975 resultados para EFFECTIVE SOLAR-RADIATION


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We present models predicting the potential distribution of a threatened ant species, Formica exsecta Nyl., in the Swiss National Park ( SNP). Data to fit the models have been collected according to a random-stratified design with an equal number of replicates per stratum. The basic aim of such a sampling strategy is to allow the formal testing of biological hypotheses about those factors most likely to account for the distribution of the modeled species. The stratifying factors used in this study were: vegetation, slope angle and slope aspect, the latter two being used as surrogates of solar radiation, considered one of the basic requirements of F. exsecta. Results show that, although the basic stratifying predictors account for more than 50% of the deviance, the incorporation of additional non-spatially explicit predictors into the model, as measured in the field, allows for an increased model performance (up to nearly 75%). However, this was not corroborated by permutation tests. Implementation on a national scale was made for one model only, due to the difficulty of obtaining similar predictors on this scale. The resulting map on the national scale suggests that the species might once have had a broader distribution in Switzerland. Reasons for its particular abundance within the SNP might possibly be related to habitat fragmentation and vegetation transformation outside the SNP boundaries.

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The long-term mean properties of the global climate system and those of turbulent fluid systems are reviewed from a thermodynamic viewpoint. Two general expressions are derived for a rate of entropy production due to thermal and viscous dissipation (turbulent dissipation) in a fluid system. It is shown with these expressions that maximum entropy production in the Earth s climate system suggested by Paltridge, as well as maximum transport properties of heat or momentum in a turbulent system suggested by Malkus and Busse, correspond to a state in which the rate of entropy production due to the turbulent dissipation is at a maximum. Entropy production due to absorption of solar radiation in the climate system is found to be irrelevant to the maximized properties associated with turbulence. The hypothesis of maximum entropy production also seems to be applicable to the planetary atmospheres of Mars and Titan and perhaps to mantle convection. Lorenz s conjecture on maximum generation of available potential energy is shown to be akin to this hypothesis with a few minor approximations. A possible mechanism by which turbulent fluid systems adjust themselves to the states of maximum entropy production is presented as a selffeedback mechanism for the generation of available potential energy. These results tend to support the hypothesis of maximum entropy production that underlies a wide variety of nonlinear fluid systems, including our planet as well as other planets and stars

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The potential ecological impact of ongoing climate change has been much discussed. High mountain ecosystems were identified early on as potentially very sensitive areas. Scenarios of upward species movement and vegetation shift are commonly discussed in the literature. Mountains being characteristically conic in shape, impact scenarios usually assume that a smaller surface area will be available as species move up. However, as the frequency distribution of additional physiographic factors (e.g., slope angle) changes with increasing elevation (e.g., with few gentle slopes available at higher elevation), species migrating upslope may encounter increasingly unsuitable conditions. As a result, many species could suffer severe reduction of their habitat surface, which could in turn affect patterns of biodiversity. In this paper, results from static plant distribution modeling are used to derive climate change impact scenarios in a high mountain environment. Models are adjusted with presence/absence of species. Environmental predictors used are: annual mean air temperature, slope, indices of topographic position, geology, rock cover, modeled permafrost and several indices of solar radiation and snow cover duration. Potential Habitat Distribution maps were drawn for 62 higher plant species, from which three separate climate change impact scenarios were derived. These scenarios show a great range of response, depending on the species and the degree of warming. Alpine species would be at greatest risk of local extinction, whereas species with a large elevation range would run the lowest risk. Limitations of the models and scenarios are further discussed.

