971 resultados para relative utility models


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1. The niche variation hypothesis predicts that among-individual variation in niche use will increase in the presence of intraspecific competition and decrease in the presence of interspecific competition. We sought to determine whether the local isotopic niche breadth of fish inhabiting a wetland was best explained by competition for resources and the niche variation hypothesis, by dispersal of individuals from locations with different prey resources or by a combination of the two. We analysed stable isotopes of carbon and nitrogen as indices of feeding niche and compared metrics of within-site spread to characterise site-level isotopic niche breadth. We then evaluated the explanatory power of competing models of the direct and indirect effects of several environmental variables spanning gradients of disturbance, competition strength and food availability on among-individual variation of the eastern mosquitofish (Gambusia holbrooki). 2. The Dispersal model posits that only the direct effect of disturbance (i.e. changes in water level known to induce fish movement) influences among-individual variation in isotopic niche. The Partitioning model allows for only direct effects of local food availability on among-individual variation. The Combined model allows for both hypotheses by including the direct effects of disturbance and food availability. 3. A linear regression of the Combined model described more variance than models limited to the variables of either the Dispersal or Partitioning models. Of the independent variables considered, the food availability variable (per cent edible periphyton) explained the most variation in isotopic niche breadth, followed closely by the disturbance variable (days since last drying event). 4. Structural equation modelling provided further evidence that the Combined model was best supported by the data, with the Partitioning and the Dispersal models only modestly less informative. Again, the per cent edible periphyton was the variable with the largest direct effect on niche variability, with other food availability variables and the disturbance variable only slightly less important. Indirect effects of heterospecific and conspecific competitor densities were also important, through their effects on prey density. 5. Our results support the Combined hypotheses, although partitioning mechanisms appear to explain the most diet variation among individuals in the eastern mosquitofish. The results also support some predictions of the niche variation hypothesis, although both conspecific and interspecific competition appeared to increase isotopic niche breadth in contrast to predictions that interspecific competition would decrease it. We think this resulted from high diet overlap of co-occurring species, most of which consume similar macroinvertebrates.

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The relative abundance of diatom species in different habitats can be used as a tool to infer prior environmental conditions and evaluate management decisions that influence habitat quality. Diatom distribution patterns were examined to characterize relationships between assemblage composition and environmental gradients in a subtropical estuarine watershed. We identified environmental correlates of diatom distribution patterns across the Charlotte Harbor, Florida, watershed; evaluated differences among three major river drainages; and determined how accurately local environmental conditions can be predicted using inference models based on diatom assemblages. Sampling locations ranged from freshwater to marine (0.1–37.2 ppt salinity) and spanned broad nutrient concentration gradients. Salinity was the predominant driver of difference among diatom assemblages across the watershed, but other environmental variables had stronger correlations with assemblages within the subregions of the three rivers and harbor. Eighteen indicator taxa were significantly affiliated with subregions. Relationships between diatom taxon distributions and salinity, distance from the harbor, total phosphorus (TP), and total nitrogen (TN) were evaluated to determine the utility of diatom assemblages to predict environmental values using a weighted averaging-regression approach. Diatom-based inferences of these variables were strong (salinity R 2 = 0.96; distance R 2 = 0.93; TN R 2 = 0.83; TP R 2 = 0.83). Diatom assemblages provide reliable estimates of environmental parameters on different spatial scales across the watershed. Because many coastal diatom taxa are ubiquitous, the diatom training sets provided here should enable diatom-based environmental reconstructions in subtropical estuaries that are being rapidly altered by land and water use changes and sea level rise.

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Software engineering researchers are challenged to provide increasingly more powerful levels of abstractions to address the rising complexity inherent in software solutions. One new development paradigm that places models as abstraction at the forefront of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code.^ Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process.^ The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources.^ At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM's synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise.^ This dissertation investigates how to decouple the DSK from the MoE and subsequently producing a generic model of execution (GMoE) from the remaining application logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis component of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions.^ This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.^

