Hidroquímica e qualidade das águas subterrâneas da Ilha de Santiago - Cabo Verde

A ilha de Santiago, Cabo Verde é uma ilha de origem vulcânica, constituída basicamente por lavas e piroclastos, localizada no Oceano Atlântico ao lado da costa ocidental de África. A ilha é caracterizada por três unidades hidrogeológicas, sendo estas a Formação de Base (semi-confinada), a Formação Intermédia (freática) e a Formação Recente (freática), que apresentam características geológicas e comportamentos hidráulicos que as diferenciam, recebendo recarga directa e/ ou diferida por infiltração das águas de chuva e descarregam ao mar, na rede hidrográfica ou, ainda, em outros níveis aquíferos subjacentes, desde que induzidos por gradientes hidráulicos favoráveis. O clima de Santiago é árido a semi-árido, com precipitações muito escassas e irregulares, condicionadas na sua distribuição pela altitude, ventos e orientação das vertentes, dando por vezes origem a períodos de seca prolongados. Em anos de ‘boa’ chuva, as precipitações propiciam a existência temporária de recursos hídricos superficiais e a recarga dos recursos de água subterrânea. Foi realizado um estudo hidrogeoquímico detalhado da ilha que incluiu a recolha de amostras em 133 pontos de água, entre furos, poços e nascentes. A composição química das águas analisadas na ilha de Santiago apresenta significativas variações em função da geologia e do tempo de residência. Na ausência de episódios de contaminação, as águas subterrâneas têm uma composição do tipo bicarbonatada-sódica (HCO3-Na) nas zonas mais altas da ilha, onde afloram as formações da Unidade Aquífera Intermédia. Nas zonas mais próximas da costa ocorrem águas de composição cloretada-magnesiana (Cl-Mg) ou cloretada-sódica (Cl-Na). Estas últimas predominam nas partes terminais das ribeiras, onde afloram materiais de elevada permeabilidade, e o excesso de bombagem para irrigação tem conduzido a um avanço da cunha de intrusão marinha. A ocorrência da fácies Cl-Na é neste caso o resultado de processos de intercâmbio catiónico que ocorrem durante o processo de intrusão e é concordante com os elevados teores de cloretos e de condutividade eléctrica observados. Os resultados das análises de isótopos estáveis de oxigénio-18 e deutério, realizadas em amostras recolhidas a distintas altitudes, revelam um gradiente negativo com a altitude, que já tinha sido verificado em outras ilhas com declives acentuados, permitindo assim determinar altitudes de recarga de água subterrânea. Os estudos hidrogeoquímicos até agora realizados permitiram caracterizar os principais níveis aquíferos da ilha de Santiago, colocando em evidência a limitada recarga do aquífero e o risco de gradual degradação dos recursos de água subterrânea por fenómenos de intrusão salina e contaminação agrícola. Estes resultados revelam a importância da gestão integrada da qualidade e quantidade dos parcos recursos de água subterrânea na ilha de Santiago.

Fuzzy model identification by evolutionary, gradient based and memtic algorithms

One of the crucial problems of fuzzy rule modeling is how to find an optimal or at least a quasi-optimal rule base fro a certain system. In most applications there is no human expert available, or, the result of a human expert's decision is too much subjective and is not reproducible, thus some automatic method to determine the fuzzy rule base must be deployed.

Design of neuro-fuzzy models by evolutionary and gradient-based algorithms

All systems found in nature exhibit, with different degrees, a nonlinear behavior. To emulate this behavior, classical systems identification techniques use, typically, linear models, for mathematical simplicity. Models inspired by biological principles (artificial neural networks) and linguistically motivated (fuzzy systems), due to their universal approximation property, are becoming alternatives to classical mathematical models. In systems identification, the design of this type of models is an iterative process, requiring, among other steps, the need to identify the model structure, as well as the estimation of the model parameters. This thesis addresses the applicability of gradient-basis algorithms for the parameter estimation phase, and the use of evolutionary algorithms for model structure selection, for the design of neuro-fuzzy systems, i.e., models that offer the transparency property found in fuzzy systems, but use, for their design, algorithms introduced in the context of neural networks. A new methodology, based on the minimization of the integral of the error, and exploiting the parameter separability property typically found in neuro-fuzzy systems, is proposed for parameter estimation. A recent evolutionary technique (bacterial algorithms), based on the natural phenomenon of microbial evolution, is combined with genetic programming, and the resulting algorithm, bacterial programming, advocated for structure determination. Different versions of this evolutionary technique are combined with gradient-based algorithms, solving problems found in fuzzy and neuro-fuzzy design, namely incorporation of a-priori knowledge, gradient algorithms initialization and model complexity reduction.

