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Many modern consumer devices rely on network connections and cloud services to perform their core functions. This dependency is especially present in Internet of Things (IoT) devices, which combine hardware and software with network connections (e.g., a 'smart' doorbell with a camera). This paper argues that current European product legislation, which aims to protect consumers of, inter alia, IoT devices, has a blind spot for an increasing problem in the competitive IoT market: manufacturer cessation. Without the manufacturer's cloud servers, many IoT devices cannot perform core functions such as data analysis. If an IoT manufacturer ceases their operations, consumers of the manufacturer's devices are thus often left with a dysfunctional device and, as the paper shows, hardly any legal remedies. This paper therefore investigates three properties that could support legislators in finding a solution for IoT manufacturer cessation: i) pre-emptive measures, aimed at ii) manufacturer-independent iii) collective control. The paper finally shows how these three properties already align with current legislative processes surrounding 'interoperability' and open-source software development.

For an endofunctor $F\colon\mathcal{C}\to\mathcal{C}$ on an ($\infty$-)category $\mathcal{C}$ we define the $\infty$-category $\operatorname{Cart}(\mathcal{C},F)$ of generalized Cartier modules as the lax equalizer of $F$ and the identity. This generalizes the notion of Cartier modules on $\mathbb{F}_p$-schemes considered in the literature. We show that in favorable cases $\operatorname{Cart}(\mathcal{C},F)$ is monadic over $\mathcal{C}$. If $\mathcal{A}$ is a Grothendieck abelian category and $F\colon\mathcal{A}\to\mathcal{A}$ is an exact and colimit-preserving endofunctor, we use this fact to construct an equivalence $\mathcal{D}(\operatorname{Cart}(\mathcal{A},F)) \simeq \operatorname{Cart}(\mathcal{D}(\mathcal{A}),\mathcal{D}(F))$ of stable $\infty$-categories. We use this equivalence to give a more conceptual construction of the perverse t-structure on $\mathcal{D}^b_{\operatorname{coh}}(\operatorname{Cart}(\operatorname{QCoh}(X), F_*))$ for any Noetherian $\mathbb{F}_p$-scheme $X$ with finite absolute Frobenius $F\colon X\to X$., Comment: 35 pages, comments welcome!

Probabilistic relational models provide a well-established formalism to combine first-order logic and probabilistic models, thereby allowing to represent relationships between objects in a relational domain. At the same time, the field of artificial intelligence requires increasingly large amounts of relational training data for various machine learning tasks. Collecting real-world data, however, is often challenging due to privacy concerns, data protection regulations, high costs, and so on. To mitigate these challenges, the generation of synthetic data is a promising approach. In this paper, we solve the problem of generating synthetic relational data via probabilistic relational models. In particular, we propose a fully-fledged pipeline to go from relational database to probabilistic relational model, which can then be used to sample new synthetic relational data points from its underlying probability distribution. As part of our proposed pipeline, we introduce a learning algorithm to construct a probabilistic relational model from a given relational database., Comment: Accepted to the Proceedings of the 47th German Conference on Artificial Intelligence (KI 2024)

Near-infrared emitting colloidal two-dimensional (2D) PbX (X=S, Se) nanoplatelets have emerged as interesting materials with strong size quantisation in the thickness dimension. They act as model systems for efficient charge carrier multiplication and hold potential as intriguing candidates for finer-based photonic quantum applications. However, synthetic access to the third family member, 2D PbTe, remains elusive due to a challenging precursor chemistry. Here, we report a direct synthesis for 2D PbTe nanoplatelets (NPLs) with unable photoluminescence (PL, 910-1460 nm (1.36-0.85 eV), PLQY 1-15 %), based on aminophosphine precursor chemistry. Ex-situ transamination of tris(dimethylamino)phosphine telluride with octylamine is confirmed by 31P NMR and yields a reactive tellurium precursor for the formation of 2D PbTe NPLs at temperatures as low as 0 {\deg}C. The PL position of the PbTe NPLs is unable by controlling the Pb:Te ration in the reaction. GIWAXS confirms the 2D geometry of the NPLs and the formation of superlattices. The importance of a post-synthetic passivation of the PbTe NPLs by PbI2 to ensure colloidal stability of the otherwise oxygen sensitive samples is supported by X-ray photoelectron spectroscopy. Our results expand and complete the row of lead chalcogenide-based 2D NPLs, opening up new ways for further pushing the optical properties of 2D NPLs into the infrared and toward technologically relevant wavelengths.

