Sexual Symmetry in Natural Populations of the Patagonian Cypress (Austrocedrus chilensis)

AbstractSexual symmetry, defined as equal allelic frequencies among reproduction effective gametes of both sexes, was analysed by means of 10 isozyme loci in three natural populations of Austrocedrus chilensis (dioecious and wind pollinated tree species). Haplotypes of effective gametes were inferred by analysing side-by-side both the embryo and the endosperm of seeds collected from 20 to 27 trees per population. The allelic frequencies of effective ovules and pollen were compared in each of the three populations. The hypothesis of sexual symmetry could only be rejected in case of one locus in two out of three analysed populations. That is, most of the loci surveyed turned out to be symmetric in the three sampled populations in spite of their contrasting environmental conditions. Therefore, sexual symmetry in A. chilensis seems to be mainly uninfluenced by the environment. On the other hand, all loci showed Hardy- Weinberg (HW) proportions in the three populations, even those that resulted asymmetric. HW structure is usually considered as enough evidence of panmixia, what implies sexual symmetry, and consequently this result gives an example of the low reliability of indirect methods of testing genetic processes, such as the classical HW test

Mean properties and Free Energy of a few hard spheres confined in a spherical cavity

We use analytical calculations and event-driven molecular dynamics simulations to study a small number of hard sphere particles in a spherical cavity. The cavity is taken also as the thermal bath so that the system thermalizes by collisions with the wall. In that way, these systems of two, three and four particles, are considered in the canonical ensemble. We characterize various mean and thermal properties for a wide range of number densities. We study the density profiles, the components of the local pressure tensor, the interface tension, and the adsorption at the wall. This spans from the ideal gas limit at low densities to the high-packing limit in which there are significant regions of the cavity for which the particles have no access, due the conjunction of excluded volume and confinement. The contact density and the pressure on the wall are obtained by simulations and compared to exact analytical results. We also obtain the excess free energy for N=4, by using a simulated-assisted approach in which we combine simulation results with the knowledge of the exact partition function for two and three particles in a spherical cavity.Comment: 11 pages, 9 figures and two table

Static and dynamic properties of the interface between a polymer brush and a melt of identical chains

Molecular dynamics simulations of a short-chain polymer melt between two brush-covered surfaces under shear have been performed. The end-grafted polymers which constitute the brush have the same chemical properties as the free chains in the melt and provide a soft deformable substrate. Polymer chains are described by a coarse-grained bead-spring model with Lennard-Jones interactions between the beads and a FENE potential between nearest neighbors along the backbone of the chains. The grafting density of the brush layer offers a way of controlling the behavior of the surface without altering the molecular interactions. We perform equilibrium and non-equilibrium Molecular Dynamics simulations at constant temperature and volume using the Dissipative Particle Dynamics thermostat. The equilibrium density profiles and the behavior under shear are studied as well as the interdigitation of the melt into the brush, the orientation on different length scales (bond vectors, radius of gyration, and end-to-end vector) of free and grafted chains, and velocity profiles. The viscosity and slippage at the interface are calculated as functions of grafting density and shear velocity.Comment: 12 pages, submitted to J Chem Phy

Semantic Segmentation of Remote-Sensing Images Through Fully Convolutional Neural Networks and Hierarchical Probabilistic Graphical Models

