983 resultados para Lagrange multiplier test


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A avaliação da qualidade do solo (QS) é importante estratégia no planejamento agrícola, possibilitando a identificação e o aprimoramento de sistemas de manejo com características de alta produtividade e de preservação ambiental. O presente estudo foi realizado em dois experimentos de longa duração (10 e 15 anos) conduzidos no Sul do Brasil e teve por objetivo avaliar o efeito de sistemas de manejo na QS, utilizando um kit de análise expedita de qualidade de solo (KQS), desenvolvido pelo Instituto de Qualidade do Solo-USDA-ARS. A eficiência desse kit foi avaliada pela comparação com os métodos tradicionais utilizados na ciência do solo. Nas duas áreas experimentais investigou-se um total de 12 tratamentos, os quais englobaram sistemas de preparo com diferentes intensidades de revolvimento do solo (preparo convencional, preparo reduzido e plantio direto) e sistemas de culturas com ampla faixa de adição de resíduos vegetais ao solo, além da aplicação de doses anuais de N-uréia, variando de 0 a 144 kg ha-1. Em cada base experimental uma área sob campo natural foi avaliada, servindo como referência da condição do solo na ausência de interferência antrópica. Como indicadores de QS, foram avaliados infiltração de água, respiração do solo, densidade do solo, teor de nitrato+nitrito (N-NO3- + N-NO2-), estabilidade de agregados em água e pH. De maneira geral, os coeficientes de correlação entre os métodos do KQS e os métodos tradicionais foram elevados, sendo o mais alto para o indicador pH (r = 0,98) e o menor para o indicador infiltração de água no solo (r = 0,42). Os tratamentos selecionados foram teoricamente ordenados em ordem crescente de QS, a qual foi reproduzida de forma eficiente pelo índice de estoque de carbono (IEC), calculado pela razão entre o estoque de C orgânico do solo, na camada de 0-5 cm, de cada tratamento e o estoque de C orgânico no solo sob campo natural. Os indicadores estabilidade de agregados, N-NO3- + N-NO2- e respiração do solo foram os mais eficientes em discriminar a QS. O KQS foi eficiente em avaliar a QS dos tratamentos nas duas áreas experimentais. Os níveis mais elevados de QS foram alcançados nos tratamentos com plantio direto e consórcio de gramíneas e leguminosas tropicais, devido à cobertura do solo e às elevadas adições de C e N via resíduos culturais.

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L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

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Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

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Selostus: Kasvatushäkin ympäristön vaikutus hopeakettujen käyttäytymiseen

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Several unit root tests in panel data have recently been proposed. The test developed by Harris and Tzavalis (1999 JoE) performs particularly well when the time dimension is moderate in relation to the cross-section dimension. However, in common with the traditional tests designed for the unidimensional case, it was found to perform poorly when there is a structural break in the time series under the alternative. Here we derive the asymptotic distribution of the test allowing for a shift in the mean, and assess the small sample performance. We apply this new test to show how the hypothesis of (perfect) hysteresis in Spanish unemployment is rejected in favour of the alternative of the natural unemployment rate, when the possibility of a change in the latter is considered.

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BACKGROUND: Because of denervation supersensitivity, a miotic pupil in a sympathetically-denervated eye dilates in response to a dilute or weak alpha-1-agonist drug. A reversal of anisocoria after topical apraclonidine is considered as a positive test result that diagnoses a unilateral Horner syndrome. HISTORY AND SIGNS: Two women aged 34 and 46 years with a cocaine-confirmed oculosympathetic defect (Horner syndrome) were tested with 1 % topical apraclonidine on separate days. THERAPY AND OUTCOME: In one patient, her miotic Horner pupil dilated marginally but not enough to reverse the baseline anisocoria. Additionally, the upper lid on the same side retracted. There was no discernable effect of apraclonidine on the normal, contralateral eye. In the second patient, there was no pupillary response to apraclonidine but there was resolution of her ptosis. CONCLUSIONS: Neither patient demonstrated a reversal of anisocoria, the current criterion for diagnosing a Horner syndrome using apraclonidine. Thus, these two patients with an established oculosympathetic defect were said to have a "negative test" for Horner syndrome. Yet both women showed subtle pupil and/or lid changes in response to apraclonidine that were consistent with sympathetic denervation supersensitivity. Reversal of anisocoria following topical apraclonidine does not occur in all patients with a unilateral oculosympathetic defect and more specific parameters for defining a positive test result might optimize apraclonidine's utility as a diagnostic test for Horner syndrome

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In a weighted spatial network, as specified by an exchange matrix, the variances of the spatial values are inversely proportional to the size of the regions. Spatial values are no more exchangeable under independence, thus weakening the rationale for ordinary permutation and bootstrap tests of spatial autocorrelation. We propose an alternative permutation test for spatial autocorrelation, based upon exchangeable spatial modes, constructed as linear orthogonal combinations of spatial values. The coefficients obtain as eigenvectors of the standardised exchange matrix appearing in spectral clustering, and generalise to the weighted case the concept of spatial filtering for connectivity matrices. Also, two proposals aimed at transforming an acessibility matrix into a exchange matrix with with a priori fixed margins are presented. Two examples (inter-regional migratory flows and binary adjacency networks) illustrate the formalism, rooted in the theory of spectral decomposition for reversible Markov chains.

