The electronic structure of the aqueous permanganate ion aqueous phase energetics and molecular bonding studied using liquid jet photoelectron spectroscopy

Permanganate aqueous solutions, MnO4 aq. , were studied using liquid micro jet based soft X ray non resonant and resonant photoelectron spectroscopy to determine valence and core level binding energies. To identify possible differences in the energetics between the aqueous bulk and the solution gas interface, non resonant spectra were recorded at two different probing depths. Similar experiments were performed with different counter ions, Na and K , with the two solutions yielding indistinguishable anion electron binding energies. Our resonant photoelectron spectroscopy measurements, performed near the Mn LII,III and O K edges, selectively probed valence charge distributions between the Mn metal center, O ligands, and first solvation shell in the aqueous bulk. Associated resonantly enhanced solute ionisation signals revealed hybridisation of the solute constituents atomic orbitals, including the inner valence Mn 3p and O 2s. We identified intermolecular Coulombic decay relaxation processes following resonant X ray excitation of the solute that highlight valence MnO4 aq. H2O l electronic couplings. Furthermore, our results allowed us to infer oxidative reorganisation energies of MnO4 aq. and adiabatic valence ionisation energies of MnO4 aq. , revealing the Gibbs free energy of oxidation and permitting estimation of the vertical electron affinity of MnO4 aq. . Finally, the Gibbs free energy of hydration of isolated MnO4 was determined. Our results and analysis allowed a near complete binding energy scaled MnO4 aq. molecular orbital and a valence energy level diagram to be produced for the MnO4 aq. MnO4 aq. system. Cumulatively, our mapping of the aqueous phase electronic structure of MnO4 is expected to contribute to a deeper understanding of the exceptional redox properties of this widely applied aqueous transition metal complex ion

The merger fraction of post-starburst galaxies in UNIONS

Funding information: CB gratefully acknowledges support from the Natural Sciences and Engineering Council of Canada (NSERC) as part of their post-doctoral fellowship program (PDF-546234-2020) and VW acknowledges STFC grant ST/V000861/1.Post-starburst galaxies (PSBs) are defined as having experienced a recent burst of star formation, followed by a prompt truncation in further activity. Identifying the mechanism(s) causing a galaxy to experience a post-starburst phase therefore provides integral insight into the causes of rapid quenching. Galaxy mergers have long been proposed as a possible post-starburst trigger. Effectively testing this hypothesis requires a large spectroscopic galaxy survey to identify the rare PSBs as well as high-quality imaging and robust morphology metrics to identify mergers. We bring together these critical elements by selecting PSBs from the overlap of the Sloan Digital Sky Survey and the Canada–France Imaging Survey and applying a suite of classification methods: non-parametric morphology metrics such as asymmetry and Gini-M20, a convolutional neural network trained to identify post-merger galaxies, and visual classification. This work is therefore the largest and most comprehensive assessment of the merger fraction of PSBs to date. We find that the merger fraction of PSBs ranges from 19 per cent to 42 per cent depending on the merger identification method and details of the PSB sample selection. These merger fractions represent an excess of 3–46× relative to non-PSB control samples. Our results demonstrate that mergers play a significant role in generating PSBs, but that other mechanisms are also required. However, applying our merger identification metrics to known post-mergers in the IllustrisTNG simulation shows that 70 per cent of recent post-mergers (≲200 Myr) would not be detected. Thus, we cannot exclude the possibility that nearly all PSBs have undergone a merger in their recent past.Publisher PDFPeer reviewe

The limitations (and potential) of non-parametric morphology statistics for post-merger identification

