Finding new examples of compact simply connected spaces admitting a Riemannian metric of positive sectional curvature is a fundamental problem in differential geometry. Likewise, studying topological properties of families of manifolds is very interesting to topologists. The Eschenburg spaces combine both of those interests: they are positively curved Riemannian manifolds whose topological classification is known. There is a second family consisting of the Witten manifolds: they are the examples of compact simply connected spaces admitting Einstein metrics of positive Ricci curvature. Thirdly, there is a notion of generalized Witten manifold as well. Topologically, all three families share the same cohomology ring. This common ring structure motivates the definition of a manifold of type r, where r is the order of the fourth cohomology group. In 1991, M. Kreck and S. Stolz classified manifolds M of type r up to homeomorphism and dieomorphism using invariants s̄[subscript i](M) and s[subscript i](M), for i = 1, 2, 3. This gave rise to many new examples of nondieomorphic but homeomorphic manifolds. In this dissertation, new versions of the homeomorphism and dieomorphism classification of manifolds of type r are proven. In particular, we can replace s̄₁ and s̄₃ by the first Pontrjagin class and the self-linking number in the homeomorphism classification of spin manifolds of type r. As the formulas of the two latter invariants are in general much easier to compute, this simplifies the classification of these manifolds up to homeomorphism significantly. / Graduation date: 2012

In recent years, increasing attention has turned toward the effect of health information or health knowledge on nutrient intake. In determining the effect of health information on nutrient demand, researchers face the estimation problem of dealing with the endogeneity of health information knowledge. The standard approach for dealing with this problem is an instrumental variables (IV) procedure. Unfortunately, recent research has demonstrated that the IV procedure may not be reliable in the types of data sets that contain health information and nutrient intakes because the instruments are not sufficiently correlated with the endogenous variables (i.e., instruments are weak). This thesis compares the reliability of the IV procedure (and the Hausman test) with a relatively new procedure, directed graphs, given weak instruments. The goal is to determine if the method of directed graphs performs better in identifying an endogenous variable and also relevant instruments. The performance of the Hausman test and directed graphs are first assessed through conducting a Monte-Carlo sampling experiment containing weak instruments. Because the structure of the model is known in the Monte-Carlo experiment, these results are used as a guideline to determine which procedure would be more reliable in a real world setting. The procedures are then applied to a real-world cross-sectional dataset on nutrient intake. This thesis provides empirical evidence that neither the IV estimator (and Hausman test) or the directed graphs are reliable when instruments are weak, as in a cross-sectional dataset.

The world is experiencing yet another energy- and fuel predicament as oil prices are escalating to new hights. Alternative fuels are being promoted globally as the increasing gasoline prices trigger inflation. Basic food commodities are some of the goods hit by this inflation and the purpose of this thesis is to analyse whether the higher maize and sugar prices are having any effect on the expanding ethanol production. This thesis focuses on the two major crop inputs in ethanol production: maize (in the US) and sugar cane (in Brazil). Econometric tests using cross-sectional data were carried through to find the elasticities of the variables. The crops prices were tested against ethanol output using the log-linear model in several regressions to find a relationship. In addition, the output levels of the crops were tested using the same method. It was found that maize prices and output affects ethanol production. Sugar cane prices do not have any significant impact on ethanol production while sugar cane output has a small, yet significant relationhip with ethanol. Consequently, ethanol’s rise in the fuel market could be a result of increased maize input, rather than sugar. / Dagens värld upplever ännu ett energi- och bränsle predikament när oljepriser eskalerar mot nya höjder. Alternativa bränslen marknadsförs globalt samtidigt som de stigande bensinpriserna stimulerar inflationen. Några av de varor som drabbas av denna inflation är grundläggande livsmedelsprodukter och syftet med denna uppsats är att analysera huruvida de högre priserna på majs och socker påverkar den expanderande etanolproduktionen. Uppsatsen fokuserar på de två stora grödor som används som insatsvaror vid framställningen av etanol: majs (i USA) och sockerrör (i Brasilien). Ekonometriska tester genomfördes för att erhålla variablernas elasticiteter med hjälp av den cross-sectional data som behandlades. Genom log-linear modellen utfördes det ett antal regressioner för att hitta ett samband mellan grödornas priser och etanolproduktionen. Därutöver genomfördes tester för att hitta sambandet mellan grödornas utbud och etanol med hjälp av samma modell. Det upptäcktes att både pris och utbudet av majs påverkar etanolproduktionen. Sockerrörspriser har ingen signifikant inverkan på etanolproduktionen medan utbudet av sockerrör har en signifikant, om än svag, relation till etanol. Följaktligen kan etanols tillväxt i  bränslemarknaden tolkas som ett resultat av en stigande majsinsats snarare än sockerinstats vid etanolframställningen.

