As glaciações do Quaternário moldaram os padrões filogeográficos das espécies em geral. Em algumas regiões da América do Sul, (e.g. Cerrado e Caatinga) a mudança estrutural foi mais acentuada, havendo o predomino de savanas, ao passo que em outras regiões (e.g. Amazônica e Mata Atlântica) as mudanças foram menores, formando áreas de refúgios florestais. A Modelagem Preditiva de Distribuição de espécies usa associações entre variáveis ambientais e registros de ocorrência da espécie para estimar modelos que representam as condições ambientais favoráveis à espécie. Neste trabalho foram estudadas três espécies de figueiras Neotropicais com características ecológicas distintas, representando duas linhagens filogenéticas independentes, i.e., seções Americana (Ficus citrifolia) e Pharmacosycea (Ficus adhatodifolia e Ficus insipida). Foram gerados modelos para os cenários passados (Interglacial 140.000 e Glacial 21.000 anos atrás), presente e futuro (2050 e 2070, nos cenários otimistas e pessimistas) para as três espécies estudadas usando o programa Maxent 3.3.3k. Os resultados obtidos mostram que para F. adhatodifolia as variáveis mais importantes nos modelos foram temperatura mínima do mês mais frio e precipitação do mês mais seco. Para F. insipida as variáveis mais importantes nos modelos foram temperatura mínima do mês mais frio e precipitação anual. Para F. citrifolia as variáveis mais importantes nos modelos foram temperatura mínima do mês mais frio e precipitação do mês mais chuvoso. Os modelos projetados no cenário interglacial, para as três espécies estudadas, apresentaram áreas de adequabilidade ambiental próximas ao cenário atual. Durante o período glacial F. adhatodifolia mostrou uma mudança considerável em sua área de ocorrência, ocorrendo em regiões consideradas refúgios para algumas espécies. Ficus insipida apresentou uma retração na sua adequabilidade ambiental, porém mantendo-se na região amazônica, enquanto que F. citrifolia teve um aumento na sua área de adequabilidade. Nos cenários futuros (2050 e 2070) F.adhatodifolia apresentou uma diminuição em sua área de ocorrência em ambos os cenários otimista e pessimista, F. insipida apresentou um aumento em sua área de adequabilidade ambiental e F.citrifolia apresentou uma diminuição e fragmentação na região Amazônica nos cenários otimista e pessimista de 2050 e otimista de 2070. As exigências ambientais e os possíveis padrões filogeográficos das três espécies são discutidos no contexto dos modelos preditivos gerados. / The Quaternary glaciations shaped the phylogeographic patterns of species in general. In some regions of South America (e.g.Cerrado and Caatinga) structural change was more pronounced and savannas predominated, whereas in other regions (e.g. Amazon and Atlantic Forest) changes were minor, forming areas of forest refuges. Species distribution Predictive Modeling uses associations between environmental variables and species occurrence records to estimate models that represent the environmental conditions favorable to the species. In the present study we chose three species of Neotropical Ficus with different ecological characteristics, representing two independent phylogenetic lineages, i.e., sections Americana (Ficus citrifolia) and Pharmacosycea (F.adhatodifolia and F.insipida). We generated models for the past (interglacial 140,000 years ago and Glacial 21,000 years ago), present and future scenarios (2050 and 2070 in optimistic and pessimistic scenarios) for the three study species using Maxent 3.3.3k program. Our results showed thatfor F. adhatodifolia the most important variables in the models were minimum temperature in the coldest month and precipitation in the driest month. For F.insipida the most important variables in the models were minimum temperature in the coldest month and annual precipitation. For F. citrifolia the most important variables in the models were minimum temperature in the coldest month and precipitation in the wettest month. The models designed for the interglacial stage showed areas of environmental suitability similar to the current scenario of the three species. During the glacial period F. adhatodifolia showed a considerable change in its range, occurring in regions considered refuges for some species. Ficus insipida had its environmental suitability decreased, but remained in the Amazon region, while F. citrifolia increased its area of suitability. In the future models (2050 and 2070) F.adhatodifolia showed a decrease in its range on both optimistic and pessimistic scenarios, F.insipida showed an increase in its area of environmental suitability and F.citrifolia has been decreasing and fragmentation in the Amazon region in the optimistic and pessimistic scenarios 2050 and optimistic 2070. The environmental requirements and the potential phylogeographic patterns of the study species are discussed in the context of the generated predictive models.

