Um modelo matemático foi desenvolvido, para avaliar o perfil Compton produzido por diferentes distribuições de momento do elétron. Estas distribuições de momento são avaliadas a partir das funções de onda dos elétrons orbitais. Perfis Compton para cinco elementos (Pb POT. 82 , W POT. 74 , Ag POT. 47, Cu POT. 29 e Al POT. 13) e para três ângulos de espalhamento (30º ,15º , 10º) foram calculados usando funções hidrogenóides e Hartree-Fock relativísticas. Experimentalmente usando um de 662 Kev de energia mediu-se, com um detetor GeLi, o perfil Compton desses elementos nas condições geométricas acima, observando-se boa concordância com as distribuições de momento relativístico, calculadas por Biggs, Mendelsohn e Mann. Este acordo, entretanto só foi conseguido quanto utilizamos as correções propostas for Ribberford, que permitem associar o conceito de perfil Compton para qualquer ângulo de espalhamento. Isto mostra que é possível associar univocamente o perfil Compton às distribuições de momento para qualquer ângulo de espalhamento ao contrário do que tradicionalmente se aceitava (apenas 180º). O modelo matemático foi estendido para cálculos de perfis Compton com feixes incidentes e emergentes polarizados. / .

A simulação de dados que seguem distribuição de Poisson é essencial em muitas aplicações reais de várias áreas, tais como saúde, marketing, ciências agronômicas, entre outras em que os dados são contagens multivariadas. Métodos de simulação atuais sofrem de limitações computacionais e restrições à estrutura de correlação e, portanto, são raramente usados. Neste trabalho propôs-se uma modificação do método NORTA para gerar dados com distribuição Poisson multivariada a partir de uma distribuição normal multivariada com matriz de correlações e vetor de médias pré estabelecidos. Como as distribuições Normal multivariada e univariada e a distribuição Poisson univariada já estão implementadas em softwares estatísticos, inclusive no R, implementou-se algumas linhas de código. Mostrou-se que o método funciona bem e é altamente preciso na geração de dados multivariados com distribuição marginais de Poisson, para diferentes estruturas de correlações (negativas e positivas e variando os valores) e para altos e baixos valores de médias. Mostrou-se as vantagens práticas da simulação de dados de Poisson multivariada sobre a normal multivariada na detecção da taxa de falsos alertas de super populações de percevejos, evidenciando que simulações inadequadas podem levar a excesso de falsos alertas. Uma vez que os dados seguem distribuição Poisson multivariada, a taxa de falsos alertas pode ser maior do que a imaginada. Essa taxa pode ser estimada por um modelo ajustado. A mesma técnica pode ser aplicada em diversos problemas de várias áreas do conhecimento. / The simulation data that follow a Poisson distribution is essential in many real applications in various areas such as healthcare, marketing, agronomic sciences, among others that the data are multivariate counts. Current simulation methods suffer from limitations and constraints on computing correlation structure and are therefore seldom used. This paper proposed a modification of the NORTA method for generating data with multivariate Poisson distribution from a multivariate normal distribution with correlation matrix and vector of predetermined average. As the multivariate and univariate Normal distribution and univariate Poisson distribution are already implemented in statistical software, including R, was implemented just a few lines of code. It was shown that the method works well and is highly accurate in generating multivariate data with marginal Poisson distribution structures for different correlations (negative and positive values) and for high and low ?. Proved the practical benefits of the simulation data on the multivariate Poisson multivariate normal in the detection of super bugs populations, inadequate simulations can lead to excessive false alerts. Once the data are multivariate Poisson distribution, the rate of false alarms can be greater than the imagined. This rate can be estimated by an adjusted model. The same technique can be applied to many problems in various fields of knowledge.

