Sensory overload is the feeling of over-stimulation that may lead to increased anxiety and panic in individuals with psychiatric disorders such as autism, post traumatic stress disorder, etc. Understanding visual processing is crucial to enhancing our treatments for disorders where sensory overload is a symptom. How do changes in internal states such as stress or hunger alter visual processing? This project aims to explore how visual processing is affected by signaling in the hypothalamus, an area of the brain regulating changes in internal states and stress. Preliminary studies revealed there are a number of neurons projecting from the lateral area of the hypothalamus to the visual cortex. We want to understand the specific location, identity, and neural circuits of these neurons. Visual cortex neurons were retrogradely traced to identify which inputs originate from the hypothalamus, and the geographical location of these cells was mapped out. The molecular identities of these projection neurons was further explored using specific RNAScope probes to check if those cells are expressing any of four genes most commonly expressed in the hypothalamus: Gal, Crh, Hcrt, and Pmch. This exploration will help us understand the type of signals communicated from the hypothalamic nuclei to the visual cortex to modulate visual processing.

Under what conditions has Russia adopted assertive foreign policies towards neighbouring states in order to pursue regional primacy? Scholars usually map Russia’s foreign policy according to theoretical approaches that are generated either from the individual, the state or the structural levels of analysis. However, each of them, taken individually, cannot account for Russia’s foreign policy across space and time. This study analyses the complex interplay between causal factors by developing a neoclassical realist model of Russia’s pursue of regional primacy in the contested neighbourhood with the EU. This study employs fuzzy-set Qualitative Comparative Analysis (fsQCA) at a cross-case level and Process Tracing at within-case level. fsQCA aims to test the explanatory value of systemic conditions such as external pressure in the regional neighbourhood by other regional powers and membership of target states in a military alliance (i.e. NATO); and of domestic conditions such as Russia’s status recognition by the West, and Russia’s state capacity. This analysis is based on 27 cases of Russia’s interaction with post-Soviet states between 1992 and 2015. Process Tracing is employed as a confirmatory method for within-case analysis.The results of the study suggest that Russia was inclined to adopt assertive foreign policy instruments, particularly military intervention, if external pressure from other great powers in a neighbouring country was combined with Russia’s high state capacity to mobilise resources. Due to NATO membership by neighbouring states, Russia resorted to coercive instruments rather than to direct use of force to maintain regional primacy. Finally, from the comparative process tracing, it emerged that, besides international security concerns and domestic constraints related to Russia’s status recognition, the two violent conflicts of Nagorno-Karabakh and South Ossetia/Abkhazia in the 1990s, which were of equal threat to Russia’s regional primacy in the South Caucasus, bore a different ‘iconic significance’ to Russia.

No description available.

No description available.

The Super Dual Auroral Radar Network (SuperDARN) is an international network of high frequency (HF) coherent scatter radars, employed to detect backscatter from magnetic field aligned plasma irregularities in the ionosphere and to study the near- Earth space weather. Space weather impacts many technological systems including HF communications, Global Positioning System (GPS), and surveillance radars. Variations in the pattern of the backscatter from the ground ("ground scatter") observed by the SuperDARN radars give information regarding the state of the ionosphere. In this thesis, ray tracing simulation of the observed ground scatter pattern for the mid-latitude SuperDARN radar at Blackstone, Virginia is implemented. An existing ray tracing code was modified, to incorporate the IRI-2007 model for electron density. This ray tracing code was used to simulate the ground scatter pattern observed at Blackstone in the year 2009. Simulations were compared with the observed ground scatter to assess our understanding of the ionospheric conditions. The IRI-2007 model is found to be adequate to predict the average ground scatter pattern observed through the year, including the winter anomaly. However, one deficiency with the IRI-2007 model is its inability to predict the sporadic E layer formation in summer and an anomalous evening enhancement in backscatter power observed in some months of the year, described here for the first time. Finally some suggestions are presented for the further improvement of the simulation methods for backscatter prediction. / Master of Science

