Results 181 to 190 of about 224,776 (267)
The spread of non‐native species
Biological Reviews, EarlyView.ABSTRACT The global redistribution of species through human agency is one of the defining ecological signatures of the Anthropocene, with biological invasions reshaping biodiversity patterns, ecosystem processes and services, and species interactions globally.
Phillip J. Haubrock +16 more
wiley +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT Investors have long recognized the importance of firms in promoting sustainability, leading to the rise of socially responsible investment (SRI). Specifically, there is a growing preference for exchange‐traded funds (ETFs) that prioritize environmental, social, and governance (ESG) principles.
Sandra Tenorio‐Salgueiro +3 more
wiley +1 more source
Business Strategy and the Environment, EarlyView.ABSTRACT This study examines the economic consequences of Digital Technologies Disclosure (DTD), focusing on its impact on the cost of capital. The increasing significance of digital transformation in shaping corporate strategies and market perceptions motivates the study.
Hussein Mohsen Saber Ahmed +2 more
wiley +1 more source
Biotechnology Progress, EarlyView.Abstract Artificial intelligence and automation are no longer just buzzwords in the biopharmaceutical industry. The manufacturing of a class of biologics, comprising monoclonal antibodies, cell therapies, and gene therapies, is far more complex than that of traditional small molecule drugs.
Shyam Panjwani, Hao Wei, John Mason
wiley +1 more source
Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions
Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
wiley +1 more source
Data‐Driven Design of Scalable Perovskite Film Fabrication via Machine Learning–Guided Processing
Carbon Energy, EarlyView.Considering complex process parameters and poor reproducibility in perovskite thin film fabrication, this study uses machine learning to analyze and predict high‐dimensional process variables. The Random Forest model, identified as the most effective, can effectively analyze and rapidly predict optimal process parameters from extensive data.
Hong Liu +9 more
wiley +1 more source
Bayesian neural networks for detecting epistasis in genetic association studies. [PDF]
BMC Bioinformatics, 2014 Beam AL, Motsinger-Reif A, Doyle J.
europepmc +1 more source
Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches
Chemistry – A European Journal, EarlyView.Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Bidhan Chandra Garain +3 more
wiley +1 more source
An observation‐driven state‐space model for claims size modelling
Canadian Journal of Statistics, EarlyView.Abstract State‐space models are popular in econometrics. Recently, these models have gained some popularity in the actuarial literature. The best known state‐space models are of the Kalman‐filter type. These are called parameter‐driven because the observations do not impact the state‐space dynamics.
Jae Youn Ahn +2 more
wiley +1 more source
Neural mechanisms of flexible perceptual inference. [PDF]
PLoS Comput BiolSchwarcz J +6 more
europepmc +1 more source