Tooth cusp radius of curvature (RoC) has been hypothesized to play an important role in food item breakdown, but has remained largely unstudied due to difficulties in measuring and modeling RoC in multicusped teeth. We tested these hypotheses using a parametric model of a four cusped, maxillary, bunodont molar in conjunction with finite element analysis. When our data failed to support existing hypotheses, we put forth and tested the Complex Cusp Hypothesis which states that, during brittle food items breakdown, an optimally shaped molar would be maximizing stresses in the food item while minimizing stresses in the enamel. After gaining support for this hypothesis, we tested the effects of relative food item size on optimal molar morphology and found that the optimal set of RoCs changed as relative food item size changed. However, all optimal morphologies were similar, having one dull cusp that produced high stresses in the food item and three cusps that acted to stabilize the food item. We then set out to measure tooth cusp RoC in several species of extant apes to determine if any of the predicted optimal morphologies existed in nature and whether tooth cusp RoC was correlated with diet. While the optimal morphologies were not found in apes, we did find that tooth cusp RoC was correlated with diet and folivores had duller cusps while frugivores had sharper cusps. We hypothesize that, because of wear patterns, tooth cusp RoC is not providing a mechanical advantage during food item breakdown but is instead causing the tooth to wear in a beneficial fashion. Next, we investigate two possible relationships between tooth cusp RoC and enamel thickness, as enamel thickness plays a significant role in the way a tooth wears, using CT scans from hundreds of unworn cusps. There was no relationship between the two variables, indicating that selection may be acting on both variables independently to create an optimally shaped tooth. Finally, we put forth a framework for testing the functional optimality in teeth that takes into account tooth strength, food item breakdown efficiency, and trapability (the ability to trap and stabilize a food item).

It is believed that a large number of people experience remaining symptoms after COVID-19, so-called post-COVID. The formal definition and diagnostic criteria of post-COVID have been a scientific controversy. So far, there is no reliable system for distinguishing the severity of post-COVID. This type of measurement would be helpful in future targeted therapies. Therefore, this thesis aims to evaluate the relationship between an individual’s functional status today and the symptoms present as well as identify relevant groups of post-COVID based on these 17 long-term symptoms of post-COVID. Further, to produce a model for which of these groups an individual belongs to. By using cluster analysis and ordinal logistic regression, Post-COVID Syndrome scores are produced. That is based upon both subjects who were hospitalised and those who were not, collected through a project called COMBAT post-covid. The individuals are then divided into groups based on these scores, and a prediction model is made using ordinal logistic regression and backward deletion. Three well-separated groups of post-COVID are found based on the produced scores. The prediction model indicates that the nine variables Sex, BMI, Smoking, Snuff, Heart disease, Lung disease, Diabetes, Chronic pain and Symptom severity at the onset seem important for predicting someone’s group. This study showed that the remaining symptoms affected an individual’s functional status, including self-reported working ability and general health.

Denna studie syftar till att anpassa Skogsviks konkursprediktionsmodell från 1987 för svenska små och medelstora företag (SMEs). Studien fokuserar även på hur nya redovisningsstandarder för immateriella tillgångar påverkar modellen. Genom att inkludera ett nyckeltal som speglar förhållandet mellan immateriella tillgångar och totala tillgångar (IA) i den justerade modellen, möjliggör studien en jämförelse med Skogsviks Modell. Detta för att utvärdera nyckeltalets relevans i förutsägelsen av konkursrisk för SMEs och undersöka den justerade modellens prediktionsförmåga. Studien undersöker även vilka av Skogsviks Modells variabler som är effektiva för att förutspå konkurs för SMEs. Denna studie bidrar till forskning om redovisningsbaserade konkursprediktionsmodeller för SMEs inom ramen för svensk redovisningspraxis. Modellen skapas genom en probit regression och utvärderas sedan genom två valideringstester, Receiver Operating Characteristic (ROC) och Cumulative Accuracy Profile (CAP). Analysen omfattar data från 544 svenska företag, varav 81 har gått i konkurs. Resultaten visar att den justerade modellen, med nyckeltalet IA, har en högre prediktionsförmåga för SMEs jämfört med Skogsviks Modell utifrån dagens redovisningsstandarder för immateriella tillgångar. Studien bekräftar även att nyckeltalen ROA (Avkastning på totala tillgångar), ETA (Eget kapitalandel) och IA (Immateriella tillgångar i relation till totala tillgångar) är effektiva indikatorer för att förutspå konkursrisken för svenska SMEs idag.

