No / This article explores the need for a framework that will assist social workers to identify when religion and belief are significant in the lives and circumstances of service users and how to take sufficient account of these issues in specific pieces of practice. It outlines the Furness / Gilligan framework and suggests that such frameworks should be used as a part of any assessment, while also being potentially useful at all stages of intervention. It reports on feedback gathered by the authors from first and final MA Social Work students who were asked to pilot the framework. It analyses their responses, in the context of national and international literature. It concludes that such a framework provides the necessary structure and challenge to assist social workers in acknowledging and engaging with issues arising from religion and belief that otherwise may remain overlooked, ignored or avoided, regardless of how significant they are to service users.

This article reports on the findings of questionnaires completed by fifty-seven social work students studying at four universities in northern England and the English midlands. The questionnaires surveyed students' views about the extent to which issues of religion and belief had been discussed in practice settings over a twelve-month period. A range of factors are identified that either encourage or discourage them from considering or exploring religion and belief in their work, in relation to the attitudes of colleagues and service users, themselves and their agencies. Their responses suggest that individual perspectives on and experiences of religion together with the informal views of colleagues determine whether and how religion and belief are acknowledged as significant and relevant. Students reported that few agencies promoted any opportunity for staff development and training in respect of this area, perhaps because issues of religion and belief are not considered important or are given less priority amongst other issues and responsibilities.

As wireless communication systems continue to push the limits of energy and spectral efficiency, increased demands are placed on the capabilities of the receiver. At the same time, the computational resources available for processing received signals will continue to grow. This opens the door for iterative algorithms to play an increasing role in the next generation of communication receivers. In the context of receivers, the goal of iterative probabilistic processing is to approximate maximum a posteriori (MAP) symbol-by-symbol detection of the information bits and estimation of the unknown channel or signal parameters. The sum-product algorithm is capable of efficiently approximating the marginal posterior probabilities desired for MAP detection and provides a unifying framework for the development of iterative receiver algorithms. However, in some applications the sum-product algorithm is computationally infeasible. Specifically, this is the case when both continuous and discrete parameters are present within the model. Also, the complexity of the sum-product algorithm is exponential in the number of variables connected to a particular factor node and can be prohibitive in multi-user and multi-antenna applications. In this dissertation we identify three key problems which can benefit from iterative probabilistic processing, but for which the sum-product algorithm is too complex. They are (1) joint synchronization and detection in multipath channels with emphasis on frame timing, (2) detection in co-channel interference and non-Gaussian noise, and (3) joint channel estimation and multi-signal detection. This dissertation presents the advances we have made in iterative probabilistic processing in order to tackle these problems. The motivation behind the work is to (a) compromise as little as possible on the performance that is achieved while limiting the computational complexity and (b) maintain good theoretical justification to the algorithms that are developed. / Ph. D.

This dissertation consists of two essays that focus on the topics related to asset pricing with jump risks. The first essay explores the effect of disaster risk on the beliefs and portfolio choices of ambiguity-averse agents. With the introduction of Cressie-Read discrepancies, a time-varying pessimism state variable arises endogenously, generating time-varying disaster risk. In the event of a disaster, agents heighten their pessimism, anticipating subsequent disasters to arrive sooner. Within this framework, we deduce optimal consumption and portfolio choices that are robust to model misspecification. Additionally, our measure of pessimism aids in understanding the stylized facts derived from Vanguard’s retail investor survey data, as reported in Giglio et al. (2021). In the second essay, I construct a novel measure to assess the impact of macro announcements on investors’ risk expectations using S&P 500 index and Treasury futures options. This measure corrects the systematic downward jumps in the option- implied variance measure and isolates innovations of investors’ risk expectations after macro-announcements. Applied to key economic releases, including FOMC meetings, GDP, PPI, and Employment data announcements, this measure reveals that macro announcements significantly increase investors’ risk expectations compared to pre-announcement levels. Furthermore, I show investor sentiment significantly declines following macro-announcements with heightened risk expectations, and tail risk positively correlates with risk expectations.

