This investigation was designed to test a hypothesis formulated by Julia Sherman (1967) concerning the development of spatial visualization and mathematic skills. The intention of the study was to examine the influence of early physical training on spatial visualization and mathematic skills, to determine whether intensive training in spatial relations would have a differential impact on male/female spatial performance and to gather information concerning the relationship between spatial visualization and mathematic performance. The investigation was divided into three studies and used 166 college students as subjects. Study one examined the impact of long term physical training, gymnastics, on spatial visualization and mathematic scores of two matched-groups selected from 99 subjects. The two groups, gymnast and control, each consisted of 28 subjects (14 males and 14 females) and were matched on IQ score, age, ethnic group, socioeconomic status, parental and sex-role identification, achievement motivation and years of training in other sports. Gymnasts averaged 5.5 years of gymnastic training: the control group had none. Study two examined spatial visualization scores obtained by 67 architectural students (49 males and 18 females) before and after a semester's training in spatial relations. Study three compared scores obtained by all 166 subjects on the Shepard Metzler Mental Rotation Test and a mathematic test derived from the Otis Test of Mental Abilities. The test of the hypothesis relating to the influence of early physical training on spatial and mathematic performance was not successful as the training of the gymnasts did not extend to early childhood. While significant sex-related differences favoring males were found in spatial performance, the amount of variance in spatial scores accounted for by sex was small, only 8%. No significant sex-related differences in mathematic performance were found. In study two, both males and females significantly improved spatial performance following training, but females did not demonstrate a significantly greater rate of improvement as predicted. The results of the third study indicated a moderate positive relationship between spatial and mathematic performance, however, no evidence was found to support a direct causal relationship between spatial skill and mathematic performance.

This thesis examines the role of a distinctive group of monastic buildings, those constructed for the use of visitors, placing them in the distinctive cultural settings of the monastery and the surrounding secular landscape. It reconsiders the applicability of the inside/outside, secular/monastic dichotomy, which tends to imply restriction of access to the house, and examines human behaviour in and around visitors' structures, in the form of ritualized hospitality. It is thus concerned with the recursive relationships between monastic and secular cultures, and between individuals negotiating power through their manipulation and structuring of space. This thesis employs an explicitly archaeological research agenda and recording methodology which explores the evidence at both extensive and intensive levels. An extensive survey of surviving gatehouse remains was undertaken to examine the apparent `liminal' role of these structures. At the intensive level, detailed building recording was undertaken on two complexes, at Stoneleigh Abbey and Gloucester Cathedral, whose primary function was to provide hospitality to outsiders. These are used as primary case studies, and are supplemented by textual, pictorial, and landscape evidence in order to investigate what monastic hospitality was, in what manner it was expressed, and how it was experienced.

