Likelihood inferences in animal breeding under selection: a missing-data theory view point

Data available in animal breeding are often subject to selection. Such data can be viewed as data with missing values. In this paper, inferences based on likelihoods derived from statistical models for missing data are applied to production records subject to selection. Conditions for ignoring the selection process are discussed.Les données disponibles en génétique animale sont souvent issues d’un processus préalable de sélection. On peut donc considérer comme manquants les attributs (non observés) associés aux individus éliminés, et analyser les données recueillies comme provenant d’un échantillon avec données manquantes. Dans cet article,on développe les méthodes d’inférence fondées sur les vraisemblances, en explicitant dans leur calcul le processus, dû à la sélection, qui induit les données manquantes. On discute les conditions dans lesquelles on peut ignorer la sélection, et donc considérer seulement la vraisemblance des données effectivement recueillies

Relationships between neuronal cell adhesion molecule and LHRH neurons in the urodele brain: a developmental immunohistochemical study

Polysialic acid (PSA), a homopolymer attached to neural cell adhesion molecule (NCAM) is considered a major hallmark of vertebrate cell migration. We studied the distribution of PSA-NCAM by immunohistochemistry, during brain development, in two urodele amphibians, Pleurodeles waltl and the neotenic newt Ambystoma mexicanum. In both species a gradual increase of immunolabelling was observed throughout the brain from developmental stage 30 to stage 52. At the onset of metamorphosis, some differences became evident: in Pleurodeles immunostaining was gradually restricted to the olfactory system while in Ambystoma, PSA-NCAM maintained a more extended distribution (for example throughout the telencephalic walls) suggesting, for the brain of this latter species, a rather preserved neuronal plasticity. The aim of the present work was to correlate the above described PSA-NCAMimmunoreactivity (IR) with the distribution of luteinizing hormone-releasing hormone (LH-RH) containing neurons, which represent a well known example of neural elements migrating from the olfactory placode. LHRH-IR, undetectable till stage 30, was later found together with PSA-NCAM-IR in both the olfactory system and septo-hypothalamic areas. Such observations further support a role of PSA in providing a migration route toward the establishment of a part, at least, of the urodele LHRH system. The possible functional meaning of the LHRH-containing neurons localized between dorsal and ventral thalamus of Ambystoma, never reported before in this area, almost devoid of PSANCAM- IR, is discussed

Decidable Fragments of LTLf Modulo Theories

We study Linear Temporal Logic Modulo Theories over Finite Traces (LTLMTf), a recently introduced extension of LTL over finite traces (LTLf) where propositions are replaced by first-order formulas and where first-order variables referring to different time points can be compared. In general, LTLMTf was shown to be semi-decidable for any decidable first-order theory (e.g., linear arithmetics), with a tableau-based semi-decision procedure. In this paper we present a sound and complete pruning rule for the LTLMTf tableau. We show that for any LTLMTf formula that satisfies an abstract, semantic condition, that we call finite memory, the tableau augmented with the new rule is also guaranteed to terminate. Last but not least, this technique allows us to establish novel decidability results for the satisfiability of several fragments of LTLMTf, as well as to give new decidability proofs for classes that are already known

