Streamlining Local-Let Federal-Aid Transportation Processes in Ohio

SJN 135519Ohio\u2019s local public agencies (LPAs) administer an average of $335 million of Federal-aid projects annually through the ODOT local-let program. ODOT has made significant strides to improve the efficiency of its Federal-aid program delivery process for LPA-administered projects in recent years. The objective of this research was to undertake a review of ODOT\u2019s local-let program requirements in the areas of real estate/right-of-way, construction contract administration, and finance to determine if any additional process streamlining could be achieved. This review found that a vast majority of activities LPAs are required to perform as part of Federal-aid project administration were consistent with applicable Federal requirements. Outreach to Ohio\u2019s LPAs and other State DOTs yielded valuable insight on best practices and potential strategies for streamlining the administration of Federal-aid projects by Ohio\u2019s LPAs at both the project and program level. Eight recommendations for streamlining are presented; implementation of these recommendations is expected to result in improvements to the delivery of ODOT\u2019s local-let program, including more efficient use of ODOT and LPA resources, cost and time savings for project delivery, and greater clarity on program performance

Upsilon (1S+2S+3S) production in d+Au and p+p collisions at sqrt(s_NN)=200 GeV and cold-nuclear matter effects

The three Upsilon states, Upsilon(1S+2S+3S), are measured in d+Au and p+p collisions at sqrt(s_NN)=200 GeV and rapidities 1.2<|y|<2.2 by the PHENIX experiment at the Relativistic Heavy-Ion Collider. Cross sections for the inclusive Upsilon(1S+2S+3S) production are obtained. The inclusive yields per binary collision for d+Au collisions relative to those in p+p collisions (R_dAu) are found to be 0.62 +/- 0.26 (stat) +/- 0.13 (syst) in the gold-going direction and 0.91 +/- 0.33 (stat) +/- 0.16 (syst) in the deuteron-going direction. The measured results are compared to a nuclear-shadowing model, EPS09 [JHEP 04, 065 (2009)], combined with a final-state breakup cross section, sigma_br, and compared to lower energy p+A results. We also compare the results to the PHENIX J/psi results [Phys. Rev. Lett. 107, 142301 (2011)]. The rapidity dependence of the observed Upsilon suppression is consistent with lower energy p+A measurements.Comment: 495 authors, 11 pages, 9 figures, 5 tables. Submitted to Phys. Rev. C. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P &lt; 5 × 10(-8), in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms

Measurements of elliptic and triangular flow in high-multiplicity 3^{3}He++Au collisions at sNN=200\sqrt{s_{_{NN}}}=200 GeV

We present the first measurement of elliptic ($v_2$) and triangular ($v_3$) flow in high-multiplicity $^{3}$He$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV. Two-particle correlations, where the particles have a large separation in pseudorapidity, are compared in $^{3}$He$+$Au and in $p$$+$$p$ collisions and indicate that collective effects dominate the second and third Fourier components for the correlations observed in the $^{3}$He$+$Au system. The collective behavior is quantified in terms of elliptic $v_2$ and triangular $v_3$ anisotropy coefficients measured with respect to their corresponding event planes. The $v_2$ values are comparable to those previously measured in $d$$+$Au collisions at the same nucleon-nucleon center-of-mass energy. Comparison with various theoretical predictions are made, including to models where the hot spots created by the impact of the three $^{3}$He nucleons on the Au nucleus expand hydrodynamically to generate the triangular flow. The agreement of these models with data may indicate the formation of low-viscosity quark-gluon plasma even in these small collision systems.Comment: 630 authors, 9 pages, 4 figures, 2 tables. v2 is the version accepted for publication by Physical Review Letters. Plain text data tables for the points plotted in figures for this and previous PHENIX publications are (or will be) publicly available at http://www.phenix.bnl.gov/papers.htm

The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008

Genomic atlas of the human plasma proteome

Although plasma proteins have important roles in biological processes and are the direct targets of many drugs, the genetic factors that control inter-individual variation in plasma protein levels are not well understood. Here we characterize the genetic architecture of the human plasma proteome in healthy blood donors from the INTERVAL study. We identify 1,927 genetic associations with 1,478 proteins, a fourfold increase on existing knowledge, including trans associations for 1,104 proteins. To understand the consequences of perturbations in plasma protein levels, we apply an integrated approach that links genetic variation with biological pathway, disease, and drug databases. We show that protein quantitative trait loci overlap with gene expression quantitative trait loci, as well as with disease-associated loci, and find evidence that protein biomarkers have causal roles in disease using Mendelian randomization analysis. By linking genetic factors to diseases via specific proteins, our analyses highlight potential therapeutic targets, opportunities for matching existing drugs with new disease indications, and potential safety concerns for drugs under development