Evidence for HI replenishment in massive galaxies through gas accretion from the cosmic web

We examine the H i -to-stellar mass ratio (H i fraction) for galaxies near filament backbones within the nearby Universe (d < 181 Mpc). This work uses the 6 degree Field Galaxy Survey (6dFGS) and the Discrete Persistent Structures Extractor (DisPerSE) to define the filamentary structure of the local cosmic web. H i spectral stacking of H i Parkes All Sky Survey (HIPASS) observations yield the H i fraction for filament galaxies and a field control sample. The H i fraction is measured for different stellar masses and 5th nearest neighbour projected densities (Σ5) to disentangle what influences cold gas in galaxies. For galaxies with stellar masses log(M⋆) ≤ 11 M⊙ in projected densities 0 ≤ Σ5 < 3 galaxies Mpc−2, all H i fractions of galaxies near filaments are statistically indistinguishable from the control sample. Galaxies with stellar masses log(M⋆) ≥ 11 M⊙ have a systematically higher H i fraction near filaments than the control sample. The greatest difference is 0.75 dex, which is 5.5σ difference at mean projected densities of 1.45 galaxies Mpc−2. We suggest that this is evidence for massive galaxies accreting cold gas from the intra-filament medium which can replenish some H i gas. This supports cold mode accretion where filament galaxies with a large gravitational potential can draw gas from the large scale structure

Kernel arquitecture for CAD/CAM in shipbuilding enviroments

The capabilities of complex software products such as CAD/CAM systems are strongly supported by basic information technologies related with data management, visualization, communication, geometry modeling and others related with the development process. These basic information technologies are involved in a continuous evolution process, but over recent years this evolution has been dramatic. The main reason for this has been that new hardware capabilities (including graphic cards) are available at very low cost, but also a contributing factor has been the evolution of the prices of basic software. To take advantage of these new features, the existing CAD/CAM systems must undergo a complete and drastic redesign. This process is complicated but strategic for the future evolution of a system. There are several examples in the market of how a bad decision has lead to a cul-de-sac (both technically and commercially). This paper describes what the authors consider are the basic architectural components of a kernel for a CAD/CAM system oriented to shipbuilding. The proposed solution is a combination of in-house developed frameworks together with commercial products that are accepted as standard components. The proportion of in-house frameworks within this combination of products is a key factor, especially when considering CAD/CAM systems oriented to shipbuilding. General-purpose CAD/CAM systems are mainly oriented to the mechanical CAD market. For this reason several basic products exist devoted to geometry modelling in this context. But these basic products are not well suited to deal with the very specific geometry modelling requirements of a CAD/CAM system oriented to shipbuilding. The complexity of the ship model, the different model requirements through its short and changing life cycle and the many different disciplines involved in the process are reasons for this inadequacy. Apart from these basic frameworks, specific shipbuilding frameworks are also required. This second layer is built over the basic technology components mentioned above. This paper describes in detail the technological frameworks which have been used to develop the latest FORAN version.Postprint (published version

Spatial fluctuations at vertices of epithelial layers: quantification of regulation by Rho pathway

In living matter, shape fluctuations induced by acto-myosin are usually studied in vitro via reconstituted gels, whose properties are controlled by changing the concentrations of actin, myosin and cross-linkers. Such an approach deliberately avoids to consider the complexity of biochemical signaling inherent to living systems. Acto-myosin activity inside living cells is mainly regulated by the Rho signaling pathway which is composed of multiple layers of coupled activators and inhibitors. We investigate how such a pathway controls the dynamics of confluent epithelial tissues by tracking the displacements of the junction points between cells. Using a phenomenological model to analyze the vertex fluctuations, we rationalize the effects of different Rho signaling targets on the emergent tissue activity by quantifying the effective diffusion coefficient, the persistence time and persistence length of the fluctuations. Our results reveal an unanticipated correlation between layers of activation/inhibition and spatial fluctuations within tissues. Overall, this work connects the regulation via biochemical signaling with mesoscopic spatial fluctuations, with potential application to the study of structural rearrangements in epithelial tissues.Comment: 8 pages, 3 figure