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The Proctor test is time-consuming and requires sampling of several kilograms of soil. Proctor test parameters were predicted in Mollisols, Entisols and Vertisols of the Pampean region of Argentina under different management systems. They were estimated from a minimum number of readily available soil properties (soil texture, total organic C) and management (training data set; n = 73). The results were used to generate a soil compaction susceptibility model, which was subsequently validated using a second group of independent data (test data set; n = 24). Soil maximum bulk density was estimated as follows: Maximum bulk density (Mg m-3) = 1.4756 - 0.00599 total organic C (g kg-1) + 0.0000275 sand (g kg-1) + 0.0539 management. Management was equal to 0 for uncropped and untilled soils and 1 for conventionally tilled soils. The established models predicted the Proctor test parameters reasonably well, based on readily available soil properties. Tillage systems induced changes in the maximum bulk density regardless of total organic matter content or soil texture. The lower maximum apparent bulk density values under no-tillage require a revision of the relative compaction thresholds for different no-tillage crops.

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To express the negative effects of soil compaction, some researchers use critical values for soil mechanical strength that severely impair plant growth. The aim of this study was to identify this critical compaction depth, to test the functionality of a new, portable penetrometer developed from a spring dynamometer, and compare it to an electronic penetrometer traditionally used in compaction studies of agricultural soils. Three soils with distinct texture were conventionally tilled using a disk plow, and cultivated with different plant species. The critical soil resistance defined to establish critical compaction depth was equal to 1.5 MPa. The results of the new equipment were similar to the electronic penetrometer, indicating its viability as a tool for assessing the soil physical conditions for plant growth.

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We analyzed the initial adhesion and biofilm formation of Staphylococcus aureus (ATCC 29213) and S. epidermidis RP62A (ATCC 35984) on various bone grafts and bone graft substitutes under standardized in vitro conditions. In parallel, microcalorimetry was evaluated as a real-time microbiological assay in the investigation of biofilm formation and material science research. The materials beta-tricalcium phosphate (beta-TCP), processed human spongiosa (Tutoplast) and poly(methyl methacrylate) (PMMA) were investigated and compared with polyethylene (PE). Bacterial counts (log(10) cfu per sample) were highest on beta-TCP (S. aureus 7.67 +/- 0.17; S. epidermidis 8.14 +/- 0.05) while bacterial density (log(10) cfu per surface) was highest on PMMA (S. aureus 6.12 +/- 0.2, S. epidermidis 7.65 +/- 0.13). Detection time for S. aureus biofilms was shorter for the porous materials (beta-TCP and processed human spongiosa, p < 0.001) compared to the smooth materials (PMMA and PE), with no differences between beta-TCP and processed human spongiosa (p > 0.05) or PMMA and PE (p > 0.05). In contrast, for S. epidermidis biofilms the detection time was different (p < 0.001) between all materials except between processed human spongiosa and PE (p > 0.05). The quantitative analysis by quantitative culture after washing and sonication of the material demonstrated the importance of monitoring factors like specific surface or porosity of the test materials. Isothermal microcalorimetry proved to be a suitable tool for an accurate, non-invasive and real-time microbiological assay, allowing the detection of bacterial biomass without removing the biofilm from the surface.

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Moisture sensitivity of Hot Mix Asphalt (HMA) mixtures, generally called stripping, is a major form of distress in asphalt concrete pavement. It is characterized by the loss of adhesive bond between the asphalt binder and the aggregate (a failure of the bonding of the binder to the aggregate) or by a softening of the cohesive bonds within the asphalt binder (a failure within the binder itself), both of which are due to the action of loading under traffic in the presence of moisture. The evaluation of HMA moisture sensitivity has been divided into two categories: visual inspection test and mechanical test. However, most of them have been developed in pre-Superpave mix design. This research was undertaken to develop a protocol for evaluating the moisture sensitivity potential of HMA mixtures using the Nottingham Asphalt Tester (NAT). The mechanisms of HMA moisture sensitivity were reviewed and the test protocols using the NAT were developed. Different types of blends as moisture-sensitive groups and non-moisture-sensitive groups were used to evaluate the potential of the proposed test. The test results were analyzed with three parameters based on performance character: the retained flow number depending on critical permanent deformation failure (RFNP), the retained flow number depending on cohesion failure (RFNC), and energy ratio (ER). Analysis based on energy ratio of elastic strain (EREE ) at flow number of cohesion failure (FNC) has higher potential to evaluate the HMA moisture sensitivity than other parameters. If the measurement error in data-acquisition process is removed, analyses based on RFNP and RFNC would also have high potential to evaluate the HMA moisture sensitivity. The vacuum pressure saturation used in AASHTO T 283 and proposed test has a risk to damage specimen before the load applying.

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PURPOSE: The current study tested the applicability of Jessor's problem behavior theory (PBT) in national probability samples from Georgia and Switzerland. Comparisons focused on (1) the applicability of the problem behavior syndrome (PBS) in both developmental contexts, and (2) on the applicability of employing a set of theory-driven risk and protective factors in the prediction of problem behaviors. METHODS: School-based questionnaire data were collected from n = 18,239 adolescents in Georgia (n = 9499) and Switzerland (n = 8740) following the same protocol. Participants rated five measures of problem behaviors (alcohol and drug use, problems because of alcohol and drug use, and deviance), three risk factors (future uncertainty, depression, and stress), and three protective factors (family, peer, and school attachment). Final study samples included n = 9043 Georgian youth (mean age = 15.57; 58.8% females) and n = 8348 Swiss youth (mean age = 17.95; 48.5% females). Data analyses were completed using structural equation modeling, path analyses, and post hoc z-tests for comparisons of regression coefficients. RESULTS: Findings indicated that the PBS replicated in both samples, and that theory-driven risk and protective factors accounted for 13% and 10% in Georgian and Swiss samples, respectively in the PBS, net the effects by demographic variables. Follow-up z-tests provided evidence of some differences in the magnitude, but not direction, in five of six individual paths by country. CONCLUSION: PBT and the PBS find empirical support in these Eurasian and Western European samples; thus, Jessor's theory holds value and promise in understanding the etiology of adolescent problem behaviors outside of the United States.