VictorJuiz/thesis huggingface dataset:
The effects of team member intrinsic differences on emergent team dynamics and long-term innovative performance in engineering design teams [electronic resource]
Keywords: Mechanical Engineering

An increasing amount of work and learning takes place in a team context. Corporations rely on multidisciplinary teams to create innovative products, and team-based education is becoming an established and widespread practice. But what really makes for a great team? How do we put teams together, and how can we guarantee that they will be effective? Moreover, how can we encourage those teams to be more creative in their problem-solving? In many ways, we lack standard measurements of these individual aspects (e.g. there is no single accepted measure for team performance) and we also lack a holistic model describing the interplay between these aspects. This study takes a particular focus on design engineering teams working to develop innovative solutions to challenging multidisciplinary problems. Prior research informs us that intrinsic functional diversity can create the precondition for constructive task-based conflict within the team, contributing to an increased likelihood of innovative outcomes. However, diversity is also known to have mixed and often negative effects on team function, particularly at the level of emergent team phenomena such as conflict and communication (broadly defined as the team dynamic). A coherent model is needed to understand how intrinsic compositional aspects reliably impact team dynamics, and ultimately, how the team dynamics and underlying compositional characteristics interact to affect performance. A methodology is presented that attempts such an end-to-end description of team composition, dynamics and performance, principally relying on the Wilde Type indicator as a measurement of intrinsic differences. Results support the use of this instrument at the individual and team level, as well as offering insight into the impact of composition and diversity on team dynamics, and the ultimate effects on performance. Opportunities are explored for improved interventions in the team dynamic on the basis of these results.
Efficient algorithms for collaborative filtering [electronic resource]
Keywords: Electrical Engineering

Collaborative filtering is a novel statistical technique to obtain useful information or to make predictions based on data from multiple agents. A large number of such datasets are naturally represented in matrix form. Typically, there exists a matrix M from which we know a (typically sparse) subset of entries M_ij for (i, j) in some set E. The problem then is to predict/approximate the unseen entries. This framework of matrix completion is extremely general and applications include personalized recommendation systems, sensor positioning, link prediction and so on. Low rank models have traditionally been used to learn useful information from such datasets. Low-dimensional representations simplify the description of the dataset and often yield predictive powers. As an added benefit, it is easier to store and retrieve low dimensional representations. Finally, many computationally intensive operations such as matrix multiplication and inversion are simplified with low dimensional representations. Singular Value Decomposition (SVD) has traditionally been used to find the lowdimensional representation of a fully revealed matrix. There are numerous algorithms for computing the SVD of a matrix including several parallel implementations and implementations for sparse matrices. However, when the matrix is only partially observed, we show that SVD techniques are sub-optimal. In this work, we will develop algorithms to learn a low rank model from a partially revealed matrix. These algorithms are computationally efficient and highly parallelizable. We will show that the proposed algorithms achieve a performance close to the fundamental limit in a number of scenarios. Finally, the algorithms achieve significantly better performance than the state-of-the-art algorithms on many real collaborative filtering datasets.
Efficient methods for the study of subcontinental structure in admixed populations [electronic resource]
Keywords: Genetics

The central theme of this work revolves around the genetics of admixed individuals---individuals who derive their ancestry from two or more different ancestral populations.The genomes of admixed individuals exhibit unique properties that make them both fascinating and challenging to study using existing statistical methods. Their uniqueness lies in their block-like structure, a feature that is the direct result of generations of recombination events. An important advance in the field of admixture genetics has been the development of algorithms capable of determining the ancestry of different regions in the admixed genome. As we will illustrate in this work, local ancestry information can readily be harnessed towards the investigation of subcontinental structure, by which we attempt to determine the specific ancestral populations that gave rise to the admixed genomes under study, and whether differences exist in the ancestral makeup of these admixed samples. The latter line of investigation is of particular relevance to genome-wide association studies, which are prone to confounding if structure in a population has not been explicitly corrected for. This work is thus divided into three parts. We first apply some straightforward multivariate statistical methods such as PCA to gain insights into the African ancestry of African Americans. To this end, we introduce a novel method for the study of specific components of admixture in admixed individuals. We then expand on this work to introduce more sophisticated algorithms for the study of admixed genomics. These methods entail the development of an improved method for local ancestry deconvolution, and the implementation of a PCA approach designed to handle large amounts of missing data. We illustrate the power of using these methods in conjunction with one another with the study of two Latino populations. Finally, we describe a novel phasing algorithm designed to incorporate sequencing information into the process of haplotype reconstruction---an important upstream step for many of the analyses described here.
Efficient microarchitecture for network-on-chip routers [electronic resource]
Keywords: Electrical Engineering

