Comparative Performance of Different Nanostructured Electrochemical Sensors on Insulin Detection

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Publications associées (30)

Validating functional redundancy with mixed generative adversarial networks

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Data redundancy has been one of the most important problems in data-intensive applications such as data mining and machine learning. Removing data redundancy brings many benefits in efficient data updating, effective data storage, and error-free query proc ...

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The Impact of Data Persistence Bias on Social Media Studies

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Social media studies often collect data retrospectively to analyze public opinion. Social media data may decay over time and such decay may prevent the collection of the complete dataset. As a result, the collected dataset may differ from the complete data ...

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This dataset supports the publication 'Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid' by Lebo Molefe and John M. Kolinski, Physical Review E, (2023). The data are surface profiles of textured surf ...

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Uncovering personalized glucose responses and circadian rhythms from multiple wearable biosensors with Bayesian dynamical modeling

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Wearable biosensors and smartphone applications can measure physiological variables over multiple days in free-living conditions. We measure food and drink ingestion, glucose dynamics, physical activity, heart rate (HR), and heart rate variability (HRV) in ...

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Data and code associated with the paper 'Mode-Specific Coupling of Nanoparticle-on-Mirror Cavities with Cylindrical Vector Beams'

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Data and code associated with the following paper: V. Vento et al, Nano Lett. 2023 A thorough explanation of the experiment performed is available there. The name of each sub-folder and file in Maps_data_code.zip indicates the correspondin ...

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ALMOST SURE SCATTERING OF THE ENERGY-CRITICAL NLS IN d > 6

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We study the energy-critical nonlinear Schrodinger equation with randomised initial data in dimensions d > 6. We prove that the Cauchy problem is almost surely globally well-posed with scattering for randomised supercritical initial data in H-s(Rd) wheneve ...

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Data and Workflow to: Three-dimensional buoyant hydraulic fractures: finite volume release (Möri and Lecampion, (2023))

Andreas Möri, Brice Tanguy Alphonse Lecampion

This upload contains the relevant scripts, notebooks, and datasets to reproduce the numerically obtained results of the Journal article "Three-dimensional buoyant hydraulic fractures: finite volume release" by Möri and Lecampion, (2023). ...

Zenodo2023

Shared metadata for data-centric materials science

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The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps rather than hinders scientific work, the implementation of the FAIR-data prin ...

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Data-driven Methods for Control: from Linear to Lifting

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The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...

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Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Christophe Ballif, Nicolas Würsch, Laure-Emmanuelle Perret Aebi, Marine Dominique Cauz

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

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