Results 91 to 100 of about 211,113 (260)

One-loop quantization of Euclidean D3-branes in holographic backgrounds

Journal of High Energy Physics
In this note we analyze the semi-classical quantization of D3-branes in three different holographic backgrounds in type IIB string theory. The first background is Euclidean AdS5 with S 1 × S 3 boundary accompanied with a twist to preserve supersymmetry ...
Friðrik Freyr Gautason, Jesse van Muiden   +1 more
doaj   +1 more source

Holography, probe branes and isoperimetric inequalities

Physics Letters B, 2015
In many instances of holographic correspondences between a d-dimensional boundary theory and a (d+1)-dimensional bulk, a direct argument in the boundary theory implies that there must exist a simple and precise relation between the Euclidean on-shell ...
Frank Ferrari, Antonin Rovai
doaj   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

Advanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Manifold Learning via the Principle Bundle Approach

Frontiers in Applied Mathematics and Statistics, 2018
In this paper, we propose a novel principal bundle model and apply it to the image denoising problem. This model is based on the fact that the patch manifold admits canonical groups actions such as rotation.
Chen-Yun Lin, Arin Minasian, Xin Jessica Qi, Hau-Tieng Wu, Hau-Tieng Wu, Hau-Tieng Wu   +5 more
doaj   +1 more source

Discovery of Novel Materials with Giant Dielectric Constants via First‐Principles Phonon Calculations and Machine Learning

Advanced Intelligent Discovery, EarlyView.
We discovered novel materials with giant dielectric constants by combining first‐principles phonon calculations and machine learning. Screening 525 perovskites identified six candidates. RbNbO3 was synthesized under pressure and showed ε ≈ 800–1000. This validates our framework as a powerful tool for high‐performance dielectric materials discovery.
Hiroki Moriwake, Kazuki Shitara, Rie Yokoi, Takeharu Kato, Isao Tanaka, Ayako Yamamoto, Kimitoshi Murase, Yosuke Hamasaiki, Yoshitaka Ehara, Mitsuru Itoh   +9 more
wiley   +1 more source

Log‐Euclidean bag of words for human action recognition

IET Computer Vision, 2015
Representing videos by densely extracted local space–time features has recently become a popular approach for analysing actions. In this study, the authors tackle the problem of categorising human actions by devising bag of words (BoWs) models based on ...
Masoud Faraki, Maziar Palhang, Conrad Sanderson   +2 more
doaj   +1 more source

Skin‐Conformal Myography for Real‐Time Hand Tracking Using a Laser‐Induced Graphene Strain Sensor Array

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A skin‐conformal wearable device based on laser‐induced graphene is developed for continuous strain measurement across the circumference of the forearm for gesture recognition and hand‐tracking applications. Post material optimization, the strain sensor array is integrated with a wearable wireless readout circuit for real‐time control of a robotic arm,
Vinay Kammarchedu, Monther AlSiyabi, Aida Ebrahimi   +2 more
wiley   +1 more source

On the design and evaluation of generative models in high energy density physics

Communications Physics
Understanding high energy density physics (HEDP) is critical for advancements in fusion energy and astrophysics. The computational demands of the computer models used for HEDP studies have led researchers to explore deep learning methods to enhance ...
Ankita Shukla, Yamen Mubarka, Rushil Anirudh, Eugene Kur, Derek Mariscal, Blagoje Djordjevic, Bogdan Kustowski, Kelly Swanson, Brian Spears, Peer-Timo Bremer, Tammy Ma, Pavan Turaga, Jayaraman J. Thiagarajan   +12 more
doaj   +1 more source

Benoit Mandelbrot (1924 - 2011 ) : A Greek among Romans [PDF]

Posthumous tributes to Benoit Mandelbrot (1924-2010) have highlighted his remarkable influence on the natural sciences, from geometry to meteorology, to theories with non-Euclidean spaces and geospatial models approach.
Estrada, Fernando
core   +1 more source