Balancing the role of the dental school in teaching, research and patient care; including care for underserved areas

Inequalities within dentistry are common and are reflected in wide differences in the levels of oral health and the standard of care available both within and between countries and communities. Furthermore there are patients, particularly those with special treatment needs, who do not have the same access to dental services as the general public. The dental school should aim to recruit students from varied backgrounds into all areas covered by the oral healthcare team and to train students to treat the full spectrum of patients including those with special needs. It is essential, however, that the dental student achieves a high standard of clinical competence and this cannot be gained by treating only those patients with low expectations for care. Balancing these aspects of clinical education is difficult. Research is an important stimulus to better teaching and better clinical care. It is recognized that dental school staff should be active in research, teaching, clinical work and frequently administration. Maintaining a balance between the commitments to clinical care, teaching and research while also taking account of underserved areas in each of these categories is a difficult challenge but one that has to be met to a high degree in a successful, modern dental school.

The role of the South Indian and Pacific oceans in South American monsoon variability

This work has investigated the impact of three different low-frequency sea surface temperature (SST) variability modes located in the Indian and the Pacific Oceans on the interannual variability of the South American Monsoon System (SAMS) using observed and numerical data. Rotated Empirical Orthogonal Function (REOF) analysis and numerical simulations with a General Circulation Model (GCM) were used. One of the three SST variability modes is located close to southeastern Africa. According to the composites, warmer waters over this region are associated with enhanced austral summer precipitation over the sub-tropics. The GCM is able to reproduce this anomalous precipitation pattern, simulating a wave train emanating from the Indian Ocean towards South America (SA). A second SST variability mode was located in the western Pacific Ocean. REOF analysis indicates that warmer waters are associated with drought conditions over the South Atlantic Convergence Zone (SACZ) and enhanced precipitation over the sub-tropics. The GCM indicates that the warmer waters over Indonesia generate drought conditions over tropical SA through a Pacific South America-like (PSA) wave pattern emanating from the western Pacific. Finally, the third SST variability mode is located over the southwestern South Pacific. The composites indicate that warmer waters are associated with enhanced precipitation over the SACZ and drought conditions over the sub-tropics. There is a PSA-like wave train emanating from Indonesia towards SA, and another crossing the Southern Hemisphere in the extra-tropics, probably associated with transient activity. The GCM is able to reproduce the anomalous precipitation pattern, although it is weaker than observed. The PSA-like pattern is simulated, but the model fails in reproducing the extra-tropical wave activity.

Reappraisal of the effective elastic thickness for the sub-Andes using 3-D finite element flexural modelling, gravity and geological constraints

P>Estimates of effective elastic thickness (T(e)) for the western portion of the South American Plate using, independently, forward flexural modelling and coherence analysis, suggest different thermomechanical properties for the same continental lithosphere. We present a review of these T(e) estimates and carry out a critical reappraisal using a common methodology of 3-D finite element method to solve a differential equation for the bending of a thin elastic plate. The finite element flexural model incorporates lateral variations of T(e) and the Andes topography as the load. Three T(e) maps for the entire Andes were analysed: Stewart & Watts (1997), Tassara et al. (2007) and Perez-Gussinye et al. (2007). The predicted flexural deformation obtained for each T(e) map was compared with the depth to the base of the foreland basin sequence. Likewise, the gravity effect of flexurally induced crust-mantle deformation was compared with the observed Bouguer gravity. T(e) estimates using forward flexural modelling by Stewart & Watts (1997) better predict the geological and gravity data for most of the Andean system, particularly in the Central Andes, where T(e) ranges from greater than 70 km in the sub-Andes to less than 15 km under the Andes Cordillera. The misfit between the calculated and observed foreland basin subsidence and the gravity anomaly for the Maranon basin in Peru and the Bermejo basin in Argentina, regardless of the assumed T(e) map, may be due to a dynamic topography component associated with the shallow subduction of the Nazca Plate beneath the Andes at these latitudes.

