MDMP: Managed Data Message Passing

MDMP is a new parallel programming approach that aims to provide users with an easy way to add parallelism to programs, optimise the message passing costs of traditional scientific simulation algorithms, and enable existing MPI-based parallel programs to be optimised and extended without requiring the whole code to be re-written from scratch. MDMP utilises a directives based approach to enable users to specify what communications should take place in the code, and then implements those communications for the user in an optimal manner using both the information provided by the user and data collected from instrumenting the code and gathering information on the data to be communicated. This work will present the basic concepts and functionality of MDMP and discuss the performance that can be achieved using our prototype implementation of MDMP on some model scientific simulation applications.Comment: Submitted to SC13, 10 pages, 5 figure

Objective and Subjective Sleep in Rheumatoid Arthritis and Severe Seasonal Allergy : Preliminary Assessments of the Role of Sickness, Central and Peripheral Inflammation

Introduction: Disturbed sleep in inflammatory disorders such as allergy and rheumatoid arthritis (RA) is common and may be directly or indirectly related to disease processes, but has not been well characterized in these patient groups, especially not with objective methods. Aim: The present study aimed to characterize objective and subjective sleep in patients with allergy or RA using sleep diaries, one-channel EEG and actigraphy. It also aimed to investigate if sleep measures were associated with central immune activation, assessed using translocator protein (TSPO) positron emission tomography, as well as cytokine markers of peripheral inflammation and disease-specific symptoms or general symptoms of sickness. Methods: In total, 18 patients with seasonal pollen allergy, 18 patients with RA and 26 healthy controls were included in the study. Allergy patients and matched controls were assessed twice, in and out of pollen season, and RA patients and controls were assessed once. Sleep was recorded for approximately 1 week at each occasion. Results: Patients with allergy had increased levels of slow-wave sleep during pollen season. In contrast, patients with RA had less SWS compared to healthy controls, while no differences were observed in sleep duration or subjective sleep quality. Across groups, neither proinflammatory cytokines, grey matter TSPO levels nor general sickness symptoms were associated with objective or subjective measures of sleep. Rhinitis, but not conjunctivitis, was correlated to worse subjective sleep and more slow wave sleep in allergy. Functional status, but not disease activity, predicted lower subjective sleep in RA. Conclusion: This study tentatively indicates that both patients with allergy and RA display sleep alterations but does not support inflammation as an independent predictor of the sleep disturbance across these patient groups

Runaway electron modelling in the self-consistent core European Transport Simulator

Relativistic runaway electrons are a major concern in tokamaks. Although significant theoretical development had been undertaken in recent decades, we still lack a self-consistent simulator that could simultaneously capture all aspects of this phenomenon. The European framework for Integrated Modelling (EU-IM) facilitates the integration of different plasma simulation tools by providing a standard data structure for communication that enables relatively easy integration of different physics codes. A three-level modelling approach was adopted for runaway electron simulations within the EU-IM. Recently, a number of runaway electron modelling modules have been integrated into this framework. The first level of modelling (Runaway Indicator) is limited to the indication if runaway electron generation is possible or likely. The second level (Runaway Fluid) adopts an approach similar to e.g. the GO code, using analytical formulas to estimate changes in the runaway electron current density. The third level is based on the solution of the electron kinetics. One such code is LUKE that can handle the toroidicity-induced effects by solving the bounce-averaged Fokker-Planck equation. Another approach is used in NORSE, which features a fully nonlinear collision operator that makes it capable of simulating major changes in the electron distribution, for example slide-away. Both codes handle the effect of radiation on the runaway distribution. These runaway-electron modelling codes are in different stages of integration into the EU-IM infrastructure, and into the European Transport Simulator (ETS), which is a fully capable modular 1.5D core transport simulator. The ETS with Runaway Fluid was benchmarked to the GO code implementing similar physics. Coherent integration of kinetic solvers requires more effort on the coupling, especially regarding the definition of the boundary between runaway and thermal populations, and on consistent calculation of resistivity. Some of these issues are discussed

Evidence of fatigue, disordered sleep and peripheral inflammation, but not increased brain TSPO expression, in seasonal allergy : A [11C]PBR28 PET study

Allergy is associated with non-specific symptoms such as fatigue, sleep problems and impaired cognition. One explanation could be that the allergic inflammatory state includes activation of immune cells in the brain, but this hypothesis has not been tested in humans. The aim of the present study was therefore to investigate seasonal changes in the glial cell marker translocator protein (TSPO), and to relate this to peripheral inflammation, fatigue and sleep, in allergy. We examined 18 patients with severe seasonal allergy, and 13 healthy subjects in and out-of pollen season using positron emission tomography (n = 15/13) and the TSPO radioligand [C-11]PBR28. In addition, TNF-alpha, IL-5, IL-6, IL-8 and IFN-gamma were measured in peripheral blood, and subjective ratings of fatigue and sleepiness as well as objective and subjective sleep were investigated. No difference in levels of TSPO was seen between patients and healthy subjects, nor in relation to pollen season. However, allergic subjects displayed both increased fatigue, sleepiness and increased percentage of deep sleep, as well as increased levels of IL-5 and TNF-alpha during pollen season, compared to healthy subjects. Allergic subjects also had shorter total sleep time, regardless of season. In conclusion, allergic subjects are indicated to respond to allergen exposure during pollen season with a clear pattern of behavioral disruption and peripheral inflammatory activation, but not with changes in brain TSPO levels. This underscores a need for development and use of more specific markers to understand brain consequences of peripheral inflammation that will be applicable in human subjects

