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The SRG/eROSITA All-Sky Surveys (eRASSs) combine the advantages of complete sky coverage and the energy resolution provided by the charge couple device and offer the most holistic and detailed view of the diffuse soft X-ray background (SXRB) to date. The first eRASS (eRASS1) was completed at solar minimum, when solar wind charge exchange emission was minimal, providing the clearest view of the SXRB. We aim to extract spatial and spectral information from each constituent of the SXRB in the western Galactic hemisphere, focusing on the local hot bubble (LHB). We extracted and analysed eRASS1 spectra from almost all directions in the western Galactic hemisphere by dividing the sky into equal signal-to-noise bins. We fitted all bins with fixed spectral templates of known background constituents. We find the temperature of the LHB exhibits a north-south dichotomy at high latitudes ($|b|>30^{\circ}$), with the south being hotter, with a mean temperature at $kT=121.8\pm0.6\,$eV and the north at $kT=100.8\pm0.5\,$eV. At low latitudes, the LHB temperature increases towards the Galactic plane, especially towards the inner Galaxy. The LHB emission measure (${\rm EM_{LHB}}$) enhances approximately towards the Galactic poles. The ${\rm EM_{LHB}}$ map shows clear anti-correlation with the local dust column density. In particular, we found tunnels of dust cavities filled with hot plasma, potentially forming a wider network of hot interstellar medium. We also constructed a three-dimensional LHB model from ${\rm EM_{LHB}}$, assuming constant density. The average thermal pressure of the LHB is $P_{\rm thermal}/k=10100^{+1200}_{-1500}\,{\rm cm^{-3}\,K}$, a lower value than typical supernova remnants and wind-blown bubbles. This could be an indication of the LHB being open towards high Galactic latitudes., Comment: 31 pages, 37 figures, published in A&A

There are two contradictory views of the eROSITA bubbles: either a 10 kpc-scale pair of giant bubbles blown by the Galactic center (GC), or a 100 pc-scale local structure coincidentally located in the direction of GC. A key element of this controversy is the distance to the bubbles. Based on the 3D dust distribution in the Galactic plane, we found three isolated, distant (500-800 pc) clouds at intermediate Galactic latitudes. Their projected morphologies perfectly match the X-ray shadows on the defining features of the north eROSITA bubble, i.e., the North Polar Spur (NPS) and the Lotus Petal Cloud (LPC), indicating that both the NPS and LPC are distant with a distance lower limit of nearly 1kpc. In the X-ray dark region between the NPS and LPC, we found a few polarized radio arcs and attributed them to the bubble's shock front. These arcs match up perfectly with the outer border of the NPS and LPC and provide a way to define the bubble's border. The border defined in this way can be well described by the line-of-sight tangent of a 3D skewed cup model rooted in the GC. We conclude that, instead of being two independent, distant features, NPS and LPC compose a single, giant bubble, which, therefore, is most plausibly a 10-kpc scale bubble rooted at the GC., Comment: Accepted for publication in ApJL. 11 pages, 5 figures

Methods. We utilized the combined five SRG/eROSITA All-Sky Survey data (eRASS:5) to perform X-ray imaging and spectral analyses of the Centaurus cluster in various directions to large radii. Surface brightness (SB) profiles out to $2R_{200}$ were constructed. We acquired gas temperature, metallicity, and normalization per area profiles out to $R_{200}$. We compared our results with previous Centaurus studies, cluster outskirts measurements, and simulations. Comprehensive sky background analysis was done across the FoV, in particular, to assess the variation of the eROSITA Bubble emission that partially contaminates the field. Results. The processed X-ray images show the known sloshing-induced structures in the core. The core ($r\leq11~\mathrm{kpc}$) is better described with a 2T model than a 1T model. Here, we measured lower T from the cooler component (~1.0 keV) and higher Z ($\sim\!1.6Z_\odot$), signifying an iron bias. In the intermediate radial range, we observed prominent SB and normalization per area excesses in the eastern sector (Cen 45 location), reaching out to $R_{500}$. Temperature enhancements near the location of Cen 45 imply that the gas is shock-heated due to the interaction with Cen 30, the significant excess behind Cen 45 center might be the tail/ram-pressure-stripped gas. We found good agreement between the outskirt temperatures with the profile from simulations and fit from Suzaku outskirts measurements. We detected significant SB emission to the sky background level out to $R_{200}$ with a $3.5\sigma$ and followed by $2.9\sigma$ at $1.1R_{200}$. The metallicity at $R_{500}-R_{200}$ is low but within the ranges of other outskirts studies. Conclusions. We present the first measurement of ICM morphology and properties of Centaurus cluster sampling the whole azimuth beyond $30'$, increasing the probed volume by a factor of almost 30., Comment: Submitted to the Astronomy & Astrophysics journal: 19 pages, 10 figures (main text), 2 figure (appendix)

