arXiv subjects

Lin Li

Publications and source records attributed to Lin Li.

At least 361 records · Page 20Linked to original sources

arXiv2020

Taking the pulse of COVID-19: A spatiotemporal perspective

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts; in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies.

physics.soc-ph↗

arXiv2020

Dirac Fermions in Antiferromagnetic FeSn Kagome Lattices with Combined Space Inversion and Time Reversal Symmetry

Symmetry principles play a critical role in formulating the fundamental laws of nature, with a large number of symmetry-protected topological states identified in recent studies of quantum materials. As compelling examples, massless Dirac fermions are jointly protected by the space inversion symmetry $P$ and time reversal symmetry $T$ supplemented by additional crystalline symmetry, while evolving into Weyl fermions when either $P$ or $T$ is broken. Here, based on first-principles calculations, we reveal that massless Dirac fermions are present in a layered FeSn crystal containing antiferromagnetically coupled ferromagnetic Fe kagome layers, where each of the $P$ and $T$ symmetries is individually broken but the combined $PT$ symmetry is preserved. These stable Dirac fermions protected by the combined $PT$ symmetry with additional non-symmorphic $S_{\rm{2z}}$ symmetry can be transformed to either massless/massive Weyl or massive Dirac fermions by breaking the $PT$ or $S_{\rm{2z}}$ symmetry. Our angle-resolved photoemission spectroscopy experiments indeed observed the Dirac states in the bulk and two-dimensional Weyl-like states at the surface. The present study substantially enriches our fundamental understanding of the intricate connections between symmetries and topologies of matter, especially with the spin degree of freedom playing a vital role.

cond-mat.mtrl-sci↗

arXiv2020

Many-body chiral edge currents and sliding phases of atomic spinwaves in momentum-space lattice

Collective excitations (spinwaves) of long-lived atomic hyperfine states can be synthesized into a Bose-Hubbard model in momentum space. We explore many-body ground states and dynamics of a two-leg momentum-space lattice formed by two coupled hyperfine states. Essential ingredients of this setting are a staggered artificial magnetic field engineered by lasers that couple the spinwave states, and a state-dependent long-range interaction, which is induced by laser-dressing a hyperfine state to a Rydberg state. The Rydberg dressed two-body interaction gives rise to a state-dependent blockade in momentum space, and can amplify staggered flux induced anti-chiral edge currents in the many-body ground state in the presence of magnetic flux. When the Rydberg dressing is applied to both hyperfine states, exotic sliding insulating and superfluid/supersolid phases emerge. Due to the Rydberg dressed long-range interaction, spinwaves slide along a leg of the momentum-space lattice without costing energy. Our study paves a route to the quantum simulation of topological phases and exotic dynamics with interacting spinwaves of atomic hyperfine states in momentum-space lattice.

cond-mat.quant-gas↗

arXiv2020

Effects of biaxial strain and local constant potential on electronic structure of monolayer SnSe

We use the modified Becke-Johnson exchange potential (mBJ) with the spin-orbit coupling effect (SOC) to study effects of biaxial strain and local constant potential on electronic structure of monolayer SnSe. Our results show the fundamental band gap size can be tuned via biaxial strain. Compressive strain (tensile strain) can narrow (enlarge) band gap, and compressive strain causes the transition from quasi-direct to indirect band gap. Moreover, considering that any tuning of electronic structure is realized by changing the periodic potential distribution in the crystalline, we directly add constant potential (CP) to muffin-tin spheres. The results demonstrate that positive and negative CPs can narrow and enlarge band gap, respectively. At CP of 0.9 Ry, semiconductor-metal transition appears, and interestingly a new type of nearly linear dispersions occur at band edge. Our work is good for inspiring more experimental and further theoretical research works.

cond-mat.mtrl-sci↗

arXiv2020

Performance of the T-matrix based master equation for Coulomb drag in double quantum dots

