arXiv subjects

Yu Liu

Publications and source records attributed to Yu Liu.

At least 919 records · Page 51Linked to original sources

arXiv2020

Complete Strain Mapping of Nanosheets of Tantalum Disulfide

Quasi-two-dimensional (quasi-2D) materials hold promise for future electronics because of their unique band structures that result in electronic and mechanical properties sensitive to crystal strains in all three dimensions. Quantifying crystal strain is a prerequisite to correlating it with the performance of the device, and calls for high resolution but spatially resolved rapid characterization methods. Here we show that using fly-scan nano X-ray diffraction we can accomplish a tensile strain sensitivity below 0.001% with a spatial resolution of better than 80 nm over a spatial extent of 100 $μ$m on quasi 2D flakes of 1T-TaS2. Coherent diffraction patterns were collected from a $\sim$ 100 nm thick sheet of 1T-TaS2 by scanning 12keV focused X-ray beam across and rotating the sample. We demonstrate that the strain distribution around micron and sub-micron sized 'bubbles' that are present in the sample may be reconstructed from these images. The experiments use state of the art synchrotron instrumentation, and will allow rapid and non-intrusive strain mapping of thin film samples and electronic devices based on quasi 2D materials.

cond-mat.mtrl-sci↗

arXiv2020

Complementary Boundary Generator with Scale-Invariant Relation Modeling for Temporal Action Localization: Submission to ActivityNet Challenge 2020

This technical report presents an overview of our solution used in the submission to ActivityNet Challenge 2020 Task 1 (\textbf{temporal action localization/detection}). Temporal action localization requires to not only precisely locate the temporal boundaries of action instances, but also accurately classify the untrimmed videos into specific categories. In this paper, we decouple the temporal action localization task into two stages (i.e. proposal generation and classification) and enrich the proposal diversity through exhaustively exploring the influences of multiple components from different but complementary perspectives. Specifically, in order to generate high-quality proposals, we consider several factors including the video feature encoder, the proposal generator, the proposal-proposal relations, the scale imbalance, and ensemble strategy. Finally, in order to obtain accurate detections, we need to further train an optimal video classifier to recognize the generated proposals. Our proposed scheme achieves the state-of-the-art performance on the temporal action localization task with \textbf{42.26} average mAP on the challenge testing set.

cs.CV↗

arXiv2020

Three-dimensional Ising Ferrimagnetism of Cr-Fe-Cr trimers in FeCr2Te4

We carried out a comprehensive study of magnetic critical behavior in single crystals of ternary chalcogenide FeCr$_2$Te$_4$ that undergoes a ferrimagnetic transition below $T_c$ $\sim$ 123 K. Detailed critical behavior analysis and scaled magnetic entropy change indicate a second-order ferrimagentic transition. Critical exponents $β= 0.30(1)$ with $T_c = 122.4(5)$ K, $γ= 1.22(1)$ with $T_c = 122.8(1)$ K, and $δ= 4.24(2)$ at $T_c$ $\sim$ 123 K suggest that the spins approach three-dimensional Ising ($β$ = 0.325, $γ$ = 1.24, and $δ$ = 4.82) model coupled with the attractive long-range interactions between spins that decay as $J(r)\approx r^{-4.88}$. Our results suggest that the ferrimagnetism in FeCr$_2$Te$_4$ is due to itinerant ferromagnetism among the antiferromagnetically coupled Cr-Fe-Cr trimers.

cond-mat.str-el↗

arXiv2020

Room-Temperature Skyrmion Thermopower in Fe3Sn2

We present first room-temperature thermoelectric signature of the skyrmion lattice. This was observed in Fe3Sn2, a Kagome Dirac crystal with massive Dirac fermions that features high-temperature skyrmion phase. The room-temperature skyrmion lattice shows magnetic-field dependence of the wavevector whereas thermopower is dominated by the electronic diffusion mechanism, allowing for the skyrmionic bubble lattice detection. Our results pave the way for the future skyrmion-based devices based on the manipulation of the thermal gradient.

