arXiv subjects

Hui Li

Publications and source records attributed to Hui Li.

At least 667 records · Page 37Linked to original sources

arXiv2020

Quantifying socioeconomic activities and weather effects on the global spread of COVID-19 epidemic

The COVID-19 has caused more than three million infections and over two hundred thousand deaths by April 20201. Limiting socioeconomic activities (SA) is among the most adopted governmental mitigating efforts to combat the transmission of the virus, though the degree varies dramatically among different regimes2. This study aims to quantify the contribution from the SA and weather conditions to the transmission of COVID-19 at global scale. Ruling out the unobservable factors including medical facilities and other control policies (MOC) through region-by-time fixed effects3,4, we show that the limiting SA has a leading contribution to lower the reproductive number by 18.3%, while weather conditions, including ultraviolet, relative humidity, and wind explain a smaller amount of variation. Temperature might have a non-monotonic impact on the transmission. We further show that in developed countries5 and China, the SA effect is more pronounced whereas the weather effect is significantly downplayed possibly because people tend to stay indoors most of the time with a controlled climate. We finally estimate the reduced reproductive number and the population spared from infections due to restricting SA at 40,964, 180,336, 174,494, in China, United States, and Europe respectively. From late January to mid-April, all regions, except for China, Australia, and south Korea show a steep upward trend of spared infections due to restricting SA. US and Europe, in particular, show far steeper upward trends of spared infections in the analyzed timeframe, signaling a greater risk of reopening the economy too soon.

q-bio.PE↗

arXiv2020

Photon-mediated charge-exchange reactions between 39K atoms and 40Ca+ ions in a hybrid trap

We present experimental evidence of charge exchange between laser-cooled potassium $^{39}$K atoms and calcium $^{40}$Ca$^+$ ions in a hybrid atom-ion trap and give quantitative theoretical explanations for the observations. The $^{39}$K atoms and $^{40}$Ca$^+$ ions are held in a magneto-optical (MOT) and a linear Paul trap, respectively. Fluorescence detection and high resolution time of flight mass spectra for both species are used to determine the remaining number of $^{40}$Ca$^+$ ions, the increasing number of $^{39}$K$^+$ ions, and $^{39}$K number density as functions of time. Simultaneous trap operation is guaranteed by alternating periods of MOT and $^{40}$Ca$^+$ cooling lights, thus avoiding direct ionization of $^{39}$K by the $^{40}$Ca$^+$ cooling light. We show that the K-Ca$^+$ charge-exchange rate coefficient increases linearly from zero with $^{39}$K number density and, surprisingly, the fraction of $^{40}$Ca$^+$ ions in the 4p\,$^2$P$_{1/2}$ electronically-excited state. Combined with our theoretical analysis, we conclude that these data can only be explained by a process that starts with a potassium atom in its electronic ground state and a calcium ion in its excited 4p\,$^2$P$_{1/2}$ state producing ground-state $^{39}$K$^+$ ions and metastable, neutral Ca\,(3d4p$^3$P$_1$) atoms, releasing only 150 cm$^{-1}$ equivalent relative kinetic energy. Charge-exchange between either ground- or excited-state $^{39}$K and ground-state $^{40}$Ca$^+$ is negligibly small as no energetically-favorable product states are available. Our experimental and theoretical rate coefficients of $9\times10^{-10}$ cm$^3$/s are in agreement given the uncertainty budgets.

physics.atom-ph↗

arXiv2020

A Fast Radio Burst discovered in FAST drift scan survey

We report the discovery of a highly dispersed fast radio burst, FRB~181123, from an analysis of $\sim$1500~hr of drift-scan survey data taken using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). The pulse has three distinct emission components, which vary with frequency across our 1.0--1.5~GHz observing band. We measure the peak flux density to be $>0.065$~Jy and the corresponding fluence $>0.2$~Jy~ms. Based on the observed dispersion measure of 1812~cm$^{-3}$~pc, we infer a redshift of $\sim 1.9$. From this, we estimate the peak luminosity and isotropic energy to be $\lesssim 2\times10^{43}$~erg~s$^{-1}$ and $\lesssim 2\times10^{40}$~erg, respectively. With only one FRB from the survey detected so far, our constraints on the event rate are limited. We derive a 95\% confidence lower limit for the event rate of 900 FRBs per day for FRBs with fluences $>0.025$~Jy~ms. We performed follow-up observations of the source with FAST for four hours and have not found a repeated burst. We discuss the implications of this discovery for our understanding of the physical mechanisms of FRBs.