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Porphyrins have been the center of numerous investigations in different areas of chemistry, geochemistry, and the life sciences. In nature the conformation of the porphyrin macrocycle varies, depending on the function of its apoenzyme. It is believed that the conformation of the porphyrin ring is necessary for the enzyme to achieve its function and modify its reactivity. It is important to understand how the conformation of the porphyrin ring will influence its properties. In synthetic porphyrins particular conformations and ring deformations can be achieved by peripheral substitution, metallation, core substitution, and core protonation among other alterations of the macrocycle. The macrocyclic distortions will affect the ring current, the ability of pyrroles to intramolecularly hydrogen bond and the relative basicity of each of the porphyrins. To understand these effects different theoretical models are used. The ground state structure of each of 19 free base porphyrins is determined using molecular mechanics (MM+) and semiempirical methods (PM3). The energetics of deformation of the macrocyclic core is calculated by carrying out single point energy calculations for the conformation achieved by each synthetic compound. Enthalpies of solution and enthalpies of protonation of 10 porphyrins with varying degrees of macrocyclic deformation and varying electron withdrawing groups in the periphery are determined using solution calorimetry. Using Hess's Law, the relative basicity of each of the different free base porphyrins is calculated. NMR results are described, including the determination of free energies of activation of ring tautomerization and hydrogen bonding for several compounds. It was found that in the absence of electronic effects, the greater macrocyclic deformation, the greater the basicity of the porphyrins. This basicity is attenuated by the presence of electron withdrawing groups and ability to of the macrocycle to intramolecularly hydrogen bond.

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This study reports one of the first controlled studies to examine the impact of a school based positive youth development program (Lerner, Fisher, & Weinberg, 2000) on promoting qualitative change in life course experiences as a positive intervention outcome. The study built on a recently proposed relational developmental methodological metanarrative (Overton, 1998) and advances in use of qualitative research methods (Denzin & Lincoln, 2000). The study investigated the use the Life Course Interview (Clausen, 1998) and an integrated qualitative and quantitative data analytic strategy (IQDAS) to provide empirical documentation of the impact the Changing Lives Program on qualitative change in positive identity in a multicultural population of troubled youth in an alternative public high school. The psychosocial life course intervention approach used in this study draws its developmental framework from both psychosocial developmental theory (Erikson, 1968) and life course theory (Elder, 1998) and its intervention strategies from the transformative pedagogy of Freire's (1983/1970). Using the 22 participants in the Intervention Condition and the 10 participants in the Control Condition, RMANOVAs found significantly more positive qualitative change in personal identity for program participants relative to the non-intervention control condition. In addition, the 2X2X2X3 mixed design RMANOVA in which Time (pre, post) was the repeated factor and Condition (Intervention versus Control), Gender, and Ethnicity the between group factors, also found significant interactions for the Time by Gender and Time by Ethnicity. Moreover, the directionality of the basic pattern of change was positive for participants of both genders and all three ethnic groups. The pattern of the moderation effects also indicated a marked tendency for participants in the intervention group to characterize their sense of self as more secure and less negative at the end of the their first semester in the intervention, that was stable across both genders and all three ethnicities. The basic differential pattern of an increase in the intervention condition of a positive characterization of sense of self relative to both pre test and relative to the directionality of the movement of the non-intervention controls, was stable across both genders and all three ethnic groups.