A dissertation submitted in fulfilment of the academic requirements for the degree of Master of Science in the School of Animal, Plant and Environmental Sciences, University of the Witwatersrand, Johannesburg. June 2016 / The African baobab (Adansonia digitata) is a charismatic and iconic tree. This keystone species has highly specific moisture requirements for recruitment, a very slow life history, low dispersal capabilities, and is exposed to heavy, often destructive utilization by baboons, elephants and humans. These characteristics result in the reduced ability for baobabs to accommodate and respond to changing environmental conditions. During periods of unfavourable conditions, baobabs rely on the persistence of established individuals for the survival of the population. The Kruger National Park (KNP), South Africa falls within the southern-most distribution of the baobab. A perceived lack of recruitment together with high numbers of dead large baobabs recorded in aerial surveys prompted concern over local population decline in the early 1990s. Long-term monitoring is necessary in order to quantify changes occurring within the KNP baobab population. For this reason Dr Ian Whyte sampled 424 baobab trees in northern KNP in 1995/1996 to describe population size-class distributions and elephant damage. Nearly all of these baobabs, with the addition of 486 individuals were resampled in 2001 by Michele Hofmeyr. This study resampled the majority of these 910 baobabs plus 126 individuals within 50m of those previously sampled, culminated in a data set spanning 18 years and most of the dominant vegetation and climatic zones within the baobab’s KNP range. Photographs taken in 1995/6 and repeated in 2013 allowed for simultaneous direct visual comparisons of elephant damage to baobab stems. This study aimed to record the temporal and spatial changes in the demographics of, and damage to, this sample of 1036 baobabs in order to define and evaluate the factors threatening KNP baobab persistence. The overall population stem diameter structure of baobabs in the KNP showed a healthy inverse J-shaped distribution, with a high proportion of smaller trees and a decreasing proportion of larger trees at each sampling snapshot. However no seedling recruitment was observed during intensive searches within 50m of sampled trees, accumulating in a total area of 4km2. Growth was only noticeable in sub-adult trees >0.15m and <1m in stem diameter. Annualised mortality increased three-fold between the periods 1995/6-2001 (0.25%) and 2001-2013 (0.79%). It is speculated that this increase in mortality is due to the cumulative effect of increased elephant damage, together with below average rainfall years of 2002 to 2013. Trees that had previously sustained severe and very severe damage contributed the highest proportion (32%) of mortality. When comparing sizeclasses, the majority of mortality (61%) was recorded within the <1m stem diameter size-class. However, a high proportion of very large trees (21% of the 4- 4.5m and 29% of the 5-5.5m stem-diameter baobabs sampled) had died from unknown causes. With no recruitment of seedlings evident and little recruitment between size classes, mortality alone was not enough to significantly change the baobab population structure between 1995/6, 2001 and 2013. This might change should more very large (>4m stem-diameter) trees die, as these size classes make up less than 2% of the population. At a spatial scale, maximum fire return interval, level of elephant damage and mean annual temperature all had significant impacts on the size-class distribution of baobabs. Longer (>30 years) maximum fire return intervals and higher mean annual temperatures (23°C) supported an inverse J-shaped baobab population structure whilst shorter (<30 years) maximum fire return intervals and lower mean annual temperatures (21-22°C) supported a bell-shaped population structure. Increases in bark damage over time correlated with increased elephant density (primarily attributed to mature male elephant density). Smaller baobabs – those less than <1m in stem diameter, generally escaped elephant utilization altogether, or suffered very severe damage by elephants. Despite a 3-fold increase in mortality and no recruitment over the 18 year study period, the KNP baobab population has maintained its inverse J-shaped population structure. The high proportion of mortality in the >4m stem diameter is however concerning as the persistence of these large baobabs is essential for the survival of the population during unfavourable conditions for recruitment.

This thesis develops methodologies for continuous estimation of hydrological variables which infill missing daily rainfall data and the forecast of weekly streamflows from a watershed. Several mathematical programming formulations were developed and used to estimate missing historical rainfall data. Functional relationships were created between radar precipitation and known rain gauge data then are used to estimate the missing data. Streamflow predictions models require highly non-linear mathematical models to capture the complex physical characteristics of a watershed. An artificial neural network model was developed for streamflow prediction. There are no set methods of creating a neural network and the selection of architecture and inputs to a neural network affects the performance. This thesis addresses this issue with automated input and network architecture selection through optimization. MATLABª scripts are developed and used to test many combinations and select a model through optimization. / by Ricardo Eric Brown. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2012. Mode of access: World Wide Web.

Researchers increasingly advocate the use of ecosystem-based management (EBM) for managing complex marine ecosystems. This approach requires managers to focus on processes and cross-scale interactions, rather than individual components. However, they often lack appropriate tools and data sources to pursue this change in management approach. One method that has been proposed to understand the ecological complexity inherent in marine ecosystems is the study of biological hotspots. Biological hotspots are locations where organisms from different trophic levels aggregate to feed on abundant supplies, and they are considered a first step toward understanding the processes driving spatial and temporal heterogeneity in marine systems. Biological hotspots are supported by phytoplankton aggregations, which are characterized by high spatial and temporal variability. As a result, methods developed to locate biological hotspots in relatively stable terrestrial systems are not well suited for more dynamic marine ecosystems. The main objective of this thesis is thus to identify and characterize local-scale biological hotspots in the western side of the Gulf of Maine. The first chapter describes a new methodological framework with the steps needed to locate these types of hotspots in marine ecosystems using remote sensing datasets. Then, in the second chapter these hotspots are characterized using a novel metric that uses time series information and spatial statistics to account for both the temporal variability and spatial structure of these marine aggregations. This metric redefines biological hotspots as areas with a high probability of exhibiting positive anomalies of productivity compared to the expected regional seasonal pattern. Finally, the third chapter compares the resulting biological hotspots to fishery-dependent abundance indices of surface and benthic predators to determine the effect of the location and magnitude of phytoplankton aggregations on the rest of the ecosystem. Analyses indicate that the spatial scale and magnitude of biological hotspots in the Gulf of Maine depend on the location and time of the year. Results also show that these hotspots change over time in response to both short-term oceanographic processes and long-term climatic cycles. Finally, the new metric presented here facilitates the spatial comparison between different trophic levels, thus allowing interdisciplinary ecosystem-wide studies.

