Privacy-Preserving Individual-Level COVID-19 Infection Prediction via Federated Graph Learning

Accurately predicting individual-level infection state is of great value since its essential role in reducing the damage of the epidemic. However, there exists an inescapable risk of privacy leakage in the fine-grained user mobility trajectories required by individual-level infection prediction. In this paper, we focus on developing a framework of privacy-preserving individual-level infection prediction based on federated learning (FL) and graph neural networks (GNN). We propose Falcon, a Federated grAph Learning method for privacy-preserving individual-level infeCtion predictiON. It utilizes a novel hypergraph structure with spatio-temporal hyperedges to describe the complex interactions between individuals and locations in the contagion process. By organically combining the FL framework with hypergraph neural networks, the information propagation process of the graph machine learning is able to be divided into two stages distributed on the server and the clients, respectively, so as to effectively protect user privacy while transmitting high-level information. Furthermore, it elaborately designs a differential privacy perturbation mechanism as well as a plausible pseudo location generation approach to preserve user privacy in the graph structure. Besides, it introduces a cooperative coupling mechanism between the individual-level prediction model and an additional region-level model to mitigate the detrimental impacts caused by the injected obfuscation mechanisms. Extensive experimental results show that our methodology outperforms state-of-the-art algorithms and is able to protect user privacy against actual privacy attacks. Our code and datasets are available at the link: https://github.com/wjfu99/FL-epidemic.Comment: accepted by TOI

Application of modal decomposition technique in network traffic prediction

Network traffic prediction is an important means of network security monitoring, and modal decomposition technology is the key to improve the accuracy of network traffic prediction. Therefore, it is imperative to study modal decomposition technology. In this paper, the advantages of Variational Mode Decomposition (VMD) are explored by summarizing and reviewing the application of modal decomposition in network traffic prediction. The findings show that the performance of VMD mainly depends on its decomposition layers k, penalty factor C and Lagrange multiplier Θ. We propose a novel algorithm structure based on square root difference and minimum Theil inequality coefficient to optimize the performance of VMD by finding the best value for these parameters. Optimized Variational Mode Decomposition (OVMD) has improved the network traffic prediction accuracy in network security management

A hybrid pulsed laser deposition approach to grow thin films of chalcogenides

Vapor-pressure mismatched materials such as transition metal chalcogenides have emerged as electronic, photonic, and quantum materials with scientific and technological importance. However, epitaxial growth of vapor-pressure mismatched materials are challenging due to differences in the reactivity, sticking coefficient, and surface adatom mobility of the mismatched species constituting the material, especially sulfur containing compounds. Here, we report a novel approach to grow chalcogenides - hybrid pulsed laser deposition - wherein an organosulfur precursor is used as a sulfur source in conjunction with pulsed laser deposition to regulate the stoichiometry of the deposited films. Epitaxial or textured thin films of sulfides with variety of structure and chemistry such as alkaline metal chalcogenides, main group chalcogenides, transition metal chalcogenides and chalcogenide perovskites are demonstrated, and structural characterization reveal improvement in thin film crystallinity, and surface and interface roughness compared to the state-of-the-art. The growth method can be broadened to other vapor-pressure mismatched chalcogenides such as selenides and tellurides. Our work opens up opportunities for broader epitaxial growth of chalcogenides, especially sulfide-based thin film technological applications.Comment: 27 page

S3: Social-network Simulation System with Large Language Model-Empowered Agents

Social network simulation plays a crucial role in addressing various challenges within social science. It offers extensive applications such as state prediction, phenomena explanation, and policy-making support, among others. In this work, we harness the formidable human-like capabilities exhibited by large language models (LLMs) in sensing, reasoning, and behaving, and utilize these qualities to construct the S$^3$ system (short for $\textbf{S}$ocial network $\textbf{S}$imulation $\textbf{S}$ystem). Adhering to the widely employed agent-based simulation paradigm, we employ prompt engineering and prompt tuning techniques to ensure that the agent's behavior closely emulates that of a genuine human within the social network. Specifically, we simulate three pivotal aspects: emotion, attitude, and interaction behaviors. By endowing the agent in the system with the ability to perceive the informational environment and emulate human actions, we observe the emergence of population-level phenomena, including the propagation of information, attitudes, and emotions. We conduct an evaluation encompassing two levels of simulation, employing real-world social network data. Encouragingly, the results demonstrate promising accuracy. This work represents an initial step in the realm of social network simulation empowered by LLM-based agents. We anticipate that our endeavors will serve as a source of inspiration for the development of simulation systems within, but not limited to, social science

