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Latent geometry emerging from network-driven processes

Understanding network functionality requires integrating structure and dynamics, and emergent latent geometry induced by network-driven processes captures the low-dimensional spaces governing this interplay. In this Perspective, we review generative-model-based approaches, distinguishing two reconstruction classes: fixed-time methods, which infer geometry at specific temporal scales (e.g., equilibrium), and multi-resolution methods, which integrate dynamics across near- and far-from-equilibri...

A Practical Tutorial on Explainable AI Techniques

The past years have been characterized by an upsurge in opaque automatic decision support systems, such as Deep Neural Networks (DNNs). Although DNNs have great generalization and prediction abilities, it is difficult to obtain detailed explanations for their behavior. As opaque Machine Learning models are increasingly being employed to make important predictions in critical domains, there is a danger of creating and using decisions that are not justifiable or legitimate. Therefore, there is ...

Formation of luminescent defects in 4H-SiC upon ion irradiation and ns laser annealing

We present a novel approach for the optical activation of the negatively-charged silicon vacancy ( VSi−) center in ion irradiated silicon carbide (SiC) via ns-pulsed laser annealing in the 234–2180 mJ cm− 2 energy density range. The laser annealing process is investigated under 355 nm and 532 nm wavelengths at pulse energy densities below the melting threshold and validated by means of Raman spectroscopy and photoluminescence mapping. The combined effect of ns pulsed laser annealing and subse...

Super Resolution of Satellite-Based Land Surface Temperature Through Airborne Thermal Imaging

Urban heat island pose a significant threat to public health and urban livability. UHI maps are created using satellite thermal data, a crucial source for earth monitoring and for delivering mitigation strategies. Nowadays there is still a resolution gap between high-resolution optical data and low-resolution satellite thermal imagery. This study introduces a novel deep learning approach—named Dilated Spatio-Temporal U-Net (DST-UNet)—to bridge this gap. DST-UNET is a modified U-Net architectu...

Multispacecraft Observations of the 27 Day Periodicity in Galactic Protons from 2018 to 2019

Galactic cosmic-ray (GCR) intensities exhibit recurrent variations caused by their passage through plasma interaction regions corotating with the Sun, with the ∼27 day periodicity being the most prominent one. Data collected by the High-Energy Particle Detector (HEPD-01) on board the China Seismo-Electromagnetic Satellite in Low-Earth Orbit have been used to derive daily proton fluxes from 2018 to 2019 August, in the energy range between ∼55 and ∼200 MeV. Daily fluxes from HEPD-01 have been a...

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