Results 241 to 250 of about 418,224 (320)
Multistage prediction approach of EVs charging performance in smart transportation systems by deep learning technique. [PDF]
Abdelaziz MM +3 more
europepmc +1 more source
Characterization of downwelling radiance measured from a ground-based microwave radiometer using numerical weather prediction model data [PDF]
Myoung‐Hwan Ahn +4 more
openalex +1 more source
Macrophages infiltrate the spinal cord post‐injury, decreasing over time. Microglia phagocytose myelin debris, increasing lipid accumulation. Macrophage deletion improves outcomes, while microglial deletion worsens them. The LD+ microglia subtype shows abnormal Pparg signaling.
Mingran Luo +17 more
wiley +1 more source
Interpretable deep multimodal-based tomato disease diagnosis and severity estimation. [PDF]
Nasir N +7 more
europepmc +1 more source
Depth‐Dependence Changes in Soil Stoichiometry in China's Croplands Over the Past Four Decades
This study reveals depth‐dependent changes in soil C:N:P ratios across Chinese croplands over four decades. Changes in stoichiometry vary markedly between topsoil and subsoil, with initial soil C:N:P ratios playing a key role in determining their trajectories.
Xiaodong Sun +8 more
wiley +1 more source
Short term demand forecasting of electric vehicle charging stations using context aware temporal transformer model. [PDF]
Hussain A +4 more
europepmc +1 more source
Here, a microfluidic‐based robotic lab‐on‐a‐chip (LoC) device is presented for automated, continuous‐flow investigation and manipulation of single pollen tube growth under precisely controlled chemical gradients. This closed‐loop system streamlines data collection and analysis while enhancing experimental precision compared to manual methods ...
Jiawei Zhu +10 more
wiley +1 more source
Forecasting temperature and rainfall using deep learning for the challenging climates of Northern India. [PDF]
Bukhari SNH, Ogudo KA.
europepmc +1 more source
A predictive model for 3D printability is developed by integrating rheological analysis, including the Large Amplitude Oscillatory Shear (LAOS) test, with machine learning. With prediction errors under 10%, the model shows that post‐extrusion recovery controls horizontal printability, while high‐strain‐rate nozzle flow dictates vertical printability ...
Eun Hui Jeong +7 more
wiley +1 more source