Cross-sectional surveys are often used in epidemiological studies to identify subjects with a disease. When estimating the survival function from onset of disease, this sampling mechanism introduces bias, which must be accounted for. If the onset times of the disease are assumed to be coming from a stationary Poisson process, this bias, which is caused by the sampling of prevalent rather than incident cases, is termed length-bias. A one-sample Kolomogorov-Smirnov type of goodness-of-fit test for right-censored length-biased data is proposed and investigated with Weibull, log-normal and log-logistic models. Algorithms detailing how to efficiently generate right-censored length-biased survival data of these parametric forms are given. Simulation is employed to assess the effects of sample size and censoring on the power of the test. Finally, the test is used to evaluate the goodness-of-fit using length-biased survival data of patients with dementia from the Canadian Study of Health and Aging.

Introduction. Wrist (Colles') and forearm fractures commonly occur when a person falls on the outstretched forearm and the force exceeds bone strength. There is lack of experimental evidence testing the available force prediction models and assessing factors that determine forearm forces during a fall.<p> Objective. The primary objective was to compare experimentally measured force peaks (F1max-E and F2max-E) to the force peaks that were predicted by an engineering based force prediction model (F1max-M and F2max-M), at heights greater than 5cm. The second objective was to describe the relationships between the experimentally measured peak forces and forearm bone and muscle strength properties, body mass, and stature as a function of fall height.<p> Methods. Using 3D motion tracking, we assessed the first (F1max) and second (F2max) peak forces from 10 young adults (5 male; 5 female) who volunteered to fall from heights up to 25cm onto a foam covered force plate. Peripheral QCT was used to determine the bone strength index (BSIc), strength-strain index (SSIp), and muscle cross sectional area (MCSA) of each participant. Two 2x8 between-within factorial ANOVAs determined the difference between the experimental and model force peaks, with post hoc analyses at all fall heights. Pearson's correlation was used to determine the relationship between the pQCT-derived bone and muscle strength indices and the force peaks.<p> Results. There was no significant differences between F1max-E and F1max-M across all fall heights, but the model significantly over-predicted the F2max-E across all fall heights. After controlling F1max-E and F2max-E for body mass, the force peaks appeared to be weakly related to the anthropometric as well as bone and muscle strength outcomes (r=0.2-0.7, p>0.05). The relationship between bone and muscle strength outcomes appeared to have a tendency to get stronger at higher fall heights.<p> Conclusion. The model predicted experimental F1max, but not experimental F2max. This study presents preliminary pilot results. Larger sample size is needed to confirm whether incorporating bone and muscle strength estimates into fall force prediction models could enhance forearm fracture risk assessments.

Introduction. Wrist (Colles') and forearm fractures commonly occur when a person falls on the outstretched forearm and the force exceeds bone strength. There is lack of experimental evidence testing the available force prediction models and assessing factors that determine forearm forces during a fall.<p> Objective. The primary objective was to compare experimentally measured force peaks (F1max-E and F2max-E) to the force peaks that were predicted by an engineering based force prediction model (F1max-M and F2max-M), at heights greater than 5cm. The second objective was to describe the relationships between the experimentally measured peak forces and forearm bone and muscle strength properties, body mass, and stature as a function of fall height.<p> Methods. Using 3D motion tracking, we assessed the first (F1max) and second (F2max) peak forces from 10 young adults (5 male; 5 female) who volunteered to fall from heights up to 25cm onto a foam covered force plate. Peripheral QCT was used to determine the bone strength index (BSIc), strength-strain index (SSIp), and muscle cross sectional area (MCSA) of each participant. Two 2x8 between-within factorial ANOVAs determined the difference between the experimental and model force peaks, with post hoc analyses at all fall heights. Pearson's correlation was used to determine the relationship between the pQCT-derived bone and muscle strength indices and the force peaks.<p> Results. There was no significant differences between F1max-E and F1max-M across all fall heights, but the model significantly over-predicted the F2max-E across all fall heights. After controlling F1max-E and F2max-E for body mass, the force peaks appeared to be weakly related to the anthropometric as well as bone and muscle strength outcomes (r=0.2-0.7, p>0.05). The relationship between bone and muscle strength outcomes appeared to have a tendency to get stronger at higher fall heights.<p> Conclusion. The model predicted experimental F1max, but not experimental F2max. This study presents preliminary pilot results. Larger sample size is needed to confirm whether incorporating bone and muscle strength estimates into fall force prediction models could enhance forearm fracture risk assessments.

