A5101963863- Parallel Computing and Optimization Techniques
- VLSI and FPGA Design Techniques
- Advanced X-ray and CT Imaging
- Cancer Genomics and Diagnostics
- Nonlinear Dynamics and Pattern Formation
- Nonlinear Differential Equations Analysis
- Mathematical and Theoretical Epidemiology and Ecology Models
- Advanced Differential Equations and Dynamical Systems
- Quantum chaos and dynamical systems
- Differential Equations and Numerical Methods
- Aortic aneurysm repair treatments
- Cardiac, Anesthesia and Surgical Outcomes
- Ferroelectric and Negative Capacitance Devices
- Complex Systems and Time Series Analysis
- Pancreatic and Hepatic Oncology Research
- Multi-Agent Systems and Negotiation
- Evolutionary Algorithms and Applications
- Optical Systems and Laser Technology
- Aortic Disease and Treatment Approaches
- Advanced Neural Network Applications
- Stability and Controllability of Differential Equations
- Advanced Graph Neural Networks
- CAR-T cell therapy research
- Cardiac Fibrosis and Remodeling
- Topic Modeling
First Bethune Hospital of Jilin University
2025
National Center for Clinical Laboratories
2023-2024
Chinese Academy of Medical Sciences & Peking Union Medical College
2023-2024
Beijing Hospital
2023-2024
Institute of Computing Technology
2023-2024
Chinese Academy of Sciences
2020-2024
University of Chinese Academy of Sciences
2020-2024
New York University
2020
Changchun Institute of Optics, Fine Mechanics and Physics
2020
Jilin University
2008-2019
Heterogeneous graph neural networks (HGNNs) have emerged as powerful algorithms for processing heterogeneous graphs (HetGs), widely used in many critical fields. To capture both structural and semantic information HetGs, HGNNs first aggregate the neighboring feature vectors each vertex then fuse aggregated results across all vertex. Unfortunately, existing network accelerators are ill-suited to accelerate HGNNs. This is because they fail efficiently tackle specific execution patterns exploit...
Type A aortic dissection (TAAD) is a lethal cardiovascular disease characterized by the separation of layers within wall. The underlying pathological mechanisms TAAD requires further elucidation to develop effective prevention and pharmacological treatment strategies. Inflammation plays crucial role in pathogenesis. Disulfidptosis, an emerging type cell death, may shed light on mechanisms. This study investigates disulfidptosis-related genes immune infiltration TAAD. gene expression datasets...
Abstract Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due variability in technical details across different laboratories, particularly terms panel size, somatic detection TMB calculation rules. Currently, systematic evaluations impact these factors on existing best practice recommendations remain lacking. We assessed performance 50...
Medical imaging examination on patients usually involves more than one modalities, such as Computed Tomography (CT), Magnetic Resonance (MR) and Positron Emission Tomography(PET) imaging. Multimodal allows examiners to benefit from the advantage of each modalities. For example, for Abdominal Aortic Aneurysm, CT shows calcium deposits in aorta clearly while MR distinguishes thrombus soft tissues better.1 Analysing segmenting both images combine results will greatly help radiologists doctors...
To accelerate the time-consuming multi-objective design space exploration of CPU, previous work trains prediction models using a set cycle per instruction and power performance metrics derived from few simulations for sampled points, then exploits predicted rest points to perform exploration. Unfortunately, low accuracy limits effect, how balance exploitation while reducing time is challenging. In this paper, we an open-source high-accurate framework. A bagging ensemble model designed...
Tumor mutational burden (TMB) is a significant biomarker for predicting immune checkpoint inhibitor response, but the clinical performance of whole-exome sequencing (WES)-based TMB estimation has received less attention compared to panel-based methods. This study aimed assess reliability and comparability WES-based analysis among laboratories under routine testing conditions.
To accelerate time-consuming multi-objective design space exploration of CPU, previous work trains prediction models using a set performance metrics derived from few simulations, then predicts the rest. Unfortunately, low accuracy limits effect, and how to achieve good trade-off between multiple objectives is challenging.In this paper, we investigate various find out most accurate basic model. We enhance model by ensemble learning improve accuracy. A hypervolume-improvement-based...
By using variational methods and Morse theory, we study the multiplicity of periodic solutions for a class difference equations with double resonance at infinity. To best our knowledge, investigations on double-resonant systems have not been seen in literature.
Currently, DNA-based nucleic acid amplification tests (NAATs) and RNA-based NAATs are employed to detect reproductive tract infection (RTI) pathogens including Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), Ureaplasma urealyticum (UU). Although evaluations of have already existed, the comparison two methods is scarce. Thus, we compared limits detection (LODs) on same experimental conditions. Inactivated culture supernatants CT, NG, UU with determined pathogen DNA RNA load were used...
To perform cross-workload design space exploration of CPU, previous works implicitly transfer knowledge from several existing source workloads and try to make predictions on the target one. However, they do not fully explore transferability across their single basic prediction models limit accuracy. In this paper, an open-source Transfer learning Ensemble Design Space Exploration framework (TrEnDSE) is proposed performance predictions. The black-box between quantitatively dissected...
Existence and stability of stationary solutions nonlinear random difference equations are studied in this note. Firstly, we give the weak conditions that guarantee continuity Lypanunov exponents under small perturbations. Secondly, find out which ratio norm standard Euclidean has deterministic bounds. Based on these new results, provide easy-to-use existence almost sure a solution. In addition, also prove solution converges with probability one to fixed point corresponding system as noise...
In this paper, a multi-agent based process management system is proposed to modularize, simulate and analyze the existing industrial business environment dynamically; The different computational agents of are presented in hierarchical architecture, which offers intelligent behavior at level. At bottom level, modularize typical environments for its basic data acquisition pre-processing, will generate concerned event on rules embedded inside system, middle layer, enable assessments...
The real-time processing of synthetic aperture radar (SAR) data has a high requirement for the processor, which is difficult problem in SAR processing. With rapid development optoelectronic devices, traditional electrical can be converted into to improve speed. In this paper, new type optical device proposed speed data. help spatial light modulator (SLM), initial signal and matched filter function are loaded on input plane spectrum 4f system, respectively. Using an lens with Fourier...
To accelerate time-consuming multi-objective design space exploration of CPU microarchitecture, previous work trains prediction models using a set performance metrics derived from few simulations, then predicts the rest. Unfortunately, low accuracy limits effect, and how to achieve good trade-off between multiple objectives while reducing time is challenging. In this paper, we investigate various find out most accurate basic model. We enhance model by ensemble learning generate...
In this paper we describe an infrastructure for implementing autonomous Forex trading agents without human supervision; the are based on traditional strategies including ARIMA+GARCH, Kalman Filter, expert system, empirical experiences, etc. of combined above is rule based, which capable algorithms, rules systems and experiences from third parties; We used four major foreign currency pairs trading, i.e. USD/JPY, USD/CHF, EUR/USD, GBP/USD, with daily historical data dated 1st January 2003...