A5062186990- Gaussian Processes and Bayesian Inference
- Time Series Analysis and Forecasting
- Advanced Vision and Imaging
- EEG and Brain-Computer Interfaces
- Chaos-based Image/Signal Encryption
- Advanced Neural Network Applications
- Advanced Photocatalysis Techniques
- Advanced Steganography and Watermarking Techniques
- Adversarial Robustness in Machine Learning
- Forecasting Techniques and Applications
- Domain Adaptation and Few-Shot Learning
- Diamond and Carbon-based Materials Research
- Nanoplatforms for cancer theranostics
- Generative Adversarial Networks and Image Synthesis
- Cryptographic Implementations and Security
- IoT-based Smart Home Systems
- Covalent Organic Framework Applications
- Semiconductor materials and devices
- Brain Tumor Detection and Classification
- Characterization and Applications of Magnetic Nanoparticles
- Radioactive element chemistry and processing
- Theoretical and Computational Physics
- HIV Research and Treatment
- Extracellular vesicles in disease
- PARP inhibition in cancer therapy
Liaocheng University
2025
Hangzhou Dianzi University
2025
Xidian University
2025
Beijing University of Posts and Telecommunications
2020-2024
Shenyang Pharmaceutical University
2021-2022
Hospital for Sick Children
2022
Toronto Metropolitan University
2015-2021
Harbin Institute of Technology
2003-2019
China Academy of Engineering Physics
2019
We conducted integrative somatic-germline analyses by deeply sequencing 864 cancer-associated genes, complete genomes and transcriptomes for 300 mostly previously treated children adolescents/young adults with cancer of poor prognosis or rare tumors enrolled in the SickKids Cancer Sequencing (KiCS) program. Clinically actionable variants were identified 56% patients. Improved diagnostic accuracy led to modified management a subset. Therapeutically targetable (54% patients) unanticipated...
Many effective solutions have been proposed to reduce the redundancy of models for inference acceleration. Nevertheless, common approaches mostly focus on eliminating less important filters or constructing efficient operations, while ignoring pattern in feature maps. We reveal that many maps within a layer share similar but not identical patterns. However, it is difficult identify if features with patterns are redundant contain essential details. Therefore, instead directly removing...
A biomimetic nanocomposite made of a ginger-derived exosome and an inorganic framework enables high-performance delivery infliximab via the oral route for inflammatory bowel disease therapy.
Traditional economic models have rigid-form transition functions when modeling time-varying volatility of financial time series data and cannot capture other dynamics in the market. In this paper, combining Gaussian process state-space model framework stochastic (SV) model, we introduce a new regression (GPRSV) building procedures for analysis modeling. The GPRSV extends SV model. flexible nature state description allows to more We also present estimation methods demonstrate superior...
The conversion of solar energy into chemical fuels using photocatalysts has attracted a lot attention. Herein, two conjugated porous polymers (CPPs) are synthesized the Suzuki–Miyaura coupling reaction, linking 2,4,6-triphenyl-s-triazine (PTA) with either 1,10-phenanthroline [photoluminescence spectrum (PL)] or phenanthrene (PR), yielding designated as PTA–PL and PTA–PR, respectively. Incorporating pyridinic nitrogen atoms in PL is compared PR to assess its influence on photocatalytic...
Electroencephalography (EEG) reflects brain mechanisms, and existing research leverages EEG-based brain-computer interfaces for remote sensing image target detection. While most studies focus on achieving recognition, there has been less emphasis localization, which explores spatial information to enhance detection efficiency. An effective approach localization is through eye tracking. In this paper, we propose a Brain-Eye Collaboration Framework (BECF) that enables both recognition...
In this paper, we propose a novel nonparametric modeling framework for financial time series data analysis, and apply it to the problem of varying volatility modeling. Existing parametric models have rigid-form transition function they often over-fitting problems when model parameters are estimated using maximum likelihood methods. These drawbacks effect models' prediction performance. To solve problem, take Bayesian approach. By adding Gaussian process prior hidden state process, extend...
The carbon nitride films deposited by rf magnetron sputtering in a pure N2 discharge were annealed vacuum up to 900 °C. chemical composition and bonding structure of the studied using x-ray photoelectron spectroscopy, Raman Fourier transform infrared spectroscopy. It was found that nitrogen atoms bound sp, sp2, sp3 hybridized as-deposited films. effects thermal annealing on electron field emission characteristics CNx investigated. results showed treatment caused great loss N content favor...
It is essential to estimate the sleep quality and diagnose clinical stages in time at home, because they are closely related important causes of chronic diseases daily life dysfunctions. However, existing "gold-standard" sensing machine for diagnosis (Polysomnography (PSG) with Electroencephalogram (EEG) measurements) almost infeasible deploy home a "ubiquitous" manner. In addition, it costly train clinicians conditions. this paper, we proposed novel technical systematic attempt tackle...
Iron nitride films were deposited by dc magnetron sputtering using an Ar/N2 gas mixture. The structure, roughness, and surface morphology of the investigated x-ray diffraction, grazing incidence scattering (GIXS), atomic force microscopy (AFM). It was found that morphologies structures influenced N2 fraction. perpendicular fluctuations in height h(x,t) also analyzed AFM GIXS light dynamical scaling approach. surfaces typically exhibited self-affining both space time. two dependent nontrivial...
Estimating and monitoring the sleep states at home using ubiquitous infrared (IR) visual camera sensors is an essential healthcare problem. Currently, common challenge of IoT to predict stages “semantic gap” between sensory signals medical signals, where fewer correlations stage labels are observed. To bridge this gap, we propose a novel systematic methodological design (IoT-V2E) retrieve most similar EEG signal representations in database given IR query for sleep-related analysis....
It is inevitably crucial to classify sleep stage for the diagnosis of various diseases. However, existing automated methods mostly adopt "gold-standard" lectroencephalogram (EEG) or other uni-modal sensing signal PolySomnoGraphy (PSG) machine in hospital, that are expensive, importable and therefore unsuitable point-of-care monitoring at home. To enable home, this paper, we analyze relationship between infrared videos EEG propose a new task: using by distilling useful knowledge from signals...
Many effective solutions have been proposed to reduce the redundancy of models for inference acceleration. Nevertheless, common approaches mostly focus on eliminating less important filters or constructing efficient operations, while ignoring pattern in feature maps. We reveal that many maps within a layer share similar but not identical patterns. However, it is difficult identify if features with patterns are redundant contain essential details. Therefore, instead directly removing...
Video prediction is a challenging task with wide application prospects in meteorology and robot systems. Existing works fail to trade off short-term long-term performances extract robust latent dynamics laws video frames. We propose two-branch seq-to-seq deep model disentangle the Taylor feature residual frames by novel recurrent module (TaylorCell) module. TaylorCell can expand frames' high-dimensional features into finite series describe laws. In TaylorCell, we unit (TPU) memory correction...