Pair production of 125 GeV Higgs boson in the SM extension with color-octet scalars at the LHC

Although the Higgs boson mass and single production rate have been determined more or less precisely, its other properties may deviate significantly from its predictions in the standard model (SM) due to the uncertainty of Higgs data. In this work we study the Higgs pair production at the LHC in the Manohar-Wise model, which extends the SM by one family of color-octet and isospin-doublet scalars. We first scanned over the parameter space of the Manohar-Wise model considering exprimental constraints and performed fits in the model to the latest Higgs data by using the ATLAS and CMS data separately. Then we calculated the Higgs pair production rate and investigated the potential of its discovery at the LHC14. We conclude that: (i) Under current constrains including Higgs data after Run I of the LHC, the cross section of Higgs pair production in the Manohar-Wise model can be enhanced up to even $10^3$ times prediction in the SM. (ii) Moreover, the sizable enhancement comes from the contributions of the CP-odd color-octet scalar $S^A_I$. For lighter scalar $S^A_I$ and larger values of $|\lambda_I|$, the cross section of Higgs pair production can be much larger. (iii) After running again of LHC at 14 TeV, most of the parameter spaces in the Manohar-Wise model can be test. For an integrated luminosity of 100 fb$^{-1}$ at the LHC14, when the normalized ratio $R=10$, the process of Higgs pair production can be detected.Comment: 13 pages, 4 figure

OGS : a lightweight object-oriented graphics system for instruction

Existing graphics systems are too large for students to study in an introductory computer graphics course. We have implemented a lightweight, object-oriented graphics system called OGS for instruction. OGS is written in Java. It demonstrates how a graphics system is implemented from scratch and is intended to help students understand graphics algorithms at the source code level. OGS im­plements window-viewport coordinate transformation, projection, 3D transformation, hidden surface elimination, Lambert shading, Phong hading, Constructive Solid Geometry, and ray tracing. OGS is able to model specular highlight, shadow, reflection and transmission.Keywords and Phases: OGS, computer graphics, polygon mesh, ray tracin

Room-Temperature Structures of Solid Hydrogen at High Pressures

By employing first-principles metadynamics simulations, we explore the 300 K structures of solid hydrogen over the pressure range 150-300 GPa. At 200 GPa, we find the ambient-pressure disordered hexagonal close-packed (hcp) phase transited into an insulating partially ordered hcp phase (po-hcp), a mixture of ordered graphene-like H2 layers and the other layers of weakly coupled, disordered H2 molecules. Within this phase, hydrogen remains in paired states with creation of shorter intra-molecular bonds, which are responsible for the very high experimental Raman peak above 4000 cm-1. At 275 GPa, our simulations predicted a transformation from po-hcp into the ordered molecular metallic Cmca phase (4 molecules/cell) that was previously proposed to be stable only above 400 GPa. Gibbs free energy calculations at 300 K confirmed the energetic stabilities of the po-hcp and metallic Cmca phases over all known structures at 220-242 GPa and >242 GPa, respectively. Our simulations highlighted the major role played by temperature in tuning the phase stabilities and provided theoretical support for claimed metallization of solid hydrogen below 300 GPa at 300 K.Comment: Accepted in Journal of Chemical Physic

Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks

<p>Abstract</p> <p>Background</p> <p>Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are used to discretize microarray data. Selection of the discretization method is often arbitrary and no systematic comparison of different discretization has been conducted, in the context of gene regulatory network inference from time series gene expression data.</p> <p>Results</p> <p>In this study, we propose a new discretization method "bikmeans", and compare its performance with four other widely-used discretization methods using different datasets, modeling algorithms and number of intervals. Sensitivities, specificities and total accuracies were calculated and statistical analysis was carried out. Bikmeans method always gave high total accuracies.</p> <p>Conclusions</p> <p>Our results indicate that proper discretization methods can consistently improve gene regulatory network inference independent of network modeling algorithms and datasets. Our new method, bikmeans, resulted in significant better total accuracies than other methods.</p

Synthesis of x

The xLiMnPO4·yLi3V2(PO4)3/C (x/y = 1 : 0, 12 : 1, 8 : 1, 6 : 1, 4 : 1, 0 : 1) composite cathode materials are synthesized using tributyl phosphate as a novel organic phosphor source via a solid-state reaction process. All obtained xLiMnPO4·yLi3V2(PO4)3/C composites present similar particles morphology with an average size of ca. 100 nm and low extent agglomeration. The electrochemical performance of pristine LiMnPO4/C can be effectively improved by adding small amounts of Li3V2(PO4)3 additives. The 4LiMnPO4·Li3V2(PO4)3/C has a high discharge capacity of 143 mAh g−1 at 0.1 C and keeps its 94% at the end of 100 cycles

GsAPK, an ABA-Activated and Calcium-Independent SnRK2-Type Kinase from G. soja, Mediates the Regulation of Plant Tolerance to Salinity and ABA Stress

Plant Snf1 (sucrose non-fermenting-1) related protein kinase (SnRK), a subfamily of serine/threonine kinases, has been implicated as a crucial upstream regulator of ABA and osmotic signaling as in many other signaling cascades. In this paper, we have isolated a novel plant specific ABA activated calcium independent protein kinase (GsAPK) from a highly salt tolerant plant, Glycine soja (50109), which is a member of the SnRK2 family. Subcellular localization studies using GFP fusion protein indicated that GsAPK is localized in the plasma membrane. We found that autophosphorylation and Myelin Basis Protein phosphorylation activity of GsAPK is only activated by ABA and the kinase activity also was observed when calcium was replaced by EGTA, suggesting its independence of calcium in enzyme activity. We also found that cold, salinity, drought, and ABA stress alter GsAPK gene transcripts and heterogonous overexpression of GsAPK in Arabidopsis alters plant tolerance to high salinity and ABA stress. In summary, we demonstrated that GsAPK is a Glycine soja ABA activated calcium independent SnRK-type kinase presumably involved in ABA mediated stress signal transduction

A novel method for inference of acyclic chemical compounds with bounded branch-height based on artificial neural networks and integer programming

Analysis of chemical graphs is becoming a major research topic in computational molecular biology due to its potential applications to drug design. One of the major approaches in such a study is inverse quantitative structure activity/property relationship (inverse QSAR/QSPR) analysis, which is to infer chemical structures from given chemical activities/properties. Recently, a novel two-phase framework has been proposed for inverse QSAR/QSPR, where in the first phase an artificial neural network (ANN) is used to construct a prediction function. In the second phase, a mixed integer linear program (MILP) formulated on the trained ANN and a graph search algorithm are used to infer desired chemical structures. The framework has been applied to the case of chemical compounds with cycle index up to 2 so far. The computational results conducted on instances with n non-hydrogen atoms show that a feature vector can be inferred by solving an MILP for up to n=40, whereas graphs can be enumerated for up to n=15. When applied to the case of chemical acyclic graphs, the maximum computable diameter of a chemical structure was up to 8. In this paper, we introduce a new characterization of graph structure, called “branch-height” based on which a new MILP formulation and a new graph search algorithm are designed for chemical acyclic graphs. The results of computational experiments using such chemical properties as octanol/water partition coefficient, boiling point and heat of combustion suggest that the proposed method can infer chemical acyclic graphs with around n=50 and diameter 30