915 resultados para Environmental assessment tools


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This is the report of the first workshop on Incorporating In Vitro Alternative Methods for Developmental Neurotoxicity (DNT) Testing into International Hazard and Risk Assessment Strategies, held in Ispra, Italy, on 19-21 April 2005. The workshop was hosted by the European Centre for the Validation of Alternative Methods (ECVAM) and jointly organized by ECVAM, the European Chemical Industry Council, and the Johns Hopkins University Center for Alternatives to Animal Testing. The primary aim of the workshop was to identify and catalog potential methods that could be used to assess how data from in vitro alternative methods could help to predict and identify DNT hazards. Working groups focused on two different aspects: a) details on the science available in the field of DNT, including discussions on the models available to capture the critical DNT mechanisms and processes, and b) policy and strategy aspects to assess the integration of alternative methods in a regulatory framework. This report summarizes these discussions and details the recommendations and priorities for future work.

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INTRODUCTION: Ventilator-associated pneumonia remains the most common nosocomial infection in the critically ill and contributes to significant morbidity. Eventual decisions regarding withdrawal or maximal therapy are demanding and rely on physicians' experience. Additional objective tools for risk assessment may improve medical judgement. Copeptin, reflecting vasopressin release, as well as the Sequential Organ Failure Assessment (SOFA) score, reflecting the individual degree of organ dysfunction, might qualify for survival prediction in ventilator-associated pneumonia. We investigated the predictive value of the SOFA score and copeptin in ventilator-associated pneumonia. METHODS: One hundred one patients with ventilator-associated pneumonia were prospectively assessed. Death within 28 days after ventilator-associated pneumonia onset was the primary end point. RESULTS: The SOFA score and the copeptin levels at ventilator-associated pneumonia onset were significantly elevated in nonsurvivors (P = .002 and P = .017, respectively). Both markers had different time courses in survivors and nonsurvivors (P < .001 and P = .006). Mean SOFA (average SOFA of 10 days after VAP onset) was superior in predicting 28-day survival as compared with SOFA and copeptin at ventilator-associated pneumonia onset (area under the curve, 0.90 vs 0.73 and 0.67, respectively). CONCLUSIONS: The predictive value of serial-measured SOFA significantly exceeds those of single SOFA and copeptin measurements. Serial SOFA scores accurately predict outcome in ventilator-associated pneumonia.

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Biofuels are considered as a promising substitute for fossil fuels when considering the possible reduction of greenhouse gases emissions. However limiting their impacts on potential benefits for reducing climate change is shortsighted. Global sustainability assessments are necessary to determine the sustainability of supply chains. We propose a new global criterion based framework enabling a comprehensive international comparison of bioethanol supply chains. The interest of this framework is that the selection of the sustainability indicators is qualified on three criterions: relevance, reliability and adaptability to the local context. Sustainability issues have been handled along environmental, social and economical issues. This new framework has been applied for a specific issue: from a Swiss perspective, is locally produced bioethanol in Switzerland more sustainable than imported from Brazil? Thanks to this framework integrating local context in its indicator definition, Brazilian production of bioethanol is shown as energy efficient and economically interesting for Brazil. From a strictly economic point of view, bioethanol production within Switzerland is not justified for Swiss consumption and questionable for the environmental issue. The social dimension is delicate to assess due to the lack of reliable data and is strongly linked to the agricultural policy in both countries. There is a need of establishing minimum sustainability criteria for imported bioethanol to avoid unwanted negative or leakage effects.

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The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.

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INTRODUCTION: Occupational exposure to bioaerosols in wastewater treatment plants (WWTP) and its consequence on workers׳ health are well documented. Most studies were devoted to enumerating and identifying cultivable bacteria and fungi, as well as measuring concentrations of airborne endotoxins, as these are the main health-related factors found in WWTP. Surprisingly, very few studies have investigated the presence and concentrations of airborne virus in WWTP. However, many enteric viruses are present in wastewater and, due to their small size, they should become aerosolized. Two in particular, the norovirus and the adenovirus, are extremely widespread and are the major causes of infectious gastrointestinal diseases reported around the world. The third one, hepatitis E virus, has an emerging status. GOAL AND METHODS: This study׳s objectives were to detect and quantify the presence and concentrations of 3 different viruses (adenovirus, norovirus and the hepatitis E virus) in air samples from 31 WWTPs by using quantitative polymerase chain reaction (qPCR) during two different seasons and two consecutive years. RESULTS: Adenovirus was present in 100% of summer WWTP samples and 97% of winter samples. The highest airborne concentration measured was 2.27×10(6) genome equivalent/m(3) and, on average, these were higher in summer than in winter. Norovirus was detected in only 3 of the 123 air samples, and the hepatitis E virus was not detected. CONCLUSIONS: Concentrations of potentially pathogenic viral particles in WWTP air are non-negligible and could partly explain the work-related gastrointestinal symptoms often reported in employees in this sector.

