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Group contribution method for thermodynamic analysis of complex metabolic networks

Publications associées (28)

Acute TNF alpha levels predict cognitive impairment 6-9 months after COVID-19 infection

Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Alexandre Cionca, Idris Guessous

Background: A neurocognitive phenotype of post-COVID-19 infection has recently been described that is characterized by a lack of awareness of memory impairment (i.e., anosognosia), altered functional connectivity in the brain's default mode and limbic netw ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Comparison of regression techniques for generating surrogate models to predict the thermodynamic behavior of biomass gasification systems

François Maréchal, Daniel Alexander Florez Orrego, Julia Granacher, Meire Ellen Gorete Ribeiro Domingos

Biomass resources can play an important role in the energy transition, being a dynamic feedstock that can be transformed either into solid, liquid or gaseous fuels. The biomass gasification is a versatile way to convert wastes into energy. In this work, th ...

Elsevier2023

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0

Tobias Jonas, Adrien Michel

Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model a ...

COPERNICUS GESELLSCHAFT MBH2023

Climatic and Economic Background Determine the Disparities in Urbanites’ Expressed Happiness during the Summer Heat

Rui Yin, Gabriele Manoli

Climate-change-induced extreme weather events increase heat-related mortality and health risks for urbanites, which may also affect urbanites’ expressed happiness (EH) and well-being. However, the links among EH, climate, and socioeconomic factors remain u ...

2023

Deep Learning Generalization with Limited and Noisy Labels

Mahsa Forouzesh

Deep neural networks have become ubiquitous in today's technological landscape, finding their way in a vast array of applications. Deep supervised learning, which relies on large labeled datasets, has been particularly successful in areas such as image cla ...

EPFL2023

An Unbiased Method of Measuring the Ratio of Two Data Sets

Jean-Paul Richard Kneib, Huanyuan Shan

In certain cases of astronomical data analysis, the meaningful physical quantity to extract is the ratio R between two data sets. Examples include the lensing ratio, the interloper rate in spectroscopic redshift samples, and the decay rate of gravitational ...

IOP Publishing Ltd2023

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

EPFL2023

Influence of temperature on phase assemblages of belite-ye'elimite cement

Karen Scrivener, Barbara Lothenbach, Natechanok Chitvoranund, Diana Londoño Zuluaga

This paper studies the effect of temperature on the phase assemblages of belite-ye'elimite cement. A comparison is made between thermodynamic modelling and experimental data at 28 and 180 days of hydration at 5, 20, 40, and 60 degrees C. The fast reaction ...

Pergamon-Elsevier Science Ltd2023