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Optimizing Transformer-Based Network via Advanced Decoder Design for Medical Image Segmentation.
Biomed Phys Eng Express
January 2025
Shandong University, No. 72, Binhai Road, Jimo, Qingdao City, Shandong Province, Qingdao, 266200, CHINA.
U-Net is widely used in medical image segmentation due to its simple and flexible architecture design. To address the challenges of scale and complexity in medical tasks, several variants of U-Net have been proposed. In particular, methods based on Vision Transformer (ViT), represented by Swin UNETR, have gained widespread attention in recent years.
View Article and Find Full Text PDFRelativistic CASPT2/RASPT2 Program along with DIRAC Software.
J Chem Theory Comput
January 2025
Department of Chemistry, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima City, Hiroshima 739-8526, Japan.
Exploring electronic states in actinide compounds is a critical aspect of nuclear science. However, considering relativistic effects and electron correlation in theoretical calculations poses a complex challenge. To tackle this, we developed the CASPT2/RASPT2 program along with the DIRAC program, enabling calculations of electron correlation methods using multiconfigurational perturbation theory with various relativistic Hamiltonians.
View Article and Find Full Text PDFAdvancements in Wound Bed Preparation of Chronic Wounds.
Surg Technol Int
January 2025
Dr. Phillip Frost Department of Dermatology & Cutaneous Surgery, University of Miami Miller School of Medicine, Miami, Florida.
Chronic wounds are notoriously challenging to heal as they are often halted in their normal healing process. The concept of TIME (Tissue, Inflammation/Infection, Moisture imbalance, Epithelial edge advancement) has been widely utilized in clinical practice to prepare wound beds and promote healing, particularly in longstanding wounds. Traditional methods of wound bed preparation are often inadequate in healing chronic wounds or they may not be tolerated by patients.
View Article and Find Full Text PDFForce-Trainable Liquid Crystal Elastomer Enabled by Mechanophore-Induced Radical Polymerization.
Angew Chem Int Ed Engl
January 2025
Southeast University, Institute of Advanced Materials and School of Chemistry and Chemical Engineering, Institute of Advanced Materials and School of Chemistry and Chemical Engineering, 211189, Nanjing, CHINA.
In nature, organisms adapt to environmental changes through training to learn new abilities, offering valuable insights for developing intelligent materials. However, replicating this adaptive learning in synthetic materials presents a significant challenge. This study introduces a feasible approach to train liquid crystal elastomers (LCEs) by integrating a mechanophore tetraarylsuccinonitrile (TASN) into their main chain, addressing the challenge of enabling synthetic materials to exchange substances with their environment.
View Article and Find Full Text PDFDepolarized Forward Light Scattering for Subnanometer Precision in Biomolecular Layer Analysis on Gold Nanorods.
J Phys Chem Lett
January 2025
Department of Physics, Chalmers University of Technology, 412 96 Göteborg, Sweden.
Functional gold nanoparticles have emerged as a cornerstone in targeted drug delivery, imaging, and biosensing. Their stability, distribution, and overall performance in biological systems are largely determined by their interactions with molecules in biological fluids as well as the biomolecular layers they acquire in complex environments. However, real-time tracking of how biomolecules attach to colloidal nanoparticles, a critical aspect for optimizing nanoparticle function, has proven to be experimentally challenging.
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