Colossal optical anisotropy from atomic-scale modulations

In modern optics, materials with large birefringence ({\Delta}n, where n is the refractive index) are sought after for polarization control (e.g. in wave plates, polarizing beam splitters, etc.), nonlinear optics and quantum optics (e.g. for phase matching and production of entangled photons), micromanipulation, and as a platform for unconventional light-matter coupling, such as Dyakonov-like surface polaritons and hyperbolic phonon polaritons. Layered "van der Waals" materials, with strong intra-layer bonding and weak inter-layer bonding, can feature some of the largest optical anisotropy; however, their use in most optical systems is limited because their optic axis is out of the plane of the layers and the layers are weakly attached, making the anisotropy hard to access. Here, we demonstrate that a bulk crystal with subtle periodic modulations in its structure -- Sr9/8TiS3 -- is transparent and positive-uniaxial, with extraordinary index n_e = 4.5 and ordinary index n_o = 2.4 in the mid- to far-infrared. The excess Sr, compared to stoichiometric SrTiS3, results in the formation of TiS6 trigonal-prismatic units that break the infinite chains of face-shared TiS6 octahedra in SrTiS3 into periodic blocks of five TiS6 octahedral units. The additional electrons introduced by the excess Sr subsequently occupy the TiS6 octahedral blocks to form highly oriented and polarizable electron clouds, which selectively boost the extraordinary index n_e and result in record birefringence ({\Delta}n > 2.1 with low loss). The connection between subtle structural modulations and large changes in refractive index suggests new categories of anisotropic materials and also tunable optical materials with large refractive-index modulation and low optical losses.Comment: Main text + supplementar

Giant Modulation of Refractive Index from Correlated Disorder

Correlated disorder has been shown to enhance and modulate magnetic, electrical, dipolar, electrochemical and mechanical properties of materials. However, the possibility of obtaining novel optical and opto-electronic properties from such correlated disorder remains an open question. Here, we show unambiguous evidence of correlated disorder in the form of anisotropic, sub-angstrom-scale atomic displacements modulating the refractive index tensor and resulting in the giant optical anisotropy observed in BaTiS3, a quasi-one-dimensional hexagonal chalcogenide. Single crystal X-ray diffraction studies reveal the presence of antipolar displacements of Ti atoms within adjacent TiS6 chains along the c-axis, and three-fold degenerate Ti displacements in the a-b plane. 47/49Ti solid-state NMR provides additional evidence for those Ti displacements in the form of a three-horned NMR lineshape resulting from low symmetry local environment around Ti atoms. We used scanning transmission electron microscopy to directly observe the globally disordered Ti a-b plane displacements and find them to be ordered locally over a few unit cells. First-principles calculations show that the Ti a-b plane displacements selectively reduce the refractive index along the ab-plane, while having minimal impact on the refractive index along the chain direction, thus resulting in a giant enhancement in the optical anisotropy. By showing a strong connection between correlated disorder and the optical response in BaTiS3, this study opens a pathway for designing optical materials with high refractive index and functionalities such as a large optical anisotropy and nonlinearity.Comment: 24 pages, 3 figure

Unconventional Charge-density-wave Order in a Dilute d-band Semiconductor

Electron-lattice coupling effects in low dimensional materials give rise to charge density wave (CDW) order and phase transitions. These phenomena are critical ingredients for superconductivity and predominantly occur in metallic model systems such as doped cuprates, transition metal dichalcogenides, and more recently, in Kagome lattice materials. However, CDW in semiconducting systems, specifically at the limit of low carrier concentration region, is uncommon. Here, we combine electrical transport, synchrotron X-ray diffraction and optical spectroscopy to discover CDW order in a quasi-one-dimensional (1D), dilute d-band semiconductor, BaTiS3, which suggests the existence of strong electron-phonon coupling. The CDW state further undergoes an unusual transition featuring a sharp increase in carrier mobility. Our work establishes BaTiS3 as a unique platform to study the CDW physics in the dilute filling limit to explore novel electronic phases

Numerical investigation on transverse flow of helical cruciform fuel rod assembly in a lead-bismuth cooled fast reactor

The helical cruciform fuel (HCF) rod assembly is a new type of fuel for the lead-bismuth (LBE) fast reactor. It can be self-positioned and realize a coolant mixing without wrapped wire or grid spacer. This kind of fuel assembly can not only realize the function of the traditional wire-wrapped fuel assembly, but also omit the wire -wrapped structure, which provides a satisfactory prospect for the development of LBE reactor. In this study, the coolant mixing in the LBE cooled reactor with HCF assembly was analyzed numerically. The influence of the Reynolds number and different coolant mediums were investigated. Advantages and disadvantages of the HCF assembly were analyzed and compared with the wire-wrapped fuel