Event co-occurrences have been proved effective for event extraction (EE) in previous studies, but not considered argument (EAE) recently. In this paper, we try to fill gap between EE research and EAE research, by highlighting the question that “Can models learn better when being aware of co-occurrences?”. To answer question, reformulate as a problem table generation extend SOTA prompt-based model into non-autoregressive framework, called TabEAE, which is able extract arguments multiple...

Social comparison, especially upward social has always been a common concern and experience in people's lives. Although comparison its consequences have extensively studied previous literature, few scholars paid attention to influencing mechanism boundary conditions on the compensatory consumption of variety-seeking. This study used experimental methods investigate whether is related variety-seeking behavior, explore mediating role lack perceived control moderating self-reflection. In total,...

Visual Language Models (VLMs) have emerged as pivotal tools for robotic systems, enabling cross-task generalization, dynamic environmental interaction, and long-horizon planning through multimodal perception semantic reasoning. However, existing open-source VLMs predominantly trained generic vision-language alignment tasks fail to model temporally correlated action semantics that are crucial manipulation effectively. While current image-based fine-tuning methods partially adapt applications,...

Entity Set Expansion (ESE) is a promising task which aims to expand entities of the target semantic class described by small seed entity set. Various NLP and IR applications will benefit from ESE due its ability discover knowledge. Although previous methods have achieved great progress, most them still lack handle hard negative (i.e., that are difficult distinguish entities), since two may or not belong same based on different granularity levels we analyze on. To address this challenge,...

In the Internet of Vehicles (IoV), vehicle terminal and user information collection are main data sources. But sharing these can easily violate personal privacy security. To solve this problem, in paper we propose a secure proxy re-encryption (PRE) scheme, which uses identity-based broadcast encryption to provide fine-grained control, while ensuring preventing leakage. The proposed called plus (PIB-PRE+), has non-transferability non-transitivity ensure security ciphertext. PIB-PRE+ also...

Recently, joint recognition of flat, nested and discontinuous entities has received increasing attention. Motivated by the observation that target output NER is essentially a set sequences, we propose novel entity generation framework for general scenes in this paper. Different from sequence-to-sequence methods, our method does not force to be generated predefined order can get rid problem error propagation inefficient decoding. Distinguished set-prediction framework, treats each as sequence...

Although the performance of unmanned aerial vehicle (UAV) tracking has benefited from successful application discriminative correlation filters (DCF) and convolutional neural networks (CNNs), UAV under occlusion deformation remains a challenge. The main dilemma is that challenging scenes, such as or deformation, are very complex changeable, making it difficult to obtain training data covering all situations, resulting in trained may be confused by new contexts differ historical information....

The 2D MoS 2 /ReS and ReS /MoS vertical heterostructures have been synthesized via the one-step CVD method by alternatively choosing different Re-based precursors.

Abstract The adenosine concentration and forkhead box protein (Foxp3) expression in T regulatory cells (T regs ) are increased during sepsis. However, the mechanism by which induces Foxp3 is incompletely understood. A cecal ligation puncture (CLP) model was constructed using C57BL/J mice. plasma splenic were consistently for 15 days after sepsis onset. Analysis of mean fluorescence intensity same mice revealed a linear correlation. In CLP model, 2a receptor (A2aR) blockade inhibited . vitro...

Two-dimensional (2D) bilayer transition-metal dichalcogenide (TMD) vertical homostructures with tunable twist angles in the range of 0–60° have been intensively studied owing to twist-angle-dependent novel optical properties, offering new opportunities for design optoelectronic devices. However, trilayer TMD two twisted interfaces can create more freedom modulate physical and direct chemical vapor deposition (CVD) growth such unique structures has rarely reported. Here, we present a...

Increasingly, cyber aggression becomes the prevalent phenomenon that erodes social media environment. However, due to subjective and expense, traditional self-reporting questionnaire is hard be employed in current area. In this study, we put forward prediction model for based on cutting-edge deep learning algorithm. Building 320 active Weibo users' activities, construct basic, dynamic, content features. We elaborate three dimensions: exclusion, malicious humour, guilt induction. then build...

Indirect aggression has become a prevalent phenomenon that erodes the social media environment. Due to expense and difficulty in determining objectively what constitutes indirect aggression, traditional self-reporting questionnaire is hard be employed current cyber area. In this study, we present model for predicting online based on pre-trained models. Building Weibo users' activities, constructed basic, dynamic, content features classified into three subtypes: exclusion, malicious humour,...

To investigate the effects of oxygen concentration and reactive species (ROS) on biological characteristics hematopoietic stem cells (HSC) to analyzed relationship among concentration, ROS mouse HSC through simulation environment experienced by PB during transplantation.The detection (ROS), in vitro amplification, directional differentiation (BFU-E, CFU-GM, CFU-Mix), homing adhesion molecules (CXCR4, CD44, VLA4, VLA5, P-selectin), migration rate, CFU-S NOD/SCID mice irradiated with sublethal...

Existing supervised Convolutional Neural Network (CNN) approaches for cervical cytology image analysis generally rely on the heavy manual annotation each cell or mass and thus lead to extensive time effort. In this paper, we propose a global-local network weakly region of interest (ROI) analysis. It aims perform classification ROIs further classify cells only with ROI labels. Specifically, proposed method firstly detects within extracts CNN features cells. Then attention-based bidirectional...

This article has been retracted by the publisher.