Assessment of data-driven modeling strategies for water delivery canals

The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.

Effects of home environment and center-based child care quality on children’s

This study examined the joint effects of home environment and center-based child care quality on children’s language, communication, and early literacy development, while also considering prior developmental level. Participants were 95 children (46 boys), assessed as toddlers (mean age = 26.33 months;Time 1) and preschoolers (mean age = 68.71 months; Time 2) and their families. At both times, children attended center-based child care classrooms in the metropolitan area of Porto, Portugal. Results from hierarchical linear models indicated that home environment and preschool quality, but not center-based toddler child care quality, were associated with children’s language and literacy outcomes at Time 2. Moreover, the quality of preschool classrooms moderated the association between home environment quality and children’s language and early literacy skills – but not communication skills – at Time 2, suggesting the positive cumulative effects of home environment and preschool quality. Findings further support the existence of a detrimental effect of low preschool quality on children’s language and early literacy outcomes: positive associations among home environment quality and children’s developmental outcomes were found to reduce substantially when children attended low-quality preschool classrooms.

Factors associated with vaccination coverage in children < 5 years in Angola

OBJECTIVE To analyze vaccination coverage and factors associated with a complete immunization scheme in children < 5 years old. METHODS This cross-sectional household census survey evaluated 1,209 children < 5 years old living in Bom Jesus, Angola, in 2010. Data were obtained from interviews, questionnaires, child immunization histories, and maternal health histories. The statistical analysis used generalized linear models, in which the dependent variable followed a binary distribution (vaccinated, unvaccinated) and the association function was logarithmic and had the children’s individual, familial, and socioeconomic factors as independent variables. RESULTS Vaccination coverage was 37.0%, higher in children < 1 year (55.0%) and heterogeneous across neighborhoods; 52.0% of children of both sexes had no immunization records. The prevalence rate of vaccination significantly varied according to child age, mother’s level of education, family size, ownership of household appliances, and destination of domestic waste. CONCLUSIONS Vulnerable groups with vaccination coverage below recommended levels continue to be present. Some factors indicate inequalities that represent barriers to full immunization, indicating the need to implement more equitable policies. The knowledge of these factors contributes to planning immunization promotion measures that focus on the most vulnerable groups.

Spatial distribution and socioeconomic context of tuberculosis in Rio de Janeiro, Brazil

OBJECTIVE To analyze the spatial distribution of risk for tuberculosis and its socioeconomic determinants in the city of Rio de Janeiro, Brazil.METHODS An ecological study on the association between the mean incidence rate of tuberculosis from 2004 to 2006 and socioeconomic indicators of the Censo Demográfico (Demographic Census) of 2000. The unit of analysis was the home district registered in the Sistema de Informação de Agravos de Notificação (Notifiable Diseases Information System) of Rio de Janeiro, Southeastern Brazil. The rates were standardized by sex and age group, and smoothed by the empirical Bayes method. Spatial autocorrelation was evaluated by Moran’s I. Multiple linear regression models were studied and the appropriateness of incorporating the spatial component in modeling was evaluated.RESULTS We observed a higher risk of the disease in some neighborhoods of the port and north regions, as well as a high incidence in the slums of Rocinha and Vidigal, in the south region, and Cidade de Deus, in the west. The final model identified a positive association for the variables: percentage of permanent private households in which the head of the house earns three to five minimum wages; percentage of individual residents in the neighborhood; and percentage of people living in homes with more than two people per bedroom.CONCLUSIONS The spatial analysis identified areas of risk of tuberculosis incidence in the neighborhoods of the city of Rio de Janeiro and also found spatial dependence for the incidence of tuberculosis and some socioeconomic variables. However, the inclusion of the space component in the final model was not required during the modeling process.

