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1. Complicaciones intestinales graves en pacientes SARS-CoV-2 recibiendo manejo protocolizado

Author

S.C. Estevez-Cerda, J.A. Saldaña-Rodríguez, A.G. Alam-Gidi, A. Riojas-Garza, M. Rodarte-Shade, J. Velazco-de la Garza, A. Leyva-Alvizo, R. Gonzalez-Ruvalcaba, M.F. Martinez-Resendez, and J.I. Ortiz de Elguea-Lizarraga

Subjects
COVID-19, Bowel perforation, Mesenteric ischemia, Mesenteric thrombosis, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Resumen: Introducción y objetivos: Presentamos una serie de casos de 10 pacientes recibiendo manejo protocolizado para infección por SARS-CoV-2 que desarrollaron complicaciones gastrointestinales severas. El objetivo del estudio es contribuir a la discusión sobre las complicaciones gastrointestinales de la infección por SARS-CoV-2. Hasta el momento y tras una revisión de la literatura, se trata de la primera serie de casos detallada sobre este tema. Materiales y métodos: Se realizó una búsqueda retrospectiva y filtrada de todos los pacientes ingresados en nuestro hospital por infección por SARS-CoV-2 que desarrollaron complicaciones gastrointestinales severas. Se obtuvieron del expediente clínico todos los datos relevantes al manejo intrahospitalario antes y después de la cirugía. Resultados: De 905 pacientes ingresados a la fecha del 26 de agosto de 2020 en nuestro hospital por infección por SARS-CoV-2, 10 pacientes desarrollaron complicaciones gastrointestinales severas. Siete de ellos fueron hombres. Se presentaron 4 perforaciones del yeyuno proximal, 3 perforaciones del colon ascendente, una perforación concomitante del colon sigmoides e íleon terminal, una necrosis intestinal masiva y una defunción prequirúrgica. Se realizaron 3 colectomías derechas, 4 resecciones intestinales, un procedimiento de Hartmann con resección intestinal y una reparación primaria de intestino delgado. La mortalidad del grupo estudiado fue del 50%. Conclusión: Las perforaciones intestinales espontáneas y la isquemia mesentérica aguda están surgiendo como complicaciones severas y que ponen en riesgo la vida de pacientes hospitalizados por SARS-CoV-2. Se requiere más evidencia para identificar factores de riesgo, establecer medidas preventivas y analizar los posibles efectos adversos de los protocolos de manejo actuales. Abstract: Introduction and aims: A case series of ten patients that received protocolized care for SARS-CoV-2 infection and developed severe gastrointestinal complications, is presented. The aim of our study was to contribute to the ongoing discussion regarding gastrointestinal complications related to SARS-CoV-2 infection. After reviewing the current literature, ours appears to be the first detailed case series on the topic. Materials and methods: A retrospective filtered search of all patients admitted to our hospital for SARS-CoV-2 infection, who developed severe gastrointestinal complications, was performed. All relevant data on hospital patient management, before and after surgery, were collected from the medical records. Results: Of the 905 patients admitted to our hospital due to SARS-CoV-2 infection, as of August 26, 2020, ten of them developed severe gastrointestinal complications. Seven of those patients were men. There were four cases of perforation of the proximal jejunum, three cases of perforations of the ascending colon, one case of concomitant perforation of the sigmoid colon and terminal ileum, one case of massive intestinal necrosis, and one preoperative death. Three right colectomies, four intestinal resections, one Hartmann's procedure with bowel resection, and one primary repair of the small bowel were performed. The mortality rate of the patients analyzed was 50%. Conclusion: Spontaneous bowel perforations and acute mesenteric ischemia are emerging as severe, life-threatening complications in hospitalized SARS-CoV-2 patients. More evidence is needed to identify risk factors, establish preventive measures, and analyze possible adverse effects of the current treatment protocols.

Published
2021
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3. Severe bowel complications in SARS-CoV-2 patients receiving protocolized care

Author

S.C. Estevez-Cerda, J.A. Saldaña-Rodríguez, A.G. Alam-Gidi, A. Riojas-Garza, M. Rodarte-Shade, J. Velazco-de la Garza, A. Leyva-Alvizo, R. Gonzalez-Ruvalcaba, M.F. Martinez-Resendez, and J.I. Ortiz de Elguea-Lizarraga

Subjects
COVID-19, Perforación intestinal, Isquemia mesentérica, Trombosis mesentérica, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Introduction and aims: A case series of ten patients that received protocolized care for SARS-CoV-2 infection and developed severe gastrointestinal complications, is presented. The aim of our study was to contribute to the ongoing discussion regarding gastrointestinal complications related to SARS-CoV-2 infection. After reviewing the current literature, ours appears to be the first detailed case series on the topic. Materials and methods: A retrospective filtered search of all patients admitted to our hospital for SARS-CoV-2 infection, who developed severe gastrointestinal complications, was performed. All relevant data on hospital patient management, before and after surgery, were collected from the medical records. Results: Of the 905 patients admitted to our hospital due to SARS-CoV-2 infection, as of August 26, 2020, ten of them developed severe gastrointestinal complications. Seven of those patients were men. There were four cases of perforation of the proximal jejunum, three cases of perforations of the ascending colon, one case of concomitant perforation of the sigmoid colon and terminal ileum, one case of massive intestinal necrosis, and one preoperative death. Three right colectomies, four intestinal resections, one Hartmann’s procedure with bowel resection, and one primary repair of the small bowel were performed. The mortality rate of the patients analyzed was 50%. Conclusion: Spontaneous bowel perforations and acute mesenteric ischemia are emerging as severe, life-threatening complications in hospitalized SARS-CoV-2 patients. More evidence is needed to identify risk factors, establish preventive measures, and analyze possible adverse effects of the current treatment protocols. Resumen: Introducción y objetivos: Presentamos una serie de casos de diez pacientes recibiendo manejo protocolizado para infección por SARS-CoV-2 que desarrollaron complicaciones gastrointestinales severas. El objetivo del estudio es contribuir a la discusión sobre las complicaciones gastrointestinales de la infección por SARS-CoV-2. Hasta el momento y tras una revisión de la literatura, se trata de la primera serie de casos detallada sobre este tema. Materiales y métodos: Se realizó una búsqueda retrospectiva y filtrada de todos los pacientes ingresados en nuestro hospital por infección por SARS-CoV-2 que desarrollaron complicaciones gastrointestinales severas. Se obtuvieron del expediente clínico todos los datos relevantes al manejo intrahospitalario antes y después de la cirugía. Resultados: De 905 pacientes ingresados a la fecha del 26 de agosto de 2020 en nuestro hospital por infección por SARS-CoV-2, diez pacientes desarrollaron complicaciones gastrointestinales severas. Siete de ellos fueron hombres. Se presentaron cuatro perforaciones del yeyuno proximal, tres perforaciones del colon ascendente, una perforación concomitante del colon sigmoides e íleon terminal, una necrosis intestinal masiva y una defunción prequirúrgica. Se realizaron tres colectomías derechas, cuatro resecciones intestinales, un procedimiento de Hartmann con resección intestinal y una reparación primaria de intestino delgado. La mortalidad del grupo estudiado fue de 50%. Conclusión: Las perforaciones intestinales espontáneas y la isquemia mesentérica aguda están surgiendo como complicaciones severas y que ponen en riesgo la vida de pacientes hospitalizados por SARS-CoV-2. Se requiere más evidencia para identificar factores de riesgo, establecer medidas preventivas y analizar los posibles efectos adversos de los protocolos de manejo actuales.

