Results 191 to 200 of about 23,211 (261)
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob +2 more
wiley +1 more source
Quantitative analysis of lung microwave ablation zone volume and shape. [PDF]
Salkin RS +12 more
europepmc +1 more source
Objective The objective of this study was to quantify incremental diagnostic yield and prognostic value of continuous electroencephalography (cEEG; ≥12 hours) versus a 60‐minute short electroencephalography (sEEG) in predicting post‐stroke epilepsy (PSE) in patients without acute symptomatic seizures.
Kai Michael Schubert +8 more
wiley +1 more source
Medium-Range Structural Order in Amorphous Arsenic. [PDF]
Liu Y +6 more
europepmc +1 more source
Development of Design‐Phase Digital Twin for Structural Optimization of a Biomedical Device
A digital twin optimized the structural performance of a multi‐component biomedical device interface by 75%. The work shows that wider adoption of digital twins can accelerate safer, more predictive medical device development across design, verification, and optimization stages.
Tanguy René Pinol +3 more
wiley +1 more source
A novel NSD2 pathogenic variant in a Chinese patient with Rauch-Steindl syndrome: a case report. [PDF]
Zhu H +7 more
europepmc +1 more source
Benchmarking Non‐Port‐Hashing Routers With Multiple IP Addresses: Test Setup Recommendations
Contemporary routers distribute the load among their processing elements by using IP addresses and/or port numbers for hashing. Unbiased benchmarking of non‐port‐hashing routers requires the use of pseudorandom IP addresses. Two test setups are examined: a direct connection between the Tester and the Device Under Test, and a gateway‐based approach ...
Gábor Lencse, Keiichi Shima, Ole Trøan
wiley +1 more source
Regulatory grammar in human promoters uncovered by MPRA-based deep learning. [PDF]
Barbadilla-Martínez L +20 more
europepmc +1 more source

