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Search Results: 1 - 10 of 78851 matches for " Xiaohong Chen "
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Spatio-Temporal Variations of Precipitation Extremes in the Yangtze River Basin (1960-2002), China  [PDF]
Qiang Zhang, Xiaohong Chen, Becker Stefan
Atmospheric and Climate Sciences (ACS) , 2011, DOI: 10.4236/acs.2011.11001
Abstract: Daily precipitation data during 1960-2002 from 150 stations in the Yangtze River basin were analyzed with the help of linear trend analysis. Highest 5-day and 10-day precipitation amount (R5D and R10D) and percentile daily precipitation maxima (prec95p for 95th percentile and prec99p for 99th percentile) were accepted as the precipitation extreme index. The frequency of the R5D and R10D was in downward trend, this phenomenon is more obvious in the middle Yangtze River basin; The stations with total precipitation of R5D and R10D are in significant upward trend (> 95% confidence level) are mostly located in the lower Yangtze River basin and the south-western part of the Yangtze River basin; 2) the spatial distribution of the frequency of total precipitation of the percentile daily precipitation maxima is similar to that of R5D and R10D. However the frequency of prec95p and prec99p is in significant upward trend. The upward trend of total precipitation changes of prec95p and prec99p is more obvious than that of frequency of prec95p and prec99p. The regions dominated by upward trend of frequency/total precipitation of prec95p and prec99p are also the lower Yangtze River basin and south-western part of the Yangtze River basin. Therefore the occurrence probability of the flash floods in the lower Yangtze River basin and south-western part of the Yangtze River basin will be greater.
Regional Evaluations of the Meteorological Drought Characteristics across the Pearl River Basin, China  [PDF]
Qiang Zhang, Mingzhong Xiao, Xiaohong Chen
American Journal of Climate Change (AJCC) , 2012, DOI: 10.4236/ajcc.2012.11005
Abstract: Regional evaluation of drought characteristics provides critical information for water resource management. In this case, this study attempts to analyze the probability behaviors of drought events of a given severity in the Pearl River Basin and to construct severity-area-frequency curves of drought events. Due to possible impacts of complicated topographical properties and diverse climate types within the Pearl River Basin, the entire Pearl River Basin is subdivided into different homogeneous regions. In general, the Pearl River Basin can be categorized into four homogeneous regions, and the severity-area-frequency analysis results for the short-, medium- and long-term drought episodes within each homogeneous regions indicate stressful challenge for the water resource management in the Pearl River Basin due to the fact that severe droughts usually occur over the entire Pearl River Basin. Meanwhile, the Pearl River Delta will face a higher risk of drought when compared to other regions of the Pearl River Basin in terms of the medium-term drought. The Pearl River Basin is highly economically development and is heavily populated, thus impacts of droughts and related resilience resolutions or policies should be taken into account in the formulation of regional sustainable development of water resources and socio-economy within the Pearl River Basin, China.
Interval-Valued Intuitionistic Fuzzy Multicriteria Group Decision Making Based on VIKOR and Choquet Integral
Chunqiao Tan,Xiaohong Chen
Journal of Applied Mathematics , 2013, DOI: 10.1155/2013/656879
Abstract: An effective decision making approach based on VIKOR and Choquet integral is developed to solve multicriteria group decision making problem with conflicting criteria and interdependent subjective preference of decision makers in a fuzzy environment where preferences of decision makers with respect to criteria are represented by interval-valued intuitionistic fuzzy sets. First, an interval-valued intuitionistic fuzzy Choquet integral operator is given. Some of its properties are investigated in detail. The extended VIKOR decision procedure based on the proposed operator is developed for solving the multicriteria group decision making problem where the interactive criteria weight is measured by Shapley value. An illustrative example is given for demonstrating the applicability of the proposed decision procedure for solving the multi-criteria group decision making problem in interval-valued intuitionistic fuzzy environment. 1. Introduction The increasing complexity of the socioeconomic environments makes it less and less possible for a single decision maker to consider all relevant aspects of a problem. Hence, in order to get a more reasonable decision result, a decision organization, such as the board of directors of a company, which contains a collection of decision makers, is set up explicitly or implicitly to assess the alternatives. The analysis must be extended to account, somehow, for group decision makers, each one potentially exhibiting a unique preference structure, perceiving different consequences, and responding to a diverse array of aspirations [1]. Multiple criteria or attribute decision making (MCDM or MADM) problems is to find the best compromise solution among all feasible alternatives assessed on the basis of multiple criteria or attributes, both quantitative and qualitative. Due to the complex structure of the problem and conflicting nature of the criteria for multi-criteria decision making, trade-offs assessment is one of the most difficult issues in multi-criteria decision making. There may be no solution satisfying all criteria simultaneously. Thus, the solution is a set of noninferior solutions or a compromise solution according to the decision maker’s preferences. By using compromise programming, the compromise solution was established by Yu [2] and Zeleny [3] for a problem with conflicting criteria and it can be helping the decision makers to reach a final solution. The compromise solution is a feasible solution, which is the closest to the ideal, and compromise means an agreement established by mutual concessions. Based on the
On rate optimality for ill-posed inverse problems in econometrics
Xiaohong Chen,Markus Reiss
Mathematics , 2007,
Abstract: In this paper, we clarify the relations between the existing sets of regularity conditions for convergence rates of nonparametric indirect regression (NPIR) and nonparametric instrumental variables (NPIV) regression models. We establish minimax risk lower bounds in mean integrated squared error loss for the NPIR and the NPIV models under two basic regularity conditions that allow for both mildly ill-posed and severely ill-posed cases. We show that both a simple projection estimator for the NPIR model, and a sieve minimum distance estimator for the NPIV model, can achieve the minimax risk lower bounds, and are rate-optimal uniformly over a large class of structure functions, allowing for mildly ill-posed and severely ill-posed cases.