Galactic-scale outflows of molecular gas from star-forming galaxies constitute the most direct evidence for regulation of star formation. In the early universe ($ z > 4 $), such outflows have recently been inferred from gravitationally-lensed dusty star-forming galaxies (DSFGs) based on ubiquitous detections of OH absorption extending to more blueshifted velocities than [CII] or CO emission in spatially-integrated spectra. Because these lines are redshifted to sub-mm wavelengths, such measurements require careful corrections for atmospheric absorption lines, and a proper accounting of sometimes large variations in measurement uncertainties over these lines. Taking these factors into consideration, we re-analyze OH and [CII] data taken with ALMA for the five sources where such data is available, of which four were categorised as exhibiting outflows. Based on their spatially-integrated spectra alone, we find statistically significant ($ \geq 3 \sigma $) OH absorption more blueshifted than [CII] emission in only one source. By contrast, searching channel maps for signals diluted below the detection threshold in spatially-integrated spectra, we find evidence for a separate kinematic component in OH absorption in all five sources in the form of: (i) more blueshifted OH absorption than [CII] emission and/or (ii) a component in OH absorption exhibiting a different spatio-kinematic pattern than [CII] emission, the latter presumably tracing gas in a rotating disc. Providing a more complete and accurate assessment of molecular outflows in gravitationally-lensed DSFGs, we suggest methods to better assess the precision of corrections for atmospheric absorption and to more accurately measure the source continuum in future observations., Comment: 18 pages, 8 figures, 2 tables

[abridged] Hot plasma plays a crucial role in regulating the baryon cycle within the Milky Way, flowing from the energetic sources in the Galactic center and disc, to the corona and the halo. This hot plasma represents an important fraction of the Galactic baryons, plays a key role in galactic outflows and is an important ingredient in galaxy evolution models. Taking advantage of the Spectrum-Roentgen-Gamma (SRG))/eROSITA first all-sky survey (eRASS1), in this work, we aim to provide a panoramic view of the hot circumgalactic medium (CGM) of the Milky Way. Here we present the eROSITA eRASS1 half sky maps in narrow energy bands corresponding to the most prominent soft X-ray lines: OVII and OVIII, which allow us to constrain the distribution of the hot plasma within and surrounding the Milky Way. We corrected the maps by removing the expected contribution associated with the cosmic X-ray background, the time-variable solar wind charge exchange, and the local hot bubble. We applied corrections to mitigate the effect of absorption, therefore highlighting the emission from the CGM of the Milky Way. We use the line ratio of the oxygen lines as a proxy to constrain the temperature of the warm-hot CGM, and we define a pseudo-temperature $\mathcal{T}$ map. The map highlights how different regions are dominated by different thermal components. Towards the outer halo, the temperature distribution of the CGM on angular scales of 2-20 deg is consistent with being constant $\Delta \mathcal{T} / \langle \mathcal{T}\rangle \leq 4\%$, with a marginal detection of $\Delta \mathcal{T} / \langle \mathcal{T}\rangle = 2.7 \% \pm 0.2\%$ (statistical) $\pm 0.6\%$ (systematic) in the southern hemisphere. Instead, significant variations $\sim 12\%$ are observed on many tens of degrees scales when comparing the northern and southern hemispheres., Comment: 15 pages, 14 figures, 1 table, A&A in press

