VictorJuiz/thesis huggingface dataset:
Noise Sensitivity and Distraction in Youth with ADHD: The Role of Individual Difference Factors and Noise Types
Keywords: Academic performance
ADHD
Noise
Noise preferences
Noise sensitivity
Youth

Noise is a prevalent feature of many academic environments. Research examining the impact of noise on the cognitive performance of children with Attention-Deficit/Hyperactivity Disorder (ADHD) has demonstrated a positive effect of white noise and an adverse effect of silence/speech. These results are consistent with the Moderate Brain Arousal (MBA) model of ADHD, in which stimuli that evoke moderate arousal lead to improved performance over noises that are under- or over-stimulating. The present dissertation aims to investigate the noise sensitivity and preferences of adolescents with (n = 52) and without ADHD (n = 51), and the impact of noise on the academic performance of youth with ADHD. First, participants completed a questionnaire examining their levels of noise sensitivity. Youth with ADHD reported higher levels of noise sensitivity than their peers without ADHD, and noise sensitivity was significantly associated with gender and youth-reported inattention and hyperactivity/impulsivity. Second, a subset of participants (n = 16, half with ADHD) completed an interview examining their noise preferences while studying. The responses of youth with ADHD indicated a preference for some noise versus no noise during studying, and difficulties studying in the presence of conversation. In contrast, youth without ADHD did not report a consistent preference for background noise.The third study examined the effects of two noises (babble and white noise) relative to a no noise condition on reading and writing tasks for youth with ADHD. Youth were also asked to rate the perceived difficulty of each task. Planned contrasts revealed that participants in the white noise condition read the passage in less time and wrote more words in their composition compared to participants in the other conditions, though white noise did not improve reading and writing accuracy. The contrasts also revealed that the participants in the babble condition rated the tasks as more difficult than those in the no noise condition. Overall, the findings provided some support for past research and the MBA model. The results also highlight the need for further investigations of noise sensitivity and the effects of noise on academic measures in youth with ADHD. Educational and clinical implications are discussed.
Class Identification in Modern Democracies: A Comparative Study of its Sources and Effects
Keywords: Class awareness
Class identity
Income inequality
Puclic Policy
Social Mobility

This dissertation explores the extent to which people are class aware in modern democratic society. I investigate whether the positions people occupy in the class structure, and the perceptions of where they think they fit, influence attitudes toward economic inequality. This research also considers the social and political consequences of national-level income inequality for class awareness. Market household income inequality has grown substantially in most modern societies since the 1990s. At the same time, government effort to reduce inequality has waned. I examine whether attitudes differ in countries with low and high inequality, and whether class awareness plays a role in shaping how people think about economic inequality. I find that class identities are more polarized in unequal societies, and that even if people perceive inequality as legitimate, they would prefer it to be reduced if it might improve their own economic position.My findings suggest that people's class identities and their preferences for inequality strongly reflect their economic positions. Yet, I also find that class attitudes change at different levels of income inequality. This is because when inequality rises more people in society feel its adverse effects. My research shows that people across the class structure in all societies understand how economic inequality affects their lives. More importantly, people understand how they might benefit from inequality changing. This awareness holds significant policy implications, especially if inequality continues to grow. These conclusions are drawn from two sources of individual-level survey data spanning nearly two decades. Each substantive chapter employs a cross-national analysis. In total, I investigate class identification and awareness in 42 countries, using three waves of the World Values Survey (WVS) collected from 1990-2006, and two waves of the International Social Survey Program (ISSP) Inequality Module collected from 1999-2009. I extract country-level data from various sources, including the Luxembourg Income Study (LIS), the Organization for Economic Co-operation and Development (OECD), the Standardized Income Inequality Database (SWIID), the World Bank (www.worldbank.org), and the CIA World Factbook (www.cia.gov).
Two Avenues of Inference: The Evidential Paradigm and Relative Belief Theory
Keywords: a priori bias
composite likelihoods
evidential paradigm
genetic association analysis
measure of statistical evidence
relative belief inferences

