Échanges d’énergie et d’eau des écosystèmes nordiques dans un contexte de changement climatique

Le réchauffement climatique affecte fortement les régions nordiques du Canada où le dégel du pergélisol discontinu à sa limite sud est accompagné du mouvement de la limite des arbres vers le nord en zone de pergélisol continu. Ces altérations faites aux paysages de la Taïga des Plaines sont le point de départ de plusieurs rétroactions puisque les changements apportés aux caractéristiques de la surface (au niveau de l’albédo, l’humidité du sol et la rugosité de la surface) vont à leur tour entraîner des modifications biophysiques et éventuellement influencer l’augmentation ou la diminution subséquente des températures et de l’humidité de l’air. Seulement, il y a un nombre important de facteurs d’influence qu’il est difficile de projeter toutes les boucles rétroactives qui surviendront avec les présents changements climatiques en régions nordiques. Dans le but de caractériser les échanges d’eau et d’énergie entre la surface et l’atmosphère de trois sites des Territoires du Nord-Ouest subissant les conséquences de l’augmentation des températures de l’air, la méthode micro-météorologique de covariance des turbulences fut utilisée en 2013 aux sites de Scotty Creek (forêt boréale et tourbière nordique en zone de pergélisol sporadique-discontinu), de Havikpak Creek (forêt boréale nordique en zone de pergélisol continu) et de Trail Valley Creek (toundra arctique en zone de pergélisol continu). En identifiant les procédés biotiques et abiotiques (ex. intensité lumineuse, disponibilité en eau, etc.) d’évapotranspiration aux trois sites, les contrôles par l’eau et l’énergie furent caractérisés et permirent ainsi de projeter une augmentation de la limitation en eau, mais surtout en énergie du site de Trail Valley Creek. La répartition de l’énergie projetée est semblable à celle de Havikpak Creek, avec une augmentation de la proportion du flux de chaleur sensible au détriment de celui latent suite aux modifications des caractéristiques de la surface (albédo, rugosité et humidité du sol). L’augmentation relative du flux d’énergie sensible laisse présager une boucle rétroactive positive de l’augmentation des températures de l’air à ce site. Ensuite, en comparant des données modelées de la hauteur de la couche limite planétaire et des données provenant de profils atmosphériques d’Environnement Canada entre les trois sites, les changements de hauteur de cette couche atmosphérique furent aussi projetés. Trail Valley Creek pourrait connaître une hausse de la hauteur de sa couche limite planétaire avec le temps alors que Scotty Creek connaîtrait une diminution de celle-ci. Ces changements au niveau des couches atmosphériques liés à la répartition des flux d’énergie dans les écosystèmes se répercuteraient alors sur le climat régional de façon difficile à déterminer pour l’instant. Les changements apportés désignent une boucle rétroactive positive des températures de l’air à Trail Valley Creek et l’inverse à Scotty Creek. Les deux axes d’analyse arrivent donc aux mêmes conclusions et soulignent aussi l’importance de l’influence mutuelle entre le climat et les caractéristiques spécifiques des écosystèmes à la surface.

O enquadramento da disciplina de Canto no Ensino Artístico Especializado em Portugal desde o século XVIII até à atualidade

Este trabalho tem como principal objetivo a investigação e reflexão do ensino da música, designadamente do ensino de Canto, analisando não apenas a prática vocal, mas primordialmente a experiência pedagógica praticada ao longo dos últimos anos. Num primeiro momento, é apresentada uma contextualização histórica do ensino da música em Portugal, em meados do século XVIII. Este percurso pretende ainda expor a evolução do ensino musical desde a criação do primeiro Conservatório de Música de Lisboa em 1835 até à atualidade, identificando as especificidades pedagógicas mais recentes no que respeita à disciplina de Canto. Em segundo lugar, são identificados os aspetos progressivos e regressivos do ensino de Canto, através da análise de todos os diplomas legais aplicáveis. Relativamente à apreciação evolutiva desta disciplina, o presente estudo centra-se na Escola Artística do Conservatório de Música de Coimbra (EACMC) e nos seus 30 anos de existência. Neste sentido, são mencionadas as principais causas de sucesso e/ou insucesso da referida disciplina, apresentando algumas soluções para os problemas identificados.

