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347 results on '"LU Yingjie"'

1. Clinical Efficacy of Da Vinci Robot-assisted Subxiphoid Versus Lateral Thoracic Approach for Treatment of Anterior Mediastinal Tumors

Author

HONG Ziqiang, SHENG Yannan, BAI Xiangdou, CUI Baiqiang, LU Yingjie, WU Xusheng, CHENG Tao, JIN Dacheng, and GOU Yunjiu

Subjects
robot-assisted thoracoscopic surgery, anterior mediastinal tumor, subxiphoid approach, lateral thoracic approach, laryngeal mask anesthesia, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Objective To compare the perioperative efficacy and safety of da Vinci robot-assisted thoracoscopic surgery (RATS) for treatment of anterior mediastinal tumors through subxiphoid versus lateral thoracic approaches under the laryngeal mask anesthesia. Methods We retrospectively analyzed the clinical data of 102 patients with anterior-mediastinal tumors treated by RATS under laryngeal mask anesthesia completed by the same operator. Forty-five patients underwent the subxiphoid approach (subxiphoid group), and 57 patients were treated with the lateral thoracic approach (lateral thoracic group). The operating time, intraoperative bleeding, and total postoperative drainage volume in the two groups were compared and analyzed. Results All patients successfully completed resection of the anterior mediastinal tumor without the occurrence of perioperative death. In terms of total postoperative drainage volume, postoperative drainage time, postoperative hospital stay, and VAS pain on postoperative days 2 and 3, the subxiphoid group was more advantages (P < 0.05). No statistically significant difference was found between the two groups in terms of operative time, docking time, total operative time, intraoperative bleeding volume, postoperative day 1 VAS pain score, or postoperative complications (P > 0.05). Conclusion The subxiphoid approach of RATS is safe and feasible for resection of anterior mediastinal tumors. Compared with the lateral thoracic approach, the subxiphoid approach has advantages in terms of rapid postoperative recovery and postoperative pain.

Published
2023
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2. Attack Anything: Blind DNNs via Universal Background Adversarial Attack

Author

Lian, Jiawei, Mei, Shaohui, Wang, Xiaofei, Wang, Yi, Wang, Lefan, Lu, Yingjie, Ma, Mingyang, and Chau, Lap-Pui

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Cryptography and Security, Computer Science - Machine Learning
Abstract

It has been widely substantiated that deep neural networks (DNNs) are susceptible and vulnerable to adversarial perturbations. Existing studies mainly focus on performing attacks by corrupting targeted objects (physical attack) or images (digital attack), which is intuitively acceptable and understandable in terms of the attack's effectiveness. In contrast, our focus lies in conducting background adversarial attacks in both digital and physical domains, without causing any disruptions to the targeted objects themselves. Specifically, an effective background adversarial attack framework is proposed to attack anything, by which the attack efficacy generalizes well between diverse objects, models, and tasks. Technically, we approach the background adversarial attack as an iterative optimization problem, analogous to the process of DNN learning. Besides, we offer a theoretical demonstration of its convergence under a set of mild but sufficient conditions. To strengthen the attack efficacy and transferability, we propose a new ensemble strategy tailored for adversarial perturbations and introduce an improved smooth constraint for the seamless connection of integrated perturbations. We conduct comprehensive and rigorous experiments in both digital and physical domains across various objects, models, and tasks, demonstrating the effectiveness of attacking anything of the proposed method. The findings of this research substantiate the significant discrepancy between human and machine vision on the value of background variations, which play a far more critical role than previously recognized, necessitating a reevaluation of the robustness and reliability of DNNs. The code will be publicly available at https://github.com/JiaweiLian/Attack_Anything

Published
2024

5. Air cold atmospheric plasma with patterns for anaplastic squamous cell carcinoma treatment

Author

Bai, Fan, Lu, Yingjie, Zhi, Yujie, Huang, Yueye, Li, Long, Luo, Jiaoxiao, Razzokov, Jamoliddin, Koval, Olga, Yusupov, Maksudbek, Chen, Guojun, and Chen, Zhitong

Subjects
Physics - Medical Physics, Physics - Biological Physics
Abstract

In recent years, cold atmospheric plasma (CAP) using inert gas has been successfully applied for biomedicine, such as sterilization, wound healing, skin diseases, and tumor treatment. Here, we reported air cold atmospheric plasma with three different patterns (I. Non: basic square grid structure; II. Square: basic square grid structure + square node; III. Circle: basic square grid structure + circle node) for anaplastic squamous cell carcinoma treatment (VX2 cell line). Various plasma diagnostic techniques were applied to evaluate the physics of air CAP with patterns such as discharge voltage, plasma initial generating process, plasma temperature, and optical emission spectroscopy (OES). The direct effects of air CAP with patterns on anaplastic squamous cell carcinoma treatment (VX2 cell line) were investigated in vitro. We also studied the ROS (reactive oxygen species) and RNS (reactive nitrogen species) generation in cultured media released from VX2 cells after the treatment of air CAP with patterns. The results showed that the air CAP with circle-pattern generated more active substances during at 60s treatment time, which resulted in a higher death rate of VX2 cells. These initial observations establish the air CAP with patterns as potential clinical applications for cancer therapy.

Published
2023

30. High-Switching-Frequency SiC Power Conversion Systems with Improved Finite Control Set Method Prediction Control.

Author

Fan, Yibiao, Tong, Lixia, Lu, Yingjie, Cai, Xiaowei, Fu, Zhihe, and Mao, Xingkui

Subjects
VECTOR spaces, HIGH voltages, COMPUTATIONAL complexity, CAPACITORS, TOPOLOGY, ELECTRIC inverters
Abstract

With the development of power conversion systems or bidirectional grid-connected inverters characterized by high DC voltage, high efficiency, and high-power density, high-switching-frequency SiC power switches are being widely used, and these require a short computational time of control algorithm. Based on the sector judgment of a space voltage vector and the midpoint potential control balancing of a DC bus, an improved finite control set method prediction control (FCS-MPC) method was proposed for a T-type three-level PCS. This improved FCS-MPC first judges the sector of the space voltage vector and locates the position of the corresponding large sector according to phase lock information; then, it analyzes the sampled voltage of the upper and lower bus capacitors to obtain the midpoint potential situation and selects appropriate small vectors based on the midpoint potential situation. This simple improved strategy can reduce the computational complexity of traditional MPC for rolling optimization, resulting in a reduction in the vectors from 27 to 8. A SiC-based 10 kW bidirectional PCS prototype verified the improved FCS-MPC, and the computational time was reduced about by 56% in comparison to traditional FCS-MPC. [ABSTRACT FROM AUTHOR]

Published
2024
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45. Retuning Mitochondrial Apoptosis/Mitophagy Balance via SIRT3‐Energized and Microenvironment‐Modulated Hydrogel Microspheres to Impede Osteoarthritis

Author

Xia, Xiaowei, primary, Liu, Yang, additional, Lu, Yingjie, additional, Liu, Junlin, additional, Deng, Yaoge, additional, Wu, Yubin, additional, Hou, Mingzhuang, additional, He, Fan, additional, Yang, Huilin, additional, Xu, Yong, additional, Zhang, Yijian, additional, and Zhu, Xuesong, additional

Published
2023
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