Assessment of data-driven modeling strategies for water delivery canals

Conferência: CONTROLO’2012 - 16-18 July 2012 - Funchal

Age-period-cohort effects in the incidence of hip fractures: political and economic events are coincident with changes in risk

Introduction: Healthcare improvements have allowed prevention but have also increased life expectancy, resulting in more people being at risk. Our aim was to analyse the separate effects of age, period and cohort on incidence rates by sex in Portugal, 2000–2008. Methods: From the National Hospital Discharge Register, we selected admissions (aged ≥49 years) with hip fractures (ICD9-CM, codes 820.x) caused by low/moderate trauma (falls from standing height or less), readmissions and bone cancer cases. We calculated person-years at risk using population data from Statistics Portugal. To identify period and cohort effects for all ages, we used an age–period–cohort model (1-year intervals) followed by generalised additive models with a negative binomial distribution of the observed incidence rates of hip fractures. Results: There were 77,083 hospital admissions (77.4 % women). Incidence rates increased exponentially with age for both sexes (age effect). Incidence rates fell after 2004 for women and were random for men (period effect). There was a general cohort effect similar in both sexes; risk of hip fracture altered from an increasing trend for those born before 1930 to a decreasing trend following that year. Risk alterations (not statistically significant) coincident with major political and economic change in the history of Portugal were observed around birth cohorts 1920 (stable–increasing), 1940 (decreasing–increasing) and 1950 (increasing–decreasing only among women). Conclusions: Hip fracture risk was higher for those born during major economically/politically unstable periods. Although bone quality reflects lifetime exposure, conditions at birth may determine future risk for hip fractures.

Osteoporotic hip fractures: Bisphosphonates sales and observed turning point in trend. A population-based retrospective study

The aim is to examine the temporal trends of hip fracture incidence in Portugal by sex and age groups, and explore the relation with anti-osteoporotic medication. From the National Hospital Discharge Database, we selected from 1st January 2000 to 31st December 2008, 77,083 hospital admissions (77.4% women) caused by osteoporotic hip fractures (low energy, patients over 49 years-age), with diagnosis codes 820.x of ICD 9-CM. The 2001 Portuguese population was used as standard to calculate direct age-standardized incidence rates (ASIR) (100,000 inhabitants). Generalized additive and linear models were used to evaluate and quantify temporal trends of age specific rates (AR), by sex. We identified 2003 as a turning point in the trend of ASIR of hip fractures in women. After 2003, the ASIR in women decreased on average by 10.3 cases/100,000 inhabitants, 95% CI (− 15.7 to − 4.8), per 100,000 anti-osteoporotic medication packages sold. For women aged 65–69 and 75–79 we identified the same turning point. However, for women aged over 80, the year 2004 marked a change in the trend, from an increase to a decrease. Among the population aged 70–74 a linear decrease of incidence rate (95% CI) was observed in both sexes, higher for women: − 28.0% (− 36.2 to − 19.5) change vs − 18.8%, (− 32.6 to − 2.3). The abrupt turning point in the trend of ASIR of hip fractures in women is compatible with an intervention, such as a medication. The trends were different according to gender and age group, but compatible with the pattern of bisphosphonates sales.

Modelação e reforço de vigas de betão armado com laminados de fibra de carbono

Com o atual estado da construção em Portugal, a reabilitação urbana é uma realidade. Com muitos dos edifícios a necessitarem de reforço, procurou-se abordar o comportamento real das estruturas, indo além da típica análise linear elástica. Desta forma, pretendeu-se aumentar o conhecimento acerca da modelação numérica não-linear de estruturas de betão armado, expondo modelos de cálculo relativamente simples e de fácil compreensão, com o objetivo de servir de base a uma avaliação da capacidade de carga de um elemento estrutural. O modelo de cálculo foi validado com recurso ao trabalho experimental de Bresler e Scordelis (1963). Analisou-se o comportamento até à rotura de três vigas ensaiadas à flexão. Posteriormente, foi realizado um estudo paramétrico de algumas propriedades do betão com vista à discussão do melhor de ajuste. Em seguida, já no campo do reforço estrutural, simulou-se numericamente vigas reforçadas com CFRP, com recurso à técnica EBR e NSM. Comparam-se os resultados numéricos com os ensaios experimentais de Cruz et al. (2011a). Avaliou-se ainda o desempenho de soluções alternativas com variações na área e comprimento dos laminados. Para finalizar, foi desenvolvida uma campanha experimental com diferentes áreas de reforço. Conceberam-se e executaram-se três vigas de betão armado sobre as quais se instalaram laminados de CFRP. Os resultados experimentais são apresentados e discutidos à luz dos resultados do respetivo modelo numérico. No cômputo geral, o presente trabalho permitiu aferir a validade de modelos não-lineares na previsão do comportamento efetivo das estruturas até à rotura. Assinala-se a concordância em vários resultados experimentais analisados. Ficaram também patentes os principais fenómenos ligados ao reforço de vigas com CFRP, focados nos respetivos modelos de cálculo e nos resultados experimentais apresentados.

