Azimuthal anisotropy and correlations at large transverse momenta in p+pp+p and Au+Au collisions at sNN\sqrt{s_{_{NN}}}= 200 GeV

Results on high transverse momentum charged particle emission with respect to the reaction plane are presented for Au+Au collisions at $\sqrt{s_{_{NN}}}$= 200 GeV. Two- and four-particle correlations results are presented as well as a comparison of azimuthal correlations in Au+Au collisions to those in $p+p$ at the same energy. Elliptic anisotropy, $v_2$, is found to reach its maximum at $p_t \sim 3$ GeV/c, then decrease slowly and remain significant up to $p_t\approx 7$ -- 10 GeV/c. Stronger suppression is found in the back-to-back high-$p_t$ particle correlations for particles emitted out-of-plane compared to those emitted in-plane. The centrality dependence of $v_2$ at intermediate $p_t$ is compared to simple models based on jet quenching.Comment: 4 figures. Published version as PRL 93, 252301 (2004

Azimuthal anisotropy in Au+Au collisions at sqrtsNN = 200 GeV

The results from the STAR Collaboration on directed flow (v_1), elliptic flow (v_2), and the fourth harmonic (v_4) in the anisotropic azimuthal distribution of particles from Au+Au collisions at sqrtsNN = 200 GeV are summarized and compared with results from other experiments and theoretical models. Results for identified particles are presented and fit with a Blast Wave model. Different anisotropic flow analysis methods are compared and nonflow effects are extracted from the data. For v_2, scaling with the number of constituent quarks and parton coalescence is discussed. For v_4, scaling with v_2^2 and quark coalescence is discussed.Comment: 26 pages. As accepted by Phys. Rev. C. Text rearranged, figures modified, but data the same. However, in Fig. 35 the hydro calculations are corrected in this version. The data tables are available at http://www.star.bnl.gov/central/publications/ by searching for "flow" and then this pape

Large-scale and rapid synthesis of disk-shaped and nano-sized graphene

We synthesized disk-shaped and nano-sized graphene (DSNG) though a novel ion-exchange methodology. This new methodology is achieved by constructing metal ion/ion-exchange resin framework. The morphology and size of the graphene can be modulated by changing the mass ratio of the carbon-containing resin to the cobalt-containing precursor. This is the first time to show that the DSNG formed on the granular transition metal substrate. The DSNG gives a high intensity of photoluminescence at near-UV wavelength of 311 nm which may provide a new type of fluorescence for applications in laser devices, ultraviolet detector UV-shielding agent and energy technology. The emission intensity of the DSNG is thirty times higher than that of the commercial large graphene. Our approach for graphene growth is conveniently controllable, easy to scale-up and the DSNG shows superior luminescent properties as compared to conventional large graphene

Regulation of N-WASP and the Arp2/3 Complex by Abp1 Controls Neuronal Morphology

Polymerization and organization of actin filaments into complex superstructures is indispensable for structure and function of neuronal networks. We here report that knock down of the F-actin-binding protein Abp1, which is important for endocytosis and synaptic organization, results in changes in axon development virtually identical to Arp2/3 complex inhibition, i.e., a selective increase of axon length. Our in vitro and in vivo experiments demonstrate that Abp1 interacts directly with N-WASP, an activator of the Arp2/3 complex, and releases the autoinhibition of N-WASP in cooperation with Cdc42 and thereby promotes N-WASP-triggered Arp2/3 complex-mediated actin polymerization. In line with our mechanistical studies and the colocalization of Abp1, N-WASP and Arp2/3 at sites of actin polymerization in neurons, we reveal an essential role of Abp1 and its cooperativity with Cdc42 in N-WASP-induced rearrangements of the neuronal cytoskeleton. We furthermore show that introduction of N-WASP mutants lacking the ability to bind Abp1 or Cdc42, Arp2/3 complex inhibition, Abp1 knock down, N-WASP knock down and Arp3 knock down, all cause identical neuromorphological phenotypes. Our data thus strongly suggest that these proteins and their complex formation are important for cytoskeletal processes underlying neuronal network formation

Holocene dynamics of the Southern Hemisphere westerly winds and possible links to CO2 outgassing

