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Relatively complex Augmented Reality (AR) algorithms are becoming widely available due to advancements in affordable mobile computer hardware. To take advantage of this a new method is developed for tracking 2D regions without a prior knowledge of an environment and without developing a computationally expensive world model. In the method of this paper, affinely invariant planar regions in a scene are found using the Maximally Stable Extremal Region (MSER) detector. A region is selected by the user to define a search space, and then the Scale Invariant Feature Transform (SIFT) is used to detect affine invariant keypoints in the region. If three or more keypoint matches across frames are found, the affine transform A of a region is calculated. A 2D image is then transformed by A causing it to appear stationary on the 2D region being tracked. The search region is tracked by transforming the previous search region by A, defining a new location, size, and shape for the search region. Testing reveals that the method is robust to tracking planar surfaces despite affine changes in the geometry of a scene. Many real world surfaces provide adequate texture for successful augmentation of a scene. Regions found multiple frames are consistent with one another, with a mean cross-correlation of 0.608 relating augmented regions. The system can handle up to a 45° out of plane viewpoint change with respect to the camera. Although rotational changes appear to skew the affine transform slightly, translational and scale based have little distortion and provide convincing augmentations of graphics onto the real world.

Modern theories of authoritarianism have stressed the importance of threat to the expression of authoritarian attitudes and intolerance. Arguably, authoritarian tendencies may have increased during COVID-19 pandemic, a major threat to life and security. One issue arising when comparing mean scores is that of measurement invariance. Meaningful comparisons are only possible, if latent constructs are similar between groups and/or across time. This prerequisite is rarely ever tested in research on authoritarianism. In this study, we aim to analyze the short scale for authoritarianism KSA-3 by investigating its measurement invariance on two levels (three first-order and one second-order factors) and latent mean changes using two German representative samples (N = 4,905). Specifically, we look at differences before and during the pandemic (2017 vs. 2020). While measurement invariance holds across both levels in all conditions, we find a decrease in latent means in 2020, contrary to expectations and established theories. Moreover, latent means differ with regard to gender, education, and east–west Germany. We conclude that analyses of latent means and measurement invariance instead of mean comparisons with composites should become the standard. Future studies should focus on threat as a moderator between authoritarianism and intolerance, and on possible interactions with context variables.

Family functioning has long been a focus of research in psychopathology. Decades of research has shown that family factors are associated with symptom severity, relapse, functional outcomes, and conversion to psychosis among at-risk individuals. Previous studies suggest family functioning varies across cultures, which raises the possibility that associations between family factors and psychopathology may also differ by culture. Furthermore, family functioning assessment generally involves instruments that have not been systematically validated for use with individuals from diverse cultural backgrounds. The current study used data from the Adolescent Brain Cognitive Development study (N = 11,138) to: (1) evaluate three family functioning scales (i.e., Family Environment Scale, Child's Report of Parental Behavior Inventory, Parental Monitoring Survey) and the Prodromal Questionnaire – Brief Child version for measurement invariance across racial/ethnic groups; (2) investigate the relations between family factors and psychosis; and (3) compare relations derived from Step 2 between racial/ethnic groups. Full scalar invariance was tenable for the CRPBI and the PQ-BC, providing statistical support for mean comparisons across groups. The FES and the PMQ lacked scalar invariance, which suggests mean comparisons across groups may not be appropriate. The CRPBI and the PMQ are significantly associated with the PQ-BC, and all three family scales had equivalent relations with the PQ-BC across groups. The current study highlights the importance of evaluating assessment instruments for measurement invariance across racial/ethnic groups. Results also help to connect specific family factors to the etiology of psychotic disorders among US children and adolescents.

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<p>This dissertation examined several dimensions of the development of physical aggression and indirect aggression in a longitudinal sample of boys and girls. These data are part of the National Longitudinal Study of Children and Youth which evaluated the development of children bi-annually from 1994 to 2010. The data for this thesis come from individuals aged 10 and 11 in Cycle 1 (1994) through to Cycle 5 (2002) when they were 18 and 19. In an attempt to explore trends in the development of aggression, the research is presented as three separate projects that examine the following: (1) measurement of physical and indirect aggression by informant and sex; (2) group-based trajectories of physical and indirect aggression and outcomes of trajectories in emerging adulthood; and (3) association between indirect aggression in adolescence and depression in emerging adulthood when physical aggression is taken into account. This is the first longitudinal study to investigate group-based physical and indirect aggression trajectories in childhood and adolescence and outcomes in emerging adulthood. The contribution of this thesis to the field of epidemiological research on aggression is the importance of considering distinct subgroups within both physical and indirect aggression, and joint trajectory groups of both physical and indirect aggression when exploring developmental trends and outcomes of aggression.</p> / Doctor of Philosophy (PhD)

