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The making of a World Trade Network of capital goods after the SecondWorld War. Reversal of fortune?
No full textThis paper studies the pattern of world trade in capital goods during the two key decades following World War II (1954-1973) by applying the Network Analysis methodology to study world trade as proposed by De Benedictis and Tajoli (2011). Departing from the technological superiority of US and Germany in machinery and transport equipment industries, their role asthe world main exporters is unquestionable. However, their relative presence in the world market, and more specifically in the European market, changed along the Golden Age period. While exports from the US dominated the European markets in the aftermath of the Second World War, the way the reconstruction was addressed and the new order favorable to tradeliberalization consolidated a network less dependent on the quasi-aboslute dominace of the United States prevailing after the war
DynoStore: A wide-area distribution system for the management of data over heterogeneous storage
No full textProceedings of: 2025 IEEE 25th International Symposium on Cluster, Cloud and Internet Computing (CCGrid). 19-22 May 2025. Tromsø (Norway)Data distribution across different facilities offers benefits such as enhanced resource utilization, increased resilience through replication, and improved performance by processing data near its source. However, managing such data is challenging due to heterogeneous access protocols, disparate authentication models, and the lack of a unified coordination framework. This paper presents DynoStore, a system that manages data across heterogeneous storage systems. At the core of DynoStore are data containers, an abstraction that provides standardized interfaces for seamless data management, irrespective of the underlying storage systems. Multiple data container connections create a cohesive wide-area storage network, ensuring resilience using erasure coding policies. Furthermore, a load-balancing algorithm ensures equitable and efficient utilization of storage resources. We evaluate DynoStore using benchmarks and realworld case studies, including the management of medical and satellite data across geographically distributed environments. Our results demonstrate a 10 % performance improvement compared to centralized cloud-hosted systems while maintaining competitive performance with state-of-the-art solutions such as Redis and IPFS. DynoStore also exhibits superior fault tolerance, withstanding more failures than traditional systems
Authorization models for IoT environments: A survey
Get PDFAuthorization models are pivotal in the Internet of Things (IoT) ecosystem, ensuring secure management of data access and communication. These models function after authentication, determining the specific actions that a device is allowed to perform. This paper aims to provide a comprehensive and comparative analysis of authorization solutions within IoT contexts, based on the requirements identified from the existing literature. We critically assess the functionalities and capabilities of various authorization solutions, particularly those designed for IoT cloud platforms and distributed architectures. Our findings highlight the urgent need for further development of authorization models optimized for the unique demands of IoT environments. Consequently, we address both the persistent challenges and the gaps within this domain. As IoT continues to reshape the technological landscape, the refinement and adaptation of authorization models remain imperative ongoing pursuits.This work was supported by the Spanish Government under the grant TED-2021-130369B-C32, funded by MICIU/AEI/ 10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR” and the grant PID2020-113795RB-C32, fun-ded by MICIU/AEI /10.13039/501100011033. In addition, it was partially supported by project i-SHAPER, which is being carried out within the framework of the Recovery, Transformation, and Resilience Plan funds, funded by the European Union (Next Generation)
Step-by-step learning
Get PDFThe natural or generational learning process consists of building models based on available experiences. Each generation learns from the models obtained by its predecessors and obtains a new model for its own batch of experiences. In this paper, we discuss this step-by-step learning procedure for supervised classification and regression problems on large datasets. We show that the stepwise learning procedure performs competitively with respect to the approach that uses a single model for the entire dataset. This allows the step-by-step procedure to address larger datasets, and also, if necessary, respect the confidentiality of data from previous generations.The author acknowledges the partial funding of the Spanish Ministry of Science and Innovation projects PID2022-138114NB-I00 and PID2023-151013NB-I00, funded by MCIN/AEI/10.13039/501100011033 and by FEDER/UE
Inteligencia Artificial y Postproducción. Integración de nuevas competencias digitales en la docencia universitaria de Comunicación Audiovisual
Get PDFDiscovery and Measurement of Coherent Patterns in Boundary Layer Flows
