Dynamics of ionization wave splitting and merging of atmospheric-pressure plasmas in branched dielectric tubes and channels

Atmospheric-pressure fast ionization waves (FIWs) generated by nanosecond, high voltage pulses are able to propagate long distances through small diameter dielectric tubes or channels, and so deliver UV fluxes, electric fields, charged and excited species to remote locations. In this paper, the dynamics of FIW splitting and merging in a branched dielectric channel are numerically investigated using a two-dimensional plasma hydrodynamics model with radiation transport, and the results are compared with experiments. The channel consists of a straight inlet section branching 90° into a circular loop which terminates to form a second straight outlet section aligned with the inlet section. The plasma is sustained in neon gas with a trace amount of xenon at atmospheric pressure. The FIW generated at the inlet approaches the first branch point with speeds of ≈10 8 cm s −1 , and produces a streamer at the inlet–loop junction. The induced streamer then splits into two FIW fronts, each propagating in opposite directions through half of the loop channel. The FIWs slow as they traverse the circular sections due to a shorting of the electric field by the other FIW. Approaching the loop–outlet junction, the two FIW fronts nearly come to a halt, induce another streamer which goes through further splitting and finally develops into a new FIW front. The new FIW increases in speed and plasma density propagating in the straight outlet channel. The electrical structure of the FIWs and the induced streamers during the splitting and merging processes are discussed with an emphasis on their mutual influence and their interaction with the channel wall. The FIW propagation pattern is in good agreement with experimental observations. Based on numerical and experimental investigations, a model for the splitting and merging FIWs in the branched loop channel is proposed.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98591/1/0022-3727_45_27_275201.pd

Rare gas flow structuration in plasma jet experiments

Modifications of rare gas flow by plasma generated with a plasma gun (PG) are evidenced through simultaneous time-resolved ICCD imaging and schlieren visualization. The geometrical features of the capillary inside which plasma propagates before in-air expansion, the pulse repetition rate and the presence of a metallic target are playing a key role on the rare gas flow at the outlet of the capillary when the plasma is switched on. In addition to the previously reported upstream offset of the laminar to turbulent transition, we document the reverse action leading to the generation of long plumes at moderate gas flow rates together with the channeling of helium flow under various discharge conditions. For higher gas flow rates, in the l min−1 range, time-resolved diagnostics performed during the first tens of ms after the PG is turned on, evidence that the plasma plume does not start expanding in a laminar neutral gas flow. Instead, plasma ignition leads to a gradual laminar-like flow build-up inside which the plasma plume is generated. The impact of such phenomena for gas delivery on targets mimicking biological samples is emphasized, as well as their consequences on the production and diagnostics of reactive species

Group connectivity in COSMOS: a tracer of mass assembly history

Cosmic filaments are the channel through which galaxy groups assemble their mass. Cosmic connectivity, namely the number of filaments connected to a given group, is therefore expected to be an important ingredient in shaping group properties. The local connectivity is measured in COSMOS around X-ray-detected groups between redshift 0.5 and 1.2. To this end, large-scale filaments are extracted using the accurate photometric redshifts of the COSMOS2015 catalogue in two-dimensional slices of thickness 120 comoving Mpc centred on the group's redshift. The link between connectivity, group mass, and the properties of the brightest group galaxy (BGG) is investigated. The same measurement is carried out on mocks extracted from the light-cone of the hydrodynamical simulation HORIZON-AGN in order to control systematics. More massive groups are on average more connected. At fixed group mass in low-mass groups, BGG mass is slightly enhanced at high connectivity, while in high-mass groups BGG mass is lower at higher connectivity. Groups with a star-forming BGG have on average a lower connectivity at given mass. From the analysis of the HORIZON-AGN simulation, we postulate that different connectivities trace different paths of group mass assembly: at high group mass, groups with higher connectivity are more likely to have grown through a recent major merger, which might be in turn the reason for the quenching of the BGG. Future large-field photometric surveys, such as Euclid and LSST, will be able to confirm and extend these results by probing a wider mass range and a larger variety of environment

