Miracle-dz/UniFAR-FTUs huggingface dataset:
X-RAY AND GAMMA-RAY EMISSION FROM MIDDLE-AGED SUPERNOVA REMNANTS IN CAVITIES. I. SPHERICAL SYMMETRY

We present analytical and numerical studies of models of supernova-remnant (SNR) blast waves in one spatial dimension expanding into uniform media and interacting with a denser cavity wall. We predict the nonthermal emission from such blast waves: synchrotron emission at radio and X-ray energies, and bremsstrahlung, inverse-Compton emission (from cosmic-microwave-background seed photons; ICCMB), and emission from the decay of mesons produced in inelastic collisions between accelerated ions and thermal gas, at GeV and TeV energies. Accelerated-particle spectra are assumed to be power laws with exponential cutoffs at energies limited by the remnant age or (for electrons, if lower) by radiative losses. We compare the results with those from homogeneous (“one-zone”) models. Such models give fair representations of the 1D results for uniform media, but cavity-wall interactions produce effects for which one-zone models are inadequate. We study the time evolution of SNR morphology and emission with time. Strong morphological differences exist between ICCMB and -decay emission; at some stages, the TeV emission can be dominated by the former and the GeV by the latter, resulting in strong energy dependence of morphology. Integrated gamma-ray spectra show apparent power laws of slopes that vary with time, but do not indicate the energy distribution of a single population of particles. As observational capabilities at GeV and TeV energies improve, spatial inhomogeneity in SNRs will need to be accounted for.
UV-IR mixing in nonassociative Snyder ϕ^4 theory

Using a quantization of the nonassociative and noncommutative Snyder ϕ4 scalar field theory in a Hermitian realization, we present in this article analytical formulas for the momentum-conserving part of the one-loop two-point function of this theory in D-, 4-, and 3-dimensional Euclidean spaces, which are exact with respect to the noncommutative deformation parameter β. We prove that these integrals are regularized by the Snyder deformation. These results indicate that the Snyder deformation does partially regularize the UV divergences of the undeformed theory, as it was proposed decades ago. Furthermore, it is observed that different nonassociative ϕ4 products can generate different momentum-conserving integrals. Finally, most importantly, a logarithmic infrared divergence emerges in one of these interaction terms. We then analyze sample momentum nonconserving integral qualitatively and show that it could exhibit IR divergence too. Therefore, infrared divergences should exist, in general, in the Snyder ϕ4 theory. We consider infrared divergences at the limit p→0 as UV/IR mixings induced by nonassociativity, since they are associated to the matching UV divergence in the zero-momentum limit and appear in specific types of nonassociative ϕ4 products. We also discuss the extrapolation of the Snyder deformation parameter β to negative values as well as certain general properties of one-loop quantum corrections in Snyder ϕ4 theory at the zero-momentum limit.
Effects of ordering degree on the dielectric and ferroelectric behaviors of relaxor ferroelectric Pb(Sc1/2Nb1/2)O3 ceramics

Relaxor ferroelectric Pb(Sc0.5Nb0.5)O3 ceramics were synthesized by a modified solid oxide reaction method. The x-ray diffraction and Raman scattering analysis affirmed that annealing dominated the ordering degree of PSN samples. The measurements on dielectric response and ferroelectric behavior indicate the prominent impact of the ordering degree. The dielectric response of a relaxor ferroelectric is determined by the growing and freezing behaviors of the polar regions, which is correlated with the ordering degree. In addition, the behavior of the ferroelectric phase transition was controlled by the lattice distortion in ordered domain due to the displacement of Pb and ferroelectrically active Nb cations in the PSN lattice.
Evaluation of FASTEM and FASTEM2

