927 resultados para Computational Catastrophes
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This paper reviews the methods, benefits and challenges associated with the adoption and translation of computational fluid dynamics (CFD) modelling within cardiovascular medicine. CFD, a specialist area of mathematics and a branch of fluid mechanics, is used routinely in a diverse range of safety-critical engineering systems, which increasingly is being applied to the cardiovascular system. By facilitating rapid, economical, low-risk prototyping, CFD modelling has already revolutionised research and development of devices such as stents, valve prostheses, and ventricular assist devices. Combined with cardiovascular imaging, CFD simulation enables detailed characterisation of complex physiological pressure and flow fields and the computation of metrics which cannot be directly measured, for example, wall shear stress. CFD models are now being translated into clinical tools for physicians to use across the spectrum of coronary, valvular, congenital, myocardial and peripheral vascular diseases. CFD modelling is apposite for minimally-invasive patient assessment. Patient-specific (incorporating data unique to the individual) and multi-scale (combining models of different length- and time-scales) modelling enables individualised risk prediction and virtual treatment planning. This represents a significant departure from traditional dependence upon registry-based, population-averaged data. Model integration is progressively moving towards 'digital patient' or 'virtual physiological human' representations. When combined with population-scale numerical models, these models have the potential to reduce the cost, time and risk associated with clinical trials. The adoption of CFD modelling signals a new era in cardiovascular medicine. While potentially highly beneficial, a number of academic and commercial groups are addressing the associated methodological, regulatory, education- and service-related challenges.
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This article centers on the computational performance of the continuous and discontinuous Galerkin time stepping schemes for general first-order initial value problems in R n , with continuous nonlinearities. We briefly review a recent existence result for discrete solutions from [6], and provide a numerical comparison of the two time discretization methods.
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BACKGROUND Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with uncertain risk for invasive progression. Usual care (UC) for DCIS consists of treatment upon diagnosis, thus potentially overtreating patients with low propensity for progression. One strategy to reduce overtreatment is active surveillance (AS), whereby DCIS is treated only upon detection of invasive disease. Our goal was to perform a quantitative evaluation of outcomes following an AS strategy for DCIS. METHODS Age-stratified, 10-year disease-specific cumulative mortality (DSCM) for AS was calculated using a computational risk projection model based upon published estimates for natural history parameters, and Surveillance, Epidemiology, and End Results data for outcomes. AS projections were compared with the DSCM for patients who received UC. To quantify the propagation of parameter uncertainty, a 95% projection range (PR) was computed, and sensitivity analyses were performed. RESULTS Under the assumption that AS cannot outperform UC, the projected median differences in 10-year DSCM between AS and UC when diagnosed at ages 40, 55, and 70 years were 2.6% (PR = 1.4%-5.1%), 1.5% (PR = 0.5%-3.5%), and 0.6% (PR = 0.0%-2.4), respectively. Corresponding median numbers of patients needed to treat to avert one breast cancer death were 38.3 (PR = 19.7-69.9), 67.3 (PR = 28.7-211.4), and 157.2 (PR = 41.1-3872.8), respectively. Sensitivity analyses showed that the parameter with greatest impact on DSCM was the probability of understaging invasive cancer at diagnosis. CONCLUSION AS could be a viable management strategy for carefully selected DCIS patients, particularly among older age groups and those with substantial competing mortality risks. The effectiveness of AS could be markedly improved by reducing the rate of understaging.
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The study investigates the role of credit risk in a continuous time stochastic asset allocation model, since the traditional dynamic framework does not provide credit risk flexibility. The general model of the study extends the traditional dynamic efficiency framework by explicitly deriving the optimal value function for the infinite horizon stochastic control problem via a weighted volatility measure of market and credit risk. The model's optimal strategy was then compared to that obtained from a benchmark Markowitz-type dynamic optimization framework to determine which specification adequately reflects the optimal terminal investment returns and strategy under credit and market risks. The paper shows that an investor's optimal terminal return is lower than typically indicated under the traditional mean-variance framework during periods of elevated credit risk. Hence I conclude that, while the traditional dynamic mean-variance approach may indicate the ideal, in the presence of credit-risk it does not accurately reflect the observed optimal returns, terminal wealth and portfolio selection strategies.