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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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Ces dernières années, de nombreuses recherches ont mis en évidence les effets toxiques des micropolluants organiques pour les espèces de nos lacs et rivières. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, alors que les organismes sont exposés tous les jours à des milliers de substances en mélange. Or les effets de ces cocktails ne sont pas négligeables. Cette thèse de doctorat s'est ainsi intéressée aux modèles permettant de prédire le risque environnemental de ces cocktails pour le milieu aquatique. Le principal objectif a été d'évaluer le risque écologique des mélanges de substances chimiques mesurées dans le Léman, mais aussi d'apporter un regard critique sur les méthodologies utilisées afin de proposer certaines adaptations pour une meilleure estimation du risque. Dans la première partie de ce travail, le risque des mélanges de pesticides et médicaments pour le Rhône et pour le Léman a été établi en utilisant des approches envisagées notamment dans la législation européenne. Il s'agit d'approches de « screening », c'est-à-dire permettant une évaluation générale du risque des mélanges. Une telle approche permet de mettre en évidence les substances les plus problématiques, c'est-à-dire contribuant le plus à la toxicité du mélange. Dans notre cas, il s'agit essentiellement de 4 pesticides. L'étude met également en évidence que toutes les substances, même en trace infime, contribuent à l'effet du mélange. Cette constatation a des implications en terme de gestion de l'environnement. En effet, ceci implique qu'il faut réduire toutes les sources de polluants, et pas seulement les plus problématiques. Mais l'approche proposée présente également un biais important au niveau conceptuel, ce qui rend son utilisation discutable, en dehors d'un screening, et nécessiterait une adaptation au niveau des facteurs de sécurité employés. Dans une deuxième partie, l'étude s'est portée sur l'utilisation des modèles de mélanges dans le calcul de risque environnemental. En effet, les modèles de mélanges ont été développés et validés espèce par espèce, et non pour une évaluation sur l'écosystème en entier. Leur utilisation devrait donc passer par un calcul par espèce, ce qui est rarement fait dû au manque de données écotoxicologiques à disposition. Le but a été donc de comparer, avec des valeurs générées aléatoirement, le calcul de risque effectué selon une méthode rigoureuse, espèce par espèce, avec celui effectué classiquement où les modèles sont appliqués sur l'ensemble de la communauté sans tenir compte des variations inter-espèces. Les résultats sont dans la majorité des cas similaires, ce qui valide l'approche utilisée traditionnellement. En revanche, ce travail a permis de déterminer certains cas où l'application classique peut conduire à une sous- ou sur-estimation du risque. Enfin, une dernière partie de cette thèse s'est intéressée à l'influence que les cocktails de micropolluants ont pu avoir sur les communautés in situ. Pour ce faire, une approche en deux temps a été adoptée. Tout d'abord la toxicité de quatorze herbicides détectés dans le Léman a été déterminée. Sur la période étudiée, de 2004 à 2009, cette toxicité due aux herbicides a diminué, passant de 4% d'espèces affectées à moins de 1%. Ensuite, la question était de savoir si cette diminution de toxicité avait un impact sur le développement de certaines espèces au sein de la communauté des algues. Pour ce faire, l'utilisation statistique a permis d'isoler d'autres facteurs pouvant avoir une influence sur la flore, comme la température de l'eau ou la présence de phosphates, et ainsi de constater quelles espèces se sont révélées avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps. Fait intéressant, une partie d'entre-elles avait déjà montré des comportements similaires dans des études en mésocosmes. En conclusion, ce travail montre qu'il existe des modèles robustes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques, et qu'ils peuvent être utilisés pour expliquer le rôle des substances dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application. - Depuis plusieurs années, les risques que posent les micropolluants organiques pour le milieu aquatique préoccupent grandement les scientifiques ainsi que notre société. En effet, de nombreuses recherches ont mis en évidence les effets toxiques que peuvent avoir ces substances chimiques sur les espèces de nos lacs et rivières, quand elles se retrouvent exposées à des concentrations aiguës ou chroniques. Cependant, la plupart de ces études se sont focalisées sur la toxicité des substances individuelles, c'est à dire considérées séparément. Actuellement, il en est de même dans les procédures de régulation européennes, concernant la partie évaluation du risque pour l'environnement d'une substance. Or, les organismes sont exposés tous les jours à des milliers de substances en mélange, et les effets de ces "cocktails" ne sont pas négligeables. L'évaluation du risque écologique que pose ces mélanges de substances doit donc être abordé par de la manière la plus appropriée et la plus fiable possible. Dans la première partie de cette thèse, nous nous sommes intéressés aux méthodes actuellement envisagées à être intégrées dans les législations européennes pour l'évaluation du risque des mélanges pour le milieu aquatique. Ces méthodes sont basées sur le modèle d'addition des concentrations, avec l'utilisation des valeurs de concentrations des substances estimées sans effet dans le milieu (PNEC), ou à partir des valeurs des concentrations d'effet (CE50) sur certaines espèces d'un niveau trophique avec la prise en compte de facteurs de sécurité. Nous avons appliqué ces méthodes à deux cas