Doctor of Philosophy

dissertationThe primary objective of this study is to determine what drives water planners to plan for the impacts of a changing climate. As the climate continues to change, climate scientists have projected changes in water quantities available for human and other uses. This multimethod study addresses these questions through three interlinked studies focusing on state level data and planning. The first study examines how Americans form policy preferences on climate change. This question is particularly relevant in today's environment of decreasing public support, especially from 2008 onward, for climate change initiatives even as climate scientists' confidence in future global warming increases. Results from previous research reporting several significant predictor variables for climate change policy preferences including scientific knowledge, partisan identification, general environmental beliefs, and vulnerability are tested with contemporary data at the state level. I found that following the 2008 election, partisan identification became a much stronger predictor at the state level while the other predictors diminished in importance. The second study examines how state water plans and state hazard mitigation plans address climate change. Plans were coded for the extent to which they address climate change in their calculations for future supply and demand. Multivariable Linear Regression models were developed to test the predictive value of independent variables including statewide voting, vulnerability to climate change, and recent experience with droughts and natural disasters. The most significant predictor variable for both state water planning and state hazard mitigation planning was the statewide voting record. Democratic leaning states were much more likely to plan for climate change in their plans than were Republican leaning states. The third study is a qualitative comparison of the Texas and California state water plans. These two states were chosen because of their political differences but otherwise largely similar challenges with water resources, projected decreases in available water resources due to climate change, similar water planning paradigms at the state level, and similar demographics. While Texas is maintaining a traditional water planning effort focusing on infrastructure construction and conservation, California is focusing on environmental protection, social equity, and has adopted a scenario based approach accounting for uncertainties not only from climate change but also from population growth and changing demand patterns

Valuation bubbles and sequential bubbles

Price bubbles in an Arrow-Debreu valuation equilibrium in infinite-time economy are a manifestation of lack of countable additivity of valuation of assets. In contrast, known examples of price bubbles in sequential equilibrium in infinite time cannot be attributed to the lack of countable additivity of valuation. In this paper we develop a theory of valuation of assets in sequential markets (with no uncertainty) and study the nature of price bubbles in light of this theory. We consider an operator, called payoff pricing functional, that maps a sequence of payoffs to the minimum cost of an asset holding strategy that generates it. We show that the payoff pricing functional is linear and countably additive on the set of positive payoffs if and only if there is no Ponzi scheme, and provided that there is no restriction on long positions in the assets. In the known examples of equilibrium price bubbles in sequential markets valuation is linear and countably additive. The presence of a price bubble indicates that the asset's dividends can be purchased in sequential markers at a cost lower than the asset's price. We also present examples of equilibrium price bubbles in which valuation is nonlinear but not countably additive.Asset price bubbles, linear valuation, sequential equilibria, valuation equilibria

Implementing Arrow-Debreu Equilibria by Trading Infinitely-Lived Securities

We study the question of implementing Arrow-Debreu equilibrium allocations in infinite-time economy under uncertainty by sequential trading of infinitely-lived securities. The crucial aspect of implementation is the choice of feasibility constraints on agents' portfolio strategies. The main difficulty lies in the possibility of price bubbles in security markets. We derive an exact relation between Arrow-Debreu equilibrium allocations and sequential equilibrium allocations in security markets under two portfolio feasibility constraints: the wealth constraint, and the bounded borrowing constraint. We show that sequential equilibria with price bubbles correspond to Arrow-Debreu equilibria with income transfers.

Annotating affective neuroscience data with the Emotion Ontology

The Emotion Ontology is an ontology covering all aspects of emotional and affective mental functioning. It is being developed following the principles of the OBO Foundry and Ontological Realism. This means that in compiling the ontology, we emphasize the importance of the nature of the entities in reality that the ontology is describing. One of the ways in which realism-based ontologies are being successfully used within biomedical science is in the annotation of scientific research results in publicly available databases. Such annotation enables several objectives, including searching, browsing and cross-database data integration. A key benefit conferred by realismbased ontology is that suitably annotated research results are able to be aggregated and compared in a fashion that is based on the underlying reality that the science is studying. This has the potential of increasing the power of statistical analysis and meta-analysis in data-driven science. This aspect has been fruitfully exploited in the investigation of the functions of genes in molecular biology. Cognitive neuroscience uses functional neuroimaging to investigate the brain correlates of areas of mental functioning such as memory, planning and emotion. The use of functional neuroimaging to study affective phenomena such as the emotions is called ‘affective neuroscience’. BrainMap is the largest curated database of coordinates and metadata for studies in cognitive neuroscience, including affective neuroscience (Laird et al., 2005). BrainMap data is already classified and indexed using a terminology for classification, called the ‘Cognitive Paradigm Ontology’ (CogPO), that has been developed to facilitate searching and browsing. However, CogPO has been developed specifically for the BrainMap database, and the data are thus far not annotated to a realism-based ontology which would allow the discovery of interrelationships between research results across different databases on the basis of what the research is about. In this contribution, we describe ongoing work that aims to annotate affective neuroscience data, starting with the BrainMap database, using the Emotion Ontology. We describe our objectives and technical approach to the annotation, and mention some of the challenges

