Improving Scalability and Maintenance of Software for High-Performance Scientific Computing by Combining MDE and Frameworks

International audienceIn recent years, numerical simulation has attracted increasing interest within industry and among academics. Paradoxically, the development and maintenance of high performance scientific computing software has become more complex due to the diversification of hardware architectures and their related programming languages and libraries. In this paper, we share our experience in using model-driven development for numerical simulation software. Our approach called MDE4HPC proposes to tackle development complexity by using a domain specific modeling language to describe abstract views of the software. We present and analyse the results obtained with its implementation when deriving this abstract model to target Arcane, a development framework for 2D and 3D numerical simulation software

Why do herbivorous mites suppress plant defenses?

Plants have evolved numerous defensive traits that enable them to resist herbivores. In turn, this resistance has selected for herbivores that can cope with defenses by either avoiding, resisting or suppressing them. Several species of herbivorous mites, such as the spider mites Tetranychus urticae and Tetranychus evansi, were found to maximize their performance by suppressing inducible plant defenses. At first glimpse it seems obvious why such a trait will be favored by natural selection. However, defense suppression appeared to readily backfire since mites that do so also make their host plant more suitable for competitors and their offspring more attractive for natural enemies. This, together with the fact that spider mites are infamous for their ability to resist (plant) toxins directly, justifies the question as to why traits that allow mites to suppress defenses nonetheless seem to be relatively common? We argue that this trait may facilitate generalist herbivores, like T. urticae, to colonize new host species. While specific detoxification mechanisms may, on average, be suitable only on a narrow range of similar hosts, defense suppression may be more broadly effective, provided it operates by targeting conserved plant signaling components. If so, resistance and suppression may be under frequency-dependent selection and be maintained as a polymorphism in generalist mite populations. In that case, the defense suppression trait may be under rapid positive selection in subpopulations that have recently colonized a new host but may erode in relatively isolated populations in which host-specific detoxification mechanisms emerge. Although there is empirical evidence to support these scenarios, it contradicts the observation that several of the mite species found to suppress plant defenses actually are relatively specialized. We argue that in these cases buffering traits may enable such mites to mitigate the negative side effects of suppression in natural communities and thus shield this trait from natural selection

Properties of healthcare teaming networks as a function of network construction algorithms

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: The Center for Medicare Services Outpatient Claims DE-SynPUF (DE-SynPUF)\cite{RN120} test set is publicly available from the CMS web site. The full 2013 Medicare Part B Limited Data Set for Medicare claims can be obtained from the Center for Medicare Services. This data is bound by a privacy and limited distribution agreement, as well as HIPAA regulations, and thus cannot be made public with this manuscript. However, the files can be requested from the Center for Medicare Services by individual investigators and used to reproduce our findings. Release of the derived networks is also limited by Medicare requirements to remove nodes and edges where the total number of shared patients 11 shared patients, and these are available on figshare.com as referenced in the Supplemental Data section of the manuscript.Network models of healthcare systems can be used to examine how providers collaborate, communicate, refer patients to each other, and to map how patients traverse the network of providers. Most healthcare service network models have been constructed from patient claims data, using billing claims to link a patient with a specific provider in time. The data sets can be quite large (106±108 individual claims per year), making standard methods for network construction computationally challenging and thus requiring the use of alternate construction algorithms. While these alternate methods have seen increasing use in generating healthcare networks, there is little to no literature comparing the differences in the structural properties of the generated networks, which as we demonstrate, can be dramatically different. To address this issue, we compared the properties of healthcare networks constructed using different algorithms from 2013 Medicare Part B outpatient claims data. Three different algorithms were compared: Binning, sliding frame, and trace-route. Unipartite networks linking either providers or healthcare organizations by shared patients were built using each method. We find that each algorithm produced networks with substantially different topological properties, as reflected by numbers of edges, network density, assortativity, clustering coefficients and other structural measures. Provider networks adhered to a power law, while organization networks were best fit by a power law with exponential cutoff. Censoring networks to exclude edges with less than 11 shared patients, a common de-identification practice for healthcare network data, markedly reduced edge numbers and network density, and greatly altered measures of vertex prominence such as the betweenness centrality. Data analysis identified patterns in the distance patients travel between network providers, and a striking set of teaming relationships between providers in the Northeast United States and Florida, likely due to seasonal residence patterns of Medicare beneficiaries. We conclude that the choice of network construction algorithm is critical for healthcare network analysis, and discuss the implications of our findings for selecting the algorithm best suited to the type of analysis to be performed.National Institute of HealthPhilip Templeton FoundationUniversity of Rochester Center for Health Informatic

A percolation context evidenced by thermostimulated currents in oil-resin art media

Degradation over time of home-made thixotropic oil/resin mixtures, similar to those used as natural media by the art painter J.M. William Turner (1775–1851) is investigated by using a combination of dielectric methods, i.e., low-frequency dielectric spectroscopy (LFDS) and the technique of thermostimulated currents (TSC). These address the direct conductivity (d.c.), i.e., the circulation of free charges, and the anelastic orientation of permanent dipoles, respectively. The oil/resin mixtures can be regarded as conducting/insulating-like composite systems with respect to the two conductivities. This provides the opportunity to follow selectively the behavior of the oil, at any composition. In fresh mixtures, LFDS measurements give evidence for three d.c. regimes, delimited by the critical resin-contents (R) R 1∼30% and R 2∼60%. This parallels observation with the naked eye of phase separation at RR 2 in four-year-old naturally-aged samples. Such a stable composition-dependent context with two marked thresholds encourages a discussion of the time-behavior in terms of percolation, i.e., relative spatial organization of the parent substances, rather than by using a microscopic approach at the molecular scale. At R>R 1 the surveillance of the TSC signal indicates that the oil clusters tend to coalesce so as to form bigger clusters with aging. The coalescence process appears to be more efficient when the resin forms a continuum (R>R 2) than a dispersion (R<R 2)

Influence of Sisal fiber’s treatment on the kinetics of hydration, morphological and thermophysical properties of the composite cementitious mortar

Currently, cement-based bio-composite is a relevant concept for researchers in the building. However, these researches highlighted some handicaps. Plant fibers are acting as a retarder in the setting time of the cement. In this study, Sisal fiber (SF) (4% by mass of cement) was subjected to different treatments to improve bio-composites hydration kinetics (KH) “tested by isotherm calorimetry”. The treatment slowed down both alkaline hydrolysis and mineralization of fiber cell walls by promoting the hydration of cement. This result was coherent with morphological properties. In fact, the images obtained by scanning electron microscopy (SEM) showed a tinier calcium layer around the (SF) treated with NaOH and Paraffin oil on the adhesion surface. The Fourier transform infrared spectroscopy (FTIR) test revealed a disparity in the peaks of the absorption strips of CaCO3 and Ca(OH)2 and thus cement hydration. In addition, the tests results showed a decrease in thermal conductivity (λ) and volumetric heat capacity (ρ.CV) after treatment of (SF). Resistance (RTh) and thermal diffusivity (α) slightly increased with treated fiber. Considering that, the bio-mortar with treated Sisal fiber can be promising material from an insulation point of view