This thesis focuses on two inferential theories, the Evidential paradigm (Royall, 1997) and (Bayesian) relative belief inferences (Evans, 1997), both of which are concerned with characterizing statistical evidence. We investigate the success of these theories in quantifying the strength of statistical evidence in a number of statistical problems. We contribute evidential methodology for the analysis of genetic association in family data using the ratio of composite likelihoods as our evidence function. We show that composite likelihoods, with a robust adjustment, have the two crucial performance properties of the Evidential paradigm: (1) The evidence function will support the true value over the false value by an arbitrarily large factor as the sample size increases, and (2) for large samples, the probability of misleading evidence, is approximated by the bump function which has a small upper bound. Thus, in the Evidential paradigm, composite likelihood ratios can be used as a surrogate for the likelihood ratios constructed from true likelihoods when evaluating the full likelihood is not convenient.We illustrate an approach to Bayesian point null hypothesis assessment based on relative belief inferences. We develop a methodology to assess possible bias inherent in the relative belief ratio, the evidence function, which measures the change in belief after seeing the data. We then present the application of these inferences to independent binary data in a logistic regression setting. We derive a goodness-of-fit test for logistic regression based on a weakly informative prior. When no lack of fit is detected, we show how to use these priors to induce priors on model parameters. These priors do not have the issues that the more commonly used priors have on the model parameters, e.g. a common approach is to assign diffuse priors on the model coefficients s to reflect little information, which in fact induces an informative prior on the
Influence of Beliefs about Cancer Pain and Analgesics on Pain Experience Outcomes in Taiwanese Patients with Lung or Colorectal Cancer
Keywords: Cancer pain-related beliefs
Pain experience outcomes
Taiwanese cancer outpatients

Pain is a common problem and patients' cancer pain-related beliefs may be a contributing factor to pain experience. Despite research attention to this problem, evidence suggests that pain management remains insufficient in Taiwanese outpatients with lung or colorectal cancer. Thus, the purpose of this study was to describe the pattern of cancer pain-related beliefs and to examine the independent contribution of beliefs and use of analgesics on pain experience guided by Horne's extended Common Sense Model (CSM) of self- regulation. This study was conducted in a sample of 151 cancer outpatients (lung 44%, colorectal 56%, with a mean age of 63.8 (SD=11.2) years. Measures included the Chinese version of Illness Perception Questionnaire-Revised for Cancer Pain (IPQ-CaCP) for cancer pain beliefs, the Beliefs Medicines Questionnaire (BMQ) for beliefs about analgesics, the Medication Adherence Report Scale-5 (MARS-5) for use of analgesics, and the Taiwanese version of Brief Pain Inventory-Short Form (BPI-T) for pain experience. Results indicated participants endorsed more negative cancer pain beliefs and less positive cancer pain beliefs consistent with Horne's CSM model, and the sub-optimal use of analgesics reflected that they balanced the necessity of analgesics with concerns about adverse consequences of analgesics. In hierarchical linear regression analyses, the contribution to worst pain intensity included more serious consequence beliefs and a lower level of treatment control beliefs. Serious consequence beliefs, age, pain duration, physical performance status, and worst pain intensity were significant predictors of pain interference. Use of analgesics found no contribution to pain experience. These findings highlight the independent contribution of a comprehensive set of cancer pain-related beliefs to pain experience in Taiwanese patients with lung and colorectal cancer in the home setting. Pain assessment and education should take into account the role of these beliefs on pain experience. Future research should determine if these beliefs change over time.
Towards Targeted Photodynamic Therapy: Synthesis and Characterization of Aziridine Aldehyde-cyclized Cancer-targeting Peptides and Bacteriochlorin Photosensitizers
Keywords: Cancer
Peptides
Photodynamic therapy
Photosensitizers

This thesis presents the contributions we made towards achieving targeted photodynamic therapy (PDT) by synthesizing and characterizing new aziridine aldehyde-cyclized cancer-targeting peptides and bacteriochlorin photosensitizers (PSs). The new peptides are based on the integrin-targeting sequence, arginine-glycine-aspartic acid (RGD), and were cyclized by aziridine aldehyde-driven macrocyclization chemistry. We developed a versatile conjugation strategy, and created two useful RGD macrocycles that specifically bound to integrin receptors in vitro. Computer modeling and competitive binding studies found that this macrocyclization chemistry modulated the binding affinity of these peptides by tuning the geometry of peptides of different lengths. The new PSs described herein include bacteriochlorophyll derivatives that efficiently produced reactive oxygen species (ROS) upon illumination with red light. We discovered two simple structural modifications that enhanced the photogeneration of ROS, and suggest that future studies make use of these design parameters to create next generation bacteriochlorin PSs with superior photoactivity compared to known derivatives. In addition, we optimized a facile synthetic reaction for creating a new natural product analog with a distinct exocyclic F-ring, and found it was capable of PDT. Unlike some of its natural chlorin counterparts, our bacteriochlorin was not a potent antioxidant. Yet, we suggest that future efforts make use of our simple reaction to expand the library of F-ring containing bacteriochlorins to elucidate key structural modifications that can tune the PDT efficacy and antioxidant activity of this distinct class of bacteriochlorins. Finally, this thesis presents preliminary investigations that attempted to develop new cancer-targeting PDT agents. While the goal of achieving optimal cancer-targeted PDT was not accomplished in this work, it is envisioned that this thesis will provide useful data and insights that will contribute to the development of optimal aziridine aldehyde-cyclized peptide-bacteriochlorin PS conjugates for efficient in vivo cancer-specific PDT.
Identification of Genes for Spontaneous Neuropathic Pain in Mice: Whole Genome and Candidate Gene Approaches
Keywords: Autotomy Behaviour
CSF2RB1
ependymal cells
Gene Expression Profiling
Neuropathic Pain
TLR4