Recently, novel Coulomb drag mechanisms in capacitively coupled double quantum dots were uncovered by the T-matrix based master equation (TME). The TME is so far the primary approach to studying Coulomb drag in the weak-coupling regime; however, its accuracy and reliability remain unexplored. Here, we evaluate the performance of the TME for Coulomb drag via a comparison with numerically exact results obtained by the hierarchical equation-of-motion approach. We find that the TME can capture qualitative current evolutions versus dot levels, temperature, and effective coupling strengths, but only partially succeeds at the quantitative level. Specifically, the TME gives highly inaccurate drag currents when large charge fluctuations on dots exist and the fourth-order tunneling processes make a leading-order contribution. This failure of the TME is attributed to the combined effect of the unique drag mechanisms and its overlook of the fourth-order single-electron tunnelings. We identify the reliable regions to facilitate further quantitative studies on Coulomb drag by the TME.

cond-mat.mes-hall↗

arXiv2020

A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts

The emergence and rapid progress of the Internet have brought ever-increasing impact on financial domain. How to rapidly and accurately mine the key information from the massive negative financial texts has become one of the key issues for investors and decision makers. Aiming at the issue, we propose a sentiment analysis and key entity detection approach based on BERT, which is applied in online financial text mining and public opinion analysis in social media. By using pre-train model, we first study sentiment analysis, and then we consider key entity detection as a sentence matching or Machine Reading Comprehension (MRC) task in different granularity. Among them, we mainly focus on negative sentimental information. We detect the specific entity by using our approach, which is different from traditional Named Entity Recognition (NER). In addition, we also use ensemble learning to improve the performance of proposed approach. Experimental results show that the performance of our approach is generally higher than SVM, LR, NBM, and BERT for two financial sentiment analysis and key entity detection datasets.

cs.CL↗

arXiv2020

Possible Formation Scenarios of ZTF J153932.16+502738.8-A Gravitational Source Close to the Peak of LISA's Sensitivity

ZTF J153932.16+502738.8 (ZTFJ1539) is an eclipsing double-white-dwarf system with an orbital period of 6.91 minutes, and is a significant source of LISA detecting gravitational wave. However, the massive white dwarf (WD) with mass of about 0.61 M$_\odot$ has a high effective temperature (48900 K), and the lower mass WD with mass of about 0.21 M$_{\odot}$ has a low effective temperature($<$10000 K). It is challenging the popular theory of binary evolution. We investigate the formation of ZTFJ1539 via nova and Algol scenarios. Assuming that the massive WD in ZTFJ1539 just experiences a thermalnuclear runaway, nova scenario can explain the effective temperatures of two WDs in ZTFJ1539. However, in order to enlarging a semi-detached orbit of about 4---5 minutes to a detached orbit of about 7 minutes, nova scenario needs a much high kick velocity of about 200 km s$^{-1}$ during nova eruption. The high kick velocity can result in high eccentricity of about 0.2---0.6. Algol scenario can also produce ZTFJ1539 if we take a high efficient parameter for ejecting common envelope and enhance the mass-loss rate via stellar wind trigger by tidal effect.

astro-ph.SR↗

arXiv2019

Deep Visual Waterline Detection within Inland Marine Environment

Waterline usually plays as an important visual cue for maritime applications. However, the visual complexity of inland waterline presents a significant challenge for the development of highly efficient computer vision algorithms tailored for waterline detection in a complicated inland water environment. This paper attempts to find a solution to guarantee the effectiveness of waterline detection for inland maritime applications with general digital camera sensor. To this end, a general deep-learning-based paradigm applicable in variable inland waters, named DeepWL, is proposed, which concerns the efficiency of waterline detection simultaneously. Specifically, there are two novel deep network models, named WLdetectNet and WLgenerateNet respectively, cooperating in the paradigm that afford a continuous waterline image-map estimation from a single captured video stream. Experimental results demonstrate the effectiveness and superiority of the proposed approach via qualitative and quantitative assessment on the concerned performances. Moreover, due to its own generality, the proposed approach has the potential to be applied to the waterline detection tasks of other water areas such as coastal waters.

