A classification system for global wave energy resources based on multivariate clustering

Better understanding of the global wave climate is required to inform wave energy device design and large-scale deployment. Spatial variability in the global wave climate is analysed here to provide a range of characteristic design wave climates. K-means clustering was used to split the global wave resource into 6 classes in a device agnostic, data-driven method using data from the ECMWF ERA5 reanalysis product. Classification using two sets of input data were considered: a simple set (based on significant wave height and peak wave period) and a comprehensive set including a wide range of relevant wave climate parameters. Both classifications gave resource classes with similar characteristics; 55% of tested locations were assigned to the same class. Two classes were low energy, found in enclosed seas and sheltered regions. Two classes were moderate wave energy classes; one swell dominated and the other in areas with wave action often generated by more local storms. Of the two higher energy classes; one was more often found in the northern hemisphere and the other, most energetic, predominantly on the tips of continents in the southern hemisphere. These classes match existing regional understanding of resource. Consideration of publicly available device power matrices showed good performance was primarily realised for the two highest energy resource classes (25–30% of potential deployment locations); it is suggested that effort should focus on optimising devices for additional resource classes. The authors hypothesise that the low-risk, low variability, swell dominated moderate wave energy class would be most suitable for future exploitation

Fenoterol depot and fenoterol in premature uterine contractions — a multicentric double-blind comparative study

Peer Reviewe

The development of wayfinding abilities in children: Learning routes with and without landmarks

Young children experience wayfinding difficulties. A better understanding of the development of wayfinding abilities may inform strategies that can be used to improve these skills in children. The ability to learn and remember a route was assessed in 220 6-, 8-, and 10-year old children and adults. Participants were shown a route in a virtual environment, before they were asked to retrace this route until they had achieved two consecutive trials without error. The virtual environment contained (i) no landmarks (ii) landmarks or (iii) landmarks that were verbally labelled. Adults, 10-year-olds and most 8-year-olds learnt the route when landmarks were present, but not all the 6-year-olds were successful. All age groups of children improved when the landmarks were labelled. Children were much poorer when there were no landmarks. This is the first study to distinguish between route learning dependent on landmarks, and route learning without landmarks (i.e. dependent on directions)