Despite strong evidence that screening for Colorectal cancer (CRC) can reduce cancer incidence and mortality, screening adherence remains low. Racial differences in CRC incidence and mortality are well documented in the literature. Racial differences in CRC screening use remain mixed with most studies using race as an independent variable and focusing on racial differences in CRC screening rates. Few studies have examined correlates of CRC screening use, stratifying by race. The purpose of this study was to determine if there are racial differences in correlates of CRC screening, using the Health Belief Model as the theoretical framework. Data analyzed in this study came from the 2003 Health Information National Trends Survey (HINTS) of the National Cancer Institute. White (n=1988) and non-white (562) respondents age ≥50 years, without a history of cancer were interviewed by phone. Multivariable logistic regression was used to identify correlates of FOBT and endoscopy adherence stratified by race and screening test. Independent variables included age, gender, education, income, insurance status, regular care visit frequency, perceived risk of CRC, family history of cancer, CRC knowledge, cancer worry, perceptions of screening benefits, and perceptions of expense as a barrier. Predictors of adherence to FOBT for whites included being older and having at least 1 regular car visit. Predictors of FOBT adherence for non-whites included having health insurance. Endoscopy adherence for whites was significantly associated with being older, being female, and agreeing with perceptions of benefits to CRC screening. Predictors of endoscopy adherence for non-whites included being older, and disagreeing with perceptions of benefits to CRC screening. Such differences, if confirmed in future studies, may inform race-specific interventions to increase CRC screening utilization.

Using a sample of 51 banking organizations, I examine the effect of the Statement of Financial Accounting Standard 133 on the belief heterogeneity of market participants and how this heterogeneity affects abnormal trading volume surrounding earnings announcements. SFAS 133 is the first standard to require that all derivatives be recognized at fair-value and that the fluctuations in derivative fair-values be reported in either net income or other comprehensive income. The behavior of derivative instruments and the fair-valuation and treatment prescribed by SFAS 133 are complex. Due to the underlying complexity of both derivatives and the accounting treatment prescribed by the SFAS 133 standard, I expect that investors may have differing interpretations of the newly provided information. My hypothesis is that the income effects arising from the fair-value accounting for derivatives (SFAS 133) are associated with an increase in differing beliefs among individuals. I find that the income effects of SFAS 133 are significantly and positively related to belief heterogeneity among investors. The net income and other comprehensive income effects of SFAS 133 are significantly and positively related to increasing levels of abnormal trading volume surrounding earnings announcements. Additionally, levels of SFAS 133 net income is positively and significantly associated with three measures of belief heterogeneity derived from analysts’ forecasts. In an extended analysis I model the SFAS 133 income effects on abnormal volume using the three belief heterogeneity measures as the conduit. I find support for two of the three heterogeneity measures acting as a conduit for the effect of the SFAS 133 related income measures on abnormal volume. The results of this study indicate that, while the recognized fair-value of derivatives is value relevant to equity prices (Ahmed, Kilic, & Lobo, 2006), the income effects of the same financial standard causes heterogeneity in beliefs about the firm. This suggests that, at least in the case of derivative fair-values, there exists a trade-off between value relevance and the strength of consensus surrounding beliefs in the market.