Published
2021
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5. A Python Framework Enhancement for Neutrosophic Topologies

Author

Nordo, Giorgio, Jafari, Saeid, and Vazquez, Maikel Yelandi Leyva

Subjects
Mathematics - General Mathematics, 03E72, 54A40, 54D99, 68W99
Abstract

This paper introduces an extension to the Python Neutrosophic Sets (PYNS) framework, originally detailed in Nordo et al. 2024, with the addition of the NSfamily class for constructing and manipulating neutrosophic topologies. Building on existing classes like NSuniverse and NSset, the NSfamily class enables the definition and testing of neutrosophic families as basis and sub-basis for neutrosophic topological spaces. This extension provides tools for verifying closure properties under union and intersection, and for determining whether a given family constitutes a neutrosophic topology. Through implemented algorithms, the framework automates the generation of topologies from families of neutrosophic sets, offering an efficient tool for advancing research in neutrosophic topology. Practical applications are demonstrated with detailed examples, showcasing how this class enhances the scope and flexibility of neutrosophic modeling within the PYNS framework.

Published
2024

6. Coexistence of Real-Time Source Reconstruction and Broadband Services Over Wireless Networks

Author

Mishra, Anup, Pappas, Nikolaos, Stefanović, Čedomir, Ayan, Onur, An, Xueli, Wu, Yiqun, Popovski, Petar, and Leyva-Mayorga, Israel

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Achieving a flexible and efficient sharing of wireless resources among a wide range of novel applications and services is one of the major goals of the sixth-generation of mobile systems (6G). Accordingly, this work investigates the performance of a real-time system that coexists with a broadband service in a frame-based wireless channel. Specifically, we consider real-time remote tracking of an information source, where a device monitors its evolution and sends updates to a base station (BS), which is responsible for real-time source reconstruction and, potentially, remote actuation. To achieve this, the BS employs a grant-free access mechanism to serve the monitoring device together with a broadband user, which share the available wireless resources through orthogonal or non-orthogonal multiple access schemes. We analyse the performance of the system with time-averaged reconstruction error, time-averaged cost of actuation error, and update-delivery cost as performance metrics. Furthermore, we analyse the performance of the broadband user in terms of throughput and energy efficiency. Our results show that an orthogonal resource sharing between the users is beneficial in most cases where the broadband user requires maximum throughput. However, sharing the resources in a non-orthogonal manner leads to a far greater energy efficiency.

Published
2024

7. Coexistence of Radar and Communication with Rate-Splitting Wireless Access

Author

Mishra, Anup, Leyva-Mayorga, Israel, and Popovski, Petar

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

This work investigates the coexistence of sensing and communication functionalities in a base station (BS) serving a communication user in the uplink and simultaneously detecting a radar target with the same frequency resources. To address inter-functionality interference, we employ rate-splitting (RS) at the communication user and successive interference cancellation (SIC) at the joint radar-communication receiver at the BS. This approach is motivated by RS's proven effectiveness in mitigating inter-user interference among communication users. Building on the proposed system model based on RS, we derive inner bounds on performance in terms of ergodic data information rate for communication and ergodic radar estimation information rate for sensing. Additionally, we present a closed-form solution for the optimal power split in RS that maximizes the communication user's performance. The bounds achieved with RS are compared to conventional methods, including spectral isolation and full spectral sharing with SIC. We demonstrate that RS offers a superior performance trade-off between sensing and communication functionalities compared to traditional approaches. Pertinently, while the original concept of RS deals only with digital signals, this work brings forward RS as a general method for including non-orthogonal access for sensing signals. As a consequence, the work done in this paper provides a systematic and parametrized way to effectuate non-orthogonal sensing and communication waveforms.

Published
2024

8. LLMs for Domain Generation Algorithm Detection

Author

La O, Reynier Leyva, Catania, Carlos A., and Parlanti, Tatiana

Subjects
Computer Science - Computation and Language, Computer Science - Cryptography and Security
Abstract

This work analyzes the use of large language models (LLMs) for detecting domain generation algorithms (DGAs). We perform a detailed evaluation of two important techniques: In-Context Learning (ICL) and Supervised Fine-Tuning (SFT), showing how they can improve detection. SFT increases performance by using domain-specific data, whereas ICL helps the detection model to quickly adapt to new threats without requiring much retraining. We use Meta's Llama3 8B model, on a custom dataset with 68 malware families and normal domains, covering several hard-to-detect schemes, including recent word-based DGAs. Results proved that LLM-based methods can achieve competitive results in DGA detection. In particular, the SFT-based LLM DGA detector outperforms state-of-the-art models using attention layers, achieving 94% accuracy with a 4% false positive rate (FPR) and excelling at detecting word-based DGA domains.

Published
2024

9. A Game-Theoretic Perspective for Efficient Modern Random Access

Author

Hansen, Andreas Peter Juhl, Münster, Jeppe Roden, Villadsen, Rasmus Erik, Segaard, Simon Bock, Rasmussen, Søren Pilegaard, Biscio, Christophe, and Leyva-Mayorga, Israel

Subjects
Computer Science - Information Theory, Computer Science - Computer Science and Game Theory
Abstract

Modern random access mechanisms combine packet repetitions with multi-user detection mechanisms at the receiver to maximize the throughput and reliability in massive Internet of Things (IoT) scenarios. However, optimizing the access policy, which selects the number of repetitions, is a complicated problem, and failing to do so can lead to an inefficient use of resources and, potentially, to an increased congestion. In this paper, we follow a game-theoretic approach for optimizing the access policies of selfish users in modern random access mechanisms. Our goal is to find adequate values for the rewards given after a success to achieve a Nash equilibrium (NE) that optimizes the throughput of the system while considering the cost of transmission. Our results show that a mixed strategy, where repetitions are selected according to the irregular repetition slotted ALOHA (IRSA) protocol, attains a NE that maximizes the throughput in the special case with two users. In this scenario, our method increases the throughput by 30% when compared to framed ALOHA. Furthermore, we present three methods to attain a NE with near-optimal throughput for general modern random access scenarios, which exceed the throughput of framed ALOHA by up to 34%., Comment: Submitted for publication to IEEE WCNC 2025

Published
2024

10. Content-based Wake-up for Energy-efficient and Timely Top-k IoT Sensing Data Retrieval

Author

Shiraishi, Junya, Kalør, Anders E., Leyva-Mayorga, Israel, Chiariotti, Federico, Popovski, Petar, and Yomo, Hiroyuki

