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"A Consciência da Revolução Síria": Criatividade na Busca pela Liberdade nas Faixas de Kafranbel (2011-2018)
Full text linkThis paper examines the revolutionary storytelling and communication process of Kafranbel, a town in northern Syria celebrated as "the conscience of the Syrian revolution". Known for its impactful banners, the town' production spanned from 2011 to 2018 and featured images of people holding banners with written messages, drawings, and caricatures. These banners were regularly shared on social media, reflecting a nuanced and evolving creative process. This study employs a descriptive and qualitative research methodology to analyze a dataset of images (n=214) compiled and organized chronologically. Additionally, insights from nine semi-structured in-terviews conducted in Spanish, English, and Arabic are included in the analysis. These interviews involved residents, witnesses, and experts who have closely followed the uprising, providing a comprehensive understanding of Kafranbel's communicative efforts. The findings highlight how Kafranbel's banners emerged and consolidated as a response to both the Syrian regime's crackdown and the threat increasingly posed by extremist groups, including the Islamic State of Iraq and Syria (ISIS). The town's storytelling employed human-centered and persuasive elements, such as the portrayal of children and references to global struggles and icons, to engage both local and international audiences. Patterns in the banners reveal a shift in tone and language choices as the conflict intensified and the town became more desperate for help. The absence of banners during periods of intense bombing underscores the harsh realities faced by the town's residents, which culminated in the town's silence following its recapture by the Syrian regime and the assassination of journalist Raed Fares by ISIS-affiliated gunmen. This study fills a significant gap in existing research, offering a detailed analysis of Kafranbel's unique communication strategy within the broader narrative of the Syrian uprising.Este artigo examina a narrativa revolucionária e o processo de comunicação de Kafranbel, uma cidade no norte da Síria amplamente reconhecida como “a consciência da revolução síria”. Célebre pelas suas emblemáticas faixas e cartazes, a produção da cidade decorreu entre 2011 e 2018, abrangendo imagens de pessoas a segurar faixas e cartazes com mensagens escritas, desenhos e caricaturas. Estas faixas e cartazes eram regularmente partilhados nas redes sociais, refletindo um processo criativo dinâmico e em constante evolução. Este estudo recorre a uma metodologia de investigação descritiva e qualitativa para analisar um conjunto de imagens (n = 214) compiladas e organizadas cronologicamente. Além disso, integra na análise as perceções de nove entrevistas semiestruturadas conduzidas em espanhol, inglês e árabe. Estas entrevistas, realizadas junto de residentes, testemunhas e especialistas que acompanharam de perto a revolta, proporcionam uma visão abrangente dos esforços de comunicação de Kafranbel.
As conclusões destacam a forma como as faixas e cartazes de Kafranbel surgiram e se consolidaram como resposta à repressão do regime sírio e à crescente ameaça representada por grupos extremistas, incluindo o Estado Islâmico do Iraque e da Síria (Daesh). A narrativa da cidade recorreu a elementos persuasivos e centrados no ser humano, como a representação de crianças e referências a lutas e ícones globais, para envolver tanto o público local como internacional. A análise das faixas e cartazes revela uma mudança no tom e nas escolhas linguísticas à medida que o conflito se intensificava e a cidade se via cada vez mais desesperada por auxílio. A ausência de faixas e cartazes durante períodos de bombardeamento intenso evidencia as duras realidades enfrentadas pelos residentes, culminando no silêncio da cidade após a sua recaptura pelo regime sírio e o assassinato do jornalista Raed Fares por homens armados afiliados ao Daesh. Este estudo preenche uma lacuna significativa na investigação existente, oferecendo uma análise detalhada da estratégia de comunicação singular de Kafranbel no contexto mais amplo da revolta síria
Generación de Datos Biométricos con Inteligencia Artificial Generativa
Full text linkA medida que evoluciona la tecnología, también aumentan los datos personales generados, y con ello, el riesgo a que sean vulnerados. Es por esto que surge la necesidad
de que la información se mantenga de forma privada, mediante mecanismos de seguridad como la autenticación de usuarios, asegurando que solamente puedan acceder a los datos
los individuos con la autorización correspondiente. Son muchos los tipos de autenticación que existen, pero se ha demostrado en numerosos estudios que algunos no son lo suficientemente seguros y presentan vulnerabilidades claras, por lo que se necesita de un sistema robusto, personal y con pocos frentes de ataque. La biometría expone estas características, ya que presenta peculiaridades que la hacen especial, como ser única para cada usuario o ser difícilmente replicable. Uno de los sistemas biométricos con más potencial futuro debido a diversas características es la autenticación basada en electrocardiogramas.
