Results 121 to 130 of about 250,812 (289)

Selective Benzene Capture by Metal‐Organic Frameworks

open access: yesAdvanced Functional Materials, EarlyView.
Metal‐organic frameworks (MOFs) hold significant potential for capturing benzene from air emissions and hydrocarbon mixtures in liquid phases. This capability stems from their precisely engineered structures, versatile chemistries, and diverse binding interactions.
Zongsu Han   +4 more
wiley   +1 more source

Using smart devices for prenatal care: Assessing the willingness among women with pregnancy-related anxiety

open access: yesDigital Health
Background Wearables and smart devices could complement face-to-face prenatal care appointments by monitoring pregnant women's health, especially since pregnancy may be a vulnerable time when mental health issues and pregnancy-related anxiety may arise ...
Stefanie Altmannshofer   +11 more
doaj   +1 more source

Electroactive Metal–Organic Frameworks for Electrocatalysis

open access: yesAdvanced Functional Materials, EarlyView.
Electrocatalysis is crucial in sustainable energy conversion as it enables efficient chemical transformations. The review discusses how metal–organic frameworks can revolutionize this field by offering tailorable structures and active site tunability, enabling efficient and selective electrocatalytic processes.
Irena Senkovska   +7 more
wiley   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

open access: yesAdvanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz   +3 more
wiley   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

open access: yesAdvanced 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

A study protocol for a systematic review and meta-analysis on macroscopic body movements as a marker for acute stress

open access: yesSystematic Reviews
Background Experiencing stress is a normative part of human life. Due to its major impact on health and longevity, effort has been put into understanding underlying determinants and consequences. For stress measurement, a vast number of different methods,
Miriam Kurz   +8 more
doaj   +1 more source

Machine Learning for Data Mining, Data Science and Data Analytics

open access: yesRecent Advances in Computer Science and Communications, 2021
Vangipuram Radhakrishna   +3 more
openaire   +1 more source

Chemoselective Sequential Polymerization: An Approach Toward Mixed Plastic Waste Recycling

open access: yesAdvanced Functional Materials, EarlyView.
Inspired by biological protein metabolism, this study demonstrates the closed‐loop recycling of mixed synthetic polymers via ring‐closing depolymerization followed by a chemoselective sequential polymerizations process. The approach recovers pure polymers from mixed feedstocks, even in multilayer formats, highlighting a promising strategy to overcome a
Gadi Slor   +5 more
wiley   +1 more source

Auto‐Generated Valence States in Electrocatalysts for Boosting Oxygen and Hydrogen Evolution Kinetics in Alkaline Water/Alkaline Seawater/Simulated Seawater/Natural Seawater

open access: yesAdvanced Functional Materials, EarlyView.
This review systematically highlights the latest achievements in mixed‐valence states relevant to hydrogen and oxygen evolution reactions, providing essential insights into future directions and methods for large‐scale practical implementation. This critical review is expected to provide an overview of recent advancements in diverse valence‐state metal
Jitendra N. Tiwari   +4 more
wiley   +1 more source

A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs

open access: yesScientific Reports
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are costly,
Fatemeh Salehi   +7 more
doaj   +1 more source

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