Fiber-reinforced composite fixed dental prostheses: Studies of the materials used as pontics

Fiber-reinforced composite fixed dental prostheses – Studies of the materials used as pontics University of Turku, Faculty of Medicine, Institute of Dentistry, Department of Biomaterials Science, Finnish Doctoral Program in Oral Sciences – FINDOS, Annales Universitatis Turkuensis, Turku, Finland 2015 Fiber-reinforced composites (FRC), a non-metallic biomaterial, represent a suitable alternative in prosthetic dentistry when used as a component of fixed dental prostheses (FDPs). Some drawbacks have been identified in the clinical performance of FRC restorations, such as delamination of the veneering material and fracture of the pontic. Therefore, the current series of studies were performed to investigate the possibilities of enhancing the mechanical and physical properties of FRC FDPs by improving the materials used as pontics, to then heighten their longevity. Four experiments showed the importance of the pontic design and surface treatment in the performance of FRC FDPs. In the first, the load-bearing capacities of inlay-retained FRC FDPs with pontics of various materials and thicknesses were evaluated. Three different pontic materials were assessed with different FRC framework vertical positioning. Thicker pontics showed increased load-bearing capacities, especially ceramic pontics. A second study was completed investigating the influence of the chemical conditioning of the ridge-lap surface of acrylic resin denture teeth on their bonding to a composite resin. Increased shear bond strength demonstrated the positive influence of the pretreatment of the acrylic surfaces, indicating dissolution of the denture surfaces, and suggesting potential penetration of the monomer systems into the surface of denture teeth. A third study analyzed the penetration depth of different monomer systems on the acrylic resin denture teeth surfaces. The possibility of establishing a durable bond between acrylic pontics and FRC frameworks was demonstrated by the ability of monomers to penetrate the surface of acrylic resin denture teeth, measured by a confocal scanning type microscope. A fourth study was designed to evaluate the load-bearing capacities of FRC FDPs using the findings of the previous three studies. In this case, the performance of pre-shaped acrylic resin denture teeth used as pontics with different composite resins as filling materials was evaluated. The filling material influenced the load-bearing capacities, providing more durable FRC FDPs. It can be concluded that the mechanical and physical properties of FRC FDPs can be improved as has been shown in the development of this thesis. The improvements reported then might provide long lasting prosthetic solutions of this kind, positioning them as potentially permanent rehabilitation treatments. Key words: fiber-reinforced composite, fixed dental prostheses, inlay-retained bridges, adhesion, acrylic resin denture teeth, dental material.

Ordered probit regression analysis of the effect of brand name on beer acceptance by consumers

Ordered probit regression was used to analyze data of sensory acceptance tests designed to study the effect of brand name on the acceptability of beer samples. Eight different brands of Pilsen beer were evaluated by 101 consumers in two sessions of acceptance tests: blind evaluation and brand information test. Ordered probit regression, although a relatively sophisticated technique compared to others used to analyze sensory data, was chosen to enable the observation of consumers' behavior using graphical interpretations of estimated probabilities plotted against hedonic scales. It can be concluded that brands B, C, and D had a positive effect on the sensory acceptance of the product, whereas brands A, F, G, and H had a negative influence on consumers' evaluation of the samples. On the other hand, brand E had little influence on consumers' assessment.

Multivariate study and regression analysis of gluten-free granola

This study developed a gluten-free granola and evaluated it during storage with the application of multivariate and regression analysis of the sensory and instrumental parameters. The physicochemical, sensory, and nutritional characteristics of a product containing quinoa, amaranth and linseed were evaluated. The crude protein and lipid contents ranged from 97.49 and 122.72 g kg-1 of food, respectively. The polyunsaturated/saturated, and n-6:n-3 fatty acid ratios ranged from 2.82 and 2.59:1, respectively. Granola had the best alpha-linolenic acid content, nutritional indices in the lipid fraction, and mineral content. There were good hygienic and sanitary conditions during storage; probably due to the low water activity of the formulation, which contributed to inhibit microbial growth. The sensory attributes ranged from 'like very much' to 'like slightly', and the regression models were highly fitted and correlated during the storage period. A reduction in the sensory attribute levels and in the product physical stabilisation was verified by principal component analysis. The use of the affective test acceptance and instrumental analysis combined with statistical methods allowed us to obtain promising results about the characteristics of gluten-free granola.