cs.CV↗

arXiv2019

When is ACL's Deadline? A Scientific Conversational Agent

Our conversational agent UKP-ATHENA assists NLP researchers in finding and exploring scientific literature, identifying relevant authors, planning or post-processing conference visits, and preparing paper submissions using a unified interface based on natural language inputs and responses. UKP-ATHENA enables new access paths to our swiftly evolving research area with its massive amounts of scientific information and high turnaround times. UKP-ATHENA's responses connect information from multiple heterogeneous sources which researchers currently have to explore manually one after another. Unlike a search engine, UKP-ATHENA maintains the context of a conversation to allow for efficient information access on papers, researchers, and conferences. Our architecture consists of multiple components with reference implementations that can be easily extended by new skills and domains. Our user-based evaluation shows that UKP-ATHENA already responds 45% of different formulations of defined intents with 37% information coverage rate.

cs.CL↗

arXiv2019

Tuning Excited State Electron Transfer in Fe Tetracyano-Polypyridyl Complexes

We have investigated photoinduced intramolecular electron transfer dynamics following metal-to-ligand charge-transfer (MLCT) excitation of [Fe(CN)$_4$(2,2'-bipyridine)]$^{2-}$ (1), [Fe(CN)$_4$(2,3-bis(2-pyridyl)pyrazine)]$^{2-}$ (2) and [Fe(CN)$_4$(2,2'-bipyrimidine)]$^{2-}$ (3) complexes in various solvents with static and time-resolved UV-visible absorption spectroscopy and Fe 2p3d resonant inelastic X-ray scattering. We observe $^3$MLCT lifetimes from 180 fs to 67 ps over a wide range of MLCT energies in different solvents by utilizing the strong solvatochromism of the complexes. Intramolecular electron transfer lifetimes governing $^3$MLCT relaxation increase monotonically and (super)exponentially as the $^3$MLCT energy is decreased in 1 and 2 by changing the solvent. This behavior can be described with non-adiabatic classical Marcus electron transfer dynamics along the indirect $^3$MLCT->$^3$MC pathway, where the $^3$MC is the lowest energy metal-centered (MC) excited state. In contrast, the $^3$MLCT lifetime in 3 changes non-monotonically and exhibits a maximum. This qualitatively different behaviour results from direct electron transfer from the $^3$MLCT to the electronic ground state (GS). This pathway involves nuclear tunnelling for the high-frequency polypyridyl skeleton mode ($\hbarω$ = 1530 cm$^{-1}$), which is more displaced for 3 than for either 1 or 2, therefore making the direct pathway significantly more efficient in 3. To our knowledge, this is the first observation of an efficient $^3$MLCT->GS relaxation pathway in an Fe polypyridyl complex. Our study suggests that further extending the MLCT state lifetime requires (1) lowering the $^3$MLCT state energy with respect to the $^3$MC state and (2) suppressing the intramolecular distortion of the electron-accepting ligand in the $^3$MLCT excited state to suppress the rate of direct $^3$MLCT->GS electron transfer.

physics.chem-ph↗

arXiv2019

The Formation of Bimodal Dust Species in Nova Ejecta

The formation of bimodal dust species (namely the silicate and amorphous carbon dust grains coexistent) in a nova eruption is an open problem. According to the nova model simulated by Modules for Experiments in Stellar Astrophysics code, we calculate the formation and growth of carbon (C) and forsterite (Mg2SiO4) dust grains purely in nova ejecta for the fee-expansion model and the radiative shock model by assuming spherical geometry of the nova ejecta. In these models, the chemical properties of pre-existing circumstellar medium are not taken into account. In the free-expansion model, the nova ejecta is not an idea environment for dust nucleation. However, it can efficiently produce dust in the radiative shock model. We estimate that every nova can produce C grains with an average mass of about $10^{-9}$ and $10^{-8}$ ${\rm M_\odot}$, and Mg$_2$SiO$_4$ grains with an average mass of about $10^{-8}$ and $10^{-7}$ ${\rm M_\odot}$. Based on the mass of ejected gas, the ratio of dust to gas is about 1\%. The C grains form first after several or tens of days of nova eruption. After that, the Mg$_2$SiO$_4$ grains begin to grow in tens of days, which is consistent with observations.

