932 resultados para 760203 Rights to environmental and natural resources
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Salamanca, situated in center of Mexico is among the cities which suffer most from the air pollution in Mexico. The vehicular park and the industry, as well as orography and climatic characteristics have propitiated the increment in pollutant concentration of Sulphur Dioxide (SO2). In this work, a Multilayer Perceptron Neural Network has been used to make the prediction of an hour ahead of pollutant concentration. A database used to train the Neural Network corresponds to historical time series of meteorological variables and air pollutant concentrations of SO2. Before the prediction, Fuzzy c-Means and K-means clustering algorithms have been implemented in order to find relationship among pollutant and meteorological variables. Our experiments with the proposed system show the importance of this set of meteorological variables on the prediction of SO2 pollutant concentrations and the neural network efficiency. The performance estimation is determined using the Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that the information obtained in the clustering step allows a prediction of an hour ahead, with data from past 2 hours.
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Las alteraciones del sistema climático debido al aumento de concentraciones de gases de efecto invernadero (GEI) en la atmósfera, tendrán implicaciones importantes para la agricultura, el medio ambiente y la sociedad. La agricultura es una fuente importante de emisiones de gases de efecto invernadero (globalmente contribuye al 12% del total de GEI), y al mismo tiempo puede ser parte de la solución para mitigar las emisiones y adaptarse al cambio climático. Las acciones frente al desafío del cambio climático deben priorizar estrategias de adaptación y mitigación en la agricultura dentro de la agenda para el desarrollo de políticas. La agricultura es por tanto crucial para la conservación y el uso sostenible de los recursos naturales, que ya están sometidos a impactos del cambio climático, al mismo tiempo que debe suministrar alimentos para una población creciente. Por tanto, es necesaria una coordinación entre las actuales estrategias de política climática y agrícola. El concepto de agricultura climáticamente inteligente ha surgido para integrar todos estos servicios de la producción agraria. Al evaluar opciones para reducir las amenazas del cambio climático para la agricultura y el medio ambiente, surgen dos preguntas de investigación: • ¿Qué información es necesaria para definir prácticas agrarias inteligentes? • ¿Qué factores influyen en la implementación de las prácticas agrarias inteligentes? Esta Tesis trata de proporcionar información relevante sobre estas cuestiones generales con el fin de apoyar el desarrollo de la política climática. Se centra en sistemas agrícolas Mediterráneos. Esta Tesis integra diferentes métodos y herramientas para evaluar las alternativas de gestión agrícola y políticas con potencial para responder a las necesidades de mitigación y adaptación al cambio climático. La investigación incluye enfoques cuantitativos y cualitativos e integra variables agronómicas, de clima y socioeconómicas a escala local y regional. La investigación aporta una recopilación de datos sobre evidencia experimental existente, y un estudio integrado sobre el comportamiento de los agricultores y las posibles alternativas de cambio (por ejemplo, la tecnología, la gestión agrícola y la política climática). Los casos de estudio de esta Tesis - el humedal de Doñana (S España) y la región de Aragón (NE España) - permiten ilustrar dos sistemas Mediterráneos representativos, donde el uso intensivo de la agricultura y las condiciones semiáridas son ya una preocupación. Por este motivo, la adopción de estrategias de mitigación y adaptación puede desempeñar un papel muy importante a la hora de encontrar un equilibrio entre la equidad, la seguridad económica y el medio ambiente en los escenarios de cambio climático. La metodología multidisciplinar de esta tesis incluye una amplia gama de enfoques y métodos para la recopilación y el análisis de datos. La toma de datos se apoya en la revisión bibliográfica de evidencia experimental, bases de datos públicas nacionales e internacionales y datos primarios recopilados mediante entrevistas semi-estructuradas con los grupos de interés (administraciones públicas, responsables políticos, asesores agrícolas, científicos y agricultores) y encuestas con agricultores. Los métodos de análisis incluyen: meta-análisis, modelos de gestión de recursos hídricos (modelo WAAPA), análisis multicriterio para la toma de decisiones, métodos estadísticos (modelos de regresión logística y de Poisson) y herramientas para el desarrollo de políticas basadas en la ciencia. El meta-análisis identifica los umbrales críticos de temperatura que repercuten en el crecimiento y el desarrollo de los tres cultivos principales para la seguridad alimentaria (arroz, maíz y trigo). El modelo WAAPA evalúa el efecto del cambio climático en la gestión del agua para la agricultura de acuerdo a diferentes alternativas políticas y escenarios climáticos. El análisis multicriterio evalúa la viabilidad de las prácticas agrícolas de mitigación en dos escenarios climáticos de acuerdo a la percepción de diferentes expertos. Los métodos estadísticos analizan los determinantes y las barreras para la adopción de prácticas agrícolas de mitigación. Las herramientas para el desarrollo de políticas basadas en la ciencia muestran el