Inferring the eccentricity distribution

Standard maximum-likelihood estimators for binary-star and exoplanet eccentricities are biased high, in the sense that the estimated eccentricity tends to be larger than the true eccentricity. As with most non-trivial observables, a simple histogram of estimated eccentricities is not a good estimate of the true eccentricity distribution. Here we develop and test a hierarchical probabilistic method for performing the relevant meta-analysis, that is, inferring the true eccentricity distribution, taking as input the likelihood functions for the individual-star eccentricities, or samplings of the posterior probability distributions for the eccentricities (under a given, uninformative prior). The method is a simple implementation of a hierarchical Bayesian model; it can also be seen as a kind of heteroscedastic deconvolution. It can be applied to any quantity measured with finite precision--other orbital parameters, or indeed any astronomical measurements of any kind, including magnitudes, parallaxes, or photometric redshifts--so long as the measurements have been communicated as a likelihood function or a posterior sampling.Comment: Ap

Tracing the Hercules stream around the Galaxy

It has been proposed that the Hercules stream, a group of co-moving stars in the Solar neighborhood offset from the bulk of the velocity distribution, is the result of resonant interactions between stars in the outer disk and the Galactic bar. So far it has only been seen in the immediate Solar neighborhood, but the resonance model makes a prediction over a large fraction of the Galactic disk. I predict the distribution of stellar velocities and the changing Hercules feature in this distribution as a function of location in the Galactic disk in a simple model for the Galaxy and the bar that produces the observed Hercules stream. The Hercules feature is expected to be strong enough to be unambiguously detected in the distribution of line-of-sight velocities in selected directions. I identify quantitatively the most promising lines of sight for detection in line-of-sight velocities using the Kullback-Leibler divergence between the predictions of the resonance model and an axisymmetric model; these directions are at 250 deg <~ l <~ 290 deg. The predictions presented here are only weakly affected by distance uncertainties, assumptions about the distribution function in the stellar disk, and the details of the Galactic potential including the effect of spiral structure. Gaia and future spectroscopic surveys of the Galactic disk such as APOGEE and HERMES will be able to robustly test the origin of the Hercules stream and constrain the properties of the Galactic bar

A Survey on Aerial Swarm Robotics

The use of aerial swarms to solve real-world problems has been increasing steadily, accompanied by falling prices and improving performance of communication, sensing, and processing hardware. The commoditization of hardware has reduced unit costs, thereby lowering the barriers to entry to the field of aerial swarm robotics. A key enabling technology for swarms is the family of algorithms that allow the individual members of the swarm to communicate and allocate tasks amongst themselves, plan their trajectories, and coordinate their flight in such a way that the overall objectives of the swarm are achieved efficiently. These algorithms, often organized in a hierarchical fashion, endow the swarm with autonomy at every level, and the role of a human operator can be reduced, in principle, to interactions at a higher level without direct intervention. This technology depends on the clever and innovative application of theoretical tools from control and estimation. This paper reviews the state of the art of these theoretical tools, specifically focusing on how they have been developed for, and applied to, aerial swarms. Aerial swarms differ from swarms of ground-based vehicles in two respects: they operate in a three-dimensional space and the dynamics of individual vehicles adds an extra layer of complexity. We review dynamic modeling and conditions for stability and controllability that are essential in order to achieve cooperative flight and distributed sensing. The main sections of this paper focus on major results covering trajectory generation, task allocation, adversarial control, distributed sensing, monitoring, and mapping. Wherever possible, we indicate how the physics and subsystem technologies of aerial robots are brought to bear on these individual areas

Roles of the HIF-1 Hypoxia-inducible Factor during Hypoxia Response in Caenorhabditis elegans

The human hypoxia-inducible transcription factor HIF-1 is a critical regulator of cellular and systemic responses to low oxygen levels. When oxygen levels are high, the HIF-1α subunit is hydroxylated and is targeted for degradation by the von Hippel-Lindau tumor suppressor protein (VHL). This regulatory pathway is evolutionarily conserved, and the Caenorhabditis elegans hif-1 and vhl-1 genes encode homologs of the HIF-1α subunit and VHL. To understand and describe more fully the molecular basis for hypoxia response in this important genetic model system, we compared hypoxia-induced changes in mRNA expression in wild-type, hif-1-deficient, and vhl-1-deficient C. elegans using whole genome microarrays. These studies identified 110 hypoxia-regulated gene expression changes, 63 of which require hif-1 function. Mutation of vhl-1 abrogates most hif-1-dependent changes in mRNA expression. Genes regulated by C. elegans hif-1 have predicted functions in signal transduction, metabolism, transport, and extracellular matrix remodeling. We examined the in vivo requirement for 16 HIF-1 target genes and discovered that the phy-2 prolyl 4-hydroxylase α subunit is critical for survival in hypoxic conditions. Some HIF-1 target genes negatively regulate formation of stress-resistant dauer larvae. The microarray data presented herein also provide clear evidence for an HIF-1-independent pathway for hypoxia response, and this pathway regulates the expression of multiple heat shock proteins and several transcription factors

