A5103218026- Aluminum toxicity and tolerance in plants and animals
- Alzheimer's disease research and treatments
- 3D Shape Modeling and Analysis
- Brain Tumor Detection and Classification
- Advanced Neural Network Applications
- Neuroinflammation and Neurodegeneration Mechanisms
- Computer Graphics and Visualization Techniques
- Advanced Numerical Analysis Techniques
- Neuroscience and Neuropharmacology Research
- Curcumin's Biomedical Applications
- Medical Image Segmentation Techniques
- Natural product bioactivities and synthesis
- Heavy Metal Exposure and Toxicity
- Parkinson's Disease Mechanisms and Treatments
- Methane Hydrates and Related Phenomena
- Nanoparticles: synthesis and applications
- Neurological Disease Mechanisms and Treatments
- Coagulation and Flocculation Studies
- Augmented Reality Applications
- Advanced Image Fusion Techniques
- Tryptophan and brain disorders
- Medicinal Plants and Neuroprotection
- Seaweed-derived Bioactive Compounds
- Radiomics and Machine Learning in Medical Imaging
- Soft Robotics and Applications
Shuguang Hospital
2020-2025
Shanghai University of Traditional Chinese Medicine
2020-2025
Northeastern University
2025
Universidad del Noreste
2025
Dalian Medical University
2022-2025
Second Affiliated Hospital of Dalian Medical University
2022-2025
Northeastern University
2020-2024
Shanxi Medical University
2020-2024
Nanjing Agricultural University
2023-2024
China Construction Eighth Engineering Division (China)
2023
Greenness identification from crop images captured outdoors is the important step for growth monitoring. The commonly used methods greenness are based on visible spectral-index, such as excess green index, minus red vegetative color index of vegetation extraction, combined index. All these spectral-index working assumption that plants display a clear high degree greenness, and soil only background element. In fact, brightness contrast an image coming outdoor environments seriously affected...
Recent hardware advances have led to the development and consumerization of mobile devices, which mainly include smartphones various wearable devices. To protect privacy users, user authentication mechanisms been proposed. In particular, biometrics has widely used for multi-factor authentication. However, biometrics-based usually require costly sensors deployed on rely explicit input Internet connection performing this article, we propose a system, called RISKCOG, can authenticate ownership...
Two novel Flammulina velutipes (F. velutipes) polysaccharides, FVPH1 and FVPH2, were isolated purified after hot water extraction. The structural characterization revealed that the backbone of consisted mainly →6)-α-D-Glcp(1→, →3,4)-α-D-Galp(1→, →4)-α-L-Fucp(1→, →4)-β-D-Manp(1→, while FVPH2 →3)-α-D-Galp(1→, →3,4)-α-D-Manp(1→,→6)-α-D-Glcp(1→. branches contained →6)-α-D-Glcp(1→ α-D-Glcp(1→ β-L-Fucp(1→. exhibited significantly better immunostimulatory activity than (P < 0.05), as evidenced by...
Recently, the state-of-art models for medical image segmentation is U-Net and their variants. These networks, though succeeding in deriving notable results, ignore practical problem hanging over field: overfitting small dataset. The over-complicated deep neural networks unnecessarily extract meaningless information, a majority of them are not suitable lung slice CT task. To overcome two limitations, we proposed new whole-process network merging advanced UNet++ model. comprises three main...
Recently, the state-of-art models for medical image segmentation is U-Net and their variants. These networks, though succeeding in deriving notable results, ignore practical problem hanging over field: overfitting small dataset. The over- complicated deep neural networks unnecessarily extract meaningless information, a majority of them are not suitable lung slice CT task. To overcome two limitations, we proposed new whole-process network merging advanced UNet++ model. comprises three main...
Accurate identification and localisation of brain tumours from medical images remain challenging due to tumour variability structural complexity. Convolutional Neural Networks (CNNs), particularly ResNet Unet, have made significant progress in image processing, offering robust capabilities for segmentation. However, limited research has explored their integration with human-computer interaction (HCI) enhance usability, interpretability, clinical applicability. This paper introduces...
The application of novel organic fertilizers derived from secondary raw materials has emerged as a promising &#160;sustainable agricultural practice in recent years. This study investigates the potential produced fishery waste to be applied alternatives for synthetic nitrogen (N) through comprehensive soil incubation and pot experiments. N content eight selected ranged 1.9% 9.8%, which some them were rich labile such protein fractions amino acids. In 120-day trial, six these N-rich...
At present, the traditional machine learning methods and convolutional neural network (CNN) are mostly used in image recognition. The feature extraction process for recognition is executed by manual, its generalization ability not strong enough. earliest also has many defects, such as high hardware requirements, large training sample size, long time, slow convergence speed low accuracy. To solve above problems, this paper proposes a novel deep LeNet-5 model On basis of Lenet-5 with...
Flammulina velutipes (F. velutipes) polysaccharides were modified by ultrasound at the rated power of 150 W and 900 W. The monosaccharide composition, ultraviolet-visible, Fourier transform infrared spectral characteristics F. (FVP) their ultrasonic modification products (U-FVPs) determined. protective effects FVP U-FVPs on human gastric mucosal cells GES-1 confirmed for first time. mole ratios glucose galactose decreased ratio mannose was increased after modification. Compared with original...