Generating realistic scaled complex networks

Research on generative models is a central project in the emerging field of network science, and it studies how statistical patterns found in real networks could be generated by formal rules. Output from these generative models is then the basis for designing and evaluating computational methods on networks, and for verification and simulation studies. During the last two decades, a variety of models has been proposed with an ultimate goal of achieving comprehensive realism for the generated networks. In this study, we (a) introduce a new generator, termed ReCoN; (b) explore how ReCoN and some existing models can be fitted to an original network to produce a structurally similar replica, (c) use ReCoN to produce networks much larger than the original exemplar, and finally (d) discuss open problems and promising research directions. In a comparative experimental study, we find that ReCoN is often superior to many other state-of-the-art network generation methods. We argue that ReCoN is a scalable and effective tool for modeling a given network while preserving important properties at both micro- and macroscopic scales, and for scaling the exemplar data by orders of magnitude in size.Comment: 26 pages, 13 figures, extended version, a preliminary version of the paper was presented at the 5th International Workshop on Complex Networks and their Application

Generating realistic scaled complex networks

Research on generative models plays a central role in the emerging field of network science, studying how statistical patterns found in real networks could be generated by formal rules. Output from these generative models is then the basis for designing and evaluating computational methods on networks including verification and simulation studies. During the last two decades, a variety of models has been proposed with an ultimate goal of achieving comprehensive realism for the generated networks. In this study, we (a) introduce a new generator, termed ReCoN; (b) explore how ReCoN and some existing models can be fitted to an original network to produce a structurally similar replica, (c) use ReCoN to produce networks much larger than the original exemplar, and finally (d) discuss open problems and promising research directions. In a comparative experimental study, we find that ReCoN is often superior to many other state-of-the-art network generation methods. We argue that ReCoN is a scalable and effective tool for modeling a given network while preserving important properties at both micro- and macroscopic scales, and for scaling the exemplar data by orders of magnitude in size

Characterization of Structural Defects in (Cd,Zn)Te Crystals Grown by the Travelling Heater Method

Structural defects and compositional uniformity remain the major problems affecting the performance of (Cd, Zn)Te (CZT) based detector devices. Understanding the mechanism of growth and defect formation is therefore fundamental to improving the crystal quality. In this frame, space experiments for the growth of CZT by the Travelling Heater Method (THM) under microgravity are scheduled. A detailed ground-based program was performed to determine experimental parameters and three CZT crystals were grown by the THM. The structural defects, compositional homogeneity and resistivity of these ground-based crystals were investigated. A ZnTe content variation was observed at the growth interface and a high degree of stress associated with extensive dislocation networks was induced, which propagated into the grown crystal region according to the birefringence and X-ray White Beam Topography (XWBT) results. By adjusting the growth parameters, the ZnTe variations and the resulting stress were efficiently reduced. In addition, it was revealed that large inclusions and grain boundaries can generate a high degree of stress, leading to the formation of dislocation slip bands and subgrain boundaries. The dominant defects, including grain boundaries, dislocation networks and cracks in the interior of crystals, led to the resistivity variation in the crystals. The bulk resistivity of the as-grown crystals ranged from 109 Ωcm to 1010 Ωcm

A Near-Infrared Spectroscopic Survey of Class I Protostars

We present the results of a near-IR spectroscopic survey of 110 Class I protostars observed from 0.80 microns to 2.43 microns at a spectroscopic resolution of R=1200. We find that Class I objects exhibit a wide range of lines and the continuum spectroscopic features. 85% of Class I protostars exhibit features indicative of mass accretion, and we found that the veiling excess, CO emission, and Br Gamma emission are closely related. We modeled the spectra to estimate the veiling excess (r_k) and extinction to each target. We also used near-IR colors and emission line ratios, when available, to also estimate extinction. In the course of this survey, we observed the spectra of 10 FU Orionis-like objects, including 2 new ones, as well as 3 Herbig Ae type stars among our Class I YSOs. We used photospheric absorption lines, when available, to estimate the spectral type of each target. Although most targets are late type stars, there are several A and F-type stars in our sample. Notably, we found no A or F class stars in the Taurus-Auriga or Perseus star forming regions. There are several cases where the observed CO and/or water absorption bands are deeper than expected from the photospheric spectral type. We find a correlation between the appearance of the reflection nebula, which traces the distribution of material on very large scales, and the near-IR spectrum, which probes smaller scales. The spectra of the components of spatially resolved protostellar binaries tend to be very similar. In particular both components tend to have similar veiling and H_2 emission, inconsistent with random selection from the sample as a whole. There is a strong correlation between [Fe II] and H_2 emission, supporting previous results showing that H_2 emission in the spectra of young stars is usually shock excited by stellar winds.Comment: 89 pages, 13 figures, 7 Table

