981 resultados para cluster as a service


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The College previously used the old Server Certificate Service and has now progressed to using the Janet Certificate Service. It has two particular uses for server certificates: one is to guarantee its Shibboleth  erver and the other is to guarantee another single sign on document management system employed by the College. JL

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Building trust between your website and users. JL

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Read about how the service has evolved and improved over the past four years. JL

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Executive Summary: A number of studies have shown that mobile, bottom-contact fishing gear (such as otter trawls) can alter seafloor habitats and associated biota. Considerably less is known about the recovery of these resources following such disturbances, though this information is critical for successful management. In part, this paucity of information can be attributed to the lack of access to adequate control sites – areas of the seafloor that are closed to fishing activity. Recent closures along the coast of central California provide an excellent opportunity to track the recovery of historically trawled areas and to compare recovery rates to adjacent areas that continue to be trawled. In June 2006 we initiated a multi-year study of the recovery of seafloor microhabitats and associated benthic fauna inside and outside two new Essential Fish Habitat (EFH) closures within the Cordell Bank and Gulf of the Farallones National Marine Sanctuaries. Study sites inside the EFH closure at Cordell Bank were located in historically active areas of fishing effort, which had not been trawled since 2003. Sites outside the EFH closure in the Gulf of Farallones were located in an area that continues to be actively trawled. All sites were located in unconsolidated sands at equivalent water depths. Video and still photographic data collected via a remotely operated vehicle (ROV) were used to quantify the abundance, richness, and diversity of microhabitats and epifaunal macro-invertebrates at recovering and actively trawled sites, while bottom grabs and conductivity/temperature/depth (CTD) casts were used to quantify infaunal diversity and to characterize local environmental conditions. Analysis of still photos found differences in common seafloor microhabitats between the recovering and actively trawled areas, while analysis of videographic data indicated that biogenic mound and biogenic depression microhabitats were significantly less abundant at trawled sites. Each of these features provides structure with which demersal fishes, across a wide range of size classes, have been observed to associate. Epifaunal macro-invertebrates were sparsely distributed and occurred in low numbers in both treatments. However, their total abundance was significantly different between treatments, which was attributable to lower densities at trawled sites. In addition, the dominant taxa were different between the two sites. Patchily-distributed buried brittle stars dominated the recovering site, and sea whips (Halipteris cf. willemoesi) were most numerous at the trawled site though they occurred in only five of ten transects. Numerical classification (cluster analysis) of the infaunal samples also revealed a clear difference between benthic assemblages in the recovering vs. trawled areas due to differences in the relative abundances of component species. There were no major differences in infaunal species richness, H′ diversity, or J′ evenness between recovering vs. trawled site groups. However, total infaunal abundance showed a significant difference attributable to much lower densities at trawled sites. This pattern was driven largely by the small oweniid polychaete Myriochele gracilis, which was the most abundant species in the overall study region though significantly less abundant at trawled sites. Other taxa that were significantly less abundant at trawled sites included the polychaete M. olgae and the polychaete family Terebellidae. In contrast, the thyasirid bivalve Axinopsida serricata and the polychaetes Spiophanes spp. (mostly S. duplex), Prionospio spp., and Scoloplos armiger all had significantly to near significantly higher abundances at trawled sites. As a result of such contrasting species patterns, there also was a significant difference in the overall dominance structure of infaunal assemblages between the two treatments. It is suggested that the observed biological patterns were the result of trawling impacts and varying levels of recovery due to the difference in trawling status between the two areas. The EFH closure was established in June 2006, within a month of when sampling was conducted for the present study, however, the stations within this closure area are at sites that actually have experienced little trawling since 2003, based on National Marine Fishery Service trawl records. Thus, the three-year period would be sufficient time for some post-trawling changes to have occurred. Other results from this study (e.g., similarly moderate numbers of infaunal species in both areas that are lower than values recorded elsewhere in comparable habitats along the California continental shelf) also indicate that recovery within the closure area is not yet complete. Additional sampling is needed to evaluate subsequent recovery trends and persistence of effects. Furthermore, to date, the study has been limited to unconsolidated substrates. Ultimately, the goal of this project is to characterize the recovery trajectories of a wide spectrum of seafloor habitats and communities and to link that recovery to the dynamics of exploited marine fishes. (PDF has 48 pages.)

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We present a scheme to generate clusters submodels with stage ordering from a (symmetric or a nonsymmetric one) multistage stochastic mixed integer optimization model using break stage. We consider a stochastic model in compact representation and MPS format with a known scenario tree. The cluster submodels are built by storing first the 0-1 the variables, stage by stage, and then the continuous ones, also stage by stage. A C++ experimental code has been implemented for reordering the stochastic model as well as the cluster decomposition after the relaxation of the non-anticipativiy constraints until the so-called breakstage. The computational experience shows better performance of the stage ordering in terms of elapsed time in a randomly generated testbed of multistage stochastic mixed integer problems.

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This is a version of the Jisc ‘Six Elements of Digital Capabilities’ model, specifically to support Jisc’s members in the area of Digital Leadership. It is one example of the base model being used in a particular context and is not meant to be definitive.

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