Le résumé en français n'a pas été communiqué par l'auteur. / This paper studies firms’ disclosure decisions of product information in a duopoly setting, as well as the welfare implication of compulsory disclosure policy. I show that there is a problem of externality between the two firms: even if disclosure weakens price competition in the market and increases total industry profits, a firm could have incentive not to disclose product information because it decreases his market share. As a result, regulatory policy could increase total industry profits as it could rectify the problem of externality. Therefore, despite more information allows consumers to make a better choice between different alternatives, it might backfire as it could increase the average price in the market. I also present simple conditions on when providing more information could harm consumers, and when it will improve consumer welfare. This paper studies the information processing behavior of a decision maker (DM) who has limited information processing ability. More specifically, the DM can process only a subset of all available information. Before taking an action, he chooses whether to process or ignore signals about the state of the world which he receives sequentially. I show that at the optimum, the DM processes only signals which are strong enough, but will process a weaker signal if it confirms his existing strong belief or if it supports a much more desirable state of the world. This explains some phenomena which have been well documented in the psychology literature, such as preference for strong signals, confirmation bias for individuals with strong prior and wishful thinking. Moreover, I analyze how the Internet, and in general changes in information structures, affects the processing behavior of the DM. The results shed light on different issues in the information era, including polarization and media strategy. This paper studies experimentally whether confirmation bias arises when individuals are exposed to information overload, or equivalently have limited ability to perfectly update their belief with all available information. In our experiment, subjects have to form beliefs as they navigate a sequence of signals within a limited period of time. We compare belief formation under two settings, where the treatment setting imposes a larger information/cognitive load than the control setting. We find that subjects in the treatment setting exhibit a stronger confirmation bias than those in the control setting. Upon receiving a belief-challenging signal, subjects in the treatment group update their belief less than those in the control group. In contrast, upon receiving a belief-confirming signal, subjects update similarly in both settings. As a result, subjects in the treatment setting are also less likely to switch sides: once they believe that one state is more probable than another, they are less likely to switch even if they receive enough belief-challenging signals. Not only do these results show that the limited ability of information processing plays a role in the formation of confirmation bias, they also improve our understanding on the impact of information overload, for example on polarization.

Thesis advisor: James E. Anderson / Thesis advisor: Rosen Valchev / The effect of uncertainty on firms' behavior and on the macroeconomy is generally negative in the literature. Extensive research has also demonstrated that financial frictions limit the extent of firms' activities and growth prospects. In the first two chapters of this dissertation, I study both empirically and theoretically how a specific type of uncertainty, exchange rate uncertainty, interacts with financial frictions to affect the behavior of exporting firms. In line with the existing literature, I find in the first chapter that exports of manufacturing sectors in which firms are more financially constrained decrease by more in times of high uncertainty. Having more tangible capital, which can potentially be used as collateral, makes the effect of uncertainty less negative, especially im sectors where firms are large. Relying more on external financing, on the other hand, makes the effect more negative and affects sectors with small firms more. Current theoretical models have little to say about the effect of uncertainty on heterogeneous firms. To address this issue, I introduce in the second chapter a model of financially-constrained heterogeneous exporting firms in which credit conditions depend on the degree of exchange rate uncertainty. Firms in different sectors face different types of financial constraints, and are therefore differently affected by uncertainty. I use the calibrated model to evaluate potential policies that could be implemented to alleviate the negative effect of exchange rate uncertainty on exports. The uncovered interest parity puzzle is the empirical finding that countries with higher risk-free interest rates tend to see their currencies appreciate in the short run. Typical two-country macroeconomic models instead predict that high interest-rate currencies depreciate, with arbitrage opportunities eliminating profitable carry trade strategies. The international finance literature responded to this puzzle by providing several alternative theoretical models able to explain the puzzle. In the third chapter of this dissertation, I study how the predictions of two of these alternative models - the habit model of Verdelhan (2010) and the distorted belief model of Gourinchas and Tornell (2004) - are affected when re-cast in a standard dynamic stochastic general equilibrium framework. I investigate how the mechanisms rely on specific parameter values in order to find under which conditions, if any, they can explain the UIP puzzle. In addition, I obtain business cycle moments from model simulations and compare them to the moments obtained from a standard two-country DSGE model and from the data. My results show that for the first model, the habit model, the UIP results disappear under realistic calibrations. For the second model, the distorted beliefs model, UIP properties remain under some calibrations. In addition, business cycle predictions remain close to empirical evidence. / Thesis (PhD) — Boston College, 2019. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Economics.

