Particle Fluxes and Transport Proceses Along the Continental Margins and in Deep Sea Environments.

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Influence of distributary channels on sediment and organic matter supply in event-dominated coastal margins: the Po prodelta as a study case

From November 2008 through May 2009, the Po river (Italy) experienced several floods exceeding 5000 m<sup>3</sup> s<sup>−1</sup>. This long series of events ended with a large flood in early May 2009 (~8000 m<sup>3</sup> s<sup>−1</sup>). An event-response sampling was carried out in the Po prodelta in April–May 2009 to characterize the preservation of this series of floods in the sediment record and to describe the event-supply and deposition of riverborne particulate material during the May 2009 flood. The water sampling was carried out early in the event under conditions of moderate river flow (~5000 m<sup>3</sup> s<sup>−1</sup>) and 24 h later during the peak discharge (~8000 m<sup>3</sup> s<sup>−1</sup>). Sediment cores were collected in the prodelta before and after the peak flood. At each station, profiles of conductivity, transmittance, and fluorescence were acquired. Surface and bottom waters were sampled to collect sediments in suspension. In addition, a few days before the May 2009 event, suspended sediments were collected at Pontelagoscuro gauging station, ~90 km upstream from the coast. Biogeochemical compositions and sedimentological characteristics of suspended and sediment samples were investigated using bulk and biomarker analyses. Furthermore, <sup>7</sup>Be and radiographs were used to analyze the internal stratigraphy of sediment cores. <br><br> During moderate flow, the water column did not show evidence of plume penetration. Stations re-occupied 24 h later exhibited marked physical and biogeochemical changes during the peak flood. However, the concentration of terrestrially-derived material in surface waters was still less than expected. These results suggested that, since material enters the Adriatic as buoyancy-driven flow with a reduced transport capacity, settling and flocculation processes result in trapping a significant fraction of land-derived material in shallow sediments and/or within distributary channels. <br><br> Although numerous discharge peaks occurred from November 2008 through April 2009 (4000–6000 m<sup>3</sup> s<sup>−1</sup>), sediment cores collected in late April 2009 showed lack of event-strata preservation and reduced <sup>7</sup>Be penetrations. This suggested that only a small fraction of the sediment supply during ordinary events reaches the deepest region of the prodelta (12–20 m water depth). As a result, these event-strata have a thickness not sufficient to be preserved in the sediment record because of post-depositional processes that destroy the flood signal. <br><br> Stations in the northern and central prodelta were re-occupied after the peak of the May 2009 flood. Based on <sup>7</sup>Be and radiographs, we estimated event layers of 17 and 6 cm thickness, respectively. Selective trapping of coarse material occurred in the central prodelta likely because of the geomorphologic setting of the central outlet characterized by an estuary-like mouth. Despite these settling processes, lignin-based parameters indicated that the composition of the terrigenous OC was fairly homogenous throughout the network of channels and between size-fractions

Suppression subtractive hybridization analysis of genes regulated by magnaporthe oryzae infection in wheat adult plants.

Blast (also known as brusone), caused by the fungus Magnaporthe oryzae, is a serious disease of wheat (Triticum aestivum) across central and southern Brazil. The pathogen is a hemibiotrophic ascomycete that attacks several grass species. The disease was first described in rice in 1600 in China and it was reported infecting wheat ears in 1985 in Paraná state, Brazil, and since spread to all growing-regions in the country. Currently has been also reported on wheat fields in Bolivia, Paraguay and Argentina. The rice blast disease has emerged as a model for the study of phytopathogenic fungi showing that this pathogen initially colonizes host tissues as a biotroph, without causing detectable symptoms. Approximately 72?96 h after infection, lesions become apparent in the plant, characterizing the necrotrophic growth of M. oryzae. In wheat plants, depending on the developmental stage at which infection occurs blast can be devastating. Infected heads produce small and wrinkled grains with low specific weight. Few cultivars are described as resistant to wheat blast and fungicides have low control efficiency of the disease. Little is known about the molecular mechanism of wheat resistance to the pathogen. Here, we investigated the responses of wheat to M. oryzae infection in reproductive stage at 40 h after inoculation. The aim of this study was to identify genes that are differentially up- or downregulated in adults plants of Triticum aestivum infected with Magnaporthe oryzae. For this, we used a suppression subtractive hybridization (SSH) approach. A total of 420 high-quality contigs were isolated, 415 of them were mapped in Triticum aestivum genome. The 420 contigs were searched against the non-redundant nucleotide and protein databases in GenBank to predict the function for the corresponding genes. Fifty-five contigs corresponded to defense-related genes. We used the quantitative RT-PCR analysis to validate the differential expression patterns for 16 Triticum aestivum genes between control and inoculated spikes. Nine genes presented higher transcript levels under inoculation, including one gene previously described as responsive to Magnaporthe infection on wheat seedlings. This gene coding one protein membrane-associated that may increase the adhesion of the plasma membrane to the cell wall during pathogen infection. In contrast, the other 7 genes presented higher expression in mock-inoculated spikes. The study of these genes and the associated defense mechanisms can provide a significant advance in our understanding of the putative determinants of the resistance mechanisms of this wheat resistant genotype

A comparison of node vaccination strategies to halt SIR epidemic spreading in real-world complex networks

: We compared seven node vaccination strategies in twelve real-world complex networks. The node vaccination strategies are modeled as node removal on networks. We performed node vaccination strategies both removing nodes according to the initial network structure, i.e., non-adaptive approach, and performing partial node rank recalculation after node removal, i.e., semi-adaptive approach. To quantify the efficacy of each vaccination strategy, we used three epidemic spread indicators: the size of the largest connected component, the total number of infected at the end of the epidemic, and the maximum number of simultaneously infected individuals. We show that the best vaccination strategies in the non-adaptive and semi-adaptive approaches are different and that the best strategy also depends on the number of available vaccines. Furthermore, a partial recalculation of the node centrality increases the efficacy of the vaccination strategies by up to 80%

Network structure indexes to forecast epidemic spreading in real-world complex networks

Complex networks are the preferential framework to model spreading dynamics in several real-world complex systems. Complex networks can describe the contacts between infectious individuals, responsible for disease spreading in real-world systems. Understanding how the network structure affects an epidemic outbreak is therefore of great importance to evaluate the vulnerability of a network and optimize disease control. Here we argue that the best network structure indexes (NSIs) to predict the disease spreading extent in real-world networks are based on the notion of network node distance rather than on network connectivity as commonly believed. We numerically simulated, via a type-SIR model, epidemic outbreaks spreading on 50 real-world networks. We then tested which NSIs, among 40, could a priori better predict the disease fate. We found that the “average normalized node closeness” and the “average node distance” are the best predictors of the initial spreading pace, whereas indexes of “topological complexity” of the network, are the best predictors of both the value of the epidemic peak and the final extent of the spreading. Furthermore, most of the commonly used NSIs are not reliable predictors of the disease spreading extent in real-world networks

Considering weights in real social networks: A review

Network science offers powerful tools to model complex social systems. Most social network science research focuses on topological networks by simply considering the binary state of the links, i.e., their presence or absence. Nonetheless, complex social systems present heterogeneity in link interactions (link weight), and accounting for this heterogeneity, it is mandatory to design reliable social network models. Here, we revisit the topic of weighted social networks (WSNs). By summarizing the main notions, findings, and applications in the field of WSNs, we outline how WSN methodology may improve the modeling of several real problems in social sciences. We are convinced that WSNs may furnish ideas and insights to open interesting lines of new research in the social sciences