Results 211 to 220 of about 43,750 (296)

Bridging model performance and clinical utility in T cell receptor-epitope binding prediction. [PDF]

Clin Transl Med
Wang Y, Lu Y, Suo S.
europepmc   +1 more source

Crease‐Encoded Soft Origami Chambers: A Unified Design‐to‐Fabrication Framework for Low‐Pressure Pneumatic Joints

Advanced Intelligent Systems, EarlyView.
Origami turns a single silicone chamber into three different soft fluidic actuators. Crease angles alone decide whether it elongates, bends, or twists, and the fully folded chambers are cast monolithically in one day. Below 15 kPa, they reach 268% axial stretch, 72° bending, and 55° twist—no strain‐limiting layers, no rigid reinforcements, no vacuum ...
Alexia Le Gall, Mattia Franchi de’ Cavalieri, Gastone Ciuti, Arianna Menciassi, Matteo Cianchetti   +4 more
wiley   +1 more source

Sources and consequences of self-doubt in patients with Ehlers-Danlos syndrome: a qualitative study in Europe and North America. [PDF]

BMJ Open
Halverson CME, Vershaw SL, Francomano CA, Doyle T.   +3 more
europepmc   +1 more source

Integration of Liquid Handling Robotics, Turbidimetry, and Machine Learning Toward Inverse Design of Lower Critical Solution Temperature Polymer Formulations

Advanced Intelligent Systems, EarlyView.
An integrated OT‐2/plate reader platform automates LCST cloud point measurement of NIPAM‐co‐DMAEMA copolymers across high‐dimensional formulation spaces. Machine learning trained on the resulting high‐throughput datasets achieves R2 up to 0.96 and enables inverse design of polymer formulations to target transition temperatures with <1% error.
Lachlan Alexander, Vianna F. Jafari, Tanja Junkers   +2 more
wiley   +1 more source

Determinants of WHO's Problem Management Plus (PM+) uptake within health and integration sectors in Switzerland: a qualitative study. [PDF]

BMJ Public Health
Keyan D, Spaaij J, Schick M, Bryant RA, Morina N.   +4 more
europepmc   +1 more source

Dual‐View Representation Learning for Deployable Humanoid Whole‐Body Control

Advanced Intelligent Systems, EarlyView.
Humanoid robots must learn control from limited onboard sensing, although simulation provides richer training‐only states. DVP learning pairs these views of each simulated motion and aligns their latent control features inside the policy‐learning loop. This direct, deployment‐aware supervision accelerates learning while the deployed policy relies only ...
Haolin Song, Wengang Zhou, Mingxiao Feng, Houqiang Li   +3 more
wiley   +1 more source

The implementation of mindfulness-based cognitive therapy for patients with inflammatory bowel disease: a qualitative study. [PDF]

BMC Psychol
Bosman SJE, van der Leegte M, Ter Avest MM, Huijbers MJ, Nissen LHC, Kievit W, Speckens AEM, Kwakkenbos L.   +7 more
europepmc   +1 more source

Objectives and Key Results–Driven Multiagent Framework for Mechanical Design and Simulation

Advanced Intelligent Systems, EarlyView.
Objectives and key results (OKR)‐agent, an OKR‐driven multiagent framework, turns a plain‐language engineering goal into completed mechanical simulations. Three peer agents—supervisor, modeler, and simulator—share a compact board of OKR and coordinate external molecular dynamics (MD) and finite‐element solvers through a standardized tool interface. The
Jie Tian, Lin Pang, Jixin Hou, Xiao Sun, James Jaraczewski, Xianyan Chen, Kenan Song, Xiaoming Zhai, Tianming Liu, Keke Tang, Xianqiao Wang   +10 more
wiley   +1 more source

Between a rock and a hard place: balancing roles of clinician and co-researcher in a primary health care setting - A qualitative study. [PDF]

Chiropr Man Therap
Allen-Unhammer A, Vøllestad NK, Mengshoel AM.   +2 more
europepmc   +1 more source

Vector‐Based SparseGPT: A Vector‐Based Sparsity Method for Large Language Model

Advanced Intelligent Systems, EarlyView.
Conventional pruning such as SparseGPT produces harmful accumulated errors through step‐by‐step weight editing. V‐SparseGPT prunes and updates target weights simultaneously to curb these errors for N:M structured sparsity. Block‐sparsity and layer‐parallel sparsity greatly boost pruning efficiency.
Junfei He, Mingxi Tan, Junchao Dong, Pengfei Ying   +3 more
wiley   +1 more source