Landscape and forest structure at moose mortality sites on Isle Royale National Park. A LiDAR based assessment

Landscape structure and heterogeneity play a potentially important, but little understood role in predator-prey interactions and behaviourally-mediated habitat selection. For example, habitat complexity may either reduce or enhance the efficiency of a predator's efforts to search, track, capture, kill and consume prey. For prey, structural heterogeneity may affect predator detection, avoidance and defense, escape tactics, and the ability to exploit refuges. This study, investigates whether and how vegetation and topographic structure influence the spatial patterns and distribution of moose (Alces alces) mortality due to predation and malnutrition at the local and landscape levels on Isle Royale National Park. 230 locations where wolves (Canis lupus) killed moose during the winters between 2002 and 2010, and 182 moose starvation death sites for the period 1996-2010, were selected from the extensive Isle Royale Wolf-Moose Project carcass database. A variety of LiDAR-derived metrics were generated and used in an algorithm model (Random Forest) to identify, characterize, and classify three-dimensional variables significant to each of the mortality classes. Furthermore, spatial models to predict and assess the likelihood at the landscape scale of moose mortality were developed. This research found that the patterns of moose mortality by predation and malnutrition across the landscape are non-random, have a high degree of spatial variability, and that both mechanisms operate in contexts of comparable physiographic and vegetation structure. Wolf winter hunting locations on Isle Royale are more likely to be a result of its prey habitat selection, although they seem to prioritize the overall areas with higher moose density in the winter. Furthermore, the findings suggest that the distribution of moose mortality by predation is habitat-specific to moose, and not to wolves. In addition, moose sex, age, and health condition also affect mortality site selection, as revealed by subtle differences between sites in vegetation heights, vegetation density, and topography. Vegetation density in particular appears to differentiate mortality locations for distinct classes of moose. The results also emphasize the significance of fine-scale landscape and habitat features when addressing predator-prey interactions. These finer scale findings would be easily missed if analyses were limited to the broader landscape scale alone.

COMPUTATIONAL STUDY OF MICROSTRUCTURE-PROPERTYMECHANISM RELATIONS IN FERROIC COMPOSITES

Ferroic materials, as notable members of smart materials, have been widely used in applications that perform sensing, actuation and control. The macroscopic property change of ferroic materials may become remarkably large during ferroic phase transition, leading to the fact that the macroscopic properties can be tuned by carefully applying a suitable external field (electric, magnetic, stress). To obtain an enhancement in physical and/or mechanical properties, different kinds of ferroic composites have been fabricated. The properties of a ferroic composite are determined not only by the properties and relative amounts of the constituent phases, but also by the microstructure of individual phase such as the phase connectivity, phase size, shape and spatial arrangement. This dissertation mainly focuses on the computational study of microstructure – property – mechanism relations in two representative ferroic composites, i.e., two-phase particulate magnetoelectric (ME) composite and polymer matrix ferroelectric composite. The former is a great example of ferroic composite exhibiting a new property and functionality that neither of the constituent phases possesses individually. The latter well represents the kind of ferroic composites having property combinations that are better than the existing materials. Phase field modeling was employed as the computing tool, and the required models for ferroic composites were developed based on existing models for monolithic materials. Extensive computational simulations were performed to investigate the microstructure-property relations and the underlying mechanism in ferroic composites. In particulate, it is found that for ME composite 0-3 connectivity (isolated magnetostrictive phase) is necessary to exhibit ME effect, and small but finite electrical conductivity of isolated magnetic phase can beneficially enhance ME effect. It is revealed that longitudinal and transverse ME coefficients of isotropic 0-3 particulate composites can be effectively tailored by controlling magnetic domain structures without resort to anisotropic two-phase microstructures. Simulations also show that the macroscopic properties of the ferroelectricpolymer composites critically depend on the ferroelectric phase connectivity while are not sensitive to the sizes and internal grain structures of the ceramic particles. Texturing is found critical to exploit the paraelectric«ferroelectric phase transition and nonlinear polarization behavior in paraelectric polycrystal and its polymer matrix composite. Additionally, a Diffuse Interface Field model was developed to simulate packing and motion in liquid phase which is promising for studying the fabrication of particulatepolymer composites.

