The chirally-odd twist-3 distribution e(x)

Properties of the nucleon twist-3 distribution function e(x) are reviewed. It is emphasized that the QCD equations of motion imply the existence of a delta-function at x=0 in e(x), which gives rise to the pion-nucleon sigma-term. According to the resulting ``practical'' DIS sum rules the first and the second moment of e(x) vanish, a situation analogue to that of the pure twist-3 distribution function $\bar{g}_2(x)$.Comment: 19 pages, 3 figures, new references and figures adde

Azimuthal asymmetries and Collins analyzing power

Spin azimuthal asymmetries in pion electro-production in deep inelastic scattering off longitudinally polarized protons, measured by HERMES, are well reproduced theoretically with no adjustable parameters. Predictions for azimuthal asymmetries for a longitudinally polarized deuteron target are given. The z-dependence of the Collins fragmentation function is extracted. The first information on e(x) is extracted from CLAS A_LU asymmetry.Comment: 5 pages, 7 figures. Talk presented by A.V. Efremov at DIS2002, Cracow, Poland, 30 April to 4 May 2002. To appear in Acta Physica Polonica

Transversity in Drell-Yan process of polarized protons and antiprotons in PAX experiment

Estimates are given for the double spin asymmetry in lepton-pair production from collisions of transversely polarized protons and antiprotons for the kinematics of the recently proposed PAX experiment at GSI on the basis of predictions for the transversity distribution from the chiral quark soliton model.Comment: 4 pages, 2 eps-figures, style files. To be published in Proceedings of 16th Intern. spin physics symposium, October 10-16, Trieste, Ital

Data-driven modeling of collaboration networks: A cross-domain analysis

We analyze large-scale data sets about collaborations from two different domains: economics, specifically 22.000 R&D alliances between 14.500 firms, and science, specifically 300.000 co-authorship relations between 95.000 scientists. Considering the different domains of the data sets, we address two questions: (a) to what extent do the collaboration networks reconstructed from the data share common structural features, and (b) can their structure be reproduced by the same agent-based model. In our data-driven modeling approach we use aggregated network data to calibrate the probabilities at which agents establish collaborations with either newcomers or established agents. The model is then validated by its ability to reproduce network features not used for calibration, including distributions of degrees, path lengths, local clustering coefficients and sizes of disconnected components. Emphasis is put on comparing domains, but also sub-domains (economic sectors, scientific specializations). Interpreting the link probabilities as strategies for link formation, we find that in R&D collaborations newcomers prefer links with established agents, while in co-authorship relations newcomers prefer links with other newcomers. Our results shed new light on the long-standing question about the role of endogenous and exogenous factors (i.e., different information available to the initiator of a collaboration) in network formation.Comment: 25 pages, 13 figures, 4 table