Highly-mass-loaded hot galactic winds are unstable to cool filament formation

When cool clouds are ram-pressure accelerated by a hot supersonic galactic wind, some of the clouds may be shredded by hydrodynamical instabilities and incorporated into the hot flow. Recent one-dimensional steady-state calculations show how cool cloud entrainment directly affects the bulk thermodynamics, kinematics, and observational characteristics of the hot gas. In particular, mass-loading decelerates the hot flow and changes its entropy. Here, we investigate the stability of planar and spherical mass-loaded hot supersonic flows using both perturbation analysis and three-dimensional time-dependent radiative hydrodynamical simulations. We show that mass-loading is stable over a broad range of parameters and that the 1D time-steady analytic solutions exactly reproduce the 3D time-dependent calculations, provided that the flow does not decelerate sufficiently to become subsonic. For higher values of the mass-loading, the flow develops a sonic point and becomes thermally unstable, rapidly cooling and forming elongated dense cometary filaments. We explore the mass-loading parameters required to reach a sonic point and the radiative formation of these filaments. For certain approximations, we can derive simple analytic criteria. In general a mass-loading rate similar to the initial mass outflow rate is required. In this sense, the destruction of small cool clouds by a hot flow may ultimately spontaneously generate fast cool filaments, as observed in starburst superwinds. Lastly, we find that the kinematics of filaments is sensitive to the slope of the mass-loading function. Filaments move faster than the surrounding wind if mass-loading is over long distances whereas filaments move slower than their surroundings if mass-loading is abrupt.Comment: 12 pages, 15 figures, submitted to MNRAS (21 July 2023

Temperature and Metallicity Gradients in the Hot Gas Outflows of M82

We utilize deep Chandra X-ray Observatory imaging and spectra of M82, the prototype of a starbursting galaxy with a multiphase wind, to map the hot plasma properties along the minor axis of the galaxy. We extract spectra from 11 regions up to 2.5 kpc from the starbursting midplane and model the data as a multi-temperature, optically thin thermal plasma with contributions from a non-thermal (power-law) component and from charge exchange (CX). We examine the gradients in best-fit parameters, including the intrinsic column density, plasma temperature, metal abundances, and number density of the hot gas as a function of distance from the M82 nucleus. We find that the temperatures and number densities of the warm-hot and hot plasma peak at the starbursting ridge and decreases along the minor axis. The temperature and density profiles are inconsistent with spherical adiabatic expansion of a super-heated wind and suggest mass loading and mixing of the hot phase with colder material. Non-thermal emission is detected in all of the regions considered, and CX comprises 8-25% of the total absorption-corrected, broad-band (0.5-7 keV) X-ray flux. We show that the abundances of O, Ne, Mg, and Fe are roughly constant across the regions considered, while Si and S peak within 500 pc of the central starburst. These findings support a direct connection between the M82 superwind and the warm-hot, metal-rich circumgalactic medium (CGM).Comment: 15 pages, 8 figures, ApJ in pres

Neural ODEs as a discovery tool to characterize the structure of the hot galactic wind of M82

Dynamic astrophysical phenomena are predominantly described by differential equations, yet our understanding of these systems is constrained by our incomplete grasp of non-linear physics and scarcity of comprehensive datasets. As such, advancing techniques in solving non-linear inverse problems becomes pivotal to addressing numerous outstanding questions in the field. In particular, modeling hot galactic winds is difficult because of unknown structure for various physical terms, and the lack of \textit{any} kinematic observational data. Additionally, the flow equations contain singularities that lead to numerical instability, making parameter sweeps non-trivial. We leverage differentiable programming, which enables neural networks to be embedded as individual terms within the governing coupled ordinary differential equations (ODEs), and show that this method can adeptly learn hidden physics. We robustly discern the structure of a mass-loading function which captures the physical effects of cloud destruction and entrainment into the hot superwind. Within a supervised learning framework, we formulate our loss function anchored on the astrophysical entropy ($K \propto P/\rho^{5/3}$). Our results demonstrate the efficacy of this approach, even in the absence of kinematic data $v$. We then apply these models to real Chandra X-Ray observations of starburst galaxy M82, providing the first systematic description of mass-loading within the superwind. This work further highlights neural ODEs as a useful discovery tool with mechanistic interpretability in non-linear inverse problems. We make our code public at this GitHub repository (https://github.com/dustindnguyen/2023_NeurIPS_NeuralODEs_M82).Comment: 9 Pages, 2 Figures, Accepted at the NeurIPS 2023 workshop on Machine Learning and the Physical Science