potencial y el coste para reducir GEI mediante las prácticas agrícolas. En general, los resultados de esta Tesis proporcionan información sobre la adaptación y la mitigación del cambio climático a nivel de explotación para desarrollar una política climática más integrada y ayudar a los agricultores en la toma de decisiones. Los resultados muestran las temperaturas umbral y la respuesta del arroz, el maíz y el trigo a temperaturas extremas, siendo estos valores de gran utilidad para futuros estudios de impacto y adaptación. Los resultados obtenidos también aportan una serie de estrategias flexibles para la adaptación y la mitigación a escala local, proporcionando a su vez una mejor comprensión sobre las barreras y los incentivos para su adopción. La capacidad de mejorar la disponibilidad de agua y el potencial y el coste de reducción de GEI se han estimado para estas estrategias en los casos de estudio. Estos resultados podrían ayudar en el desarrollo de planes locales de adaptación y políticas regionales de mitigación, especialmente en las regiones Mediterráneas. ABSTRACT Alterations in the climatic system due to increased atmospheric concentrations of greenhouse gas emissions (GHG) are expected to have important implications for agriculture, the environment and society. Agriculture is an important source of GHG emissions (12 % of global anthropogenic GHG), but it is also part of the solution to mitigate emissions and to adapt to climate change. Responses to face the challenge of climate change should place agricultural adaptation and mitigation strategies at the heart of the climate change agenda. Agriculture is crucial for the conservation and sustainable use of natural resources, which already stand under pressure due to climate change impacts, increased population, pollution and fragmented and uncoordinated climate policy strategies. The concept of climate smart agriculture has emerged to encompass all these issues as a whole. When assessing choices aimed at reducing threats to agriculture and the environment under climate change, two research questions arise: • What information defines smart farming choices? • What drives the implementation of smart farming choices? This Thesis aims to provide information on these broad questions in order to support climate policy development focusing in some Mediterranean agricultural systems. This Thesis integrates methods and tools to evaluate potential farming and policy choices to respond to mitigation and adaptation to climate change. The assessment involves both quantitative and qualitative approaches and integrates agronomic, climate and socioeconomic variables at local and regional scale. The assessment includes the collection of data on previous experimental evidence, and the integration of farmer behaviour and policy choices (e.g., technology, agricultural management and climate policy). The case study areas -- the Doñana coastal wetland (S Spain) and the Aragón region (NE Spain) – illustrate two representative Mediterranean regions where the intensive use of agriculture and the semi-arid conditions are already a concern. Thus the adoption of mitigation and adaptation measures can play a significant role for reaching a balance among equity, economic security and the environment under climate change scenarios. The multidisciplinary methodology of this Thesis includes a wide range of approaches for collecting and analysing data. The data collection process include revision of existing experimental evidence, public databases and the contribution of primary data gathering by semi-structured interviews with relevant stakeholders (i.e., public administrations, policy makers, agricultural advisors, scientist and farmers among others) and surveys given to farmers. The analytical methods include meta-analysis, water availability models (WAAPA model), decision making analysis (MCA, multi-criteria analysis), statistical approaches (Logistic and Poisson regression models) and science-base policy tools (MACC, marginal abatement cost curves and SOC abatement wedges). The meta-analysis identifies the critical temperature thresholds which impact on the growth and development of three major crops (i.e., rice, maize and wheat). The WAAPA model assesses the effect of climate change for agricultural water management under different policy choices and climate scenarios. The multi-criteria analysis evaluates the feasibility of mitigation farming practices under two climate scenarios according to the expert views. The statistical approaches analyses the drivers and the barriers for the adoption of mitigation farming practices. The science-base policy tools illustrate the mitigation potential and cost effectiveness of the farming practices. Overall, the results of this Thesis provide information to adapt to, and mitigate of, climate change at farm level to support the development of a comprehensive climate policy and to assist farmers. The findings show the key temperature thresholds and response to extreme temperature effects for rice, maize and wheat, so such responses can be included into crop impact and adaptation models. A portfolio of flexible adaptation and mitigation choices at local scale are identified. The results also provide a better understanding of the stakeholders oppose or support to adopt the choices which could be used to incorporate in local adaptation plans and mitigation regional policy. The findings include estimations for the farming and policy choices on the capacity to improve water supply reliability, abatement potential and cost-effective in Mediterranean regions.
