The coordinated development of the agricultural circular economy and rural tourism provides an important pathway for transforming rural ecological advantages, strengthening industrial resilience, and advancing rural revitalization. The agricultural circular economy improves resou…
Background Ischemic stroke is a leading global cause of death and disability. Accurate, rapid infarct territory localization is critical for timely treatment, but ultra-early ischemic changes on non-contrast CT (NCCT) are subtle and highly physician-dependent. Methods This retros…
Biocatalysts are prized for their enantioselectivity, but slow chromatographic separations required to measure enantiomeric excess bottleneck their development. To overcome this limitation, we evolve enantioselective transcription factors (eTFs) that convert enzyme-catalyzed enan…
Long-document multimodal question answering requires more than retrieving relevant chunks from a large document. Different queries require different evidence behavior. Existing multimodal RAG systems improve evidence access through text chunks, page images, graph links, or hetero…
Cotton squares are important phenotypic indicators of the early reproductive growth of cotton, and automatic field detection of cotton squares provides an important basis for cotton growth monitoring and precision cultivation management. However, early cotton square detection in…
Parkinson's disease (PD) affects millions worldwide and causes severe motor symptoms. Adaptive deep brain stimulation (aDBS) delivers physiologically informed stimulation that can track fluctuations in PD motor symptoms, enabling more intelligent DBS control. However, most existi…
Graph Neural Networks (GNNs) have been widely used to capture spatial functional connectivity patterns to improve electroencephalography (EEG)-based depression recognition performance. However, the functional connectivity of brain networks in patients with depression exhibits an…
Camouflaged Object Detection (COD) aims to locate and segment objects that blend into their surroundings, presenting challenges due to weak edge cues and ill-defined boundaries. Traditional COD models rely on hand-designed architectures and multi-scale feature fusion, which are o…
Spatial intelligence remains a persistent challenge for Multimodal Large Language Models (MLLMs), as it requires coherent spatial scene representations beyond basic object recognition. Existing methods typically build such representations through textual reasoning or 3D reconstru…
Birds are significant bioindicators in the assessment of habitat biodiversity, ecological impacts and ecosystem health. Against the backdrop of easier bird vocalization data acquisition, and with deep learning and machine learning technologies as the technical support, exploring…
Sentiment analysis is a key technique in natural language processing that enables computers to understand human emotions expressed in text. It is widely used in applications such as customer feedback analysis, social media monitoring, and product reviews. However, sentiment analy…