Results 201 to 210 of about 43,564 (255)

FKRR-MVSF: A Fuzzy Kernel Ridge Regression Model for Identifying DNA-Binding Proteins by Multi-View Sequence Features via Chou's Five-Step Rule. [PDF]

Int J Mol Sci, 2019
Zou Y, Ding Y, Tang J, Guo F, Peng L.
europepmc   +1 more source

Subperiosteal peri‐implant augmented layer to correct bone dehiscence at immediate implant placement

Clinical Advances in Periodontics, EarlyView.
Abstract Background The purpose of the present case report is to describe the potential of the subperiosteal peri‐implant augmented layer (SPAL) technique in peri‐implant bone dehiscence (PIBD) correction at immediate implant placement (IIP). Methods This case report describes the application of the SPAL technique in two patients undergoing IIP at ...
Tommaso Grenzi, Chiara Franzini, Mattia Severi, Leonardo Trombelli   +3 more
wiley   +1 more source

Merging computational fluid dynamics and 4D Flow MRI using proper orthogonal decomposition and ridge regression. [PDF]

J Biomech, 2017
Bakhshinejad A, Baghaie A, Vali A, Saloner D, Rayz VL, D'Souza RM.   +5 more
europepmc   +1 more source

Subperiosteal tunnel assisted graft (STAG) technique: Report of two cases

Clinical Advances in Periodontics, EarlyView.
Abstract Background This case report describes the clinical application of the subperiosteal tunnel‐assisted graft (STAG) technique, a novel approach for peri‐implant phenotype modification and keratinized tissue augmentation. Although free gingival grafts remain the gold standard for increasing keratinized tissue width, their effectiveness may be ...
Seiko Min
wiley   +1 more source

Forecasting COVID-19 Outbreak Progression Using Hybrid Polynomial-Bayesian Ridge Regression Model

, 2020
Saqib M.
europepmc   +1 more source

The Influence of Aesthetic Liking on Product Evaluation: How and When It Differs With Brand Strength and Product Type

Journal of Consumer Behaviour, EarlyView.
ABSTRACT This research provides comprehensive insight into the influence of aesthetic liking on product preference across different types of durable product categories by uncovering the underlying process. Distinguishing a direct expressive influence of aesthetic liking and an indirect influence as a quality signal, referring to signaling theory, we ...
Mariëlle E. H. Creusen, Ruth Mugge, Jan P. L. Schoormans   +2 more
wiley   +1 more source

Machine Learning Paradigm for Advanced Battery Electrolyte Development

Carbon 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, Mengfan Pei, Keyu Chen, Xigao Jian, Fangyuan Hu   +4 more
wiley   +1 more source

Nonlinear permuted Granger causality

Canadian Journal of Statistics, EarlyView.
Abstract Granger causality is an established, contentious method that seeks causal temporal connections via association and precedence. While not true causal inference, it assists in mapping networks of information flow that may warrant further study.
Noah D. Gade, Jordan Rodu
wiley   +1 more source

Do Investors React Differently to GHG Emission in Stock Pricing Across Firms? Evidence From Commonwealth African Countries Using a Novel Wavelet‐Enhanced QQR Approach

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study examines the intricate and asymmetric relationship between corporate greenhouse gas emission disclosure and stock returns and crash risks, focusing on listed firms in six Commonwealth African countries characterized by regulatory fragility, limited investor protection, and growing climate vulnerability.
Idorenyin J. Okon, Adeolu O. Adewuyi, Simplice A. Asongu   +2 more
wiley   +1 more source

The AI Sustainability Paradox: How Verification and Regulation Synergize to Curb Greenwashing in Emerging Markets

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Artificial intelligence (AI) reflects a paradox for corporate sustainability: it provides tools for genuine socio‐economic improvement and enables greenwashing at scale. This study examines this duality in emerging Asian markets, where rapid AI adoption coincides with evolving regulatory regimes.
Ashutosh Yadav, Simplice A. Asongu
wiley   +1 more source