The Southern Hemisphere westerly winds (SHW) play an important role in regulating the capacity of the Southern Ocean carbon sink. They modulate upwelling of carbon-rich deep water and, with sea ice, determine the ocean surface area available for air–sea gas exchange. Some models indicate that the current strengthening and poleward shift of these winds will weaken the carbon sink. If correct, centennial- to millennial-scale reconstructions of the SHW intensity should be linked with past changes in atmospheric CO2, temperature and sea ice. Here we present a 12,300-year reconstruction of wind strength based on three independent proxies that track inputs of sea-salt aerosols and minerogenic particles accumulating in lake sediments on sub-Antarctic Macquarie Island. Between about 12.1 thousand years ago (ka) and 11.2 ka, and since about 7 ka, the wind intensities were above their long-term mean and corresponded with increasing atmospheric CO2. Conversely, from about 11.2 to 7.2 ka, the wind intensities were below their long-term mean and corresponded with decreasing atmospheric CO2. These observations are consistent with model inferences of enhanced SHW contributing to the long-term outgassing of CO2 from the Southern Ocean

Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting

<p>Abstract</p> <p>Background</p> <p>The World Health Organisation estimates that by 2030 there will be approximately 350 million people with type 2 diabetes. Associated with renal complications, heart disease, stroke and peripheral vascular disease, early identification of patients with undiagnosed type 2 diabetes or those at an increased risk of developing type 2 diabetes is an important challenge. We sought to systematically review and critically assess the conduct and reporting of methods used to develop risk prediction models for predicting the risk of having undiagnosed (prevalent) or future risk of developing (incident) type 2 diabetes in adults.</p> <p>Methods</p> <p>We conducted a systematic search of PubMed and EMBASE databases to identify studies published before May 2011 that describe the development of models combining two or more variables to predict the risk of prevalent or incident type 2 diabetes. We extracted key information that describes aspects of developing a prediction model including study design, sample size and number of events, outcome definition, risk predictor selection and coding, missing data, model-building strategies and aspects of performance.</p> <p>Results</p> <p>Thirty-nine studies comprising 43 risk prediction models were included. Seventeen studies (44%) reported the development of models to predict incident type 2 diabetes, whilst 15 studies (38%) described the derivation of models to predict prevalent type 2 diabetes. In nine studies (23%), the number of events per variable was less than ten, whilst in fourteen studies there was insufficient information reported for this measure to be calculated. The number of candidate risk predictors ranged from four to sixty-four, and in seven studies it was unclear how many risk predictors were considered. A method, not recommended to select risk predictors for inclusion in the multivariate model, using statistical significance from univariate screening was carried out in eight studies (21%), whilst the selection procedure was unclear in ten studies (26%). Twenty-one risk prediction models (49%) were developed by categorising all continuous risk predictors. The treatment and handling of missing data were not reported in 16 studies (41%).</p> <p>Conclusions</p> <p>We found widespread use of poor methods that could jeopardise model development, including univariate pre-screening of variables, categorisation of continuous risk predictors and poor handling of missing data. The use of poor methods affects the reliability of the prediction model and ultimately compromises the accuracy of the probability estimates of having undiagnosed type 2 diabetes or the predicted risk of developing type 2 diabetes. In addition, many studies were characterised by a generally poor level of reporting, with many key details to objectively judge the usefulness of the models often omitted.</p

CASTLEGUARD : anonymised data streams with guaranteed differential privacy

Data streams are commonly used by data controllers to outsource the processing of real-time data to third-party data processors. Data protection legislation and best practice in data management support the view that data controllers are responsible for providing a guarantee of privacy for user data contained within published data streams. Continuously Anonymising STreaming data via adaptive cLustEring (CASTLE) is an established method for anonymising data streams with a guarantee of k-anonymity. However, k-anonymity has been shown to be a weak privacy guarantee that has vulnerabilities in practical applications. In this paper we propose Continuously Anonymising STreaming data via adaptive cLustEring with GUAR-anteed Differential privacy (CASTLEGUARD), a data stream anonymisation algorithm that provides a reliable guarantee of k-anonymity, l-diversity and differential privacy to data subjects. We analyse CASTLEGUARD to show that, through safe k-anonymisation and β-sampling, the proposed approach satisfies differentially private k-anonymity. Further, we demonstrate the efficacy of the approach in the context of machine learning, presenting experimental analysis to demonstrate that it can be used to protect the individual privacy of users whilst maintaining the utility of a data stream