X-ray Properties of NGC 253's Starburst-Driven Outflow

We analyze image and spectral data from $\approx$365~ks of observations from the {\it Chandra} X-ray Observatory of the nearby, edge-on starburst galaxy NGC~253 to constrain properties of the hot phase of the outflow. We focus our analysis on the $-$1.1 to $+$0.63 kpc region of the outflow and define several regions for spectral extraction where we determine best-fit temperatures and metal abundances. We find that the temperatures and electron densities peak in the central $\sim$250 pc region of the outflow and decrease with distance. These temperature and density profiles are in disagreement with an adiabatic spherically expanding starburst wind model and suggest the presence of additional physics such as mass loading and non-spherical outflow geometry. Our derived temperatures and densities yield few-Myr cooling times in the nuclear region, which may imply that the hot gas can undergo bulk radiative cooling as it escapes along the minor axis. Our metal abundances of O, Ne, Mg, Si, S, and Fe all peak in the central region and decrease with distance along the outflow, with the exception of Ne which maintains a flat distribution. The metal abundances indicate significant dilution outside of the starburst region. We also find estimates on the mass outflow rates which are $2.8\:M_{\odot}/\rm{yr}$ in the northern outflow and $3.2\:M_{\odot}/\rm{yr}$ in the southern outflow. Additionally, we detect emission from charge exchange and find it has a significant contribution ($20-42$\%) to the total broad-band ($0.5-7$~keV) X-ray emission in the central and southern regions of the outflow.Comment: 15 pages, 9 figure

The Eighth Data Release of the Sloan Digital Sky Survey: First Data from SDSS-III

The Sloan Digital Sky Survey (SDSS) started a new phase in August 2008, with new instrumentation and new surveys focused on Galactic structure and chemical evolution, measurements of the baryon oscillation feature in the clustering of galaxies and the quasar Ly alpha forest, and a radial velocity search for planets around ~8000 stars. This paper describes the first data release of SDSS-III (and the eighth counting from the beginning of the SDSS). The release includes five-band imaging of roughly 5200 deg^2 in the Southern Galactic Cap, bringing the total footprint of the SDSS imaging to 14,555 deg^2, or over a third of the Celestial Sphere. All the imaging data have been reprocessed with an improved sky-subtraction algorithm and a final, self-consistent photometric recalibration and flat-field determination. This release also includes all data from the second phase of the Sloan Extension for Galactic Understanding and Evolution (SEGUE-2), consisting of spectroscopy of approximately 118,000 stars at both high and low Galactic latitudes. All the more than half a million stellar spectra obtained with the SDSS spectrograph have been reprocessed through an improved stellar parameters pipeline, which has better determination of metallicity for high metallicity stars.Comment: Astrophysical Journal Supplements, in press (minor updates from submitted version

Bioactive Hydrogel Substrates: Probing Leukocyte Receptor–Ligand Interactions in Parallel Plate Flow Chamber Studies

The binding of activated integrins on the surface of leukocytes facilitates the adhesion of leukocytes to vascular endothelium during inflammation. Interactions between selectins and their ligands mediate rolling, and are believed to play an important role in leukocyte adhesion, though the minimal recognition motif required for physiologic interactions is not known. We have developed a novel system using poly(ethylene glycol) (PEG) hydrogels modified with either integrin-binding peptide sequences or the selectin ligand sialyl Lewis X (SLe(X)) within a parallel plate flow chamber to examine the dynamics of leukocyte adhesion to specific ligands. The adhesive peptide sequences arginine–glycine–aspartic acid–serine (RGDS) and leucine–aspartic acid–valine (LDV) as well as sialyl Lewis X were bound to the surface of photopolymerized PEG diacrylate hydrogels. Leukocytes perfused over these gels in a parallel plate flow chamber at physiological shear rates demonstrate both rolling and firm adhesion, depending on the identity and concentration of ligand bound to the hydrogel substrate. This new system provides a unique polymer-based model for the study of interactions between leukocytes and endothelium as well as a platform to develop improved scaffolds for cardiovascular tissue engineering

Lovastatin delays infection and increases survival rates in AG129 mice infected with dengue virus serotype 2

