Intervention of carbonate components in petrogenesis of the pyroxene nephelinites from the Jbel Saghro (Anti-Atlas, Morocco)

The Jbel Saghro alkaline complex was emplaced close to the eastern edge of the Moroccan Anti-Atlas. Within the northern part, two types of nephelinite were recognized [Ibhi and Nachit, 1999 and lbhi, 2000]. The first type (olivine-rich nephelinite) constitutes the main volcanic mass south of the Bou Gafer granit (fig. 1), where the volcanism had been active at least during 2 Ma, between 9.6 and 7.5 +/- 0.1 Ma [Berrahma et al., 1993]. The second group outcrops in the north (Foum El Kouss). It consists of pyroxene nephelinites which are younger (2.9 +/- 0.1 Ma) [Berrahma et al., 1993], and bears carbonatitic xenoliths, melteigitic pyroxenites and metasomatised peridotite xenoliths. Geochemically, the pyroxene nephelinite is highly enriched in LILE compared with the first one. The mineralogical and geochemical characteristics may be explained by the incorporation of carbonatitic and melteigitic pyroxenite segregates of carbonatitic affinity.

Machine learning analysis and modeling of interest rate curves

The present research deals with the review of the analysis and modeling of Swiss franc interest rate curves (IRC) by using unsupervised (SOM, Gaussian Mixtures) and supervised machine (MLP) learning algorithms. IRC are considered as objects embedded into different feature spaces: maturities; maturity-date, parameters of Nelson-Siegel model (NSM). Analysis of NSM parameters and their temporal and clustering structures helps to understand the relevance of model and its potential use for the forecasting. Mapping of IRC in a maturity-date feature space is presented and analyzed for the visualization and forecasting purposes.

Integration of Bridge Damage Detection Concepts and Components (3 volumes), TR-636, 2013

This work is divided into three volumes: Volume I: Strain-Based Damage Detection; Volume II: Acceleration-Based Damage Detection; Volume III: Wireless Bridge Monitoring Hardware. Volume I: In this work, a previously-developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The statistical damage-detection tool, control-chart-based damage-detection methodologies, were further investigated and advanced. For the validation of the damage-detection approaches, strain data were obtained from a sacrificial specimen attached to the previously-utilized US 30 Bridge over the South Skunk River (in Ames, Iowa), which had simulated damage,. To provide for an enhanced ability to detect changes in the behavior of the structural system, various control chart rules were evaluated. False indications and true indications were studied to compare the damage detection ability in regard to each methodology and each control chart rule. An autonomous software program called Bridge Engineering Center Assessment Software (BECAS) was developed to control all aspects of the damage detection processes. BECAS requires no user intervention after initial configuration and training. Volume II: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. The objective of this part of the project was to validate/integrate a vibration-based damage-detection algorithm with the strain-based methodology formulated by the Iowa State University Bridge Engineering Center. This report volume (Volume II) presents the use of vibration-based damage-detection approaches as local methods to quantify damage at critical areas in structures. Acceleration data were collected and analyzed to evaluate the relationships between sensors and with changes in environmental conditions. A sacrificial specimen was investigated to verify the damage-detection capabilities and this volume presents a transmissibility concept and damage-detection algorithm that show potential to sense local changes in the dynamic stiffness between points across a joint of a real structure. The validation and integration of the vibration-based and strain-based damage-detection methodologies will add significant value to Iowa’s current and future bridge maintenance, planning, and management Volume III: In this work, a previously developed structural health monitoring (SHM) system was advanced toward a ready-for-implementation system. Improvements were made with respect to automated data reduction/analysis, data acquisition hardware, sensor types, and communication network architecture. This report volume (Volume III) summarizes the energy harvesting techniques and prototype development for a bridge monitoring system that uses wireless sensors. The wireless sensor nodes are used to collect strain measurements at critical locations on a bridge. The bridge monitoring hardware system consists of a base station and multiple self-powered wireless sensor nodes. The base station is responsible for the synchronization of data sampling on all nodes and data aggregation. Each wireless sensor node include a sensing element, a processing and wireless communication module, and an energy harvesting module. The hardware prototype for a wireless bridge monitoring system was developed and tested on the US 30 Bridge over the South Skunk River in Ames, Iowa. The functions and performance of the developed system, including strain data, energy harvesting capacity, and wireless transmission quality, were studied and are covered in this volume.

