RAP-modulated fluid processes:First passages and the stationary distribution

We construct a stochastic fluid process with an underlying piecewise deterministic Markov process (PDMP) akin to the one used in the construction of the rational arrival process (RAP) in Asmussen and Bladt (1999) which we call the RAP-modulated fluid process. As opposed to the classic Markov-modulated fluid process driven by a Markov jump process, the underlying PDMP of a RAP-modulated fluid process has a continuous state space and is driven by matrix parameters which may not be related to an intensity matrix. Through novel techniques we show how well-known formulae associated to the Markov-modulated fluid process, such as first passage probabilities and the stationary distribution of its queue, translate to its RAP-modulated counterpart.</p

Considerations on how to conduct a survey about long-distance travel with reduced memory effect

The paper presents a survey about international trips with overnight stays. Contrary to traditional retrospective long-distance travel surveys, respondents are asked for their 3-4 most recent trips. Due to this, the traditional huge memory effect is eliminated. The main part of the paper is dedicated to considerations on how to estimate the annual number of trips with this concept. Estimations based on the cumulated hazard function, which is a normal mathematical solution, are rejected because a new journey cannot start until the former was finished. Instead, extra trips should be simulated until all trips during a year are included

Influence of engineered self-healing systems on ASR damage development in concrete

Supplementary cementing materials (SCMs) have proven effective in minimizing alkali-silica reaction (ASR) development. In addition, crystalline admixtures (CAs) have been identified as potential solutions to counteract damage in concrete. However, limited data on this topic is available in the literature. This study investigates the impact of CA on concrete damage and is divided into two phases: 1) the effectiveness of CA in self-healing cracks and restoring the mechanical properties of mechanically damaged concrete; 2) it explores concrete mixtures incorporating a wide range of binder compositions (i.e., general use type cement, silica fume, fly ash, slag and Metakaolin) and chemical admixtures (i.e., commercially available CAs and modified versions) in conditions enabling ASR development. Both phases involve microscopic/mechanical analyses to assess the effects of CA on damage, and comparisons with concrete mixtures without CAs are made. The results reveal that CA enhanced the self-healing of cracks up to 82 % of cracks in cement paste (115 % higher values than concrete mixtures without CA) and restored 69 % of compressive strength. Furthermore, although CAs could change the damage mechanism of ASR, they did not “safely” mitigate it. However, combining SCMs and CAs effectively reduces ASR-induced expansion

A NIRCam-dark Galaxy Detected with the MIRI/F1000W Filter in the MIDIS/JADES Hubble Ultra Deep Field

We report the discovery of Cerberus, an extremely red object detected with the MIRI Deep Imaging Survey (MIDIS) observations in the F1000W filter of the Hubble Ultra Deep Field. The object is detected at signal-to-noise ratio (S/N) ∼ 6, with F1000W ∼ 27 mag, and undetected in the NIRCam data gathered by the JWST Advanced Deep Extragalactic Survey (JADES), fainter than the 30.0-30.5 mag 5σ detection limits in individual bands, as well as in the MIDIS F560W ultradeep data (∼29 mag, 5σ). Analyzing the spectral energy distribution built with low-S/N (&lt;5) measurements in individual optical-to-mid-infrared filters and higher-S/N (≳5) measurements in stacked NIRCam data, we discuss the possible nature of this red NIRCam-dark source using a battery of codes. We discard the possibility of Cerberus being a solar system body based on the &lt;0.″016 proper motion in the 1 yr apart JADES and MIDIS observations. A substellar Galactic nature is deemed unlikely, given that the Cerberus’s relatively flat NIRCam-to-NIRCam and very red NIRCam-to-MIRI flux ratios are not consistent with any brown dwarf model. The extragalactic nature of Cerberus offers three possibilities: (1) a z ∼ 0.4 galaxy with strong emission from polycyclic aromatic hydrocarbons—the very low inferred stellar mass, M ⋆ = 105-106 M ⊙, makes this possibility highly improbable; (2) a dusty galaxy at z ∼ 4 with an inferred stellar mass M ⋆ ∼ 108 M ⊙; and (3) a galaxy with observational properties similar to those of the reddest little red dots discovered around z ∼ 7, but Cerberus lying at z ∼ 15, with the rest-frame optical dominated by emission from a dusty torus or a dusty starburst.</p

Electron-photon exchange-correlation approximation for quantum-electrodynamical density-functional theory

Quantum-electrodynamical density-functional theory (QEDFT) provides a promising avenue for exploring complex light-matter interactions in optical cavities for real materials. Similar to conventional density-functional theory, the Kohn-Sham formulation of QEDFT needs approximations for the generally unknown exchange-correlation functional. In addition to the usual electron-electron exchange-correlation potential, an approximation for the electron-photon exchange-correlation potential is needed. A recent electron-photon exchange functional [C. Schäfer, Proc. Natl. Acad. Sci. USA 118, e2110464118 (2021)0027-842410.1073/pnas.2110464118], derived from the equation of motion of the nonrelativistic Pauli-Fierz Hamiltonian, shows robust performance in one-dimensional systems across weak- and strong-coupling regimes. Yet, its performance in reproducing electron densities in higher dimensions remains unexplored. Here we consider this QEDFT functional approximation from one- to three-dimensional finite systems and across weak to strong light-matter couplings. The electron-photon exchange approximation provides excellent results in the ultrastrong-coupling regime. However, to ensure accuracy also in the weak-coupling regime across higher dimensions, we introduce a computationally efficient renormalization factor for the electron-photon exchange functional, which accounts for part of the electron-photon correlation contribution. These findings extend the applicability of photon-exchange-based functionals to realistic cavity-matter systems, fostering the field of cavity QED (quantum-electrodynamics) materials engineering.</p

