Xiaohui Chen

Bio: Xiaohui Chen is an academic researcher from Fujian Agriculture and Forestry University. The author has contributed to research in topics: High-performance liquid chromatography & Estimator. The author has an hindex of 30, co-authored 261 publications receiving 3685 citations. Previous affiliations of Xiaohui Chen include University of Leeds & Toyota Technological Institute.

Covariance and precision matrix estimation for high-dimensional time series

Abstract: We consider estimation of covariance matrices and their inverses (a.k.a. precision matrices) for high-dimensional stationary and locally stationary time series. In the latter case the covariance matrices evolve smoothly in time, thus forming a covariance matrix function. Using the functional dependence measure of Wu [Proc. Natl. Acad. Sci. USA 102 (2005) 14150-14154 (electronic)], we obtain the rate of convergence for the thresholded estimate and illustrate how the dependence affects the rate of convergence. Asymptotic properties are also obtained for the precision matrix estimate which is based on the graphical Lasso principle. Our theory substantially generalizes earlier ones by allowing dependence, by allowing nonstationarity and by relaxing the associated moment conditions.

Covariance and precision matrix estimation for high-dimensional time series

Abstract: We consider estimation of covariance matrices and their inverses (a.k.a. precision matrices) for high-dimensional stationary and locally stationary time series. In the latter case the covariance matrices evolve smoothly in time, thus forming a covariance matrix function. Using the functional dependence measure of Wu [Proc. Natl. Acad. Sci. USA 102 (2005) 14150–14154 (electronic)], we obtain the rate of convergence for the thresholded estimate and illustrate how the dependence affects the rate of convergence. Asymptotic properties are also obtained for the precision matrix estimate which is based on the graphical Lasso principle. Our theory substantially generalizes earlier ones by allowing dependence, by allowing nonstationarity and by relaxing the associated moment conditions.

Simultaneous determination of seven bioactive components in Oolong tea Camellia sinensis: quality control by chemical composition and HPLC fingerprints.

Abstract: A simple and reliable method of high-performance liquid chromatography (HPLC) was developed for the quality control of oolong tea (the dry leaves of Camellia sinensis): the quality control included the HPLC fingerprint and the quantitative determination of seven bioactive compounds chemicals, namely, (−)-gallocatechin, (−)-epigallocatechin, (−)-epigallocatechin gallate, caffeine, (−)-epicatechin, gallocatechin gallate, and (−)-epicatechin gallate. The developed analyses of the chemicals excelled in quantifying the chemicals in oolong tea. The chemical fingerprint of oolong tea was established using the raw materials of three main production sites in China, that is, Fujian (southern and northern parts), Taiwan, and Guangdong. The fingerprints from different cultivated sources were analyzed by hierarchical cluster analysis, similarity analysis, principal component analysis (PCA), analysis of variance (ANOVA), and discriminant analysis. The results indicated that the combination of chromatographic fingerprin...

The Theory of Island Biogeography

Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

Random graphs

Abstract: We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Singular Value Decomposition for Genome-Wide Expression Data Processing and Modeling

Abstract: ‡We describe the use of singular value decomposition in transforming genome-wide expression data from genes 3 arrays space to reduced diagonalized ‘‘eigengenes’’ 3 ‘‘eigenarrays’’ space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.

In vivo photodynamic therapy using upconversion nanoparticles as remote-controlled nanotransducers

Abstract: Conventional photodynamic therapy (PDT) is limited by the penetration depth of visible light needed for its activation. Here we used mesoporous-silica-coated upconversion fluorescent nanoparticles (UCNs) as a nanotransducer to convert deeply penetrating near-infrared light to visible wavelengths and a carrier of photosensitizers. We also used the multicolor-emission capability of the UCNs at a single excitation wavelength for simultaneous activation of two photosensitizers for enhanced PDT. We showed a greater PDT efficacy with the dual-photosensitizer approach compared to approaches using a single photosensitizer, as determined by enhanced generation of singlet oxygen and reduced cell viability. In vivo studies also showed tumor growth inhibition in PDT-treated mice by direct injection of UCNs into melanoma tumors or intravenous injection of UCNs conjugated with a tumor-targeting agent into tumor-bearing mice. As the first demonstration, to the best of our knowledge, of the photosensitizer-loaded UCN as an in vivo-targeted PDT agent, this finding may serve as a platform for future noninvasive deep-cancer therapy.