Climate Dynamics: A Network-Based Approach for the Analysis of Global Precipitation

Precipitation is one of the most important meteorological variables for defining the climate dynamics, but the spatial patterns of precipitation have not been fully investigated yet. The complex network theory, which provides a robust tool to investigate the statistical interdependence of many interacting elements, is used here to analyze the spatial dynamics of annual precipitation over seventy years (1941-2010). The precipitation network is built associating a node to a geographical region, which has a temporal distribution of precipitation, and identifying possible links among nodes through the correlation function. The precipitation network reveals significant spatial variability with barely connected regions, as Eastern China and Japan, and highly connected regions, such as the African Sahel, Eastern Australia and, to a lesser extent, Northern Europe. Sahel and Eastern Australia are remarkably dry regions, where low amounts of rainfall are uniformly distributed on continental scales and small-scale extreme events are rare. As a consequence, the precipitation gradient is low, making these regions well connected on a large spatial scale. On the contrary, the Asiatic South-East is often reached by extreme events such as monsoons, tropical cyclones and heat waves, which can all contribute to reduce the correlation to the short-range scale only. Some patterns emerging between mid-latitude and tropical regions suggest a possible impact of the propagation of planetary waves on precipitation at a global scale. Other links can be qualitatively associated to the atmospheric and oceanic circulation. To analyze the sensitivity of the network to the physical closeness of the nodes, short-term connections are broken. The African Sahel, Eastern Australia and Northern Europe regions again appear as the supernodes of the network, confirming furthermore their long-range connection structure. Almost all North-American and Asian nodes vanish, revealing that extreme events can enhance high precipitation gradients, leading to a systematic absence of long-range patterns

Interpretable statistics for complex modelling: quantile and topological learning

As the complexity of our data increased exponentially in the last decades, so has our need for interpretable features. This thesis revolves around two paradigms to approach this quest for insights. In the first part we focus on parametric models, where the problem of interpretability can be seen as a “parametrization selection”. We introduce a quantile-centric parametrization and we show the advantages of our proposal in the context of regression, where it allows to bridge the gap between classical generalized linear (mixed) models and increasingly popular quantile methods. The second part of the thesis, concerned with topological learning, tackles the problem from a non-parametric perspective. As topology can be thought of as a way of characterizing data in terms of their connectivity structure, it allows to represent complex and possibly high dimensional through few features, such as the number of connected components, loops and voids. We illustrate how the emerging branch of statistics devoted to recovering topological structures in the data, Topological Data Analysis, can be exploited both for exploratory and inferential purposes with a special emphasis on kernels that preserve the topological information in the data. Finally, we show with an application how these two approaches can borrow strength from one another in the identification and description of brain activity through fMRI data from the ABIDE project

Multicast Mobility in Mobile IP Version 6 (MIPv6) : Problem Statement and Brief Survey

Publisher PD

Dense active matter model of motion patterns in confluent cell monolayers

Epithelial cell monolayers show remarkable displacement and velocity correlations over distances of ten or more cell sizes that are reminiscent of supercooled liquids and active nematics. We show that many observed features can be described within the framework of dense active matter, and argue that persistent uncoordinated cell motility coupled to the collective elastic modes of the cell sheet is sufficient to produce swirl-like correlations. We obtain this result using both continuum active linear elasticity and a normal modes formalism, and validate analytical predictions with numerical simulations of two agent-based cell models, soft elastic particles and the self-propelled Voronoi model together with in-vitro experiments of confluent corneal epithelial cell sheets. Simulations and normal mode analysis perfectly match when tissue-level reorganisation occurs on times longer than the persistence time of cell motility. Our analytical model quantitatively matches measured velocity correlation functions over more than a decade with a single fitting parameter.Comment: updated version accepted for publication in Nat. Com