191 research outputs found

    Crustal and upper-mantle structure in the Eastern Mediterranean from the analysis of surface wave dispersion curves

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    The dispersive properties of surface waves are used to infer earth structure in the Eastern Mediterranean region. Using group velocity maps for Rayleigh and Love waves from 7100 s, we invert for the best 1D crust and uppermantle structure at a regular series of points. Assembling the results produces a 3D lithospheric model, along with corresponding maps of sediment and crustal thickness. A comparison of our results to other studies finds the uncertainties of the Moho estimates to be about 5 km. We find thick sediments beneath most of the Eastern Mediterranean basin, in the Hellenic subduction zone and the Cyprus arc. The Ionian Sea is more characteristic of oceanic crust than the rest of the Eastern Mediterranean region as demonstrated in particular by the crustal thickness. We also find significant crustal thinning in the Aegean Sea portion of the backarc, particularly towards the south. Notably slower Swave velocities are found in the uppermantle, especially in the northern Red Sea and Dead Sea Rift, central Turkey, and along the subduction zone. The low velocities in the uppermantle that span from North Africa to Crete, in the Libyan Sea, might be an indication of serpentinized mantle from the subducting African lithosphere. We also find evidence of a strong reverse correlation between sediment and crustal thickness which, while previously demonstrated for extensional regions, also seems applicable for this convergence zone

    Coastal sensitivity/vulnerability characterization and adaptation strategies: A review

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    Coastal area constitutes a vulnerable environment and requires special attention to preserve ecosystems and human activities therein. To this aim, many studies have been devoted both in past and recent years to analyzing the main factors affecting coastal vulnerability and susceptibility. Among the most used approaches, the Coastal Vulnerability Index (CVI) accounts for all relevant variables that characterize the coastal environment dealing with: (i) forcing actions (waves, tidal range, sea-level rise, etc.), (ii) morphological characteristics (geomorphology, foreshore slope, dune features, etc.), (iii) socio-economic, ecological and cultural aspects (tourism activities, natural habitats, etc.). Each variable is evaluated at each portion of the investigated coast, and associated with a vulnerability level which usually ranges from 1 (very low vulnerability), to 5 (very high vulnerability). Following a susceptibility/vulnerability analysis of a coastal stretch, specific strategies must be chosen and implemented to favor coastal resilience and adaptation, spanning from hard solutions (e.g., groins, breakwaters, etc.) to soft solutions (e.g., beach and dune nourishment projects), to the relocation option and the establishment of accommodation strategies (e.g., emergency preparedness)

    The Partial Visibility Representation Extension Problem

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    For a graph GG, a function ψ\psi is called a \emph{bar visibility representation} of GG when for each vertex vV(G)v \in V(G), ψ(v)\psi(v) is a horizontal line segment (\emph{bar}) and uvE(G)uv \in E(G) iff there is an unobstructed, vertical, ε\varepsilon-wide line of sight between ψ(u)\psi(u) and ψ(v)\psi(v). Graphs admitting such representations are well understood (via simple characterizations) and recognizable in linear time. For a directed graph GG, a bar visibility representation ψ\psi of GG, additionally, puts the bar ψ(u)\psi(u) strictly below the bar ψ(v)\psi(v) for each directed edge (u,v)(u,v) of GG. We study a generalization of the recognition problem where a function ψ\psi' defined on a subset VV' of V(G)V(G) is given and the question is whether there is a bar visibility representation ψ\psi of GG with ψ(v)=ψ(v)\psi(v) = \psi'(v) for every vVv \in V'. We show that for undirected graphs this problem together with closely related problems are \NP-complete, but for certain cases involving directed graphs it is solvable in polynomial time.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

    Microstructural and morphological properties of homoepitaxial (001)ZnTe layers investigated by x-ray diffuse scattering

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    The microstructural and morphological properties of homoepitaxial (001)ZnTe layers are investigated by x-ray diffuse scattering. High resolution reciprocal space maps recorded close to the ZnTe (004) Bragg peak show different diffuse scattering features. One kind of cross-shaped diffuse scattering streaks along directions can be attributed to stacking faults within the epilayers. Another kind of cross-shaped streaks inclined at an angle of about 80deg with respect to the in-plane direction arises from the morphology of the epilayers. (abridged version

    Image sensors for wave monitoring in shore protection: Characterization through a machine learning algorithm