Este trabajo presenta una investigación acerca de un tipo de ataque que se realiza sobre esta clase de biometría, la generación de datos sintéticos mediante IA generativa. En
primer lugar, se implementa un sistema de autenticación basado en electrocardiogramas preciso y robusto para, en segundo lugar, tratar de vulnerarlo autenticando a un usuario
mediante un electrocardiograma suyo generado con IA. Para ello, se desarrolla una arquitectura de redes neuronales generativas con la capacidad de generar datos biométricos
sintéticos. Este estudio trata de mostrar cómo, incluso sistemas de identificación robustos, pueden ser vulnerados, por lo que necesitan de capas de seguridad más sofisticadas frente a este tipo de ataques. El sistema de autenticación implementado logra una precisión competitiva, aproximada al 90 %, utilizada posteriormente como métrica para el modelo generativo desarrollado con los latidos sintéticos, que mediante distintas optimizaciones, logra una precisión del 87.56 %.Grado en Ingeniería Informátic
The Economics of Forced Labour: Mining in Twentieth-Century Colonial Africa
Full text linkMención Internacional en el título de doctorPrograma de Doctorado en Historia Económica por la Universidad Carlos III de Madrid; la Universidad de Barcelona y la Universitat de València (Estudi General)Presidenta: Marlous Van Waijenburg.- Secretaria: Laura Maravall Buckwalter.- Vocal: Federico Tade
Energy-aware Joint Orchestration of 5G and Robots: Experimental Testbed and Field Validation
Full text link5G mobile networks introduce a new dimension for connecting and operating mobile robots in outdoor environments, leveraging cloud-native and offloading features of 5G networks to enable fully flexible and collaborative cloud robot operations. However, the limited battery life of robots remains a significant obstacle to their effective adoption in real-world exploration scenarios. This paper explores, via field experiments, the potential energy-saving gains of, a joint orchestration of 5G and Robot Operating System (ROS) that coordinates multiple 5G-connected robots both in terms of navigation and sensing, as well as optimizes their cloud-native service resource utilization while minimizing total resource and energy consumption on the robots based on real-time feedback. We designed, implemented and evaluated our proposed in an experimental testbed composed of commercial off-the-shelf robots and a local 5G infrastructure deployed on a campus. The experimental results demonstrated that significantly outperforms state-of-the-art approaches in terms of energy savings by offloading demanding computational tasks to the 5G edge infrastructure and dynamic energy management of on-board sensors (e.g., switching them off when they are not needed). This strategy achieves approximately ~15% energy savings on the robots, thereby extending battery life, which in turn allows for longer operating times and better resource utilization.The research leading to these results has been supported in part by the CERCA Programme / Generalitat de Catalunya, by the European Union’s H2020 6GGOALS Project (grant no. 101139232), by the SNS JU under the European Union’s Horizon Europe MultiX Project (grant no. 101192521) and Predict Project (grant no. 101095890), and by the Spanish Ministry of Economic Affairs and Digital Transformation and the European Union – NextGeneration EU (Call UNICO I+D 5G 2021, ref. number TSI-063000-2021-6 and TSI-063000-2021-122)
Development, 3D printing, and Mechanics of Novel Auxetic Unit Cell Monostructures
Full text linkComplex structures with unique mechanics are pivotal to advancing additive manufacturing, enabling applications where traditional methods are impractical. This study presents a novel 3D auxetic S-shaped monostructure designed for scalability, tunability, and printability using vat photopolymerization. Unit cell geometries were fabricated and experimentally evaluated under quasi-static loading conditions, with full-field analyses providing insights into their structural performance. Benchmarking against common auxetic structures (re-entrant and star topologies) highlighted the superior capabilities of the proposed design. The S-shaped monostructures exhibited geometric insensitivity in their force-displacement responses, with a stiffness of 180 N/m, withstanding large displacements of 11 mm without fracture or self-contact and supporting forces up to 1.8 N (i.e., 95 times their weight) before fully recovering upon unloading. Computational