Thesis (Ed.D.)--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. / The use of data by school counselors has grown increasingly important over the past few years, and has a prominent place in the American School Counselor Association's National Model for School Counseling Programs (ASCA, 2003). This study examines the effect and effectiveness of four variations of a workshop designed to improve school counselors' data use skills. The workshops were designed to vary along two dimensions; the amount of conceptual knowledge participants were exposed to, and the amount of a technology application participants were exposed to. The technology application, dubbed "EZAnalyze," was developed specifically for use in this study, as no suitable technology tools existed. The quantitative results of the study indicate that being exposed to technology did not have a statistically significant impact. The qualitative results indicate lack of time and knowledge were the most prominent barriers to applying what was learned during the workshop, and technology and access to useful data were the most prominent facilitators of data use. / 2031-01-02

Geosynthetic reinforced soil (GRS) is a soil improvement technology in which closely spaced horizontal layers of geosynthetic are embedded in a soil mass to provide lateral support and increase strength. GRS is popular due to a relatively new application for bridge support, as well as long-standing application in mechanically stabilized earth walls. Several different GRS design methods have been used, and some are application-specific and not based on fundamental principles of mechanics. Because consensus regarding fundamental behavior of GRS is lacking, numerical and mathematical analyses were performed for laboratory tests obtained from the published literature of GRS under triaxial compression in consolidated-drained conditions. A three-dimensional numerical model was developed using FLAC3D. An existing constitutive model for the soil component was modified to incorporate confining pressure dependency of friction angle and dilation parameters, while retaining the constitutive model's ability to represent nonlinear stress-strain response and plastic yield. Procedures to obtain the parameter values from drained triaxial compression tests on soil specimens were developed. A method to estimate the parameter values from particle size distribution and relative compaction was also developed. The geosynthetic reinforcement was represented by two-dimensional orthotropic elements with soil-geosynthetic interfaces on each side. Comparisons between the numerical analyses and laboratory tests exhibited good agreement for strains from zero to 3% for tests with 1 to 3 layers of reinforcement. As failure is approached at larger strains, agreement was good for specimens that had 1 or 2 layers of reinforcement and soil friction angle less than 40 degrees. For other conditions, the numerical model experienced convergence problems that could not be overcome by mesh refinement or reducing the applied loading rate; however, it appears that, if convergence problems can be solved, the numerical model may provide a mechanics-based representation of GRS behavior, at least for triaxial test conditions. Three mathematical theories of GRS failure available in published literature were applied to the laboratory triaxial tests. Comparisons between the theories and the tests results demonstrated that all three theories have important limitations. These numerical and mathematical evaluations of laboratory GRS tests provided a basis for recommending further research. / Ph. D.

