Perturbative and nonperturbative contributions to the strange quark asymmetry in the nucleon

There are two mechanisms for the generation of an asymmetry between the strange and anti-strange quark distributions in the nucleon: nonperturbative contributions originating from nucleons fluctuating into virtual baryon-meson pairs such as $\Lambda K$ and $\Sigma K$, and perturbative contributions arising from gluons splitting into strange and anti-strange quark pairs. While the nonperturbative contributions are dominant in the large-$x$ region, the perturbative contributions are more significant in the small-$x$ region. We calculate this asymmetry taking into account both nonperturbative and perturbative contributions, thus giving a more accurate evaluation of this asymmetry over the whole domain of $x$. We find that the perturbative contributions are generally a few times larger in magnitude than the nonperturbative contributions, which suggests that the best region to detect this asymmetry experimentally is in the region $0.02 < x < 0.03$. We find that the asymmetry may have more than one node, which is an effect that should be taken into account, e.g. for parameterizations of the strange and anti-strange quark distributions used in global analysis of parton distributions.Comment: 14 pages, 4 figures, figures comparing theoretical calculations with NNPDF global analysis added, accepted for publication in EPJ

Light-cone QCD Sum Rules for the Λ\Lambda Baryon Electromagnetic Form Factors and its magnetic moment

We present the light-cone QCD sum rules up to twist 6 for the electromagnetic form factors of the $\Lambda$ baryon. To estimate the magnetic moment of the baryon, the magnetic form factor is fitted by the dipole formula. The numerical value of our estimation is $\mu_\Lambda=-(0.64\pm0.04)\mu_N$, which is in accordance with the experimental data and the existing theoretical results. We find that it is twist 4 but not the leading twist distribution amplitudes that dominate the results.Comment: 13 page, 7 figures, accepted for publication in Euro. Phys. J.

A Biased Review of Sociophysics

Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.Comment: 16 pages for J. Stat. Phys. including 2 figures and numerous reference

Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Altres ajuts: Max Planck Society (Germany).The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes