In arid and semi-arid ecosystems, dominant tree species create dramatic mosaics of plant islands of fertility and relatively barren plant interspaces that exert immense pressure on ecosystem processes and offers an ideal opportunity to explore the impact of bacterial communities. We evaluated potential links between soil respiration and N mineralization, and community co-occurrence networks and predicted gene function across three tree island microsites (i.e., beneath tree canopies, at the canopy edge, and in interspaces) in a replicated field experiment in thirty-eight woodlands sites in the Great Basin Desert in UT, USA. Additionally, we potentially intensified the effects of tree islands by creating a treatment where whole trees were shredded and the resulting fine woody debris (FWD) was deposited onto the soil surface and measured a suite of characteristics relating to the metabolic functional state of communities (i.e., microbial efficiency as the microbial quotient, C substrate quality, biomass, and dissolved organic C) to improve our interpretation of potential links between function and structure. We found that tree islands were the predominant driver, creating highly complex and connected assemblies of bacterial populations and easily discernable differences in abundance and composition of predicted functional genes. Specifically, communities directly beneath Juniperus and Pinus canopies were comprised of at least 5.2-times more connections between bacterial taxa than present in networks from interspace and edge. Using Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) to predict the gene expression, differences in the functional potential mirrored shifts in network complexity. Tree island communities expressed 236 genes with many related to the degradation of polyaromatic or polycyclic compounds, while interspace communities expressed only 66 genes associated with the decomposition of more labile C substrates. We observed a robust tree island microsite effect on all ecosystem processes, with soil respiration rates increasing 12% and N mineralization decreasing 29% in canopy than interspace soils demonstrating that a more recalcitrant substrate from a sole C source provided high amounts of low quality of DOC and lead to a decrease in metabolic efficiency, but ultimately selected for a specific community assembly. Alternatively, communities at the edge of canopies, experiencing both tree island and interspace soil conditions generated similar levels of soil respiration as canopy soils regardless of not selecting for a highly connected community and/or specific genes suggesting that a diverse composition of labile and recalcitrant C substrates from multiple sources (e.g., trees, perennial grasses, annual grasses, and forbs) potentially elevates function by promoting the activity of a wide range of taxa. Our results identify that tree islands exert enough pressure to create distinct interactions between bacteria and alter gene expression resulting in changes in ecosystem function, but the link between structure and function is mediated through the diversity and quality of C substrates.

This dissertation is a theoretical and empirical supported discussion about Women’s professional soccer (WPS) in the USA. The aim is to discuss the challenges to establish a professional soccer league for women. Questions of importance are what is the product, how is the product marketed, and who is the intended consumer. The material for the discussion is extracted from interviews with people who are or have been involved with the WPS. Other sources are material from the Internet that concerns or relates to the WPS as well as literature about marketing, product development and soccer in the US. The theory that’s mostly used is C Wright Mills ideas about individual and structure and also management and marketing models that are used to explain the material when it’s needed. Four areas are defined as the foundation, which correlates to each other. First what the discussion revolves around: the WPS. Then there’s the format of the WPS, which is franchise. Further, a sport franchise needs to be sellable to an audience. Therefore matters concerning product and marketing need to be addressed. These are the four principal areas that will be discussed, to begin with. Later in the discussion the question of gender arises. But equality between the sexes is not a prerequisite for the WPS, as the other four areas are, it’s mere a possible result. Therefore other theories than gender theories are in focus since the aim is to locate strengths, weaknesses and challenges for the league. With that said a gender perspective is present and will be explored at the end. The core discussion is turned towards the consumer and the target market. Do the management of the WPS actually know who is coming to the games? Do they know what these consumers want from the product? And if they don’t know this, they can’t know how to market the product.

This thesis describes an improved methodology for embedded software development. MATLAB and Simulink allow engineers to simplify algorithm development and avoid duplication of effort in deploying these algorithms to the end hardware. Special new hardware targeting capabilities of MATLAB and Simulink are described in detail. A motor control system design served to demonstrate the efficacy of this new method. Initial data was collected to help model the motor in Simulink. This allowed for the design of the open and closed loop control systems. The designed system was very effective, with good response and no steady state error. The entire design process and deployment to a digital signal processor took significantly less time and effort than other typical methods. The results of the control system design as well as the details of these development improvements are described.

