Are Particles in Advection-Dominated Accretion Flows Thermal?

We investigate the form of the momentum distribution function for protons and electrons in an advection-dominated accretion flow (ADAF). We show that for all accretion rates, Coulomb collisions are too inefficient to thermalize the protons. The proton distribution function is therefore determined by the viscous heating mechanism, which is unknown. The electrons, however, can exchange energy quite efficiently through Coulomb collisions and the emission and absorption of synchrotron photons. We find that for accretion rates greater than \sim 10^{-3} of the Eddington accretion rate, the electrons have a thermal distribution throughout the accretion flow. For lower accretion rates, the electron distribution function is determined by the electron's source of heating, which is primarily adiabatic compression. Using the principle of adiabatic invariance, we show that an adiabatically compressed collisionless gas maintains a thermal distribution until the particle energies become relativistic. We derive a new, non-thermal, distribution function which arises for relativistic energies and provide analytic formulae for the synchrotron radiation from this distribution. Finally, we discuss its implications for the emission spectra from ADAFs.Comment: 29 pages (Latex), 3 Figures. Submitted to Ap

Bayesian Methods for Genomic Prediction and Genome-Wide Association Studies combining Information on Genotyped and Non-Genotyped Individuals

Genomic prediction involves using high-density marker genotypes to characterize the impact on performance of every region of the genome, and using that information to predict performance of genotyped selection candidates. This is a relatively new technology and is now gaining traction in personalized medicine and in various livestock industries. Our new approach promises to overcome serious limitations with existing techniques for genomic prediction

Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.Comment: 9 pages, 5 figures Corrected errors in equation 1

Improved Accuracy of Genomic Prediction for Traits with Rare QTL by Fitting Haplotypes

Genomic prediction estimates breeding values by exploiting linkage disequilibrium (LD) between quantitative trait loci (QTL) and single nucleotide polymorphisms (SNPs). High LD cannot occur when QTL and SNPs have different minor allele frequencies (MAF). Marker panels tend to use SNPs with high MAF and will have limited ability to predict rare QTL alleles. In practice, increasing SNP density has not improved prediction accuracy. A possible reason is that many traits are characterized by rare QTL. In that case, linear models fitting haplotypes could have advantage because haplotypes can be in complete LD with QTL alleles. SNP genotypes were simulated to resemble 600K chip for the bovine genome. Genomic breeding values were predicted using either SNP genotypes or non-overlapping haplotypes. When QTL had low MAF, the haplotype model had significantly higher accuracy than the SNP model. Results show that fitting haplotypes can improve the accuracy of genomic prediction for traits controlled by rare QTL

Genomic Prediction Using Linkage Disequilibrium and Co-segregation

A linear mixed model fitting both genome-wide cosegregation (CS) and linkage disequilibrium (LD) was developed to improve accuracy of genetic prediction for pedigreed populations of unrelated families that have half sibs represented in both training and validation. Cosegregation was modeled as the effects of genome-wide1-centimorgan haplotypes that one individual inherits from pedigree founders through identity-by-descent, while LD was modeled as allele substitution effects of all marker genotypes. Prediction accuracy of the LD-CS method was compared to the accuracy of three LD methods – GBLUP, BayesA and BayesB, using simulated datasets of varying numbers of paternal half sib families. Results show that the LD-CS method tended to have higher accuracy than any of the LD methods. With an increase in the number of families, the accuracy of the LD-CS method persisted, while the accuracy of the LD methods dropped. The results indicate that by fitting CS explicitly, the LD-CS method has higher and more consistent prediction accuracy than LD methods

Asrij Maintains the Stem Cell Niche and Controls Differentiation during Drosophila Lymph Gland Hematopoiesis

Several signaling pathways control blood cell (hemocyte) development in the Drosophila lymph gland. Mechanisms that modulate and integrate these signals are poorly understood. Here we report that mutation in a conserved endocytic protein Asrij affects signal transmission and causes aberrant lymph gland hematopoiesis. Mammalian Asrij (Ociad1) is expressed in stem cells of the blood vascular system and is implicated in several cancers. We found that Drosophila Asrij is a pan-hemocyte marker and localizes to a subset of endocytic vesicles. Loss of asrij causes hyperproliferation of lymph gland lobes coupled with increased hemocyte differentiation, thereby depleting the pool of quiescent hemocyte precursors. This co-relates with fewer Col+ cells in the hematopoietic stem cell niche of asrij mutants. Asrij null mutants also show excess specification of crystal cells that express the RUNX factor Lozenge (Lz), a target of Notch signaling. Asrij mutant lymph glands show increased N in sorting endosomes suggesting aberrant trafficking. In vitro assays also show impaired traffic of fluorescent probes in asrij null hemocytes. Taken together our data suggest a role for Asrij in causing increased Notch signaling thereby affecting hemocyte differentiation. Thus, conserved endocytic functions may control blood cell progenitor quiescence and differentiation

Genomic Selection of Purebred Animals for Crossbred Performance in the Presence of Dominant Gene Action

The primary objective of this study was to assess the performance of different genomic prediction models applied to the selection of purebreds for crossbred performancebased on high-density marker data. Our results suggest that in the presence of dominant gene action, selection based on the dominance model is superior to both the a breed-specific allele model and an additive model in terms of maximizing crossbred performance through purebred selection, especially when training is not updated each generatio

A Particle-based Multiscale Solver for Compressible Liquid-Vapor Flow

To describe complex flow systems accurately, it is in many cases important to account for the properties of fluid flows on a microscopic scale. In this work, we focus on the description of liquid-vapor flow with a sharp interface between the phases. The local phase dynamics at the interface can be interpreted as a Riemann problem for which we develop a multiscale solver in the spirit of the heterogeneous multiscale method, using a particle-based microscale model to augment the macroscopic two-phase flow system. The application of a microscale model makes it possible to use the intrinsic properties of the fluid at the microscale, instead of formulating (ad-hoc) constitutive relations