Theoretical procedures are developed to account for the effect of emotion and perception in strategic conflict. The <em>possibility principle</em> facilitates modeling the effects of emotions on future scenarios contemplated by decision makers; <em>perceptual graph models</em> and a <em>graph model system</em> permit the decision makers (DMs) to experience and view the conflict independently; and <em>perceptual stability analysis</em>, which is based on individual- and meta-stability analysis techniques, is employed in analyzing graph model systems when the DMs have inconsistent perceptions. These developments improve the methodology of the Graph Model for Conflict Resolution by reconciling emotion, perception, and strategy to make predictions consistent with the actual unfolding of events. <br /><br /> Current research in neuroscience suggests that emotions are a necessary component of cognitive processes such as memory, attention, and reasoning. The somatic marker hypothesis, for example, holds that feelings are necessary to reasoning, especially during social interactions (Damasio, 1994, 2003). Somatic markers are memories of past emotions: we use them to predict future outcomes. To incorporate the effect of emotion in conflict, the underlying principle of Damasio?s hypothesis is used in developing the possibility principle, which significantly expands the paradigm of the Graph Model for Conflict Resolution of Fang, Hipel, and Kilgour (1993). <br /><br /> State identification is a crucial step in determining future scenarios for DMs. The possibility principle is integrated into the modeling stage of the Graph Model by refining the method of determining feasible states. The possibility principle enables analysts and DMs to include emotion in a conflict model, without sacrificing the parsimonious design of the Graph Model methodology, by focusing attention on two subsets of the set of feasible states: <em>hidden</em> and <em>potential</em> states. Hidden states are logically valid, feasible states that are invisible because of the presence of negative emotions such as anger and fear; potential states are logically valid, feasible states that are invisible because of missing positive emotions. Dissipating negative emotions will make the hidden states visible, while expressing the appropriate positive emotions will make the potential states visible. The possibility principle has been applied to a number of real world conflicts. In all cases, eliminating logically valid states not envisioned by any DM simplifies a conflict model substantially, expedites the analysis, and makes it an intuitive and a realistic description of the DMs' conceptualizations of the conflict. <br /><br /> A fundamental principle of the Graph Model methodology is that all DMs' directed graphs must have the same set of feasible states, which are integrated into a <em>standard</em> graph model. The possibility principle may modify the set of feasible states perceived by each DM according to his or her emotion, making it impossible to construct a single standard graph model. When logically valid states are no longer achievable for one or more DMs due to emotions, the apprehension of conflict becomes inconsistent, and resolution may become difficult to predict. Therefore, reconciling emotion and strategy requires that different apprehensions of the underlying decision problem be permitted, which can be accomplished using a perceptual graph model for each DM. A perceptual graph model inherits its primitive ingredients from a standard graph model, but reflects a DM's emotion and perception with no assumption of complete knowledge of other DMs' perceptions. <br /><br /> Each DM's perceptual graph model constitutes a complete standard graph model. Hence, conclusions drawn from a perceptual graph model provide a limited view of equilibria and predicted resolutions. A graph model system, which consists of a list of DMs' perceptual graph models, is defined to reconcile perceptions while facilitating conclusions that reflect each DM's viewpoint. However, since a DM may or may not be aware that other graph models differ from his or her own, different variants of graph model systems are required to describe conflicts. Each variant of graph model system corresponds to a configuration of awareness, which is a set of ordered combinations of DMs' viewpoints. <br /><br /> Perceptual stability analysis is a new procedure that applies to graph model systems. Its objective is to help an <em>outside</em> analyst predict possible resolutions, and gauge the robustness and sustainability of these predictions. Perceptual stability analysis takes a two-phase approach. In Phase 1, the stability of each state in each perceptual graph model is assessed from the point of view of the owner of the model, for each DM in the model, using standard or perceptual solution concepts, depending on the owner's awareness of others' perceptions. (In this research, only perceptual solution concepts for the 2-decision maker case are developed. ) In Phase 2, meta-stability analysis is employed to consolidate the stability assessments of a state in all perceptual graph models and across all variants of awareness. Distinctive modes of equilibria are defined, which reflect incompatibilities in DMs' perceptions and viewpoints but nonetheless provide important insights into possible resolutions of conflict. <br /><br /> The possibility principle and perceptual stability analysis are integrative techniques that can be used as a basis for empathetically studying the interaction of emotion and reasoning in the context of strategic conflict. In general, these new techniques expand current modeling and analysis capabilities, thereby facilitating realistic, descriptive models without exacting too great a cost in modeling complexity. In particular, these two theoretical advances enhance the applicability of the Graph Model for Conflict Resolution to real-world disputes by integrating emotion and perception, common ingredients in almost all conflicts. <br /><br /> To demonstrate that the new developments are practical, two illustrative applications to real-world conflicts are presented: the US-North Korea conflict and the confrontation between Russia and Chechen Rebels. In both cases, the analysis yields new strategic insights and improved advice.

Marfan Syndrome (MFS) is one of the most common monogenic diseases and affects approximately 1 in 5,000 individuals worldwide. The syndrome is characterized by elongated extremities, tall stature, slender frame, and cardiac, and vision abnormalities due to severe connective tissue defects. It is caused by mutations in the fbn1 gene, which encodes an extracellular matrix glycoprotein, and is required for proper cardiac and skeletal development and for sequestration of TGFβ (transforming growth factor beta) and BMP (bone morphogenetic protein) within the extracellular matrix (ECM). The primary objective of this study was to establish a C.elegans MFS model and use this model to determine which genes interact with a C.elegans fbn1 homolog, MUA-3 and ascertain the role of metabolic rate in the development of MFS pathology. We isolated a temperature sensitive mutant of mua-3, a fbn1 homolog. We found that at the fourth larval molt, when animals shed the exoskeleton and rebuild a new one, the mutants die due to extensive mechanical stress in connective tissue shown as fragmented internal structures. Using this mutant, an unbiased forward genetic screen to isolate the genetic interactors of the fibrillin gene homolog, was completed. A collagen gene, that has been implicated to genetically interact with a bone morphogenetic protein (BMP), was isolated. This suggests that mua-3(uy19) may interact with genes involved in TGFβ regulation during the L4 molt and that fibrillin-1, TGF-β, and metalloproteases may act in-concert to modulate TGFβ availability and connective tissue integrity in C. elegans. In addition, we found that two independent mutations of mua-3 show temperature-sensitive phenotypes. Based on this result, we propose that increase of temperature aggravates the phenotype potentially due to increased metabolism. This hypothesis, if correct, will suggest a potential connection between metabolic rate and severity of MFS pathology.

