Formation of helium spectrum in solar quiescent prominences

We present new non-LTE modelling of the helium spectrum emitted by quiescent solar prominences. The calculations are made in the frame of a one-dimensional plane-parallel slab. The physical parameters of our models are the electron temperature, the gas pressure, the slab width, the microturbulent velocity and the height above the solar surface. In this paper, we present isothermal isobaric models for a large range of temperature and pressure values. This work brings considerable improvements over the calculations of Heasley and co-workers (Heasley et al. 1974, Heasley and Milkey 1976, 1978, 1983) with the inclusion in our calculations of partial redistribution effects in the formation of the HI Lyα, Lyβ, HeI λ 584 Å and HeII λ 304 Å lines. In addition we consider detailed incident profiles for the principal transitions. The statistical equilibrium equations are solved for a 33 bound levels (HeI and HeII) plus continuum atom, and the radiative transfer equations are solved by the Feautrier method with variable Eddington factors. In this way we obtain the helium level populations and the emergent line profiles. We discuss the influence of the physical parameters on the helium level populations and on the main helium spectral lines. The effect of helium abundance in the prominence plasma is also studied. Some relations between singlet and triplet lines are given, as well as between optically thin or thick lines, HeI and HeII lines, and between the HeI λ 5876 Å and HI λ 4863 Å lines. In a future work this numerical code will be used for the diagnostic of the prominence plasma by comparing the results with SUMER observations

Social listening, modern slavery, and COVID-19

In addition to the public health crisis visited upon the world, the COVID-19 pandemic has created unique uncertainties for organisations engaged with the United Nations Sustainable Development Goals (SDGs), spanning a range of matters, such as maintaining operational momentum, financial sustainability, achieving policy influence, and engaging in strategic communications. In this article, we focus on organisations engaged in the fight against modern slavery, a significant part of Sustainable Development Goal 8, which seeks to ‘promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all’ with a particular focus on the call for states to ‘[t]ake immediate and effective measures to … end modern slavery’ (SDG 8.7). Our analysis highlights the importance of ‘social listening’ during the temporal and spatial progression of COVID-19 to: (a) facilitate the identification of agenda proxies reflected in strategic communications used by anti-slavery organisations, and (b) to provide insights into changing communication tactics deployed by these organisations in the context of mass-communication using social media as a result of the global pandemic

Numerical simulation of colloidal dispersion filtration: description of critical flux and comparison with experimental results

During filtration via membrane processes, colloids accumulate at the porous surface leading to fouling phenomena. In this study, a rigorous simulation of momentum and mass transfer using CFD modelling has been developed to describe such an accumulation during cross flow filtration. These simulations integrate detailed modeling of physicochemical properties specific to colloidal dispersions (because of the surface interactions (repulsive and attractive) occurring between the colloids particles). These interactions are accounted for via the experimental variation of the colloidal osmotic pressure with volume fraction (associated with a variation in the diffusion coefficient) which are fitted by a relationship integrated into the CFD code. It contains a description of the colloidal phase transition leading to the formation of a condensed phase (deposit or gel layer) from the accumulated dispersed phase (concentration polarization). It is then possible to determine the critical flux which separates filtration conditions below which mass accumulation is reversible (in the dispersed phase) and above which it is irreversible (in the condensed phase). The computed value of critical flux is compared with that determined experimentally for a dispersion of latex particles

Management of Residual or Recurrent Disease Following Thermal Ablation of Renal Cortical Tumors

Management of residual or recurrent disease following thermal ablation of renal cortical tumors includes surveillance, repeat ablation, or surgical extirpation. We present a multicenter experience with regard to the management of this clinical scenario. Prospectively maintained databases were reviewed to identify 1265 patients who underwent cryoablation (CA) or radiofrequency ablation (RFA) for enhancing renal masses. Disease persistence or recurrence was classified into one of the three categories: (i) residual disease in ablation zone; (ii) recurrence in the ipsilateral renal unit; and (iii) metastatic/extra-renal disease. Seventy seven patients (6.1%) had radiographic evidence of disease persistence or recurrence at a median interval of 13.7 months (range, 1–65 months) post-ablation. Distribution of disease included 47 patients with residual disease in ablation zone, 29 with ipsilateral renal unit recurrences (all in ablation zone), and one with metastatic disease. Fourteen patients (18%) elected for surveillance, and the remaining underwent salvage ablation (n = 50), partial nephrectomy (n = 5), or radical nephrectomy (n = 8). Salvage ablation was successful in 38/50 (76%) patients, with 12 failures managed by observation (3), tertiary ablation (6), and radical nephrectomy (3). At a median follow-up of 28 months, the actuarial cancer-specific survival and overall survival in this select cohort of patients was 94.8 and 89.6%, respectively