Optimal Uniform Convergence Rates for Sieve Nonparametric Instrumental Variables Regression
Xiaohong Chen,Timothy Christensen
Statistics , 2013,
Abstract: We study the problem of nonparametric regression when the regressor is endogenous, which is an important nonparametric instrumental variables (NPIV) regression in econometrics and a difficult ill-posed inverse problem with unknown operator in statistics. We first establish a general upper bound on the sup-norm (uniform) convergence rate of a sieve estimator, allowing for endogenous regressors and weakly dependent data. This result leads to the optimal sup-norm convergence rates for spline and wavelet least squares regression estimators under weakly dependent data and heavy-tailed error terms. This upper bound also yields the sup-norm convergence rates for sieve NPIV estimators under i.i.d. data: the rates coincide with the known optimal $L^2$-norm rates for severely ill-posed problems, and are power of $\log(n)$ slower than the optimal $L^2$-norm rates for mildly ill-posed problems. We then establish the minimax risk lower bound in sup-norm loss, which coincides with our upper bounds on sup-norm rates for the spline and wavelet sieve NPIV estimators. This sup-norm rate optimality provides another justification for the wide application of sieve NPIV estimators. Useful results on weakly-dependent random matrices are also provided.
Optimal Uniform Convergence Rates and Asymptotic Normality for Series Estimators Under Weak Dependence and Weak Conditions
Xiaohong Chen,Timothy Christensen
Statistics , 2014,
Abstract: We show that spline and wavelet series regression estimators for weakly dependent regressors attain the optimal uniform (i.e. sup-norm) convergence rate $(n/\log n)^{-p/(2p+d)}$ of Stone (1982), where $d$ is the number of regressors and $p$ is the smoothness of the regression function. The optimal rate is achieved even for heavy-tailed martingale difference errors with finite $(2+(d/p))$th absolute moment for $d/p<2$. We also establish the asymptotic normality of t statistics for possibly nonlinear, irregular functionals of the conditional mean function under weak conditions. The results are proved by deriving a new exponential inequality for sums of weakly dependent random matrices, which is of independent interest.
Sieve Wald and QLR Inferences on Semi/nonparametric Conditional Moment Models
Xiaohong Chen,Demian Pouzo
Statistics , 2014,
Abstract: This paper considers inference on functionals of semi/nonparametric conditional moment restrictions with possibly nonsmooth generalized residuals, which include all of the (nonlinear) nonparametric instrumental variables (IV) as special cases. These models are often ill-posed and hence it is difficult to verify whether a (possibly nonlinear) functional is root-$n$ estimable or not. We provide computationally simple, unified inference procedures that are asymptotically valid regardless of whether a functional is root-$n$ estimable or not. We establish the following new useful results: (1) the asymptotic normality of a plug-in penalized sieve minimum distance (PSMD) estimator of a (possibly nonlinear) functional; (2) the consistency of simple sieve variance estimators for the plug-in PSMD estimator, and hence the asymptotic chi-square distribution of the sieve Wald statistic; (3) the asymptotic chi-square distribution of an optimally weighted sieve quasi likelihood ratio (QLR) test under the null hypothesis; (4) the asymptotic tight distribution of a non-optimally weighted sieve QLR statistic under the null; (5) the consistency of generalized residual bootstrap sieve Wald and QLR tests; (6) local power properties of sieve Wald and QLR tests and of their bootstrap versions; (7) asymptotic properties of sieve Wald and SQLR for functionals of increasing dimension. Simulation studies and an empirical illustration of a nonparametric quantile IV regression are presented.