An isometric, zero-order (position), one dimensional pursuit tracking task was used to investigated the effects of alterations in the speed of target movement and the control/response ratio (C/R ratio) on human tracking performance. The speed of target movement was varied through different frequency sine-wave forcing functions. The C/R ratio was controlled by varying the force level required to track the target. This required force level was individually tailored I with force levels scaled to the isometric maximum voluntary contraction (MVC) of elbow extension for each subject. It was hypothesized that higher frequencies of forcing function (5 levels) and higher required force levels (5 levels) would result in degraded tracking performance. The dependent variable investigated was absolute tracking error as a proportion of the required force level for the trial. Results revealed significant main effects for both Frequency and Force, but not for any of the two- or three-way interactions. The trend was linear for Frequency, with superior tracking occurring at slower frequencies. The effect of Force level was modelled using a second-order polynomial, indicating that superior tracking occurred at the middle required force levels. Regression analysis provided a predicted optimal force level of approximately 65% extension MVC. Subjective mental workload evaluations using the Modified Cooper-Harper scale showed similar results. Results are interpreted with regards to selecting optimum system gains for human manual control. / Master of Science

Cellular Thermal Shift Assay (CETSA) is a method of identifying protein-drug interactions by monitoring changes in protein thermal stability. CETSA is traditionally performed by using Western Blotting to examine the thermal stability shifts of a single protein of interest. By combining CETSA with Mass Spectrometry the shifts in thermal stability can be examined for an entire proteome in a single experiment in a technique known as CETSA-MS or Thermal Proteome Profiling (TPP). This can be used to identify targets of a compound of interest in order to further understand the compounds mechanism of interest, potentially making CETSA a powerful tool for target discovery. Here we attempt to develop a protocol by which CETSA can be used as a drug target discovery tool. Our work has allowed us to create a protocol that can reliably identify soluble drug targets. Our results demonstrate the capacity of CETSA to screen multiple compounds as well as to perform more in depth dose response studies, and highlight how future improvements could be made to the protocol

Visual search consists of locating a known target amongst a field of distractors. Often times, observers must search for more than one object at once. Eye movements were monitored in a series of visual search experiments examining search efficiency and how color is represented in order to guide search for multiple targets. The results demonstrated that observers were very color selective when searching for a single color. However, when searching for two colors at once, the degree of similarity between the two target colors had varying effects on fixation patterns. Search for two very similar colors was almost as efficient as search for a single color. As this similarity between the targets deceased, search efficiency suffered, resulting in more fixations on objects dissimilar to both targets. In terms of representation, the results suggest that the guiding template or templates prevailed throughout search, and were relatively unaffected by the objects encountered. Fixation patterns revealed that two similarly colored objects may be represented as a single, unitary range containing the target colors as well as the colors in between in color space. As the degree of similarity between the targets decreased, the two targets were more likely to be represented as discrete separate templates.

The main idea of this thesis is to formulate the smooth variable structure filter (SVSF) for target tracking applications in the presence of measurement origin uncertainty. Tracking, by definition is the recursive estimation of the states of an unknown target from indirect, inaccurate and uncertain measurements. The measurement origin uncertainty introduces the data association problem to the tracking system. The SVSF estimation strategy was first presented in 2007. This filter is based on sliding mode concepts formulated in a predictor-corrector form. Essentially, the SVSF uses an existence subspace and smoothing boundary layer to bind the estimated state trajectory to within a subspace around the true trajectory. The SVSF is demonstrated to be robust to modeling uncertainties and provide extra measures of performance such as magnitude of the chattering signal. Therefore, with respect to specific nature of car tracking problems that involves modeling uncertainty, it was hypothesized that a robust estimation strategy such as the SVSF, would improve the performance of the tracking system and give more robust tracking results. Also, having the extra information provided by the SVSF strategy, i.e. the chattering magnitude signal, would lead to algorithms that could better account for measurement origin uncertainty in the context of the data association process. Further to these hypotheses, this research has focused on investigating the performance of the SVSF in the target tracking problems, advancing the development of the SVSF, and employing its characteristics to deal with data association problems. The performance of the SVSF, in its current form, can be improved when there is fewer measurements than states by using its error covariance in target tracking. As the first contribution in this research, the SVSF is formulated in the context of target tracking in clutter and combined with data association algorithms, resulting in the SVSF-based probabilistic data association (PDA) and joint probabilistic data association (JPDA) for non-maneuvering and maneuvering targets. The results are promising in the tracking scenarios with modeling uncertainties. Therefore, the thesis is then expanded by generalizing the covariance of the SVSF for the cases where the number of measurements is less than the number of states. The generalized covariance formulation is then used to derive a generalized variable boundary layer (GVBL) SVSF. This new derivation gives an estimation method that is optimal in the MMSE sense and in the meantime preserves the robustness of the SVSF. The proposed algorithm improves the performance measures and makes a more reliable tracking algorithm. This thesis explores the hypothesis that multiple target tracking performance can be substantially improved by including chattering information from SVSF-based filtering in the data association method. A Bayesian framework is used to formulate a new set of augmented association probabilities which include the chattering information. The simulation and experimental results demonstrate that the proposed augmented probabilistic data association improves the performance of the tracking system including maneuvering cars, in particular for highly cluttered environments. The derived methods are applied on simulations and also on real data from an experimental setup. This thesis is made up of a compilation of papers that include three conference papers and three journal papers. / Thesis / Doctor of Philosophy (PhD)