cond-mat.mtrl-sci↗

arXiv2020

Single Cell Transcriptome Research in Human Placenta

Human placenta is a complex and heterogeneous organ interfacing between the mother and the fetus that supports fetal development. Alterations to placental structural components are associated with various pregnancy complications. To reveal the heterogeneity among various placenta cell types in normal and diseased placentas, as well as elucidate molecular interactions within a population of placental cells, a new genomics technology called single cell RNA-Seq (or scRNA-seq) has been employed in the last couple of years. Here we review the principles of scRNA-seq technology, and summarize the recent human placenta studies at scRNA-seq level across gestational ages as well as in pregnancy complications such as preterm birth and preeclampsia. We list the computational analysis platforms and resources available for the public use. Lastly, we discuss the future areas of interest for placenta single cell studies, as well as the data analytics needed to accomplish them.

q-bio.TO↗

arXiv2020

Dual Gaussian-based Variational Subspace Disentanglement for Visible-Infrared Person Re-Identification

Visible-infrared person re-identification (VI-ReID) is a challenging and essential task in night-time intelligent surveillance systems. Except for the intra-modality variance that RGB-RGB person re-identification mainly overcomes, VI-ReID suffers from additional inter-modality variance caused by the inherent heterogeneous gap. To solve the problem, we present a carefully designed dual Gaussian-based variational auto-encoder (DG-VAE), which disentangles an identity-discriminable and an identity-ambiguous cross-modality feature subspace, following a mixture-of-Gaussians (MoG) prior and a standard Gaussian distribution prior, respectively. Disentangling cross-modality identity-discriminable features leads to more robust retrieval for VI-ReID. To achieve efficient optimization like conventional VAE, we theoretically derive two variational inference terms for the MoG prior under the supervised setting, which not only restricts the identity-discriminable subspace so that the model explicitly handles the cross-modality intra-identity variance, but also enables the MoG distribution to avoid posterior collapse. Furthermore, we propose a triplet swap reconstruction (TSR) strategy to promote the above disentangling process. Extensive experiments demonstrate that our method outperforms state-of-the-art methods on two VI-ReID datasets.

cs.CV↗

arXiv2020

Comparative Analyses of Plasma Properties and Composition in Two Types of Small-Scale Interplanetary Flux-ropes

The origin of small-scale interplanetary magnetic flux-ropes (SIMFRs) and the relationship between SIMFRs and magnetic clouds (MCs) are still controversial. In this study, two populations of SMIFRs were collected, i.e., SIMFRs originating from the Sun (SIMFR-SUN) and those originating from the solar wind (SIMFR-SW). We defined the SIMFR-SUN (SIMFR-SW) as the SMIFRs that include (exclude) the counter-streaming suprathermal electrons and stay away from (close to) the heliospheric current sheet. After fitting with force-free flux-rope model, 52 SIMFR-SUN and 57 SIMFR-SW events observed by Advanced Composition Explorer (ACE) from 1998 February to 2011 August were qualified. Using the approach of relating the measurements to their spatial position within the flux-ropes, a comparative survey of plasma and composition characteristics inside the two populations of SIMFRs is presented. Results show that the two populations of SIMFRs have apparent differences. Compared with SIMFR-SW, SIMFR-SUN are MC-like, featuring lower central proton density, higher Vrad, higher low-FIP element abundances, higher and more fluctuate average ion charge-states and the ion chargestate ratios which are related to the heating in low corona. In addition, for the ion charge-state distributions inside SIMFR-SUN, the sunward side is higher than earthward, which might be caused by the flare heating during eruption. Moreover, both SIMFR-SUN and MCs show anti-correlation between plasma beta and He/P trend. These characteristics indicate that SIMFR-SUN and MCs are very likely to have the identical origination. This study supports the two-source origin of SIMFRs, i.e., the solar corona and the solar wind.

astro-ph.SR↗

arXiv2020

Deep Reinforcement Learning for Dynamic Spectrum Sensing and Aggregation in Multi-Channel Wireless Networks