Citrus as a component of the Mediterranean Diet

Citrus are native to southeastern Asia, but are present in the Mediterranean basin for centuries. This group of species has reached great importance in some of the Mediterranean countries and, in the case of orange, mandarin and lemon trees, they found here soil and climatic conditions which allows them to achieve a high level of fruit quality, even better than in the regions where they came from. Citrus fruits are present in the diet of the peoples living on the Mediterranean basin, at least since the time of the Roman Empire. In the 20th century they became the main crop in various agricultural areas of the Mediterranean, playing an important role in the landscape, in the diet of the overall population, and also in international trade. They are present in the gardens of palaces and monasteries, but also in the courtyards and orchards of the poorest families. Their fruits are not only a refreshing dessert, but also a condiment, or even a major component of many dishes. Citrus fruits have well-documented nutritional and health benefits. They can actually help prevent and cure some diseases and, above all, they are essential in a balanced and tasty diet.

Changes in the spatial distribution of tree species in a terra firme rain forest in Brazilian Amazonia after logging.

The objective of this paper was to determine changes in the spatial distribution of tree species in a logged compared to an unlogged forest of the Tapajos National Forest in the municipality of Belterra, State of Para, Brazil, over an eight-year period. The distribution pattern was determined for trees> 5 cm dbh and, also, for trees > 30 cm dbh. The relationship (a quadrate method) discussed by McGinnis was selected to be used in this study. Forty-seven percent of species with trees > 5 cm dbh showed clumped distribution in the studied forests. Geissospermwn sericeunz Benth & Hook., Minquartia guianensis Aubl., Poureria bilocularis (H. Winkler) Bachni, Protium guacayantan Cuatrec, Sclerolobium chrysophyllunz Poepp. et Endl. and the Sapotaceae family (9 species) occurred in clumps of small trees (5 cm 5 dbh < 30 cm) and big trees (dbh > 30 cm) in both the logged and undisturbed forest. Trees in all sizes of these species certainly have aggregation characteristics in different light condition's during the whole growth-cycle. Only Sclerolobium cizzysophylltan out of fourteen species that occurred aggregated in all forest conditions was light demanding. The shade-tolerant Lecythis lurida (Miers) Mori and Manilkara huberi (Ducke) Stand!. showed also aggregated distribution for small and big trees in the unlogged forest. An aggregated distribution is not always directly correlated to abundance, considering that most of the clumped species had less than seven trees per hectare.

Synchronizing the in vitro germination of Psidium guineense Sw. seeds by means of osmotic priming.

The Brazilian guava (Psidium guineense Swartz) is seed-propagated and, being native to the Caatinga biome, may frequently have uneven germination.Thus, we aimed to evaluate the synchronization of the in vitro seed germination of three accessions of the Brazilian guava, using water, polyethyleneglycol (PEG 6000), and potassium nitrate (KNO3) at different potentials and times of osmotic priming. Seeds from three accessions of the Brazilian guava (Y85, Y93,and Y97) from the UNEB/BA Germplasm Active Bank were subjected to the following pretreatments: -0.6, -1.0, -1.4, and -1,8 MPa PEG 6000; 10 and 20% KNO3 for 24h; 10 and 20% KNO3 for 48h; water for 24 and 48h; and non-primed seeds as the control. The experimental design was therefore a 10x3+1 factorial scheme. We assessed the germination percentage (G), mean germination time (MGT), germination speed (GS), and germination speed index (GSI). Data was subjected to analysis of variance followed by a means test (Duncan at 5% probability) and regression. There was interaction between the priming treatments and accessions for all evaluated features, except G. PEG 6000 decreased the MGT (from 6 to 8 days) and increased GS and GSI of seeds from all three accessions at potentials -1.0 to -1.5 MPa.Water-priming had a positive effect on MGT, GS, and GSI of accession Y85 seeds. KNO3 negatively affected germination of seeds from all three accessions. Thereby, we could synchronize seed germination of accessions Y85 and Y97 with PEG 6000.

Distributed non-cooperative robust economic predictive control for dynamically coupled linear systems.