Components del procés interactiu que afavoreixen la formació de l'alumnat a l'educació secundària obligatòria

L'educació secundària obligatòria sembla que estigui permanentment en crisi: situacions conflictives entre els diferents agents, fracàs escolar, bullying o reiterades modificacions curriculars són alguns dels múltiples exemples que envaeixen els medis educatius i el debat social i accentuen les crítiques i les experiències negatives que es donen en aquesta etapa educativa. Certament, la secundària obligatòria té com a repte fonamental la comprensivitat, que comporta l'atenció a la diversitat de tots els adolescents en una etapa vital complicada; aquest repte educatiu i social, sens dubte, ha de tenir ombres, però també té llums en forma d'experiències reeixides que convergeixen en un millor i major aprenentatge de l¿alumnat. La recerca que es presenta en aquest article es proposa fer emergir i difondre les característiques que reuneixen les pràctiques exitoses que es donen a les aules de la secundària obligatòria. La metodologia usada per assolir aquesta finalitat essencial ha estat el recull i l'anàlisi de relats de persones de diferents trams d'edat sobre les seves millors experiències en la secundària obligatòria com a alumnes.Els diversos objectius que es pretenen amb el recull i l'estructuració d'aquestes veus es poden sintetitzar en dos: identificar les característiques essencials o components de les «bones pràctiques» i contribuir a la reflexió i el debat en la formació inicial i permanent del professorat. A partir de les aportacions recollides es pot concloure que: - A l'ESO, en el nostre context, es registren nombroses experiències reeixides per a l'aprenent. Les experiències tenen incomptables formes de concretar-se en la pràctica (en forma de projectes, plans estratègics, programes concrets de determinades matèries, etc.). - Malgrat la diversitat de pràctiques concretes, hi ha un nombre reduït de components que determinen i caracteritzen aquestes pràctiques reeixides. El nostre treball identifica aquests components i els agrupa en cinc categories que es refereixen a aspectes de metodologia, continguts, relació educativa, relació entre iguals i projecte de centre.

" Arabidopsis Thaliana " response to insect feeding : new components controlling defense gene expression and plant resistance