Em 2015 ocorreram no mundo 210.758 casos novos de hanseníase, representando uma taxa de detecção de 3,2 casos para cada 100.000 habitantes. O Brasil foi o segundo país em número de casos, com um coeficiente de detecção de 14,6 casos por 100.000 habitantes. Uma das principais características epidemiológicas da hanseníase é sua heterogeneidade e desigualdade de distribuição em um local geograficamente definido, o que torna relevante identificar áreas mais suscetíveis que explicam a ocorrência da doença nesses locais. Objetivo: Identificar áreas de maior e de menor risco para a ocorrência de hanseníase em Ribeirão Preto/SP. Materiais e Métodos: Trata-se de um estudo ecológico, realizado no município de Ribeirão Preto/SP, em que foram considerados os casos de hanseníase notificados no SINAN no período de janeiro de 2006 a dezembro de 2013. Para detecção de risco para aglomerados espaciais e espaço-temporais dos casos de hanseníase procedeu-se inicialmente a geocodificação dos casos por meio do software TerraView versão 4.2.2, utilizando como unidade de análise ecológica o setor censitário urbano. A técnica de estatística de varredura foi processada controlando- se a ocorrência de casos pelo tamanho da população dos setores censitários, por sua distribuição etária e do sexo, com vistas a detecção de aglomerados no espaço e no espaço-tempo de alto e baixo risco relativo (RR) com seus respectivos intervalos de confiança em 95%. Fixou-se erro tipo I em 5% (p<0,05) como estatisticamente significativos. A técnica de varredura foi processada no software SaTScan 9.4 e os mapas temáticos contendo o RR dos aglomerados foram feitos por meio do software ArcGIS 10.1. O estudo foi aprovado pelo Comitê de Ética em Pesquisa da Escola de Enfermagem de Ribeirão Preto/USP (nº 44637215.0.0000.5393). Resultados: Foram notificados 434 casos de hanseníase no período de investigação, dos quais 392 casos foram geocodificados (95%). A análise de varredura dos casos de hanseníase possibilitou a detecção de dois aglomerados espaciais estatisticamente significativos (p<0,05), no qual um aglomerado de alto risco (RR=3,41; IC95%: 2,721-4,267; p=0,000), e um de baixo risco (RR=0,41; IC95%: 0,326-0,528; p=0,000). Na análise espaço-temporal, foram identificados três aglomerados estatisticamente significativos (p<0,05), sendo dois de alto risco (RR=24,35; IC95%: 11,133-52,984; p=0,006), (RR=15,24, IC95%: 10,114-22,919; p=0,000) ocorridos no período de 2012 a 2012 e 2012 a 2013, respectivamente; e um aglomerado de baixo risco (RR=0,35; IC95%: 0,252-0,485) no período de 2008 a 2011. Conclusões: O estudo possibilitou a identificação das áreas de maior e menor risco para o acometimento pela hanseníase. Os locais com maior RR situam-se nos distritos de saúde Norte, Oeste e Central, caracterizados por apresentar os piores indicadores socioeconômicos do município, com carências em habitação, renda, escolaridade e acesso a serviços de saúde, o que evidencia a desigualdade social no local sob estudo / In 2015, 210,758 new cases of leprosy occurred in the world, representing a detection rate of 3.2 cases per 100,000 inhabitants. Brazil was the second country in terms of number of cases, with a detection coefficient of 14.6 cases per 100,000 inhabitants. The main epidemiological characteristics of leprosy is its heterogeneity and inequality distribution in an area geographically located, which becomes the disease an important issue to identify areas with Risk. Objective: To identify areas with high and low risk for occurrence of leprosy in Ribeirão Preto / SP. Materials and Methods: This is an ecological study, carried out in Ribeirão Preto / SP, in which the cases were gathered through SINAN from January 2006 to December 2013. For the detection of areas with Spatial Risk and Spatial Temporal Risk, initially the cases of leprosy cases were geocoded cases using TerraView software version 4.2.2; Census tract was considered as ecological analysis unit or urban. The scan statistic was performed considering occurrence of cases by size of the population in census tract according age and sex. It was measured the Relative Risk and its confident interval by 95%. Type I error was set at 5% (p <0.05) as statistically significant. The scanning technique was used by SaTScan 9.4 software and the thematic maps was constructed by ArcGIS 10.1. The study was approved by the Research Ethics Committee of Ribeirão Preto School of Nursing - USP (nº 44637215.0.0000.5393). Results: A total of 434 leprosy cases were reported, of which 392 cases were geocoded (95%). Through Scan Statistic two areas were observed as statistically significant (p <0.05), being one area with high risk (RR = 3.41; CI95%: 2.721-4.267; p=0.000), and another one with low risk (RR = 0.41; CI95%: 0.326-0.528; p=0.000). In the space-time analysis, three statistically significant clusters (p <0.05) were identified, two of them were with high risk (RR = 24.35; CI95%: 11.133-52.984; p=0.006), (RR = 15.24; CI95%: 10.114-22.919; p=0.000) and one with low risk (RR = 0, 35; CI95%: 0.252-0.485; p=0.000). Conclusions: The study provided the identification of the areas with high and low risk for transmission of leprosy. The areas with high Risk are located in the districts of North, West and Central health, which also present the social vulnerability in terms of dwelling, income, schooling and access to the health services

