arXiv subjects

Jun Chen

Publications and source records attributed to Jun Chen.

At least 379 records · Page 21Linked to original sources

arXiv2020

APB2FaceV2: Real-Time Audio-Guided Multi-Face Reenactment

Audio-guided face reenactment aims to generate a photorealistic face that has matched facial expression with the input audio. However, current methods can only reenact a special person once the model is trained or need extra operations such as 3D rendering and image post-fusion on the premise of generating vivid faces. To solve the above challenge, we propose a novel \emph{R}eal-time \emph{A}udio-guided \emph{M}ulti-face reenactment approach named \emph{APB2FaceV2}, which can reenact different target faces among multiple persons with corresponding reference face and drive audio signal as inputs. Enabling the model to be trained end-to-end and have a faster speed, we design a novel module named Adaptive Convolution (AdaConv) to infuse audio information into the network, as well as adopt a lightweight network as our backbone so that the network can run in real time on CPU and GPU. Comparison experiments prove the superiority of our approach than existing state-of-the-art methods, and further experiments demonstrate that our method is efficient and flexible for practical applications https://github.com/zhangzjn/APB2FaceV2

cs.CV↗

arXiv2020

Ferroelectricity and ferromagnetism in VOI$_2$ monolayer: the role of Dzyaloshinskii-Moriya interaction

Multiferroics with intrinsic ferromagnetism and ferroelectricity are highly desired but rather rare, while most ferroelectric magnets are antiferromagnetic. A recent theoretical work [Phys. Rev. B {\bf 99}, 195434 (2019)] predicted that oxyhalides VO$X_2$ ($X$: halogen) monolayers are two-dimensional multiferroics by violating the empirical $d^0$ rule. Most interestingly, the member VOI$_2$ are predicted to exhibit spontaneous ferromagnetism and ferroelectricity. In this work, we extend the previous study on the structure and magnetism of VOI$_2$ monolayer by using density functional theory and Monte Carlo simulation. The presence of the heavy element iodine with a strong spin-orbit coupling leads an effective Dzyaloshinskii-Moriya interaction in the polar structure, which favors a short-period spiral a magnetic structure.. Another interesting result is that the on-site Coulomb interaction can strongly suppress the polar distortion thus leading to a ferromagnetic metallic state. Therefore, the VOI2 monolayer is either a ferroelectric insulator with spiral magnetism or a ferromagnetic metal, instead of a ferromagnetic ferroelectric system. Our study highlights the key physical role of the Dzyaloshinskii-Moriya interaction.

cond-mat.mtrl-sci↗

arXiv2020

Temporal Positive-unlabeled Learning for Biomedical Hypothesis Generation via Risk Estimation

Understanding the relationships between biomedical terms like viruses, drugs, and symptoms is essential in the fight against diseases. Many attempts have been made to introduce the use of machine learning to the scientific process of hypothesis generation(HG), which refers to the discovery of meaningful implicit connections between biomedical terms. However, most existing methods fail to truly capture the temporal dynamics of scientific term relations and also assume unobserved connections to be irrelevant (i.e., in a positive-negative (PN) learning setting). To break these limits, we formulate this HG problem as future connectivity prediction task on a dynamic attributed graph via positive-unlabeled (PU) learning. Then, the key is to capture the temporal evolution of node pair (term pair) relations from just the positive and unlabeled data. We propose a variational inference model to estimate the positive prior, and incorporate it in the learning of node pair embeddings, which are then used for link prediction. Experiment results on real-world biomedical term relationship datasets and case study analyses on a COVID-19 dataset validate the effectiveness of the proposed model.

cs.LG↗

arXiv2020

Prediction of two-dimensional ferromagnetic ferroelectric VOF$_2$ monolayer

Nowadays, designing and searching for materials with multiple functional characteristics are the key to achieving high-performance electronic devices. Among many candidates, two-dimensional multiferroic materials have great potential to be applied in highly-integrated magnetoelectric devices, such as high-density non-volatile memories. Here, we predict a two-dimensional material VOF2 monolayer to possess intrinsic ferroelectric and ferromagnetic properties. The VOF$_2$ monolayer own the largest in-plane ferroelectric polarization ($332$ pC/m) in the family of VO$X_2$ ($X$: halogen) oxyhalides. Different from other VO$X_2$ monolayers whose magnetic ground states are antiferromagnetic or noncollinear spiral textures, the VOF$_2$ monolayer owns a robust ferromagnetic ground state, which is rare but highly desirable. Our theoretical prediction provides a good candidate and starting point for the further pursuit of more two-dimensional multiferroic materials with high-performance magnetoelectricity.

