Measurements of differential production cross sections for a Z boson in association with jets in pp collisions at root s=8 TeV

Peer reviewe

Charged-particle nuclear modification factors in PbPb and pPb collisions at √=sNN=5.02 TeV

The spectra of charged particles produced within the pseudorapidity window |η| < 1 at √ sNN = 5.02 TeV are measured using 404 µb −1 of PbPb and 27.4 pb−1 of pp data collected by the CMS detector at the LHC in 2015. The spectra are presented over the transverse momentum ranges spanning 0.5 < pT < 400 GeV in pp and 0.7 < pT < 400 GeV in PbPb collisions. The corresponding nuclear modification factor, RAA, is measured in bins of collision centrality. The RAA in the 5% most central collisions shows a maximal suppression by a factor of 7–8 in the pT region of 6–9 GeV. This dip is followed by an increase, which continues up to the highest pT measured, and approaches unity in the vicinity of pT = 200 GeV. The RAA is compared to theoretical predictions and earlier experimental results at lower collision energies. The newly measured pp spectrum is combined with the pPb spectrum previously published by the CMS collaboration to construct the pPb nuclear modification factor, RpA, up to 120 GeV. For pT > 20 GeV, RpA exhibits weak momentum dependence and shows a moderate enhancement above unity

Logic mining in neural network: reverse analysis method

Neural networks are becoming very popular with data mining practitioners because they have proven through comparison their predictive power with statistical techniques using real data sets. Based on this idea, we will present a method for inducing logical rules from empirical data-Reverse Analysis. When the values of the connections of a neural network resulting from Hebbian learning for the data are given, we hope to know what logical rules are entrenched in it. This method is tested with some real life data sets. In real life data sets, logical rules are assumed to be in conjunctive normal form (CNF) since Horn clauses are inadequate

Use of four-electrode arrays in three-dimensional electrical resistivity imaging survey

The objective of this paper is to investigate the applicability of four-electrode arrays in 3D electrical resistivity imaging survey. A 3D resistivity imaging survey was carried out along fourteen parallel lines using dipole-dipole, Wenner-Schlumberger, and Wenner arrays with 2 m minimum electrode spacings. Roll-along measurements using a line spacing of 1 m were carried out covering a grid of 20 x 14 electrodes. The 3D least squares algorithm, based on the robust inversion method, was used in the inversion of the 3D apparent resistivity data sets. The results show that the 3D electrical resistivity imaging survey using the Wenner-Schlumberger and the dipole-dipole arrays, or the Wenner and the dipole-dipole arrays, in combination with an appropriate 3D inversion method, can be highly useful when the site conditions do not allow using the pole-pole or pole-dipole arrays

Inversion of quasi-3D DC resistivity imaging data using artificial neural networks

The objective of this paper is to investigate the applicability of Artificial neural networks in inverting quasi-3D DC resistivity imaging data. An electrical resistivity imaging survey was carried out along seven parallel lines using a dipole-dipole array to confirm the validation of the results of an inversion using an artificial neural network technique. The model used to produce synthetic data to train the artificial neural network was a homogeneous medium of 100 Omega m resistivity with an embedded anomalous body of 1000 Omega m resistivity. The network was trained using 21 datasets (comprising 12159 data points) and tested on another 11 synthetic datasets (comprising 6369 data points) and on real field data. Another 24 test datasets (comprising 13896 data points) consisting of different resistivities for the background and the anomalous bodies were used in order to test the interpolation and extrapolation of network properties. Different learning paradigms were tried in the training process of the neural network, with the resilient propagation paradigm being the most efficient. The number of nodes, hidden layers, and efficient values for learning rate and momentum coefficient have been studied. Although a significant correlation between results of the neural network and the conventional robust inversion technique was found, the ANN results show more details of the subsurface structure, and the RMS misfits for the results of the neural network are less than seen with conventional methods. The interpreted results show that the trained network was able to invert quasi-3D electrical resistivity imaging data obtained by dipole-dipole configuration both rapidly and accurately