Chronic neuropathic pain (NP) affects many people worldwide; causing suffering that is difficult to treat, incurable and not preventable. There is growing hope that pain genetics may identify novel treatment targets. In this dissertation we report on candidate NP genes using a mouse NP model produced by hindpaw denervation. Previous research showed that inbred A/J (A-mice) but not C57BL6/J (B-mice) express highly variable levels of self-mutilation of the denervated hindpaw (`autotomy', a behaviour related to NP). This suggested that genetic and environmental factors interact (GXE) in controlling this variance. Using this NP model in recombinant inbred mice, a region on chromosome-15 (`Pain1') was identified as harbouring autotomy gene(s). Here we report that Csf2rb1, a gene encoding the colony stimulating factor-2Beta1 common receptor of GM-CSF (granulocyte-macrophage colony stimulating factor), and interleukins 3 and 5, is a candidate autotomy gene in Pain1. Up-regulation in Csf2rb1 expression levels in the lumbar spinal cord correlated autotomy levels in denervated A and B mice vs. their na誰ve or sham groups. Csf2rb1-expressing cells were labelled immunohistologically in several CNS structures known to process pain inputs, including spinal dorsal horn, central canal, and select spinal white matter regions, hippocampal dentate gyrus, ventricle linings and periventricular and arcuate hypothalamus nuclei. CSF2RB1 protein levels were increased in spinal cord and brain of denervated A mice expressing autotomy vs. non-autotomizing A and B mice, and vs. their control groups (na誰ve and sham A and B mice). Based on cyto-morphology and co-localization with Vimentin, but not GFAP (astrocytes), OX42 (microglia), NeuN (neurons), MAP2 (neurons), and NG2 (oligodendrocytes) markers, Csf2rb1-expressing cells were identified as ependymal cells/radial glia/tanycytes. Previous studies showed that C3H/HeN mice express significantly more pain behaviour than C3H/HeJ mice in several models. This contrast has been attributed to a mutation in Tlr4 encoding Toll-like receptor-4 in C3H/HeJ mice. We show here that denervated C3H/HeN mice express higher autotomy levels than C3H/HeJ mice. Spinal Csf2rb1 expression levels increased significantly post-denervation in C3H/HeN but not C3H/HeJ mice. Thus, we propose that spontaneous NP behaviour in mice is associated with up-regulated Csf2rb1 and CSF2RB1 levels in the CNS and associated with TLR4 signalling.
Ambiguity Aversion in Algorithmic and High Frequency Trading
Keywords: high frequency trading
mathematical finance
stochastic control

The concept of model uncertainty is one of increasing importance in the field of Mathematical Finance. The main goal of this work is to explore model uncertainty in the specific area of algorithmic and high frequency trading. From a behavioural perspective, model uncertainty naturally leads to the notion of ambiguity aversion - a person's tendency to avoid situations in which randomness plays a role, but the type of randomness itself is uncertain.Electronic trading algorithms rely heavily on stochastic models of relevant variables, and the act of postulating a specific model creates vulnerabilities and risks due to model misspecification. Within the setting of a commonly used model for limit order and market order dynamics, the effects of protecting oneself against such misspecification in both high frequency market making and liquidation scenarios are investigated. In this case, different types of ambiguity aversion are shown to have different effects on optimal behaviour.Further in this work, a new reference model is introduced in order to alleviate some practical issues with the original model. This model results in a highly simplified set of allowable trading behaviours, but introduces powerful predictive elements. This work concludes with another investigation of the effects of ambiguity aversion in the context of this new model.
Decentralized Coordinated Optimal Ramp Metering using Multi-agent Reinforcement Learning
Keywords: Freeway Traffic Control
Function Approximation
Game Theory
Optimal Control
Ramp Metering
Reinforcement Learning