The normative foundation (axioms) of Bayesian belief updating has long been established in the literature of decision science. However, psychology and experiments suggest that while rational decision making is ideal, it is rarely achievable for ordinary people. Therefore, it is important to explore the foundations and consequences of rational decision making within the field of economics. This thesis involves three papers on this. In the first paper, I explore the consequences of wishful thinking on mechanism design. It suggests that wishful thinking bias could be profit-generating for mechanism designers. In the second paper, I investigate conservative updating and provide a foundation for it. The main behavioral axiom, ``conservative consistency," suggests that decision-makers may partially incorporate information, particularly when it requires them to revise their previous preferences (the preferences order according to their prior belief). In the third paper, I reframe the model selection problem as a rational decision-making problem. The decision-maker is restricted to choosing an advisor to delegate their choices. I explore the conditions under which a rational decision-maker selects models (or advisors) according to Bayes factor criteria. / Doctor of Philosophy / Most of us do not always make decisions completely rational. This thesis digs into how irrational decision-making fits into economics, with three papers to break it down. The first paper looks at wishful thinking and how it affects our decisions. It suggests that if we understand our biases, we can design better mechanism to generate profit. The second paper talks about conservative updating, which is all about how we pick and choose what information matters, especially when it clashes with our existing belief. Lastly, the third paper explores how we choose advisors to help us make decisions. It looks at when it is smart to pick based on Bayes factor criteria. Through these papers, this thesis helps us understand how rational decision-making plays out in real-life economics.

We propose sparse-matrix belief propagation, which executes loopy belief propagation in Markov random fields by replacing indexing over graph neighborhoods with sparse-matrix operations. This abstraction allows for seamless integration with optimized sparse linear algebra libraries, including those that perform matrix and tensor operations on modern hardware such as graphical processing units (GPUs). The sparse-matrix abstraction allows the implementation of belief propagation in a high-level language (e.g., Python) that is also able to leverage the power of GPU parallelization. We demonstrate sparse-matrix belief propagation by implementing it in a modern deep learning framework (PyTorch), measuring the resulting massive improvement in running time, and facilitating future integration into deep learning models. / Master of Science / We propose sparse-matrix belief propagation, a modified form of loopy belief propagation that encodes the structure of a graph with sparse matrices. Our modifications replace a potentially complicated design of indexing over graph neighborhoods with more optimized and easily interpretable sparse-matrix operations. These operations, available in sparse linear algebra libraries, can also be performed on modern hardware such as graphical processing units (GPUs). By abstracting away the original index-based design with sparse-matrices it is possible to implement belief propagation in a high-level language such as Python that can also use the power of GPU parallelization, rather than rely on abstruse low-level language implementations. We show that sparse-matrix belief propagation, when implemented in a modern deep learning framework (PyTorch), results in massive improvements irunning time when compared against the original index-based version. Additionally this implementation facilitates future integration into deep learning models for wider adoption and use by data scientists.

Thesis (D.N.S.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / This study investigated of the capacity of self-efficiency (SE) and the Health Belief Model (HBM) to predict diabetes self care. Research questions derived from Bandura's Social Cognitive Theory asked the associations between SE, HBM, and their interaction on reported self care (SC). / 2999-01-01

