A5100764999- Integrated Circuits and Semiconductor Failure Analysis
- Lipid metabolism and biosynthesis
- Physical Unclonable Functions (PUFs) and Hardware Security
- Statistical Methods and Inference
- Adversarial Robustness in Machine Learning
- Fault Detection and Control Systems
- Control Systems and Identification
- Cancer-related molecular mechanisms research
- Electromagnetic Simulation and Numerical Methods
- Circular RNAs in diseases
- Gene expression and cancer classification
- Advanced Malware Detection Techniques
- Transition Metal Oxide Nanomaterials
- Microbial Metabolic Engineering and Bioproduction
- Numerical methods in inverse problems
- Neural Networks and Applications
- Numerical methods for differential equations
- Advancements in Battery Materials
- Advanced Vision and Imaging
- Dyeing and Modifying Textile Fibers
- Machine Learning and ELM
- Wireless Communication Security Techniques
- Electrostatic Discharge in Electronics
- Digital Imaging for Blood Diseases
- Stochastic Gradient Optimization Techniques
Huazhong Agricultural University
2022-2025
China Special Equipment Inspection and Research Institute
2025
Capital University of Physical Education and Sports
2016-2024
Huadong Hospital
2023
Fudan University
2023
Shanghai University
2023
Tongren Hospital
2023
Technical Institute of Physics and Chemistry
2022-2023
Chinese Academy of Sciences
2022-2023
Soochow University
2023
Trojans represent a severe threat to hardware security and trust. This work investigates the Trojan detection problem from unique viewpoint proposes novel localization method targeting FPGA netlists. The proposed automatically extracts rich structural behavioral features at look-up-table (LUT) level train an explainable graph neural network (GNN) model for classifying design nodes in netlists identifying Trojan-infected ones. Experimental results using 183 benchmarks show that our...
This paper proposes a high-precision filtering scheme for standard bottle calibration pressure based on Transformer model feature extraction and Kalman methods, which is used to analyze the data of over time. Firstly, employed as extractor transform sequence time into high-dimensional vectors, thereby capturing rich semantic information input data. Then, filter designed, using vectors extracted by observation values, combined with state transition equations estimate these vectors. By...
Lipid droplets (LDs) are the main fat storing sites in almost all species from bacteria to humans. The perilipin family has been found as LD proteins mammals, Drosophila, and a couple of slime molds, but no bacterial containing sequence conservation were identified. In this study, we reported that hydroxysteroid dehydrogenase (HSD) was on LDs across organisms by proteomic analysis. Imaging experiments confirmed targeting three representative HSD including ro01416 RHA1, DHS-3 C. elegans,...
An efficient and scalable strategy has been developed for the synthesis of Ag nanoparticles anchored on β-AgVO3 nanobelts via a template-free hydrothermal reaction. The Ag/β-AgVO3 demonstrate enhanced lithium intercalation capacity, rate capability cyclic stability.
A carboxylesterase gene from thermophilic bacterium, Alicyclobacillus tengchongensis, was cloned and expressed in Escherichia coli BL21 (DE3). The coded for a 513 amino acid protein with calculated molecular mass of 57.82 kDa. deduced sequence had structural features highly conserved among serine hydrolases, including Ser204, Glu325, His415 as catalytic triad, well type-B active site (FGGDPENITIGGQSAG) signature 2 (EDCLYLNIWTP). purified enzyme exhibited optimum activity β-naphthyl acetate...
This work proposes a novel hardware Trojan detection method that leverages static structural features and behavioral characteristics in field programmable gate array (FPGA) netlists. Mapping of design sources to look-up-table (LUT) networks makes these explicit, allowing automated feature extraction further effective through machine learning. Four-dimensional are extracted for each signal random forest classifier is trained net classification. Experiments using Trust-Hub benchmarks show...
Abstract In this study, we developed a complex polyphenol‐metal ion system, in which two polyphenols represented by gallic acid (GA) and tannic (TA) chelated with metal ions leading to the formation of pigments composed metal‐phenol networks (MPN). The doping GA TA creates mutual synergistic effect, makes it chelate produce more structure MPN, finally obtain colorful MPN pigments. can be easily deposited on hair surface through covalent non‐covalent interactions, resulting series dyeing...
Background and Objective: The public's safety has been significantly jeopardized by the pandemic of COVID-19, which is brought on highly virulent contagious SARS-CoV-2 virus. Finding novel antiviral drugs currently utmost importance for treatment patients with COVID-19. Main protease (3CLpro) involved in replication virus, so it considered as a promising target. Using small molecules to inhibit SARS-CoV-2-3CLpro activity may be an effective way prevent viral fight Despite fact that some...
The traditional 3d reconstruction method of stereo vision is based on image feature point extraction, but it very inconvenient to extract points in more complex cases, and the reconstructed 3D information not comprehensive. In this paper, a three-frequency heterodyne four-step phase shift proposed. System parameters obtained by binocular calibration algorithm first, then using digital grating projector object under test three groups different frequency fringe collecting images, four step...
Given the incomplete knowledge of classes that exist in world, Open-set Recognition (OSR) enables networks to identify and reject unseen after training. This problem breaking common closed-set assumption is far from being solved. Recent studies focus on designing new losses, neural network encoding structures, calibration methods optimize a feature space for OSR relevant tasks. In this work, we make first attempt tackle by searching architecture Neural Network (NN) under open-set assumption....
Stochastic bilevel optimization (SBO) has been integrated into many machine learning paradigms recently including hyperparameter optimization, meta learning, reinforcement etc. Along with the wide range of applications, there have abundant studies on concerning computing behaviors SBO. However, generalization guarantees SBO methods are far less understood from lens statistical theory. In this paper, we provide a systematical analysis first-order gradient-based methods. Firstly, establish...