Is the present the key to the past? : A global characterization of modern sedimentary basins

Date of Acceptance: 06/05/2015 We thank the FORCE Consortium for funding this research, Rob Butler and Walter Wheeler for quality control on the global basin classification, and David MacDonald for reviewing an earlier draft of this manuscript. We also thank Gary Weissmann, Andrew Miall, Raymond Ingersoll, John Holbrook, Stephen Flint, and editor Ellen Thomas for their constructive reviews.

Derivation and Validation of a Novel Prognostic Scale (Modified–Stroke Subtype, Oxfordshire Community Stroke Project Classification, Age, and Prestroke Modified Rankin) to Predict Early Mortality in Acute Stroke

© 2015 American Heart Association, Inc.

GRADE Evidence to Decision (EtD) frameworks : a systematic and transparent approach to making well informed healthcare choices. 2: Clinical practice guidelines

Funding: Work on this article has been partially funded by the European Commission FP7 Program (grant agreement 258583) as part of the DECIDE project. Sole responsibility lies with the authors; the European Commission is not responsible for any use that may be made of the information contained therein.

PET Tracers to Study Clinically Relevant Hepatic Transporters

Date of Acceptance: 02/06/2015

‘Quite destitute and … very desirous of going to North America’ : The Roots and Repercussions of Emigration from Sutherland and Caithness

Peer reviewed

Identification of the mRNA targets of tRNA-­specific regulation using genome-­wide simulation of translation

FUNDING Biotechnology and Biological Sciences Research Council (BBSRC) [BB/I020926/1 to I.S.]; BBSRC PhD studentship award [C103817D to I.S. and M.C.R.]; Scottish Universities Life Science Alliance PhD studentship award (to M.C.R. and I.S.]. Funding for open access charge: BBSRC. Conflict of interest statement. None declared.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

Image Noise Removal on Heterogeneous CPU-GPU Configurations

A parallel algorithm to remove impulsive noise in digital images using heterogeneous CPU/GPU computing is proposed. The parallel denoising algorithm is based on the peer group concept and uses an Euclidean metric. In order to identify the amount of pixels to be allocated in multi-core and GPUs, a performance analysis using large images is presented. A comparison of the parallel implementation in multi-core, GPUs and a combination of both is performed. Performance has been evaluated in terms of execution time and Megapixels/second. We present several optimization strategies especially effective for the multi-core environment, and demonstrate significant performance improvements. The main advantage of the proposed noise removal methodology is its computational speed, which enables efficient filtering of color images in real-time applications.

Teaching as a fractal: from experience to model

The aim of this work is to improve students’ learning by designing a teaching model that seeks to increase student motivation to acquire new knowledge. To design the model, the methodology is based on the study of the students’ opinion on several aspects we think importantly affect the quality of teaching (such as the overcrowded classrooms, time intended for the subject or type of classroom where classes are taught), and on our experience when performing several experimental activities in the classroom (for instance, peer reviews and oral presentations). Besides the feedback from the students, it is essential to rely on the experience and reflections of lecturers who have been teaching the subject several years. This way we could detect several key aspects that, in our opinion, must be considered when designing a teaching proposal: motivation, assessment, progressiveness and autonomy. As a result we have obtained a teaching model based on instructional design as well as on the principles of fractal geometry, in the sense that different levels of abstraction for the various training activities are presented and the activities are self-similar, that is, they are decomposed again and again. At each level, an activity decomposes into a lower level tasks and their corresponding evaluation. With this model the immediate feedback and the student motivation are encouraged. We are convinced that a greater motivation will suppose an increase in the student’s working time and in their performance. Although the study has been done on a subject, the results are fully generalizable to other subjects.

The Role of Enjoyment and Motivational Climate in Relation to the Personal Development of Team Sport Athletes

Sport has been identified as a context in which youth encounter positive and negative experiences. However, relatively little is known about the factors that lead to positive and negative personal development among sport participants. The purpose of this study was to investigate the role of enjoyment and motivational climate on positive and negative personal development of team sport participants. A sample of 510 athletes between the ages of 9 and 19 completed questionnaires on positive and negative personal development, enjoyment, and motivational climate. Stepwise multiple regression analyses examined the effects of enjoyment and motivational climate on the personal development of the athletes. Results demonstrated that positive experiences in sport were most strongly predicted by affiliation with peers, self-referenced competency, effort expenditure, and a task climate. Negative experiences were most strongly predicted by an ego climate and other-referenced competency. Results suggest that creating an environment that encourages peer affiliation and personal achievement can result in the positive personal development of youth sport participants.