Understanding how the properties of galaxies relate to the properties of the hot circum-galactic medium (CGM) around them can constrain galaxy evolution models. We measured the X-ray luminosity of the hot CGM based on the surface brightness profiles of central galaxy samples measured from Spectrum Roentgen Gamma (SRG)/eROSITA all-sky survey data. We related the X-ray luminosity to the galaxies' stellar and halo mass, and we compared the observed relations to the self-similar model and intrinsic (i.e., not forward-modeled) output of the IllustrisTNG, EAGLE, and SIMBA simulations. The average hot CGM X-ray luminosity ($L_{\rm X,CGM}$) correlates with the galaxy's stellar mass ($M_*$). It increases from $(1.6 \pm 2.1)\times10^{39} \rm erg\,s^{-1}$ to $(3.4 \pm 0.3)\times10^{41} \rm erg\,s^{-1}$, when $\log(M_*)$ increases from 10.0 to 11.5. A power law describes the correlation as $\log(L_{\rm X,CGM})= (2.4\pm 0.1)\times \log(M_*)+(14.6\pm1.5)$. The hot CGM X-ray luminosity as a function of halo mass is measured within $\log(M_{\rm 500c})=11.3-13.7$, extending our knowledge of the scaling relation by more than two orders of magnitude. $L_{\rm X,CGM}$ increases with $M_{\rm 500c}$ from $(3.0 \pm 1.6)\times10^{39}\ \rm erg\,s^{-1}$ at $\log(M_{\rm 500c})=11.3$ to $(1.3 \pm 0.1)\times10^{42}\ \rm erg\,s^{-1}$ at $\log(M_{\rm 500c})=13.7$. The relation follows a power law of $\log(L_{\rm X,CGM})= (1.32\pm 0.05)\times \log(M_{\rm 500c})+(24.1\pm0.7)$. Our observations highlight the necessity of non-gravitational processes at the galaxy group scale while suggesting these processes are sub-dominant at the galaxy scale. We show that the outputs of current cosmological galaxy simulations generally align with the observational results uncovered here but with possibly important deviations in selected mass ranges., Comment: Abstract abridged for arXiv submission, accepted by A&A

The circumgalactic medium (CGM) provides the material needed for galaxy formation and influences galaxy evolution. The hot ($T>10^6K$) CGM is poorly detected around galaxies with stellar masses ($M_*$) lower than $3\times10^{11}M_\odot$ due to the low surface brightness. We used the X-ray data from the first four SRG/eROSITA All-Sky Surveys (eRASS:4). Based on the SDSS spectroscopic survey and halo-based group finder algorithm, we selected central galaxies with spectroscopic redshifts of $z_{\rm spec}<0.2$ and stellar masses of $10.0<\log(M_*/M_\odot)<11.5$ (85,222 galaxies) -- or halo masses of $11.5<\log(M_{\rm 200m}/M_\odot)<14.0$ (125,512 galaxies). By stacking the X-ray emission around galaxies, masking the detected X-ray point sources and carefully modeling the X-ray emission from the unresolved active galactic nuclei (AGN) and X-ray binaries (XRB), we obtain the X-ray emission from the hot CGM. We detected the X-ray emission around MW-mass and more massive central galaxies extending up to the virial radius ($R_{\rm vir}$). We used a $\beta$ model to describe the X-ray surface brightness profile and found $\beta =0.43^{+0.10}_{-0.06}\,(0.37^{+0.04}_{-0.02})$ for MW-mass (M31-mass) galaxies.We estimated the baryon budget of the hot CGM and obtained a value that is lower than the prediction of $\Lambda$CDM cosmology, indicating significant gas depletion in these halos. We extrapolated the hot CGM profile measured within $R_{\rm vir}$ to larger radii and found that within $\approx 3 R_{\rm vir}$, the baryon budget is close to the $\Lambda$CDM cosmology prediction. Our results set a firm footing for the presence of the hot CGM around such galaxies. These measurements constitute a new benchmark for galaxy evolution models and possible implementations of feedback processes therein., Comment: Abstract abridged for arXiv submission, accepted by A&A