Species distributions reflect the suite of resources and range of environmental conditions required by a species. Distributions of many species change seasonally, however, in response to changes in resource availability and environmental conditions, many of which are projected to shift in response to climate change. We sought to identify environmental and anthropogenic factors associated with seasonal changes in the distribution of vertebrates that inhabit the Madrean Archipelago in southern Arizona, which is important for identifying mechanisms through which climate change may affect these species. From July 2012 to February 2015 (966 days), we used remote cameras to survey 200 sites across 16 mountain ranges for a total of 69,434 trap days and used dynamic occupancy models to determine how landscape features, vegetation composition, and anthropogenic factors influenced the distributions and seasonal rates of local colonization and extinction of 13 vertebrates. For these 13 species, we recorded 37,888 detections, with gray foxes, skunks, and squirrels detected most frequently. Bobcats, cottontails, gray foxes, skunks, squirrels, javelina, puma, and coatimundis were all detected across the entire range of elevations surveyed, from 935 to 2395 m. Black bears and wild turkeys were never detected below 1270 m, Sonoran opossums never detected above 1980 m, and coyotes and ringtails never detected above 2020 m. Composition and structure of vegetation in the understory, midstory, and overstory influenced initial occupancy of several species, including skunks, coatimundis, Sonoran opossums, and cottontails. Season, either directly or as an interaction with the estimated amount of solar radiation reaching a site, influenced local extinction rates of all 13 target species and local colonization rates of 9 of 13 species. Elevation influenced local colonization rates of black bears and coatimundis positively, and coyotes, Sonoran opossums, and cottontails negatively, and local extinction rates of skunks negatively and coyotes and black bears positively. These patterns indicate that the distributions of many species in this region change seasonally, likely as a mechanism to meet dietary, behavioral, or physiological needs in response to shifts in environmental conditions and resource availability. Therefore, species that depend on seasonal resources may be at higher risk of distributional shifts or range contractions if the distribution and phenology of these resources change in response to changes in climate.

Background: Trees play crucial roles in the biosphere and societies worldwide, with a total of 60,065 tree species currently identified. Increasingly, a large amount of data on tree species occurrences is being generated worldwide: from inventories to pressed plants. While many of these data are currently available in big databases, several challenges hamper their use, notably geolocation problems and taxonomic uncertainty. Further, we lack a complete picture of the data coverage and quality assessment for open/public databases of tree occurrences. Methods: We combined data from five major aggregators of occurrence data (e.g. Global Biodiversity Information Facility, Botanical Information and Ecological Network v.3, DRYFLOR, RAINBIO and Atlas of Living Australia) by creating a workflow to integrate, assess and control data quality of tree species occurrences for species distribution modeling. We further assessed the coverage - the extent of geographical data - of five economically important tree families (Arecaceae, Dipterocarpaceae, Fagaceae, Myrtaceae, Pinaceae). Results: Globally, we identified 49,206 tree species (84.69% of total tree species pool) with occurrence records. The total number of occurrence records was 36.69 M, among which 6.40 M could be considered high quality records for species distribution modeling. The results show that Europe, North America and Australia have a considerable spatial coverage of tree occurrence data. Conversely, key biodiverse regions such as South-East Asia and central Africa and parts of the Amazon are still characterized by geographical open-public data gaps. Such gaps are also found even for economically important families of trees, although their overall ranges are covered. Only 15,140 species (26.05%) had at least 20 records of high quality. Conclusions: Our geographical coverage analysis shows that a wealth of easily accessible data exist on tree species occurrences worldwide, but regional gaps and coordinate errors are abundant. Thus, assessment of tree distributions will need accurate occurrence quality control protocols and key collaborations and data aggregation, especially from national forest inventory programs, to improve the current publicly available data.

Wet central heating systems account for a very large portion of energy consumption in the UK and recent figures indicate that its usage in households will be increasing even further. Under such circumstances, it is desirable to use these systems in the most efficient way possible. However, dissolved gases that penetrate into central heating systems are later released as bubbles due to local supersaturated conditions occurring on the primary heat exchanger wall of the boiler. This leads to a two-phase flow throughout the pipework, causing microbubbles to escape to the upper parts of the system and creating cold spots in the radiators, thus, reducing its efficiency. There is an increasing trend in building services to install devices that remove these unwanted gases. Therefore, investigation of two-phase structures throughout different pipe installations will facilitate companies in enhancing their deaerator designs. In this regard, extensive experimental and computational investigations of two-phase flow structures were conducted within this study. Two-phase flow structures were measured by a photographic technique and investigated in means of void fractions, bubble sizes, and velocities. Fluid velocities in the range of 0.5 to 1.1 m/s at typical wet central heating temperature (60 to 80 °C) and pressures (2.2 to 27 bar) were utilized. Results show that that bubble production increases as temperature, boiler heating load, and saturation ratio escalate. On the other hand, it reduces when the pressure and flow rate of the system gets higher. A clear relationship between bubble sizes and system parameters was non-existent, except for the system flow rate (where bubble diameters decrease as the flow rate increases). Moreover, bubbles were evenly distributed during vertical flow when compared to horizontal flow, where bubbles tend to flow at the upper parts of the pipe. Furthermore, it was shown that bubble distributions were highly affected by obstacles like the 90 degree bend, thermocouple or pressure sensors. In addition, it was observed that axial flow development of bubbly flow was a continuous process and void fraction at the upper part of the pipe increased as the flow travelled through horizontal pipeline. Regarding the bubble velocity measurements, it was concluded that, bubble velocity profiles show development along both vertical and horizontal flows and approach to profiles which can be expressed with the power-law. Moreover, coalescence of two bubbles during horizontal flow was captured, emphasizing that the effect of coalescences should not be neglected at low void fractions. It was also found that bubbly flow in central heating systems was in a coalescences dominant regime and maximum bubble diameter observed at most positions were higher than theoretically defined values. Moreover, bubble dissolution effect was not observed at any of the test rig conditions. The reasons were thought to be the variation saturation ratio and axial flow development of two-phase flow, which supress the effect of dissolution and favour coalescence phenomenon. Finally, after evaluating conclusions from the experimental results and computational study regarding the effect of the 90 degree bend on void fraction distributions, it was concluded that the employed physical model and solver settings in ANSYS Fluent 14.5, can be utilized to predict bubble distribution developments throughout the central heating systems’ pipework. Keywords: Central heating systems, two-phase flow, bubbly flow, bubble distributions, bubble sizes, bubble velocities, coalescence, image processing, experimental fluid easurements.

