Alberto Sols Biomedical Research Institute
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Hydrothermal carbonization of swine manure in a continuous flow reactor pilot plant with process water recycling
No full textThis paper deals with hydrothermal carbonization (HTC) of swine manure in a pilot plant setup operating in continuous mode. Two temperatures (210 °C and 250 °C) were tested and recycling of the liquid fraction was studied to improve the quality of the resulting hydrochar. The hydrochars obtained at 210 °C fulfill the criteria to be used as solid biofuels (ISO 17225–8:2023). Increasing the reaction temperature led to a dramatic reduction of hydrochar yield (from 50 to 20 %) in conventional HTC (with tap water), accompanied by a moderate improvement of higher heating value (HHV, 18.2–20.4 MJ/kg), which decreased the energy yield (from 52.2 % to 23.8 %). Process water recycling significantly improved the hydrochar yield, reaching more than 80 % and 55 % at 210 °C and 250 °C, respectively, because of the formation of secondary hydrochar. C content and HHV also increased, giving rise to substantially higher energy recovery, which surpassed 93 % after four recycling tests at 210 °C. Fouling and alkali indexes of hydrochars showed much lower values than those of the feedstock mainly attributed to the solubilization of Na and K. At 210 °C, process water recycling favored a further reduction of those indexes. N and P were largely transferred to the liquid fraction, particularly the latter. Zn and Cu were, by far, the most abundant heavy metals in hydrochars, with a Zn content being slightly above the value established in Decision (EU) 2022/1244 for their application as a soil amendmentAuthors greatly appreciate funding from Spanish MCIN/AEI/ 10.13039/501100011033 and European Union “NextGenerationEU/PRTR” (TED2021-130287B-I00, PID 2022-138632OB-I00) and and Community of Madrid (TEC-2024/BIO-177). R.P. Ipiales acknowledges the financial support from the Community of Madrid (IND2019/AMB-17092) and Arquimea Agrotech company. Authors thank M. Colas for her valuable hel
Understanding information propagation in online social networks: A systematic mapping study
No full textOnline Social Networks (OSNs) have become a significant research focus across various fields. The increase in their use has prompted numerous studies, particularly on the complex Information Propagation (IP) process, which researchers have approached from different perspectives and lines of investigation. The work presented in this article aims to analyse the state of the art on IP in OSNs, mapping the models, methods, algorithms, tools, and techniques developed in this domain. In particular, we have conducted a Systematic Mapping Study (SMS). To our knowledge, this is the first study to address this issue. The SMS collected 424 studies and analysed 175 primary studies, and the results reveal that most studies are model proposals, the most researched topic is Influence Maximisation (IM), and Twitter (now X) is the most commonly used resource in experiments. Also, the SMS reveals that there is no formal classification of the terms to refer to propagated information. In addition, we also found several proposals to mitigate or control IP. However, there is no common methodological framework to reduce IP. To conclude the study, we propose groups of features/attributes of users during IP and a propagated information classification. This research provides a general and organised overview for the scientific community regarding studies on IP in OSN
Second FRCSyn-onGoing: Winning solutions and post-challenge analysis to improve face recognition with synthetic data
No full textArtículo escrito por un elevado número de autores, solo se referencian el que aparece en primer lugar, el nombre del grupo de colaboración, si le hubiere, y los autores pertenecientes a la UAMSynthetic data is gaining increasing popularity for face recognition technologies, mainly due to the privacy concerns and challenges associated with obtaining real data, including diverse scenarios, quality, and demographic groups, among others. It also offers some advantages over real data, such as the large amount of data that can be generated or the ability to customize it to adapt to specific problem-solving needs. To effectively use such data, face recognition models should also be specifically designed to exploit synthetic data to its fullest potential. In order to promote the proposal of novel Generative AI methods and synthetic data, and investigate the application of synthetic data to better train face recognition systems, we introduce the 2nd FRCSyn-onGoing challenge, based on the 2nd Face Recognition Challenge in the Era of Synthetic Data (FRCSyn), originally launched at CVPR 2024. This is an ongoing challenge that provides researchers with an accessible platform to benchmark (i) the proposal of novel Generative AI methods and synthetic data, and (ii) novel face recognition systems that are specifically proposed to take advantage of synthetic data. We focus on exploring the use of synthetic data