Sensors are getting smaller, inexpensive and sophisticated, with an increased availability. Compared to 25 years ago, an object tracking system now can easily achieve twice the accuracy, a much larger coverage and fault tolerance, without any significant changes in the overall cost. This is possible by simply employing more than just one sensor and processing measurements from individual sensors sequentially (or even in a batch form). %This is the centralized scheme of multi-sensor target tracking wherein the sensors send their individual detections to a central facility, where tracking related tasks such as data association, filtering, and track management etc. are performed. This is also perhaps the simplest solution for a multi-sensor approach and also optimal in the sense of minimum mean square error (MMSE) among all other multi-sensor scenario. In sophisticated sensors, the number of detections can reach thousands in a single frame. The communication and computation load for gathering all such detections at the fusion center will hamper the system's performance while also being vulnerable to faults. A better solution is a distributed architecture wherein the individual sensors are equipped with processing capabilities such that they can detect measurements, extract clutter, form tracks and transmit them to the fusion center. The fusion center now fuses tracks instead of measurements, due to which this scheme is commonly termed track-level fusion. In addition to sub-optimality, the track-level fusion suffers from a very coarse problem, which occurs due to correlations between the tracks to be fused. Often, in realistic scenarios, the cross-correlations are unknown, without any means to calculate them. Thus, fusion cannot be performed using traditional methods unless extra information is transmitted from the fusion center. This thesis proposes a novel and generalized method of fusing any two probability density functions (pdf) such that a positive cross-correlation exists between them. In modern tracking systems, the tracks are essentially pdfs and not necessarily Gaussian. We propose harmonic mean density based fusion and prove that it obeys all the necessary requirements of being a viable fusion mechanism. We show that fusion in this case is a classical example of agreement between the fused and participating densities based on average $\chi^2$ divergence. Compared to other such fusion techniques in the literature, the HMD performs exceptionally well. Transmitting covariance matrices in distributed architecture is not always possible in cases for e.g. tactical and automotive systems. Fusion of tracks without the knowledge of uncertainty is another problem discussed in the thesis. We propose a novel technique for local covariance reconstruction at the fusion center with the knowledge of estimates and a vector of times when update has occurred at local sensor node. It has been shown on a realistic scenario that the reconstructed covariance converges to the actual covariance, in the sense of Frobenius norm, making fusion without covariance, possible. / Thesis / Doctor of Philosophy (PhD)

Several large-scale projects including FamilySearch, Ancestry, BALSAC (University of Quebec), and others have gathered incredible amounts of genealogical data ranging from millions to billions of individuals. To study the structure of this data, we propose a model that generates a genealogical network based on real-world genealogical data using two key features: (i) geodesic distance between couples prior to union and (ii) the number of children per couple. The distribution of the distance to a couples' nearest common ancestor in an observed community captures the global scale at which biological cycles form in the underlying genealogical network. Similarly, the number of children per couple captures the local structure given by the degree distribution in the genealogical network. Constructing imitation data which approximates a real-world network's structure and growth rate is desirable for use in generalizable machine learning models. This model, which we refer to as the Target Model, provides a foundation for further work in predicting family network growth and structure.

Within population biology, models are often analyzed for the net reproduction number or other generalized target reproduction numbers, which describe the growth or decline of the population based on specific mechanisms. This is useful in determining the strength and efficiency of control measures for inhibiting or enhancing population growth. The literature contains many algebraic and combinatorial approaches for deriving the net reproduction number and generalized target reproduction numbers from digraphs and associated matrices. Finding, categorizing, and counting the permutations of disjoint cycles, or cycles unions is a requirement of the Cycle Union approach by Lewis et al. (2019). These cycles and subsequent cycle unions can be found via the digraphs and associated matrices. We developed cycle counting patterns for targeting fertilities within Leslie Matrices, Lefkovitch Matrices, Sub-Diagonal Lower Triangle Transition Matrices, and Lower Triangle Transition Matrices to serve as a foundation for future work. Presented are the counting patterns and closed-form summations of the cycle unions.