A feed through circuit for an integrated circuit, including a first I/O pad (39); an input buffer (37) having an input connected to the first I/O pad and having an output; a second I/O pad (19); and an output buffer (15) having an input that is connected to the output of the input buffer and not connected to core logic circuitry of the integrated circuit, and further having an output that is connected to the second I/O pad; whereby a signal on the first I/O pad is fed through to the second I/O pad. Also disclosed is a feed through circuit that includes a first I/O pad (29); an input buffer (27) having an input that is connected to the first I/O pad and an output that is not connected to core logic circuitry of the integrated circuit; a multiplexer (21) having first and second inputs and an output, the first input being connected to the core logic circuitry and the second input being connected to the output of the input buffer; a second I/O pad (39); and an output buffer (35) having an input connected to the output of the multiplexer and an output connected to the first I/O pad; whereby a signal on the first I/O pad is fed through to the second I/O pad.
Bulk locality and asymptotic causal diamonds

In AdS/CFT, the non-uniqueness of the reconstructed bulk from boundary subregions has motivated the notion of code subspaces. We present some closely related structures that arise in flat space. A useful organizing idea is that of an asymptotic causal diamond (ACD): a causal diamond attached to the conformal boundary of Minkowski space. The space of ACDs is defined by pairs of points, one each on the future and past null boundaries, I^{\pm}I±. We observe that for flat space with an IR cut-off, this space (a) encodes a preferred class of boundary subregions, (b) is a plausible way to capture holographic data for local bulk reconstruction, (c) has a natural interpretation as the kinematic space for holography, (d) leads to a holographic entanglement entropy in flat space that matches previous definitions and satisfies strong sub-additivity, and, (e) has a bulk union/intersection structure isomorphic to the one that motivated the introduction of quantum error correction in AdS/CFT. By sliding the cut-off, we also note one substantive way in which flat space holography differs from that in AdS. Even though our discussion is centered around flat space (and AdS), we note that there are notions of ACDs in other spacetimes as well. They could provide a covariant way to abstractly characterize tensor sub-factors of Hilbert spaces of holographic theories.
Effects of Mass-Loading Variations and Applied Moments on Motion and Control of a Manned Rotating Space Vehicle

An analytical study has been made to determine the effects of mass-loading variations and onboard rotating machinery on a hypothetical earth-satellite space station, rotating to provide an artificial gravity equal to one-fourth of that at the earth's surface. Attempts were also made to damp out or minimize undesirable motions by using mass shifts, constant-rate inertia wheels, or jet-reaction moments. Results obtained indicate that the shifting of masses within the rotating space station could bring about large roll oscillations (plus or minus 100 degrees) or even continuous rolling motions if the craft is rotating about the axis of intermediate moment of inertia. The pitch angles obtained were generally small (less than plus or minus 1 degree). The amplitudes of the roll and pitch oscillations are dependent upon the angle of displacement of the greatest principal axis of inertia from the initial spin axis. In attempting to damp out or minimize undesirable motions, it was found that a constant-rate inertia wheel located on and rotating about the axis about which the craft is rotating (Z-axis) was beneficial in keeping the roll angles relatively small, provided it had a sufficient amount of angular momentum. It was also found that the use of jet-reaction moments was very satisfactory for damping undesirable motions in that the roll oscillations could be damped.
The Korean 1592-1593 Record of a Guest Star: An 'Impostor' of the Cassiopeia A Supernova?

The missing historical record of the Cassiopeia A (Cas A) supernova (SN) event implies a large extinction to the SN, possibly greater than the interstellar extinction to the current SN remnant. Here we investigate the possibility that the guest star that appeared near Cas A in 1592{1593 in Korean history books could have been an `impostor" of the Cas A SN, i.e., a luminous transient that appeared to be a SN but did not destroy the progenitor star, with strong mass loss to have provided extra circumstellar extinction. We first review the Korean records and show that a spatial coincidence between the guest star and Cas A cannot be ruled out, as opposed to previous studies. Based on modern astrophysical findings on core-collapse SN, we argue that Cas A could have had an impostor and derive its anticipated properties. It turned out that the Cas A SN impostor must have been bright (M V = -14.7 ± 2:2 mag) and an amount of dust with visual extinction of ≥ 2.8 ± 2:2 mag should have formed in the ejected envelope and/or in a strong wind afterwards. The mass loss needs to have been spherically asymmetric in order to see the light echo from the SN event but not the one from the impostor event.
Limits on the variation of fundamental atomic quantities over cosmic time scales. [Products of. cap