Empirical Bayes estimation of parameters for n polygenic binary traits

The conditional probability of an observation in a subpopulation i (a combination of levels of explanatory variables) falling into one of 2n mutually exclusive and exhaustive categories is modelled using a normal integral in n-dimensions. The mean of subpopulation i is written as a linear combination of an unknown vector θ which can include « fixed » effects (e.g., nuisance environmental effects, genetic group effects) and « random » effects such as additive genetic value or producing ability. Conditionally on θ, the normal integral depends on an unknown matrix R comprising residual correlations in a multivariate standard normal conceptual scale. The random variables in θ have a dispersion matrix G X A, where usually A is a known matrix of additive genetic relationships, and G is a matrix of unknown genetic variances and covariances. It is assumed a priori that θ follows a multivariate normal distribution f (θ | G), which does not depend on R, and the likelihood function is taken as product multinomial. The point estimator of θ is the mode of the posterior distribution f (θ | Y, G = G*, R = R*) where Y is data, and G* and R* are the components of the mode of the marginal posterior distribution f (G, R | Y) using « flat » priors for G and R. The matrices G* and R* correspond to the marginal maximum likelihood estimators of the corresponding matrices. The point estimator of θ is of the empirical Bayes types. Overall, computations involve solving 3 non-linear systems in θ, G and R. G* can be computed with an expectation-maximization type algorithm ; an estimator of R* is suggested, and this is related to results published elsewhere on maximum likelihood estimation in contingency tables. Problems discussed include non-linearity, size of the system to be solved, rate of convergence, approximations made and the possible use of informative priors for the dispersion parameters.La probabilité conditionnelle qu’une observation d’une sous-population donnée (combinaison de niveaux de facteurs) se trouve dans l’une des 2" catégories possibles de réponse (exclusives et exhaustives) est modélisée par une intégrale normale à n-dimensions. La moyenne de la ﺎe sous population s’écrit comme une combinaison linéaire d’un vecteur θ de paramètres inconnus qui peuvent comprendre des effets « fixes » (effets de milieu parasites, effets de groupe génétique) et des effets aléatoires (valeur génétique additive ou aptitude à la production). Sachant θ, l’intégrale normale dépend d’une matrice inconnue R fonction des corrélations résiduelles entre les n variables normales sous-jacentes standardisées. Les effets aléatoires de θ présentent une matrice de dispersion de la forme G X A où A est généralement une matrice connue de parenté et G une matrice inconnue de variances et covariances génétiques. On suppose qu’a priori θ suit une loi multinormale de densité f (θ | G) qui ne dépend pas de R. La vraisemblance s’exprime alors comme un produit de multinomiales. L’estimateur de position de θ est défini comme le mode de la distribution a posteriori f (θ | Y, G = G*, R = R*) où Y est le vecteur des données, G* et R* sont les composantes du mode de la distribution marginale f (G, R | Y) avec des a priori uniformes pour G et R. G* et R* correspondent alors aux estimateurs du maximum de vraisemblance marginale et θ à un estimateur de type bayésien empirique. Les calculs impliquent la résolution de 3 systèmes non-linéaires en θ, G et R. G* se calcule selon un algorithme de type E.M. Une approximation de R* est suggérée en relation avec des résultats antérieurs publiés à propos d’une estimation du maximum de vraisemblance pour les tables de contingence. Divers problèmes sont abordés en discussion tels que la non-linéarité, la taille du système à résoudre, la vitesse de convergence, le degré d’approximation et l’emploi possible d’a priori informatifs pour les paramètres de dispersion

Bayesian inference in threshold models using Gibbs sampling

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Strengthening from dislocation restructuring and local climb at platelet linear complexions in Al-Cu alloys

Stress-driven segregation at dislocations can lead to structural transitions between different linear complexion states. In this work, we examine how platelet array linear complexions influence dislocation motion and quantify the associated strengthening effect in Al-Cu alloys using atomistic simulations. The presence of platelet complexions leads to faceting of the dislocations, with nanoscale segments climbing upwards along the platelet growth direction, resulting in a complex non-planar configuration that restricts subsequent dislocation motion. Upon deformation, the leading partial dislocation must climb down from the platelet complexions first, followed by a similar sequence at the trailing partial dislocation, in order to overcome the precipitates and commence plastic slip. The dislocation depinning mechanism of linear complexions is strikingly different from traditional precipitation-strengthened alloys, where dislocations overcome obstacles by either shearing through or looping around obstacles. The critical shear stress required to unpin dislocations from platelet complexions is found to be inversely proportional to precipitate spacing, which includes not just the open space (as observed in Orowan bowing) but also the region along the platelet particle where climb occurs. Thus, platelet linear complexions provide a new way to modify dislocation structure directly and improve the mechanical properties of metal alloys