Towards Resilient Energy Forecasting: A Robust Optimization Approach

Energy forecasting models deployed in industrial applications face uncertainty w.r.t. data availability, due to network latency, equipment malfunctions or data-integrity attacks. In particular, the case when a subset of features that has been used for model training becomes unavailable when the model is used operationally poses a major challenge to forecasting performance. Ad-hoc solutions, e.g., retraining without the missing features, may work for a small number of features, but they soon become impractical, as the number of models grows exponentially with the number of features. In this work, we present a principled approach to introducing resilience against missing features in energy forecasting applications via robust optimization. Specifically, we formulate a robust regression model that is optimally resilient against missing features at test time, considering both point and probabilistic forecasting. We develop three solution methods for the proposed robust formulation, all leading to Linear Programming problems, with varying degrees of tractability and conservativeness. We provide an extensive empirical validation of the proposed methods in prevalent applications, namely, electricity price, load, wind production, and solar production, forecasting, and we further compare against well-established benchmark models and methods of dealing with missing features, i.e., imputation and retraining. Our results demonstrate that the proposed robust optimization approach outperforms imputation-based models and exhibits similar performance to retraining without the missing features, while also maintaining computational practicality. To the best of our knowledge, this is the first work that introduces resilience against missing features into energy forecasting

Optimal Design of Volt/VAR Control Rules for Inverter-Interfaced Distributed Energy Resources

The IEEE 1547 Standard for the interconnection of distributed energy resources (DERs) to distribution grids provisions that smart inverters could be implementing Volt/VAR control rules among other options. Such rules enable DERs to respond autonomously in response to time-varying grid loading conditions. The rules comprise affine droop control augmented with a deadband and saturation regions. Nonetheless, selecting the shape of these rules is not an obvious task, and the default options may not be optimal or dynamically stable. To this end, this work develops a novel methodology for customizing Volt/VAR rules on a per-bus basis for a single-phase feeder. The rules are adjusted by the utility every few hours depending on anticipated demand and solar scenarios. Using a projected gradient descent-based algorithm, rules are designed to improve the feeder’s voltage profile, comply with IEEE 1547 constraints, and guarantee stability of the underlying nonlinear grid dynamics. The stability region is inner approximated by a polytope and the rules are judiciously parameterized so their feasible set is convex. Numerical tests using real-world data on the IEEE 141-bus feeder corroborate the scalability of the methodology and explore the trade-offs of Volt/VAR control with alternatives

Time-series sewage metagenomics distinguishes seasonal, human-derived and environmental microbial communities potentially allowing source-attributed surveillance

Sewage metagenomics has risen to prominence in urban population surveillance of pathogens and antimicrobial resistance (AMR). Unknown species with similarity to known genomes cause database bias in reference-based metagenomics. To improve surveillance, we seek to recover sewage genomes and develop a quantification and correlation workflow for these genomes and AMR over time. We use longitudinal sewage sampling in seven treatment plants from five major European cities to explore the utility of catch-all sequencing of these population-level samples. Using metagenomic assembly methods, we recover 2332 metagenome-assembled genomes (MAGs) from prokaryotic species, 1334 of which were previously undescribed. These genomes account for ~69% of sequenced DNA and provide insight into sewage microbial dynamics. Rotterdam (Netherlands) and Copenhagen (Denmark) show strong seasonal microbial community shifts, while Bologna, Rome, (Italy) and Budapest (Hungary) have occasional blooms of Pseudomonas-dominated communities, accounting for up to ~95% of sample DNA. Seasonal shifts and blooms present challenges for effective sewage surveillance. We find that bacteria of known shared origin, like human gut microbiota, form communities, suggesting the potential for source-attributing novel species and their ARGs through network community analysis. This could significantly improve AMR tracking in urban environments

WISDOM Project - XXI. Giant molecular clouds in the central region of the barred spiral galaxy NGC 613:a steep size-linewidth relation

NGC 613 is a nearby barred spiral galaxy with a nuclear ring. Exploiting high spatial resolution (≈20 pc) Atacama Large Millimetre/submillimetre Array 12CO(1–0) observations, we study the giant molecular clouds (GMCs) in the nuclear ring and its vicinity, identifying 158 spatially and spectrally resolved GMCs. The GMC sizes (Rc) are comparable to those of the clouds in the Milky Way (MW) disc, but their gas masses, observed linewidths (σobs,los), and gas mass surface densities are larger