An experimental-numerical study of moisture absorption in an epoxy

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Surface-based inflatables are composed of two thin layers of nearly inextensible sheet material joined together along carefully selected fusing curves. During inflation, pressure forces separate the two sheets to maximize the enclosed volume. The fusing c ...

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, ...

Oil -based polymeric resins are widely used in the manufacture of fibre -reinforced polymer (FRP) composites, contributing up to 70 % to their total weight. In an effort to reduce the dependence on oil -based feedstock, bio-based alternatives are being inc ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

Frontal polymerisation has the potential to bring unprecedented reductions in energy demand and process time to produce fibre reinforced polymer composites. Production of epoxy-based fibre reinforced polymer parts with high fibre volume content, commonly e ...

An experimental-numerical study of moisture absorption in an epoxy

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Computational Homogenization for Inverse Design of Surface-based Inflatables

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Life cycle assessment of an innovative bio-based unsaturated polyester resin and its use in glass fibre reinforced bio-composites produced by vacuum infusion

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Reliable data-driven decision-making through optimal transport

Robust machine learning for neuroscientific inference

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Self-catalysed frontal polymerisation enables fast and low-energy processing of fibre reinforced polymer composites