Simulation-based Microstructure Imaging: From Forward Signal Modeling to Machine Learning

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Real-time bioaerosol monitoring is improving the quality of life for people affected by allergies, but it often relies on deep learning models which pose challenges for widespread adoption. These models are typically trained in a supervised fashion and req ...

Examining the performance of an existing bridge requires information on several aspects, such as design choices, material properties, and ongoing degradation processes. It often happens that some critical information is not available. The traditional appro ...

Recent studies have reported social cognitive deficits, particularly in emotional processing, in Parkinson's disease (PD). However, a comprehensive characterization of these deficits and their underlying neural correlates remains elusive. Therefore, this s ...

Now is an exciting time for the domain of Earth observation (EO), with a multitude of diverse sensors looking at the planet from satellites, airplanes or drones. The volume of imagery acquired is massive, and hold great potential for a variety of applicati ...

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

In a collaboration between Ecole Polytechnique Fédérale de Lausanne (EPFL) and CEA, in the fall of 2020, the experimental Programme d’Étude en Transmission de l’Acier Lourd et ses Eléments (PETALE) was successfully carried out in the CROCUS reactor of EPFL ...

Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

We present a numerical model for the approximation of multiphase flows with free surfaces and strong interfacial effects. The model relies on the multiphase incompressible Navier-Stokes equations, and includes surface tension effects on the interfaces betw ...

Most codes of practice adopt a semi probabilistic design approach for the dimensioning and assessment of structures. Accordingly, structural safety is ensured by performing limit state verifications using design values determined with adequately calibrated ...

Understanding the interplay between human brain structure and function is crucial to discern neural dynamics. This study explores the relation between brain structure and macroscale functional activity using subject-specific structural connectome eigenmode ...

Steel frame structures are essential components of modern infrastructure. Understanding their behavior under seismic loading is critical for ensuring public safety and minimizing damage that occurs during earthquakes. To accurately predict the response of ...

Background: Fetal brain MRI is increasingly used to complement ultrasound imaging. Images are processed using complex super-resolution reconstruction pipelines, which may bias biometric and volumetric measurements. Objective: To assess the consistency of 2 ...

Reinforcement learning (RL) has shown promising results for real-time control systems, including the domain of plasma magnetic control. However, there are still significant drawbacks compared to traditional feedback control approaches for magnetic confinem ...

Low-level light detection with high spatial and timing accuracy is a growing area of interest by virtue of applications such as light detection and ranging (LiDAR), biomedical imaging, time-resolved Raman spectroscopy, and quantum applications. Single-phot ...

Sign Language conveys information through multiple channels composed of manual (handshape, hand movement) and non-manual (facial expression, mouthing, body posture) components. Sign language assessment involves giving granular feedback to a learner, in ter ...

The evolution of edge computing has advanced the accessibility of E-health recommendation services, encompassing areas such as medical consultations, prescription guidance, and diagnostic assessments. Traditional methodologies predominantly utilize central ...

The development of Ultra-High Performance Fibre-Reinforced Cementitious Composite (UHPFRC) has enabled the design of lightweight constructions. Although the greenhouse gas emissions of UHPFRC per volume are higher than that of conventional concr ...

This paper introduces MNE-RT, a Python package designed for real-time neural feature extraction from magne-toencephalography (MEG) and electroencephalography (EEG) signals in Brain-Computer Interface (BCI) systems. The package incorporates efficient algori ...

Carefully extracting reinforced concrete (RC) elements from soon-to-be demolished structures and reusing them as load-bearing components is an emerging circular low-carbon alternative to building new structures. As floor construction typically accounts for ...

Simulation-based Microstructure Imaging: From Forward Signal Modeling to Machine Learning

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Self-supervised and few-shot learning for robust bioaerosol monitoring

A global framework for data-informed bridge examination

Mental State Recognition Deficits Linked to Brain Changes in Parkinson's Disease Without Dementia

Interact with Earth Observation Images using AI: Transparent Methods and Evaluation for Visual Question Answering

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Improving the accuracy and interpretability of neural networks for wind power forecasting

High-Resolution Modeling Without Computation Slowdown for PETALE in CROCUS

Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology

A cut-cell method for the numerical simulation of 3D multiphase flows with strong interfacial effects

Influence of model uncertainty and long term deformations in action effects calculation in reinforced concrete structures

On Reconstruction of Cortical Functional Maps Using Subject-Specific Geometric and Connectome Eigenmodes

A Softening Constitutive Law and Gradient-Inelastic Fiber-Based Element for 3-Dimensional Frame Simulations Under Seismic Excitations

Biometry and volumetry in multi-centric fetal brain magnetic resonance imaging: assessing the bias of super-resolution reconstruction

Towards practical reinforcement learning for tokamak magnetic control

Advanced Silicon and SWIR Single-Photon Avalanche Diodes: Design, Simulation, and Characterization

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

On-device diagnostic recommendation with heterogeneous federated BlockNets

Methods to assess the carbon footprint of structures involving UHPFRC elements

Advances on Real Time M/EEG Neural Feature Extraction

FLO:RE – A new floor system made of reused reinforced concrete and steel elements