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In conventional ferroelectrics the electric dipoles are generated by off-center displacements of ions. In recent years, a new type of so-called electronic ferroelectrics has attracted great attention, where the polarization is driven by electronic degrees of freedom. Of particular interest are materials with strong electronic correlations, featuring a variety of intriguing phenomena and instabilities, which may interact with or even induce electronic ferroelectricity. In this review, we will focus on the class of strongly correlated charge-transfer salts, where electronic ferroelectricity was suggested by theory and has been confirmed by numerous experiments. The paper summarizes some basic physical properties of various relevant quasi-two dimensional salts and gives some background on the experimental tools applied to establish ferroelectricity. We discuss the key experimental observations, including the exciting discovery of multiferroicity, and provide some theoretical considerations on the magnetoelectric couplings that are of relevance here.

Low-carbon hydrogen (H2) is envisioned to play a central role in decarbonizing European hard-to-abate industries, such as refineries, ammonia, methanol, steel, and cement. To enable its widespread use, H2 supply chain (HSC) infrastructure is required. Mature and economically viable low-carbon H2 production pathways include steam methane reforming (SMR) of natural gas coupled with carbon dioxide capture and storage (CCS), water-electrolysis from renewable electricity, biomethane reforming, and biomass gasification. However, uncertainties surrounding demand and feedstock availabilities hamper their proliferation. Here, we investigate the impact of uncertainty in H2 demand and biomass availability on the optimal HSC design. The HSC is modeled as a network of H2 production and consumption sites that are interconnected with H2 and biomass transport technologies. A CCS supply chain is modeled alongside the HSC. The cost-optimal HSC design is determined based on a linear optimization problem that considers a regional resolution and a multi-year time horizon (2022-2050). We adopt a scenario-based uncertainty quantification approach and define discrete H2 demand and biomass availability scenarios. Applying a minimum-regret strategy, we show that sufficiently large low-carbon H2 production capacities (about 9.6 Mt/a by 2030) are essential to flexibly scale up HSCs and accommodate H2 demands of up to 35 Mt/a by 2050. While biomass-based H2 production emerges as the most cost-efficient low-carbon H2 production pathway, investments are not recommended unless the availability of biomass feedstocks is guaranteed. Instead, investments in SMR-CCS and electrolysis often offer greater flexibility. In addition, we highlight the importance of CCS infrastructure, which is required across scenarios., Comment: 20 pages, 7 figures

We discuss some categorical aspects of the objects that appear in the construction of the Monster and other sporadic simple groups. We define the basic representation of the categorical torus $\mathcal T$ classified by an even symmetric bilinear form $I$ and of the semi-direct product of $\mathcal T$ with its canonical involution. We compute the centraliser of the basic representation of $\mathcal T\rtimes\{\pm1\}$ and find it to be a categorical extension of the extraspecial $2$-group with commutator $I\mod 2$. We study the inertia groupoid of a categorical torus and find that it is given by the torsor of the topological Looijenga line bundle, so that $2$-class functions on $\mathcal T$ are canonically theta-functions. We discuss how discontinuity of the categorical character in our formalism means that the character of the basic representation fails to be a categorical class function. We compute the automorphisms of $\mathcal T$ and of $\mathcal T\rtimes\{\pm1\}$ and relate these to the Conway groups., Comment: 33 pages

We present results of the coefficient of thermal expansion for the frustrated quasi-two-dimensional molecular conductor $\theta$-(BEDT-TTF)$_2$RbZn(SCN)$_4$ for temperatures 1.5 K $\leq T \leq$ 290 K. A pronounced first-order phase transition anomaly is observed at the combined charge-order/structural transition at 215 K. Furthermore, clear evidence is found for two separate glasslike transitions at $T_{\mathrm{g}}$ = 90-100 K and $T_{\mathrm{g}}^\dagger$ = 120-130 K, similar to previous findings for $\theta$-(BEDT-TTF)$_2$CsZn(SCN)$_4$ and $\theta$-(BEDT-TTF)$_2$CsCo(SCN)$_4$, reported in T. Thomas et al., Phys. Rev. B 105, L041114 (2022), both of which lack the charge-order/structural transition. Our findings indicate that these glasslike transitions are common features for the $\theta$-(BEDT-TTF)$_2MM^\prime$(SCN)$_4$ family with $M$ = (Rb, Cs) and $M^\prime$ = (Co, Zn), irrespective of the presence or absence of charge order. These results are consistent with our model calculations on the glasslike dynamics associated with the flexible ethylene endgroups of the BEDT-TTF molecules for various $\theta$-(BEDT-TTF)$_2MM^\prime$(SCN)$_4$ salts, predicting two different conformational glass transitions. Moreover, calculations of the hopping integrals show a substantial degree of dependence on the endgroups' conformation, suggesting a significant coupling to the electronic degrees of freedom. Our findings support the possibility that the glassy freezing of the ethylene endgroups could drive or enhance glassy charge dynamics., Comment: 11 pages, 10 figures, 1 table

