MERLIN2: Sistema cognitivo para ROS 2

[ES] Desplegar robots sociales que realicen tareas en entornos reales conlleva desarrollar software complejo dada la cantidad de información involucrada en la toma de decisiones de un robot. Uno de los mecanismos habituales para gestionar y modelar el conocimiento para su inclusión en el sistema de toma de decisiones de un robot es el uso de arquitecturas cognitivas. Este Trabajo de Fin de Máster (TFM) presenta el desarrollo de una arquitectura cognitiva híbrida para robots de servicio llamada MERLIN2. MERLIN2 es capaz de gestionar las mecanismos habituales de razonamiento y planificación que un robot asistencial lleva a cabo en entornos dinámicos. Por un lado, se presenta el diseño multicapa de la arquitectura que hace uso de conceptos clásicos como son los sistemas reactivos, de planificación y de gestión del conocimiento. Por otro lado, se implementa dicha arquitectura centrándose en el uso de diversos patrones de diseño software y utilizando el framework ROS 2. Por último, se presenta su aplicación real mediante demos sobre los robots RB1 y TiaGo dónde se validará su funcionamiento en entornos reales y simulados

Towards explainability in robotics: A performance analysis of a cloud accountability system

[EN] Understanding why a robot's behaviour was triggered is a growing concern to get human-acceptable social robots. Every action, expected and unexpected, should be able to be explained and audited. The formal model proposed here deals with different information levels, from low-level data, such as sensors' data logging; to high-level data that provide an explanation of the robot's behaviour. This study examines the impact on the robot system of a custom log engine based on a custom ROS logging node and investigates pros and cons when used together with a NoSQL database locally and in a cloud environment. Results allow to characterize these alternatives and explore the best strategy for offering a fully log-based accountability engine that maximizes the mapping between robot behaviour and robot logs.SIInstituto Nacional de CiberseguridadMinisterio de Ciencia e Innovació

Integration of Large Language Models within Cognitive Architectures for Autonomous Robots

The usage of Large Language Models (LLMs) has increased recently, not only due to the significant improvements in their accuracy but also because of the use of the quantization that allows running these models without intense hardware requirements. As a result, the LLMs have proliferated. It implies the creation of a great variety of LLMs with different capabilities. This way, this paper proposes the integration of LLMs in cognitive architectures for autonomous robots. Specifically, we present the design, development and deployment of the llama\_ros tool that allows the easy use and integration of LLMs in ROS 2-based environments, afterward integrated with the state-of-the-art cognitive architecture MERLIN2 for updating a PDDL-based planner system. This proposal is evaluated quantitatively and qualitatively, measuring the impact of incorporating the LLMs in the cognitive architecture.Comment: 8 pages, 6 figures, 2 tables, Submitted to ICRA 202

Using Large Language Models for Interpreting Autonomous Robots Behaviors

The deployment of autonomous robots in various domains has raised significant concerns about their trustworthiness and accountability. This study explores the potential of Large Language Models (LLMs) in analyzing ROS 2 logs generated by autonomous robots and proposes a framework for log analysis that categorizes log files into different aspects. The study evaluates the performance of three different language models in answering questions related to StartUp, Warning, and PDDL logs. The results suggest that GPT 4, a transformer-based model, outperforms other models, however, their verbosity is not enough to answer why or how questions for all kinds of actors involved in the interaction

YASMIN: Yet Another State MachINe library for ROS 2

State machines are a common mechanism for defining behaviors in robots, defining them based on identifiable stages. There are several libraries available for easing the implementation of state machines in ROS 1, as SMACH or SMACC, but there are fewer alternatives for ROS 2. YASMIN is yet another library specifically designed for ROS 2 for easing the design of robotic behaviors using state machines. It is available in C++ and Python, provides some default states to speed up the development, and a web viewer for monitoring the execution of the system and helping in the debugging.Comment: 4 pages, 2 figures, ROSCon FR 202

Impact of Advanced Age on the Incidence of Major Adverse Cardiovascular Events in Patients with Type 2 Diabetes Mellitus and Stable Coronary Artery Disease in a Real-World Setting in Spain