This thesis explores the development of residential segregation over a long time period in Stockholm, Sweden. By following the spatial distribution of two socio- economic indicators and two indicators of housing characteristics between 1930 and 2015, it describes how changing housing policy has affected the indicators. Historic data was gathered and compiled in a longitudinal data base. Spatial analysis of the variables produced results that indicate spatio-temporal variation in all variables, and indicate a central-peripheral pattern that has developed and persisted for long time periods. Variation in spatial distributions of the variables is furthermore connected to changes in undertaken housing policy. Regression models also indicate that the characteristics of residential segregation has arguably been different in different times. The long time period is argued to be important in segregation research because of the longevity of many segregation processes. Following continuous indices of residential segregation over long time periods is important as it may help us understand contemporary trends better, conversely creating better knowledge for policy makers when counter segregation policy is implemented. Long time approaches are, however, lacking the literature, motivating the analysis performed in this thesis.

The focus of this thesis is extremal dependence among spatial observations. In particular, this research extends the notion of the extremogram to the spatial process setting. Proposed by Davis and Mikosch (2009), the extremogram measures extremal dependence for a stationary time series. The versatility and flexibility of the concept made it well suited for many time series applications including from finance and environmental science. After defining the spatial extremogram, we investigate the asymptotic properties of the empirical estimator of the spatial extremogram. To this end, two sampling scenarios are considered: 1) observations are taken on the lattice and 2) observations are taken on a continuous region in a continuous space, in which the locations are points of a homogeneous Poisson point process. For both cases, we establish the central limit theorem for the empirical spatial extremogram under general mixing and dependence conditions. A high level overview is as follows. When observations are observed on a lattice, the asymptotic results generalize those obtained in Davis and Mikosch (2009). For non-lattice cases, we define a kernel estimator of the empirical spatial extremogram and establish the central limit theorem provided the bandwidth of the kernel gets smaller and the sampling region grows at proper speeds. We illustrate the performance of the empirical spatial extremogram using simulation examples, and then demonstrate the practical use of our results with a data set of rainfall in Florida and ground-level ozone data in the eastern United States. The second part of the thesis is devoted to bootstrapping and variance estimation with a view towards constructing asymptotically correct confidence intervals. Even though the empirical spatial extremogram is asymptotically normal, the limiting variance is intractable. We consider three approaches: for lattice data, we use the circular bootstrap adapted to spatial observations, jackknife variance estimation, and subsampling variance estimation. For data sampled according to a Poisson process, we use subsampling methods to estimate the variance of the empirical spatial extremogram. We establish the (conditional) asymptotic normality for the circular block bootstrap estimator for the spatial extremogram and show L2 consistency of the variance estimated by jackknife and subsampling. Then, we propose a portmanteau style test to check the existence of extremal dependences at multiple lags. The validity of confidence intervals produced from these approaches and a portmanteau style test are demonstrated through simulation examples. Finally, we illustrate this methodology to two data sets. The first is the amount of rainfall over a grid of locations in northern Florida. The second is ground-level ozone in the eastern United States, which are recorded on an irregularly spaced set of stations.

