Global Helium Industry Intelligence
Energies, Vol. 19, Pages 1511: Field Tests and Applicability Analysis of an Underground Cooling Installation Powered by Ventilation Air Methane (VAM) Energies doi: 10.3390/en19061511 Authors: Robert…
Energies, Vol. 19, Pages 1512: Phase-Space Reconstruction and 2-D Fourier Descriptor Features for Appliance Classification in Non-Intrusive Load Monitoring Energies doi: 10.3390/en19061512 Authors: Motaz Abu Sbeitan…
Energies, Vol. 19, Pages 1513: Evidential Deep Learning for Quantification of Uncertainty in Lithium-Ion Batteries Remaining Useful Life Estimation Energies doi: 10.3390/en19061513 Authors: Luca Martiri Loredana…
arXiv:2603.13838v1 Announce Type: new Abstract: High-quality proton beams generated by laser-plasma interactions are of significant interest for applications ranging from tumor therapy to fast ignition in…
arXiv:2603.13797v1 Announce Type: new Abstract: Collective optical excitations, such as localized surface plasmons in metallic nanoparticles and Mie resonances in high-index dielectrics, play a central role…
arXiv:2603.13715v1 Announce Type: new Abstract: Large-scale land enclosure for speculative mega-development constitutes a non-equilibrium spatial process whose velocity, topology, and irreversibility remain poorly quantified. We study…
arXiv:2603.13697v1 Announce Type: new Abstract: A high-resolution Eulerian method for simulating high-speed polydisperse granular multiphase flows has been developed. The governing equations include a compressible gas…
arXiv:2603.13687v1 Announce Type: new Abstract: Murray’s cubic branching law ($alpha=3$) predicts a universal diameter scaling exponent for all hierarchical transport networks, yet arterial trees yield $alpha…
arXiv:2603.13658v1 Announce Type: new Abstract: Reduced graphene oxide (rGO) exhibits strong anisotropic light absorption and high compatibility with photonic integrated chips, making it a promising material…
arXiv:2603.13645v1 Announce Type: new Abstract: We introduce the Seismic Waveforms dataset for Automatic Neural-network processing (SWAN), a comprehensive and standardized benchmark designed to advance data-driven seismic…