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The short-lived K(892)* resonance provides an efficient tool to probe properties of the hot and dense medium produced in relativistic heavy-ion collisions. We report measurements of K* in sqrt[sNN]=200GeV Au+Au and p+p collisions reconstructed via its hadronic decay channels K(892)*0-->K pi and K(892)*±-->K0S pi ± using the STAR detector at the Relativistic Heavy Ion Collider at Brookhaven National Laboratory. The K*0 mass has been studied as a function of pT in minimum bias p+p and central Au+Au collisions. The K*pT spectra for minimum bias p+p interactions and for Au+Au collisions in different centralities are presented. The K*/K yield ratios for all centralities in Au+Au collisions are found to be significantly lower than the ratio in minimum bias p+p collisions, indicating the importance of hadronic interactions between chemical and kinetic freeze-outs. A significant nonzero K*0 elliptic flow (v2) is observed in Au+Au collisions and is compared to the K0S and Lambda v2. The nuclear modification factor of K* at intermediate pT is similar to that of K0S but different from Lambda . This establishes a baryon-meson effect over a mass effect in the particle production at intermediate pT (2<pT <= 4GeV/c).
Midrapidity open charm spectra from direct reconstruction of D0(D0-bar)-->K± pi ± in d+Au collisions and indirect electron-positron measurements via charm semileptonic decays in p+p and d+Au collisions at sqrt[sNN]=200 GeV are reported. The D0(D0-bar) spectrum covers a transverse momentum (pT) range of 0.1<pT<3 GeV/c, whereas the electron spectra cover a range of 1<pT<4 GeV/c. The electron spectra show approximate binary collision scaling between p+p and d+Au collisions. From these two independent analyses, the differential cross section per nucleon-nucleon binary interaction at midrapidity for open charm production from d+Au collisions at BNL RHIC is d sigma NNcc-bar/dy=0.30±0.04(stat)±0.09(syst) mb. The results are compared to theoretical calculations. Implications for charmonium results in A+A collisions are discussed.
Correlations in the hadron distributions produced in relativistic Au+Au collisions are studied in the discrete wavelet expansion method. The analysis is performed in the space of pseudorapidity (| eta | <= 1) and azimuth(full 2 pi ) in bins of transverse momentum (pt) from 0.14 <= pt <= 2.1GeV/c. In peripheral Au+Au collisions a correlation structure ascribed to minijet fragmentation is observed. It evolves with collision centrality and pt in a way not seen before, which suggests strong dissipation of minijet fragmentation in the longitudinally expanding medium.
Elliptic flow from nuclear collisions is a hadronic observable sensitive to the early stages of system evolution. We report first results on elliptic flow of charged particles at midrapidity in Au+Au collisions at sqrt[sNN] = 130 GeV using the STAR Time Projection Chamber at the Relativistic Heavy Ion Collider. The elliptic flow signal, v2, averaged over transverse momentum, reaches values of about 6% for relatively peripheral collisions and decreases for the more central collisions. This can be interpreted as the observation of a higher degree of thermalization than at lower collision energies. Pseudorapidity and transverse momentum dependence of elliptic flow are also presented.
Elliptic flow from nuclear collisions is a hadronic observable sensitive to the early stages of system evolution. We report first results on elliptic flow of charged particles at midrapidity in Au+Au collisions at sqrt(s_NN)=130 GeV using the STAR TPC at RHIC. The elliptic flow signal, v_2, averaged over transverse momentum, reaches values of about 6% for relatively peripheral collisions and decreases for the more central collisions. This can be interpreted as the observation of a higher degree of thermalization than at lower collision energies. Pseudorapidity and transverse momentum dependence of elliptic flow are also presented.
Coronavirus disease 2019 (COVID-19) is a global pandemic posing significant health risks. The diagnostic test sensitivity of COVID-19 is limited due to irregularities in specimen handling. We propose a deep learning framework that identifies COVID-19 from medical images as an auxiliary testing method to improve diagnostic sensitivity. We use pseudo-coloring methods and a platform for annotating X-ray and computed tomography images to train the convolutional neural network, which achieves a performance similar to that of experts and provides high scores for multiple statistical indices (F1 scores > 96.72% (0.9307, 0.9890) and specificity >99.33% (0.9792, 1.0000)). Heatmaps are used to visualize the salient features extracted by the neural network. The neural network-based regression provides strong correlations between the lesion areas in the images and five clinical indicators, resulting in high accuracy of the classification framework. The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice.
The results from the STAR Collaboration on directed flow (v1), elliptic flow (v2), and the fourth harmonic (v4) in the anisotropic azimuthal distribution of particles from Au+Au collisions at sqrt[sNN]=200GeV 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 v2, scaling with the number of constituent quarks and parton coalescence are discussed. For v4, scaling with v22 and quark coalescence are discussed.
Background: Nitric oxide synthase 1 adaptor protein (NOS1AP; previously named CAPON) is linked to the glutamatergic postsynaptic density through interaction with neuronal nitric oxide synthase (nNOS). NOS1AP and its interaction with nNOS have been associated with several mental disorders. Despite the high levels of NOS1AP expression in the hippocampus and the relevance of this brain region in glutamatergic signalling as well as mental disorders, a potential role of hippocampal NOS1AP in the pathophysiology of these disorders has not been investigated yet.
Methods: To uncover the function of NOS1AP in hippocampus, we made use of recombinant adeno-associated viruses to overexpress murine full-length NOS1AP or the NOS1AP carboxyterminus in the hippocampus of mice. We investigated these mice for changes in gene expression, neuronal morphology, and relevant behavioural phenotypes.
Findings: We found that hippocampal overexpression of NOS1AP markedly increased the interaction of nNOS with PSD-95, reduced dendritic spine density, and changed dendritic spine morphology at CA1 synapses. At the behavioural level, we observed an impairment in social memory and decreased spatial working memory capacity.
Interpretation: Our data provide a mechanistic explanation for a highly selective and specific contribution of hippocampal NOS1AP and its interaction with the glutamatergic postsynaptic density to cross-disorder pathophysiology. Our findings allude to therapeutic relevance due to the druggability of this molecule.
Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.