882 resultados para Large-Scale Optimization
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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.
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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.
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BACKGROUND: The Complete Arabidopsis Transcript MicroArray (CATMA) initiative combines the efforts of laboratories in eight European countries 1 to deliver gene-specific sequence tags (GSTs) for the Arabidopsis research community. The CATMA initiative offers the power and flexibility to regularly update the GST collection according to evolving knowledge about the gene repertoire. These GST amplicons can easily be reamplified and shared, subsets can be picked at will to print dedicated arrays, and the GSTs can be cloned and used for other functional studies. This ongoing initiative has already produced approximately 24,000 GSTs that have been made publicly available for spotted microarray printing and RNA interference. RESULTS: GSTs from the CATMA version 2 repertoire (CATMAv2, created in 2002) were mapped onto the gene models from two independent Arabidopsis nuclear genome annotation efforts, TIGR5 and PSB-EuGène, to consolidate a list of genes that were targeted by previously designed CATMA tags. A total of 9,027 gene models were not tagged by any amplified CATMAv2 GST, and 2,533 amplified GSTs were no longer predicted to tag an updated gene model. To validate the efficacy of GST mapping criteria and design rules, the predicted and experimentally observed hybridization characteristics associated to GST features were correlated in transcript profiling datasets obtained with the CATMAv2 microarray, confirming the reliability of this platform. To complete the CATMA repertoire, all 9,027 gene models for which no GST had yet been designed were processed with an adjusted version of the Specific Primer and Amplicon Design Software (SPADS). A total of 5,756 novel GSTs were designed and amplified by PCR from genomic DNA. Together with the pre-existing GST collection, this new addition constitutes the CATMAv3 repertoire. It comprises 30,343 unique amplified sequences that tag 24,202 and 23,009 protein-encoding nuclear gene models in the TAIR6 and EuGène genome annotations, respectively. To cover the remaining untagged genes, we identified 543 additional GSTs using less stringent design criteria and designed 990 sequence tags matching multiple members of gene families (Gene Family Tags or GFTs) to cover any remaining untagged genes. These latter 1,533 features constitute the CATMAv4 addition. CONCLUSION: To update the CATMA GST repertoire, we designed 7,289 additional sequence tags, bringing the total number of tagged TAIR6-annotated Arabidopsis nuclear protein-coding genes to 26,173. This resource is used both for the production of spotted microarrays and the large-scale cloning of hairpin RNA silencing vectors. All information about the resulting updated CATMA repertoire is available through the CATMA database http://www.catma.org.
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A first assessment of debris flow susceptibility at a large scale was performed along the National Road N7, Argentina. Numerous catchments are prone to debris flows and likely to endanger the road-users. A 1:50,000 susceptibility map was created. The use of a DEM (grid 30 m) associated to three complementary criteria (slope, contributing area, curvature) allowed the identification of potential source areas. The debris flow spreading was estimated using a process- and GISbased model (Flow-R) based on basic probabilistic and energy calculations. The best-fit values for the coefficient of friction and the mass-to-drag ratio of the PCM model were found to be ? = 0.02 and M/D = 180 and the resulting propagation on one of the calibration site was validated using the Coulomb friction model. The results are realistic and will be useful to determine which areas need to be prioritized for detailed studies.
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Many terrestrial and marine systems are experiencing accelerating decline due to the effects of global change. This situation has raised concern about the consequences of biodiversity losses for ecosystem function, ecosystem service provision, and human well-being. Coastal marine habitats are a main focus of attention because they harbour a high biological diversity, are among the most productive systems of the world and present high anthropogenic interaction levels. The accelerating degradation of many terrestrial and marine systems highlights the urgent need to evaluate the consequence of biodiversity loss. Because marine biodiversity is a dynamic entity and this study was interested global change impacts, this study focused on benthic biodiversity trends over large spatial and long temporal scales. The main aim of this project was to investigate the current extent of biodiversity of the high diverse benthic coralligenous community in the Mediterranean Sea, detect its changes, and predict its future changes over broad spatial and long temporal scales. These marine communities are characterized by structural species with low growth rates and long life spans; therefore they are considered particularly sensitive to disturbances. For this purpose, this project analyzed permanent photographic plots over time at four locations in the NW Mediterranean Sea. The spatial scale of this study provided information on the level of species similarity between these locations, thus offering a solid background on the amount of large scale variability in coralligenous communities; whereas the temporal scale was fundamental to determine the natural variability in order to discriminate between changes observed due to natural factors and those related to the impact of disturbances (e.g. mass mortality events related to positive thermal temperatures, extreme catastrophic events). This study directly addressed the challenging task of analyzing quantitative biodiversity data of these high diverse marine benthic communities. Overall, the scientific knowledge gained with this research project will improve our understanding in the function of marine ecosystems and their trajectories related to global change.