When comparing speech sounds across languages, scholars often make use of feature representations of individual sounds in order to determine fine-grained sound similarities. Although binary feature systems for large numbers of speech sounds have been proposed, large-scale computational applications often face the challenges that the proposed feature systems -- even if they list features for several thousand sounds -- only cover a smaller part of the numerous speech sounds reflected in actual cross-linguistic data. In order to address the problem of missing data for attested speech sounds, we propose a new approach that can create binary feature vectors dynamically for all sounds that can be represented in the the standardized version of the International Phonetic Alphabet proposed by the Cross-Linguistic Transcription Systems (CLTS) reference catalog. Since CLTS is actively used in large data collections, covering more than 2,000 distinct language varieties, our procedure for the generation of binary feature vectors provides immediate access to a very large collection of multilingual wordlists. Testing our feature system in different ways on different datasets proves that the system is not only useful to provide a straightforward means to compare the similarity of speech sounds, but also illustrates its potential to be used in future cross-linguistic machine learning applications., Comment: To appear in the Proceedings of the 2024 Meeting of the Society for Computation in Linguistics (SCiL)

We show that for a large class of $\infty$-topoi there exist unstable arithmetic fracture squares, i.e. squares which recover a nilpotent sheaf $F$ as the pullback of the rationalization of $F$ with the product of the $p$-completions of $F$ ranging over all primes $p\in\mathbb Z$., Comment: 34 pages. Comments welcome!

We construct the pro-Nisnevich topology, an analog of the pro-\'etale topology. We then show that the Nisnevich $\infty$-topos embeds into the pro-Nisnevich $\infty$-topos, and that the pro-Nisnevich $\infty$-topos is locally of homotopy dimension $0$., Comment: 10 pages, Comments welcome!

Climate neutrality paradigms put electricity systems at the core of a clean energy supply. At the same time, indirect electrification, with a potential uptake of hydrogen or derived fuel economy, plays a crucial role in decarbonising the energy supply and industrial processes. Besides energy markets coordinating the transition, climate and energy policy targets require fundamental changes and expansions in the energy transmission, import, distribution, and storage infrastructures. While existing studies identify relevant demands for hydrogen, critical decisions involve imports versus domestic fuel production and investments in new or repurposing existing pipeline and storage infrastructure. Linking the pan-European energy system planning model SCOPE SD with the multiperiod European gas market model IMAGINE, the case study analysis and its transformation pathway results indicate extensive network development of hydrogen infrastructure, including expansion beyond refurbished methane infrastructure. However, the ranges of future hydrogen storage costs and market uptake restrictions expose and quantify the uncertainty of its role in Europes transformation. The study finds that rapidly planning the construction of hydrogen storage and pipeline infrastructure is crucial to achieving the required capacity by 2050.

Lifted inference exploits symmetries in probabilistic graphical models by using a representative for indistinguishable objects, thereby speeding up query answering while maintaining exact answers. Even though lifting is a well-established technique for the task of probabilistic inference in relational domains, it has not yet been applied to the task of causal inference. In this paper, we show how lifting can be applied to efficiently compute causal effects in relational domains. More specifically, we introduce parametric causal factor graphs as an extension of parametric factor graphs incorporating causal knowledge and give a formal semantics of interventions therein. We further present the lifted causal inference algorithm to compute causal effects on a lifted level, thereby drastically speeding up causal inference compared to propositional inference, e.g., in causal Bayesian networks. In our empirical evaluation, we demonstrate the effectiveness of our approach., Comment: Accepted to the Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR-24)

Closely related languages show linguistic similarities that allow speakers of one language to understand speakers of another language without having actively learned it. Mutual intelligibility varies in degree and is typically tested in psycholinguistic experiments. To study mutual intelligibility computationally, we propose a computer-assisted method using the Linear Discriminative Learner, a computational model developed to approximate the cognitive processes by which humans learn languages, which we expand with multilingual semantic vectors and multilingual sound classes. We test the model on cognate data from German, Dutch, and English, three closely related Germanic languages. We find that our model's comprehension accuracy depends on 1) the automatic trimming of inflections and 2) the language pair for which comprehension is tested. Our multilingual modelling approach does not only offer new methodological findings for automatic testing of mutual intelligibility across languages but also extends the use of Linear Discriminative Learning to multilingual settings., Comment: To appear in: Proceedings of the 6th Workshop on Research in Computational Linguistic Typology and Multilingual NLP (SIGTYP 2024)

