Publications related to Data & Figures on the Multiscale Spatiotemporal Characterization of Embodied Environmental Efficiency of Building Structures in Geneva from 1850 to 2018

Data and scripts for the RaFSIP scheme

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

Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"

Alexis Berne, Satoshi Takahama, Athanasios Nenes, Georgia Sotiropoulou, Anne-Claire Marie Billault--Roux, Paraskevi Georgakaki, Romanos Foskinis, Kunfeng Gao

This repository contains field observations and processed data from the Weather Research and Forecasting (WRF) model simulations and the Cloud Resolving Model Radar Simulator (CR-SIM), alongside scripts designed to reproduce the figures presented in the pa ...

Zenodo2024

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

Extensions of Peer Prediction Incentive Mechanisms

Adam Julian Richardson

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

E-Scan: Consuming Contextual Data with Model Plugins

Anastasia Ailamaki, Viktor Sanca

Extracting value and insights from increasingly heterogeneous data sources involves multiple systems combining and consuming the data. With multi-modal and context-rich data such as strings, text, videos, or images, the problem of standardizing the data mo ...

2023

Methodology for selecting measurement points that optimize information gain for model updating

Ian Smith, Numa Joy Bertola

Information collected through sensor measurements has the potential to improve knowledge of complex-system behavior, leading to better decisions related to system management. In this situation, and particularly when using digital twins, the quality of sens ...

2023

Toward a common standard for data and specimen provenance in life sciences

Marco Mattavelli, Anna Marsano

Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and knowledge derived is thus significantly influenced by t ...

WILEY2023

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 ...

2023

Bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols measured in the Swiss container during MOSAiC 2019/2020

Benjamin Jérémy Laurent Heutte, Julia Schmale, Ivo Fabio Beck, Lubna Dada, Hélène Paule Angot, Imad El Haddad

This dataset contains the bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols (NR-PM1) measured during the MOSAiC expedition from October 2019 to July 2020. These include the mass concentrations of sulfate (S ...

Zenodo2023

Dielectric metasurfaces and their applications for optical biosensing

Yasaman Jahani

Over the past century, our understanding of life has been focused on its most fundamental building blocks: molecules. Biological molecules, such as proteins found in blood, other body fluids, or tissues, are excellent guides to identifying a normal or abno ...

EPFL2023

On Artificial Intelligence and Manipulation

Marcello Ienca

The increasing diffusion of novel digital and online sociotechnical systems for arational behavioral influence based on Artificial Intelligence (AI), such as social media, microtargeting advertising, and personalized search algorithms, has brought about ne ...

SPRINGER2023

1805-1898 Census Records of Lausanne : a Long Digital Dataset for Demographic History

Marion Kramer, Isabella Di Lenardo, Rémi Guillaume Petitpierre, Lucas Arnaud André Rappo

This historical dataset stems from the project of automatic extraction of 72 census records of Lausanne, Switzerland. The complete dataset covers a century of historical demography in Lausanne (1805-1898), which corresponds to 18,831 pages, and nearly 6 mi ...

Zenodo2023

Dataset for "Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid"

John Martin Kolinski

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 ...

Zenodo2023

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Henry Markram, Henry Genet, Alejandra Garcia Rojas Martinez, Sean Lewis Hill, Huanxiang Lu, Mohameth François Sy, Samuel Claude Kerrien, Michaël Fernand Paul Dupont, Silvia Rosario Jimenez Tejeda, Bogdan Roman, Ian Lavriushev, Anna-Kristin Kaufmann, Didac Montero Mendez, Wojciech Adam Wajerowicz, Pierre-Alexandre Fonta, Kenneth William Pirman, Julien Antonin Machon, Jonathan Raël Lurie, Dhanesh Neela Mana, Natalia Stafeeva, Alexander Désiré Ulbrich, Carolina Johanna Elisabeth Lindqvist

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

2023

Gospel of the Marseille Docker - Nicholas Derybolsky from 1952

Sila Karatas

This text, accompanied by a ‘gospel’ that I made by montaging the US-recorded captions, is an attempt for re-narrating Marshall Plan’s discourse on the working class, aka the so-called ‘free labor’ of the US against the ‘communist labor’ of the “Soviet thr ...

EPFL Press2023

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

Automatic and high-precision acoustic emission-based structural health monitoring of concrete structures

Brice Tanguy Alphonse Lecampion, Seyyedmaalek Momeni

Acoustic emission (AE) monitoring is a useful technique to monitor the health of a structure continuously, helping to prevent potential failure. AE are elastic waves produced and emitted during fracture processes inside a material and are recorded by senso ...

DESTech publications inc.2023

Housing, street and health: a new systemic research framework

Stéphane Joost, Paola Viganò, Catarina Wall Gago, Anna Pagani, Derek Pierre Christie, Dusan Licina, Valentin Daniel Maurice Bourdon, Idris Guessous, Mathias Lerch

As the world’s population grows in cities, urban dwellers spend a large amount of time inside their home, making housing health ever more important. Critical for residents’ health, the interactions between indoor residential environments and outdoor enviro ...

2023

A Framework for Autonomic Computing for In Situ Imageomics

Nina Marion Aurélia Van Tiel

In situ imageomics is a new approach to study ecological, biological and evolutionary systems wherein large image and video data sets are captured in the wild and machine learning methods are used to infer biological traits of individual organisms, animal ...

The Institute of Electrical and Electronics Engineers, Inc2023

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Pascal Fua, Sean Lewis Hill, Amos Sironi, Jiancheng Yang, Jian Zhou, Siqi Liu, Xiang Li, Jie Zhou

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in m ...

2023