Publications associées à Aerosol optical absorption coefficients at seven wavelengths in 10 min resolution measured in the Swiss container during MOSAiC 2019/2020

Equivalent black carbon concentration measured with an aethalometer AE33 during the Arctic Ocean 2018 expedition

Benjamin Jérémy Laurent Heutte, Julia Schmale, Andrea Baccarini

Equivalent black carbon (eBC) mass concentration was measured with a commercial aethalometer (model AE33, Magee Scientific, Berkeley, USA). Measurements were performed onboard of the Swedish icebreaker (I/B) Oden from August to September 2018 as part of th ...

EPFL Infoscience2024

Gaia's brightest very metal-poor (VMP) stars Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra

Nicolas Lawrence Etienne Longeard

Context. Gaia DR3 has offered the scientific community a remarkable dataset of approximately one million spectra acquired with the radial velocity spectrometer (RVS) in the calcium II triplet region, which is well suited to identify very metal-poor (VMP) s ...

Edp Sciences S A2024

The Influence of the Planetary Boundary Layer on the Atmospheric State at an Orographic Site at the Eastern Mediterranean

Athanasios Nenes, Romanos Foskinis, Kunfeng Gao

We studied the influence of the Planetary Boundary Layer (PBL) on the air masses sampled at the mountaintop Hellenic Atmospheric Aerosol and Climate Change station ((HAC) 2 ) at Mount Helmos (Greece) during the Cloud-AerosoL InteractionS in the Helmos back ...

Stockholm Univ Press2024

Measurement of the Higgs boson production via vector boson fusion and its decay into bottom quarks in proton-proton collisions at √s=13 TeV

Rakesh Chawla, Andrea Rizzi, Matthias Finger, Federica Legger, Matteo Galli, Sun Hee Kim, João Miguel das Neves Duarte, Tagir Aushev, Hua Zhang, Alexis Kalogeropoulos, Yixing Chen, Tian Cheng, Ioannis Papadopoulos, Gabriele Grosso, Valérie Scheurer, Meng Xiao, Qian Wang, Michele Bianco, Varun Sharma, Joao Varela, Sourav Sen, Ashish Sharma, Seungkyu Ha, David Vannerom, Csaba Hajdu, Sanjeev Kumar, Sebastiana Gianì, Kun Shi, Abhisek Datta, Siyuan Wang, Anton Petrov, Jian Wang, Yi Zhang, Muhammad Ansar Iqbal, Yong Yang, Xin Sun, Muhammad Ahmad, Donghyun Kim, Matthias Wolf, Anna Mascellani, Paolo Ronchese, , , , , , , , , , , , , , , , , , , ,

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Danick Briand, Nicolas Francis Fumeaux

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Zenodo2024

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Alok Rudra, Anna Fontcuberta i Morral, Sara Marti Sanchez, Santhanu Panikar Ramanandan, Joel René Sapera, Vladimir Dubrovskii

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

EPFL Infoscience2024

Data and scripts for the RaFSIP scheme

Athanasios Nenes, Paraskevi Georgakaki

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Zenodo2024

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron

Andreas Mortensen, Léa Deillon, Alejandra Inés Slagter, Eva Luisa Vogt, David Hernandez Escobar, Jonathan Aristya Setyadji

Dataset corresponding to the following manuscript: Slagter, A., Setyadji, J.A., Vogt, E.L. et al. Nanoindentation Hardness and Modulus of Al2O3–SiO2–CaO and MnO–SiO2–FeO Inclusions in Iron. Metall Mater Trans A (2024). https://doi.org/10.1007/s11661-024-0 ...

Zenodo2024

High-throughput parallel testing of ten photoelectrochemical cells for water splitting: case study on the effects of temperature in hematite photoanodes

Sophia Haussener, Isaac Thomas Holmes-Gentle, Roberto Valenza, Franky Esteban Bedoya Lora

High-throughput testing of photoelectrochemical cells and materials under well-defined operating conditions can accelerate the discovery of new semiconducting materials, the characterization of the phenomena occurring at the semiconductor-electrolyte inter ...

Royal Soc Chemistry2024

Generation of entangled photon pairs from a silicon bichromatic photonic crystal cavity

Matteo Galli, Thanavorn Poempool, Marco Clementi

Integrated quantum photonics leverages the on-chip generation of nonclassical states of light to realize key functionalities of quantum devices. Typically, the generation of such nonclassical states relies on whispering gallery mode resonators, such as int ...

Aip Publishing2024

Data-driven statistical optimization of a groundwater monitoring network

Andrea Rinaldo, Gianluca Botter

We propose a comparative study of three different methods aimed at optimizing existing groundwater monitoring networks. Monitoring piezometric heads in subsurface porous formations is crucial at regional scales to properly characterize the relevant subsurf ...

Elsevier2024

Robust machine learning for neuroscientific inference

Steffen Schneider

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 ...

EPFL2024

Dataset for "Complexity of crack front geometry enhances toughness of brittle solids"

John Martin Kolinski, Chenzhuo Li, Xinyue Wei

This data package supports the publication 'Complexity of crack front geometry enhances toughness of brittle solids' by Xinyue Wei, Chenzhuo Li, Cían McCarthy, and John M. Kolinski Nature physics (2024) - https://doi.org/10.1038/s41567-024-02435-x DOI: 1 ...

Zenodo2024

Spectral Estimators for High-Dimensional Matrix Inference

Farzad Pourkamali

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

EPFL2024

Orchestrating chromosome conformation capture analysis with Bioconductor

Cyril Matthey-Doret

Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

Nature Research2024

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Ian Smith, Katrin Beyer, Bryan German Pantoja Rosero, Mathias Christian Haindl Carvallo

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Springer2024

Probabilistic and Deterministic Wellposedness for Low Regularity Dispersive Equations

Katie Sabrina Catherine Rosie Marsden

In this thesis we will present two results on global existence for nonlinear dispersive equations with data at or below the scaling regularity. In chapter 1 we take a probabilistic perspective to study the energy-critical nonlinear Schrödinger equation in ...

EPFL2024

Hybrid Simulator for Capturing Dynamics of Synthetic Populations

Michel Bierlaire, Marija Kukic

This paper presents a novel hybrid framework for generating and updating a synthetic population. We call it hybrid because it combines model-based and data-driven approaches. Existing generators produce a snapshot of synthetic data that becomes outdated ov ...

IEEE2024

Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

Nicolas Henchoz, Delphine Ribes Lemay, Emily Clare Groves, Margherita Motta

Despite the widespread use of self-tracking technologies for promoting personal wellbeing, there is limited research on the monitoring of intimate data, particularly urine. To shed light on the design possibilities within this unexplored domain we designed ...

DRS Digital Library2024

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Arnout Jan J Devos

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

EPFL2024