astro-ph.SR↗

arXiv2019

Adaptive Short-time Fourier Transform and Synchrosqueezing Transform for Non-stationary Signal Separation

The synchrosqueezing transform, a kind of reassignment method, aims to sharpen the time-frequency representation and to separate the components of a multicomponent non-stationary signal. In this paper, we consider the short-time Fourier transform (STFT) with a time-varying parameter, called the adaptive STFT. Based on the local approximation of linear frequency modulation mode, we analyze the well-separated condition of non-stationary multicomponent signals using the adaptive STFT with the Gaussian window function. We propose the STFT-based synchrosqueezing transform (FSST) with a time-varying parameter, named the adaptive FSST, to enhance the time-frequency concentration and resolution of a multicomponent signal, and to separate its components more accurately. In addition, we also propose the 2nd-order adaptive FSST to further improve the adaptive FSST for the non-stationary signals with fast-varying frequencies. Furthermore, we present a localized optimization algorithm based on our well-separated condition to estimate the time-varying parameter adaptively and automatically. Simulation results on synthetic signals and the bat echolocation signal are provided to demonstrate the effectiveness and robustness of the proposed method.

eess.SP↗

arXiv2019

Adaptive Synchrosqueezing Transform with a Time-Varying Parameter for Non-stationary Signal Separation

The continuous wavelet transform (CWT) is a linear time-frequency representation and a powerful tool for analyzing non-stationary signals. The synchrosqueezing transform (SST) is a special type of the reassignment method which not only enhances the energy concentration of CWT in the time-frequency plane, but also separates the components of multicomponent signals. The "bump wavelet" and Morlet's wavelet are commonly used continuous wavelets for the wavelet-based SST. There is a parameter in these wavelets which controls the widths of the time-frequency localization window. In most literature on SST, this parameter is a fixed positive constant. In this paper, we consider the CWT with a time-varying parameter (called the adaptive CWT) and the corresponding SST (called the adaptive SST) for instantaneous frequency estimation and multicomponent signal separation. We also introduce the 2nd-order adaptive SST. We analyze the separation conditions for non-stationary multicomponent signals with the local approximation of linear frequency modulation mode. We derive well-separated conditions of a multicomponent signal based on the adaptive CWT. We propose methods to select the time-varying parameter so that the corresponding adaptive SSTs of the components of a multicomponent signal have sharp representations and are well-separated, and hence the components can be recovered more accurately. We provide comparison experimental results to demonstrate the efficiency and robustness of the proposed adaptive CWT and adaptive SST in separating components of multicomponent signals with fast varying frequencies.

eess.SP↗

arXiv2019

Nonlocal Kirchhoff superlinear equations with indefinite nonlinearity and lack of compactness

We study the following Kirchhoff equation $$- \left(1 + b \int_{\mathbb{R}^3} |\nabla u|^2 dx \right) Δu + V(x) u = f(x,u), \ x \in \mathbb{R}^3.$$ A special feature of this paper is that the nonlinearity $f$ and the potential $V$ are indefinite, hence sign-changing. Under some appropriate assumptions on $V$ and $f$, we prove the existence of two different solutions of the equation via the Ekeland variational principle and Mountain Pass Theorem.

math.AP↗

arXiv2019

Leveraging User Engagement Signals For Entity Labeling in a Virtual Assistant

Personal assistant AI systems such as Siri, Cortana, and Alexa have become widely used as a means to accomplish tasks through natural language commands. However, components in these systems generally rely on supervised machine learning algorithms that require large amounts of hand-annotated training data, which is expensive and time consuming to collect. The ability to incorporate unsupervised, weakly supervised, or distantly supervised data holds significant promise in overcoming this bottleneck. In this paper, we describe a framework that leverages user engagement signals (user behaviors that demonstrate a positive or negative response to content) to automatically create granular entity labels for training data augmentation. Strategies such as multi-task learning and validation using an external knowledge base are employed to incorporate the engagement annotated data and to boost the model's accuracy on a sequence labeling task. Our results show that learning from data automatically labeled by user engagement signals achieves significant accuracy gains in a production deep learning system, when measured on both the sequence labeling task as well as on user facing results produced by the system end-to-end. We believe this is the first use of user engagement signals to help generate training data for a sequence labeling task on a large scale, and can be applied in practical settings to speed up new feature deployment when little human annotated data is available.

