996 resultados para Environmental color


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Selostus: Korkealla virranvoimakkuudella tainnutettujen broilereiden rintafileen irroitushetken vaikutus lihaksen leikkausvoiman vastukseen, pH:hon, keittohävikkiin ja väriin

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We present new geochemical and sedimentological data from marginal marine strata of Penarth Bay, south Wales (UK) to elucidate the origin of widespread but enigmatic concentrations of vertebrate hard parts (bonebeds) in marine successions of Rhaetian age (late Triassic). Sedimentological evidence shows that the phosphatic constituents of the bonebeds were subjected to intense phosphatization in shallow current-dominated settings and subsequently reworked and transported basinward by storms. Interbedded organic-rich strata deposited under quiescent and poorly oxygenated conditions record enhanced phosphorus regeneration from sedimentary organic matter into the water column and probably provided the main source of phosphate required for heavy bonebed clast phosphatization. The stratigraphically limited interval showing evidence for oxygen depletion and accelerated P-cycling coincides with a negative 4% organic carbon isotope excursion, which possibly reflects supra-regional changes in carbon cycling and clearly predates the 'initial isotope excursion' characterizing many Triassic-Jurassic boundary strata. our data indicate that Rhaetian bonebeds are the lithological signature of profound, climatically driven changes in carbon cycling and redox conditions and support the idea of a multi-pulsed environmental crisis at the end of the Triassic, possibly linked to successive episodes of igneous activity in the central Atlantic Magmatic Province.

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The paper deals with the development and application of the generic methodology for automatic processing (mapping and classification) of environmental data. General Regression Neural Network (GRNN) is considered in detail and is proposed as an efficient tool to solve the problem of spatial data mapping (regression). The Probabilistic Neural Network (PNN) is considered as an automatic tool for spatial classifications. The automatic tuning of isotropic and anisotropic GRNN/PNN models using cross-validation procedure is presented. Results are compared with the k-Nearest-Neighbours (k-NN) interpolation algorithm using independent validation data set. Real case studies are based on decision-oriented mapping and classification of radioactively contaminated territories.

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A lot of research in cognition and decision making suffers from a lack of formalism. The quantum probability program could help to improve this situation, but we wonder whether it would provide even more added value if its presumed focus on outcome models were complemented by process models that are, ideally, informed by ecological analyses and integrated into cognitive architectures.

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Discriminating complex sounds relies on multiple stages of differential brain activity. The specific roles of these stages and their links to perception were the focus of the present study. We presented 250ms duration sounds of living and man-made objects while recording 160-channel electroencephalography (EEG). Subjects categorized each sound as that of a living, man-made or unknown item. We tested whether/when the brain discriminates between sound categories even when not transpiring behaviorally. We applied a single-trial classifier that identified voltage topographies and latencies at which brain responses are most discriminative. For sounds that the subjects could not categorize, we could successfully decode the semantic category based on differences in voltage topographies during the 116-174ms post-stimulus period. Sounds that were correctly categorized as that of a living or man-made item by the same subjects exhibited two periods of differences in voltage topographies at the single-trial level. Subjects exhibited differential activity before the sound ended (starting at 112ms) and on a separate period at ~270ms post-stimulus onset. Because each of these periods could be used to reliably decode semantic categories, we interpreted the first as being related to an implicit tuning for sound representations and the second as being linked to perceptual decision-making processes. Collectively, our results show that the brain discriminates environmental sounds during early stages and independently of behavioral proficiency and that explicit sound categorization requires a subsequent processing stage.

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Knowledge of the role of origin-related, environmental, sex, and age factors on host defence mechanisms is important to understand variation in parasite intensity. Because alternative components of parasite defence may be differently sensitive to various factors, they may not necessarily covary. Many components should therefore be considered to tackle the evolution of host-parasite interactions. In a population of barn owls (Tyto alba), we investigated the role of origin-related, environmental (i.e. year, season, nest of rearing, and body condition), sex, and age factors on 12 traits linked to immune responses [humoral immune responses towards sheep red blood cells (SRBC), human serum albumin (HSA) and toxoid toxin TT, T-cell mediated immune response towards the mitogen phytohemagglutinin (PHA)], susceptibility to ectoparasites (number and fecundity of Carnus haemapterus, number of Ixodes ricinus), and disease symptoms (size of the bursa of Fabricius and spleen, proportion of proteins that are immunoglobulins, haematocrit and blood concentration in leucocytes). Cross-fostering experiments allowed us to detect a heritable component of variation in only four out of nine immune and parasitic parameters (i.e. SRBC- and HSA-responses, haematocrit, and number of C. haemapterus). However, because nestlings were not always cross-fostered just after hatching, the finding that 44% of the immune and parasitic parameters were heritable is probably an overestimation. These experiments also showed that five out of these nine parameters were sensitive to the nest environment (i.e. SRBC- and PHA-responses, number of C. haemapterus, haematocrit and blood concentration in leucocytes). Female nestlings were more infested by the blood-sucking fly C. haemapterus than their male nestmates, and their blood was less concentrated in leucocytes. The effect of year, season, age (i.e. reflecting the degree of maturation of the immune system), brood size, position in the within-brood age hierarchy, and body mass strongly differed between the 12 parameters. Different components of host defence mechanisms are therefore not equally heritable and sensitive to environmental, sex, and age factors, potentially explaining why most of these components did not covary.