Ao longo das últimas décadas, o declínio organizacional despertou interesse de pesquisadores em função da necessidade de se compreender a dinâmica organizacional por uma perspectiva oposta ao crescimento. Esse desejo surge em função da crescente dificuldade das grandes organizações em conseguir manter sua posição competitiva: acredita-se que a perpetuação do bom desempenho depende cada vez mais de quão adaptáveis estas organizações são às turbulências do ambiente de negócios. Porém, esta flexibilidade não depende apenas da capacidade de antecipar as mudanças estratégicas, mas também de como a sua estrutura organizacional está estabelecida e da sua capacidade empreendedora. Assim, pelo fato da teoria do declínio organizacional ser relativamente recente, inúmeras definições taxonômicas ainda precisam ser debatidas, além de se ressaltar a necessidade de explorar melhor o próprio conceito do declínio e compreender sua origem. Considerando este contexto, o presente trabalho desenvolve um modelo de diagnóstico do declínio organizacional, cujo objetivo central é identificar o estágio de declínio das organizações. Para cumprir com este propósito, estudos de casos múltiplos foram aplicados em empresas do segmento automobilísticos (montadoras), tanto pelo fato de estarem presentes no Brasil há vários ciclos econômicos quanto por se depararem com uma intensa necessidade de reavaliação do modelo de negócio nos últimos anos. Para a definição dos constructos que compõem o arcabouço teórico, foi realizada uma análise bibliométrica e, posteriormente, uma análise cienciométrica, de modo a permitir a compreensão da estrutura cognitiva da teoria do declínio organizacional, a partir da qual foi desenvolvida uma proposta aqui denominada modelo 3E, pois contempla as seguintes dimensões: Estratégia, Estrutura e Empreendedorismo. Os resultados obtidos validam o modelo proposto e permitem inferir não apenas a situação do setor automobilístico, mas também posicionar cada montadora em seu estágio de declínio correspondente com base em uma análise temporal da organização: passado, presente e futuro. Como efeito colateral, o modelo oferece um roteiro para verificar a coerência da estrutura à estratégia, a eficiência da estrutura organizacional e também a capacidade empreendedora destas organizações em definir o horizonte estratégico adequado. / Along the latest decades, organizational decline raised interest on the part of scholars due to the need of understanding the organizational dynamics from a perspective opposed to growth. This occurs in function of the increasing difficulty of large organizations in managing to keep their competitive position; the perpetuation of good performance is believed to depend more and more on how adaptable these organizations are to the turbulences of the business environment. However, this flexibility does not only depend on the capacity of anticipating strategic changes, but also on how their organizational structure is established and on their entrepreneurial capacity. Hence, once the organizational decline theory is relatively recent, a number of taxonomic definitions still have to be discussed before the need to better explore the very concept of decline and understanding its source is felt. Considering this context, a model for diagnosing organizational decline is developed herein, the central goal of which is to identify the organizations decline stage. To meet this goal, multiple case studies were conducted in organizations in the automotive sector (assemblers), both for the fact of their being present in Brazil along several economic cycles and for their facing an intense need to reassess their business model in the last years. For defining the constructs composing the theoretical framework, a bibliometric analysis was conducted and, later, a scientometric analysis, so as to allow understanding the cognitive structure of the organizational decline theory, from which a proposal was developed and denominated 3E model here, contemplating the following dimensions: Strategy, Structure and Entrepreneurship (which start with an E in Portuguese). The results validate the model proposed and allow inferring not only the automotive sector scenario, but also placing each assembler in its corresponding decline stage based on a temporal analysis of the organization: past, present and future. As a side effect, the model provides a script for verifying the adherence of the structure to the strategy, the efficiency of the organizational structure, as well as the entrepreneurial capacity of these organizations in defining an adequate strategic horizon.

