Results 181 to 190 of about 70,162 (241)

Wine Tourism as a Catalyst for Sustainable Performance: The Mediating Role of Corporate Legitimacy and Green Innovation

Agribusiness, EarlyView.
ABSTRACT This study aims to explore the influence of Wine Tourism (WT) on the Sustainable Performance (SP) of wineries in Spain. It particularly investigates how Corporate Social Legitimacy (CSL) and Green Innovation (GI) may act as intermediary factors in this relationship.
Javier Martínez‐Falcó, Eduardo Sánchez‐García, Bartolomé Marco‐Lajara, Luis A. Millán‐Tudela   +3 more
wiley   +1 more source

Real-World Outcomes of Aflibercept 2 mg Using a Treat-and-Extend Protocol for Neovascular Age-Related Macular Degeneration: A 24-Month Retrospective Study in a Chinese Population. [PDF]

Drug Des Devel Ther
Qi Y, Cheng A, Xu J, Zhang C, Li S.
europepmc   +1 more source

Universally Accurate or Specifically Inadequate? Stress‐Testing General Purpose Machine Learning Interatomic Potentials

Advanced Intelligent Discovery, EarlyView.
We investigate MACE‐MP‐0 and M3GNet, two general‐purpose machine learning potentials, in materials discovery and find that both generally yield reliable predictions. At the same time, both potentials show a bias towards overstabilizing high energy metastable states. We deduce a metric to quantify when these potentials are safe to use.
Konstantin S. Jakob, Karsten Reuter, Johannes T. Margraf   +2 more
wiley   +1 more source

Outcomes of keraring implantation for high regular astigmatism in non-ectatic corneas: A prospective pilot case series. [PDF]

Sci Rep
Mounir A, Mossa EAM, Mahmoud A.
europepmc   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Multiple linear regression analysis of factors affecting better-eye visual acuity in retinitis pigmentosa patients: A cross-sectional study. [PDF]

Medicine (Baltimore)
Xu L, Dai G, Ren Y, Sun Y, Hu S, Dang Y, Qin G, He W.   +7 more
europepmc   +1 more source

Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

Advanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

Rotational Stability of the Clareon PanOptix Toric (CNWTTx) Hydrophobic Multifocal IOL: Real-World Clinical Outcomes. [PDF]

Clin Ophthalmol
Agarwal S, Chang LY, Thornell E.
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source