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Both long-duration gamma-ray bursts (LGRBs) from core collapse of massive stars and short-duration GRBs (SGRBs) from mergers of binary neutron star (BNS) or neutron star--black hole (NSBH) are expected to occur in the accretion disk of active galactic nuclei (AGNs). We show that GRB jets embedded in the migration traps of AGN disks are promised to be choked by the dense disk material. Efficient shock acceleration of cosmic rays at the reverse shock is expected, and high-energy neutrinos would be produced. We find that these sources can effectively produce detectable TeV--PeV neutrinos through $p\gamma$ interactions. From a choked LGRB jet with isotropic equivalent energy of $10^{53}\,{\rm erg}$ at $100\,{\rm Mpc}$, one expects $\sim2\,(7)$ neutrino events detectable by IceCube (IceCube-Gen2). The contribution from choked LGRBs to the observed diffuse neutrino background depends on the unknown local event rate density of these GRBs in AGN disks. For example, if the local event rate density of choked LGRBs in AGN disk is $\sim5\%$ that of low-luminosity GRBs $(\sim10\,{\rm Gpc}^{-3}\,{\rm yr}^{-1})$, the neutrinos from these events would contribute to $\sim10\%$ of the observed diffuse neutrino background. Choked SGRBs in AGN disks are potential sources for future joint electromagnetic, neutrino, and gravitational wave multi-messenger observations., Comment: 9 pages, 4 figures, 1 table, accepted for publication in ApJL

Neutron star mergers are believed to occur in accretion disks around supermassive black holes. Here we show that a putative jet launched from the merger of a binary neutron star (BNS) or a neutron star--black hole (NSBH) merger occurring at the migration trap in an active galactic nucleus (AGN) disk would be choked. The jet energy is deposited within the disk materials to power a hot cocoon. The cocoon is energetic enough to break out from the AGN disk and produce a bright X-ray shock breakout transient peaking at $\sim0.15\,{\rm d}$ after the merger. The peak luminosity is estimated as $\sim 10^{46}\,{\rm erg}\,{\rm s}^{-1}$, which can be discovered by Einstein Probe from $z\lesssim 0.5$. Later on, the non-relativistic ejecta launched from the merger would break out the disk, powering an X-ray/UV flare peaking at $\sim 0.5\,{\rm d}$ after the merger. This second shock breakout signal may be detected by UV transient searches. The cocoon cooling emission and kilonova emission are outshone by the disk emission and difficult to be detected. Future joint observations of gravitational waves from BNS/NSBH mergers and associated two shock breakout signatures can provide a strong support for the compact binary coalescence formation channel in AGN disks., Comment: 9 pages, 3 figures, accepted for publication in ApJL

We present detailed simulations of black hole-neutron star (BH-NS) mergers kilonova and gamma-ray burst (GRB) afterglow and kilonova luminosity function, and discuss the detectability of electromagnetic (EM) counterpart in connection with gravitational wave (GW) detections, GW-triggered target-of-opportunity observations, and time-domain blind searches. The predicted absolute magnitude of the BH-NS kilonovae at $0.5\,{\rm days}$ after the merger falls in $[-10,-15.5]$. The simulated luminosity function contains the potential viewing-angle distribution information of the anisotropic kilonova emission. We simulate the GW detection rates, detectable distances and signal duration, for the future networks of 2nd/2.5th/3rd-generation GW detectors. BH-NSs tend to produce brighter kilonovae and afterglows if the BH has a higher aligned-spin, and a less massive NS with a stiffer EoS. The detectability of kilonova is especially sensitive to the BH spin. If BHs typically have low spins, the BH-NS EM counterparts are hard to discover. For the 2nd generation GW detector networks, a limiting magnitude of $m_{\rm limit}\sim23-24\,{\rm mag}$ is required to detect the kilonovae even if BH high spin is assumed. Thus, a plausible explanation for the lack of BH-NS associated kilonova detection during LIGO/Virgo O3 is that either there is no EM counterpart (plunging events), or the current follow-ups are too shallow. These observations still have the chance to detect the on-axis jet afterglow associated with an sGRB or an orphan afterglow. Follow-up observations can detect possible associated sGRB afterglows, from which kilonova signatures may be studied. For time-domain observations, a high-cadence search in redder filters is recommended to detect more BH-NS associated kilonovae and afterglows., Comment: Accepted for Publication in ApJ, 36 pages, 17 figures, 6 tables

Microsatellite instability (MSI) is associated with several tumor types and its status has become increasingly vital in guiding patient treatment decisions. However, in clinical practice, distinguishing MSI from its counterpart is challenging since the diagnosis of MSI requires additional genetic or immunohistochemical tests. In this study, interpretable pathological image analysis strategies are established to help medical experts to automatically identify MSI. The strategies only require ubiquitous Haematoxylin and eosin-stained whole-slide images and can achieve decent performance in the three cohorts collected from The Cancer Genome Atlas. The strategies provide interpretability in two aspects. On the one hand, the image-level interpretability is achieved by generating localization heat maps of important regions based on the deep learning network; on the other hand, the feature-level interpretability is attained through feature importance and pathological feature interaction analysis. More interestingly, both from the image-level and feature-level interpretability, color features and texture characteristics are shown to contribute the most to the MSI predictions. Therefore, the classification models under the proposed strategies can not only serve as an efficient tool for predicting the MSI status of patients, but also provide more insights to pathologists with clinical understanding.