This thesis aims to shed light on the role of religious, spiritual and secular beliefs in individuals’ recovery from problematic substance use in Scotland. The findings are based on semi-structured interviews with twenty individuals, living in Scotland, who had past experience of problematic substance use. The methodology was influenced by narrative theory and the analysis drew on a thematic narrative approach. It is suggested that individuals in recovery construct personal belief systems by drawing chiefly on established cultural belief systems. Personal belief systems are learned and reinforced through practice, notably, engaging with belief-orientated communities and practising personal rituals. Participants use their personal belief systems as frameworks to interpret and give meaning to fundamental experiences that were part of their recovery. Personal belief systems are also integral to the construction of identity in recovery, helping individuals to establish a new self or reclaim an idealised past self. While personal belief systems did not often fit within neat religious, spiritual or secular categories, those with religious and/or spiritual beliefs often stressed the importance of their beliefs and associated practices to their recovery. Secular existential beliefs were also important to some people. The implications of these findings are discussed in terms of research, policy and practice.

Belief Revision addresses the problem of how to change epistemic states, usually represented in the literature by sets of logical sentences. Solid theoretical results were consolidated with the AGM paradigm, which deals with theories (logically closed sets of sentences). After that, the theory was extended to belief bases, that is, arbitrary sets of sentences. Besides all this theoretical framework, AI researchers face serious difficulties when trying to implement belief revision systems. One of the major complications is the closure required by AGM theory, which cannot be easily computed. Even belief bases, which do not require closure, seem to be improper for practical purposes, since their changes are usually very rigid (syntax dependent). Some operations, known as pseudo-contractions, are in the middle ground between belief set change and belief base change. In the present work we have proposed a new pseudo-contraction operation, studied its properties and characterized it. We have also found connections between this operator and some other pseudo-contractions. / Revisão de Crenças aborda o problema de como alterar estados epistêmicos, normalmente representados na literatura como conjuntos de sentenças lógicas. Resultados teóricos sólidos foram consolidados com o paradigma AGM, que lida com teorias (conjuntos de sentenças logicamente fechados). Depois disso, a teoria foi estendida para bases de crenças, isto é, conjuntos arbitrários de sentenças. Apesar de todo esse arcabouço teórico, pesquisadores de IA enfrentam sérias dificuldades ao tentar implementar sistemas de revisão de crenças. Uma das maiores complicações é o fecho exigido pela teoria AGM, que não pode ser facilmente computado. Mesmo bases de crenças, que não exigem fechamento, parecem ser impróprias para fins práticos, pois suas alterações são geralmente muito rígidas (dependentes de sintaxe). Algumas operações, conhecidas como pseudo-contrações, estão no meio do caminho entre mudanças para conjuntos de crenças e mudanças para bases de crenças. Nesse trabalho, propomos uma nova operação de pseudo-contração, estudamos suas propriedades e a caracterizamos. Também encontramos conexões entre esse operador e algumas outras pseudo-contrações.

A presente dissertação trata das crenças e representações de alunos e professores de língua estrangeira como fatores que interferem no processo de ensino/aprendizagem. O trabalho resulta de uma pesquisa de cunho qualitativo na qual foram utilizadas como base teórica as noções de crença e de reprodução cultural, de Bourdieu, e o conceito de representação, de Chartier. O enfoque do tema também considerou as contribuições teóricas em aquisição e aprendizagem de línguas. Foi empregada na pesquisa a metodologia etnográfica, incluindo observação participante e elaboração de notas de campo. A análise do material produzido durante as atividades da pesquisa aponta para a importância da explicitação das crenças e representações em jogo no processo de ensino/aprendizagem de língua estrangeira, como mais um recurso para o professor no processo de reflexão sobre sua prática e solução de problemas didáticos. / The present dissertation discusses beliefs and representations of foreign language students and teachers as factors which interfere with teaching and learning processes. The work stems from a qualitative research project in which Bourdieu´s notions of belief and cultural reproduction, as well as Chartier´s concept of representation, were used as theoretical bases. The theme focus has also taken into account theoretical contributions related to language acquisition and learning. Ethnographic methodology was employed, which included in-class participative observation and elaboration of field notes. Analysis of material produced during research activities points out the importance of explicitness of those beliefs and representations in play at foreign language teaching and learning processes, as they constitute one more set of resources to teachers within their reflection process about practices and solutions to didactical issues.

