oalib

Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99

Submit

Any time

2019 ( 47 )

2018 ( 461 )

2017 ( 511 )

2016 ( 444 )

Custom range...

Search Results: 1 - 10 of 33011 matches for " Xiang Fang "
All listed articles are free for downloading (OA Articles)
Page 1 /33011
Display every page Item
Internet-Future Business Development Focus  [PDF]
Xiang Fang, Yangping Zhou
American Journal of Industrial and Business Management (AJIBM) , 2012, DOI: 10.4236/ajibm.2012.23011
Abstract: The paper compares the characteristics of traditional business model to future business model development. Internet will be the most important growth point on business development. With the internet business growth and development or the potential customers growth, future business development and enlargement should be focused. The relevant contents discussion will be good to the future business development.
On a Question of Arveson about Ranks of Hilbert modules
Xiang Fang
Mathematics , 2001,
Abstract: It's well known that the functional Hilbert space over the unit ball in $B_{d} \in C^d$, with kernel function $K(z,w)=\frac{1}{1-z_{1}w_{1}-... -z_{d}w_{d}}$, admits a natural $A(B_{d})$-module structure. We show the rank of a nonzero submodule is infinity if and only if the submodule is of infinite codimension. Together with Arveson's dilation theory, our result shows that Hilbert modules stand in stark contrast with Hilbert basis theorem for algebraic modules. This result answers a question of Arveson.
The Fredholm index of a pair of commuting operators
Xiang Fang
Mathematics , 2005,
Abstract: This paper concerns Fredholm theory in several variables, and its applications to Hilbert spaces of analytic functions. One feature is the introduction of ideas from commutative algebra to operator theory. Specifically, we introduce a method to calculate the Fredholm index of a pair of commuting operators. To achieve this, we define and study the Hilbert space analogs of Samuel multiplicities in commutative algebra. Then the theory is applied to the symmetric Fock space. In particular, our results imply a satisfactory answer to Arveson's program on developing a Fredholm theory for pure $d$-contractions when $d=2$, including both the Fredholmness problem and the calculation of indices. We also show that Arveson's curvature invariant is in fact always equal to the Samuel multiplicity for an arbitrary pure d-contraction with finite defect rank. It follows that the curvature is a similarity invariant.
Computer Assisted Pathway Generation for Atrazine Degradation in Advanced Oxidation Processes  [PDF]
Xiang Li, Fang Zeng, Ke Li
Journal of Environmental Protection (JEP) , 2013, DOI: 10.4236/jep.2013.41B012
Abstract: A model was developed to generate the complex degradation pathway of contaminants initiated by hydroxyl radical in the advanced oxidation processes. The model abstracts chemical structures into mathematic graphs. The manipulation of the graphs enumerates the reactions among the large number of molecules, radicals, and other intermediates in the advanced oxidation processes. Using Canonical Simplified Molecular Input Line Entry Specification (Canonical SMILE) representation, the algorithm was able to simulate the reaction of contaminants containing both chain and ring structures. The input chemicals, reaction pattern, and the reaction rules could be specified by users through a graphical user interface. The degradation pathway of Atrazine was used as an example to demonstrate the capability of the algorithm. The generated reaction pathways were compared with those reported in literatures.
Therapeutics Progression in Pancreatic Cancer and Cancer Stem Cells  [PDF]
Minwei Zhou, Yantian Fang, Jianbin Xiang, Zongyou Chen
Journal of Cancer Therapy (JCT) , 2015, DOI: 10.4236/jct.2015.63026
Abstract:

Pancreatic cancer (PC) is one of the most lethal malignant tumors, which often result from diagnoses of advanced stages and ineffective therapies. A main reason for this extremely poor prognosis is the cancer’s tendency to invade adjacent tissues and metastasize to regional lymph at a relatively early stage. Nowadays, the resistance to conventional chemotherapy is becoming crucial in poor clinical outcomes of PC. In order to improve the prognosis and clinical outcomes of PC, there is a pressing need to develop new therapeutic strategies not only aimed at preventing invasion and metastasis, but also improving the resistance of chemotherapies. The resistance to conventional therapeutic agents in cancer may be sustained by a fraction of cancer cells within the tumor, which is called the cancer stem cells (CSCs). Combined therapies targeting CSCs and their progenies may represent the most promising approach for the future treatment of patients with PC.