Carbon key-properties for microcystin adsorption in drinking water treatment: structure or surface chemistry?

Dissertação para Obtenção de Grau de Mestre em Engenharia Química e Bioquímica

The effect of water inorganic matrix in ibuprofen adsorption onto activated carbon for water and wastewater treatment

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

The Effect of Long-Chain Polyunsaturated Fatty Acids Intake During Pregnancy on Adiposity of Healthy Full-Term Offspring at Birth

OBJECTIVE: The adjusted effect of long-chain polyunsaturated fatty acid (LCPUFA) intake during pregnancy on adiposity at birth of healthy full-term appropriate-for-gestational age neonates was evaluated. STUDY DESIGN: In a cross-sectional convenience sample of 100 mother and infant dyads, LCPUFA intake during pregnancy was assessed by food frequency questionnaire with nutrient intake calculated using Food Processor Plus. Linear regression models for neonatal body composition measurements, assessed by air displacement plethysmography and anthropometry, were adjusted for maternal LCPUFA intakes, energy and macronutrient intakes, prepregnancy body mass index and gestational weight gain. RESULT: Positive associations between maternal docosahexaenoic acid intake and ponderal index in male offspring (β=0.165; 95% confidence interval (CI): 0.031-0.299; P=0.017), and between n-6:n-3 LCPUFA ratio intake and fat mass (β=0.021; 95% CI: 0.002-0.041; P=0.034) and percentage of fat mass (β=0.636; 95% CI: 0.125-1.147; P=0.016) in female offspring were found. CONCLUSION: Using a reliable validated method to assess body composition, adjusted positive associations between maternal docosahexaenoic acid intake and birth size in male offspring and between n-6:n-3 LCPUFA ratio intake and adiposity in female offspring were found, suggesting that maternal LCPUFA intake strongly influences fetal body composition.

Predicting GDP growth in the Euro Area

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Métodos estatísticos aplicados à modelação de dados oncológicos

