Results 91 to 100 of about 111,787 (220)
Accurately Quantifying the Subsequent Search Miss Effect in Multiple-Target Visual Search
Journal of Vision, 2019 Stephen Adamo +3 more
openaire +1 more source
A PRACTICAL APPROACH TO MODEL BANKING RISKS USING LOSS DISTRIBUTION APPROACH (LDA) IN BASEL II FRAMEWORK [PDF]
In Basel II Capital Accord, the Advanced Measurement Approaches (AMA) is stated as one of the pillar stone methods for calculating corporate risk reserves.
Qi TANG, Raquel BARREIRA, Tristan PRYER
core
Advanced Functional Materials, EarlyView.Cu‐based catalysts as a cornerstone in advancing sustainable energy technologies are fully reviewed in this manuscript, highlighting their potential in photo‐ and electrocatalysis. It includes metallic copper, copper oxides, copper sulfides, copper halide perovskites, copper‐based metal–organic frameworks (MOFs), and covalent organic frameworks (COFs),
Jéssica C. de Almeida +16 more
wiley +1 more source
Advanced Functional Materials, EarlyView.By integrating machine learning into flux‐regulated crystallization (FRC), accurate prediction of solvent evaporation rates in real time, improving crystallization control and reducing crystal growth variability by over threefold, is achieved. This enhances the reproducibility and quality of perovskite single crystals, leading to reproducible ...
Tatiane Pretto +8 more
wiley +1 more source
Answering Complex Questions by Joining Multi-Document Evidence with Quasi Knowledge Graphs
, 2019 Direct answering of questions that involve multiple entities and relations is a challenge for text-based QA. This problem is most pronounced when answers can be found only by joining evidence from multiple documents.
Abujabal, A. +5 more
core
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
Advanced Functional Materials, EarlyView.A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Advanced Functional Materials, EarlyView.In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken +6 more
wiley +1 more source
Proteins, Processing, and Properties of Adhesive Fluid Condensates Purified from Mussels
Advanced Functional Materials, EarlyView.Mussels exhibit an unmatched proficiency for adhering to wet surfaces in salty environments—a remarkable ability that could inspire new biomedical and technical glues. The fluid protein condensates used to form the underwater mussel glue are extracted, reconstituted and characterized with advanced spectroscopy and nanomechanical analysis, revealing ...
Mathieu D. Rivard +8 more
wiley +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
Advanced Functional Materials, EarlyView.An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source