Protestants often think that 1he ROC has no mission just because Orthodoxy pays to more attention to Service life. We tried to understand motives, goals and objectives of the ROC missionary activity. We found out that the ecclesiologic way of thinking was the basis missionary idea of the eastern missionary practice and it showed itself differently in special historical moments. This work divides the whole history of the Orthodox Church in Russia (XI - XX centuries) into 3 periods of mission and makes its brief survey and analysis. In the first period (XI-XVI) only single monks-colonialists realized the Great Commission among Finnish tribes and russifed it Only certain people used the methods of well planned contextualizating mission, like Stephen of Penn. During the second period (1552-middl.XIX) the ROC worked in close combination with the State to the detriment of the deep evangelization of natives. In the third period (the middle of XIX- the beginning of XX) the missionaries of Orthodox Missionary Society used all the achievements of the native and foreign missionary: contextualization, Liturgies in the national languages. enlightenment by schools of all levels, the training of national leaders, social work ets. At the present time, the ROC is renewing its own mission tradition after the sleep of the Soviet period. / Christian Spirituality, Church History and Missiology / M. Th. (Missiology)

Protestants often think that 1he ROC has no mission just because Orthodoxy pays to more attention to Service life. We tried to understand motives, goals and objectives of the ROC missionary activity. We found out that the ecclesiologic way of thinking was the basis missionary idea of the eastern missionary practice and it showed itself differently in special historical moments. This work divides the whole history of the Orthodox Church in Russia (XI - XX centuries) into 3 periods of mission and makes its brief survey and analysis. In the first period (XI-XVI) only single monks-colonialists realized the Great Commission among Finnish tribes and russifed it Only certain people used the methods of well planned contextualizating mission, like Stephen of Penn. During the second period (1552-middl.XIX) the ROC worked in close combination with the State to the detriment of the deep evangelization of natives. In the third period (the middle of XIX- the beginning of XX) the missionaries of Orthodox Missionary Society used all the achievements of the native and foreign missionary: contextualization, Liturgies in the national languages. enlightenment by schools of all levels, the training of national leaders, social work ets. At the present time, the ROC is renewing its own mission tradition after the sleep of the Soviet period. / Christian Spirituality, Church History and Missiology / M. Th. (Missiology)

Le ranking multipartite est un problème d'apprentissage statistique qui consiste à ordonner les observations qui appartiennent à un espace de grande dimension dans le même ordre que les labels, de sorte que les observations avec le label le plus élevé apparaissent en haut de la liste. Cette thèse vise à comprendre la nature probabiliste du problème de ranking multipartite afin d'obtenir des garanties théoriques pour les algorithmes de ranking. Dans ce cadre, la sortie d'un algorithme de ranking prend la forme d'une fonction de scoring, une fonction qui envoie l'espace des observations sur la droite réelle et l'ordre final est construit en utilisant l'ordre induit par la droite réelle. Les contributions de ce manuscrit sont les suivantes : d'abord, nous nous concentrons sur la caractérisation des solutions optimales de ranking multipartite. Une nouvelle condition sur les rapports de vraisemblance est introduite et jugée nécessaire et suffisante pour rendre le problème de ranking multipartite bien posé. Ensuite, nous examinons les critères pour évaluer la fonction de scoring et on propose d'utiliser une généralisation de la courbe ROC nommée la surface ROC pour cela ainsi que le volume induit par cette surface. Pour être utilisée dans les applications, la contrepartie empirique de la surface ROC est étudiée et les résultats sur sa consistance sont établis. Le deuxième thème de recherche est la conception d'algorithmes pour produire des fonctions de scoring. La première procédure est basée sur l'agrégation des fonctions de scoring apprises sur des sous-problèmes de ranking binaire. Dans le but d'agréger les ordres induits par les fonctions de scoring, nous utilisons une approche métrique basée sur le de Kendall pour trouver une fonction de scoring médiane. La deuxième procédure est une méthode récursive, inspirée par l'algorithme TreeRank qui peut être considéré comme une version pondérée de CART. Une simple modification est proposée pour obtenir une approximation de la surface ROC optimale en utilisant une fonction de scoring constante par morceaux. Ces procédures sont comparées aux algorithmes de l'état de l'art pour le ranking multipartite en utilisant des jeux de données réelles et simulées. Les performances mettent en évidence les cas où nos procédures sont bien adaptées, en particulier lorsque la dimension de l'espace des caractéristiques est beaucoup plus grand que le nombre d'étiquettes. Enfin, nous revenons au problème de ranking binaire afin d'établir des vitesses minimax adaptatives de convergence. Ces vitesses sont montrées pour des classes de distributions contrôlées par la complexité de la distribution a posteriori et une condition de faible bruit. La procédure qui permet d'atteindre ces taux est basée sur des estimateurs de type plug-in de la distribution a posteriori et une méthode d'agrégation utilisant des poids exponentiels.

