arXiv subjects

Wei Lv

Publications and source records attributed to Wei Lv.

At least 37 records · Page 2Linked to original sources

arXiv2025

Benders decomposition for the large-scale probabilistic set covering problem

In this paper, we consider a probabilistic set covering problem (PSCP) in which each 0-1 row of the constraint matrix is random with a finite discrete distribution, and the objective is to minimize the total cost of the selected columns such that each row is covered with a prespecified probability. We develop an effective decomposition algorithm for the PSCP based on the Benders reformulation of a standard mixed integer programming (MIP) formulation. The proposed Benders decomposition (BD) algorithm enjoys two key advantages: (i) the number of variables in the underlying Benders reformulation is equal to the number of columns but independent of the number of scenarios of the random data; and (ii) the Benders feasibility cuts can be separated by an efficient polynomial-time algorithm, which makes it particularly suitable for solving large-scale PSCPs. We enhance the BD algorithm by using initial cuts to strengthen the relaxed master problem, implementing an effective heuristic procedure to find high-quality feasible solutions, and adding mixed integer rounding enhanced Benders feasibility cuts to tighten the problem formulation. Numerical results demonstrate the efficiency of the proposed BD algorithm over a state-of-the-art MIP solver. Moreover, the proposed BD algorithm can efficiently identify optimal solutions for instances with up to 500 rows, 5000 columns, and 2000 scenarios of the random rows.

math.OC↗

arXiv2025

Correlated electronic structures and unconventional superconductivity in bilayer nickelate heterostructures

The recent discovery of ambient-pressure superconductivity in thin-film bilayer nickelates opens new possibilities for investigating electronic structures in this new class of high-transition temperature $T_C$ superconductors. Here, we construct a realistic multi-orbital Hubbard model for the thin-film system, by integrating ab initio calculations with scanning transmission electron microscopy (STEM) measurements, which reveal a higher-symmetry lattice. The interaction parameters are calculated with the constrained random phase approximation (cRPA). Density functional theory (DFT) plus cluster dynamical mean-field theory (CDMFT) calculations, with cRPA calculated on-site Coulomb repulsive $U$ and experimentally measured electron filling $n$, quantitatively reproduces Fermi surfaces from angle-resolved photoemission spectroscopy (ARPES) experiments. The distinct Fermi surface topology from simple DFT+$U$ results features the indispensable role of correlation effects. Based upon the correlated electronic structures, A modified random-phase-approximation (RPA) approach yields a pronounced $s^{\pm}$-wave pairing instability, due to the strong spin fluctuations originated from Fermi surface nesting between bands with predominantly $d_{z^{2}}$ characters. Our findings highlight the quantitative effectiveness of the DFT+cRPA+CDMFT approach that precisely determines correlated electronic structure parameters without fine-tuning. The revealed intermediate correlation effect may explain the same order-of-magnitude onset $T_C$ observed both in pressured bulk and strained thin film bilayer nickelates.

cond-mat.str-el↗

arXiv2024

CosIn: A Statistical-based Algorithm for Computation of Space-speed Time Delay in Pedestrian Motion

Precise assessment of Space-speed time delay (TD) is critical for distinguishing between anticipation and reaction behaviors within pedestrian motion. Besides, the TD scale is instrumental in the evaluation of potential collision tendency of the crowd, thereby providing essential quantitative metrics for assessing risk. In this consideration, this paper introduced the CosIn algorithm for evaluating TD during pedestrian motion, which includes both the CosIn-1 and CosIn-2 algorithms. CosIn-1 algorithm analytically calculates TD, replacing the numerical method of discrete cross-correlation, whereas the CosIn-2 algorithm estimates the TD from a statistical perspective. Specifically, the CosIn-1 algorithm addresses the precise computation of TD for individual pedestrians, while the CosIn-2 algorithm is employed for assessing TD at the crowd scale, concurrently addressing the imperative of real-time evaluation. Efficacy analyses of the CosIn-1 and CosIn-2 algorithms are conducted with data from single-file pedestrian experiments and crowd-crossing experiments, respectively. During this process, the discrete cross-correlation method was employed as a baseline to evaluate the performance of both algorithms, which demonstrated notable accuracy. This algorithm facilitate the precise evaluation of behavior patterns and collision tendency within crowds, thereby enabling us to understand the crowds dynamics from a new perspective.

physics.soc-ph↗

arXiv2024

Ambient-pressure superconductivity onset above 40 K in bilayer nickelate ultrathin films

