Semantic and Structural Difficulties with the Unified Modeling Language Use-Case Notation version 1.3

A case study was undertaken to examine and apply the UML use-case notation version 1.3. This study shows that the notation is open to interpretation and the semantics of the use-case relationships are confusing. The attempt to bolt on the object-oriented inheritance structure to the use-case notation is shown to cause problems with users

Covariate-assisted spectral clustering

Biological and social systems consist of myriad interacting units. The interactions can be represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications such as connectomics, social networks, and genomics, graph data are accompanied by contextualizing measures on each node. We utilize these node covariates to help uncover latent communities in a graph, using a modification of spectral clustering. Statistical guarantees are provided under a joint mixture model that we call the node-contextualized stochastic blockmodel, including a bound on the mis-clustering rate. The bound is used to derive conditions for achieving perfect clustering. For most simulated cases, covariate-assisted spectral clustering yields results superior to regularized spectral clustering without node covariates and to an adaptation of canonical correlation analysis. We apply our clustering method to large brain graphs derived from diffusion MRI data, using the node locations or neurological region membership as covariates. In both cases, covariate-assisted spectral clustering yields clusters that are easier to interpret neurologically.Comment: 28 pages, 4 figures, includes substantial changes to theoretical result

Constrained simulations of the Antennae Galaxies: Comparison with Herschel-PACS observations

We present a set of hydro-dynamical numerical simulations of the Antennae galaxies in order to understand the origin of the central overlap starburst. Our dynamical model provides a good match to the observed nuclear and overlap star formation, especially when using a range of rather inefficient stellar feedback efficiencies (0.01 < q_EoS < 0.1). In this case a simple conversion of local star formation to molecular hydrogen surface density motivated by observations accounts well for the observed distribution of CO. Using radiative transfer post-processing we model synthetic far-infrared spectral energy distributions (SEDs) and two-dimensional emission maps for direct comparison with Herschel-PACS observations. For a gas-to-dust ratio of 62:1 and the best matching range of stellar feedback efficiencies the synthetic far-infrared SEDs of the central star forming region peak at values of ~65 - 81 Jy at 99 - 116 um, similar to a three-component modified black body fit to infrared observations. Also the spatial distribution of the far-infrared emission at 70 um, 100 um, and 160 um compares well with the observations: >50% (> 35%) of the emission in each band is concentrated in the overlap region while only < 30% (< 15%) is distributed to the combined emission from the two galactic nuclei in the simulations (observations). As a proof of principle we show that parameter variations in the feedback model result in unambiguous changes both in the global and in the spatially resolved observable far-infrared properties of Antennae galaxy models. Our results strengthen the importance of direct, spatially resolved comparative studies of matched galaxy merger simulations as a valuable tool to constrain the fundamental star formation and feedback physics.Comment: 17 pages, 8 figures, 4 tables, submitted to MNRAS, including revisions after first referee report, comments welcom

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