RESUMO: A estrutura demográfica portuguesa é marcada por baixas taxas de natalidade e mortalidade, onde a população idosa representa uma fatia cada vez mais representativa, fruto de uma maior longevidade. A incidência do cancro, na sua generalidade, é maior precisamente nessa classe etária. A par de outras doenças igualmente lesivas (e.g. cardiovasculares, degenerativas) cuja incidência aumenta com a idade, o cancro merece relevo. Estudos epidemiológicos apresentam o cancro como líder mundial na mortalidade. Em países desenvolvidos, o seu peso representa 25% do número total de óbitos, percentagem essa que mais que duplica noutros países. A obesidade, a baixa ingestão de frutas e vegetais, o sedentarismo, o consumo de tabaco e a ingestão de álcool, configuram-se como cinco dos fatores de risco presentes em 30% das mortes diagnosticadas por cancro. A nível mundial e, em particular no Sul de Portugal, os cancros do estômago, recto e cólon apresentam elevadas taxas de incidência e de mortalidade. Do ponto de vista estritamente económico, o cancro é a doença que mais recursos consome enquanto que do ponto de vista físico e psicológico é uma doença que não limita o seu raio de ação ao doente. O cancro é, portanto, uma doença sempre atual e cada vez mais presente, pois reflete os hábitos e o ambiente de uma sociedade, não obstante as características intrínsecas a cada indivíduo. A adoção de metodologia estatística aplicada à modelação de dados oncológicos é, sobretudo, valiosa e pertinente quando a informação é oriunda de Registos de Cancro de Base Populacional (RCBP). A pertinência é justificada pelo fato destes registos permitirem aferir numa população específica, o risco desta sofrer e/ou vir a sofrer de uma dada neoplasia. O peso que as neoplasias do estômago, cólon e recto assumem foi um dos elementos que motivou o presente estudo que tem por objetivo analisar tendências, projeções, sobrevivências relativas e a distribuição espacial destas neoplasias. Foram considerados neste estudo todos os casos diagnosticados no período 1998-2006, pelo RCBP da região sul de Portugal (ROR-Sul). O estudo descritivo inicial das taxas de incidência e da tendência em cada uma das referidas neoplasias teve como base uma única variável temporal - o ano de diagnóstico - também designada por período. Todavia, uma metodologia que contemple apenas uma única variável temporal é limitativa. No cancro, para além do período, a idade à data do diagnóstico e a coorte de nascimento, são variáveis temporais que poderão prestar um contributo adicional na caracterização das taxas de incidência. A relevância assumida por estas variáveis temporais justificou a sua inclusão numaclasse de modelos designada por modelos Idade-Período-Coorte (Age-Period-Cohort models - APC), utilizada na modelação das taxas de incidência para as neoplasias em estudo. Os referidos modelos permitem ultrapassar o problema de relações não lineares e/ou de mudanças súbitas na tendência linear das taxas. Nos modelos APC foram consideradas a abordagem clássica e a abordagem com recurso a funções suavizadoras. A modelação das taxas foi estratificada por sexo. Foram ainda estudados os respectivos submodelos (apenas com uma ou duas variáveis temporais). Conhecido o comportamento das taxas de incidência, uma questão subsequente prende-se com a sua projeção em períodos futuros. Porém, o efeito de mudanças estruturais na população, ao qual Portugal não é alheio, altera substancialmente o número esperado de casos futuros com cancro. Estimativas da incidência de cancro a nível mundial obtidas a partir de projeções demográficas apontam para um aumento de 25% dos casos de cancro nas próximas duas décadas. Embora a projeção da incidência esteja associada a alguma incerteza, as projeções auxiliam no planeamento de políticas de saúde para a afetação de recursos e permitem a avaliação de cenários e de intervenções que tenham como objetivo a redução do impacto do cancro. O desconhecimento de projeções da taxa de incidência destas neoplasias na área abrangida pelo ROR-Sul, levou à utilização de modelos de projeção que diferem entre si quanto à sua estrutura, linearidade (ou não) dos seus coeficientes e comportamento das taxas na série histórica de dados (e.g. crescente, decrescente ou estável). Os referidos modelos pautaram-se por duas abordagens: (i)modelos lineares no que concerne ao tempo e (ii) extrapolação de efeitos temporais identificados pelos modelos APC para períodos futuros. Foi feita a projeção das taxas de incidência para os anos de 2007 a 2010 tendo em conta o género, idade e neoplasia. É ainda apresentada uma estimativa do impacto económico destas neoplasias no período de projeção. Uma questão pertinente e habitual no contexto clínico e a que o presente estudo pretende dar resposta, reside em saber qual a contribuição da neoplasia em si para a sobrevivência do doente. Nesse sentido, a mortalidade por causa específica é habitualmente utilizada para estimar a mortalidade atribuível apenas ao cancro em estudo. Porém, existem muitas situações em que a causa de morte é desconhecida e, mesmo que esta informação esteja disponível através dos certificados de óbito, não é fácil distinguir os casos em que a principal causa de morte é devida ao cancro. A sobrevivência relativa surge como uma medida objetiva que não necessita do conhecimento da causa específica da morte para o seu cálculo e dar-nos-á uma estimativa da probabilidade de sobrevivência caso o cancro em análise, num cenário hipotético, seja a única causa de morte. Desconhecida a principal causa de morte nos casos diagnosticados com cancro no registo ROR-Sul, foi determinada a sobrevivência relativa para cada uma das neoplasias em estudo, para um período de follow-up de 5 anos, tendo em conta o sexo, a idade e cada uma das regiões que constituem o registo. Foi adotada uma análise por período e as abordagens convencional e por modelos. No epílogo deste estudo, é analisada a influência da variabilidade espaço-temporal nas taxas de incidência. O longo período de latência das doenças oncológicas, a dificuldade em identificar mudanças súbitas no comportamento das taxas, populações com dimensão e riscos reduzidos, são alguns dos elementos que dificultam a análise da variação temporal das taxas. Nalguns casos, estas variações podem ser reflexo de flutuações aleatórias. O efeito da componente temporal aferida pelos modelos APC dá-nos um retrato incompleto da incidência do cancro. A etiologia desta doença, quando conhecida, está associada com alguma frequência a fatores de risco tais como condições socioeconómicas, hábitos alimentares e estilo de vida, atividade profissional, localização geográfica e componente genética. O “contributo”, dos fatores de risco é, por vezes, determinante e não deve ser ignorado. Surge, assim, a necessidade em complementar o estudo temporal das taxas com uma abordagem de cariz espacial. Assim, procurar-se-á aferir se as variações nas taxas de incidência observadas entre os concelhos inseridos na área do registo ROR-Sul poderiam ser explicadas quer pela variabilidade temporal e geográfica quer por fatores socioeconómicos ou, ainda, pelos desiguais estilos de vida. Foram utilizados os Modelos Bayesianos Hierárquicos Espaço-Temporais com o objetivo de identificar tendências espaço-temporais nas taxas de incidência bem como quantificar alguns fatores de risco ajustados à influência simultânea da região e do tempo. Os resultados obtidos pela implementação de todas estas metodologias considera-se ser uma mais valia para o conhecimento destas neoplasias em Portugal.