Wind energy is the world´s fastest-growing renewable energy source. Thus, the amount of people exposed to wind farm noise is increasing. Due to its broadband amplitude modulated characteristic, wind turbine noise (WTN) is more annoying than noise produced by other common community/industrial sources. Aerodynamic noise along the blade span is the dominant noise source of modern large wind turbines. This type of noise propagates through the atmosphere in the proximity of wind farms. However, modelling and simulating WTN propagation over large distances is challenging due to the complexity of atmospheric conditions. Real temperature, wind velocity and relative humidity measurements typically show a characteristic nonlinear behavior. A comprehensive propagation model that addresses this problem while maintaining high accuracy and computational efficiency is necessary. A Hamiltonian Ray tracing (HRT) technique coupled to aerodynamically induced WTN is presented in this work. It incorporates acoustic wave refraction due to spatial speed of sound gradients, a full Doppler Effect formulation resulting from wind velocities in any arbitrary direction, proper acoustic energy dissipation during propagation, and ground reflection. The HRT method averts many of the setbacks presented by other common numerical approaches such as fast field program (FFP), parabolic equation methods (PE), and the standard Eikonal ray tracing (ERT) technique. In addition, it is not bounded to the linearity assumptions made for analytic propagation solutions. A wave phase tracking analysis through inhomogeneous and moving media is performed. Curved ray-paths are numerically computed by solving a non-linear system of coupled first order differential equations. Sound pressure levels through the propagation media are then calculated by using standard ray tubes and performing energy analysis along them. The ray model is validated by comparing a monopole’s ray path results against analytically obtained ones. Sound pressure level predictions are also validated against both FFP and ERT methods. Finally, results for a 5MW modern wind turbine over a flat acoustically soft terrain are provided. / Master of Science / Modelling propagation of noise produced by wind turbines over large distances is a challenging task. Real temperature distributions, flow characteristics around wind turbines, and relative humidity are some of the parameters that affect the behavior of the produced sound in the atmosphere. To this end, a Hamiltonian ray tracing tool that models the propagation of wind turbine noise has been developed and is the main focus of this thesis. This method avoids many of the limitations and inaccurate assumptions presented by other common numerical and analytical approaches. In addition, current commercial noise propagation codes are incapable of fully capturing the physical complexity of the problem. Finally, validation and simulation results for a wind turbine over flat terrain are presented in order to demonstrate the superior accuracy and computational efficiency of the Hamiltonian approach.

Since the 1980s, private sector spending on Research and Development (RandD) has outpaced federal RandD spending. For example, while the Department of Defense (DoD) spent $64 billion on RandD in fiscal year 2015, the private sector spent $260 billion. DoD relies on the private sector to develop advanced technologies for defense requirements. However, some innovative businesses are hesitant to work with DoD because of the perceived bureaucracy of the DoD procurement system. Recognizing this problem, in 1989, Congress created a new type of non-procurement agreement for DoD called Other Transactions Agreements (OTs). OTs are excluded from most laws and regulations that govern traditional procurement agreements. OTs can be written to meet the needs of the parties and the project, enabling agreements that resemble commercial contracting. Congress has expanded OT authority, and DoD has issued OT guidance to its employees. But DoD has not used OTs as widely as expected. This is puzzling because commentators find OTs are helpful to DoD and the private sector in reducing the legal and regulatory compliance costs associated with the DoD procurement system. Using qualitative methods, and drawing on the OT and historical institutionalism literature, this study explores institutional factors that may explain why DoD has not more widely used OTs. The study relied on interviews with DoD employees and contractors. OT case studies were used to triangulate the interview findings. Potential causal mechanisms are identified to support future research of the DoD OT program using causal process tracing. The study findings are used to offer policy recommendations to support the wider use of OTs by DoD. / Ph. D. / Some innovative businesses are reluctant to work with the Department of Defense (DoD) due to the perceived bureaucracy of the DoD procurement system. Recognizing this problem, in 1989, Congress created a new type of non-procurement agreement for DoD called Other Transactions Agreements (OTs). Unlike traditional procurement agreements, OTs are excluded from many of the laws and regulations that reportedly deter the private sector from doing business with DoD. OTs enable agreements that more closely resemble commercial contracting. The terms and conditions of the OT can be written to meet the needs of the parties and the OT project. Thus, OTs are a flexible tool to help attract innovative businesses that would not otherwise work for DoD under traditional procurement agreements. Congress has expanded OT authority to encourage DoD to use OTs more widely. DoD has issued guidance to help its employees negotiate and administer OTs. But DoD has not used OTs as much as expected. This is puzzling because procurement and policy experts find that OTs are helpful to DoD and the private sector in reducing the legal and regulatory compliance costs often associated with the DoD procurement system. This study explores institutional and other factors that may help explain why DoD has not more widely used OTs. The study relied on interviews with DoD employees and contractors. OT case studies were used to corroborate the interview findings. The study findings are used to offer policy recommendations to support the wider use of OTs by DoD.

