Holocene relative mean sea-level changes in the Wadden Sea area, northern Netherlands

Although the Netherlands has a long tradition of sea-level research, no Holocene relative sea-level curve is available for the north of the country. Previous studies hypothesized that the relative sea-level reconstruction for the western Netherlands is also valid for the northern part of the country. However, glacial isostatic adjustment (GIA) models predict a lower and steeper relative sea-level curve because of greater postglacial isostatic subsidence. Long-term data of relative sea-level change are important to inform GIA models and understand postglacial vertical land motion related to the rebound of Fennoscandia and neotectonic activity. We compiled and evaluated a set of basal peat radiocarbon dates to reconstruct the Holocene relative mean sea-level rise in the Dutch Wadden Sea area. For the early Holocene, this reconstruction is lower than the western Netherlands curve. After 6400 cal a BP, the curve for the Wadden Sea is statistically indistinguishable from that for the western Netherlands, a result that conflicts with GIA model results. It remains to be investigated whether the problem lies with the GIA model predictions or with the quality of the available data. Additional basal peat radiocarbon dates from suitable sites should be collected to further resolve this problem

Gaussian Process training with input noise

In standard Gaussian Process regression input locations are assumed to be noise free. We present a simple yet effective GP model for training on input points corrupted by i.i.d. Gaussian noise. To make computations tractable we use a local linear expansion about each input point. This allows the input noise to be recast as output noise proportional to the squared gradient of the GP posterior mean. The input noise variances are inferred from the data as extra hyperparameters. They are trained alongside other hyperparameters by the usual method of maximisation of the marginal likelihood. Training uses an iterative scheme, which alternates between optimising the hyperparameters and calculating the posterior gradient. Analytic predictive moments can then be found for Gaussian distributed test points. We compare our model to others over a range of different regression problems and show that it improves over current methods

Parametric design of field hockey sticks

Hockey as a game has been subject of little research. The authors of this paper outline a modified body model of the hockey stick impact, using coefficient of restitution (COR) values that take into account different ball and stick properties. Field data was taken from a number of players, including two internationals, giving a wide range of data for comparison. Basic physical properties were recorded for a selection of hockey sticks, and COR data was acquired for different hockey balls using a range of impact velocities. It was found that the COR of hockey balls decreases with increasing approach velocity, and that balls of different construction exhibit a wider range of response at high velocity. The top carbon fibre stick tested here hits a ball around 6% faster than a wooden stick under the same conditions. The modified rigid body model successfully predicts a ball departure velocity to within 3% of experimental data across a wide range of velocities