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

Energy efficiency and information freshness are key requirements for sensor nodes serving Industrial Internet of Things (IIoT) applications, where a sink node collects informative and fresh data before a deadline, e.g., to control an external actuator. Content-based wake-up (CoWu) activates a subset of nodes that hold data relevant for the sink's goal, thereby offering an energy-efficient way to attain objectives related to information freshness. This paper focuses on a scenario where the sink collects fresh information on top-k values, defined as data from the nodes observing the k highest readings at the deadline. We introduce a new metric called top-k Query Age of Information (k-QAoI), which allows us to characterize the performance of CoWu by considering the characteristics of the physical process. Further, we show how to select the CoWu parameters, such as its timing and threshold, to attain both information freshness and energy efficiency. The numerical results reveal the effectiveness of the CoWu approach, which is able to collect top-k data with higher energy efficiency while reducing k-QAoI when compared to round-robin scheduling, especially when the number of nodes is large and the required size of k is small., Comment: Submitted for IEEE Transactions on Communications

Published
2024

11. Unveiling Stereotypes: A Study on Science Perceptions among Children in Northwest Mexico

Author

Ulises Bardullas and Eugenio Leyva-Figueroa

Abstract

The prevailing portrayal of science and scientists within the public domain is a multifaceted mix of conventional stereotypes. Our study investigates these perceptions among Mexican children, analyzing 816 drawings and descriptions collected from fourth to seventh graders in rural and urban schools in Northwestern Mexico. Drawings were analyzed for the scientist's appearance, location, and activity using mDAST/DAST, and each category was subcategorized for deeper compressive. The results confirm stereotypical depictions in all categories, however, girls draw more female scientists, mainly characterized by Caucasian features. Likewise, although stereotypical lab depictions persist, many drawings show alternative lab research and outdoor activities. Our study highlights the importance of promoting a diverse and inclusive image of scientists and their work, starting from an early age, using inclusive textbooks and effective pedagogical strategies.

Published
2024
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14. First operation of LArTPC in the stratosphere as an engineering GRAMS balloon flight (eGRAMS)

Author

Nakajima, R., Arai, S., Aoyama, K., Utsumi, Y., Tamba, T., Odaka, H., Tanaka, M., Yorita, K., Aramaki, T., Asaadi, J., Bamba, A., Cannady, N., Coppi, P., De Nolfo, G., Errando, M., Fabris, L., Fujiwara, T., Fukazawa, Y., Ghosh, P., Hagino, K., Hakamata, T., Hijikata, U., Hiroshima, N., Ichihashi, M., Ichinohe, Y., Inoue, Y., Ishikawa, K., Ishiwata, K., Iwata, T., Karagiorgi, G., Kato, T., Kawamura, H., Krizmanic, J., Leyva, J., Malige, A., Mitchell, J. G., Mitchell, J. W., Mukherjee, R., Nakazawa, K., Okuma, K., Perez, K., Poudyal, N., Safa, I., Sasaki, M., Seligman, W., Shirahama, K., Shiraishi, T., Smith, S., Suda, Y., Suraj, A., Takahashi, H., Takashima, S., Tandon, S., Tatsumi, R., Tomsick, J., Tsuji, N., Uchida, Y., Watanabe, S., Yano, Y., Yawata, K., Yoneda, H., Yoshimoto, M., and Zeng, J.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

GRAMS (Gamma-Ray and AntiMatter Survey) is a next-generation balloon/satellite experiment utilizing a LArTPC (Liquid Argon Time Projection Chamber), to simultaneously target astrophysical observations of cosmic MeV gamma-rays and conduct an indirect dark matter search using antimatter. While LArTPCs are widely used in particle physics experiments, they have never been operated at balloon altitudes. An engineering balloon flight with a small-scale LArTPC (eGRAMS) was conducted on July 27th, 2023, to establish a system for safely operating a LArTPC at balloon altitudes and to obtain cosmic-ray data from the LArTPC. The flight was launched from the Japan Aerospace Exploration Agency's (JAXA) Taiki Aerospace Research Field in Hokkaido, Japan. The total flight duration was 3 hours and 12 minutes, including a level flight of 44 minutes at a maximum altitude of 28.9 km. The flight system was landed on the sea and successfully recovered. The LArTPC was successfully operated throughout the flight, and about 0.5 million events of the cosmic-ray data including muons, protons, and Compton scattering gamma-ray candidates, were collected. This pioneering flight demonstrates the feasibility of operating a LArTPC in high-altitude environments, paving the way for future GRAMS missions and advancing our capabilities in MeV gamma-ray astronomy and dark matter research.

Published
2024

15. Semantic and goal-oriented edge computing for satellite Earth Observation

Author

Soret, Beatriz, Leyva-Mayorga, Israel, Mercado-Martínez, Antonio M., Moretti, Marco, Jurado-Navas, Antonio, Martinez-Gost, Marc, de Miguel, Celia Sánchez, Salas-Prendes, Ainoa, and Popovski, Petar

Subjects
Computer Science - Networking and Internet Architecture
Abstract

The integration of Semantic Communications (SemCom) and edge computing in space networks enables the optimal allocation of the scarce energy, computing, and communication resources for data-intensive applications. We use Earth Observation (EO) as a canonical functionality of satellites and review its main characteristics and challenges. We identify the potential of the space segment, represented by a low Earth orbit (LEO) satellite constellation, to serve as an edge layer for distributed intelligence. Based on that, propose a system architecture that supports semantic and goal-oriented applications for image reconstruction and object detection and localization. The simulation results show the intricate trade-offs among energy, time, and task-performance using a real dataset and State-of-the-Art (SoA) processing and communication parameters., Comment: Submitted for publication to IEEE Communications Magazine

Published
2024

16. An additively optimal interpreter for approximating Kolmogorov prefix complexity

Author

Leyva-Acosta, Zoe, Yeomans, Eduardo Acuña, and Hernandez-Quiroz, Francisco

Subjects
Computer Science - Information Theory
Abstract

We study practical approximations to Kolmogorov prefix complexity (K) using IMP2, a high-level programming language. Our focus is on investigating the interpreter optimality for this language as the reference machine for the Coding Theorem Method (CTM). A method advanced to deal with applications to algorithmic complexity different to the popular traditional lossless compression approach based on the principles of algorithmic probability. The chosen model of computation is proven to be suitable for this task and a comparison to other models and methods is performed. Our findings show that CTM approximations using our model do not always correlate with results from lower-level models of computation. This suggests some models may require a larger program space to converge to Levin's universal distribution. Furthermore, we compare CTM with an upper bound to Kolmogorov complexity and find a strong correlation, supporting CTM's validity as an approximation method with finer-grade resolution of K., Comment: 17 pages, 3 tables and 3 figures

Published
2024

17. Unified Deep Learning Framework for Many-Body Quantum Chemistry via Green's Functions

Author

Venturella, Christian, Li, Jiachen, Hillenbrand, Christopher, Peralta, Ximena Leyva, Liu, Jessica, and Zhu, Tianyu

Subjects
Physics - Chemical Physics, Condensed Matter - Materials Science, Physics - Computational Physics
Abstract