Mapping Paratope on Antithrombotic Antibody 6B4 to Epitope on Platelet Glycoprotein Ibalpha via Molecular Dynamic Simulations
Xiang Fang,Ying Fang,Li Liu,Guangjian Liu,Jianhua Wu
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0042263
Abstract: Binding of platelet receptor glycoprotein Ibα (GPIbα) to the A1 domain of von Willebrand factor (vWF) is a critical step in both physiologic hemostasis and pathologic thrombosis, for initiating platelet adhesion to subendothelium of blood vessels at sites of vascular injury. Gain-of-function mutations in GPIbα contribute to an abnormally high-affinity binding of platelets to vWF and can lead to thrombosis, an accurate complication causing heart attack and stroke. Of various antithrombotic monoclonal antibodies (mAbs) targeting human GPIbα, 6B4 is a potent one to inhibit the interaction between GPIbα and vWF-A1 under static and flow conditions. Mapping paratope to epitope with mutagenesis experiments, a traditional route in researches of these antithrombotic mAbs, is usually expensive and time-consuming. Here, we suggested a novel computational procedure, which combines with homology modeling, rigid body docking, free and steered molecular dynamics (MD) simulations, to identify key paratope residues on 6B4 and their partners on GPIbα, with hypothesis that the stable hydrogen bonds and salt bridges are the important linkers between paratope and epitope residues. Based on a best constructed model of 6B4 bound with GPIbα, the survival ratios and rupture times of all detected hydrogen bonds and salt bridges in binding site were examined via free and steered MD simulations and regarded as indices of thermal and mechanical stabilizations of the bonds, respectively. Five principal paratope residues with their partners were predicted with their high survival ratios and/or long rupture times of involved hydrogen bonds, or with their hydrogen bond stabilization indices ranked in top 5. Exciting, the present results were in good agreement with previous mutagenesis experiment data, meaning a wide application prospect of our novel computational procedure on researches of molecular of basis of ligand-receptor interactions, various antithrombotic mAbs and other antibodies as well as theoretically design of biomolecular drugs.
Proposal for a Loophole-Free Bell Test with Electron Spins of Donors in Silicon  [PDF]
Fang-Yu Hong, Shi-Jie Xiong, Yang Xiang, Wei Hua Tang
Journal of Modern Physics (JMP) , 2011, DOI: 10.4236/jmp.2011.29128
Abstract: So far, all experimental tests of Bell inequalities which must be satisfied by all local realistic hidden-variable theories and are violated by quantum mechanical predictions have left at least one loophole open. We propose a feasible setup allowing for a loophole-free test of the Bell inequalities. Two electron spin qubits of donors31P in a nanoscale silicon host in different cavities 300 m apart are entangled through a bright coherent light and postselections using homodyne measurements. The electron spins are then read out randomly and independently by Alice and Bob, respectively, with unity efficiency in less than 0.7 µs by using optically induced spin to charge transduction detected by radio-frequency single electron transistor. A violation of Bell inequality larger than 37% and 18% is achievable provided that the detection accuracy is 0.99 and 0.95, respectively.
Nuclear Power Plant Operator Reliability Research Based on Fuzzy Math
Fang Xiang,Zhou Yangping,Li Fu
Science and Technology of Nuclear Installations , 2011, DOI: 10.1155/2011/262585
Abstract: This paper makes use of the concept and theory of fuzzy number in fuzzy mathematics, to research for the response time of operator in accident of Chinese nuclear power plant. Through the quantitative analysis for the performance shape factors (PSFs) which influence the response time of operators, the formula of the operator response time is obtained based on the possibilistic fuzzy linear regression model which is used for the first time in this kind of research. The research result shows that the correct research method can be achieved through the analysis of the information from a small sample. This method breaks through the traditional research method and can be used not only for the reference to the safe operation of nuclear power plant, but also in other areas.
Sparse Representation for Classification of Tumors Using Gene Expression Data
Xiyi Hang,Fang-Xiang Wu
Journal of Biomedicine and Biotechnology , 2009, DOI: 10.1155/2009/403689
Abstract: Personalized drug design requires the classification of cancer patients as accurate as possible. With advances in genome sequencing and microarray technology, a large amount of gene expression data has been and will continuously be produced from various cancerous patients. Such cancer-alerted gene expression data allows us to classify tumors at the genomewide level. However, cancer-alerted gene expression datasets typically have much more number of genes (features) than that of samples (patients), which imposes a challenge for classification of tumors. In this paper, a new method is proposed for cancer diagnosis using gene expression data by casting the classification problem as finding sparse representations of test samples with respect to training samples. The sparse representation is computed by the 1-regularized least square method. To investigate its performance, the proposed method is applied to six tumor gene expression datasets and compared with various support vector machine (SVM) methods. The experimental results have shown that the performance of the proposed method is comparable with or better than those of SVMs. In addition, the proposed method is more efficient than SVMs as it has no need of model selection.
Mining and state-space modeling and verification of sub-networks from large-scale biomolecular networks
Xiaohua Hu, Fang-Xiang Wu
BMC Bioinformatics , 2007, DOI: 10.1186/1471-2105-8-324
Abstract: In this paper, we present a novel method to model the regulatory system which executes a cellular function and can be represented as a biomolecular network. Our method consists of two steps. First, a novel scale-free network clustering approach is applied to the large-scale biomolecular network to obtain various sub-networks. Second, a state-space model is generated for the sub-networks and simulated to predict their behavior in the cellular context. The modeling results represent hypotheses that are tested against high-throughput data sets (microarrays and/or genetic screens) for both the natural system and perturbations. Notably, the dynamic modeling component of this method depends on the automated network structure generation of the first component and the sub-network clustering, which are both essential to make the solution tractable.Experimental results on time series gene expression data for the human cell cycle indicate our approach is promising for sub-network mining and simulation from large-scale biomolecular network.We are in the era of holistic biology. Massive amounts of biological data await interpretation. This calls for formal modeling and computational methods. In this paper, we present a method to model the regulatory system which executes a cellular function and can be represented as a biomolecular network. Understanding the biomolecular network implementing some cellular function goes beyond the old dogma of "one gene: one function": only through comprehensive system understanding can we predict the impact of genetic variation in the population, design effective disease therapeutics, and evaluate the potential side-effects of therapies. As biomolecular networks grow in size and complexity, the model of a biomolecular network must become more rigorous to keep track of all the components and their interactions. In general this presents the need for computer simulation to manipulate and understand the biomolecular network model. However, a major ch
Page 1 /33011
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.