Accurate and efficient localization of facial features is a crucial first step in many face-related computer vision tasks. Some of these tasks include, but not limited to: identity recognition, expression recognition, and head-pose estimation. Most effort in the field has been exerted towards developing better ways of modeling prior appearance knowledge and image observations. Modeling prior shape knowledge, on the other hand, has not been explored as much. In this dissertation I primarily focus on the limitations of the existing methods in terms of modeling the prior shape knowledge. I first introduce a new pose-constrained shape model. I describe my shape model as being "highly flexible yet sufficiently strict". Existing pose-constrained shape models are either too strict, and have questionable generalization power, or they are too loose, and have questionable localization accuracies. My model tries to find a good middle-ground by learning which shape constraints are more "informative" and should be kept, and which ones are not-so-important and may be omitted. I build my pose-constrained facial feature localization approach on this new shape model using a probabilistic graphical model framework. Within this framework, observed and unobserved variables are defined as the local image observations, and the feature locations, respectively. Feature localization, or "probabilistic inference", is then achieved by nonparametric belief propagation. I show that this approach outperforms other popular pose-constrained methods through qualitative and quantitative experiments. Next, I expand my pose-constrained localization approach to unconstrained setting using a multi-model strategy. While doing so, once again I identify and address the two key limitations of existing multi-model methods: 1) semantically and manually defining the models or "guiding" their generation, and 2) not having efficient and effective model selection strategies. First, I introduce an approach based on unsupervised clustering where the models are automatically learned from training data. Then, I complement this approach with an efficient and effective model selection strategy, which is based on a multi-class naive Bayesian classifier. This way, my method can have many more models, each with a higher level of expressive power, and consequently, provides a more effective partitioning of the face image space. This approach is validated through extensive experiments and comparisons with state-of-the-art methods on state-of-the-art datasets. In the last part of this dissertation I discuss a particular application of the previously introduced techniques; facial feature localization in unconstrained videos. I improve the frame-by-frame localization results, by estimating the actual head-movement from a sequence of noisy head-pose estimates, and then using this information for detecting and fixing the localization failures. / text

Tidigare studier har påvisat att språkliga förmågor har ett nära samband med Theory of Mind (ToM). På senare tid har studier med hjälp av ögonrörelseteknik kunnat undersöka ToMförmåga implicit och fynden tyder på att barn redan i tvåårsåldern verkar ha en välutvecklad implicit ToM-förmåga. Resultaten från en av dessa studier har funnit att språkutvecklingen kan spela en avgörande roll i tillägnandet av ToM och tyder på att det kan finnas ett orsakssamband mellan språk och ToM. En viktig aspekt för att närmare förstå ToMutvecklingen är att undersöka vilken betydelse den språkliga förmågan har i tillägnandet av ToM. Det är fortfarande oklart om specifika delar av språket har mer betydelse för ToMutvecklingen än andra och hur sambandet mellan språkliga förmågor och ToM ser ut. Syftet med föreliggande studie var att undersöka hur ToM-förmåga och False Beliefförståelse förhåller sig till språkliga förmågor hos typiskt utvecklade barn i treårsåldern samt om dessa förmågor påverkas av barnens demografiska faktorer. Studien inkluderade sammanlagt 21 treåringar. Den språkliga förmågan undersöktes med mått på impressiv och expressiv grammatik samt med mått på expressivt ordförråd, som en del av den semantiska förmågan. För att undersöka ToM-förmågan som helhet användes mått på olika delförmågor av ToM. Vidare undersöktes False Belief-förståelse explicit, med klassiska FB-uppgifter, och implicit, med hjälp av ögonrörelseteknik.Studiens resultat påvisar att språkliga förmågor och ToM-förmåga har ett mycket nära samband, och att den semantiska förmågan är den del av språkförmågan som har den enskilt starkaste påverkan på ToM-förmågan. Resultaten visar även att den impressiva grammatiska förmågan är mer betydande specifikt för FB-förståelse än för ToM-förmågan som helhet. Ingen påverkan på språklig förmåga, ToM-förmåga och FB-förståelse hittades vad gäller barnens demografiska faktorer. Resultaten av det implicita FB-testet visar att majoriteten av de deltagande barnen inte har förstått vad testet går ut på och därför kan inga slutsatser dras vad gäller barnens implicita FB-förståelse. Detta resultat motsäger den tidigare forskningen med yngre barn. Många frågetecken kvarstår kring implicita test, vilket visar på vikten av mer forskning inom området. I den aktuella studien diskuteras även komplexiteten i förhållandet mellan språkliga förmågor och ToM. / Previous studies have shown that linguistic abilities are closely linked with Theory of Mind (ToM). Recently, studies using eyetracking technology have been able to investigate ToM understanding with implicit measures. The findings suggest that children as young as two years old appear to have a well-developed implicit ToM understanding. Results from one of these studies have found that language development could play a crucial role in the acquisition of ToM, suggesting that there may be a causal link between language and ToM. An important aspect to further understand ToM development is to investigate the impact of language in the acquisition of ToM understanding. It remains unclear whether specific aspects of language are more relevant to ToM development than others and how language abilities and ToM are interconnected. The aim of the present study was to investigate how ToM ability and False Belief understanding relates to linguistic abilities of typically developing three-year-olds and if childrens´ demographic factors affect these abilities. The study included a total of 21 children.  Language competence was assessed with measures of reception and production of syntax and a measure of vocabulary production, as part of the semantic ability. In order to investigate ToM ability, measures of different types of mental-state understandings were included. False Belief understanding was assessed with explicit measures, using standard FB tasks, and with implicit measures, using eyetracking technology. The results obtained in the present study confirm that linguistic abilities and ToM ability are strongly related, and that semantic ability is the part of language that has the strongest influence on ToM understanding. The results also indicate that receptive syntax is more important to specifically FB understanding, than to ToM ability in general. The childrens´ demographic factors were not found to affect their language ability, ToM ability or FB understanding. Regarding children's implicit FB understanding the results of the implicit measures reveal that the majority of the participating children did not understand the purpose of the test and therefore no conclusions of their implicit understanding could be drawn. This finding contradicts previous research including younger children. Questions remain concerning implicit measures, indicating the importance of further research in this field. The present study also discusses the complexity of the relationship between linguistic abilities and ToM.

