On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Global, regional, and national levels of maternal mortality, 1990�2015: a systematic analysis for the Global Burden of Disease Study 2015

Background In transitioning from the Millennium Development Goal to the Sustainable Development Goal era, it is imperative to comprehensively assess progress toward reducing maternal mortality to identify areas of success, remaining challenges, and frame policy discussions. We aimed to quantify maternal mortality throughout the world by underlying cause and age from 1990 to 2015. Methods We estimated maternal mortality at the global, regional, and national levels from 1990 to 2015 for ages 10�54 years by systematically compiling and processing all available data sources from 186 of 195 countries and territories, 11 of which were analysed at the subnational level. We quantified eight underlying causes of maternal death and four timing categories, improving estimation methods since GBD 2013 for adult all-cause mortality, HIV-related maternal mortality, and late maternal death. Secondary analyses then allowed systematic examination of drivers of trends, including the relation between maternal mortality and coverage of specific reproductive health-care services as well as assessment of observed versus expected maternal mortality as a function of Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Findings Only ten countries achieved MDG 5, but 122 of 195 countries have already met SDG 3.1. Geographical disparities widened between 1990 and 2015 and, in 2015, 24 countries still had a maternal mortality ratio greater than 400. The proportion of all maternal deaths occurring in the bottom two SDI quintiles, where haemorrhage is the dominant cause of maternal death, increased from roughly 68 in 1990 to more than 80 in 2015. The middle SDI quintile improved the most from 1990 to 2015, but also has the most complicated causal profile. Maternal mortality in the highest SDI quintile is mostly due to other direct maternal disorders, indirect maternal disorders, and abortion, ectopic pregnancy, and/or miscarriage. Historical patterns suggest achievement of SDG 3.1 will require 91 coverage of one antenatal care visit, 78 of four antenatal care visits, 81 of in-facility delivery, and 87 of skilled birth attendance. Interpretation Several challenges to improving reproductive health lie ahead in the SDG era. Countries should establish or renew systems for collection and timely dissemination of health data; expand coverage and improve quality of family planning services, including access to contraception and safe abortion to address high adolescent fertility; invest in improving health system capacity, including coverage of routine reproductive health care and of more advanced obstetric care�including EmOC; adapt health systems and data collection systems to monitor and reverse the increase in indirect, other direct, and late maternal deaths, especially in high SDI locations; and examine their own performance with respect to their SDI level, using that information to formulate strategies to improve performance and ensure optimum reproductive health of their population. Funding Bill & Melinda Gates Foundation. © 2016 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY licens

Alzheimer's disease and symbiotic microbiota: an evolutionary medicine perspective

Microorganisms resident in our bodies participate in a variety of regulatory and pathogenic processes. Here, we describe how etiological pathways implicated in Alzheimer’s disease (AD) may be regulated or disturbed by symbiotic microbial activity. Furthermore, the composition of symbiotic microbes has changed dramatically across human history alongside the rise of agriculturalism, industrialization, and globalization. We postulate that each of these lifestyle transitions engendered progressive depletion of microbial diversity and enhancement of virulence, thereby enhancing AD risk pathways. It is likely that the human life span extended into the eighth decade tens of thousands of years ago, yet little is known about premodern geriatric epidemiology. We propose that microbiota of the gut, oral cavity, nasal cavity, and brain may modulate AD pathogenesis, and that changes in the microbial composition of these body regions across history suggest escalation of AD risk. Dysbiosis may promote immunoregulatory dysfunction due to inadequate education of the immune system, chronic inflammation, and epithelial barrier permeability. Subsequently, proinflammatory agents—and occasionally microbes—may infiltrate the brain and promote AD pathogenic processes. APOE genotypes appear to moderate the effect of dysbiosis on AD risk. Elucidating the effect of symbiotic microbiota on AD pathogenesis could contribute to basic and translational research

Ion cyclotron resonance heating for tungsten control in various JET H-mode scenarios

