Doping change and distortion effect on double-exchange ferromagnetism

Doping change and distortion effect on the double-exchange ferromagnetism are studied within a simplified double-exchange model. The presence of distortion is modelled by introducing the Falicov-Kimball interaction between itinerant electrons and classical variables. By employing the dynamical mean-field theory the charge and spin susceptibility are exactly calculated. It is found that there is a competition between the double-exchange induced ferromagnetism and disorder-order transition. At low temperature various long-range order phases such as charge ordered and segregated phases coexist with ferromagnetism depending on doping and distortion. A rich phase diagram is obtained.Comment: 8 pages, 8 figure

The Vietnamese shrimp trade: livelihoods analysis of stakeholders and market chain analysis

Aquaculture and capture fisheries in Vietnam have been increasing fast in the last decade, especially aquaculture growth rate is 12% for the 1999 – 2003 period, contributing a significant part into the hunger eradication and poverty reduction1. Vietnam is to be ranked into one of the countries potential to produce the aquatic economic in the world, and the fact is that, after 40 years of establishing, the fisheries sector has made remarkable contributions to the country. By the list, at the moment the aquatic products make up about 4 - 5% of GDP and create job opportunities for over 3 three million employees (VASEP, 2004), in which the largest contribution is from shrimp farming. [PDF contains 124 pages.

Probabilistic Random Walk Models for Comparative Network Analysis

Graph-based systems and data analysis methods have become critical tools in many fields as they can provide an intuitive way of representing and analyzing interactions between variables. Due to the advances in measurement techniques, a massive amount of labeled data that can be represented as nodes on a graph (or network) have been archived in databases. Additionally, novel data without label information have been gradually generated and archived. Labeling and identifying characteristics of novel data is an important first step in utilizing the valuable data in an effective and meaningful way. Comparative network analysis is an effective computational means to identify and predict the properties of the unlabeled data by comparing the similarities and differences between well-studied and less-studied networks. Comparative network analysis aims to identify the matching nodes and conserved subnetworks across multiple networks to enable a prediction of the properties of the nodes in the less-studied networks based on the properties of the matching nodes in the well-studied networks (i.e., transferring knowledge between networks). One of the fundamental and important questions in comparative network analysis is how to accurately estimate node-to-node correspondence as it can be a critical clue in analyzing the similarities and differences between networks. Node correspondence is a comprehensive similarity that integrates various types of similarity measurements in a balanced manner. However, there are several challenges in accurately estimating the node correspondence for large-scale networks. First, the scale of the networks is a critical issue. As networks generally include a large number of nodes, we have to examine an extremely large space and it can pose a computational challenge due to the combinatorial nature of the problem. Furthermore, although there are matching nodes and conserved subnetworks in different networks, structural variations such as node insertions and deletions make it difficult to integrate a topological similarity. In this dissertation, novel probabilistic random walk models are proposed to accurately estimate node-to-node correspondence between networks. First, we propose a context-sensitive random walk (CSRW) model. In the CSRW model, the random walker analyzes the context of the current position of the random walker and it can switch the random movement to either a simultaneous walk on both networks or an individual walk on one of the networks. The context-sensitive nature of the random walker enables the method to effectively integrate different types of similarities by dealing with structural variations. Second, we propose the CUFID (Comparative network analysis Using the steady-state network Flow to IDentify orthologous proteins) model. In the CUFID model, we construct an integrated network by inserting pseudo edges between potential matching nodes in different networks. Then, we design the random walk protocol to transit more frequently between potential matching nodes as their node similarity increases and they have more matching neighboring nodes. We apply the proposed random walk models to comparative network analysis problems: global network alignment and network querying. Through extensive performance evaluations, we demonstrate that the proposed random walk models can accurately estimate node correspondence and these can lead to improved and reliable network comparison results

Gene expression and splicing alterations analyzed by high throughput RNA sequencing of chronic lymphocytic leukemia specimens.

BackgroundTo determine differentially expressed and spliced RNA transcripts in chronic lymphocytic leukemia specimens a high throughput RNA-sequencing (HTS RNA-seq) analysis was performed.MethodsTen CLL specimens and five normal peripheral blood CD19+ B cells were analyzed by HTS RNA-seq. The library preparation was performed with Illumina TrueSeq RNA kit and analyzed by Illumina HiSeq 2000 sequencing system.ResultsAn average of 48.5 million reads for B cells, and 50.6 million reads for CLL specimens were obtained with 10396 and 10448 assembled transcripts for normal B cells and primary CLL specimens respectively. With the Cuffdiff analysis, 2091 differentially expressed genes (DEG) between B cells and CLL specimens based on FPKM (fragments per kilobase of transcript per million reads and false discovery rate, FDR q < 0.05, fold change >2) were identified. Expression of selected DEGs (n = 32) with up regulated and down regulated expression in CLL from RNA-seq data were also analyzed by qRT-PCR in a test cohort of CLL specimens. Even though there was a variation in fold expression of DEG genes between RNA-seq and qRT-PCR; more than 90 % of analyzed genes were validated by qRT-PCR analysis. Analysis of RNA-seq data for splicing alterations in CLL and B cells was performed by Multivariate Analysis of Transcript Splicing (MATS analysis). Skipped exon was the most frequent splicing alteration in CLL specimens with 128 significant events (P-value <0.05, minimum inclusion level difference >0.1).ConclusionThe RNA-seq analysis of CLL specimens identifies novel DEG and alternatively spliced genes that are potential prognostic markers and therapeutic targets. High level of validation by qRT-PCR for a number of DEG genes supports the accuracy of this analysis. Global comparison of transcriptomes of B cells, IGVH non-mutated CLL (U-CLL) and mutated CLL specimens (M-CLL) with multidimensional scaling analysis was able to segregate CLL and B cell transcriptomes but the M-CLL and U-CLL transcriptomes were indistinguishable. The analysis of HTS RNA-seq data to identify alternative splicing events and other genetic abnormalities specific to CLL is an added advantage of RNA-seq that is not feasible with other genome wide analysis

