Results 81 to 90 of about 222 (197)

Transcranial direct current stimulation enhances delayed retention after 5 days of lower‐limb motor skill learning

open access: yesThe Journal of Physiology, EarlyView.
Abstract figure legend Schematic overview of the 5 day lower‐limb motor skill learning protocol combining ankle visuomotor practice with transcranial direct current stimulation (tDCS). Participants were allocated to motor skill practice with active tDCS over the leg representation of primary motor cortex (SKILL‐STIM), motor skill practice with sham ...
August Lomholt Kvistad   +5 more
wiley   +1 more source

Logical entropy of dynamical systems in product MV-algebras and general scheme

open access: yesAdvances in Difference Equations, 2019
The present paper is aimed at studying the entropy of dynamical systems in product MV-algebras. First, by using the concept of logical entropy of a partition in a product MV-algebra introduced and studied by Markechová et al.
Dagmar Markechová, Beloslav Riečan
doaj   +1 more source

Nanofluidic Spiking Logics Solves Linearly Inseparable and Separable Tasks

open access: yesAdvanced Computing, Volume 1, Issue 1, December 2026.
This work reports the biomimetic nanofluidic spiking logics capable of solving both linearly inseparable and separable tasks. By emulating the non‐monotonic and monotonic activation functions of biological ion channels, it can not only perform linearly separable AND and OR operations, but also implement the linearly inseparable XOR task, an ...
Shuang Wu   +5 more
wiley   +1 more source

A Representation Theorem for MV-algebras [PDF]

open access: yesSoft Computing, 2006
An {\em MV-pair} is a pair $(B,G)$ where $B$ is a Boolean algebra and $G$ is a subgroup of the automorphism group of $B$ satisfying certain conditions. Let $\sim_G$ be the equivalence relation on $B$ naturally associated with $G$. We prove that for every MV-pair $(B,G)$, the effect algebra $B/\sim_G$ is an MV- effect algebra.
openaire   +3 more sources

Four Directions, One Solution: Enabling Rapid Diffusion Tensor MRI for Ultra‐Low Field Using Deep Learning

open access: yesMagnetic Resonance in Medicine, Volume 96, Issue 3, Page 1413-1426, September 2026.
ABSTRACT Purpose This study revisits the tetrahedral encoding strategy originally proposed to accelerate Diffusion Tensor Magnetic Resonance Imaging (DT‐MRI) by reducing the requisite number of diffusion‐weighted measurements to four. We examine its practical limitations and explore how artificial intelligence (AI) can extend its utility. Specifically,
Joshua Mawuli Ametepe   +4 more
wiley   +1 more source

Representation theory of MV-algebras

open access: yesAnnals of Pure and Applied Logic, 2010
35 ...
Eduardo J. Dubuc, Yuri A. Poveda
openaire   +4 more sources

Predicting Grade 7 Academic Skills: The Role of Self‐Regulated Learning Competencies of Grade 2 Students

open access: yesEuropean Journal of Education, Volume 61, Issue 3, September 2026.
ABSTRACT The article describes the model and standardized web‐based tool for assessing indicators of self‐regulated learning (SRL) from three areas—motivation, cognition, and metacognition. The aim of this exploratory study is to investigate which SRL indicators in Grade 2 predict students' academic skills in Grade 7.
Eve Kikas   +4 more
wiley   +1 more source

Reconstructing Classical Algebras via Ternary Operations

open access: yesMathematics
Although algebraic structures are frequently analyzed using unary and binary operations, they can also be effectively defined and unified using ternary operations.
Jorge P. Fatelo, Nelson Martins-Ferreira
doaj   +1 more source

A Review of Mechanical Reinforcement and Piezoresistive Self‐Sensing in Carbon Nanotube Fiber Composites

open access: yesPolymer Composites, Volume 47, Issue 16, Page 14313-14338, 20 August 2026.
PSPP‐TRL mapping of CNT‐modified CFRP literature, with four recurring confusions resolved and five scale‐up problems quantified. ABSTRACT Carbon nanotube‐modified fiber composites are often presented as a route to stronger, tougher, and self‐sensing structural materials.
Sanan H. Khan
wiley   +1 more source

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