spécifiques, le lac Léman et le Rhône situés en Suisse, et discuté les résultats de ces applications. Ces premières étapes d'évaluation ont montré que le risque des mélanges pour ces cas d'étude atteint rapidement une valeur au dessus d'un seuil critique. Cette valeur atteinte est généralement due à deux ou trois substances principales. Les procédures proposées permettent donc d'identifier les substances les plus problématiques pour lesquelles des mesures de gestion, telles que la réduction de leur entrée dans le milieu aquatique, devraient être envisagées. Cependant, nous avons également constaté que le niveau de risque associé à ces mélanges de substances n'est pas négligeable, même sans tenir compte de ces substances principales. En effet, l'accumulation des substances, même en traces infimes, atteint un seuil critique, ce qui devient plus difficile en terme de gestion du risque. En outre, nous avons souligné un manque de fiabilité dans ces procédures, qui peuvent conduire à des résultats contradictoires en terme de risque. Ceci est lié à l'incompatibilité des facteurs de sécurité utilisés dans les différentes méthodes. Dans la deuxième partie de la thèse, nous avons étudié la fiabilité de méthodes plus avancées dans la prédiction de l'effet des mélanges pour les communautés évoluant dans le système aquatique. Ces méthodes reposent sur le modèle d'addition des concentrations (CA) ou d'addition des réponses (RA) appliqués sur les courbes de distribution de la sensibilité des espèces (SSD) aux substances. En effet, les modèles de mélanges ont été développés et validés pour être appliqués espèce par espèce, et non pas sur plusieurs espèces agrégées simultanément dans les courbes SSD. Nous avons ainsi proposé une procédure plus rigoureuse, pour l'évaluation du risque d'un mélange, qui serait d'appliquer d'abord les modèles CA ou RA à chaque espèce séparément, et, dans une deuxième étape, combiner les résultats afin d'établir une courbe SSD du mélange. Malheureusement, cette méthode n'est pas applicable dans la plupart des cas, car elle nécessite trop de données généralement indisponibles. Par conséquent, nous avons comparé, avec des valeurs générées aléatoirement, le calcul de risque effectué selon cette méthode plus rigoureuse, avec celle effectuée traditionnellement, afin de caractériser la robustesse de cette approche qui consiste à appliquer les modèles de mélange sur les courbes SSD. Nos résultats ont montré que l'utilisation de CA directement sur les SSDs peut conduire à une sous-estimation de la concentration du mélange affectant 5 % ou 50% des espèces, en particulier lorsque les substances présentent un grand écart- type dans leur distribution de la sensibilité des espèces. L'application du modèle RA peut quant à lui conduire à une sur- ou sous-estimations, principalement en fonction de la pente des courbes dose- réponse de chaque espèce composant les SSDs. La sous-estimation avec RA devient potentiellement importante lorsque le rapport entre la EC50 et la EC10 de la courbe dose-réponse des espèces est plus petit que 100. Toutefois, la plupart des substances, selon des cas réels, présentent des données d' écotoxicité qui font que le risque du mélange calculé par la méthode des modèles appliqués directement sur les SSDs reste cohérent et surestimerait plutôt légèrement le risque. Ces résultats valident ainsi l'approche utilisée traditionnellement. Néanmoins, il faut garder à l'esprit cette source d'erreur lorsqu'on procède à une évaluation du risque d'un mélange avec cette méthode traditionnelle, en particulier quand les SSD présentent une distribution des données en dehors des limites déterminées dans cette étude. Enfin, dans la dernière partie de cette thèse, nous avons confronté des prédictions de l'effet de mélange avec des changements biologiques observés dans l'environnement. Dans cette étude, nous avons utilisé des données venant d'un suivi à long terme d'un grand lac européen, le lac Léman, ce qui offrait la possibilité d'évaluer dans quelle mesure la prédiction de la toxicité des mélanges d'herbicide expliquait les changements dans la composition de la communauté phytoplanctonique. Ceci à côté d'autres paramètres classiques de limnologie tels que les nutriments. Pour atteindre cet objectif, nous avons déterminé la toxicité des mélanges sur plusieurs années de 14 herbicides régulièrement détectés dans le lac, en utilisant les modèles CA et RA avec les courbes de distribution de la sensibilité des espèces. Un gradient temporel de toxicité décroissant a pu être constaté de 2004 à 2009. Une analyse de redondance et de redondance partielle, a montré que ce gradient explique une partie significative de la variation de la composition de la communauté phytoplanctonique, même après avoir enlevé l'effet de toutes les autres co-variables. De plus, certaines espèces révélées pour avoir été influencées, positivement ou négativement, par la diminution de la toxicité dans le lac au fil du temps, ont montré des comportements similaires dans des études en mésocosmes. On peut en conclure que la toxicité du mélange herbicide est l'un des paramètres clés pour expliquer les changements de phytoplancton dans le lac Léman. En conclusion, il existe diverses méthodes pour prédire le risque des mélanges de micropolluants sur les espèces aquatiques et celui-ci peut jouer un rôle dans le fonctionnement des écosystèmes. Toutefois, ces modèles ont bien sûr des limites et des hypothèses sous-jacentes qu'il est important de considérer lors de leur application, avant d'utiliser leurs résultats pour la gestion des risques environnementaux. - For several years now, the scientists as well as the society is concerned by the aquatic risk organic micropollutants may pose. Indeed, several researches have shown the toxic effects these substances may induce on organisms living in our