The detection of Mg II fine structure and hydrogen hyperfine absorption lines toward the radio source AO 0235+164 allows us to place upper limits on the variability of three products of the fine-structure constant, the nuclear g factor of the proton, and the ratio of electron to proton mass, viz. . cap alpha. /sup 2/g/subp/m/M, g/subp/m/M, and . cap alpha. Since the spectral lines are observed at a high red shift, z=0.5, the limits obtained on the variation with time of these quantities (adopting z as a measure of the Hubble expansion) apply over at least 35% of the age of the universe. (AIP)
Analysis of Discontinuities in a Rectangular Waveguide Using Dyadic Green''s Function Approach in Conjunction With Method of Moments

The dyadic Green''s function for an electric current source placed in a rectangular waveguide is derived using a magnetic vector potential approach. A complete solution for the electric and magnetic fields including the source location is obtained by simple differentiation of the vector potential around the source location. The simple differentiation approach which gives electric and magnetic fields identical to an earlier derivation is overlooked by the earlier workers in the derivation of the dyadic Green''s function particularly around the source location. Numerical results obtained using the Green''s function approach are compared with the results obtained using the Finite Element Method (FEM).
Ab initio
 electronic stationary states for nuclear projectiles in solids

The process by which a nuclear projectile is decelerated by the electrons of the condensed matter it traverses is currently being studied by following the explicit dynamics of projectile and electrons from ﬁrst principles in a simulation box with a sample of the host matter in periodic boundary conditions. The approach has been quite successful for diverse systems even in the strong-coupling regime of maximal dissipation. This technique is here revisited for periodic solids in the light of the Floquet theory of stopping, a time-periodic scattering framework characterizing the stationary dynamical solutions for a constant velocity projectile in an inﬁnite solid. The eﬀect of proton projectiles in diamond is studied under that light, using time-dependent density-functional theory in real time. The Floquet quasi-energy conserving stationary scattering regime, characterized by time-periodic properties such as particle density and the time derivative of energy, is obtained for a converged system size of one thousand atoms. The validity of the customary calculation of electronic stopping power from the average slope of the density-functional total energy is discussed. Quasi-energy conservation, as well as the implied fundamental approximations, are critically reviewed.
On the Benefit of Dual-Domain Denoising in a Self-Supervised Low-Dose CT Setting

Computed tomography (CT) is routinely used for three-dimensional non-invasive imaging. Numerous data-driven image denoising algorithms were proposed to restore image quality in low-dose acquisitions. However, considerably less research investigates methods already intervening in the raw detector data due to limited access to suitable projection data or correct reconstruction algorithms. In this work, we present an end-to-end trainable CT reconstruction pipeline that contains denoising operators in both the projection and the image domain and that are optimized simultaneously without requiring ground-truth high-dose CT data. Our experiments demonstrate that including an additional projection denoising operator improved the overall denoising performance by 82.4–94.1 %/12.5–41.7 % (PSNR/SSIM) on abdomen CT and 1.5–2.9 %/0.4–0.5 % (PSNR/SSIM) on XRM data relative to the low-dose baseline. We make our entire helical CT reconstruction framework publicly available that contains a raw projection rebinning step to render helical projection data suitable for differentiable fan-beam reconstruction operators and end-to-end learning.
CarDD: A New Dataset for Vision-Based Car Damage Detection

Automatic car damage detection has attracted significant attention in the car insurance business. However, due to the lack of high-quality and publicly available datasets, we can hardly learn a feasible model for car damage detection. To this end, we contribute with Car Damage Detection (CarDD), the first public large-scale dataset designed for vision-based car damage detection and segmentation. Our CarDD contains 4,000 high-resolution car damage images with over 9,000 well-annotated instances of six damage categories. We detail the image collection, selection, and annotation processes, and present a statistical dataset analysis. Furthermore, we conduct extensive experiments on CarDD with state-of-the-art deep methods for different tasks and provide comprehensive analyses to highlight the specialty of car damage detection. CarDD dataset and the source code are available at https://cardd-ustc.github. io.
BUbble Flow Field: a Simulation Framework for Evaluating Ultrasound Localization Microscopy Algorithms