astro-ph.HE↗

arXiv2020

Longitudinal fluid response and pseudorapidity dependent flow in relativistic heavy-ion collisions

We study the pseudorapidity dependent hydrodynamic response in heavy-ion collisions. A differential hydrodynamic relation is obtained for elliptic flow. Using event-by-event simulations of 3+1D MUSIC, with initial conditions generated via a multi-phase transport (AMPT) model, the differential response relation is verified. Based on the response relation, we find that the two-point correlation of elliptic flow in pseudorapidity are separated into the fluid response and the two-point correlation of initial eccentricity.

nucl-th↗

arXiv2020

Underwater image enhancement with Image Colorfulness Measure

Due to the absorption and scattering effects of the water, underwater images tend to suffer from many severe problems, such as low contrast, grayed out colors and blurring content. To improve the visual quality of underwater images, we proposed a novel enhancement model, which is a trainable end-to-end neural model. Two parts constitute the overall model. The first one is a non-parameter layer for the preliminary color correction, then the second part is consisted of parametric layers for a self-adaptive refinement, namely the channel-wise linear shift. For better details, contrast and colorfulness, this enhancement network is jointly optimized by the pixel-level and characteristiclevel training criteria. Through extensive experiments on natural underwater scenes, we show that the proposed method can get high quality enhancement results.

cs.CV↗

arXiv2020

Time-step dependent force interpolation scheme for suppressing numerical Cherenkov instability in relativistic particle-in-cell simulations

The WT scheme, a piecewise polynomial force interpolation scheme with time-step dependency, is proposed in this paper for relativistic particle-in-cell (PIC) simulations. The WT scheme removes the lowest order numerical Cherenkov instability (NCI) growth rate for arbitrary time steps allowed by the Courant condition. While NCI from higher order resonances is still present, the numerical tests show that for smaller time steps, the numerical instability grows much slower than using the optimal time step found in previous studies. The WT scheme is efficient for improving the quality and flexibility of relativistic PIC simulations.

physics.comp-ph↗

arXiv2020

Smart Prediction of the Complaint Hotspot Problem in Mobile Network

In mobile network, a complaint hotspot problem often affects even thousands of users' service and leads to significant economic losses and bulk complaints. In this paper, we propose an approach to predict a customer complaint based on real-time user signalling data. Through analyzing the network and user sevice procedure, 30 key data fields related to user experience have been extracted in XDR data collected from the S1 interface. Furthermore, we augment these basic features with derived features for user experience evaluation, such as one-hot features, statistical features and differential features. Considering the problems of unbalanced data, we use LightGBM as our prediction model. LightGBM has strong generalization ability and was designed to handle unbalanced data. Experiments we conducted prove the effectiveness and efficiency of this proposal. This approach has been deployed for daily routine to locate the hot complaint problem scope as well as to report affected users and area.

cs.NI↗

arXiv2020

Studying particle acceleration from driven magnetic reconnection at the termination shock of a relativistic striped wind using particle-in-cell simulations

A rotating pulsar creates a surrounding pulsar wind nebula (PWN) by steadily releasing an energetic wind into the interior of the expanding shockwave of supernova remnant or interstellar medium. At the termination shock of a PWN, the Poynting-flux-dominated relativistic striped wind is compressed. Magnetic reconnection is driven by the compression and converts magnetic energy into particle kinetic energy and accelerating particles to high energies. We carrying out particle-in-cell (PIC) simulations to study the shock structure as well as the energy conversion and particle acceleration mechanism. By analyzing particle trajectories, we find that many particles are accelerated by Fermi-type mechanism. The maximum energy for electrons and positrons can reach hundreds of TeV.