DEFORMATION MECHANISMS IN NANOCRYSTALLINE ALUMINUM THIN FILMS: AN EXPERIMENTAL INVESTIGATION

Materials consisting of grains or crystallites with sizes below a hundred nanometers have exhibited unprecedented physical and mechanical properties in comparison to their coarse-grained counterparts. As a result, nanocrystalline materials have garnered considerable interest and a quest to uncover the new deformation mechanisms that give rise to this superior response has revealed that nanoscale behavior is quite different from that described by continuum plasticity. While the production of nanocrystalline materials with reasonable sizes for structural applications remains a challenge, thin metallic films used in next-generation MEMS and NEMS devices can be nanostructured by virtue of their limited dimensions. Ultimately, the reliability and lifetime prediction of these devices will hinge on the accurate modeling of their mechanical response. This dissertation describes efforts to elucidate the deformation mechanisms operating in nanocrystalline aluminum freestanding submicron thin films. Results obtained from these films demonstrate unique mechanical behavior, where discontinuous grain growth results in a fundamental change in the way in which the material deforms. In contrast to the low tensile ductility generally associated with nanocrystalline metals, these nanocrystalline films demonstrate extended tensile ductility. In situ X-ray diffraction and post-mortem transmission electron microscopy point to the importance of stress-assisted room temperature grain growth in transforming the underlying processes that govern the ii mechanical response of the films; nanoscale deformation mechanisms give way to microscale plasticity. The findings highlighted in this work emphasize that the microstructure and the attendant properties are dynamic; they evolve as the nanocrystalline material is being deformed. Experiments designed to address the role of impurities in stabilizing the microstructure against an applied stress are used to demonstrate that a critical concentration of impurities can effectively pin the grain boundaries from any motion. A detailed comparison of the characteristics of grain growth with traditional driving forces for grain boundary migration reveals the need for an alternative description. Measurements of surface topography evolution indicate that shear stresses directly couple to grain boundaries, induce motion, and result in grain growth that dramatically changes the mechanical behavior of these films. Finally, comparison with recently published theoretical formulations and molecular dynamics simulations is shown

Characteristics of academic publications, preprints, and registered clinical trials on the COVID-19 pandemic

The COVID-19 pandemic has unleashed a deluge of publications. For this cross-sectional study we compared the amount and reporting characteristics of COVID-19-related academic articles and preprints and the number of ongoing clinical trials and systematic reviews. To do this, we searched the PubMed database of citations and abstracts for published life science journals by using appropriate combinations of medical subject headings (MeSH terms), and the COVID-19 section of the MedRxiv and BioRxiv archives up to 20 May 2020 (21 weeks). In addition, we searched Clinicaltrial.gov, Chinese Clinical Trial Registry, EU Clinical Trials Register, and 15 other trial registers, as well as PROSPERO, the international prospective register of systematic reviews. The characteristics of each publication were extracted. Regression analyses and Z tests were used to detect publication trends and their relative proportions. A total of 3635 academic publications and 3805 preprints were retrieved. Only 8.6% (n = 329) of the preprints were already published in indexed journals. The number of academic and preprint publications increased significantly over time (p<0.001). Case reports (6% academic vs 0.9% preprints; p<0.001) and letters (17.4% academic vs 0.5% preprints; p<0.001) accounted for a greater share of academic compared to preprint publications. Differently, randomized controlled trials (0.22% vs 0.63%; p<0.001) and systematic reviews (0.08% vs 5%) made up a greater share of the preprints. The relative proportion of clinical studies registered at Clinicaltrials.gov, Chinese Clinical Trial Registry, and EU Clinical Trials Register was 57.9%, 49.5%, and 98.9%, respectively, most of which were still "recruiting". PROSPERO listed 962 systematic review protocols. Preprints were slightly more prevalent than academic articles but both were increasing in number. The void left by the lack of primary studies was filled by an outpour of immediate opinions (i.e., letters to the editor) published in PubMed-indexed journals. Summarizing, preprints have gained traction as a publishing response to the demand for prompt access to empirical, albeit not peer-reviewed, findings during the present pandemic.publishersversionpublishe