Effect of a chitosan additive to a Sn(2+)-containing toothpaste on its anti-erosive/anti-abrasive efficacy-a controlled randomised in situ trial

OBJECTIVES It is well known that Sn(2+) is a notable anti-erosive agent. There are indications that biopolymers such as chitosan can enhance the effect of Sn(2+), at least in vitro. However, little information exists about their anti-erosive/anti-abrasive in situ effects. In the present in situ study, the efficacy of Sn(2+)-containing toothpastes in the presence or absence of chitosan was tested. METHODS Ten subjects participated in the randomised crossover study, wearing mandibular appliances with human enamel specimens. Specimens were extraorally demineralised (7 days, 0.5 % citric acid, pH 2.6; 6 × 2 min/day) and intraorally exposed to toothpaste suspensions (2 × 2 min/day). Within the suspension immersion time, one half of the specimens were additionally brushed intraorally with a powered toothbrush (5 s, 2.5 N). Tested preparations were a placebo toothpaste (negative control), two experimental toothpastes (F/Sn = 1,400 ppm F(-), 3,500 ppm Sn(2+); F/Sn/chitosan = 1,400 ppm F(-), 3,500 ppm Sn(2+), 0.5 % chitosan) and an SnF2-containing gel (positive control, GelKam = 3,000 ppm Sn(2+), 1,000 ppm F(-)). Substance loss was quantified profilometrically (μm). RESULTS In the placebo group, tissue loss was 11.2 ± 4.6 (immersion in suspension) and 17.7 ± 4.7 (immersion in suspension + brushing). Immersion in each Sn(2+)-containing suspension significantly reduced tissue loss (p ≤ 0.01); after immersion in suspension + brushing, only the treatments with GelKam (5.4 ± 5.5) and with F/Sn/chitosan (9.6 ± 5.6) significantly reduced loss [both p ≤ 0.05 compared to placebo; F/Sn 12.8 ± 6.4 (not significant)] CONCLUSION Chitosan enhanced the efficacy of the Sn(2+)-containing toothpaste as an anti-erosive/anti-abrasive agent. CLINICAL RELEVANCE The use of Sn(2+)- and chitosan-containing toothpaste is a good option for symptomatic therapy in patients with regular acid impacts.

On trend estimation under monotone Gaussian subordination with long-memory: application to fossil pollen series

Fossil pollen data from stratigraphic cores are irregularly spaced in time due to non-linear age-depth relations. Moreover, their marginal distributions may vary over time. We address these features in a nonparametric regression model with errors that are monotone transformations of a latent continuous-time Gaussian process Z(T). Although Z(T) is unobserved, due to monotonicity, under suitable regularity conditions, it can be recovered facilitating further computations such as estimation of the long-memory parameter and the Hermite coefficients. The estimation of Z(T) itself involves estimation of the marginal distribution function of the regression errors. These issues are considered in proposing a plug-in algorithm for optimal bandwidth selection and construction of confidence bands for the trend function. Some high-resolution time series of pollen records from Lago di Origlio in Switzerland, which go back ca. 20,000 years are used to illustrate the methods.

Estimating and quantifying uncertainties on level sets using the Vorob'ev expectation and deviation with Gaussian process models

Several methods based on Kriging have recently been proposed for calculating a probability of failure involving costly-to-evaluate functions. A closely related problem is to estimate the set of inputs leading to a response exceeding a given threshold. Now, estimating such a level set—and not solely its volume—and quantifying uncertainties on it are not straightforward. Here we use notions from random set theory to obtain an estimate of the level set, together with a quantification of estimation uncertainty. We give explicit formulae in the Gaussian process set-up and provide a consistency result. We then illustrate how space-filling versus adaptive design strategies may sequentially reduce level set estimation uncertainty.