From the viewpoint of the public, academic work is relatively autonomous, stable, and stress-free as opposed to other professions. However, as the societal environment evolves, high satisfaction is no more an absolute consequence of academic work. Even in comparison to other professionals, the academics experienced longer working hours and heavier occupational stress; hence the events of ¡§Karoshi¡¨ among university academics happened from time to time. Actually, the reason resulting in ¡§Karoshi¡¨ has been proved related to health behavior, and the health behavior also has been proved associated with health belief. Following this concept, a study based upon ¡§health belief model¡¨ was carried out to investigate the health belief, health behavior, and health status of university academics, respectively, and the possible relationships among the aforementioned health related concepts. In total, 4,000 subjects were selected from among the 43,050 or so university academics nationwide based on stratified sampling approach. Data were collected through survey questionnaires which include personal demographics, health belief, health behavior, and health status information. From June through August 2004, 1,778 questionnaires returned with a response rate of 44.45%. SPSS was used for descriptive analysis and basic hypothesis test, and then the software package AMOS was used for structural equation modeling examination. Compared to the general population with the same age, the health status of university academics was worse in both physical and psychological function. Further, it was found that the factor work significantly contributed to each component of health belief (i.e. perceived susceptibility, perceived seriousness, perceived barriers, and perceived benefits). In terms of health behavior, although the academics had no unhealthy habits (i.e. smoking or excessive drinking), the average working hour after 10 pm was more than one hour and one in three teachers didn¡¦t take exercise regularly, which altogether are definitely harmful to health. The structural equation modeling showed that an academic¡¦s health belief would influence his/her health behavior and then influence the health status indirectly. In other words, positive health belief will lead to healthy status in the long run, and negative health belief will conduce to unhealthy status. To sum up, the issue on improving the health status of academics is on edge and the responsibility for taking this issue would be shouldered by teamwork¡X individuals, educational authorities, and public health agencies. An academic should try his/her best to improve the health; the educational authorities should assess the job loading on academic population from time to time and draw up a better educational system; and finally, the public health agency should play the role of information disseminator and catalyst for strengthening the health belief and then improving the health behavior and health status among the academics.