3 resultados para Fallback path
em Duke University
Resumo:
Precision medicine is an emerging approach to disease treatment and prevention that considers variability in patient genes, environment, and lifestyle. However, little has been written about how such research impacts emergency care. Recent advances in analytical techniques have made it possible to characterize patients in a more comprehensive and sophisticated fashion at the molecular level, promising highly individualized diagnosis and treatment. Among these techniques are various systematic molecular phenotyping analyses (e.g., genomics, transcriptomics, proteomics, and metabolomics). Although a number of emergency physicians use such techniques in their research, widespread discussion of these approaches has been lacking in the emergency care literature and many emergency physicians may be unfamiliar with them. In this article, we briefly review the underpinnings of such studies, note how they already impact acute care, discuss areas in which they might soon be applied, and identify challenges in translation to the emergency department (ED). While such techniques hold much promise, it is unclear whether the obstacles to translating their findings to the ED will be overcome in the near future. Such obstacles include validation, cost, turnaround time, user interface, decision support, standardization, and adoption by end-users.
Resumo:
The Central American Free Trade Agreement (CAFTA) has been a mixed blessing for economic development. While exports to the US economy have increased, dependency may hinder economic growth if countries do not diversify or upgrade before temporary provisions expire. This article evaluates the impact of the temporary Tariff Preference Levels (TPLs) granted to Nicaragua under CAFTA and the consequences of TPL expiration. Using trade statistics, country- and firm-level data from Nicaragua’s National Free Zones Commission (CNZF) and data from field research, we estimate Nicaragua’s apparel sector will contract as much as 30–40% after TPLs expire. Our analysis underscores how rules of origin and firm nationality affect where and how companies do business, and in so doing, often constrain sustainable export growth.
Resumo:
Free energy calculations are a computational method for determining thermodynamic quantities, such as free energies of binding, via simulation.
Currently, due to computational and algorithmic limitations, free energy calculations are limited in scope.
In this work, we propose two methods for improving the efficiency of free energy calculations.
First, we expand the state space of alchemical intermediates, and show that this expansion enables us to calculate free energies along lower variance paths.
We use Q-learning, a reinforcement learning technique, to discover and optimize paths at low computational cost.
Second, we reduce the cost of sampling along a given path by using sequential Monte Carlo samplers.
We develop a new free energy estimator, pCrooks (pairwise Crooks), a variant on the Crooks fluctuation theorem (CFT), which enables decomposition of the variance of the free energy estimate for discrete paths, while retaining beneficial characteristics of CFT.
Combining these two advancements, we show that for some test models, optimal expanded-space paths have a nearly 80% reduction in variance relative to the standard path.
Additionally, our free energy estimator converges at a more consistent rate and on average 1.8 times faster when we enable path searching, even when the cost of path discovery and refinement is considered.