The discovery of bilayer nickelate superconductors under high pressure has opened a new chapter in high-transition temperature (high-TC) superconductivity. Here, we report ambient-pressure superconductivity onset above the McMillan limit (40 K) in bilayer nickelate epitaxial ultrathin films. Three-unit-cell (3UC) thick La2.85Pr0.15Ni2O7 single-phase-crystalline films are grown using the gigantic-oxidative atomic-layer-by-layer epitaxy (GOALL-Epitaxy) on SrLaAlO4 substrates. Resistivity measurements and magnetic-field responses indicate onset TC = 45 K. The transition to zero resistance exhibits characteristics consistent with a Berezinskii-Kosterlitz-Thouless (BKT)-like behavior, with TBKT = 9 K. Meissner diamagnetic effect is observed at TM = 8.5 K via a mutual inductance setup, in agreement with the BKT-like transition. In-plane and out-of-plane critical magnetic fields exhibit anisotropy. Scanning transmission electron microscopy (STEM) images and X-ray reciprocal space mappings (RSMs) show that the films maintain a tetragonal phase with coherent epitaxial compressive strain ~2% in the NiO2 planes relative to the bulk. Our findings pave the way for comprehensive investigations of nickelate superconductors under ambient pressure conditions and for exploring superconductivity at higher transition temperature through strain engineering in heterostructures.

cond-mat.supr-con↗

arXiv2024

Gigantic-oxidative atomic-layer-by-layer epitaxy for artificially designed complex oxides

In designing material functionalities for transition metal oxides, lattice structure and d-orbital occupancy are key determinants. However, the modulation of these two factors is inherently limited by the need to balance thermodynamic stability, growth kinetics, and stoichiometry precision, particularly for metastable phases. We introduce a methodology, namely the gigantic-oxidative atomic-layer-by-layer epitaxy (GOALL-Epitaxy), enhancing oxidation power 3-4 orders of magnitude beyond conventional pulsed laser deposition (PLD) and oxide molecular beam epitaxy (OMBE), while ensuring atomic-layer-by-layer growth of designed complex structures. Thermodynamic stability is markedly augmented with stronger oxidation at elevated temperatures, whereas growth kinetics is sustained by laser ablation at lower temperatures. We demonstrate the accurate growth of complex nickelates and cuprates, especially an artificially designed structure with alternating single and double NiO2 layers possessing distinct nominal d-orbital occupancy, as a parent of high-temperature superconductor. The GOALL-Epitaxy enables material discovery within the vastly broadened growth parameter space.

cond-mat.str-el↗

arXiv2024

A Galton Board Approximation Method for Estimating Pedestrian Walking Preferences within Crowds

This paper proposes a Galton board approximation method to analyze the potential walking preferences of pedestrians. We employ the binomial distribution to estimate the walking preferences of pedestrians in dynamic crowds. Estimating the probability of the right-side preference ($p$) based on observed data poses the challenge, as statistical measures such as means and variances often lead to divergent results. This study aims to explore this issue.

physics.soc-ph↗

arXiv2024

A cellular automata approach for modelling pedestrian-vehicle mixed traffic flow in urban city

In urban streets, the intrusion of pedestrians presents significant safety challenges. Modelling mixed pedestrian-vehicle traffic is complex due to the distinct motion characteristics and spatial dimensions of pedestrians and vehicles, making unified modelling difficult, with few studies addressing these issues. This paper employs a multi-grid cellular automata model to bridge the gap between vehicle and pedestrian models. An Improved Kerner-Klenov-Wolf (IKKW) model and a pedestrian motion model that incorporates Time-To-Collision (TTC) are introduced. Both models update the spatial motions of vehicles and pedestrians uniformly. Empirical analysis indicates that the model achieves high simulation accuracy. This model effectively illustrates the impact of pedestrian intrusion within mixed traffic scenario. The fundamental diagram of heterogeneous traffic reveals substantial differences, highlighting the effects of pedestrian intrusion on traffic flow states and identifying six phase regions in mixed traffic. Additionally, this paper examines conflicts between pedestrians and vehicles under varying speed limits and sidewalk widths, demonstrating that lower speeds and broader sidewalks significantly reduce the frequency of pedestrian-vehicle conflicts. Notably, the frequency of peak conflicts at a vehicle speed limit of 60.48 km/h is more than three times higher than at 30.24 km/h. This model offers a potential approach to studying mixed traffic flows and exhibits substantial scalability.

physics.soc-ph↗

arXiv2024

Nonreciprocal interactions in crowd dynamics: investigating the impact of moving threats on pedestrian speed preferences

