Prevent in Cloud Liferay Edition

Este proyecto de fin de carrera consiste en el desarrollo de una aplicación que sirva para gestionar la prevención de riesgos laborales a través de la herramienta Liferay. Gracias a ella toda la información quedará alojada en la nube.

Shock-Induced Dust Cloud Over a Deposit Layer of Fine Particles

The present paper investigates particle density pro les of a dust cloud induced by a normal shock wave moving at a constant speed along a at surface deposited with ne particles. In shock-fixxed coordinates, numerical simulation of ow structures of the carrier- and dispersed- phases was performed for the M = 2 case. The neness and non-uniformity of the particle size are taken into account and their effcts on the dust cloud are discussed in detail.

Assessment of cobia, Rachycentron canadum, in the waters of the U.S. Gulf of Mexico

This assessment applies to cobia (Rachycentron canadum) located in the territorial waters of the U.S. Gulf of Mexico. Separation of the Gulf of Mexico and Atlantic Ocean is defined by the seaward extension of the Dade/Monroe county line in south Florida. Mixing of fish between the Atlantic and Gulf of Mexico occurs in the Florida Keys during winter months. Cobia annually migrate north in early spring in the Gulf to spawning grounds in the northern Gulf of Mexico, returning to the Florida Keys by winter. Catches of cobia in the Gulf of Mexico are dominated by recreational landings, accounting for nearly 90% of the total. Since 1980, the landings of cobia in the recreational fishery have remained fairly stable at around 400-600 mt with a slight peak of 1,014 mt in 1997. The recreational fishery was estimated to have landed 471 mt in 2000. The landings from the commercial fishery have shown a steady increase from 45 mt in 1980 to a peak of 120 mt in 1994, followed by a decline to 62 mt in 2000. The previous assessment of cobia occurred in 1996 using a virtual population analysis (VPA) model. For this analysis a surplus-production model (ASPIC) and a forward-projecting, age-structured population model programmed in the AD Model Builder (ADMB) software were applied to cobia data from the Gulf of Mexico. The primary data consisted of four catch-per-unit-effort (CPUE) indices derived from the Marine Recreational Fisheries Statistics Survey (MRFSS) (1981-1999), Southeast region headboat survey (1986-1999), Texas creel survey (1983-1999), and shrimp bycatch estimates (1980-1999). Length samples were available from the commercial (1983-2000) and recreational (1981-2000) fisheries. The ASPIC model applied to the cobia data provided unsatisfactory results. The ADMB model fit described the observed length composition data and fishery landings fairly well based on graphical examination of model residuals. The CPUE indices indicated some disagreement for various years, but the model fit an overall increasing trend from 1992-1997 for the MRFSS, headboat, and Texas creel indices. The shrimp bycatch CPUE was treated as a recruitment index in the model. The fit to these data followed an upward trend in recruitment from 1988-1997, but did not fit the 1994-1997 data points very well. This was likely the result of conflicting information from other data sources. Natural mortality (M) for cobia is unknown. As a result, a range of values for M from 0.2-0.4, based on longevity and growth parameters, were selected for use in the age-structured model. The choice of natural mortality appears to greatly influence the perceived status of the population. Population status as measured by spawning stock biomass in the last year relative to the value at maximum sustainable yield (SSB2000/SSBMSY), spawning stock biomass in the last year relative to virgin spawning stock biomass (SSB2000/S0), and static spawning stock biomass per recruit (SSBR) all indicate the population is either depleted, near MSY, or well above MSY depending on the choice of M. The variance estimates for these benchmarks are very large and in most cases ranges from depleted to very healthy status. The only statement that can be made with any degree of certainty about cobia in the Gulf of Mexico is that the population has increased since the 1980s. (PDF contains 61 pages)

PAnalyzer: A software tool for protein inference in shotgun proteomics

Background Protein inference from peptide identifications in shotgun proteomics must deal with ambiguities that arise due to the presence of peptides shared between different proteins, which is common in higher eukaryotes. Recently data independent acquisition (DIA) approaches have emerged as an alternative to the traditional data dependent acquisition (DDA) in shotgun proteomics experiments. MSE is the term used to name one of the DIA approaches used in QTOF instruments. MSE data require specialized software to process acquired spectra and to perform peptide and protein identifications. However the software available at the moment does not group the identified proteins in a transparent way by taking into account peptide evidence categories. Furthermore the inspection, comparison and report of the obtained results require tedious manual intervention. Here we report a software tool to address these limitations for MSE data. Results In this paper we present PAnalyzer, a software tool focused on the protein inference process of shotgun proteomics. Our approach considers all the identified proteins and groups them when necessary indicating their confidence using different evidence categories. PAnalyzer can read protein identification files in the XML output format of the ProteinLynx Global Server (PLGS) software provided by Waters Corporation for their MSE data, and also in the mzIdentML format recently standardized by HUPO-PSI. Multiple files can also be read simultaneously and are considered as technical replicates. Results are saved to CSV, HTML and mzIdentML (in the case of a single mzIdentML input file) files. An MSE analysis of a real sample is presented to compare the results of PAnalyzer and ProteinLynx Global Server. Conclusions We present a software tool to deal with the ambiguities that arise in the protein inference process. Key contributions are support for MSE data analysis by ProteinLynx Global Server and technical replicates integration. PAnalyzer is an easy to use multiplatform and free software tool.

Cloud computing for research - final report

Curtis+Cartwright Consulting Ltd, working with the University of Surrey and Professor Charles Oppenheim, has been commissioned by Jisc to investigate Cloud Computing for Research. This document is the final report, and is accompanied by a briefing paper which provides advice targeted at researchers.

Review of the environmental and organisational implications of cloud computing in higher and further education

The review of the environmental and organisational implications of cloud computing in higher and further education was commissioned by Jisc as part of its green ICT programme.

FleSSR project: Sustainable business models for community cloud infrastructure in the UK higher education sector

Cloud-based infrastructure essentially comprises two offerings, cloud-based compute and cloud-based storage. These are perhaps best typified for most people by the two main components of the Amazon Web Services (AWS)1 public cloud offer, the Elastic Compute Cloud (EC2)2 and the Simple Storage Service (S3)3, though, of course, there are many other related services offered by Amazon and many other providers of similar public cloud infrastructure across the Internet.