Este trabalho apresenta uma análise estatística de contagens multivariadas proveniente de várias populações através de modelos de regressão. Foram considerados casos onde os vetores respostas obedeçam às distribuições Poisson multivariada e Poisson log-normal multivariada. Esta distribuição admite correlação de ambos sinais entre componentes do vetor resposta, enquanto que as distribuições mais usuais para dados de contagens (como a Poisson multivariada) admitem apenas correlação positiva entre as componentes do vetor resposta. São discutidos métodos de estimação e testes de hipóteses sobre os parâmetros do modelo para o caso bivariado. Estes modelos de regressão foram aplicados a um conjunto de dados referentes a contagens de dois tipos de defeitos em 100 gramas de fibras têxteis de quatro máquinas craqueadeiras, sendo duas de um fabricante e as outras de um segundo fabricante. Os resultados obtidos nos diferentes modelos de regressão foram comparados. Para estudar o comportamento das estimativas dos parâmetros de uma distribuição Poisson Log-Normal, amostras foram simuladas segundo esta distribuição. / Regression models are presented to analyse multivariate counts from many populations. Due to the random vector characteristic, we consider two classes of probability models: Multivariate Poisson distribution and Multivariate Poisson Log-Normal distribution. The last distribution admits negative and positive correlations between two components of a random vector under study, while other distributions (as Multivariate Poisson) admit only positive correlation. Estimation methods and test of hypothese on the parameters in bivariate case are discussed. The proposed techniques are illustrated by numerical examples, considering counts of two types of defects in 100g of textile fibers produced by four machines, two from one manufacturer and the other two from another one. The results from different regression models are compared. The empirical distribution of Poisson Log-Normal parameter estimations are studied by simulated samples.

Adverse childhood experiences (ACEs) are linked to increased mental health problems in children, but their association with mental health services utilization is not well known. This secondary analysis used 2016 National Survey of Children’s Health data from two samples: children aged 6-17-years-old with a mental or behavioral condition in need of treatment or counseling (N = 5,723); and a subsample of children who experienced at least one ACE (n = 3,812). Multiple logistic regression and latent class analysis (LCA) were performed to examine the association between ACEs and mental health services utilization. Multiple logistic regressions also examined the associations of parent/caretaker vulnerability, school-system, and medical-system factors on mental health services utilization for children with ACEs using the Gelberg-Andersen Behavioral Model for Vulnerable Populations and a Systems of Care approach as the framework for model building. Children with increased ACE scores did not have higher odds of utilizing mental health services compared to children at lower levels of or no ACEs. For children who experienced adversity, increased parent/caretaker vulnerability was associated with lower odds and the current receipt of special education services with increased odds of mental health services utilization in adjusted models. Strengths of this study included the large dataset and generalizability to the U.S. population. There were limitations to the measurement of ACEs and other key variables. The current study identified children who experienced adversity as an underserviced population for mental health services.

The objective of the research is to identify how information can influence development in the developing countries, especially in Bangladesh. A variety of information gathering stages were undertaken including documentary analysis, interviews with key officials, structured interviews with individuals living in rural and urban slum areas and focus groups. Officials at the central planning level responsible for community development and information services in Bangladesh were interviewed to ascertain their views of the relation of information and development in Bangladesh. At the grassroots level both information providers and users were interviewed to collect information relating to the impact of information services on development in rural and poor urban areas of Bangladesh. Structured interviews which allowed for quantitative analysis were undertaken in four remote villages and two poor urban areas. Analysis of the data collected has led to the development of a model for community information centres which might become central to information dissemination and provide a focus for information policy in Bangladesh.

Flexible approaches for eliciting preferences of decision makers involved in a conflict are developed along with applications to real-world disputes. More specifically, two multiple criteria decision making approaches are proposed for capturing the relative preferences of a decision maker participating in a conflict situation. A case study in logistics concerned with the conflict arising over the expansion of port facilities on the west coast of North America as well as a transportation negotiation dispute are used to illustrate how these approaches can be integrated with the Graph Model for Conflict Resolution, a practical conflict analysis methodology. Ascertaining the preferences of the decision makers taking part in a conflict constitutes a key element in the construction of a formal conflict model. In practice, the relative preferences, which reflect each decision maker’s objectives or goals in a given situation, are rather difficult to obtain. The first method for preference elicitation is to integrate an Analytic Hierarchy Process (AHP) preference ranking method with the Graph Model for Conflict Resolution. The AHP approach is used to elicit relative preferences of decision makers, and this preference information is then fed into a graph model for further stability analyses. The case study of the Canadian west coast port congestion conflict is investigated using this integrated model. Another approach is based on a fuzzy multiple criteria out-ranking technique called ELECTRE III. It is also employed for ranking states or possible scenarios in a conflict from most to least preferred, with ties allowed, by the decision maker according to his or her own value system. The model is applied to a transportation negotiation dispute between the two key parties consisting of shippers and carriers.

