Text-Enhanced Graph Attention Hashing for Cross-Modal Retrieval.

Deep hashing technology, known for its low-cost storage and rapid retrieval, has become a focal point in cross-modal retrieval research as multimodal data continue to grow. However, existing supervised methods often overlook noisy labels and multiscale features in different modal datasets, leading to higher information entropy in the generated hash codes and features, which reduces retrieval performance. The variation in text annotation information across datasets further increases the information entropy during text feature extraction, resulting in suboptimal outcomes.

Poly (Betulinic Acid) Nanoparticles Loaded with bFGF Improve Functional Recovery After Spinal Cord Injury.

Oxidative stress (OS) is one of the crucial molecular events of secondary spinal cord injury (SCI). Basic fibroblast growth factor (bFGF) is a multipotent cell growth factor with an anti-oxidant effect. However, bFGF has a short half-life in vivo, which limits its therapeutic application.

Over-activation of TRPM2 ion channel accelerates blood-spinal cord barrier destruction in diabetes combined with spinal cord injury rat.

Spinal cord injury (SCI) is a devastating neurological disorder that often results in loss of motor and sensory function. Diabetes facilitates the blood-spinal cord barrier (BSCB) destruction and aggravates SCI recovery. However, the molecular mechanism underlying it is still unclear.

Asymmetric coordinate attention spectral-spatial feature fusion network for hyperspectral image classification.

In recent years, the hyperspectral classification algorithm based on deep learning has received widespread attention, but the existing network models have higher model complexity and require more time consumption. In order to further improve the accuracy of hyperspectral image classification and reduce model complexity, this paper proposes an asymmetric coordinate attention spectral-spatial feature fusion network (ACAS2F2N) to capture distinguishing hyperspectral features. Specifically, adaptive asymmetric iterative attention was proposed to obtain the discriminative spectral-spatial features.