Results 171 to 180 of about 145,710 (264)

BAMITA: Bayesian multiple imputation for tensor arrays. [PDF]

Biostatistics
Jiang Z, Li G, Lock EF.
europepmc   +1 more source

Exploring the Role of Green Training on Organizational Resilience: A Multisectoral European Analysis

Business Strategy and the Environment, EarlyView.
ABSTRACT The double transition paradigm has imposed to redefine the rules to compete. The demand for green skills, driven by European policy targets, currently outpaces the supply available in the labor market. This study surveys European companies across multiple sectors to assess the role of green training, a key element of green human resource ...
Giulia Alessandri, Fabio Iannone, Annamaria Pesci, Tiberio Daddi, Fabio Iraldo   +4 more
wiley   +1 more source

Ninja optimization algorithm based ultra wideband antenna electromagnetic band gap modeling via a generative adversarial network. [PDF]

Sci Rep
Alhussan AA, Khafaga DS, El-Kenawy EM, Abdelhamid AA, Ibrahim A, Singla MK, Gupta J, Gupta A, Thakur E, Eid MM.   +9 more
europepmc   +1 more source

Does Managerial Ability Improve Environmental Performance and Overall ESG Ratings? The Impact of the European Sustainability Reporting Mandate

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines the role of managerial ability in driving environmental performance and overall environmental, social, and governance (ESG) ratings in the context of the European Union sustainability reporting regulations. Using a sample of 7242 firm‐year observations over the period 2015–2023, our results indicate a structural change in ...
Mihaela Ionașcu, Ion Ionașcu, Elena Turuianu   +2 more
wiley   +1 more source

Establishment of accurate estimation equations for area under the concentration curves using simultaneous limited sampling for extended-release tacrolimus and mycophenolic acid in kidney transplant recipients. [PDF]

Front Immunol
Minamisono K, Nakao T, Ohyama T, Nishida S, Sasaki H, Hirose T, Hotta K, Mieno M, Iwami D.   +8 more
europepmc   +1 more source

Do Governance Structures Drive Green Building Adoption? A Machine Learning Approach With Random Forests

Business Strategy and the Environment, EarlyView.
ABSTRACT This study examines the determinants of firms' propensity to adopt green buildings in the Euro Stoxx 300 and the S&P 500 indices, during 2012–2023. Using random forest binary classifiers, we assess the relative importance of financial, sectoral, geographic, and climate governance predictors and uncover nonlinear relationships often overlooked ...
María del Carmen Valls Martínez, José Manuel Santos‐Jaén, María Estefanía Sánchez Pacheco, Fernando José Zambrano Farías   +3 more
wiley   +1 more source

Data-driven regression analysis of amylose using Sombor molecular descriptors. [PDF]

Sci Rep
Mufti ZS, Asim M, Shflot AS, Saeed ST, Younis J.   +4 more
europepmc   +1 more source

Innovation Pathways to Carbon Efficiency: Disentangling the Effects of AI, R&D, and Clean Energy Blessings on U.S. Environmental Sustainability

Business Strategy and the Environment, EarlyView.
ABSTRACT The United States (U.S.) faces challenges in achieving its ambitious net‐zero carbon emissions target by 2050, with current emissions having fallen by less than 1% in 2024. Despite an investment of $500 billion in low‐carbon resources while holding the second‐largest green technology patent portfolio globally, it is further imperative to ...
Md Zubair Ahmad, Jewel Rana, Mohammad Fakhrul Islam, Md Nazmul Islam Jihad, Md. Rashed, Md. Kamal Uddin   +5 more
wiley   +1 more source

Ensemble learning for air quality index prediction: integrating gradient boosting, XGBoost, and stacking with SHAP-based interpretability. [PDF]

Sci Rep
Singh S, Kumar M, Sengar V, Kumar A, Abhishek K, Shafeeq BMA.   +5 more
europepmc   +1 more source

Machine Learning‐Driven Prediction and Optimization of Cu‐Based Catalysts for CO2 Hydrogenation to Methanol

Carbon and Hydrogen, EarlyView.
A machine‐learning framework integrating multimodel prediction, feature selection, and SHAP interpretability is developed to uncover structure–performance relationships of Cu‐based CO2‐to‐methanol catalysts. The optimized XGBoost model and an online prediction platform enable accurate selectivity prediction and data‐driven catalyst design.
Conglong Su, Zhangkai Jing, Qiuming Zhou, Yuan Zhu, Sishi Ye, Tianye Wang, Kuo Chen, Xuebin Luan, Zhigang Tang, Run Xu, Chaopeng Hou, Hongwei Li   +11 more
wiley   +1 more source