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This study explores the applicability of the Laffer Curve in the context of the European Union (EU) by analyzing the relationship between taxation and fiscal revenue across personal income tax (PIT), corporate income tax (CIT), and value-added tax (VAT). Utilizing a comprehensive panel data set spanning 1995 to 2022 across all 27 EU member states, the research also integrates the Bird Index to assess fiscal effort and employs advanced econometric techniques, including the Hausman Test and log-quadratic regression models, to capture the non-linear dynamics of the Laffer Curve. The findings reveal that excessively high tax rates, particularly in some larger member states, may lead to revenue losses due to reduced economic activity and tax evasion, highlighting the existence of optimal tax rates that maximize revenue while sustaining economic growth. By estimating threshold tax rates and incorporating the Bird Index, the study provides a nuanced perspective on tax efficiency and fiscal sustainability, offering evidence-based policy recommendations for optimizing tax systems in the European Union to balance revenue generation with economic competitiveness.

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The relationship of a patient with a hospital from admission to discharge is often kept in a series of textual documents that describe the patient’s journey. These documents are important to analyze the different steps of the clinical process and to make aggregated studies of the paths of patients in the hospital. In this paper, we explore the potential of Large Language Models (LLMs) to generate realistic and comprehensive patient journeys in European Portuguese, addressing the scarcity of medical data in this specific context. We employed Google’s Gemini 1.5 Flash model and utilized a dataset of 285 European Portuguese published case reports from the SPMI website, published by the Portuguese Society of Internal Medicine, as references for generating synthetic medical reports. Our methodology involves a sequential approach to generating a synthetic patient journey. Initially, we generate an admission report, followed by a discharge report. Subsequently, we generate a comprehensive patient journey that integrates the admission, multiple daily progress reports, and the discharge into a cohesive narrative. This end-to-end process ensures a realistic and detailed representation of the patient’s clinical pathway as a patient’s journey. The generated reports were rigorously evaluated by medical and linguistic professionals, as well as automatic metrics to measure the inclusion of key medical entities, similarity to the case report, and correct Portuguese variant. Both qualitative and quantitative evaluations confirmed that the generated synthetic reports are predominantly written in European Portuguese without the loss of important medical information from the case reports. This work contributes to developing high-quality synthetic medical data for training LLMs and advancing AI-driven healthcare applications in under-resourced language settings. © 2025 Copyright for this paper by its authors.

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Introduction: The importance of investigating innovative technologies to improve patient rehabilitation is fundamental in the current context of healthcare. This highlights the need to map the technological resources used in the rehabilitation of adult burn patients. Methods: A scoping review was conducted according to the parameters set by the Joanna Briggs Institute (JBI) guidelines and structured using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and MetaAnalyses for Scoping Reviews). The scientific literature search covered various databases: Medline, CINAHL, SportDiscus, Psychology & Behavioral Sciences Collection, Scopus, SciELO, and the Cochrane Library. The inclusion criteria considered studies related to the use of technological resources in the rehabilitation of burn patients. The research was conducted until November 2024. Results: A total of 19 articles published between 2000 and 2024 were included. The technological resources analyzed included virtual reality (10 studies), exergames (6 studies), exoskeletons (4 studies), and augmented reality (1 study). These resources primarily aimed to promote motor functionality, increase muscle strength, and enhance joint range of motion. Conclusion: The technologies applied to the rehabilitation of burn patients represent a promising advancement, with the potential to transform the paradigm of rehabilitation, making it more interactive. Future research should focus on a detailed analysis of the long-term benefits and on integrating these technologies into standard rehabilitation protocols.

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Digital twins are increasingly used, as they allow the creation of detailed virtual representations of physical products and systems. They face, however, significant challenges such as heterogeneous data integration and high costs. This article presents an innovative methodology that uses Large Language Models to unify information and automate the generation of Digital Twin models. The proposal comprises several modules, covering the stages of data collection, semantic processing, modular construction and validation of the Digital Twin. In this way, the proposed model guarantees interoperability, efficiency and scalability for various domains. © 2025 IEEE.

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