Quantum many-body methods provide a systematic route to computing electronic properties of molecules and materials, but high computational costs restrict their use in large-scale applications. Due to the complexity in many-electron wavefunctions, machine learning models capable of capturing fundamental many-body physics remain limited. Here, we present a deep learning framework targeting the many-body Green's function, which unifies predictions of electronic properties in ground and excited states, while offering deep physical insights into electron correlation effects. By learning the $GW$ or coupled-cluster self-energy from mean-field features, our graph neural network achieves competitive performance in predicting one- and two-particle excitations and quantities derivable from one-particle density matrix. We demonstrate its high data efficiency and good transferability across chemical species, system sizes, molecular conformations, and correlation strengths in bond breaking, through multiple molecular and nanomaterial benchmarks. This work opens up new opportunities for utilizing machine learning to solve many-electron problems., Comment: 16 pages, 5 figures

Published
2024

18. Light Dark Matter Constraints from SuperCDMS HVeV Detectors Operated Underground with an Anticoincidence Event Selection

Author

SuperCDMS Collaboration, Albakry, M. F., Alkhatib, I., Alonso-González, D., Amaral, D. W. P., Anczarski, J., Aralis, T., Aramaki, T., Arnquist, I. J., Langroudy, I. Ataee, Azadbakht, E., Bathurst, C., Bhattacharyya, R., Biffl, A. J., Brink, P. L., Buchanan, M., Bunker, R., Cabrera, B., Calkins, R., Cameron, R. A., Cartaro, C., Cerdeño, D. G., Chang, Y. -Y., Chaudhuri, M., Chen, J. -H., Chen, R., Chott, N., Cooley, J., Coombes, H., Cushman, P., Cyna, R., Das, S., De Brienne, F., Dharani, S., di Vacri, M. L., Diamond, M. D., Elwan, M., Fascione, E., Figueroa-Feliciano, E., Fouts, K., Fritts, M., Germond, R., Ghaith, M., Golwala, S. R., Hall, J., Harms, S. A. S., Harris, K., Hassan, N., Hong, Z., Hoppe, E. W., Hsu, L., Huber, M. E., Iyer, V., Jardin, D., Kashyap, V. K. S., Keller, S. T. D., Kelsey, M. H., Kennard, K. T., Kubik, A., Kurinsky, N. A., Lee, M., Leyva, J., Liu, J., Liu, Y., Loer, B., Asamar, E. Lopez, Lukens, P., MacFarlane, D. B., Mahapatra, R., Mammo, J. S., Mast, N., Mayer, A. J., Theenhausen, H. Meyer zu, Michaud, É., Michielin, E., Mirabolfathi, N., Mirzakhani, M., Mohanty, B., Monteiro, D., Nelson, J., Neog, H., Novati, V., Orrell, J. L., Osborne, M. D., Oser, S. M., Pandey, L., Pandey, S., Partridge, R., Pedreros, D. S., Peng, W., Perna, L., Perry, W. L., Podviianiuk, R., Poudel, S. S., Pradeep, A., Pyle, M., Rau, W., Reid, E., Ren, R., Reynolds, T., Rios, M., Roberts, A., Robinson, A. E., Ryan, J. L., Saab, T., Sadek, D., Sadoulet, B., Sahoo, S. P., Saikia, I., Sander, J., Sattari, A., Schmidt, B., Schnee, R. W., Scorza, S., Serfass, B., Simchony, A., Sincavage, D. J., Sinervo, P., Street, J., Sun, H., Tanner, E., Terry, G. D., Toback, D., Verma, S., Villano, A. N., von Krosigk, B., Watkins, S. L., Wen, O., Williams, Z., Wilson, M. J., Winchell, J., Wykoff, K., Yellin, S., Young, B. A., Yu, T. C., Zatschler, B., Zatschler, S., Zaytsev, A., Zhang, E., Zheng, L., Zuniga, A., and Zurowski, M. J.

Subjects
High Energy Physics - Experiment, Astrophysics - Cosmology and Nongalactic Astrophysics, Physics - Instrumentation and Detectors
Abstract

This article presents constraints on dark-matter-electron interactions obtained from the first underground data-taking campaign with multiple SuperCDMS HVeV detectors operated in the same housing. An exposure of 7.63 g-days is used to set upper limits on the dark-matter-electron scattering cross section for dark matter masses between 0.5 and 1000 MeV/$c^2$, as well as upper limits on dark photon kinetic mixing and axion-like particle axioelectric coupling for masses between 1.2 and 23.3 eV/$c^2$. Compared to an earlier HVeV search, sensitivity was improved as a result of an increased overburden of 225 meters of water equivalent, an anticoincidence event selection, and better pile-up rejection. In the case of dark-matter-electron scattering via a heavy mediator, an improvement by up to a factor of 25 in cross-section sensitivity was achieved., Comment: 7 pages + title and references, 4 figures, and 1 table

Published
2024

19. Integrated Sensing and Communications for Resource Allocation in Non-Terrestrial Networks

Author

Leyva-Mayorga, Israel, Saggese, Fabio, Li, Lintao, and Popovski, Petar

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

The integration of Non-Terrestrial Networks (NTNs) with Low Earth Orbit (LEO) satellite constellations into 5G and Beyond is essential to achieve truly global connectivity. A distinctive characteristic of LEO mega-constellations is that they constitute a global infrastructure with predictable dynamics, which enables the pre-planned allocation of the radio resources. However, the different bands that can be used for ground-to-satellite communication are affected differently by atmospheric conditions such as precipitation, which introduces uncertainty on the attenuation of the communication links at high frequencies. Based on this, we present a compelling case for applying integrated sensing and communications (ISAC) in heterogeneous and multi-layer LEO satellite constellations over wide areas. Specifically, we present an ISAC framework and frame structure to accurately estimate the attenuation in the communication links due to precipitation, with the aim of finding the optimal serving satellites and resource allocation for downlink communication with users on ground. The results show that, by dedicating an adequate amount of resources for sensing and solving the association and resource allocation problems jointly, it is feasible to increase the average throughput by 59% and the fairness by 600% when compared to solving these problems separately., Comment: Submitted for publication to IEEE Transactions on Wireless Communications

Published
2024

20. An open source Multi-Agent Deep Reinforcement Learning Routing Simulator for satellite networks

Author

Lozano-Cuadra, Federico, Thorsager, Mathias D., Leyva-Mayorga, Israel, and Soret, Beatriz

Subjects
Computer Science - Machine Learning, Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

This paper introduces an open source simulator for packet routing in Low Earth Orbit Satellite Constellations (LSatCs) considering the dynamic system uncertainties. The simulator, implemented in Python, supports traditional Dijkstra's based routing as well as more advanced learning solutions, specifically Q-Routing and Multi-Agent Deep Reinforcement Learning (MA-DRL) from our previous work. It uses an event-based approach with the SimPy module to accurately simulate packet creation, routing and queuing, providing real-time tracking of queues and latency. The simulator is highly configurable, allowing adjustments in routing policies, traffic, ground and space layer topologies, communication parameters, and learning hyperparameters. Key features include the ability to visualize system motion and track packet paths. Results highlight significant improvements in end-to-end (E2E) latency using Reinforcement Learning (RL)-based routing policies compared to traditional methods. The source code, the documentation and a Jupyter notebook with post-processing results and analysis are available on GitHub.

