Results 221 to 230 of about 389,689 (283)

Bayesian deep learning for probabilistic aquifer vulnerability and uncertainty prediction. [PDF]

Sci Rep
Mengistu TD, Kim MG, Chung IM, Chang SW.
europepmc   +1 more source

Intelligent Acousto‐Electrical Metamaterials (IAM) for Sound Source Detection

Advanced Materials, EarlyView.
Our proposed metamaterial concept enables sound source detection using a single material, in contrast to conventional arrays that require dozens or even hundreds of transducers. We show that the coupled acoustic–vibrational–electrical responses in piezoelectric metamaterials give rise to topology‐governed charge transport, producing distinct voltage ...
Victor Couëdel, Haotian Lu, Jiayan Zhang, Desheng Yao, Ananya Bhardwaj, Ramiro Contreras, Karim Sabra, Xiaoyu (Rayne) Zheng   +7 more
wiley   +1 more source

Bayesian networks for predicting clinical outcomes in COVID-19 patients: A retrospective study in a resource-limited setting. [PDF]

PLoS One
Filamant TC, Raherinirina AF, Totohasina A.   +2 more
europepmc   +1 more source

Triply‐Twinned Metamaterials: Unraveling the Mechanics and Failure Pathways Through High‐Resolution XCT

Advanced Materials, EarlyView.
Triply‐twinned architected lattices transform deformation from bending to stretching of struts, delivering up to threefold increases in stiffness and strength across polymeric and metallic systems. High‐resolution synchrotron XCT and image‐based simulations reveal how meta‐grain architecture, defects, and AM build orientation govern failure pathways ...
David McArthur, George Maddison, Jaianth Vijayakumar, Paul Tafforeau, Kathy Christofidou, Peter David Lee, PJ Tan, Chu Lun Alex Leung   +7 more
wiley   +1 more source

Subway door fault prediction employing stacking ensemble learning. [PDF]

Sci Rep
Song H, Tang S, Xia J, Zhang L, Kang H, Li P.   +5 more
europepmc   +1 more source

Light‐Induced Entropy for Secure Vision

Advanced Materials, EarlyView.
This work realized a ternary true random number generator by exploiting stochastic traps emerging within multiple junction interfaces, and quantitatively validated the generation of high‐quality random numbers. Furthermore, it successfully demonstrated diverse applications, including AI‐resilient image security, thereby providing a valuable guide for ...
Juhyung Seo, Seungme Kang, Chaehyun Kim, Taehyun Park, Youngwoo Yoo, Yeong Kwon Kim, Wonjun Shin, Byung Chul Jang, Young‐Joon Kim, Hocheon Yoo   +9 more
wiley   +1 more source

Cost-Effectiveness of a Quality of Life Predictor to Guide Psychosocial Support in Breast Cancer. [PDF]

Cancers (Basel)
Hakkarainen T, Haavisto I, Nuutinen M, Hynninen Y, Poikonen-Saksela P, Mattson J, Kondylak H, Kolokotroni E, Mazzocco K, Sousa B, Manica I, Pat-Horenczyk R, Leskelä RL.   +12 more
europepmc   +1 more source

DengueGNN: Graph-based deep learning for modeling disease spread dynamics and prediction. [PDF]

Sci Rep
GulMohamed RB, Hetany W, Almaimani HA, Khiery FAS.   +3 more
europepmc   +1 more source

ArchesWeatherGen: Skillful and compute-efficient probabilistic weather forecasting with machine learning. [PDF]

Sci Adv
Couairon G, Singh R, Charantonis A, Lessig C, Monteleoni C.   +4 more
europepmc   +1 more source

Hybrid Deep Learning Model for EI-MS Spectra Prediction. [PDF]

Int J Mol Sci
Majewski B, Łabuda M.
europepmc   +1 more source