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Early detection of COVID-19 is key in containing the pandemic. Disease detection and evaluation based on imaging is fast and cheap and therefore plays an important role in COVID-19 handling. COVID-19 is easier to detect in chest CT, however, it is expensive, non-portable, and difficult to disinfect, making it unfit as a point-of-care (POC) modality. On the other hand, chest X-ray (CXR) and lung ultrasound (LUS) are widely used, yet, COVID-19 findings in these modalities are not always very clear. Here we train deep neural networks to significantly enhance the capability to detect, grade and monitor COVID-19 patients using CXRs and LUS. Collaborating with several hospitals in Israel we collect a large dataset of CXRs and use this dataset to train a neural network obtaining above 90% detection rate for COVID-19. In addition, in collaboration with ULTRa (Ultrasound Laboratory Trento, Italy) and hospitals in Italy we obtained POC ultrasound data with annotations of the severity of disease and trained a deep network for automatic severity grading., Comment: Not approved for arXiv

In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in the diagnosis and monitoring of patients with COVID-19. Machine learning solutions have been shown to be useful for X-ray analysis and classification in a range of medical contexts. The purpose of this study is to create and evaluate a machine learning model for diagnosis of COVID-19, and to provide a tool for searching for similar patients according to their X-ray scans. In this retrospective study, a classifier was built using a pre-trained deep learning model (ReNet50) and enhanced by data augmentation and lung segmentation to detect COVID-19 in frontal CXR images collected between January 2018 and July 2020 in four hospitals in Israel. A nearest-neighbors algorithm was implemented based on the network results that identifies the images most similar to a given image. The model was evaluated using accuracy, sensitivity, area under the curve (AUC) of receiver operating characteristic (ROC) curve and of the precision-recall (P-R) curve. The dataset sourced for this study includes 2362 CXRs, balanced for positive and negative COVID-19, from 1384 patients (63 +/- 18 years, 552 men). Our model achieved 89.7% (314/350) accuracy and 87.1% (156/179) sensitivity in classification of COVID-19 on a test dataset comprising 15% (350 of 2326) of the original data, with AUC of ROC 0.95 and AUC of the P-R curve 0.94. For each image we retrieve images with the most similar DNN-based image embeddings; these can be used to compare with previous cases., Comment: Elisha Goldstein, Daphna Keidar, and Daniel Yaron have made an equal contribution and are equal first authors, listed alphabetically

We present numerical simulations of the evolution of a supernova (SN) remnant expanding into a uniform background medium with density $n_H = 1.0$ cm$^{-3}$ and temperature of $10^4$ K. We include a dynamically evolving non-equilibrium ionisation (NEI) network (consisting of all the ions of H, He, C, N, O, Ne, Mg, Si, S, Fe), frequency dependent radiation transfer (RT), thermal conduction, and a simple dust evolution model, all intra-coupled to each other and to the hydrodynamics. We assume spherical symmetry. Photo-ionisation, radiation losses, photo-heating, charge-exchange heating/cooling and radiation pressure are calculated on-the-fly depending on the local radiation field and ion fractions. We find that the dynamics and energetics (but not the emission spectra) of the SN remnants can be well modelled by collisional equilibrium cooling curves even in the absence of non-equilibrium cooling and radiative transport. We find that the effect of precursor ionising radiation at different stages of SN remnant are dominated by rapid cooling of the shock and differ from steady state shocks. The predicted column densities of different ions such as N II, C IV and N V, can be higher by up to several orders of magnitude compared to steady state shocks. We also present some high esolution emission spectra that can be compared with the observed remnants to obtain important information about the physical and chemical states of the remnant, as well as constrain the background ISM., Comment: 18 pages, accepted by MNRAS. Added implications towards 1D oscillatory instability in SN remnants