cond-mat.mtrl-sci↗

arXiv2020

AWNet: Attentive Wavelet Network for Image ISP

As the revolutionary improvement being made on the performance of smartphones over the last decade, mobile photography becomes one of the most common practices among the majority of smartphone users. However, due to the limited size of camera sensors on phone, the photographed image is still visually distinct to the one taken by the digital single-lens reflex (DSLR) camera. To narrow this performance gap, one is to redesign the camera image signal processor (ISP) to improve the image quality. Owing to the rapid rise of deep learning, recent works resort to the deep convolutional neural network (CNN) to develop a sophisticated data-driven ISP that directly maps the phone-captured image to the DSLR-captured one. In this paper, we introduce a novel network that utilizes the attention mechanism and wavelet transform, dubbed AWNet, to tackle this learnable image ISP problem. By adding the wavelet transform, our proposed method enables us to restore favorable image details from RAW information and achieve a larger receptive field while remaining high efficiency in terms of computational cost. The global context block is adopted in our method to learn the non-local color mapping for the generation of appealing RGB images. More importantly, this block alleviates the influence of image misalignment occurred on the provided dataset. Experimental results indicate the advances of our design in both qualitative and quantitative measurements. The code is available publically.

eess.IV↗

arXiv2020

Exploring the potentiality of standard sirens to probe cosmic opacity at high redshifts

In this work, using the Gaussian process, we explore the potentiality of future gravitational wave (GW) measurements to probe cosmic opacity at high redshifts through comparing its opacity-free luminosity distance (LD) with the opacity-dependent one from the combination of Type Ia supernovae (SNIa) and gamma-ray bursts (GRBs). The GW data, SNIa and GRB data are simulated from the measurements of the future Einstein Telescope, the actual Pantheon compilation and the latest observation of GRBs compiled by L. Amati {\it et al}, respectively. A nonparametric method is proposed to probe the spatial homogeneity of cosmic transparency at high redshift by comparing the LD reconstructed from the GW data with that reconstructed from the Pantheon and GRB data. In addition, the cosmic opacity is tested by using the parametrization for the optical depth, and the results show that the constraints on cosmic opacity are more stringent than the previous ones. It shows that the future GW measurements may be used as an important tool to probe the cosmic opacity in the high redshift region.

astro-ph.CO↗

arXiv2020

Nanoscale control of LaAlO3/SrTiO3 metal-insulator transition using ultra-low-voltage electron-beam lithography

We describe a method to control the insulator-metal transition at the LaAlO3/SrTiO3 interface using ultra-low-voltage electron beam lithography (ULV-EBL). Compared with previous reports that utilize conductive atomic-force-microscope lithography (c-AFM), this approach can provide comparable resolution (~10 nm) at write speeds (10 mm/s) that are up to 10,000x faster than c-AFM. The writing technique is non-destructive and the conductive state is reversible via prolonged exposure to air. Transport properties of representative devices are measured at milli-Kelvin temperatures, where superconducting behavior is observed. We also demonstrate the ability to create conducting devices on graphene/LaAlO3/SrTiO3 heterostructures. The underlying mechanism is believed to be closely related to the same mechanism regulating c-AFM-based methods.

cond-mat.mes-hall↗

arXiv2020

Subsonic flows past a profile with a vortex line at the trailing edge

We established the existence, uniqueness and stability of subsonic flows past an airfoil with a vortex line at the trailing edge. Such a flow pattern is governed by the two dimensional steady compressible Euler equations. The vortex line attached to the trailing edge is a contact discontinuity for the Euler system and is treated as a free boundary. The problem is formulated and solved by using the implicit function theorem. The main difficulties are due to the fitting of the vortex line with the profile at the trailing edge and the possible subtle instability of the vortex line at the far field. Suitable choices of the weights and elaborate barrier functions are found to deal with such difficulties.

math.AP↗

arXiv2020

Population dynamics of Varroa mite and honeybee: Effects of parasitism with age structure and seasonality

