1. Software for the simulation study in "Data-driven formulation of the Kalman filter and its Application to Predictive Control" 

   Smith, Roy (2024)

   Data-driven methods for predictive control rely on input-output data to give a Hankel matrix representation of the set of system behaviours. They are poorly suited to situations where both process noise and measurement noise dominate the behaviour whereas Kalman filters optimally estimate system states in this scenario. We derive a data-driven Kalman filter formulation based on dynamic evolution of Hankel matrix output predictions. ...

   Software

2. The genomic potential of photosynthesis in piconanoplankton is functionally redundant but taxonomically structured at a global scale 

   Schickele, Alexandre; Debeljak, Pavla; Ayata, Sakina-Dorothée; et al. (2024)

   Science Advances

   Carbon fixation is a key metabolic function shaping marine life, but the underlying taxonomic and functional diversity involved is only partially understood. Using metagenomic resources targeted at marine piconanoplankton, we provide a reproducible machine learning framework to derive the potential biogeography of genomic functions through the multi-output regression of gene read counts on environmental climatologies. Leveraging the Marine ...

   Journal Article

3. The Hydrogen Intensity Real-time Analysis eXperiment: Overview and Status Update 

   Walters, Anthony; Bechoo, Keshav; Bhatporia, Shruti; et al. (2024)

   2024 18TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION, EUCAP

   The Hydrogen Intensity Real-time Analysis eXperiment (HIRAX) will be a large interferometric array of drift-scan radio telescopes designed to map the large-scale spatial fluctuations of neutral hydrogen in the Universe, in order to better understand the nature of dark energy. It will operate between 400-800 MHz, and is currently under construction in the Karoo desert of South Africa. It will also be a powerful tool for studying astronomical ...

   Conference Paper

4. Molecular Transducers of Physical Activity Consortium (MoTrPAC): human studies design and protocol 

   Jakicic J.M.; Kohrt W.M.; Houmard J.A.; et al. (2024)

   Journal of Applied Physiology

   Physical activity, including structured exercise, is associated with favorable health-related chronic disease outcomes. Although there is evidence of various molecular pathways that affect these responses, a comprehensive molecular map of these molecular responses to exercise has not been developed. The Molecular Transducers of Physical Activity Consortium (MoTrPAC) is a multicenter study designed to isolate the effects of structured ...

   Journal Article

5. Numerical analysis of physics-informed neural networks and related models in physics-informed machine learning 

   De Ryck T.; Mishra S. (2024)

   Acta Numerica

   Physics-informed neural networks (PINNs) and their variants have been very popular in recent years as algorithms for the numerical simulation of both forward and inverse problems for partial differential equations. This article aims to provide a comprehensive review of currently available results on the numerical analysis of PINNs and related models that constitute the backbone of physics-informed machine learning. We provide a unified ...

   Journal Article

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