lakes or rivers, especially when they are exposed to acute or chronic concentrations. However, most of the studies focused on the toxicity of single compounds, i.e. considered individually. The same also goes in the current European regulations concerning the risk assessment procedures for the environment of these substances. But aquatic organisms are typically exposed every day simultaneously to thousands of organic compounds. The toxic effects resulting of these "cocktails" cannot be neglected. The ecological risk assessment of mixtures of such compounds has therefore to be addressed by scientists in the most reliable and appropriate way. In the first part of this thesis, the procedures currently envisioned for the aquatic mixture risk assessment in European legislations are described. These methodologies are based on the mixture model of concentration addition and the use of the predicted no effect concentrations (PNEC) or effect concentrations (EC50) with assessment factors. These principal approaches were applied to two specific case studies, Lake Geneva and the River Rhône in Switzerland, including a discussion of the outcomes of such applications. These first level assessments showed that the mixture risks for these studied cases exceeded rapidly the critical value. This exceeding is generally due to two or three main substances. The proposed procedures allow therefore the identification of the most problematic substances for which management measures, such as a reduction of the entrance to the aquatic environment, should be envisioned. However, it was also showed that the risk levels associated with mixtures of compounds are not negligible, even without considering these main substances. Indeed, it is the sum of the substances that is problematic, which is more challenging in term of risk management. Moreover, a lack of reliability in the procedures was highlighted, which can lead to contradictory results in terms of risk. This result is linked to the inconsistency in the assessment factors applied in the different methods. In the second part of the thesis, the reliability of the more advanced procedures to predict the mixture effect to communities in the aquatic system were investigated. These established methodologies combine the model of concentration addition (CA) or response addition (RA) with species sensitivity distribution curves (SSD). Indeed, the mixture effect predictions were shown to be consistent only when the mixture models are applied on a single species, and not on several species simultaneously aggregated to SSDs. Hence, A more stringent procedure for mixture risk assessment is proposed, that would be to apply first the CA or RA models to each species separately and, in a second step, to combine the results to build an SSD for a mixture. Unfortunately, this methodology is not applicable in most cases, because it requires large data sets usually not available. Therefore, the differences between the two methodologies were studied with datasets created artificially to characterize the robustness of the traditional approach applying models on species sensitivity distribution. The results showed that the use of CA on SSD directly might lead to underestimations of the mixture concentration affecting 5% or 50% of species, especially when substances present a large standard deviation of the distribution from the sensitivity of the species. The application of RA can lead to over- or underestimates, depending mainly on the slope of the dose-response curves of the individual species. The potential underestimation with RA becomes important when the ratio between the EC50 and the EC10 for the dose-response curve of the species composing the SSD are smaller than 100. However, considering common real cases of ecotoxicity data for substances, the mixture risk calculated by the methodology applying mixture models directly on SSDs remains consistent and would rather slightly overestimate the risk. These results can be used as a theoretical validation of the currently applied methodology. Nevertheless, when assessing the risk of mixtures, one has to keep in mind this source of error with this classical methodology, especially when SSDs present a distribution of the data outside the range determined in this study Finally, in the last part of this thesis, we confronted the mixture effect predictions with biological changes observed in the environment. In this study, long-term monitoring of a European great lake, Lake Geneva, provides the opportunity to assess to what extent the predicted toxicity of herbicide mixtures explains the changes in the composition of the phytoplankton community next to other classical limnology parameters such as nutrients. To reach this goal, the gradient of the mixture toxicity of 14 herbicides regularly detected in the lake was calculated, using concentration addition and response addition models. A decreasing temporal gradient of toxicity was observed from 2004 to 2009. Redundancy analysis and partial redundancy analysis showed that this gradient explains a significant portion of the variation in phytoplankton community composition, even when having removed the effect of all other co-variables. Moreover, some species that were revealed to be influenced positively or negatively, by the decrease of toxicity in the lake over time, showed similar behaviors in mesocosms studies. It could be concluded that the herbicide mixture toxicity is one of the key parameters to explain phytoplankton changes in Lake Geneva. To conclude, different methods exist to predict the risk of mixture in the ecosystems. But their reliability varies depending on the underlying hypotheses. One should therefore carefully consider these hypotheses, as well as the limits of the approaches, before using the results for environmental risk management