Many continuous medical tests often rely on a threshold for diagnosis. There are two sequential testing strategies of interest: Believe the Positive (BP) and Believe the Negative (BN). BP classifies a patient positive if either the first test is greater than a threshold θ1 or negative on the first test and greater than θ2 on the second test. BN classifies a patient positive if the first test is greater than a threshold θ3 and greater than θ4 on the second test. Threshold pairs θ = (θ1, θ2) or (θ3, θ4), depending on strategy, are defined as optimal if they maximized GYI = Se + r(Sp – 1). Of interest is to determine if these optimal threshold, or optimal operating point (OOP), estimates are “good” when calculated from a sample. The methods proposed in this dissertation derive formulae to estimate θ assuming tests follow a binormal distribution, using the Newton-Raphson algorithm with ridging. A simulation study is performed assessing bias, root mean square error, percentage of over estimation of Se/Sp, and coverage of simultaneous confidence intervals and confidence regions for sets of population parameters and sample sizes. Additionally, OOPs are compared to the traditional empirical approach estimates. Bootstrapping is used to estimate the variance of each optimal threshold pair estimate. The study shows that parameters such as the area under the curve, ratio of standard deviations of disease classification groups within tests, correlation between tests within a disease classification, total sample size, and allocation of sample size to each disease classification group were all influential on OOP estimation. Additionally, the study shows that this method is an improvement over the empirical estimate. Equations for researchers to use in estimating total sample size and SCI width are also developed. Although the models did not produce high coefficients of determination, they are a good starting point for researchers when designing a study. A pancreatic cancer dataset is used to illustrate the OOP estimation methodology for sequential tests.

The practice of sequential testing is followed by the evaluation of accuracy, but often not by the evaluation of cost. This research described and compared three sequential testing strategies: believe the negative (BN), believe the positive (BP) and believe the extreme (BE), the latter being a less-examined strategy. All three strategies were used to combine results of two medical tests to diagnose a disease or medical condition. Descriptions of these strategies were provided in terms of accuracy (using the maximum receiver operating curve or MROC) and cost of testing (defined as the proportion of subjects who need 2 tests to diagnose disease), with the goal to minimize the number of tests needed for each subject while maintaining test accuracy. It was shown that the cost of the test sequence could be reduced without sacrificing accuracy beyond an acceptable range by setting an acceptable tolerance (q) on maximum test sensitivity. This research introduced a newly-developed ROC curve reflecting this reduced sensitivity and cost of testing called the Minimum Cost Maximum Receiver Operating Characteristic (MCMROC) curve. Within these strategies, four different parameters that could influence the performance of the combined tests were examined: the area under the curve (AUC) of each individual test, the ratio of standard deviations (b) from assumed underlying disease and non-disease populations, correlation (rho) between underlying disease populations, and disease prevalence. The following patterns were noted: Under all parameter settings, the MROC curve of the BE strategy never performed worse than the BN and BP strategies, and it most frequently had the lowest cost. The parameters tended to have less of an effect on the MROC and MCMROC curves than they had on the cost curves, which were affected greatly. The AUC values and the ratio of standard deviations both had a greater effect on cost curves, MROC curves, and MCMROC curves than prevalence and correlation. The use of BMI and plasma glucose concentration to diagnose diabetes in Pima Indians was presented as an example of a real-world application of these strategies. It was found that the BN and BE strategies were the most consistently accurate and least expensive choice.

Doctor of Philosophy / Department of Statistics / Paul I. Nelson / Rank based inference using independent random samples to compare K>1 continuous distributions, called the K-sample problem, based on precedence probabilities is developed and explored. There are many parametric and nonparametric approaches, most dealing with hypothesis testing, to this important, classical problem. Most existing tests are designed to detect differences among the location parameters of different distributions. Best known and most widely used of these is the F- test, which assumes normality. A comparable nonparametric test was developed by Kruskal and Wallis (1952). When dealing with location-scale families of distributions, both of these tests can perform poorly if the differences among the distributions are among their scale parameters and not in their location parameters. Overall, existing tests are not effective in detecting changes in both location and scale. In this dissertation, I propose a new class of rank-based, asymptotically distribution- free tests that are effective in detecting changes in both location and scale based on precedence probabilities. Let X_{i} be a random variable with distribution function F_{i} ; Also, let _pi_ be the set of all permutations of the numbers (1,2,...,K) . Then P(X_{i_{1}}<...<X_{i_{K}}) is a precedence probability if (i_{1},...,i_{K}) belongs to _pi_. Properties of these of tests are developed using the theory of U-statistics (Hoeffding, 1948). Some of these new tests are related to volumes under ROC (Receiver Operating Characteristic) surfaces, which are of particular interest in clinical trials whose goal is to use a score to separate subjects into diagnostic groups. Motivated by this goal, I propose three new index measures of the separation or similarity among two or more distributions. These indices may be used as “effect sizes”. In a related problem, Properties of precedence probabilities are obtained and a bootstrap algorithm is used to estimate an interval for them.

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