and experimental results demonstrated robust spatial auxeticity, persisting up to 85 % of axial global displacement due to geometry-driven rigid body motion, independent of base material properties. The S-shaped structures achieved superior auxetic performance ( 0.43) compared to re-entrant ( 0.30) and star ( 0.05) counterparts, with a monotonic and reversible auxetic response throughout loading. Strain contour analyses from digital image correlation validated the reduced stress concentrations and rigid body-dominated mechanism. The exceptional auxeticity and mechanical resilience of the S-shaped monostructures suggest promising applications in advanced designs, including 3D stackable configurations for impact mitigation applications.The authors acknowledge the support of the National Science Foundation under Grant No. 2035663 (G.Y.) and Grant No. 2035660 (B.K.). The authors are also grateful for internal funding from San Diego State University, Rowan University, and Universidad Carlos III de Madrid. In particular, this work was supported by the MCIN/AEI/10.13039/501100011033 and “European Union NextGenerationEU/PRTR” under grant PDC2021–121368-C21; the MCIN/AEI/10.13039/501100011033 under grants PID2020–112628RA-I00 and PID2020–118480RB-C22. Funding from the U.S. Department of Defense (W911NF1410039, W911NF1810477, W911NF2310150, and N00174–23–1–0009) is also acknowledged
Desarrollo de un simulador en 3D para la formación de controladores de tráfico aéreo en torre de control: optimización desde un entorno 2D
Full text linkEste documento tiene como objetivo documentar el trabajo realizado durante las prácticas curriculares y extracurriculares en SENASA, desarrollando mejoras para el simulador de torre de control, Altius. Este simulador constaba con una versión preliminar sobre la que se ha documentado e implementado un visor 3D simulando la vista desde la torre de control. Concretamente se ha trabajado sobre el aeropuerto de Alicante.Grado en Ingeniería Informátic
Mechanical performance of 3D-printed TPU auxetic structures for energy absorption applications
Full text linkThe emergence of metamaterials and layered structures obtained through additive manufacturing (AM) techniques opens a new paradigm of mechanical properties for advanced applications that need to be explored. This study investigates the mechanical behavior of 3D-printed auxetic structures, fabricated from thermoplastic polyurethane (TPU), under tensile and compressive loads. Utilizing fused deposition modeling (MEX), we examined the influence of printing direction on the anisotropic mechanical properties of TPU, with a particular focus on energy absorption, stress–strain responses, and damping capabilities. The research employs the Ogden model for hyperelastic characterization, demonstrating excellent correlation with experimental data. Thus, the novelty of this work relies on an approach that – with a focus in the precision and accuracy of the mechanical performance assessment – through a robust novel methodology combining the Ogden’s analytical model with numerical simulation provided by Ansys® and experimental tests of tensile and compression allows to comprehensively understand the mechanical performance of novel auxetic structures intended to energy absorption and impact resistance applications. Our findings reveal significant variations in mechanical performance based on printing orientation, with the 0°direction offering superior ductility and strength. These results suggest that optimizing the printing direction is crucial for enhancing the performance of TPU auxetic structures, particularly in applications requiring high impact resistance, energy absorption, and damping. This study contributes to the advancement of 3D printing technology for the development of next-generation materials with potential applications in protective gear, medical devices or damping devices, among others.This work has been developed within the framework of the Projects ‘PID2022-143329OA-I00’ (financed by MCIN/AEI) and ‘PLEC2021-007750’ (financed by MCIN/AEI/10.13039/501100011033 and by the European Union NextGenerationEU/PRTR ). This work has been supported by the Madrid Government (Comunidad de Madrid - Spain) under the Multiannual Agreement with UC3M (PRODEM-CM-UC3M) The authors also acknowledge the Research Group of the UNED “Industrial Production and Manufacturing Engineering (IPME)
From polymer electrolytes to calcium-conducting ionomers: A route towards rechargeable calcium batteries?