Stain variation is a unique challenge associated with automated analysis of digital pathology. Numerous methods have been developed to improve the robustness of machine learning methods to stain variation, but comparative studies have demonstrated limited benefits to performance. Moreover, methods to handle stain variation were largely developed for H&E stained data, with evaluation generally limited to classification tasks. Here we propose Stain Consistency Learning, a novel framework combining stain-specific augmentation with a stain consistency loss function to learn stain colour invariant features. We perform the first, extensive comparison of methods to handle stain variation for segmentation tasks, comparing ten methods on Masson's trichrome and H&E stained cell and nuclei datasets, respectively. We observed that stain normalisation methods resulted in equivalent or worse performance, while stain augmentation or stain adversarial methods demonstrated improved performance, with the best performance consistently achieved by our proposed approach. The code is available at: https://github.com/mlyg/stain_consistency_learning

SRG/eROSITA is situated in a halo orbit around L2 where the highly variable solar wind charge exchange (SWCX) emission from Earth's magnetosheath is expected to be negligible. The soft X-ray foreground emissions from the local hot bubble (LHB) and the remaining heliospheric SWCX emissions could be studied in unprecedented detail with eROSITA All-Sky Survey (eRASS) data in a 6-month cadence and better spectral resolution than ROSAT. We aim to use eRASS data of the sight lines towards three giant molecular clouds away from the Galactic plane to isolate and study the soft X-ray diffuse foreground emission. These X-ray shadows will serve as calibration baselines for the future three-dimensional structural study of the LHB. We conducted spectral analysis on the diffuse X-ray spectra of these clouds from the first four eRASSs to estimate and separate the heliospheric SWCX contribution from the LHB emission. We find the density of the LHB to be independent of the sight line with $n_e \sim 4 \times 10^{-3}\,$cm$^{-3}$, but not the temperature. We report a lower temperature of $kT_{\mathrm{LHB}}=0.084\pm0.004\,$keV towards Chamaeleon$~$II & III (Cha$~$II & III) than Ophiuchus (Oph) and Corona Australis (CrA), in which we measured $0.102\pm0.006$ and $0.112\pm0.009\,$keV, respectively. We measured the emission measure of the LHB to be $\sim 2\times10^{-3}\,$cm$^{-6}\,$pc at medium Galactic latitudes ($|b| \sim 20^{\circ}$). A monotonic increase in the SWCX contribution has been observed since the start of 2020, coincidental with the beginning of solar cycle 25. For Oph, SWCX has dominated the LHB in the $0.3$-$0.7\,$keV band intensity since eRASS2. We observed lower SWCX contributions in Cha$~$II & III and CrA, consistent with the expected decreasing solar wind ion density at high heliographic latitudes., Comment: 22 pages, 15 figures. Accepted for publication in A&A

Unveiling the true nature of Dark Matter (DM), which manifests itself only through gravity, is one of the principal quests in physics. Leading candidates for DM are weakly interacting massive particles (WIMPs) or ultralight bosons (axions), at opposite extremes in mass scales, that have been postulated by competing theories to solve deficiencies in the Standard Model of particle physics. Whereas DM WIMPs behave like discrete particles ($\varrho$DM), quantum interference between DM axions is manifested as waves ($\psi$DM). Here, we show that gravitational lensing leaves signatures in multiply-lensed images of background galaxies that reveal whether the foreground lensing galaxy inhabits a $\varrho$DM or $\psi$DM halo. Whereas $\varrho$DM lens models leave well documented anomalies between the predicted and observed brightnesses and positions of multiply-lensed images, $\psi$DM lens models correctly predict the level of anomalies left over by $\varrho$DM lens models. More challengingly, when subjected to a battery of tests for reproducing the quadruply-lensed triplet images in the system HS 0810+2554, $\psi$DM is able to reproduce all aspects of this system whereas $\varrho$DM often fails. The ability of $\psi$DM to resolve lensing anomalies even in demanding cases like HS 0810+2554, together with its success in reproducing other astrophysical observations, tilt the balance toward new physics invoking axions., Comment: Updated with accepted version. The Version of Record of this article is published in Nature Astronomy, and is available online at https://www.nature.com/articles/s41550-023-01943-9. Free online version : https://rdcu.be/damHj

