The ratio of the yields of antiprotons to protons in pp collisions has been measured by the ALICE experiment at sqrt[s]=0.9 and 7 TeV during the initial running periods of the Large Hadron Collider. The measurement covers the transverse momentum interval 0.45

The production of π + , π − , K + , K − , p, and p at mid-rapidity has been measured in proton-proton collisions at √ s = 900 GeV with the ALICE detector. Particle identification is performed using the specific energy loss in the inner tracking silicon detector and the time projection chamber. In addition, time-of-flight information is used to identify hadrons at higher momenta. Finally, the distinctive kink topology of the weak decay of charged kaons is used for an alternative measurement of the kaon transverse momentum (p t ) spectra. Since these various particle identification tools give the best separation capabilities over different momentum ranges, the results are combined to extract spectra from p t = 100 MeV/c to 2.5 GeV/c. The measured spectra are further compared with QCD-inspired models which yield a poor description. The total yields and the mean p t are compared with previous measurements, and the trends as a function of collision energy are discussed.t Deceased.

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An absolute measurement of K^ photoproduction on the proton has been carried out in the threshold region (from 144.7 to 173 MeV) by use of tagged annihilation photons. The measured cross sections, differential in the recoiling-proton energy, are used to perform a multipole analysis which gives a value (-0.5±0.3)x 10""V' w^+ for the dipole amplitude EQ+, in disagreement with low-energy-theorem predictions. Total cross sections and coefficients of the K^ angular distribution are presented.PACS numbers: 13.60.LePion photoproduction amplitudes at threshold are fundamental quantities of jp-wave pion-nucleon physics. Low-energy theorems for soft photons and pions together with the PCAC (partial conservation of axial-vector current) hypothesis allow the expression of the pion photoproduction amplitude in terms of the pion-nucleon coupling constant and the static properties of the nucleon. ^ Charged-pion amplitudes are predicted up to first order in a mjM (the ratio of pion to nucleon mass) expansion. The corresponding experimental values are in good agreement with this approximation. From this comparison one can set limits for terms of higher order in the expansion. These terms are essentially dispersive corrections involving A^* resonances and vector-meson exchange.In the case of neutral-pion photoproduction, only the proton amplitude can be directly measured. Low-energy theorems show that this amplitude vanishes with mjM and they predict contributions up to second order. Within this framework, the electric dipole amplitude £o+(p;r^) is^ -2.4x 10~V/w^+ (these units will be used throughout the text). The mass difference of neutral and charged pions or nucleons induces, through the properties of unitarity and analyticity of the S matrix, an anomaly ("cusp") in the variation of EQ^ipn^) with energy.^'"* The coupling of n^p and n'^n channels (i) produces an imaginary part in the E^+ipn^) amplitude above K^ threshold (151.4 MeV), and (ii) enhances the real part of EQ+ipit^), as compared to its value when mass differences within multiplets are neglected, in the region between the it^ threshold (144.7 MeV) and the n'^ threshold. It is the value of this ideal isospinsymmetric amplitude at threshold which we will quote as EQ+ipjc^) and which is to be compared to the lowenergy-theorem predictions.Until now there has been no reliable experimental information on the threshold cross section, since all existing measurements have been performed with use of bremsstrahlung photon spectra with end-point energies exceeding the reaction threshold by more than 15 MeV. Extraction of the slope of the cross section at threshold from these experiments requires averaging and extrapolation procedures with uncertainties which are only partially accounted for in the quoted error. The current experimental value is EQ+(p7t^) '"-l.S±.0.6,^ in agreement with theoretical predictions.We report here an absolute measurement of neutralpion photoproduction on the proton using a tagged annihilation photon beam and covering the energy region from threshold ...

We report on the measurement of two-pion correlation functions from pp collisions at ffiffi ffi s p ¼ 900 GeV performed by the ALICE experiment at the Large Hadron Collider. Our analysis shows an increase of the Hanbury Brown-Twiss radius with increasing event multiplicity, in line with other measurements done in particle-and nuclear collisions. Conversely, the strong decrease of the radius with increasing transverse momentum, as observed at the Relativistic Heavy Ion Collider and at Tevatron, is not manifest in our data.

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Motivation Antibody structure is largely conserved, except for a complementarity-determining region featuring six variable loops. Five of these loops adopt canonical folds which can typically be predicted with existing methods, while the remaining loop (CDR H3) remains a challenge due to its highly diverse set of observed conformations. In recent years, deep neural networks have proven to be effective at capturing the complex patterns of protein structure. This work proposes DeepH3, a deep residual neural network that learns to predict inter-residue distances and orientations from antibody heavy and light chain sequence. The output of DeepH3 is a set of probability distributions over distances and orientation angles between pairs of residues. These distributions are converted to geometric potentials and used to discriminate between decoy structures produced by RosettaAntibody and predict new CDR H3 loop structures de novo. Results When evaluated on the Rosetta antibody benchmark dataset of 49 targets, DeepH3-predicted potentials identified better, same and worse structures [measured by root-mean-squared distance (RMSD) from the experimental CDR H3 loop structure] than the standard Rosetta energy function for 33, 6 and 10 targets, respectively, and improved the average RMSD of predictions by 32.1% (1.4 Å). Analysis of individual geometric potentials revealed that inter-residue orientations were more effective than inter-residue distances for discriminating near-native CDR H3 loops. When applied to de novo prediction of CDR H3 loop structures, DeepH3 achieves an average RMSD of 2.2 ± 1.1 Å on the Rosetta antibody benchmark. Availability and Implementation DeepH3 source code and pre-trained model parameters are freely available at https://github.com/Graylab/deepH3-distances-orientations. Supplementary information Supplementary data are available at Bioinformatics online.

Antibody structure is largely conserved, except for a complementarity-determining region featuring six variable loops. Five of these loops adopt canonical folds which can typically be predicted with existing methods, while the remaining loop (CDR H3) remains a challenge due to its highly diverse set of observed conformations. In recent years, deep neural networks have proven to be effective at capturing the complex patterns of protein structure. This work proposes DeepH3, a deep residual neural network that learns to predict inter-residue distances and orientations from antibody heavy and light chain sequence. The output of DeepH3 is a set of probability distributions over distances and orientation angles between pairs of residues.These distributions are converted to geometric potentials and used to discriminate between decoy structures produced by RosettaAntibody. When evaluated on the Rosetta Antibody Benchmark dataset of 49 targets, DeepH3-predicted potentials identified better, same, and worse structures (measured by root-mean-squared distance [RMSD] from the experimental CDR H3 loop structure) than the standard Rosetta energy function for 30, 13, and 6 targets, respectively, and improved the average RMSD of predictions by 21.3% (0.48 Å). Analysis of individual geometric potentials revealed that inter-residue orientations were more effective than inter-residue distances for discriminating near-native CDR H3 loop structures.