Results 231 to 240 of about 195,711 (268)
As‐spun carbon materials produced from Lignosulfonate, gelatin, and alginate, selected for water solubility, and ability to produce templated sustainable carbon nanostructures. Gelatin and alginate are sacrificial during thermal processing, allowing the production of engineered high surface area nanostructures, which are further characterized for ...
Judith Miralda‐Jalle +6 more
wiley +1 more source
Conductive Hydrogels for Exogenous Sensing and Cell Fate Control
We engineer electrically conductive hydrogels by combining sulfated glycosaminoglycans with semiconducting polymers. These hydrogels bind bioactive proteins, including growth factors, whose release or retention can be modulated by low‐voltage stimulation. The hydrogels are also integrated as 3D channels in organic electrochemical transistors as part of
Teuku Fawzul Akbar +15 more
wiley +1 more source
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald +7 more
wiley +1 more source
Improved data quality and statistical power of trial-level event-related potentials with Bayesian random-shift Gaussian processes. [PDF]
Pluta D +5 more
europepmc +1 more source
Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung +9 more
wiley +1 more source
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano +5 more
wiley +1 more source
Atomically precise functionalization by N‐heterocyclic carbenes enhances the catalytic efficiency of macroscopically defined step edges toward electrochemical CO2${\rm CO}_2$ reduction. Sub‐molecular imaging reveals conformational differences between specific NHCs, which can be correlated with their catalytic performance. Photoelectron spectroscopy and
Philipp Wiesener +9 more
wiley +1 more source
Super‐Resolution Ultrasound Based Cell Tracking With Polymeric Nanobubbles
This study presents a super‐resolution ultrasound platform for tracking cells in vivo. Biocompatible polymeric nanobubbles are used as highly echogenic intracellular labels. Following the injection of cells and microbubbles, ultrasound localization microscopy (ULM) can dynamically match the microvascular architecture and individual cell trajectories ...
Junlin Chen +19 more
wiley +1 more source
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2016 IEEE International Conference on Image Processing (ICIP), 2016
We introduce the Gaussian Process Transform (GPT), an orthogonal transform for signals defined on a finite but otherwise arbitrary set of points in a Euclidean domain. The GPT is obtained as the Karhunen-Loeve Transform (KLT) of the marginalization of a Gaussian Process defined on the domain.
Philip A. Chou, Ricardo L. de Queiroz
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We introduce the Gaussian Process Transform (GPT), an orthogonal transform for signals defined on a finite but otherwise arbitrary set of points in a Euclidean domain. The GPT is obtained as the Karhunen-Loeve Transform (KLT) of the marginalization of a Gaussian Process defined on the domain.
Philip A. Chou, Ricardo L. de Queiroz
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Acta Mathematicae Applicatae Sinica, 1994
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