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This article describes the *Confluence Framework*, a novel framework for proving and disproving confluence using a divide-and-conquer modular strategy, and its implementation in CONFident. Using this approach, we are able to automatically prove and disprove confluence of *Generalized Term Rewriting Systems*, where (i) only selected arguments of function symbols can be rewritten and (ii) a rather general class of conditional rules can be used. This includes, as particular cases, several variants of rewrite systems such as (context-sensitive) *term rewriting systems*, *string rewriting systems*, and (context-sensitive) *conditional term rewriting systems*. The divide-and-conquer modular strategy allows us to combine in a proof tree different techniques for proving confluence, including modular decompositions, checking joinability of (conditional) critical and variable pairs, transformations, etc., and auxiliary tasks required by them, e.g., joinability of terms, joinability of conditional pairs, etc., Comment: Extended and revised version of our LOPSTR 2022 paper (https://doi.org/10.1007/978-3-031-16767-6_2)

Single implementing, concatenating, adding or replacing of the representations has yielded significant improvements on many NLP tasks. Mainly in Relation Extraction where static, contextualized and others representations that are capable of explaining word meanings through the linguistic features that these incorporates. In this work addresses the question of how is improved the relation extraction using different types of representations generated by pretrained language representation models. We benchmarked our approach using popular word representation models, replacing and concatenating static, contextualized and others representations of hand-extracted features. The experiments show that representation is a crucial element to choose when DL approach is applied. Word embeddings from Flair and BERT can be well interpreted by a deep learning model for RE task, and replacing static word embeddings with contextualized word representations could lead to significant improvements. While, the hand-created representations requires is time-consuming and not is ensure a improve in combination with others representations., Comment: 11 pages, 3 tables, 4 Figures

In order to automatically infer the resource consumption of programs, analyzers track how data sizes change along program's execution. Typically, analyzers measure the sizes of data by applying norms which are mappings from data to natural numbers that represent the sizes of the corresponding data. When norms are defined by taking type information into account, they are named typed-norms. This article presents a transformational approach to resource analysis with typed-norms that are inferred by a data-flow analysis. The analysis is based on a transformation of the program into an intermediate abstract program in which each variable is abstracted with respect to all considered norms which are valid for its type. We also present the data-flow analysis to automatically infer the required, useful, typed-norms from programs. Our analysis is formalized on a simple rule-based representation to which programs written in different programming paradigms (e.g., functional, logic, imperative) can be automatically translated. Experimental results on standard benchmarks used by other type-based analyzers show that our approach is both efficient and accurate in practice. Under consideration in Theory and Practice of Logic Programming (TPLP)., Comment: Under consideration in Theory and Practice of Logic Programming (TPLP)

Decision procedures can be either theory-specific, e.g., Presburger arithmetic, or theory-generic, applying to an infinite number of user-definable theories. Variant satisfiability is a theory-generic procedure for quantifier-free satisfiability in the initial algebra of an order-sorted equational theory $({\Sigma},E \cup B)$ under two conditions: (i) $E \cup B$ has the finite variant property and $B$ has a finitary unification algorithm; and (ii) $({\Sigma},E \cup B)$ protects a constructor subtheory $({\Omega},E_{\Omega} \cup B_{\Omega})$ that is OS-compact. These conditions apply to many user-definable theories, but have a main limitation: they apply well to data structures, but often do not hold for user-definable predicates on such data structures. We present a theory-generic satisfiability decision procedure, and a prototype implementation, extending variant-based satisfiability to initial algebras with user-definable predicates under fairly general conditions., Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854)

ESASky is a science-driven discovery portal to explore the multi-wavelength sky and visualise and access multiple astronomical archive holdings. The tool is a web application that requires no prior knowledge of any of the missions involved and gives users world-wide simplified access to the highest-level science data products from multiple astronomical space-based astronomy missions plus a number of ESA source catalogues. The first public release of ESASky features interfaces for the visualisation of the sky in multiple wavelengths, the visualisation of query results summaries, and the visualisation of observations and catalogue sources for single and multiple targets. This paper describes these features within ESASky, developed to address use cases from the scientific community. The decisions regarding the visualisation of large amounts of data and the technologies used were made in order to maximise the responsiveness of the application and to keep the tool as useful and intuitive as possible., Comment: Published in PASP; ESASky: http://sky.esa.int

ESASky is a new science-driven discovery portal for all ESA astronomical missions that gives users worldwide a simplified access to high-level science-ready products from ESA and other data providers. The tool features a sky exploration interface and a single/multiple target interface, and it requires no prior knowledge of specific details of each mission. Users can explore the sky in multiple wavelengths, quickly see the data available for their targets, and retrieve the relevant products, with just a few clicks. The first version of the tool, released in May 2016, provides access to imaging data and a number of catalogues. Future releases will enable retrieval of spectroscopic data and will incorporate futures to allow time-domain exploration and the study of Solar System objects., Comment: To be published in: Highlights of Spanish Astrophysics IX, Proceedings of the XII Scientific Meeting of the Spanish Astronomical Society held on July 18-22, 2016, in Bilbao, Spain

We present a science-driven discovery portal for all the ESA Astronomy Missions called ESA Sky that allow users to explore the multi-wavelength sky and to seamlessly retrieve science-ready data in all ESA Astronomy mission archives from a web application without prior-knowledge of any of the missions. The first public beta of the service has been released, currently featuring an interface for exploration of the multi-wavelength sky and for single and/or multiple target searches of science-ready imaging data and catalogues. Future releases will enable retrieval of spectra and will have special time-domain exploration features. From a technical point of view, the system offers progressive multi-resolution all-sky projections of full mission datasets using a new generation of HEALPix projections called HiPS, developed at the CDS; detailed geometrical footprints to connect the all-sky mosaics to individual observations; and direct access to science-ready data at the underlying mission-specific science archives., Comment: 4 pages, 2 figures, ADASS XXV conference proceedings; ESA Sky Beta: http://archives.esac.esa.int/esasky-beta/ ; ESA Sky Beta documentation: http://www.cosmos.esa.int/web/esdc/esasky-help