Ultrasound contrast enhanced imaging has seen widespread uptake in research and clinical diagnostic imaging. This includes applications such as vector flow imaging, functional ultrasound and super-resolution Ultrasound Localization Microscopy (ULM). All of these require testing and validation during development of new algorithms with ground truth data. In this work we present a comprehensive simulation platform BUbble Flow Field (BUFF) that generates contrast enhanced ultrasound images in vascular tree geometries with realistic flow characteristics and validation algorithms for ULM. BUFF allows complex micro-vascular network generation of random and user-defined vascular networks. Blood flow is simulated with a fast Computational Fluid Dynamics (CFD) solver and allows arbitrary input and output positions and custom pressures. The acoustic field simulation is combined with non-linear Microbubble (MB) dynamics and simulates a range of point spread functions based on user-defined MB characteristics. The validation combines both binary and quantitative metrics. BFF's capacity to generate and validate user-defined networks is demonstrated through its implementation in the Ultrasound Localisation and TRacking Algorithms for Super Resolution (ULTRA-SR) Challenge at the International Ultrasonics Symposium (IUS) 2022 of the Institute of Electrical and Electronics Engineers (IEEE). The ability to produce ULM images, and the availability of a ground truth in localisation and tracking enables objective and quantitative evaluation of the large number of localisation and tracking algorithms developed in the field. BUFF can also benefit deep learning based methods by automatically generating datasets for training. BUFF is a fully comprehensive simulation platform for testing and validation of novel ULM techniques and is open source.
Bipartite Mixed Membership Distribution-Free Model. A novel model for community detection in overlapping bipartite weighted networks

Modeling and estimating mixed memberships for overlapping unipartite un-weighted networks has been well studied in recent years. However, to our knowledge, there is no model for a more general case, the overlapping bipartite weighted networks. To close this gap, we introduce a novel model, the Bipartite Mixed Membership Distribution-Free (BiMMDF) model. Our model allows an adjacency matrix to follow any distribution as long as its expectation has a block structure related to node membership. In particular, BiMMDF can model overlapping bipartite signed networks and it is an extension of many previous models, including the popular mixed membership stochastic blcokmodels. An efficient algorithm with a theoretical guarantee of consistent estimation is applied to fit BiMMDF. We then obtain the separation conditions of BiMMDF for different distributions. Furthermore, we also consider missing edges for sparse networks. The advantage of BiMMDF is demonstrated in extensive synthetic networks and eight real-world networks.
The nature of the brightest galactic center He I emission line star

We present near-infrared spectroscopy and unified atmosphere/wind models of the brightest He I 2.058 μm emission line star (hereafter denoted AF) in the Galactic center. The near-infrared spectrum of this star exhibits broad emission lines of He I and H, with the strongest line at 2.058 μm showing shallow P-Cygni absorption, strengthening the stellar wind interpretation for the origin of the lines. None of the higher excitation lines typical of classical Wolf-Rayet stars are detected. From the atmosphere models we conclude that the star is undergoing extensive mass loss (M˙∼6 to 10×10 −5 M ○. yr −1 ), has a luminosity of 2 to 3 10 5 L ○. , a moderate end velocity (V∞∼700 km s −1 ) and a strongly enhanced helium abundance (N He /N H >.5)
Deep Reinforcement Learning for Power Control in Next-Generation WiFi Network Systems