We introduce a new general-purpose time-dependent ionisation network (IN) and a radiation transport (RT) module in the magneto-hydrodynamic (MHD) code PLUTO. Our ionisation network is reliable for temperatures ranging from 5e3 to 3e8 K, and includes all ionisation states of H, He, C, N, O, Ne, Mg, Si, S and Fe making it suitable for studying a variety of astrophysical scenarios. Radiation loss for each ion-electron pair is calculated using CLOUDY-17 data on-the-fly. Photo-ionisation and charge exchange are the chemical heating mechanisms. The IN is fully coupled to the radiation transport module over a very large range of opacities at different frequencies. The RT module employs a method of short characteristics assuming spherical symmetry. The radiation module requires the assumption of spherical symmetry, while the IN is compatible with full 3D. We also include a simple prescription for dust opacity, grain destruction, and the dust contribution to radiation pressure. We present numerical tests to show the reliability and limitations of the new modules. We also present a post-processing tool to calculate projected column densities and emission spectra., Comment: 19 pages, accepted by MNRAS. Added error estimates for radiative transfer, and runtime plots for different components of the code. Added late time (>1Myr) dynamics of the HII region

We contrast the gas kinematics and dark matter contents of $z=2$ star-forming galaxies (SFGs) from state-of-the-art cosmological simulations within the $\Lambda$CDM framework to observations. To this end, we create realistic mock observations of massive SFGs ($M_*>4\times10^{10} M_{\odot}$, SFR $>50~M_{\odot}$ yr$^{-1}$) from the TNG50 simulation of the IllustrisTNG suite, resembling near-infrared, adaptive-optics assisted integral-field observations from the ground. Using observational line fitting and modeling techniques, we analyse in detail the kinematics of seven TNG50 galaxies from five different projections per galaxy, and compare them to observations of twelve massive SFGs by Genzel et al. (2020). The simulated galaxies show clear signs of disc rotation but mostly exhibit more asymmetric rotation curves, partly due to large intrinsic radial and vertical velocity components. At identical inclination angle, their one-dimensional velocity profiles can vary along different lines of sight by up to $\Delta v=200$ km s$^{-1}$. From dynamical modelling we infer rotation speeds and velocity dispersions that are broadly consistent with observational results. We find low central dark matter fractions compatible with observations ($f_{\rm DM}^v(

The standard cosmological model ($\Lambda$CDM) predicts the existence of the cosmic web: a distribution of matter into sheets and filaments connecting massive halos. However, observational evidence has been elusive due to the low surface brightness of the filaments. Recent deep MUSE/VLT data and upcoming observations offer a promising avenue for Ly$\alpha$ detection, motivating the development of modern theoretical predictions. We use hydrodynamical cosmological simulations run with the AREPO code to investigate the potential detectability of large-scale filaments, excluding contributions from the halos embedded in them. We focus on filaments connecting massive ($M_{200c}\sim(1-3)\times10^{12} M_\odot$) halos at z=3, and compare different simulation resolutions, feedback levels, and mock-image pixel sizes. We find increasing simulation resolution does not substantially improve detectability notwithstanding the intrinsic enhancement of internal filament structure. By contrast, for a MUSE integration of 31 hours, including feedback increases the detectable area by a factor of $\simeq$5.5 on average compared with simulations without feedback, implying that even the non-bound components of the filaments have substantial sensitivity to feedback. Degrading the image resolution from the native MUSE scale of (0.2")$^2$ per pixel to (5.3")$^2$ apertures has the strongest effect, increasing the detectable area by a median factor of $\simeq$200 and is most effective when the size of the pixel roughly matches the width of the filament. Finally, we find the majority of Ly$\alpha$ emission is due to electron impact collisional excitations, as opposed to radiative recombination.

Over the past decade increasingly robust estimates of the dense molecular gas content in galaxy populations between redshift 0 and the peak of cosmic galaxy/star formation from redshift 1-3 have become available. This rapid progress has been possible due to the advent of powerful ground-based, and space telescopes for combined study of several millimeter to far-IR, line or continuum tracers of the molecular gas and dust components. The main conclusions of this review are: 1. Star forming galaxies contained much more molecular gas at earlier cosmic epochs than at the present time. 2. The galaxy integrated depletion time scale for converting the gas into stars depends primarily on z or Hubble time, and at a given z, on the vertical location of a galaxy along the star-formation rate versus stellar mass "main-sequence" (MS) correlation. 3. Global rates of galaxy gas accretion primarily control the evolution of the cold molecular gas content and star formation rates of the dominant MS galaxy population, which in turn vary with the cosmological expansion. A second key driver may be global disk fragmentation in high-z, gas rich galaxies, which ties local free-fall time scales to galactic orbital times, and leads to rapid radial matter transport and bulge growth. Third, the low star formation efficiency inside molecular clouds is plausibly set by super-sonic streaming motions, and internal turbulence, which in turn may be driven by conversion of gravitational energy at high-z, and/or by local feedback from massive stars at low-z. 4. A simple 'gas regulator' model is remarkably successful in predicting the combined evolution of molecular gas fractions, star formation rates, galactic winds, and gas phase metallicities., Comment: To be published in Annual Reviews of Astronomy and Astrophysics

