Biometria ocular na espécie Cebus apella

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aplicação de sistemas imunológicos artificiais para biometria facial: Reconhecimento de identidade baseado nas características de padrões binários

Pós-graduação em Engenharia Elétrica - FEIS

Qualidade dos fenos de capim-tifton 85 e alfafa sobre a biometria corporal e o desempenho esportivo de cavalos atletas na modalidade de três tambores

Pós-graduação em Zootecnia - FMVZ

Testes oftálmicos, biometria ocular e cálculo do poder dióptrico da lente em corujas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Efeitos das antocianinas, ácidos hidroxinâmicos e vitamina C sobre a biometria, composição corporal e qualidade óssea de ratos Wistar

Pós-graduação em Medicina Veterinária - FCAV

Biometria de frutos e sementes, crescimento e produção de mudas de Campomanesia adamantium Blume e Campomanesia pubescens O. Berg

Campomanesia adamantium and Campomanesia pubescens are morphologically similar, occur in the same regions of the Cerrado, are difficult to differentiate and exhibit naturally slow growth and development. The objectives of this study were to analyze fruit and seed biometric data, emergence capacity and seedling growth characteristics. Fruit from both species was collected and used to measure biometric data of the fruit and seeds and to set up two emergence and two seedling growth experiments. C. adamantium fruit is round and has wider, pale yellow seeds while C. pubescens fruit is ellipsoidal to pyriform with yellow gold seeds. C. adamantium’s greater fresh fruit mass and biometric variability favors selection of promising material for commercialization. Seed drying reduced the speed and rate of seedling emergence of C. adamantium, but had no effect on C. pubescens. Leaf number, height, shoot dry weight and the ratio of shoot dry weight to root dry weight were greater in C. adamantium than in the slower growing C. pubescens. Increases in substrate volume favor seedling development. Slow-release fertilizer application at 1g per 115 cm3 substrate increased leaf formation, plant height and shoot dry weight of seedlings of both species and lateral budding in C. adamantium. Until 120 days after transplant, lateral budding was not observed in C. pubescens seedlings. For all traits evaluated in this experiment, C. adamantium seedling growth was greater than that of C. pubescens.

Biometria do endocarpo de taperebá (Spondias mombin L. - Anacardiaceae).

2015

Biometria de frutos e sementes de abiu e influência do sombreamento na emergência das plântulas.

O Abiu [Pouteria caimito (Ruiz & Pav.) Radlk.] é uma espécie arbórea frutífera com o consumo difundido principalmente nos estados do Acre, Amapá e Pará. O objetivo foi avaliar aspectos biométricos de frutos e sementes e a influência do sombreamento na emergência de plântulas de abiu. Foram coletados 50 frutos, em Santa Bárbara (PA) e, foram realizadas mensurações do comprimento, diâmetro, massa, e contagem do número de sementes por fruto. Posteriormente, foram separadas 100 sementes e mediu-se o comprimento, largura e a espessura. Para estudar a influência do nível de sombreamento na emergência foram utilizados quatro tratamentos: pleno sol, 30, 50 e 70%, constando de quatro repetições de 25 sementes por tratamento. Foram avaliados a porcentagem e o tempo médio de emergência. Os aspectos biométricos de frutos e sementes foram submetidos à análise descritiva e a porcentagem de emergência e tempo médio submetidas à análise de variância. Os frutos apresentaram tamanho médio igual a 58,99 e 51,66 mm para comprimento e diâmetro, respectivamente. As sementes apresentaram tamanho médio igual a 36,01; 16,06; 13,61 mm para comprimento, largura e espessura, respectivamente. Para a porcentagem de emergência de plântulas não houve diferença estatística entre os tratamentos, entretanto para o tempo médio os níveis de sombreamento foram menores diferindo estatisticamente em relação ao pleno sol.

Agrupamento e biometria de pontoações intervasculares, densidade e vasos/poros de madeiras da família Leguminosae com raios unisseriados.

A anatomia da madeira é caracterizada pela análise dos elementos celulares do xilema secundário de espécies arbóreas, constituindo-se em uma valiosa ferramenta para a identificação de espécies florestais. O objetivo deste trabalho foi agrupar 18 gêneros da família Leguminosae com raios predominantemente unisseriados, considerando a estratificação, composição (homogeneidade e heterogeneidade), densidade da madeira, os usos comerciais associados, assim como a análise da biometria dos poros/vasos (frequência e diâmetro) e o diâmetro das pontoações intervasculares. Foram analisadas amostras de madeira do acervo da Xiloteca da Embrapa Amazônia Oriental, Belém- PA. Realizaram-se também consultas bibliográficas. Dez gêneros foram agrupados como possuindo raios estratificados e homogêneos e oito raios não estratificados e heterogêneos. Da mesma forma o grupo das medianamente pesadas foi representado por oito gêneros, enquanto que o das madeiras pesadas reuniu dez gêneros. O agrupamento das estruturas permite a classificação e identificação das espécies, contribuindo para ações de fiscalização e melhor direcionamento para o manejo florestal.

