Thesis (Ph. D.)--University of Washington, 2001. / Vita. Includes bibliographical references (p. 139-145).

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2009. / Includes bibliographical references (p. 95-99).

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Im Rahmen eines explorativen Vergleichsuntersuchungsplans wurde untersucht, inwieweit sich die durch biologische Faktoren bedingte unterschiedliche Lebenserfahrung sowie die Sozialisationsbedingungen in der psychosexuellen Entwicklung bei hetero-, homo- und postoperativen transsexuellen Männern (N = 191) auf die Integration der Geschlechterstereotypen in die kognitiven (Selbst-, Fremdwahrnehmung), emotionalen (Selbst- und Fremdbewertung) und verhaltensmäßigen Aspekte (Normen der geschlechtsspezifischen Verhaltens) der Geschlechtsidentität auswirken und ob sich Identifikationsmuster der Entwicklung des geschlechtlichen Selbstkonzepts ableiten lassen. Die Messung der kognitiven Aspekte des geschlechtlichen Selbstkonzepts (Maskulinität und Femininität) erfolgte mittels der GERO-Skala von Brengelmann und Hendrich (1990). Zur Erfassung der emotionalen Aspekte und Identifikationsmuster der Entwicklung des geschlechtlichen Selbstkonzepts wurden die Werte für die Variablen Maskulinität und Femininität zuerst mittels der computergesteuerten Methodik IDEXMONO und IDEXIDIO, die auf der Identitätsstrukturanalyse (Identity Structure Analysis) von Weinreich (2003) basiert, aufgearbeitet und weiter interferenzstatistisch ausgewertet. Weiterhin wurden der Fragebogen zur Messung normativer Geschlechtsrollenorientierung (NGRO) von Athenstaedt (2000) sowie ein ad hoc entworfener demographischer Fragebogen eingesetzt. Die Ergebnisse zeigen, dass der Verlauf der psychosexuellen Entwicklung einen starken Einfluss auf die Integration der Geschlechterstereotypen in die geschlechtliche Selbst- und Fremdwahrnehmung hat. Im kognitiven Bereich, bezogen auf die persönliche Identität (Grad der Selbstzuschreibung männlicher und weiblicher Merkmale), stellt die Maskulinität eine stabile und erstrebenswerte Variable zur Herausbildung des geschlechtlichen Selbstkonzepts bei allen Gruppen dar. Die Femininität trägt am meisten zur Differenzierung zwischen den Hetero-, Homo- und Transsexuellen bei. Sie wird, je nach der Entwicklungsphase, unterschiedlich in das geschlechtliche Selbstkonzept integriert. Hinsichtlich der sozialen Identität (Zugehörigkeitsgefühl) lassen sich die Gruppen bezüglich der wahrgenommenen Ähnlichkeiten sowohl mit männlichen als auch weiblichen Personen, je nach der Entwicklungsphase, unterscheiden. Die soziale Wahrnehmung von Männern und Frauen (Fremdwahrnehmung), ist bei Transsexuellen traditioneller als die der Hetero- und Homosexuellen. Bei der Selbst- und Fremdbewertung ergaben sich keine signifikanten Unterschiede. Bei der Internalisierung der sozialen Normen des geschlechtsspezifischen Verhaltens zeigt sich, dass Heterosexuelle der Ausübung der Geschlechterrollen gegenüber egalitärer eingestellt sind als Trans- und Homosexuelle. Bei den Sozialisationsfaktoren ist hervorzuheben, dass generell weibliche Identifikationspersonen einen stärkeren Einfluss auf die Herausbildung des geschlechtlichen Selbstkonzeptes hatten als männliche Identifikationspersonen. Es scheint jedoch, dass Homosexuelle bei der Entwicklung ihres geschlechtlichen Selbstkonzepts stärker unter dem Einfluss der Frauen stehen als die anderen zwei erforschten Gruppen. Zur Beantwortung der Frage, welche selbstkonzeptbezogenen Variablen und Entwicklungsfaktoren die größte statistische Bedeutung für die Trennung und Prädiktion der einzelnen untersuchten Gruppen haben, wurde eine Diskriminanzanalyse berechnet. Die größte diskriminatorische Bedeutung besitzen die Variablen „Stereotypische Wahrnehmung der männlichen Personen“ und „Ego-Involvement mit weiblichen Personen“ für die Diskriminanzfunktion 1 (Trennung der Transsexuellen von Hetero- und Homosexuellen) und die Variablen „Empathische Identifikation mit männlichen Personen in der Vergangenheit“ und „Zuwachs an empathischer Identifikation mit weiblichen Personen“ für die Diskriminanzfunktion 2 (Trennung der Hetero- von Homosexuellen). / The aim of the present explorative-comparative study was to find out to which extent the biologically determined differences as well as socialization conditions in the psychosexual development of hetero-, homo- and transsexual men (N = 191) affect the integration of the gender stereotypes in cognitive (self-perception und perception of the others), emotional (appraisal of self and the others), and behavioral aspects (norms of gender behavior) of gender identity, as well as to deduce identification patterns in the development of the gender self-concept. The GERO-scale by Brengelmann und Hendrich (1990) was used to measure the cognitive aspects of the self-concept of gender (masculinity and femininity). The collected data of masculinity and femininity were further processed using the computer-operated Identity Structure Analysis based method IDEXMONO and IDEXIDIO (Weinreich, 2003) to detect the emotional aspects and identification patterns of the development of the self-concept of gender. Furthermore, the questionnaire of normative gender role orientation by Athenstaedt (2000) and an ad hoc designed demographic questionnaire were applied. The results show that the course of the psychosexual development has a strong impact upon the integration of the gender stereotypes in gender related self-perception and perception of others. As for cognitive aspects related to personal identity (grade of self-attribution of masculine and feminine traits), the masculinity represents a stable and desirable variable in the construction of the self-concept of gender in all samples. The femininity contributes the most to the differentiation between hetero-, homo- and trans-sexuals. Femininity has been integrated in the gender self-concept to a different extent, depending on the phase of the psychosexual development. As for social identity (feeling of social affiliation), there are differences among the samples in self-perceived similarities to both masculine and feminine persons, depending on the phase of the psychosexual development. The social perception of men and women (perception of the others) is more traditionally oriented in transsexuals than in hetero- and homosexuals. There are no significant differences in the appraisal of self and the others. As for the internalization of the social norms of gender specific behavior, heterosexuals are more egalitarian in their attitude towards the practice of gender roles than homo- and transsexuals. The examination of the socialization conditions shows that in general, feminine identification persons have a stronger impact upon the construction of self-concept of gender than masculine ones. However, it seems as though women have a stronger impact upon the construction of self-concept of gender in homosexuals than in the other groups. A discriminant analysis was computed to answer the question which self-related variables and developmental factors have the strongest statistical importance for the division and prediction of the samples. The variables “stereotypic perception of masculine persons” and “ego-involvement with feminine persons” have the strongest discriminant importance for the discriminant function 1 (division of transsexuals from hetero- and homosexuals) and the variables “empathic identification with masculine persons in the past” and “growth of empathic identification with feminine persons” for the discriminant function 2 (division of heterosexuals from homosexuals).

