2,286 research outputs found

    Attribute Equilibrium Dominance Reduction Accelerator (DCCAEDR) Based on Distributed Coevolutionary Cloud and Its Application in Medical Records

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    © 2013 IEEE. Aimed at the tremendous challenge of attribute reduction for big data mining and knowledge discovery, we propose a new attribute equilibrium dominance reduction accelerator (DCCAEDR) based on the distributed coevolutionary cloud model. First, the framework of N-populations distributed coevolutionary MapReduce model is designed to divide the entire population into N subpopulations, sharing the reward of different subpopulations' solutions under a MapReduce cloud mechanism. Because the adaptive balancing between exploration and exploitation can be achieved in a better way, the reduction performance is guaranteed to be the same as those using the whole independent data set. Second, a novel Nash equilibrium dominance strategy of elitists under the N bounded rationality regions is adopted to assist the subpopulations necessary to attain the stable status of Nash equilibrium dominance. This further enhances the accelerator's robustness against complex noise on big data. Third, the approximation parallelism mechanism based on MapReduce is constructed to implement rule reduction by accelerating the computation of attribute equivalence classes. Consequently, the entire attribute reduction set with the equilibrium dominance solution can be achieved. Extensive simulation results have been used to illustrate the effectiveness and robustness of the proposed DCCAEDR accelerator for attribute reduction on big data. Furthermore, the DCCAEDR is applied to solve attribute reduction for traditional Chinese medical records and to segment cortical surfaces of the neonatal brain 3-D-MRI records, and the DCCAEDR shows the superior competitive results, when compared with the representative algorithms

    香港GPS基准站坐标序列特征分析

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    Author name used in this publication: 丁晓利, DING Xiao-liAuthor name used in this publication: 陈武Author name used in this publication: 陈少彬Author name used in this publication: 周锦添Title in Traditional Chinese: 香港GPS基準站座標序列特徵分析Journal title in Traditional Chinese: 地球物理學報2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

    Spatio-Temporal Characteristics of Global Warming in the Tibetan Plateau during the Last 50 Years Based on a Generalised Temperature Zone - Elevation Model

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    Temperature is one of the primary factors influencing the climate and ecosystem, and examining its change and fluctuation could elucidate the formation of novel climate patterns and trends. In this study, we constructed a generalised temperature zone elevation model (GTEM) to assess the trends of climate change and temporal-spatial differences in the Tibetan Plateau (TP) using the annual and monthly mean temperatures from 1961-2010 at 144 meteorological stations in and near the TP. The results showed the following: (1) The TP has undergone robust warming over the study period, and the warming rate was 0.318°C/decade. The warming has accelerated during recent decades, especially in the last 20 years, and the warming has been most significant in the winter months, followed by the spring, autumn and summer seasons. (2) Spatially, the zones that became significantly smaller were the temperature zones of -6°C and -4°C, and these have decreased 499.44 and 454.26 thousand sq km from 1961 to 2010 at average rates of 25.1% and 11.7%, respectively, over every 5-year interval. These quickly shrinking zones were located in the northwestern and central TP. (3) The elevation dependency of climate warming existed in the TP during 1961-2010, but this tendency has gradually been weakening due to more rapid warming at lower elevations than in the middle and upper elevations of the TP during 1991-2010. The higher regions and some low altitude valleys of the TP were the most significantly warming regions under the same categorizing criteria. Experimental evidence shows that the GTEM is an effective method to analyse climate changes in high altitude mountainous regions

    Decitabine impact on the endocytosis regulator RhoA, the folate carriers RFC1 and FOLR1, and the glucose transporter GLUT4 in human tumors.

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    BackgroundIn 31 solid tumor patients treated with the demethylating agent decitabine, we performed tumor biopsies before and after the first cycle of decitabine and used immunohistochemistry (IHC) to assess whether decitabine increased expression of various membrane transporters. Resistance to chemotherapy may arise due to promoter methylation/downregulation of expression of transporters required for drug uptake, and decitabine can reverse resistance in vitro. The endocytosis regulator RhoA, the folate carriers FOLR1 and RFC1, and the glucose transporter GLUT4 were assessed.ResultsPre-decitabine RhoA was higher in patients who had received their last therapy >3 months previously than in patients with more recent prior therapy (P = 0.02), and varied inversely with global DNA methylation as assessed by LINE1 methylation (r = -0.58, P = 0.006). Tumor RhoA scores increased with decitabine (P = 0.03), and RFC1 also increased in patients with pre-decitabine scores ≤150 (P = 0.004). Change in LINE1 methylation with decitabine did not correlate significantly with change in IHC scores for any transporter assessed. We also assessed methylation of the RFC1 gene (alias SLC19A1). SLC19A1 methylation correlated with tumor LINE1 methylation (r = 0.45, P = 0.02). There was a small (statistically insignificant) decrease in SLC19A1 methylation with decitabine, and there was a trend towards change in SLC19A1 methylation with decitabine correlating with change in LINE1 methylation (r = 0.47, P <0.15). While SLC19A1 methylation did not correlate with RFC1 scores, there was a trend towards an inverse correlation between change in SLC19A1 methylation and change in RFC1 expression (r = -0.45, P = 0.19).ConclusionsIn conclusion, after decitabine administration, there was increased expression of some (but not other) transporters that may play a role in chemotherapy uptake. Larger patient numbers will be needed to define the extent to which this increased expression is associated with changes in DNA methylation

    Strong signature of natural selection within an FHIT intron implicated in prostate cancer risk