We address the nature and origin of Super Star Clusters (SSCs) discovered by Holtzman et al. (1992) within a radius of $\sim$$5\,\rm kpc$ from the center of NGC 1275, the giant elliptical galaxy at the center of the Perseus Cluster. We show that, in contrast with the much more numerous population of SSCs subsequently discovered up to $\sim$$30\,\rm kpc$ from the center of this galaxy, the central SSC population have maximal masses an order of magnitude higher and a mass function with a shallower power-law slope. Furthermore, whereas the outer SSC population have ages spanning a few $\rm Myr$ to at least $\sim$$1\,\rm Gyr$, the central SSC population have ages strongly concentrated around $\sim$$500 \rm \, Myr$ with a $1\,\sigma$ dispersion of $\sim$$100\,\rm Myr$. These SSCs share a close spatial and temporal relationship with the "central spiral," which also has a radius $\sim$$5\,\rm kpc$ centered on NGC 1275 and a characteristic stellar age of $\sim$$150\,\rm Myr$ (Paper I). We argue that both the central SSC population and the central spiral formed from gas deposited by a residual cooling flow, with the SSCs forming first followed by the formation of the stellar body of the central spiral $\sim$$300$-$400\,\rm Myr$ later. The ages of the central SSC population imply that they are able to withstand very strong tidal fields near the center of NGC 1275, making them genuine progenitor globular clusters. Evidently, a spiral disk hosting progenitor globular clusters has recently formed at the center of a giant elliptical galaxy., Comment: 11 pages, 6 figures, accepted by ApJ

We address the nature and origin of a spiral disk at the center of NGC 1275, the giant elliptical galaxy at the center of the Perseus cluster, that spans a radius of $\sim$$5\,\rm kpc$. By comparing stellar absorption lines measured in long-slit optical spectra with synthetic spectra for single stellar populations, we find that fitting of these lines requires two stellar populations: (i) a very young population that peaks in radial velocity at $\pm 250 {\rm \, km \, s^{-1}}$ of the systemic velocity within a radius of $\sim$$720\,\rm pc$ of the nucleus, a $1\,\sigma$ velocity dispersion significantly lower than $140 {\rm \, km \, s^{-1}}$, and an age of $0.15 \pm 0.05 \rm\,Gyr$; and (ii) a very old population having a constant radial velocity with a radius corresponding to the systemic velocity, a much broader velocity dispersion of $\sim$$250 {\rm \, km \, s^{-1}}$, and an age of around $10\,\rm Gyr$. We attribute the former to a post-starburst population associated with the spiral disk, and the latter to the main stellar body of NGC 1275 along the same sight line. If the spiral disk is the remnant of a cannibalized galaxy, then its progenitor would have had to retain an enormous amount of gas in the face of intensive ram-pressure stripping so as to form a total initial mass in stars of $\sim 3 \times 10^9 \,M_\odot$. More likely, the central spiral originally comprised a gaseous body accreted over the distant past from a residual cooling flow, before experiencing a starburst $\sim$$0.15\,\rm Gyr$ ago to form its stellar body., Comment: 34 pages, 14 figures, accepted by ApJ

In recent years, there has been increasing interest to incorporate attention into deep learning architectures for biomedical image segmentation. The modular design of attention mechanisms enables flexible integration into convolutional neural network architectures, such as the U-Net. Whether attention is appropriate to use, what type of attention to use, and where in the network to incorporate attention modules, are all important considerations that are currently overlooked. In this paper, we investigate the role of the Focal parameter in modulating attention, revealing a link between attention in loss functions and networks. By incorporating a Focal distance penalty term, we extend the Unified Focal loss framework to include boundary-based losses. Furthermore, we develop a simple and interpretable, dataset and model-specific heuristic to integrate the Focal parameter into the Squeeze-and-Excitation block and Attention Gate, achieving optimal performance with fewer number of attention modules on three well-validated biomedical imaging datasets, suggesting judicious use of attention modules results in better performance and efficiency.