Investors and financial analysts spend an inordinate amount of time, resources and effort in an attempt to perfect the science of maximising the level of financial returns. To this end, the field of distribution modelling and analysis of firm size effect is important as an investment analysis and appraisal tool. Numerous studies have been conducted to determine which distribution best fits stock returns (Mandelbrot, 1963; Fama, 1965 and Akgiray and Booth, 1988). Analysis and review of earlier research has revealed that researchers claim that the returns follow a normal distribution. However, the findings have not been without their own limitations in terms of the empirical results in that many also say that the research done does not account for the fat tails and skewness of the data. Some research studies dealing with the anomaly of firm size effect have led to the conclusion that smaller firms tend to command higher returns relative to their larger counterparts with a similar risk profile (Banz, 1981). Recently, Janse van Rensburg et al. (2009a) conducted a study in which both non- normality of stock returns and firm size effect were addressed simultaneously. They used a scale mixture of two normal distributions to compare the stock returns of large capitalisation and small capitalisation shares portfolios. The study concluded that in periods of high volatility, the small capitalisation portfolio is far more risky than the large capitalisation portfolio. In periods of low volatility they are equally risky. Janse van Rensburg et al. (2009a) identified a number of limitations to the study. These included data problems, survivorship bias, exclusion of dividends, and the use of standard statistical tests in the presence of non-normality. They concluded that it was difficult to generalise findings because of the use of only two (limited) portfolios. In the extension of the research, Janse van Rensburg (2009b) concluded that a scale mixture of two normal distributions provided a more superior fit than any other mixture. The scope of this research is an extension of the work by Janse van Rensburg et al. (2009a) and Janse van Rensburg (2009b), with a view to addressing several of the limitations and findings of the earlier studies. The Janse van rensburg (2009b) study was based on data from the Johannesburg Stock Exchange (JSE); this study seeks to compare their research by looking at the New York Stock Exchange (NYSE) to determine if similar results occur in developed markets. For analysis purposes, this study used the statistical software package R (R Development Core Team 2008) and its package mixtools (Young, Benaglia, Chauveau, Elmore, Hettmansperg, Hunter, Thomas, Xuan 2008). Some computation was also done using Microsoft Excel. This dissertation is arranged as follows: Chapter 2 is a literature review of some of the baseline studies and research that supports the conclusion that earlier research finding had serious limitations. Chapter 3 describes the data used in the study and gives a breakdown of portfolio formation and the methodology used in the study. Chapter 4 provides the statistical background of the methods used in this study. Chapter 5 presents the statistical analysis and distribution fitting of the data. Finally, Chapter 6 gives conclusions drawn from the results obtained in the analysis of data as well as recommendations for future work.

