Model transformations and Tool Integration

Model transformations are increasingly recognised as being of significant importance to many areas of software development and integration. Recent attention on model transformations has particularly focused on the OMGs Queries/Views/Transformations (QVT) Request for Proposals (RFP). In this paper I motivate the need for dedicated approaches to model transformations, particularly for the data involved in tool integration, outline the challenges involved, and then present a number of technologies and techniques which allow the construction of flexible, powerful and practical model transformations

Muscle fiber typology substantially influences time to recover from high-intensity exercise

Human fast-twitch muscle fi- bers generate high power in a short amount of time but are easily fatigued, whereas slow-twitch fibers are more fatigue resistant. The transfer of this knowledge to coaching is hampered by the invasive nature of the current evaluation of muscle typology by biopsies. Therefore, a noninvasive method was developed to estimate muscle typology through proton magnetic resonance spectroscopy in the gastrocnemius. The aim of this study was to investigate whether male subjects with an a priori-determined fast typology (FT) are character- ized by a more pronounced Wingate exercise-induced fatigue and delayed recovery compared with subjects with a slow typology (ST). Ten subjects with an estimated higher percentage of fast-twitch fibers and 10 subjects with an estimated higher percentage of slow-twitch fibers underwent the test protocol, consisting of three 30-s all-out Wingate tests. Recovery of knee extension torque was evaluated by maximal voluntary contraction combined with electrical stimulation up to 5 h after the Wingate tests. Although both groups delivered the same mean power across all Wingates, the power drop was higher in the FT group (—61%) compared with the ST group (—41%). The torque at maximal voluntary contraction had fully recovered in the ST group after 20 min, whereas the FT group had not yet recovered 5 h into recovery. This noninvasive estimation of muscle typology can predict the extent of fatigue and time to recover following repeated all-out exercise and may have applications as a tool to individualize training and recovery cycles. NEW & NOTEWORTHY A one-fits-all training regime is present in most sports, though the same training implies different stimuli in athletes with a distinct muscle typology. Individualization of training based on this muscle typology might be important to optimize per- formance and to lower the risk for accumulated fatigue and potentially injury. When conducting research, one should keep in mind that the muscle typology of participants influences the severity of fatigue and might therefore impact the results

ArguBlogging:an application for the Argument Web

In this paper, we present a software tool for ‘ArguBlogging’, which allows users to construct debate and discussions across blogs, linking existing and new online resources to form distributed, structured conversations. Arguments and counterarguments can be posed by giving opinions on one’s own blog and replying to other bloggers’ posts. The resulting argument structure is connected to the Argument Web, in which argumentative structures are made semantically explicit and machine-processable. We discuss the ArguBlogging tool and the underlying infrastructure and ontology of the Argument Web

Review of latest developments of ions sources

International audienc

GANIL status report

International audienc

From Pokémon go to hashtags: how digital and social media is changing the church

What impact is social and digital media having on religion? Here Bex Lewis explores its impact on the Church. She finds that as the Church starts engaging its followers online it has become a space to debate issues, connect to others and reach people and, in turn, humanise the Church. Church activities are being taken back out into the online world and Church leaders have taken to digital platforms to speak out on social and political debates from Brexit to international terrorism. Public conversations have always been key for public theology but the Information Age we’re living in means that many of these public conversations will today take place in the digital sphere

Learning Curves for Mutual Information Maximization

An unsupervised learning procedure based on maximizing the mutual information between the outputs of two networks receiving different but statistically dependent inputs is analyzed (Becker and Hinton, Nature, 355, 92, 161). For a generic data model, I show that in the large sample limit the structure in the data is recognized by mutual information maximization. For a more restricted model, where the networks are similar to perceptrons, I calculate the learning curves for zero-temperature Gibbs learning. These show that convergence can be rather slow, and a way of regularizing the procedure is considered.Comment: 13 pages, to appear in Phys.Rev.

NMR-based applications in elite sports performance

Nuclear magnetic resonance (NMR) scanners can be used in athlete populations because of its non-invasive nature. Both spectroscopy (MRS) and imaging (MRI) are harmless techniques which can be used in several applications towards sport science. The studies in this PhD thesis included two major topics. In the first section (study 1 and 2), the focus was put on a better understanding of the muscle carnosine loading protocol. Secondly, study 3, 4 and 5 investigated musculo-skeletal characteristics of the athlete itself. Altogether, this thesis contributed to new insights in the applications of NMR in sport science. A first application was situated in the field of sport nutrition by investigating carnosine loading strategies. Additionally, MRS and MRI were used to reveal specific muscle characteristics in different athlete populations