Results 71 to 80 of about 854,773 (255)

Plasma EV Proteomics Identifies ECM Remodeling and Inflammatory Proteins LUM and C7 as Candidate Biomarkers in FSHD

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Facioscapulohumeral muscular dystrophy (FSHD) is one of the most debilitating and common muscular dystrophies. Despite its severity, no approved therapy exists for FSHD patients. However, several therapeutic candidates are currently under development, and some have recently entered clinical trials, marking the need for reliable ...
Mustafa Bilal Bayazit, Chiranth K. Nagaraj, Jackson S. Newell, Kim Truc Nguyen, Xilal Y. Rima, Jacob Doon‐Ralls, Eduardo Reátegui, Jeffrey M. Statland, Rabi Tawil, Kevin M. Flanigan, Scott Q. Harper, Nizar Y. Saad   +11 more
wiley   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

Complementing Engel Classification: Postoperative Scalp EEG as an Objective Indicator in SEEG‐Guided Radiofrequency Thermocoagulation—A Seizure‐Onset Pattern‐Based Stratified Analysis—

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Stereoelectroencephalography‐guided radiofrequency thermocoagulation (SEEG‐RFTC) is a minimally invasive therapy for drug‐resistant focal epilepsy. However, the relationship between specific seizure‐onset patterns (SOPs), particularly low‐voltage fast activity (LVFA), and postoperative scalp EEG normalization remains inadequately ...
Yi‐qing Yang, Rui Zhang, Haiyan Ma, Lu Yang, Xuefeng Qu, Qiqi Chen, Yan Zhang   +6 more
wiley   +1 more source

Grid cells on the ball

Journal of Statistical Mechanics: Theory and Experiment, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Stella, Federico, SI, BAILU, Kropff, Emilio, Treves, Alessandro   +3 more
openaire   +4 more sources

Models of grid cells and theta oscillations [PDF]

Nature, 2012
Arising from M. M.Yartsev, M. P. Witter & N. Ulanovsky , 103–107 (2011)10.1038/nature10583 Grid cells recorded in the medial entorhinal cortex (MEC) of freely moving rodents show a markedly regular spatial firing pattern whose underlying mechanism has been the subject of intense interest. Yartsev et
Barry, C, Bush, D, O'Keefe, J, Burgess, N   +3 more
openaire   +3 more sources

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Spreading grid cells

CoRR, 2009
Let $S$ be a set of $n^2$ symbols. Let $A$ be an $n\times n$ square grid with each cell labeled by a distinct symbol in $S$. Let $B$ be another $n\times n$ square grid, also with each cell labeled by a distinct symbol in $S$. Then each symbol in $S$ labels two cells, one in $A$ and one in $B$. Define the \emph{combined distance} between two symbols in $
Minghui Jiang 0001, Pedro J. Tejada
openaire   +2 more sources

Grid cells and their potential application in AI

CoRR, 2022
Since their Nobel Prize winning discovery in 2005, grid cells have been studied extensively by neuroscientists. Their multi-scale periodic firing rates tiling the environment as the animal moves around has been shown as critical for path integration. Multiple experiments have shown that grid cells also fire for other representations such as olfactory ...
openaire   +2 more sources

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source