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The many initiatives on trustworthy AI result in a confusing and multipolar landscape that organizations operating within the fluid and complex international value chains must navigate in pursuing trustworthy AI. The EU's AI Act will now shift the focus of such organizations toward conformance with the technical requirements for regulatory compliance, for which the Act relies on Harmonized Standards. Though a high-level mapping to the Act's requirements will be part of such harmonization, determining the degree to which standards conformity delivers regulatory compliance with the AI Act remains a complex challenge. Variance and gaps in the definitions of concepts and how they are used in requirements between the Act and harmonized standards may impact the consistency of compliance claims across organizations, sectors, and applications. This may present regulatory uncertainty, especially for SMEs and public sector bodies relying on standards conformance rather than proprietary equivalents for developing and deploying compliant high-risk AI systems. To address this challenge, this paper offers a simple and repeatable mechanism for mapping the terms and requirements relevant to normative statements in regulations and standards, e.g., AI Act and ISO management system standards, texts into open knowledge graphs. This representation is used to assess the adequacy of standards conformance to regulatory compliance and thereby provide a basis for identifying areas where further technical consensus development in trustworthy AI value chains is required to achieve regulatory compliance., Comment: This work was presented at the 9th International Symposium on Language & Knowledge Engineering (LKE 2024) Dublin, Ireland, 4 - 6 June, 2024

This paper introduces a collaborative, human-centred taxonomy of AI, algorithmic and automation harms. We argue that existing taxonomies, while valuable, can be narrow, unclear, typically cater to practitioners and government, and often overlook the needs of the wider public. Drawing on existing taxonomies and a large repository of documented incidents, we propose a taxonomy that is clear and understandable to a broad set of audiences, as well as being flexible, extensible, and interoperable. Through iterative refinement with topic experts and crowdsourced annotation testing, we propose a taxonomy that can serve as a powerful tool for civil society organisations, educators, policymakers, product teams and the general public. By fostering a greater understanding of the real-world harms of AI and related technologies, we aim to increase understanding, empower NGOs and individuals to identify and report violations, inform policy discussions, and encourage responsible technology development and deployment., Comment: 21 pages, 2 figures; typos corrected, reference missing fields fixed, printer-friendly version of a diagram added

Considering that there is very little information on the behavior habits of guigna cats, as well as investigations in which small populations are captured to place radiocollars on them and then release them in the place where they were captured, which is done with the intention of collecting data on their positions in a territory and thus make estimates of the mean distances they usually travel. Under the hypothesis that guignas maintain a sedentary behavior in a specific area of a given territory, this paper shows one way to simulate a distribution of points in a territory using random walkers to emulate the distribution of the data that would be obtained by placing radiocollars in a population of guignas, with which it is possible to make estimates of the mean distances that move away from a certain fixed position, and the interactions they can have with points in the territory that represent a high probability of lethality, such as farms, packs of dogs, roads, urban areas, etc. It is necessary to mention that by estimating the possible interactions that a guignas population may have with possible predators in a territory with the help of a satellite image, it is possible to evaluate the points of a territory that represent a potentially lethal risk for the guignas, and thus generate relocation strategies that help preserve them.

The gVOF package includes a complete and self-contained set of routines for volume of fluid initialization, interface reconstruction and fluid advection, which are used to implement several accurate and efficient geometric volume of fluid (VOF) methods on arbitrary grids, either structured or unstructured with convex or non-convex cells, based on multidimensional unsplit advection and piecewise linear interface calculation (PLIC) schemes. The package uses the non-convex analytical and geometrical tools developed by L\'opez et al. [J. Comput. Phys. 392 (2019) 666-693] and the isosurface extraction procedure proposed by L\'opez et al. [J. Comput. Phys. 444 (2021) 110579]. The operations required during the advection step of unsplit geometric VOF methods in general involve handling of high-complex non-convex flux polyhedra, even with self-intersecting faces, which are robustly and efficiently treated in this work without the need of costly techniques based on convex decomposition. Results for the accuracy, computational efficiency, and volume (local and global) conservation properties of different combinations of the implemented advection and reconstruction methods are presented for several numerical tests on structured and unstructured grids. An extensive comparison with results obtained by other authors using advanced geometric VOF methods shows the outstanding performance of the gVOF package in terms of efficiency and accuracy. To demonstrate the performance of the package in solving complex two-phase flow problems, the implemented methods are combined with an existing in-house code to simulate the impact of a water drop on a free surface. The package can be used in FORTRAN or C languages and will be publicly available for download. The OpenMP application programming interface is also used to improve computational efficiency., Comment: 76 pages, 30 figures

Bimetric gravity theories describes gravitational interactions in the presence of an extra spin-2 field. The Hassan-Rosen (HR) nonlinear massive minimal bigravity theory is a ghost-free bimetric theory formulated with respect a flat, dynamical reference metric. In this work the deformation quantization formalism is applied to a HR cosmological model in the minisuperspace. The quantization procedure is performed explicitly for quantum cosmology in the minisuperspace. The Friedmann-Lema\^itre-Robertson-Walker (FLRW) model with flat metrics is worked out and the computation of the Wigner functions for theHartle-Hawking, Vilenkin and Linde wavefunctions are done numerically and, in the Hartle-Hawking case, also analytically. From the stability analysis in the quantum minisuper phase space it is found an interpretation of the mass of graviton as an emergent cosmological constant and as a measure of the deviation of classical behavior of the Wigner functions. Also, from the Hartle-Hawking case, an interesting relation between the curvature and the mass of graviton in a cusp catastrophe surface is discussed, Comment: This is a post-peer-review, pre-copyedit version of an article published in General Relativity and Gravitation. The final authenticated version is available online at: https://doi.org/10.1007/s10714-021-02822-2 25 pages, 10 figures

In the past decade, the DBpedia community has put significant amount of effort on developing technical infrastructure and methods for efficient extraction of structured information from Wikipedia. These efforts have been primarily focused on harvesting, refinement and publishing semi-structured information found in Wikipedia articles, such as information from infoboxes, categorization information, images, wikilinks and citations. Nevertheless, still vast amount of valuable information is contained in the unstructured Wikipedia article texts. In this paper, we present DBpedia NIF - a large-scale and multilingual knowledge extraction corpus. The aim of the dataset is two-fold: to dramatically broaden and deepen the amount of structured information in DBpedia, and to provide large-scale and multilingual language resource for development of various NLP and IR task. The dataset provides the content of all articles for 128 Wikipedia languages. We describe the dataset creation process and the NLP Interchange Format (NIF) used to model the content, links and the structure the information of the Wikipedia articles. The dataset has been further enriched with about 25% more links and selected partitions published as Linked Data. Finally, we describe the maintenance and sustainability plans, and selected use cases of the dataset from the TextExt knowledge extraction challenge., Comment: 15 pages, 1 figure, 4 tables, 1 listing