------------ABSTRACT: mortality rates, with the elderly being an increasingly representative sector of the population, mainly due to greater longevity. The incidence of cancer, in general, is greater precisely in that age group. Alongside with other equally damaging diseases (e.g. cardiovascular,degenerative), whose incidence rates increases with age, cancer is of special note. In epidemiological studies, cancer is the global leader in mortality. In developed countries its weight represents 25% of the total number of deaths, with this percentage being doubled in other countries. Obesity, a reduce consumption of fruit and vegetables, physical inactivity, smoking and alcohol consumption, are the five risk factors present in 30% of deaths due to cancer. Globally, and in particular in the South of Portugal, the stomach, rectum and colon cancer have high incidence and mortality rates. From a strictly economic perspective, cancer is the disease that consumes more resources, while from a physical and psychological point of view, it is a disease that is not limited to the patient. Cancer is therefore na up to date disease and one of increased importance, since it reflects the habits and the environment of a society, regardless the intrinsic characteristics of each individual. The adoption of statistical methodology applied to cancer data modelling is especially valuable and relevant when the information comes from population-based cancer registries (PBCR). In such cases, these registries allow for the assessment of the risk and the suffering associated to a given neoplasm in a specific population. The weight that stomach, colon and rectum cancers assume in Portugal was one of the motivations of the present study, that focus on analyzing trends, projections, relative survival and spatial distribution of these neoplasms. The data considered in this study, are all cases diagnosed between 1998 and 2006, by the PBCR of Portugal, ROR-Sul.Only year of diagnosis, also called period, was the only time variable considered in the initial descriptive analysis of the incidence rates and trends for each of the three neoplasms considered. However, a methodology that only considers one single time variable will probably fall short on the conclusions that could be drawn from the data under study. In cancer, apart from the variable period, the age at diagnosis and the birth cohort are also temporal variables and may provide an additional contribution to the characterization of the incidence. The relevance assumed by these temporal variables justified its inclusion in a class of models called Age-Period-Cohort models (APC). This class of models was used for the analysis of the incidence rates of the three cancers under study. APC models allow to model nonlinearity and/or sudden changes in linear relationships of rate trends. Two approaches of APC models were considered: the classical and the one using smoothing functions. The models were stratified by gender and, when justified, further studies explored other sub-models where only one or two temporal variables were considered. After the analysis of the incidence rates, a subsequent goal is related to their projections in future periods. Although the effect of structural changes in the population, of which Portugal is not oblivious, may substantially change the expected number of future cancer cases, the results of these projections could help planning health policies with the proper allocation of resources, allowing for the evaluation of scenarios and interventions that aim to reduce the impact of cancer in a population. Worth noting that cancer incidence worldwide obtained from demographic projections point out to an increase of 25% of cancer cases in the next two decades. The lack of projections of incidence rates of the three cancers under study in the area covered by ROR-Sul, led us to use a variety of forecasting models that differ in the nature and structure. For example, linearity or nonlinearity in their coefficients and the trend of the incidence rates in historical data series (e.g. increasing, decreasing or stable).The models followed two approaches: (i) linear models regarding time and (ii) extrapolation of temporal effects identified by the APC models for future periods. The study provide incidence rates projections and the numbers of newly diagnosed cases for the year, 2007 to 2010, taking into account gender, age and the type of cancer. In addition, an estimate of the economic impact of these neoplasms is presented for the projection period considered. This research also try to address a relevant and common clinical question in these type of studies, regarding the contribution of the type of cancer to the patient survival. In such studies, the primary cause of death is commonly used to estimate the mortality specifically due to the cancer. However, there are many situations in which the cause of death is unknown, or, even if this information is available through the death certificates, it is not easy to distinguish the cases where the primary cause of death is the cancer. With this in mind, the relative survival is an alternative measure that does not need the knowledge of the specific cause of death to be calculated. This estimate will represent the survival probability in the hypothetical scenario of a certain cancer be the only cause of death. For the patients with unknown cause of death that were diagnosed with cancer in the ROR-Sul, the relative survival was calculated for each of the cancers under study, for a follow-up period of 5 years, considering gender, age and each one of the regions that are part the registry. A period analysis was undertaken, considering both the conventional and the model approaches. In final part of this study, we analyzed the influence of space-time variability in the incidence rates. The long latency period of oncologic diseases, the difficulty in identifying subtle changes in the rates behavior, populations of reduced size and low risk are some of the elements that can be a challenge in the analysis of temporal variations in rates, that, in some cases, can reflect simple random fluctuations. The effect of the temporal component measured by the APC models gives an incomplete picture of the cancer incidence. The etiology of this disease, when known, is frequently associated to risk factors such as socioeconomic conditions, eating habits and lifestyle, occupation, geographic location and genetic component. The "contribution"of such risk factors is sometimes decisive in the evolution of the disease and should not be ignored. Therefore, there was the need to consider an additional approach in this study, one of spatial nature, addressing the fact that changes in incidence rates observed in the ROR-Sul area, could be explained either by temporal and geographical variability or by unequal socio-economic or lifestyle factors. Thus, Bayesian hierarchical space-time models were used with the purpose of identifying space-time trends in incidence rates together with the the analysis of the effect of the risk factors considered in the study. The results obtained and the implementation of all these methodologies are considered to be an added value to the knowledge of these neoplasms in Portugal.