Nonreciprocal interaction crowd systems, such as human-human, human-vehicle, and human-robot systems, often have serious impacts on pedestrian safety and social order. A more comprehensive understanding of these systems is needed to optimize system stability and efficiency. Despite the importance of these interactions, empirical research in this area remains limited. Thus, in our study we explore this underresearched area, focusing on scenarios where nonreciprocity plays a critical role, such as mass stabbings, which pose a substantial risk to public safety. We conducted the first experiments on this system and analysed high-accuracy data obtained from these experiments. The extent of the direct threat zone is determined by the speed of the moving threat and the radius of danger occurrence. We further categorize potential threats into direct, adjacent, and rear-view zones, quantifying the level of threat for pedestrians. Our study revealed that a pedestrian's desired velocity correlated positively with potential threat intensity, increasing until near the direct threat zone. An emerging steady state is observed when escape routes are blocked by moving threats. This deviation affects the density-velocity relationship, making it distinct from the general relationship. This deviation signifies unique pedestrian behaviour in the presence of moving threats. Additionally, the rate of change in the angle for pedestrian motion in various desired directions is synchronized. This indicates the emergence of collective intelligence in nonreciprocal interaction crowd systems. As a result, our study may constitute a pioneering step towards understanding nonreciprocal interactions in crowd systems through laboratory experiments. These findings may enhance pedestrian safety and inform not only government crowd management strategies but also individual self-protection measures.

physics.soc-ph↗

arXiv2023

Exploring crowd persistent dynamism from pedestrian crossing perspective: An empirical study

Crowd studies have gained increasing relevance due to the recurring incidents of crowd crush accidents. In addressing the issue of the crowd's persistent dynamism, this paper explored the macroscopic and microscopic features of pedestrians crossing in static and dynamic contexts, employing a series of systematic experiments. Firstly, empirical evidence has confirmed the existence of crowd's persistent dynamism. Subsequently, the research delves into two aspects, qualitative and quantitative, to address the following questions:(1) Cross pedestrians tend to avoid high-density areas when crossing static crowds and particularly evade pedestrians in front to avoid deceleration, thus inducing the formation of cross-channels, a self-organization phenomenon.(2) In dynamic crowds, when pedestrian suffers spatial constrained, two patterns emerge: decelerate or detour. Research results indicate the differences in pedestrian crossing behaviors between static and dynamic crowds, such as the formation of crossing channels, backward detours, and spiral turning. However, the strategy of pedestrian crossing remains consistent: utilizing detours to overcome spatial constraints. Finally, the empirical results of this study address the final question: pedestrians detouring causes crowds' persistent collective dynamism. These findings contribute to an enhanced understanding of pedestrian dynamics in extreme conditions and provide empirical support for research on individual movement patterns and crowd behavior prediction.

physics.soc-ph↗

arXiv2023

Simulation method of urban evacuation based on mesoscopic cellular automata

This study integrates pedestrian flow characteristics to formulate a mesoscopic cellular automata model tailored for simulating evacuations in large-scale scenarios. Departing from the conventional planar grid cell division, the model employs road cell segmentation, thereby physically enlarging the dimensions of individual cells. This augmentation accommodates an increased occupancy of individuals per cell, representing pedestrian flow parameters within each cell through state variables. The source loading cell facilitates the simulation of pedestrian behavior transitioning from buildings to roads during an actual evacuation event, while the unloading cell situated at the exit removes evacuees from the system. The continuity equation for state transitions comprehensively encapsulates the dynamics of pedestrians throughout the evacuation process. Potential challenges in actual evacuation processes are identified through the simulation, offering valuable insights for improvement. This research aims to contribute to a more effective and informed approach to evacuation planning and management.

physics.soc-ph↗

arXiv2023

Joint Projection Learning and Tensor Decomposition Based Incomplete Multi-view Clustering

