High Bee and Wasp Diversity in a Heterogeneous Tropical Farming System Compared to Protected Forest

It is a globally important challenge to meet increasing demands for resources and, at the same time, protect biodiversity and ecosystem services. Farming is usually regarded as a major threat to biodiversity due to its expansion into natural areas. We compared biodiversity of bees and wasps between heterogeneous small-scale farming areas and protected forest in northern coastal Belize, Central America. Malaise traps operated for three months during the transition from wet to dry season. Farming areas consisted of a mosaic of mixed crop types, open habitat, secondary forest, and agroforestry. Mean species richness per site (alpha diversity), as well as spatial and temporal community variation (beta diversity) of bees and wasps were equal or higher in farming areas compared to protected forest. The higher species richness and community variation in farmland was due to additional species that did not occur in the forest, whereas most species trapped in forest were also found in farming areas. The overall regional species richness (gamma diversity) increased by 70% with the inclusion of farming areas. Our results suggest that small-scale farming systems adjacent to protected forest may not only conserve, but even favour, biodiversity of some taxonomic groups. We can, however, not exclude possible declines of bee and wasp diversity in more intensified farmland or in landscapes completely covered by heterogeneous farming systems.

A mass spectrometric multicenter study supports classification of preeclampsia as heterogeneous disorder

The diagnostic value of affinity-based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis to distinguish preeclampsia (PE) from matched controls was tested in a multicenter setting.

MODELING FUNCTIONAL DATA WITH SPATIALLY HETEROGENEOUS SHAPE CHARACTERISTICS

We propose a novel class of models for functional data exhibiting skewness or other shape characteristics that vary with spatial or temporal location. We use copulas so that the marginal distributions and the dependence structure can be modeled independently. Dependence is modeled with a Gaussian or t-copula, so that there is an underlying latent Gaussian process. We model the marginal distributions using the skew t family. The mean, variance, and shape parameters are modeled nonparametrically as functions of location. A computationally tractable inferential framework for estimating heterogeneous asymmetric or heavy-tailed marginal distributions is introduced. This framework provides a new set of tools for increasingly complex data collected in medical and public health studies. Our methods were motivated by and are illustrated with a state-of-the-art study of neuronal tracts in multiple sclerosis patients and healthy controls. Using the tools we have developed, we were able to find those locations along the tract most affected by the disease. However, our methods are general and highly relevant to many functional data sets. In addition to the application to one-dimensional tract profiles illustrated here, higher-dimensional extensions of the methodology could have direct applications to other biological data including functional and structural MRI.

In-situ electrical, mechanical and electrochemical characterizations of one-dimensional nanostructures

One-dimensional nanostructures initiated new aspects to the materials applications due to their superior properties compared to the bulk materials. Properties of nanostructures have been characterized by many techniques and used for various device applications. However, simultaneous correlation between the physical and structural properties of these nanomaterials has not been widely investigated. Therefore, it is necessary to perform in-situ study on the physical and structural properties of nanomaterials to understand their relation. In this work, we will use a unique instrument to perform real time atomic force microscopy (AFM) and scanning tunneling microscopy (STM) of nanomaterials inside a transmission electron microscopy (TEM) system. This AFM/STM-TEM system is used to investigate the mechanical, electrical, and electrochemical properties of boron nitride nanotubes (BNNTs) and Silicon nanorods (SiNRs). BNNTs are one of the subjects of this PhD research due to their comparable, and in some cases superior, properties compared to carbon nanotubes. Therefore, to further develop their applications, it is required to investigate these characteristics in atomic level. In this research, the mechanical properties of multi-walled BNNTs were first studied. Several tests were designed to study and characterize their real-time deformation behavior to the applied force. Observations revealed that BNNTs possess highly flexible structures under applied force. Detailed studies were then conducted to understand the bending mechanism of the BNNTs. Formations of reversible ripples were observed and described in terms of thermodynamic energy of the system. Fracture failure of BNNTs were initiated at the outermost walls and characterized to be brittle. Second, the electrical properties of individual BNNTs were studied. Results showed that the bandgap and electronic properties of BNNTs can be engineered by means of applied strain. It was found that the conductivity, electron concentration and carrier mobility of BNNTs can be tuned as a function of applied stress. Although, BNNTs are considered to be candidate for field emission applications, observations revealed that their properties degrade upon cycles of emissions. Results showed that due to the high emission current density, the temperature of the sample was increased and reached to the decomposition temperature at which the B-N bonds start to break. In addition to BNNTs, we have also performed in-situ study on the electrochemical properties of silicon nanorods (SiNRs). Specifically, lithiation and delithiation of SiNRs were studied by our STM-TEM system. Our observations showed the direct formation of Li22Si5 phases as a result of lithium intercalation. Radial expansion of the anode materials were observed and characterized in terms of size-scale. Later, the formation and growth of the lithium fibers on the surface of the anode materials were observed and studied. Results revealed the formation of lithium islands inside the ionic liquid electrolyte which then grew as Li dendrite toward the cathode material.

