9 resultados para Bus and Car relationship

em Digital Commons at Florida International University


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This study examined links between adolescent depressive symptoms, actual pubertal development, perceived pubertal timing relative to one’s peers, adolescent-maternal relationship satisfaction, and couple sexual behavior. Assessments of these variables were made on each couple member separately and then these variables were used to predict the sexual activity of the couple. Participants were drawn from the National Longitudinal Study of Adolescent Health (Add Health; Bearman et al., 1997; Udry, 1997) data set (N = 20,088; aged 12–18 years). Dimensions of adolescent romantic experiences using the total sample were described and then a subsample of romantically paired adolescents ( n = 1,252) were used to test a risk and protective model for predicting couple sexual behavior using the factors noted above. Relevant measures from the Wave 1 Add Health measures were used. Most of the items used in Add Health to assess romantic relationship experiences, adolescent depressive symptoms, pubertal development (actual and perceived), adolescent-maternal relationship satisfaction, and couple sexual behavior were drawn from other national surveys or from scales with well documented psychometric properties. Results demonstrated that romantic relationships are part of most adolescents’ lives and that adolescents’ experiences with these relationships differ markedly by age, sex, and race/ethnicity. Further, each respective couple member’s pubertal development, perceived pubertal timing, and maternal relationship satisfaction were useful in predicting sexual risk-promoting and risk-reducing behaviors in adolescent romantic couples. Findings in this dissertation represent an initial step toward evaluating explanatory models of adolescent couple sexual behavior.

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The thesis argues for the inclusion of the study of religion within the public school curriculum. It argues that the whole division between “religious” and “secular” spaces and institutions is itself rooted in a specific religious tradition. Using the theories of Jacques Derrida, I argue that, unless the present process of globalization is tempered with alternative models of organizing that don’t include this secular/sacred division, the very process of Western globalization acts as a moral religion. Derrida calls this process “globalatinization,” the imposition of Western defined institutions upon other cultures. The process creates a type of religious violence through act of imposing notions of “secular/public” and “sacred/private.” Drawing from Mark Juergensmeyer’s theory of religious violence, and Derrida’s and Foucault’s understanding of discursive formations, I argue that religious studies should enter this “secular/public” space in the form of educating about the world’s religions. Such education would go a long way in preventing the demonization of the “other” through promoting empathy, understanding, and respect for “other” traditions. Finally, education would provide a needed self-critique of the dividing of “secular/sacred” in contemporary Western life.

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Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

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This study examined links between adolescent depressive symptoms, actual pubertal development, perceived pubertal timing relative to one’s peers, adolescent-maternal relationship satisfaction, and couple sexual behavior. Assessments of these variables were made on each couple member separately and then these variables were used to predict the sexual activity of the couple. Participants were drawn from the National Longitudinal Study of Adolescent Health (Add Health; Bearman et al., 1997; Udry, 1997) data set (N = 20,088; aged 12-18 years). Dimensions of adolescent romantic experiences using the total sample were described and then a subsample of romantically paired adolescents (n = 1,252) were used to test a risk and protective model for predicting couple sexual behavior using the factors noted above. Relevant measures from the Wave 1 Add Health measures were used. Most of the items used in Add Health to assess romantic relationship experiences, adolescent depressive symptoms, pubertal development (actual and perceived), adolescent-maternal relationship satisfaction, and couple sexual behavior were drawn from other national surveys or from scales with well documented psychometric properties. Results demonstrated that romantic relationships are part of most adolescents’ lives and that adolescents’ experiences with these relationships differ markedly by age, sex, and race/ethnicity. Further, each respective couple member’s pubertal development, perceived pubertal timing, and maternal relationship satisfaction were useful in predicting sexual risk-promoting and risk-reducing behaviors in adolescent romantic couples. Findings in this dissertation represent an initial step toward evaluating explanatory models of adolescent couple sexual behavior.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

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The purpose of this thesis was to redesign a commercial center in Miami, Florida in a manner that incorporates the needs of pedestrians as well as the automobile. In my research, I studied projects that had been successful at integrating cars in retail design. I applied the strategies learned from this research to the design of a center that creates a positive interaction of pedestrian and car traffic, addressing the needs of the surrounding community. I designed a master plan that includes a mix of residential, retail, commercial and parking space. The parking is designed so that the retail center is not dominated by surface parking. Rather, the automobile is introduced into the different layers of the proposed buildings. The design focused on connecting pedestrian plazas and parking areas beneath them through the introduction of light and greenery. The findings show how a shopping center might transform the area around it by including spaces for residential, civic, cultural and social functions, as well as for the automotive infrastructure that make those functions possible.

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This research investigated the relationship between investments in fixed assets and free cash flows of U.S. restaurant firms while controlling for future investment opportunities and financial constraints. It also investigated investment and cash-flow sensitivity in the context of economic conditions. Results suggested that investments in small firms (with higher financial constraints) had relatively weaker sensitivity to cash flows than investments in large firms (with higher sensitivity). Controlling for economic conditions did not significantly change results. While the debate over sensitivity of investments to cash flows remains unresolved, it has not been explored widely in industry contexts, especially in services such as the restaurant industry. In addition to its contribution to this literature, this paper provides implications for cash-flow management in publicly traded restaurant companies.

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The purpose of this study was to determine whether or not new and significant developments for the Hindu and Jewish faiths, and the relationship that exists between them, can be demonstrated from the results of the Hindu-Jewish Leadership Summits of 2007 and 2008 in Delhi and Jerusalem. I argue that new and significant developments can be observed with this Hindu-Jewish encounter with regards to official rulings of Halacha (Jewish law), proper understandings of sacred symbols of Hinduism, and even improved Islamic-Jewish relations. After analyzing the approaches, themes, and unique framework found within this encounter, it is clear that the Hindu-Jewish leadership summits mark new and significant developments in inter-religious dialogue between the two traditions, culminating in the redefinition of Hinduism as a monotheistic religion.