Advanced lightweight structural materials like composites are being increasingly utilized in various engineering applications due to high specific strength and stiffness with tailorable properties. Even though composites have the advantage of modulating a large number of design parameters to achieve various application-specific requirements, this concurrently brings the challenge of dealing with inevitable uncertainties during manufacturing and service-life conditions. This dissertation focuses on practically relevant modelling of random spatial variability coupled with the influence of damage to quantify the effect of source-uncertainties following an efficient surrogate based framework. Layer-wise random variable based approach and the random field based approaches of uncertainty modelling are investigated to quantify the stochastic dynamics and stability characteristics of in a probabilistic multi-scale framework. A novel concept of stochastic representative volume element is proposed to consider the spatially varying structural attributes effectively. A physically relevant random field based modelling approach with correlated material properties is adopted based on the Karhunen-Loève expansion. To understand the relative influences, sensitivity of the stochastic input parameters are analyzed for the global structural responses of composite laminates considering micro and macro mechanical properties separately. Besides the conventional sources of uncertainty in material and structural properties, another source of uncertainty is considered in the form of noise. Besides probabilistic analysis, this dissertation proposes a fuzzy representative volume element based approach for modelling spatial variability in non-probabilistic analysis for the cases where statistical distributions of the stochastic input parameters are not available. The results reveal that stochasticity affects the system performance significantly. A notable difference in the global stochastic behaviour is identified depending upon the adopted uncertainty modeling approach. Thus, it is imperative to appropriately model the sourceuncertainties during the analysis and design process. The dissertation provides comprehensive insights on the effect of source-uncertainties on composites following an efficient, yet practically relevant modelling approach.

Harbour porpoise (Phocoena phocoena) are the most abundant cetacean in UK waters, and are likely to be affected by a variety of marine industries and activities. This research uses data collected by acoustic recorders (C-PODs) and aerial video surveys to investigate patterns in porpoise detection. The findings can be split into five key themes, and are used to support the development of spatial management and survey recommendations. 1. Porpoise detection changes based on time of day in different habitats, indicating possible differences in diel habitat use and highlighting potential issues with visual or video data collection methods for assessing distribution. 2. Porpoise exhibit seasonal shifts in detection, yet year-round data are often lacking, therefore seasonal changes in distribution are often unknown. 3. The highest proportions of buzzes (associated with foraging) are not detected in areas with the highest relative density of porpoise. I propose that porpoise use different foraging strategies in different habitats which are not equally detectable by acoustic recorders. 4. Porpoise distribution may be influenced by the distribution of perceived risk from predator / competitor species (dolphins). Temporal partitioning of sites may arise either from porpoise actively avoiding times when bottlenose dolphins are expected to be present, or from porpoise and bottlenose preferences for different environmental conditions. 5. The choice of spatial modelling method can influence the fine-scale predictions of areas with the highest density. Improving our understanding of top and mesopredator ecology is informative for management strategies. Each of the points raised above should be considered when determining management strategies to minimise the impact from fisheries, offshore developments and other industrial activities on harbour porpoise.