Although not often discussed in planning curriculum across the United States, airports are a very significant part of the country’s transportation infrastructure. With so much emphasis placed on ground transportation modes such as light rail, bus, and bike, the impact of aviation on the transportation world gets lost in translation. This study seeks to bring airport planning back into the conversation by analyzing population projections, income, and industry and their affect on airport preparedness to meet increasing population demands. By using population projections through 2035 for the State of Texas, gross population and population growth rates were used to select counties within Texas that may be most in need of airport planning considerations. Counties along the Texas-Mexico border were analyzed in further detail for planning considerations and preparedness based on their population growth rates. Hidalgo County’s McAllen-Miller International Airport (MFE) was found to be proactively seeking changes to their airfield that matched recommendations based on their population increase. However, the level of coordination with city or county level authorities is lacking. / text

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

Scientific knowledge on a population's religious composition is essential to understand the challenges faced by societies today. It arises in opposition to speculations about the actual size of religious groups that have been increasingly present in the public discourse in Europe for many years. This is particularly the case in Austria where the flows of refugees and migrants coming from the Middle East and Afghanistan have intensified since 2011 and culminated in 2015. These sparked a debate on the actual size of the Muslim population in Austria. This study fills the gap by presenting estimates of the religious composition for 2016 and projections until 2046 based on several scenarios related to the three major forces affecting the religious composition: migration (including asylum seekers), differential fertility and secularisation. The projections demonstrate that religious diversity is bound to increase, mostly through immigration and fertility. We further focus on the role and implications of international migration on the age and sex composition within the six religious groups: Roman Catholics, Protestants, Orthodox, Muslims, other religions and unaffiliated. We find that the volume and composition of international migrants can maintain youthful age compositions in minority religions - Muslims and Orthodox. Sustained immigration leads to slower ageing but does not stop or reverse the process. The disparity between older majority and younger minority religious groups will further increase the cultural generation gap.

The quantitative assessment of the global effects of climate change requires the construction of income projections spanning large time horizons. Exploiting the robust link between educational attainment, age structure dynamics and economic growth, we use population projections by age, sex and educational attainment to obtain income per capita paths to the year 2100 for 144 countries. Such a framework offers a powerful, consistent methodology which can be used to study the future environmental challenges and to address potential policy reactions.

vii, 99 p. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number. / We investigate Cesàro summability of the Fourier orthogonal expansion of functions on B d × I m , where B d is the closed unit ball in [Special characters omitted] and I m is the m -fold Cartesian product of the interval [-1, 1], in terms of orthogonal polynomials with respect to the weight functions (1 - z ) α (1 + z ) β (1 - |x| 2 ) λ-1/2 , with z ∈ I m and x ∈ B d . In addition, we study a discretized Fourier orthogonal expansion on the cylinder B 2 × [-1, 1], which uses a finite number of Radon projections. The Lebesgue constant of this operator is obtained, and the proof utilizes generating functions for associated orthogonal series. / Committee in charge: Yuan Xu, Chairperson, Mathematics; Huaxin Lin, Member, Mathematics Jonathan Brundan, Member, Mathematics; Marcin Bownik, Member, Mathematics; Jun Li, Outside Member, Computer & Information Science

Background: People who are religiously unaffiliated (including self-identifying atheists and agnostics, as well as those who say their religion is "nothing in particular") made up 16.4% of the world's population in 2010. Unaffiliated populations have been growing in North America and Europe, leading some to expect that this group will grow as a share of the world's population. However, such forecasts overlook the impact of demographic factors, such as fertility and the large, aging unaffiliated population in Asia. Objective: We project the future size of religiously affiliated and unaffiliated populations around the world. Methods: We use multistate cohort-component methods to project the size of religiously affiliated and unaffiliated populations. Projection inputs such as religious composition, differential fertility, and age structure data, as well as religious switching patterns, are based on the best available census and survey data for each country. This research is based on an analysis of more than 2,500 data sources. Results: Taking demographic factors into account, we project that the unaffiliated will make up 13.2% of the world's population in 2050. The median age of religiously affiliated women is six years younger than unaffiliated women. The 2010-15 Total Fertility Rate for those with a religious affiliation is 2.59 children per woman, nearly a full child higher than the rate for the unaffiliated (1.65 children per woman). Conclusions: The religiously unaffiliated are projected to decline as a share of the world's population in the decades ahead because their net growth through religious switching will be more than offset by higher childbearing among the younger affiliated population.

