Results 91 to 100 of about 77,468 (304)

Aqueous Two‐Phase Bioinks for Discrete Packing and Compartmentalization of 3D Bioprinted Cells

open access: yesAdvanced Healthcare Materials, EarlyView.
Aqueous two‐phase systems (ATPS) enable the formation of biomimetic interfaces crucial for tissue engineering. However, clinical translation remains limited by the challenge of precisely controlling cellular compartmentalization. Here, we developed ATPS biomaterial inks for 3D bioprinting allowing tuneable droplet formation via NaCl modulation.
Martina Marcotulli   +17 more
wiley   +1 more source

A Systematic Study of GelMA‐Carbopol Bioinks for High‐Fidelity Extrusion 3D Bioprinting at Physiological Temperatures

open access: yesAdvanced Healthcare Materials, EarlyView.
Gonzalez Martinez and collaborators develop a strategy to formulate high performance GelMA‐based bioinks with low solids contents. The resulting bioinks enable 3D bioprinting at 37 °C of high‐fidelity structures with tunable mechanical properties that support high cell viability and function.
David A. González‐Martínez   +8 more
wiley   +1 more source

Dependence in Classification of Aluminium Waste

open access: yesJournal of Physics: Conference Series, 2015
Based on the dependence between edge and colour intensity of aluminium waste image, the aim of this paper is to classify the aluminium waste into three types; pure aluminium, not pure aluminium type-1 (mixed iron/lead) and not pure aluminium type 2 (unrecycle).
openaire   +1 more source

Microgel‐Based 3D Bioprinting: A Convergent Strategy Integrating Material Design, Jamming Dynamics, and Biological Function

open access: yesAdvanced Healthcare Materials, EarlyView.
Microgel‐based 3D printed constructs represent a compelling and versatile innovation for engineering architecturally complex, dynamically remodelable, and biocompatible structures with high structural fidelity and bioactivity. By integrating material design, biofabrication, and biological function, these systems enable the development of adaptive ...
Elena Ghighină   +2 more
wiley   +1 more source

Limitations of Influence-Based Dataset Compression for Waste Classification

open access: yesData
Influence-based data selection methods, such as TracIn, aim to estimate the impact of individual training samples on model predictions and are increasingly used for dataset curation and reduction.
Julian Aberger   +5 more
doaj   +1 more source

Medical waste classification by material.

open access: yes, 2016
Medical waste classification by material.
Zheng Wang (25883)   +3 more
core   +1 more source

Natural Biomaterials for Osteochondral Repair: From Source to Strategy

open access: yesAdvanced Healthcare Materials, EarlyView.
Biological origin‐guided overview of natural biomaterials and therapeutic strategies for osteochondral tissue engineering. The circular diagram categorizes representative materials and strategies into plant/algae‐derived, microbial‐derived, animal‐derived, and human‐derived sources, centered on an osteochondral defect repair model.
Hengyu Liu   +5 more
wiley   +1 more source

Hybrid cnn–densenet121 architecture for intelligent waste classification in sustainable smart cities [PDF]

open access: yesEPJ Web of Conferences
The growing volume of waste produced around the world has posed serious problems for recycling and environmental sustainability. Correct waste classification is a key to successful waste recycling, and the current type of systems remains dependent on ...
Mahmoud Sawsan M.   +1 more
doaj   +1 more source

Classification of waste in natural environments

open access: yesMATEC Web of Conferences
A worldwide issue affecting the world is waste disposal; hence, the need to construct a waste detection system that is based on deep learning. Ten wastes are evaluated in this article with a view of providing an integrated framework for measurement and evaluation.
Kumar Kanaparthi Suresh   +5 more
openaire   +2 more sources

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

open access: yesAdvanced Materials, EarlyView.
This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley   +1 more source

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