Full text linkThis work presents the synthesis of a new family of ionic monomers based on a diallylamine structure, designed to develop ionomers capable of conducting several types of monovalent and divalent cations (Li+, Na+, Ca2+, etc.). For this purpose, polymer electrolytes based on lithium and calcium salts at different O/M ratios are prepared using dialyzed poly(oxyethylene) (DIAPOE) as polymer backbone. These polymer electrolytes are fully characterized in terms of microstructure (scanning electronic microscopy, X-Ray mapping), thermal properties (thermogravimetric analysis, differential scanning calorimetry) and ionic conductivity (electrochemical impedance spectroscopy) to elucidate the underlying ion diffusion mechanisms. To validate the reliability of the proposed ionomers and their synthesis procedure, a series of films were produced by crosslinking the corresponding ionic monomers, IMOfr, with an unsaturated poly(oxyethylene), yielding IMOfr-NPC1000 ionomers. The results show that DIAPOE membranes exhibit higher ionic conductivity at high temperatures, achieving values in the range of 10–4 S cm-1. To further promote ionic conductivity at ambient temperature, the cross-linked structure of IMOfr-NPC1000 electrolytes were swelled in different polar solvents, demonstrating a conductivity increase of about two orders of magnitude without compromising their physical integrity. This study paves the way for the development of single-cation conducting ionomeric electrolytes towards safer, reliable and sustainable energy storage devices.This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 829145 (FETOPEN-VIDICAT). Justine Solier thanks ERAS-Labo and ANRT for the funding of her PhD grant (CIFRE fellowship)
An h-Adaptive Collocation Method for Physic-Informed Neural Networks
Full text linkDespite their flexibility and success in solving partial differential equations, Physics-Informed Neural Networks (PINNs) often suffer from convergence issues, even failing to converge, particularly in problems with steep gradients or localized features. Several remedies have been suggested to solve this problem, but one of the most promising is the dynamical adaptation of the collocation points. This paper explores a novel adaptive sampling method, of a stochastic nature, based on the Adaptive Mesh Refinement used in the Finite Element Method. The error estimates in our refinement algorithm are based on the value of the residual loss function. We tested our method against a variety of 1D and 2D benchmark problems that exhibit steep gradients near certain boundaries, with promising results.The authors are grateful for the support from the funds that the Polish Ministry of Science and Higher Education assigned to the AGH University of Krakow. The work was partially supported by the Excellence initiative - research university for the AGH University of Krakow. Albert Oliver-Serra is supported by the "Ayudas para la recualificación del sistema universitario español" (grant funded by the ULPGC, the Ministry of Universities by Order UNI/501/2021 of 26 May, and the European Union-Next Generation EU Funds) and by the grant contract "PRECOMP02 SD-24/03" (awarded by the Ministry of Universities, Science, Innovation, and Culture of the Government of the Canary Islands to the University of Las Palmas de Gran Canaria). Luis E. Garcia-Castillo has been supported by the Spanish Government throughout the project PDC2023-145929-C31 and by the Regional Government of Madrid throughout the project DISCO6G-CM