Published
2024

22. Addressing Missing Data Due to COVID-19: Two Early Childhood Case Studies

Author

Avi Feller, Maia C. Connors, Christina Weiland, John Q. Easton, Stacy B. Ehrlich, John Francis, Sarah E. Kabourek, Diana Leyva, Anna Shapiro, and Gloria Yeomans-Maldonado

Abstract

One part of COVID-19's staggering impact on education has been to suspend or fundamentally alter ongoing education research projects. This article addresses how to analyze the simple but fundamental example of a multi-cohort study in which student assessment data for the final cohort are missing because schools were closed, learning was virtual, and/or assessments were canceled or inconsistently collected due to COVID-19. We argue that current best-practice recommendations for addressing missing data may fall short in such studies because the assumptions that underpin these recommendations are violated. We then provide a new, simple decision-making framework for empirical researchers facing this situation and provide two empirical examples of how to apply this framework drawn from early childhood studies, one a cluster randomized trial and the other a descriptive longitudinal study. Based on this framework and the assumptions required to address missing data, we advise against the standard recommendation of adjusting for missing outcomes (e.g., via imputation or weighting). Instead, we generally recommend changing the target quantity by restricting to fully observed cohorts or by pivoting to focusing on an alternative outcome. [This is the online first version of an article published in "Journal of Research on Educational Effectiveness."]

Published
2024
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23. OpenPiton4HPC: Optimizing OpenPiton Toward High-Performance Manycores

Author

Leyva, Neiel, Monemi, Alireza, Oliete-Escuín, Noelia, López-Paradís, Guillem, Abancens, Xabier, Balkind, Jonathan, Vallejo, Enrique, Moretó, Miquel, and Alvarez, Lluc

Subjects
Engineering, Electrical Engineering, Electronics, Sensors and Digital Hardware, Multicore processing, Optimization, Memory management, Circuits and systems, Random access memory, Program processors, Bandwidth, Many-core, network-on-chip, optimization, OpenPiton, RISC-V, Electrical engineering
Published
2024

24. Planning for Mobility Justice in Los Angeles: Client Project for Our Streets Action Committee

Author

Angon, Zeltzin, Becerra, Yesenia, Chacon, Genevieve, Donovan, Michael, Fisher, Kimberly, Leyva, Joanny, Lopez, Jessica, Mutoni, Divine, Nahl, William D, Ong, Dominique, Ortega, Dilia, Swint, Rebecca S, Shockley, Kelsey, Teves, Cristina, and Ventura, Ariella

Abstract

This report offers starting points for fulfilling objectives identified by Our Streets Action Committee (OSAC), a Los Angeles-based coalition of organizations focused on transportation equity and mobility justice.The report is organized around four topics:1. Indicators of Mobility (In)Justice explores data tools for visualizing the infrastructure and safety deficits we know overburden many of Los Angeles’ communities of color and low-income neighborhoods.2. Change in Paradigm: Reparative Models of Engagement lays out the shift needed to move urban planning from an extractive practice to a reparative one that builds regenerative cities, as well as examples of how planners and community organizations are accelerating this transition.3. The Funding Analysis examines how the region funds Los Angeles’ street infrastructure development and maintenance and suggests directions for increasing priority investments.4. Political Strategy for Mobility Organizing offers analysis of Los Angeles City Councilmembers’ voting records on mobility issues, along with analysis of opportunities for strategic organizing toward equitable and just mobility improvements.

Published
2024

25. Continual Deep Reinforcement Learning for Decentralized Satellite Routing

Author

Lozano-Cuadra, Federico, Soret, Beatriz, Leyva-Mayorga, Israel, and Popovski, Petar

Subjects
Computer Science - Machine Learning, Computer Science - Information Theory
Abstract

This paper introduces a full solution for decentralized routing in Low Earth Orbit satellite constellations based on continual Deep Reinforcement Learning (DRL). This requires addressing multiple challenges, including the partial knowledge at the satellites and their continuous movement, and the time-varying sources of uncertainty in the system, such as traffic, communication links, or communication buffers. We follow a multi-agent approach, where each satellite acts as an independent decision-making agent, while acquiring a limited knowledge of the environment based on the feedback received from the nearby agents. The solution is divided into two phases. First, an offline learning phase relies on decentralized decisions and a global Deep Neural Network (DNN) trained with global experiences. Then, the online phase with local, on-board, and pre-trained DNNs requires continual learning to evolve with the environment, which can be done in two different ways: (1) Model anticipation, where the predictable conditions of the constellation are exploited by each satellite sharing local model with the next satellite; and (2) Federated Learning (FL), where each agent's model is merged first at the cluster level and then aggregated in a global Parameter Server. The results show that, without high congestion, the proposed Multi-Agent DRL framework achieves the same E2E performance as a shortest-path solution, but the latter assumes intensive communication overhead for real-time network-wise knowledge of the system at a centralized node, whereas ours only requires limited feedback exchange among first neighbour satellites. Importantly, our solution adapts well to congestion conditions and exploits less loaded paths. Moreover, the divergence of models over time is easily tackled by the synergy between anticipation, applied in short-term alignment, and FL, utilized for long-term alignment., Comment: 30 pages, 11 figures

Published
2024

26. End-to-End Delivery in LEO Mega-constellations and the Reordering Problem

Author

Frederiksen, Rasmus Sibbern, Mulvad, Thomas Gundgaard, Leyva-Mayorga, Israel, Madsen, Tatiana Kozlova, and Chiariotti, Federico

Subjects
Computer Science - Networking and Internet Architecture
Abstract

Low Earth orbit (LEO) satellite mega-constellations with hundreds or thousands of satellites and inter-satellite links (ISLs) have the potential to provide global end-to-end connectivity. Furthermore, if the physical distance between source and destination is sufficiently long, end-to-end routing over the LEO constellation can provide lower latency when compared to the terrestrial infrastructure due to the faster propagation of electromagnetic waves in space than in optic fiber. However, the frequent route changes due to the movement of the satellites result in the out-of-order delivery of packets, causing sudden changes to the Round-Trip Time (RTT) that can be misinterpreted as congestion by congestion control algorithms. In this paper, the performance of three widely used congestion control algorithms, Cubic, Reno, and BBR, is evaluated in an emulated LEO satellite constellation with Free-Space Optical (FSO) ISLs. Furthermore, we perform a sensitivity analysis for Cubic by changing the satellite constellation parameters, length of the routes, and the positions of the source and destination to identify problematic routing scenarios. The results show that route changes can have profound transient effects on the goodput of the connection, posing problems for typical broadband applications., Comment: Submitted to IEEE PIMRC Workshops 2024

Published
2024

27. Intelligent Duty Cycling Management and Wake-up for Energy Harvesting IoT Networks with Correlated Activity

Author

Ruíz-Guirola, David E., López, Onel L. A., Montejo-Sánchez, Samuel, Mayorga, Israel Leyva, Han, Zhu, and Popovski, Petar