Theoretical procedures are developed to account for the effect of emotion and perception in strategic conflict. The <em>possibility principle</em> facilitates modeling the effects of emotions on future scenarios contemplated by decision makers; <em>perceptual graph models</em> and a <em>graph model system</em> permit the decision makers (DMs) to experience and view the conflict independently; and <em>perceptual stability analysis</em>, which is based on individual- and meta-stability analysis techniques, is employed in analyzing graph model systems when the DMs have inconsistent perceptions. These developments improve the methodology of the Graph Model for Conflict Resolution by reconciling emotion, perception, and strategy to make predictions consistent with the actual unfolding of events. <br /><br /> Current research in neuroscience suggests that emotions are a necessary component of cognitive processes such as memory, attention, and reasoning. The somatic marker hypothesis, for example, holds that feelings are necessary to reasoning, especially during social interactions (Damasio, 1994, 2003). Somatic markers are memories of past emotions: we use them to predict future outcomes. To incorporate the effect of emotion in conflict, the underlying principle of Damasio?s hypothesis is used in developing the possibility principle, which significantly expands the paradigm of the Graph Model for Conflict Resolution of Fang, Hipel, and Kilgour (1993). <br /><br /> State identification is a crucial step in determining future scenarios for DMs. The possibility principle is integrated into the modeling stage of the Graph Model by refining the method of determining feasible states. The possibility principle enables analysts and DMs to include emotion in a conflict model, without sacrificing the parsimonious design of the Graph Model methodology, by focusing attention on two subsets of the set of feasible states: <em>hidden</em> and <em>potential</em> states. Hidden states are logically valid, feasible states that are invisible because of the presence of negative emotions such as anger and fear; potential states are logically valid, feasible states that are invisible because of missing positive emotions. Dissipating negative emotions will make the hidden states visible, while expressing the appropriate positive emotions will make the potential states visible. The possibility principle has been applied to a number of real world conflicts. In all cases, eliminating logically valid states not envisioned by any DM simplifies a conflict model substantially, expedites the analysis, and makes it an intuitive and a realistic description of the DMs' conceptualizations of the conflict. <br /><br /> A fundamental principle of the Graph Model methodology is that all DMs' directed graphs must have the same set of feasible states, which are integrated into a <em>standard</em> graph model. The possibility principle may modify the set of feasible states perceived by each DM according to his or her emotion, making it impossible to construct a single standard graph model. When logically valid states are no longer achievable for one or more DMs due to emotions, the apprehension of conflict becomes inconsistent, and resolution may become difficult to predict. Therefore, reconciling emotion and strategy requires that different apprehensions of the underlying decision problem be permitted, which can be accomplished using a perceptual graph model for each DM. A perceptual graph model inherits its primitive ingredients from a standard graph model, but reflects a DM's emotion and perception with no assumption of complete knowledge of other DMs' perceptions. <br /><br /> Each DM's perceptual graph model constitutes a complete standard graph model. Hence, conclusions drawn from a perceptual graph model provide a limited view of equilibria and predicted resolutions. A graph model system, which consists of a list of DMs' perceptual graph models, is defined to reconcile perceptions while facilitating conclusions that reflect each DM's viewpoint. However, since a DM may or may not be aware that other graph models differ from his or her own, different variants of graph model systems are required to describe conflicts. Each variant of graph model system corresponds to a configuration of awareness, which is a set of ordered combinations of DMs' viewpoints. <br /><br /> Perceptual stability analysis is a new procedure that applies to graph model systems. Its objective is to help an <em>outside</em> analyst predict possible resolutions, and gauge the robustness and sustainability of these predictions. Perceptual stability analysis takes a two-phase approach. In Phase 1, the stability of each state in each perceptual graph model is assessed from the point of view of the owner of the model, for each DM in the model, using standard or perceptual solution concepts, depending on the owner's awareness of others' perceptions. (In this research, only perceptual solution concepts for the 2-decision maker case are developed. ) In Phase 2, meta-stability analysis is employed to consolidate the stability assessments of a state in all perceptual graph models and across all variants of awareness. Distinctive modes of equilibria are defined, which reflect incompatibilities in DMs' perceptions and viewpoints but nonetheless provide important insights into possible resolutions of conflict. <br /><br /> The possibility principle and perceptual stability analysis are integrative techniques that can be used as a basis for empathetically studying the interaction of emotion and reasoning in the context of strategic conflict. In general, these new techniques expand current modeling and analysis capabilities, thereby facilitating realistic, descriptive models without exacting too great a cost in modeling complexity. In particular, these two theoretical advances enhance the applicability of the Graph Model for Conflict Resolution to real-world disputes by integrating emotion and perception, common ingredients in almost all conflicts. <br /><br /> To demonstrate that the new developments are practical, two illustrative applications to real-world conflicts are presented: the US-North Korea conflict and the confrontation between Russia and Chechen Rebels. In both cases, the analysis yields new strategic insights and improved advice.