This paper presents a deep reinforcement learning (DRL) solution for power control in wireless communications, describes its embedded implementation with WiFi transceivers for a WiFi network system, and evaluates the performance with high-fidelity emulation tests. In a multi-hop wireless network, each mobile node measures its link quality and signal strength, and controls its transmit power. As a model-free solution, reinforcement learning allows nodes to adapt their actions by observing the states and maximize their cumulative rewards over time. For each node, the state consists of transmit power, link quality and signal strength; the action adjusts the transmit power; and the reward combines energy efficiency (throughput normalized by energy consumption) and penalty of changing the transmit power. As the state space is large, Q-learning is hard to implement on embedded platforms with limited memory and processing power. By approximating the Q-values with a deep Q-network (DQN), DRL is implemented for the embedded platform of each node combining an ARM processor and a WiFi transceiver for 802.11n. Controllable and repeatable emulation tests are performed by inducing realistic channel effects on RF signals. Performance comparison with benchmark schemes of fixed and myopic power allocations shows that power control with DRL provides major improvements to energy efficiency and throughput in WiFi network systems.
Dominance of Smartphone Exposure in 5G Mobile Networks

The deployment of 5G networks is sometimes questioned due to the impact of ElectroMagnetic Field (EMF) generated by Radio Base Station (RBS) on users. The goal of this work is to analyze such issue from a novel perspective, by comparing RBS EMF against exposure generated by 5G smartphones in commercial deployments. The measurement of exposure from 5G is hampered by several implementation aspects, such as dual connectivity between 4G and 5G, spectrum fragmentation, and carrier aggregation. To face such issues, we deploy a novel framework, called 5G-EA, tailored to the assessment of smartphone and RBS exposure through an innovative measurement algorithm, able to remotely control a programmable spectrum analyzer. Results, obtained in both outdoor and indoor locations, reveal that smartphone exposure (upon generation of uplink traffic) dominates over the RBS one. Moreover, Line-of-Sight locations experience a reduction of around one order of magnitude on the overall exposure compared to Non-Line-of-Sight ones. In addition, 5G exposure always represents a small share (up to 38%) compared to the total one radiated by the smartphone.
Instrumental Processes Using Integrated Covariances

Instrumental variable methods are often used for parameter estimation in the presence of confounding. They can also be applied in stochastic processes. Instrumental variable analysis exploits moment equations to obtain estimators for causal parameters. We show that in stochastic processes one can find such moment equations using an integrated covariance matrix. This provides new instrumental variable methods, instrumental variable methods in a class of continuous-time processes as well as a unified treatment of discrete- and continuous-time processes.
Two-Stream Network for Sign Language Recognition and Translation

Sign languages are visual languages using manual articulations and non-manual elements to convey information. For sign language recognition and translation, the majority of existing approaches directly encode RGB videos into hidden representations. RGB videos, however, are raw signals with substantial visual redundancy, leading the encoder to overlook the key information for sign language understanding. To mitigate this problem and better incorporate domain knowledge, such as handshape and body movement, we introduce a dual visual encoder containing two separate streams to model both the raw videos and the keypoint sequences generated by an off-the-shelf keypoint estimator. To make the two streams interact with each other, we explore a variety of techniques, including bidirectional lateral connection, sign pyramid network with auxiliary supervision, and frame-level self-distillation. The resulting model is called TwoStream-SLR, which is competent for sign language recognition (SLR). TwoStream-SLR is extended to a sign language translation (SLT) model, TwoStream-SLT, by simply attaching an extra translation network. Experimentally, our TwoStream-SLR and TwoStream-SLT achieve state-of-the-art performance on SLR and SLT tasks across a series of datasets including Phoenix-2014, Phoenix-2014T, and CSL-Daily. Code and models are available at: https://github.com/FangyunWei/SLRT.
IVOA Recommendation: HiPS - Hierarchical Progressive Survey

This document presents HiPS, a hierarchical scheme for the description, storage and access of sky survey data. The system is based on hierarchical tiling of sky regions at finer and finer spatial resolution which facilitates a progressive view of a survey, and supports multi-resolution zooming and panning. HiPS uses the HEALPix tessellation of the sky as the basis for the scheme and is implemented as a simple file structure with a direct indexing scheme that leads to practical implementations.