Subjects
Electrical Engineering and Systems Science - Systems and Control, Computer Science - Artificial Intelligence
Abstract

This paper presents an approach for energy-neutral Internet of Things (IoT) scenarios where the IoT devices (IoTDs) rely entirely on their energy harvesting capabilities to sustain operation. We use a Markov chain to represent the operation and transmission states of the IoTDs, a modulated Poisson process to model their energy harvesting process, and a discrete-time Markov chain to model their battery state. The aim is to efficiently manage the duty cycling of the IoTDs, so as to prolong their battery life and reduce instances of low-energy availability. We propose a duty-cycling management based on K- nearest neighbors, aiming to strike a trade-off between energy efficiency and detection accuracy. This is done by incorporating spatial and temporal correlations among IoTDs' activity, as well as their energy harvesting capabilities. We also allow the base station to wake up specific IoTDs if more information about an event is needed upon initial detection. Our proposed scheme shows significant improvements in energy savings and performance, with up to 11 times lower misdetection probability and 50\% lower energy consumption for high-density scenarios compared to a random duty cycling benchmark.

Published
2024

28. Effects of marine biofloc on the metabolism, hematology, and antioxidant capacity of juvenile red tilapia (Oreochromis sp.) fed commercial diets containing different protein levels

Author

Martinez-Montano, Emmanuel, de Oca, Gustavo Alejandro Rodriguez-Montes, Roman-Reyes, Jose Cristobal, Gomez-Avila, Edgar, Castaneda-Farias, Daniel, Frias-Espericueta, Martin Gabriel, Salazar-Leyva, Jesus Aaron, Hernandez, Crisantema, Lopez-Peraza, Diana Judith, and Banuelos-Vargas, Isaura

Published
2024
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29. Seasonal anestrus of sheep flocks

Author

Barron-Gonzalez, Jose E., Avila-Castillo, Bias R., Salinas-Martinez, Jesus A., Gonzalez-Avalos, Jose, Olave-Leyva, Jose I., and Posadas-Dominguez, Rodolfo R.