In this paper, the problem of dynamic spectrum sensing and aggregation is investigated in a wireless network containing N correlated channels, where these channels are occupied or vacant following an unknown joint 2-state Markov model. At each time slot, a single cognitive user with certain bandwidth requirement either stays idle or selects a segment comprising C (C < N) contiguous channels to sense. Then, the vacant channels in the selected segment will be aggregated for satisfying the user requirement. The user receives a binary feedback signal indicating whether the transmission is successful or not (i.e., ACK signal) after each transmission, and makes next decision based on the sensing channel states. Here, we aim to find a policy that can maximize the number of successful transmissions without interrupting the primary users (PUs). The problem can be considered as a partially observable Markov decision process (POMDP) due to without full observation of system environment. We implement a Deep Q-Network (DQN) to address the challenge of unknown system dynamics and computational expenses. The performance of DQN, Q-Learning, and the Improvident Policy with known system dynamics is evaluated through simulations. The simulation results show that DQN can achieve near-optimal performance among different system scenarios only based on partial observations and ACK signals.

eess.SP↗

arXiv2020

Learning Where to Focus for Efficient Video Object Detection

Transferring existing image-based detectors to the video is non-trivial since the quality of frames is always deteriorated by part occlusion, rare pose, and motion blur. Previous approaches exploit to propagate and aggregate features across video frames by using optical flow-warping. However, directly applying image-level optical flow onto the high-level features might not establish accurate spatial correspondences. Therefore, a novel module called Learnable Spatio-Temporal Sampling (LSTS) has been proposed to learn semantic-level correspondences among adjacent frame features accurately. The sampled locations are first randomly initialized, then updated iteratively to find better spatial correspondences guided by detection supervision progressively. Besides, Sparsely Recursive Feature Updating (SRFU) module and Dense Feature Aggregation (DFA) module are also introduced to model temporal relations and enhance per-frame features, respectively. Without bells and whistles, the proposed method achieves state-of-the-art performance on the ImageNet VID dataset with less computational complexity and real-time speed. Code will be made available at https://github.com/jiangzhengkai/LSTS.

cs.CV↗

arXiv2020

Anisotropic magnetocaloric effect and critical behavior in CrSbSe$_3$

We report anisotropic magnetocaloric effect and critical behavior in quasi-one-dimensional ferromagnetic CrSbSe$_3$ single crystal. The maximum magnetic entropy change $-ΔS_M^{max}$ is 2.16 J kg$^{-1}$ K$^{-1}$ for easy $a$ axis (2.03 J kg$^{-1}$ K$^{-1}$ for hard $b$ axis) and the relative cooling power $RCP$ is 163.1 J kg$^{-1}$ for easy $a$ axis (142.1 J kg$^{-1}$ for hard $b$ axis) near $T_c$ with a magnetic field change of 50 kOe. The magnetocrystalline anisotropy constant $K_u$ is estimated to be 148.5 kJ m$^{-3}$ at 10 K, decreasing to 39.4 kJ m$^{-3}$ at 70 K. The rescaled $ΔS_M(T,H)$ curves along all three axes collapse onto a universal curve, respectively, confirming the second order ferromagnetic transition. Further critical behavior analysis around $T_c \sim$ 70 K gives that the critical exponents $β$ = 0.26(1), $γ$ = 1.32(2), and $δ$ = 6.17(9) for $H\parallel a$, while $β$ = 0.28(2), $γ$ = 1.02(1), and $δ$ = 4.14(16) for $H\parallel b$. The determined critical exponents suggest that the anisotropic magnetic coupling in CrSbSe$_3$ is strongly dependent on orientations of the applied magnetic field.

cond-mat.str-el↗

arXiv2020

Anisotropic magnetocaloric effect and critical behavior in CrCl$_3$

We report anisotropic magnetocaloric effect and magnetic critical behavior in van der Waals crystal CrCl$_3$. The maximum magnetic entropy change $-ΔS_M^{max} \sim 14.6$ J kg$^{-1}$ K$^{-1}$ and the relative cooling power $RCP \sim 340.3$ J kg$^{-1}$ near $T_c$ with a magnetic field change of 5 T are much larger when compared to CrI$_{3}$ or CrBr$_{3}$. The rescaled $ΔS_M(T,H)$ curves collapse onto a universal curve, confirming the second order ferromagnetic transition. Further critical behavior analysis around $T_c$ presents a set of critical exponents $β$ = 0.28(1) with $T_c$ = 19.4(2) K, $γ$ = 0.89(1) with $T_c$ = 18.95(8) K, and $δ$ = 4.6(1) at $T_c$ = 19 K, which are close to those of theoretical tricritical mean field model.