Aim It is commonly asserted that climate presents the primary constraint on species’ geographic distributions, and therefore, that species' ranges shift in response to changing climate given their specific climatic tolerances. However, supporting evidence is surprisingly inconsistent. Alternatively, spatially structured processes (e.g., dispersal) could more strongly determine species’ geographic distributions. Is climate the primary determinant of species’ geographic distributions, or might non-climatic, spatial processes constitute a stronger influence, such that the effect of climate is indirect? This study tests a number of predictions made by each of these hypotheses, during a single period of time. Location Contiguous United States and southern Canada. Methods We used 19 species of passerine birds whose distributions fall entirely within the area sampled by the North American Breeding Bird Survey from 1990-2000. We related these distributions to the mean breeding season climate, geographic locations and neighbourhood effects. Two spatial scales were addressed to assess the geographic location of species’ ranges and species' distributions within ranges. Results On average, geographic coordinates and a model representing neighbourhood occupancy outperform a simple climatic model. After controlling for geographic coordinates, species occupancy is poorly related to climate. A neighbourhood model on average accounts for the majority of variance captured by geographic coordinates within ranges, and more for the continental placement of ranges. Spatially explicit variables are more important than macroclimatic variables in a predictive model of species occupancy on average. Main Conclusions The geographic distributions of wide-spread North American passerine birds appear not to be primarily determined by climate. Our results are consistent with the hypothesis that localized spatial processes such as dispersal are stronger determinants of both continental range placement and within-range distributions of North American birds.

Les Distributions de Partons Généralisées (GPDs) encodent les corrélations entre impulsion longitudinale et position transverse des partons dans les hadrons et permettent d'imager la structure du nucléon en 2+1 dimensions. Elles ont été étudiées théoriquement et expérimentalement pendant deux décennies et une nouvelle ère expérimentale débute actuellement (à Jefferson Lab et COMPASS, mais aussi à l'avenir à un collisionneur électron-ion) pour les extraire avec grande précision. La difficulté est que seul un accès expérimental indirect est possible, à travers divers canaux de diffusion exclusive et les observables associés. Cela implique de prendre nécessairement en compte les nombreuses contraintes théoriques si l'on veut concevoir des modèles fiables pour la phénoménologie. En particulier, deux contraintes cruciales sont les propriétés de "polynomialité" et de "positivité". L'approche de cette thèse consiste à tirer partie des deux propriétés en modélisant d'abord les fonctions d'onde sur le cône de lumière des premiers états de Fock du nucléon, permettant d'obtenir une GPD dans la région appelée DGLAP via overlap où le nombre de partons est conservé, puis l'étendre de manière covariante à la région ERBL, avec une inversion de transformée de Radon. In fine, le but est d'appliquer cette procédure à un modèle de quark-constituant pour GPDs de valence, ce qui permettrait de produire de manière inédite pour ce genre de modèle des résultats à comparer à l'expérience (sur le processus de diffusion Compton profondément virtuelle en l’occurrence). Pour atteindre cette objectif, on utilise la librairie PARTONS sous différentes hypothèses perturbatives. / Generalized Parton Distributions (GPDs) encode the correlations between longitudinal momentum and transverse position of partons inside hadrons and can give access to a picture of the nucleon structure in 2+1 dimensions. They have been studied theoretically and experimentally for almost two decades and a new experimental era is starting (at JLab and COMPASS currently, and in the future at an EIC) to extract them. The difficulty is that only an indirect experimental access is so far possible, through different exclusive channels and various observables. Therefore, one has to take into account the many theoretical constraints to be able to produce accurate models and rely on their phenomenology. Two important constraints are called the polynomiality and positivity properties. The approach of this thesis is to make use of both of them by first modeling low Fock states light-front wave-functions, which gives a GPD in the DGLAP region by a parton number conserved overlap, and then covariantly extending this GPD to the ERBL region, through an inverse radon transform. In fine, the goal is to apply this on a constituent quark-like model for valence GPDs, which would allow to produce a phenomenological output (on DVCS data for instance) from this kind of models, which was impossible before. We make use of the versatile PARTONS framework to achieve this under various perturbative QCD assumptions.

The diploma thesis deals with a theoretical description and practical use of probit analysis, which is a part of survival analysis. The thesis shows different probit models, their differences and appropriateness on analised data. The used data belong to the molecular diagnostic area and are provided by Genex CZ company. The result is an analysis of probit analysis output data from Minitab 14 software. The thesis was supported by project from MSMT of the Czech Republic no. 1M06047 Center for Quality and Reliability of Production.

This thesis deals with the problem of estimating statistical distributions from data. In the first part, the method of moments is used in combination with computational algebraic techniques in order to estimate parameters coming from local Dirac mixtures and their convolutions. The second part focuses on the nonparametric setting, in particular on combinatorial and algebraic aspects of the estimation of log-concave distributions.