Browsing by Author "Chen, M"

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    Behavior of different numerical schemes for random genetic drift
    (BIT Numerical Mathematics, 2019-09-01) Xu, S; Chen, M; Liu, C; Zhang, R; Yue, X
    In the problem of random genetic drift, the probability density of one gene is governed by a degenerated convection-dominated diffusion equation. Dirac singularities will always be developed at boundary points as time evolves, which is known as the fixation phenomenon in genetic evolution. Three finite volume methods: FVM1-3, one central difference method: FDM1 and three finite element methods: FEM1-3 are considered. These methods lead to different equilibrium states after a long time. It is shown that only schemes FVM3 and FEM3, which are the same, preserve probability, expectation and positiveness and predict the correct probability of fixation. FVM1-2 wrongly predict the probability of fixation due to their intrinsic viscosity, even though they are unconditionally stable. Contrarily, FDM1 and FEM1-2 introduce different anti-diffusion terms, which make them unstable and fail to preserve positiveness.
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    Clinical epidemiology and outcome of HIV-associated talaromycosis in Guangdong, China, during 2011-2017.
    (HIV medicine, 2020-12) Ying, RS; Le, T; Cai, WP; Li, YR; Luo, CB; Cao, Y; Wen, CY; Wang, SG; Ou, X; Chen, WS; Chen, SZ; Guo, PL; Chen, M; Guo, Y; Tang, XP; Li, LH

    Objectives

    Talaromycosis is an invasive mycosis endemic to Southeast Asia. This study aimed to investigate the epidemiology, clinical features and prognostic factors of HIV-associated talaromycosis in Guangdong, China.

    Methods

    We retrospectively evaluated HIV patients hospitalized with histopathology- or culture-confirmed talaromycosis between 2011 and 2017. Factors associated with poor prognosis were identified using logistic regression.

    Results

    Overall, 1079 patients with HIV-associated talaromycosis were evaluated. Both the number and prevalence of talaromycosis among HIV admissions increased from 125 and 15.7% in 2011 to 253 and 18.8% in 2017, respectively, reflecting the increase in HIV admissions. Annual admissions peaked during the rainy season between March and August. Common clinical manifestations included fever (85.6%), peripheral lymphadenopathy (72.3%), respiratory symptoms (60.8%), weight loss (49.8%), skin lesions (44.5%) and gastrointestinal symptoms (44.3%). Common laboratory abnormalities were hypoalbuminaemia (98.6%), anaemia (95.6%), elevated aspartate aminotransferase level (AST) (76.9%), elevated alkaline phosphatase level (55.8%) and thrombocytopenia (53.7%). The median CD4 count was 9 cells/μL. Talaromyces marneffei was isolated from blood and bone marrow cultures of 66.6% and 74.5% of patients, respectively. The rate increased to 86.6% when both cultures were performed concurrently. At discharge, 14% of patients showed worsening conditions or died. Leucocytosis, thrombocytopenia, elevated AST, total bilirubin, creatinine and azole monotherapy independently predicted poor prognosis.

    Conclusions

    The incidence of HIV-associated talaromycosis has increased in Guangdong with the high HIV burden in China. Skin lesions were seen in less than half of patients. Induction therapy with azole alone is associated with higher mortality. Findings from this study should help to improve treatment of the disease.
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    Communications inspired linear discriminant analysis
    (Proceedings of the 29th International Conference on Machine Learning, ICML 2012, 2012-10-10) Chen, M; Carson, W; Rodrigues, M; Calderbank, R; Carin, L
    We study the problem of supervised linear dimensionality reduction, taking an information-theoretic viewpoint. The linear projection matrix is designed by maximizing the mutual information between the projected signal and the class label. By harnessing a recent theoretical result on the gradient of mutual information, the above optimization problem can be solved directly using gradient descent, without requiring simplification of the objective function. Theoretical analysis and empirical comparison are made between the proposed method and two closely related methods, and comparisons are also made with a method in which Rényi entropy is used to define the mutual information (in this case the gradient may be computed simply, under a special parameter setting). Relative to these alternative approaches, the proposed method achieves promising results on real datasets. Copyright 2012 by the author(s)/owner(s).
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    Communications-inspired projection design with application to compressive sensing
    (SIAM Journal on Imaging Sciences, 2012-12-01) Carson, WR; Chen, M; Rodrigues, MRD; Calderbank, R; Carin, L
    We consider the recovery of an underlying signal x ∈ ℂm based on projection measurements of the form y = Mx+w, where y ∈ ℂℓ and w is measurement noise; we are interested in the case ℓ ≪ m. It is assumed that the signal model p(x) is known and that w ~ CN(w; 0,Σw) for known Σ w. The objective is to design a projection matrix M ∈ ℂℓ×m to maximize key information-theoretic quantities with operational significance, including the mutual information between the signal and the projections I(x; y) or the Rényi entropy of the projections hα (y) (Shannon entropy is a special case). By capitalizing on explicit characterizations of the gradients of the information measures with respect to the projection matrix, where we also partially extend the well-known results of Palomar and Verdu ́ from the mutual information to the Rényi entropy domain, we reveal the key operations carried out by the optimal projection designs: mode exposure and mode alignment. Experiments are considered for the case of compressive sensing (CS) applied to imagery. In this context, we provide a demonstration of the performance improvement possible through the application of the novel projection designs in relation to conventional ones, as well as justification for a fast online projection design method with which state-of-the-art adaptive CS signal recovery is achieved. © 2012 Society for Industrial and Applied Mathematics.
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    Modeling and Simulating Asymmetrical Conductance Changes in Gramicidin Pores
    (Computational and Mathematical Biophysics, 2014-01-01) Xu, S; Chen, M; Majd, S; Yue, X; Liu, C
    Gramicidin A is a small and well characterized peptide that forms an ion channel in lipid membranes. An important feature of gramicidin A (gA) pore is that its conductance is affected by the electric charges near the its entrance. This property has led to the application of gramicidin A as a biochemical sensor for monitoring and quantifying a number of chemical and enzymatic reactions. Here, a mathematical model of conductance changes of gramicidin A pores in response to the presence of electrical charges near its entrance, either on membrane surface or attached to gramicidin A itself, is presented. In this numerical simulation, a two dimensional computational domain is set to mimic the structure of a gramicidin A channel in the bilayer surrounded by electrolyte. The transport of ions through the channel is modeled by the Poisson-Nernst-Planck (PNP) equations that are solved by Finite Element Method (FEM). Preliminary numerical simulations of this mathematical model are in qualitative agreement with the experimental results in the literature. In addition to the model and simulations, we also present the analysis of the stability of the solution to the boundary conditions and the convergence of FEM method for the two dimensional PNP equations in our model.
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    Optimal Monitoring Schedule in Dynamic Contracts
    (2017-09-16) Chen, M; Sun, P; Xiao, Y