VictorJuiz/thesis huggingface dataset:
Understanding the Role of Latent Heating in the Heat and Mass Transport of the Global Atmospheric Circulation
Keywords: Atmospheric Dynamics
Climate Dynamics
Fluid Mechanics
General Circulation Modelling
Global Circulation
Thermodynamics

Almost one quarter of the insolation from the sun evaporates water vapor at the surface, which adds thermal energy to the atmosphere through latent heating. The main goals of this thesis are to diagnose and quantify the role that this latent heating plays in atmospheric transport and the global general circulation. Using the equivalent potential temperature (θe) as a variable to study the circulation implicitly accounts for the effects of latent heating on the dynamics, suggesting that tropospheric transport should follow these surfaces. In chapter 2 this idea is heuristically tested using an idealized moist general circulation model with perturbed midlatitude surface temperatures; the atmosphere responds by transporting warm air along climatological θe surfaces. In chapter 3 we study the mass transport of the general circulation projected onto θe surfaces using the Statistical Transformed Eulerian Mean (STEM), which parameterizes this circulation using zonal mean statistics. The functional dependence of the STEM is exploited to understand the response of the circulation on θe surfaces to climate perturbations, by calculating the functional derivatives. One key finding is that the sensitivity of the circulation is inversely proportional to the zonal mean standard deviation of θe. The preceding analysis using θe is complemented in chapter 4 by a novel heat tagging method developed in this thesis which allows us to attribute the potential temperature (θ) content of the atmosphere to specific diabatic processes. The heat tags includes both locally produced and remotely advected tagged tracer content, providing insight into regions which may be sensitive to remote diabatic processes. This method is applied to an idealized moist general circulation model. The majority of θ in the troposphere is from latent heating, even in the poles here where there is no latent heating. The variability of the heat tags, their use in decomposing heat transport, and the response to a CO2 doubling experiment are also studied.
The Unique and Cumulative Predictive Capacity of Validity Measures to Detect Feigned Psychological, Cognitive, and Medical Conditions: An Analogue Investigation
Keywords: Minnesota Multiphasic Personality Inventory-2-RF
Performance validity measures
Predictive validity
Symptom validity measures

Contemporary psychological assessments regularly inform high-stakes decisions (e.g., access to treatment, disability status, personnel selection, psychological capacity, work accommodations); the appropriateness of these decisions is not only dependent on accurate test data but also on a clinician’s skill in interpreting response validity. One strength of the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) is its array of validity scales designed to detect symptom over-reporting, with certain scales designed to target specific (feigned) symptom clusters (e.g., psychotic, emotional, somatic, cognitive symptoms). Empirical evidence consistently demonstrates that the MMPI-2-RF over-reporting validity scales can systematically differentiate between veridical and non-veridical response styles in both clinical and non-clinical samples. However, recent research suggests that the MMPI-2-RF five over-reporting validity scales, which ostensibly target different sets of feigned symptoms, may lack specificity in differentiating between different types of known-feigning groups. The primary goal of this study was to examine the unique contribution of each of these five MMPI-2-RF over-reporting scales to detect differentially the feigning of psychotic, emotional, cognitive, or somatic disorders/conditions using analogue samples. The secondary goal of this study aimed to explore whether commonly used performance-based validity measures (PVT) offer incremental validity to the MMPI-2-RF over-reporting validity scales in detecting these feigned disorders/conditions. To achieve these goals, 185 undergraduate students participated in a part mixed-model analogue design and were randomly assigned to one of six experimental groups. Participants completed the MMPI-2-RF on two occasions; once with the standard test instructions and then again with different sets of instructions, in which they were coached to feign one of several disorders/conditions; on this occasion the participants also completed a battery of PVTs. Results from this study are broadly consistent with past research indicating that the MMPI-2-RF over-reporting scales can effectively differentiate between veridical and feigned response styles. However, the results from this study offer evidence of incongruence between the conceptual underpinnings and reputed function of some of the over-reporting scales to differentially predict some of the feigned disorders/conditions. Results for the PVTs used in this study highlight the potential benefit of using a multi-method measurement approach in the assessment of non-credible responding.
Pollen Ice Nucleating Particles and Their Response to Atmospheric Processing
Keywords: Atmopsheric processing
Continuous Flow Diffusion Chamber
Droplet Freezing Technique
Ice nucleation
Particle enrichment
Primary Biological Aerosol Particles