Incomplete multi-view clustering (IMVC) has received increasing attention since it is often that some views of samples are incomplete in reality. Most existing methods learn similarity subgraphs from original incomplete multi-view data and seek complete graphs by exploring the incomplete subgraphs of each view for spectral clustering. However, the graphs constructed on the original high-dimensional data may be suboptimal due to feature redundancy and noise. Besides, previous methods generally ignored the graph noise caused by the inter-class and intra-class structure variation during the transformation of incomplete graphs and complete graphs. To address these problems, we propose a novel Joint Projection Learning and Tensor Decomposition Based method (JPLTD) for IMVC. Specifically, to alleviate the influence of redundant features and noise in high-dimensional data, JPLTD introduces an orthogonal projection matrix to project the high-dimensional features into a lower-dimensional space for compact feature learning.Meanwhile, based on the lower-dimensional space, the similarity graphs corresponding to instances of different views are learned, and JPLTD stacks these graphs into a third-order low-rank tensor to explore the high-order correlations across different views. We further consider the graph noise of projected data caused by missing samples and use a tensor-decomposition based graph filter for robust clustering.JPLTD decomposes the original tensor into an intrinsic tensor and a sparse tensor. The intrinsic tensor models the true data similarities. An effective optimization algorithm is adopted to solve the JPLTD model. Comprehensive experiments on several benchmark datasets demonstrate that JPLTD outperforms the state-of-the-art methods. The code of JPLTD is available at https://github.com/weilvNJU/JPLTD.

cs.LG↗

arXiv2023

HODOR: Shrinking Attack Surface on Node.js via System Call Limitation

Node.js provides Node.js applications with system interaction capabilities using system calls. However, such convenience comes with a price, i.e., the attack surface of JavaScript arbitrary code execution (ACE) vulnerabilities is expanded to the system call level. There lies a noticeable gap between existing protection techniques in the JavaScript code level (either by code debloating or read-write-execute permission restriction) and a targeted defense for emerging critical system call level exploitation. To fill the gap, we design and implement HODOR, a lightweight runtime protection system based on enforcing precise system call restrictions when running a Node.js application. HODOR achieved this by addressing several nontrivialial technical challenges. First, HODOR requires to construct high-quality call graphs for both the Node.js application (in JavaScript) and its underlying Node.js framework (in JavaScript and C/C++). Specifically, HODOR incorporates several important optimizations in both the JavaScript and C/C++ level to improve the state-of-the-art tools for building more precise call graphs. Then, HODOR creates the main-thread whitelist and the thread-pool whitelist respectively containing the identified necessary system calls based on the call graphs mappings. Finally, with the whitelists, HODOR implements lightweight system call restriction using the Linux kernel feature Secure Computing Mode (seccomp) to shrink the attack surface. We utilize HODOR to protect 83 real-world Node.js applications compromised by arbitrary code/command execution attacks. HODOR could reduce the attack surface to 16.75% on average with negligible runtime overhead (i.e., <3%).

cs.CR↗

arXiv2022

Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition

The sensor-based human activity recognition (HAR) in mobile application scenarios is often confronted with sensor modalities variation and annotated data deficiency. Given this observation, we devised a graph-inspired deep learning approach toward the sensor-based HAR tasks, which was further used to build a deep transfer learning model toward giving a tentative solution for these two challenging problems. Specifically, we present a multi-layer residual structure involved graph convolutional neural network (ResGCNN) toward the sensor-based HAR tasks, namely the HAR-ResGCNN approach. Experimental results on the PAMAP2 and mHealth data sets demonstrate that our ResGCNN is effective at capturing the characteristics of actions with comparable results compared to other sensor-based HAR models (with an average accuracy of 98.18% and 99.07%, respectively). More importantly, the deep transfer learning experiments using the ResGCNN model show excellent transferability and few-shot learning performance. The graph-based framework shows good meta-learning ability and is supposed to be a promising solution in sensor-based HAR tasks.

cs.CV↗

arXiv2021

Micro-scale opto-thermo-mechanical actuation in the dry adhesive regime

Realizing optical manipulation of microscopic objects is crucial in the research fields of life science, condensed matter physics and physical chemistry. In non-liquid environments, this task is commonly regarded as difficult due to strong adhesive surface force ($\simμ\rm N$) between solid interfaces that makes tiny optical driven force ($\sim\rm pN$) insignificant. Here, by recognizing the microscopic interaction mechanism between friction force -- the parallel component of surface force on the contact surface -- and thermoelastic waves induced by pulsed optical absorption, we establish a general principle enabling the actuation of micro-objects on dry frictional surfaces based on the opto-thermo-mechanical effects. Theoretically, we predict that nanosecond pulsed optical absorption with mW-scale peak power is sufficient to tame $μ\rm N$-scale friction force. Experimentally, we demonstrate that two-dimensional spiral motion of gold plates on micro-fibers driven by a nanosecond pulsed laser, and reveal the specific rules of motion control. Our results pave the way for future development of micro-scale actuators in nonliquid environments.