both individually and in combination with real data to solve current challenges in face recognition such as demographic bias, domain adaptation, and performance constraints in demanding situations, such as age disparities between training and testing, changes in the pose, or occlusions. Very interesting findings are obtained in this second edition, including a direct comparison with the first one, in which synthetic databases were restricted to DCFace and GANDiffFaceThis study is supported by INTER-ACTION (PID2021-126521OBI00 MICINN/FEDER), Cátedra ENIA UAM-VERIDAS en IA Responsable (NextGenerationEU PRTR TSI-100927-2023-2), R&D Agreement DGGC/UAM/FUAM for Biometrics and Cybersecurity, and PowerAI+ (SI4/PJI/2024-00062, funded by Comunidad de Madrid, Spain through the grant agreement for the promotion of research and technology transfer at UAM). It is also supported by the German Federal Ministry of Education and Research and the Hessian Ministry of Higher Education, Research, Science, and the Arts within their joint support of the National Research Center for Applied Cybersecurity ATHENE. K-IBS-DS was supported by the Institute for Basic Science, Republic of Korea, (IBS-R029-C2). UNICA-IGD-LSI was supported by the ARIS program P2-0250
Mecanismos de la actividad física en el sistema inmune de los pacientes con enfermedad pulmonar obstructiva crónica (EPOC)
No full textTesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Medicina. Fecha de Lectura: 12-03-202
Automorphisms of the Rado meet-tree
No full textWe prove that the group of automorphisms of the generic meet-tree expansion of an infinite non-unary free Fraïssé limit over a finite relational language is simple. As a prototypical case, the group of automorphisms of the Rado meet-tree (i.e. the Fraïssé limit of finite graphs which are also meet-trees) is simpleKaplan would like to thank The Israel Science Foundation (ISF) for their support of this research (grants no. 1254/18 and 804/22). Rodríguez Fanlo was supported by the Israel Academy of Sciences and Humanities & Council for Higher Education Excellence Fellowship Program for International Postdoctoral Researcher
Robust and adaptable monocular pose estimation of non-cooperative spacecraft
No full textTesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Escuela Politécnica Superior, Departamento de Tecnología Electrónica y de las Comunicaciones. Fecha de Lectura: 03-03-2025Estimar con precisión la pose de una nave espacial no cooperativa es una capacidad clave tanto para la
eliminación activa de basura espacial como la reparación autónoma en órbita. Sin embargo, hay una
gran ausencia de datos adquiridos en condiciones reales, causado principalmente por los altos costes
asociados. Tradicionalmente, este problema se ha mitigado empleando simuladores de datos sintéticos.
Si bien estos simuladores han resuelto el problema de la disponibilidad de datos, han introducido el
problema de la diferencia entre dominio sintético y real. Esta diferencia se traduce en una bajada de
rendimiento de los modelos entrenados con datos sintéticos y probados con datos reales.
En esta tesis se exploran métodos para superar los problemas introducidos por la diferencia de
dominio siguiendo tres estrategias principales: a) Simulando datos que se asemejen más a los datos
de prueba reales; b) Introduciendo conocimientos a priori del dominio en el proceso de aprendizaje; c)
Adaptando los modelos al dominio de prueba optimizando objetivos auto supervisados. En esta línea,
las contribuciones presentadas son: a) La primera herramienta de código abierto para generar imágenes
de naves espaciales, junto a un estudio sobre el papel de simular datos visualmente más cercanos al
escenario objetivo; b) Un conjunto de funciones de coste robustas al cambio de dominio en la tarea
de estimación de pose de naves espaciales. En esta línea, exploramos un trabajo secundario utilizando
función de coste basada en frecuencia para la estimación de odometría visual y profundidad monocular
en la navegación de rovers; c) Dos métodos para ajustar modelos al dominio de test de manera auto
supervisada para la estimación de pose de naves espaciales. Siendo uno basado en imágenes estáticas
y otro que explota información temporalAlthough accurately estimating the pose of a non-cooperative spacecraft is a key capability to enable
active-debris removal and in-orbit servicing, there is a major absence of data acquired in operational or
hardware-in-the-loop scenarios. This, in part caused by the high associated costs, has been mitigated
by employing synthetic data simulators. While these simulators have solved the problem of data
availability, they have introduced the problem of the domain-gap that causes a performance drop for
models trained over synthetic data and tested over test data.
In this thesis we explore methods to overcome this domain-gap by following three main strategies:
a) Simulating data that resembles more to the real test data; b) Introducing domain priors in the
learning process; c) Adapting the models over the test-domain by optimising self-supervised objectives.