Get PDFMención Internacional en el título de doctorTesis por compendio de publicacionesEsta tesis contiene artículos de investigaciónFrom the first powered flight to the turbines driving the green energy revolution, understanding how fluids move over solid surfaces has been at the heart of engineering innovation. Wall-bounded flows are central to generating lift, minimizing drag, and optimizing heat transfer, shaping the efficiency of systems in aerospace, energy, and automotive industries. Among these, turbulent boundary layers (TBLs)—where interactions near solid walls drive energy transfer and momentum exchange are particularly significant. Yet, the chaotic and nonlinear nature of turbulence presents a formidable challenge. This thesis focuses on advancing the detection and characterization of coherent structures in TBLs, which are patterns of organized motion that govern energy transfer, mixing, and drag generation. These structures form the backbone of turbulence dynamics and are critical for developing effective flow control strategies. By developing state-of-the-art experimental techniques and innovative data-driven methodologies, this work addresses the inefficiencies posed by turbulence and deepens our understanding of boundary layer behaviour. The findings include the advancement of non-intrusive sensing techniques for convective heat transfer at the wall and of data-driven methods for the modelling of transition from laminar to turbulent flow. This thesis is structured into two main parts. The first part focuses on experimental investigations conducted in the water channel facility at Universidad Carlos III de Madrid and the wind tunnel facilities at TU Delft. In these studies, well-characterized turbulent boundary layers were established under controlled laboratory conditions, enabling precise observations using non-intrusive measurement techniques such as particle image velocimetry and time-resolved infrared thermography. These methods provided critical insights into the velocity fields and thermal imprints left by turbulent structures, facilitating a direct comparison of results obtained in water and air. This cross-media validation ensured the consistency of observed turbulent features and demonstrated the reliability of the applied measurement techniques. The second block emphasizes a data-driven approach, leveraging machine learning techniques to analyse complex flow datasets. By employing unsupervised learning methods such as clustering, the study identified transitional and turbulent flow regions directly from the data, bypassing the need for predefined labels. This approach provided a computationally efficient method for capturing the key flow characteristics -such as coherent structures and dominant flow patterns - that fundamentally govern the dynamics of turbulent and transitional regimes, and showed the potential of reduced-order models to simplify the inherent complexity of turbulent flows while retaining the core physical information. By integrating experimental rigour with data-driven techniques, this thesis contributes to advancing the understanding of TBLs and offers practical tools for real-time flow control and predictive modelling. It contributes to the theoretical and practical research, laying the groundwork for further exploration in fluid dynamics and turbulence research.This thesis has been carried out in the Aerospace Engineering Department at Universidad Carlos III de Madrid. The financial support has been provided by the Universidad Carlos III de Madrid through a PIPF scholarship awarded on a competitive basis and by the following research projects: COTURB (COherent structures in wall-bounded TURBulence), funded by H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC), under grant ERC-2014.AdG-669505; ARTURO (Active contRol of Turbulence for sUstainable aiRcraft propulsiOn), ref. PID2019-109717RB-I00/AEI/10.13039/501100011033, funded by the Spanish State Research Agency (SRA); PITUFLOW(Pattern Identification in TUrbulence for FLOW control), ref. PITUFLOW-CM-UC3M, funded by the Madrid Government (Comunidad de Madrid) under the Multiannual Agreement with UC3M in the line of “Fostering Young Doctors Research” and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation).Programa de Doctorado en Mecánica de Fluidos por la Universidad Carlos III de Madrid; la Universidad de Jaén; la Universidad de Zaragoza; la Universidad Nacional de Educación a Distancia; la Universidad Politécnica de Madrid y la Universidad Rovira iPresidente: Gennaro Cardone.- Secretario: Carlos Sanmiguel Vila.- Vocal: Gioacchino Cafier
Low-velocity impact response of hybrid sheet moulding compound composite laminates
Get PDFThis work presents a comprehensive study on the impact damage tolerance of Sheet Moulding Compounds (SMCs). The performance of glass, carbon and hybrid glass/carbon SMCs are compared by means of tensile, compression, low-velocity impact and compression after impact experiments. Damage analysis of the impacted laminates was performed by ultrasonic and X-ray methodologies. The glass SMC exhibited the highest damage tolerance in low-velocity impact with the smallest damaged area, crack density and loss in compression after impact (CAI) strength. On the other hand, the carbon SMC demonstrated superior in-plane stiffness and strength, but exhibited a large damaged area and crack density under impact. The hybrid SMC displayed an optimal compromise, exhibiting intermediate tensile in-plane performance and excellent damage tolerance at lower impact energy levels, but suffered from extensive delamination at the highest impact energy. Overall, the findings highlight the suitability of hybrid SMCs for structural applications with potential impact risks.The author acknowledges the PhD funding supplied by WAE Technologies Limited and the National Manufacturing Institute Scotland funded by the Scottish Research Partnership in Engineering [grant number NMIS-IDP/032]. Access to X-ray beamtime was granted to JP through the Henry Royce Institute (EPSRC) [grant number EP/R00661X/1]. This investigation was also supported by the Spanish Agency of Research (Agencia Estatal de Investigacion, AEI) [grant number TED2021-131154B-l00]
Mirror Dwellers in Social VR: Investigating Reasons and Perception of Mirror Watching