Supersonic turbulence results in strong density fluctuations in the interstellar medium (ISM), which have a profound effect on the chemical structure. Particularly useful probes of the diffuse ISM are the ArH$^+$, OH$^+$, H$_2$O$^+$ molecular ions, which are highly sensitive to fluctuations in the density and the H$_2$ abundance. We use isothermal magnetohydrodynamic (MHD) simulations of various sonic Mach numbers, $\mathcal{M}_s$, and density decorrelation scales, $y_{\rm dec}$, to model the turbulent density field. We post-process the simulations with chemical models and obtain the probability density functions (PDFs) for the H$_2$, ArH$^+$, OH$^+$ and H$_2$O$^+$ abundances. We find that the PDF dispersions increases with increasing $\mathcal{M}_s$ and $y_{\rm dec}$, as the magnitude of the density fluctuations increases, and as they become more coherent. Turbulence also affects the median abundances: when $\mathcal{M}_s$ and $y_{\rm dec}$ are high, low-density regions with low H$_2$ abundance become prevalent, resulting in an enhancement of ArH$^+$ compared to OH$^+$ and H$_2$O$^+$. We compare our models with Herschel observations. The large scatter in the observed abundances, as well as the high observed ArH$^+$/OH$^+$ and ArH$^+$/H$_2$O$^+$ ratios are naturally reproduced by our supersonic $(\mathcal{M}_s=4.5)$, large decorrelation scale $(y_{\rm dec}=0.8)$ model, supporting a scenario of a large-scale turbulence driving. The abundances also depend on the UV intensity, CR ionization rate, and the cloud column density, and the observed scatter may be influenced by fluctuations in these parameters., Comment: Accepted for publication in the Astrophysical Journal

We construct a new analytic phenomenological model for the extended circumgalactic material (CGM) of $L^*$ galaxies. Our model reproduces the OVII/OVIII absorption observations of the Milky Way (MW) and the OVI measurements reported by the COS-Halos and eCGM surveys. The warm/hot gas is in hydrostatic equilibrium in a MW gravitational potential, and we adopt a barotropic equation of state, resulting in a temperature variation as a function of radius. A pressure component with an adiabatic index of $\gamma=4/3$ is included to approximate the effects of a magnetic field and cosmic rays. We introduce a metallicity gradient motivated by the enrichment of the inner CGM by the Galaxy. We then present our fiducial model for the corona, tuned to reproduce the observed OVI-OVIII column densities, and with a total mass of $M_{\rm gas} \approx 5.5 \times 10^{10}~{\rm M_{\odot}}$ inside $r_{\rm cgm} \approx 280$ kpc. The gas densities in the CGM are low ($n_{\rm H} = 10^{-5} - 3 \times 10^{-4}~{\rm cm^{-3}}$) and its collisional ionization state is modified by the metagalactic radiation field (MGRF). We show that for OVI-bearing warm/hot gas with typical observed column densities $N_{\rm OVI} \sim 3 \times 10^{14}~{\rm cm^{-2}}$ at large ($\gtrsim 100$ kpc) impact parameters from the central galaxies, the ratio of the cooling to dynamical times, $t_{\rm cool}/t_{\rm dyn}$, has a model-independent upper limit of $\lesssim 4$. In our model, $t_{\rm cool}/t_{\rm dyn}$ at large radii is $\sim 2-3$. We present predictions for a wide range of future observations of the warm/hot CGM, from UV/X-ray absorption and emission spectroscopy, to dispersion measure (DM) and Sunyaev-Zeldovich CMB measurements. We provide the model outputs in machine-readable data files, for easy comparison and analysis., Comment: 24 pages, 15 figures. Accepted to ApJ