physics.plasm-ph↗

arXiv2020

MDLatLRR: A novel decomposition method for infrared and visible image fusion

Image decomposition is crucial for many image processing tasks, as it allows to extract salient features from source images. A good image decomposition method could lead to a better performance, especially in image fusion tasks. We propose a multi-level image decomposition method based on latent low-rank representation(LatLRR), which is called MDLatLRR. This decomposition method is applicable to many image processing fields. In this paper, we focus on the image fusion task. We develop a novel image fusion framework based on MDLatLRR, which is used to decompose source images into detail parts(salient features) and base parts. A nuclear-norm based fusion strategy is used to fuse the detail parts, and the base parts are fused by an averaging strategy. Compared with other state-of-the-art fusion methods, the proposed algorithm exhibits better fusion performance in both subjective and objective evaluation.

cs.CV↗

arXiv2020

Remarks On the K-theory of C*-Algebras of Products of Odometers

We pose a conjecture on the K-theory of the self-similar $k$-graph C*-algebra of a standard product of odometers. We generalize the C*-algebra $\mathcal{Q}_S$ to any subset of $\mathbb{N}^\times \setminus \{1\}$ and then realize it as the self-similar $k$-graph C*-algebra of a standard product of odometers.

math.OA↗

arXiv2020

Planet-induced Vortices with Dust Coagulation in Protoplanetary Disks

In this work, we study how the dust coagulation/fragmentation will influence the evolution and observational appearances of vortices induced by a massive planet embedded in a low viscosity disk by performing global 2D high-resolution hydrodynamical simulations. Within the vortex, due to its higher gas surface density and steeper pressure gradients, dust coagulation, fragmentation and drift (to the vortex center) are all quite efficient, producing dust particles ranging from micron to $\sim 1.0\ {\rm cm}$, as well as overall high dust-to-gas ratio (above unity). In addition, the dust size distribution is quite non-uniform inside the vortex, with the mass weighted average dust size at the vortex center ($\sim 4.0$ mm) being a factor of $\sim10$ larger than other vortex regions. Both large ($\sim$ mm) and small (tens of micron) particles contribute strongly to affect the gas motion within the vortex. As such, we find that the inclusion of dust coagulation has a significant impact on the vortex lifetime and the typical vortex lifetime is about 1000 orbits. After the initial gaseous vortex is destroyed, the dust spreads into a ring with a few remaining smaller gaseous vortices with a high dust concentration and a large maximum size ($\sim$ mm). At late time, the synthetic dust continuum images for the coagulation case show as a ring inlaid with several hot spots at 1.33 mm band, while only distinct hot spots remain at 7.0 mm.

astro-ph.EP↗

arXiv2020

NSFnets (Navier-Stokes Flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations

We employ physics-informed neural networks (PINNs) to simulate the incompressible flows ranging from laminar to turbulent flows. We perform PINN simulations by considering two different formulations of the Navier-Stokes equations: the velocity-pressure (VP) formulation and the vorticity-velocity (VV) formulation. We refer to these specific PINNs for the Navier-Stokes flow nets as NSFnets. Analytical solutions and direct numerical simulation (DNS) databases provide proper initial and boundary conditions for the NSFnet simulations. The spatial and temporal coordinates are the inputs of the NSFnets, while the instantaneous velocity and pressure fields are the outputs for the VP-NSFnet, and the instantaneous velocity and vorticity fields are the outputs for the VV-NSFnet. These two different forms of the Navier-Stokes equations together with the initial and boundary conditions are embedded into the loss function of the PINNs. No data is provided for the pressure to the VP-NSFnet, which is a hidden state and is obtained via the incompressibility constraint without splitting the equations. We obtain good accuracy of the NSFnet simulation results upon convergence of the loss function, verifying that NSFnets can effectively simulate complex incompressible flows using either the VP or the VV formulations. We also perform a systematic study on the weights used in the loss function for the data/physics components and investigate a new way of computing the weights dynamically to accelerate training and enhance accuracy. Our results suggest that the accuracy of NSFnets, for both laminar and turbulent flows, can be improved with proper tuning of weights (manual or dynamic) in the loss function.