Continuing advances in semiconductor technology, coupled with an increasing concern for energy efficiency, have led to an industry-wide shift in focus towards modular designs that leverage parallelism in order to meet performance goals. Networks-on-Chip (NoCs) are widely regarded as a promising approach for addressing the communication challenges associated with future Chip Multi-Processors (CMPs) in the face of further increases in integration density. In the present thesis, we investigate implementation aspects and design trade-offs in the context of routers for NoC applications. In particular, our focus is on developing efficient control logic for high-performance router implementations. Using parameterized RTL implementations, we first evaluate representative Virtual Channel (VC) and switch allocator architectures in terms of matching quality, delay, area and power. We also investigate the sensitivity of these properties to key network parameters, as well as the impact of allocation on overall network performance. Based on the results of this study, we propose microarchitectural modifications that improve delay, area and energy efficiency: Sparse VC allocation reduces the complexity of VC allocators by exploiting restrictions on transitions between packet classes. Two improved schemes for speculative switch allocation improve delay and cost while maintaining the critical latency improvements at low to medium load; this is achieved by incurring a minimal loss in throughput near the saturation point. We also investigate a practical implementation of combined VC and switch allocation and its impact on network cost and performance. The second part of the thesis focuses on router input buffer management. We explore the design trade-offs involved in choosing a buffer organization, and we evaluate practical static and dynamic buffer management schemes and their impact on network performance and cost. We furthermore show that buffer sharing can lead to severe performance degradation in the presence of congestion. To address this problem, we introduce Adaptive Backpressure (ABP), a novel scheme that improves the utilization of dynamically managed router input buffers by varying the stiffness of the flow control feedback loop based on downstream congestion. By inhibiting unproductive buffer occupancy, this mitigates undesired interference effects between workloads with differing performance characteristics.
Efficient, stable locomotion in legged robots [electronic resource]
Keywords: Mechanical Engineering

Legged animals have explored more of the Earth's surface than any human designed vehicle. The agility, adaptability, and efficiency found in nature continues to inspire robotics researchers to develop efficient leg designs robust, stable and adaptable control strategies that can rapid changes in the environment. Understanding the dynamics of ground collision and contact is critical to advancing the state of the art of legged robotics and allowing legged robotics to narrow the performance gap with legged animals. Unfortunately modeling the dynamics of collision requires attention not just to whole cycle measures like the coefficient of restitution but also to the transient measures of slip and initiation of chatter. This thesis contributes to the model-based design and control of legged robots by developing compliant contact models for systems where the deformation of the contact bodies is small and the contact forces can be considered to act through a single point. A novel visco-plastic contact model is developed to represent collision dynamics during legged locomotion. The relationship between the model's damping parameter and the coefficient of restitution is formulated using the energetic coefficient which permits energy consistent formulation for collisions that are non-collinear and include slip reversal. Given experimental data of the position and force of the foot, the model parameter estimation is performed with an offline genetic algorithm and an online unscented Kalman filter. The effectiveness of the methods are demonstrated on one-dimensional collisions of a single mass and a mass spring damper system. The methods presented allow for a physics-based study of the effect of leg and foot compliance on the energy efficiency of legged locomotion and of locomotion controllers. An actuated, non conservative, continuous contact SLIP model is developed for greater analysis of dynamics of running. Methodologies for finding passive (and active) gait controllers are of great interest to robotics but for non-conservative models, there are no passively stable fixed points around which to build such controllers. Minimal heuristic controllers are generated for bouncing gait generation which allow for stable hopping in the presence of actuator and ground contact energy losses. Together with the online inverse model parameter estimation, the approach advances robotics toward realizing adaptive optimal efficiency locomotion based on terrain measurements.
An egalitarian theory of the rule of law [electronic resource]
Keywords: Political Science

This dissertation offers a new theory of the rule of law, its moral value and what it requires of states. It argues that the rule of law is required for states to treat citizens as equals, not, as conventionally understood, to guarantee citizens' liberty. This claim is defended as part of a coherentist account of the rule of law, where the normative argument and the conceptual argument (about the demands of the rule of law) depend on one another, and draw from our understanding of real-world states. Chapter one defends the egalitarian account of the rule of law. Chapter two criticizes the traditional account, on which the rule of law responds to citizens' interests in individual liberty. Chapter three demonstrates the application of this theory to classical Athens. Chapter four demonstrates its application to the United Kingdom.
Electric field-induced conductivity switching in vanadium sesquioxide nanostructures [electronic resource]
Keywords: Applied Physics

