Brain homeostasis : VEGF receptor 1 and 2 ; two unequal brothers in mind

Vascular endothelial growth factors (VEGFs), initially thought to act specifically on the vascular system, exert trophic effects on neural cells during development and adulthood. Therefore, the VEGF system serves as a promising therapeutic target for brain pathologies, but its simultaneous action on vascular cells paves the way for harmful side effects. To circumvent these deleterious effects, many studies have aimed to clarify whether VEGFs directly affect neural cells or if the effects are mediated secondarily via other cell types, like vascular cells. A great number of reports have shown the expression and function of VEGF receptors (VEGFRs), mainly VEGFR-1 and -2, in neural cells, where VEGFR-2 has been described as the major mediator of VEGF-A signals. This review aims to summarize and compare the divergent roles of VEGFR-1 and -2 during CNS development and homeostasis

Hydrodynamical simulations and similarity relations for eruptive mass loss from massive stars

Motivated by the eruptive mass loss inferred from Luminous Blue Variable (LBV) stars, we present 1D hydrodynamical simulations of the response from sudden energy injection into the interior of a very massive ($100 \, M_\odot$) star. For a fiducial case with total energy addition set to a factor $f=0.5$ of the net stellar binding energy, and applied within the stellar envelope, we detail the dynamical response that leads to ejection of the outermost $7.2 \, M_\odot$. We find that the ejecta's variations in time $t$ and radius $r$ for the velocity $v$, density $\rho$, and temperature $T$ are quite well fit by similarity forms in the variable $r/t \approx v$. Specifically the scaled density follows a simple exponential decline $\rho t^{3} \sim \exp (-r/v_{\rm o} t)$. This `exponential similarity' leads to analytic scaling relations for total ejecta mass $\Delta M$ and kinetic energy $\Delta K$ that agree well with the hydrodynamical simulations, with the specific-energy-averaged speed related to the exponential scale speed $v_{\rm o}$ through ${\bar v} \equiv \sqrt{2 \Delta K/\Delta M} = \sqrt{12} \, v_{\rm o}$, and a value comparable to the star's surface escape speed, $v_{\rm esc}$. Models with energy added in the core develop a surface shock breakout that propels an initial, higher-speed ejecta ($>$5000km s$^{-1}$), but the bulk of the ejected material still follows the same exponential similarity scalings with ${\bar v} \approx v_{\rm esc}$. A broader parameter study examines how the ejected mass and energy depends on the energy-addition factor $f$, for three distinct model series that locate the added energy in either the core, envelope, or near-surface. We conclude by discussing the relevance of these results for understanding LBV outbursts and other eruptive phenomena, such as failed supernovae and pulsational pair instability events.Comment: 14 Pages, 12 figures; MNRAS, in pres

Statistical Analyses of Massive Stars and Stellar Populations

Massive stars, i.e. stars more massive than about ten times that of the Sun, are key agents in the Universe. They synthesise many of the chemical elements that are so important for life on Earth, helped reionising the early Universe and end their lives in spectacular supernova explosions that are visible out to large distances. Because of their important role for much of astrophysics, accurate and reliable stellar evolution models are essential. However, recent developments regarding wind mass loss rates, internal mixing processes and duplicity seriously challenge our understanding of massive stars and stellar populations. It is now established that most, if not all, massive stars reside in binaries or higher order multiple systems such that more than two-thirds of all massive stars are expected to interact through mass transfer with a binary companion during their lives. We investigate the consequences of this finding for coeval stellar populations and show that the most massive stars in star clusters are likely all rejuvenated binary products that may seriously bias the determination of cluster ages. We further find that wind mass loss from stars and binary mass transfer leave their fingerprints in the high mass end of stellar mass functions. Using these fingerprints, we are able to age-date the young Arches and Quintuplet star clusters with far reaching consequences for the stellar upper mass limit that we revise to be in the range 200–500 solar masses. Such an upper mass limit would allow for pair-instability supernovae in the local Universe. Large spectroscopic surveys such as the VLT-FLAMES Tarantula Survey (VFTS) deliver many atmospheric parameters of hundreds of massive stars that are ideal to probe and calibrate the physics used in stellar models. To make use of such data, we develop the Bayesian code BONNSAI and make it available through a web-interface. With BONNSAI we are able to match all available observables of stars including their uncertainties simultaneously to stellar models to determine fundamental stellar parameters like mass and age while taking prior knowledge such as initial mass functions into account. A key aspect of BONNSAI is that it allows us to identify stars that cannot be reproduced by stellar models. We use BONNSAI to test the Milky Way stellar models of Brott et al. (2011) with eclipsing binaries and find good agreement. We further use BONNSAI in combination with data from the VFTS to study the massive O and WNh stars in one of the largest starburst regions known to date, 30 Doradus. In particular we investigate their age distributions to learn about their formation history. The VFTS stars in our sample are mostly found outside clusters and associations and we do not find spatially coherent age patterns. The stars either formed continuously over the 30 Doradus field or in clusters and associations from where they were ejected to their current positions. The age distributions of our sample stars are consistent with the existence of at least two to four coeval stellar populations which would imply that most of the VFTS stars in our sample formed in clusters and associations

