Applying MDL to Learning Best Model Granularity

The Minimum Description Length (MDL) principle is solidly based on a provably ideal method of inference using Kolmogorov complexity. We test how the theory behaves in practice on a general problem in model selection: that of learning the best model granularity. The performance of a model depends critically on the granularity, for example the choice of precision of the parameters. Too high precision generally involves modeling of accidental noise and too low precision may lead to confusion of models that should be distinguished. This precision is often determined ad hoc. In MDL the best model is the one that most compresses a two-part code of the data set: this embodies ``Occam's Razor.'' In two quite different experimental settings the theoretical value determined using MDL coincides with the best value found experimentally. In the first experiment the task is to recognize isolated handwritten characters in one subject's handwriting, irrespective of size and orientation. Based on a new modification of elastic matching, using multiple prototypes per character, the optimal prediction rate is predicted for the learned parameter (length of sampling interval) considered most likely by MDL, which is shown to coincide with the best value found experimentally. In the second experiment the task is to model a robot arm with two degrees of freedom using a three layer feed-forward neural network where we need to determine the number of nodes in the hidden layer giving best modeling performance. The optimal model (the one that extrapolizes best on unseen examples) is predicted for the number of nodes in the hidden layer considered most likely by MDL, which again is found to coincide with the best value found experimentally.Comment: LaTeX, 32 pages, 5 figures. Artificial Intelligence journal, To appea

Multiple phenotype modeling in pleiotropic effect studies of quantitative trait loci

Pleiotropy refers to the shared effects of a gene or genes on multiple phenotypes, a major reason for genetic correlation between phenotypes. For example, for osteoporosis, bone mineral densities at different skeletal sites may share common genetic factors; thus, examining the shared effects of genes may enable more effective fracture treatments. To date, methods are not available for estimating and testing the pleiotropic effects of single nucleotide polymorphisms (SNPs) in genetic association studies. In this dissertation, we explore two types of methods to evaluate the SNP-specific pleiotropic effect based on multivariate techniques. First, we propose two approaches based on variance components (VC) analysis for family-based studies, which quantify and test the pleiotropic effect by examining the contribution of specific genetic marker(s) to polygenic correlation or covariance of traits. Second, we propose a multivariate linear regression approach for population-based studies with samples of families or unrelated subjects. This method partitions the specific effect of the marker(s) from phenotypic covariance. We evaluate the performance of our proposed methods in simulation studies, compare them to existing multivariate analysis methods and illustrate their application using real data to assess candidate SNPs for osteoporosis-related phenotypes in the Framingham Osteoporosis Study. In contrast to existing methods, our newly proposed approaches allow the quantification of pleiotropic effects. The bootstrap resampling percentile method is used to construct confidence intervals for statistical hypothesis testing. Simulation results suggest that the VC-based approaches are affected by the polygenic correlation level. The covariance analysis approach outperforms the VC-based approaches, with unbiased estimates and better power, which remain consistent regardless of the polygenic correlation. In addition, the covariance analysis approach is simple to implement and can be applied to both family data and genetically unrelated data. Using simulation, we also show that existing methods, such as MANOVA, can have high rejection rates when a SNP has a large effect on a single trait, which prevent us from using them for pleiotropic effect analysis. In summary, this dissertation introduces promising new approaches in multiple phenotypic models for SNP-specific pleiotropic effect

Light-weight Mg/Al dissimilar structures welded by CW laser for weight saving applications

With the increasing demand of light-weight alloys, such as magnesium (Mg) and aluminum (Al), the need for joining these two alloys is unavoidable. In this study, AZ31B Mg and 1060 Al alloys were joined by continuous wave laser micro-welding using a 0.05 mm thick Cu/Zn interlayer. The microstructure and phases constituent of the weld seam were examined by optical microscope, SEM and EDS. The formation and distribution of the intermetallic compounds (IMCs) and the relationship between these structures and the micro-hardness of the weld were discussed in detail. The effect of Cu/Zn interlayer on the performance of Mg/Al joint was also analyzed. The results showed that Mg/Al IMCs were formed in the weld, which indicates that the Cu/Zn foil could not prevent the reaction between Mg and Al. However, the addition of Cu and Zn into the weld pool refined the microstructure by improving the number of eutectic structures. The micro-hardness of Mg/Al IMCs in the middle of the weld was very high which can be detrimental to the toughness of the Mg/Al joints

