Results 171 to 180 of about 46,986 (307)
Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly +2 more
wiley +1 more source
In order to solve the problems of the poor adaptability to nonlinear systems, cumbersome parameter adjustment, and sensing-execution delay facing PID control for trawl winch tension control on fishing vessels, a prediction model for trawl winch cable ...
Quanliang Liu, Ya Wang, Mingwei Xu
core +1 more source
[Application effects of feedforward control theory in the rollover bed treatment of mass patients with burn-explosion combined injury]. [PDF]
Chen HQ +7 more
europepmc +1 more source
Solid–liquid triboelectric nanogenerators are conceptualized as dynamic physicochemical encoders that encode intrinsic liquid properties into distinguishable triboelectric fingerprints. This review provides a unified framework for these platforms, covering sensing mechanisms in droplet impact, continuous flow, and immersion modes.
Mingrui Wang +8 more
wiley +1 more source
The importance of gene polymorphism in familial inheritance of endometriosis
Abstract Objective The study aimed to investigate familial transmission patterns in women with endometriosis by generating a customized single‐nucleotide polymorphism (SNP) array. Methods Patients aged 18–45 who were diagnosed histopathologically with endometriosis were included in the study.
Hale Goksever Celik +4 more
wiley +1 more source
This study presents a SnSe2/DNTT heterostructure photonic synaptic transistor that exhibits wavelength‐dependent photoresponses and synaptic plasticity. Operating with low energy consumption, the device extends spectral sensitivity from ultraviolet (UV) to near‐infrared (NIR) wavelengths, significantly enhancing neuromorphic computing performance. When
Shuying He +7 more
wiley +1 more source
ABSTRACT Accurate estimation of reference evapotranspiration (ET0) and crop coefficients (Kc) is critical for irrigation planning, particularly in data‐limited regions where agriculture dominates freshwater consumption. Although machine learning (ML) methods have been widely applied to ET0 and Kc estimation, most studies address these parameters ...
Ilker Angin +4 more
wiley +1 more source
Feedforward Control for Single Particle Tracking Synthetic Motion. [PDF]
Vickers NA, Andersson SB.
europepmc +1 more source
Optimizing feather hydrolysate via machine learning for microbial recycling of waste concrete fines
Abstract BACKGROUND The concrete industry faces significant challenges from CO2 emissions and the disposal of waste concrete fines (WCF). Microbially induced calcite precipitation (MICP) can bind WCF into bioconcrete, but the high cost of commercial culture media hinders its application.
Henrietta Ottová +5 more
wiley +1 more source
Mapping the Landscape of Over‐Scanning in CT Imaging: A Scoping Review
Over‐scanning in CT is highly prevalent and contributes to unnecessary radiation exposure, with notable impact on radiosensitive organs. Standardised protocols and AI‐assisted planning show strong potential to optimise scan range and reduce excess dose.
Mo'men Bani‐Ahmad +5 more
wiley +1 more source