Sequence analysis and structure analysis are two of the fundamental areas of bioinformatics research. This dissertation discusses, specifically, protein structure related problems including protein structure alignment and query, and genome sequence related problems including haplotype reconstruction and genome rearrangement. It first presents an algorithm for pairwise protein structure alignment that is tested with structures from the Protein Data Bank (PDB). In many cases it outperforms two other well-known algorithms, DaliLite and CE. The preliminary algorithm is a graph-theory based approach, which uses the concept of \stars" to reduce the complexity of clique-finding algorithms. The algorithm is then improved by introducing \double-center stars" in the graph and applying a self-learning strategy. The updated algorithm is tested with a much larger set of protein structures and shown to be an improvement in accuracy, especially in cases of weak similarity. A protein structure query algorithm is designed to search for similar structures in the PDB, using the improved alignment algorithm. It is compared with SSM and shows better performance with lower maximum and average Q-score for missing proteins. An interesting problem dealing with the calculation of the diameter of a 3-D sequence of points arose and its connection to the sublinear time computation is discussed. The diameter calculation of a 3-D sequence is approximated by a series of sublinear time deterministic, zero-error and bounded-error randomized algorithms and we have obtained a series of separations about the power of sublinear time computations. This dissertation also discusses two genome sequence related problems. A probabilistic model is proposed for reconstructing haplotypes from SNP matrices with incomplete and inconsistent errors. The experiments with simulated data show both high accuracy and speed, conforming to the theoretically provable e ciency and accuracy of the algorithm. Finally, a genome rearrangement problem is studied. The concept of non-breaking similarity is introduced. Approximating the exemplar non-breaking similarity to factor n1..f is proven to be NP-hard. Interestingly, for several practical cases, several polynomial time algorithms are presented.