A área de visualização volumétrica engloba um conjunto de técnicas utilizadas na representação, manipulação e exibição de dados associados à região de um volume, possibilitando, assim, a exploração e melhor compreensão do interior de objetos de natureza tridimensional. Contudo, algumas limitações ainda são encontradas nessa área, como, por exemplo, a exploração de mais de um valor simultaneamente em conjuntos de dados volumétricos multivariados. Além desse desafio, outro objeto de grande interesse da comunidade científica é a exploração de volumes variantes no tempo. A complexidade nesse caso está em tratar ou processar uma quantidade muito grande de dados buscando descobrir propriedades, estruturas ou características que variam com o tempo. O presente trabalho propõe técnicas e abordagens, baseadas no conceito de projeções multidimensionais, visando dar apoio à análise de conjuntos volumétricos multivariados que variam no tempo. A primeira técnica proposta, denominada Fastmap*, possibilitou a projeção de espaços de alta dimensionalidade em fluxo contínuo. A segunda técnica apresentada, denominada RLNP, permitiu a projeção de dados por vizinhança mantendo a coerência temporal nos dados projetados, além de possuir a capacidade de projetar espaços de alta dimensão com um nível de stressbaixo. Também, propomos uma abordagem para a análise baseada em atributos, denominada Scatter Projection, que facilita a exploração focada em um atributo específico junto com a similaridade dos dados entre eles. Finalmente, propõe-se uma abordagem baseada na reprojeção de agrupamentos usando técnicas de seleção de atributos para tentar identificar melhor as estruturas internas do volume. Assim, o presente trabalho contribui no sentido de levantar e discutir limitações das técnicas disponíveis, e em seguida, buscar possibilidades de solução para tais questões, propondo técnicas e abordagens que possibilitam a exploração de grandes conjuntos de dados volumétricos multivariados, mantendo a coerência temporal / The area of volume visualization encompasses a set of techniques used for representation, manipulation and display of data associated with a region of a volume, thus enabling the exploration and understanding of the interior of three-dimensional objects. However, some limitations are still encountered in this area. For example, the simultaneous exploration of more than one value in multivariate volumetric datasets. Beyond this challenge, another issue of great interest to the scientific community is the exploration of time-varying volumes. The complexity of this case lies in treatment or processing of a very large amount of data, seeking to discover properties, structures, or characteristics that may vary in time. This work proposes techniques and approaches, based on the concept of multidimensional projections, in order to support multivariate volumetric analysis of time varying data sets. The first technique proposed, called Fastmap*, enables the projection of high dimensional streaming data. The second technique presented, called Recursive Laplacian-based Neiboorhood Projection, allows the projection of data sets based on neighborhoods, maintaining the temporal coherence in the projected data, besides having the ability to project highdimensional spaces with a low level of stress. Also, we propose an approach for the analysis of specific attributes, referred to as Scatter Projection, which facilitates the exploration focused on a specific attribute and on the similarity between them. Finally, we propose an approach based on reprojection of groups using feature selection techniques for better identification of internal structures of the volume. Thus, this study contributes towards surveying and discussing limitations of the area, and then seeks ways of solving these issues, proposing techniques and approaches that enable the exploration of multidimensional volumetric time varying data sets, maintaining the temporal coherence