The Prognostic Value of Mitotic Activity Index (MAI), Phosphohistone H3 (PPH3), Cyclin B1, Cyclin A, and Ki67, Alone and in Combinations, in Node-Negative Premenopausal Breast Cancer

Proliferation, either as the main common denominator in genetic profiles, or in the form of single factors such as Ki67, is recommended for clinical use especially in estrogen receptor-positive (ER) patients. However, due to high costs of genetic profiles and lack of reproducibility for Ki67, studies on other proliferation factors are warranted. The aim of the present study was to evaluate the prognostic value of the proliferation factors mitotic activity index (MAI), phosphohistone H3 (PPH3), cyclin B1, cyclin A and Ki67, alone and in combinations. In 222 consecutive premenopausal node-negative breast cancer patients (87% without adjuvant medical treatment), MAI was assessed on whole tissue sections (predefined cut-off >= 10 mitoses), and PPH3, cyclin B1, cyclin A, and Ki67 on tissue microarray (predefined cut-offs 7th decile). In univariable analysis (high versus low) the strongest prognostic proliferation factor for 10-year distant disease-free survival was MAI (Hazard Ratio (HR)=3.3, 95% Confidence Interval (CI): 1.8-6.1), followed by PPH3, cyclin A, Ki67, and cyclin B1. A combination variable, with patients with MAI and/or cyclin A high defined as high-risk, had even stronger prognostic value (HR=4.2, 95% CI: 2.2-7). When stratifying for ER-status, MAI was a significant prognostic factor in ER-positive patients only (HR=7.0, 95% CI: 3.1-16). Stratified for histological grade, MAI added prognostic value in grade 2 (HR=7.2, 95% CI: 3.1-38) and grade 1 patients. In multivariable analysis including HER2, age, adjuvant medical treatment, ER, and one proliferation factor at a time, only MAI (HR=2.7, 95% CI: 1.1-6.7), and cyclin A (HR=2.7, 95% CI: 1.2-6.0) remained independently prognostic. In conclusion this study confirms the strong prognostic value of all proliferation factors, especially MAI and cyclin A, in all patients, and more specifically in ER-positive patients, and patients with histological grade 2 and 1. Additionally, by combining two proliferation factors, an even stronger prognostic value may be found

Validation of D–T fusion power prediction capability against 2021 JET D–T experiments

JET experiments using the fuel mixture envisaged for fusion power plants, deuterium and tritium (D–T), provide a unique opportunity to validate existing D–T fusion power prediction capabilities in support of future device design and operation preparation. The 2021 JET D–T experimental campaign has achieved D–T fusion powers sustained over 5 s in ITER-relevant conditions i.e. operation with the baseline or hybrid scenario in the full metallic wall. In preparation of the 2021 JET D–T experimental campaign, extensive D–T predictive modelling was carried out with several assumptions based on D discharges. To improve the validity of ITER D–T predictive modelling in the future, it is important to use the input data measured from 2021 JET D–T discharges in the present core predictive modelling, and to specify the accuracy of the D–T fusion power prediction in comparison with the experiments. This paper reports on the validation of the core integrated modelling with TRANSP, JINTRAC, and ETS coupled with a quasilinear turbulent transport model (Trapped Gyro Landau Fluid or QualLiKiz) against the measured data in 2021 JET D–T discharges. Detailed simulation settings and the heating and transport models used are described. The D–T fusion power calculated with the interpretive TRANSP runs for 38 D–T discharges (12 baseline and 26 hybrid discharges) reproduced the measured values within 20%. This indicates the additional uncertainties, that could result from the measurement error bars in kinetic profiles, impurity contents and neutron rates, and also from the beam-thermal fusion reaction modelling, are less than 20% in total. The good statistical agreement confirms that we have the capability to accurately calculate the D–T fusion power if correct kinetic profiles are predicted, and indicates that any larger deviation of the D–T fusion power prediction from the measured fusion power could be attributed to the deviation of the predicted kinetic profiles from the measured kinetic profiles in these plasma scenarios. Without any posterior adjustment of the simulation settings, the ratio of predicted D–T fusion power to the measured fusion power was found as 65%–96% for the D–T baseline and 81%–97% for D–T hybrid discharge. Possible reasons for the lower D–T prediction are discussed and future works to improve the fusion power prediction capability are suggested. The D–T predictive modelling results have also been compared to the predictive modelling of the counterpart D discharges, where the key engineering parameters are similar. Features in the predicted kinetic profiles of D–T discharges such as underprediction of ne are also found in the prediction results of the counterpart D discharges, and it leads to similar levels of the normalized neutron rate prediction between the modelling results of D–T and the counterpart D discharges. This implies that the credibility of D–T fusion power prediction could be a priori estimated by the prediction quality of the preparatory D discharges, which will be attempted before actual D–T experiments