Occurrence of severe dengue in Rio de Janeiro: an ecological study

Introduction This study aimed to analyze the relationship between the incidence of severe dengue during the 2008 epidemic in Rio de Janeiro, Brazil, and socioeconomic indicators, as well as indicators of health service availability and previous circulation of the dengue virus serotype-3 (DENV-3). Methods In this ecological study, the units of analysis were the districts of Rio de Janeiro. The data were incorporated into generalized linear models, and the incidence of severe dengue in each district was the outcome variable. Results The districts with more cases of dengue fever in the 2001 epidemic and a higher percentage of residents who declared their skin color or race as black had higher incidence rates of severe dengue in the 2008 epidemic [incidence rate ratio (IRR)= 1.21; 95% confidence interval (95%CI)= 1.05-1.40 and IRR= 1.34; 95%CI= 1.16-1.54, respectively]. In contrast, the districts with Family Health Strategy (FHS) clinics were more likely to have lower incidence rates of severe dengue in the 2008 epidemic (IRR= 0.81; 95%CI= 0.70-0.93). Conclusions At the ecological level, our findings suggest the persistence of health inequalities in this region of Brazil that are possibly due to greater social vulnerability among the self-declared black population. Additionally, the protective effect of FHS clinics may be due to the ease of access to other levels of care in the health system or to a reduced vulnerability to dengue transmission that is afforded by local practices to promote health.

