A5046442547- Space Satellite Systems and Control
- Energy, Environment, Economic Growth
- Advanced Authentication Protocols Security
- Physical Unclonable Functions (PUFs) and Hardware Security
- Climate Change Policy and Economics
- IoT and Edge/Fog Computing
- Advanced SAR Imaging Techniques
- Library Science and Information
- Peptidase Inhibition and Analysis
- Gaze Tracking and Assistive Technology
- Boron and Carbon Nanomaterials Research
- Dynamics and Control of Mechanical Systems
- Internet Traffic Analysis and Secure E-voting
- Video Surveillance and Tracking Methods
- Control and Stability of Dynamical Systems
- Fatty Acid Research and Health
- Hepatitis B Virus Studies
- Silk-based biomaterials and applications
- Computer Science and Engineering
- Multiple Myeloma Research and Treatments
- Liver Disease Diagnosis and Treatment
- Micro and Nano Robotics
- Advanced Technologies in Various Fields
- Target Tracking and Data Fusion in Sensor Networks
- Wnt/β-catenin signaling in development and cancer
Northwestern Polytechnical University
2024-2025
Innovation Team (China)
2025
Xi'an Jiaotong University
2024
Dalian University of Technology
2023-2024
Chongqing University of Posts and Telecommunications
2022-2023
Shandong University of Traditional Chinese Medicine
2023
Hebei Medical University
2023
Zunyi Medical University
2014-2022
State Grid Corporation of China (China)
2022
Yunnan University
2010
This work focuses on the safety of learning-based control for unknown nonlinear system, considering stability learned dynamics and modeling mismatch between true one. A scheme imposing constraint is proposed in this stable system. Specifically, a linear representation established using Koopman theory. Then, deep learning approach utilized to approximate embedding functions operator For safe manipulation real-world applications, Lipschitz are considered model prediction control. Moreover,...
The objective of this study is to investigate pharmacokinetics gelatin sponge microparticles (GSMs) combined with epirubicin in a rabbit VX2 liver tumor model hepatic arterial chemoembolization (TACE). Eighteen successful models New Zealand white rabbits was established, which were divided into three groups randomly: HAI group (n = 6), the solution (epirubicin 10 mg mixed saline ml artery); GSMs-TACE GSMs (20 mg) (1 mg/ml); c-TACE (10 lipiodol ml). Each administrated at dose adjusted for 1...
Due to the heterogeneity of hepatocellular carcinoma (HCC), hepatocelluarin-associated differentially expressed genes were analyzed by bioinformatics methods screen molecular markers for HCC prognosis and potential targets immunotherapy.RNA-seq data clinical follow-up downloaded from The Cancer Genome Atlas (TCGA) database. Multivariate Cox analysis Lasso regression used identify robust immunity-related genes. Finally, a risk model immune gene pairs was established verified features, test...
Hepatocellular carcinoma associated with chronic hepatitis B virus infection seriously affects human health. Present studies suggest that genetic susceptibility plays an important role in the mechanism of cancer development. Therefore, this study focused on single nucleotide polymorphisms (SNPs) MMR genes HBV-HCC. Five groups participants were included study, which healthy control group (HC), spontaneous clearance (SC), (CHB), HBV-related liver cirrhosis (LC) and hepatocellular (HBV-HCC). A...
Signet ring cell carcinoma (SRCC) is a specific type of mucinous secretory adenocarcinoma, which contains abundant mucus in the cytoplasm and pushes nucleus to one side membrane, forming round or oval, nuclear deviations give cells signet ring-like appearance. SRCC often originates gastrointestinal tract, especially stomach. However, primary extrahepatic bile duct extremely rare. Therefore, little known about its epidemiology, treatment, prognosis.An 82-year-old female was admitted with...
Car detection is an important task that serves as a crucial prerequisite for many automated driving functions. The large variations in lighting/weather conditions and vehicle densities of the scenes pose significant challenges to existing car algorithms meet highly accurate perception demand safety, due unstable/limited color information, which impedes extraction meaningful/discriminative features cars. In this work, we present novel learning-based method leverages trichromatic linear...
Car detection is an important task that serves as a crucial prerequisite for many automated driving functions. The large variations in lighting/weather conditions and vehicle densities of the scenes pose significant challenges to existing car algorithms meet highly accurate perception demand safety, due unstable/limited color information, which impedes extraction meaningful/discriminative features cars. In this work, we present novel learning-based method leverages trichromatic linear...
In the context of dual-carbon goal, improving level scientific and technological innovation modern carbon emissions achieving comprehensive green development are not only one trends important reform directions today’s world development, but also core content sustainable development. Taking power industry as an breakthrough, this paper uses blockchain technology privacy computing to integrate data from government, grid, taxation banks, proposes a blockchain-based algorithm for emission scores...
Aerial robotics for transporting suspended payloads as the form of freely-floating manipulator are growing great interest in recent years. However, prior information payload, such mass, is always hard to obtain accurately practice. The force/torque caused by payload and residual dynamics will introduce unmodeled perturbations system, which negatively affects closed-loop performance. Different from estimation-like methods, this paper proposes Neural Predictor, a learning-based approach model...
Abstract As an emerging trading mechanism, the carbon market has been widely promoted and paid attention to. On basis of analyzing current status emission in my country’s pilot cities, this paper considers 12 risk evaluation indicators from four dimensions external risk, transaction operational management uses entropy weight-TOPSIS method to establish a city emissions. Market model, select Guangzhou carry out empirical analysis. The results show that greater impact on corresponding should be...
To avoid complex constraints of the traditional nonlinear method for tethered space robot (TSR) deployment, this paper proposes a data-driven optimal control framework with an improved deep learning based Koopman operator that could be applied to environments. In consideration TSR's nonlinearity, its finite dimensional lifted representation is derived state-dependent only embedding functions in framework. A approach adopted approximate global linear TSR. Deep neural networks (DNN) are...