Publications by authors named "Carlos Agostinho"

With the proliferation and growing complexity of healthcare systems emerges the challenge of implementing scalable and interoperable solutions to seamlessly integrate heterogenous data from sources such as wearables, electronic health records, and patient reports that can provide a comprehensive and personalized view of the patient's health. Lack of standardization hinders the coordination between systems and stakeholders, impacting continuity of care and patient outcomes. Common musculoskeletal conditions affect people of all ages and can have a significant impact on quality of life.

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Article Synopsis
  • Explainable AI (XAI) is crucial for making black box AI models in manufacturing more transparent and understandable, facilitating better collaboration between humans and machines.
  • The XMANAI platform specifically addresses industry challenges by creating interpretable AI models that maintain high performance while promoting trust and transparency.
  • The paper outlines the development of the XMANAI platform, its functionalities, and how it fosters better decision-making in manufacturing by improving operational efficiency and optimizing business value.*
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Mitochondrial molecular markers (DNA sequences of D-loop, cytochrome b and cytochrome c oxidase I) were employed to characterize populations of the piranha Serrasalmus maculatus from Upper Paraná, Upper Paraguay and Tocantins River basins. D-loop sequences of S. maculatus population from Paraná-Paraguay River basin exhibited tandem repeats of short motifs (12 base pairs) and variable numbers depending on specimens, accounting for length variation.

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The use of sensors and actuators as a form of controlling cyber-physical systems in resource networks has been integrated and referred to as the Internet of Things (IoT). However, the connectivity of many stand-alone IoT systems through the Internet introduces numerous cybersecurity challenges as sensitive information is prone to be exposed to malicious users. This paper focuses on the improvement of IoT cybersecurity from an ontological analysis, proposing appropriate security services adapted to the threats.

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In the context of diversity gradients, the metabolic theory of ecology (MTE) posits that the logarithm of species richness should decrease linearly with the inverse of temperature, resulting in a specific slope. However, the empirical validity of this model depends on whether the data do not violate certain assumptions. Here, we test the predictions of MTE evaluating all of its assumptions simultaneously.

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