Retina image processing is one of the crucial and popular topics of medical image processing. The macula fovea is responsible for sharp central vision, which is necessary for human behaviors where visual detail is of primary importance, such as reading, writing, driving, etc. This paper proposes a novel method to locate the macula through a series of morphological processing. On the premise of maintaining high accuracy, our approach is simpler and faster than others. Furthermore, for the hospital's real images, our method is also able to detect the macula robustly.

When the magnetosphere of a magnetar is perturbed by crustal deformation, an electric field $E_\parallel$ parallel to the magnetic field line would appear via Alvf\'en waves in the charge starvation region. The electron-positron pair bunches will be generated via two-stream instability in the magnetosphere, and these pairs will undergo charge separation in the $E_\parallel$ and in the meantime emit coherent curvature radiation. Following the approach of Yang & Zhang (2018), we find that the superposed curvature radiation becomes narrower due to charge separation, with the width of spectrum depending on the separation between the electron and positron clumps. This mechanism can interpret the narrow spectra of FRBs, in particular, the spectrum of Galactic FRB 200428 recently detected in association with a hard X-ray burst from the Galactic magnetar SGR J1935+2154., Comment: 7 pages, 3 figures, accepted for publication in ApJL

Recent attempts at Super-Resolution for medical images used deep learning techniques such as Generative Adversarial Networks (GANs) to achieve perceptually realistic single image Super-Resolution. Yet, they are constrained by their inability to generalise to different scale factors. This involves high storage and energy costs as every integer scale factor involves a separate neural network. A recent paper has proposed a novel meta-learning technique that uses a Weight Prediction Network to enable Super-Resolution on arbitrary scale factors using only a single neural network. In this paper, we propose a new network that combines that technique with SRGAN, a state-of-the-art GAN-based architecture, to achieve arbitrary scale, high fidelity Super-Resolution for medical images. By using this network to perform arbitrary scale magnifications on images from the Multimodal Brain Tumor Segmentation Challenge (BraTS) dataset, we demonstrate that it is able to outperform traditional interpolation methods by up to 20$\%$ on SSIM scores whilst retaining generalisability on brain MRI images. We show that performance across scales is not compromised, and that it is able to achieve competitive results with other state-of-the-art methods such as EDSR whilst being fifty times smaller than them. Combining efficiency, performance, and generalisability, this can hopefully become a new foundation for tackling Super-Resolution on medical images. Check out the webapp here: https://metasrgan.herokuapp.com/ Check out the github tutorial here: https://github.com/pancakewaffles/metasrgan-tutorial, Comment: 12 pages, 8 figures, 1 table, to appear as a full paper with oral contribution in AIAI 2020

In this paper, we present a numerical method to study the predicted lightcurves as a function of viewing angle. We extrapolate the fitting formulae for the mass and velocity of tidal dynamical ejecta across a wide range of mass ratio validated with 66 simulations and use them in the calculations of the kilonova lightcurves. The calculated peak luminosity of a BH-NS merger kilonova is typically about a few times $10^{41}\ {\rm erg\ s^{-1}}$, which is always $\lesssim4.5\times10^{41}\ {\rm erg\ s^{-1}}$. This corresponds to the AB absolute magnitudes fainter than $\sim -15\ {\rm mag}$ in optical and $\sim -16\ {\rm mag}$ in infrared. Since the projected photosphere area of the dynamical ejecta is much larger than that of the disk wind outflows, the dynamical ejecta usually contribute to the majority of the kilonova emission from BH-NS mergers. The fitted blackbody temperature and the shape of the observed multi-band lightcurves are insensitive to the line of sight. The peak time of the observed multi-band lightcurves, affected by the light propagation effect, is related to the relative motion direction between the dynamical ejecta and the observer. The observed luminosity varies with the projected photosphere area determined by the viewing angles. However, the predicted peak luminosity only varies by a factor of $\sim (2 - 3)$ (or by $\sim1\ {\rm mag}$) for different viewing angles. When the short-duration gamma-ray burst afterglow is taken into account, for an on-axis geometry, the kilonova emission is usually outshone by the afterglow emission and can be only observed in the redder bands, especially in the $K$-band at late times. Compared with GW170817/AT2017gfo, the BH-NS merger kilonovae are optically dim but possibly infrared bright. At the same epoch after the merger, the blackbody fitting temperature of the BH-NS merger kilonovae is lower than that of GW170817/AT2017gfo., Comment: 44 pages, 19 figures, 3 tables, accepted for publication in ApJ