Mao, Yina. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 67-73). / Abstracts in English and Chinese. / List of Tables --- p.2 / List of Figures --- p.3 / Abstract --- p.4 / 摘要 --- p.5 / Acknowledgement --- p.6 / Chapter 1. --- Introduction --- p.7 / Chapter 2. --- Theories and hypotheses --- p.10 / Chapter 2.1 --- actors and third parties --- p.10 / Chapter 2.1.1 --- Belief in a just world --- p.10 / Chapter 2.1.2 --- Threat to the belief in a just world --- p.13 / Chapter 2.1.3 --- Maintenance of the belief in a just world --- p.14 / Chapter 2.1.4 --- Current research focus and the research gap --- p.15 / Chapter 2.1.5 --- Actors and third parties --- p.17 / Chapter 2.1.6 --- Hypothesis development --- p.22 / Chapter 2.2. --- Heuristic cues --- p.27 / Chapter 2.3 --- Multiple strategies --- p.29 / Chapter 2.3.1 --- Co-occurrence of strategies --- p.29 / Chapter 3. --- Method --- p.37 / Chapter 3.1 --- Research design --- p.37 / Chapter 3.2 --- Scenarios --- p.38 / Chapter 3.3 --- Pilot study --- p.40 / Chapter 3.3.1 --- Measurements --- p.40 / Chapter 3.3.2 --- Description of the sample --- p.43 / Chapter 3.3.3 --- Analysis --- p.43 / Chapter 3.3.4 --- Adjustments --- p.45 / Chapter 3.4 --- Power analysis --- p.45 / Chapter 3.5 --- Main study --- p.47 / Chapter 3.6 --- results --- p.48 / Chapter 4. --- Conclusions and implications --- p.58 / References --- p.67 / Appendix: Questionnaire used in this study (Chinese version) based on scenario 1 --- p.74