In this thesis, a tube-based Distributed Economic Predictive Control (DEPC) scheme is presented for a group of dynamically coupled linear subsystems. These subsystems are components of a large scale system and control inputs are computed based on optimizing a local economic objective. Each subsystem is interacting with its neighbors by sending its future reference trajectory, at each sampling time. It solves a local optimization problem in parallel, based on the received future reference trajectories of the other subsystems. To ensure recursive feasibility and a performance bound, each subsystem is constrained to not deviate too much from its communicated reference trajectory. This difference between the plan trajectory and the communicated one is interpreted as a disturbance on the local level. Then, to ensure the satisfaction of both state and input constraints, they are tightened by considering explicitly the effect of these local disturbances. The proposed approach averages over all possible disturbances, handles tightened state and input constraints, while satisfies the compatibility constraints to guarantee that the actual trajectory lies within a certain bound in the neighborhood of the reference one. Each subsystem is optimizing a local arbitrary economic objective function in parallel while considering a local terminal constraint to guarantee recursive feasibility. In this framework, economic performance guarantees for a tube-based distributed predictive control (DPC) scheme are developed rigorously. It is presented that the closed-loop nominal subsystem has a robust average performance bound locally which is no worse than that of a local robust steady state. Since a robust algorithm is applying on the states of the real (with disturbances) subsystems, this bound can be interpreted as an average performance result for the real closed-loop system. To this end, we present our outcomes on local and global performance, illustrated by a numerical example.

Perspective of Healthcare Workers about Digitization in the Healthcare Sector in Armed Forces Hospitals in Taif Region, Saudi Arabia

Aim: The purpose of the present study was to determine the impact of digitization in healthcare on health workers' perceptions in Armed Forces Hospital, Taif. Methodology: A quantitative descriptive design based on deductive approach was used in the study. 370 participants employed in Armed Force hospitals in Taif were recruited based on convenience sampling. A survey was distributed among participants to collect demographic data and data on digitization benefits, challenges, and status and perceptions of health workers. The collected responses were then entered into SPSS software for performing descriptive stats, ANOVA test and regression analysis to determine the relationship between research variables. Results: The demographic results showed more male participants (64.9%) than females (35%), with more participants having a Master's education. Results from the ANOVA test and regression analysis revealed a positive and significant correlation between digitization benefits (0.842), digitization challenges (0.838), and digitization status (0.898) with health workers' perceptions. Also, a 1% change in digitization benefits, challenges, and status can result in an 18% change in perceptions. Conclusion: Overall, the study found a significant and positive relationship impact of digitization of health on perceptions of health workers. Recommendation: It is suggested that future studies investigate the factors and strategies influencing the change of perceptions associated with the digitization of health.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

WOOD DENSITY VARIATION AND TREE RING DEMARCATION IN Gmelina arborea TREES USING X-RAY DENSITOMETRY

Due to its relationship with other properties, wood density is the main wood quality parameter. Modern, accurate methods - such as X-ray densitometry - are applied to determine the spatial distribution of density in wood sections and to evaluate wood quality. The objectives of this study were to determinate the influence of growing conditions on wood density variation and tree ring demarcation of gmelina trees from fast growing plantations in Costa Rica. The wood density was determined by X-ray densitometry method. Wood samples were cut from gmelina trees and were exposed to low X-rays. The radiographic films were developed and scanned using a 256 gray scale with 1000 dpi resolution and the wood density was determined by CRAD and CERD software. The results showed tree-ring boundaries were distinctly delimited in trees growing in site with rainfall lower than 25 10 mm/year. It was demonstrated that tree age, climatic conditions and management of plantation affects wood density and its variability. The specific effect of variables on wood density was quantified by for multiple regression method. It was determined that tree year explained 25.8% of the total variation of density and 19.9% were caused by climatic condition where the tree growing. Wood density was less affected by the intensity of forest management with 5.9% of total variation.

COMPETITION AMONG EUCALYPTUS TREES DEPENDS ON GENETIC VARIATION AND RESOURCE SUPPLY

Genetic variation and environmental heterogeneity fundamentally shape the interactions between plants of the same species. According to the resource partitioning hypothesis, competition between neighbors intensifies as their similarity increases. Such competition may change in response to increasing supplies of limiting resources. We tested the resource partitioning hypothesis in stands of genetically identical (clone-origin) and genetically diverse (seed-origin) Eucalyptus trees with different water and nutrient supplies, using individual-based tree growth models. We found that genetic variation greatly reduced competitive interactions between neighboring trees, supporting the resource partitioning hypothesis. The importance of genetic variation for Eucalyptus growth patterns depended strongly on local stand structure and focal tree size. This suggests that spatial and temporal variation in the strength of species interactions leads to reversals in the growth rank of seed-origin and clone-origin trees. This study is one of the first to experimentally test the resource partitioning hypothesis for intergenotypic vs. intragenotypic interactions in trees. We provide evidence that variation at the level of genes, and not just species, is functionally important for driving individual and community-level processes in forested ecosystems.