Clouds are crucial to life on Earth as they help regulate temperature and distribute water resources. Yet, large uncertainties exist around cloud development and evolution with many open questions about processes spanning from micro- to macro-scales. On the micro-scale, ice formation contributes to precipitation formation and cloud radiative properties; yet our understanding of this process is limited. This thesis assesses the ice nucleating (IN) ability of pollen and subpollen particles (SPPs) under mixed-phase and cold cloud conditions. In a first step, pollen IN activity was investigated under mixed-phase cloud conditions where IN activity was found to vary between pollen types and that submicron SPPs drive pollen IN activity. Additionally, one pollen type, grey alder, was identified to initiate freezing above −10°C, thus contributing to a small set of highly active ice nucleating particles (INPs). In a second step, atmospheric processing of SPPs was investigated, as SPPs can experience atmospheric transport and exposure to varying environmental conditions. Several processing pathways were found to compromise pollen IN activity. The largest impacts were observed for the most IN active pollen by exposure to simulated solar radiation. Under cold cloud conditions, chemical oxidation negatively impacts the IN activity of silver birch and grey alder pollen, occurring on a similar timescale as changes to the molecular structure were observed. The findings from laboratory INP measurements were translated to parametrize INP concentrations from SPPs, indicating INP concentrations below 10-2 m-3 in one modeling scenario. To overcome potential barriers in detecting such low INP concentrations by commonly used INP instruments, a Portable Fine Particle Concentrator was evaluated for INP measurements in the field. Enrichment factors are found to be particle size dependent while an INP enrichment factor of 16±5 was achieved in a mountain-top field study. The insights gained from this thesis will help assess the importance of pollen as INPs and reduce uncertainties that cloud processes currently impose on weather and climate predictions.
Crude Regulation: Environmental Assessments and the Newfoundland and Labrador Offshore Oil Industry
Keywords: Canada
environmental assessment
Newfoundland and Labrador
offshore oil
regulation approach
strategic environmental assessment

This research examines the role that environmental assessment and strategic environmental assessment processes play in the commercial development of oil in the Newfoundland and Labrador (NL) offshore. It draws on the Regulation Approach as a way of examining the geographical and cultural specificity of the oil industry and environmental regulation in NL and how this ties to broader questions of development and capitalism, specifically the development and perpetuation of petro-capitalism in NL. Through document analysis, meeting observation, and interviews, this work examines environmental assessment processes in two locations. First, in offshore eastern NL, where all commercial offshore oil development and a significant amount of exploration has taken place. Dozens of environmental assessments have been done in the region but there has been little public contention or opposition to oil. The second location, the west coast of the island of Newfoundland, has far less experience with environmental assessment processes and oil activities. However, overlapping assessments for offshore drilling and fracking, as well as a strategic environmental assessment, led to the mobilization of communities in five provinces around the Gulf of St. Lawrence. Examining the history, current experiences, and outcomes of environmental assessments and oil industry activities in these locations illustrates the somewhat contradictory role that environmental assessments play in both supporting and challenging oil development in the province. The overarching emphasis on oil as a source of jobs and revenue in NL, especially since the cod fishery moratorium in 1992, has meant that environmental assessments often support and facilitate oil development and thus help to maintain provincial petro-capitalism. They help to contain and diffuse contention that could, if not addressed, lead to disruptions in oil-based accumulation. Yet at the same time, environmental assessments are also a space of contention where there are opportunities to challenge development projects and potentially question the province’s dependence on oil.
Physical and Mathematical Modeling of Water Atomization for Metal Powder Production
Keywords: Computational Fluid Dynamics
Metal Additive Manufacturing
Metal Powder
Optical Imaging
Powder Metallurgy
Water Atomization

