Results 251 to 260 of about 235,639 (329)

BN-BacArena: Bayesian network extension of BacArena for the dynamic simulation of microbial communities

open access: gold
Telmo Blasco   +8 more
openalex   +1 more source

Climate Stress Testing on European SME Securitised Loans Under Climate Mitigation Scenarios

open access: yesBusiness Strategy and the Environment, EarlyView.
ABSTRACT Assessing the future impact of climate risks on the probability of default (PD) of small and medium enterprises (SMEs) is challenging due to limited disclosure, policy uncertainty and exposure to physical risks. This paper addresses this gap by integrating macroeconomic variables from the Network for Greening the Financial System (NGFS ...
Luca Zanin, Raffaella Calabrese
wiley   +1 more source

Consumer Adoption of Internet of Things

open access: yesJournal of Consumer Behaviour, Volume 24, Issue 2, Page 673-693, March 2025.
ABSTRACT The Internet of Things (IoT), a pivotal technology in enhancing user connectivity, faces a paradox: its widespread potential yet limited consumer adoption. This study addresses this dichotomy by synthesizing a large‐scale meta‐analytic structural equation modeling (MASEM) and hierarchical linear meta‐analysis (HiLMA) of 2736 effect sizes from ...
Wagner Junior Ladeira   +6 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

open access: yesCarbon Energy, EarlyView.
Electrolyte materials determine ion transport kinetics within the bulk and interphases, ultimately influencing the performance of battery systems. As data‐driven paradigms increasingly reshape materials discovery, this review provides an application‐oriented exploration of the intersection between machine learning and electrolyte science. By evaluating
Chang Su   +4 more
wiley   +1 more source

Data‐driven simulation of crude distillation using Aspen HYSYS and comparative machine learning models

open access: yesThe Canadian Journal of Chemical Engineering, EarlyView.
Integrated Aspen HYSYS–machine learning framework for predicting product yields and quality variables. Abstract Crude oil refining is a complex process requiring precise modelling to optimize yield, quality, and efficiency. This study integrates Aspen HYSYS® simulations with machine learning techniques to develop predictive models for key refinery ...
Aldimiro Paixão Domingos   +3 more
wiley   +1 more source

Home - About - Disclaimer - Privacy