Honeybees play an important role in the production of many agricultural crops and in sustaining plant diversity in undisturbed ecosystems. The rapid decline of honeybee populations have sparked great concern worldwide. Previous studies have shown that the parasitic Varroa mite could be the main reason for colony losses. In order to understand how mites affect population dynamics of honeybees and a colony health, we propose a brood-adult bee-mite model in which the time lag from brood to adult is taken into account. Noting that the dynamics of a honeybee colony varies with respect to season, we validate the model and perform parameter estimations under both constant and fluctuating seasonality scenarios. Our analytical and numerical studies reveal the following: (a) In the presence of parasite mites, the large time lag from brood to adult could destabilize population dynamics and drive the colony to collapse; but the small natural mortality of the adult population can promote a mite-free colony when time lag is small or at an intermediate level; (b) Small brood' infestation rates could stabilize all populations at the unique interior equilibrium under constant seasonality while may drive the mite population to die out when seasonality is taken into account; (c) High brood' infestation rates can destabilize the colony dynamics leading to population collapse depending on initial population size under constant and seasonal conditions; (d) Results from sensitivity analysis indicate the queen's egg-laying may have the greatest effect on colony population size. The brood death rate and the colony size at which brood survivability is the half maximal were also shown to be highly sensitive with an inverse correlation to the colony population size. Our results provide insights on the effects of seasonality on the dynamics.

q-bio.PE↗

arXiv2020

Controlling the helicity of magnetic skyrmions by electrical field in frustrated magnets

The skyrmions generated by frustration in centrosymmetric structures host extra internal degrees of freedom: vorticity and helicity, resulting in distinctive properties and potential functionality, which are not shared by the skyrmions stemming from the Dzyaloshinskii-Moriya interaction in noncentrosymmetric structures. The present work indicates that the magnetism-driven electric polarization carried by skyrmions provides a direct handle for tuning helicity. Especially for the in-plane magnetized skyrmions, the helicity can be continuously rotated and exactly picked by applying an external electric field for both skyrmions and antiskyrmions. The in-plane uniaxial anisotropy is beneficial to this manipulation.

cond-mat.mtrl-sci↗

arXiv2020

Potential Energy Landscape of CO Adsorbates on NaCl(100) and Implications in Isomerization of Vibrationally Excited CO

Several full-dimensional potential energy surfaces (PESs) are reported for vibrating CO adsorbates at two coverages on a rigid NaCl(100) surface based on first principles calculations. These PESs reveal a rather flat energy landscape for physisorption of vibrationless CO on NaCl(100), evidenced by various C-down adsorption patterns within a small energy range. Agreement with available experimental results is satisfactory, although quantitative differences exist. These PESs are used to explore isomerization pathways between the C-down and higher energy O-down configurations, which reveal a significant isomerization barrier. As CO vibration is excited, however, the energy order of the two isomer changes, which helps to explain the experimental observed flipping of vibrationally excited CO adsorbates.

physics.chem-ph↗

arXiv2020

Electric Currents through J-shaped and Non-J-shaped Flare Ribbons

Recently solar flares exhibiting a double J-shaped ribbons in the lower solar atmosphere have been paid increasing attention in the context of extending the two-dimensional standard flare model to three dimensions, as motivated by the spatial correlation between photospheric current channels and flare ribbons. Here we study the electric currents through the photospheric area swept by flare ribbons (termed synthesized ribbon area or SRA), with a sample of 71 two-ribbon flares, of which 36 are J-shaped. Electric currents flowing through one ribbon are highly correlated with those through the other, therefore belonging to the same current system. The non-neutrality factor of this current system is independent of the flare magnitude, implying that both direct and return currents participate in flares. J-shaped flares are distinct from non-J-shaped flares in the following aspects: 1) Electric current densities within J-shaped SRA are significantly smaller than those within non-J-shaped SRA, but J-shaped SRA and its associated magnetic flux are also significantly larger. 2) Electric currents through SRA are positively correlated with the flare magnitude, but J-shaped flares show stronger correlation than non-J-shaped flares. 3) The majority (75\%) of J-shaped flares are eruptive, while the majority (86\%) of non-J-shaped flares are confined; accordingly, hosting active regions of J-shaped flares are more likely to be sigmoidal than non-J-shaped flares. Thus, J-shaped flares constitute a distinct subset of two-ribbon flares, probably the representative of eruptive ones. Further, we found that combining SRA and its associated magnetic flux has the potential to differentiate eruptive from confined flares.

astro-ph.SR↗

arXiv2020

Covariate Adaptive False Discovery Rate Control with Applications to Omics-Wide Multiple Testing

Conventional multiple testing procedures often assume hypotheses for different features are exchangeable. However, in many scientific applications, additional covariate information regarding the patterns of signals and nulls are available. In this paper, we introduce an FDR control procedure in large-scale inference problem that can incorporate covariate information. We develop a fast algorithm to implement the proposed procedure and prove its asymptotic validity even when the underlying model is misspecified and the p-values are weakly dependent (e.g., strong mixing). Extensive simulations are conducted to study the finite sample performance of the proposed method and we demonstrate that the new approach improves over the state-of-the-art approaches by being flexible, robust, powerful and computationally efficient. We finally apply the method to several omics datasets arising from genomics studies with the aim to identify omics features associated with some clinical and biological phenotypes. We show that the method is overall the most powerful among competing methods, especially when the signal is sparse. The proposed Covariate Adaptive Multiple Testing procedure is implemented in the R package CAMT.