Deep learning (DL) is currently the dominant approach to image classification and segmentation, but the performances of DL methods are remarkably influenced by the quantity and quality of the ground truth (GT) used for training. In this article, a DL method is presented to deal with the semantic segmentation of very-high-resolution (VHR) remote-sensing data in the case of scarce GT. The main idea is to combine a specific type of deep convolutional neural networks (CNNs), namely fully convolutional networks (FCNs), with probabilistic graphical models (PGMs). Our method takes advantage of the intrinsic multiscale behavior of FCNs to deal with multiscale data representations and to connect them to a hierarchical Markov model (e.g., making use of a quadtree). As a consequence, the spatial information present in the data is better exploited, allowing a reduced sensitivity to GT incompleteness to be obtained. The marginal posterior mode (MPM) criterion is used for inference in the proposed framework. To assess the capabilities of the proposed method, the experimental validation is conducted with the ISPRS 2D Semantic Labeling Challenge datasets on the cities of Vaihingen and Potsdam, with some modifications to simulate the spatially sparse GTs that are common in real remote-sensing applications. The results are quite significant, as the proposed approach exhibits a higher producer accuracy than the standard FCNs considered and especially mitigates the impact of scarce GTs on minority classes and small spatial details

Hierarchical Probabilistic Graphical Models and Deep Convolutional Neural Networks for Remote Sensing Image Classification

The method presented in this paper for semantic segmentation of multiresolution remote sensing images involves convolutional neural networks (CNNs), in particular fully convolutional networks (FCNs), and hierarchical probabilistic graphical models (PGMs). These approaches are combined to overcome the limitations in classification accuracy of CNNs for small or non-exhaustive ground truth (GT) datasets. Hierarchical PGMs, e.g., hierarchical Markov random fields (MRFs), are structured output learning models that exploit information contained at different image scales. This perfectly matches the intrinsically multiscale behavior of the processes of a CNN (e.g., pooling layers). The framework consists of a hierarchical MRF on a quadtree and a planar Markov model on each layer, modeling the interactions among pixels and accounting for both the multiscale and the spatial-contextual information. The marginal posterior mode criterion is used for inference. The adopted FCN is the U-Net and the experimental validation is conducted on the ISPRS 2D Semantic Labeling Challenge Vaihingen dataset, with some modifications to approach the case of scarce GTs and to assess the classification accuracy of the proposed technique. The proposed framework attains a higher recall compared to the considered FCNs, progressively more relevant as the training set is further from the ideal case of exhaustive GTs

Variación genética de poblaciones naturales de Ciprés de la Cordillera con regímenes de precipitación contrastados, en la eficiencia del uso del agua de plántulas, a través de la discriminación isotópica del carbono

Water-use efficiency (WUE) is a physiological parameter that plays a significant role in the evolutionary dynamics of many forest tree species. It can be estimated indirectly through carbon isotope discrimination (Δ). In general, plants of more arid origins have lower values of Δ. In order to study the degree of genetic control of this parameter and the genetic variation in Δ of Patagonian Cypress seedlings, three Argentinean natural populations chosen to represent two contrasting precipitation regimes were sampled in a common garden trial. The dry situation was represented by two neighboring marginal forest patches from the steppe, while the humid condition was represented by a population with 1,200 mm higher mean annual precipitation. Height (H) and Δ were measured in 246 five-year-old seedlings from 41 open-pollinated families. The factor ‘family’ had a significant effect on both variables; however heritability for Δ was found not to be significant in two out of the three populations. This could be explained by low sample size in one of them and by a real evolutionary effect in the other. An inverse association between H and Δ was verified, which is interpreted as evidence of an adaptation process at the intra-population level. The studied populations were not shown to discriminate carbon isotopes differently; hence evidence of adaptation to current environmental conditions could not be obtained. On the other hand, the arid populations proved to be quite different in terms of genetic variation, which seems to be the consequence of genetic drift and isolation.La eficiencia en el uso del agua es un parámetro fisiológico que desempeña un rol significativo en la dinámica evolutiva de muchas especies forestales. Puede estimarse indirectamente a través de la discriminación isotópica del carbono (Δ). En general, las plantas de orígenes más áridos tienen valores de Δ más bajos. Con el propósito de estudiar el grado de control genético de Δ y la variación genética en este parámetro en plántulas de Ciprés de la Cordillera, tres poblaciones naturales elegidas para representar dos regímenes de precipitación contrastados fueron muestreadas en un ensayo de ambiente común. La condición árida estuvo representada por dos fragmentos de bosque esteparios marginales, vecinos entre sí, mientras que la condición húmeda fue representada por una población con una precipitación media anual 1.200 mm superior a la de las áridas. Se midió altura total (H) y Δ en 246 plántulas de 5 años de edad correspondientes a 41 familias de polinización abierta. El factor ‘familia’ tuvo un efecto significativo en ambas variables; sin embargo, la heredabilidad para Δ no resultó significativa en dos de las tres poblaciones. En una de ellas esto podría explicarse por el restringido tamaño muestreal, mientras que en la otra por un verdadero efecto evolutivo. Asimismo se verificó una asociación inversa entre H y Δ, la cual es interpretada como evidencia de un proceso de adaptación a nivel intra-poblacional. No se observó que las poblaciones estudiadas discriminaran los isótopos del carbono de un modo diferencial, y por lo tanto no se obtuvieron evidencias de adaptación a las condiciones ambientales actuales. Por otro lado, las poblaciones áridas probaron ser muy diferentes entre sí en términos de variación genética, lo que parece ser la consecuencia de deriva y aislamiento genéticos