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Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

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Résumé : Le glioblastome (GBM, WHO grade IV) est la tumeur cérébrale primaire la plus fréquente et la plus maligne, son pronostic reste très réservé et sa réponse aux différents traitements limitée. Récemment, une étude clinique randomisée (EORTC 26981/NCIC CE.3) a démontré que le traitement combiné de temozolomide et radiothérapie (RT/TMZ) est le meilleur dans les cas de GBM nouvellement diagnostiqués [1]. Cependant, seul un sous-groupe de patients bénéficie du traitement RT/TMZ et même parmi eux, leur survie reste très limitée. Pour tenter de mieux comprendre les réponses au traitement RT/TMZ, la biologie du GBM, identifier d'autres facteurs de résistance et découvrir de nouvelles cibles aux traitements, nous avons conduit une analyse moléculaire étendue à 73 patients inclus dans cette étude clinique. Nous avons complété les résultats moléculaires déjà obtenus par un profil génomique du nombre de copies par Array Comparative Genomic Hybridization. Afin d'atteindre nos objectifs, nous avons analysé en parallèle les données cliniques des patients et leurs profils moléculaires. Nos résultats confirment des analyses connues dans le domaine des aberrations du nombre de copies (CNA) et de profils du glioblastome. Nous avons observé une bonne corrélation entre le CNA génomique et l'expression de l'ARN messager dans le glioblastome et identifié un nouveau modèle de CNA du chromosome 7 pouvant présenter un intérêt clinique. Nous avons aussi observé par l'analyse du CNA que moins de 10% des glioblastomes conservent leurs mécanismes de suppression de tumeurs p53 et Rb1. Nous avons aussi observé que l'amplification du CDK4 peut constituer un facteur supplémentaire de résistance au traitement RT/TMZ, cette observation nécessite confirmation sur un plus grand nombre d'analyses. Nous avons montré que dans notre analyse des profils moléculaires et cliniques, il n'est pas possible de différencier le GBM à composante oligodendrogliale (GBM-O) du glioblastome. En superposant les profils moléculaires et les modèles expérimentaux in vitro, nous avons identifié WIF-1 comme un gène suppresseur de tumeur probable et une activation du signal WNT dans la pathologie du glioblastome. Ces observations pourraient servir à une meilleure compréhension de cette maladie dans le futur. Abstract : Glioblastoma, (GBM, WHO grade IV) is the most malignant and most frequent primary brain tumor with a very poor prognosis and response to therapy. A recent randomized clinical trial (EORTC26981/NCIC CE.3) established RT/TMZ as the 1St effective chemo-radiation therapy in newly diagnosed GBM [1]. However only a genetic subgroup of patients benefit from RT/TMZ and even in this subgroup overall survival remains very dismal. To explain the observed response to RT/TMZ, have a better understanding of GBM biology, identify other resistance factors and discover new drugable targets a comprehensive molecular analysis was performed in 73 of these GBM trial cohort. We complemented the available molecular data with a genomic copy number profiling by Array Comparative Genomic Hybridization. We proceeded to align the molecular profiles and the Clinical data, to meet our project objectives. Our data confirm known GBM Copy Number Aberrations and profiles. We observed a good correlation of genomic CN and mRNA expression in GBM, and identified new interesting CNA pattern for chromosome 7 with a potential clinical value. We also observed that by copy number aberration data alone, less than 10% of GBM have an intact p53 and Rb1 tumor .suppressor pathways. We equally observed that CDK4 amplification might constitute an additional RT/TMZ resistant factor, an observation that will need confirmation in a larger data set. We show that the molecular and clinical profiles in our data set, does not support the identification of GBM-O as a new entity in GBM. By combining the molecular profiles and in vitro model experiments we identify WIF1 as a potential GBM TSG and an activated WNT signaling as a pathologic event in GBM worth incorporation in attempts to better understand and impact outcome in this disease.