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The terrigenous sediment proportion of the deep sea sediments from off Northwest Africa has been studied in order to distinguish between the aeolian and the fluvial sediment supply. The present and fossil Saharan dust trajectories were recognized from the distribution patterns of the aeolian sediment. The following timeslices have been investigated: Present, 6,000, 12,000 and 18,000 y. B. P. Furthermore, the quantity of dust deposited off the Saharan coast has been estimated. For this purpose, 80 surface sediment samples and 34 sediment cores have been analysed. The stratigraphy of the cores has been achieved from oxygen isotopic curves, 14C-dating, foraminiferal transfer temperatures, and carbonate contents. Silt sized biogenic opal generally accounts for less than 2 % of the total insoluble sediment proportion. Only under productive upwelling waters and off river mouths, the opal proportion exceeds 2 % significantly. The modern terrigenous sediment from off the Saharan coast is generally characterized by intensely stained quartz grains. They indicate an origin from southern Saharan and Sahelian laterites, and a zonal aeolian transport in midtropospheric levels, between 1.5 an 5.5 km, by 'Harmattan' Winds. The dust particles follow large outbreaks of Saharan air across the African coast between 15° and 21° N. Their trajectories are centered at about 18° N and continue further into a clockwise gyre situated south of the Canary Islands. This course is indicated by a sickle-shaped tongue of coarser grain sizes in the deep-sea sediment. Such loess-sized terrigenous particles only settle within a zone extending to 700 km offshore. Fine silt and clay sized particles, with grain sizes smaller than 10- 15 µm, drift still further west and can be traced up to more than 4,000 km distance from their source areas. Additional terrigenous silt which is poor in stained quartz occurs within a narrow zone off the western Sahara between 20° and 27° N only. It depicts the present dust supply by the trade winds close to the surface. The dust load originates from the northwestern Sahara, the Atlas Mountains and coastal areas, which contain a particularly low amount of stained quartz. The distribution pattern of these pale quartz sediments reveals a SSW-dispersal of dust being consistent with the present trade wind direction from the NNE. In comparison to the sediments from off the Sahara and the deeper subtropical Atlantic, the sediments off river mouths, in particular off the Senegal river, are characterized by an additional input of fine grained terrigenous particles (< 6 µm). This is due to fluvial suspension load. The fluvial discharge leads to a relative excess of fine grained particles and is observed in a correlation diagram of the modal grain sizes of terrigenous silt with the proportion of fine fraction (< 6 µm). The aeolian sediment contribution by the Harmattan Winds strongly decreased during the Climatic Optimum at 6,000 y. B. P. The dust discharge of the trade winds is hardly detectable in the deep-sea sediments. This probably indicates a weakened atmospheric circulation. In contrast, the fluvial sediment supply reached a maximum, and can be traced to beyond Cape Blanc. Thus, the Saharan climate was more humid at 6,000 y B. P. A latitudinal shift of the Harmattan driven dust outbreaks cannot be observed. Also during the Glacial, 18,000 y. B. P., Harmattan dust transport crossed the African coast at latitudes of 15°-20° N. Its sediment load increased intensively, and markedly coarser grains spread further into the Atlantic Ocean. An expanded zone of pale-quart sediments indicates an enhanced dust supply by the trade winds blowing from the NE. No synglacial fluvial sediment contribution can be recognized between 12° and 30° N. This indicates a dry glacial climate and a strengthened stmospheric circulation over the Sahelian and Saharan region. The climatic transition pahes, at 12, 000 y. B. P., between the last Glacial and the Intergalcial, which is compareable to the Alerod in Europe, is characterized by an intermediate supply of terrigenous particles. The Harmattan dust transport wa weaker than during the Glacial. The northeasterly trade winds were still intensive. River supply reached a first postglacial maximum seaward of the Senegal river mouth. This indicates increasing humidity over the southern Sahara and a weaker atmospheric circulation as compared to the glacial. The accumulation rates of the terrigenous silt proportion (> 6 µm) decrcase exponentially with increasing distance from the Saharan coast. Those of the terrigenous fine fraction (< 6 µm) follow the same trend and show almost similar gradients. Accordingly, also the terrigenous fine fraction is believed to result predominantly from aeolian transport. In the Atlantic deep-sea sediments, the annual terrigenous sediment accumulation has fluctuated, from about 60 million tons p. a. during the Late Glacial (13,500-18,000 y. B. P, aeolian supply only) to about 33 million tons p. a. during the Holocene Climatic Optimum (6,000-9,000 y. B. P, mainly fluvial supply), when the river supply has reached a maximum, and to about 45 million tons p. a. during the last 4,000 years B. P. (fluvial supply only south of 18° N).