Traditional deep learning (DL) models are powerful classifiers, but many approaches do not provide uncertainties for their estimates. Uncertainty quantification (UQ) methods for DL models have received increased attention in the literature due to their usefulness in decision making, particularly for high-consequence decisions. However, there has been little research done on how to evaluate the quality of such methods. We use statistical methods of frequentist interval coverage and interval width to evaluate the quality of credible intervals, and expected calibration error to evaluate classification predicted confidence. These metrics are evaluated on Bayesian neural networks (BNN) fit using Markov Chain Monte Carlo (MCMC) and variational inference (VI), bootstrapped neural networks (NN), Deep Ensembles (DE), and Monte Carlo (MC) dropout. We apply these different UQ for DL methods to a hyperspectral image target detection problem and show the inconsistency of the different methods' results and the necessity of a UQ quality metric. To reconcile these differences and choose a UQ method that appropriately quantifies the uncertainty, we create a simulated data set with fully parameterized probability distribution for a two-class classification problem. The gold standard MCMC performs the best overall, and the bootstrapped NN is a close second, requiring the same computational expense as DE. Through this comparison, we demonstrate that, for a given data set, different models can produce uncertainty estimates of markedly different quality. This in turn points to a great need for principled assessment methods of UQ quality in DL applications.

As the number of recorded meetings increases, it becomes increasingly important to utilize summarization technology to create useful summaries of these recordings. However, there is a crucial lack of annotated meeting corpora for developing this technology, as it can be hard to collect meetings, especially when the topics discussed are confidential. Furthermore, meeting summaries written by experienced writers are scarce, making it hard for abstractive summarizers to produce sensible output without a reliable reference. This lack of annotated corpora has hindered the development of meeting summarization technology. In this paper, we present MeetingBank, a new benchmark dataset of city council meetings over the past decade. MeetingBank is unique among other meeting corpora due to its divide-and-conquer approach, which involves dividing professionally written meeting minutes into shorter passages and aligning them with specific segments of the meeting. This breaks down the process of summarizing a lengthy meeting into smaller, more manageable tasks. The dataset provides a new testbed of various meeting summarization systems and also allows the public to gain insight into how council decisions are made. We make the collection, including meeting video links, transcripts, reference summaries, agenda, and other metadata, publicly available to facilitate the development of better meeting summarization techniques. Our dataset can be accessed at: https://meetingbank.github.io, Comment: ACL 2023 Long Paper

Purpose: Determine the correct mathematical phase description for balanced steady-state free precession (bSSFP) signals in multicompartment systems. Theory and Methods: Based on published bSSFP signal models, two distinct phase descriptions can be formulated: one predicting the presence and the other predicting the absence of destructive interference effects in multicompartment systems. Numerical simulations of bSSFP signals of water and acetone were performed to evaluate the predictions of these two distinct phase descriptions. For experimental validation, bSSFP profiles were measured at 3T using phase-cycled bSSFP acquisitions performed in a phantom containing mixtures of water and acetone, which replicates a system with two signal components. Localized single voxel MRS was performed at 7T to determine the relative chemical-shift of the acetone-water mixtures. Results: Based on the choice of phase description, the simulated bSSFP profiles of water-acetone mixtures varied significantly, either displaying or lacking destructive interference effects, as predicted theoretically. In phantom experiments, destructive interference was consistently observed in the measured bSSFP profiles of water-acetone mixtures, an observation which excludes the phase description that predicts an absence of destructive interference. The connection between the choice of phase description and predicted observation enables an unambiguous experimental identification of the correct phase description for multicompartment bSSFP profiles, which is consistent with Bloch equations. Conclusion: The study emphasizes that consistent phase descriptions are crucial for accurately describing multi-compartment bSSFP signals, as incorrect phase descriptions result in erroneous predictions., Comment: Submitted to Magn. Reson. Med

Conceptual Scaling is a useful standard tool in Formal Concept Analysis and beyond. Its mathematical theory, as elaborated in the last chapter of the FCA monograph, still has room for improvement. As it stands, even some of the basic definitions are in flux. Our contribution was triggered by the study of concept lattices for tree classifiers and the scaling methods used there. We extend some basic notions, give precise mathematical definitions for them and introduce the concept of scaling dimension. In addition to a detailed discussion of its properties, including an example, we show theoretical bounds related to the order dimension of concept lattices. We also study special subclasses, such as the ordinal and the interordinal scaling dimensions, and show for them first results and examples.

The rising share of volatile renewable generation increases the demand for flexibility in the electricity grid. Flexible capacity can be offered by industrial energy systems through participation on either the continuous intraday, day-ahead, or balancing-power markets. Thus, industrial energy systems face the problem of where to market their flexible capacity. Here, we propose a method to integrate trading on the continuous intraday market into a multi-market optimization for flexible industrial energy systems. To estimate the intraday market revenues, we employ option-price theory. Subsequently, a multi-stage stochastic optimization determines an optimized bidding strategy and allocates the flexible capacity. The method is applied to a case study of a multi-energy system showing that coordinated bidding in all three considered markets reduces cost most. A sensitivity analysis for the intraday market volatility reveals changing market preferences, thus emphasizing the need for multi-market optimization. The proposed method provides a practical decision-support tool in short-term electricity and balancing-power markets., Comment: manuscript (25 pages, 9 figures, 2 tables)

The intersection of topology, symmetry, and magnetism yields a rich structure of possible phases. In this work, we study theoretically the consequences of magnetism on IrF4, which was recently identified as a possible candidate topological nodal chain semimetal in the absence of magnetic order. We show that the spin-orbital nature of the Ir moments gives rise to strongly anisotropic magnetic couplings resembling a tetrahedral compass model on a diamond lattice. The predicted magnetic ground state preserves key symmetries protecting the nodal lines, such that they persist into the ordered phase at the mean-field level. The consequences for other symmetry reductions are also discussed.