Results 181 to 190 of about 30,698 (299)

Algorithm for the virtual vectors modulation in three-level inverters with a voltage-balance control loop

, 2005
D. Boroyevich, J. Pou, S. Busquets-Monge, P. Rodriguez, V. Sala   +4 more
core   +1 more source

${\rm MnBr}_2$ on the Graphene on Ir(110) Substrate: Growth, Structure, and Super-Moiré. [PDF]

Small
Safeer A, Güleryüz O, Atodiresei N, Jolie W, Michely T, Fischer J.   +5 more
europepmc   +1 more source

The Role of Actual and Purported Origin in e‐Commerce Wine Pricing: Evidence From Italian and French Names on Labels

Agribusiness, EarlyView.
ABSTRACT The origin of a product, if associated with good quality, can contribute to building a positive collective reputation, leading to a potential price premium. However, it is conceivable that a producer markets a product by evoking symbols, images, words, and values typical of places other than where it was designed or produced, creating a ...
Annalisa Caloffi, Amir Maghssudipour, Gianluca Stefani   +2 more
wiley   +1 more source

Space vector modulation for a single-phase converter with parallel legs using virtual vectors concept

, 2013
Felipe Bovolini Grigoletto, Humberto Pinheiro, Hilton Abilio Grundling, Joao Marcos Kanieski   +3 more
core   +1 more source

Honeybees express foodward flight vectors after a detour. [PDF]

J Exp Biol
Hadjitofi A, Messerich M, Landgraf T, Webb B.   +3 more
europepmc   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

Inverse hysteresis effects in a real and virtual environment. [PDF]

Front Sports Act Living
Schütz C.
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
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, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

A modular architecture for trial-by-trial learning of redundant muscle activity patterns in novel sensorimotor tasks. [PDF]

PLoS Comput Biol
Dal'Bello LR, Berger DJ, Borzelli D, Burdet E, d'Avella A.   +4 more
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source