113 resultados para causal discovery


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Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.

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Herein we report the discovery and SAR of a novel series of non-MPEP site metabotropic glutamate receptor 5 (mGlu(5)) positive allosteric modulators (PAMs) based on an aryl glycine sulfonamide scaffold. This series represents a rare non-MPEP site mGlu(5) PAM chemotype.

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Burkholderia cenocepacia is a Gram-negative aerobic bacterium that belongs to a group of opportunistic pathogens displaying diverse environmental and pathogenic lifestyles. B. cenocepacia is known for its ability to cause lung infections in people with cystic fibrosis and it possesses a large 8?Mb multireplicon genome encoding a wide array of pathogenicity and fitness genes. Transcriptomic profiling across nine growth conditions was performed to identify the global gene expression changes made when B. cenocepacia changes niches from an environmental lifestyle to infection. In comparison to exponential growth, the results demonstrated that B. cenocepacia changes expression of over one-quarter of its genome during conditions of growth arrest, stationary phase and surprisingly, under reduced oxygen concentrations (6% instead of 20.9% normal atmospheric conditions). Multiple virulence factors are upregulated during these growth arrest conditions. A unique discovery from the comparative expression analysis was the identification of a distinct, co-regulated 50-gene cluster that was significantly upregulated during growth under low oxygen conditions. This gene cluster was designated the low-oxygen-activated (lxa) locus and encodes six universal stress proteins and proteins predicted to be involved in metabolism, transport, electron transfer and regulation. Deletion of the lxa locus resulted in B. cenocepacia mutants with aerobic growth deficiencies in minimal medium and compromised viability after prolonged incubation in the absence of oxygen. In summary, transcriptomic profiling of B. cenocepacia revealed an unexpected ability of aerobic Burkholderia to persist in the absence of oxygen and identified the novel lxa locus as key determinant of this important ecophysiological trait.

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A boronic acid moiety was found to be a critical pharmacophore for enhanced in vitro potency against wild type hepatitis C replicons and known clinical polymorphic and resistant HCV mutant replicons. The synthesis, optimization, and structure-activity relationships associated with inhibition of HCV replication in a sub-genomic replication system for a series of non-nucleoside boron-containing HCV RNA-Dependent RNA Polymerase (NS5B) inhibitors are described. A summary of the discovery of GSK5852 (3), a molecule which entered clinical trials in subjects infected with HCV in 2011, is included.

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This paper identifies and analyses the means of accessing and collecting foreign-based evidence in transnational antitrust cases. It makes an original contribution to the existing scholarship by critically addressing the available mechanisms of judicial cooperation, the possibility of reliance on domestic discovery in transnational context, as well as the existing instruments allowing for cooperation between antitrust agencies. It identifies the shortcomings of the current regulatory framework and points out to the existing good practices in those jurisdictions which provide their antitrust agencies with more leeway in sharing confidential information with foreign counterparts.

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We report the discovery of two transiting hot Jupiters, WASP-65b (Mpl = 1.55 ± 0.16 MJ; Rpl = 1.11 ± 0.06 RJ), and WASP-75b (Mpl = 1.07 ± 0.05 MJ; Rpl = 1.27 ± 0.05 RJ). They orbit their host star every ∼2.311, and ∼2.484 days, respectively. The planet host WASP-65 is a G6 star (Teff = 5600 K, [Fe/H] = −0.07 ± 0.07, age 8 Gyr); WASP-75 is an F9 star (Teff = 6100 K, [Fe/H] = 0.07 ± 0.09, age ∼ 3 Gyr). WASP-65b is one of the densest known exoplanets in the mass range 0.1 and 2.0 MJ (ρpl = 1.13 ± 0.08 ρJ), a mass range where a large fraction of planets are found to be inflated with respect to theoretical planet models. WASP-65b is one of only a handful of planets with masses of ∼1.5 MJ, a mass regime surprisingly underrepresented among the currently known hot Jupiters. The radius of WASP-75b is slightly inflated (10%) as compared to theoretical planet models with no core, and has a density similar to that of Saturn (ρpl = 0.52 ± 0.06 ρJ). Key words. planetary systems – stars: individual:

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Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

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The operant learning theory account of behaviors of clinical significance in people with intellectual disability (ID) has dominated the field for nearly 50 years. However, in the last two decades, there has been a substantial increase in published research that describes the behavioral phenotypes of genetic disorders and shows that behaviors such as self-injury and aggression are more common in some syndromes than might be expected given group characteristics. These cross-syndrome differences in prevalence warrant explanation, not least because this observation challenges an exclusively operant learning theory account. To explore this possible conflict between theoretical account and empirical observation, we describe the genetic cause and physical, social, cognitive and behavioral phenotypes of four disorders associated with ID (Angleman, Cornelia de Lange, Prader-Willi and Smith-Magenis syndromes) and focus on the behaviors of clinical significance in each syndrome. For each syndrome we then describe a model of the interactions between physical characteristics, cognitive and motivational endophenotypes and environmental factors (including operant reinforcement) to account for the resultant behavioral phenotype. In each syndrome it is possible to identify pathways from gene to physical phenotype to cognitive or motivational endophenotype to behavior to environment and back to behavior. We identify the implications of these models for responsive and early intervention and the challenges for research in this area. We identify a pressing need for meaningful dialog between different disciplines to construct better informed models that can incorporate all relevant and robust empirical evidence.