Published
2024

45. Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry

Author

Jitendra PS. Sawhney, Veerappa A. Kothiwale, Vikas Bisne, Rajashekhar Durgaprasad, Praveen Jadhav, Manoj Chopda, Velam Vanajakshamma, Ramdhan Meena, Govindan Vijayaraghavan, Kamaldeep Chawla, Jagan Allu, Karen S. Pieper, A. John Camm, Ajay K. Kakkar, Jean-Pierre Bassand, David A. Fitzmaurice, Samuel Z. Goldhaber, Shinya Goto, Sylvia Haas, Werner Hacke, Lorenzo G. Mantovani, Frank Misselwitz, Alexander G.G. Turpie, Martin van Eickels, Freek W.A. Verheugt, Gloria Kayani, Keith A.A. Fox, Bernard J. Gersh, Hector Lucas Luciardi, Harry Gibbs, Marianne Brodmann, Frank Cools, Antonio Carlos Pereira Barretto, Stuart J. Connolly, Alex Spyropoulos, John Eikelboom, Ramon Corbalan, Dayi Hu, Petr Jansky, Jørn Dalsgaard Nielsen, Hany Ragy, Pekka Raatikainen, Jean-Yves Le Heuzey, Harald Darius, Matyas Keltai, Sanjay Kakkar, Jitendra Pal Singh Sawhney, Giancarlo Agnelli, Giuseppe Ambrosio, Yukihiro Koretsune, Carlos Jerjes Sánchez Díaz, Hugo Ten Cate, Dan Atar, Janina Stepinska, Elizaveta Panchenko, Toon Wei Lim, Barry Jacobson, Seil Oh, Xavier Viñolas, Marten Rosenqvist, Jan Steffel, Pantep Angchaisuksiri, Ali Oto, Alex Parkhomenko, Wael Al Mahmeed, David Fitzmaurice, D.Y. Hu, K.N. Chen, Y.S. Zhao, H.Q. Zhang, J.Z. Chen, S.P. Cao, D.W. Wang, Y.J. Yang, W.H. Li, Y.H. Yin, G.Z. Tao, P. Yang, Y.M. Chen, S.H. He, Ying Wang, Yong Wang, G.S. Fu, X. Li, T.G. Wu, X.S. Cheng, X.W. Yan, R.P. Zhao, M.S. Chen, L.G. Xiong, P. Chen, Y. Jiao, Y. Guo, L. Xue, F.Z. Wang, H. Li, Z.M. Yang, C.L. Bai, J. Chen, J.Y. Chen, X. Chen, S. Feng, Q.H. Fu, X.J. Gao, W.N. Guo, R.H. He, X.A. He, X.S. Hu, X.F. Huang, B. Li, J. Li, L. Li, Y.H. Li, T.T. Liu, W.L. Liu, Y.Y. Liu, Z.C. Lu, X.L. Luo, T.Y. Ma, J.Q. Peng, X. Sheng, X.J. Shi, Y.H. Sun, G. Tian, K. Wang, L. Wang, R.N. Wu, Q. Xie, R.Y. Xu, J.S. Yang, L.L. Yang, Q. Yang, Y. Ye, H.Y. Yu, J.H. Yu, T. Yu, H. Zhai, Q. Zhan, G.S. Zhang, Q. Zhang, R. Zhang, Y. Zhang, W.Y. Zheng, B. Zhou, Z.H. Zhou, X.Y. Zhu, S. Kakkar, J.P.S. Sawhney, P. Jadhav, R. Durgaprasad, A.G. Ravi Shankar, R.K. Rajput, K. Bhargava, R. Sarma, A. Srinivas, D. Roy, U.M. Nagamalesh, M. Chopda, R. Kishore, G. Kulkarni, P. Chandwani, R.A. Pothiwala, M. Padinhare Purayil, S. Shah, K. Chawla, V.A. Kothiwale, B. Raghuraman, G. Vijayaraghavan, V.M. Vijan, G. Bantwal, V. Bisne, A. Khan, J.B. Gupta, S. Kumar, D. Jain, S. Abraham, D. Adak, A. Barai, H. Begum, P. Bhattacharjee, M. Dargude, D. Davies, B. Deshpande, P. Dhakrao, V. Dhyani, S. Duhan, M. Earath, A. Ganatra, S. Giradkar, V. Jain, R. Karthikeyan, L. Kasala, S. Kaur, S. Krishnappa, A. Lawande, B. Lokesh, N. Madarkar, R. Meena, P. More, D. Naik, K. Prashanth, M. Rao, N.M. Rao, N. Sadhu, D. Shah, M. Sharma, P. Shiva, S. Singhal, S. Suresh, V. Vanajakshamma, S.G. Panse, Y. Koretsune, S. Kanamori, K. Yamamoto, K. Kumagai, Y. Katsuda, K. Sadamatsu, F. Toyota, Y. Mizuno, I. Misumi, H. Noguchi, S. Ando, T. Suetsugu, M. Minamoto, Hiroshi Oda, K. Shiraishi, S. Adachi, K. Chiba, H. Norita, M. Tsuruta, T. Koyanagi, H. Ando, T. Higashi, K. Okada, S. Azakami, S. Komaki, K. Kumeda, T. Murayama, J. Matsumura, Y. Oba, R. Sonoda, K. Goto, K. Minoda, Y. Haraguchi, H. Suefuji, H. Miyagi, H. Kato, Tadashi Nakamura, Tsugihiro Nakamura, H. Nandate, R. Zaitsu, Yoshihisa Fujiura, A. Yoshimura, H. Numata, J. Ogawa, H. Tatematsu, Y. Kamogawa, K. Murakami, Y. Wakasa, M. Yamasawa, H. Maekawa, S. Abe, H. Kihara, S. Tsunoda, Katsumi Saito, Kazuyuki Saito, T. Fudo, K. Obunai, H. Tachibana, I. Oba, T. Kuwahata, S. Higa, M. Gushiken, T. Eto, H. Yoshida, D. Ikeda, Yoshitake Fujiura, M. Ishizawa, M. Nakatsuka, K. Murata, C. Ogurusu, M. Shimoyama, M. Akutsu, I. Takamura, F. Hoshino, N. Yokota, T. Iwao, K. Tsuchida, M. Takeuchi, Y. Hatori, Y. Kitami, Yoichi Nakamura, R. Oyama, M. Ageta, Hiroyuki Oda, Y. Go, K. Mishima, T. Unoki, S. Morii, Yuhei Shiga, H. Sumi, T. Nagatomo, K. Sanno, K. Fujisawa, Y. Atsuchi, T. Nagoshi, T. Seto, T. Tabuchi, M. Kameko, K. Nii, K. Oshiro, H. Takezawa, S. Nagano, N. Miyamoto, M. Iwaki, Yuichiro Nakamura, M. Fujii, M. Okawa, Masahiko Abe, Masatake Abe, Mitsunori Abe, T. Saito, T. Mito, K. Nagao, J. Minami, T. Mita, I. Sakuma, T. Taguchi, S. Marusaki, H. Doi, M. Tanaka, T. Fujito, M. Matsuta, T. Kusumoto, S. Kakinoki, K. Ashida, N. Yoshizawa, J. Agata, O. Arasaki, M. Manita, M. Ikemura, S. Fukuoka, H. Murakami, S. Matsukawa, Y. Hata, T. Taniguchi, T. Ko, H. Kubo, M. Imamaki, M. Akiyama, M. Inagaki, H. Odakura, T. Ueda, Y. Katsube, A. Nakata, H. Watanabe, M. Techigawara, M. Igarashi, K. Taga, T. Kimura, S. Tomimoto, M. Shibuya, M. Nakano, K. Ito, T. Seo, S. Hiramitsu, H. Hosokawa, M. Hoshiai, M. Hibino, K. Miyagawa, Hajime Horie, N. Sugishita, Yukio Shiga, A. Soma, K. Neya, Tetsuro Yoshida, Tomoki Yoshida, M. Mizuguchi, M. Ishiguro, T. Minagawa, M. Wada, H. Mukawa, F. Okuda, S. Nagasaka, Y. Abe, Sen Adachi, Susumu Adachi, T. Adachi, K. Akahane, T. Amano, K. Aoki, T. Aoyama, H. Arai, S. Arima, T. Arino, H. Asano, T. Asano, J. Azuma, T. Baba, T. Betsuyaku, H. Chibana, H. Date, J. Doiuchi, Y. Emura, M. Endo, Y. Fujii, R. Fujiki, A. Fujisawa, Y. Fujisawa, T. Fukuda, T. Fukui, N. Furukawa, T. Furukawa, W. Furumoto, T. Goto, M. Hamaoka, N. Hanazono, K. Hasegawa, T. Hatsuno, Y. Hayashi, K. Higuchi, K. Hirasawa, H. Hirayama, M. Hirose, S. Hirota, M. Honda, Hideki Horie, T. Ido, O. Iiji, H. Ikeda, K. Ikeda, K. Ikeoka, M. Imaizumi, H. Inaba, T. Inoue, F. Iseki, A. Ishihara, N. Ishioka, N. Ito, T. Iwase, H. Kakuda, J. Kamata, H. Kanai, H. Kanda, M. Kaneko, H. Kano, T. Kasai, T. Kato, Y. Kato, Y. Kawada, K. Kawai, K. Kawakami, S. Kawakami, T. Kawamoto, S. Kawano, J. Kim, T. Kira, H. Kitazawa, H. Kitazumi, T. Kito, T. Kobayashi, T. Koeda, J. Kojima, H. Komatsu, I. Komatsu, Y. Koshibu, T. Kotani, T. Kozuka, Y. Kumai, T. Kumazaki, I. Maeda, K. Maeda, Y. Maruyama, S. Matsui, K. Matsushita, Y. Matsuura, K. Mineoi, H. Mitsuhashi, N. Miura, S. Miyaguchi, S. Miyajima, H. Miyamoto, A. Miyashita, S. Miyata, I. Mizuguchi, A. Mizuno, T. Mori, O. Moriai, K. Morishita, O. Murai, Sho