Results 151 to 160 of about 1,334,722 (325)
Research on time series prediction of hybrid intelligent systems based on deep learning
Power forecasting plays a crucial role in the operation of smart grid system, which is indispensable for making the operation plan of power system, improving economic efficiency and ensuring the quality of power supply.
Shang Jin +3 more
doaj +1 more source
This study examines how pore shape and manufacturing‐induced deviations affect the mechanical properties of 3D‐printed lattice materials with constant porosity. Combining µ‐CT analysis, FEM, and compression testing, the authors show that structural imperfections reduce stiffness and strength, while bulk material inhomogeneities probably enhance ...
Oliver Walker +5 more
wiley +1 more source
Reevaluating the Activity of ZIF‐8 Based FeNCs for Electrochemical Ammonia Production
Though receiving much attention, the field of electrochemical nitrogen reduction reaction (eNRR) to ammonia is marked by doubts about whether this reaction is possible in aqueous media. This work sheds light on this question for iron single‐atom on N‐doped carbon (FeNC) catalysts—a class of well‐known catalysts that is also worth testing for the sister
Caroline Schneider +6 more
wiley +1 more source
The Order Barrier for Strong Approximation of Rough Volatility Models
We study the strong approximation of a rough volatility model, in which the log-volatility is given by a fractional Ornstein-Uhlenbeck process with Hurst parameter ...
Neuenkirch, Andreas, Shalaiko, Taras
core
Implementation of Drug‐Induced Rhabdomyolysis and Acute Kidney Injury in Microphysiological System
A modular Muscle–Kidney proximal tubule‐on‐a‐chip integrates 3D skeletal muscle and renal proximal tubule tissues to model drug‐induced rhabdomyolysis and acute kidney injury. The coculture system enables dynamic tissue interaction, functional contraction monitoring, and quantification of nephrotoxicity, revealing drug side effect‐induced metabolic ...
Jaesang Kim +4 more
wiley +1 more source
A miniaturized mechano‐acoustic sensor is developed using an electrospun PVDF nanomesh as the diaphragm in a capacitive sensor structure. Unlike conventional nanomesh‐based sensors, it achieves high linear sensitivity, a broad and flat frequency response, and a compact form factor.
Jeng‐Hun Lee +8 more
wiley +1 more source
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Multiband Switchable Microwave Absorbing Metamaterials Based on Reconfigurable Kirigami–Origami
A reconfigurable metamaterial featuring tunable microwave‐absorbing and load‐bearing performance is proposed. Stretchable kirigami and bistable origami configurations are integrated as actuating components, and the synergistic deformation mechanisms are systematically analyzed.
Weimin Ding +7 more
wiley +1 more source
Fitting Heterogeneous Lanchester Models on the Kursk Campaign
The battle of Kursk between Soviet and German is known to be the biggest tank battle in the history. The present paper uses the tank and artillery data from the Kursk database for fitting both forms of homogeneous and heterogeneous Lanchester model ...
Das, Sumanta Kumar
core

