Alberto Sols Biomedical Research Institute
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Integrating voltammetry and substrate-enhanced luminescence for noninvasive glucose sensing
No full textThis study presents a novel noninvasive and enzyme-free dual sensor based on porous silicon (PSi) for the detection of D-glucose through tear fluid analysis. The sensor incorporates NaGdF4:20% Yb3+, 2% Er3+ nanoparticles (YbEr-NPs) immobilized on a PSi substrate functionalized with a phenylboronic ester molecule. The YbEr-NPs enable luminescence-based sensing, exploiting the sensitivity of Er3+ ions to the OH vibrational groups present in D-glucose. Electrodes fabricated on a PSi substrate allow for voltammetric analysis, providing a second detection method. The voltammetric sensor achieved a limit of detection (LoD) of 20 mg/dL in the range of 20–200 mg/dL, which is suitable for detecting D-glucose concentrations in the tear fluid of diabetic patients. The luminescence-based sensor, utilizing the red-to-green emission ratio of YbEr-NPs, reached a LoD of 140 mg/dL in the range of 10–70 mg/dL, covering the hyperglycemic range. The interaction between the YbEr-NPs and the PSi substrate led to the appearance of new emission bands and increased intensity, attributed to surface defects acting as an additional excitation source. The 556 nm emission band showed a strong dependence on the D-glucose concentration, improving the LoD to 110 mg/dL. This provides a novel strategy for D-glucose detection based on the effect of the molecule on the interaction between the Rare-earth-doped nanoparticles and the PSi substrate. This triple-sensing approach offers a promising solution for noninvasive glucose monitoring, enabling detection in both the hypoglycemic and hyperglycemic rangesThis work was financed by the Comunidad de Madrid and Universidad Autónoma de Madrid (Project SI3/PJI/2021-00211). Additional funding was received from grant PID2020-118878RB-I00 (RETINanoTHERMIA) by MCIN/AEI/10.13039/501100011033; grant CNS2023-145366 funded by MICIU/AEI/10.13039/501100011033 and by the European Union Next Generation EU/PRTR; grant PID2023-151371OB-C22 by MCIN/AEI/10.13039/501100011033 and by ERDF, EU; grant CPP2021-008902 funded by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR and by the Comunidad Autónoma de Madrid (S2022/BMD-7403 RENIM-CM) and co-financed by the European structural and investment fund. Additional financial support from grant PID2020-116712RBC21 funded by MCIN/AEI/10.13039/501100011033 is acknowledged by A. A., and MICIN (Grant PID2020-113059 GB-C22 and PID2023- 146801NB-C32) is acknowledged by M.R
Uses and Applications of Artificial Intelligence in Financial Markets
No full textTrabajo Fin de Grado. Curso Académico 2024-2025. Grado en Administración y Dirección de EmpresasLa selección de acciones es clave en la gestión de carteras y, tradicionalmente, se ha abordado mediante modelos como el CAPM o Fama y French. Aunque siguen siendo una referencia habitual, sus limitaciones ante la complejidad del mercado actual han impulsado el uso de enfoques más flexibles. El aprendizaje automático (Machine Learning, ML) permite superar estas restricciones al captar relaciones no lineales y adaptarse a condiciones cambiantes. Este Trabajo de Fin de Grado aplica algoritmos de clasificación supervisada —Decision Tree, Random Forest y XGBoost— para seleccionar acciones del EuroStoxx 50, siguiendo la metodología propuesta por Caparrini et al. (2024), originalmente aplicada al índice S&P 500. Se emplea un marco de validación robusto, con técnicas de backtesting y validación cruzada, y se comparan los resultados con modelos factoriales tradicionales y el índice EuroStoxx 50. Los resultados muestran el potencial del ML para mejorar las decisiones de inversión y adaptarse a entornos de mercado dinámicosStock selection is key in portfolio management and has traditionally been approached through models like CAPM or Fama and French. While these remain common references, their limitations in dealing with today’s market complexity have led to the adoption of more flexible approaches. Machine Learning (ML) techniques help overcome these constraints by capturing nonlinear relationships and adapting to changing conditions. This Bachelor's Thesis applies supervised classification algorithms—Decision Tree, Random Forest, and XGBoost—to select stocks in the EuroStoxx 50, following the methodology proposed by Caparrini et al. (2024), originally applied to the S&P 500 index. A robust validation framework is employed, including backtesting and cross-validation techniques, and the results are compared with traditional factor-based models and the EuroStoxx 50 index. The results highlight the potential of ML to improve investment decision-making and adapt to dynamic market environment
The Financial Document Causality Detection Shared Task (FinCausal 2025)
No full textWe present the Financial Document Causality Detection Task (FinCausal 2025), a multilingual challenge to identify causal relationships within financial texts. This task comprises English and Spanish subtasks, with datasets compiled from British and Spanish annual reports. Participants were tasked with identifying and generating answers to questions about causes or effects within specific text segments. The dataset combines extractive and generative question-answering (QA) methods, with abstractly formulated questions and directly extracted answers from the text. Systems performance is evaluated using exact matching and semantic similarity metrics. The challenge attracted submissions from 10 teams for the English subtask and 10 teams for the Spanish subtask. FinCausal 2025 is part of the 6th Financial Narrative Processing Workshop (FNP 2025), hosted at COLING 2025 in Abu DhabiThis publication is part of the project GRESEL (PID2023-
151280OB-C21) funded by the Spanish Ministry
of Science and Innovation and Universities.