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The cytochromes P450 comprise a superfamily of heme-containing mono-oxygenases. These enzymes metabolize numerous xenobiotics, but also play a role in metabolism of endogenous compounds. The P450 1A1 enzyme generally metabolizes polycyclic aromatic hydrocarbons, and its expression can be induced by aryl hydrocarbon receptor (AhR) activation. CYP1A1 is an exception to the generality that the majority of CYPs demonstrate highest expression in liver; CYP1Al is present in numerous extrahepatic tissues, including brain. This P450 has been observed in two forms, wildtype (WT) and brain variant (BV), arising from alternatively spliced mRNA transcripts. The CYP1A1 BV mRNA presented an exon deletion and was detected in human brain but not liver tissue of the same individuals. ^ Quantitative PCR analyses were performed to determine CYP1A1 WT and BV transcript expression levels in normal, bipolar disorder or schizophrenic groups. In our samples, we show that CYP1A1 BV mRNA, when present, is found alongside the full-length form. Furthermore, we demonstrate a significant decrease in expression of CYP1A1 in patients with bipolar disorder or schizophrenia. The expression level was not influenced by post-mortem interval, tissue pH, age, tobacco use, or lifetime antipsychotic medication load. ^ There is no indication of increased brain CYP1A1 expression in normal smokers versus non-smokers in these samples. We observed slightly increased CYP1A1 expression only in bipolar and schizophrenic smokers versus non-smokers. This may be indicative of complex interactions between neuronal chemical environments and AhR-mediated CYP1A1 induction in brain. ^ Structural homology modeling demonstrated that P450 1A1 BV has several alterations to positions/orientations of substrate recognition site residues compared to the WT isoform. Automated substrate docking was employed to investigate the potential binding of neurological signaling molecules and neurotropic drugs, as well as to differentiate specificities of the two P450 1A1 isoforms. We consistently observed that the BV isoform produced energetically favorable substrate dockings in orientations not observed for the same substrate in the WT isoform. These results demonstrated that structural differences, namely an expanded substrate access channel and active site, confer greater capacity for unique compound docking positions suggesting a metabolic profile distinct from the wildtype form for these test compounds. ^
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The Geographical Simulation Model developed by IDE-JETRO (IDE-GSM) is a computer simulation model based on spatial economics. IDE-GSM enables us to predict the economic impacts of various trade and transport facilitation measures. Here, we mainly compare the prioritized projects of the Master Plan on ASEAN Connectivity (MPAC) and the Comprehensive Asia Development Plan (CADP). MPAC focus on specific hard or soft infrastructure projects that connect one ASEAN member state to another while the CADP emphasizes the importance of economic corridors or linkages between a large cluster and another cluster. As compared with MPAC projects, the simulation analysis shows that CADP projects have much larger positive impacts on ASEAN countries.
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In this paper, several computational schemes are presented for the optimal tuning of the global behavior of nonlinear dynamical sys- tems. Specifically, the maximization of the size of domains of attraction associated with invariants in parametrized dynamical sys- tems is addressed. Cell Mapping (CM) tech- niques are used to estimate the size of the domains, and such size is then maximized via different optimization tools. First, a ge- netic algorithm is tested whose performance shows to be good for determining global maxima at the expense of high computa- tional cost. Secondly, an iterative scheme based on a Stochastic Approximation proce- dure (the Kiefer-Wolfowitz algorithm) is eval- uated showing acceptable performance at low cost. Finally, several schemes combining neu- ral network based estimations and optimiza- tion procedures are addressed with promising results. The performance of the methods is illus- trated with two applications: first on the well-known van der Pol equation with stan- dard parametrization, and second the tuning of a controller for saturated systems.
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A low complex but highly-efficient object counter algorithm is presented that can be embedded in hardware with a low computational power. This is achieved by a novel soft-data association strategy that can handle multimodal distributions.
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Although several profiling techniques for identifying performance bottlenecks in logic programs have been developed, they are generally not automatic and in most cases they do not provide enough information for identifying the root causes of such bottlenecks. This complicates using their results for guiding performance improvement. We present a profiling method and tool that provides such explanations. Our profiler associates cost centers to certain program elements and can measure different types of resource-related properties that affect performance, preserving the precedence of cost centers in the cali graph. It includes an automatic method for detecting procedures that are performance bottlenecks. The profiling tool has been integrated in a previously developed run-time checking framework to allow verification of certain properties when they cannot be verified statically. The approach allows checking global computational properties which require complex instrumentation tracking information about previous execution states, such as, e.g., that the execution time accumulated by a given procedure is not greater than a given bound. We have built a prototype implementation, integrated it in the Ciao/CiaoPP system and successfully applied it to performance improvement, automatic optimization (e.g., resource-aware specialization of programs), run-time checking, and debugging of global computational properties (e.g., resource usage) in Prolog programs.
