SOME RESULTS REGARDING PARTIAL DIFFERENTIAL POLYNOMIALS AND THE UNIQUENESS OF MEROMORPHIC FUNCTIONS IN SEVERAL VARIABLES

In this paper,we mainly investigate the value distribution of meromorphic functions in Cmwith its partial differential and uniqueness problem on meromorphic functions in Cmand with its k-th total derivative sharing small functions.As an application of the value distribution result,we study the defect relation of a nonconstant solution to the partial differential equation.In particular,we give a connection between the Picard type theorem of Milliox-Hayman and the characterization of entire solutions of a partial differential equation.

Neural Mechanisms of Mental Fatigue Revisited: New Insights from the Brain Connectome

Maintaining sustained attention during a prolonged cognitive task often comes at a cost: high levels of mental fatigue. Heuristically, mental fatigue refers to a feeling of tiredness or exhaustion, and a disengagement from the task at hand;it manifests as impaired cognitive and behavioral performance. In order to effectively reduce the undesirable yet preventable consequences of mental fatigue in many real-world workspaces, a better understanding of the underlying neural mechanisms is needed, and continuous efforts have been devoted to this topic. In comparison with conventional univariate approaches, which are widely utilized in fatigue studies, convergent evidence has shown that multivariate functional connectivity analysis may lead to richer information about mental fatigue. In fact, mental fatigue is increasingly thought to be related to the deviated reorganization of functional connectivity among brain regions in recent studies. In addition, graph theoretical analysis has shed new light on quantitatively assessing the reorganization of the brain functional networks that are modulated by mental fatigue. This review article begins with a brief introduction to neuroimaging studies on mental fatigue and the brain connectome, followed by a thorough overview of connectome studies on mental fatigue. Although only a limited number of studies have been published thus far, it is believed that the brain connectome can be a useful approach not only for the elucidation of underlying neural mechanisms in the nascent field of neuroergonomics, but also for the automatic detection and classification of mental fatigue in order to address the prevention of fatigue-related human error in the near future.

Apparent diffusion coefficient evaluation for secondary changes in the cerebellum of rats after middle cerebral artery occlusion

Supratentorial cerebral infarction can cause functional inhibition of remote regions such as the cerebellum, which may be relevant to diaschisis. This phenomenon is often analyzed using positron emission tomography and single photon emission CT. However, these methods are expensive and radioactive. Thus, the present study quantified the changes of infarction core and remote regions after unilateral middle cerebral artery occlusion using apparent diffusion coefficient values. Diffu- sion-weighted imaging showed that the area of infarction core gradually increased to involve the cerebral cortex with increasing infarction time. Diffusion weighted imaging signals were initially in- creased and then stabilized by 24 hours. With increasing infarction time, the apparent diffusion co- efficient value in the infarction core and remote bilateral cerebellum both gradually decreased, and then slightly increased 3-24 hours after infarction. Apparent diffusion coefficient values at remote regions （cerebellum） varied along with the change of supratentorial infarction core, suggesting that the phenomenon of diaschisis existed at the remote regions. Thus, apparent diffusion coefficient values and diffusion weighted imaging can be used to detect early diaschisis.

复微分-差分方程组的超越解 献给余家荣教授100华诞

本文利用复差分值分布理论和复微分方程理论,将复差分方程和微分方程结合起来,首先研究一类复高阶微分-差分方程超越整函数解,给出其超越整函数解的具体形式.其次,进一步考虑更为复杂的两类复微分-差分方程组超越整函数解的形式以及微分-差分方程组解的存在性问题,得到在一定条件下不存在超越整函数解的结论,例子表明本文定理中的条件是精确的.第三,讨论一类复微分-差分方程组,得到关于解的增长级的一个结果.最后,讨论一类复高阶?差分微分-函数方程超越亚纯解的特征函数,在对其系数的特征函数给出限制时,得到其超越亚纯解的特征估计,例子也表明本文的条件是精确的.

Hybrid Method Based on Information Gain and Support Vector Machine for Gene Selection in Cancer Classi?cation

It remains a great challenge to achieve sufficient cancer classification accuracy with the entire set of genes, due to the high dimensions, small sample size, and big noise of gene expression data. We thus proposed a hybrid gene selection method, Information Gain-Support Vector Machine （IG-SVM） in this study. IG was initially employed to filter irrelevant and redundant genes. Then, further removal of redundant genes was performed using SVM to eliminate the noise in the datasets more effectively. Finally, the informative genes selected by IG-SVM served as the input for the LIBSVM classifier. Compared to other related algorithms, IG-SVM showed the highest classification accuracy and superior performance as evaluated using five cancer gene expression datasets based on a few selected genes. As an example, IG-SVM achieved a classification accuracy of 90.32% for colon cancer, which is difficult to be accurately classified, only based on three genes including CSRP1, MYLg, and GUCA2B.