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We report results on an elastic cross section measurement in proton-proton collisions at a center-of-mass energy s√=510 GeV, obtained with the Roman Pot setup of the STAR experiment at the Relativistic Heavy Ion Collider (RHIC). The elastic differential cross section is measured in the four-momentum transfer squared range 0.23≤−t≤0.67 GeV2. We find that a constant slope B does not fit the data in the aforementioned t range, and we obtain a much better fit using a second-order polynomial for B(t). The t dependence of B is determined using six subintervals of t in the STAR measured t range, and is in good agreement with the phenomenological models. The measured elastic differential cross section dσ/dt agrees well with the results obtained at s√=546~GeV for proton--antiproton collisions by the UA4 experiment. We also determine that the integrated elastic cross section within the STAR t-range is σfidel=462.1±0.9(stat.)±1.1(syst.)±11.6(scale) μb.
The differential cross section for 𝑍0 production, measured as a function of the boson’s transverse momentum (𝑝T), provides important constraints on the evolution of the transverse momentum dependent parton distribution functions (TMDs). The transverse single spin asymmetry (TSSA) of the 𝑍0 is sensitive to one of the polarized TMDs, the Sivers function, which is predicted to have the opposite sign in 𝑝 + 𝑝 → 𝑊 ∕𝑍 + 𝑋 from that which enters in semi-inclusive deep inelastic scattering. In this Letter, the STAR Collaboration reports the first measurement of the 𝑍0∕𝛾∗ differential cross section as a function of its 𝑝T in 𝑝+𝑝 collisions at a center-of-mass energy of 510 GeV, together with the 𝑍0∕𝛾∗ total cross section. We also report the measurement of 𝑍0∕𝛾∗ TSSA in transversely polarized 𝑝+𝑝 collisions at 510 GeV.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. In other words, any two signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks, and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy for auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. brain signals can either share common information (redundancy) or they can encode complementary information that is only available when both signals are considered together (synergy). Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in five common awake marmosets performing two distinct auditory oddball tasks and investigated to what extent event-related potentials (ERP) and broadband (BB) dynamics encoded redundant and synergistic information during auditory prediction error processing. In both tasks, we observed multiple patterns of synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between auditory and frontal regions. Using a brain-constrained neural network, we simulated the spatio-temporal patterns of synergy and redundancy observed in the experimental results and further demonstrated that the emergence of synergy between auditory and frontal regions requires the presence of strong, long-distance, feedback and feedforward connections. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
The emerging disciplines of lipidomics and metabolomics show great potential for the discovery of diagnostic biomarkers, but appropriate pre-analytical sample-handling procedures are critical because several analytes are prone to ex vivo distortions during sample collection. To test how the intermediate storage temperature and storage period of plasma samples from K3EDTA whole-blood collection tubes affect analyte concentrations, we assessed samples from non-fasting healthy volunteers (n = 9) for a broad spectrum of metabolites, including lipids and lipid mediators, using a well-established LC-MS-based platform. We used a fold change-based approach as a relative measure of analyte stability to evaluate 489 analytes, employing a combination of targeted LC-MS/MS and LC-HRMS screening. The concentrations of many analytes were found to be reliable, often justifying less strict sample handling; however, certain analytes were unstable, supporting the need for meticulous processing. We make four data-driven recommendations for sample-handling protocols with varying degrees of stringency, based on the maximum number of analytes and the feasibility of routine clinical implementation. These protocols also enable the simple evaluation of biomarker candidates based on their analyte-specific vulnerability to ex vivo distortions. In summary, pre-analytical sample handling has a major effect on the suitability of certain metabolites as biomarkers, including several lipids and lipid mediators. Our sample-handling recommendations will increase the reliability and quality of samples when such metabolites are necessary for routine clinical diagnosis.
An important question concerning inter-areal communication in the cortex, is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in three common awake marmosets and investigated to what extent event-related-potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy in auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
An important question concerning inter-areal communication in the cortex is whether these interactions are synergistic, i.e. convey information beyond what can be performed by isolated signals. Here, we dissociated cortical interactions sharing common information from those encoding complementary information during prediction error processing. To this end, we computed co-information, an information-theoretical measure that distinguishes redundant from synergistic information among brain signals. We analyzed auditory and frontal electrocorticography (ECoG) signals in three common awake marmosets and investigated to what extent event-related-potentials (ERP) and broadband (BB) dynamics exhibit redundancy and synergy for auditory prediction error signals. We observed multiple patterns of redundancy and synergy across the entire cortical hierarchy with distinct dynamics. The information conveyed by ERPs and BB signals was highly synergistic even at lower stages of the hierarchy in the auditory cortex, as well as between lower and higher areas in the frontal cortex. These results indicate that the distributed representations of prediction error signals across the cortical hierarchy can be highly synergistic.
The longitudinal and transverse spin transfers to Λ (Λ¯¯¯¯) hyperons in polarized proton-proton collisions are expected to be sensitive to the helicity and transversity distributions, respectively, of (anti-)strange quarks in the proton, and to the corresponding polarized fragmentation functions. We report improved measurements of the longitudinal spin transfer coefficient, DLL, and the transverse spin transfer coefficient, DTT, to Λ and Λ¯¯¯¯ in polarized proton-proton collisions at s√ = 200 GeV by the STAR experiment at RHIC. The data set includes longitudinally polarized proton-proton collisions with an integrated luminosity of 52 pb−1, and transversely polarized proton-proton collisions with a similar integrated luminosity. Both data sets have about twice the statistics of previous results and cover a kinematic range of |ηΛ(Λ¯¯¯¯)| < 1.2 and transverse momentum pT,Λ(Λ¯¯¯¯) up to 8 GeV/c. We also report the first measurements of the hyperon spin transfer coefficients DLL and DTT as a function of the fractional jet momentum z carried by the hyperon, which can provide more direct constraints on the