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My thesis examines fine-scale habitat use and movement patterns of age 1 Greenland cod (Gadus macrocephalus ogac) tracked using acoustic telemetry. Recent advances in tracking technologies such as GPS and acoustic telemetry have led to increasingly large and detailed datasets that present new opportunities for researchers to address fine-scale ecological questions regarding animal movement and spatial distribution. There is a growing demand for home range models that will not only work with massive quantities of autocorrelated data, but that can also exploit the added detail inherent in these high-resolution datasets. Most published home range studies use radio-telemetry or satellite data from terrestrial mammals or avian species, and most studies that evaluate the relative performance of home range models use simulated data. In Chapter 2, I used actual field-collected data from age-1 Greenland cod tracked with acoustic telemetry to evaluate the accuracy and precision of six home range models: minimum convex polygons, kernel densities with plug-in bandwidth selection and the reference bandwidth, adaptive local convex hulls, Brownian bridges, and dynamic Brownian bridges. I then applied the most appropriate model to two years (2010-2012) of tracking data collected from 82 tagged Greenland cod tracked in Newman Sound, Newfoundland, Canada, to determine diel and seasonal differences in habitat use and movement patterns (Chapter 3). Little is known of juvenile cod ecology, so resolving these relationships will provide valuable insight into activity patterns, habitat use, and predator-prey dynamics, while filling a knowledge gap regarding the use of space by age 1 Greenland cod in a coastal nursery habitat. By doing so, my thesis demonstrates an appropriate technique for modelling the spatial use of fish from acoustic telemetry data that can be applied to high-resolution, high-frequency tracking datasets collected from mobile organisms in any environment.

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Calmette Bay within Marguerite Bay along the western side of the Antarctic Peninsula contains one of the most continuous flights of raised beaches described to date in Antarctica. Raised beaches extend to 40.8 m above sea level (masl) and are thought to reflect glacial isostatic adjustment due to the retreat of the Antarctic Peninsula Ice Sheet. Using optically stimulated luminescence (OSL), we dated quartz extracts from cobble surfaces buried in raised beaches at Calmette Bay. The beaches are separated into upper and lower beaches based on OSL ages, geomorphology, and sedimentary fabric. The two sets of beaches are separated by a prominent scarp. One of our OSL ages from the upper beaches dates to 9.3 thousand years ago (ka; as of 1950) consistent with previous extrapolation of sea-level data and the time of ice retreat from inner Marguerite Bay. However, four of the seven ages from the upper beaches date to the timing of glaciation. We interpret these ages to represent reworking of beaches deposited prior to the Last Glacial Maximum (LGM) by advancing and retreating LGM ice. Ages from the lower beaches record relative sea-level fall due to Holocene glacial-isostatic adjustment. We suggest a Holocene marine limit of 21.7 masl with an age of 5.5-7.3 ka based on OSL ages from Calmette Bay and other sea-level constraints in the area. A marine limit at 21.7 masl implies half as much relative sea-level change in Marguerite Bay during the Holocene as suggested by previous sea-level reconstructions. No evidence for a relative sea-level signature of neoglacial events, such as a decrease followed by an increase in RSL fall due to ice advance and retreat associated with the Little Ice Age, is found within Marguerite Bay indicating either: (1) no significant neoglacial advances occurred within Marguerite Bay; (2) rheological heterogeneity allows part of the Antarctic Peninsula (i.e. the South Shetland Islands) to respond to rapid ice mass changes while other regions are incapable of responding to short-lived ice advances; or (3) the magnitude of neoglacial events within Marguerite Bay is too small to resolve through relative sea-level reconstructions. Although the application of reconstructing sea-level histories using OSL-dated raised beach deposits provides a better understanding of the timing and nature of relative sea-level change in Marguerite Bay, we highlight possible problems associated with using raised beaches as sea-level indices due to post-depositional reworking by storm waves.

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Acknowledgements This study was part of the Tursiops Project of the Dolphin Research Centre of Caprera, La Maddalena. Financial and logistical support was provided by the Centro Turistico Studentesco (CTS) and by the National Park of the Archipelago de La Maddalena. We thank the Natural Reserve of Bocche di Bonifacio for the support provided during data collection. The authors thank the numerous volunteers of the Caprera Dolphin Research Centre and especially Marco Ferraro, Mirko Ugo, Angela Pira and Maurizio Piras whose assistance during field observation and skills as a boat driver were invaluable.

