Results 151 to 160 of about 36,209 (267)
XGBoost prediction of adverse neurodevelopmental outcomes in hypoxic-ischemic encephalopathy neonates. [PDF]
Kim TY, Park HM, Youn YA.
europepmc +1 more source
ABSTRACT Despite growing attention to the circular bioeconomy (CBE), the steel industry currently lacks a standardised, sectoral measurement framework to facilitate a low‐carbon transition. In this study, a decision‐support framework for evaluating CBE performance in the steel industry is proposed.
Ali Zamani Babgohari +2 more
wiley +1 more source
Evaluating comorbidity scoring systems for flumatinib therapy in chronic myeloid leukemia: a machine learning and SHAP-based predictive analysis. [PDF]
Yang Y, Li Y, Wang J.
europepmc +1 more source
Do Banks in the Middle East and North Africa Region Price Carbon Exposure?
ABSTRACT This study examines whether carbon exposure is incorporated into corporate borrowing costs within the Middle East and North Africa (MENA) region. Using a panel of 771 firm‐year observations from publicly listed non‐financial firms between 2016 and 2023, the analysis investigates the relationship between carbon intensity and firms' cost of debt
Yara Ibrahim +2 more
wiley +1 more source
ABSTRACT Prior research has mostly relied on linear and parametric models while explaining environmental non‐compliance, but they have a limited capacity to capture non‐linear and asymmetric effects of elements affecting firms' environmental compliance.
Ashutosh Singh +4 more
wiley +1 more source
ABSTRACT Predicting corporate environmental violations remains a key challenge in practice and in environmental governance research. However, existing studies have largely focused on ex post associations between stakeholder pressures and realized environmental violations, offering limited insight into whether stakeholder pressures can be used ex ante ...
Xiaolan Chen +4 more
wiley +1 more source
Optimized ML framework for predicting RP and Dj phases in perovskite solar cells. ABSTRACT Two‐dimensional (2D) lead halide perovskites (LHPs) have captured a range of interest for the advancement of state‐of‐the‐art optoelectronic devices, highly efficient solar cells, next‐generation energy harvesting technologies owing to their hydrophobic nature ...
Basir Akbar, Kil To Chong, Hilal Tayara
wiley +1 more source
ABSTRACT Biochar has emerged as a useful and adaptable source of carbon for supercapacitor electrodes. Its value comes from the way biomass chemistry, thermal conversion, and activation conditions shape the resulting pore network, surface groups, and degree of carbon ordering.
Soumen Mandal +6 more
wiley +1 more source
Porous Carbon Materials for Carbon Dioxide Capture
This work aims to address the current status and challenges associated with the regulation of pore structures, as well as the influence of pore structures on CO2 capture. Systematic quantitative analysis of structure–property relationships, combined with machine learning approaches, can effectively evaluate the contributions of structural ...
Zhifu Liu +6 more
wiley +1 more source
Machine Learning Paradigm for Advanced Battery Electrolyte Development
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