Regulation of Lysosomal Adaptation to Nutrient Starvation by Lysosomal TRPML1 and PIKfyve

Lysosomes play an active role in sensing, signaling, and responding to nutrient availability, in addition to their well-established role in degradation. Lysosomes undergo multifaceted changes in lysosome pH, size, number, and activity, referred to as lysosomal adaptation”, via a transcriptional factor EB (TFEB)-mediated lysosome-to-nucleus signaling pathway. The mechanistic target of rapamycin (mTOR) is a nutrient-sensitive protein kinase that regulates TFEB. When nutrients are abundant, mTOR phosphorylates TFEB on the lysosomal membrane and retains it in the cytosol. When nutrients are deprived, TFEB is dephosphorylated and translocates to the nucleus. Here, I identified two novel components required for lysosomal adaptation: the lysosomal Ca2+ release channel TRPML1 and phosphatidylinositol 3-phosphate (PI3P) 5-kinase PIKfyve. Upon starvation, TRPML1 is activated and PIKfyve is inhibited, both triggering the dephosphorylation and subsequent nuclear translocation of TFEB independent of mTOR. This results in lysosomal changes to enhance degradation capabilities. Moreover, the expression level of TRPML1 is potently and rapidly increased. Pharmacological inhibition or genetic deletion of TRPML1 completely abolishes the effects of starvation on boosting the degradation capability of lysosomes, suggesting that TRPML1 is essential for lysosomal adaptation during prolonged starvation. Collectively, lysosomes may adapt to cellular changes under nutrient deprivation by generating a transcriptional response via TRPML1 activation and PIKfyve inhibition. Modulation of lysosomal function by activating the TRPML1-TFEB pathway may dramatically promote cellular clearance, hence representing a promising therapeutic strategy for many lysosome-related disorders.PHDMolecular, Cellular, and Developmental BiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138614/1/joangao_1.pd

Crustal structure and deformation beneath the NE margin of the Tibetan plateau constrained by teleseismic receiver function data

We analysed a large amount of teleseismic receiver function data recorded by 172 broadband stations in the NE Tibetan plateau and its surrounding areas to investigate the crustal velocity and anisotropy structure beneath the margin. We first applied the modified H–κ stacking technique to measure the crustal thickness and average Vp/Vs ratio, and then employed a joint inversion scheme to measure azimuthal anisotropy of the crust beneath each station. The observed crustal thickness and Vp/Vs ratio exhibit large variations across the study area, varying from 32 to 75.6 km and from 1.601 to 1.864, respectively. We also found significant azimuthal anisotropy within the crust beneath 12 stations, with a splitting time between 0.36 and 1.06s. The fast polarization directions align well with surface structures, and follow the directions of the maximum horizontal tensile stress. The low Vp/Vs ratio and the strong azimuthal anisotropy observed beneath the margin suggest that whole crustal shortening might be the dominant mechanism for producing the thick crust in NE Tibet. We compared the measured seismic anisotropy with those measured from XKS (SKS, PKS and SKKS), and found that crustal anisotropy appears to play an important role in explaining the amount of XKS splitting times. More importantly, the Moho Ps and the XKS share similar fast polarization directions, suggesting a vertically coherent deformation within the lithosphere beneath the margin

Tectorigenin monohydrate: an isoflavone from Belamcanda chinensis

The title compound [systematic name: 5,7-dihydr­oxy-3-(4-hydroxy­phen­yl)-6-meth­oxy-4H-chromen-4-one monohydrate], C16H12O6·H2O, is isolated from Belamcanda chinensis and is said to have anti­microbiotic and anti-inflammatory effects. The chromen-4-one system and the benzene ring are inclined at a dihedral angle of 36.79 (6)°. Molecules are linked by inter- and intramolecular O—H⋯O hydrogen bonds

Dynamical analysis of a thin-walled rectangular plate with preload force

Finite element (FE) models are utilized to investigate the influence of preload force and the stress stiffening on the dynamic characteristics of a thin-walled rectangular plate. An experimental platform system is established to obtain the dynamic characteristics of the specimen using the resonance method. Simulation and experimental results agree well with each other, which validates the effectiveness of the FE model. The results show that the preload force not only improves the overall dynamic performances of the thin-walled plate but also contributes to the local stiffness of the loading position because of the generation of stress