A5071771834- Smart Agriculture and AI
- Face and Expression Recognition
- Spectroscopy and Chemometric Analyses
- Remote Sensing and Land Use
- Virus-based gene therapy research
- Advanced Neural Network Applications
- Cancer Research and Treatments
- Advanced Image and Video Retrieval Techniques
- Remote-Sensing Image Classification
- Cancer-related Molecular Pathways
- Gene expression and cancer classification
- Leaf Properties and Growth Measurement
- Computational Drug Discovery Methods
- Seismic Imaging and Inversion Techniques
- Microbial Natural Products and Biosynthesis
- Gait Recognition and Analysis
- Superconducting Materials and Applications
- Machine Learning in Bioinformatics
- Hydrocarbon exploration and reservoir analysis
- Image Retrieval and Classification Techniques
- Rough Sets and Fuzzy Logic
- Cancer-related molecular mechanisms research
- Advanced Computational Techniques and Applications
- Date Palm Research Studies
- Hand Gesture Recognition Systems
Xijing University
2016-2025
Yangzhou University
2018-2025
Jinan University
2025
Ministry of Agriculture and Rural Affairs
2025
Chinese Academy of Sciences
2010-2024
Scripps (United States)
2022-2024
South China Sea Institute Of Oceanology
2017-2024
Institute of Oceanology
2017-2024
University of Chinese Academy of Sciences
2017-2024
The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology
2024
Accumulating clinical researches have shown that specific microbes with abnormal levels are closely associated the development of various human diseases. Knowledge microbe-disease associations can provide valuable insights for complex disease mechanism understanding as well prevention, diagnosis and treatment However, little effort has been made to predict microbial candidates diseases on a large scale.In this work, we developed new computational model predicting by combining two single...
Thousands of long noncoding RNAs (lncRNAs) have been identified in mouse, rat, and human testes, some which play important roles testis development spermatogenesis. However, systematic analysis lncRNAs expressed postnatal pig testes has not reported. Thus, this study, we present the expression characterization immature (30-day-old [D30]) mature (180-day-old [D180]) testes. A total 90 440 168 (85.75%) 97 001 700 (95.35%) 150-base-pair paired-end clean reads were generated D30 D180 cDNA...
Purpose To centrally assess the safety, efficacy, and 6-year follow-up of recombinant adenovirus-p53 (rAd-p53) combined with radiotherapy (RT) for patients nasopharyngeal carcinoma (NPC). Patients Methods A randomized controlled clinical study on rAd-p53 RT in 42 NPC was compared a control group 40 treated alone. In receiving RT, intratumorally injected once week 8 weeks. Concurrent (70 Gy 35 fractions) given to tumor neck lymph node. tumors were monitored adverse events responses. Results...
Side-scan sonar is an important application in the field of ocean exploration. Accurate segmentation target regions side-scan images a challenging issue due to low-resolution and strong noise interference. To accurately faster segment different categories image, novel convolutional neural networks (CNNs) model proposed this study. Firstly, deep separable residual module used for multi-scale feature extraction suppression information interference, multi-channel fusion method enhance transfer...
Crop pests seriously affect the yield and quality of crops. Accurately rapidly detecting segmenting insect in crop leaves is a premise for effectively controlling pests.
Automatic underwater target detection plays a vital role in sonar image processing and analysis, its core task is to discriminate categories achieve precise positioning. However, the interfered by seafloor reverberation noise complex background, which brings more significant challenges accurate of target. To different targets image, we proposed an adaptive global feature enhancement network (AGFE-Net), uses multi-scale convolution attention mechanisms with receptive field obtain semantic...
Abstract Circularized nandiscs (cNDs) exhibit superb monodispersity and have the potential to transform functional structural studies of membrane proteins. In particular, cNDs can stabilize large patches lipid bilayers for reconstitution complex biochemical reactions, enabling capture crucial intermediates involved in synaptic transmission viral entry. However, previous methods building require multiple steps suffer from low yields. We herein introduce a simple, one-step approach ease...
Despite recent works that have achieved remarkable progress on salient object detection for natural scene images, to detect various types and scales of objects, complex backgrounds in remote sensing images are still challenging. In this study, a novel global perception network (GPNet) is constructed the images. The proposed GPNet includes module (GPM), an axial attention block (AAB), feature distillation structure (FDS). GPM used preserve relationships entire dataset, AAB designed capture...
For semantic segmentation of remote sensing images, convolutional neural networks (CNNs) have proven to be powerful tools. However, the existing CNN-based methods problems feature information loss, serious interference by clutter information, and ignoring correlation between different scale features. To solve these problems, this article proposes a novel hidden feature-guided network (HFGNet) for which achieves accurate hierarchically extracting fusing valuable information. Specifically,...
mRNA lipid nanoparticles (LNPs) have emerged as powerful modalities for gene therapies to control cancer and infectious immune diseases. Despite the escalating interest in mRNA-LNPs over past few decades, endosomal entrapment of delivered mRNAs vastly impedes therapeutic developments. In addition, molecular mechanism LNP-mediated delivery is poorly understood guide further improvement through rational design. To tackle these challenges, we characterized using a library small molecules...
Chest X-ray is one of the most common radiological examinations for screening thoracic diseases. Despite existing methods based on convolution neural network that have achieved remarkable progress in disease classification from chest images, scale variation pathological abnormalities different diseases still challenging image classification. Based above problems, this paper proposes a residual model pyramidal module and shuffle attention (PCSANet). Specifically, pyramid used to extract more...