Computational studies on the cognate and non-cognate aminoacyl-tRNAs

Although kinetic proofreading plays a major role in the fidelity of protein synthesis, it only includes the codon-anticodon interaction without considering the amino acid side chain. It is not known whether the ribosome has a specific interaction with the amino acid side chain or if the correctly charged tRNA behaves in such a way that brings this fidelity to protein synthesis process. To answer this question, we performed some preliminary calculations using numerical analysis on the misacylated tRNAs and compared the results with that of the cognate aminoacyl-tRNAs. Due to the large size of the molecule, we used 2-layered ONIOM (QM/MM) calculations. Interestingly, it was observed that only the initiator tRNA, mat has a specific interaction with the amino acid side chain

Comparison of Wenner and dipole-dipole arrays in the study of an underground three-dimensional cavity

The objective of this paper was to compare Wenner and dipole-dipole configurations in delineating an underground cavity at a site near the University of Malaya, Malaysia. A three-dimensional electrical resistivity imaging survey was carried out along seven parallel lines using Wenner and dipole-dipole arrays. A three-dimensional least-squares algorithm, based on the robust inversion method, was used in the inversion of the apparent resistivity data. In the inverted model, both the horizontal and vertical extents of the anomalous zones were displayed. Results indicate the superiority of the Wenner array over the dipole-dipole array for determining the vertical distribution of the subsurface resistivity, although the dipole-dipole array produced a better lateral extent of the subsurface features. The results show that the three-dimensional electrical resistivity imaging survey using both the Wenner and dipole-dipole arrays, in combination with an appropriate three-dimensional inversion method and synthetic model analysis, can be highly useful for engineering and environmental applications, especially for underground three-dimensional cavity detection

The role of initiator tRNA I met in fidelity of initiation of protein synthesis

The proper arrangement of amino acids in a protein determines its proper function, which is vital for the cellular metabolism. This indicates that the process of peptide bond formation requires high fidelity. One of the most important processes for this fidelity is kinetic proofreading. As biochemical experiments suggest that kinetic proofreading plays a major role in ensuring the fidelity of protein synthesis, it is not certain whether or not a misacylated tRNA would be corrected by kinetic proofreading during the peptide bond formation. Using 2-layered ONIOM (QM/MM) computational calculations, we studied the behavior of misacylated tRNAs and compared the results with these for cognate aminoacyl-tRNAs during the process of peptide bond formation to investigate the effect of nonnative amino acids on tRNAs. The difference between the behavior of initiator tRNA i met compared to the one for the elongator tRNAs indicates that only the initiator tRNA i met specifies the amino acid side chain. Copyright © Taylor and Francis Group, LLC

Scaled momentum spectra in deep inelastic scattering at HERA

Charged particle production has been studied in neutral current deep inelastic ep scattering with the ZEUS detector at HERA using an integrated luminosity of 0.44 fb(-1). Distributions of scaled momenta in the Breit frame are presented for particles in the current fragmentation region. The evolution of these spectra with the photon virtuality, Q(2), is described in the kinematic region 10 < Q(2) < 41000 Ge V-2. Next-to-leading-order and modified leading-log-approximation QCD calculations as well as predictions from Monte Carlo models are compared to the data. The results are also compared to e(+)e(-) annihilation data. The dependences of the pseudorapidity distribution of the particles on Q(2) and on the energy in the gamma p system, W, are presented and interpreted in the context of the hypothesis of limiting fragmentation

Inclusive dijet cross sections in neutral current deep inelastic scattering at HERA

Single- and double-differential inclusive dijet cross sections in neutral current deep inelastic ep scattering have been measured with the ZEUS detector using an integrated luminosity of 374 pb(-1). The measurement was performed at large values of the photon virtuality, Q (2), between 125 and 20 000 GeV2. The jets were reconstructed with the k (T) cluster algorithm in the Breit reference frame and selected by requiring their transverse energies in the Breit frame, E-jet (T,B), to be larger than 8 GeV. In addition, the invariant mass of the dijet system, M-jj,M- was required to be greater than 20 GeV. The cross sections are described by the predictions of next-to-leading-order QCD