Results 151 to 160 of about 77,814,939 (211)

Robotics in Ionizing Radiation Environments: Vulnerabilities, Hardening, and Future Directions

Advanced Robotics Research, EarlyView.
Radiation exposure causes cumulative degradation in robotic sensors, actuators, and electronic logic, often leading to undetected failures. This study maps component vulnerabilities, evaluates hardening and shielding strategies, and identifies testing gaps that must be addressed to enable next‐generation radiation‐tolerant robotic systems.
Francis A. K. Djirackor, Josephine T. Djirackor, Amanuel Abrdo Tereda, Sun Yi, Younho Seong   +4 more
wiley   +1 more source

Iran road map 1:2 500 000 [cartographic material] /

, 1956
Ed.2-AMS. Road map of Iran showing international and ostan boundaries, transportation, water features and populated places. Relief shown by shading and spot heights.; Includes glossary and diagram of ostan boundaries.; "Series K201".; Also available ...
United States. Army Map Service.
core  

Consensus Formation and Change are Enhanced by Neutrality

Advanced Science, EarlyView.
Neutral agents are shown to enhance both the formation and overturning of consensus in collective decision‐making. A general mathematical model and experiments with locusts and humans reveal that neutrality enables robust consensus via simple interactions and accelerates consensus change by reducing effective population size.
Andrei Sontag, Janina A. Hoffmann, Tim Rogers, Christian A. Yates   +3 more
wiley   +1 more source

Memory and Identity in the Emotive Map of Alain Resnais’ Hiroshima Mon Amour (1959)

, 2014
The focus of this article is Alain Resnais’ representation of collective and individual memory and identity in Hiroshima Mon Amour (1959). The film is based on Marguerite Duras’ script from 1958 and remains faithful to this original text.
Jytte Holmqvist
core  

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source

Neural Fields for Highly Accelerated 2D Cine Phase Contrast MRI

Advanced Science, EarlyView.
ABSTRACT 2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal
Pablo Arratia, Martin J. Graves, Mary McLean, Carolin Pirkl, Carola‐Bibiane Schönlieb, Timo Schirmer, Florian Wiesinger, Matthias J. Ehrhardt   +7 more
wiley   +1 more source

A Critical Time Window of Neocortex Modulation for Remote Fear Memory in Rats and Humans

Advanced Science, EarlyView.
This study identifies a delayed consolidation window around 18 h after fear learning in the mPFC essential for remote fear memory. VTA dopaminergic input during this window sustains remote memory in rats, while non‐invasive stimulation of homologous human mPFC at the corresponding time selectively weakens remote but not recent fear memory, revealing a ...
Lu Cao, Yu‐Xin Zhang, Xiao‐Xing Liu, Zi‐Hang Li, Tang‐Sheng Lu, Jia‐Hui Deng, Wen Zhang, Peng Li, Xiao Lin, Shu‐Fei Feng, Ting‐Ting Li, Shi‐Qiu Meng, Xiang‐Dong Tang, Tian‐Ye Jia, Trevor W. Robbins, Jie Shi, Ying Han, Yan‐Xue Xue, Lin Lu, Kai Yuan   +19 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

Advanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li, Kelly Yichen Li, Chiara Nicoletti, Stephen Kwok‐Wing Tsui, Pier Lorenzo Puri, Qin Cao, Kevin Y. Yip   +6 more
wiley   +1 more source