cs.LG↗

arXiv2019

Social Influence-based Attentive Mavens Mining and Aggregative Representation Learning for Group Recommendation

Frequent group activities of human beings have become an indispensable part in their daily life. Group recommendation can recommend satisfactory activities to group members in the recommender systems, and the key issue is how to aggregate preferences in different group members. Most existing group recommendation employed the predefined static aggregation strategies to aggregate the preferences of different group members, but these static strategies cannot simulate the dynamic group decision-making. Meanwhile, most of these methods depend on intuitions or assumptions to analyze the influence of group members and lack of convincing theoretical support. We argue that the influence of group members plays a particularly important role in group decision-making and it can better assist group profile modeling and perform more accurate group recommendation. To tackle the issue of preference aggregation for group recommendation, we propose a novel attentive aggregation representation learning method based on sociological theory for group recommendation, namely SIAGR (short for "Social Influence-based Attentive Group Recommendation"), which takes attention mechanisms and the popular method (BERT) as the aggregation representation for group profile modeling. Specifically, we analyze the influence of group members based on social identity theory and two-step flow theory and exploit an attentive mavens mining method. In addition, we develop a BERT-based representation method to learn the interaction of group members. Lastly, we complete the group recommendation under the neural collaborative filtering framework and verify the effectiveness of the proposed method by experimenting.

cs.SI↗

arXiv2019

Time-Optimal Path Tracking for Industrial Robots: A Dynamic Model-Free Reinforcement Learning Approach

In pursuit of the time-optimal path tracking (TOPT) trajectory of a robot manipulator along a preset path, a beforehand identified robot dynamic model is usually used to obtain the required optimal trajectory for perfect tracking. However, due to the inevitable model-plant mismatch, there may be a big error between the actually measured torques and the calculated torques by the dynamic model, which causes the obtained trajectory to be suboptimal or even be infeasible by exceeding given limits. This paper presents a TOPT-oriented SARSA algorithm (TOPTO-SARSA) and a two-step method for finding the time-optimal motion and ensuring the feasibility : Firstly, using TOPTO-SARSA to find a safe trajectory that satisfies the kinematic constraints through the interaction between reinforcement learning agent and kinematic model. Secondly, using TOPTO-SARSA to find the optimal trajectory through the interaction between the agent and the real world, and assure the actually measured torques satisfy the given limits at the last interaction. The effectiveness of the proposed algorithm has been verified through experiments on a 6-DOF robot manipulator.

cs.RO↗

arXiv2019

Moiré Engineering of Electronic Phenomena in Correlated Oxides

Moiré engineering has recently emerged as a capable approach to control quantum phenomena in condensed matter systems. In van der Waals heterostructures, moiré patterns can be formed by lattice misorientation between adjacent atomic layers, creating long range electronic order. To date, moiré engineering has been executed solely in stacked van der Waals multilayers. Herein, we describe our discovery of electronic moiré patterns in films of a prototypical magnetoresistive oxide La0.67Sr0.33MnO3 (LSMO) epitaxially grown on LaAlO3 (LAO) substrates. Using scanning probe nano-imaging, we observe microscopic moiré profiles attributed to the coexistence and interaction of two distinct incommensurate patterns of strain modulation within these films. The net effect is that both electronic conductivity and ferromagnetism of LSMO are modulated by periodic moiré textures extending over mesoscopic scales. Our work provides an entirely new route with potential to achieve spatially patterned electronic textures on demand in strained epitaxial materials.

cond-mat.mes-hall↗