physics.comp-ph↗

arXiv2020

Recovering compressed images for automatic crack segmentation using generative models

In a structural health monitoring (SHM) system that uses digital cameras to monitor cracks of structural surfaces, techniques for reliable and effective data compression are essential to ensure a stable and energy efficient crack images transmission in wireless devices, e.g., drones and robots with high definition cameras installed. Compressive sensing (CS) is a signal processing technique that allows accurate recovery of a signal from a sampling rate much smaller than the limitation of the Nyquist sampling theorem. The conventional CS method is based on the principle that, through a regularized optimization, the sparsity property of the original signals in some domain can be exploited to get the exact reconstruction with a high probability. However, the strong assumption of the signals being highly sparse in an invertible space is relatively hard for real crack images. In this paper, we present a new approach of CS that replaces the sparsity regularization with a generative model that is able to effectively capture a low dimension representation of targeted images. We develop a recovery framework for automatic crack segmentation of compressed crack images based on this new CS method and demonstrate the remarkable performance of the method taking advantage of the strong capability of generative models to capture the necessary features required in the crack segmentation task even the backgrounds of the generated images are not well reconstructed. The superior performance of our recovery framework is illustrated by comparing with three existing CS algorithms. Furthermore, we show that our framework is extensible to other common problems in automatic crack segmentation, such as defect recovery from motion blurring and occlusion.

eess.IV↗

arXiv2020

NuSTAR and Chandra Observation of the Galactic Center Non-thermal X-ray Filament G0.13-0.11: A Pulsar Wind Nebula Driven Magnetic Filament

One of the most unique phenomena in the Galactic center region is the existence of numerous long and narrow filamentary structures within a few hundred parsecs of Sgr A$^{\star}$. While more than one than one hundred radio filaments have been revealed by MeerKAT, about two dozens X-ray filaments have been discovered so far. In this article, we report our analysis on the deep Chandra and NuSTAR observations of a non-thermal X-ray filament, G0.13-0.11, which is located adjacent to the Radio arc. Chandra revealed a unique morphology of G0.13-0.11, which is an elongated (0.1 pc in width and 3.2 pc in length) structure slightly bended towards the Radio arc. A pulsar candidate ($Γ\sim 1.4$) is detected in the middle of the filament, with a tail of diffuse non-thermal X-ray emission on one side of the filament. The filament is detected by NuSTAR up to 79 keV, with the hard X-ray centroid consistent with the pulsar candidate. We found that the X-ray intensity decays along the filament farther away from the pulsar candidate, dropping to half of its peak value at 2.2 pc away. This system is mostly likely a Pulsar Wind Nebula interacting with ambient interstellar magnetic field, where the filaments are kinetic jets from PWN as recently proposed. The nature of this filament adds to complex origin of the X-ray filaments, which serve as powerful tools to probe local and global powerful particle accelerators in the Galactic center.

astro-ph.HE↗

arXiv2020

Magnitude and significance of the peak of early embryonic mortality

Biologically, for any organism life does not start at birth but at fertilization of the embryo. Embryonic development is of great importance because it determines congenital anomalies and influences their severity. Whereas there is detailed qualitative knowledge of the successive steps of embryonic development, little is known about their probabilities of success or failure. Embryonic mortality as a function of post fertilization time provides a simple (albeit crude) way to identify major defects. We find that, in line with the few other species for which data are available, the embryonic mortality of zebrafish has a prominent peak shortly after fertilization. This is called the early embryonic mortality (EEM) effect. Although a number of immediate causes of death (e.g. infection, excess of carbon dioxide or of lactic acid, chromosomal defects) can be cited, the common underlying factor remains unknown. After reviewing embryonic mortality data available for chicken and a few other farm animals, we explain that zebrafish are particularly suited for such a study because embryogenesis can be followed from its very beginning and can be observed easily thanks to transparent egg shells. We report the following findings. (i) The mortality peak occurs in the first 15% of the 75-80 hours of embryogenesis and it is about 50 times higher than the low plateau which follows. (ii) The shape of the age-specific death rate is largely independent of the death level. Presently, little is known about the nature of embryonic defects. However, by reviewing two special cases we show that even small initial defects, e.g. spatial cellular asymmetries or irregularities in the timing of development, carry with them lethal effects in later stages of embryogenesis.

