A computer program for the mixed analysis of variance model based on maximum likelihood

Computer program for mixed analysis of variance model based on maximum likelihoo

A 3D Face Modelling Approach for Pose-Invariant Face Recognition in a Human-Robot Environment

Face analysis techniques have become a crucial component of human-machine interaction in the fields of assistive and humanoid robotics. However, the variations in head-pose that arise naturally in these environments are still a great challenge. In this paper, we present a real-time capable 3D face modelling framework for 2D in-the-wild images that is applicable for robotics. The fitting of the 3D Morphable Model is based exclusively on automatically detected landmarks. After fitting, the face can be corrected in pose and transformed back to a frontal 2D representation that is more suitable for face recognition. We conduct face recognition experiments with non-frontal images from the MUCT database and uncontrolled, in the wild images from the PaSC database, the most challenging face recognition database to date, showing an improved performance. Finally, we present our SCITOS G5 robot system, which incorporates our framework as a means of image pre-processing for face analysis

Implementation of a combined association-linkage model for quantitative traits in linear mixed model procedures of statistical packages

Atransmission disequilibrium test for quantitative traits which combines association and linkage analyses is currently available in several dedicated software packages. We describe how to implement such models in linear mixed model procedures that are available in widely used statistical packages such as SPSS. We also briefly mention a few extensions of the model that become naturally available once the model is implemented in such procedures. Genotyping of many microsatellite markers or single nucleotide polymorphisms (SNPs) over the entire genome is becoming increasingly common in human genetics. In those high-resolution maps the average distance between microsatellite markers may be as small as 5 cM and between SNPs one half cM or less. At those small distances it becomes fairly likely that some markers in the set are in linkage disequilibrium (LD) with a gene affecting the trait (a so-called quantitative trait locus or QTL if the trait or the vulnerability distribution is quantitative). Different alleles or combinations of alleles of the markers or SNPs can then be associated with different trait means. Association studies are conducted to discover such allelic effects. Abecasis et al. (2000) generalized the model proposed by Fulker et al. (1999) for combined linkage and association tests, within and between families. The Fulker-Abecasis or F-A model is implemented in the program QTD

Phase I study of TP300 in patients with advanced solid tumors with pharmacokinetic, pharmacogenetic and pharmacodynamic analyses

Background: A Phase I dose escalation first in man study assessed maximum tolerated dose (MTD), dose-limiting toxicity (DLT) and recommended Phase II dose of TP300, a water soluble prodrug of the Topo-1 inhibitor TP3076, and active metabolite, TP3011. <p/>Methods: Eligible patients with refractory advanced solid tumors, adequate performance status, haematologic, renal, and hepatic function. TP300 was given as a 1-hour i.v. infusion 3-weekly and pharmacokinetic (PK) profiles of TP300, TP3076 and TP3011 were analysed. Polymorphisms in CYP2D6, AOX1 and UGT1A1 were studied and DNA strand-breaks measured in peripheral blood mononuclear cells (PBMCs). <p/>Results: 32 patients received TP300 at 1, 2, 4, 6, 8, 10, 12 mg/m2. MTD was 10 mg/m2; DLTs at 12 (2/4 patients) and 10 mg/m2 (3/12) included thrombocytopenia and febrile neutropenia; diarrhea was uncommon. Six patients (five had received irinotecan), had stable disease for 1.5-5 months. TP3076 showed dose proportionality in AUC and Cmax from 1--10 mg/m2. Genetic polymorphisms had no apparent influence on exposure. DNA strand-breaks were detected after TP300 infusion. <p/>Conclusions: TP300 had predictable hematologic toxicity, and diarrhea was uncommon. AUC at MTD is substantially greater than for SN38. TP3076 and TP3011 are equi-potent with SN38, suggesting a PK advantage

The role of mass and environment in the build up of the quenched galaxy population since cosmic noon

We conduct the first study of how the relative quenching probability of galaxies depends on environment over the redshift range $0.5 < z < 3$, using data from the UKIDSS Ultra-Deep Survey. By constructing the stellar mass functions for quiescent and post-starburst (PSB) galaxies in high, medium and low density environments to $z = 3$, we find an excess of quenched galaxies in dense environments out to at least $z \sim 2$. Using the growth rate in the number of quenched galaxies, combined with the star-forming galaxy mass function, we calculate the probability that a given star-forming galaxy is quenched per unit time. We find a significantly higher quenching rate in dense environments (at a given stellar mass) at all redshifts. Massive galaxies (M$_* > 10^{10.7}$ M$_{\odot}$) are on average 1.7 $\pm$ 0.2 times more likely to quench per Gyr in the densest third of environments compared to the sparsest third. Finally, we compare the quiescent galaxy growth rate to the rate at which galaxies pass through a PSB phase. Assuming a visibility timescale of 500 Myr, we find that the PSB route can explain $\sim$ 50\% of the growth in the quiescent population at high stellar mass (M$_* > 10^{10.7}$ M$_{\odot}$) in the redshift range $0.5 < z < 3$, and potentially all of the growth at lower stellar masses.Comment: 12 pages, 8 figures. Accepted for publication in MNRA

