21 research outputs found
Flow Dominance and Factorization of Transverse Momentum Correlations in Pb-Pb Collisions at the LHC
We present the first measurement of the two-particle transverse momentum differential correlation function, P2≡ ΔpTΔpT/ pT2, in Pb-Pb collisions at sNN=2.76 TeV. Results for P2 are reported as a function of the relative pseudorapidity (Δη) and azimuthal angle (Δφ) between two particles for different collision centralities. The Δφ dependence is found to be largely independent of Δη for |Δη|≥0.9. In the 5% most central Pb-Pb collisions, the two-particle transverse momentum correlation function exhibits a clear double-hump structure around Δφ=π (i.e., on the away side), which is not observed in number correlations in the same centrality range, and thus provides an indication of the dominance of triangular flow in this collision centrality. Fourier decompositions of P2, studied as a function of the collision centrality, show that correlations at |Δη|≥0.9 can be well reproduced by a flow ansatz based on the notion that measured transverse momentum correlations are strictly determined by the collective motion of the system
A Long Short-Term Memory Network for Sparse Spatiotemporal EEG Source Imaging.
EEG inverse problem is underdetermined, which poses a long standing challenge in Neuroimaging. The combination of source-imaging and analysis of cortical directional networks enables us to noninvasively explore the underlying neural processes. However, existing EEG source imaging approaches mainly focus on performing the direct inverse operation for source estimation, which will be inevitably influenced by noise and the strategy used to find the inverse solution. Here, we develop a new source imaging technique, Deep Brain Neural Network (DeepBraiNNet), for robust sparse spatiotemporal EEG source estimation. In DeepBraiNNet, considering that Recurrent Neural Network (RNN) are usually "deep" in temporal dimension and thus suitable for time sequence modelling, the RNN with Long Short-Term Memory (LSTM) is utilized to approximate the inverse operation for the lead field matrix instead of performing the direct inverse operation, which avoids the possible effect of the direct inverse operation on the underdetermined lead field matrix prone to be influenced by noise. Simulations on various source patterns and noise conditions confirmed that the proposed approach could actually recover the spatiotemporal sources well, outperforming existing state of-the-art methods. DeepBraiNNet also estimated sparse MI related activation patterns when it was applied to a real Motor Imagery dataset, consistent with other findings based on EEG and fMRI. Based on the spatiotemporal sources estimated from DeepBraiNNet, we constructed MI related cortical neural networks, which clearly exhibited strong contralateral network patterns for the two MI tasks. Consequently, DeepBraiNNet may provide an alternative way different from the conventional approaches for spatiotemporal EEG source imaging
Can personal qualities of medical students predict in-course examination success and professional behaviour? An exploratory prospective cohort study
The incidence and importance of bacterial contaminants of cadaveric renal perfusion fluid
Simple and sensitive BIO-PCR detection of potato blackleg pathogens from stem, tuber, and soil samples
Pharmacokinetic study of methotrexate, folinic acid and their serum metabolites in children treated with high-dose methotrexate and leucovorin rescue
Absolute seafloor vertical positioning using combined pressure gauge and kinematic GPS data
Synthesis, characterization and catalytic activity of Au supported on functionalized SBA-15 for low temperature CO oxidation
SBA-15 functionalization with 3-mercaptopropyltrimethoxysilane was used to prepare a supported gold catalyst for the low temperature CO oxidation reaction. Catalytic runs were performed at atmospheric pressure and T = 40–150 °C and the influence of different thermal treatments of the sample prior to reaction was studied. The modifications induced by the pre-treatments in the physicochemical properties of both the carrier and the disperse phase were investigated by chemical analysis, CHS elemental analysis, N2 adsorption–desorption, X-ray diffraction (XRD), transmission electron microscopy (TEM), solid state cross-polarization magic-angle-spinning nuclear magnetic resonance spectroscopy (CPMAS NMR) of 29Si and 13C and Fourier transform infrared spectroscopy (FTIR). The pre-treatment conditions were found to strongly affect both the gold particle size and the nature of the Au surface species. An appreciable catalytic activity was found on samples treated at 600 °C in H2/He atmosphere, provided that the functionalizing agent had been
completely removed by a previous high-temperature calcination