Results 61 to 70 of about 426,517 (268)

Confinement and short distance physics

, 2000
We consider non-perturbative effects at short distances in theories with confinement. The analysis is straightforward within the Abelian models in which the confinement arises on classical level.
Akhoury, Bali, Bali, Buchmuller, Burgio, Casimir, Chetyrkin, Del Debbio, F.V. Gubarev, Fingberg, Gubarev, Huber, M.N. Chernodub, M.V. Polikarpov, Mack, Polyakov, Polyakov, V.I. Zakharov   +17 more
core   +1 more source

Composition‐Tuned Enhancement of the Anomalous Nernst Effect in FeCo–Pt Thin Films on Rigid and Flexible Substrates

Advanced Engineering Materials, EarlyView.
Disordered (Fe50Co50)1−xPtx thin films exhibit a pronounced anomalous Nernst effect (ANE) with a strong composition dependence on both rigid and flexible substrates. The transverse thermoelectric response peaks near 22.5 at.% Pt, accompanied by enhanced αxy/σxy scaling, thermal transport, and ANE sensitivity.
Mojtaba Mohammadi, Hiroyuki Awano, Kenji Tanabe   +2 more
wiley   +1 more source

Interpretable machine learning for atomic scale magnetic anisotropy in quantum materials

npj Computational Materials
The rising demand for digital storage and environmental concerns necessitate ultra-high-density, energy-efficient solutions. Atomic-scale magnets (ASMs) based on transition metal (TM) dimers on defective graphene exhibit promising magnetic anisotropy ...
Jan Navrátil, Rafał Topolnicki, Michal Otyepka, Piotr Błoński   +3 more
doaj   +1 more source

Discerning dynamics in synchrophasor data using topological data analysis

International Journal of Electrical Power & Energy Systems
This paper explores the application of topological data analysis (TDA) for capturing relevant dynamic behavior (modes) in ambient synchrophasor data. In frequency domain, dominant dynamics correspond to prominent spectral peaks, which persist under a ...
Chetan Mishra, Luigi Vanfretti, Jaime Delaree, Jr., Kevin D. Jones   +3 more
doaj   +1 more source

A topological data analysis based classification method for multiple measurements

BMC Bioinformatics, 2020
Background Machine learning models for repeated measurements are limited. Using topological data analysis (TDA), we present a classifier for repeated measurements which samples from the data space and builds a network graph based on the data topology.
Henri Riihimäki, Wojciech Chachólski, Jakob Theorell, Jan Hillert, Ryan Ramanujam   +4 more
doaj   +1 more source

OxCOVID19 Database, a multimodal data repository for better understanding the global impact of COVID-19

Scientific Reports, 2021
Oxford COVID-19 Database (OxCOVID19 Database) is a comprehensive source of information related to the COVID-19 pandemic. This relational database contains time-series data on epidemiology, government responses, mobility, weather and more across time and ...
Adam Mahdi, Piotr Błaszczyk, Paweł Dłotko, Dario Salvi, Tak-Shing Chan, John Harvey, Davide Gurnari, Yue Wu, Ahmad Farhat, Niklas Hellmer, Alexander Zarebski, Bernie Hogan, Lionel Tarassenko   +12 more
doaj   +1 more source

Statistical topological data analysis using persistence landscapes [PDF]

, 2015
We define a new topological summary for data that we call the persistence landscape. Since this summary lies in a vector space, it is easy to combine with tools from statistics and machine learning, in contrast to the standard topological summaries ...
Bubenik, Peter
core  

Additive Manufacturing of Continuous Fibre Reinforced Composites: Process, Characterisation, Modelling, and Sustainability

Advanced Engineering Materials, EarlyView.
Additive manufacturing provides precise control over the placement of continuous fibres within polymer matrices, enabling customised mechanical performance in composite components. This article explores processing strategies, mechanical testing, and modelling approaches for additive manufactured continuous fibre‐reinforced composites.
Cherian Thomas, Amir Hosein Sakhaei
wiley   +1 more source

Persistent Topological Laplacians—A Survey

Mathematics
Persistent topological Laplacians constitute a new class of tools in topological data analysis (TDA). They are motivated by the necessity to address challenges encountered in persistent homology when handling complex data.
Xiaoqi Wei, Guo-Wei Wei
doaj   +1 more source

Tracking collective cell motion by topological data analysis.

PLoS Computational Biology, 2020
By modifying and calibrating an active vertex model to experiments, we have simulated numerically a confluent cellular monolayer spreading on an empty space and the collision of two monolayers of different cells in an antagonistic migration assay.
Luis L Bonilla, Ana Carpio, Carolina Trenado   +2 more
doaj   +1 more source