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In the Swiss canton of Geneva, an energy efficiency portfolio has been operated since 2009. In contrast, such programs have been in place for more than 40 years in the US. There are numerous lessons to be learnt from their experience. We have therefore conducted a comparative analysis including Geneva and 11 leading states in the US, with the objective to identify explanatory factors for the succe
Heating systems must be subjected to hydraulic balancing in order to ensure proper operation. When the heating system is hydraulically imbalanced, heat is unevenly distributed across dwellings resulting in a large temperature spread, overheating, and consequently, waste of energy. In this study, we investigate the extent to which hydraulic imbalance affects the thermal energy consumption in buildi
A search for R-parity-conserving supersymmetry in events with large missing transverse momentum, jets and at least one hadronically decaying τ-lepton is presented. Both gluino and squark pair production are considered, with the cascade decay of each gluino or squark producing either a τ-slepton or a τ-sneutrino. Three channels are examined, requiring either exactly one hadronically decaying τ-lept
Modern battery chargers require AC-DC converters with high input power quality, nearly unity power factor, and low current harmonics to meet grid standards such as IEC 61000-3-2. This paper proposes a two-stage charger topology: a front-end bridgeless interleaved boost PFC converter followed by a synchronous buck DC-DC stage. The interleaved boost stage reduces input current ripple and losses whil
In order for any learning-based model to be considered reliable, it needs a well-behaved uncertainty or confidence estimate. Most modern neural networks do produce a confidence estimate in the form of their softmax output probability. However, the softmax probability is invalid for out-of-distribution data. Gaussian processes are known to produce a well-behaved confidence estimate that is aware of
The efficiency and durability of Polymer Electrolyte Fuel Cells (PEFCs) depend on optimizing porous media components such as gas diffusion and catalyst layers. In parallel, the Lattice Boltzmann Method (LBM) has emerged as a powerful tool to model fluid flow, mass transport, and multiphase interactions in complex porous structures. This works provides a concise overview of recent advances in apply
The field of general-purpose robotics has recently embraced powerful probabilistic diffusion-based models to learn the complex embodiment behaviours. However, existing models often come with significant trade-offs, namely high computational costs for inference and a fundamental inability to quantify output uncertainty. We introduce Normalizing Flows Policy (NF-P), a conditional normalizing flow-ba