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    Previously, a candidate gene linkage approach on brother pairs affected with prostate cancer identified a locus of prostate cancer susceptibility at D3S1234 within the fragile histidine triad gene (FHIT), a tumor suppressor that induces apoptosis. Subsequent association tests on 16 SNPs spanning approximately 381 kb surrounding D3S1234 in Americans of European descent revealed significant evidence of association for a single SNP within intron 5 of FHIT. In the current study, resequencing and genotyping within a 28.5 kb region surrounding this SNP further delineated the association with prostate cancer risk to a 15 kb region. Multiple SNPs in sequences under evolutionary constraint within intron 5 of FHIT defined several related haplotypes with an increased risk of prostate cancer in European-Americans. Strong associations were detected for a risk haplotype defined by SNPs 138543, 142413, and 152494 in all cases (Pearson's χ2 = 12.34, df 1, P = 0.00045) and for the homozygous risk haplotype defined by SNPs 144716, 142413, and 148444 in cases that shared 2 alleles identical by descent with their affected brothers (Pearson's χ2 = 11.50, df 1, P = 0.00070). In addition to highly conserved sequences encompassing SNPs 148444 and 152413, population studies revealed strong signatures of natural selection for a 1 kb window covering the SNP 144716 in two human populations, the European American (π = 0.0072, Tajima's D= 3.31, 14 SNPs) and the Japanese (π = 0.0049, Fay & Wu's H = 8.05, 14 SNPs), as well as in chimpanzees (Fay & Wu's H = 8.62, 12 SNPs). These results strongly support the involvement of the FHIT intronic region in an increased risk of prostate cancer. © 2008 Ding et al

    A Didactic Model of Macromolecular Crowding Effects on Protein Folding

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    A didactic model is presented to illustrate how the effect of macromolecular crowding on protein folding and association is modeled using current analytical theory and discrete molecular dynamics. While analytical treatments of crowding may consider the effect as a potential of average force acting to compress a polypeptide chain into a compact state, the use of simulations enables the presence of crowding reagents to be treated explicitly. Using an analytically solvable toy model for protein folding, an approximate statistical thermodynamic method is directly compared to simulation in order to gauge the effectiveness of current analytical crowding descriptions. Both methodologies are in quantitative agreement under most conditions, indication that both current theory and simulation methods are capable of recapitulating aspects of protein folding even by utilizing a simplistic protein model

    Pt-decorated nanoporous gold for glucose electrooxidation in neutral and alkaline solutions

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    Exploiting electrocatalysts with high activity for glucose oxidation is of central importance for practical applications such as glucose fuel cell. Pt-decorated nanoporous gold (NPG-Pt), created by depositing a thin layer of Pt on NPG surface, was proposed as an active electrode for glucose electrooxidation in neutral and alkaline solutions. The structure and surface properties of NPG-Pt were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray powder diffraction (XRD), and cyclic voltammetry (CV). The electrocatalytic activity toward glucose oxidation in neutral and alkaline solutions was evaluated, which was found to depend strongly on the surface structure of NPG-Pt. A direct glucose fuel cell (DGFC) was performed based on the novel membrane electrode materials. With a low precious metal load of less than 0.3 mg cm-2 Au and 60 μg cm-2 Pt in anode and commercial Pt/C in cathode, the performance of DGFC in alkaline is much better than that in neutral condition

    The Interplay Between GUT and Flavour Symmetries in a Pati-Salam x S4 Model

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    Both Grand Unified symmetries and discrete flavour symmetries are appealing ways to describe apparent structures in the gauge and flavour sectors of the Standard Model. Both symmetries put constraints on the high energy behaviour of the theory. This can give rise to unexpected interplay when building models that possess both symmetries. We investigate on the possibility to combine a Pati-Salam model with the discrete flavour symmetry S4S_4 that gives rise to quark-lepton complementarity. Under appropriate assumptions at the GUT scale, the model reproduces fermion masses and mixings both in the quark and in the lepton sectors. We show that in particular the Higgs sector and the running Yukawa couplings are strongly affected by the combined constraints of the Grand Unified and family symmetries. This in turn reduces the phenomenologically viable parameter space, with high energy mass scales confined to a small region and some parameters in the neutrino sector slightly unnatural. In the allowed regions, we can reproduce the quark masses and the CKM matrix. In the lepton sector, we reproduce the charged lepton masses, including bottom-tau unification and the Georgi-Jarlskog relation as well as the two known angles of the PMNS matrix. The neutrino mass spectrum can present a normal or an inverse hierarchy, and only allowing the neutrino parameters to spread into a range of values between λ2\lambda^{-2} and λ2\lambda^2, with λ0.2\lambda\simeq0.2. Finally, our model suggests that the reactor mixing angle is close to its current experimental bound.Comment: 62 pages, 4 figures; references added, version accepted for publication in JHE

    Integration of decision support systems to improve decision support performance

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    Decision support system (DSS) is a well-established research and development area. Traditional isolated, stand-alone DSS has been recently facing new challenges. In order to improve the performance of DSS to meet the challenges, research has been actively carried out to develop integrated decision support systems (IDSS). This paper reviews the current research efforts with regard to the development of IDSS. The focus of the paper is on the integration aspect for IDSS through multiple perspectives, and the technologies that support this integration. More than 100 papers and software systems are discussed. Current research efforts and the development status of IDSS are explained, compared and classified. In addition, future trends and challenges in integration are outlined. The paper concludes that by addressing integration, better support will be provided to decision makers, with the expectation of both better decisions and improved decision making processes
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