Publications associées à Clothing-Mediated Exposures to Chemicals and Particles

Inhalation of Microplastics—A Toxicological Complexity

Florian Frédéric Vincent Breider, Myriam Borgatta

Humans are chronically exposed to airborne microplastics (MPs) by inhalation. Various types of polymer particles have been detected in lung samples, which could pose a threat to human health. Inhalation toxicological studies are crucial for assessing the e ...

2024

Holography and localization of information in quantum gravity

Kyriakos Papadodimas, Alexandre Mathieu Frédéric Belin

Within the AdS/CFT correspondence, we identify a class of CFT operators which represent diff-invariant and approximately local observables in the gravitational dual. Provided that the bulk state breaks all asymptotic symmetries, we show that these operator ...

Springer Nature2024

Overview of fast particle experiments in the first MAST Upgrade experimental campaigns

Matteo Vallar

MAST-U is equipped with on-axis and off-axis neutral beam injectors (NBI), and these external sources of super-Alfv & eacute;nic deuterium fast-ions provide opportunities for studying a wide range of phenomena relevant to the physics of alpha-particles in ...

IOP Publishing Ltd2024

Modeling friction and wear using an adaptive discrete-continuum coupling

Manon Eugénie Voisin--Leprince

When two objects slide against each other, wear and friction occur at their interface. The accumulation of wear forms what is commonly referred to as a ``third-body''. Understanding third-body evolution has significant applications in industry, where contr ...

EPFL2024

Thermal Conditions in Indoor Environments: Exploring the Reasoning behind Standard-Based Recommendations

Dolaana Khovalyg

Professionals in the building design and operation fields typically look at standards and guidelines as a reliable source of information and guidance with regard to procedural, contractual, and legal scope and requirements that are relevant to accountabili ...

2023

When do Minimax-fair Learning and Empirical Risk Minimization Coincide?

Volkan Cevher

Minimax-fair machine learning minimizes the error for the worst-off group. However, empirical evidence suggests that when sophisticated models are trained with standard empirical risk minimization (ERM), they often have the same performance on the worst-of ...

2023

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

Nanoindentation of embedded particles

Andreas Mortensen, Alejandra Inés Slagter, Joris Pierre Everaerts

We address the effect of elastic inhomogeneity on elastic modulus and hardness determinations made by depth-sensing indentations performed on individual particles embedded within a matrix of different elastic modulus. Finite element simulations and nanoind ...

SPRINGER HEIDELBERG2023

Predicting party switching through machine learning and open data

Silvestro Micera, Emanuele Rossi

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

CELL PRESS2023

Ricca's factors as mobile proteinaceous effectors of electrical signaling

Satyam Tiwari, Jian Wang

Leaf-feeding insects trigger high-amplitude, defense-inducing electrical signals called slow wave potentials (SWPs). These signals are thought to be triggered by the long-distance transport of low molecular mass elicitors termed Ricca's factors. We sought ...

CELL PRESS2023