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Polistine wasps are important in Neotropical ecosystems due to their ubiquity and diversity. Inventories have not adequately considered spatial attributes of collected specimens. Spatial data on biodiversity are important for study and mitigation of anthropogenic impacts over natural ecosystems and for protecting species. We described and analyzed local-scale spatial patterns of collecting records of wasp species, as well as spatial variation of diversity descriptors in a 2500-hectare area of an Amazon forest in Brazil. Rare species comprised the largest fraction of the fauna. Close range spatial effects were detected for most of the more common species, with clustering of presence-data at short distances. Larger spatial lag effects could also be identified in some species, constituting probably cases of exogenous autocorrelation and candidates for explanations based on environmental factors. In a few cases, significant or near significant correlations were found between five species (of Agelaia, Angiopolybia, and Mischocyttarus) and three studied environmental variables: distance to nearest stream, terrain altitude, and the type of forest canopy. However, association between these factors and biodiversity variables were generally low. When used as predictors of polistine richness in a linear multiple regression, only the coefficient for the forest canopy variable resulted significant. Some level of prediction of wasp diversity variables can be attained based on environmental variables, especially vegetation structure. Large-scale landscape and regional studies should be scheduled to address this issue.
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Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.
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We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.
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Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.
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To date, published studies of alluvial bar architecture in large rivers have been restricted mostly to case studies of individual bars and single locations. Relatively little is known about how the depositional processes and sedimentary architecture of kilometre-scale bars vary within a multi-kilometre reach or over several hundreds of kilometres downstream. This study presents Ground Penetrating Radar and core data from 11, kilometre-scale bars from the Rio Parana, Argentina. The investigated bars are located between 30km upstream and 540km downstream of the Rio Parana - Rio Paraguay confluence, where a significant volume of fine-grained suspended sediment is introduced into the network. Bar-scale cross-stratified sets, with lengths and widths up to 600m and thicknesses up to 12m, enable the distinction of large river deposits from stacked deposits of smaller rivers, but are only present in half the surface area of the bars. Up to 90% of bar-scale sets are found on top of finer-grained ripple-laminated bar-trough deposits. Bar-scale sets make up as much as 58% of the volume of the deposits in small, incipient mid-channel bars, but this proportion decreases significantly with increasing age and size of the bars. Contrary to what might be expected, a significant proportion of the sedimentary structures found in the Rio Parana is similar in scale to those found in much smaller rivers. In other words, large river deposits are not always characterized by big structures that allow a simple interpretation of river scale. However, the large scale of the depositional units in big rivers causes small-scale structures, such as ripple sets, to be grouped into thicker cosets, which indicate river scale even when no obvious large-scale sets are present. The results also show that the composition of bars differs between the studied reaches upstream and downstream of the confluence with the Rio Paraguay. Relative to other controls on downstream fining, the tributary input of fine-grained suspended material from the Rio Paraguay causes a marked change in the composition of the bar deposits. Compared to the upstream reaches, the sedimentary architecture of the downstream reaches in the top ca 5m of mid-channel bars shows: (i) an increase in the abundance and thickness (up to metre-scale) of laterally extensive (hundreds of metres) fine-grained layers; (ii) an increase in the percentage of deposits comprised of ripple sets (to >40% in the upper bar deposits); and (iii) an increase in bar-trough deposits and a corresponding decrease in bar-scale cross-strata (<10%). The thalweg deposits of the Rio Parana are composed of dune sets, even directly downstream from the Rio Paraguay where the upper channel deposits are dominantly fine-grained. Thus, the change in sedimentary facies due to a tributary point-source of fine-grained sediment is primarily expressed in the composition of the upper bar deposits.
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Background Biological rhythmicity has been extensively studied in animals for many decades. Although temporal patterns of physical activity have been identified in humans, no large-scale, multi-national study has been published, and no comparison has been attempted of the ubiquity of activity rhythms at different time scales (such as daily, weekly, monthly, and annual). Methods Using individually worn actigraphy devices, physical activity of 2,328 individuals from five different countries (adults of African descent from Ghana, South Africa, Jamaica, Seychelles, and the United States) was measured for seven consecutive days at different times of the year. Results Analysis for rhythmic patterns identified daily rhythmicity of physical activity in all five of the represented nationalities. Weekly rhythmicity was found in some, but not all, of the nationalities. No significant evidence of lunar rhythmicity or seasonal rhythmicity was found in any of the groups. Conclusions These findings extend previous small-scale observations of daily rhythmicity to a large cohort of individuals from around the world. The findings also confirm the existence of modest weekly rhythmicity but not lunar or seasonal rhythmicity in human activity. These differences in rhythm strength have implications for the management of health hazards of rhythm misalignment. Key Messages Analysis of the pattern of physical activity of 2,328 individuals from five countries revealed strong daily rhythmicity in all five countries, moderate weekly rhythmicity in some countries, and no lunar rhythmicity or seasonal rhythmicity in any of the countries.