Steady State Temperature Study on RF LDMOS with Structure Modification  [PDF]
Xiaohong Sun, Haodong Wu, Qiang Chen, Huai Gao
Engineering (ENG) , 2012, DOI: 10.4236/eng.2012.47049
Abstract: This paper is devoted to temperature analysis on power RF LDMOS with different feature parameters of die thickness, pitch S length and finger width. The significance of these three parameters is determined from temperature comparison obtained by 3D Silvaco-Atlas device simulator. The first three simulations focus on temperature variation with the three factors at different output power density respectively. The results indicate that both the thinner die thickness and the broaden pitch S length have distinct advantages over the shorter finger width. The device, at the same time, exhibits higher temperature at a larger output power density. Simulations are further carried out on structure with combination of different pitch s length and die thickness at a large 1W/mm output power density and the temperature reduction reaches as high as 55%.
Utilization of Dispersive Liquid-Liquid Microextraction Coupled with HPLC-UV as a Sensitive and Efficient Method for the Extraction and Determination of Oleanolic Acid and Ursolic Acid in Chinese Medicinal Herbs  [PDF]
Yaomei Hao, Xuan Chen, Shuang Hu, Xiaohong Bai, Deshuang Gu
American Journal of Analytical Chemistry (AJAC) , 2012, DOI: 10.4236/ajac.2012.310089
Abstract: Isomeric triterpenic acids of oleanolic acid (OA) and ursolic acid (UA) both have very low ultraviolet absorption and always exist in the same plant, so the separation and simultaneous determination of them have been a difficult task. In this study, a sensitive method combining dispersive liquid-liquid microextraction (DLLME) with HPLC-UV was developed for the extraction and determination of OA and UA in traditional Chinese medicinal herbs (CMHs). Variables influencing DLLME such as type and volume of extraction solvent, volume of dispersive solvent, ionic strength, aqueous phase pH, extraction time, centrifugation speed and time, and sample volume were investigated and optimized. Under the optimum conditions, both OA and UA attained favorable extraction efficiencies with enrichment factors 1378 and 933, respectively. The linear dynamic ranges of 0.07 - 30.4 μg?mL–1 for OA and 0.08 - 33.6 μg?mL–1 for UA were obtained with square correlation coefficients of 0.9963. The detection limits of OA and UA were both 0.02 μg?mL–1. The method recoveries ranged between 88.2% - 116.2% for OA and 85.7% - 108.2% for UA with the RSDs (n = 5) lower than 8.6%. The proposed method was successfully applied to concentrate and simultaneously determine these two triterpenic acids in Hedyotis diffusa and Eriobotrya japonica samples.
Research of Anti-Cancer Components in Traditional Chinese Medicine on Hollow Fibre Cell Fishing and Hollow Fibre Liquid Phase Microextraction  [PDF]
Feixue Li, Xuan Chen, Yanli Xu, Xiaohong Bai
American Journal of Analytical Chemistry (AJAC) , 2016, DOI: 10.4236/ajac.2016.710063
Abstract: Hollow fibre cell fishing with HPLC (HFCF-HPLC) based on the human ovarian cancer cell line SKOV-3, human renal tubular cell line ACHN or hepatoma cell line HepG-2 was employed to screen active groups of coumarin and volatile oil in Radix angelicae sinensis, Radix angelicae dahuricae and Fructus citri sarcodactylis. Simultaneously, hollow fibre liquid phase microextraction with HPLC (HFLPME-HPLC) was conducted to enrich and determine the contents of active components in the same sample solution. Before application, for HFCF-HPLC, cells growth states and survival rates on the fibre, effect of ethanol concentration in the extract of samples on cell survival rates, non-specific binding between fibre active centres and the target components, positive and negative controls and repeatabilities were validated; for HFLPME, extraction solvent, sample phase pH, agitation speed, extraction time and sample phase volume were investigated. Many active components were screened from three medicines. Some of them, such as scoparone, psoralen, bergapten, oxypeucedanin, imperatorin, ligustilide, were identified by MS. The target fishing factors of active components and the cell apoptosis rates of three cells under the medicines effect were researched. The binding sites of active groups on HepG-2 cells were preliminarily determined. The results demonstrated that HFCF-HPLC, coupled with HFLPME-HPLC, is a simple and universal approach to find bioactive components at the cellular level, determine their content and research traditional Chinese medicines (TCMs) entirety effect of multi-component and multi-target. The approach may provide us a new and good solution to clarify the material basis of anti-cancer effect and conduct personalized quality control for the components associated with efficacy in TCMs.
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