Edge Shear Flows and Particle Transport near the Density Limit in the HL-2A Tokamak

Edge shear flow and its effect on regulating turbulent transport have long been suspected to play an important role in plasmas operating near the Greenwald density limit $n_G$. In this study, equilibrium profiles as well as the turbulent particle flux and Reynolds stress across the separatrix in the HL-2A tokamak are examined as $n_G$ is approached in ohmic L-mode discharges. As the normalized line-averaged density $\bar{n}_e/n_G$ is raised, the shearing rate of the mean poloidal flow $\omega_{\rm sh}$ drops, and the turbulent drive for the low-frequency zonal flow (the Reynolds power $\mathcal{P}_{Re}$) collapses. Correspondingly, the turbulent particle transport increases drastically with increasing collision rates. The geodesic acoustic modes (GAMs) gain more energy from the ambient turbulence at higher densities, but have smaller shearing rate than low-frequency zonal flows. The increased density also introduces decreased adiabaticity which not only enhances the particle transport but is also related to a reduction in the eddy-tilting and the Reynolds power. Both effects may lead to the cooling of edge plasmas and therefore the onset of MHD instabilities that limit the plasma density

Genome sequence of foot-and-mouth disease virus serotype O lineage ind-2001d collected in vietnam in 2015

© 2017 Arzt et al. In 2015, foot-and-mouth disease (FMD) virus lineage Ind-2001 was detected for the first time in Southeast Asia. This report contains the first nearcomplete genome sequence of a viral isolate from this lineage collected from an outbreak in Vietnam. This novel incursion has substantial implications for regional FMD control measures

A comparison of transgenic rodent mutation and in vivo comet assay responses for 91 chemicals.

A database of 91 chemicals with published data from both transgenic rodent mutation (TGR) and rodent comet assays has been compiled. The objective was to compare the sensitivity of the two assays for detecting genotoxicity. Critical aspects of study design and results were tabulated for each dataset. There were fewer datasets from rats than mice, particularly for the TGR assay, and therefore, results from both species were combined for further analysis. TGR and comet responses were compared in liver and bone marrow (the most commonly studied tissues), and in stomach and colon evaluated either separately or in combination with other GI tract segments. Overall positive, negative, or equivocal test results were assessed for each chemical across the tissues examined in the TGR and comet assays using two approaches: 1) overall calls based on weight of evidence (WoE) and expert judgement, and 2) curation of the data based on a priori acceptability criteria prior to deriving final tissue specific calls. Since the database contains a high prevalence of positive results, overall agreement between the assays was determined using statistics adjusted for prevalence (using AC1 and PABAK). These coefficients showed fair or moderate to good agreement for liver and the GI tract (predominantly stomach and colon data) using WoE, reduced agreement for stomach and colon evaluated separately using data curation, and poor or no agreement for bone marrow using both the WoE and data curation approaches. Confidence in these results is higher for liver than for the other tissues, for which there were less data. Our analysis finds that comet and TGR generally identify the same compounds (mainly potent mutagens) as genotoxic in liver, stomach and colon, but not in bone marrow. However, the current database content precluded drawing assay concordance conclusions for weak mutagens and non-DNA reactive chemicals

Tuning of Human Modulation Filters Is Carrier-Frequency Dependent

Licensed under the Creative Commons Attribution License

A Discrete Choice Experiment to assess patients’ preferences for HIV treatment in the rural population in Colombia

"Aim: To elicit patients’ preferences for HIV treatment of the rural population in Colombia. Methods: A discrete choice experiment (DCE), conducted in a HIV clinic in Bogotá, was used to examine the trade-off between five HIV treatment attributes: effect on life expectancy, effect on physical activity, risk of moderate side-effects, accessibility to clinic, and economic costs to access controls. Attributes selection was based on literature review, expert consultation and a focus group with six patients. An efficient experimental design was used to define two versions of the questionnaire with each of 12 choice sets and a dominance task was added to check reliability. A mixed logit model was then used to analyse the data and sub-group analyses were conducted on the basis of age, gender, education, and sexual preference. Results: A total of 129 HIV patients were included for analysis. For all treatment attributes, significant differences between at least two levels were observed, meaning that all attributes were significant predictors of choice. Patients valued the effect on physical activity (conditional relative importance of 27.5%) and the effect on life expectancy (26.0%) the most. Sub-group analyses regard age and education showed significant differences: younger patients and high educated patients valued the effect on physical activity the most important, whereas older patients mostly valued the effect on life expectancy and low educated patients mostly valued the accessibility to clinic. Limitations: One potential limitation is selection bias, as only patients from one HIV clinic were reached. Additionally, questionnaires were partly administered in the waiting rooms, which potentially led to noise in the data. Conclusions: This study suggests that all HIV treatment characteristics included in this DCE were important and that HIV patients from rural Colombia valued short-term efficacy (i.e. effect on physical activity) and long-term efficacy (i.e. effect on life expectancy) the most. © 2020, © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor and Francis Group.

A Discrete Choice Experiment to assess patients’ preferences for HIV treatment in the urban population in Colombia

Aim: This study aimed to assess patients' preferences for HIV treatment in an urban Colombian population. Methods: A Discrete Choice Experiment (DCE) was conducted. Urban Colombian HIV patients were asked to repetitively choose between two hypothetical treatments that differ in regard to five attributes 'effect on life expectancy', 'effect on physical activity', 'risk of moderate side effects, 'accessibility to clinic' and 'economic cost to access controls'. Twelve choice sets were made using an efficient design. A Mixed Logit Panel Model was used for the analysis and subgroup analyses were performed according to age, gender, education level and sexual preference. Results: A total of 224 HIV patients were included. All attributes were significant, indicating that there were differences between at least two levels of each attribute. Patients preferred to be able to perform all physical activity without difficulty, to have large positive effects on life expectancy, to travel less than 2 h, to have lower risk of side-effects and to have subsidized travel costs. The attributes 'effect on physical activity' and 'effects on life expectancy' were deemed the most important. Sub-analyses showed that higher educated patients placed more importance on the large positive effects of HIV treatment, and a more negative preference for subsidized travel cost (5% level). Limitations: A potential limitation is selection bias as it is difficult to make a systematic urban/rural division of respondents. Additional, questionnaires were partly administered in the waiting rooms, which potentially led to some noise in the data. Conclusions: Findings suggests that short-term efficacy (i.e. effect on physical activity) and long-term efficacy (i.e. effect on life expectancy) are the most important treatment characteristics for HIV urban patients in Colombia. Preference data could provide relevant information for clinical and policy decision-making to optimize HIV care

Inverse Modeling for MEG/EEG data

We provide an overview of the state-of-the-art for mathematical methods that are used to reconstruct brain activity from neurophysiological data. After a brief introduction on the mathematics of the forward problem, we discuss standard and recently proposed regularization methods, as well as Monte Carlo techniques for Bayesian inference. We classify the inverse methods based on the underlying source model, and discuss advantages and disadvantages. Finally we describe an application to the pre-surgical evaluation of epileptic patients.Comment: 15 pages, 1 figur