We also gratefully acknowledge the financial
support received by the second author through a
FPU grant (FPU20/04007) awarded by the Spanish
Ministry of Science, Innovation and Universitie
Ascriptivism, life forms, and recognition. On the social constitution of normativity
No full textThe present work deals with the problem that negligence poses for the relationship between agency and responsibility, that is, it is not possible to establish a sharp connection between the agent's guilty mind and the wrongful situation. A critical examination of the various strategies that attempt to deal with this problem is presented, and an ascriptivist conception of action and responsibility, as well as the distinction between conduct rules and imputation rules, is developed to address the problem. As a result, a complex theory of agency is defended, the distinction between tracing and non-tracing cases is supported, and it is proposed to understand the latter under the social and normative aspects of agenc
Connecting the dots: Regional assessment of landscape connectivity in amphibian communities in Central Spain
No full textContext Habitat fragmentation and loss are major contributing factors in the global biodiversity crisis. This is especially concerning for low-dispersing organisms in anthropized areas, where artifcial elements separating suitable habitat patches impede landscape connectivity, compromising long-term population viability. Robust comparative assessments of regional population connectivity can drive evidence-based conservation measures for biological communities, but require comprehensive feld surveys to provide reliable inferences. Objectives We focused on amphibians, low-dispersing taxa with declining populations worldwide, primarily due to habitat loss and fragmentation. We assessed patterns of landscape connectivity in 16 native amphibian species grouped in four communities in the most populated region in Spain (Community of Madrid). Methods We surveyed 2303 water bodies across the entire region to characterize amphibian communities and developed whole-range distribution models relating species presence data and remote sensing covariates. Then, we projected predicted global distributions in the study region with high resolution and used landscape resistance models and clustering analyses to reconstruct connectivity networks of all species and identify potential ecological corridors and barriers contributing to population fragmentation. Results We recorded 18–866 breeding sites per species, and generated models with high statistical performance. Connectivity varied spatially and across communities and species, highlighting barriers to dispersal comprising natural (mountains, rivers) and artifcial features (water reservoirs, dammed rivers, urban areas), and also ecological corridors, including peri-urban green areas, river valleys, moorlands and mountain passes. Conclusions Our work presents a novel methodological framework leveraging data from local (feld surveys) and global (online databases) scales across multiple species, enabling robust assessment of community-level connectivity patterns to inform conservation planningThis study forms part of projects PID2020-116289 GB-I00 and PID2023-150595NBI00 (PI: IMS), funded by FEDER/Ministerio de Ciencia, Innovación y Universidades–Agencia Estatal de Investigación (Spain), with additional funds from Asociación Herpetológica Española, Community of Madrid and Universidad Autónoma de Madrid (grant PEJD-2019-PRE/AMB-14950 and assistant professor position 22/23–499 to CCD). PT was supported by FCT—Fundação para a Ciência e Tecnologia, I.P. by contract reference DL57/2016/CP1440/CT0008 and DOI identiferhttps://sciproj.ptcris.pt/5012EE
Tunable doping and optoelectronic modulation in graphene-covered 4H-SiC surfaces
No full textSemiconducting graphene is pivotal for the advancement of nanoelectronics due to its unique electronic properties. In this context, silicon carbide (SiC) surfaces have been proposed as ideal supports for inducing semiconducting characteristics in graphene. Here, we employ many-body perturbation theory to investigate the electronic structure and optical properties of graphene-covered 4H-SiC surfaces. Our analysis reveals that pristine 4H-SiC surfaces with dangling bonds exhibit a reduced transport gap and enhanced optically active states within the visible spectrum compared to bulk 4H-SiC. Strong interfacial interactions resulting from the adsorption of a single graphene layer (GL) significantly alter graphene’s dispersion, yielding a semiconducting interface with modified optoelectronic properties. While the addition of a second GL restores Dirac dispersion, the two polar faces of the underlying 4H-SiC induce either metallic n-type doping or behavior similar to that of freestanding graphene. Furthermore, we investigate the adsorption of a molecular electron acceptor on SiC covered with one and two GLs. Our findings reveal notable renormalization of the molecular energy levels upon adsorption, resulting in the emergence of distinct new optically excited states. Additionally, a shift in the Fermi level, attributed to partial charge transfer, indicates effective p-type doping. The tunable doping characteristics and optical profiles across various energy ranges highlight the potential of graphene-covered 4H-SiC surfaces as versatile materials for a wide range of technological applicationsAll calculations were performed at the Mare Nostrum Supercomputer of the Red Espanola de Supercomputación (BSC-RES) and the Centro de Computación Científica de la Universidad Autónoma de Madrid (CCC-UAM). This work has been supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 951224, TOMATTO), the Ministerio de Ciencia e Innovación MICINN (Spain) through the projects PID2022-138288NB-C31 and PID2022-138288NB-C33, the “Severo Ochoa” Programme for Centres of Excellence in R&D (CEX2020-001039-S), and the “María de Maeztu” Programme for Units of Excellence in R&D (CEX2018-000805-M
