affective experience, where affects are characterized as an ordering on the circumference of a circle. A sticky infinite state hidden Markov model via hierarchical Dirichlet proces is used to address the time related state-switching structure and the self-transition feature. The method is assessed by a simulation study and an emotion data set for the dynamics of emotion regulation

HoMM: Higher-order Moment Matching for Unsupervised Domain Adaptation

Minimizing the discrepancy of feature distributions between different domains is one of the most promising directions in unsupervised domain adaptation. From the perspective of distribution matching, most existing discrepancy-based methods are designed to match the second-order or lower statistics, which however, have limited expression of statistical characteristic for non-Gaussian distributions. In this work, we explore the benefits of using higher-order statistics (mainly refer to third-order and fourth-order statistics) for domain matching. We propose a Higher-order Moment Matching (HoMM) method, and further extend the HoMM into reproducing kernel Hilbert spaces (RKHS). In particular, our proposed HoMM can perform arbitrary-order moment tensor matching, we show that the first-order HoMM is equivalent to Maximum Mean Discrepancy (MMD) and the second-order HoMM is equivalent to Correlation Alignment (CORAL). Moreover, the third-order and the fourth-order moment tensor matching are expected to perform comprehensive domain alignment as higher-order statistics can approximate more complex, non-Gaussian distributions. Besides, we also exploit the pseudo-labeled target samples to learn discriminative representations in the target domain, which further improves the transfer performance. Extensive experiments are conducted, showing that our proposed HoMM consistently outperforms the existing moment matching methods by a large margin. Codes are available at \url{https://github.com/chenchao666/HoMM-Master}Comment: Accept by AAAI-2020, codes are available at https://github.com/chenchao666/HoMM-Maste

Effects of 12-Week Endurance Training at Natural Low Altitude on the Blood Redox Homeostasis of Professional Adolescent Athletes: A Quasi-Experimental Field Trial

This field study investigated the influences of exposure to natural low altitude on endurance training-induced alterations of redox homeostasis in professional adolescent runners undergoing 12-week off-season conditioning program at an altitude of 1700 m (Alt), by comparison with that of their counterparts completing the program at sea-level (SL). For age-, gender-, and Tanner-stage-matched comparison, 26 runners (n=13 in each group) were selected and studied. Following the conditioning program, unaltered serum levels of thiobarbituric acid reactive substances (TBARS), total antioxidant capacity (T-AOC), and superoxide dismutase accompanied with an increase in oxidized glutathione (GSSG) and decreases of xanthine oxidase, reduced glutathione (GSH), and GSH/GSSG ratio were observed in both Alt and SL groups. Serum glutathione peroxidase and catalase did not change in SL, whereas these enzymes, respectively, decreased and increased in Alt. Uric acid (UA) decreased in SL and increased in Alt. Moreover, the decreases in GSH and GSH/GSSG ratio in Alt were relatively lower compared to those in SL. Further, significant interindividual correlations were found between changes in catalase and TBARS, as well as between UA and T-AOC. These findings suggest that long-term training at natural low altitude is unlikely to cause retained oxidative stress in professional adolescent runners

Semiparametric Bayesian local functional models for diffusion tensor tract statistics

We propose a semiparametric Bayesian local functional model (BFM) for the analysis of multiple diffusion properties (e.g., fractional anisotropy) along white matter fiber bundles with a set of covariates of interest, such as age and gender. BFM accounts for heterogeneity in the shape of the fiber bundle diffusion properties among subjects, while allowing the impact of the covariates to vary across subjects. A nonparametric Bayesian LPP2 prior facilitates global and local borrowings of information among subjects, while an infinite factor model flexibly represents low-dimensional structure. Local hypothesis testing and credible bands are developed to identify fiber segments, along which multiple diffusion properties are significantly associated with covariates of interest, while controlling for multiple comparisons. Moreover, BFM naturally group subjects into more homogeneous clusters. Posterior computation proceeds via an efficient Markov chain Monte Carlo algorithm. A simulation study is performed to evaluate the finite sample performance of BFM. We apply BFM to investigate the development of white matter diffusivities along the splenium of the corpus callosum tract and the right internal capsule tract in a clinical study of neurodevelopment in new born infants

Tai chi as an alternative exercise to improve physical fitness for children and adolescents with intellectual disability