GENERATING PLANS IN CONCURRENT, PROBABILISTIC, OVER-SUBSCRIBED DOMAINS

Planning in realistic domains typically involves reasoning under uncertainty, operating under time and resource constraints, and finding the optimal subset of goals to work on. Creating optimal plans that consider all of these features is a computationally complex, challenging problem. This dissertation develops an AO* search based planner named CPOAO* (Concurrent, Probabilistic, Over-subscription AO*) which incorporates durative actions, time and resource constraints, concurrent execution, over-subscribed goals, and probabilistic actions. To handle concurrent actions, action combinations rather than individual actions are taken as plan steps. Plan optimization is explored by adding two novel aspects to plans. First, parallel steps that serve the same goal are used to increase the plan’s probability of success. Traditionally, only parallel steps that serve different goals are used to reduce plan execution time. Second, actions that are executing but are no longer useful can be terminated to save resources and time. Conventional planners assume that all actions that were started will be carried out to completion. To reduce the size of the search space, several domain independent heuristic functions and pruning techniques were developed. The key ideas are to exploit dominance relations for candidate action sets and to develop relaxed planning graphs to estimate the expected rewards of states. This thesis contributes (1) an AO* based planner to generate parallel plans, (2) domain independent heuristics to increase planner efficiency, and (3) the ability to execute redundant actions and to terminate useless actions to increase plan efficiency.

Strategies to determine the biological function of microRNAs

MicroRNAs (miRNAs) are regulators of gene expression that control many biological processes in development, differentiation, growth and metabolism. Their expression levels, small size, abundance of repetitive copies in the genome and mode of action pose unique challenges in studies elucidating the function of miRNAs. New technologies for identification, expression profiling and target gene validation, as well as manipulation of miRNA expression in vivo, will facilitate the study of their contribution to biological processes and disease. Such information will be crucial to exploit the emerging knowledge of miRNAs for the development of new human therapeutic applications.

Evaluating retraining rules for semi-supervised learning in neural network based cursive word recognition

Training a system to recognize handwritten words is a task that requires a large amount of data with their correct transcription. However, the creation of such a training set, including the generation of the ground truth, is tedious and costly. One way of reducing the high cost of labeled training data acquisition is to exploit unlabeled data, which can be gathered easily. Making use of both labeled and unlabeled data is known as semi-supervised learning. One of the most general versions of semi-supervised learning is self-training, where a recognizer iteratively retrains itself on its own output on new, unlabeled data. In this paper we propose to apply semi-supervised learning, and in particular self-training, to the problem of cursive, handwritten word recognition. The special focus of the paper is on retraining rules that define what data are actually being used in the retraining phase. In a series of experiments it is shown that the performance of a neural network based recognizer can be significantly improved through the use of unlabeled data and self-training if appropriate retraining rules are applied.

Exploiting Runtime Information in the IDE

Developers rely on the mechanisms provided by their IDE to browse and navigate a large software system. These mechanisms are usually based purely on a system's static source code. The static perspective, however, is not enough to understand an object-oriented program's behavior, in particular if implemented in a dynamic language. We propose to enhance IDEs with a program's runtime information (eg. message sends and type information) to support program comprehension through precise navigation and informative browsing. To precisely specify the type and amount of runtime data to gather about a system under development, dynamically and on demand, we adopt a technique known as partial behavioral reflection. We implemented navigation and browsing enhancements to an IDE that exploit this runtime information in a prototype called Hermion. We present preliminary validation of our experimental enhanced IDE by asking developers to assess its usefulness to understand an unfamiliar software system.