Group connectivity in COSMOS : a tracer of mass assembly history

Cosmic filaments are the channel through which galaxy groups assemble their mass. Cosmic connectivity, namely the number of filaments connected to a given group, is therefore expected to be an important ingredient in shaping group properties. The local connectivity is measured in COSMOS around X-ray-detected groups between redshift 0.5 and 1.2. To this end, large-scale filaments are extracted using the accurate photometric redshifts of the COSMOS2015 catalogue in two-dimensional slices of thickness 120 comoving Mpc centred on the group's redshift. The link between connectivity, group mass, and the properties of the brightest group galaxy (BGG) is investigated. The same measurement is carried out on mocks extracted from the light-cone of the hydrodynamical simulation HORIZON-AGN in order to control systematics. More massive groups are on average more connected. At fixed group mass in low-mass groups, BGG mass is slightly enhanced at high connectivity, while in high-mass groups BGG mass is lower at higher connectivity. Groups with a star-forming BGG have on average a lower connectivity at given mass. From the analysis of the HORIZON-AGN simulation, we postulate that different connectivities trace different paths of group mass assembly: at high group mass, groups with higher connectivity are more likely to have grown through a recent major merger, which might be in turn the reason for the quenching of the BGG. Future large-field photometric surveys, such as Euclid and LSST, will be able to confirm and extend these results by probing a wider mass range and a larger variety of environment.Peer reviewe

Euclid preparation. III. Galaxy cluster detection in the wide photometric survey, performance and algorithm selection

Galaxy cluster counts in bins of mass and redshift have been shown to be a competitive probe to test cosmological models. This method requires an efficient blind detection of clusters from surveys with a well-known selection function and robust mass estimates, which is particularly challenging at high redshift. The Euclid wide survey will cover 15 000 deg2 of the sky, avoiding contamination by light from our Galaxy and our solar system in the optical and near-infrared bands, down to magnitude 24 in the H-band. The resulting data will make it possible to detect a large number of galaxy clusters spanning a wide-range of masses up to redshift ∼2 and possibly higher. This paper presents the final results of the Euclid Cluster Finder Challenge (CFC), fourth in a series of similar challenges. The objective of these challenges was to select the cluster detection algorithms that best meet the requirements of the Euclid mission. The final CFC included six independent detection algorithms, based on different techniques, such as photometric redshift tomography, optimal filtering, hierarchical approach, wavelet and friend-of-friends algorithms. These algorithms were blindly applied to a mock galaxy catalog with representative Euclid-like properties. The relative performance of the algorithms was assessed by matching the resulting detections to known clusters in the simulations down to masses of M₂₀₀ ∼ 10^(13.25) M⊙. Several matching procedures were tested, thus making it possible to estimate the associated systematic effects on completeness to 80% completeness for a mean purity of 80% down to masses of 10¹⁴ M⊙ and up to redshift z = 2. Based on these results, two algorithms were selected to be implemented in the Euclid pipeline, the Adaptive Matched Identifier of Clustered Objects (AMICO) code, based on matched filtering, and the PZWav code, based on an adaptive wavelet approach

The effects of cognitive therapy versus 'treatment as usual' in patients with major depressive disorder

BACKGROUND: Major depressive disorder afflicts an estimated 17% of individuals during their lifetimes at tremendous suffering and costs. Cognitive therapy may be an effective treatment option for major depressive disorder, but the effects have only had limited assessment in systematic reviews. METHODS/PRINCIPAL FINDINGS: Cochrane systematic review methodology, with meta-analyses and trial sequential analyses of randomized trials, are comparing the effects of cognitive therapy versus 'treatment as usual' for major depressive disorder. To be included the participants had to be older than 17 years with a primary diagnosis of major depressive disorder. Altogether, we included eight trials randomizing a total of 719 participants. All eight trials had high risk of bias. Four trials reported data on the 17-item Hamilton Rating Scale for Depression and four trials reported data on the Beck Depression Inventory. Meta-analysis on the data from the Hamilton Rating Scale for Depression showed that cognitive therapy compared with 'treatment as usual' significantly reduced depressive symptoms (mean difference -2.15 (95% confidence interval -3.70 to -0.60; P<0.007, no heterogeneity)). However, meta-analysis with both fixed-effect and random-effects model on the data from the Beck Depression Inventory (mean difference with both models -1.57 (95% CL -4.30 to 1.16; P = 0.26, I(2) = 0) could not confirm the Hamilton Rating Scale for Depression results. Furthermore, trial sequential analysis on both the data from Hamilton Rating Scale for Depression and Becks Depression Inventory showed that insufficient data have been obtained. DISCUSSION: Cognitive therapy might not be an effective treatment for major depressive disorder compared with 'treatment as usual'. The possible treatment effect measured on the Hamilton Rating Scale for Depression is relatively small. More randomized trials with low risk of bias, increased sample sizes, and broader more clinically relevant outcomes are needed