Object recognition is imperfect; often incomplete processing or deprived information yield misperceptions (i.e., misidentification) of objects. While quickly rectified and typically benign, instances of such errors can produce dangerous consequences (e.g., police shootings). Through a series of experiments, this study examined the competitive process of multiple object interpretations (candidates) during the earlier stages of object recognition process using a lexical decision task paradigm. Participants encountered low-pass filtered objects that were previously demonstrated to evoke multiple responses: a highly frequented interpretation (“primary candidates”) and a lesser frequented interpretation (“secondary candidates”). When objects were presented without context, no facilitative effects were observed for primary candidates. However, secondary candidates demonstrated evidence for being actively suppressed. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

A criação e confecção de joias, objetos de adorno, remete aos primórdios da humanidade. Ao longo da história as técnicas construtivas foram aprimoradas, porém os métodos produtivos do ramo joalheiro ainda hoje possuem forte caráter empírico de desenvolvimento. Nesse contexto, a presente pesquisa explora a possibilidade de simulação e avaliação do comportamento mecânico da joia, aplicada em etapas que precedem à produção. Busca-se como a análise estrutural por elementos finitos pode auxiliar o designer na avaliação de joias em processos de pré-fabricação. Para isso tem-se a criação dos corpos de prova gerados pela modelagem virtual, através do software Rhinoceros 3D. Os corpos de prova são exportados para o software Abaqus CAE, no qual são configuradas as propriedades do material, condições de carregamento e de suporte, simulando aspectos do uso diário da joia. Como material para simulação, são analisados aqueles mais utilizados no segmento, o ouro, a prata e o latão. Os resultados da simulação gerados no Abaqus CAE permitem avaliar as tensões geradas sobre o modelo, bem como os deslocamentos e deformações. Assim são identificados pontos frágeis na estrutura ou mesmo onde pode ter uma otimização da quantidade de material utilizado para cada joia, reavaliando a necessidade de aumentar ou reduzir o uso do material, buscando o equilíbrio estrutural do qual a joia necessitará. Os resultados obtidos comprovam que o método converge para uma importante ferramenta que proporciona dados sobre cada projeto a ser desenvolvido. Esses dados geram uma visão analítica onde as empresas podem definir qual a prioridade para cada projeto através de índices precisos, o que reduz a taxa de erro por projeto, auxilia no consumo adequado de matéria-prima, gerando economia de tempo e dinheiro. / The creation and production of jewelry, adornment objects, refers to the beginnings of humanity. Throughout the history, the construction techniques were improved, however the production methods of the jewelry industry today still have a strong empirical development and production. With this premise, the present research explores the possibility of simulation and evaluation of mechanical behavior for jewelry, in stages that are prior to production. With the application of external loads, the behavior of the jewelry through situations that may occur during the daily use can be analyzed. To create the study object it is used the software Rhinoceros 3D for make the virtual models. In the simulations the most used materials in the jewelry segment are analyzed, as gold, silver and brass. The Finite Element software Abaqus CAE is used for the structural analysis. The results show that the method is an important tool to provide data about the development of each project. These data give an analytical perception in which companies can define projects priorities through precise indexes, reducing error rates, helping in a suitable consumption of raw materials, saving time and money.

In medical, behavioral, and social-psychological sciences, latent variable models are useful in handling variables that cannot be directly measured by a single observed variable, but instead are assessed through a number of observed variables. Traditional latent variable models are usually based on parametric assumptions on both relations between outcome and explanatory latent variables, and error distributions. In this thesis, semiparametric models with Bayesian P-splines are developed to relax these rigid assumptions. / In the fourth part of the thesis, the methodology developed in the third part is further extended to a varying coefficient model with latent variables. Varying coefficient model is a class of flexible semiparametric models in which the effects of covariates are modeled dynamically by unspecified smooth functions. A transformation varying coefficient model can handle arbitrarily distributed dynamic data. A simulation study shows that our proposed method performs well in the analysis of this complex model. / In the last part of the thesis, we propose a finite mixture of varying coefficient models to analyze dynamic data with heterogeneity. A simulation study demonstrates that our proposed method can explore possible existence of different groups in a dynamic data, where in each group the dynamic influences of covariates on the response variables have different patterns. The proposed method is applied to a longitudinal study concerning the effectiveness of heroin treatment. Distinct patterns of heroin use and treatment effect in different patient groups are identified. / In the second part of the thesis, a latent variable model is proposed to relax the first assumption, in which unknown additive functions of latent variables in the structural equation are modeled by Bayesian P-splines. The estimation of nonparametric functions is based on powerful Markov chain Monte Carlo (MCMC) algorithm with block update scheme. A simulation study shows that the proposed method can handle much wider situation than traditional models. The proposed semiparametric latent variable model is applied to a study on osteoporosis prevention and control. Some interesting functional relations, which may be overlooked by traditional parametric latent variable models, are revealed. / In the third part of the thesis, a transformation model is developed to relax the second assumption, which usually assumes the normality of observed variables and random errors. In our proposed model, the nonnormal response variables are transformed to normal by unknown functions modeled with Bayesian P-splines. This semiparametric transformation model is shown to be applicable to a wide range of statistical analysis. The model is applied to a study on the intervention treatment of polydrug use in which the traditional model assumption is violated because many observed variables exhibit serious departure from normality. / Lu, Zhaohua. / Adviser: Xin-Yuan Song. / Source: Dissertation Abstracts International, Volume: 72-04, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 119-130). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.