Spatial pattern of black spot incidence within citrus trees related to disease severity and pathogen dispersal

Guignardia citricarpa, the causal agent of citrus black spot, forms airborne ascospores on decomposing citrus leaves and water-spread conidia on fruits, leaves and twigs. The spatial pattern of diseased fruit in citrus tree canopies was used to assess the importance of ascospores and conidia in citrus black spot epidemics in Sao Paulo State, Brazil. The aggregation of diseased fruit in the citrus tree canopy was quantified by the binomial dispersion index (D) and the binary form of Taylor`s Power Law for 303 trees in six groves. D was significantly greater than 1 in 251 trees. The intercept of the regression line of Taylor`s Power Law was significantly greater than 0 and the slope was not different from 1, implying that diseased fruit was aggregated in the canopy independent of disease incidence. Disease incidence (p) and severity (S) were assessed in 2875 citrus trees. The incidence-severity relationship was described (R-2 = 88.7%) by the model ln(S) = ln(a) + bCLL(p) where CLL = complementary log-log transformation. The high severity at low incidence observed in many cases is also indicative of low distance spread of G. citricarpa spores. For the same level of disease incidence, some trees had most of the diseased fruit with many lesions and high disease severity, whereas other trees had most of the fruit with few lesions and low disease severity. Aggregation of diseased fruit in the trees suggests that splash-dispersed conidia have an important role in increasing the disease in citrus trees in Brazil.

Multicollinearity and financial constraint in investment decisions: a Bayesian generalized ridge regression

This paper addresses the investment decisions considering the presence of financial constraints of 373 large Brazilian firms from 1997 to 2004, using panel data. A Bayesian econometric model was used considering ridge regression for multicollinearity problems among the variables in the model. Prior distributions are assumed for the parameters, classifying the model into random or fixed effects. We used a Bayesian approach to estimate the parameters, considering normal and Student t distributions for the error and assumed that the initial values for the lagged dependent variable are not fixed, but generated by a random process. The recursive predictive density criterion was used for model comparisons. Twenty models were tested and the results indicated that multicollinearity does influence the value of the estimated parameters. Controlling for capital intensity, financial constraints are found to be more important for capital-intensive firms, probably due to their lower profitability indexes, higher fixed costs and higher degree of property diversification.

Backward elimination model construction for regression and classification using leave-one-out criteria

A fundamental principle in practical nonlinear data modeling is the parsimonious principle of constructing the minimal model that explains the training data well. Leave-one-out (LOO) cross validation is often used to estimate generalization errors by choosing amongst different network architectures (M. Stone, "Cross validatory choice and assessment of statistical predictions", J. R. Stast. Soc., Ser. B, 36, pp. 117-147, 1974). Based upon the minimization of LOO criteria of either the mean squares of LOO errors or the LOO misclassification rate respectively, we present two backward elimination algorithms as model post-processing procedures for regression and classification problems. The proposed backward elimination procedures exploit an orthogonalization procedure to enable the orthogonality between the subspace as spanned by the pruned model and the deleted regressor. Subsequently, it is shown that the LOO criteria used in both algorithms can be calculated via some analytic recursive formula, as derived in this contribution, without actually splitting the estimation data set so as to reduce computational expense. Compared to most other model construction methods, the proposed algorithms are advantageous in several aspects; (i) There are no tuning parameters to be optimized through an extra validation data set; (ii) The procedure is fully automatic without an additional stopping criteria; and (iii) The model structure selection is directly based on model generalization performance. The illustrative examples on regression and classification are used to demonstrate that the proposed algorithms are viable post-processing methods to prune a model to gain extra sparsity and improved generalization.

Automatic nonlinear predictive model-construction algorithm using forward regression and the PRESS statistic

An automatic nonlinear predictive model-construction algorithm is introduced based on forward regression and the predicted-residual-sums-of-squares (PRESS) statistic. The proposed algorithm is based on the fundamental concept of evaluating a model's generalisation capability through crossvalidation. This is achieved by using the PRESS statistic as a cost function to optimise model structure. In particular, the proposed algorithm is developed with the aim of achieving computational efficiency, such that the computational effort, which would usually be extensive in the computation of the PRESS statistic, is reduced or minimised. The computation of PRESS is simplified by avoiding a matrix inversion through the use of the orthogonalisation procedure inherent in forward regression, and is further reduced significantly by the introduction of a forward-recursive formula. Based on the properties of the PRESS statistic, the proposed algorithm can achieve a fully automated procedure without resort to any other validation data set for iterative model evaluation. Numerical examples are used to demonstrate the efficacy of the algorithm.