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Beijing, China

Tan Y.,Chinese Academy of Sciences | Jia D.,Science Press | Lin Z.,Shanghai University | Guo B.,Hong Kong Baptist University | And 12 more authors.
International Journal of Molecular Sciences | Year: 2016

Determining sensitive biomarkers in the peripheral blood to identify interstitial lung abnormalities (ILAs) is essential for the simple early diagnosis of ILAs. This study aimed to determine serum metabolic biomarkers of ILAs and the corresponding pathogenesis. Three groups of subjects undergoing health screening, including healthy subjects, subjects with ILAs, and subjects who were healthy initially and with ILAs one year later (Healthy→ILAs), were recruited for this study. The metabolic profiles of all of the subjects’ serum were analyzed by liquid chromatography quadruple time-of-flight mass spectrometry. The metabolic characteristics of the ILAs subjects were discovered, and the corresponding biomarkers were predicted. The metabolomic data from the Healthy→ILAs subjects were collected for further verification. The results indicated that five serum metabolite alterations (up-regulated phosphatidylcholine, phosphatidic acid, betaine aldehyde and phosphatidylethanolamine, as well as down-regulated 1-acylglycerophosphocholine) were sensitive and reliable biomarkers for identifying ILAs. Perturbation of the corresponding biological pathways (RhoA signaling, mTOR/P70S6K signaling and phospholipase C signaling) might be at least partially responsible for the pathogenesis of ILAs. This study may provide a good template for determining the early diagnostic markers of subclinical disease status and for obtaining a better understanding of their pathogenesis. © 2016 by the authors; licensee MDPI, Basel, Switzerland. Source


Wang S.,Shanxi University | Wang S.,Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education | Li D.,Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education | Li D.,Shanxi University | And 3 more authors.
Expert Systems with Applications | Year: 2011

Owing to its openness, virtualization and sharing criterion, the Internet has been rapidly becoming a platform for people to express their opinion, attitude, feeling and emotion. As the subjectivity texts are often too many for people to go through, how to automatically classify them into different sentiment orientation categories (e.g. positive/negative) has become an important research problem. In this paper, based on Fisher's discriminant ratio, an effective feature selection method is proposed for subjectivity text sentiment classification. In order to validate the proposed method, we compared it with the method based on Information Gain while Support Vector Machine is adopted as the classifier. Two experiments are conducted by combining different feature selection methods with two kinds of candidate feature sets. Under 2739 subjectivity documents of COAE2008s and 1006 car-related subjectivity documents, the experimental results indicate that the Fisher's discriminant ratio based on word frequency estimation has the best performance respectively with accuracy 86.61% and 82.80% under two corpus while the candidate features are the words which appear in both positive and negative texts. © 2011 Elsevier Ltd. All rights reserved. Source


Wang P.,Peking University | Wang P.,CAS Guangzhou Institute of Geochemistry | Wang Y.,Science Press | Yang Y.-F.,Chengdu Center
Ore Geology Reviews | Year: 2016

The Tangjiaping Mo deposit is located in the Dabie Shan in eastern China. Molybdenum (Mo) mineralization mainly occurs as veinlets in the Tangjiaping granite porphyry, which is featured by the development of potassic-silicic-, phyllic- and propylitic alterations. The Mo-mineralized granite porphyry yields a zircon UPb age of 118.1±0.8Ma (MSWD=1.6, 2σ, n=24), and may have formed under post-collision extensional tectonics after the Yangtze-North China collision. The Tangjiaping granite porphyry is characterized by the enrichments of LILEs and LREEs, depletions of Ba, Nb, Ta, Sr, P, Ti and HREEs, and negative Eu anomaly. Zircons from the granite porphyry yield negative εHf(t) of -15.3 to -9.9, with TDM2(Hf) ages of 1.80 to 2.14Ga. The 206Pb/204Pb, 207Pb/204Pb and 208Pb/204Pb of the granite porphyry and its K-feldspar are 16.842-17.342, 15.388-15.439 and 37.706-38.260, respectively, while those of the sulfides are 17.090-17.832, 15.420-15.510, and 37.550-38.026, respectively. The δ34S of these sulfides exhibit a relatively narrow range of 3.2-4.9‰, with an average of 4.0‰. The HfPbS isotopic signatures indicate that the granite porphyry and the ore-forming materials at Tangjiaping were mainly derived from the partial melting of both the Southern Dabie Complex and the Precambrian basement of the North China Craton. © 2016 Elsevier B.V. Source


Zhou G.,Hunan Normal University | He Y.,Hunan Normal University | Tang C.,Hunan Normal University | Yu T.,Science Press | Xiao G.,Hunan Normal University
Acta Geographica Sinica | Year: 2011

This paper makes a deep analysis of the influencing factors in rural settlements evolution, including natural environment constraints, infrastructure, regional cultural inheritance and integration, urbanization and rural industry transformation, land use reformation and innovation, rural household behavior conversion, macro-control policy factors, and so on. Based on the differences between their effective way and degree to rural settlements evolution, these factors are classified into base factors, new-type factors and mutation factors. The driving of base factors is mainly focused on traditional inheritance of rural settlements, the new-type factors mainly have effect on rural settlements transition, and the mutation factors may bring about sudden change. All these factors constitute "three-wheel" driving mechanism of rural settlements evolution, and shape three typical driver paths, which are slow smooth path under the base factors, new path to rapid development under the new-type factors, sudden change path under the mutation factors. The paper also investigates the overall situation of rural settlements evolution in the aspects of the settlement system, settlements scale, settlements morphology, settlements function, settlements culture, settlements environment, and so on. And the general process of rural settlements evolution is divided into four stages, i.e., initial stage, transitional stage, development stage and mature stage. Source


Wang S.,Shanxi University | Li D.,Shanxi University | Wei Y.,Science Press
Jisuanji Yanjiu yu Fazhan/Computer Research and Development | Year: 2011

Facing with promptly increasing reviews on the Web, it has been great challenge for information science and technology that how people effectively organize and process document data hiding large amounts of information to meet with particular needs. Text sentiment classification aims at developing some new theories and methods to automatically explore the sentiment orientation of a text by mining and analyzing subjective information in texts such as standpoint, view, attitude, mood, and so on. A method of text sentiment classification based on weighted rough membership is proposed in this paper. In the method, the model of text expression is established based on two-tuples attribute (feature, feature orientation intensity), by introducing feature orientation intensity into the method of vector space representation. An attribute discretization method is proposed based on the sentiment orientation sequence for feature selection unifying the discretization processing to depress data dimension. To utilize the feature orientation intensity, a weighted rough membership is defined for classifying new sentiment text. Compared with SVM classifier, on the reality car review corpus, the proposed method based on rough membership for text sentiment classification has the best performance after data being compressed in a certainty extent for text sentiment classification. Source

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