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Information about the computational cost of programs is potentially useful for a variety of purposes, including selecting among different algorithms, guiding program transformations, in granularity control and mapping decisions in parallelizing compilers, and query optimization in deductive databases. Cost analysis of logic programs is complicated by nondeterminism: on the one hand, procedures can return múltiple Solutions, making it necessary to estímate the number of solutions in order to give nontrivial upper bound cost estimates; on the other hand, the possibility of failure has to be taken into account while estimating lower bounds. Here we discuss techniques to address these problems to some extent.
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This paper presents some brief considerations on the role of Computational Logic in the construction of Artificial Intelligence systems and in programming in general. It does not address how the many problems in AI can be solved but, rather more modestly, tries to point out some advantages of Computational Logic as a tool for the AI scientist in his quest. It addresses the interaction between declarative and procedural views of programs (deduction and action), the impact of the intrinsic limitations of logic, the relationship with other apparently competing computational paradigms, and finally discusses implementation-related issues, such as the efficiency of current implementations and their capability for efficiently exploiting existing and future sequential and parallel hardware. The purpose of the discussion is in no way to present Computational Logic as the unique overall vehicle for the development of intelligent systems (in the firm belief that such a panacea is yet to be found) but rather to stress its strengths in providing reasonable solutions to several aspects of the task.
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We discuss from a practical point of view a number of issues involved in writing Internet and WWW applications using LP/CLP systems. We describe Pd_l_oW, a public-domain Internet and WWW programming library for LP/CLP systems which we argüe significantly simplifies the process of writing such applications. Pd_l_oW provides facilities for generating HTML structured documents, producing HTML forms, writing form handlers, accessing and parsing WWW documents, and accessing code posted at HTTP addresses. We also describe the architecture of some application classes, using a high-level model of client-server interaction, active modules. We then propose an architecture for automatic LP/CLP code downloading for local execution, using generic browsers. Finally, we also provide an overview of related work on the topic. The PiLLoW library has been developed in the context of the &- Prolog and CIAO systems, but it has been adapted to a number of popular LP/CLP systems, supporting most of its functionality.
Resumo:
We discuss from a practical point of view a number of issues involved in writing Internet and WWW applications using LP/CLP systems. We describe PiLLoW, an Internet and WWW programming library for LP/CLP systems which we argüe significantly simplifies the process of writing such applications. PiLLoW provides facilities for generating HTML structured documents, producing HTML forms, writing form handlers, accessing and parsing WWW documents, and accessing code posted at HTTP addresses. We also describe the architecture of some application classes, using a high-level model of client-server interaction, active modules. Finally we describe an architecture for automatic LP/CLP code downloading for local execution, using generic browsers. The PiLLoW library has been developed in the context of the &-Prolog and CIAO systems, but it has been adapted to a number of popular LP/CLP systems, supporting most of its functionality.
Resumo:
Although several profiling techniques for identifying performance bottlenecks in logic programs have been developed, they are generally not automatic and in most cases they do not provide enough information for identifying the root causes of such bottlenecks. This complicates using their results for guiding performance improvement. We present a profiling method and tool that provides such explanations. Our profiler associates cost centers to certain program elements and can measure different types of resource-related properties that affect performance, preserving the precedence of cost centers in the call graph. It includes an automatic method for detecting procedures that are performance bottlenecks. The profiling tool has been integrated in a previously developed run-time checking framework to allow verification of certain properties when they cannot be verified statically. The approach allows checking global computational properties which require complex instrumentation tracking information about previous execution states, such as, e.g., that the execution time accumulated by a given procedure is not greater than a given bound. We have built a prototype implementation, integrated it in the Ciao/CiaoPP system and successfully applied it to performance improvement, automatic optimization (e.g., resource-aware specialization of programs), run-time checking, and debugging of global computational properties (e.g., resource usage) in Prolog programs.