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Grassland birds are highly imperiled because of historical habitat loss and ongoing conversion of grasslands to agricultural and urban land uses. Therefore, prioritizing and further justifying conservation action in remaining grasslands is critical to protecting what remains. Grassland bird conservation has focused on identifying and protecting large grassland complexes referred to as Grassland Bird Conservation Areas (GBCAs). We identified and classified GBCAs in a region highly impacted by both agricultural and urban land conversion using previously developed methods. Then, we extended the analysis to include estimated relative abundance of five grassland focal species in each GBCA. Models of relative abundance were built using eight years of monitoring data collected by citizen scientists. Finally, we quantified the value of ecosystem services provided by each GBCA. There were nearly 55,000 ha of grassland habitats in the Chicago Metropolitan Region that met GBCA criteria, 33% (18,415 ha) of which were protected. Proportion of abundance in protected versus unprotected areas was similar for Bobolink (Dolichonyx oryzivorus; 46%), Grasshopper Sparrow (Ammodramus savannarum; 52%), and Sedge Wren (Cistothorus platensis; 48%), whereas, Henslow’s Sparrow (Ammodramus henslowii; 75%) had a higher proportion of relative abundance in protected GBCAs and Eastern Meadowlark (Sturnella magna) had lower proportions (37%). GBCAs provisioned just under $900 million annually in ecosystem services, 73% of which is because of flood control. Outputs of this comprehensive approach will inform grassland bird conservation by providing detailed information about the value for birds and people of grassland habitats.

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An abstract of a thesis devoted to using helix-coil models to study unfolded states.\\

Research on polypeptide unfolded states has received much more attention in the last decade or so than it has in the past. Unfolded states are thought to be implicated in various

misfolding diseases and likely play crucial roles in protein folding equilibria and folding rates. Structural characterization of unfolded states has proven to be

much more difficult than the now well established practice of determining the structures of folded proteins. This is largely because many core assumptions underlying

folded structure determination methods are invalid for unfolded states. This has led to a dearth of knowledge concerning the nature of unfolded state conformational

distributions. While many aspects of unfolded state structure are not well known, there does exist a significant body of work stretching back half a century that

has been focused on structural characterization of marginally stable polypeptide systems. This body of work represents an extensive collection of experimental

data and biophysical models associated with describing helix-coil equilibria in polypeptide systems. Much of the work on unfolded states in the last decade has not been devoted

specifically to the improvement of our understanding of helix-coil equilibria, which arguably is the most well characterized of the various conformational equilibria

that likely contribute to unfolded state conformational distributions. This thesis seeks to provide a deeper investigation of helix-coil equilibria using modern

statistical data analysis and biophysical modeling techniques. The studies contained within seek to provide deeper insights and new perspectives on what we presumably

know very well about protein unfolded states. \\

Chapter 1 gives an overview of recent and historical work on studying protein unfolded states. The study of helix-coil equilibria is placed in the context

of the general field of unfolded state research and the basics of helix-coil models are introduced.\\

Chapter 2 introduces the newest incarnation of a sophisticated helix-coil model. State of the art modern statistical techniques are employed to estimate the energies

of various physical interactions that serve to influence helix-coil equilibria. A new Bayesian model selection approach is utilized to test many long-standing

hypotheses concerning the physical nature of the helix-coil transition. Some assumptions made in previous models are shown to be invalid and the new model

exhibits greatly improved predictive performance relative to its predecessor. \\

Chapter 3 introduces a new statistical model that can be used to interpret amide exchange measurements. As amide exchange can serve as a probe for residue-specific

properties of helix-coil ensembles, the new model provides a novel and robust method to use these types of measurements to characterize helix-coil ensembles experimentally

and test the position-specific predictions of helix-coil models. The statistical model is shown to perform exceedingly better than the most commonly used

method for interpreting amide exchange data. The estimates of the model obtained from amide exchange measurements on an example helical peptide

also show a remarkable consistency with the predictions of the helix-coil model. \\

Chapter 4 involves a study of helix-coil ensembles through the enumeration of helix-coil configurations. Aside from providing new insights into helix-coil ensembles,

this chapter also introduces a new method by which helix-coil models can be extended to calculate new types of observables. Future work on this approach could potentially

allow helix-coil models to move into use domains that were previously inaccessible and reserved for other types of unfolded state models that were introduced in chapter 1.