Real-Time Joint Coupling of the Spine for Inverse Kinematics

In this paper we propose a simple model for the coupling behavior of the human spine for an inverse kinematics framework. Our spine model exhibits anatomically correct motions of the vertebrae of virtual mannequins by coupling standard swing and revolute joint models. The adjustement of the joints is made with several simple (in)equality constraints, resulting in a reduction of the solution space dimensionality for the inverse kinematics solver. By reducing the solution space dimensionality to feasible spine shapes, we prevent the inverse kinematics algorithm from providing infeasible postures for the spine.In this paper, we exploit how to apply these simple constraints to the human spine by a strict decoupling of the swing and torsion motion of the vertebrae. We demonstrate the validity of our approach on various experiments.

How Individual Scholars Can Reduce the Rigor-Relevance Gap in Management Research

This paper discusses a number of avenues management scholars could follow to reduce the existing gap between scientific rigor and practical relevance without relativizing the importance of the first goal dimension. Such changes are necessary because many management studies do not fully exploit the possibilities to increase their practical relevance while maintaining scientific rigor. We argue that this rigor-relevance gap is not only the consequence of the currently prevailing institutional context in the scientific system, but that individual scholars can reduce the gap between rigorous and practically relevant research by modifying their research work. Thus, most of our suggestions refer to individual scholars’ research activities and relate to specific steps in the (empirical) research process. Our discussion does not imply that all management studies should be practically oriented; basic research will remain a very important part of management research. However, we believe that not enough management research studies are significantly influenced by practical relevance.

OCTAVIS: Optimization Techniques for Multi-GPU Multi-View Rendering

We present a high performance-yet low cost-system for multi-view rendering in virtual reality (VR) applications. In contrast to complex CAVE installations, which are typically driven by one render client per view, we arrange eight displays in an octagon around the viewer to provide a full 360° projection, and we drive these eight displays by a single PC equipped with multiple graphics units (GPUs). In this paper we describe the hardware and software setup, as well as the necessary low-level and high-level optimizations to optimally exploit the parallelism of this multi-GPU multi-view VR system.

Does organic grassland farming benefit plant and arthropod diversity at the expense of yield and soil fertility?

Organic management is one of the most popular strategies to reduce negative environmental impacts of intensive agriculture. However, little is known about benefits for biodiversity and potential worsening of yield under organic grasslands management across different grassland types, i.e. meadow, pasture and mown pasture. Therefore, we studied the diversity of vascular plants and foliage-living arthropods (Coleoptera, Araneae, Heteroptera, Auchenorrhyncha), yield, fodder quality, soil phosphorus concentrations and land-use intensity of organic and conventional grasslands across three study regions in Germany. Furthermore, all variables were related to the time since conversion to organic management in order to assess temporal developments reaching up to 18 years. Arthropod diversity was significantly higher under organic than conventional management, although this was not the case for Araneae, Heteroptera and Auchenorrhyncha when analyzed separately. On the contrary, arthropod abundance, vascular plant diversity and also yield and fodder quality did not considerably differ between organic and conventional grasslands. Analyses did not reveal differences in the effect of organic management among grassland types. None of the recorded abiotic and biotic parameters showed a significant trend with time since transition to organic management, except soil organic phosphorus concentrations which decreased with time. This implies that permanent grasslands respond slower and probably weaker to organic management than crop fields do. However, as land-use intensity and inorganic soil phosphorus concentrations were significantly lower in organic grasslands, overcoming seed and dispersal limitation by re-introducing plant species might be needed to exploit the full ecological potential of organic grassland management. We conclude that although organic management did not automatically increase the diversity of all studied taxa, it is a reasonable and useful way to support agro-biodiversity.

Dose optimization approach to fast X-ray microtomography of the lung alveoli

A basic prerequisite for in vivo X-ray imaging of the lung is the exact determination of radiation dose. Achieving resolutions of the order of micrometres may become particularly challenging owing to increased dose, which in the worst case can be lethal for the imaged animal model. A framework for linking image quality to radiation dose in order to optimize experimental parameters with respect to dose reduction is presented. The approach may find application for current and future in vivo studies to facilitate proper experiment planning and radiation risk assessment on the one hand and exploit imaging capabilities on the other.