Abstract: Plants cannot run away to escape attacking herbivores, but they defend themselves by producing anti-digestive proteins and toxic compounds (for example glucosinolates). The first goal of this thesis was to study changes in gene expression after insect attack using microarrays. The responses of Arabidopsis thaliana to feeding by the specialist Pieris rapae and the generalist Spodoptera liffora is were compared. We found that the transcript profiles after feeding by the two chewing insects were remarkably similar, although the generalist induced a slightly stronger response. The second goal was to evaluate the implication of the four signals jasmonic acid (JA), salicylic acid (SA), ethylene (ET), and abscisic acid (ABA) in the control of insect-regulated gene expression. Using signaling mutants, we observed that JA was the predominant signal and that ABA modulated defense gene expression. In contrast, SA and ET appeared to control slightly gene expression, but only after feeding by S. litforalis. The third goal was to establish whether plant responses are really effective against insects. In accordance with the transcript profile, both insects were affected by the JA-dependent defenses, as they performed better on the JA-insensitive mutant. S. littoralis also performed better on ABA-deficient mutants, providing evidence for the role of ABA in defense against insects. When testing indole or aliphatic glucosinolate deficient mutants, we found that they were also more susceptible to insect feeding, providing some of the first genetic evidence for the defensive role of glucosinolates in planta. Finally, a glutathione-deficient mutant, pad2-1, was also more susceptible to insect feeding and we could attribute this phenotype to a lowered accumulation of the major indole glucosinolate. In this thesis, we provide a comprehensive list of insect-regulated genes, including many transcription factors that constitute interesting candidate genes for the further study of insect-induced expression changes. Understanding how the plant responses to insects are regulated will provide tools for a better management of insect pest in the field. Résumé: Les plantes ne peuvent s'échapper pour fuir les insectes qui les attaquent, mais elles se défendent en produisant des protéines anti-digestives et des composés toxiques (par exemple des glucosinolates). Le premier but de cette thèse était d'étudier les changements de l'expression génétique lors d'attaque par des insectes en utilisant des puces à ADN. Nous avons comparé la réponse d'Arabidopsis thaliana à deux espèces d'insectes avec des habitudes alimentaires différentes : le spécialiste Pieris rapae et le généraliste Spodoptera littoralis. Nous avons trouvé que les profils de transcription après l'attaque par les deux insectes sont remarquablement similaires, bien que le généraliste induise une réponse légèrement plus forte. Le deuxième but était de déterminer l'implication de quatre signaux dans le contrôle de la réponse :l'acide jasmonique (JA), l'acide salicylique (SA), l'éthylène (ET), et l'acide abscissique (ABA). En utilisant de mutants de signalisation, nous avons montré que l'acide jasmonique était le signal prédominant et que l'acide abscissique modulait l'expression génétique. D'autre part, l'acide salicylique et l'éthylène contrôlent à un degré moindre l'expression génétique, mais seulement après l'attaque par S. littoralís. Le troisième but était d'établir si les réponses des plantes sont efficaces contre les insectes. En accord avec le profil de transcription, les deux espèces d'insectes se sont mieux développées sur un mutant insensible au JA, indiquant que les défenses contrôlées par ce signal sont cruciales pour la plante. De plus, les larves de S. littorales se sont mieux développées sur des mutants déficients en ABA, ce qui fournit une preuve du rôle de l'acide abscissique dans la défense contre les insectes. En testant des mutants déficients en glucosinolates de type indole ou aliphatique, nous avons trouvé qu'ils étaient plus sensibles aux insectes, démontrant ainsi le rôle défensif des glucosinolates in planta. Finalement, le mutant déficient en glutathion pad2-1 était aussi plus sensible à l'attaque des insectes, et nous avons pu attribuer ce phénotype à une plus faible augmentation d'un indole glucosinolate dans ce mutant. Dans cette thèse, nous avons mis en évidence un nombre important de gènes contrôlés par les insectes, comprenant de nombreux facteurs de transcription qui constituent des candidats intéressants pour`étudier plus en détail les changements d'expression génétique induits par les insectes. Une meilleure compréhension de la réponse des plantes contre l'attaque des insectes devrait nous permettre de développer de nouvelles stratégies pour mieux gérer les ravageurs des cultures.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.

Applying machine learning methods to avalanche forecasting

Avalanche forecasting is a complex process involving the assimilation of multiple data sources to make predictions over varying spatial and temporal resolutions. Numerically assisted forecasting often uses nearest neighbour methods (NN), which are known to have limitations when dealing with high dimensional data. We apply Support Vector Machines to a dataset from Lochaber, Scotland to assess their applicability in avalanche forecasting. Support Vector Machines (SVMs) belong to a family of theoretically based techniques from machine learning and are designed to deal with high dimensional data. Initial experiments showed that SVMs gave results which were comparable with NN for categorical and probabilistic forecasts. Experiments utilising the ability of SVMs to deal with high dimensionality in producing a spatial forecast show promise, but require further work.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Analysis of experiments in square lattice with emphasis on variance components. i. Individual analysis

This paper focused on four alternatives of analysis of experiments in square lattice as far as the estimation of variance components and some genetic parameters are concerned: 1) intra-block analysis with adjusted treatment and blocks within unadjusted repetitions; 2) lattice analysis as complete randomized blocks; 3) intrablock analysis with unadjusted treatment and blocks within adjusted repetitions; 4) lattice analysis as complete randomized blocks, by utilizing the adjusted means of treatments, obtained from the analysis with recovery of interblock information, having as mean square of the error the mean effective variance of this same analysis with recovery of inter-block information. For the four alternatives of analysis, the estimators and estimates were obtained for the variance components and heritability coefficients. The classification of material was also studied. The present study suggests that for each experiment and depending of the objectives of the analysis, one should observe which alternative of analysis is preferable, mainly in cases where a negative estimate is obtained for the variance component due to effects of blocks within adjusted repetitions.