stat.ME↗

arXiv2020

Joint Optimization of Transfer Location and Capacity in a Multimodal Transport Network: Bilevel Modeling and Paradoxes

With the growing attention towards developing the multimodal transport system to enhance urban mobility, there is an increasing need to construct new, rebuild or expand existing infrastructure to facilitate existing and accommodate newly generated travel demand. Therefore, this paper develops a bilevel model to simultaneously determine the location and capacity of the transfer infrastructure to be built considering elastic demand in a multimodal transport network. The upper level problem is formulated as a mixed integer linear programming problem, while the lower level problem is the capacitated combined trip distribution assignment model that depicts both destination and route choices of travelers via the multinomial logit formula. To solve the model, the paper develops a matheuristics algorithm that integrates a Genetic Algorithm and a successive linear programming solution approach. Numerical studies are conducted to demonstrate the existence and examine two Braess like paradox phenomena in a multimodal transport network. The first one states that under fixed demand constructing parking spaces to stimulate the usage of Park and Ride service could deteriorate the system performance, measured by the total passengers travel time, while the second one reveals that under variable demand increasing the parking capacity for the Park and Ride services to promote the usages may fail, represented by the decline in its modal share. Meanwhile, the last experiment suggests that constructing transfer infrastructures at distributed stations outperforms building a large transfer center in terms of attracting travelers using sustainable transit modes.

math.OC↗

arXiv2020

NTIRE 2020 Challenge on Image Demoireing: Methods and Results

This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demoireing is a difficult task of removing moire patterns from an image to reveal an underlying clean image. The challenge was divided into two tracks. Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image. Track 2 focused on the burst demoireing problem, where a set of degraded moire images of the same scene were provided as input, with the goal of producing a single demoired image as output. The methods were ranked in terms of their fidelity, measured using the peak signal-to-noise ratio (PSNR) between the ground truth clean images and the restored images produced by the participants' methods. The tracks had 142 and 99 registered participants, respectively, with a total of 14 and 6 submissions in the final testing stage. The entries span the current state-of-the-art in image and burst image demoireing problems.

cs.CV↗

arXiv2020

A Maximin Optimal Online Power Control Policy for Energy Harvesting Communications

A general theory of online power control for discrete-time battery limited energy harvesting communications is developed, which leads to, among other things, an explicit characterization of a maximin optimal policy. This policy only requires the knowledge of the (effective) mean of the energy arrival process and maximizes the minimum asymptotic expected average reward (with the minimization taken over all energy arrival distributions of a given (effective) mean). Moreover, it is universally near optimal and has a strictly better worst-case performance as well as a strictly improved lower multiplicative factor in comparison with the fixed fraction policy proposed by Shaviv and Özgür when the objective is to maximize the throughput over an additive white Gaussian noise channel. The competitiveness of this maximin optimal policy is also demonstrated via numerical examples.

cs.IT↗

arXiv2020

Trivial Entropy of Matter in Gravitation

Expanding the black hole thermodynamics from the horizon to achronal Cauchy hypersurface, the general relation between the Einstein equation and thermodynamics is established. Starting from trivial entropy that is generalized by Bekenstein-Hawking entropy, the entropic mass of matter emerges naturally together with Unruh temperature. The key idea is that the cause of mass formation comes down to trivial entropy, and mass density is just the external manifestation of mass. The full Einstein equation with the cosmological constant is derived from the requirement that entropic mass and proper mass are equivalent. This perspective suggests that trivial entropy that causes mass in gravitation may be the best choice for the origin of space-time geometry.

hep-th↗

arXiv2020

Efficient long-distance relation extraction with DG-SpanBERT

In natural language processing, relation extraction seeks to rationally understand unstructured text. Here, we propose a novel SpanBERT-based graph convolutional network (DG-SpanBERT) that extracts semantic features from a raw sentence using the pre-trained language model SpanBERT and a graph convolutional network to pool latent features. Our DG-SpanBERT model inherits the advantage of SpanBERT on learning rich lexical features from large-scale corpus. It also has the ability to capture long-range relations between entities due to the usage of GCN on dependency tree. The experimental results show that our model outperforms other existing dependency-based and sequence-based models and achieves a state-of-the-art performance on the TACRED dataset.

cs.CL↗