Water atomization (WA) of a molten metal is a well-established and cost-effective industrial approach to producing low-reactive metal powders. However, WA powders are characterized by a wide spread of particle size unsuitable for certain powder metallurgy applications. To address this limitation, this thesis examines some of the poorly understood fluid mechanics phenomena involved in WA, to develop fundamental knowledge that describes the relationships between the design and operating conditions of a water atomizer, and the particle size distribution (PSD) of the resulting powder. In the first part of the thesis, a flat fan water spray is studied by experiment and computational fluid dynamics (CFD) simulation. The disintegration of a liquid sheet into a spray is examined, an optical technique to measure a multi-range droplet size distribution (DSD) in a developing spray is presented, and an enhanced model to quantify the momentum flux of a spray where it impinges a melt stream is proposed. The model suggests that the momentum flux of a spray, and thus the atomization capacity, increases with spray pressure and decreases with the travel distance of the spray from the nozzle to the impingement point and with the spray spreading angle. In the second part of the thesis, the above findings are examined via production of a low melting point alloy (Bi-42% Sn) powder using a laboratory-scale water atomizer that was designed and built for this work. The effects of various design and operating parameters, including water pressure, melt superheat, apex angle, and spray configuration on the mass median size (d50) and standard deviation (SD) of the powder PSD are investigated, and correlations proposed. These correlations can be used to control the size features of water atomized powders produced at industrial scale, by engineering various design and operating parameters, and thus expanding the market for water atomized powders.
Optimizing Distributed Computing Systems via Machine Learning
Keywords: Distributed Computing System
Machine Learning

The prosperity of Big Data owes to the advances in distributed computing systems, which make it possible to process massive volumes of data in parallel efficiently. As distributed architectures enable scalable and parallel computation with thousands of servers, critical challenges---allocating resources, scheduling tasks, and optimizing computation algorithms across servers---also arise. The dynamic performance of distributed architectures makes it too volatile to address these challenges with deterministic algorithms. In this dissertation, we apply machine learning techniques to optimize distributed systems. Particularly, we contribute to the following two areas that drive the advance of distributed systems in resource provisioning, task scheduling, and architecture design. Optimizing large-scale data analytics systems. Large-scale data analytics---processing data across geographically distributed datacenters---suffers from fluctuating resource provisioning and heterogeneous demands. However, most of the existing solutions are based on simplified heuristics derived from prior experiences, assuming the network bandwidth is a bottleneck. However, we find that the performance bottleneck is alternating---disk I/O and memory can also become the bottleneck. We propose Lube, a new system that detects bottlenecks at runtime and minimizes job computation times by mitigating the bottlenecks. By examining the execution of analytic queries, we show that existing query optimizers choose the slowest execution plan due to the agnostic of bandwidth fluctuations. In this dissertation, we present Turbo, a system that dynamically optimizes execution plans in response to runtime resource variations. Accelerating distributed machine learning systems. Traditional machine learning collecting training data to a server-based cluster has introduced non-trivial overhead and data privacy issues. To address such problems, we propose to refactor distributed machine learning systems with new architectures. In this dissertation, Siren enables distributed machine learning with serverless architectures and simplifies the way of machine learning development and deployment by learning the optimal resource allocation for machine learning training. We then focus on optimizing federated learning---a new distributed machine learning paradigm---that performs training locally on devices to preserve data privacy. However, the statistical issues posed by the local data significantly slow down existing federated learning algorithms. We present Favor, a framework that optimizes federated learning by carefully selecting devices to address the statistical issues.
Contaminated Environmentalism: The Visual Rhetoric of 1970s Ecocinema
Keywords: 1970s Environmentalism
Ecocinema
Ecocriticism
Film Philosophy
Rhetoric
Science Fiction