Manual segmentation is used as the gold-standard for evaluating neural networks on automated image segmentation tasks. Due to considerable heterogeneity in shapes, colours and textures, demarcating object boundaries is particularly difficult in biomedical images, resulting in significant inter and intra-rater variability. Approaches, such as soft labelling and distance penalty term, apply a global transformation to the ground truth, redefining the loss function with respect to uncertainty. However, global operations are computationally expensive, and neither approach accurately reflects the uncertainty underlying manual annotation. In this paper, we propose the Boundary Uncertainty, which uses morphological operations to restrict soft labelling to object boundaries, providing an appropriate representation of uncertainty in ground truth labels, and may be adapted to enable robust model training where systematic manual segmentation errors are present. We incorporate Boundary Uncertainty with the Dice loss, achieving consistently improved performance across three well-validated biomedical imaging datasets compared to soft labelling and distance-weighted penalty. Boundary Uncertainty not only more accurately reflects the segmentation process, but it is also efficient, robust to segmentation errors and exhibits better generalisation.

The Dice similarity coefficient (DSC) is both a widely used metric and loss function for biomedical image segmentation due to its robustness to class imbalance. However, it is well known that the DSC loss is poorly calibrated, resulting in overconfident predictions that cannot be usefully interpreted in biomedical and clinical practice. Performance is often the only metric used to evaluate segmentations produced by deep neural networks, and calibration is often neglected. However, calibration is important for translation into biomedical and clinical practice, providing crucial contextual information to model predictions for interpretation by scientists and clinicians. In this study, we provide a simple yet effective extension of the DSC loss, named the DSC++ loss, that selectively modulates the penalty associated with overconfident, incorrect predictions. As a standalone loss function, the DSC++ loss achieves significantly improved calibration over the conventional DSC loss across six well-validated open-source biomedical imaging datasets, including both 2D binary and 3D multi-class segmentation tasks. Similarly, we observe significantly improved calibration when integrating the DSC++ loss into four DSC-based loss functions. Finally, we use softmax thresholding to illustrate that well calibrated outputs enable tailoring of recall-precision bias, which is an important post-processing technique to adapt the model predictions to suit the biomedical or clinical task. The DSC++ loss overcomes the major limitation of the DSC loss, providing a suitable loss function for training deep learning segmentation models for use in biomedical and clinical practice. Source code is available at: https://github.com/mlyg/DicePlusPlus.

Background: Colonoscopy remains the gold-standard screening for colorectal cancer. However, significant miss rates for polyps have been reported, particularly when there are multiple small adenomas. This presents an opportunity to leverage computer-aided systems to support clinicians and reduce the number of polyps missed. Method: In this work we introduce the Focus U-Net, a novel dual attention-gated deep neural network, which combines efficient spatial and channel-based attention into a single Focus Gate module to encourage selective learning of polyp features. The Focus U-Net further incorporates short-range skip connections and deep supervision. Furthermore, we introduce the Hybrid Focal loss, a new compound loss function based on the Focal loss and Focal Tversky loss, to handle class-imbalanced image segmentation. For our experiments, we selected five public datasets containing images of polyps obtained during optical colonoscopy: CVC-ClinicDB, Kvasir-SEG, CVC-ColonDB, ETIS-Larib PolypDB and EndoScene test set. To evaluate model performance, we use the Dice similarity coefficient (DSC) and Intersection over Union (IoU) metrics. Results: Our model achieves state-of-the-art results for both CVC-ClinicDB and Kvasir-SEG, with a mean DSC of 0.941 and 0.910, respectively. When evaluated on a combination of five public polyp datasets, our model similarly achieves state-of-the-art results with a mean DSC of 0.878 and mean IoU of 0.809, a 14% and 15% improvement over the previous state-of-the-art results of 0.768 and 0.702, respectively. Conclusions: This study shows the potential for deep learning to provide fast and accurate polyp segmentation results for use during colonoscopy. The Focus U-Net may be adapted for future use in newer non-invasive screening and more broadly to other biomedical image segmentation tasks involving class imbalance and requiring efficiency.