This thesis describes advanced techniques for site-specific propagation prediction. The need for accurate site-specific propagation is discussed in the context of current trends in the wireless industry. The first half of the report is dedicated to measuring and modeling continuous wave (CW) local-area path loss. Specifically, the text uses examples from a 5.85 GHz CW measurement campaign in and around suburban homes. Not only do these measurements demonstrate the validity of the original models and techniques presented in the thesis, but the results themselves may prove particularly useful for developing in-home wireless devices operating in the National Information Infrastructure band. This unlicensed spectrum was allocated in January of 1997 and holds promising applications for public and private telecommunications, home-based wireless internet, wireless local loops, and any number of wideband wireless applications. There is an in-depth development of deterministic propagation prediction techniques in the latter half of the thesis. The use of geometrical optics for terrestrial microwave propagation is discussed as well as an overview of the numerous ray tracing techniques that exist in the literature. Finally, a new 3D ray launching method is presented which improves upon many of the existing ray tracing algorithms. The thesis demonstrates how this algorithm is capable of recovering very detailed channel information from a wideband deterministic propagation prediction. / Master of Science

Yes / Contact tracing involves collecting people’s information to track the spread of COVID-19 and to warn people who have been in the proximity of infected individuals. This measure is important to public health and safety during the pandemic. However, customers’ concerns about the violation of their privacy might inhibit their cooperation in the contact tracing process, which poses a risk to public safety. This research investigates how to facilitate customers’ cooperative behavior in contact tracing based on cognitive trust and affective trust. The findings show that cognitive trust increases people’s willingness to disclose information and reduces their willingness to falsify it, whereas affective trust increases the willingness for both disclosure and falsification. This research contributes to the literature on customer data privacy by illuminating how cognitive and affective trust distinctly influence cooperative behavior, which has important implications for hospitality businesses.

With rising complexity of high performance computing systems and their parallel software, performance analysis and optimization has become essential in the development of efficient applications. The comparison of performance data is a key operation required in performance analysis. An analyst may conduct different types of comparisons in order to understand the performance properties of an application. One use case is comparing performance data from multiple measurements. Typical examples for such comparisons are before/after comparisons when applying optimizations or changing code versions. Besides comparing performance between multiple runs, also comparing performance characteristics across the parallel execution streams of an application is essential to detect performance problems. This is typically useful to detect imbalances, outliers, or changing runtime behavior during the execution of an application. While such comparisons are straightforward for the aggregated data in performance profiles, only limited solutions exist for comparing event traces. Trace-based analysis, i.e., the collection of fine-grained information on individual application events with timestamps and application context, has proven to be a powerful technique. The detailed performance information included in event traces make them very suitable for performance analysis. However, this level of detail also presents a challenge because it implies a large and overwhelming amount of data. Currently, users need to perform manual comparison of event traces, which is extremely challenging and time consuming because of the large volume of detailed data and the need to correctly line up trace events. To fill the gap of missing solutions for automatic comparison of event traces, this work proposes a set of techniques that automatically align traces. The alignment allows their structural comparison and the highlighting of differences between them. A set of novel metrics provide the user with an objective measure of the differences between traces, both in terms of differences in the event stream and timing differences across events. An additional important aspect of trace-based analysis is the visualization of performance data in event timelines. This has proven to be a powerful approach for the detection of various types of performance problems. However, visualization of large numbers of event timelines quickly hits the limits of available display resolution. Likewise, identifying performance problems is challenging in the large amount of visualized performance data. To alleviate these problems this work proposes two new approaches for event timeline visualization. First, novel folding strategies for event timelines facilitate visual scalability and provide powerful overviews of performance data at the same time. Second, this work presents an effective approach that automatically identifies and highlights several types of performance critical sections in an application run. This approach identifies time dominant functions of an application and subsequently uses them to analyze runtime imbalances throughout the application run. Intuitive visualizations present the resulting runtime variations and guide the analyst to performance hot spots. Evaluations with benchmarks and real-world applications assess all introduced techniques. The effectiveness of the comparison approaches is demonstrated by showing automatically detected performance issues and structural differences between different versions of applications and across parallel execution streams. Case studies showcase the capabilities of the event timeline visualization techniques by demonstrating scalable performance data visualizations and detecting performance problems and code inefficiencies in real-world applications.