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    Waves propagating on the water surface can be considered as propagating in a dispersive medium, where gravity and surface tension at the air–water interface act as restoring forces. The velocity at which energy is transported in water waves is defined by the group velocity. The paper reports the use of video‐camera observations to study the impact of water waves on an urban shore. The video‐monitoring system consists of two separate cameras equipped with progressive RGB CMOS sensors that allow 1080p HDTV video recording. The sensing system delivers video signals that are processed by a machine learning technique. The scope of the research is to identify features of water waves that cannot be normally observed. First, a conventional modelling was performed using data delivered by image sensors together with additional data such as temperature, and wind speed, measured with dedicated sensors. Stealth waves are detected, as are the inverting phenomena encompassed in waves. This latter phenomenon can be detected only through machine learning. This double approach allows us to prevent extreme events that can take place in offshore and onshore areas

    Recovery of pectinases from Aspergillus niger using aqueous two-phase systems / Recuperação de pectinases de Aspergillus niger usando sistemas aquosos bifásicos

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    This work aimed to study the purification of pectinases by aqueous two-phase systems (ATPS). The crude enzymatic extract was produced by Aspergillus niger ATCC 9642 and contained exo-polygalacturonase (exo-PG), pectinmethylesterase (PME) and pectin lyase (PMGL). The ATPS systems tested consisted in the combinations of polyethylene glycol (PEG) and potassium phosphate and sodium citrate, alcohol (ethanol, n-propanol and isopropanol) and salt (ammonium sulfate, potassium phosphate and sodium citrate). The experiments showed higher recoveries using ATPS system - PEG/phosphate for the exo-PG were using 16% PEG 4.0 kDa/4.8% NaCl and 16% PEG 1.5 kDa/without NaCl, obtaining purification factors (PF) of 1.37 and 1.21 times and recovery (R) of 49 and 59%, respectively. However, for the enzymes PME and PMGL were of 4.8 and 4.7 fold and 478 and 241%, respectively. When used ATPS system - PEG/sodium citrate the best PF were of 2.4, 7.85 and 5.7 and R of 100, 331 and 239% for exo-PG, PME and PMGL, respectively. The ATPS system is an alternative and efficient method for the recovery and/or purification of pectinases. This work aimed to study the purification of pectinases by aqueous two-phase systems (ATPS). The crude enzymatic extract was produced by Aspergillus niger ATCC 9642 and contained exo-polygalacturonase (exo-PG), pectinmethylesterase (PME) and pectin lyase (PMGL). The ATPS systems tested consisted in the combinations of polyethylene glycol (PEG) and potassium phosphate and sodium citrate, alcohol (ethanol, n-propanol and isopropanol) and salt (ammonium sulfate, potassium phosphate and sodium citrate). The experiments showed higher recoveries using ATPS system - PEG/phosphate for the exo-PG were using 16% PEG 4.0 kDa/4.8% NaCl and 16% PEG 1.5 kDa/without NaCl, obtaining purification factors (PF) of 1.37 and 1.21 times and recovery (R) of 49 and 59%, respectively. However, for the enzymes PME and PMGL were of 4.8 and 4.7 fold and 478 and 241%, respectively. When used ATPS system - PEG/sodium citrate the best PF were of 2.4, 7.85 and 5.7 and R of 100, 331 and 239% for exo-PG, PME and PMGL, respectively. The ATPS system is an alternative and efficient method for the recovery and/or purification of pectinases. This work aimed to study the purification of pectinases by aqueous two-phase systems (ATPS). The crude enzymatic extract was produced by Aspergillus niger ATCC 9642 and contained exo-polygalacturonase (exo-PG), pectinmethylesterase (PME) and pectin lyase (PMGL). The ATPS systems tested consisted in the combinations of polyethylene glycol (PEG) and potassium phosphate and sodium citrate, alcohol (ethanol, n-propanol and isopropanol) and salt (ammonium sulfate, potassium phosphate and sodium citrate). The experiments showed higher recoveries using ATPS system - PEG/phosphate for the exo-PG were using 16% PEG 4.0 kDa/4.8% NaCl and 16% PEG 1.5 kDa/without NaCl, obtaining purification factors (PF) of 1.37 and 1.21 times and recovery (R) of 49 and 59%, respectively. However, for the enzymes PME and PMGL were of 4.8 and 4.7 fold and 478 and 241%, respectively. When used ATPS system - PEG/sodium citrate the best PF were of 2.4, 7.85 and 5.7 and R of 100, 331 and 239% for exo-PG, PME and PMGL, respectively. The ATPS system is an alternative and efficient method for the recovery and/or purification of pectinases