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On a geological time scale the conditions on earth are very variable and biological patterns (for example the distributions of species) are very dynamic. Understanding large scale patterns of variation observed today thus requires a deep understanding of the historical factors that drove their evolution. In this thesis, we reevaluated the evolution and maintenance of a continental color cline observed in the European barn owl (Tyto alba) using population genetic tools. The colour cline spans from south-est Europe where most individual have pure white underparts to north and east Europe where most individuals have rufous-brown underparts. Our results globally showed that the old scenario, stipulating that the color cline evolved by secondary contact of two color morphs (white and rufous) that evolved in allopatry during the last ice age has to be revised. We collected samples of about 700 barn owls from the Western Palearctic to establish the first population genetic data set for this species. Individuals were genotyped at 22 microsatellites markers, at one mitochondrial gene, and at a candidate color gene. The color of each individuals was assessed and their sex determined by molecular methods. We first showed that the genetic variation in Western Europe is very limited compared to the heritable color variation. We found no evidences of different glacial lineages, and showed that selection must be involved in the maintenance of the color cline (chapter 1). Using computer simulations, we demonstrated that the post-glacial colonization of Europe occurred from the Iberian Peninsula and that the color cline could not have evolved by neutral demographic processes during this colonization (chapter 2). Finally we reevaluated the whole history of the establishment of the Western Palearctic variation of the barn owl (chapter 3): This study showed that all Western European barn owls descend from white barn owls phenotypes from the Middle East that colonized the Iberian Peninsula via North-Africa. Following the end of the last ice age (20'000 years ago), these white barn owls colonized Western Europe and under selection a novel rufous phenotype evolved (during or after the colonization). An important part of the color variation could be explained by a single mutation in the melanocortin-1-receptor (MC1R) gene that appeared during or after the colonization. The colonization of Europe reached until Greece, where the rufous birds encountered white ones (which reached Greece from the Middle East over the Bosporus) in a secondary contact zone. Our analyses show that white and rufous barn owls in Greece interbreed only to a limited extent. This suggests that barn owls are at the verge of becoming two species in Greece and demonstrates that European barn owls represent an incipient ring species around the Mediterranean. The revisited history of the establishment of the European barn owl color cline makes this model system remarkable for several aspects. It is a very clear example of strong local adaptation that can be achieved despite high gene flow (strong color and MC1R differentiation despite almost no neutral genetic differentiation). It also offers a wonderful model system to study the interactions between colonization processes and selection processes which have, for now, been remarkably understudied despite their potentially ubiquitous importance. Finally it represents a very interesting case in the speciation continuum and appeals for further studying the amount of gene flow that occurs between the color morphs in Greece. -- Sur l'échelle des temps géologiques, les conditions sur terre sont très variables et les patrons biologiques (telle que la distribution des espèces) sont très dynamiques. Si l'on veut comprendre des patrons que l'on peut observer à large échelle aujourd'hui, il est nécessaire de d'abord comprendre les facteurs historiques qui ont gouverné leur établissement. Dans cette thèse, nous allons réévaluer, grâce à des outils modernes de génétique des populations, l'évolution et la maintenance d'un cline de couleur continental observé chez l'effraie des clochers européenne (Tyto alba). Globalement, nos résultats montrent que le scenario accepté jusqu'à maintenant, qui stipule que le cline de couleur a évolué à partir du contact secondaire de deux morphes de couleur (blanches et rousses) ayant évolué en allopatrie durant les dernières glaciations, est