Species Richness-Environment Relationships of European Arthropods at Two Spatial Grains: Habitats and Countries

We study how species richness of arthropods relates to theories concerning net primary productivity, ambient energy, water-energy dynamics and spatial environmental heterogeneity. We use two datasets of arthropod richness with similar spatial extents (Scandinavia to Mediterranean), but contrasting spatial grain (local habitat and country). Samples of ground-dwelling spiders, beetles, bugs and ants were collected from 32 paired habitats at 16 locations across Europe. Species richness of these taxonomic groups was also determined for 25 European countries based on the Fauna Europaea database. We tested effects of net primary productivity (NPP), annual mean temperature (T), annual rainfall (R) and potential evapotranspiration of the coldest month (PETmin) on species richness and turnover. Spatial environmental heterogeneity within countries was considered by including the ranges of NPP, T, R and PETmin. At the local habitat grain, relationships between species richness and environmental variables differed strongly between taxa and trophic groups. However, species turnover across locations was strongly correlated with differences in T. At the country grain, species richness was significantly correlated with environmental variables from all four theories. In particular, species richness within countries increased strongly with spatial heterogeneity in T. The importance of spatial heterogeneity in T for both species turnover across locations and for species richness within countries suggests that the temperature niche is an important determinant of arthropod diversity. We suggest that, unless climatic heterogeneity is constant across sampling units, coarse-grained studies should always account for environmental heterogeneity as a predictor of arthropod species richness, just as studies with variable area of sampling units routinely consider area.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Processing and mechanical properties of cast aluminum containing scandium, zirconium, and ytterbium

A series of aluminum alloys containing additions of scandium, zirconium, and ytterbium were cast to evaluate the effect of partial ytterbium substitution for scandium on tensile behavior. Due to the high price of scandium, a crucible-melt interaction study was performed to ensure no scandium was lost in graphite, alumina, magnesia, or zirconia crucibles after holding a liquid Al-Sc master alloy for 8 hours at 900 °C in an argon atmosphere. The alloys were subjected to an isochronal aging treatment and tested for conductivity and Vickers microhardness after each increment. For scandium-containing alloys, peak hardnesses of 520-790 MPa, and peak tensile stresses of 138-234 MPa were observed after aging from 150-350 °C for 3 hours in increments of 50 °C, and for alloys without scandium, peak hardnesses of 217-335 MPa and peak tensile stresses of 45-63 MPa were observed after a 3 hour, 150 °C aging treatment. The hardness and tensile strength of the ytterbium containing alloy was found to be lower than in the alloy with no ytterbium substitution.

Digital processing and data compilation approach for using remotely sensed imagery to identify geological lineaments in hard-rock terrains : an application for groundwater explorations in Nicaragua

Sustainable yields from water wells in hard-rock aquifers are achieved when the well bore intersects fracture networks. Fracture networks are often not readily discernable at the surface. Lineament analysis using remotely sensed satellite imagery has been employed to identify surface expressions of fracturing, and a variety of image-analysis techniques have been successfully applied in “ideal” settings. An ideal setting for lineament detection is where the influences of human development, vegetation, and climatic situations are minimal and hydrogeological conditions and geologic structure are known. There is not yet a well-accepted protocol for mapping lineaments nor have different approaches been compared in non-ideal settings. A new approach for image-processing/synthesis was developed to identify successful satellite imagery types for lineament analysis in non-ideal terrain. Four satellite sensors (ASTER, Landsat7 ETM+, QuickBird, RADARSAT-1) and a digital elevation model were evaluated for lineament analysis in Boaco, Nicaragua, where the landscape is subject to varied vegetative cover, a plethora of anthropogenic features, and frequent cloud cover that limit the availability of optical satellite data. A variety of digital image processing techniques were employed and lineament interpretations were performed to obtain 12 complementary image products that were evaluated subjectively to identify lineaments. The 12 lineament interpretations were synthesized to create a raster image of lineament zone coincidence that shows the level of agreement among the 12 interpretations. A composite lineament interpretation was made using the coincidence raster to restrict lineament observations to areas where multiple interpretations (at least 4) agree. Nine of the 11 previously mapped faults were identified from the coincidence raster. An additional 26 lineaments were identified from the coincidence raster, and the locations of 10 were confirmed by field observation. Four manual pumping tests suggest that well productivity is higher for wells proximal to lineament features. Interpretations from RADARSAT-1 products were superior to interpretations from other sensor products, suggesting that quality lineament interpretation in this region requires anthropogenic features to be minimized and topographic expressions to be maximized. The approach developed in this study has the potential to improve siting wells in non-ideal regions.

