Results 61 to 70 of about 1,871,607 (274)
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi +7 more
wiley +1 more source
bayesian: Bindings for Bayesian TidyModels
Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels' via 'bayesian' . 'tidymodels' is a collection of packages for machine learning; see Kuhn and Wickham (2020) ). The technical details of 'brms' and 'Stan' are described in Bürkner (2017) ,
Bürkner, Paul-Christian +1 more
core +4 more sources
In psychology, small sample sizes are a frequent challenge—particularly when studying specific expert populations or using complex and cost-intensive methods like human scoring of creative answers—as they reduce statistical power, bias results, and limit
Selina Weiss +2 more
doaj +1 more source
Estimation of simultaneous equation models by backpropagation method using stochastic gradient descent [PDF]
Simultaneous equation model (SEM) is an econometric technique traditionally used in economics but with many applications in other sciences. This model allows the bidirectional relationship between variables and a simultaneous relationship between the ...
Belén Pérez-Sánchez +3 more
doaj +2 more sources
Translucency of a Dental Porcelain Mixed by Two Ceramic Slurry Methods: A Bayesian Comparison
Background. The ceramics industry produces porcelain pastes using a controlled ratio of water and porcelain powder. Two methods are used to produce a dental porcelain paste: one-step mixing or incremental mixing. Objective.
Catalina Serna-Meneses +7 more
doaj +1 more source
A Robotic Testing Platform for Pipelined Discovery of Resilient Dielectric Elastomer Actuators
This work introduces a robotic testing platform enabling high‐throughput, multi‐parameter lifetime mapping of linear dielectric elastomer actuators (DEAs). By integrating programmable high‐voltage control and automated electromechanical measurements, the system identifies material and operating conditions that double actuator lifetime.
Ang (Leo) Li +10 more
wiley +1 more source
Gene regulatory networks (GRNs) are underlying networks identified by interactive relationships between genes. Reconstructing GRNs from massive genetic data is important for understanding gene functions and biological mechanism, and can provide effective
Yan Li +5 more
doaj +1 more source
Bayesian-Torch: Bayesian neural network layers for uncertainty estimation
Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable the user to perform stochastic variational inference in Bayesian deep neural networks.
Pi Esposito +2 more
core +1 more source
Perceived Time Shapes Physical Fatigue Accumulation and Its Neural Oscillatory Correlates
Can a clock change the course of physical fatigue? By covertly manipulating the clock calibration during repeated isometric contractions, we showed that perceived time shapes fatigue accumulation and frontal oscillatory dynamics. While fatigue accumulation was only reduced when the clock was slowed down, frontal oscillatory dynamics followed perceived ...
Pierre‐Marie Matta +3 more
wiley +1 more source
During pancreatitis, IL‐1α is released from necrotic acinar cells. In response to IL‐1α, pancreatic fibroblasts release chemokines and cytokines that regulate the recruitment of immune cells to the damaged organ. Furthermore, IL‐1α primes fibroblasts, resulting in increased tissue fibrosis during chronic pancreatitis.
Hala Mazloum +13 more
wiley +1 more source