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ABSTRACT Quantitative assessment of soil physical quality is of great importance for eco-environmental pollution and soil quality studies. In this paper, based on the S-theory, data from 16 collection sites in the Haihe River Basin in northern China were used, and the effects of soil particle size distribution and bulk density on three important indices of theS-theory were investigated on a regional scale. The relationships between unsaturated hydraulic conductivityKi at the inflection point and S values (S/hi) were also studied using two different types of fitting equations. The results showed that the polynomial equation was better than the linear equation for describing the relationships between -log Ki and -logS, and -log Kiand -log (S/hi)2; and clay content was the most important factor affecting the soil physical quality index (S). The variation in the S index according to soil clay content was able to be fitted using a double-linear-line approach, with decrease in the S index being much faster for clay content less than 20 %. In contrast, the bulk density index was found to be less important than clay content. The average S index was 0.077, indicating that soil physical quality in the Haihe River Basin was good.

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ABSTRACT Heavy metals contained in electronic waste, if discarded improperly, can become bioavailable after vermicomposting, posing a risk to the environment. Small-scale vermicomposting experiments were carried out with printed circuit boards (PCBs) to investigate the migration of heavy metals (Cu, Pb, Zn, Ni, and Sn) to the final compost, as well as the mobility and bioavailability of these metals. High total levels of Pb, Sn and Cu in samples of manure with electronic waste (MEW) and vegetables with electronic waste (VEW) were detected. Based on the initial metal levels in the PCBs and their concentration in the resulting compost, the order of migration of these metals to the MEW and VEW samples was Sn (23.1 %)>Pb (18.4 %)>Ni (4.63 %)>Zn (0.46 %)>Cu (0.14 %) and Sn (24.3 %)>Pb (23.6 %)>Ni (11.33 %)>Zn (1.76 %)>Cu (0.60 %), respectively. Mobility and bioavailability of these metals in the compost were evaluated by three-stage sequential extraction, where F1 was the exchangeable fraction, F2 the organic fraction and F3 the residual fraction. The bioavailability factor (BF) was calculated by the ratio of the sum of fractions F1 and F2 divided by the total sum of the fractions (F1 + F2 + F3). The highest bioavailability factor (BF = 0.92) was found for Pb, the heavy metal considered the greatest environmental concern in this study, indicating the high mobility and the possibility of becoming bioavailable of this metal.