Strong interactions, or correlations, between the d or f electrons in transition metal oxides can lead to various types of metal-insulator transitions which may be triggered by external parameters such as temperature, pressure, doping and magnetic field. Recent theoretical and experimental reports have suggested that this transition can also be triggered by a threshold electric field. Fully realized, this effect could lead to an entirely new class of electronic switches based on materials with strongly correlated electron systems. However, significant questions remain about the detailed nature of the experimental results, especially the degree to which Joule heating plays a role. In this work, we present an investigation of time-resolved, voltage-induced conductivity switching in the canonical metal-insulator transition system V2O3. The main findings can be categorized into three parts: film growth, electrical measurement, and electro-thermal modeling. First we discuss the growth, optimization and characterization of high-quality epitaxial V2O3 films, including the effect of oxygen pressure, substrate temperature and substrate material on the film properties. Next we show experimental results on electric field-induced phase transitions in V2O3 nanostructures fabricated by electron beam lithography. We observe that a threshold electric field of approximately 10^7 V/m applied across two-terminal nanostructures causes a metallization of V2O3's low-temperature Mott insulating state, preceded by a nanosecond-scale delay time. Lastly, we explore the feasibility of Joule heating as an explanation for the switching process. After fully accounting for temperature-related feedback and subthreshold nonlinear current-voltage characteristics, we find remarkably good agreement between the predicted and observed threshold voltages and switching delay times as a function of temperature, suggesting the switching mechanism is thermal in origin. We believe these findings have important implications for recent reports of voltage-induced switching in the related materials VO2 and Fe3O4 and will also help to guide future research on this phenomenon.
Electrothermal properties of nanowire materials for energy conversion systems [electronic resource]
Keywords: Mechanical Engineering

Worldwide energy demand is projected to increase 40% by 2035. Thermoelectric power generators could be a rapid, powerful way to meet the increased need for energy by converting wasted heat energy into useful electrical energy. However, inter-disciplinary factors determining the feasibility of widespread thermoelectric power generation systems have been minimally explored. This work connects materials and manufacturing costs, materials properties, and system level design to identify the factors necessary for successful thermoelectric generators. First, an economic analysis links materials and manufacturing costs with material performance to produce a thermoelectric device cost-performance metric. Current and potential thermoelectric materials are evaluated using this metric to determine which materials are promising candidates. Next, thermoelectric energy system modeling demonstrates the potential for increased energy efficiency in existing energy systems. Thermoelectric waste heat recovery is simulated for three applications: a home water heater, an automotive exhaust system, and an industrial furnace. The impact of system and material parameters on power generation efficiency is determined. Engineering at the nanoscale produces materials with combinations of properties absent in the natural world, enabling tunable and enhanced energy conversion in these systems. In particular, zinc oxide nanowires may offer improved thermoelectric energy conversion. Finally, characterization of electrothermal transport phenomena in single zinc oxide nanowire structures demonstrates the impact of nanowire contacts on the realization of functional nanowire materials.
The emergent effects of ocean acidification [electronic resource] : linking individuals to ecosystems
Keywords: Biology.

Ocean acidification represents a pervasive environmental change that could impact a wide range of species and cause extensive changes in marine ecosystems. An understanding of the potential emergent effects of acidification requires an integrated knowledge of the impacts on single species, species interactions, community structure, and ecosystem function. By using meta-analysis and field experiments in a naturally acidified ecosystem, this dissertation investigates how the responses of individual species to ocean acidification combine to affect the community and ecosystem. This research highlights the key role of species interactions in the emergent effects of ocean acidification. While meta-analyses underline the sensitivity of a wide range of species that build their shells or skeletons of calcium carbonate to acidification, field experiments in a naturally acidified ecosystem suggest that the loss or reduced abundance of the sensitive calcareous species in acidified conditions is compensated by an increased abundance of more tolerant species, resulting in an entire reorganization of the community. Analyses of succession patterns of the benthic rocky reef communities in the naturally acidified ecosystem suggest the reduced abundance of some calcareous species is linked to the increased abundance of fleshy seaweeds. While some calcareous species are able to recruit and grow at similar rates in non-acidified and acidified conditions during early stages of succession, their abundance is limited by the rapid growth of fleshy seaweeds in acidified conditions during the later stages of succession. Furthermore, analyses of recovery patterns suggest the role of calcareous herbivores is altered in acidified conditions. While recovery from disturbance in non-acidified conditions is highly variable and contingent on grazing by calcareous herbivores, the effects of grazing are not apparent in acidified conditions. Instead, recovery patterns in acidified conditions are canalized and consistently result in similar assemblages dominated by fleshy seaweed. Together, the results from this dissertation suggest ocean acidification causes a reorganization of a benthic rocky reef community, resulting in assemblages dominated by fleshy seaweeds with reduced diversity, invertebrate biomass, and trophic complexity. Furthermore, acidification affects the temporal and spatial dynamics of benthic rocky reef communities, leading to reduced habitat patchiness and diversity at the landscape scale.
Emerging immunosuppressants [electronic resource] : the identification, characterization and in vivo application of orai channel inhibitors
Keywords: Chemical and Systems Biology.