Representing Mental Functioning: Ontologies for Mental Health and Disease

Mental and behavioral disorders represent a significant portion of the public health burden in all countries. The human cost of these disorders is immense, yet treatment options for sufferers are currently limited, with many patients failing to respond sufficiently to available interventions and drugs. High quality ontologies facilitate data aggregation and comparison across different disciplines, and may therefore speed up the translation of primary research into novel therapeutics. Realism-based ontologies describe entities in reality and the relationships between them in such a way that – once formulated in a suitable formal language – the ontologies can be used for sophisticated automated reasoning applications. Reference ontologies can be applied across different contexts in which different, and often mutually incompatible, domain-specific vocabularies have traditionally been used. In this contribution we describe the Mental Functioning Ontology (MF) and Mental Disease Ontology (MD), two realism-based ontologies currently under development for the description of humanmental functioning and disease. We describe the structure and upper levels of the ontologies and preliminary application scenarios, and identify some open questions

Rehabilitación y mejoramiento de la carretera rural, que conduce del Gancho en cantón Flor de Mayo hacia el entronque de la aldea El Rosario, Tacaná, San Marcos

Desarrollar una investigación monográfica de la aldea donde se realizará la ampliación y mejoramiento de la carretera rural, así diseñar la carretera de acuerdo a los códigos establecidos por la Dirección General de Caminos y elaborar las características de la carretera y luego realizar planos, presupuesto, cronograma y evaluación ambiental del proyecto

What’s Spurious, What’s Real? Measuring the Productivity Impacts of ICT at the Firm-Level

In order to assess the productivity effects of information and communication technologies (ICT), regressions based on cross–sectional firm–level data may yield unreliable results for the commonly employed production function framework. In this paper, various estimation biases and econometric strategies to overcome their sources are discussed. The effects are illustrated on the basis of a representative set of panel data for German service firms. The application of a suited SYS–GMM estimator yields evidence for significant productivity effects of ICT which are substantially smaller though than those suggested by cross–section or pooled OLS estimates

Automated Academic and Professional Behaviors Student Tracking Systems

The purpose of this presentation is to describe a novel program faculty designed automated academic and professional behaviors student tracking system in select programs at three campuses of the University of St Augustine for Health Sciences. The automated tracking systems streamlined and served to improve both faculty and student understanding of both academic and professional behavior performance, across three programs and three campuses at this multi campus university Early detection of performance insufficiencies was critical to changing performance and behavior

Using postmarket surveillance to assess safety-related events in a digital rehabilitation app (Kaia App): Observational study

BACKGROUND: Low back pain (LBP) affects nearly 4 out of 5 individuals during their lifetime and is the leading cause of disability globally. Digital therapeutics are emerging as effective treatment options for individuals experiencing LBP. Despite the growth of evidence demonstrating the benefits of these therapeutics in reducing LBP and improving functional outcomes, little data has been systematically collected on their safety profiles. OBJECTIVE: This study aims to evaluate the safety profile of a multidisciplinary digital therapeutic for LBP, the Kaia App, by performing a comprehensive assessment of reported adverse events (AEs) by users as captured by a standardized process for postmarket surveillance. METHODS: All users of a multidisciplinary digital app that includes physiotherapy, mindfulness techniques, and education for LBP (Kaia App) from 2018 to 2019 were included. Relevant messages sent by users via the app were collected according to a standard operating procedure regulating postmarket surveillance of the device. These messages were then analyzed to determine if they described an adverse event (AE). Messages describing an AE were then categorized based on the type of AE, its seriousness, and its relatedness to the app, and they were described by numerical counts. User demographics, including age and gender, and data on app use were collected and evaluated to determine if they were risk factors for increased AE reporting. RESULTS: Of the 138,337 active users of the Kaia App, 125 (0.09%) reported at least one AE. Users reported 0.00014 AEs per active day on the app. The most common nonserious AE reported was increased pain. Other nonserious AEs reported included muscle issues, unpleasant sensations, headache, dizziness, and sleep disturbances. One serious AE, a surgery, was reported. Details of the event and its connection to the intervention were not obtainable, as the user did not provide more information when asked to do so; therefore, it was considered to be possibly related to the intervention. There was no relationship between gender and AE reporting (P\u3e.99). Users aged 25 to 34 years had reduced odds (odds ratio [OR] 0.31, 95% CI 0.08-0.95; P=.03) of reporting AEs, while users aged 55 to 65 years (OR 2.53, 95% CI 1.36-4.84, P=.002) and ≥75 years (OR 4.36, 95% CI 1.07-13.26; P=.02) had increased odds. AEs were most frequently reported by users who had 0 to 99 active days on the app, and less frequently reported by users with more active days on the app. CONCLUSIONS: This study on the Kaia App provides the first comprehensive assessment of reported AEs associated with real-world use of digital therapeutics for lower back pain. The overall rate of reported AEs was very low, but significant reporting bias is likely to be present. The AEs reported were generally consistent with those described for in-person therapies for LBP

Managerial Ratings of in‐Role Behaviors, Organizational Citizenship Behaviors, and Overall Performance: Testing Different Models of Their Relationship

We utilized confirmatory factor analysis to test several of the assumptions behind this new direction for OCB research. First, in support of prior research, we found that in-role behaviors (IRBs) and two dimensions of OCB (altruism and conscientiousness) were empirically distinct. Next, we found that overall performance ratings were predicted by ratings given concerning IRB and altruism, though not by ratings of the OCB dimension of conscientiousness. Third, a second-order factor analysis that specified four first-order factors loading on one general factor of performance was found to be consistent with the data. This is presented as support for including OCB dimensions within current definitions of employee performance. Finally, to address possible halo in the data, a second causal model was evaluated, where overall performance was viewed as causally prior to the other three measures. Implications are discussed. D 2000 Elsevier Science Inc. All rights reserved. Keywords: In-role behavior; Organizational citizenship behavior; Overall performance; Halo The past decade has seen a large amount of research and conceptual development concerning organizational citizenship behavior, or OCB (Smith et a