Ion cyclotron resonance heating (ICRH) in the hydrogen minority scheme provides central ion heating and acts favorably on the core tungsten transport. Full wave modeling shows that, at medium power level (4 MW), after collisional redistribution, the ratio of power transferred to the ions and the electrons vary little with the minority (hydrogen) concentration n H/n e but the high-Z impurity screening provided by the fast ions temperature increases with the concentration. The power radiated by tungsten in the core of the JET discharges has been analyzed on a large database covering the 2013-2014 campaign. In the baseline scenario with moderate plasma current (I p = 2.5 MA) ICRH modifies efficiently tungsten transport to avoid its accumulation in the plasma centre and, when the ICRH power is increased, the tungsten radiation peaking evolves as predicted by the neo-classical theory. At higher current (3-4 MA), tungsten accumulation can be only avoided with 5 MW of ICRH power with high gas injection rate. For discharges in the hybrid scenario, the strong initial peaking of the density leads to strong tungsten accumulation. When this initial density peaking is slightly reduced, with an ICRH power in excess of 4 MW,very low tungsten concentration in the core (∼10-5) is maintained for 3 s. MHD activity plays a key role in tungsten transport and modulation of the tungsten radiation during a sawtooth cycle is correlated to the fishbone activity triggered by the fast ion pressure gradient

Sparse representation of signals: From astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Efficient, real-time and automated data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, two examples of which include the JET and ITER tokamaks. One problem which is common to these fields is the determination of the pulsation modes from an irregularly sampled time series. To this end, there are a wealth of signal processing techniques that are being applied to post-pulse and real-time data analysis in such complex systems. Here, we wish to present a review of the applications of a method based on the sparse representation of signals, using examples of the synergies that can be exploited when combining ideas and methods from very different fields, such as astronomy, astrophysics and thermonuclear fusion plasmas. Examples of this work in astronomy and astrophysics are the analysis of pulsation modes in various classes of stars and the orbit determination software of the Pioneer spacecraft. Two examples of this work in thermonuclear fusion plasmas include the detection of magneto-hydrodynamic instabilities, which is now performed routinely in JET in real-time on a sub-millisecond time scale, and the studies leading to the optimization of the magnetic diagnostic system in ITER and TCV. These questions have been solved by formulating them as inverse problems, despite the fact that these applicative frameworks are extremely different from the classical use of sparse representations, from both the theoretical and computational point of view. The requirements, prospects and ideas for the signal processing and real-time data analysis applications of this method to the routine operation of ITER will also be discussed. Finally, a very recent development has been the attempt to apply this method to the deconvolution of the measurement of electric potential performed during a ground-based survey of a proto-Villanovian necropolis in central Italy

Effect of PFC Recycling Conditions on JET Pedestal Density

There is experimental evidence that the pedestal dynamics in type-I ELMy H-mode discharges is significantly affected by a change in the recycling conditions at the tungsten plasma-facing components (W-PFCs) after an ELM event. The integrated code JINTRAC has been employed to assess the impact of recycling conditions during type-I ELMs in JET ITER-like wall H-mode discharges. By employing a heuristic approach, a model to mimic the physical processes leading to formation and release (i.e. outgassing) of finite near-surface fuel reservoirs in W-PFCs has been implemented into the EDGE2D-EIRENE plasma-wall interaction code being part of JINTRAC. As main result it is shown, that a delay in the density pedestal build-up after an ELM event can be provoked by reduced recycling induced by depleted W-PFC particle near-surface reservoirs. However the pedestal temperature evolution is barely affected by the change in recycling parameters suggesting that the presented model is incomplete

Real-time-capable prediction of temperature and density profiles in a tokamak using RAPTOR and a first-principle-based transport model

The RAPTOR code is a control-oriented core plasma profile simulator with various applications in control design and verification, discharge optimization and real-time plasma simulation. To date, RAPTOR was capable of simulating the evolution of poloidal flux and electron temperature using empirical transport models, and required the user to input assumptions on the other profiles and plasma parameters. We present an extension of the code to simulate the temperature evolution of both ions and electrons, as well as the particle density transport. A proof-of-principle neural-network emulation of the quasilinear gyrokinetic QuaLiKiz transport model is coupled to RAPTOR for the calculation of first-principle-based heat and particle turbulent transport. These extended capabilities are demonstrated in a simulation of a JET discharge. The multi-channel simulation requires ∼0.2 s to simulate 1 second of a JET plasma, corresponding to ∼20 energy confinement times, while predicting experimental profiles within the limits of the transport model. The transport model requires no external inputs except for the boundary condition at the top of the H-mode pedestal. This marks the first time that simultaneous, accurate predictions of Te, Tiand nehave been obtained using a first-principle-based transport code that can run in faster-than-real-time for present-day tokamaks