Exact Pseudofermion Action for Monte Carlo Simulation of Domain-Wall Fermion

We present an exact pseudofermion action for hybrid Monte Carlo simulation (HMC) of one-flavor domain-wall fermion (DWF), with the effective 4-dimensional Dirac operator equal to the optimal rational approximation of the overlap-Dirac operator with kernel $H = c H_w (1 + d \gamma_5 H_w)^{-1}$, where $c$ and $d$ are constants. Using this exact pseudofermion action, we perform HMC of one-flavor QCD, and compare its characteristics with the widely used rational hybrid Monte Carlo algorithm (RHMC). Moreover, to demonstrate the practicality of the exact one-flavor algorithm (EOFA), we perform the first dynamical simulation of the (1+1)-flavors QCD with DWF.Comment: 13 pages, 4 figures, v2: Simulation of (1+1)-flavors QCD with DWF, and references added. To appear in Phys. Lett.

GSAE: an autoencoder with embedded gene-set nodes for genomics functional characterization

Bioinformatics tools have been developed to interpret gene expression data at the gene set level, and these gene set based analyses improve the biologists' capability to discover functional relevance of their experiment design. While elucidating gene set individually, inter gene sets association is rarely taken into consideration. Deep learning, an emerging machine learning technique in computational biology, can be used to generate an unbiased combination of gene set, and to determine the biological relevance and analysis consistency of these combining gene sets by leveraging large genomic data sets. In this study, we proposed a gene superset autoencoder (GSAE), a multi-layer autoencoder model with the incorporation of a priori defined gene sets that retain the crucial biological features in the latent layer. We introduced the concept of the gene superset, an unbiased combination of gene sets with weights trained by the autoencoder, where each node in the latent layer is a superset. Trained with genomic data from TCGA and evaluated with their accompanying clinical parameters, we showed gene supersets' ability of discriminating tumor subtypes and their prognostic capability. We further demonstrated the biological relevance of the top component gene sets in the significant supersets. Using autoencoder model and gene superset at its latent layer, we demonstrated that gene supersets retain sufficient biological information with respect to tumor subtypes and clinical prognostic significance. Superset also provides high reproducibility on survival analysis and accurate prediction for cancer subtypes.Comment: Presented in the International Conference on Intelligent Biology and Medicine (ICIBM 2018) at Los Angeles, CA, USA and published in BMC Systems Biology 2018, 12(Suppl 8):14

An integrated perspective of TOE framework and innovation diffusion in broadband mobile applications adoption by enterprises

This study aimed at exploring the critical factors for enterprises to adopt broadband mobile applications. The results are expected to guide enterprises to strengthen their competitiveness. Further, since the broadband mobile applications were integrated with many characteristics of information communication technologies, this study combined the Technology-Organization-Environment (TOE) framework and Diffusion of Innovation Theory in an effort to establish a comprehensive view and to increase the level of understanding. The Structural Equation Modeling and AMOS were applied for analysis; which discovered that the adoption of broadband mobile applications by enterprises is significantly affected by technological, organizational and environmental contexts. This paper also identified eleven critical factors from technological, organizational and environmental aspects, as well as two vital control variables. Based on the research outcome, this paper conducted an in-depth discussion and drew conclusions. Finally, the research implications were provided

THE EFFECTS OF RUNNING VELOCITY AND LOWER EXTREMITY LOADING ON BIARTICULAR LEG MUSCLES DURING TREADMILL RUNNING

The purpose of this study was to investigate the changes in muscle activity levels in treadmill running while using wearable resistance as a function of running speed. Nine recreational runners participated in this study; they were requested to perform the running without and with wearable resistance at four discrete speeds ranging from 2.5 to 7.0 m/s on a treadmill. The mass of wearable resistance was set at one third of each participant’s shank and foot mass. Repeated-measures two-way ANOVA analysis was then used to explore the effect of loaded and speed. The data showed that shank loading enlarged the activation amplitude of the biceps femoris (BF) for the concentric action of hip extension following the stretch of knee extension at a high running speed. The loaded condition facilitated the rectus femoris (RF) to be stretched

T Oligo-Primed Polymerase Chain Reaction (TOP-PCR): A Robust Method for the Amplification of Minute DNA Fragments in Body Fluids.

Body fluid DNA sequencing is a powerful noninvasive approach for the diagnosis of genetic defects, infectious agents and diseases. The success relies on the quantity and quality of the DNA samples. However, numerous clinical samples are either at low quantity or of poor quality due to various reasons. To overcome these problems, we have developed T oligo-primed polymerase chain reaction (TOP-PCR) for full-length nonselective amplification of minute quantity of DNA fragments. TOP-PCR adopts homogeneous "half adaptor" (HA), generated by annealing P oligo (carrying a phosphate group at the 5' end) and T oligo (carrying a T-tail at the 3' end), for efficient ligation to target DNA and subsequent PCR amplification primed by the T oligo alone. Using DNA samples from body fluids, we demonstrate that TOP-PCR recovers minute DNA fragments and maintains the DNA size profile, while enhancing the major molecular populations. Our results also showed that TOP-PCR is a superior method for detecting apoptosis and outperforms the method adopted by Illumina for DNA amplification