OALib Journal期刊

ISSN: 2333-9721



匹配条件: “Haixuan;” ,找到相关结果约5条。
The existence of identity of periodic semigroup rings
Haixuan Yang,Yanfeng Luo
Chinese Science Bulletin , 1997, DOI: 10.1007/BF03182632
Proteomic Investigation of Changes in Rat Skeletal Muscle after Exercise-Induced Fatigue
Zhao,Liping; Yan,Wenhui; Xiang,Heng; Wang,Xiaoyang; Qiao,Haixuan;
Biological Research , 2012, DOI: 10.4067/S0716-97602012000100010
Abstract: the mechanisms of exercise-induced fatigue have not been investigated using proteomic techniques, an approach that could improve our understanding and generate novel information regarding the effects of exercise. in this study, the proteom alterations of rat skeletal muscle were investigated during exercise-induced fatigue. the proteins were extracted from the skeletal muscle of sd rat thigh, and then analyzed by two-dimensional electrophoresis and pdquest software. compared to control samples, 10 significantly altered proteins were found in exercise samples, two of them were upregulated and eight of them were downregulated. these proteins were identified by maldi tof-ms. the two upregulated proteins were identified as mlc1 and myosin l2 (dtnb) regulatory light-chain precursors. the eight decreased proteins are glyceraldehyde-3-phosphate dehydrogenas (gapdh); beta enolase; creatine kinase m chain (m-ck); atp-amp transphosphorylase (ak1); myosin heavy chain (mhc); actin; troponin i, fast-skeletal muscle (troponin i fast-twitch isoform), fstni; troponin t, fast-skeletal muscle isoforms (tntf). in these proteins, four of the eight decreased proteins are related directly or indirectly to exercise induced fatigue. the other proteins represent diverse sets of proteins including enzymyes related to energy metabolism, skeletal muscle fabric protein and protein with unknown functions. they did not exhibit evident relationship with exercise-induced fatigue. whereas the two identified increased proteins exhibit evident relationship with fatigue. these findings will help in understanding the mechanisms involved in exercise-induced fatigue.
Kinetic Activation-Relaxation Technique and Self-Evolving Atomistic Kinetic Monte Carlo: Comparison of on-the-fly kinetic Monte Carlo algorithms
Laurent K Béland,Yuri Osetskiy,Roger Stoller,Haixuan Xu
Physics , 2014,
Abstract: We present a comparison of the kinetic Activation-Relaxation Technique (k-ART) and the Self-Evolving Atomistic Kinetic Monte Carlo (SEAKMC), two off-lattice, on-the-fly kinetic Monte Carlo (KMC) techniques that were recently used to solve several materials science problems. We show that if the initial displacements are localized the dimer method and the Activation-Relaxation Technique \emph{nouveau} provide similar performance. We also show that k-ART and SEAKMC, although based on different approximations, are in agreement with each other, as demonstrated by the examples of 50 vacancies in a 1950-atom Fe box and of interstitial loops in 16000-atom boxes. Generally speaking, k-ART's treatment of geometry and flickers is more flexible, e.g. it can handle amorphous systems, and rigorous than SEAKMC's, while the later's concept of active volumes permits a significant speedup of simulations for the systems under consideration and therefore allows investigations of processes requiring large systems that are not accessible if not localizing calculations.
Computational Selection of Transcriptomics Experiments Improves Guilt-by-Association Analyses
Prajwal Bhat, Haixuan Yang, László B?gre, Alessandra Devoto, Alberto Paccanaro
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0039681
Abstract: The Guilt-by-Association (GBA) principle, according to which genes with similar expression profiles are functionally associated, is widely applied for functional analyses using large heterogeneous collections of transcriptomics data. However, the use of such large collections could hamper GBA functional analysis for genes whose expression is condition specific. In these cases a smaller set of condition related experiments should instead be used, but identifying such functionally relevant experiments from large collections based on literature knowledge alone is an impractical task. We begin this paper by analyzing, both from a mathematical and a biological point of view, why only condition specific experiments should be used in GBA functional analysis. We are able to show that this phenomenon is independent of the functional categorization scheme and of the organisms being analyzed. We then present a semi-supervised algorithm that can select functionally relevant experiments from large collections of transcriptomics experiments. Our algorithm is able to select experiments relevant to a given GO term, MIPS FunCat term or even KEGG pathways. We extensively test our algorithm on large dataset collections for yeast and Arabidopsis. We demonstrate that: using the selected experiments there is a statistically significant improvement in correlation between genes in the functional category of interest; the selected experiments improve GBA-based gene function prediction; the effectiveness of the selected experiments increases with annotation specificity; our algorithm can be successfully applied to GBA-based pathway reconstruction. Importantly, the set of experiments selected by the algorithm reflects the existing literature knowledge about the experiments. [A MATLAB implementation of the algorithm and all the data used in this paper can be downloaded from the paper website: http://www.paccanarolab.org/papers/CorrG?ene/].
Slow relaxation of cascade-induced defects in Fe
Laurent Karim Béland,Yuri Osetskiy,Roger E. Stoller,Haixuan Xu
Physics , 2014, DOI: 10.1103/PhysRevB.91.054108
Abstract: On-the-fly kinetic Monte Carlo (KMC) simulations are performed to investigate slow relaxation of non-equilibrium systems. Point defects induced by 25 keV cascades in $\alpha$-Fe are shown to lead to a characteristic time-evolution, described by the \emph{replenish and relax} mechanism. Then, we produce an atomistically-based assessment of models proposed to explain the slow structural relaxation by focusing on the aggregation of 50 vacancies and 25 self-interstital atoms (SIA) in 10-lattice-parameter $\alpha$-Fe boxes, two processes that are closely related to cascade annealing and exhibit similar time signature. Four atomistic effects explain the timescales involved in the evolution: defect concentration heterogeneities, concentration-enhanced mobility, cluster-size dependent bond energies and defect-induced pressure. These findings suggest that the two main classes of models to explain slow structural relaxation, the Eyring model and the Gibbs model, both play a role to limit the rate of relaxation of these simple point-defect systems.

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