Toward Liquid Reconfigurable Antenna Arrays for Wireless Communications

Liquid-based antennas promise to overcome crucial limitations of traditional solid-based ones. Here, we describe different liquid antenna technologies that can be used to build arrays with the unprecedented flexibility and adaptivity needed to enable an evolution in wireless communications. We focus on two approaches that use either metallic or non-metallic liquids as radiating elements. In both cases, the resulting devices can be reconfigured dynamically, thus modifying the radiation parameters of an antenna in real time in an inexpensive way. To that end, we describe some of the challenges which arise when integrating such antennas as part of a whole communication system. We discuss the solutions adopted in some initial prototypes and summarize some of the problems that need to be solved to pave the way for integrating fully reconfigurable liquid antenna arrays in wireless communication systems

Effect of corticosteroid therapy on influenza-related mortality: a systematic review and meta-analysis

Background: Most studies have reported that corticosteroid therapy adversely influences influenza-related outcomes. Methods: Electronic databases were searched from inception to March 2013 for experimental and observational studies investigating systemic corticosteroid therapy for presumed influenza-associated complications. Meta-analysis of Observational Studies in Epidemiology guidelines were adopted. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using random-effects models, and heterogeneity was assessed using the I2 statistic. Quality of evidence was assessed using the Grading Assessment, Development, and Evaluation system. Results: We identified 16 eligible studies (3039 individuals), all of which were observational; 10 (1497 individuals) were included in the meta-analysis of mortality, of which 9 studied patients with 2009 pandemic influenza A virus subtype H1N1. Risk of bias was greatest in the comparability domain of the Newcastle–Ottawa scale, consistent with potential confounding by indication, and data specific to mortality were of low quality. Meta-analysis found an increased odds of mortality (OR, 2.12; 95% CI, 1.36–3.29) associated with corticosteroid therapy. Subgroup analysis of adjusted estimates from 4 studies with very low statistical heterogeneity found a similar association (OR, 2.58; 95% CI, 1.39–4.79). Conclusions: No completed clinical trials were identified. Evidence from observational studies, with important limitations, suggests that corticosteroid therapy for presumed influenza-associated complications is associated with increased mortality

DeepSF: deep convolutional neural network for mapping protein sequences to folds

Motivation Protein fold recognition is an important problem in structural bioinformatics. Almost all traditional fold recognition methods use sequence (homology) comparison to indirectly predict the fold of a tar get protein based on the fold of a template protein with known structure, which cannot explain the relationship between sequence and fold. Only a few methods had been developed to classify protein sequences into a small number of folds due to methodological limitations, which are not generally useful in practice. Results We develop a deep 1D-convolution neural network (DeepSF) to directly classify any protein se quence into one of 1195 known folds, which is useful for both fold recognition and the study of se quence-structure relationship. Different from traditional sequence alignment (comparison) based methods, our method automatically extracts fold-related features from a protein sequence of any length and map it to the fold space. We train and test our method on the datasets curated from SCOP1.75, yielding a classification accuracy of 80.4%. On the independent testing dataset curated from SCOP2.06, the classification accuracy is 77.0%. We compare our method with a top profile profile alignment method - HHSearch on hard template-based and template-free modeling targets of CASP9-12 in terms of fold recognition accuracy. The accuracy of our method is 14.5%-29.1% higher than HHSearch on template-free modeling targets and 4.5%-16.7% higher on hard template-based modeling targets for top 1, 5, and 10 predicted folds. The hidden features extracted from sequence by our method is robust against sequence mutation, insertion, deletion and truncation, and can be used for other protein pattern recognition problems such as protein clustering, comparison and ranking.Comment: 28 pages, 13 figure

The HIF-1 Hypoxia-Inducible Factor Modulates Lifespan in C. elegans

During normal development or during disease, animal cells experience hypoxic (low oxygen) conditions, and the hypoxia-inducible factor (HIF) transcription factors implement most of the critical changes in gene expression that enable animals to adapt to this stress. Here, we examine the roles of HIF-1 in post-mitotic aging. We examined the effects of HIF-1 over-expression and of hif-1 loss-of-function mutations on longevity in C. elegans, a powerful genetic system in which adult somatic cells are post-mitotic. We constructed transgenic lines that expressed varying levels of HIF-1 protein and discovered a positive correlation between HIF-1 expression levels and lifespan. The data further showed that HIF-1 acted in parallel to the SKN-1/NRF and DAF-16/FOXO transcription factors to promote longevity. HIF-1 over-expression also conferred increased resistance to heat and oxidative stress. We isolated and characterized additional hif-1 mutations, and we found that each of 3 loss-of-function mutations conferred increased longevity in normal lab culture conditions, but, unlike HIF-1 over-expression, a hif-1 deletion mutation did not extend the lifespan of daf-16 or skn-1 mutants. We conclude that HIF-1 over-expression and hif-1 loss-of-function mutations promote longevity by different pathways. These data establish HIF-1 as one of the key stress-responsive transcription factors that modulate longevity in C. elegans and advance our understanding of the regulatory networks that link oxygen homeostasis and aging