Patients with type 2 diabetes mellitus (T2DM) and coronary artery disease (CAD) without myocardial infarction (MI) or stroke are at high risk for major cardiovascular events (MACEs). We aimed to provide real-world data on age-related clinical characteristics, treatment management, and incidence of major cardiovascular outcomes in T2DM-CAD patients in Spain from 2014 to 2018. We used EHRead (R) technology, which is based on natural language processing and machine learning, to extract unstructured clinical information from electronic health records (EHRs) from 12 hospitals. Of the 4072 included patients, 30.9% were younger than 65 years (66.3% male), 34.2% were aged 65-75 years (66.4% male), and 34.8% were older than 75 years (54.3% male). These older patients were more likely to have hypertension (OR 2.85), angina (OR 1.64), heart valve disease (OR 2.13), or peripheral vascular disease (OR 2.38) than those aged <65 years (p < 0.001 for all comparisons). In general, they were also more likely to receive pharmacological and interventional treatments. Moreover, these patients had a significantly higher risk of MACEs (HR 1.29; p = 0.003) and ischemic stroke (HR 2.39; p < 0.001). In summary, patients with T2DM-CAD in routine clinical practice tend to be older, have more comorbidities, are more heavily treated, and have a higher risk of developing MACE than is commonly assumed from clinical trial data

Ingeniería Geológica en Terrenos Volcánicos. Métodos, Técnicas y Experiencias en las Islas Canarias

La presente obra es un compendio de conceptos, metodologías y técnicas útiles para acometer proyectos y obras en terrenos volcánicos desde el punto de vista de la ingeniería geológica y la geotecnia. El libro se presenta en tres partes diferenciadas. La primera es conceptual y metodológica, con capítulos que tratan sobre la clasificación de las rocas volcánicas con fines geotécnicos, la caracterización geomecánica, los problemas geotécnicos y constructivos asociados a los distintos materiales, y una guía metodológica para la redacción de informes geotécnicos para la edificación. La segunda parte aborda las aplicaciones a obras de ingeniería, incluyendo deslizamientos, obras subterráneas,infraestructuras marítimas y obras públicas. La tercera parte recoge capítulos dedicados a describir distintos casos prácticos de obras y proyectos en los que la problemática geotécnica en terrenos volcánicos ha tenido un papel relevante. Los capítulos han sido elaborados por técnicos y científicos de reconocido prestigio en el campo de la ingeniería geológica en terrenos volcánicos, que han plasmado en ellos sus conocimientos y experiencias en la materia.Los editores y autores de parte de los capítulos del libro, los Doctores Luis E. Hernández Gutiérrez (Geólogo) y Juan Carlos Santamarta Cerezal (Ingeniero de Montes, Civil y Minas), son los responsables del grupo de investigación INGENIA (Ingeniería Geológica, Innovación y Aguas). Su actividad investigadora comprende más de 200 publicaciones en el área de la ingeniería geológica, la geotecnia, medio ambiente y el aprovechamiento del agua en islas y terrenos volcánicos. En relación a la docencia han impartido y dirigido más de 90 seminarios y cursos de especialización a nivel nacional e internacional, incluyendo la organización de 4 congresos internacionales. Fueron premiados por la Universidad de La Laguna en los años 2012, 2013 y 2014 por su calidad docente e innovación universitaria, y son pioneros en los laboratorios virtuales para la enseñanza de la ingeniería. Participan activamente como profesores colaboradores e investigadores en varias universidades e instituciones españolas e internacionales. Todas sus publicaciones están disponibles en internet, con libre acceso. Ingeniería geológica en terrenos volcánicos, es una obra de gran interés para, consultores, técnicos de administraciones públicas, proyectistas y demás profesionales implicados en obras y proyectos de infraestructuras en terrenos volcánicos; también es útil para académicos y estudiantes de ingeniería o ciencias geológicas que quieran investigar o iniciarse en las singularidades que presentan los materiales volcánicos en la edificación o en la ingeniería civil y minera