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations

In the context of expensive numerical experiments, a promising solution for alleviating the computational costs consists of using partially converged simulations instead of exact solutions. The gain in computational time is at the price of precision in the response. This work addresses the issue of fitting a Gaussian process model to partially converged simulation data for further use in prediction. The main challenge consists of the adequate approximation of the error due to partial convergence, which is correlated in both design variables and time directions. Here, we propose fitting a Gaussian process in the joint space of design parameters and computational time. The model is constructed by building a nonstationary covariance kernel that reflects accurately the actual structure of the error. Practical solutions are proposed for solving parameter estimation issues associated with the proposed model. The method is applied to a computational fluid dynamics test case and shows significant improvement in prediction compared to a classical kriging model.

Detecting offsets in GPS time series: first results from the Detection of Offsets in GPS Experiment

The accuracy of Global Positioning System (GPS) time series is degraded by the presence of offsets. To assess the effectiveness of methods that detect and remove these offsets, we designed and managed the Detection of Offsets in GPS Experiment. We simulated time series that mimicked realistic GPS data consisting of a velocity component, offsets, white and flicker noises (1/f spectrum noises) composed in an additive model. The data set was made available to the GPS analysis community without revealing the offsets, and several groups conducted blind tests with a range of detection approaches. The results show that, at present, manual methods (where offsets are hand picked) almost always give better results than automated or semi‒automated methods (two automated methods give quite similar velocity bias as the best manual solutions). For instance, the fifth percentile range (5% to 95%) in velocity bias for automated approaches is equal to 4.2 mm/year (most commonly ±0.4 mm/yr from the truth), whereas it is equal to 1.8 mm/yr for the manual solutions (most commonly 0.2 mm/yr from the truth). The magnitude of offsets detectable by manual solutions is smaller than for automated solutions, with the smallest detectable offset for the best manual and automatic solutions equal to 5 mm and 8 mm, respectively. Assuming the simulated time series noise levels are representative of real GPS time series, robust geophysical interpretation of individual site velocities lower than 0.2–0.4 mm/yr is therefore certainly not robust, although a limit of nearer 1 mm/yr would be a more conservative choice. Further work to improve offset detection in GPS coordinates time series is required before we can routinely interpret sub‒mm/yr velocities for single GPS stations.

The additive and interactive roles of aggression, prosocial behavior, and social preference in predicting resource control in young children

Distinguishing between physical and social aggression, this study examined whether the predictive effect of aggression on resource control a) is moderated by prosocial behavior and b) corresponds to a linear or a curvilinear trend. Moderating effects of children’s social preference among peers and child sex in this context were also tested. Based on a sample of 682 kindergarten children (348 girls; average age 72.7 months, 3.6 SD), multilevel regressions revealed additive linear effects of social preference and prosociality on resource control. Moderate (but not high) levels of social aggression also facilitated resource control for disliked children. There was no such threshold effect for well liked children, who increasingly controlled the resource the more socially aggressive they were. In contrast, physical aggression hampered resource control unless used very modestly. The present study has a number of positive features. First, the distinction between physical and social aggression improves our understanding of the relation between aggression and social competence and sketches a more differentiated picture of the role of different forms of aggression in resource control. Second, this study combines the concept of resource control with the concept of social preference and investigates curvilinear effects of aggression. Third, the direct observation of resource control in the Movie Viewer increases the internal validity of this study.

Swiss Air Traffic Policy: Noise Between Berne and Berlin

This article looks at the negotiations between Switzerland and Germany on air traffic regulation with the help of negotiation analysis tools. A number of factors pre-eminent in the literature on negotiation processes and outcomes are presented and critically assessed. In particular arguments of “power”, which are often insufficiently explored in analysing interstate cooperation, are brought back into the picture. The article argues that structural power best explains the negotiation results while domestic politics and information asymmetries both account for non-ratification of the treaty. Institutionalist arguments on the constraining effects of international norms and institutions as well as explanations focusing on negotiation skills are of minor importance. Moreover, the nature of the Swiss intra-governmental setting at the federal level did not encourage the Swiss negotiators to exploit all means during the different stages of the bargaining process. The article concludes by illuminating a number of policy observations in the broader context of Swiss foreign relations and indicating avenues for further research