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Summary

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The distribution of plants along environmental gradients is constrained by abiotic and biotic factors. Cumulative evidence attests of the impact of biotic factors on plant distributions, but only few studies discuss the role of belowground communities. Soil fungi, in particular, are thought to play an important role in how plant species assemble locally into communities. We first review existing evidence, and then test the effect of the number of soil fungal operational taxonomic units (OTUs) on plant species distributions using a recently collected dataset of plant and metagenomic information on soil fungi in the Western Swiss Alps. Using species distribution models (SDMs), we investigated whether the distribution of individual plant species is correlated to the number of OTUs of two important soil fungal classes known to interact with plants: the Glomeromycetes, that are obligatory symbionts of plants, and the Agaricomycetes, that may be facultative plant symbionts, pathogens, or wood decayers. We show that including the fungal richness information in the models of plant species distributions improves predictive accuracy. Number of fungal OTUs is especially correlated to the distribution of high elevation plant species. We suggest that high elevation soil show greater variation in fungal assemblages that may in turn impact plant turnover among communities. We finally discuss how to move beyond correlative analyses, through the design of field experiments manipulating plant and fungal communities along environmental gradients.

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The present research deals with an application of artificial neural networks for multitask learning from spatial environmental data. The real case study (sediments contamination of Geneva Lake) consists of 8 pollutants. There are different relationships between these variables, from linear correlations to strong nonlinear dependencies. The main idea is to construct a subsets of pollutants which can be efficiently modeled together within the multitask framework. The proposed two-step approach is based on: 1) the criterion of nonlinear predictability of each variable ?k? by analyzing all possible models composed from the rest of the variables by using a General Regression Neural Network (GRNN) as a model; 2) a multitask learning of the best model using multilayer perceptron and spatial predictions. The results of the study are analyzed using both machine learning and geostatistical tools.

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Naive scale invariance is not a true property of natural images. Natural monochrome images possess a much richer geometrical structure, which is particularly well described in terms of multiscaling relations. This means that the pixels of a given image can be decomposed into sets, the fractal components of the image, with well-defined scaling exponents [Turiel and Parga, Neural Comput. 12, 763 (2000)]. Here it is shown that hyperspectral representations of natural scenes also exhibit multiscaling properties, observing the same kind of behavior. A precise measure of the informational relevance of the fractal components is also given, and it is shown that there are important differences between the intrinsically redundant red-green-blue system and the decorrelated one defined in Ruderman, Cronin, and Chiao [J. Opt. Soc. Am. A 15, 2036 (1998)].

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La pression exercée par les activités humaines menace pratiquement tous les écosystèmes aquatiques du globe. Ainsi, sous l'effet de divers facteurs tels que la pollution, le réchauffement climatique ou encore la pêche industrielle, de nombreuses populations de poissons ont vu leurs effectifs chuter et divers changements morphologiques ont été observés. Dans cette étude, nous nous sommes intéressés à une menace particulière: la sélection induite par la pêche sur la croissance des poissons. En effet, la génétique des populations prédit que la soustraction régulière des individus les plus gros peut entraîner des modifications rapides de certains traits physiques comme la croissance individuelle. Cela a par ailleurs été observé dans de nombreuses populations marines ou lacustres, dont les populations de féras, bondelles et autres corégones des lacs suisses. Toutefois, malgré un nombre croissant d'études décrivant ce phénomène, peu de plans de gestion en tiennent compte, car l'importance des effets génétiques liés à la pêche est le plus souvent négligée par rapport à l'impact des changements environnementaux. Le but premier de cette étude a donc été de quantifier l'importance des facteurs génétiques et environnementaux. Dans le premier chapitre, nous avons étudié la population de palée du lac de Joux (Coregonus palaea). Nous avons déterminé les différentiels de sélection dus à la pêche, c'est-à-dire l'intensité de la sélection sur le taux de croissance, ainsi que les changements nets de croissance au cours du temps. Nous avons observé une baisse marquée de croissance et un différentiel de sélection important indiquant qu'au moins 30% de la diminution de croissance observée était due à la pression de sélection induite par la pêche. Dans le deuxième chapitre, nous avons effectué les mêmes analyses sur deux espèces proches du lac de Brienz (C. albellus et C. fatioi) et avons observé des effets similaires dont l'intensité était spécifique à chaque espèce. Dans le troisième chapitre, nous avons analysé deux autres espèces : C. palaea et C. confusus du lac de Bienne, et avons constaté que le lien entre la pression de sélection et la diminution de croissance était influencé par des facteurs environnementaux. Finalement, dans le dernier chapitre, nous avons étudié les effets potentiels de différentes modifications de la taille des mailles des filets utilisés pour la pêche à l'aide de modèles mathématiques. Nous concluons que la pêche a un effet génétique non négligeable (et donc peu réversible) sur la croissance individuelle dans les populations observée, que cet effet est lié à la compétition pour la nourriture et à la qualité de l'environnement, et que certaines modifications simples de la taille des mailles des filets de pêche pourraient nettement diminuer l'effet de sélection et ainsi ralentir, voir même renverser la diminution de croissance observée.

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