A5030133393- Nanoplatforms for cancer theranostics
- Luminescence and Fluorescent Materials
- Functional Brain Connectivity Studies
- Vehicle emissions and performance
- Air Quality Monitoring and Forecasting
- Water Quality Monitoring and Analysis
- Advanced Nanomaterials in Catalysis
- Insurance, Mortality, Demography, Risk Management
- Health, Environment, Cognitive Aging
- Advanced Neuroimaging Techniques and Applications
- Diabetic Foot Ulcer Assessment and Management
- EEG and Brain-Computer Interfaces
- Polydiacetylene-based materials and applications
- Advanced Neural Network Applications
- Machine Learning in Healthcare
- Metaheuristic Optimization Algorithms Research
- Imbalanced Data Classification Techniques
- Financial Distress and Bankruptcy Prediction
- Housing Market and Economics
- Blockchain Technology Applications and Security
- Stock Market Forecasting Methods
- Financial Literacy, Pension, Retirement Analysis
- Vehicle Routing Optimization Methods
- Privacy-Preserving Technologies in Data
- Retinal Imaging and Analysis
Southern University of Science and Technology
2019-2023
Beijing University of Chemical Technology
2021
Shenzhen University
2019
Here, we describe a fluorination strategy for semiconducting polymers the development of highly bright second near-infrared region (NIR-II) probes. Tetrafluorination yielded fluorescence QY 3.2 % polymer dots (Pdots), over 3-fold enhancement compared to non-fluorinated counterparts. The was attributable nanoscale fluorous effect in Pdots that maintained molecular planarity and minimized structure distortion between excited state ground state, thus reducing nonradiative relaxations. By...
Abstract Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and engineering. However, existing machine learning methods fMRI‐based decoding either suffer from low classification performance or poor explainability. Here, we address this issue by proposing a biologically inspired architecture, Spatial Temporal‐pyramid Graph Convolutional Network (STpGCN), capture spatial–temporal graph representation of functional activities. By...
In order to improve the accuracy of predicting air pollutants in Shenzhen, a hybrid model based on ARIMA (Autoregressive Integrated Moving Average model) and prophet for mixing time space relationships was proposed. First, Prophet method were applied train data from 11 quality monitoring stations gave them different weights. Then, finished calculation about weight impact each station final results. Finally, built up did error evaluation. The result experiments illustrated that this can...
Abstract Here, we describe a fluorination strategy for semiconducting polymers the development of highly bright second near‐infrared region (NIR‐II) probes. Tetrafluorination yielded fluorescence QY 3.2 % polymer dots (Pdots), over 3‐fold enhancement compared to non‐fluorinated counterparts. The was attributable nanoscale fluorous effect in Pdots that maintained molecular planarity and minimized structure distortion between excited state ground state, thus reducing nonradiative relaxations....
Memetic algorithm (MA) is widely applied to optimize routing problems as it provides one way combine local search with global search. However, the in MA needs be carefully designed according problem's characteristics. In this article, we consider a real-world large-scale waste collection problem multiple depots, disposal facilities, trips, and working time constraints. Vehicles limited capacity can start from different collect at sites, make trips facilities empty return its origin. While...
Nonunion is one of the challenges faced by orthopedics clinics for technical difficulties and high costs in photographing interosseous capillaries. Segmenting vessels filling capillaries are critical understanding obstacles encountered capillary growth. However, existing datasets blood vessel segmentation mainly focus on large body, lack labeled image greatly limits methodological development applications filling. Here, we present a benchmark dataset, named IFCIS-155, consisting 155 2D...
High-accuracy bankruptcy prediction has been important to investors and corporate finance officers for decades. With data in China Poland given, this paper is an exploratory study attempting aid feature engineering predictions through a new method we call "Data Slicing." Our slicing analysis relies on making carefully selected sliced financial datasets measuring each dataset's accuracy. According the findings research, most related metric best variable slice get predictable dataset turn out...
Brain decoding, aiming to identify the brain states using neural activity, is important for cognitive neuroscience and engineering. However, existing machine learning methods fMRI-based decoding either suffer from low classification performance or poor explainability. Here, we address this issue by proposing a biologically inspired architecture, Spatial Temporal-pyramid Graph Convolutional Network (STpGCN), capture spatial-temporal graph representation of functional activities. By designing...
With the Chinese economy's gradual development over past decades, people's income has increased, and people are paying more attention to financial asset investment. The ratio of return on investment in household assets may be significantly affected by knowledge level. Based big data from Household Finance Survey (CHFS) questionnaire, this paper empirically tests impact returns. As an innovation, we use Sharpe that is calculated as a quantitative description rate, which relatively novel....