Interpretative and predictive modelling of Joint European Torus collisionality scans

Transport modelling of Joint European Torus (JET) dimensionless collisionality scaling experiments in various operational scenarios is presented. Interpretative simulations at a fixed radial position are combined with predictive JETTO simulations of temperatures and densities, using the TGLF transport model. The model includes electromagnetic effects and collisions as well as □(→┬E ) X □(→┬B ) shear in Miller geometry. Focus is on particle transport and the role of the neutral beam injection (NBI) particle source for the density peaking. The experimental 3-point collisionality scans include L-mode, and H-mode (D and H and higher beta D plasma) plasmas in a total of 12 discharges. Experimental results presented in (Tala et al 2017 44th EPS Conf.) indicate that for the H-mode scans, the NBI particle source plays an important role for the density peaking, whereas for the L-mode scan, the influence of the particle source is small. In general, both the interpretative and predictive transport simulations support the experimental conclusions on the role of the NBI particle source for the 12 JET discharges

Physics research on the TCV tokamak facility: from conventional to alternative scenarios and beyond

The research program of the TCV tokamak ranges from conventional to advanced-tokamak scenarios and alternative divertor configurations, to exploratory plasmas driven by theoretical insight, exploiting the device’s unique shaping capabilities. Disruption avoidance by real-time locked mode prevention or unlocking with electron-cyclotron resonance heating (ECRH) was thoroughly documented, using magnetic and radiation triggers. Runaway generation with high-Z noble-gas injection and runaway dissipation by subsequent Ne or Ar injection were studied for model validation. The new 1 MW neutral beam injector has expanded the parameter range, now encompassing ELMy H-modes in an ITER-like shape and nearly non-inductive H-mode discharges sustained by electron cyclotron and neutral beam current drive. In the H-mode, the pedestal pressure increases modestly with nitrogen seeding while fueling moves the density pedestal outwards, but the plasma stored energy is largely uncorrelated to either seeding or fueling. High fueling at high triangularity is key to accessing the attractive small edge-localized mode (type-II) regime. Turbulence is reduced in the core at negative triangularity, consistent with increased confinement and in accord with global gyrokinetic simulations. The geodesic acoustic mode, possibly coupled with avalanche events, has been linked with particle flow to the wall in diverted plasmas. Detachment, scrape-off layer transport, and turbulence were studied in L- and H-modes in both standard and alternative configurations (snowflake, super-X, and beyond). The detachment process is caused by power ‘starvation’ reducing the ionization source, with volume recombination playing only a minor role. Partial detachment in the H-mode is obtained with impurity seeding and has shown little dependence on flux expansion in standard single-null geometry. In the attached L-mode phase, increasing the outer connection length reduces the in–out heat-flow asymmetry. A doublet plasma, featuring an internal X-point, was achieved successfully, and a transport barrier was observed in the mantle just outside the internal separatrix. In the near future variable-configuration baffles and possibly divertor pumping will be introduced to investigate the effect of divertor closure on exhaust and performance, and 3.5 MW ECRH and 1 MW neutral beam injection heating will be added

Automatic Clustering of Social Tag using Community Detection

Automatically clustering social tags into semantic communities would greatly boost the ability of Web services search engines to retrieve the most relevant ones at the same time improve the accuracy of tag-based service recommendation. In this paper, we first investigate the different collaborative intention between co-occurring tags in Seekda as well as their dynamical aspects. Inspired by the relationships between co-occurring tags, we designed the social tag network. By analyzing the networks constructed, we show that the social tag network have scale free properties. In order to identify densely connected semantic communities, we then introduce a novel graph-based clustering algorithm for weighted networks based on the concept of edge betweenness with high enough intensity. Finally, experimental results on real world datasets show that our algorithm can effectively discovers the semantic communities and the resulting tag communities correspond to meaningful topic domains

Classical Liberalism in China: Some History and Prospects.

We explore (classical) liberal thought in China. In China’s long recorded history, some ideas similar to subsequent Western liberal thinking have periodically appeared. Starting in the late nineteenth century, translated Western works on liberalism became available. Currently, because of political intrigue, liberal themes are rare in official academic or political settings, but much liberal thinking is freely available, networks of liberal aficionados exist, and their activities and ideas are accessible to the public. The influence of many of these ideas is still relatively weak, and there are concerns about growing restrictions on politically threatening views. But economists most influenced by liberalism have some role in public opinion, though less so in shaping public policy. Given the huge tasks ahead in Chinese reform, liberals need to strengthen these networks, and to gain support from entrepreneurs in particular

Classical Liberalism in China: Some History and Prospects.

We explore (classical) liberal thought in China. In China’s long recorded history, some ideas similar to subsequent Western liberal thinking have periodically appeared. Starting in the late nineteenth century, translated Western works on liberalism became available. Currently, because of political intrigue, liberal themes are rare in official academic or political settings, but much liberal thinking is freely available, networks of liberal aficionados exist, and their activities and ideas are accessible to the public. The influence of many of these ideas is still relatively weak, and there are concerns about growing restrictions on politically threatening views. But economists most influenced by liberalism have some role in public opinion, though less so in shaping public policy. Given the huge tasks ahead in Chinese reform, liberals need to strengthen these networks, and to gain support from entrepreneurs in particular

EFMLNet: Fusion Model Based on End-to-End Mutual Information Learning for Hybrid EEG-fNIRS Brain-Computer Interface Applications

Electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS), both portable and non-invasive, enhance brain-computer interface (BCI) performance by integrating their spatial and temporal benefits when combined together. However, the fusion of these two signals still faces challenges. To fully unitize the complementarity of EEG and fNIRS for improved performance in EEG-fNIRS BCI, we propose an EEG-fNIRS fusion network based on end-to-end mutual information learning, named EFMLNet. In the model, EEG and fNIRS data are fed into their respective feature extractors for the extraction of temporal and spatial information. Furthermore, their complementary information is fused by two parallel mutual learning modules. We conducted classification experiments on a publicly available BCI dataset based on motor imagery (MI) task and achieved a cross-subject classification accuracy of 71.52%. This result surpasses the performance of most existing fusion methods and demonstrates the potential for real-time hybrid BCI systems