Results 211 to 220 of about 17,714 (294)

Processing properties of cell-wall disrupted macroalgae in plant-based meat and the concept of a sustainable algal modifier database. [PDF]

Curr Res Food Sci
Chang CH, Tsai SH, Fan CH, Yang CM, Chiu PC, Tsai YH, Lee MY.   +6 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

Fried green burgers: a promising food for plant-based dieters. Ingredient characterization, processing, and future development. [PDF]

J Food Sci Technol
Edris AE, Salama HH.
europepmc   +1 more source

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Colour Transition Dynamics of Commercial Plant- and Animal-Based Meat Analogues. [PDF]

Foods
Rathnayake D, Moura Nadolny J, Sultanbawa Y, Smyth HE.   +3 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Neuroscience meets food choice: Implicit and explicit consumer responses to plant-based vs animal-based foods. [PDF]

Curr Res Food Sci
Inguscio BMS, Carcaterra G, Cherubino P, Rossi D, Madini G, Fraccascia L, Babiloni F, Cartocci G.   +7 more
europepmc   +1 more source

Comparison of the quality characteristics of commercial plant-based meat analogues

Korean journal of food science and technology
Su-Bin Lim, Yoon-Hee Yang, Jung-Ah Han
openaire   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source