Freeways are the major arteries of the transportation networks. In most major cities in North America, including Toronto, infrastructure expansion has fallen behind transportation demand, causing escalating congestion problems. It has been realized that infrastructure expansion cannot provide a complete solution to congestion problems owed to economic limitations, induced demand, and, in metropolitan areas, simply lack of space. Furthermore, the drop in freeway throughput due to congestion exacerbates the problem even more during rush hours at the time the capacity is needed the most. Dynamic traffic control measures provide a set of cost effective congestion mitigation solutions, among which ramp metering (RM) is the most effective approach. This thesis proposes a novel optimal ramp control (metering) system that coordinates the actions of multiple on-ramps in a decentralized structure. The proposed control system is based on reinforcement learning (RL); therefore, the control agent learn the optimal action from interaction with the environment and without reliance on any a priori mathematical model. The agents are designed to function optimally in both independent and coordinated modes. Therefore, the whole system is robust to communication or individual agent's failure. The RL agents employ function approximation to directly represent states and action with continuous variables instead of relying on discrete state-action tables. Use of function approximation significantly speeds up the learning and reduces the complexity of the RL agents design process. The proposed RM control system is applied to a meticulously calibrated microsimulation model of the Gardiner Expressway westbound in Toronto, Canada. The Gardiner expressway is the main freeway running through Downtown Toronto and suffers from extended periods of congestion every day. It was chosen as the testbed for highlighting the effectiveness of the coordinated RM. The proposed coordinated RM algorithm when applied to the Gardiner model resulted in 50% reduction in total travel time compared with the base case scenario and significantly outperformed approaches based on the well-known ALINEA RM algorithm. This improvement was achieved while the permissible on-ramp queue limit was satisfied.
Sense of Community in Multicultural Blended Learning College Courses and the Relationship to Intercultural Sensitivity
Keywords: blended learning
college
intercultural communication competence
intercultural sensitivity
multicultural
sense of commmunity

This thesis reports findings from an investigation into sense of community developed among 124 students enrolled in 21 blended learning general education courses in one Canadian urban college. Data from an online survey questionnaire, the Classroom Community Scale (CCS), the Intercultural Sensitivity Scale (ISS) and online discussion board contributions were analyzed to identify a detailed demographic profile of participants, their sense of classroom community (SoC) and their intercultural sensitivity (IS). This study expands the use of the CCS and the ISS to a new population, multicultural Canadians. A profile emerged which showed the multicultural mix of this population and the intercultural nature of their daily interactions. Half the participants identified a language other than English as their mother tongue and approximately 25% reported completing some or all of their primary and high school studies outside of Canada. This cohort socialize frequently with linguistically and culturally distinct (LCD) friends, have very high IS and are very confident in their communications with LCD others. Through correlational analyses of the survey responses and content analysis of the discussion board postings, relationships among the demographic, course, ability and intercultural variables and participants' SoC were examined. Participants in this study reported a weak SoC but overall course satisfaction, indicating that SoC may not be as important as previously purported. Discussions focus on the factors that affect SoC, the overlap in the constructs SoC and IS, and the appropriateness of using existing scales in the Canadian context. The findings were interpreted within a theoretical mix of sociocultural theory, situated learning theory, sense of community and intercultural communicative competence theory. Individual's cultural schemas, mindfulness, sensitivity and flexibility in the interaction influence both SoC and IS. Data analyses revealed that IS, language skills, confidence using the discussion board and the frequency of socializing with culturally distinct others were related to SoC. An explanation for these findings may center on the nature of the multicultural cohort. The results of confirmatory factor analyses indicated that the CCS and the ISS may not be appropriate metrics for an interculturally savvy context like urban Canada.
Minding the Gap Between Promise and Performance: The Ontario Liberal Government's Research and Innovation Policy, 2003-2011
Keywords: Ontario
policy networks
research and innovation
research funding
universities

The Ontario Liberal government committed an unprecedented $3 billion between 2003 and 2011 to support research and innovation in order to drive economic growth and prosperity. Premier Dalton McGuinty established Ontario's first Ministry of Research and Innovation and appointed himself the inaugural minister, instantaneously pushing research and innovation to the top of the political agenda. Given the scale of new resources committed, Ontario's research and innovation actors intensified efforts to influence the development of research and innovation policy and secure their share of research and innovation money. This study examines the dynamism of policy development in a sector with a state that demonstrated a strong political will to advance an innovation-oriented agenda, and different groups of societal actors intent on influencing the development of that agenda and its supporting policies and initiatives. Using policy network analysis as an explanatory framework and bearing in mind the power of ideas on policy outcomes, this study explains why Ontario's Ministry of Research and Innovation policy developed the way that it did. The dissertation contends that various research and innovation actors played critical roles in ensuring that the ministry's suite of support programs maintained a supply-side innovation orientation between 2003 and 2007. However, changes in the policy network post-2008 made decision-makers more receptive to demand-side innovation programmatic ideas. And while the government introduced a small number of demand-side innovation initiatives to address recessionary concerns, Ontario's policy mix maintained a supply-side innovation bias. The dissertation identifies the factors that constrained a shift to a more demand-side innovation policy orientation, discusses the adverse impact these policy choices had on the government's efforts to realize its economic goals, and offers policy recommendations on how decision-makers can move forward towards implementing a strategic, integrated, place-based approach to policy development that will drive growth and sustainability.