"In modern wireless communication systems, intersymbol interference (ISI) introduced by frequency selective fading is one of the major impairments to reliable data communication. In ISI channels, the receiver observes the superposition of multiple delayed reflections of the transmitted signal, which will result errors in the decision device. As the data rate increases, the effect of ISI becomes severe. To combat ISI, equalization is usually required for symbol detectors. The optimal maximum-likelihood sequence estimation (MLSE) based on the Viterbi algorithm (VA) may be used to estimate the transmitted sequence in the presence of the ISI. However, the computational complexity of the MLSE increases exponentially with the length of the channel impulse response (CIR). Even in channels which do not exhibit significant time dispersion, the length of the CIR will effectively increase as the sampling rate goes higher. Thus the optimal MLSE is impractical to implement in the majority of practical wireless applications. This dissertation is devoted to exploring practically implementable symbol detectors with near-optimal performance in wireless ISI channels. Particularly, we focus on the design and implementation of an iterative detector based on the belief propagation (BP) algorithm. The advantage of the BP detector is that its complexity is solely dependent on the number of nonzero coefficients in the CIR, instead of the length of the CIR. We also extend the work of BP detector design for various wireless applications. Firstly, we present a partial response BP (PRBP) symbol detector with near-optimal performance for channels which have long spanning durations but sparse multipath structure. We implement the architecture by cascading an adaptive linear equalizer (LE) with a BP detector. The channel is first partially equalized by the LE to a target impulse response (TIR) with only a few nonzero coefficients remaining. The residual ISI is then canceled by a more sophisticated BP detector. With the cascaded LE-BP structure, the symbol detector is capable to achieve a near-optimal error rate performance with acceptable implementation complexity. Moreover, we present a pipeline high-throughput implementation of the detector for channel length 30 with quadrature phase-shift keying (QPSK) modulation. The detector can achieve a maximum throughput of 206 Mb/s with an estimated core area of 3.162 mm^{2} using 90-nm technology node. At a target frequency of 515 MHz, the dynamic power is about 1.096 W. Secondly, we investigate the performance of aforementioned PRBP detector under a more generic 3G channel rather than the sparse channel. Another suboptimal partial response maximum-likelihood (PRML) detector is considered for comparison. Similar to the PRBP detector, the PRML detector also employs a hybrid two-stage scheme, in order to allow a tradeoff between performance and complexity. In simulations, we consider a slow fading environment and use the ITU-R 3G channel models. From the numerical results, it is shown that in frequency-selective fading wireless channels, the PRBP detector provides superior performance over both the traditional minimum mean squared error linear equalizer (MMSE-LE) and the PRML detector. Due to the effect of colored noise, the PRML detector in fading wireless channels is not as effective as it is in magnetic recording applications. Thirdly, we extend our work to accommodate the application of Advanced Television Systems Committee (ATSC) digital television (DTV) systems. In order to reduce error propagation caused by the traditional decision feedback equalizer (DFE) in DTV receiver, we present an adaptive decision feedback sparsening filter BP (DFSF-BP) detector, which is another form of PRBP detector. Different from the aforementioned LE-BP structure, in the DFSF-BP scheme, the BP detector is followed by a nonlinear filter called DFSF as the partial response equalizer. In the first stage, the DFSF employs a modified feedback filter which leaves the strongest post-cursor ISI taps uncorrected. As a result, a long ISI channel is equalized to a sparse channel having only a small number of nonzero taps. In the second stage, the BP detector is applied to mitigate the residual ISI. Since the channel is typically time-varying and suffers from Doppler fading, the DFSF is adapted using the least mean square (LMS) algorithm, such that the amplitude and the locations of the nonzero taps of the equalized sparse channel appear to be fixed. As such, the channel appears to be static during the second stage of equalization which consists of the BP detector. Simulation results demonstrate that the proposed scheme outperforms the traditional DFE in symbol error rate, under both static channels and dynamic ATSC channels. Finally, we study the symbol detector design for cooperative communications, which have attracted a lot of attention recently for its ability to exploit increased spatial diversity available at distributed antennas on other nodes. A system framework employing non-orthogonal amplify-and-forward half-duplex relays through ISI channels is developed. Based on the system model, we first design and implement an optimal maximum-likelihood detector based on the Viterbi algorithm. As the relay period increases, the effective CIR between the source and the destination becomes long and sparse, which makes the optimal detector impractical to implement. In order to achieve a balance between the computational complexity and performance, several sub-optimal detectors are proposed. We first present a multitrellis Viterbi algorithm (MVA) based detector which decomposes the original trellis into multiple parallel irregular sub-trellises by investigating the dependencies between the received symbols. Although MVA provides near-optimal performance, it is not straightforward to decompose the trellis for arbitrary ISI channels. Next, the decision feedback sequence estimation (DFSE) based detector and BP-based detector are proposed for cooperative ISI channels. Traditionally these two detectors are used with fixed, static channels. In our model, however, the effective channel is periodically time-varying, even when the component channels themselves are static. Consequently, we modify these two detector to account for cooperative ISI channels. Through simulations in frequency selective fading channels, we demonstrate the uncoded performance of the DFSE detector and the BP detector when compared to the optimal MLSE detector. In addition to quantifying the performance of these detectors, we also include an analysis of the implementation complexity as well as a discussion on complexity/performance tradeoffs."

"A comprehensive analysis of a novel detection scheme for SISO wireless transmission scenarios is presented in this dissertation. The scheme, which is based on Belief-Propagation (BP) detectors, is evaluated in both a computer simulation environment and a custom-built software-defined radio test-bed. In this dissertation, we address the design aspects of BP-based receivers, including several approaches to minimize the bit error rate of MAP detectors. We also present the development of an interface framework for a software defined radio platform that aims to implement complex communication transceivers capable of prototyping the hybrid structure with a pre-filter filter and BP detector. Numerical simulations compared the proposed schemes with an existing approaches and showed significant performance gains without requiring great computational cost at the receiver. Furthermore, experiments using GNU Radio Companion and the FMCOMMS software defined radio hardware platform confirm the correct functionality of the proposed interface, and stress tests are conducted to assess the functionality of the interface and how it deteriorates across a range of operating conditions. Finally, we present several experiments using the FMCOMMS software defined radio platform that implement the proposed BP-based receiver scheme and discuss its capabilities and limitations."