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In the EU context extraction of shale and oil gas by hydraulic fracturing (fracking) differs from country to country in terms of legislation and implementation. While fossil fuel extraction using this technology is currently taking place in the UK, Germany and France have adopted respective moratoria. In between is the Spanish case, where hydrocarbon extraction projects through fracking have to undergo mandatory and routine environmental assessment in accordance with the last changes to environmental regulations. Nowadays Spain is at the crossroad with respect to the future of this technology. We presume a social conflictt in our country since the position and strategy of the involved and confronted social actors -national, regional and local authorities, energy companies, scientists, NGO and other social organization- are going to play key and likely divergent roles in its industrial implementation and public acceptance. In order to improve knowledge on how to address these controverted situations from the own engineering context, the affiliated units from the Higher Technical School of Mines and Energy Engineering at UPM have been working on a transversal program to teach values and ethics. Over the past seven years, this pioneering experience has shown the usefulness of applying a consequentialist ethics, based on a case-by-case approach and costs-benefits analysis both for action and inaction. As a result of this initiative a theoretical concept has arisen and crystallized in this field: it is named Inter-ethics. This theoretical perspective can be very helpful in complex situations, with multi-stakeholders and plurality of interests, when ethical management requires the interaction between the respective ethics of each group; professional ethics of a single group is not enough. Under this inter-ethics theoretical framework and applying content analysis techniques, this paper explores the articulation of the discourse in favour and against fracking technology and its underlying values as manifested in the Spanish traditional mass media and emerging social media such as Youtube. Results show that Spanish public discourse on fracking technology includes the costs-benefits analysis to communicate how natural resources from local communities may be affected by these facilities due to environmental, health and economic consequences. Furthermore, this technology is represented as a solution to the "demand of energy" according to the optimistic discourse while, from a pessimistic view, fracking is often framed as a source "environmental problems" and even natural disasters as possible earthquakes. In this latter case, this negative representation could have been influenced by the closure of a macro project to store injected natural gas in the Mediterranean Sea using the old facilities of an oil exploitation in Amposta (Proyecto Cástor). The closure of this project was due to the occurrence of earthquakes whose intensity was higher than the originally expected by the experts in the assessment stage of the project.
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Funded by COST (European Cooperation in Science and Technology) CEH projects. Grant Numbers: NEC05264, NEC05100 Natural Environment Research Council UK. Grant Number: NE/J008001/1 © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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FUNDING UK Biotechnology and Biological Sciences Research Council grant BB/L027739/1 and BB/L000113/1 (to D.E.S.), the US National Institutes of Health grant 2R01GM078536 (to D.E.S.), and the US National Science Foundation grant IOB 0419695 (to D.E.S.) ACKNOWLEDGMENTS We wish to thank our collaborators Mary Lou Guerinot, Niko Geldner, and Christian Hermans for kindly allowing us to incorporate in this update unpublished data on BRUTUS, SGN1, and SGN3, respectively. We also thank Mary Lou Guerinot, Niko Geldner, Takehiro Kamiya, and the ERACAPS Root Barrier project for productive discussions relating to ionomics and the plant ionome. No conflict of interest declared.
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High-affinity binding was demonstrated between suppressor-T-cell-derived bioactive glycosylation-inhibiting factor (GIF) and helper T hybridomas and natural killer cell line cells. Inactive GIF present in cytosol of suppressor T cells and Escherichia coli-derived recombinant human GIF (rhGIF) failed to bind to these cells. However, affinity of rhGIF for the target cells was generated by replacement of Cys-57 in the sequence with Ala or of Asn-106 with Ser or binding of 5-thio-2-nitrobenzoic acid to Cys-60 in the molecule. Such mutations and the chemical modification of rhGIF synergistically increased the affinity of GIF molecules for the target cells. The results indicated that receptors on the target cells recognize conformational structures of bioactive GIF. Equilibrium dissociation constant (Kd) of the specific binding between bioactive rGIF derivatives and high-affinity receptors was 10–100 pM. Receptors for bioactive GIF derivatives were detected on Th1 and Th2 T helper clones and natural killer NK1.1+ cells in normal spleen but not on naive T or B cells. Neither the inactive rGIF nor bioactive rGIF derivatives bound to macrophage and monocyte lines or induced macrophages for tumor necrosis factor α production.
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Jasmonic acid (JA) is a naturally occurring growth regulator found in higher plants. Several physiological roles have been described for this compound (or a related compound, methyl jasmonate) during plant development and in response to biotic and abiotic stress. To accurately determine JA levels in plant tissue, we have synthesized JA containing 13C for use as an internal standard with an isotopic composition of [225]:[224] 0.98:0.02 compared with [225]:[224] 0.15:0.85 for natural material. GC analysis (flame ionization detection and MS) indicate that the internal standard is composed of 92% 2-(+/-)-[13C]JA and 8% 2-(+/-)-7-iso-[13C]JA. In soybean plants, JA levels were highest in young leaves, flowers, and fruit (highest in the pericarp). In soybean seeds and seedlings, JA levels were highest in the youngest organs including the hypocotyl hook, plumule, and 12-h axis. In soybean leaves that had been dehydrated to cause a 15% decrease in fresh weight, JA levels increased approximately 5-fold within 2 h and declined to approximately control levels by 4 h. In contrast, a lag time of 1-2 h occurred before abscisic acid accumulation reached a maximum. These results will be discussed in the context of multiple pathways for JA biosynthesis and the role of JA in plant development and responses to environmental signals.