Measurement of the CKM angle γ from a combination of B±→Dh± analyses

A combination of three LHCb measurements of the CKM angle γ is presented. The decays B±→D K± and B±→Dπ± are used, where D denotes an admixture of D0 and D0 mesons, decaying into K+K−, π+π−, K±π∓, K±π∓π±π∓, K0Sπ+π−, or K0S K+K− final states. All measurements use a dataset corresponding to 1.0 fb−1 of integrated luminosity. Combining results from B±→D K± decays alone a best-fit value of γ =72.0◦ is found, and confidence intervals are set γ ∈ [56.4,86.7]◦ at 68% CL, γ ∈ [42.6,99.6]◦ at 95% CL. The best-fit value of γ found from a combination of results from B±→Dπ± decays alone, is γ =18.9◦, and the confidence intervals γ ∈ [7.4,99.2]◦ ∪ [167.9,176.4]◦ at 68% CL are set, without constraint at 95% CL. The combination of results from B± → D K± and B± → Dπ± decays gives a best-fit value of γ =72.6◦ and the confidence intervals γ ∈ [55.4,82.3]◦ at 68% CL, γ ∈ [40.2,92.7]◦ at 95% CL are set. All values are expressed modulo 180◦, and are obtained taking into account the effect of D0–D0 mixing

Measurement of the ratio of branching fractions BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma)

The ratio of branching fractions of the radiative B decays B0 -> K*0 gamma and Bs0 -> phi gamma has been measured using 0.37 fb-1 of pp collisions at a centre of mass energy of sqrt(s) = 7 TeV, collected by the LHCb experiment. The value obtained is BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma) = 1.12 +/- 0.08 ^{+0.06}_{-0.04} ^{+0.09}_{-0.08}, where the first uncertainty is statistical, the second systematic and the third is associated to the ratio of fragmentation fractions fs/fd. Using the world average for BR(B0 -> K*0 gamma) = (4.33 +/- 0.15) x 10^{-5}, the branching fraction BR(Bs0 -> phi gamma) is measured to be (3.9 +/- 0.5) x 10^{-5}, which is the most precise measurement to date.Comment: 15 pages, 1 figure, 2 table

Differential branching fraction and angular analysis of the decay B0→K∗0μ+μ−

The angular distribution and differential branching fraction of the decay B 0→ K ∗0 μ + μ − are studied using a data sample, collected by the LHCb experiment in pp collisions at s√=7 TeV, corresponding to an integrated luminosity of 1.0 fb−1. Several angular observables are measured in bins of the dimuon invariant mass squared, q 2. A first measurement of the zero-crossing point of the forward-backward asymmetry of the dimuon system is also presented. The zero-crossing point is measured to be q20=4.9±0.9GeV2/c4 , where the uncertainty is the sum of statistical and systematic uncertainties. The results are consistent with the Standard Model predictions

Measurements of the branching fractions of B+→ppK+ decays

The branching fractions of the decay B+ → pp̄K+ for different intermediate states are measured using data, corresponding to an integrated luminosity of 1.0 fb-1, collected by the LHCb experiment. The total branching fraction, its charmless component Mpp̄ < 2.85 GeV/c2 and the branching fractions via the resonant cc̄ states η c(1S) and ψ(2S) relative to the decay via a J/ψ intermediate state are [Equation not available: see fulltext.] Upper limits on the B + branching fractions into the η c(2S) meson and into the charmonium-like states X(3872) and X(3915) are also obtained

Search for the decay Bs0→D*∓π±

A search for the decay Bs0→D*∓π± is presented using a data sample corresponding to an integrated luminosity of 1.0  fb-1 of pp collisions collected by LHCb. This decay is expected to be mediated by a W-exchange diagram, with little contribution from rescattering processes, and therefore a measurement of the branching fraction will help us to understand the mechanism behind related decays such as Bs0→π+π- and Bs0→DD- . Systematic uncertainties are minimized by using B0→D*∓π± as a normalization channel. We find no evidence for a signal, and set an upper limit on the branching fraction of B(Bs0→D*∓π±)<6.1(7.8)×10-6 at 90% (95%) confidence level

Measurement of the relative rate of prompt χc0, χc1 and χc2 production at √s=7TeV

Prompt production of charmonium χc0, χc1 and χc2 mesons is studied using proton-proton collisions at the LHC at a centre-of-mass energy of √s=7TeV. The χc mesons are identified through their decay to J/ψγ, with J/ψ→μ+mu− using photons that converted in the detector. A data sample, corresponding to an integrated luminosity of 1.0fb−1 collected by the LHCb detector, is used to measure the relative prompt production rate of χc1 and χc2 in the rapidity range 2.0<y<4.5 as a function of the J/ψ transverse momentum from 3 to 20 GeV/c. First evidence for χc0 meson production at a hadron collider is also presented