Discrimination of low-frequency tones employs temporal fine structure

An auditory neuron can preserve the temporal fine structure of a low-frequency tone by phase-locking its response to the stimulus. Apart from sound localization, however, little is known about the role of this temporal information for signal processing in the brain. Through psychoacoustic studies we provide direct evidence that humans employ temporal fine structure to discriminate between frequencies. To this end we construct tones that are based on a single frequency but in which, through the concatenation of wavelets, the phase changes randomly every few cycles. We then test the frequency discrimination of these phase-changing tones, of control tones without phase changes, and of short tones that consist of a single wavelets. For carrier frequencies below a few kilohertz we find that phase changes systematically worsen frequency discrimination. No such effect appears for higher carrier frequencies at which temporal information is not available in the central auditory system.Comment: 12 pages, 3 figure

High-resolution mapping of cancer cell networks using co-functional interactions.

Powerful new technologies for perturbing genetic elements have recently expanded the study of genetic interactions in model systems ranging from yeast to human cell lines. However, technical artifacts can confound signal across genetic screens and limit the immense potential of parallel screening approaches. To address this problem, we devised a novel PCA-based method for correcting genome-wide screening data, bolstering the sensitivity and specificity of detection for genetic interactions. Applying this strategy to a set of 436 whole genome CRISPR screens, we report more than 1.5 million pairs of correlated "co-functional" genes that provide finer-scale information about cell compartments, biological pathways, and protein complexes than traditional gene sets. Lastly, we employed a gene community detection approach to implicate core genes for cancer growth and compress signal from functionally related genes in the same community into a single score. This work establishes new algorithms for probing cancer cell networks and motivates the acquisition of further CRISPR screen data across diverse genotypes and cell types to further resolve complex cellular processes

RadVel: The Radial Velocity Modeling Toolkit

RadVel is an open source Python package for modeling Keplerian orbits in radial velocity (RV) time series. RadVel provides a convenient framework to fit RVs using maximum a posteriori optimization and to compute robust confidence intervals by sampling the posterior probability density via Markov Chain Monte Carlo (MCMC). RadVel allows users to float or fix parameters, impose priors, and perform Bayesian model comparison. We have implemented realtime MCMC convergence tests to ensure adequate sampling of the posterior. RadVel can output a number of publication-quality plots and tables. Users may interface with RadVel through a convenient command-line interface or directly from Python. The code is object-oriented and thus naturally extensible. We encourage contributions from the community. Documentation is available at http://radvel.readthedocs.io.Comment: prepared for resubmission to PAS

The Geometry and Topology of Twisted Quiver Varieties

Quivers have a rich history of being used to construct algebraic varieties via their representations in the category of vector spaces. It is also natural to consider quiver representations in a larger category, namely that of vector bundles on some complex variety equipped with a fixed locally free sheaf that twists the morphisms. For A-type quivers, such representations can be identified with the critical points of a Morse-Bott function on the moduli space of twisted Higgs bundles. Hence these ``twisted quiver varieties'' can be used to extract topological information about the Higgs bundle moduli space. We find a formula for the dimension of the moduli space of twisted representations of A-type quivers and geometric descriptions when each node of the quiver is represented by a line bundle. We then specialize to the so-called ``argyle quivers'', studied using Bradlow-Daskaloploulous stability parameters and pullback diagrams. Next we focus on the Riemann sphere P1 and obtain explicit expressions for the twisted quiver varieties as well as a stratification of these spaces via collisions of invariant zeroes of polynomials. We apply these results to some low-rank Higgs bundle moduli spaces. We then study representations of cyclic quivers, which can be viewed as corresponding to certain deformations of the Hitchin representations in non-abelian Hodge theory. When all of the ranks are 1, we describe the moduli spaces as subvarieties of the Hitchin system. We also draw out descriptions of the twisted quiver varieties for when the underlying curve is P1 and extend this to some other labellings of the quiver. We close with a discussion of possible applications of these ideas to hyperpolygon spaces as well as possible directions that use the motivic approach to moduli theory

Evolving Material Porosity on an Additive Manufacturing Simulation with the Generalized Method of Cells

The effect of material porosity on final part distortion and residual stresses in a selective laser sintering manufacturing simulation is presented here. A time-dependent thermomechanical model is used with the open-source FEA software CalculiX. Effective homogenized material properties for Inconel 625 are precomputed using NASAs Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC). The evolving porosity of the material is estimated with each pass of the laser beam during simulation runtime. A comparison with a homogenous model and the evolving model shows that the evolving porous model predicts larger distortions with greater residual stresses

Population structure, long-term connectivity, and effective size of mutton snapper (Lutjanus analis) in the Caribbean Sea and Florida Keys

Genetic structure and average long-term connectivity and effective size of mutton snapper (Lutjanus analis) sampled from offshore localities in the U.S. Caribbean and the Florida Keys were assessed by using nuclear-encoded microsatellites and a fragment of mitochondrial DNA. No significant differences in allele, genotype (microsatellites), or haplotype (mtDNA) distributions were detected; tests of selective neutrality (mtDNA) were nonsignificant after Bonferroni correction. Heuristic estimates of average long-term rate of migration (proportion of migrant individuals/generation) between geographically adjacent localities varied from 0.0033 to 0.0054, indicating that local subpopulations could respond independently of environmental perturbations. Estimates of average longterm effective population sizes varied from 341 to 1066 and differed significantly among several of the localities. These results indicate that over time larval drift and interregional adult movement may not be sufficient to maintain population sustainability across the region and that there may be different demographic stocks at some of the localities studied. The estimate of long-term effective population size at the locality offshore of St. Croix was below the minimum threshold size considered necessary to maintain the equilibrium between the loss of adaptive genetic variance from genetic drift and its replacement by mutation. Genetic variability in mutton snapper likely is maintained at the intraregional level by aggregate spawning and random mating of local populations. This feature is perhaps ironic in that aggregate spawning also renders mutton snapper especially vulnerable to overexploitation