Flow Annealed Importance Sampling Bootstrap

Normalizing flows are tractable density models that can approximate complicated target distributions, e.g. Boltzmann distributions of physical systems. However, current methods for training flows either suffer from mode-seeking behavior, use samples from the target generated beforehand by expensive MCMC simulations, or use stochastic losses that have very high variance. To avoid these problems, we augment flows with annealed importance sampling (AIS) and minimize the mass covering $\alpha$-divergence with $\alpha=2$, which minimizes importance weight variance. Our method, Flow AIS Bootstrap (FAB), uses AIS to generate samples in regions where the flow is a poor approximation of the target, facilitating the discovery of new modes. We target with AIS the minimum variance distribution for the estimation of the $\alpha$-divergence via importance sampling. We also use a prioritized buffer to store and reuse AIS samples. These two features significantly improve FAB's performance. We apply FAB to complex multimodal targets and show that we can approximate them very accurately where previous methods fail. To the best of our knowledge, we are the first to learn the Boltzmann distribution of the alanine dipeptide molecule using only the unnormalized target density and without access to samples generated via Molecular Dynamics (MD) simulations: FAB produces better results than training via maximum likelihood on MD samples while using 100 times fewer target evaluations. After reweighting samples with importance weights, we obtain unbiased histograms of dihedral angles that are almost identical to the ground truth ones

Rewiring strategies for changing environments

A typical pervasive application executes in a changing environment: people, computing resources, software services and network connections come and go continuously. A robust pervasive application needs adapt to this changing context as long as there is an appropriate rewiring strategy that guarantees correct behavior. We combine the MERODE modeling methodology with the ReWiRe framework for creating interactive pervasive applications that can cope with changing environments. The core of our approach is a consistent environment model, which is essential to create (re)configurable context-aware pervasive applications. We aggregate different ontologies that provide the required semantics to describe almost any target environment. We present a case study that shows a interactive pervasive application for media access that incorporates parental control on media content and can migrate between devices. The application builds upon models of the run-time environment represented as system states for dedicated rewiring strategies

Upregulation of ERK1/2-eNOS via AT2 Receptors Decreases the Contractile Response to Angiotensin II in Resistance Mesenteric Arteries from Obese Rats

It has been clearly established that mitogen-activated protein kinases (MAPKS) are important mediators of angiotensin II (Ang II) signaling via AT1 receptors in the vasculature. However, evidence for a role of these kinases in changes of Ang II-induced vasoconstriction in obesity is still lacking. Here we sought to determine whether vascular MAPKs are differentially activated by Ang II in obese animals. the role of AT2 receptors was also evaluated. Male monosodium glutamate-induced obese (obese) and non-obese Wistar rats (control) were used. the circulating concentrations of Ang I and Ang II, determined by HPLC, were increased in obese rats. Ang II-induced isometric contraction was decreased in endothelium-intact resistance mesenteric arteries from obese compared with control rats and exhibited a retarded AT1 receptor antagonist response. Blocking of AT2 receptors and inhibition of either endothelial nitric oxide synthase (eNOS) or extracellular signal-regulated protein kinases 1 and 2 (ERK1/2) restored Ang II-induced contraction in obese rats. Western blot analysis revealed increased protein expression of AT2 receptors in arteries from obese rats. Basal and Ang II-induced ERK1/2 phosphorylation was also increased in obese rats. Blockade of either AT1 or AT2 receptors corrected the increased ERK1/2 phosphorylation in arteries from obese rats to levels observed in control preparations. Phosphorylation of eNOS was increased in obese rats. Incubation with the ERK1/2 inhibitor before Ang II stimulation did not affect eNOS phosphorylation in control rats; however, it corrected the increased phosphorylation of eNOS in obese rats. These results clearly demonstrate that enhanced AT2 receptor and ERK1/2-induced, NO-mediated vasodilation reduces Ang II-induced contraction in an endothelium-dependent manner in obese rats.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Univ São Paulo, Inst Biomed Sci, Dept Pharmacol, São Paulo, BrazilUniv Fed Goias, Div Cardiovasc Physiol, Dept Biol Sci, Jatai, BrazilUniversidade Federal de São Paulo, Div Nephrol, Dept Med, Escola Paulista Med, São Paulo, BrazilUniversidade Federal de São Paulo, Div Nephrol, Dept Med, Escola Paulista Med, São Paulo, BrazilFAPESP: 2007/58311-0FAPESP: 2008/51622-3FAPESP: 2010/03642-5Web of Scienc

Day-ahead allocation of operation reserve in composite power systems with large-scale centralized wind farms

This paper focuses on the day-ahead allocation of operation reserve considering wind power prediction error and network transmission constraints in a composite power system. A two-level model that solves the allocation problem is presented. The upper model allocates operation reserve among subsystems from the economic point of view. In the upper model, transmission constraints of tielines are formulated to represent limited reserve support from the neighboring system due to wind power fluctuation. The lower model evaluates the system on the reserve schedule from the reliability point of view. In the lower model, the reliability evaluation of composite power system is performed by using Monte Carlo simulation in a multi-area system. Wind power prediction errors and tieline constraints are incorporated. The reserve requirements in the upper model are iteratively adjusted by the resulting reliability indices from the lower model. Thus, the reserve allocation is gradually optimized until the system achieves the balance between reliability and economy. A modified two-area reliability test system (RTS) is analyzed to demonstrate the validity of the method.This work was supported by National Natural Science Foundation of China (No. 51277141) and National High Technology Research and Development Program of China (863 Program) (No. 2011AA05A103)