An economic appraisal of the wealth-health gradient

In this study we aim to investigate the health discrepancies arising from unequal economic status, known as the “wealth-health gradient”. Our sample comprises 47,163 individuals from 14 European countries in the SHARE Wave 4 (2011), representing the population aged 50 and older. Through a cross-sectional OLS regression model, we have tested the impact of country-level indicators to infer their effect on personal health and on the magnitude of the gradient. The results find that private expenditure yields, on average, a higher, but fast decreasing, health benefit than public expenditure; and that income inequality is irrelevant for reducing health inequalities.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

Snapshot gradient-recalled echo-planar images of rat brains at long echo time at 9.4 T.

With improved B 0 homogeneity along with satisfactory gradient performance at high magnetic fields, snapshot gradient-recalled echo-planar imaging (GRE-EPI) would perform at long echo times (TEs) on the order of T2*, which intrinsically allows obtaining strongly T2*-weighted images with embedded substantial anatomical details in ultrashort time. The aim of this study was to investigate the feasibility and quality of long TE snapshot GRE-EPI images of rat brain at 9.4 T. When compensating for B 0 inhomogeneities, especially second-order shim terms, a 200 x 200 microm2 in-plane resolution image was reproducibly obtained at long TE (>25 ms). The resulting coronal images at 30 ms had diminished geometric distortions and, thus, embedded substantial anatomical details. Concurrently with the very consistent stability, such GRE-EPI images should permit to resolve functional data not only with high specificity but also with substantial anatomical details, therefore allowing coregistration of the acquired functional data on the same image data set.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.

TONGA : un algorithme de gradient naturel pour les problèmes de grande taille

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Sea Surface Temperature-Convection Relationship in Tropical Oceans with Special Emphasis to Intraseasonal Variability of Indian Summer Monsoon

The SST convection relation over tropical ocean and its impact on the South Asian monsoon is the first part of this thesis. Understanding the complicated relation between SST and convection is important for better prediction of the variability of the Indian monsoon in subseasonal, seasonal, interannual, and longer time scales. Improved global data sets from satellite scatterometer observations of SST, precipitation and refined reanalysis of global wind fields have made it possible to do a comprehensive study of the SST convection relation. Interaction of the monsoon and Indian ocean has been discussed. A coupled feedback process between SST and the Active-Break cycle of the Asian summer monsoon is a central theme of the thesis. The relation between SST and convection is very important in the field of numerical modeling of tropical rainfall. It is well known that models generally do very well simulating rainfall in areas of tropical convergence zones but are found unable to do satisfactory simulation in the monsoon areas. Thus in this study we critically examined the different mechanisms of generation of deep convection over these two distinct regions.The study reported in chapter 3 has shown that SST - convection relation over the warm pool regions of Indian and west Pacific oceans (monsoon areas) is in such a way that convection increases with SST in the SST range 26-29 C and for SST higher than 29-30 C convection decreases with increase of SST (it is called Waliser type). It is found that convection is induced in areas with SST gradients in the warm pool areas of Indian and west Pacific oceans. Once deep convection is initiated in the south of the warmest region of warm pool, the deep tropospheric heating by the latent heat released in the convective clouds produces strong low level wind fields (Low level Jet - LLJ) on the equatorward side of the warm pool and both the convection and wind are found to grow through a positive feedback process. Thus SST through its gradient acts only as an initiator of convection. The central region of the warm pool has very small SST gradients and large values of convection are associated with the cyclonic vorticity of the LLJ in the atmospheric boundary layer. The conditionally unstable atmosphere in the tropics is favorable for the production of deep convective clouds.

The Cold Tongue in the South China Sea during Boreal Winter and Its Interaction with the Atmosphere

A distinct cold tongue has recently been noticed in the South China Sea during the winter monsoon, with the cold tongue temperature minimum occurring in the January or February. This cold tongue shows signi¯cant links with the Maritime Continent's rainfall during the winter period. The cold tongue and its interaction with the Maritime Continent's weather were studied using Reynolds SST data, wind ¯elds from the NCEP{NCAR reanalysis dataset and the quikSCAT dataset. In addition, rainfall from the GOES Precipitation Index (GPI) for the periods 2000 to 2008 was also used. The propagation of the cold tongue towards the south is explained using wind dynamics and the western boundary current. During the period of strong cold tongue, the surface wind is strong and the western boundary current advects the cold tongue to the south. During the period of strong winds the zonal gradient of SST is high [0.5±C (25 km)¡1]. The cold tongue plays an important role in regulating the climate over the Maritime Continent. It creates a zonal/meridional SST gradient and this gradient ultimately leads in the formation of convection. Hence, two maximum precipitation zones are found in the Maritime Continent, with a zone of relatively lower precipitation between, which coincides with the cold tongue's regions. It was found that the precipitation zones have strong links with the intensity of the cold tongue. During stronger cold tongue periods the precipitation on either side of the cold tongue is considerably greater than during weaker cold tongue periods. The features of convection on the eastern and western sides of the cold tongue behave di®erently. On the eastern side convection is preceded by one day with SST gradient, while on the western side it is four days.

