Publications associées à Prediction of logP for Pt(II) and Pt(IV) complexes: Comparison of statistical and quantum-chemistry based approaches

An area efficient inductorless super-regenerative receiver front-end for biomedical implant devices

Wearable and implantable medical devices are of great importance in diagnosis and treatment as they provide continuous monitoring and data collection. Considering the comfort of the patient and ease-of-operation, these devices require wireless data transmi ...

Elsevier Gmbh2024

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Cyclic Peptides for Drug Development

Christian Heinis, Xinjian Ji, Alexander Lund Nielsen

Cyclic peptides are fascinating molecules abundantly found in nature and exploited as molecular format for drug development as well as other applications, ranging from research tools to food additives. Advances in peptide technologies made over many years ...

Wiley-VCH Verlag GmbH2024

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

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

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

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Alireza Modirshanechi

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

EPFL2024

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

EPFL2024

Geospatial Tools and Remote Sensing Strategies for Timely Humanitarian Response: A Case Study on Drought Monitoring in Eswatini

Jérôme Chenal

This article explores the escalating impact of natural disasters, particularly droughts, in the Southern African Development Community (SADC), with a specific focus on Eswatini. Over the last century, approximately 63 million people in SADC countries have ...

MDPI2024

Fungal mycelia: From innovative materials to promising products: Insights and challenges

Wenjing Sun

In transitioning toward a sustainable economy, mycelial materials are recognized for their adaptability, biocompatibility, and eco-friendliness. This paper updates the exploration of mycelial materials, defining their scope and emphasizing the need for pre ...

Aip Publishing2024

A Tunable Self-Offloading Module for Plantar Pressure Regulation in Diabetic Patients

Paolo Germano, Christian Köchli, Yves Perriard, Yoan René Cyrille Civet, Kenny Jeanmonod, Sofia Lydia Ntella, Bhawnath Tiwari

Plantar pressure plays a crucial role in the pathogenesis of foot ulcers among patients with diabetes and peripheral polyneuropathy. Pressure relief is a key requirement for both the prevention and treatment of plantar ulcers. Conventional medical practice ...

2024

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Nikolaos Geroliminis, Can Chen

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

Informs2024

Hybrid organic/metal-oxide shells on semiconductor nanocrystals via colloidal atomic layer deposition

Ona Segura Lecina

The escalating energy demand and the imperative necessity to reduce the carbon footprint require transformative approaches to energy conversion. Materials chemistry plays a pivotal role in addressing these global challenges by developing novel materials fo ...

EPFL2024

Impact of substrate clogging on vertical connectivity

Giovanni De Cesare, Romain Maxime Dubuis, Robin Schroff

Connectivity between the hyporheic zone and the flow is essential for the development of benthos and the reproductive success of spawning fish. The infiltration of fine sediment leads to clogging of the riverbed, reducing porosity and vertical water exchan ...

2023

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

A recipe for cracking the quantum scaling limit with machine learned electron densities

Mario Geiger

A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

IOP Publishing Ltd2023

Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial Robot

Frank Centamori, Josephine Anna Eleanor Hughes, Max Mirko Polzin

The use of aerial vehicles for exploration and data collection has the potential to significantly aid environmental monitoring in environments which are dangerous and hard to navigate. However, within these environments navigation can often be restricted b ...

2023

Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations

Nicola Parolini, Ntorina Thanou, David Kraus, Andrea Kraus, Daniel Lopez, Markus Scholz, Benjamin Bejar Haro, Daniel Rodrigo Lopez, Ekaterina Krymova, Tao Sun

Background:Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive p ...

eLIFE SCIENCES PUBL LTD2023

Multi-campaign ship and aircraft observations of marine cloud condensation nuclei and droplet concentrations

Jian Wang, Athanasios Nenes

In-situ marine cloud droplet number concentrations (CDNCs), cloud condensation nuclei (CCN), and CCN proxies, based on particle sizes and optical properties, are accumulated from seven field campaigns: ACTIVATE; NAAMES; CAMP(2)EX; ORACLES; SOCRATES; MARCUS ...

NATURE PORTFOLIO2023