<p>This study is focused on the prediction of residual stresses and microstructure development of steel and aluminum alloys during laser-based manufacturing processes by means of multi-physics numerical modeling.</p> <p>A finite element model is developed to predict solid-state phase transformation, material hardness, and residual stresses produced during laser-based manufacturing processes such as laser hardening and laser additive manufacturing processes based on the predicted temperature and geometry from a free-surface tracking laser deposition model. The solid-state phase transformational model considers heating, cooling, and multiple laser track heating and cooling as well as multiple layer tempering effects. The residual stress model is applied to the laser hardening of 4140 steel and to laser direct deposition of H13 tool steel and includes the effects of thermal strain and solid-state phase transformational strain based on the resultant phase distributions. Predicted results, including material hardness and residual stresses, are validated with measured values.</p> <p>Two dendrite growth predictive models are also developed to simulate microsegregation and dendrite growth during laser-based manufacturing processes that involve melting and solidification of multicomponent alloys such as laser welding and laser-based additive manufacturing processes. The first model uses the Phase Field method to predict dendrite growth and microsegregation in 2D and 3D. It is validated against simple 2D and 3D cases of single dendrite growth as well as 2D and 3D cases of multiple dendrite growth. It is then applied to laser welding of aluminum alloy Al 6061 and used to predict microstructure within a small domain. </p> The second model uses a novel technique by combining the Cellular Automata method and the Phase Field method to accurately predict solidification on a larger scale with the intent of modeling dendrite growth. The greater computational efficiency of the this model allows for the simulation of entire weld pools in 2D. The model is validated against an analytical model and results in the literature.

<p> Kudzu (Pueraria montana) is an invasive woody vine widespread throughout the  southeastern United States, with recent studies predicting that its habitat will expand northward.  New occurrences and recent studies using climatic parameters suggest that the Midwestern  region of the United States is at the greatest risk of kudzu invasion. As there have already been  25 reports of kudzu within the Great Lakes basin, and no previous landscape models exist for the  basin, I developed probability models from existing spatial data (land cover, hydrology, geology,  annual precipitation, elevation, aspect, and known kudzu locations) using generalized additive,  bioclimate envelope, and maximum entropy methods. I further expanded each model to include  the basin and a 2.25-degree buffer in order to include 193 reported kudzu sites. For each  predictive model, I determined the area under the curve (AUC) for a receiver operating  characteristic curve (ROC) comparing false positive and false negative rates. I performed field  surveys at eight known sites of kudzu presence in Michigan, Indiana, and Ohio. Each presence  site was paired with a control (known kudzu absence site). I collected environmental data  including canopy cover, volumetric soil moisture, soil pH, litter depth, midstory species diversity  and diameter at breast height (DBH), and overstory basal area. Each environmental measure was  compared between kudzu presence and control survey sites as well as between in-basin and out?of-basin survey sites using a two-way ANOVA. Maximum entropy models produced the highest  AUC in both the basin and buffer models during model development. These models showed that  urban and disturbed habitats resulted in the greatest probability of potential habitat for kudzu. I  found no statistically significant differences in environmental characteristics between kudzu  absent and presence sites or between in- and out-of-basin sites, suggesting kudzu might be  dispersal-limited rather than limited by environmental characteristics. Continuing existing  management and further monitoring of kudzu spread is likely necessary to limit further  introduction and to mitigate spread of kudzu within the Great Lakes region.  </p>

Denna studie undersöker relationen mellan landskap, miljö och placeringen av boplatser från neolitikum och bronsålder i Ystadområdet. Uppsatsen åstadkommer detta genom maximal entropi modellering av boplatsernas placering i relation till flera variabler i landskapet och miljön. Uppsatsens teoretiska ramverk utgår från en antagen koppling mellan variabler i miljön och placeringen av boplatser. Resultatet av modelleringen översätts till tabeller som visar vilka variabler i miljön och landskapet som är viktiga i relation till placeringen av boplatser under dessa perioder, och till kartor som visar vilka delar av Ystadområdet som har rätt kombination av dessa variabler. Dessa används sedan för att besvara frågeställningarna. Resultaten av studien visar en stark koppling mellan kvartärsjordarten kärrtorv och närvaron av boplatser. Variablerna som föredrogs vid placeringen av boplatser visar också en viss variation mellan tidsperioderna. Utöver detta bedömdes modellen av historisk miljö från Ystadprojektet vara användbar. / This study examines the relationship between landscape, environment, and the placement of settlements during the neolithic and bronze age periods in the Ystad area. The study accomplishes this through maximal entropy modeling of the placement of settlements in relation to several variables in the landscape and environment. The theoretic framework of this study centers around a presumed connection between variables in the environment and the location of settlements. The results are translated into tables that show which of these variables were important in relation to the placement of settlements during the above-mentioned periods. The results are also translated into maps that show which areas of Ystad have the right combination of variables that were determined to be important by the model. These tables and maps are then used to produce an answer to the main questions of this paper. The results of this study show a strong connection between the quaternary soil type bog peat, and the presence of settlements. The preferred conditions also show some variation between time periods. Furthermore, the model of historic environment from the Ystad project was deemed to be useful.