Smallholder pig production systems along a periurban-rural gradient in the Western provinces of the Democratic Republic of the Congo

In the Democratic Republic of the Congo (DRC), pigs are raised almost exclusively by smallholders either in periurban areas of major cities such as Kinshasa or in rural villages. Unfortunately, little information is available regarding pig production in the Western part of the DRC, wherefore a survey was carried out to characterize and compare 319 pig production systems in their management and feeding strategies, along a periurban - rural gradient inWestern provinces of the DRC. Pig breeding was the main source of income (43%) and half of respondents were active in mixed pig and crop production, mainly vegetable garden. Depending on the location, smallholders owned on average 18 pigs, including four sows. Piglet mortality rate varied from 9.5 to 21.8% while average weaned age ranged between 2.2 and 2.8 months. The major causes of mortality reported by the farmers were African swine fever 98 %, swine erysipelas (60 %), erysipelas trypanosomiasis (31 %), swine worm infection (17 %), and diarrhoea (12 %). The majority of the pigs were reared in pens without free roaming and fed essentially with locally available by-products and forage plants whose nature varied according with the location of the farm. The pig production systems depended on the local environment; particularly in terms of workforces, herd structure and characteristics, production parameters, pig building materials, selling price and in feed resources. It can be concluded that an improvement of Congolese pig production systems should consider (1) a reduction of inbreeding, (2) an improvement in biosafety to reduce the incidence of African swine fever and the spread of other diseases, and (3) an improvement in feeding practices.

Policy gradient based Reinforcement Learning for real autonomous underwater cable tracking

This paper proposes a field application of a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot in cable tracking task. The learning system is characterized by using a direct policy search method for learning the internal state/action mapping. Policy only algorithms may suffer from long convergence times when dealing with real robotics. In order to speed up the process, the learning phase has been carried out in a simulated environment and, in a second step, the policy has been transferred and tested successfully on a real robot. Future steps plan to continue the learning process on-line while on the real robot while performing the mentioned task. We demonstrate its feasibility with real experiments on the underwater robot ICTINEU AUV

Gradient-based reinforcement learning techniques for underwater robotics behavior learning

Darrerament, l'interès pel desenvolupament d'aplicacions amb robots submarins autònoms (AUV) ha crescut de forma considerable. Els AUVs són atractius gràcies al seu tamany i el fet que no necessiten un operador humà per pilotar-los. Tot i això, és impossible comparar, en termes d'eficiència i flexibilitat, l'habilitat d'un pilot humà amb les escasses capacitats operatives que ofereixen els AUVs actuals. L'utilització de AUVs per cobrir grans àrees implica resoldre problemes complexos, especialment si es desitja que el nostre robot reaccioni en temps real a canvis sobtats en les condicions de treball. Per aquestes raons, el desenvolupament de sistemes de control autònom amb l'objectiu de millorar aquestes capacitats ha esdevingut una prioritat. Aquesta tesi tracta sobre el problema de la presa de decisions utilizant AUVs. El treball presentat es centra en l'estudi, disseny i aplicació de comportaments per a AUVs utilitzant tècniques d'aprenentatge per reforç (RL). La contribució principal d'aquesta tesi consisteix en l'aplicació de diverses tècniques de RL per tal de millorar l'autonomia dels robots submarins, amb l'objectiu final de demostrar la viabilitat d'aquests algoritmes per aprendre tasques submarines autònomes en temps real. En RL, el robot intenta maximitzar un reforç escalar obtingut com a conseqüència de la seva interacció amb l'entorn. L'objectiu és trobar una política òptima que relaciona tots els estats possibles amb les accions a executar per a cada estat que maximitzen la suma de reforços totals. Així, aquesta tesi investiga principalment dues tipologies d'algoritmes basats en RL: mètodes basats en funcions de valor (VF) i mètodes basats en el gradient (PG). Els resultats experimentals finals mostren el robot submarí Ictineu en una tasca autònoma real de seguiment de cables submarins. Per portar-la a terme, s'ha dissenyat un algoritme anomenat mètode d'Actor i Crític (AC), fruit de la fusió de mètodes VF amb tècniques de PG.

Sensitivity and specificity of tympanometric gradient and middle ear resonance in young children and infants

This paper discusses the use of tympanometric gradient, middle ear resonance and static admittance as diagnostic tools for testing the hearing of children and infants.