Modeling degradation processes of switches and crossings for maintenance and renewal planning on the Swiss railway network

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Use of an unmanned aerial-aquatic vehicle for acoustic sensing in freshwater ecosystems

Freshwater ecosystems are endangered, underfunded and understudied, making new methods such as passive acoustic monitoring (PAM) essential for improving the efficiency and effectiveness of data collection. However, many challenges are still to be addressed ...

Wiley2023

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

Artificial Neural Network Training on an Optical Processor via Direct Feedback Alignment

Florent Gérard Krzakala, Julien Marcel Daniel Emmanuel Launay

Artificial Neural Networks (ANN) are habitually trained via the back-propagation (BP) algorithm. This approach has been extremely successful: Current models like GPT-3 have O(10 11 ) parameters, are trained on O(10 11 ) words and produce awe-inspiring resu ...

IEEE2023

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

Label-free plasmonic microarray for multiplexed analysis of cells and tumor organoids

Yen-Cheng Liu

Investigating the dynamic activities of protein expression and signaling in living organisms is a crucial focus of intense research aimed at elucidating the processes that underlie disease progression and improving treatments and drug development. Resolvin ...

EPFL2023

Estimating pollution spread in water networks as a Schrödinger bridge problem with partial information

Isabel Haasler

Incidents where water networks are contaminated with microorganisms or pollutants can result in a large number of infected or ill persons, and it is therefore important to quickly detect, localize and estimate the spread and source of the contamination. In ...

Elsevier2023

Caching and Neutrality

Aikaterini Argyraki, Pavlos Nikolopoulos, Muhammad Abdullah

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

ACM Association for Computing Machinery2023

The Impact of Data Persistence Bias on Social Media Studies

Tugrulcan Elmas

Social media studies often collect data retrospectively to analyze public opinion. Social media data may decay over time and such decay may prevent the collection of the complete dataset. As a result, the collected dataset may differ from the complete data ...

Assoc Computing Machinery2023

Transfer learning application of self-supervised learning in ARPES

Gabriel Aeppli

There is a growing recognition that electronic band structure is a local property of materials and devices, and there is steep growth in capabilities to collect the relevant data. New photon sources, from small-laboratory-based lasers to free electron lase ...

IOP Publishing Ltd2023

Streamline RimNet: Tools for Automatic Classification of Paramagnetic Rim Lesions in MRI of Multiple Sclerosis

Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa, Maxence Charles F Wynen

This site provides two software tools related to "RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis" by Barquero et al. NeuroImage: Clinical (2020). People using in part or f ...

Zenodo2023

Exploration-based model learning with self-attention for risk-sensitive robot control

Sudong Lee

Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

2023

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