Anatomy of the right atrial appendage and its importance in clinical practice

The right atrial appendage is an important anatomical marker of the right heart. With the developments in cardiology, more attention has been paid to the right atrial appendage. This article summarizes the progress in research regarding the right atrial appendage anatomy and its clinical value, to collate and augment the relevant data. The shape of the right atrial appendage differs from the left atrial appendage: its outer surface is relatively flat and its internal structure comprises a terminal crest and musculi pectinati. In clinical interventional therapy, the right atrial appendage is often used as the electrode implantation site. The thickness of the musculi pectinati and the wall thickness of the right atrial appendage are closely related to the outcomes in atrial lead implantation. In terms of atrial fibrillation, wherein thrombi formation is frequent, the right atrial appendage is one of the predilection sites of thrombosis. However, the incidence of thrombosis in the right atrial appendage is lower than that in the left atrial appendage. Familiarity with the anatomy of the right atrial appendage is of prime importance in atrial lead implantation, and the role of the right atrial appendage in atrial fibrillation requires further investigation

Uncover the Premeditated Attacks: Detecting Exploitable Reentrancy Vulnerabilities by Identifying Attacker Contracts

Reentrancy, a notorious vulnerability in smart contracts, has led to millions of dollars in financial loss. However, current smart contract vulnerability detection tools suffer from a high false positive rate in identifying contracts with reentrancy vulnerabilities. Moreover, only a small portion of the detected reentrant contracts can actually be exploited by hackers, making these tools less effective in securing the Ethereum ecosystem in practice. In this paper, we propose BlockWatchdog, a tool that focuses on detecting reentrancy vulnerabilities by identifying attacker contracts. These attacker contracts are deployed by hackers to exploit vulnerable contracts automatically. By focusing on attacker contracts, BlockWatchdog effectively detects truly exploitable reentrancy vulnerabilities by identifying reentrant call flow. Additionally, BlockWatchdog is capable of detecting new types of reentrancy vulnerabilities caused by poor designs when using ERC tokens or user-defined interfaces, which cannot be detected by current rule-based tools. We implement BlockWatchdog using cross-contract static dataflow techniques based on attack logic obtained from an empirical study that analyzes attacker contracts from 281 attack incidents. BlockWatchdog is evaluated on 421,889 Ethereum contract bytecodes and identifies 113 attacker contracts that target 159 victim contracts, leading to the theft of Ether and tokens valued at approximately 908.6 million USD. Notably, only 18 of the identified 159 victim contracts can be reported by current reentrancy detection tools.Comment: Accepted by ICSE 202

A Cascade-Based Emergency Model for Water Distribution Network

Water distribution network is important in the critical physical infrastructure systems. The paper studies the emergency resource strategies on water distribution network with the approach of complex network and cascading failures. The model of cascade-based emergency for water distribution network is built. The cascade-based model considers the network topology analysis and hydraulic analysis to provide a more realistic result. A load redistribution function with emergency recovery mechanisms is established. From the aspects of uniform distribution, node betweenness, and node pressure, six recovery strategies are given to reflect the network topology and the failure information, respectively. The recovery strategies are evaluated with the complex network indicators to describe the failure scale and failure velocity. The proposed method is applied by an illustrative example. The results showed that the recovery strategy considering the node pressure can enhance the network robustness effectively. Besides, this strategy can reduce the failure nodes and generate the least failure nodes per time

Study on an elastic lever system for electromagnetic energy harvesting from rail vibration

Energy harvesting from rail vibration is a promising approach to solve the power supply problem in remote and off-grid areas. The major issue of current energy harvesting techniques and devices is the limited power generating capacity. In this paper, the authors put forward an elastic lever system to enhance the performance of an electromagnetic energy harvester. A vehicle-track coupling dynamics model is established to simulate the service condition of the energy harvester. The Power Amplification Factor (PAF), which is defined as the ratio between the output power with and without a lever system, is introduced to quantify the Enhanced Energy Harvester (EEH). It is found that the PAF can be greater than n2 with a leverage ratio of n. Simulation shows that the output power can be magnified by 430 times with an elastic lever system with a leverage ratio of 10. The amplification effect of the output power comes from two aspects, one is the magnifying effect of leverage itself and the other is the resonance effect. Additionally, it is found that a single EEH will increase the wheel-rail contact force slightly, which indicates the EEH is impractical for use as an approach for rail vibration reduction. Nevertheless, it will not have a significant negative effect on rail vibration