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Question: Outdoor workers can be exposed to intense ultraviolet (UV) solar radiation likely to results to sunburns. As sunburn is an important risk factor for skin cancer, in particular melanoma, we investigated the causes of occupational sunburns (OS) in French outdoor workers. Methods: A population-based survey was conducted in May-June 2012 through computer-assisted telephonic interviews in population 25 to 69 years of age. History of sunburn from occupational exposure within the year preceding interview was collected. We analysed the risk of OS in multivariate logistic regression. Results: Out of 1442 individuals who declared having an occupational exposure to solar UV radiation, 403 (27.9%) reported a sunburn from occupational exposure in the year preceding the interview. Sunburns were more frequent in women (30% vs. 26.4% in men although not significant p = 0.14), in younger workers (p = 0.0099), in sensitive phototype (40% in phototype I/II vs. 23% in phototype III/IV, p < 0.001) and in workers taking lunch outdoor (p = 0.0355). Some occupations were more associated with OS (more than 30%): health occupations, managing, research/engineering, construction workers and culture/art/social sciences workers. In multivariate analysis, risk factors for OS are phototype (I vs. IV, OR = 4.30 95% CI [2.65-6.98]), sunburn during leisure time (OR = 3.46 95% CI [2.62-4.59]), seasonality of exposure (seasonal vs. constant exposure OR = 1.36 95% CI [1.02-1.81] and annual UVA exposure (OR for 10J/m² daily average increment 1.08 95% CI [1.02-1.14]). In multivariate analysis the type of occupation was not associated with increased OS. Conclusion: Sunburns from occupation was also observed in non sensitive population, phototype IV, which shows that outdoor workers are potentially exposed to intense UV radiations. This study suggests that prevention should target UV sensitive outdoor workers as well as those cumulating intense UV exposure.

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The objective of this work was to develop a simplified numerical procedure for the estimation of accumulated monthly hours of solarized soil temperatures. The proposed model requires monthly means of daily solar radiation and maximum air temperature as input data, and a daily pattern of temperature variation assumed to be sine-shaped. The procedure was verified using observations made during the years 1992 and 1993 in Jaguariúna, SP. The proposed procedure can predict monthly temperature hours at 10 cm depth in the solarized soil, with acceptable accuracy, in the region for which it was developed.

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Recent studies on coffee (Coffea arabica L.) cultivation in agroforestry systems in Southern Brazil have shown the potential of partial shading to improve management of this crop. The objective of this work was to evaluate microclimatic conditions and their effects on coffee production of plants shaded with pigeon pea (Cajanus cajan) in comparison to unshaded ones, from May 2001 to August 2002 in Londrina, State of Paraná, Brazil. The appraised microclimatic characteristics were: global radiation, photosynthetic and radiation balance; air, leaf and soil temperatures; and soil humidity. Shading caused significant reduction in incident global solar radiation, photosynthetically active radiation and net radiation, and attenuated maximum leaf, air and soil temperatures, during the day. Shade also reduced the rate of cooling of night air and leaf temperatures, especially during nights with radiative frost. Soil moisture at 0-10 cm depth was higher under shade. The shaded coffee plants produced larger cherries due to slower maturation, resulting in larger bean size. Nevertheless, plants under shade emitted less plagiotropic branches, with smaller number of nodes per branch, and fewer nodes with fruits, resulting in a large reduction in coffee production. These results show the need to find an optimal tree density and management that do not compromise coffee production and protect against extreme temperatures.

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A conceptual framework for crop production efficiency was derived using thermodynamic efficiency concept, in order to generate a tool for performance evaluation of agricultural systems and to quantify the interference of determining factors on this performance. In Thermodynamics, efficiency is the ratio between the output and input of energy. To establish this relationship in agricultural systems, it was assumed that the input energy is represented by the attainable crop yield, as predicted through simulation models based on environmental variables. The method of FAO's agroecological zones was applied to the assessment of the attainable sugarcane yield, while Instituto Brasileiro de Geografia e Estatística (IBGE) data were used as observed yield. Sugarcane efficiency production in São Paulo state was evaluated in two growing seasons, and its correlation with some physical factors that regulate production was calculated. A strong relationship was identified between crop production efficiency and soil aptitude. This allowed inferring the effect of agribusiness factors on crop production efficiency. The relationships between production efficiency and climatic variables were also quantified and indicated that solar radiation, annual rainfall, water deficiency, and maximum air temperature are the main factors affecting the sugarcane production efficiency.