Sea-level fingerprints, the spatial patterns of sea level change resulting from rapid melting of glaciers and ice sheets, play an important role in understanding past and projecting future changes in relative sea level (RSL). Over century timescales, the viscous flow of Earth’s interior is a small component of the total deformation due to ice loading in most regions, so fingerprints computed using elastic Earth models are accurate. However, in regions where the viscosity is orders of magnitude lower than the global average, the viscous component of deformation can be significant, in which case it is important to consider models of viscoelastic deformation. There is evidence that the glaciated regions of Alaska, Western Canada and USA, and the Southern Andes are situated on top of mantle regions in which the local viscosity is several orders of magnitude lower than typical global mean values. The goal of this work is to determine the importance of viscous flow in computing RSL fingerprints associated with future ice mass loss from these regions. Version 5.0 of the Randolph Glacier Inventory is used to estimate the ice load distribution required for calculating sea-level fingerprints. For the glaciated regions that have lower than average viscosity, fingerprints were calculated using an elastic Earth model and a 3D viscoelastic model to quantify the influence of viscous flow on the predicted sea level changes. Using glacier mass loss values for the intermediate future climate scenario Representative Concentration Pathway (RCP) 4.5, the global sea level response was computed at 2100 CE relative to 2010 CE due to melting from all glacier regions. On comparing the results of the two models it was found that ice-load-induced viscous flow contributes significantly (more than a few cm) to the RSL fingerprints only in near-field regions. However, in these regions, the non-elastic contribution can be 10s of cm. For example, at Juneau, USA the elastic calculation gave relative sea level changes of ∼ −45 cm, compared to ∼ −120 cm based on the viscoelastic calculation.

The South Nation watershed is located in Eastern Ontario, Canada and managed under the authority of the South Nation Conservation (SNC). The watershed covers an area of 400,000 hectares with four dominant categories of land-use classes (60% agriculture, 34% forest, 5% mixed urban, and 1% other). Water quality is a great concern for the SNC as many anthropogenic activities generate harmful pollutants (such as heavy metals, nitrogen, phosphorus, and pesticides) that are discharged to the river through surface and groundwater flow. The discharge patterns of these pollutants are mainly driven by land-use distribution within the watershed which has been constantly evolving with urbanization and intensification of agriculture. Major changes in land-uses can potentially offset current SNC efforts to mitigate water pollution. The objective of the current study is to predict land-use series of maps for the South Nation watershed starting from 1991 to 2020. The prediction is carried out using the land-use allocation algorithm of the Dyna-CLUE (Dynamic Conversion of Land-Use and its Effects) model which is implemented for local regions. Dyna-CLUE is a spatially explicit hybrid land-use allocation model that combines estimation and simulation models, and its allocation procedures predict future trends of land-use surface (estimated from historical trends). The binary logistic regression is used to link preferences of land-use classes and potential demographic and geographic driving factors. Expert judgment was used to select a set of spatial driving factors believed to be responsible for changes in land-use distribution in the South Nation watershed. Three different scenarios for future development of the region were considered, with different initial conditions and conversion restrictions. The simulation results were evaluated using visual and statistical validation techniques to assess the performance of the model in generating maps similar to reality. The Dyna-CLUE model was successfully applied to the South Nation watershed. It was observed that the simulated maps generated from the model were in good agreement with the reality maps. This was confirmed through statistical validation via map pair analysis (error matrix) used to assess the overall accuracy of the model predictions. Results showed that the model was sensitive to land-use restrictions. Such type of modeling can be valuable for assessing the land-use changes at the local level, and setting up a decision support system for the South Nation Conservation towards sustainable land-use management in the watershed. Better results are expected to be achieved with more reliable datasets (i.e., accurate classification of land-use types in reality maps). Data availability and quality were the main obstacles that faced this research work. Our work has the merit to be the first application of CLUE model in Eastern Ontario.

In this study, large areas of goldfish telencephalon were ablated including rostral nucleus preopticus periventriculare (rNPP), and degenerating axons were traced by a modified Fink and Heimer procedure. The lesioning procedure ablated large regions of area dorsalis telencephali pars medialis, centralis, and dorsolateral complex; and completely removed area ventralis telencephali pars dorsalis, ventralis, and lateralis. In addition, the supracommissural nucleus and rNPP were lesioned specifically because both nuclei have been thought to be involved in courtship behavior and endocrine control of reproduction. This investigation demonstrated extensive fiber projections from telencephalic nuclei and/or rNPP to the hypothalamus. Lesioned telencephalon and/or rNPP projected bilaterally to nucleus preopticus and the suprachiasmatic nucleus and unilaterally to the following tuberal nuclei: nucleus anterior tuberis, and the lateral hypothalamic nucleus. A much larger fiber projection to the inferior lobe nuclei was also observed with a large contralateral as well as ipsilateral input.