A Cascade-Based Emergency Model for Water Distribution Network

Water distribution network is important in the critical physical infrastructure systems. The paper studies the emergency resource strategies on water distribution network with the approach of complex network and cascading failures. The model of cascade-based emergency for water distribution network is built. The cascade-based model considers the network topology analysis and hydraulic analysis to provide a more realistic result. A load redistribution function with emergency recovery mechanisms is established. From the aspects of uniform distribution, node betweenness, and node pressure, six recovery strategies are given to reflect the network topology and the failure information, respectively. The recovery strategies are evaluated with the complex network indicators to describe the failure scale and failure velocity. The proposed method is applied by an illustrative example. The results showed that the recovery strategy considering the node pressure can enhance the network robustness effectively. Besides, this strategy can reduce the failure nodes and generate the least failure nodes per time

Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling

Diffusion models excel at generating photo-realistic images but come with significant computational costs in both training and sampling. While various techniques address these computational challenges, a less-explored issue is designing an efficient and adaptable network backbone for iterative refinement. Current options like U-Net and Vision Transformer often rely on resource-intensive deep networks and lack the flexibility needed for generating images at variable resolutions or with a smaller network than used in training. This study introduces LEGO bricks, which seamlessly integrate Local-feature Enrichment and Global-content Orchestration. These bricks can be stacked to create a test-time reconfigurable diffusion backbone, allowing selective skipping of bricks to reduce sampling costs and generate higher-resolution images than the training data. LEGO bricks enrich local regions with an MLP and transform them using a Transformer block while maintaining a consistent full-resolution image across all bricks. Experimental results demonstrate that LEGO bricks enhance training efficiency, expedite convergence, and facilitate variable-resolution image generation while maintaining strong generative performance. Moreover, LEGO significantly reduces sampling time compared to other methods, establishing it as a valuable enhancement for diffusion models

Experimental investigation of kinetic instabilities driven by runaway electrons in the EXL-50 spherical torus

In this study, the first observation of high-frequency instabilities driven by runaway electrons has been reported in the EXL-50 spherical torus using a high-frequency magnetic pickup coil. The central frequency of these instabilities is found to be exponentially dependent on the plasma density, similar to the dispersion relation of the whistler wave. The instability frequency displays chirping characteristics consistent with the Berk-Breizman model of beam instability. Theoretically, the excitation threshold of the instability driven by runaway electrons is related to the ratio of the runaway electron density to the background plasma density, and such a relationship is first demonstrated experimentally in this study. The instability can be stabilized by increasing the plasma density, consistent with the wave-particle resonance mechanism. This investigation demonstrates the controlled excitation of chirping instabilities in a tokamak plasma and reveals new features of these instabilities, thereby advancing the understanding of the mechanisms for controlling and mitigating runaway electrons

Evaluation of the laser-induced thermotherapy treatment effect of breast cancer based on tissue viscoelastic properties

Photothermal therapy (PTT) has been emerging as an effective, minimally invasive approach to treat cancers. However, a method to quantitatively evaluate the treatment effect after laser-induced thermotherapy (LITT) is needed. In this study, we used 808 nm laser radiation with three different power densities to treat the breast cancer tissue from 4T1 cell lines in a mouse model. The viscoelastic properties of the treated cancer tissues were characterized by a two-term Prony series using a ramp-hold indentation method. We observed that instantaneous shear modulus G0 was significantly higher for the treated cancer tissues than that of the untreated tissue when treated with a power density of 1.5 W/cm2, but significantly lower with a power density of 2.5 W/cm2. The long-term shear modulus G∞ was also significantly higher for the cancer tissue at 1.5 W/cm2, compared to the untreated tissue. The treatment effects were verified by estimating the cell apoptosis rate using terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL). Our results indicate that the viscoelastic properties of the tissue could potentially be used as biomarkers for evaluating the LITT treatment effect. In addition, we also observed a strain-independent behavior of the treated cancer tissue, which provided useful information for applying in vivo imaging method such as magnetic resonance elastography (MRE) for treatment evaluation based on biomechanical properties

Observation of whistler wave instability driven by temperature anisotropy of energetic electrons on EXL-50 spherical torus

Electromagnetic modes in the frequency range of 30-120MHz were observed in electron cyclotron wave (ECW) steady state plasmas on the ENN XuanLong-50 (EXL-50) spherical torus. These modes were found to have multiple bands of frequencies proportional to the Alfv\'en velocity. This indicates that the observed mode frequencies satisfy the dispersion relation of whistler waves. In addition, suppression of the whistler waves by the synergistic effect of Lower Hybrid Wave (LHW) and ECW was also observed. This suggests that the whistler waves were driven by temperature anisotropy of energetic electrons. These are the first such observations (not runaway discharge) made in magnetically confined toroidal plasmas and may have important implications for studying wave-particle interactions, RF wave current driver, and runaway electron control in future fusion devices