THE EFFECT OF TRUST ON INFORMATION DIFFUSION IN ONLINE SOCIAL NETWORKS

online social networks have a explosive growth in recent years and they provide a perfect platform for information diffusion. Many models have been given to explore the information diffusion procedure and its dynamics. But the trust relationship and memory effect are ignored. Based on the complex network theory, The information diffusion model is proposed and the network users, considered as agents, are classified into susceptible, infected and recovered individuals. The users’ behaviour rule and diffusion process are designed. The proposed agent-based model is tested by simulation experiments in four different complex networks: regular network, small world network, random network and scale-free network. Moreover, the effect of four immunization strategies are explored. The research results show that the influence of users’ trust relationship on different networks is varied, and the vertex weight priority immunization strategy is the best one in all four networks

Bitstream-Corrupted Video Recovery: A Novel Benchmark Dataset and Method

The past decade has witnessed great strides in video recovery by specialist technologies, like video inpainting, completion, and error concealment. However, they typically simulate the missing content by manual-designed error masks, thus failing to fill in the realistic video loss in video communication (e.g., telepresence, live streaming, and internet video) and multimedia forensics. To address this, we introduce the bitstream-corrupted video (BSCV) benchmark, the first benchmark dataset with more than 28,000 video clips, which can be used for bitstream-corrupted video recovery in the real world. The BSCV is a collection of 1) a proposed three-parameter corruption model for video bitstream, 2) a large-scale dataset containing rich error patterns, multiple corruption levels, and flexible dataset branches, and 3) a plug-and-play module in video recovery framework that serves as a benchmark. We evaluate state-of-the-art video inpainting methods on the BSCV dataset, demonstrating existing approaches' limitations and our framework's advantages in solving the bitstream-corrupted video recovery problem. The benchmark and dataset are released at https://github.com/LIUTIGHE/BSCV-Dataset.Comment: Accepted by NeurIPS Dataset and Benchmark Track 202

Polarized Redundant-Baseline Calibration for 21 cm Cosmology Without Adding Spectral Structure

21 cm cosmology is a promising new probe of the evolution of visible matter in our universe, especially during the poorly-constrained Cosmic Dawn and Epoch of Reionization. However, in order to separate the 21 cm signal from bright astrophysical foregrounds, we need an exquisite understanding of our telescopes so as to avoid adding spectral structure to spectrally-smooth foregrounds. One powerful calibration method relies on repeated simultaneous measurements of the same interferometric baseline to solve for the sky signal and for instrumental parameters simultaneously. However, certain degrees of freedom are not constrained by asserting internal consistency between redundant measurements. In this paper, we review the origin of these "degeneracies" of redundant-baseline calibration and demonstrate how they can source unwanted spectral structure in our measurement and show how to eliminate that additional, artificial structure. We also generalize redundant calibration to dual-polarization instruments, derive the degeneracy structure, and explore the unique challenges to calibration and preserving spectral smoothness presented by a polarized measurement.Comment: 12 pages, 3 figures, updated to match the published MNRAS versio

Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity

This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As LLMs find applications across diverse domains, the reliability and accuracy of their outputs become vital. We define the Factuality Issue as the probability of LLMs to produce content inconsistent with established facts. We first delve into the implications of these inaccuracies, highlighting the potential consequences and challenges posed by factual errors in LLM outputs. Subsequently, we analyze the mechanisms through which LLMs store and process facts, seeking the primary causes of factual errors. Our discussion then transitions to methodologies for evaluating LLM factuality, emphasizing key metrics, benchmarks, and studies. We further explore strategies for enhancing LLM factuality, including approaches tailored for specific domains. We focus two primary LLM configurations standalone LLMs and Retrieval-Augmented LLMs that utilizes external data, we detail their unique challenges and potential enhancements. Our survey offers a structured guide for researchers aiming to fortify the factual reliability of LLMs.Comment: 62 pages; 300+ reference

20(S)-Protopanaxadiol Inhibits Titanium Particle-Induced Inflammatory Osteolysis and RANKL-Mediated Osteoclastogenesis via MAPK and NF-κB Signaling Pathways

Osteolysis is a principal reason for arthroplasty failure like aseptic loosening induced by Titanium (Ti) particle. It is a challenge for orthopedic surgeons. Recent researches show that 20(S)-protopanaxadiol can inhibit inflammatory cytokine release in vitro. This study aims to assess the effect of 20(S)-protopanaxadiol on Ti particle-induced osteolysis and RANKL-mediated osteoclastogenesis. Micro-CT and histological analysis in vivo indicated the inhibitory effects of 20(S)-protopanaxadiol on osteoclastogenesis and the excretion of inflammatory cytokines. Next, we demonstrated that 20(S)-protopanaxadiol inhibited osteoclast differentiation, bone resorption area, and F-actin ring formation in a dose-dependent manner. Moreover, mechanistic studies suggested that the suppression of MAPK and NF-κB signaling pathways were found to mediate the inhibitory effects of 20(S)-protopanaxadiol. In conclusion, 20(S)-protopanaxadiol may suppress osteoclastogenesis in a dose- dependent manner and it could be a potential treatment of Ti particle-induced osteolysis

Integrative Analyses of Long Non-coding RNA and mRNA Involved in Piglet Ileum Immune Response to Clostridium perfringens Type C Infection

Long non-coding RNAs (lncRNAs) have been shown to play important roles in regulating host immune and inflammatory responses to bacterial infection. Infection with Clostridium perfringens (C. perfringens), a food-borne zoonotic pathogen, can lead to a series of inflammatory diseases in human and piglet, greatly challenging the healthy development of global pig industry. However, the roles of lncRNAs involved in piglet immune response against C. perfringens type C infection remain unknown. In this study, the regulatory functions of ileum lncRNAs and mRNAs were investigated in piglet immune response to C. perfringens type C infection among resistance (IR), susceptibility (IS) and sham-inoculation (control, IC) groups. A total of 480 lncRNAs and 3,669 mRNAs were significantly differentially expressed, the differentially expressed lncRNAs and mRNAs in the IR and IS groups were enriched in various pathways of ABC transporters, olfactory transduction, PPAR signaling pathway, chemokine signaling pathway and Toll-like receptor signaling pathway, involving in regulating piglet immune responses and resistance during infection. There were 212 lncRNAs and 505 target mRNAs found to have important association with C. perfringens infectious diseases, furthermore, 25 dysregulated lncRNAs corresponding to 13 immune-related target mRNAs were identified to play potential roles in defense against bacterial infection. In conclusion, the results improve our understanding on the characteristics of lncRNAs and mRNAs on regulating host immune response against C. perfringens type C infection, which will provide a reference for future research into exploring C. perfringens-related diseases in human