physics.app-ph↗

arXiv2021

Light-induced in-plane Rotation of Microobjects on Microfibers

The transfer of angular momentum carried by photons into a microobject has been widely exploited to achieve the actuation of the microobject. However, this scheme is fundamentally defective in nonliquid environments as a result of the scale gap between friction forces ($μ$N) and optical forces (pN). To bypass this challenge, the researchers have recently proposed to take advantage of elastic waves based on opto-thermo-mechanical effects [1-4]. Grounded on this insight, we here demonstrate and characterize the in-plane rotation of a gold nanoplate in its surface contacting with a microfiber, driven by nanosecond laser pulses, which has not been explored before. Furthermore, we examine the underlying physical mechanisms and highlight the essential role of the spatial gradient of optical absorption. The combined experimental and theoretical results offer new insights into the study of the light-induced actuation of the microobjects in nonliquid environments, an emerging field far from being mature in both comprehensive understanding and practical applications.

physics.optics↗

arXiv2020

Unsaturated Single Atoms on Monolayer Transition Metal Dichalcogenides for Ultrafast Hydrogen Evolution

Large scale implementation of electrochemical water splitting for hydrogen evolution requires cheap and efficient catalysts to replace expensive platinum. Molybdenum disulfide is one of the most promising alternative catalysts but its intrinsic activity is still inferior to platinum. There is therefore a need to explore new active site origins in molybdenum disulfide with ultrafast reaction kinetics and to understand their mechanisms. Here, we report a universal cold hydrogen plasma reduction method for synthesizing different single atoms sitting on two-dimensional monolayers. In case of molybdenum disulfide, we design and identify a new type of active site, i.e., unsaturated Mo single atoms on cogenetic monolayer molybdenum disulfide. The catalyst shows exceptional intrinsic activity with a Tafel slope of 35.1 mV dec-1 and a turnover frequency of ~10^3 s-1 at 100 mV, based on single flake microcell measurements. Theoretical studies indicate that coordinately unsaturated Mo single atoms sitting on molybdenum disulfide increase the bond strength between adsorbed hydrogen atoms and the substrates through hybridization, leading to fast hydrogen adsorption/desorption kinetics and superior hydrogen evolution activity. This work shines fresh light on preparing highly-efficient electrocatalysts for water splitting and other electrochemical processes, as well as provides a general method to synthesize single atoms on two-dimensional monolayers.

cond-mat.mtrl-sci↗

arXiv2020

How many infections of COVID-19 there will be in the "Diamond Princess"-Predicted by a virus transmission model based on the simulation of crowd flow

Objectives: Simulate the transmission process of COVID-19 in a cruise ship, and then to judge how many infections there will be in the 3711 people in the "Diamond Princess" and analyze measures that could have prevented mass transmission. Methods: Based on the crowd flow model, the virus transmission rule between pedestrians is established, to simulate the spread of the virus caused by the close contact during pedestrians' daily activities on the cruise ship. Measurements and main results: Three types of simulation scenarios are designed, the Basic scenario focus on the process of virus transmission caused by a virus carrier and the effect of the personal protective measure against the virus. The condition that the original virus carriers had disembarked halfway and more and more people strengthen self-protection are considered in the Self-protection scenario, which would comparatively accord with the actual situation of "Diamond princess" cruise. Control scenario are set to simulate the effect of taking recommended or mandatory measures on virus transmission Conclusions: There are 850~1009 persons (with large probability) who have been infected with COVID-19 during the voyage of "Diamond Princess". The crowd infection percentage would be controlled effectively if the recommended or mandatory measures can be taken immediately during the alert phase of COVID-19 outbreaks.

physics.soc-ph↗

arXiv2016

Understanding Divergent Thermal Conductivity in Single Polythiophene Chains using Modal Analysis and Sonification

We used molecular dynamics simulations, the Green-Kubo Modal Analysis (GKMA) method and sonification to study the modal contributions to thermal conductivity in individual polythiophene chains. The simulations suggest that it is possible to achieve divergent thermal conductivity and the GKMA method allowed for exact pinpointing of the modes responsible for the anomalous behavior. The analysis showed that transverse vibrations in the plane of the aromatic rings at low frequencies ~ 0.05 THz are primarily responsible. Further investigation showed that the divergence arises from persistent correlation between the three lowest frequency modes on chains. Sonification of the mode heat fluxes revealed regions where the heat flux amplitude yields a somewhat sinusoidal envelope with a long period similar to the relaxation time. This characteristic in the divergent mode heat fluxes gives rise to the overall thermal conductivity divergence, which strongly supports earlier hypotheses that attribute the divergence to correlated phonon-phonon scattering/interactions.

cond-mat.soft↗