<p>In this thesis, we explore several stochastic models associated withthe two-parameter Poisson-Dirichlet distribution and population genetics.The impacts of mutation, selection and time onthe population evolutionary process will be studied by focusing on two aspects of the model:equilibrium and non-equilibrium. In the first chapter, we introduce relevant background on stochastic genetic models, andsummarize our main results and their motivations. In the second chapter, the two-parameter GEM distribution is constructedfrom a linear birth process with immigration. The derivationrelies on the limiting behavior of the age-ordered family frequencies. In the third chapter, to show the robustness of the sampling formula we derive the Laplace transform of the two-parameterPoisson-Dirichlet distribution from Pitman sampling formula. The correlationmeasure of the two-parameter point process is obtained in our proof. We also reverse this derivationby getting the sampling formula from the Laplace transform. Then,we establish a central limit theorem for the infinitely-many-neutral-alleles modelat a fixed time as the mutation rate goes to infinity.Lastly, we get the Laplace transform for the selectionmodel from its sampling formula. In the fourth chapter, we establisha central limit theorem for the homozygosity functions under overdominant selectionwith mutation approaching infinity. The selection intensity is given by a multiple of certain powerof the mutation rate. This result shows an asymptotic normality for the properly scaled homozygosities,resembling the neutral model without selection.This implies that the influence of selection can hardly be observed with large mutation. In the fifth chapter, the stochastic dynamics of the two-parameter extension of theinfinitely-many-neutral-alleles model is characterized by the derivation of its transition function,which is absolutely continuous with respect to the stationary distribution being the two-parameter Poisson-Dirichlet distribution.The transition density is obtained by the expansion of eigenfunctions.Combining this result with the correlation measure in Chapter 3, we obtain the probability generatingfunction of a random sampling from the two-parameter model at a fixed time. Finally, we obtain two results based on the quasi-invariance of the Gamma processwith respect to the multiplication transformation group.One is the quasi-invariance property of the two-parameter Poisson-Dirichletdistribution with respect to Markovian transformation group.The other one is the equivalence between the quasi-invarianceof the stationary distributions of aclass of branching processes and their reversibility.</p> / Doctor of Philosophy (PhD)

