InfoPattern: Unveiling Information Propagation Patterns in Social Media

Social media play a significant role in shaping public opinion and influencing ideological communities through information propagation. Our demo InfoPattern centers on the interplay between language and human ideology. The demo (Code: https://github.com/blender-nlp/InfoPattern ) is capable of: (1) red teaming to simulate adversary responses from opposite ideology communities; (2) stance detection to identify the underlying political sentiments in each message; (3) information propagation graph discovery to reveal the evolution of claims across various communities over time. (Live Demo: https://incas.csl.illinois.edu/blender/About

Video Event Extraction via Tracking Visual States of Arguments

Video event extraction aims to detect salient events from a video and identify the arguments for each event as well as their semantic roles. Existing methods focus on capturing the overall visual scene of each frame, ignoring fine-grained argument-level information. Inspired by the definition of events as changes of states, we propose a novel framework to detect video events by tracking the changes in the visual states of all involved arguments, which are expected to provide the most informative evidence for the extraction of video events. In order to capture the visual state changes of arguments, we decompose them into changes in pixels within objects, displacements of objects, and interactions among multiple arguments. We further propose Object State Embedding, Object Motion-aware Embedding and Argument Interaction Embedding to encode and track these changes respectively. Experiments on various video event extraction tasks demonstrate significant improvements compared to state-of-the-art models. In particular, on verb classification, we achieve 3.49% absolute gains (19.53% relative gains) in F1@5 on Video Situation Recognition

Investigation of the microcrack evolution in a Ti-based bulk metallic glass matrix composite

AbstractThe initiation and evolution behavior of the shear-bands and microcracks in a Ti-based metallic-glass–matrix composite (MGMC) were investigated by using an in-situ tensile test under transmission electron microscopy (TEM). It was found that the plastic deformation of the Ti-based MGMC related with the generation of the plastic deformation zone in crystalline and shear deformation zone in glass phase near the crack tip. The dendrites can suppress the propagation of the shear band effectively. Before the rapid propagation of cracks, the extending of plastic deformation zone and shear deformation zone ahead of crack tip is the main pattern in the composite

Transcriptome and pan-cancer system analysis identify PM2.5-induced stanniocalcin 2 as a potential prognostic and immunological biomarker for cancers

Epidemiological studies have shown that air pollution and particulate matter (PM) are closely related to the occurrence of cancer. However, the potential prognostic and immunological biomarkers for air pollution related cancers are lacking. In this study, we proved PM2.5 exposure was correlated with lung cancer through transcriptome analysis. Importantly, we identified STC2 as a key gene regulated by PM2.5, whose expression in epithelial cells was significantly increased after PM2.5 treatment and validated by using RT-qPCR and immunofluorescence. Kaplan-Meier OS curves suggested that high STC2 expression positively correlated with a poor prognosis in lung cancer. Furthermore, we discovered that STC2 was associated with multiple cancers and pathways in cancer. Next, Pan-Cancer Expression Landscape of STC2 showed that STC2 exhibited inconsistent expression across 26 types of human cancer, lower in KIRP in cancer versus adjacent normal tissues, and significantly higher in another cancers. Cox regression results suggested that STC2 expression was positively or negatively associated with prognosis in different cancers. Moreover, STC2 expression was associated with clinical phenotypes including age, gender, stage and grade. Mutation features of STC2 were also analyzed, in which the highest alteration frequency of STC2 was presented in KIRC with amplification. Meanwhile, the effects of copy number variation (CNV) on STC2 expression were investigated across various tumor types, suggesting that STC2 expression was significantly correlated with CNV in tumors. Additionally, STC2 was closely related to tumor heterogeneity, tumor stemness and tumor immune microenvironment like immune cell infiltration. In the meantime, we analyzed methylation modifications and immunological correlation of STC2. The results demonstrated that STC2 expression positively correlated with most RNA methylation genes and immunomodulators across tumors. Taken together, the findings revealed that PM2.5-induced STC2 might be a potential prognostic and immunological biomarker for cancers related to air pollution

Open Visual Knowledge Extraction via Relation-Oriented Multimodality Model Prompting

Images contain rich relational knowledge that can help machines understand the world. Existing methods on visual knowledge extraction often rely on the pre-defined format (e.g., sub-verb-obj tuples) or vocabulary (e.g., relation types), restricting the expressiveness of the extracted knowledge. In this work, we take a first exploration to a new paradigm of open visual knowledge extraction. To achieve this, we present OpenVik which consists of an open relational region detector to detect regions potentially containing relational knowledge and a visual knowledge generator that generates format-free knowledge by prompting the large multimodality model with the detected region of interest. We also explore two data enhancement techniques for diversifying the generated format-free visual knowledge. Extensive knowledge quality evaluations highlight the correctness and uniqueness of the extracted open visual knowledge by OpenVik. Moreover, integrating our extracted knowledge across various visual reasoning applications shows consistent improvements, indicating the real-world applicability of OpenVik.Comment: Accepted to NeurIPS 202

Aspirin for Primary Prevention of Cardiovascular Events: Meta-Analysis of Randomized Controlled Trials and Subgroup Analysis by Sex and Diabetes Status

Objective: To evaluate the benefits and harms of aspirin for the primary prevention of CVD and determine whether the effects vary by sex and diabetes status. Methods: We searched Medline, Embase, and Cochrane databases for randomized controlled trials comparing the effects of aspirin with placebo or control in people with no pre-existing CVD. Two investigators independently extracted data and assessed the study quality. Analyses were performed using Stata version 12. Results: Fourteen trials (107,686 participants) were eligible. Aspirin was associated with reductions in major cardiovascular events (risk ratio, 0.90; 95% confidence interval, 0.85–0.95), myocardial infarction (0.86; 0.75–0.93), ischemic stroke (0.86; 0.75–0.98) and all-cause mortality (0.94; 0.89–0.99). There were also increases in hemorrhagic stroke (1.34; 1.01–1.79) and major bleeding (1.55; 1.35–1.78) with aspirin. The number needed to treat to prevent 1 major cardiovascular event over a mean follow-up of 6.8 years was 284. By comparison, the numbers needed to harm to cause 1 major bleeding is 299. In subgroup analyses, pooled results demonstrated a reduction in myocardial infarction among men (0.71; 0.59–0.85) and ischemic stroke among women (0.77; 0.63–0.93). Aspirin use was associated with a reduction (0.65; 0.51–0.82) in myocardial infarction among diabetic men. In meta-regression analyses, the results suggested that aspirin therapy might be associated with a decrease in stroke among diabetic women and a decrease in MI among diabetic men and risk reductions achieved with low doses (75 mg/day) were as large as those obtained with higher doses (650 mg/day). Conclusions: The use of low-dose aspirin was beneficial for primary prevention of CVD and the decision regarding an aspirin regimen should be made on an individual patient basis. The effects of aspirin therapy varied by sex and diabetes status. A clear benefit of aspirin in the primary prevention of CVD in people with diabetes needs more trials