à revoir. Afin de constituer le premier jeu de données de génétique des populations pour cette espèce, nous avons récolté des échantillons d'environ 700 effraies de l'ouest Paléarctique. Nous avons génotypé tous les individus à 22 loci microsatellites, sur un gène mitochondrial et sur un autre gène participant au déterminisme de la couleur. Nous avons aussi mesuré la couleur de tous les individus et déterminé leur sexe génétiquement. Nous avons tout d'abord pu montrer que la variation génétique neutre est négligeable en comparaison avec la variation héritable de couleur, qu'il n'existe qu'une seule lignée européenne et que de la sélection doit être impliquée dans le maintien du cline de couleur (chapitre 1). Grâce à des simulations informatiques, nous avons démontré que l'ensemble de l'Europe de l'ouest a été recolonisé depuis la Péninsule Ibérique après les dernières glaciations et que le cline de couleur ne peut pas avoir évolué par des processus neutre durant cette colonisation (chapitre 2). Finalement, nous avons réévalué l'ensemble de l'histoire postglaciaire de l'espèce dans l'ouest Paléarctique (chapitre 3): l'ensemble des effraies du Paléarctique descendent d'effraie claire du Moyen-Orient qui ont colonisé la péninsule ibérique en passant par l'Afrique du nord. Après la fin de la dernière glaciation (il y a 20'000 ans), ces effraies claires ont colonisé l'Europe de l'ouest et ont évolués par sélection le phénotype roux (durant ou après la colonisation). Une part importante de la variation de couleur peut être expliquée par une mutation sur le gène MC1R qui est apparue durant ou juste après la colonisation. Cette vague de colonisation s'est poursuivie jusqu'en Grèce où ces effraies rousses ont rencontré dans une zone de contact secondaire des effraies claires (qui sont remontées en Grèce depuis le Moyen-Orient via le Bosphore). Nos analyses montrent que le flux de gènes entre effraies blanches et rousses est limité en Grèce, ce qui suggère qu'elles sont en passe de former deux espèces et ce qui montre que les effraies constituent un exemple naissant de spéciation en anneaux autour de la Méditerranée. L'histoire revisitée des effraies des clochers de l'ouest Paléarctique en fait un système modèle remarquable pour plusieurs aspects. C'est un exemple très claire de forte adaptation locale maintenue malgré un fort flux de gènes (différenciation forte de couleur et sur le gène MC1R malgré presque aucune structure neutre). Il offre également un très bon système pour étudier l'interaction entre colonisation et sélection, un thème ayant été remarquablement peu étudié malgré son importance. Et il offre finalement un cas très intéressant dans le « continuum de spéciation » et il serait très intéressant d'étudier plus en détail l'importance du flux de gènes entre les morphes de couleur en Grèce.
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Waddlia chondrophila, an obligate intracellular bacterium of the Chlamydiales order, is considered as an agent of bovine abortion and a likely cause of miscarriage in humans. Its role in respiratory diseases was questioned after the detection of its DNA in clinical samples taken from patients suffering from pneumonia or bronchiolitis. To better define the role of Waddlia in both miscarriage and pneumonia, a tool allowing large-scale serological investigations of Waddlia seropositivity is needed. Therefore, enriched outer membrane proteins of W. chondrophila were used as antigens to develop a specific ELISA. After thorough analytical optimization, the ELISA was validated by comparison with micro-immunofluorescence and it showed a sensitivity above 85% with 100% specificity. The ELISA was subsequently applied to human sera to specify the role of W. chondrophila in pneumonia. Overall, 3.6% of children showed antibody reactivity against W. chondrophila but no significant difference was observed between children with and without pneumonia. Proteomic analyses were then performed using mass spectrometry, highlighting members of the outer membrane protein family as the dominant proteins. The major Waddlia putative immunogenic proteins were identified by immunoblot using positive and negative human sera. The new ELISA represents an efficient tool with high throughput applications. Although no association with pneumonia and Waddlia seropositivity was observed, this ELISA could be used to specify the role of W. chondrophila in miscarriage and in other diseases.