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

[EN] The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method.The data collection and labeling of the cerebellum was supported in part by the NIH/NINDS grant R01 NS056307 (PI: J.L. Prince) and NIH/NIMH grants R01 MH078160 & R01 MH085328 (PI: S.H. Mostofsky). PMT is supported in part by the NIH/NIBIB grant U54 EB020403. CERES2 development was supported by grant UPV2016-0099 from the Universitat Politecnica de Valencia (PI: J.V. Manjon); the French National Research Agency through the Investments for the future Program IdEx Bordeaux (ANR-10-IDEX-03-02, HL-MRI Project; PI: P. Coupe) and Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57; PI: P. Coupe). Support for the development of LiviaNET was provided by the National Science and Engineering Research Council of Canada (NSERC), discovery grant program, and by the ETS Research Chair on Artificial Intelligence in Medical Imaging. The authors wish to acknowledge the invaluable contributions offered by Dr. George Fein (Dept. of Medicine and Psychology, University of Hawaii) in preparing this manuscript.Carass, A.; Cuzzocreo, JL.; Han, S.; Hernandez-Castillo, CR.; Rasser, PE.; Ganz, M.; Beliveau, V.... (2018). Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images. NeuroImage. 183:150-172. https://doi.org/10.1016/j.neuroimage.2018.08.003S15017218

Interleukin-18 produced by bone marrow- derived stromal cells supports T-cell acute leukaemia progression

International audienceDevelopment of novel therapies is critical for T-cell acute leukae-mia (T-ALL). Here, we investigated the effect of inhibiting the MAPK/MEK/ERK pathway on T-ALL cell growth. Unexpectedly, MEK inhibitors (MEKi) enhanced growth of 70% of human T-ALL cell samples cultured on stromal cells independently of NOTCH activa-tion and maintained their ability to propagate in vivo. Similar results were obtained when T-ALL cells were cultured with ERK1/ 2-knockdown stromal cells or with conditioned medium from MEKi-treated stromal cells. Microarray analysis identified interleu-kin 18 (IL-18) as transcriptionally up-regulated in MEKi-treated MS5 cells. Recombinant IL-18 promoted T-ALL growth in vitro, whereas the loss of function of IL-18 receptor in T-ALL blast cells decreased blast proliferation in vitro and in NSG mice. The NFKB pathway that is downstream to IL-18R was activated by IL-18 in blast cells. IL-18 circulating levels were increased in T-ALL-xeno-grafted mice and also in T-ALL patients in comparison with controls. This study uncovers a novel role of the pro-inflammatory cytokine IL-18 and outlines the microenvironment involvement in human T-ALL development

Generalized index for spatial data sets as a measure of complete spatial randomness

Spatial data sets, generated from a wide range of physical systems can be analyzed by counting the number of objects in a set of bins. Previous work has been limited to equal-sized bins, which are inappropriate for some domains (e.g., circular). We consider a nonequal size bin configuration whereby overlapping or nonoverlapping bins cover the domain. A generalized index, defined in terms of a variance between bin counts, is developed to indicate whether or not a spatial data set, generated from exclusion or nonexclusion processes, is at the complete spatial randomness (CSR) state. Limiting values of the index are determined. Using examples, we investigate trends in the generalized index as a function of density and compare the results with those using equal size bins. The smallest bin size must be much larger than the mean size of the objects. We can determine whether a spatial data set is at the CSR state or not by comparing the values of a generalized index for different bin configurations—the values will be approximately the same if the data is at the CSR state, while the values will differ if the data set is not at the CSR state. In general, the generalized index is lower than the limiting value of the index, since objects do not have access to the entire region due to blocking by other objects. These methods are applied to two applications: (i) spatial data sets generated from a cellular automata model of cell aggregation in the enteric nervous system and (ii) a known plant data distribution.Emily J. Hackett-Jones, Kale J. Davies, Benjamin J. Binder, and Kerry A. Landma