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We report the first measurement of inclusive antiproton production at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV by the STAR experiment at RHIC. The antiproton transverse mass distributions in the measured transverse momentum range of 0.25<pperp<0.95 GeV/c are found to fall less steeply for more central collisions. The extrapolated antiproton rapidity density is found to scale approximately with the negative hadron multiplicity density.
The first measurements of light antinucleus production in Au+Au collisions at the Relativistic Heavy-Ion Collider are reported. The observed production rates for d-bar and 3He-bar are much larger than in lower energy nucleus-nucleus collisions. A coalescence model analysis of the yields indicates that there is little or no increase in the antinucleon freeze-out volume compared to collisions at CERN SPS energy. These analyses also indicate that the 3He-bar freeze-out volume is smaller than the d-bar freeze-out volume.
We present the first measurement of midrapidity vector meson phi production in Au+Au collisions at RHIC (sqrt[sNN]=130 GeV) from the STAR detector. For the 11% highest multiplicity collisions, the slope parameter from an exponential fit to the transverse mass distribution is T=379±50(stat)±45(syst) MeV, the yield dN/dy=5.73±0.37(stat)±0.69(syst) per event, and the ratio N phi /Nh- is found to be 0.021±0.001(stat)±0.004(syst). The measured ratio N phi /Nh- and T for the phi meson at midrapidity do not change for the selected multiplicity bins.
We report results on the ratio of midrapidity antiproton-to-proton yields in Au+Au collisions at sqrt[sNN] = 130 GeV per nucleon pair as measured by the STAR experiment at RHIC. Within the rapidity and transverse momentum range of | y|<0.5 and 0.4<pt<1.0 GeV/c, the ratio is essentially independent of either transverse momentum or rapidity, with an average of 0.65±0.01(stat)±0.07(syst) for minimum bias collisions. Within errors, no strong centrality dependence is observed. The results indicate that at this RHIC energy, although the p-p-bar pair production becomes important at midrapidity, a significant excess of baryons over antibaryons is still present.
Abstract Geant4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics. PACS: 07.05.Tp; 13; 23
Bipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the Xchromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p = 5.87×10-9; odds ratio = 1.12) and markers within ERBB2 (rs2517959, p = 4.53×10-9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.
The goal of our current project is to build a system that can learn to imitate a version of a spoken utterance using an articulatory speech synthesiser. The approach is informed and inspired by knowledge of early infant speech development. Thus we expect our system to reproduce and exploit the utility of infant behaviours such as listening, vocal play, babbling and word imitation. We expect our system to develop a relationship between the sound-making capabilities of its vocal tract and the phonetic/phonological structure of imitated utterances. At the heart of our approach is the learning of an inverse model that relates acoustic and motor representations of speech. The acoustic to auditory mappings uses an auditory filter bank and a self-organizing phase of learning. The inverse model from auditory to vocal tract control parameters is estimated using a babbling phase, in which the vocal tract is essentially driven in a random manner, much like the babbling phase of speech acquisition in infants. The complete system can be used to imitate simple utterances through a direct mapping from sound to control parameters. Our initial results show that this procedure works well for sounds generated by its own voice. Further work is needed to build a phonological control level and achieve better performance with real speech.
Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).
A data-driven method was applied to Au+Au collisions at √sNN = 200 GeV made with the STAR detector at RHIC to isolate pseudorapidity distance η-dependent and η-independent correlations by using two- and four-particle azimuthal cumulant measurements. We identified a η-independent component of the correlation, which is dominated by anisotropic flow and flow fluctuations. It was also found to be independent of η within the measured range of pseudorapidity |η| < 1. In 20–30% central Au+Au collisions, the relative flow fluctuation was found to be 34%±2%(stat.)±3%(sys.) for particles with transverse momentum pT less than 2 GeV/c. The η-dependent part, attributed to nonflow correlations, is found to be 5% ± 2%(sys.) relative to the flow of the measured second harmonic cumulant at |η| > 0.7.