Mammographic mass-screening and future breast cancer burden in Finland

A population-based early detection program for breast cancer has been in progress in Finland since 1987. According to regulations during the study period 1987-2001, free of charge mammography screening was offered every second year to women aged 50-59 years. Recently, the screening service was decided to be extended to age group 50-69. However, the scope of the program is still frequently discussed in public and information about potential impacts of mass-screening practice changes on future breast cancer burden is required. The aim of this doctoral thesis is to present methodologies for taking into account the mass-screening invitation information in breast cancer burden predictions, and to present alternative breast cancer incidence and mortality predictions up to 2012 based on scenarios of the future screening policy. The focus of this work is not on assessing the absolute efficacy but the effectiveness of mass-screening, and, by utilizing the data on invitations, on showing the estimated impacts of changes in an existing screening program on the short-term predictions. The breast cancer mortality predictions are calculated using a model that combines incidence, cause-specific and other cause survival on individual level. The screening invitation data are incorporated into modeling of breast cancer incidence and survival by dividing the program into separate components (first and subsequent rounds and years within them, breaks, and post screening period) and defining a variable that gives the component of the screening program. The incidence is modeled using a Poisson regression approach and the breast cancer survival by applying a parametric mixture cure model, where the patient population is allowed to be a combination of cured and uncured patients. The patients risk to die from other causes than breast cancer is allowed to differ from that of a corresponding general population group and to depend on age and follow-up time. As a result, the effects of separate components of the screening program on incidence, proportion of cured and the survival of the uncured are quantified. According to the predictions, the impacts of policy changes, like extending the program from age group 50-59 to 50-69, are clearly visible on incidence while the effects on mortality in age group 40-74 are minor. Extending the screening service would increase the incidence of localized breast cancers but decrease the rates of non-localized breast cancer. There were no major differences between mortality predictions yielded by alternative future scenarios of the screening policy: Any policy change would have at the most a 3.0% reduction on overall breast cancer mortality compared to continuing the current practice in the near future.

Bayesian fisheries stock assessment: integrating and updating knowledge

In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.

Joint Regression and Association Models for Repeated Categorical Responses

The focus of this study is on statistical analysis of categorical responses, where the response values are dependent of each other. The most typical example of this kind of dependence is when repeated responses have been obtained from the same study unit. For example, in Paper I, the response of interest is the pneumococcal nasopharengyal carriage (yes/no) on 329 children. For each child, the carriage is measured nine times during the first 18 months of life, and thus repeated respones on each child cannot be assumed independent of each other. In the case of the above example, the interest typically lies in the carriage prevalence, and whether different risk factors affect the prevalence. Regression analysis is the established method for studying the effects of risk factors. In order to make correct inferences from the regression model, the associations between repeated responses need to be taken into account. The analysis of repeated categorical responses typically focus on regression modelling. However, further insights can also be gained by investigating the structure of the association. The central theme in this study is on the development of joint regression and association models. The analysis of repeated, or otherwise clustered, categorical responses is computationally difficult. Likelihood-based inference is often feasible only when the number of repeated responses for each study unit is small. In Paper IV, an algorithm is presented, which substantially facilitates maximum likelihood fitting, especially when the number of repeated responses increase. In addition, a notable result arising from this work is the freely available software for likelihood-based estimation of clustered categorical responses.

Bayesian analysis of community dynamics

Elucidating the mechanisms responsible for the patterns of species abundance, diversity, and distribution within and across ecological systems is a fundamental research focus in ecology. Species abundance patterns are shaped in a convoluted way by interplays between inter-/intra-specific interactions, environmental forcing, demographic stochasticity, and dispersal. Comprehensive models and suitable inferential and computational tools for teasing out these different factors are quite limited, even though such tools are critically needed to guide the implementation of management and conservation strategies, the efficacy of which rests on a realistic evaluation of the underlying mechanisms. This is even more so in the prevailing context of concerns over climate change progress and its potential impacts on ecosystems. This thesis utilized the flexible hierarchical Bayesian modelling framework in combination with the computer intensive methods known as Markov chain Monte Carlo, to develop methodologies for identifying and evaluating the factors that control the structure and dynamics of ecological communities. These methodologies were used to analyze data from a range of taxa: macro-moths (Lepidoptera), fish, crustaceans, birds, and rodents. Environmental stochasticity emerged as the most important driver of community dynamics, followed by density dependent regulation; the influence of inter-specific interactions on community-level variances was broadly minor. This thesis contributes to the understanding of the mechanisms underlying the structure and dynamics of ecological communities, by showing directly that environmental fluctuations rather than inter-specific competition dominate the dynamics of several systems. This finding emphasizes the need to better understand how species are affected by the environment and acknowledge species differences in their responses to environmental heterogeneity, if we are to effectively model and predict their dynamics (e.g. for management and conservation purposes). The thesis also proposes a model-based approach to integrating the niche and neutral perspectives on community structure and dynamics, making it possible for the relative importance of each category of factors to be evaluated in light of field data.