Situacions vitals i components motivacionals de la personalitat de base en la preadolescència

Con el fin de detectar los determinantes fundamentales que regulan la conducta moral de los niños, este trabajo pretende aportar bases que constituyan un fundamento válido para desarrollar materiales situacionales y motivacionales para los alumnos. El Cuestionario de Situaciones fue elaborado para describir aspectos contextuales, el contenido temático o argumento, protagonistas, reacciones o cursos de acción y la motivación subyacente. Esta información sirvió para extraer situaciones y componentes motivacionales, lo que permitió crear el Cuestionario sobre Razones. Así, era posible preguntar por qué actuaba de una manera específica el niño implicado en tales situaciones. Las razones aportadas por los alumnos quedaron reducidas a las siguientes: arbitrarias, autoritarias, aler céntricas, idealistas y personales. En consecuencia,las situaciones y las razones que explican los cursos de acción fueron utilizadas para elaborar el Test de Motivación Etica. Con 3.448 chicos y chicas, comprendidos entre los 10 Y los 15 años de edad, se han analizado los cambios motivacional es referidos a las diferencias en sexo y edad. Se apuntan implicaciones para la educación moral.

Why microalgal biofuels won't save the internal combustion machine

Proponents of microalgae biofuel technologies often claim that the world demand of liquid fuels, about 5 trillion liters per year, could be supplied by microalgae cultivated on only a few tens of millions of hectares. This perspective reviews this subject and points out that such projections are greatly exaggerated, because (1) the pro- ductivities achieved in large-scale commercial microalgae production systems, operated year-round, do not surpass those of irrigated tropical crops; (2) cultivating, harvesting and processing microalgae solely for the production of biofuels is simply too expensive using current or prospective technology; and (3) currently available (limited) data suggest that the energy balance of algal biofuels is very poor. Thus, microalgal biofuels are no panacea for depleting oil or global warming, and are unlikely to save the internal combustion machine.

Degradation of pheromone and plant volatile components by a same Odorant-Degrading Enzyme in the cotton leafworm, Spodoptera littoralis

Background: Odorant-Degrading Enzymes (ODEs) are supposed to be involved in the signal inactivation step within the olfactory sensilla of insects by quickly removing odorant molecules from the vicinity of the olfactory receptors. Only three ODEs have been both identified at the molecular level and functionally characterized: two were specialized in the degradation of pheromone compounds and the last one was shown to degrade a plant odorant. Methodology: Previous work has shown that the antennae of the cotton leafworm Spodoptera littoralis , a worldwide pest of agricultural crops, express numerous candidate ODEs. We focused on an esterase overexpressed in males antennae, namely SlCXE7. We studied its expression patterns and tested its catalytic properties towards three odorants, i.e. the two female sex pheromone components and a green leaf volatile emitted by host plants. Conclusion: SlCXE7 expression was concomitant during development with male responsiveness to odorants and during adult scotophase with the period of male most active sexual behaviour. Furthermore, SlCXE7 transcription could be induced by male exposure to the main pheromone component, suggesting a role of Pheromone-Degrading Enzyme. Interestingly, recombinant SlCXE7 was able to efficiently hydrolyze the pheromone compounds but also the plant volatile, with a higher affinity for the pheromone than for the plant compound. In male antennae, SlCXE7 expression was associated with both long and short sensilla, tuned to sex pheromones or plant odours, respectively. Our results thus suggested that a same ODE could have a dual function depending of it sensillar localisation. Within the pheromone-sensitive sensilla, SlCXE7 may play a role in pheromone signal termination and in reduction of odorant background noise, whereas it could be involved in plant odorant inactivation within the short sensilla.