Automatic segmentation methods are an important advancement in medical image analysis. Machine learning techniques, and deep neural networks in particular, are the state-of-the-art for most medical image segmentation tasks. Issues with class imbalance pose a significant challenge in medical datasets, with lesions often occupying a considerably smaller volume relative to the background. Loss functions used in the training of deep learning algorithms differ in their robustness to class imbalance, with direct consequences for model convergence. The most commonly used loss functions for segmentation are based on either the cross entropy loss, Dice loss or a combination of the two. We propose the Unified Focal loss, a new hierarchical framework that generalises Dice and cross entropy-based losses for handling class imbalance. We evaluate our proposed loss function on five publicly available, class imbalanced medical imaging datasets: CVC-ClinicDB, Digital Retinal Images for Vessel Extraction (DRIVE), Breast Ultrasound 2017 (BUS2017), Brain Tumour Segmentation 2020 (BraTS20) and Kidney Tumour Segmentation 2019 (KiTS19). We compare our loss function performance against six Dice or cross entropy-based loss functions, across 2D binary, 3D binary and 3D multiclass segmentation tasks, demonstrating that our proposed loss function is robust to class imbalance and consistently outperforms the other loss functions. Source code is available at: https://github.com/mlyg/unified-focal-loss

Machine learning methods offer great promise for fast and accurate detection and prognostication of COVID-19 from standard-of-care chest radiographs (CXR) and computed tomography (CT) images. Many articles have been published in 2020 describing new machine learning-based models for both of these tasks, but it is unclear which are of potential clinical utility. In this systematic review, we search EMBASE via OVID, MEDLINE via PubMed, bioRxiv, medRxiv and arXiv for published papers and preprints uploaded from January 1, 2020 to October 3, 2020 which describe new machine learning models for the diagnosis or prognosis of COVID-19 from CXR or CT images. Our search identified 2,212 studies, of which 415 were included after initial screening and, after quality screening, 61 studies were included in this systematic review. Our review finds that none of the models identified are of potential clinical use due to methodological flaws and/or underlying biases. This is a major weakness, given the urgency with which validated COVID-19 models are needed. To address this, we give many recommendations which, if followed, will solve these issues and lead to higher quality model development and well documented manuscripts., Comment: 35 pages, 3 figures, 2 tables, updated to the period 1 January 2020 - 3 October 2020

We point to a class of materials representing an exception to the Daltonian view that compounds maintain integer stoichiometry at low temperatures, because forming stoichiometry-violating defects cost energy. We show that carriers in the conduction band (CB) of degenerate insulators in Ca-Al-O, Ag-Al-O, or Ba-Nb-O systems can cause a self-regulating instability, whereby cation vacancies form exothermically because a fraction of the free carriers in the CB decay into the hole states formed by such vacancies, and this negative electron-hole recombination energy offsets the positive energy associated with vacancy bond breaking. This Fermi level-induced spontaneous non-stoichiometry can lead to the formation of crystallographically ordered vacancy compounds (OVCs), explaining the previously peculiar occurrence of unusual atomic sequences such as BalNbmOn with l:m:n ratios of 1:2:6, 3:5:15, or 9:10:30. This work has general ramifications as the degenerate insulators have found growing interests in many fields ranging from transparent conductors to electrides that are electron donating promotors for catalyst., Comment: 20 pages, 6 figures