Bayesian analysis and constraints on kinematic models from union SNIa

The kinematic expansion history of the universe is investigated by using the 307 supernovae type Ia from the Union Compilation set. Three simple model parameterizations for the deceleration parameter ( constant, linear and abrupt transition) and two different models that are explicitly parametrized by the cosmic jerk parameter ( constant and variable) are considered. Likelihood and Bayesian analyses are employed to find best fit parameters and compare models among themselves and with the flat Lambda CDM model. Analytical expressions and estimates for the deceleration and cosmic jerk parameters today (q(0) and j(0)) and for the transition redshift (z(t)) between a past phase of cosmic deceleration to a current phase of acceleration are given. All models characterize an accelerated expansion for the universe today and largely indicate that it was decelerating in the past, having a transition redshift around 0.5. The cosmic jerk is not strongly constrained by the present supernovae data. For the most realistic kinematic models the 1 sigma confidence limits imply the following ranges of values: q(0) is an element of [-0.96, -0.46], j(0) is an element of [-3.2,-0.3] and z(t) is an element of [0.36, 0.84], which are compatible with the Lambda CDM predictions, q(0) = -0.57 +/- 0.04, j(0) = -1 and z(t) = 0.71 +/- 0.08. We find that even very simple kinematic models are equally good to describe the data compared to the concordance Lambda CDM model, and that the current observations are not powerful enough to discriminate among all of them.

Regression Models with Heteroscedasticity using Bayesian Approach

In this paper, we compare the performance of two statistical approaches for the analysis of data obtained from the social research area. In the first approach, we use normal models with joint regression modelling for the mean and for the variance heterogeneity. In the second approach, we use hierarchical models. In the first case, individual and social variables are included in the regression modelling for the mean and for the variance, as explanatory variables, while in the second case, the variance at level 1 of the hierarchical model depends on the individuals (age of the individuals), and in the level 2 of the hierarchical model, the variance is assumed to change according to socioeconomic stratum. Applying these methodologies, we analyze a Colombian tallness data set to find differences that can be explained by socioeconomic conditions. We also present some theoretical and empirical results concerning the two models. From this comparative study, we conclude that it is better to jointly modelling the mean and variance heterogeneity in all cases. We also observe that the convergence of the Gibbs sampling chain used in the Markov Chain Monte Carlo method for the jointly modeling the mean and variance heterogeneity is quickly achieved.

Monotone positive solutions for a fourth order equation with nonlinear boundary conditions

This work is concerned with the existence of monotone positive solutions for a class of beam equations with nonlinear boundary conditions. The results are obtained by using the monotone iteration method and they extend early works on beams with null boundary conditions. Numerical simulations are also presented. (C) 2009 Elsevier Ltd. All rights reserved.

Dynamics of a class of ODEs more general than almost periodic

A temporally global solution, if it exists, of a nonautonomous ordinary differential equation need not be periodic, almost periodic or almost automorphic when the forcing term is periodic, almost periodic or almost automorphic, respectively. An alternative class of functions extending periodic and almost periodic functions which has the property that a bounded temporally global solution solution of a nonautonomous ordinary differential equation belongs to this class when the forcing term does is introduced here. Specifically, the class of functions consists of uniformly continuous functions, defined on the real line and taking values in a Banach space, which have pre-compact ranges. Besides periodic and almost periodic functions, this class also includes many nonrecurrent functions. Assuming a hyperbolic structure for the unperturbed linear equation and certain properties for the linear and nonlinear parts, the existence of a special bounded entire solution, as well the existence of stable and unstable manifolds of this solution are established. Moreover, it is shown that this solution and these manifolds inherit the temporal behaviour of the vector field equation. In the stable case it is shown that this special solution is the pullback attractor of the system. A class of infinite dimensional examples involving a linear operator consisting of a time independent part which generates a C(0)-semigroup plus a small time dependent part is presented and applied to systems of coupled heat and beam equations. (C) 2010 Elsevier Ltd. All rights reserved.