Cross-sectional surveys are often used in epidemiological studies to identify subjects with a disease. When estimating the survival function from onset of disease, this sampling mechanism introduces bias, which must be accounted for. If the onset times of the disease are assumed to be coming from a stationary Poisson process, this bias, which is caused by the sampling of prevalent rather than incident cases, is termed length-bias. A one-sample Kolomogorov-Smirnov type of goodness-of-fit test for right-censored length-biased data is proposed and investigated with Weibull, log-normal and log-logistic models. Algorithms detailing how to efficiently generate right-censored length-biased survival data of these parametric forms are given. Simulation is employed to assess the effects of sample size and censoring on the power of the test. Finally, the test is used to evaluate the goodness-of-fit using length-biased survival data of patients with dementia from the Canadian Study of Health and Aging.

Analytical Model of Traffic Signal Structures (TSS) is developed based on a continuous system method to observe dynamic characteristics of the structures. Conventional and basic continuous system method can show the approximate dynamic characteristics of the TSS, but the discretized continuous analytical model is proposed to get more accurate and realistic results of the TSS. In addition, the discretized continuous model can alternatively analyze the effect of the tapered cross-sectional members which are real model of TSS. For the verification of the analytical model, the dynamic characteristics of the numerical solutions by modal analysis in ABAQUS and the results of experimental measurements are provided. Compared with the numerical solutions and the experimental results, the analytical solution for each member shows its considerable accuracy. In addition, it will be also able to accurately express the effects of the linearly tapered cross-sectional member with more discretized continuous structural system. Moreover, the discretized analytical model of the TSS has the usability to observe the effects of boundary flexibility.

Abstract Mutual fund, which has become a popular domestic investment tool possess a lot of advantages. However, how on earth investors could choose the fund that worth investing is often confusing. This research begins from the qualities of mutual fund itself and it¡¦s manager. I¡¦ll discuss the influence that the type of fund, achievement in the past, scale of fund, turnover rate, risks and investors¡¦ age, sex, schooling record and experiences would have on its achievement. Hoping through these different sides of thinking would provide a direction for investors when choosing Mutual fund. This research was done in the period from January, 1997 to January, 2002, after excluding some of the survivorship bias, we sift through the whole information in the five years, and we acquire 59 open type that would be used as sample fund in this research. We adopt Jensen-performance-estimated model and 4-factor model as achievement measure standard. By setting tests of Pearson Correlation Coefficients and Durbin-Watson, plus OLS, we estate mate Jensen-performance-estimated model and 4-factor model, and the result of its alpha would be cross-analyzed with the multiple linear regression model, thus we¡¦ll clearly see the relation of quality between mutual fund and their managers. Before going on the cross-analysis, in order to seek for the best estimating method, we test heteroscedasticity by residual pattern and Breusch-Pagan Test. Since it comes out there is no heteroscedasticity, we still conduct the process by OLS to observe how the relation between the qualities of mutual fund itself and that of managers will affect on fund achievement. We found 4-factor model is more convincing among all other achievement evaluation model though the results vary from types of model. In the achievement index, a positive and remarkable difference type of fund is from Jensen index,, which coincided with Dahlquist, Engstrom, and Soderlind(2000)¡BJia-ling Hong(2000). Under 4-factor model, global fund and region ones appear obvious negative related, but high-tech types and general are not convincing at all. Besides, the influence of reward in the past and the scale of it shows the conclusion that two model are related positively in achievement side of short and long term, but negative in scale. Moreover, the risks can¡¦t explain the achievement difference, and turnover-rate doesn¡¦t affect achievement directly, the outcome coincided with the prove of Ippolito(1989) . Finally, which this research shows that the types results vary from managers personal qualities, but most of them can¡¦t explain the achievement differences. We only catch that under Jensen index, managers who get their MBA degree abroad tends to have positive relation in achievement of fund.

Prior research finds that mutual fund investors have adequate ability to select funds which superior performance remains persistent. Following the work of Keswani and Stolin (2008), we use a fund netflow as a proxy for investors¡¦ preference to examine whether the smart money effect exists. Furthermore, this paper differs from prior research by combining the smart money phenomenon and fund firm¡¦s marketing activities (the advertising expenditure of mutual funds). This paper generates four empirical findings. (1) Mutual funds with positive netflow subsequently have positive Carhart four-factor alpha, that is, the ¡§smart money effect¡¨ exists in Taiwanese mutual fund market. (2) The smart money effect is caused by investors¡¦ buying decisions. (3) The smart money effect is only a short-lived phenomenon. (4) Our evidence shows that advertising of funds can explain the smart money effect in Taiwanese open-end mutual fund market.