DESARROLLO DE APLICACIONES ESTADÍSTICAS PARA LA AGRICULTURA DE PRECISIÓN. STATISTICAL APPLICATIONS FOR PRECISION AGRICULTURE

A partir de las últimas décadas se ha impulsado el desarrollo y la utilización de los Sistemas de Información Geográficos (SIG) y los Sistemas de Posicionamiento Satelital (GPS) orientados a mejorar la eficiencia productiva de distintos sistemas de cultivos extensivos en términos agronómicos, económicos y ambientales. Estas nuevas tecnologías permiten medir variabilidad espacial de propiedades del sitio como conductividad eléctrica aparente y otros atributos del terreno así como el efecto de las mismas sobre la distribución espacial de los rendimientos. Luego, es posible aplicar el manejo sitio-específico en los lotes para mejorar la eficiencia en el uso de los insumos agroquímicos, la protección del medio ambiente y la sustentabilidad de la vida rural. En la actualidad, existe una oferta amplia de recursos tecnológicos propios de la agricultura de precisión para capturar variación espacial a través de los sitios dentro del terreno. El óptimo uso del gran volumen de datos derivado de maquinarias de agricultura de precisión depende fuertemente de las capacidades para explorar la información relativa a las complejas interacciones que subyacen los resultados productivos. La covariación espacial de las propiedades del sitio y el rendimiento de los cultivos ha sido estudiada a través de modelos geoestadísticos clásicos que se basan en la teoría de variables regionalizadas. Nuevos desarrollos de modelos estadísticos contemporáneos, entre los que se destacan los modelos lineales mixtos, constituyen herramientas prometedoras para el tratamiento de datos correlacionados espacialmente. Más aún, debido a la naturaleza multivariada de las múltiples variables registradas en cada sitio, las técnicas de análisis multivariado podrían aportar valiosa información para la visualización y explotación de datos georreferenciados. La comprensión de las bases agronómicas de las complejas interacciones que se producen a la escala de lotes en producción, es hoy posible con el uso de éstas nuevas tecnologías. Los objetivos del presente proyecto son: (l) desarrollar estrategias metodológicas basadas en la complementación de técnicas de análisis multivariados y geoestadísticas, para la clasificación de sitios intralotes y el estudio de interdependencias entre variables de sitio y rendimiento; (ll) proponer modelos mixtos alternativos, basados en funciones de correlación espacial de los términos de error que permitan explorar patrones de correlación espacial de los rendimientos intralotes y las propiedades del suelo en los sitios delimitados. From the last decades the use and development of Geographical Information Systems (GIS) and Satellite Positioning Systems (GPS) is highly promoted in cropping systems. Such technologies allow measuring spatial variability of site properties including electrical conductivity and others soil features as well as their impact on the spatial variability of yields. Therefore, site-specific management could be applied to improve the efficiency in the use of agrochemicals, the environmental protection, and the sustainability of the rural life. Currently, there is a wide offer of technological resources to capture spatial variation across sites within field. However, the optimum use of data coming from the precision agriculture machineries strongly depends on the capabilities to explore the information about the complex interactions underlying the productive outputs. The covariation between spatial soil properties and yields from georeferenced data has been treated in a graphical manner or with standard geostatistical approaches. New statistical modeling capabilities from the Mixed Linear Model framework are promising to deal with correlated data such those produced by the precision agriculture. Moreover, rescuing the multivariate nature of the multiple data collected at each site, several multivariate statistical approaches could be crucial tools for data analysis with georeferenced data. Understanding the basis of complex interactions at the scale of production field is now within reach the use of these new techniques. Our main objectives are: (1) to develop new statistical strategies, based on the complementarities of geostatistics and multivariate methods, useful to classify sites within field grown with grain crops and analyze the interrelationships of several soil and yield variables, (2) to propose mixed linear models to predict yield according spatial soil variability and to build contour maps to promote a more sustainable agriculture.