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Crops and forests are already responding to rising atmospheric carbon dioxide and air temperatures. Increasing atmospheric CO2 concentrations are expected to enhance plant photosynthesis. Nevertheless, after long-term exposure, plants acclimate and show a reduction in photosynthetic activity (i.e. down-regulation). If in the future the Earth"s temperature is allowed to rise further, plant ecosystems and food security will both face significant threats. The scientific community has recognized that an increase in global temperatures should remain below 2°C in order to combat climate change. All this evidence suggests that, in parallel with reductions in CO2 emissions, a more direct approach to mitigate global warming should be considered. We propose here that global warming could be partially mitigated directly through local bio-geoengineering approaches. For example, this could be done through the management of solar radiation at surface level, i.e. by increasing global albedo. Such an effect has been documented in the south-eastern part of Spain, where a significant surface air temperature trend of -0.3°C per decade has been observed due to a dramatic expansion of greenhouse horticulture.

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The objective of this work was to perform a quantitative analysis of the amino acid composition of soybean seeds as affected by climatic variables during seed filling. Amino acids were determined from seed samples taken at harvest in 31 multi-environment field trials carried out in Argentina. Total amino acids ranged from 31.69 to 49.14%, and total essential and nonessential amino acids varied from 12.83 to 19.02% and from 18.86 to 31.15%, respectively. Variance components expressed as the percentage of total variation showed that the environment was the most important source of variation for all traits, followed by the genotype x environment interaction. Significant explanatory linear regressions were detected for amino acid content regarding: average daily mean air temperature and cumulative solar radiation, during seed filling; precipitation minus potential evapotranspiration, during the whole reproductive period; and the combinations of these climatic variables. Each amino acid behaves differently according to environmental conditions, indicating compensatory effects among them.

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The objective of this work was to assess the spatial and temporal variability of sugarcane yield efficiency and yield gap in the state of São Paulo, Brazil, throughout 16 growing seasons, considering climate and soil as main effects, and socioeconomic factors as complementary. An empirical model was used to assess potential and attainable yields, using climate data series from 37 weather stations. Soil effects were analyzed using the concept of production environments associated with a soil aptitude map for sugarcane. Crop yield efficiency increased from 0.42 to 0.58 in the analyzed period (1990/1991 to 2005/2006 crop seasons), and yield gap consequently decreased from 58 to 42%. Climatic factors explained 43% of the variability of sugarcane yield efficiency, in the following order of importance: solar radiation, water deficit, maximum air temperature, precipitation, and minimum air temperature. Soil explained 15% of the variability, considering the average of all seasons. There was a change in the correlation pattern of climate and soil with yield efficiency after the 2001/2002 season, probably due to the crop expansion to the west of the state during the subsequent period. Socioeconomic, biotic and crop management factors together explain 42% of sugarcane yield efficiency in the state of São Paulo.

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The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry‑field conditions in São Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree‑days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in São Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree‑days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.

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The present paper is devoted to the results of experimental research undertaken into photocatalytical oxidation (PCO) of aqueous solutions of de-icing agents and aqueous extract of jet fuel. The report consists of introduction, literature review, description of materials and methods, discussion of results and conclusions. TiO2 was selected as a photocatalyst for the experiments with synthetic solutions of ethylene glycol, 2-ethoxyethanol and aqueous extract of jet fuel. To explain the PCO mechanisms affecting certain behaviour of de-icing agent under distinctive conditions, the following factors were studied: the impact of initial concentration of pollutant, the role of pH, the presence of tert-butanol as OH·-radicals scavenger and mineral admixtures. PCO under solar radiation performed in two ways: catalysed by irradiated TiO2 slurry or by TiO2 attached to buoyant hollow glass micro-spheres. Special attention was paid to the energy-saving PCO with reduced intensity mixing of the slurry. The effect of PCO was assessed by determination of residual chemical oxygen demand of solution (COD) and by measuring of concentration of glycols. The PCO process efficiency was assumed to be dependent on the TiO2 suspension fractional composition. Thus, the following effects of solutions’ media were viewed: presence of organic admixtures, pH influence, mixing mode during the PCO. The effects of mineral admixtures - Ca2+, Fe3+/2+, Mn2+, SO42- - that are often present in natural and wastewater systems or produced during the degradation of organic pollutants and which can affect the rate of PCO of de-icing agents, were also investigated.