In traditional studies on language evolution, scholars often emphasize the importance of sound laws and sound correspondences for phylogenetic inference of language family trees. However, to date, computational approaches have typically not taken this potential into account. Most computational studies still rely on lexical cognates as major data source for phylogenetic reconstruction in linguistics, although there do exist a few studies in which authors praise the benefits of comparing words at the level of sound sequences. Building on (a) ten diverse datasets from different language families, and (b) state-of-the-art methods for automated cognate and sound correspondence detection, we test, for the first time, the performance of sound-based versus cognate-based approaches to phylogenetic reconstruction. Our results show that phylogenies reconstructed from lexical cognates are topologically closer, by approximately one third with respect to the generalized quartet distance on average, to the gold standard phylogenies than phylogenies reconstructed from sound correspondences., Comment: Paper accepted for SIGTYP (2024): H\"auser, Luise; J\"ager, Gerhard; List, Johann-Mattis; Rama, Taraka; and Stamatakis, Alexandros (2024): Are sounds sound for phylogenetic reconstruction? In: Proceedings of the 6th Workshop on Research in Computational Linguistic Typology and Multilingual NLP (SIGTYP 2024)

We define unstable $p$-completion in general $\infty$-topoi and the unstable motivic homotopy category, and prove that the $p$-completion of a nilpotent sheaf or motivic space can be computed on its Postnikov tower. We then show that the ($p$-completed) homotopy groups of the $p$-completion of a nilpotent motivic space $X$ fit into short exact sequences $0 \to \mathbb L_0 \pi_n(X) \to \pi_n^p(X_p^\wedge) \to \mathbb L_1 \pi_{n-1}(X) \to 0$, where the $\mathbb L_i$ are (versions of) the derived $p$-completion functors, analogous to the classical situation., Comment: 98 pages. Comments welcome!

Despite the inherently fuzzy nature of reconstructions in historical linguistics, most scholars do not represent their uncertainty when proposing proto-forms. With the increasing success of recently proposed approaches to automating certain aspects of the traditional comparative method, the formal representation of proto-forms has also improved. This formalization makes it possible to address both the representation and the computation of uncertainty. Building on recent advances in supervised phonological reconstruction, during which an algorithm learns how to reconstruct words in a given proto-language relying on previously annotated data, and inspired by improved methods for automated word prediction from cognate sets, we present a new framework that allows for the representation of uncertainty in linguistic reconstruction and also includes a workflow for the computation of fuzzy reconstructions from linguistic data., Comment: To appear in: Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change

We present a cross-linguistic study that aims to quantify vowel harmony using data-driven computational modeling. Concretely, we define an information-theoretic measure of harmonicity based on the predictability of vowels in a natural language lexicon, which we estimate using phoneme-level language models (PLMs). Prior quantitative studies have relied heavily on inflected word-forms in the analysis of vowel harmony. We instead train our models using cross-linguistically comparable lemma forms with little or no inflection, which enables us to cover more under-studied languages. Training data for our PLMs consists of word lists with a maximum of 1000 entries per language. Despite the fact that the data we employ are substantially smaller than previously used corpora, our experiments demonstrate the neural PLMs capture vowel harmony patterns in a set of languages that exhibit this phenomenon. Our work also demonstrates that word lists are a valuable resource for typological research, and offers new possibilities for future studies on low-resource, under-studied languages., Comment: Presented at SIGTYP at EACL 2023

Quantum bits (qubits) are prone to several types of errors due to uncontrolled interactions with their environment. Common strategies to correct these errors are based on architectures of qubits involving daunting hardware overheads. A hopeful path forward is to build qubits that are inherently protected against certain types of errors, so that the overhead required to correct remaining ones is significantly reduced. However, the foreseen benefit rests on a severe condition: quantum manipulations of the qubit must not break the protection that has been so carefully engineered. A recent qubit - the cat-qubit - is encoded in the manifold of metastable states of a quantum dynamical system, thereby acquiring continuous and autonomous protection against bit-flips. Here, in a superconducting circuit experiment, we implement a cat-qubit with bit-flip times exceeding 10 seconds. This is a four order of magnitude improvement over previous cat-qubit implementations. We prepare and image quantum superposition states, and measure phase-flip times above 490 nanoseconds. Most importantly, we control the phase of these quantum superpositions without breaking bit-flip protection. This experiment demonstrates the compatibility of quantum control and inherent bit-flip protection at an unprecedented level, showing the viability of these dynamical qubits for future quantum technologies.

