Results 151 to 160 of about 1,218 (214)

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

A Fiducial-Marker-Based Localization Method for Automotive Chassis Bolt Assembly. [PDF]

Sensors (Basel)
Peng X, Xiao Y, Chen Z, Chen K, Huang H.
europepmc   +1 more source

Too Complex to Choose? The Role of Heuristics in Shaping Farmers' Willingness to Pay for Income Stabilization Tool in Italy

Agribusiness, EarlyView.
ABSTRACT European agriculture is increasingly exposed to economic instability driven by extreme weather events, market volatility, and geopolitical tensions. To manage these growing risks, farmers are encouraged to adopt innovative risk management strategies such as the Income Stabilization Tool (IST), which offers protection against severe income ...
Alice Stiletto, Ruggiero Rippo, Samuele Trestini, Elisa Giampietri, Roberta Raffaelli, Simone Cerroni   +5 more
wiley   +1 more source

Analytical Performances of Polymer-Based Biosensors for Real Samples Application. [PDF]

Biosensors (Basel)
Mascini M, Palmieri S, Eugelio F, Rivero MI, Del Carlo M.   +4 more
europepmc   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Non-Operative Management of a Complete ACL Rupture With the Cross-Bracing Protocol in an Elite Australian Rules Football Athlete. [PDF]

Clin Case Rep
Mead K, Dowsett M, Cass Z, Filbay S.
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

<i>Camphora officinarum</i> (Syn. <i>Cinnamomum camphora</i>): Botany, Phytochemistry, Biological Activities, Agro-Industrial Applications, and Biotechnology. [PDF]

Plants (Basel)
Shah K, Dai W, Shen Q, Zhang Y, Guo J, Qiao J, Hu J, Huang L, Yan D, Wang Y, Zuo J, Li Y, Yuan H, Zheng B.   +13 more
europepmc   +1 more source

On copositive programming and standard quadratic optimization problems.

Klerk, E. de, Quist, A.J., Bomze, I.M., Roos, C., Dür, M., Terlaky, T.   +5 more
core  

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source