The Enforceability Of Awards Set Aside At The Seat: An Asian And European Perspective [PDF]
Rana SC, Rashda
core +1 more source
Artificial Intelligence for Bone: Theory, Methods, and Applications
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
The Diabetic Hand as a Diagnostic Blind Spot: A Case of Severe Pseudohyperglycemia Masking Critical Hypoglycemia. [PDF]
Lam KHS +6 more
europepmc +1 more source
The Many Formations of the Court of Justice: 15 Years After Nice [PDF]
Prechal, Sacha
core +1 more source
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
Surgical Procedures for Planting and Revascularization in Catastrophic Hand Injuries and Preliminary Outcome Assessment: Experience of a Regional Care Center. [PDF]
González-Vargas IZ +4 more
europepmc +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Ultrasound-Guided Small-Caliber Catheter Drainage for Complex Septated Pleural Effusions: Discrimination of Septal Characteristics for Outcomes. [PDF]
Lin W, Chen P.
europepmc +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source