The log-exponentiated Weibull regression model for interval-censored data

In interval-censored survival data, the event of interest is not observed exactly but is only known to occur within some time interval. Such data appear very frequently. In this paper, we are concerned only with parametric forms, and so a location-scale regression model based on the exponentiated Weibull distribution is proposed for modeling interval-censored data. We show that the proposed log-exponentiated Weibull regression model for interval-censored data represents a parametric family of models that include other regression models that are broadly used in lifetime data analysis. Assuming the use of interval-censored data, we employ a frequentist analysis, a jackknife estimator, a parametric bootstrap and a Bayesian analysis for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Furthermore, for different parameter settings, sample sizes and censoring percentages, various simulations are performed; in addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to a modified deviance residual in log-exponentiated Weibull regression models for interval-censored data. (C) 2009 Elsevier B.V. All rights reserved.

A multivariate ultrastructural errors-in-variables model with equation error

This paper deals with asymptotic results on a multivariate ultrastructural errors-in-variables regression model with equation errors Sufficient conditions for attaining consistent estimators for model parameters are presented Asymptotic distributions for the line regression estimators are derived Applications to the elliptical class of distributions with two error assumptions are presented The model generalizes previous results aimed at univariate scenarios (C) 2010 Elsevier Inc All rights reserved

Reliability Nonparametric Bayesian Estimation in Parallel Systems

Relevant results for (sub-)distribution functions related to parallel systems are discussed. The reverse hazard rate is defined using the product integral. Consequently, the restriction of absolute continuity for the involved distributions can be relaxed. The only restriction is that the sets of discontinuity points of the parallel distributions have to be disjointed. Nonparametric Bayesian estimators of all survival (sub-)distribution functions are derived. Dual to the series systems that use minimum life times as observations, the parallel systems record the maximum life times. Dirichlet multivariate processes forming a class of prior distributions are considered for the nonparametric Bayesian estimation of the component distribution functions, and the system reliability. For illustration, two striking numerical examples are presented.

On the Hamilton-Jacobi equation in the framework of generalized functions

In this work we study, in the framework of Colombeau`s generalized functions, the Hamilton-Jacobi equation with a given initial condition. We have obtained theorems on existence of solutions and in some cases uniqueness. Our technique is adapted from the classical method of characteristics with a wide use of generalized functions. We were led also to obtain some general results on invertibility and also on ordinary differential equations of such generalized functions. (C) 2011 Elsevier Inc. All rights reserved.

Improved maximum-likelihood estimation in a regression model with general parametrization

We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.

The Impact of Foreign Direct Investment on International Trade: An Empirical Study of China

This paper investigates the impact of inward FDI (Foreign Direct Investment) on international trade of China empirically on the country level by using panel data from 1984 to 2007. Two separate transformed models which are based on the gravity equation and refer to the econometric models of some previous studies, are used in this paper to estimate the effect of FDI inflows on exports and imports respectively. The estimation results confirmed the complementary relationship between FDI inflows and trade of China both on exports and imports, which has also been supported by previous empirical studies.

A finite sample improvement of the fixed effects estimator : applied to technical infficiency

The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.

Ukrainas konstitutionella sicksackande : Regimförändring och partiutveckling under semipresidentialism

Ukraine has repeatedly shifted between the two sub-types of semi-presidentialism, i.e. between premier-presidentialism and president-parliamentarism. The aim of this article is to discuss to what extent theoretical arguments against premier-presidential and president-parliamentary systems are relevant for understanding the shifting directions of the Ukrainian regime. As a point of departure, I formulate three main claims from the literature: 1) “President-parliamentarism is less conducive to democratization than premier-presidentialism.”; 2) “Semi-presidentialism in both its variants have built-in incitements for intra-executive conflict between the president and the prime minister.”; 3) “Semi-presidentialism in general, and president-parliamentarism in particular, encourages presidentialization of political parties.” I conclude from the study’s empirical overview that the president-parliamentary system– the constitutional arrangement with the most dismal record of democratization – has been instrumental in strengthening presidential dominance and authoritarian tendencies. The premier-presidential period 2006–2010 was by no means smooth and stable, but the presidential dominance weakened and the survival of the government was firmly anchored in the parliament. During this period, there were also indications of a gradual strengthening of institutional capacity among the main political parties and the parliament began to emerge as a significant political arena.