ABSTARCT: It has been reported that treatment of DENV-infected cultures with Lovastatin (LOV), can affect viral assembly. The objective of this study was to evaluate the effect of LOV on the survival rate and viremia levels of DENV-2-infected AG129 mice. Methodology/Principal Findings: Mice were inoculated with 16106 plaque-forming units (PFU/ml) of DENV-2 and treated with LOV (200 mg/kg/day). Pre-treatment with one or three doses of LOV increased the survival rate compared to untreated mice (7.3 and 7.1 days, respectively, compared to 4.8 days). Viremia levels also decreased by 21.8% compared to untreated mice, but only in the group administered three doses prior to inoculation. When LOV was administered after viral inoculation, the survival rate increased (7.3 days in the group treated at 24 hpi, 6.8 days in the group treated at 48 hpi and 6.5 days in the group treated with two doses) compared to the untreated group (4.8 days). Interestingly, the serum viral titer increased by 24.6% in mice treated at 48 hpi with a single dose of LOV and by 21.7% in mice treated with two doses (at 24 and 48 hpi) of LOV compared to untreated mice. Finally histopathological changes in the liver and spleen in infected and untreated mice included massive extramedullary erythropoiesis foci and inflammatory filtration, and these characteristics were decreased or absent in LOV-treated mice. Conclusions/Significance: Our results suggest that the effect of LOV on viremia depends on the timing of treatment and on the number of doses administered. We observed a significant increase in the survival rate in both schemes due to a delay in the progression of the disease. However, the results obtained in the post-treatment scheme must be handled carefully because this treatment scheme increases viremia and we do not know how this increase could affect disease progression in humans

Fatty Acid Composition of Developing Sea Buckthorn (Hippophae rhamnoides L.) Berry and the Transcriptome of the Mature Seed

Background: Sea buckthorn (Hippophae rhamnoides L.) is a hardy, fruit-producing plant known historically for its medicinal and nutraceutical properties. The most recognized product of sea buckthorn is its fruit oil, composed of seed oil that is rich in essential fatty acids, linoleic (18:2\u3c9-6) and \u3b1-linolenic (18:3\u3c9-3) acids, and pulp oil that contains high levels of monounsaturated palmitoleic acid (16:1\u3c9-7). Sea buckthorn is fast gaining popularity as a source of functional food and nutraceuticals, but currently has few genomic resources; therefore, we explored the fatty acid composition of Canadian-grown cultivars (ssp. mongolica) and the sea buckthorn seed transcriptome using the 454 GS FLX sequencing technology. Results: GC-MS profiling of fatty acids in seeds and pulp of berries indicated that the seed oil contained linoleic and \u3b1-linolenic acids at 33-36% and 30-36%, respectively, while the pulp oil contained palmitoleic acid at 32-42%. 454 sequencing of sea buckthorn cDNA collections from mature seeds yielded 500,392 sequence reads, which identified 89,141 putative unigenes represented by 37,482 contigs and 51,659 singletons. Functional annotation by Gene Ontology and computational prediction of metabolic pathways indicated that primary metabolism (protein>nucleic acid>carbohydrate>lipid) and fatty acid and lipid biosynthesis pathways were highly represented categories. Sea buckthorn sequences related to fatty acid biosynthesis genes in Arabidopsis were identified, and a subset of these was examined for transcript expression at four developing stages of the berry. Conclusion: This study provides the first comprehensive genomic resources represented by expressed sequences for sea buckthorn, and demonstrates that the seed oil of Canadian-grown sea buckthorn cultivars contains high levels of linoleic acid and \u3b1-linolenic acid in a close to 1:1 ratio, which is beneficial for human health. These data provide the foundation for further studies on sea buckthorn oil, the enzymes involved in its biosynthesis, and the genes involved in the general hardiness of sea buckthorn against environmental conditions.Peer reviewed: YesNRC publication: Ye

The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III

The third generation of the Sloan Digital Sky Survey (SDSS-III) took data from 2008 to 2014 using the original SDSS wide-field imager, the original and an upgraded multi-object fiber-fed optical spectrograph, a new near-infrared high-resolution spectrograph, and a novel optical interferometer. All of the data from SDSS-III are now made public. In particular, this paper describes Data Release 11 (DR11) including all data acquired through 2013 July, and Data Release 12 (DR12) adding data acquired through 2014 July (including all data included in previous data releases), marking the end of SDSS-III observing. Relative to our previous public release (DR10), DR12 adds one million new spectra of galaxies and quasars from the Baryon Oscillation Spectroscopic Survey (BOSS) over an additional 3000 deg2 of sky, more than triples the number of H-band spectra of stars as part of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE), and includes repeated accurate radial velocity measurements of 5500 stars from the Multi-object APO Radial Velocity Exoplanet Large-area Survey (MARVELS). The APOGEE outputs now include the measured abundances of 15 different elements for each star. In total, SDSS-III added 5200 deg2 of ugriz imaging; 155,520 spectra of 138,099 stars as part of the Sloan Exploration of Galactic Understanding and Evolution 2 (SEGUE-2) survey; 2,497,484 BOSS spectra of 1,372,737 galaxies, 294,512 quasars, and 247,216 stars over 9376 deg2; 618,080 APOGEE spectra of 156,593 stars; and 197,040 MARVELS spectra of 5513 stars. Since its first light in 1998, SDSS has imaged over 1/3 of the Celestial sphere in five bands and obtained over five million astronomical spectra. \ua9 2015. The American Astronomical Society