Characteristics, Incidence, and Management of Immune Checkpoint Inhibitors Related Cardiovascular Adverse Events in Real-World Practice-A Retrospective Study in Chinese Han Population.

Purpose: This study aimed to elaborate on the incidence, clinical features, and management of immune checkpoint inhibitors (ICIs) related cardiovascular adverse events (CVAEs) in real-world practice.

Patients And Methods: We performed a retrospective chart review study on patients receiving at least one dose of ICI therapy at a Chinese tertiary hospital from March 2020 to March 2021. CVAEs were identified through clinical assessment and the Naranjo algorithm.

Image Forensics in the Encrypted Domain.

Encryption techniques used by forgers have thrown out a big possible challenge to forensics. Most traditional forensic tools will fail to detect the forged multimedia, which has been encrypted. Thus, image forensics in the encrypted domain (IFED) is significant.

Research on a Critical Link Discovery Method for Network Security Situational Awareness.

Network security situational awareness (NSSA) aims to capture, understand, and display security elements in large-scale network environments in order to predict security trends in the relevant network environment. With the internet's increasingly large scale, increasingly complex structure, and gradual diversification of components, the traditional single-layer network topology model can no longer meet the needs of network security analysis. Therefore, we conduct research based on a multi-layer network model for network security situational awareness, which is characterized by the three-layer network structure of a physical device network, a business application network, and a user role network.

End-to-End Network Intrusion Detection Based on Contrastive Learning.

The network intrusion detection system (NIDS) plays a crucial role as a security measure in addressing the increasing number of network threats. The majority of current research relies on feature-ready datasets that heavily depend on feature engineering. Conversely, the increasing complexity of network traffic and the ongoing evolution of attack techniques lead to a diminishing distinction between benign and malicious network behaviors.

Synthesis and Thermoreversible Gelation of Coil-Rod Copolymers with a Dendritic Polyethylene Core and Multiple Helical Poly(γ-benzyl-L-glutamate) Arms.

Coil-rod copolymers with a dendritic polyethylene (DPE) core and multiple helical poly(γ-benzyl-L-glutamate) (PBLG) arms (DPE-(PBLG)) were prepared by palladium-catalyzed copolymerization in tandem with ring-opening polymerization (ROP). Macroinitiator (DPE-(NH)) was firstly prepared by the group transformation of DPE-(OH) generated from palladium-catalyzed copolymerization of ethylene and acrylate comonomer. Coil-helical DPE-(PBLG) copolymers were prepared by ROP of γ-benzyl-L-glutamate-N-carboxyanhydride (BLG-NCA).

An Internet-Oriented Multilayer Network Model Characterization and Robustness Analysis Method.

The Internet creates multidimensional and complex relationships in terms of the composition, application and mapping of social users. Most of the previous related research has focused on the single-layer topology of physical device networks but ignored the study of service access relationships and the social structure of users on the Internet. Here, we propose a composite framework to understand how the interaction between the physical devices network, business application network, and user role network affects the robustness of the entire Internet.

Robust secret image sharing scheme resistance to maliciously tampered shadows by AMBTC and quantization.

For (k, n)-threshold secret image sharing (SIS) scheme, only k or more than k complete parts can recover the secret information, and the correct image cannot be obtained if the count of shadow images is not enough or the shadow images are damaged. The existing schemes are weak in resisting large-area shadow image tampering. In this paper, we propose a robust secret image sharing scheme resisting to maliciously tampered shadow images by Absolute Moment Block Truncation Coding (AMBTC) and quantization (RSIS-AQ).

Link importance assessment strategy based on improved k-core decomposition in complex networks.

Improving the effectiveness of target link importance assessment strategy has become an important research direction within the field of complex networks today. The reasearch shows that the link importance assessment strategy based on betweenness centrality is the current optimal solution, but its high computational complexity makes it difficult to meet the application requirements of large-scale networks. The k-core decomposition method, as a theoretical tool that can effectively analyze and characterize the topological properties of complex networks and systems, has been introduced to facilitate the generation of link importance assessment strategy and, based on this, a link importance assessment indicator link shell has been developed.

MTS-Stega: Linguistic Steganography Based on Multi-Time-Step.

Generative linguistic steganography encodes candidate words with conditional probability when generating text by language model, and then, it selects the corresponding candidate words to output according to the confidential message to be embedded, thereby generating steganographic text. The encoding techniques currently used in generative text steganography fall into two categories: fixed-length coding and variable-length coding. Because of the simplicity of coding and decoding and the small computational overhead, fixed-length coding is more suitable for resource-constrained environments.

Wet Paper Coding-Based Deep Neural Network Watermarking.

In recent years, the wide application of deep neural network models has brought serious risks of intellectual property rights infringement. Embedding a watermark in a network model is an effective solution to protect intellectual property rights. Although researchers have proposed schemes to add watermarks to models, they cannot prevent attackers from adding and overwriting original information, and embedding rates cannot be quantified.

Vulnerability-oriented directed fuzzing for binary programs.

Directed greybox fuzzing (DGF) is an effective method to detect vulnerabilities of the specified target code. Nevertheless, there are three main issues in the existing DGFs. First, the target vulnerable code of the DGFs needs to be manually selected, which is tedious.

PBDiff: Neural network based program-wide diffing method for binaries.

Program-wide binary code diffing is widely used in the binary analysis field, such as vulnerability detection. Mature tools, including BinDiff and TurboDiff, make program-wide diffing using rigorous comparison basis that varies across versions, optimization levels and architectures, leading to a relatively inaccurate comparison result. In this paper, we propose a program-wide binary diffing method based on neural network model that can make diffing across versions, optimization levels and architectures.

AMBTC-based visual secret sharing with different meaningful shadows.

Secret sharing based on Absolute Moment Block Truncation Coding (AMBTC) has been widely studied. However, the management of stego images is inconvenient as they seem indistinguishable. Moreover, there exists a problem of pixel expansion, which requires more storage space and higher transmission bandwidth.

Implications from China patient safety incidents reporting system.

Objective: We aimed to explain the operational mechanism of China National Patient Safety Incidents Reporting System, analyze patterns and trends of incidents reporting, and discuss the implication of the incidents reporting to improve hospital patient safety.

Design: A nationwide, registry-based, observational study design.

Data Source: The database of China National Patient Safety Incidents Reporting System.

[Canopy interception of sub-alpine dark coniferous communities in western Sichuan, China].

Based on field measurements of throughfall and stemflow in combination with climatic data collected from the meteorological station adjacent to the studied sub-alpine dark coniferous forest in Wolong, Sichuan Province, canopy interception of sub-alpine dark coniferous forests was analyzed and modeled at both stand scale and catchment scale. The results showed that monthly interception rate of Fargesia nitida, Bashania fangiana--Abies faxoniana old-growth ranged from 33% Grass to 72%, with the average of 48%. In growing season, there was a linear or powerful or exponential relationship between rainfall and interception an.