Pregnancy and birth cohort resources in europe: a large opportunity for aetiological child health research

BACKGROUND During the past 25 years, many pregnancy and birth cohorts have been established. Each cohort provides unique opportunities for examining associations of early-life exposures with child development and health. However, to fully exploit the large amount of available resources and to facilitate cross-cohort collaboration, it is necessary to have accessible information on each cohort and its individual characteristics. The aim of this work was to provide an overview of European pregnancy and birth cohorts registered in a freely accessible database located at http://www.birthcohorts.net. METHODS European pregnancy and birth cohorts initiated in 1980 or later with at least 300 mother-child pairs enrolled during pregnancy or at birth, and with postnatal data, were eligible for inclusion. Eligible cohorts were invited to provide information on the data and biological samples collected, as well as the timing of data collection. RESULTS In total, 70 cohorts were identified. Of these, 56 fulfilled the inclusion criteria encompassing a total of more than 500,000 live-born European children. The cohorts represented 19 countries with the majority of cohorts located in Northern and Western Europe. Some cohorts were general with multiple aims, whilst others focused on specific health or exposure-related research questions. CONCLUSION This work demonstrates a great potential for cross-cohort collaboration addressing important aspects of child health. The web site, http://www.birthcohorts.net, proved to be a useful tool for accessing information on European pregnancy and birth cohorts and their characteristics.

Determination of α_{s} from the QCD static energy

We compare lattice data for the short-distance part of the static energy in 21 flavor quantum chromodynamics (QCD) with perturbative calculations, up to next-to-next-to-next-to leading-logarithmic accuracy. We show that perturbation theory describes very well the lattice data at short distances, and exploit this fact to obtain a determination of the product of the lattice scale r0 with the QCD scale ΛMS. With the input of the value of r0, this provides a determination of the strong coupling αs at the typical distance scale of the lattice data. We obtain αs1.5  GeV0.3260.019, which provides a novel determination of αs with three-loop accuracy (including resummation of the leading ultrasoft logarithms), and constitutes one of the few low-energy determinations of αs available. When this value is evolved to the Z-mass scale MZ, it corresponds to αsMZ0.11560.00220.0021.

Privacy Panel: Usable and Quantifiable Mobile Privacy

The ever increasing popularity of apps stems from their ability to provide highly customized services to the user. The flip side is that in order to provide such services, apps need access to very sensitive private information about the user. This leads to malicious apps that collect personal user information in the background and exploit it in various ways. Studies have shown that current app vetting processes which are mainly restricted to install time verification mechanisms are incapable of detecting and preventing such attacks. We argue that the missing fundamental aspect here is a comprehensive and usable mobile privacy solution, one that not only protects the user's location information, but also other equally sensitive user data such as the user's contacts and documents. A solution that is usable by the average user who does not understand or care about the low level technical details. To bridge this gap, we propose privacy metrics that quantify low-level app accesses in terms of privacy impact and transforms them to high-level user understandable ratings. We also provide the design and architecture of our Privacy Panel app that represents the computed ratings in a graphical user-friendly format and allows the user to define policies based on them. Finally, experimental results are given to validate the scalability of the proposed solution.

Nuclear organization in the nematode C. elegans.

With its invariant cell lineage, easy genetics and small genome, the nematode Caenorhabditis elegans has emerged as one of the prime models in developmental biology over the last 50 years. Surprisingly however, until a decade ago very little was known about nuclear organization in worms, even though it is an ideal model system to explore the link between nuclear organization and cell fate determination. Here, we review the latest findings that exploit the repertoire of genetic tools developed in worms, leading to the identification of important sequences and signals governing the changes in chromatin tridimensional architecture. We also highlight parallels and differences to other model systems.