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Prenyltransferase enzymes promote the membrane localization of their target proteins by directing the attachment of a hydrophobic lipid group at a conserved C-terminal CAAX motif. Subsequently, the prenylated protein is further modified by postprenylation processing enzymes that cleave the terminal 3 amino acids and carboxymethylate the prenylated cysteine residue. Many prenylated proteins, including Ras1 and Ras-like proteins, require this multistep membrane localization process in order to function properly. In the human fungal pathogen Cryptococcus neoformans, previous studies have demonstrated that two distinct forms of protein prenylation, farnesylation and geranylgeranylation, are both required for cellular adaptation to stress, as well as full virulence in animal infection models. Here, we establish that the C. neoformans RAM1 gene encoding the farnesyltransferase β-subunit, though not strictly essential for growth under permissive in vitro conditions, is absolutely required for cryptococcal pathogenesis. We also identify and characterize postprenylation protease and carboxyl methyltransferase enzymes in C. neoformans. In contrast to the prenyltransferases, deletion of the genes encoding the Rce1 protease and Ste14 carboxyl methyltransferase results in subtle defects in stress response and only partial reductions in virulence. These postprenylation modifications, as well as the prenylation events themselves, do play important roles in mating and hyphal transitions, likely due to their regulation of peptide pheromones and other proteins involved in development. IMPORTANCE Cryptococcus neoformans is an important human fungal pathogen that causes disease and death in immunocompromised individuals. The growth and morphogenesis of this fungus are controlled by conserved Ras-like GTPases, which are also important for its pathogenicity. Many of these proteins require proper subcellular localization for full function, and they are directed to cellular membranes through a posttranslational modification process known as prenylation. These studies investigate the roles of one of the prenylation enzymes, farnesyltransferase, as well as the postprenylation processing enzymes in C. neoformans. We demonstrate that the postprenylation processing steps are dispensable for the localization of certain substrate proteins. However, both protein farnesylation and the subsequent postprenylation processing steps are required for full pathogenesis of this fungus.

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Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future.

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People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

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Software engineering researchers are challenged to provide increasingly more pow- erful levels of abstractions to address the rising complexity inherent in software solu- tions. One new development paradigm that places models as abstraction at the fore- front of the development process is Model-Driven Software Development (MDSD). MDSD considers models as first class artifacts, extending the capability for engineers to use concepts from the problem domain of discourse to specify apropos solutions. A key component in MDSD is domain-specific modeling languages (DSMLs) which are languages with focused expressiveness, targeting a specific taxonomy of problems. The de facto approach used is to first transform DSML models to an intermediate artifact in a HLL e.g., Java or C++, then execute that resulting code. Our research group has developed a class of DSMLs, referred to as interpreted DSMLs (i-DSMLs), where models are directly interpreted by a specialized execution engine with semantics based on model changes at runtime. This execution engine uses a layered architecture and is referred to as a domain-specific virtual machine (DSVM). As the domain-specific model being executed descends the layers of the DSVM the semantic gap between the user-defined model and the services being provided by the underlying infrastructure is closed. The focus of this research is the synthesis engine, the layer in the DSVM which transforms i-DSML models into executable scripts for the next lower layer to process. The appeal of an i-DSML is constrained as it possesses unique semantics contained within the DSVM. Existing DSVMs for i-DSMLs exhibit tight coupling between the implicit model of execution and the semantics of the domain, making it difficult to develop DSVMs for new i-DSMLs without a significant investment in resources. At the onset of this research only one i-DSML had been created for the user- centric communication domain using the aforementioned approach. This i-DSML is the Communication Modeling Language (CML) and its DSVM is the Communication Virtual machine (CVM). A major problem with the CVM’s synthesis engine is that the domain-specific knowledge (DSK) and the model of execution (MoE) are tightly interwoven consequently subsequent DSVMs would need to be developed from inception with no reuse of expertise. This dissertation investigates how to decouple the DSK from the MoE and sub- sequently producing a generic model of execution (GMoE) from the remaining appli- cation logic. This GMoE can be reused to instantiate synthesis engines for DSVMs in other domains. The generalized approach to developing the model synthesis com- ponent of i-DSML interpreters utilizes a reusable framework loosely coupled to DSK as swappable framework extensions. This approach involves first creating an i-DSML and its DSVM for a second do- main, demand-side smartgrid, or microgrid energy management, and designing the synthesis engine so that the DSK and MoE are easily decoupled. To validate the utility of the approach, the SEs are instantiated using the GMoE and DSKs of the two aforementioned domains and an empirical study to support our claim of reduced developmental effort is performed.