Get PDFIn social Virtual Reality (VR) environments, the significant trend of 'mirror dwellers,' users who often use virtual mirrors to engage with their avatars, has emerged. This study examines discussions from r/VRchat to explore the reasons for this behavior and how it is perceived within the broader community. Our findings highlight the critical role of mirrors in compensating for the sensory limitations of VR, particularly the lack of physical feedback. Users often turn to mirrors to view parts of their avatar that are not accessible from a first-person perspective. Additionally, our research uncovers that a limited Field-Of-View (FOV) hinders the development of a strong connection between users and their avatars, further driving the need for mirrors. However, while using mirrors to mitigate FOV and physical feedback limitations can be helpful, it may also disrupt social interaction in VR environments, as the excessive reliance on mirrors can hinder the social experience in VR for others. This research deepens our understanding of user behavior in social VR and provides insights that could guide future design improvements to enrich the overall user experience.This work was supported by the Research Council of Finland (#357270). Andrea Bellucci was supported by MICINN under the grant "Convocatoria de la Universidad Carlos III de Madrid de Ayudas para la recualificación del sistema universitario español para 2021-2023, de 1 de julio de 2021" (Orden UNI/551/2021)
Hemodynamics affects factor XI/XII anticoagulation efficacy in patient-derived left atrial models
Get PDFBackground and Objective: Atrial fibrillation (AF) is a common arrhythmia that disrupts blood circulation in the left atrium (LA), causing stasis in the left atrial appendage (LAA) and increasing thromboembolic risk. In patients at sufficiently high risk, anticoagulation is indicated. This benefit may be counterbalanced by an increased risk of bleeding. Novel anticoagulants under development, such as factor XI/XII inhibitors, may be associated with a lower bleeding risk. However, their efficacy in preventing thrombosis is not fully understood. We hypothesized that patient-specific flow patterns in the LA and LAA not only influence the risk of thrombosis but also the effectiveness of anticoagulation agents. Methods: To test our hypothesis, we simulated blood flow and the intrinsic coagulation pathway in patient-specific LA anatomies with and without factor XI/XII inhibition. We included a heterogeneous cohort of thirteen patients, some in sinus rhythm and others in AF, four of whom had an LAA thrombus or a history of transient ischemic attacks. We used computational fluid dynamics based on 4D CT imaging and a detailed 32-coagulation factor system to run 247 simulations. We analyzed baseline LA flow patterns and evaluated various factor XI/XII inhibition levels. Implementing a novel multi-fidelity coagulation modeling approach accelerated computations by two orders of magnitude, enabling many simulations to be performed. Results: The simulations provided spatiotemporally resolved maps of thrombin concentration throughout the LA, showing that it peaks inside the LAA. Coagulation metrics based on peak LAA thrombin dynamics suggested patients could be classified as having no, moderate or high thromboembolic risk. High-risk patients had slower flows and higher residence times in the LAA than those with moderate thromboembolic risk, and they required stronger factor XI/XII inhibition to prevent thrombin growth. These data suggest that the anticoagulation effect was also related to the LAA hemodynamics. Conclusion: The methodology outlined in this study has the potential to enable personalized assessments of coagulation risk and to tailor anticoagulation therapy by analyzing flow dynamics in patient-derived LA models, representing a significant step towards advancing the application of digital twins in cardiovascular medicine.This work was partially supported by the Spanish Research Agency (AEI, grant number PID2019-107279RB-I00), Instituto de Salud Carlos III, Spain (grant number PI21/00274- PACER1), the EU—European Regional Development Fund, and the US National Institutes of Health (grant numbers 1R01HL160024 and 1R01HL158667)
Injectable hyaluronic acid hydrogels via Michael addition as dermal fillers for skin regeneration applications
Get PDFThis study presents the development of injectable hydrogels based on hyaluronic acid for dermal filler applications, synthesized via Michael-type addition reactions between thiolated hyaluronic acid and polyethylene glycol derivatives. By varying thiol substitution, crosslinking kinetics and hydrogel properties were optimized. Biphasic gel formulations comprising crosslinked hyaluronic acid microparticles in a non-reactive fluid phase matrix enhances injectability and versatility. Key properties, including enzymatic degradation, injectability, and rheology, were evaluated, alongside a three-dimensional culture model to simulate dermal remodelling. Selected gel formulations promoted balanced collagen synthesis and degradation, essential for skin regeneration, while showing a controlled inflammatory response, supporting tissue repair and reducing adverse effects. These findings position these hydrogels as promising candidates for safe and effective dermal filler, supporting tissue remodelling and inflammation management.The authors would like to express their appreciation to E. García and M. Benito (CENQUIOR-CSIC) for the support with NMR spectroscopy. This research was funded by the Spanish Ministry of Science and Innovation through the call "Doctorados Industriales 2019" (DIN2019-010868) and the project PID2020-113045 GB-C22 funded by MCINN/AEI/10.13039/501100011033