Non-parametric morphology statistics have been used for decades to classify galaxies into morphological types and identify mergers in an automated way. In this work, we assess how reliably we can identify galaxy post-mergers with non-parametric morphology statistics. Low-redshift (z<0.2), recent (t_post-merger 100 kpc) post-merger galaxies are drawn from the IllustrisTNG100-1 cosmological simulation. Synthetic r-band images of the mergers are generated with SKIRT9 and degraded to various image qualities, adding observational effects such as sky noise and atmospheric blurring. We find that even in perfect quality imaging, the individual non-parametric morphology statistics fail to recover more than 55% of the post-mergers, and that this number decreases precipitously with worsening image qualities. The realistic distributions of galaxy properties in IllustrisTNG allow us to show that merger samples assembled using individual morphology statistics are biased towards low mass, high gas fraction, and high mass ratio. However, combining all of the morphology statistics together using either a linear discriminant analysis or random forest algorithm increases the completeness and purity of the identified merger samples and mitigates bias with various galaxy properties. For example, we show that in imaging similar to that of the 10-year depth of the Legacy Survey of Space and Time (LSST), a random forest can identify 89% of mergers with a false positive rate of 17%. Finally, we conduct a detailed study of the effect of viewing angle on merger observability and find that there may be an upper limit to merger recovery due to the orientation of merger features with respect to the observer.Comment: 32 pages, 21 figures Accepted for publication by MNRA

Highlights of the Zeno Results from the USMP-2 Mission

The Zeno instrument, a High-precision, light-scattering spectrometer, was built to measure the decay rates of density fluctuations in xenon near its liquid-vapor critical point in the low-gravity environment of the U.S. Space Shuttle. Eliminating the severe density gradients created in a critical fluid by Earth's gravity, we were able to make measurements to within 100 microKelvin of the critical point. The instrument flew for fourteen days in March, 1994 on the Space Shuttle Columbia, STS-62 flight, as part of the very successful USMP-2 payload. We describe the instrument and document its performance on orbit, showing that it comfortably reached the desired 3 microKelvin temperature control of the sample. Locating the critical temperature of the sample on orbit was a scientific challenge; we discuss the advantages and short-comings of the two techniques we used. Finally we discuss problems encountered with making measurements of the turbidity of the sample, and close with the results of the measurement of the decay rates of the critical-point fluctuations

Programmed death ligand 1 is over-expressed by neutrophils in the blood of patients with active tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains one of the world's largest infectious disease problems. Despite decades of intensive study, the immune response to Mtb is incompletely characterised, reflecting the extremely complex interaction between pathogen and host. Pathways that may alter the balance between host protection and pathogenesis are therefore of great interest. One pathway shown to play a role in the pathogenesis of chronic infections, including TB, is the programmed death-1 (PD-1) pathway. We show here that the expression of the programmed death ligand 1 (PD-L1), which interacts with PD-1, is increased in whole blood from active TB patients compared with whole blood from healthy controls or Mtb-exposed individuals, and that expression by neutrophils is largely responsible for this increase

Modeling Progressive Fibrosis with Pluripotent Stem Cells Identifies an Anti-fibrotic Small Molecule.

Progressive organ fibrosis accounts for one-third of all deaths worldwide, yet preclinical models that mimic the complex, progressive nature of the disease are lacking, and hence, there are no curative therapies. Progressive fibrosis across organs shares common cellular and molecular pathways involving chronic injury, inflammation, and aberrant repair resulting in deposition of extracellular matrix, organ remodeling, and ultimately organ failure. We describe the generation and characterization of an in&nbsp;vitro progressive fibrosis model that uses cell types derived from induced pluripotent stem cells. Our model produces endogenous activated transforming growth factor β (TGF-β) and contains activated fibroblastic aggregates that progressively increase in size and stiffness with activation of known fibrotic molecular and cellular changes. We used this model as a phenotypic drug discovery platform for modulators of fibrosis. We validated this platform by identifying a compound that promotes resolution of fibrosis in in&nbsp;vivo and ex&nbsp;vivo models of ocular and lung fibrosis

Computational Complexity of Iterated Maps on the Interval (Extended Abstract)

The exact computation of orbits of discrete dynamical systems on the interval is considered. Therefore, a multiple-precision floating point approach based on error analysis is chosen and a general algorithm is presented. The correctness of the algorithm is shown and the computational complexity is analyzed. As a main result, the computational complexity measure considered here is related to the Ljapunow exponent of the dynamical system under consideration