Resonance line-profile calculations based on hydrodynamical models of cataclysmic variable winds

We present synthetic line profiles as predicted by the models of 2-D line- driven disk winds due to Proga, Stone & Drew. We compare the model line profiles with HST observations of the cataclysmic variable IX Vel. The model wind consists of a slow outflow that is bounded on the polar side by a fast stream. We find that these two components of the wind produce distinct spectral features. The fast stream produces profiles which show features consistent with observations. These include the appearance of the P-Cygni shape for a range of inclinations, the location of the maximum depth of the absorption component at velocities less than the terminal velocity, and the transition from absorption to emission with increasing inclination. However the model profiles have too little absorption or emission equivalent width. This quantitative difference between our models and observations is not a surprise because the line-driven wind models predict a mass loss rate that is lower than the rate required by the observations. We note that the model profiles exhibit a double-humped structure near the line center which is not echoed in observations. We identify this structure with a non-negligible redshifted absorption which is formed in the slow component of the wind where the rotational velocity dominates over expansion velocity. We conclude that the next generation of disk wind models, developed for application to CVs, needs to yield stronger wind driving out to larger disk radii than do the present models.Comment: LaTeX, 19 pages, to appear in Ap

DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse points

Multi-view stereo (MVS) is the golden mean between the accuracy of active depth sensing and the practicality of monocular depth estimation. Cost volume based approaches employing 3D convolutional neural networks (CNNs) have considerably improved the accuracy of MVS systems. However, this accuracy comes at a high computational cost which impedes practical adoption. Distinct from cost volume approaches, we propose an efficient depth estimation approach by first (a) detecting and evaluating descriptors for interest points, then (b) learning to match and triangulate a small set of interest points, and finally (c) densifying this sparse set of 3D points using CNNs. An end-to-end network efficiently performs all three steps within a deep learning framework and trained with intermediate 2D image and 3D geometric supervision, along with depth supervision. Crucially, our first step complements pose estimation using interest point detection and descriptor learning. We demonstrate state-of-the-art results on depth estimation with lower compute for different scene lengths. Furthermore, our method generalizes to newer environments and the descriptors output by our network compare favorably to strong baselines. Code is available at https://github.com/magicleap/DELTASComment: ECCV 202

Climatic drivers of silicon accumulation in a model grass operate in low- but not high-silicon soils

Grasses are hyper-accumulators of silicon (Si), which is known to alleviate diverse environmental stresses, prompting speculation that Si accumulation evolved in response to unfavourable climatic conditions, including seasonally arid environments. We conducted a common garden experiment using 57 accessions of the model grass Brachypodium distachyon, sourced from different Mediterranean locations, to test relationships between Si accumulation and 19 bioclimatic variables. Plants were grown in soil with either low or high (Si supplemented) levels of bioavailable Si. Si accumulation was negatively correlated with temperature variables (annual mean diurnal temperature range, temperature seasonality, annual temperature range) and precipitation seasonality. Si accumulation was positively correlated with precipitation variables (annual precipitation, precipitation of the driest month and quarter, and precipitation of the warmest quarter). These relationships, however, were only observed in low-Si soils and not in Si-supplemented soils. Our hypothesis that accessions of B. distachyon from seasonally arid conditions have higher Si accumulation was not supported. On the contrary, higher temperatures and lower precipitation regimes were associated with lower Si accumulation. These relationships were decoupled in high-Si soils. These exploratory results suggest that geographical origin and prevailing climatic conditions may play a role in predicting patterns of Si accumulation in grasses

Stochastic Tachyon Fluctuations, Marginal Deformations and Shock Waves in String Theory

Starting with exact solutions to string theory on curved spacetimes we obtain deformations that represent gravitational shock waves. These may exist in the presence or absence of sources. Sources are effectively induced by a tachyon field that randomly fluctuates around a zero condensate value. It is shown that at the level of the underlying conformal field theory (CFT) these deformations are marginal and moreover all \a'-corrections are taken into account. Explicit results are given when the original undeformed 4-dimensional backgrounds correspond to tensor products of combinations of 2-dimensional CFT's, for instance SL(2,R)/R \times SU(2)/U(1).Comment: 26 pages, harvmac, no figures. Very minor modifications, and in addition conditions (B.3) and (B.4) were also obtained using beta-function equations. Version to appear in Phys. Rev.