HETEROTIC GROUP FORMATION IN PSIDIUM GUAJAVA L. BY ARTIFICIAL NEURAL NETWORK AND DISCRIMINANT ANALYSIS

ABSTRACT The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation.

A definition and classification of status epilepticus - Report of the ILAE Task Force on Classification of Status Epilepticus.

The Commission on Classification and Terminology and the Commission on Epidemiology of the International League Against Epilepsy (ILAE) have charged a Task Force to revise concepts, definition, and classification of status epilepticus (SE). The proposed new definition of SE is as follows: Status epilepticus is a condition resulting either from the failure of the mechanisms responsible for seizure termination or from the initiation of mechanisms, which lead to abnormally, prolonged seizures (after time point t1 ). It is a condition, which can have long-term consequences (after time point t2 ), including neuronal death, neuronal injury, and alteration of neuronal networks, depending on the type and duration of seizures. This definition is conceptual, with two operational dimensions: the first is the length of the seizure and the time point (t1 ) beyond which the seizure should be regarded as "continuous seizure activity." The second time point (t2 ) is the time of ongoing seizure activity after which there is a risk of long-term consequences. In the case of convulsive (tonic-clonic) SE, both time points (t1 at 5 min and t2 at 30 min) are based on animal experiments and clinical research. This evidence is incomplete, and there is furthermore considerable variation, so these time points should be considered as the best estimates currently available. Data are not yet available for other forms of SE, but as knowledge and understanding increase, time points can be defined for specific forms of SE based on scientific evidence and incorporated into the definition, without changing the underlying concepts. A new diagnostic classification system of SE is proposed, which will provide a framework for clinical diagnosis, investigation, and therapeutic approaches for each patient. There are four axes: (1) semiology; (2) etiology; (3) electroencephalography (EEG) correlates; and (4) age. Axis 1 (semiology) lists different forms of SE divided into those with prominent motor systems, those without prominent motor systems, and currently indeterminate conditions (such as acute confusional states with epileptiform EEG patterns). Axis 2 (etiology) is divided into subcategories of known and unknown causes. Axis 3 (EEG correlates) adopts the latest recommendations by consensus panels to use the following descriptors for the EEG: name of pattern, morphology, location, time-related features, modulation, and effect of intervention. Finally, axis 4 divides age groups into neonatal, infancy, childhood, adolescent and adulthood, and elderly.

Quantum Hall Phases of two-component bosons

The recent production of synthetic magnetic fields acting on electroneutral particles, such as atoms or photons, has boosted interest in the quantum Hall physics of bosons. Adding pseudospin 1/2 to the bosons greatly enriches the scenario, as it allows them to form an interacting integer quantum Hall (IQH) phase with no fermionic counterpart. Here we show that, for a small two-component Bose gas on a disk, the complete strongly correlated regime, extending from the integer phase at filling factor ν = 2 to the Halperin phase at filling factor ν = 2 / 3, is well described by composite fermionization of the bosons. Moreover we study the edge excitations of the IQH state, which, in agreement with expectations from topological field theory, are found to consist of forward-moving charge excitations and backward-moving spin excitations. Finally, we demonstrate how pair-correlation functions allow one to experimentally distinguish the IQH state from competing states, such as non-Abelian spin singlet (NASS) states.

Nature of the Epidemic Threshold for the Susceptible-Infected-Susceptible Dynamics in Networks

We develop an analytical approach to the susceptible-infected-susceptible epidemic model that allows us to unravel the true origin of the absence of an epidemic threshold in heterogeneous networks. We find that a delicate balance between the number of high degree nodes in the network and the topological distance between them dictates the existence or absence of such a threshold. In particular, small-world random networks with a degree distribution decaying slower than an exponential have a vanishing epidemic threshold in the thermodynamic limit.

Monoidal functors, acyclic models and chain operads

We prove that for a topological operad $P$ the operad of oriented cubical singular chains, $C^{\ord}_\ast(P)$, and the operad of simplicial singular chains, $S_\ast(P)$, are weakly equivalent. As a consequence, $C^{\ord}_\ast(P\nsemi\mathbb{Q})$ is formal if and only if $S_\ast(P\nsemi\mathbb{Q})$ is formal, thus linking together some formality results which are spread out in the literature. The proof is based on an acyclic models theorem for monoidal functors. We give different variants of the acyclic models theorem and apply the contravariant case to study the cohomology theories for simplicial sets defined by $R$-simplicial differential graded algebras.

Generative models of the human connectome.

The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.

Monitoring spatial and temporal dynamics of bird communities in Mediterranean landscapes affected by largewildfires = Seguimiento de la dinámica espacial y temporal de comunidades de aves en paisajes mediterráneos afectados por grandes fuegos

We presented a bird-monitoring database inMediterranean landscapes (Catalonia, NE Spain) affected by wildfires and we evaluated: 1) the spatial and temporal variability in the bird community composition and 2) the influence of pre-fire habitat configuration in the composition of bird communities. The DINDIS database results fromthemonitoring of bird communities occupying all areas affected by large wildfires in Catalonia since 2000.We used bird surveys conducted from 2006 to 2009 and performed a principal components analysis to describe two main gradients of variation in the composition of bird communities, which were used as descriptors of bird communities in subsequent analyses. We then analysed the relationships of these community descriptors with bioclimatic regions within Catalonia, time since fire and pre-fire vegetation (forest or shrubland).We have conducted 1,918 bird surveys in 567 transects distributed in 56 burnt areas. Eight out of the twenty most common detected species have an unfavourable conservation status, most of them being associated to open-habitats. Both bird communities’ descriptors had a strong regional component and were related to pre-fire vegetation, and to a lesser extent to the time since fire.We came to the conclusion that the responses of bird communities to wildfires are heterogeneous, complex and context dependent. Large-scale monitoring datasets, such as DINDIS, might allow identifying factors acting at different spatial and temporal scales that affect the dynamics of species and communities, giving additional information on the causes under general trends observed using other monitoring systems