PERFORMANCE ANALYSIS OF A TACTICAL ASSET ALLOCATION – Evidence from the Black–Litterman model based fixed income portfolio

Over time the demand for quantitative portfolio management has increased among financial institutions but there is still a lack of practical tools. In 2008 EDHEC Risk and Asset Management Research Centre conducted a survey of European investment practices. It revealed that the majority of asset or fund management companies, pension funds and institutional investors do not use more sophisticated models to compensate the flaws of the Markowitz mean-variance portfolio optimization. Furthermore, tactical asset allocation managers employ a variety of methods to estimate return and risk of assets, but also need sophisticated portfolio management models to outperform their benchmarks. Recent development in portfolio management suggests that new innovations are slowly gaining ground, but still need to be studied carefully. This thesis tries to provide a practical tactical asset allocation (TAA) application to the Black–Litterman (B–L) approach and unbiased evaluation of B–L models’ qualities. Mean-variance framework, issues related to asset allocation decisions and return forecasting are examined carefully to uncover issues effecting active portfolio management. European fixed income data is employed in an empirical study that tries to reveal whether a B–L model based TAA portfolio is able outperform its strategic benchmark. The tactical asset allocation utilizes Vector Autoregressive (VAR) model to create return forecasts from lagged values of asset classes as well as economic variables. Sample data (31.12.1999–31.12.2012) is divided into two. In-sample data is used for calibrating a strategic portfolio and the out-of-sample period is for testing the tactical portfolio against the strategic benchmark. Results show that B–L model based tactical asset allocation outperforms the benchmark portfolio in terms of risk-adjusted return and mean excess return. The VAR-model is able to pick up the change in investor sentiment and the B–L model adjusts portfolio weights in a controlled manner. TAA portfolio shows promise especially in moderately shifting allocation to more risky assets while market is turning bullish, but without overweighting investments with high beta. Based on findings in thesis, Black–Litterman model offers a good platform for active asset managers to quantify their views on investments and implement their strategies. B–L model shows potential and offers interesting research avenues. However, success of tactical asset allocation is still highly dependent on the quality of input estimates.

Liquidity Risk in the Finnish Stock Market

This study explores the pricing of liquidity risk and its effect on stock returns in the Finnish stock market. In addition to that, it investigates whether there is a trend in liquidity risk. Finally, it analyzes whether the two chosen liquidity measures provide different results. The data consists of all the common shares listed in the Finnish stock market during the period of 1/1997–7/2015. To examine whether liquidity risk affects stock returns in the Finnish stock market, this study utilizes a conditional version of liquidity-adjusted capital asset pricing model (LCAPM) by Acharya and Pedersen (2005). Two recently proposed illiquidity measures – PQS and AdjILLIQ – are used in the empirical estimation to see whether there are differences in the results between the measures. The time-varying conditional liquidity risks are estimated by using a multivariate DCC-GARCH model, while the pricing of the liquidity risk is conducted by applying fixed effect panel regression. The results imply that investors in the Finnish stock market are willing to pay a premium to hedge from wealth shocks and having liquid assets during the declined market liquidity. However, investors are not willing to pay a premium for stocks with higher returns during illiquid markets. The total annualized illiquidity premiums found in the Finnish stock market are 1.77% and 1.04%, based on the PQS and AdjILLIQ measures, respectively. The study also shows that liquidity risk does not exhibit decreasing trend, and investors should consider liquidity risk in their portfolio diversification in the Finnish stock market.

Pricing of Liquidity Risks in London Stock Exchange

This thesis aims to investigate pricing of liquidity risks in London Stock Exchange. Liquidity Adjusted Capital Asset Pricing Model i.e. LCAPM developed by Acharya and Pedersen (2005) is being applied to test the influence of various liquidity risks on stock returns in London Stock Exchange. The Liquidity Adjusted Capital Asset Pricing model provides a unified framework for the testing of liquidity risks. All the common stocks listed and delisted for the period of 2000 to 2014 are included in the data sample. The study has incorporated three different measures of liquidity – Percent Quoted Spread, Amihud (2002) and Turnover. The reason behind the application of three different liquidity measures is the multi-dimensional nature of liquidity. Firm fixed effects panel regression is applied for the estimation of LCAPM. However, the results are robust according to Fama-Macbeth regressions. The results of the study indicates that liquidity risks in the form of (i) level of liquidity, (ii) commonality in liquidity (iii) flight to liquidity, (iv) depressed wealth effect and market return as well as aggregate liquidity risk are priced at London Stock Exchange. However, the results are sensitive to the choice of liquidity measures.