cond-mat.mtrl-sci↗

arXiv2020

Relative rigid subcategories and $τ$-tilting theory

Let $\mathcal B$ be an extriangulated category with enough projectives $\mathcal P$ and enough injectives $\mathcal I$, and let $\mathcal R$ be a contravariantly finite rigid subcategory of $\mathcal B$ which contains $\mathcal P$. We have an abelian quotient category $\mathcal H/\mathcal R\subseteq \mathcal B/\mathcal R$ which is equivalent ${\rm mod}(\mathcal R/\mathcal P)$. In this article, we find a one-to-one correspondence between support $τ$-tilting (resp. $τ$-rigid) subcategories of $\mathcal H/\mathcal R$ and maximal relative rigid (resp. relative rigid) subcategories of $\mathcal H$, and show that support tilting subcategories in $\mathcal H/\mathcal R$ is a special kind of support $τ$-tilting subcategories. We also study the relation between tilting subcategories of $\mathcal B/\mathcal R$ and cluster tilting subcategories of $\mathcal B$ when $\mathcal R$ is cluster tilting.

math.RT↗

arXiv2020

Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases

With the rapid development of knowledge bases (KBs), link prediction task, which completes KBs with missing facts, has been broadly studied in especially binary relational KBs (a.k.a knowledge graph) with powerful tensor decomposition related methods. However, the ubiquitous n-ary relational KBs with higher-arity relational facts are paid less attention, in which existing translation based and neural network based approaches have weak expressiveness and high complexity in modeling various relations. Tensor decomposition has not been considered for n-ary relational KBs, while directly extending tensor decomposition related methods of binary relational KBs to the n-ary case does not yield satisfactory results due to exponential model complexity and their strong assumptions on binary relations. To generalize tensor decomposition for n-ary relational KBs, in this work, we propose GETD, a generalized model based on Tucker decomposition and Tensor Ring decomposition. The existing negative sampling technique is also generalized to the n-ary case for GETD. In addition, we theoretically prove that GETD is fully expressive to completely represent any KBs. Extensive evaluations on two representative n-ary relational KB datasets demonstrate the superior performance of GETD, significantly improving the state-of-the-art methods by over 15\%. Moreover, GETD further obtains the state-of-the-art results on the benchmark binary relational KB datasets.

cs.CL↗

arXiv2020

1st place solution for AVA-Kinetics Crossover in AcitivityNet Challenge 2020

This technical report introduces our winning solution to the spatio-temporal action localization track, AVA-Kinetics Crossover, in ActivityNet Challenge 2020. Our entry is mainly based on Actor-Context-Actor Relation Network. We describe technical details for the new AVA-Kinetics dataset, together with some experimental results. Without any bells and whistles, we achieved 39.62 mAP on the test set of AVA-Kinetics, which outperforms other entries by a large margin. Code will be available at: https://github.com/Siyu-C/ACAR-Net.

cs.CV↗

arXiv2020

Kondo scenario of the γ-α phase transition in single crystalline Cerium thin films