[EN] Type 1 diabetes mellitus is a chronic and incurable disease that affects millions of people all around the world. Its main characteristic is the destruction (totally or partially) of the beta cells of the pancreas. These cells are in charge of producing insulin, main hormone implied in the control of blood glucose. Keeping high levels of blood glucose for a long time has negative health effects, causing different kinds of complications. For that reason patients with type 1 diabetes mellitus need to receive insulin in an exogenous way. Since 1921 when insulin was first isolated to be used in humans and first glucose monitoring techniques were developed, many advances have been done in clinical treatment with insulin. Currently 2 main research lines focused on improving the quality of life of diabetic patients are opened. The first one is concentrated on the research of stem cells to replace damaged beta cells and the second one has a more technological orientation. This second line focuses on the development of new insulin analogs to allow emulating with higher fidelity the endogenous pancreas secretion, the development of new noninvasive continuous glucose monitoring systems and insulin pumps capable of administering different insulin profiles and the use of decision-support tools and telemedicine. The most important challenge the scientific community has to overcome is the development of an artificial pancreas, that is, to develop algorithms that allow an automatic control of blood glucose. The main difficulty avoiding a tight glucose control is the high variability found in glucose metabolism. This fact is especially important during meal compensation. This variability, together with the delay in subcutaneous insulin absorption and action causes controller overcorrection that leads to late hypoglycemia (the most important acute complication of insulin treatment). The proposals of this work pay special attention to overcome these difficulties. In that way interval models are used to represent the patient physiology and to be able to take into account parametric uncertainty. This type of strategy has been used in both the open loop proposal for insulin dosage and the closed loop algorithm. Moreover the idea behind the design of this last proposal is to avoid controller overcorrection to minimize hypoglycemia while adding robustness against glucose sensor failures and over/under- estimation of meal carbohydrates. The algorithms proposed have been validated both in simulation and in clinical trials. / [ES] La diabetes mellitus tipo 1 es una enfermedad crónica e incurable que afecta a millones de personas en todo el mundo. Se caracteriza por una destrucción total o parcial de las células beta del páncreas. Estas células son las encargadas de producir la insulina, hormona principal en el control de glucosa en sangre. Valores altos de glucosa en la sangre mantenidos en el tiempo afectan negativamente a la salud, provocando complicaciones de diversa índole. Es por eso que los pacientes con diabetes mellitus tipo 1 necesitan recibir insulina de forma exógena. Desde que se consiguiera en 1921 aislar la insulina para poder utilizarla en clínica humana, y se empezaran a desarrollar las primeras técnicas de monitorización de glucemia, se han producido grandes avances en el tratamiento con insulina. Actualmente, las líneas de investigación que se están siguiendo en relación a la mejora de la calidad de vida de los pacientes diabéticos, tienen fundamentalmente 2 vertientes: una primera que se centra en la investigación en células madre para la reposición de las células beta y una segunda vertiente de carácter más tecnológico. Dentro de esta segunda vertiente, están abiertas varias líneas de investigación, entre las que se encuentran el desarrollo de nuevos análogos de insulina que permitan emular más fielmente la secreción endógena del páncreas, el desarrollo de monitores continuos de glucosa no invasivos, bombas de insulina capaces de administrar distintos perfiles de insulina y la inclusión de sistemas de ayuda a la decisión y telemedicina. El mayor reto al que se enfrentan los investigadores es el de conseguir desarrollar un páncreas artificial, es decir, desarrollar algoritmos que permitan disponer de un control automático de la glucosa. La principal barrera que se encuentra para conseguir un control riguroso de la glucosa es la alta variabilidad que presenta su metabolismo. Esto es especialmente significativo durante la compensación de las comidas. Esta variabilidad junto con el retraso en la absorción y actuación de la insulina administrada de forma subcutánea favorece la aparición de hipoglucemias tardías (complicación aguda más importante del tratamiento con insulina) a consecuencia de la sobreactuación del controlador. Las propuestas presentadas en este trabajo hacen especial hincapié en sobrellevar estas dificultades. Así, se utilizan modelos intervalares para representar la fisiología del paciente, y poder tener en cuenta la incertidumbre en sus parámetros. Este tipo de estrategia se ha utilizado tanto en la propuesta de dosificación automática en lazo abierto como en el algoritmo en lazo cerrado. Además la principal idea de diseño de esta última propuesta es evitar la sobreactuación del controlador evitando hipoglucemias y añadiendo robustez ante fallos en el sensor de glucosa y en la estimación de las comidas. Los algoritmos propuestos han sido validados en simulación y en clínica. / [CA] La diabetis mellitus tipus 1 és una malaltia crònica i incurable que afecta milions de persones en tot el món. Es caracteritza per una destrucció total o parcial de les cèl.lules beta del pàncrees. Aquestes cèl.lules són les encarregades de produir la insulina, hormona principal en el control de glucosa en sang. Valors alts de glucosa en la sang mantinguts en el temps afecten negativament la salut, provocant complicacions de diversa índole. És per això que els pacients amb diabetis mellitus tipus 1 necessiten rebre insulina de forma exògena. Des que s'aconseguís en 1921 aïllar la insulina per a poder utilitzar-la en clínica humana, i es començaren a desenrotllar les primeres tècniques de monitorització de glucèmia, s'han produït grans avanços en el tractament amb insulina. Actualment, les línies d'investigació que s'estan seguint en relació a la millora de la qualitat de vida dels pacients diabètics, tenen fonamentalment 2 vessants: un primer que es centra en la investigació de cèl.lules mare per a la reposició de les cèl.lules beta i un segon vessant de caràcter més tecnològic. Dins d' aquest segon vessant, estan obertes diverses línies d'investigació, entre les que es troben el desenrotllament de nous anàlegs d'insulina que permeten emular més fidelment la secreció del pàncrees, el desenrotllament de monitors continus de glucosa no invasius, bombes d'insulina capaces d'administrar distints perfils d'insulina i la inclusió de sistemes d'ajuda a la decisió i telemedicina. El major repte al què s'enfronten els investigadors és el d'aconseguir desenrotllar un pàncrees artificial, és a dir, desenrotllar algoritmes que permeten disposar d'un control automàtic de la glucosa. La principal barrera que es troba per a aconseguir un control rigorós de la glucosa és l'alta variabilitat que presenta el seu metabolisme. Açò és especialment significatiu durant la compensació dels menjars. Aquesta variabilitat junt amb el retard en l'absorció i actuació de la insulina administrada de forma subcutània afavorix l'aparició d'hipoglucèmies tardanes (complicació aguda més important del tractament amb insulina) a conseqüència de la sobreactuació del controlador. Les propostes presentades en aquest treball fan especial insistència en suportar aquestes dificultats. Així, s'utilitzen models intervalares per a representar la fisiologia del pacient, i poder tindre en compte la incertesa en els seus paràmetres. Aquest tipus d'estratègia s'ha utilitzat tant en la proposta de dosificació automàtica en llaç obert com en l' algoritme en llaç tancat. A més, la principal idea de disseny d'aquesta última proposta és evitar la sobreactuació del controlador evitant hipoglucèmies i afegint robustesa. / Revert Tomás, A. (2015). Robust strategies for glucose control in type 1 diabetes [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/56001

Cross-cultural research requires tests of measurement invariance to determine if different populations have equivalent latent constructs. A psychometric assessment of the Agricultural Production Perspectives Scale (APPS) was necessary to determine the validity of the scale constructed and whether data from multiple countries could be compared. Using 918 farmers sampled from Kenya, Uganda, Mali, and Lesotho, I conducted exploratory factor analysis and scale reliability tests to determine whether the item loadings and factors were equivalent across populations. No factor structure could be obtained across country or agroecological populations. The data were reanalyzed within each agroecology to determine localized factor structures. Results indicate that a market driven factor and agrarian driven factor tend to emerge across multiple agroecologies suggesting some emergence of latent variables. Recommendations for scale revisions are included to increase reliability and measurement invariance. / Master of Science / CCRA-8 (Technology Networks for Sustainable Innovation)