COVID-19 vaccine failure

COVID-19 affects the population unequally with a higher impact on aged and immunosuppressed people. Hence, we assessed the effect of SARS-CoV-2 vaccination in immune compromised patients (older adults and oncohematologic patients), compared with healthy counterparts. While the acquired humoral and cellular memory did not predict subsequent infection 18 months after full immunization, spectral and computational cytometry revealed several subsets within the CD8+ T-cells, B-cells, NK cells, monocytes and CD45RA+ CCR7- Tγδ cells differentially expressed in further infected and non-infected individuals not just following immunization, but also prior to that. Of note, up to 7 subsets were found within the CD45RA+ CCR7- Tγδ population with some of them being expanded and other decreased in subsequently infected individuals. Moreover, some of these subsets also predicted COVID-induced hospitalization in oncohematologic patients. Therefore, we hereby have identified several cellular subsets that, even before vaccination, strongly related to COVID-19 vulnerability as opposed to the acquisition of cellular and/or humoral memory following vaccination with SARS-CoV2 mRNA vaccines.This study has been funded through Programa Estratégico Instituto de Biología y Genética Molecular (IBGM Junta de Castilla y León. Ref. CCVC8485), Junta de Castilla y León (Proyectos COVID 07.04.467B04.74011.0) and the European Commission – NextGenerationEU (Regulation EU 2020/2094), through CSIC's Global Health Platform (PTI Salud Global; SGL21-03-026 and SGL2021-03-038)N

El descubrimiento del medio físico y social a través de la educación artística

Con este proyecto se trata de alcanzar el dominio de los contenidos del área de Conocimiento del Medio a través de la expresión plástica y la dramatización. Los objetivos son:Descubrir el entorno socio-natural a través de las obras plásticas; Utilizar distintas técnicas y materiales en la producción de obras plásticas; Asimilar, comprender y respetar las distintas formas de captar la realidad en producciones propias y ajenas; Descubrir a través de las obras de algunos artístas los sucesos mas relevantes de su momento histórico; Utilizar los conocimientos plásticos básicos en la elaboración de trabajos propios; Conocer y respetar las principales manifestaciones artísticas del entorno próximo; Representar personajes, objetos y acciones que aparecen en un determinado contexto espacial y temporal; Identificar algunos de los elementos básicos de juego dramático (personajes, conflictos, trama, espacio, tiempo, etc.); Mostrar tanto la realidad de la historia o de los mensajes emitidos, como creatividad en las manifestaciones expresivas; Realizar tanto producciones artísticas como dramáticas de forma cooperativa que supongan papeles diferenciados y complementarios en la elaboración de un trabajo colectivo; Participar con agrado tanto en las manifestaciones artísticas como en las expresivas..Gobierno de Cantabria. Consejería de Educación y JuventudCantabriaES

Assessment of medical management in Coronary Type 2 Diabetic patients with previous percutaneous coronary intervention in Spain: a retrospective analysis of electronic health records using Natural Language Processing

Introduction and objectives: Patients with type 2 diabetes (T2D) and stable coronary artery disease (CAD) previously revascularized with percutaneous coronary intervention (PCI) are at high risk of recurrent ischemic events. We aimed to provide real-world insights into the clinical characteristics and management of this clinical population, excluding patients with a history of myocardial infarction (MI) or stroke, using Natural Language Processing (NLP) technology. Methods: This is a multicenter, retrospective study based on the secondary use of 2014-2018 real world data captured in the Electronic Health Records (EHRs) of 1,579 patients (0.72% of the T2D population analyzed; n = 217,632 patients) from 12 representative hospitals in Spain. To access the unstructured clinical information in EHRs, we used the EHRead® technology, based on NLP and machine learning. Major adverse cardiovascular events (MACE) were considered: MI, ischemic stroke, urgent coronary revascularization, and hospitalization due to unstable angina. The association between MACE rates and the variables included in this study was evaluated following univariate and multivariate approaches. Results: Most patients were male (72.13%), with a mean age of 70.5±10 years. Regarding T2D, most patients were non-insulin-dependent T2D (61.75%) with high prevalence of comorbidi ties. The median (Q1-Q3) duration of follow-up was 1.2 (0.3-4.5) years. Overall, 35.66% of patients suffered from at least one MACE during follow up. Using a Cox Proportional Haz ards regression model analysis, several independent factors were associated with MACE during follow up: CAD duration (p < 0.001), COPD/Asthma (p = 0.021), heart valve disease (p = 0.031), multivessel disease (p = 0.005), insulin treatment (p < 0.001), statins treatment (p < 0.001), and clopidogrel treatment (p = 0.039). Conclusions: Our results showed high rates of MACE in a large real-world series of PCI-revascularized patients with T2D and CAD with no history of MI or stroke. These data represent a potential opportunity to improve the clinical management of these patients