No description available.

No description available.

An intensive sampling of all ant species encountered on 6 Hawaiian Islands: Big Island, Maui, Oahu, Kauai, Molokai, and Lanai took place between 1988 and 1996. Species presence and absence was recorded at each site. Using remote sensing, variables were added insitu and used throughout my analysis. Species accumulation curves suggest that sampling was comprehensive. There is a significant trend between island area and species richness which validates the Theory of Island Biogeography for invasive species. Islands were found to be significantly nested by area, order, and tourism. Cluster analysis shows a link between elevation, land-use and island, and species presence. Predictive models can be built to predict spread of particular ant species as they continue toward equilibrium.

Participatory sensing frameworks use humans and their computing devices as a large mobile sensing network. Dramatic accessibility and affordability have turned mobile devices (smartphone and tablet computers) into the most popular computational machines in the world, exceeding laptops. By the end of 2013, more than 1.5 billion people on earth will have a smartphone. Increased coverage and higher speeds of cellular networks have given these devices the power to constantly stream large amounts of data. Most mobile devices are equipped with advanced sensors such as GPS, cameras, and microphones. This expansion of smartphone numbers and power has created a sensing system capable of achieving tasks practically impossible for conventional sensing platforms. One of the advantages of participatory sensing platforms is their mobility, since human users are often in motion. This dissertation presents a set of techniques for modeling and predicting user transportation patterns from cell-phone and social media check-ins. To study large-scale transportation patterns, I created a mobile phone app, Kpark, for estimating parking lot occupancy on the UCF campus. Kpark aggregates individual user reports on parking space availability to produce a global picture across all the campus lots using crowdsourcing. An issue with crowdsourcing is the possibility of receiving inaccurate information from users, either through error or malicious motivations. One method of combating this problem is to model the trustworthiness of individual participants to use that information to selectively include or discard data. This dissertation presents a comprehensive study of the performance of different worker quality and data fusion models with plausible simulated user populations, as well as an evaluation of their performance on the real data obtained from a full release of the Kpark app on the UCF Orlando campus. To evaluate individual trust prediction methods, an algorithm selection portfolio was introduced to take advantage of the strengths of each method and maximize the overall prediction performance. Like many other crowdsourced applications, user incentivization is an important aspect of creating a successful crowdsourcing workflow. For this project a form of non-monetized incentivization called gamification was used in order to create competition among users with the aim of increasing the quantity and quality of data submitted to the project. This dissertation reports on the performance of Kpark at predicting parking occupancy, increasing user app usage, and predicting worker quality.

This dissertation undertakes theoretical and computational research to characterize and understand in detail atomic configurations and electronic structural properties of surfaces and interfaces at the nano-scale, with particular emphasis on identifying the factors that control atomic-scale diffusion and transport properties. The overarching goal is to outline, with examples, a predictive modeling procedure of stable structures of novel materials that, on the one hand, facilitates a better understanding of experimental results, and on the other hand, provide guidelines for future experimental work. The results of this dissertation are useful in future miniaturization of electronic devices, predicting and engineering functional novel nanostructures. A variety of theoretical and computational tools with different degrees of accuracy is used to study problems in different time and length scales. Interactions between the atoms are derived using both ab-initio methods based on Density Functional Theory (DFT), as well as semiempirical approaches such as those embodied in the Embedded Atom Method (EAM), depending on the scale of the problem at hand. The energetics for a variety of surface phenomena (adsorption, desorption, diffusion, and reactions) are calculated using either DFT or EAM, as feasible. For simulating dynamic processes such as diffusion of adatoms on surfaces with dislocations the Molecular Dynamics (MD) method is applied. To calculate vibrational mode frequencies, the infinitesimal displacement method is employed. The combination of non-equilibrium Green’s function (NEGF) and DFT is used to calculate electronic transport properties of molecular devices as well as interfaces and junctions.

Institutions of higher education invest a significant amount of resources in recruiting, processing, and advising new students. When students leave the institution prior to graduation, the university loses considerable revenues. Therefore, it is important for colleges and universities to refine their student recruitment and retention strategies to avoid forgone revenues by predicting which students are likely to need particular types of support services (DeBerard et al, 2004). Current models of prediction utilize extensive surveys that are impractical to administer each term, and they do not adequately identify the broad range of student persistence categories needed in order to gain a greater understanding of persistence behavior (Davidson, 2005; Porter, 2000; Tinto, 1975). This study created a linear discriminant function to predict a broad range of persistence levels of first-time freshmen students at California State University, Bakersfield (CSUB), by identifying pre-enrollment and early enrollment student variables that existed within the database of the University. This information may be used to develop support service strategies to better assist incoming students predicted to have a greater probability of not persisting.