Processing and characterization of PbSnTe-based thermoelectric materials made by mechanical alloying

The research reported in this dissertation investigates the processes required to mechanically alloy Pb1-xSnxTe and AgSbTe2 and a method of combining these two end compounds to result in (y)(AgSbTe2)–(1 - y)(Pb1-xSnxTe) thermoelectric materials for power generation applications. In general, traditional melt processing of these alloys has employed high purity materials that are subjected to time and energy intensive processes that result in highly functional material that is not easily reproducible. This research reports the development of mechanical alloying processes using commercially available 99.9% pure elemental powders in order to provide a basis for the economical production of highly functional thermoelectric materials. Though there have been reports of high and low ZT materials fabricated by both melt alloying and mechanical alloying, the processing-structure-properties-performance relationship connecting how the material is made to its resulting functionality is poorly understood. This is particularly true for mechanically alloyed material, motivating an effort to investigate bulk material within the (y)(AgSbTe2)–(1 - y)(Pb1-xSnx- Te) system using the mechanical alloying method. This research adds to the body of knowledge concerning the way in which mechanical alloying can be used to efficiently produce high ZT thermoelectric materials. The processes required to mechanically alloy elemental powders to form Pb1-xSnxTe and AgSbTe2 and to subsequently consolidate the alloyed powder is described. The composition, phases present in the alloy, volume percent, size and spacing of the phases are reported. The room temperature electronic transport properties of electrical conductivity, carrier concentration and carrier mobility are reported for each alloy and the effect of the presence of any secondary phase on the electronic transport properties is described. An mechanical mixing approach for incorporating the end compounds to result in (y)(AgSbTe2)–(1-y)(Pb1-xSnxTe) is described and when 5 vol.% AgSbTe2 was incorporated was found to form a solid solution with the Pb1-xSnxTe phase. An initial attempt to change the carrier concentration of the Pb1-xSnxTe phase was made by adding excess Te and found that the carrier density of the alloys in this work are not sensitive to excess Te. It has been demonstrated using the processing techniques reported in this research that this material system, when appropriately doped, has the potential to perform as highly functional thermoelectric material.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

Antigen Processing and Presentation in Multiple Sclerosis

CD4(+) T cells play a central role in the pathogenesis of multiple sclerosis (MS). Generation, activation and effector function of these cells crucially depends on their interaction with MHC II-peptide complexes displayed by antigen presenting cells (APC). Processing and presentation of self antigens by different APC therefore influences the disease course at all stages. Selection by thymic APC leads to the generation of autoreactive T cells, which can be activated by peripheral APC. Reactivation by central nervous system APC leads to the initiation of the inflammatory response resulting in demyelination. In this review we will focus on how MHC class II antigenic epitopes are created by different APC from the thymus, the periphery and from the brain, and will discuss the relevance of the balance between creation and destruction of such epitopes in the context of MS. A solid understanding of these processes offers the possibility for designing future therapeutic strategies.

Query Technologies and Applications for Program Comprehension

Industrial software systems are large and complex, both in terms of the software entities and their relationships. Consequently, understanding how a software system works requires the ability to pose queries over the design-level entities of the system. Traditionally, this task has been supported by simple tools (e.g., grep) combined with the programmer's intuition and experience. Recently, however, specialized code query technologies have matured to the point where they can be used in industrial situations, providing more intelligent, timely, and efficient responses to developer queries. This working session aims to explore the state of the art in code query technologies, and discover new ways in which these technologies may be useful in program comprehension. The session brings together researchers and practitioners. We survey existing techniques and applications, trying to understand the strengths and weaknesses of the various approaches, and sketch out new frontiers that hold promise.