Knowledge-Enhanced Hierarchical Information Correlation Learning for Multi-Modal Rumor Detection

The explosive growth of rumors with text and images on social media platforms has drawn great attention. Existing studies have made significant contributions to cross-modal information interaction and fusion, but they fail to fully explore hierarchical and complex semantic correlation across different modality content, severely limiting their performance on detecting multi-modal rumor. In this work, we propose a novel knowledge-enhanced hierarchical information correlation learning approach (KhiCL) for multi-modal rumor detection by jointly modeling the basic semantic correlation and high-order knowledge-enhanced entity correlation. Specifically, KhiCL exploits cross-modal joint dictionary to transfer the heterogeneous unimodality features into the common feature space and captures the basic cross-modal semantic consistency and inconsistency by a cross-modal fusion layer. Moreover, considering the description of multi-modal content is narrated around entities, KhiCL extracts visual and textual entities from images and text, and designs a knowledge relevance reasoning strategy to find the shortest semantic relevant path between each pair of entities in external knowledge graph, and absorbs all complementary contextual knowledge of other connected entities in this path for learning knowledge-enhanced entity representations. Furthermore, KhiCL utilizes a signed attention mechanism to model the knowledge-enhanced entity consistency and inconsistency of intra-modality and inter-modality entity pairs by measuring their corresponding semantic relevant distance. Extensive experiments have demonstrated the effectiveness of the proposed method

First attempt of directionality reconstruction for atmospheric neutrinos in a large homogeneous liquid scintillator detector

The directionality information of incoming neutrinos is essential to atmospheric neutrino oscillation analysis since it is directly related to the oscillation baseline length. Large homogeneous liquid scintillator detectors, while offering excellent energy resolution, are traditionally very limited in their capabilities of measuring event directionality. In this paper, we present a novel directionality reconstruction method for atmospheric neutrino events in large homogeneous liquid scintillator detectors based on waveform analysis and machine learning techniques. We demonstrate for the first time that such detectors can achieve good direction resolution and potentially play an important role in future atmospheric neutrino oscillation measurements.Comment: Prepared for submission to PR

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

High-Speed Rail Network Structural Characteristics and Evolution in China

Based on high-speed rail (HSR) network data from 2008 to 2020, this study explores the structural characteristics and evolution of China’s HSR network from the perspective of the overall network and urban node network centrality. We show that the overall connectivity of the HSR network has improved significantly, whereas the accessibility of the HSR network has improved slightly. Furthermore, both the density and accessibility of the HSR network in different regions gradually show a decreasing trend from the east coast zone to the southwest. We also find that from the perspective of urban node network centrality, cities with high degree centrality and high betweenness centrality are densely distributed along the northern coast, eastern coast, as well as middle reaches of both the Yellow and Yangtze Rivers. Finally, the node cities have shown a significant increase in both degree centrality and betweenness centrality; thus, both the hub role and radiation capacity have improved. Our study suggests that the government should closely monitor the development of HSR networks in the western region

Coexistence of three heteroclinic cycles and chaos analyses for a class of 3D piecewise affine systems

Our objective is to investigate the innovative dynamics of piecewise smooth systems with multiple discontinuous switching manifolds. This paper establishes the coexistence of heteroclinic cycles in a class of 3D piecewise affine systems with three switching manifolds through rigorous mathematical analysis. By constructing suitable Poincaré maps adjacent to heteroclinic cycles, we demonstrate the occurrence of two distinct types of horseshoes and show the conditions for the presence of chaotic invariant sets. A family of attractors that satisfy the criteria are presented using this technique. It is shown that the outcomes of numerical simulation accurately reflect those of our theoretical results

An experimental study on synthesis of β-Sialon composites using fly ash and lignite char-preparation and whiskers formation

β-Sialon based composites were produced using a vertical reactor by carbothermal reduction reaction under nitrogen using fly ash and lignite chars to examine the effects of mixing, carbon content, reaction temperature and sintering time. The influences of chars as a reductant were further investigated in comparison with graphite. The evolution of phase and morphology in samples were analyzed by X-ray diffraction (XRD) and scanning electron microscope (SEM). Mechanical stirring was favored to mix fly ash and chars, while ball-milling shove the chars with porous structure due to collisions of agate balls, preventing N₂ penetration to the inner parts of reactants. When excess carbon was increased to 100%, a higher combustion reactivity of low-temperature chars resulted in the production of SiC phase. The evolution of β-Sialon with increasing reaction temperature showed the samples mixed with chars were more sensitive to reaction temperature than that with graphite. β-Sialon phase increased gradually with increasing sintering time to 6 h and decreased thereafter due to the decomposition or conversion of β-Sialon. These changes were more significantly for samples adding lignite chars. The optimal operation has been determined and rod-like β-Sialon whiskers with high aspect ratio appeared after performing the operation. In the growth process of whiskers, bead-shape whiskers were observed, suggesting that the growth mechanism was different from the conventional vaporliquidsolid (VLS) mechanism

N-glycosylated intestinal protein BCF-1 shapes microbial colonization by binding bacteria via its fimbrial protein

Summary: Microbial colonization plays an instrumental role in the health of the host. However, the host factors that facilitate the establishment of the microbial colonization remain unclear. Here, we establish a screening method to identify host factors regulating E. coli colonization in C. elegans. We find that a BCF-1 possessing N-glycosylation promotes E. coli colonization by directly binding to E. coli via its fimbrial protein, YdeR. BCF-1 is activated by the bacteria and interacts with an oligosaccharyl transferase, OSTB-1, which is critical for regulating E. coli colonization. We also show that the N-glycosylation of BCF-1 is critical for E. coli colonization. In addition, we find that the microbiota composition is shaped by BCF-1. In summary, this study shows a “scaffold model” for bacterial colonization between a host glycoprotein and E. coli, and it also introduces a powerful research approach to identify individual host factors involved in modulating bacterial colonization

Stabilization of an enzyme cytochrome c in a metal-organic framework against denaturing organic solvents

Summary: Enzymes are promising catalysts with high selectivity and activity under mild reaction conditions. However, their practical application has largely been hindered by their high cost and poor stability. Metal-organic frameworks (MOFs) as host materials show potential in protecting proteins against denaturing conditions, but a systematic study investigating the stabilizing mechanism is still lacking. In this study, we stabilized enzyme cytochrome c (cyt c) by encapsulating it in a hierarchical mesoporous zirconium-based MOF, NU-1000 against denaturing organic solvents. Cyt c@NU-1000 showed a significantly enhanced activity compared to the native enzyme, and the composite retained this enhanced activity after treatment with five denaturing organic solvents. Moreover, the composite was recyclable without activity loss for at least three cycles. Our cyt c@NU-1000 model system demonstrates that enzyme@MOF composites prepared via post-synthetic encapsulation offer a promising route to overcome the challenges of enzyme stability and recyclability that impede the widespread adoption of biocatalysis