Configurations of Resources & Capabilities and their Performance Implications: An Exploratory Study on Technology Ventures

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A Provably Stable Iterative Learning Controller for Continuum Soft Robots

Josephine Anna Eleanor Hughes, Francesco Stella

Fully exploiting soft robots' capabilities requires devising strategies that can accurately control their movements with the limited amount of control sources available. This task is challenging for reasons including the hard-to-model dynamics, the system' ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

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

Data for "Ultrafast deep-ultraviolet study of photoexcited aqueous Ferrioxalate"

Majed Chergui, Christoph Bostedt, Michele Puppin, Malte Oppermann, Hui-Yuan Chen

Data repository for the following publication: A. Duque-Prata*, H.-Y. Chen*, L. Müller, M. Oppermann, M. Puppin, C. Serpa, C. Bostedt and M. Chergui, “Ultrafast deep-ultraviolet study of photoexcited aqueous Ferrioxalate”, submitted to ChemPhotoCh ...

Zenodo2023

Toward data-driven materials design: From atoms to pilot plants

Kevin Maik Jablonka

Discovering new materials is essential but challenging, time-consuming, and expensive. In many cases, simulations can be useful for estimating material properties. For many of the most interesting properties, however, simulations are infeasible because of ...

EPFL2023

Timing and spatial selection bias in rapid extreme event attribution

Anthony Christopher Davison, Ophélia Mireille Anna Miralles

Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

ELSEVIER2023

Data-driven Methods for Control: from Linear to Lifting

Yingzhao Lian

The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...

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

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

Alberto Antonietti, Davide Bella, Pranav Rai, Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Michael Reimann, Marwan Muhammad Ahmed Abdellah, Werner Alfons Hilda Van Geit, Lida Kanari, Srikanth Ramaswamy, James Gonzalo King, Alexis Arnaudon, Ying Shi, András Ecker, Jean-Denis Georges Emile Courcol, Armando Romani, Pramod Shivaji Kumbhar, Judit Planas Carbonell, Michael Emiel Gevaert, Nadir Roman Guerrero, Liesbeth Maria L Vanherpe, Huanxiang Lu, Mohameth François Sy, Cristina Colangelo, Juan Bautista Hernando Vieites, Cyrille Pierre Henri Favreau, Genrich Ivaska, Anna-Kristin Kaufmann, Joni Henrikki Herttuainen, Elvis Boci, Vishal Sood, Thomas Brice Delemontex, Fabien Petitjean, Julian Martin Budd, Mustafa Kerem Kurban

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

2024

Radiation Hardness of MALTA2, a Monolithic Active Pixel Sensor for Tracking Applications

Edoardo Charbon, Francesco Piro

MALTA is a depleted monolithic active pixel sensor (DMAPS) developed in the Tower Semiconductor 180-nm CMOS imaging process. Monolithic CMOS sensors offer advantages over current hybrid imaging sensors in terms of both increased tracking performance due to ...

Ieee-Inst Electrical 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, Jiancheng Yang, Amos Sironi, Jian Yang

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 ...

Nature Publishing Group2023

Lightning Nowcasting Using Solely Lightning Data

Farhad Rachidi-Haeri, Marcos Rubinstein, Amirhossein Mostajabi, Seyed Mohammad Ehsan Mansouri Tehrani

Lightning is directly or indirectly responsible for significant human casualties and property damage worldwide. A timely prediction of its occurrence can enable authorities and the public to take necessary precautionary actions resulting in diminishing the ...

MDPI2023