Since the first proof-of-principle experiments 25 years ago, quantum metrology has matured from fundamental concepts to versatile and powerful tools in a large variety of research branches, such as gravitational-wave detection, atomic clocks, plasmonic sensing, and magnetometry. At the same time, two-photon interferometry, which underpins the possibility of entanglement to probe optical materials with unprecedented levels of precision and accuracy, holds the promise to stand at the heart of innovative functional quantum sensing systems. We report a novel quantum-based method for measuring the frequency dependence of the velocity in a transparent medium, i.e, the chromatic dispersion (CD). This technique, using energy-time entangled photons, allows straightforward access to CD value from the visibility of two-photon fringes recorded in a free evolution regime. In addition, our quantum approach features all advantages of classical measurement techniques, i.e, flexibility and accuracy, all in a plug-and-play system.

The determination of orientation relationships in dual or multi-phase materials is very important in the field of interface engineering for the design of materials with tailored properties. In this work, a code is developed for the automated and statistical analysis of the orientation relationship of electron backscatter diffraction data. On the example of Fe-Ni-(Si)-C alloys containing lenticular martensite and retained austenite, the code is applied and it is shown that the orientation relationship (OR) corresponds to the Greninger-Troiano OR and that a statistically reliable investigation of the OR between the retained austenite and the related martensite variants is feasible using the code developed in this study., Comment: in revision currently in Crystals

Sound correspondence patterns form the basis of cognate detection and phonological reconstruction in historical language comparison. Methods for the automatic inference of correspondence patterns from phonetically aligned cognate sets have been proposed, but their application to multilingual wordlists requires extremely well annotated datasets. Since annotation is tedious and time consuming, it would be desirable to find ways to improve aligned cognate data automatically. Taking inspiration from trimming techniques in evolutionary biology, which improve alignments by excluding problematic sites, we propose a workflow that trims phonetic alignments in comparative linguistics prior to the inference of correspondence patterns. Testing these techniques on a large standardized collection of ten datasets with expert annotations from different language families, we find that the best trimming technique substantially improves the overall consistency of the alignments. The results show a clear increase in the proportion of frequent correspondence patterns and words exhibiting regular cognate relations., Comment: The paper was accepted at the SIGTYP workshop 2023 co-located with EACL

The past years have seen a drastic rise in studies devoted to the investigation of colexification patterns in individual languages families in particular and the languages of the world in specific. Specifically computational studies have profited from the fact that colexification as a scientific construct is easy to operationalize, enabling scholars to infer colexification patterns for large collections of cross-linguistic data. Studies devoted to partial colexifications -- colexification patterns that do not involve entire words, but rather various parts of words--, however, have been rarely conducted so far. This is not surprising, since partial colexifications are less easy to deal with in computational approaches and may easily suffer from all kinds of noise resulting from false positive matches. In order to address this problem, this study proposes new approaches to the handling of partial colexifications by (1) proposing new models with which partial colexification patterns can be represented, (2) developing new efficient methods and workflows which help to infer various types of partial colexification patterns from multilingual wordlists, and (3) illustrating how inferred patterns of partial colexifications can be computationally analyzed and interactively visualized.

Language contact is a pervasive phenomenon reflected in the borrowing of words from donor to recipient languages. Most computational approaches to borrowing detection treat all languages under study as equally important, even though dominant languages have a stronger impact on heritage languages than vice versa. We test new methods for lexical borrowing detection in contact situations where dominant languages play an important role, applying two classical sequence comparison methods and one machine learning method to a sample of seven Latin American languages which have all borrowed extensively from Spanish. All methods perform well, with the supervised machine learning system outperforming the classical systems. A review of detection errors shows that borrowing detection could be substantially improved by taking into account donor words with divergent meanings from recipient words., Comment: To appear at The 17th Conference of the European Chapter of the Association for Computational Linguistics. See https://www.aclweb.org/portal/content/17th-conference-european-chapter-association-computational-linguistics