Effects of bank supervision and regulation on bank risk

In the last few decades, banking has strongly internationalized and become more complex. Hence, bank supervision and regulation has taken global perspective, too. The most important international regulation are the Basel frameworks by the Basel committee on banking supervision. This study examines the effects of bank supervision and regulation, especially the Basel II, on bank risk and risk-taking. In order to separate and recognize the efficiency of these effects, the co-effects of many supervisory and regulatory tools together with other relevant factors must be taken into account. The focus of the study is on the effects of asymmetric information and banking procyclicality on the efficiency of the Basel II. This study tries to find an answer, if the Basel II, implemented in 2008, has decreased bank risk in banks of European Union member states. This study examines empirically, if the volatility on bank stock returns have changed after the implementation of the Basel II. Panel data consists of 62 bank stock returns, bank-specific variables, economic variables and variables concerning regulatory environment between 2003 and 2011. Fixed effects regression is used for panel data analysis. Results indicate that volatility on bank stock returns has increased after 2008 and the implementation of the Basel II. Result is statistically very significant and robustness has been verified in different model specifications. The result of this study contradicts with the goal of the Basel II about banking system stability. Banking procyclicality and wrong incentives for regulatory arbitrage under asymmetric information explained in theoretical part may explain this result. On the other hand, simultaneously with the implementation of the Basel II, the global financial crisis emerged and caused severe losses in banks and increased stock volatility. However, it is clear that supervision and regulation was unable to prevent the global financial crisis. After the financial crisis, supervision and regulation have been reformed globally. The main problems of the Basel II, examined in the theoretical part, have been recognized in order to prevent problems of procyclicality and wrong incentives in the future.

The determination of the helium discharge detector response to fixed gases

The Beckman Helium Discharge Detector has been found to be sensitive to the fixed gases oxygen, nitrogen, and hydrogen at detection levels 10-100 times more sensitive than possible with a Bow-Mac Thermal Conductivity Detector. Detection levels o~ approximately 1.9 E-4 ~ v/v oxygen, 3.1 E-4 ~ v/v nitrogen, and 3.0 E-3 ~ v/v hydrogen are estimated. Response of the Helium Discharge Detector was not linear, but is useable for quantitation over limited ranges of concentration using suitably prepared working standards. Cleanliness of the detector discharge electrodes and purity of the helium carrier and discharge gas were found to be critical to the operation of the detector. Higher sensitivities of the Helium Discharge Detector may be possible by the design and installation of a sensitive, solid-state electrometer.

Dynamic Performance Evaluation of Canadian Fixed-Income Funds using Markov Regime Switching Models

This thesis examines the performance of Canadian fixed-income mutual funds in the context of an unobservable market factor that affects mutual fund returns. We use various selection and timing models augmented with univariate and multivariate regime-switching structures. These models assume a joint distribution of an unobservable latent variable and fund returns. The fund sample comprises six Canadian value-weighted portfolios with different investing objectives from 1980 to 2011. These are the Canadian fixed-income funds, the Canadian inflation protected fixed-income funds, the Canadian long-term fixed-income funds, the Canadian money market funds, the Canadian short-term fixed-income funds and the high yield fixed-income funds. We find strong evidence that more than one state variable is necessary to explain the dynamics of the returns on Canadian fixed-income funds. For instance, Canadian fixed-income funds clearly show that there are two regimes that can be identified with a turning point during the mid-eighties. This structural break corresponds to an increase in the Canadian bond index from its low values in the early 1980s to its current high values. Other fixed-income funds results show latent state variables that mimic the behaviour of the general economic activity. Generally, we report that Canadian bond fund alphas are negative. In other words, fund managers do not add value through their selection abilities. We find evidence that Canadian fixed-income fund portfolio managers are successful market timers who shift portfolio weights between risky and riskless financial assets according to expected market conditions. Conversely, Canadian inflation protected funds, Canadian long-term fixed-income funds and Canadian money market funds have no market timing ability. We conclude that these managers generally do not have positive performance by actively managing their portfolios. We also report that the Canadian fixed-income fund portfolios perform asymmetrically under different economic regimes. In particular, these portfolio managers demonstrate poorer selection skills during recessions. Finally, we demonstrate that the multivariate regime-switching model is superior to univariate models given the dynamic market conditions and the correlation between fund portfolios.

Article - "Fixed Wing to Whirly Bird"

An article written by Dorothy Rungeling about her experience flying a helicopter for the first time. She is instructed by Bert Ratliff of the Bell Helicopter Corp. in a Bell G2 Trooper.

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

On Fixed-Path Rationing Methods.

Moulin (1999) characterizes the fixed-path rationing methods by efficiency, strategy-proofness, consistency, and resource-monotonicity. In this note, we give a straightforward proof of his result.

Nonparametric Instrumental Regression

The focus of the paper is the nonparametric estimation of an instrumental regression function P defined by conditional moment restrictions stemming from a structural econometric model : E[Y-P(Z)|W]=0 and involving endogenous variables Y and Z and instruments W. The function P is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyses identification and overidentification of this model and presents asymptotic properties of the estimated nonparametric instrumental regression function.

Tests of Joint Hypotheses for Time Series Regression with a Unit Root

This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression \"F-Test\" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).