Exploring tumorigenesis as a process of phenotypic state-space exploration and selective funneling. [PDF]
Thomas F +11 more
europepmc +1 more source
In Situ Contact Angle Measurement for Autonomous Spin Coating in Self‐Driving Labs
A vision‐based add‐on transforms commercial spin coaters into autonomous modules of Self‐Driving Labs. Combining a width‐scaled U‐Net with classical geometric analysis, the system simultaneously measures contact angles and estimates substrate pose using a single camera.
Sven Fischer, Micha Hiegle, Holger Röhm
wiley +1 more source
Particle Filtering-Based In-Flight Icing Detection for Unmanned Aerial Vehicles. [PDF]
Souanef T +4 more
europepmc +1 more source
Data‐Efficient Cycle‐Level Capacity Prediction Using 1D Deep Convolutional Network
We introduce DeepBat, a deep learning framework featuring a 1D convolutional backbone designed to extract latent degradation patterns from a microstructurally diverse electrode dataset. By learning complex formulation–performance relationships, the model accurately predicts long‐term specific discharge capacity using limited early‐cycle data, providing
Tao Huang +16 more
wiley +1 more source
A theoretical framework for brain-computer interfaces: decodability, performance limits, and closed-loop adaptation. [PDF]
Fu Y +10 more
europepmc +1 more source
Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei +9 more
wiley +1 more source
Alert-Driven Active Defense for IoT-Enabled CBTC Systems Using Bayesian Hypergame Modeling and Hierarchical Reinforcement Learning. [PDF]
Zhao J +6 more
europepmc +1 more source
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
PRISM, a Bidirectional NMR Foundation Model: From Peak List to Structure and Back
Structure elucidation from NMR can consume an expert for hours or even days. PRISM addresses this with a bidirectional transformer trained on 1.19 M real experimental spectra: it translates 1H and 13C peak lists into structures with 60.1% stereo‐aware top‐1 accuracy (72.5% stereo‐unaware), and, working in reverse, predicts spectra back from structures,
Ajnabiul Hoque, Frank Glorius
wiley +2 more sources
Single-Axis Rotational Inertial Navigation Systems for USVs: A Review of Key Technologies. [PDF]
Su E +5 more
europepmc +1 more source