Revisiting Content Availability in Distributed Online Social Networks

Online Social Networks (OSN) are among the most popular applications in today's Internet. Decentralized online social networks (DOSNs), a special class of OSNs, promise better privacy and autonomy than traditional centralized OSNs. However, ensuring availability of content when the content owner is not online remains a major challenge. In this paper, we rely on the structure of the social graphs underlying DOSN for replication. In particular, we propose that friends, who are anyhow interested in the content, are used to replicate the users content. We study the availability of such natural replication schemes via both theoretical analysis as well as simulations based on data from OSN users. We find that the availability of the content increases drastically when compared to the online time of the user, e. g., by a factor of more than 2 for 90% of the users. Thus, with these simple schemes we provide a baseline for any more complicated content replication scheme.Comment: 11pages, 12 figures; Technical report at TU Berlin, Department of Electrical Engineering and Computer Science (ISSN 1436-9915

Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps

Visual robot navigation within large-scale, semi-structured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many state-of-the-art navigation approaches only operate locally instead of gaining a more conceptual understanding of the planning objective. This limits the complexity of tasks a robot can accomplish and makes it harder to deal with uncertainties that are present in the context of real-time robotics applications. In this work, we present Topomap, a framework which simplifies the navigation task by providing a map to the robot which is tailored for path planning use. This novel approach transforms a sparse feature-based map from a visual Simultaneous Localization And Mapping (SLAM) system into a three-dimensional topological map. This is done in two steps. First, we extract occupancy information directly from the noisy sparse point cloud. Then, we create a set of convex free-space clusters, which are the vertices of the topological map. We show that this representation improves the efficiency of global planning, and we provide a complete derivation of our algorithm. Planning experiments on real world datasets demonstrate that we achieve similar performance as RRT* with significantly lower computation times and storage requirements. Finally, we test our algorithm on a mobile robotic platform to prove its advantages.Comment: 8 page

Numerical Tests of Rotational Mixing in Massive Stars with the new Population Synthesis Code BONNFIRES

We use our new population synthesis code BONNFIRES to test how surface abundances predicted by rotating stellar models depend on the numerical treatment of rotational mixing, such as spatial resolution, temporal resolution and computation of mean molecular weight gradients. We find that even with identical numerical prescriptions for calculating the rotational mixing coefficients in the diffusion equation, different timesteps lead to a deviation of the coefficients and hence surface abundances. We find the surface abundances vary by 10-100% between the model sequences with short timestep of 0.001Myr to model sequences with longer timesteps. Model sequences with stronger surface nitrogen enrichment also have longer main-sequence lifetimes because more hydrogen is mixed to the burning cores. The deviations in main-sequence lifetimes can be as large as 20%. Mathematically speaking, no numerical scheme can give a perfect solution unless infinitesimally small timesteps are used. However, we find that the surface abundances eventually converge within 10% between modelling sequences with sufficiently small timesteps below 0.1Myr. The efficiency of rotational mixing depends on the implemented numerical scheme and critically on the computation of the mean molecular weight gradient. A smoothing function for the mean molecular weight gradient results in stronger rotational mixing. If the discretization scheme or the computational recipe for calculating the mean molecular weight gradient is altered, re-calibration of mixing parameters may be required to fit observations. If we are to properly understand the fundamental physics of rotation in stars, it is crucial that we minimize the uncertainty introduced into stellar evolution models when numerically approximating rotational mixing processes.Comment: 8 pages, 6 figures, accepted by A&