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The purpose of this research was to apply the use of direct ablation plasma spectroscopic techniques, including spark-induced breakdown spectroscopy (SIBS) and laser-induced breakdown spectroscopy (LIBS), to a variety of environmental matrices. These were applied to two different analytical problems. SIBS instrumentation was adapted in order to develop a fieldable monitor for the measurement of carbon in soil. SIBS spectra in the 200 nm to 400 nm region of several soils were collected, and the neutral carbon line (247.85 nm) was compared to total carbon concentration determined by standard dry combustion analysis. Additionally, Fe and Si were evaluated in a multivariate model in order to determine their impacts on the model's predictive power for total carbon concentrations. The results indicate that SIBS is a viable method to quantify total carbon levels in soils; obtaining a good correlation between measured and predicated carbon in soils. These results indicate that multivariate analysis can be used to construct a calibration model for SIBS soil spectra, and SIBS is a promising method for the determination of total soil carbon. SIBS was also applied to the study of biological warfare agent simulants. Elemental compositions (determined independently) of bioaerosol samples were compared to the SIBS atomic (Ca, Al, Fe and Si) and molecular (CN, N2 and OH) emission signals. Results indicate a linear relationship between the temporally integrated emission strength and the concentration of the associated element. Finally, LIBS signals of hematite were analyzed under low pressures of pure CO2 and compared with signals acquired with a mixture of CO2, N2 and Ar, which is representative of the Martian atmosphere. This research was in response to the potential use of LIBS instrumentation on the Martian surface and to the challenges associated with these measurements. Changes in Ca, Fe and Al lineshapes observed in the LIBS spectra at different gas compositions and pressures were studied. It was observed that the size of the plasma formed on the hematite changed in a non-linear way as a function of decreasing pressure in a CO2 atmosphere and a simulated Martian atmosphere.
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Understanding spatial distributions and how environmental conditions influence catch-per-unit-effort (CPUE) is important for increased fishing efficiency and sustainable fisheries management. This study investigated the relationship between CPUE, spatial factors, temperature, and depth using generalized additive models. Combinations of factors, and not one single factor, were frequently included in the best model. Parameters which best described CPUE varied by geographic region. The amount of variance, or deviance, explained by the best models ranged from a low of 29% (halibut, Charlotte region) to a high of 94% (sablefish, Charlotte region). Depth, latitude, and longitude influenced most species in several regions. On the broad geographic scale, depth was associated with CPUE for every species, except dogfish. Latitude and longitude influenced most species, except halibut (Areas 4 A/D), sablefish, and cod. Temperature was important for describing distributions of halibut in Alaska, arrowtooth flounder in British Columbia, dogfish, Alaska skate, and Aleutian skate. The species-habitat relationships revealed in this study can be used to create improved fishing and management strategies.
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This project analyzes the closely linked connection between the competition over limited resources and the formation of culture as it pertains to art and literature. The project is broken into three main topics: the influence of limited resources on competition, the role that competition and other factors have on the formation of culture, and finally how art and literature are reflective of resources, the competition for those resources, and other historical influences. This paper concludes that while there are many factors in the creation of cultures, competition over limited natural resources plays the most integral role in the formation of culture.
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The interaction of both natural conditions and anthropogenic environmental impacts can lead to different soft-bottom macrobenthic distribution patterns. Soft-bottom macrobenthic community was analysed at different taxonomic scales in order to evaluate whether diverse subset of organisms respond to the variability of the environmental pressures (natural and human induced) showing or not similar distribution patterns. Therefore, this long-term survey had been focused on a heterogeneous area, where both anthropogenic and natural stress may affect the community. Three perpendicular transects to the coast were established and stations at 4, 10 and 15 m depths were sampled at each transect twice a year (summer- winter) from 2004 to 2009. Non-parametric multivariate techniques were used to analyse soft-bottom macrobenthic community distribution and its relation to the environmental factors. Similar distribution patterns between investigated taxonomic levels were detected and they were mainly related to depth.
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Recent years have witnessed a surge of interest in computational methods for affect, ranging from opinion mining, to subjectivity detection, to sentiment and emotion analysis. This article presents a brief overview of the latest trends in the field and describes the manner in which the articles contained in the special issue contribute to the advancement of the area. Finally, we comment on the current challenges and envisaged developments of the subjectivity and sentiment analysis fields, as well as their application to other Natural Language Processing tasks and related domains.
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v.6:no.19(1937)
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v.6:no.8(1934)