Molecular transport and flow past hard and soft surfaces: Computer simulation of model systems

The properties of polymer liquids on hard and soft substrates are investigated by molecular dynamics simulation of a coarse-grained bead-spring model and dynamic single-chain-in-mean-field (SCMF) simulations of a soft, coarse-grained polymer model. Hard, corrugated substrates are modelled by an FCC Lennard-Jones solid while polymer brushes are investigated as a prototypical example of a soft, deformable surface. From the molecular simulation we extract the coarse-grained parameters that characterise the equilibrium and flow properties of the liquid in contact with the substrate: the surface and interface tensions, and the parameters of the hydrodynamic boundary condition. The so-determined parameters enter a continuum description like the Stokes equation or the lubrication approximation.Comment: 41 pages, 13 figure

Towards automatic pulmonary nodule management in lung cancer screening with deep learning

The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decide on a patient follow-up strategy. According to the current guidelines, the workup of screen-detected nodules strongly relies on nodule size and nodule type. In this paper, we present a deep learning system based on multi-stream multi-scale convolutional networks, which automatically classifies all nodule types relevant for nodule workup. The system processes raw CT data containing a nodule without the need for any additional information such as nodule segmentation or nodule size and learns a representation of 3D data by analyzing an arbitrary number of 2D views of a given nodule. The deep learning system was trained with data from the Italian MILD screening trial and validated on an independent set of data from the Danish DLCST screening trial. We analyze the advantage of processing nodules at multiple scales with a multi-stream convolutional network architecture, and we show that the proposed deep learning system achieves performance at classifying nodule type that surpasses the one of classical machine learning approaches and is within the inter-observer variability among four experienced human observers.Comment: Published on Scientific Report

Project MOSI: rationale and pilot-study results of an initiative to help protect zoo animals from mosquito-transmitted pathogens and contribute data on mosquito spatio–temporal distribution change

Mosquito-borne pathogens pose major threats to both wildlife and human health and, largely as a result of unintentional human-aided dispersal of their vector species, their cumulative threat is on the rise. Anthropogenic climate change is expected to be an increasingly significant driver of mosquito dispersal and associated disease spread. The potential health implications of changes in the spatio-temporal distribution of mosquitoes highlight the importance of ongoing surveillance and, where necessary, vector control and other health-management measures. The World Association of Zoos and Aquariums initiative, Project MOSI, was established to help protect vulnerable wildlife species in zoological facilities from mosquito-transmitted pathogens by establishing a zoo-based network of fixed mosquito monitoring sites to assist wildlife health management and contribute data on mosquito spatio-temporal distribution changes. A pilot study for Project MOSI is described here, including project rationale and results that confirm the feasibility of conducting basic standardized year-round mosquito trapping and monitoring in a zoo environment