Store-operated calcium (SOC) entry and channel play a central role in regulating intracellular calcium concentrations in a variety of cell types. SOC is critical for many physiological processes, most notably activation of the immune system, where its lack of function is known to cause severe combined immunodeficiency (SCID) in human patients. In lymphocytes, where SOC has been extensively studied, it has been shown that SOC is mediated by the calcium channel Orai that is activated by its direct binding to STIM, a calcium sensor localized in the endoplasmic reticulum. While it was previously thought that SOC serves an important role only in immune and non-excitable cells, it is now clear that SOC and the proteins that regulate its function are ubiquitously expressed in variety of tissues, including muscle and the nervous system, and serve a diverse set of biological functions. More recently, SOC has been shown to act in a several pathological processes, ranging from muscular dystrophy to cancer, underscoring the significance of gaining a better understanding of its mechanism of action. Here we set out to develop pharmacological blockers of SOC, in order to gain insights into its molecular mechanism and physiological role. Such blockers could allow for acute inhibition of SOC, allowing for a temporal control that is essential for mechanistic studies. If successfully developed, such reagents could also be of therapeutic use as immunosuppressants or anti thrombotic agents in human patients. We designed a novel methodology for generating SOC blockers based on the identification and targeting of minimal functional domains (MFDs) of STIM and Orai. Using this approach, we identified small molecule blockers that can inhibit SOC at high nanomolar concentrations and can also block T cell activation in vitro and in vivo. These studies not only provide an important set of tools for better understanding STIM and Orai function, but also identify compounds that could potentially be developed into therapeutic agents for the treatment of pathological conditions such as autoimmune disease.
Emotions are relational [electronic resource] : positioning and the use of affective linguistic resources
Keywords: Linguistics

To understand human beings is to understand the variety and complexity of emotional experiences they have. Understanding how language is both shaped by and used in creating and coping with these experiences is the focus of this dissertation. It offers three case studies about affective linguistic resources, advancing a theoretical framework (positioning) and a series of quantitative methodologies that grow out of information-theoretic approaches to language. The first case study shows how many different linguistic resources have prominent affective aspects by examining a single emotional relationship conversation between two friends, showing how we might confidently make claims that one section of conversation is more emotionally intense than another and how we might get experimental data about connected discourse rather than being stuck in analyses of disconnected individual sentences. The second case study focuses on the word "little", which allows speakers to position themselves closer to their audiences and others through affectionate uses, allows them to hedge positions they aren't prepared to give full illocutionary force to, and which can also be used to demean and be-little. I show the factors important to determining "little"'s meaning through three experiments and analysis of seven conversational corpora. I look at the socio-pragmatics of its use, focusing especially on power and gender. In the third case study I show that emoticons occur in about 10% of posts on Twitter that are sent by people that are actually involved in real interactions (that is, they are sending messages and receiving messages back from at least four but no more than 100 other users). In addition to describing who uses which emoticons and how, I use the emoticons to describe the major dimensions of affective meaning in Twitter using hierarchical cluster analysis, factor analysis, and topic modeling. These dimensions—positivity/negativity, immediacy, teasing, and flirting—are all positional in nature. People use language to position themselves, their audiences, and their topics relative to one another. Expressions of emotions are more than internal states made visible, they are actions that have particular interpersonal causes and consequences, which are understood linguistically ("I'm mad/happy/scared") and which collective add up. This has important ramifications for any given interaction and at a more general level, these linguistic actions reveal and perturb the affective aspects of the cultural and cognitive systems they are part of.