    Results from the seismological component of CAT/SCAN, the Calabria-Apennine Tyrrhenian/Subduction-Collision-Accretion-Network

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    The Calabrian Arc is the final remnant of a Western Mediterranean microplate driven by rollback. The Calabrian-Apennine-Tyrrhenian/Subduction-Collision-Accretion Seismic Network (CAT/SCAN) was a passive seismic experiment to study of the Calabrian Arc and its transition to the southern Apennines. The follow up Calabrian Arc project added a multidisciplinary (seismology, geology, geomorphology, geochronology, GPS, etc.) approach to better understand the tectonics of southern Italy imaged by the CAT/SCAN experiment. Here we focus on the seismological results of the two projects. The CAT/SCAN land deployment consisted of three phases. The initial phase included an array of 39 broadband seismometers onshore, deployed during the winter of 2003/4. In September 2004, the array was reduced and in April 2005, the array was reduced once again. The field deployment was completed in October 2005. Offshore, 12 broadband Ocean Bottom Seismometers (OBSs) were deployed in the beginning of October 2004. However, only 1 was recovered normally while several others were recovered after being disturbed by trawling. The experiment goal was to determine the structure of the Calabrian subduction and southern Apennine collision systems and the structure of the transition from oceanic subduction in Calabria to continental collision in the southern Apennines.Published7922T. Tettonica attivaN/A or not JCRrestricte

    Ambient Seismic Noise Image of the Structurally Controlled Heat and Fluid Feeder Pathway at Campi Flegrei Caldera

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    The TIDES-COST Action (STSM-ES1401-34011) provided a travel grant to framework the research project. The Japan Society for the Promotion of Science - Short-Term Fellowship (JSPS/OF215/022) financed the work, undertaken at Tohoku University and concluded at the University of Aberdeen. We thank Giuseppe Vilardo and Eliana Bellucci Sessa for providing the geomorphological maps, and Simona Petrosino and Paola Cusano for the P- and S-wave pickings used to localise the seismicity. Informal revisions from Guido Ventura, Nick Rawlinson and Chris Kilburn helped us improving the analyses and interpretation, respectively. We acknowledge the help of Naveed Khan in parallelising the codes and two anonymous reviewers who improved the analysis, interpretation, and readibility with their comments. All data to reproduce the maps can be downloaded from the World Data Center PANGAEA data repository, permanent link https://doi.pangaea.de/10.1594/PANGAEA.890238.Peer reviewedPublisher PD

    A quality metric for homology modeling: the H-factor

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    <p>Abstract</p> <p>Background</p> <p>The analysis of protein structures provides fundamental insight into most biochemical functions and consequently into the cause and possible treatment of diseases. As the structures of most known proteins cannot be solved experimentally for technical or sometimes simply for time constraints, <it>in silico </it>protein structure prediction is expected to step in and generate a more complete picture of the protein structure universe. Molecular modeling of protein structures is a fast growing field and tremendous works have been done since the publication of the very first model. The growth of modeling techniques and more specifically of those that rely on the existing experimental knowledge of protein structures is intimately linked to the developments of high resolution, experimental techniques such as NMR, X-ray crystallography and electron microscopy. This strong connection between experimental and <it>in silico </it>methods is however not devoid of criticisms and concerns among modelers as well as among experimentalists.</p> <p>Results</p> <p>In this paper, we focus on homology-modeling and more specifically, we review how it is perceived by the structural biology community and what can be done to impress on the experimentalists that it can be a valuable resource to them. We review the common practices and provide a set of guidelines for building better models. For that purpose, we introduce the H-factor, a new indicator for assessing the quality of homology models, mimicking the R-factor in X-ray crystallography. The methods for computing the H-factor is fully described and validated on a series of test cases.</p> <p>Conclusions</p> <p>We have developed a web service for computing the H-factor for models of a protein structure. This service is freely accessible at <url>http://koehllab.genomecenter.ucdavis.edu/toolkit/h-factor</url>.</p
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