During the 1970s a spate of ecologically-themed science fiction films were produced in North America. Films like The Planet of the Apes (1968), Silent Running (1972), Soylent Green (1973), and Logan’s Run (1976) transformed the concerns of the rapidly expanding modern environmental movement into dystopian narratives and imagery. This dissertation reads examples of science fiction ecocinema from the 1970s alongside the key environmental texts that inspired their production, such as Rachel Carson’s Silent Spring (1962) and Paul Ehrlich’s The Population Bomb (1968). This comparative reading strategy uses science fiction film as a prism through which to view North American environmental history. By placing these films, which may at first seem derivative, alongside the books that inspired the modern environmental movement it becomes possible to expose rhetorical patterns that shape how we think about nonhuman nature. By crystallizing the environmental rhetoric of authors like Carson and Ehrlich into cinematic narrative, essentially turning their doomsday predictions into future worlds, these films put so much pressure on the tropes of the environmental movement that cracks in their logic become visible. This dissertation explores these cracks, demonstrating that the contradictions they reveal lie deep within the environmental movement, continuing to plague it into the present. One such contradiction, or crack, is so prevalent that it structures the dissertation. It is the nearly ubiquitous tension between the environmentalist desire to contain and control nonhuman nature in order to preserve it on the one hand, and the fear of a contaminated environment on the other. While containing, preserving, and archiving the environment may at first seem the best way to protect nonhuman nature from devastating anthropogenic effects, it perpetuates the myth of mastery that placed nonhumans in danger in the first place. An emphasis on contamination, which seems like the opposite of an environmentalist policy, is a more effective way of representing the always chaotic and interconnected environment. The cinema is the perfect medium for exploring this ecological contradiction as it simultaneously contains, and is contaminated by, the profilmic environment.
Passive Demand but Active Pay: The Effect of ETFFlows on CEO Stock Option Compensation
Keywords: CEO compensation
ETFs
governance
Stock Options
stock price informativeness
stock return co-movement

The rising prominence of exchange-traded funds (ETFs) over the past decade has resulted in a non-fundamentals driven demand for stocks held in ETF baskets. Prior research on ETFs finds both ETF-related stock price mis-valuation and ETF-related increases in the co-movement of stock prices. Separately, prior research on CEO compensation suggests that firms should use less stock option compensation when stock prices are less informative about firm performance as it becomes more difficult to mitigate the moral hazard problem, but more stock option compensation when there is increased co-movement, as stock options become a more effective tool for retention. Motivated by the fact that stock prices play a key role in CEO compensation decisions, this study tests the effect of ETF flows on CEO stock option compensation. I find that stock option compensation is increasing with ETF flows. Further, I find that the positive relation between stock option compensation and ETF flows is prominent in cross-sections where there is an ex ante motivation to compensate executives with options for retention purposes. Additionally, I do not find a positive relationship between risk-taking or firm performance with ETF flows, but do find a decrease in CEO turnover with increased ETF flows. The combined results suggest that: 1.) ETF flows may have affected firm incentives to compensate managers with stock options for retention purposes, and 2.) incentive alignment does not appear to be a prominent factor in awarding CEO stock options.
The Politics of the Middle Class and the Left in Uruguay: Feelings of Insecurity, Solidarity, and Support for Redistribution
Keywords: Insecurity
Middle Class
Political Left
Politics of Inequality and Redistribution
Solidarity
Uruguay

