Results 61 to 70 of about 93,046 (267)

OpenSeismoMatlab: New Features, Verification and Charting Future Endeavors

Buildings
To facilitate the precise design of earthquake-resistant structures, it is imperative to accurately evaluate the impact of seismic events on these constructions and predict their responses.
George Papazafeiropoulos, Vagelis Plevris   +1 more
doaj   +1 more source

Multiobjective Codesign Optimization of a Planar Pneumatic Artificial Muscle‐Based Snake‐Like Robot for Enhanced Agility and Energy Efficiency

Advanced Robotics Research, EarlyView.
A codesign multiobjective optimization framework was developed to enhance the morphology and controller of a snake‐like robot driven by artificial muscles. It improved planar locomotion, agility, and power efficiency. The approach optimized link geometry and controller gains, revealing that shorter muscles near joints and longer linkages maximize ...
Ayla Valles, Mahdi Haghshenas‐Jaryani
wiley   +1 more source

Microscale Mapping of Fiber Strain and Damage in Composite Wrinkled Laminates Using Computed Tomography Assisted Wide‐Angle X‐Ray Scattering

Advanced Science, EarlyView.
This study combines full‐field tomography with diffraction mapping to quantify radial (ε002$\varepsilon _{002}$) and axial (ε100$\varepsilon _{100}$) lattice strain in wrinkled carbon‐fiber specimens for the first time. Radial microstrain gradients (−14.5 µεMPa$\varepsilon \mathrm{MPa}$−1) are found to signal damage‐prone zones ahead of failure, which ...
Hoang Minh Luong, James Trevarthen, Igor Dolbnya, Wadwan Singhapong, Nicholas Pilato, Richard Butler, Jiraphant Srisuriyachot, Alexander J. G. Lunt   +7 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

Resampling strategies for regression

Expert Systems, 2014
AbstractSeveral real world prediction problems involve forecasting rare values of a target variable. When this variable is nominal, we have a problem of class imbalance that was thoroughly studied within machine learning. For regression tasks, where the target variable is continuous, few works exist addressing this type of problem.
Luís Torgo, Paula Branco, Rita P. Ribeiro, Bernhard Pfahringer   +3 more
openaire   +2 more sources

Gm26550 Modulates Learning and Memory by Increasing IGF1 mRNA Expression and Stability in Nrf2−/− Mice

Advanced Science, EarlyView.
The present study shows that Nrf2 directly binds to the Gm26550 promoter, thereby activating Gm26550 transcription and increasing its expression. Mechanistically, Gm26550 promotes IGF1 expression by functionally antagonizing miR‐26a‐5p‐mediated repression and sequestering the RBP KHSRP, thereby enhancing hippocampal neuronal synaptic plasticity and ...
Hongfang Wang, Ziyao Wang, Dongyue Zuo, Zhaowen Su, Bowen Song, Jiamin Gao, Yizhou Zhang, Ruiting Zhao, Linjie Sun, Mengdi Li, Yirui Fan, Dandan Geng, Lei Wang   +12 more
wiley   +1 more source

Point Cloud Registration for Lava Tube Surface Reconstruction Using Curvature-Optimized Projection

IEEE Access
The surface reconstruction of point clouds is a key technology in lunar exploration. The generation of high-precision three-dimensional models of lunar lava tubes via surface reconstruction provides technical support for subsequent exploration.
Jiaqi Yao, Yanqiu Wang, Wen Li, Yuan Han, Hognxu Ai, Zhenchen Ji, Fu Zheng, Zhibin Sun   +7 more
doaj   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source

Tamanho de amostra para a estimação da média do comprimento, diâmetro e massa de sementes de feijão de porco e mucuna cinza Sample size for estimating the average length, diameter and weight of seeds of jack bean and velvet bean

Ciência Rural, 2012
O objetivo deste trabalho foi determinar o tamanho de amostra necessário para a estimação da média do comprimento, dos diâmetros maior e menor e da massa de sementes de feijão de porco (Canavalia ensiformis) e de mucuna cinza (Stizolobium cinereum).
Alberto Cargnelutti Filho, Marcos Toebe, Cláudia Burin, André Luis Fick, Bruna Mendonça Alves, Giovani Facco   +5 more
doaj  

Physics‐Constrained Constitutive Learning of Rate‐Limiting Timescales for Efficient Hydrogen‐Based Direct Reduction for Green Steel Making

Advanced Science, EarlyView.
A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai, Barak Ratzker, Pasquale Cavaliere, Dierk Raabe   +3 more
wiley   +1 more source