© 2019 by the authors. Licensee MDPI, Basel, Switzerland. Objective: The purpose of this study was to investigate the effects of Tai Chi (TC) on anthropometric parameters and physical fitness among children and adolescents with intellectual disabilities (ID). Methods: Sixty-six Chinese individuals engaged in sport-related extracurricular activities (TC and aerobic exercise (AE)) as exercise interventions or arts/crafts activities as a control condition (CON). The experimental protocol consisted of a baseline assessment, a 12-week intervention period, and a post-intervention assessment. Results: Significant interaction effect was only observed in the performance of a 6-min walk test. After 12 weeks of intervention, the AE group had significant changes in body mass index (p = 0.006, d = 0.11), sit-ups (p = 0.030 and d = 0.57), and 6-min walk test (p = 0.005, d = 0.89). Significant increases in vertical jump (p = 0.048, d = 0.41), lower-limb coordination (p = 0.008, d = 0.53), and upper-limb coordination (p = 0.048, d = 0.36) were observed in the TC group. Furthermore, the TC group demonstrated significantly greater improvements on balance compared to the control group (p = 0.011). Conclusions: TC may improve leg power and coordination of both lower and upper limbs, while AE may be beneficial for body mass index, sit-ups and cardiorespiratory fitness

Visual characterization of associative quasitrivial nondecreasing operations on finite chains

In this paper we provide visual characterization of associative quasitrivial nondecreasing operations on finite chains. We also provide a characterization of bisymmetric quasitrivial nondecreasing binary operations on finite chains. Finally, we estimate the number of functions belonging to the previous classes.Comment: 25 pages, 18 Figure

Effects of 12-Week Endurance Training at Natural Low Altitude on the Blood Redox Homeostasis of Professional Adolescent Athletes: A Quasi-Experimental Field Trial

This field study investigated the influences of exposure to natural low altitude on endurance training-induced alterations of redox homeostasis in professional adolescent runners undergoing 12-week off-season conditioning program at an altitude of 1700 m (Alt), by comparison with that of their counterparts completing the program at sea-level (SL). For age-, gender-, and Tanner-stagematched comparison, 26 runners ( = 13 in each group) were selected and studied. Following the conditioning program, unaltered serum levels of thiobarbituric acid reactive substances (TBARS), total antioxidant capacity (T-AOC), and superoxide dismutase accompanied with an increase in oxidized glutathione (GSSG) and decreases of xanthine oxidase, reduced glutathione (GSH), and GSH/GSSG ratio were observed in both Alt and SL groups. Serum glutathione peroxidase and catalase did not change in SL, whereas these enzymes, respectively, decreased and increased in Alt. Uric acid (UA) decreased in SL and increased in Alt. Moreover, the decreases in GSH and GSH/GSSG ratio in Alt were relatively lower compared to those in SL. Further, significant interindividual correlations were found between changes in catalase and TBARS, as well as between UA and T-AOC. These findings suggest that long-term training at natural low altitude is unlikely to cause retained oxidative stress in professional adolescent runners

Biomechanical study of two-level oblique lumbar interbody fusion with different types of lateral instrumentation: a finite element analysis

ObjectiveThe aim of this study was to verify the biomechanical properties of a newly designed angulated lateral plate (mini-LP) suited for two-level oblique lumbar interbody fusion (OLIF). The mini-LP is placed through the lateral ante-psoas surgical corridor, which reduces the operative time and complications associated with prolonged anesthesia and placement in the prone position.MethodsA three-dimensional nonlinear finite element (FE) model of an intact L1–L5 lumbar spine was constructed and validated. The intact model was modified to generate a two-level OLIF surgery model augmented with three types of lateral fixation (stand-alone, SA; lateral rod screw, LRS; miniature lateral plate, mini-LP); the operative segments were L2–L3 and L3–L4. By applying a 500 N follower load and 7.5 Nm directional moment (flexion-extension, lateral bending, and axial rotation), all models were used to simulate human spine movement. Then, we extracted the range of motion (ROM), peak contact force of the bony endplate (PCFBE), peak equivalent stress of the cage (PESC), peak equivalent stress of fixation (PESF), and stress contour plots.ResultsWhen compared with the intact model, the SA model achieved the least reduction in ROM to surgical segments in all motions. The ROM of the mini-LP model was slightly smaller than that of the LRS model. There were no significant differences in surgical segments (L1–L2, L4–L5) between all surgical models and the intact model. The PCFBE and PESC of the LRS and the mini-LP fixation models were lower than those of the SA model. However, the differences in PCFBE or PESC between the LRS- and mini-LP-based models were not significant. The fixation stress of the LRS- and mini-LP-based models was significantly lower than the yield strength under all loading conditions. In addition, the variances in the PESF in the LRS- and mini-LP-based models were not obvious.ConclusionOur biomechanical FE analysis indicated that LRS or mini-LP fixation can both provide adequate biomechanical stability for two-level OLIF through a single incision. The newly designed mini-LP model seemed to be superior in installation convenience, and equally good outcomes were achieved with both LRS and mini-LP for two-level OLIF

Pevonedistat (MLN4924), a First‐in‐Class NEDD8‐activating enzyme inhibitor, in patients with acute myeloid leukaemia and myelodysplastic syndromes: a phase 1 study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111220/1/bjh13323.pd