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Because of the development of modern transportation facilities, an ever rising number of individuals including many patients with preexisting diseases visit high-altitude locations (>2500 m). High-altitude exposure triggers a series of physiologic responses intended to maintain an adequate tissue oxygenation. Even in normal subjects, there is enormous interindividual variability in these responses that may be further amplified by environmental factors such as cold temperature, low humidity, exercise, and stress. These adaptive mechanisms, although generally tolerated by most healthy subjects, may induce major problems in patients with preexisting cardiovascular diseases in which the functional reserves are already limited. Preexposure assessment of patients helps to minimize risk and detect contraindications to high-altitude exposure. Moreover, the great variability and nonpredictability of the adaptive response should encourage physicians counseling such patients to adapt a cautionary approach. Here, we will briefly review how high-altitude adjustments may interfere with and aggravate/decompensate preexisting cardiovascular diseases. Moreover, we will provide practical recommendations on how to investigate and counsel patients with cardiovascular disease desiring to travel to high-altitude locations.

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The legislatives evolutions imply an important recourse to the psychiatric expertise in order to evaluate the potential dangerousness of a subject. However, in spite of the development of techniques and tools for this evaluation, the dangerousness assessment of a subject is in practice extremely complex and discussed in the scientific literature. The evolution of the concept of dangerousness to the risk assessment involved a technicisation of this evaluation which should not make forget the limits of these tools and the need for restoring the subject, the meaning and the clinic in this evaluation.

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Weathering steel is commonly used as a cost-effective alternative for bridge superstructures, as the costs and environmental impacts associated with the maintenance/replacement of paint coatings are theoretically eliminated. The performance of weathering steel depends on the proper formation of a surface patina, which consists of a dense layer of corrosion product used to protect the steel from further atmospheric corrosion. The development of the weathering steel patina may be hindered by environmental factors such as humid environments, wetting/drying cycles, sheltering, exposure to de-icing chlorides, and design details that permit water to pond on steel surfaces. Weathering steel bridges constructed over or adjacent to other roadways could be subjected to sufficient salt spray that would impede the development of an adequate patina. Addressing areas of corrosion on a weathering steel bridge superstructure where a protective patina has not formed is often costly and negates the anticipated cost savings for this type of steel superstructure. Early detection of weathering steel corrosion is important to extending the service life of the bridge structure; however, written inspection procedures are not available for inspectors to evaluate the performance or quality of the patina. This project focused on the evaluation of weathering steel bridge structures, including possible methods to assess the quality of the weathering steel patina and to properly maintain the quality of the patina. The objectives of this project are summarized as follows:  Identify weathering steel bridge structures that would be most vulnerable to chloride contamination, based on location, exposure, environment, and other factors.  Identify locations on an individual weathering steel bridge structure that would be most susceptible to chloride contamination, such as below joints, splash/spray zones, and areas of ponding water or debris.  Identify possible testing methods and/or inspection techniques for inspectors to evaluate the quality of the weathering steel patina at locations discussed above.  Identify possible methods to measure and evaluate the level of chloride contamination at the locations discussed above.  Evaluate the effectiveness of water washing on removing chlorides from the weathering steel patina.  Develop a general prioritization for the washing of bridge structures based on the structure’s location, environment, inspection observations, patina evaluation findings, and chloride test results.

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This guide provides a variety of tools that can help an educator, building staff or school district decide how to include environmental education in their curriculum.

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In October 1998, Hurricane Mitch triggered numerous landslides (mainly debris flows) in Honduras and Nicaragua, resulting in a high death toll and in considerable damage to property. The potential application of relatively simple and affordable spatial prediction models for landslide hazard mapping in developing countries was studied. Our attention was focused on a region in NW Nicaragua, one of the most severely hit places during the Mitch event. A landslide map was obtained at 1:10 000 scale in a Geographic Information System (GIS) environment from the interpretation of aerial photographs and detailed field work. In this map the terrain failure zones were distinguished from the areas within the reach of the mobilized materials. A Digital Elevation Model (DEM) with 20 m×20 m of pixel size was also employed in the study area. A comparative analysis of the terrain failures caused by Hurricane Mitch and a selection of 4 terrain factors extracted from the DEM which, contributed to the terrain instability, was carried out. Land propensity to failure was determined with the aid of a bivariate analysis and GIS tools in a terrain failure susceptibility map. In order to estimate the areas that could be affected by the path or deposition of the mobilized materials, we considered the fact that under intense rainfall events debris flows tend to travel long distances following the maximum slope and merging with the drainage network. Using the TauDEM extension for ArcGIS software we generated automatically flow lines following the maximum slope in the DEM starting from the areas prone to failure in the terrain failure susceptibility map. The areas crossed by the flow lines from each terrain failure susceptibility class correspond to the runout susceptibility classes represented in a runout susceptibility map. The study of terrain failure and runout susceptibility enabled us to obtain a spatial prediction for landslides, which could contribute to landslide risk mitigation.