This dissertation explores the relationships between the middle class and the Left with a specific focus on attitudes towards redistributive policies. The work is based on an examination of the social attitudes and political propensities of the Uruguayan middle class during the Left governments of the Frente Amplio (FA) (2005-2014) including the lead up to their re-election in 2014. In investigating the attitudes and political proclivities of members of the Uruguayan middle class, I incorporate a consideration of the significant political and economic changes that occurred from the middle of the twentieth century onward. The work combines historical analysis and analysis of in-depth interviews conducted by the author. I argue that the presence of two sets of factors that shape individual’s senses of insecurity and solidarity help to explain middle class support for, or opposition to, redistributive policies. One set involves the presence or absence of a complex of insecurity mitigating factors; the second involves socialization processes that inculcate support for the social norms of equality and collective responsibility. I argue that a combination of insecurity mitigating factors and exposure to socialization processes that inculcate norms of equality and collective responsibility, producing social solidarity, tends to contribute to middle class support for the Left and the redistributive measures it stands for. On the other hand, the absence of these two sets of factors increases feelings of insecurity and erodes social solidarity. Particularly when combined with economic and political uncertainly, this tends to result in middle class resistance to redistributive measures. This complex of factors is therefore important in contributing to the necessary cross-class coalition of support required for the election of Left governments and ensuing redistributive measures.
Effect of Sulfur Chemical Potentials on Identities and Involvements of Hydrogen Species in Hydrogenation of Heteroarenes and Carbonyl Compounds on Sulfided Transition Metal Clusters
Keywords: carbonyl compound
heteroarene
hydrogenation
mechanism
sulfur chemical potential
transition metal

Hydrogenation mechanisms of heteroarenes and aliphatic carbonyls on transition metal or metal sulfide catalysts depend on metal chemical states, reactive hydrogen species, and thermochemical properties of hydrocarbons. This thesis examines the structures of Ru/SiO2, Pd/SiO2, and Pt/SiO2 catalysts in the presence of H2S (1.44 × 10-3–2.64 × 10-2 H2S:H2 ratio), where Ru nanoparticles transform into metallic cores covered with one monolayer of S-deficient RuS2, whereas Pd and Pt nanoparticles retain their metallic states with surfaces covered with reversible and irreversible sulfur. On Ru sulfides, the Run+-(Hδ–)-S2–-(Hδ+) proton-hydride pairs and Run+-(SH2)-S2– protons are the reactive hydrogen species. Pyridine has a high proton affinity; its hydrogenation is initiated by a proton addition from either Run+-(Hδ–)-S2–-(Hδ+) or Run+-(SH2)-S2– at its N, followed by a kinetically relevant hydride addition from Run+-(Hδ–)-S2–-(Hδ+) at the α-C. Pyrrole has a lower proton affinity; its hydrogenation is initiated by a kinetically relevant attack of a S2–-(Hδ+) proton from Run+-(Hδ–)-S2–-(Hδ+) at β-C, followed by an addition of a Run+-(Hδ–) hydride at α-C. On Pd and Pt, the protonic, reversible HSr* species and hydridic H* adatoms are the reactive hydrogen species. Pyridine adsorbs on metallic sites either via σ-interaction through the N lone electron pair, or via π-interaction through its aromatic ring. Hydrogenation of both σ- and π-bonded pyridine requires five H* additions at C atoms and one HSr* addition at N, where the third or fourth H* addition at C limits the rates for σ-bonded pyridine, and the third or fourth HSr* attack to N limits the rates for π-bonded pyridine. The comparison of Ru sulfides, S-covered Pd and Pt shows that both hydrogenation and C-N bond hydrogenolysis reactivities have volcano dependences on metal-sulfur binding strengths, and the hydrogenolysis-to-hydrogenation rate constant ratio increases with the decreasing metal-sulfur binding strength. Finally, this thesis establishes the reactivity trends of heteroarenes and aliphatic carbonyls on Ru sulfides. For heteroarenes, the hydrogenation reactivities relate to proton affinities, because the initial proton addition limits the rates. For aliphatic carbonyls, the reactivities relate to hydride affinities, because the initial hydride addition limits the rates.