Results 111 to 120 of about 84,381 (353)

Harnessing Phase Dynamics Across Diverse Frequencies with Multifrequency Oscillatory Neural Networks

Advanced Intelligent Discovery, EarlyView.
Oscillatory Neural Networks (ONNs) are an emerging computing paradigm that encodes information in the phases of coupled oscillators. Traditionally, ONNs have been investigated using homogeneous frequency oscillators. However, physical hardware implementations are inherently subject to frequency mismatches, device variability, and nonuniformities.
Nil Dinç, Filip Sabo, Aida Todri‐Sanial   +2 more
wiley   +1 more source

Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets

Advanced Intelligent Discovery, EarlyView.
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh, Anton Bolyachkin, Hajime Nakamura, Tadakatsu Ohkubo, Hossein Sepehri‐Amin   +4 more
wiley   +1 more source

Climate change and perennial crop production: Evidence of yield impact and adaptation in California

American Journal of Agricultural Economics, EarlyView.
Abstract Perennial crops are economically important. They contribute to food security, providing essential nutrients that are often lacking in annual crops, and provide additional environmental benefits compared with annual crops. Despite their importance, empirical research on the impacts of climate change and adaptation on perennial crops remains ...
Yuanyuan Wen, Wei Zhang, Julian M. Alston   +2 more
wiley   +1 more source

Spatial Downscaling of Nighttime Land Surface Temperature Based on Geographically Neural Network Weighted Regression Kriging

Remote Sensing
Land surface temperature (LST) has a wide application in Earth Science-related fields, and spatial downscaling is an important method to retrieve high-resolution LST data.
Jihan Wang, Nan Zhang, Laifu Zhang, Haoyu Jing, Yiming Yan, Sensen Wu, Renyi Liu   +6 more
doaj   +1 more source

Ecological niche modeling reveals habitat differentiation and climatic vulnerability in two imperiled, sympatric southern Appalachian carnivorous plants

American Journal of Botany, EarlyView.
Abstract Premise Understanding the habitat requirements of imperiled flora is critical for informing ex situ conservation practices, designing effective reintroduction strategies, and understanding how climate change will impact such species, especially in montane regions with high levels of environmental heterogeneity. In southern Appalachia, USA, the
Nicholas J. Chang, Lauren Eserman, Amanda Carmichael, Adam B. Smith, Xingwen Loy, Emily E. D. Coffey, James Ojascastro   +6 more
wiley   +1 more source

Differences between Machine Learning and Traditional Downscaling Method in Processing Summer Meteorological Elements in the Yellow River Basin

Gaoyuan qixiang
Global Climate Models （GCMs） are the primary tools currently used to predict future climate change； however， their coarse spatial resolution limits their ability to assess localized impacts of climate change.To address this issue， statistical downscaling
Han CHEN, Xiaodan GUAN, Tingting MA
doaj   +1 more source

DL4DS - Deep Learning for empirical DownScaling [PDF]

, 2022
Carlos Gómez González
openalex   +1 more source

High‐elevation endemic plants predicted to lose habitat from changing climate in Washington State

American Journal of Botany, EarlyView.
Abstract Premise High‐elevation plants face unique challenges from potential climate change impacts that will likely require upslope migration into increasingly smaller suitable habitat. This situation is particularly acute for endemic species that by definition occupy small geographic ranges.
Nicholas L. Gjording, Erik W. Ertsgaard, David E. Giblin, Iris H. Dimpsey, Owen B. Bard   +4 more
wiley   +1 more source

Green Hydrogen for Public Transportation: Insights From an ABM and From Palma de Mallorca Case Study

Business Strategy and the Environment, EarlyView.
ABSTRACT The development of green hydrogen (GH2) value chains is crucial for decarbonizing sectors such as transport and industry. Their emergence, however, requires coordination among diverse actors, technologies, and regulations, which traditional analytical approaches struggle to capture.
Roberta De Cristofaro, Cristina Ponsiglione, Simonetta Primario   +2 more
wiley   +1 more source

Gaborlet‐guided sparse filtering: A novel intelligent method for lithology identification by vibration signals while drilling

Deep Underground Science and Engineering, EarlyView.
The flowchart illustrates rock specimen testing, vibration signal acquisition, and feature extraction with Gaborlet and sparse filtering for classification. Abstract Traditional lithology identification methods mainly rely on core sampling and well‐logging data.
Jian Hao, Danqi Zhang, Zhenqi Song, Jinrui Wang, Qi Wang, Heqing Liu   +5 more
wiley   +1 more source