Results 71 to 80 of about 11,549 (247)

A Comparison of ETKF and Downscaling in a Regional Ensemble Prediction System

Atmosphere, 2015
Based on the operational regional ensemble prediction system (REPS) in China Meteorological Administration (CMA), this paper carried out comparison of two initial condition perturbation methods: an ensemble transform Kalman filter (ETKF) and a dynamical
Hanbin Zhang, Jing Chen, Xiefei Zhi, Yanan Wang   +3 more
doaj   +1 more source

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

Large‐Scale and Highly Reliable Hopfield Neural Networks Using Vertical NAND Flash Memory for the In‐Memory Associative Computing

Advanced Intelligent Systems, EarlyView.
Large‐scale Hopfield neural networks (HNNs) for associative computing are implemented using vertical NAND (VNAND) flash memory. The proposed VNAND HNN with the asynchronous update scenario achieve robust image restoration performance despite fabrication variations, while significantly reducing chip area (≈117× smaller than resistive random‐access ...
Jin Ho Chang, Jae Seung Woo, Suk‐Kang Sung, Ki‐Whan Song, Woo Young Choi   +4 more
wiley   +1 more source

Data‐Driven Modeling of Forces Exerted by Pneumatic Actuators for a Pediatric Exosuit

Advanced Intelligent Systems, EarlyView.
This work presents the experimental analysis and data‐driven modeling of the interaction forces between soft pneumatic actuators designed to assist upper‐extremity motion in a pediatric exosuit and an engineered test rig, across different experimental conditions: (A) force profiling of shoulder actuators, with varying actuator anchoring points and ...
Mehrnoosh Ayazi, Ipsita Sahin, Caio Mucchiani, Elena Kokkoni, Konstantinos Karydis   +4 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

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

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

The myth of the metabolic baseline: sleep–wake cycles undermine a foundational assumption in organismal biology

Biological Reviews, EarlyView.
ABSTRACT Basal and standard metabolic rate (BMR and SMR) are cornerstones of physiological ecology and are assumed to be relatively fixed intrinsic properties of organisms that represent the minimum energy required to sustain life. However, this assumption is conceptually flawed. Many core maintenance processes underlying SMR are temporally partitioned
Helena Norman, Daphne Cortese, Amelia Munson, Jan Lindström, Shaun S. Killen   +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