In this line, the presented contributions are: a) The first open-source tool to generate spacecraft
imagery, with a study on the role of simulating data that is visually closer to the target scenario; b)
A set of robust loss terms for spacecraft pose estimation. Following this line of thought, we explore
a secondary work using a frequency-based loss for the task of visual odometry and monocular depth
estimation in rover navigation; c) Two methods to learn from the target domain in a self-supervised
manner for the task of monocular spacecraft pose estimation, one based on still images and other that
exploits temporal informationIt was supported by the Comunidad Autónoma de Madrid (Spain) under the Grant IND2020/TIC-17515 and the Ministerio de Ciencia e Innovación of the Spanish Government under the project HVD (PID2021-125051OB-I00
Infancia, derechos y ciudadanía
No full textProyecto PID2021-127680OB-I00, “Educar en valores, construir ciudadanías”, financiado por MCIN/AEI /10.13039/501100011033 y por FEDER, UE. IP1: Carlos Vidal Prado; IP2: F. Javier Díaz Revori
Formative assessment processes in elementary education. A Systematic review
No full textLa evaluación formativa es un elemento de gran interés para la investigación educativa. Por ello, es fundamental analizar de forma sistemática elementos claves de la investigación desarrollada en los últimos años. Los trabajos de revisión existentes se centran en los factores que condicionan el empleo de procesos de evaluación formativa sin atender a aspectos como los beneficios percibidos por el profesorado derivados de su uso o las estrategias de evaluación formativa empleadas. Por ello, esta revisión busca responder las siguientes preguntas: (i) ¿Qué beneficios percibe el profesorado de Educación Básica sobre el empleo de la evaluación formativa en la práctica del aula?; (ii) ¿Cuáles son los factores que influyen en las intenciones del profesorado para utilizar procesos de evaluación formativa en el aula?; (iii) ¿Cuáles son las estrategias de evaluación formativa más empleadas en el aula por parte del profesorado y cómo se emplean? Se realizó una revisión sistemática de los últimos cinco años en WOS, SCOPUS, ERIC y Psychinfo siguiendo la declaración PRISMA. Tras la aplicación de los criterios de inclusión, 36 estudios fueron analizados. Los resultados muestran que el profesorado percibe beneficios de los procesos de evaluación asociados a 10 variables relacionadas con la mejora del proceso, la regulación del aprendizaje o la mejora de la enseñanza. Por otra parte, los factores que influyen en su intención de aplicación son de carácter personal, de interacción con los demás y contextuales. Finalmente, las estrategias más empleadas son proporcionar feedback, implicar al alumnado en la evaluación, compartir los objetivos y criterios de evaluación y formular preguntar. Por tanto, este estudio contribuye a sistematizar las investigaciones realizadas en relación con los procesos de evaluación formativa, abriendo una puerta a la generación de nuevas líneas de investigación y a la aplicación de acciones concretas en la práctica educativ
Strong field physics in periodic crystals
Get PDFTesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Física Teórica de la Materia Condensada. Fecha de Lectura: 10-04-202
A general diagnostic modelling framework for forced-choice assessments
Get PDFDiagnostic classification modelling (DCM) is a family of restricted latent class models often used in educational settings to assess students' strengths and weaknesses. Recently, there has been growing interest in applying DCM to noncognitive traits in fields such as clinical and organizational psychology, as well as personality profiling. To address common response biases in these assessments, such as social desirability, Huang (2023, Educational and Psychological Measurement, 83, 146) adopted the forced-choice (FC) item format within the DCM framework, developing the FC-DCM. This model assumes that examinees with no clear preference for any statements in an FC block will choose completely at random. Additionally, the unique parametrization of the FC-DCM poses challenges for integration with established DCM frameworks in the literature. In the present study, we enhance the capabilities of DCM by introducing a general diagnostic framework for FC assessments. We present an adaptation of the G-DINA model to accommodate FC responses. Simulation results show that the G-DINA model provides accurate classifications, item parameter estimates and attribute correlations, outperforming the FC-DCM in realistic scenarios where item discrimination varies. A real FC assessment example further illustrates the better model fit of the G-DINA. Practical recommendations for using the FC format in diagnostic assessments of noncognitive traits are providedUniversidad Pontificia Comillas (2024 Call for Funding of Internal Research Projects: “Advancements in cognitive diagnosis models for formative assessments”); MICIU/AEI/10.13039/501100011033 and ERDF/EU under the project “Computerized adaptive tests based on new assessment formats” (reference: PID2022-137258NB-I00); UAM-IIC Chair Psychometric Models and Application