Atomic-scale visualization of multiferroicity in monolayer NiI2
No full textProgress in layered van der Waals materials has resulted in the discovery of ferromagnetic and ferroelectric materials down to the monolayer limit. Recently, evidence of the first purely 2D multiferroic material was reported in monolayer NiI2. However, probing multiferroicity with scattering-based and optical bulk techniques is challenging on 2D materials, and experiments on the atomic scale are needed to fully characterize the multiferroic order at the monolayer limit. Here, scanning tunneling microscopy (STM) supported by density functional theory (DFT) calculations is used to probe and characterize the multiferroic order in monolayer NiI2. It is demonstrated that the type-II multiferroic order displayed by NiI2, arising from the combination of a magnetic spin spiral order and a strong spin-orbit coupling, allows probing the multiferroic order in the STM experiments. Moreover, the magnetoelectric coupling of NiI2 is directly probed by external electric field manipulation of the multiferroic domains. The findings establish a novel point of view to analyze magnetoelectric effects at the microscopic level, paving the way toward engineering new multiferroic orders in van der Waals materials and their heterostructuresM.A. and A.O.F. contributed equally to this work. This research made use of the Aalto Nanomicroscopy Center (Aalto NMC) facilities and was supported by the European Research Council (ERC‐2017‐AdG no. 788185 “Artificial Designer Materials” and ERC‐2021‐StG no. 101039500 “Tailoring Quantum Matter on the Flatland”) and Academy of Finland (Academy professor funding nos. 318995 and 320555, Academy research fellow nos. 331342, 336243 and nos. 338478 and 346654, and Academy postdoctoral fellow no. 349696). Computing resources from the Aalto Science‐IT project and CSC Helsinki are gratefully acknowledged. V.V. acknowledges fellowship support from the Princeton Center for Complex Materials supported by NSF‐DMR‐201175
Study of strategies aimed to fractionate bioactive compounds or to improve of their release in the colon
No full textTesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Química Física Aplicada. Fecha de Lectura: 14-06-2024Esta Tesis tiene embargado el acceso al texto completo hasta el 14-12-202
Teachers’ Social Justice Attitudes and Behaviors in Challenging Contexts: A Case Study
No full textEsta investigación busca conocer las actitudes y comportamientos del profesorado de escuelas situadas en contextos desafiantes y comprender cómo algunos de ellos se convierten en docentes socialmente justos. Se utilizó el enfoque metodológico de estudios de caso en cinco centros educativos: tres públicos y uno privado-concertado, de España, y uno público, de Portugal, con una muestra conformada por el personal docente y no docente de las escuelas. El análisis de documentos, la observación no participante y la información recabada en entrevistas semiestructuradas permitieron identificar dos perfiles docentes (uno comprometido con la educación y la justicia social; y otro agotado y desmotivado), y conocer las prácticas, motivaciones y liderazgo de docentes que trabajan por la justicia social. Se evidencia, así, la necesidad de una formación específica en justicia social y sensibilización ante las desigualdade
Optimizing Body Composition in Soccer Players Through Caloric Restriction: A Randomized Controlled Trial
No full textAchieving optimal body composition can be advantageous for athletes in terms of competitive performance. To date, there is scarce research examining the effects of caloric restriction (CR) on body composition in male professional soccer players. This study aims to investigate the impact of 6 weeks of CR with protein supplementation on body composition and the maintenance of changes after stopping CR for the next 6 weeks. Methods: The study was a controlled, randomized, parallel-group, experiment involving 28 participants. Recommended energy intake (REI) was individually calculated. The experimental group received a CR diet (-25%; average REI 2650 kcal/d) and the control group received a normal caloric (NC) diet (average REI 3500 kcal/d). All participants received protein supplementation. The intervention lasted for 6 weeks, followed by 6 weeks without intervention and provision of ad libitum diet in both groups. Body composition was assessed using anthropometric measurements. Results: The study participants were aged 27.6 ± 4.4 year on average. After 12 weeks, the CR group showed a significant reduction in body weight compared with the NC group (−0.33 kg for CR vs. −0.08 kg for NC; p 0.028). Both groups experienced a reduction in adipose mass after 6 and 12 weeks. Intragroup analyses demonstrate that only CR group continued a significant reduction after 12 weeks (6w -1.06kg; 12w -1.4kg. p 0.045). Throughout the study, there was an increase in muscle mass, and no significant difference was observed between groups. Conclusions: CR with protein supplementation in male professional soccer players reduces weight and promotes sustained fat loss over time without losing muscle mas