q-bio.TO↗

arXiv2020

Dynamic Experience Replay

We present a novel technique called Dynamic Experience Replay (DER) that allows Reinforcement Learning (RL) algorithms to use experience replay samples not only from human demonstrations but also successful transitions generated by RL agents during training and therefore improve training efficiency. It can be combined with an arbitrary off-policy RL algorithm, such as DDPG or DQN, and their distributed versions. We build upon Ape-X DDPG and demonstrate our approach on robotic tight-fitting joint assembly tasks, based on force/torque and Cartesian pose observations. In particular, we run experiments on two different tasks: peg-in-hole and lap-joint. In each case, we compare different replay buffer structures and how DER affects them. Our ablation studies show that Dynamic Experience Replay is a crucial ingredient that either largely shortens the training time in these challenging environments or solves the tasks that the vanilla Ape-X DDPG cannot solve. We also show that our policies learned purely in simulation can be deployed successfully on the real robot. The video presenting our experiments is available at https://sites.google.com/site/dynamicexperiencereplay

cs.AI↗

arXiv2020

Quasi-periodic pulsation detected in Lyman-alpha emission during solar flares

We investigated the quasi-periodic pulsation (QPP) in Lyman-alpha, X-ray and extreme-ultraviolet (EUV) emissions during two solar flares, i.e., an X-class (SOL2012-01-27T) and a C-class (SOL2016-02-08T). The full-disk Lyman-alpha and X-Ray flux during these solar flares were recorded by the EUV Sensor and X-Ray Sensor on board the Geostationary Operational Environmental Satellite. The °are regions were located from the EUV images measured by the Atmospheric Imaging Assembly. The QPP could be identified as a series of regular and periodic peaks in the light curves, and its quasi-periodicity was determined from the global wavelet and Fourier power spectra. A quasi-periodicity at about 3 minutes is detected during the impulsive phase of the X-class flare, which could be explained as the acoustic wave in the chromosphere (e.g., Milligan et al. 2017). Interestingly, a quasi-periodicity at roughly 1 minute is discovered during the entire evolutionary phases of solar flares, including the precursor, impulsive, and gradual phases. This is the first report of 1-minute QPP in the Lyman-alpha emission during solar flares, in particular during the flare precursor. It may be interpreted as a self-oscillatory regime of the magnetic reconnection, such as magnetic dripping.

astro-ph.SR↗

arXiv2020

An Efficient Secure Dynamic Skyline Query Model

It is now cost-effective to outsource large dataset and perform query over the cloud. However, in this scenario, there exist serious security and privacy issues that sensitive information contained in the dataset can be leaked. The most effective way to address that is to encrypt the data before outsourcing. Nevertheless, it remains a grand challenge to process queries in ciphertext efficiently. In this work, we shall focus on solving one representative query task, namely dynamic skyline query, in a secure manner over the cloud. However, it is difficult to be performed on encrypted data as its dynamic domination criteria require both subtraction and comparison, which cannot be directly supported by a single encryption scheme efficiently. To this end, we present a novel framework called SCALE. It works by transforming traditional dynamic skyline domination into pure comparisons. The whole process can be completed in single-round interaction between user and the cloud. We theoretically prove that the outsourced database, query requests, and returned results are all kept secret under our model. Moreover, we also present an efficient strategy for dynamic insertion and deletion of stored records. Empirical study over a series of datasets demonstrates that our framework improves the efficiency of query processing by nearly three orders of magnitude compared to the state-of-the-art.

cs.DB↗