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Coal, natural gas and petroleum-based liquid fuels are still the most widely used energy sources in modern society. The current scenario contrasts with the foreseen shortage of petroleum that was spread out in the beginning of the XXI century, when the concept of "energy security" emerged as an urgent agenda to ensure a good balance between energy supply and demand. Much beyond protecting refineries and oil ducts from terrorist attacks, these issues soon developed to a portfolio of measures related to process sustainability, involving at least three fundamental dimensions: (a) the need for technological breakthroughs to improve energy production worldwide; (b) the improvement of energy efficiency in all sectors of modern society; and (c) the increase of the social perception that education is a key-word towards a better use of our energy resources. Together with these technological, economic or social issues, "energy security" is also strongly influenced by environmental issues involving greenhouse gas emissions, loss of biodiversity in environmentally sensitive areas, pollution and poor solid waste management. For these and other reasons, the implementation of more sustainable practices in our currently available industrial facilities and the search for alternative energy sources that could partly replace the fossil fuels became a major priority throughout the world. Regarding fossil fuels, the main technological bottlenecks are related to the exploitation of less accessible petroleum resources such as those in the pre-salt layer, ranging from the proper characterization of these deep-water oil reservoirs, the development of lighter and more efficient equipment for both exploration and exploitation, the optimization of the drilling techniques, the achievement of further improvements in production yields and the establishment of specialized training programs for the technical staff. The production of natural gas from shale is also emerging in several countries but its production in large scale has several problems ranging from the unavoidable environmental impact of shale mining as well as to the bad consequences of its large scale exploitation in the past. The large scale use of coal has similar environmental problems, which are aggravated by difficulties in its proper characterization. Also, the mitigation of harmful gases and particulate matter that are released as a result of combustion is still depending on the development of new gas cleaning technologies including more efficient catalysts to improve its emission profile. On the other hand, biofuels are still struggling to fulfill their role in reducing our high dependence on fossil fuels. Fatty acid alkyl esters (biodiesel) from vegetable oils and ethanol from cane sucrose and corn starch are mature technologies whose market share is partially limited by the availability of their raw materials. For this reason, there has been a great effort to develop "second-generation" technologies to produce methanol, ethanol, butanol, biodiesel, biogas (methane), bio-oils, syngas and synthetic fuels from lower grade renewable feedstocks such as lignocellulosic materials whose consumption would not interfere with the rather sensitive issues of food security. Advanced fermentation processes are envisaged as "third generation" technologies and these are primarily linked to the use of algae feedstocks as well as other organisms that could produce biofuels or simply provide microbial biomass for the processes listed above. Due to the complexity and cost of their production chain, "third generation" technologies usually aim at high value added biofuels such as biojet fuel, biohydrogen and hydrocarbons with a fuel performance similar to diesel or gasoline, situations in which the use of genetically modified organisms is usually required. In general, the main challenges in this field could be summarized as follows: (a) the need for prospecting alternative sources of biomass that are not linked to the food chain; (b) the intensive use of green chemistry principles in our current industrial activities; (c) the development of mature technologies for the production of second and third generation biofuels; (d) the development of safe bioprocesses that are based on environmentally benign microorganisms; (e) the scale-up of potential technologies to a suitable demonstration scale; and (f) the full understanding of the technological and environmental implications of the food vs. fuel debate. On the basis of these, the main objective of this article is to stimulate the discussion and help the decision making regarding "energy security" issues and their challenges for modern society, in such a way to encourage the participation of the Brazilian Chemistry community in the design of a road map for a safer, sustainable and prosper future for our nation.
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The results shown in this thesis are based on selected publications of the 2000s decade. The work was carried out in several national and EC funded public research projects and in close cooperation with industrial partners. The main objective of the thesis was to study and quantify the most important phenomena of circulating fluidized bed combustors by developing and applying proper experimental and modelling methods using laboratory scale equipments. An understanding of the phenomena plays an essential role in the development of combustion and emission performance, and the availability and controls of CFB boilers. Experimental procedures to study fuel combustion behaviour under CFB conditions are presented in the thesis. Steady state and dynamic measurements under well controlled conditions were carried out to produce the data needed for the development of high efficiency, utility scale CFB technology. The importance of combustion control and furnace dynamics is emphasized when CFB boilers are scaled up with a once through steam cycle. Qualitative information on fuel combustion characteristics was obtained directly by comparing flue gas oxygen responses during the impulse change experiments with fuel feed. A one-dimensional, time dependent model was developed to analyse the measurement data Emission formation was studied combined with fuel combustion behaviour. Correlations were developed for NO, N2O, CO and char loading, as a function of temperature and oxygen concentration in the bed area. An online method to characterize char loading under CFB conditions was developed and validated with the pilot scale CFB tests. Finally, a new method to control air and fuel feeds in CFB combustion was introduced. The method is based on models and an analysis of the fluctuation of the flue gas oxygen concentration. The effect of high oxygen concentrations on fuel combustion behaviour was also studied to evaluate the potential of CFB boilers to apply oxygenfiring technology to CCS. In future studies, it will be necessary to go through the whole scale up chain from laboratory phenomena devices through pilot scale test rigs to large scale, commercial boilers in order to validate the applicability and scalability of the, results. This thesis shows the chain between the laboratory scale phenomena test rig (bench scale) and the CFB process test rig (pilot). CFB technology has been scaled up successfully from an industrial scale to a utility scale during the last decade. The work shown in the thesis, for its part, has supported the development by producing new detailed information on combustion under CFB conditions.