The physical mechanism driving the $γ$-$α$ phase transition of face-centre-cubic (fcc) cerium (Ce) remains controversial until now. In this work, high quality single crystalline fcc-Ce thin films were grown on Graphene/6$H$-SiC(0001) substrate, and explored by XRD and ARPES measurement. XRD spectra showed a clear $γ$-$α$ phase transition at $T_{γ-α}\approx$ 50 K, which is retarded by strain effect from substrate comparing with $T_{γ-α}$ (about 140 K) of the bulk Ce metal. However, APRES spectra did not show any signature of $α$-phase emerging in the surface-layer from 300 K to 17 K, which implied that $α$-phase might form at the bulk-layer of our Ce thin films. Besides, an evident Kondo dip near Fermi energy was observed in the APRES spectrum at 80 K, indicting the formation of Kondo singlet states in $γ$-Ce. Furthermore, the DFT+DMFT calculations were performed to simulate the electronic structures and the theoretical spectral functions agreed well with the experimental ARPES spectra. In $γ$-Ce, the behavior of the self-energy's imaginary part at low frequency not only confirmed that the Kondo singlet states emerged at $T_{\rm KS} \geq 80$ K, but also implied that they became coherent states at a lower characteristic temperature ($T_{\rm coh}\sim 40$ K) due to the indirect RKKY interaction among $f$-$f$ electrons. Besides, $T_{\rm coh}$ from the theoretical simulation was close to $T_{γ-α}$ from the XRD spectra. These issues suggested that the Kondo scenario might play an important role in the $γ$-$α$ phase transition of cerium thin films.

cond-mat.str-el↗

arXiv2020

PulseGAN: Learning to generate realistic pulse waveforms in remote photoplethysmography

Remote photoplethysmography (rPPG) is a non-contact technique for measuring cardiac signals from facial videos. High-quality rPPG pulse signals are urgently demanded in many fields, such as health monitoring and emotion recognition. However, most of the existing rPPG methods can only be used to get average heart rate (HR) values due to the limitation of inaccurate pulse signals. In this paper, a new framework based on generative adversarial network, called PulseGAN, is introduced to generate realistic rPPG pulse signals through denoising the chrominance signals. Considering that the cardiac signal is quasi-periodic and has apparent time-frequency characteristics, the error losses defined in time and spectrum domains are both employed with the adversarial loss to enforce the model generating accurate pulse waveforms as its reference. The proposed framework is tested on the public UBFC-RPPG database in both within-database and cross-database configurations. The results show that the PulseGAN framework can effectively improve the waveform quality, thereby enhancing the accuracy of HR, the heart rate variability (HRV) and the interbeat interval (IBI). The proposed method achieves the best performance compared to the denoising autoencoder (DAE) and CHROM, with the mean absolute error of AVNN (the average of all normal-to-normal intervals) improving 20.85% and 41.19%, and the mean absolute error of SDNN (the standard deviation of all NN intervals) improving 20.28% and 37.53%, respectively, in the cross-database test. This framework can be easily extended to other existing deep learning based rPPG methods, which is expected to expand the application scope of rPPG techniques.

eess.IV↗

arXiv2020

From $n$-exangulated categories to $n$-abelian categories

Herschend-Liu-Nakaoka introduced the notion of $n$-exangulated categories. It is not only a higher dimensional analogue of extriangulated categories defined by Nakaoka-Palu, but also gives a simultaneous generalization of $n$-exact categories in the sense of Jasso and $(n+2)$-angulated in the sense of Geiss-Keller-Oppermann. Let $\mathscr C$ be an $n$-exangulated category with enough projectives and enough injectives, and $\mathscr X$ a cluster tilting subcategory of $\mathscr C$. In this article, we show that the quotient category $\mathscr C/\mathscr X$ is an $n$-abelian category. This extends a result of Zhou-Zhu for $(n+2)$-angulated categories. Moreover, it highlights new phenomena when it is applied to $n$-exact categories.

math.RT↗

arXiv2020

Frobenius $n$-exangulated categories

Herschend-Liu-Nakaoka introduced the notion of $n$-exangulated categories as higher dimensional analogues of extriangulated categories defined by Nakaoka-Palu. The class of $n$-exangulated categories contains $n$-exact categories and $(n+2)$-angulated categories as examples. In this article, we introduce a notion of Frobenius $n$-exangulated categories which are a generalization of Frobenius $n$-exact categories. We show that the stable category of a Frobenius $n$-exangulated category is an $(n+2)$-angulated category. As an application, this result generalizes the work by Jasso. We provide a class of $n$-exangulated categories which are neither $n$-exact categories nor $(n+2)$-angulated categories. Finally, we discuss an application of the main results and give some examples illustrating it.

math.RT↗