Aktuelle Herausforderungen der Wissenschafts- und Hochschulforschung

In den letzten Jahren ist im deutschen Sprachraum, abweichend von der internationalen Nomenklatur, vermehrt von »Wissenschafts- und Hochschulforschung« die Rede. Angezeigt ist damit die Suche nach einem Überbegriff für die diversen sozialwissenschaftlichen Perspektiven auf Wissenschaft und Universität. Vor diesem Hintergrund versteht sich der vorliegende Beitrag als kollektive Standortbestimmung. Anhand von sieben Forschungsagenden zeigen die Autor/innen das Potenzial einer stärkeren Verbindung von Wissenschafts- und Hochschulforschung. Die sieben Agenden bilden zum einen Fragen und Probleme ab, die der aktuelle Forschungsstand aufwirft, zum anderen zeigen sie Relevanz der soziologischen Perspektive für die theoretische und methodische Integration der beiden Forschungsfelder. In recent years, social science perspectives that are concerned with academic research and higher education have increasingly been subsumed under the umbrella term »science and higher education studies« – a peculiar German category that is uncommon in the international context, where »science and technology studies« and »higher education studies« are developing rather independently from each other. Against this background, the current paper documents a discussion of several scholars from both science and higher education studies. Sketching seven research agendas, the contribution identifies fields of study for which a closer interaction between the two fields would be beneficial. On the one hand, these agendas highlight open questions of the current state of research. On the other hand, the agendas illustrate how a sociological perspective can contribute to integrating science and higher education studies both theoretically and methodologically

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition

Chemokine Transfer by Liver Sinusoidal Endothelial Cells Contributes to the Recruitment of CD4+ T Cells into the Murine Liver

Leukocyte adhesion and transmigration are central features governing immune surveillance and inflammatory reactions in body tissues. Within the liver sinusoids, chemokines initiate the first crucial step of T-cell migration into the hepatic tissue. We studied molecular mechanisms involved in endothelial chemokine supply during hepatic immune surveillance and liver inflammation and their impact on the recruitment of CD4+ T cells into the liver. In the murine model of Concanavalin A-induced T cell-mediated hepatitis, we showed that hepatic expression of the inflammatory CXC chemokine ligands (CXCL)9 and CXCL10 strongly increased whereas homeostatic CXCL12 significantly decreased. Consistently, CD4+ T cells expressing the CXC chemokine receptor (CXCR)3 accumulated within the inflamed liver tissue. In histology, CXCL9 was associated with liver sinusoidal endothelial cells (LSEC) which represent the first contact site for T-cell immigration into the liver. LSEC actively transferred basolaterally internalized CXCL12, CXCL9 and CXCL10 via clathrin- coated vesicles to CD4+ T cells leading to enhanced transmigration of CXCR4+ total CD4+ T cells and CXCR3+ effector/memory CD4+ T cells, respectively in vitro. LSEC-expressed CXCR4 mediated CXCL12 transport and blockage of endothelial CXCR4 inhibited CXCL12-dependent CD4+ T-cell transmigration. In contrast, CXCR3 was not involved in the endothelial transport of its ligands CXCL9 and CXCL10. The clathrin-specific inhibitor chlorpromazine blocked endothelial chemokine internalization and CD4+ T-cell transmigration in vitro as well as migration of CD4+ T cells into the inflamed liver in vivo. Moreover, hepatic accumulation of CXCR3+ CD4+ T cells during T cell-mediated hepatitis was strongly reduced after administration of chlorpromazine. These data demonstrate that LSEC actively provide perivascularly expressed homeostatic and inflammatory chemokines by CXCR4- and clathrin-dependent intracellular transport mechanisms thereby contributing to the hepatic recruitment of CD4+ T-cell populations during immune surveillance and liver inflammation