Wonderalp. Une science émerveillée. Les Alpes et la culture de la curiosité

WonderAlp est un cabinet de curiosités réalisé à partir d'une documentation provenant d'anciens ouvrages de voyages dans les Alpes. L'app présente des images de dragons, de fossiles, de cristaux, de plantes, d'animaux, de phénomènes naturels. Elle donne des clés pour retrouver et comprendre l'émerveillement devant la nature qui animait la science à l'époque de la curiosité (XVIe-XVIIIe siècles). WonderAlp is a cabinet of curiosities that transforms your iPad or Android into an Early Modern Wunderkammer. It displays objects discovered in the Alps during the early period of exploration. These are grouped under three titles : "Dragons of the Alps", "Fossils and Crystals", "Plants to Landscapes". It helps apprehend a natural world that is both rational and wonderful, scholarly and popular, unlike the compartmentalized thinking of modern life.

Phylogenomics Controlling for Base Compositional Bias Reveals a Single Origin of Eusociality in Corbiculate Bees.

As increasingly large molecular data sets are collected for phylogenomics, the conflicting phylogenetic signal among gene trees poses challenges to resolve some difficult nodes of the Tree of Life. Among these nodes, the phylogenetic position of the honey bees (Apini) within the corbiculate bee group remains controversial, despite its considerable importance for understanding the emergence and maintenance of eusociality. Here, we show that this controversy stems in part from pervasive phylogenetic conflicts among GC-rich gene trees. GC-rich genes typically have a high nucleotidic heterogeneity among species, which can induce topological conflicts among gene trees. When retaining only the most GC-homogeneous genes or using a nonhomogeneous model of sequence evolution, our analyses reveal a monophyletic group of the three lineages with a eusocial lifestyle (honey bees, bumble bees, and stingless bees). These phylogenetic relationships strongly suggest a single origin of eusociality in the corbiculate bees, with no reversal to solitary living in this group. To accurately reconstruct other important evolutionary steps across the Tree of Life, we suggest removing GC-rich and GC-heterogeneous genes from large phylogenomic data sets. Interpreted as a consequence of genome-wide variations in recombination rates, this GC effect can affect all taxa featuring GC-biased gene conversion, which is common in eukaryotes.

A matter of scale: apparent niche differentiation of diploid and tetraploid plants may depend on extent and grain of analysis

Aim: Emerging polyploids may depend on environmental niche shifts for successful establishment. Using the alpine plant Ranunculus kuepferi as a model system, we explore the niche shift hypothesis at different spatial resolutions and in contrasting parts of the species range. Location: European Alps. Methods: We sampled 12 individuals from each of 102 populations of R. kuepferi across the Alps, determined their ploidy levels, derived coarse-grain (100x100m) environmental descriptors for all sampling sites by downscaling WorldClim maps, and calculated fine-scale environmental descriptors (2x2m) from indicator values of the vegetation accompanying the sampled individuals. Both coarse and fine-scale variables were further computed for 8239 vegetation plots from across the Alps. Subsequently, we compared niche optima and breadths of diploid and tetraploid cytotypes by combining principal components analysis and kernel smoothing procedures. Comparisons were done separately for coarse and fine-grain data sets and for sympatric, allopatric and the total set of populations. Results: All comparisons indicate that the niches of the two cytotypes differ in optima and/or breadths, but results vary in important details. The whole-range analysis suggests differentiation along the temperature gradient to be most important. However, sympatric comparisons indicate that this climatic shift was not a direct response to competition with diploid ancestors. Moreover, fine-grained analyses demonstrate niche contraction of tetraploids, especially in the sympatric range, that goes undetected with coarse-grained data. Main conclusions: Although the niche optima of the two cytotypes differ, separation along ecological gradients was probably less decisive for polyploid establishment than a shift towards facultative apomixis, a particularly effective strategy to avoid minority cytotype exclusion. In addition, our results suggest that coarse-grained analyses overestimate niche breadths of widely distributed taxa. Niche comparison analyses should hence be conducted at environmental data resolutions appropriate for the organism and question under study.

TOP - um programa de cálculo de descritores topológicos para uso em correlações entre estrutura e atividade

A computational interface, using sybyl format as an input file, was created in order to calculate connectivity indexes. After generation and classification of all substructures, which derive from the molecular structure, this interface calculates all possible orders from zero up to the maximun number of bonds in the molecule. Other topological indexes such as Wiener and Schultz indexes can also be calculated.

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Visual SLAM for underwater vehicles using video velocity log and natural landmarks

A visual SLAM system has been implemented and optimised for real-time deployment on an AUV equipped with calibrated stereo cameras. The system incorporates a novel approach to landmark description in which landmarks are local sub maps that consist of a cloud of 3D points and their associated SIFT/SURF descriptors. Landmarks are also sparsely distributed which simplifies and accelerates data association and map updates. In addition to landmark-based localisation the system utilises visual odometry to estimate the pose of the vehicle in 6 degrees of freedom by identifying temporal matches between consecutive local sub maps and computing the motion. Both the extended Kalman filter and unscented Kalman filter have been considered for filtering the observations. The output of the filter is also smoothed using the Rauch-Tung-Striebel (RTS) method to obtain a better alignment of the sequence of local sub maps and to deliver a large-scale 3D acquisition of the surveyed area. Synthetic experiments have been performed using a simulation environment in which ray tracing is used to generate synthetic images for the stereo system

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal