A5023401286- Anomaly Detection Techniques and Applications
- Fault Detection and Control Systems
- Time Series Analysis and Forecasting
- Data-Driven Disease Surveillance
- COVID-19 epidemiological studies
- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Advanced Statistical Methods and Models
- Advanced Text Analysis Techniques
- Advanced Computational Techniques and Applications
- Complex Network Analysis Techniques
- Space Satellite Systems and Control
- Financial Risk and Volatility Modeling
- Text and Document Classification Technologies
- Neural Networks and Applications
- Optical Imaging and Spectroscopy Techniques
- Nanoparticles: synthesis and applications
- Health, Environment, Cognitive Aging
- Behavioral and Psychological Studies
- Advanced Graph Neural Networks
- Early Childhood Education and Development
- Chinese history and philosophy
- Graphene and Nanomaterials Applications
- Dementia and Cognitive Impairment Research
- Bayesian Modeling and Causal Inference
Guizhou University
2025
National University of Defense Technology
2020-2024
City University of Hong Kong
2024
Peking University
2022
Peking University Stomatological Hospital
2022
Hunan University of Traditional Chinese Medicine
2022
Guangxi University
2022
Chinese Academy of Medical Sciences & Peking Union Medical College
2022
Tianjin University of Science and Technology
2020
Manganese dioxide (MnO2) nanosheets have shown exciting potential in nanomedicine because of their ultrathin thickness, large surface area, high near-infrared (NIR) absorbance and good biocompatibility. However, the effect MnO2 on bacteria is still unclear. In this study, were for first time to possess highly efficient antibacterial activity by using Salmonella as a model pathogen. The growth curve plate assay uncovered that 125 μg/mL could kill 99.2% Salmonella, which was further verified...
Most of the data-driven satellite telemetry data anomaly detection methods suffer from high false positive rate (FPR) and poor interpretability. To solve above problems, we propose an framework using causal network feature-attention-based long short-term memory (CN-FA-LSTM). In our method, a parameters is constructed by calculating normalized modified conditional transfer entropy (NMCTE) optimized independence tests based on mutual information (CMI). Then, CN-FA-LSTM established to predict...
Most of the spacecraft telemetry anomaly detection methods based on statistical models suffer from problems high false negatives, long time consumption, and poor interpretability. Besides, complex interactions, which may determine propagation anomalous mode between parameters, are often ignored. To discover interaction parameters improve efficiency accuracy detection, we propose an framework parametric causality Double-Criteria Drift Streaming Peaks Over Threshold (DCDSPOT). We Normalized...
<title>Abstract</title> Low temperatures and drought reduce forage yield quality, with protein kinases crucial for plant stress response. This study examines the LcC2DPs kinase family in <italic>Lotus corniculatus</italic>, identifying 90 members, some tandemly distributed on chromosomes 2–6, grouped into 5 subfamilies (I-V). 34 homologous gene pairs were found <italic>Arabidopsis thaliana</italic>. <italic>LcC2DP</italic> genes promoters contain hormone response elements. GO analysis...
Network control theory (NCT) has recently been utilized in neuroscience to facilitate our understanding of brain stimulation effects. A particularly useful branch NCT is optimal control, which focuses on applying theoretical and computational principles design strategies achieve specific goals neural processes. However, most existing research optimally controlling network dynamics from the original state a target at time point. In this paper, we present first investigation introducing...
Stomach adenocarcinoma (STAD) arises from the mutations of stomach cells and has poor overall survival. Chemotherapy is commonly indicated for patients with cancer following surgical resection. The most prevalent alteration that affects growth N6-methyladenosine methylation (m6A), although possible function m6A in STAD prognosis not recognized.The research measured predictive FRGs BLCA samples TCGA GEO datasets. Data on stemness indices (mRNAsi), gene mutations, copy number variations (CNV),...
It is difficult for existing deep learning-based satellite on-orbit anomaly detection methods to define the residual-based threshold and identify false anomalies. To solve above problems, this paper proposes both a determination dynamic correction method causality-based identification pruning method. We use GRU (Gated Recurrent Unit) model predict telemetry parameters obtain residual vector; determine dynamically correct according prescribed positive rate; propose an improved multivariate...
The fragmentation of the functional brain network has been identified through connectivity (FC) analysis in studies investigating anesthesia-induced loss consciousness (LOC). However, it remains unclear whether mild sedation anesthesia can cause similar effects. This paper aims to explore changes local-global topology during anesthesia, better understand macroscopic neural mechanism underlying sedation. We analyzed high-density EEG from 20 participants undergoing and moderate propofol...
In the industrial sector, malfunctions of equipment that occur during production and operation process typically necessitate human intervention to restore normal functionality. However, question follows is how design optimize measures based on modeling actual scenarios, thereby effectively resolving faults. order address aforementioned issue, we propose an improved heuristic method a causal generative model for optimal intervention, aiming determine best measure by analyzing effects among...
The next-generation radio access network (RAN), known as Open RAN, is poised to feature an AI-native interface for wireless cellular networks, including emerging satellite-terrestrial systems, making deep learning integral its operation. In this paper, we address the nonconvex optimization challenge of joint subcarrier and power allocation in with objective minimizing total consumption while ensuring users meet their transmission data rate requirements. We propose OpenRANet,...
The apolipoprotein E (APOE) ɛ4 allele is a recognized genetic risk factor for Alzheimer's Disease (AD). Studies have shown that APOE mediates the modulation of intrinsic functional brain networks in cognitively normal individuals and significantly disrupts whole-brain topological structure AD patients. However, how regulates connectivity (FC) consequently affects levels cognitive impairment patients remains unknown. In this study, we systematically analyzed magnetic resonance imaging (fMRI)...
In the chemical production process, data are characterized by high dimensionality, coupling, nonlinearity, and time-varying nature, which makes it difficult for traditional methods to evaluate analyze effectively. Therefore, a novel modeling method (Npmm) complex processes based on multivariate hybrid weighted feature selection fused with gated recursive units an attention mechanism is established in this paper. model, Least Absolute Shrinkage Selection Operator(Lasso), Extreme Gradient...
This paper presents a model SOFPSE, which is used to analyze the correlation between telemetry parameters qualitatively and quantitatively, constructs fault propagation for prediction. Firstly, SOFPSE uses Granger causality test verify whether there in sense of data parameter pairs, obtains maximum delay prediction equation pairs. Based on this, diagram constructed, then hierarchical relationship found by using analytical structural analysis. Then, strength calculated based inner product,...
<abstract><p>This paper presents a free-boundary epidemic model with subclinical infections and vaccination.We prove the existence uniqueness of solutions to model.Moreover, sufficient conditions for disease vanishing spreading are given.The will vanish if basic reproduction number $ R_0 &lt; 1 $, that corresponding ODE defines without spatial expansion. However, spread whole area R^F_0(t_0) &gt; some t_0 0 when it is introduced heterogeneity. R^F_0(0) implies spillovers...
Multivariate time series causal discovery is a very meaningful but challenging research content. Due to the influence of nonlinearity and non-stationarity series, performance traditional algorithms often unsatisfactory. We propose an information entropy measure -Modified Transfer Entropy (MTE), which can reflect causality more accurately. Further, we take MTE as basic measure, add Quantile-based Causal Significance Test (QCST) Conditional Mutual Information Coefficient-based Independence...