Simulating dioxane transport in a heterogeneous glacial aquifer system (Washtenaw County, Michigan) using publicly available models and data

The primary challenge in groundwater and contaminant transport modeling is obtaining the data needed for constructing, calibrating and testing the models. Large amounts of data are necessary for describing the hydrostratigraphy in areas with complex geology. Increasingly states are making spatial data available that can be used for input to groundwater flow models. The appropriateness of this data for large-scale flow systems has not been tested. This study focuses on modeling a plume of 1,4-dioxane in a heterogeneous aquifer system in Scio Township, Washtenaw County, Michigan. The analysis consisted of: (1) characterization of hydrogeology of the area and construction of a conceptual model based on publicly available spatial data, (2) development and calibration of a regional flow model for the site, (3) conversion of the regional model to a more highly resolved local model, (4) simulation of the dioxane plume, and (5) evaluation of the model's ability to simulate field data and estimation of the possible dioxane sources and subsequent migration until maximum concentrations are at or below the Michigan Department of Environmental Quality's residential cleanup standard for groundwater (85 ppb). MODFLOW-2000 and MT3D programs were utilized to simulate the groundwater flow and the development and movement of the 1, 4-dioxane plume, respectively. MODFLOW simulates transient groundwater flow in a quasi-3-dimensional sense, subject to a variety of boundary conditions that can simulate recharge, pumping, and surface-/groundwater interactions. MT3D simulates solute advection with groundwater flow (using the flow solution from MODFLOW), dispersion, source/sink mixing, and chemical reaction of contaminants. This modeling approach was successful at simulating the groundwater flows by calibrating recharge and hydraulic conductivities. The plume transport was adequately simulated using literature dispersivity and sorption coefficients, although the plume geometries were not well constrained.

Modeling mechanical response of heterogeneous materials

Heterogeneous materials are ubiquitous in nature and as synthetic materials. These materials provide unique combination of desirable mechanical properties emerging from its heterogeneities at different length scales. Future structural and technological applications will require the development of advanced light weight materials with superior strength and toughness. Cost effective design of the advanced high performance synthetic materials by tailoring their microstructure is the challenge facing the materials design community. Prior knowledge of structure-property relationships for these materials is imperative for optimal design. Thus, understanding such relationships for heterogeneous materials is of primary interest. Furthermore, computational burden is becoming critical concern in several areas of heterogeneous materials design. Therefore, computationally efficient and accurate predictive tools are highly essential. In the present study, we mainly focus on mechanical behavior of soft cellular materials and tough biological material such as mussel byssus thread. Cellular materials exhibit microstructural heterogeneity by interconnected network of same material phase. However, mussel byssus thread comprises of two distinct material phases. A robust numerical framework is developed to investigate the micromechanisms behind the macroscopic response of both of these materials. Using this framework, effect of microstuctural parameters has been addressed on the stress state of cellular specimens during split Hopkinson pressure bar test. A voronoi tessellation based algorithm has been developed to simulate the cellular microstructure. Micromechanisms (microinertia, microbuckling and microbending) governing macroscopic behavior of cellular solids are investigated thoroughly with respect to various microstructural and loading parameters. To understand the origin of high toughness of mussel byssus thread, a Genetic Algorithm (GA) based optimization framework has been developed. It is found that two different material phases (collagens) of mussel byssus thread are optimally distributed along the thread. These applications demonstrate that the presence of heterogeneity in the system demands high computational resources for simulation and modeling. Thus, Higher Dimensional Model Representation (HDMR) based surrogate modeling concept has been proposed to reduce computational complexity. The applicability of such methodology has been demonstrated in failure envelope construction and in multiscale finite element techniques. It is observed that surrogate based model can capture the behavior of complex material systems with sufficient accuracy. The computational algorithms presented in this thesis will further pave the way for accurate prediction of macroscopic deformation behavior of various class of advanced materials from their measurable microstructural features at a reasonable computational cost.

First-principles studies of boron nanostructures

Boron is an 'electron deficient' element which has a rather fascinating chemical versatility. In the solid state, the elemental boron has neither a pure covalent nor a pure metallic character. As a result, its vast structural dimensionally and peculiar bonding features hold a unique place among other elements in the periodic table. In order to understand and properly describe these unusual bonding features, a detailed and systematic theoretical study is needed. In this work, I will show that some of the qualitative features of boron nanostructures, including clusters, sheets and nanotubes can easily be extracted from the results of first principles calculations based on density functional theory. Specifically, the size-dependent evolution of topological structures and bonding characteristics of boron clusters, Bn will be discussed. Based on the scenario observed in the boron clusters, the unique properties of boron sheets and boron nanotubes will be described. Moreover, the ballistic electron transport in single-walled carbon nanotubes will be considered. It is expected that the theoretical results obtained in the present thesis will initiate further studies on boron nanostructures, which will be helpful in understanding, designing and realizing boron-based nanoscale devices.