Nagai, Shunichi Nagai, E. Nagata, H. Nagata, A. Nakagomi, S. Nakahara, M. Nakamura, R. Nakamura, N. Nakanishi, T. Nakayama, R. Nakazato, T. Nanke, J. Nariyama, Y. Niijima, H. Niinuma, Y. Nishida, Y. Nishihata, K. Nishino, H. Nishioka, K. Nishizawa, I. Niwa, K. Nomura, S. Nomura, M. Nozoe, T. Ogawa, N. Ohara, M. Okada, K. Okamoto, H. Okita, M. Okuyama, H. Ono, T. Ono, Y. Onuki Pearce, S. Oriso, A. Ota, E. Otaki, Y. Saito, H. Sakai, N. Sakamoto, Y. Sakamoto, Y. Samejima, Y. Sasagawa, H. Sasaguri, A. Sasaki, T. Sasaki, Kazuki Sato, Kiyoharu Sato, M. Sawano, S. Seki, Y. Sekine, Y. Seta, K. Sezaki, N. Shibata, Y. Shiina, H. Shimono, Y. Shimoyama, T. Shindo, H. Shinohara, R. Shinohe, T. Shinozuka, T. Shirai, T. Shiraiwa, Y. Shozawa, T. Suga, C. Sugimoto, Kazuo Suzuki, Keita Suzuki, Shu Suzuki, Shunji Suzuki, Susumu Suzuki, Y. Suzuki, M. Tada, A. Taguchi, T. Takagi, Y. Takagi, K. Takahashi, S. Takahashi, H. Takai, C. Takanaka, S. Take, H. Takeda, K. Takei, K. Takenaka, T. Tana, G. Tanabe, K. Taya, H. Teragawa, S. Tohyo, S. Toru, Y. Tsuchiya, T. Tsuji, K. Tsuzaki, H. Uchiyama, O. Ueda, Y. Ueyama, N. Wakaki, T. Wakiyama, T. Washizuka, M. Watanabe, T. Yamada, T. Yamagishi, H. Yamaguchi, Kenichi Yamamoto, Kentaro Yamamoto, Kunihiko Yamamoto, T. Yamamoto, M. Yamaura, M. Yamazoe, K. Yasui, Y. Yokoyama, K. Yoshida, T.W. Lim, C.K. Ching, C.G. Foo, J.H. Chow, D.D. Chen, F.R. Jaufeerally, Y.M. Lee, G. Lim, W.T. Lim, S. Thng, S.Y. Yap, C. Yeo, S. Oh, H.N. Pak, J.-B. Kim, J.H. Kim, S.-W. Jang, D.H. Kim, D.R. Ryu, S.W. Park, D.-K. Kim, D.J. Choi, Y.S. Oh, M.-C. Cho, S.-H. Kim, H.-K. Jeon, D.-G. Shin, J.S. Park, H.K. Park, S.-J. Han, J.H. Sung, J.-G. Cho, G.-B. Nam, Y.K. On, H.E. Lim, J.J. Kwak, T.-J. Cha, T.J. Hong, S.H. Park, J.H. Yoon, N.-H. Kim, K.-S. Kim, B.C. Jung, G.-S. Hwang, C.-J. Kim, D.B. Kim, J.J. Ahn, H.J. An, H. Bae, A.L. Baek, W.J. Chi, E.A. Choi, E.H. Choi, H.K. Choi, H.S. Choi, S. Han, E.S. Heo, K.O. Her, S.W. Hwang, E.M. Jang, H.-S. Jang, S. Jang, H.-G. Jeon, S.R. Jeon, Y.R. Jeon, H.K. Jeong, I.-A. Jung, Hyeon Jeong Kim, Hyun Ju Kim, Ji Seon Kim, Jung Sook Kim, J.A. Kim, K.T. Kim, M.S. Kim, Sang Hee Kim, Sang Hyun Kim, Y.-I. Kim, C.S. Lee, E.H. Lee, G.H. Lee, H.Y. Lee, H.-Y. Lee, K.H. Lee, K.R. Lee, M.S. Lee, M.-Y. Lee, R.W. Lee, S.E. Lee, S.H. Lee, S. Lee, W.Y. Lee, I.K. Noh, A.R. Park, B.R. Park, H.N. Park, J.H. Park, M. Park, Y. Park, S.-Y. Seo, J. Shim, J.H. Sim, Y.M. Sohn, W.S. Son, Y.S. Son, H.J. Song, H.K. Wi, J.J. Woo, S. Ye, K.H. Yim, K.M. Yoo, E.J. Yoon, S.Y. Yun, P. Angchaisuksiri, S. Chawanadelert, P. Mongkolwongroj, K. Kanokphatcharakun, S. Cheewatanakornkul, T. Laksomya, S. Pattanaprichakul, T. Chantrarat, S. Rungaramsin, S. Silaruks, W. Wongcharoen, K. Siriwattana, K. Likittanasombat, P. Katekangplu, W. Boonyapisit, D. Cholsaringkarl, B. Chatlaong, P. Chattranukulchai, Y. Santanakorn, P. Hutayanon, P. Khunrong, T. Bunyapipat, S. Jai-Aue, P. Kaewsuwanna, P. Bamungpong, S. Gunaparn, S. Hongsuppinyo, R. Inphontan, R. Khattaroek, K. Khunkong, U. Kitmapawanont, C. Kongsin, B. Naratreekoon, S. Ninwaranon, J. Phangyota, A. Phrommintikul, P. Phunpinyosak, K. Pongmorakot, S. Poomiphol, N. Pornnimitthum, S. Pumprueg, S. Ratchasikaew, K. Sanit, K. Sawanyawisuth, B. Silaruks, R. Sirichai, A. Sriwichian, W. Suebjaksing, P. Sukklad, T. Suttana, A. Tangsirira, O. Thangpet, W. Tiyanon, Y. Vorasettakarnkij, T. Wisaratapong, W. Wongtheptien, A. Wutthimanop, S. Yawila, A. Oto, A. Altun, I. Ozdogru, K. Ozdemir, O. Yilmaz, A. Aydinlar, M.B. Yilmaz, E. Yeter, Z. Ongen, M. Cayli, H. Pekdemir, M. Ozdemir, M. Sucu, T. Sayin, M. Demir, H. Yorgun, M. Ersanli, E. Okuyan, D. Aras, H. Abdelrahman, O. Aktas, D. Alpay, F. Aras, M.F. Bireciklioglu, S. Budeyri, M. Buyukpapuc, S. Caliskan, M. Esen, M.A. Felekoglu, D. Genc, B. Ikitimur, E.B. Karaayvaz, S. Kılıç Karataş, S. Okutucu, E. Ozcelik, A. Quisi, H. Sag, L. Sahiner, B.Y. Sayin, T. Seker, D. Uzun Alkan, E. Yildirim, R. Yildirim, F. Yilmaz, V. Yuksekdag, H.L. Luciardi, N. Vensentini, A.C. Ingaramo, G.A. Sambadaro, V. Fernandez Caputi, S.G. Berman, P. Dragotto, A.J. Kleiban, N. Centurion, G. Giacomi, R.A. Ahuad Guerrero, D. Conde, G. Zapata, L.A. Di Paola, J.L. Ramos, R.D. Dran, J. Egido, A.A. Fernandez, M.J. Fosco, S. Sassone, V.A. Sinisi, L.R. Cartasegna, M.A. Berli, O.A. Gomez Vilamajo, F. Ferroni, E.D. Alaguibe, A. Alvarez D'Amelio, C. Arabetti, L. Arias, J.A. Belardi, L. Bergesio, F. Berli, M. Berli, S. Borchowiec, C. Buzzetti, R. Cabrini, V. Campisi, A.L. Cappi, R. Carrizo, F. Colombo Berra, J.P. Costabel, O.J.A. Costamagna, A.A. Damonte, I.N. De Urquiza, F. Diez, M.F. 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Dumikyan, S. Erofeeva, E. Gorbunova, T. Gorshkova, A. Gubanov, M. Gurmach, Y. Ivanova, T. Kolesova, D. Konyushenko, O. Korneeva, O. Kropova, P. Kuchuk, O. Kungurtseva, T. Kupriyanova, B. Kurylo, M. Kuvanova, O. Lebedeva, E. Lileeva, O. Machilskaya, T. Medvedeva, G. Monako, I. Motylev, G. Nagibovich, E. Novikova, Y. Orlov, Y. Osmolovskaya, A. Ovsannikova, D. Platonov, S. Rachkova, O. Sinitsina, S. Speshilova, O. Suslova, A. Ushakov, O. Volodicheva, O. Zemlianskaia, I. Zhirov, E. Zhuravleva, I. Zotova, X. Viñolas, P. Alvarez Garcia, M.F. López Fernández, L. Tercedor, S. Tranche Iparraguirre, P. Torán Monserrat, E. Márquez Contreras, J. Isart Rafecas, J. Motero Carrasco, P. García Pavía, C. Gómez Pajuelo, C. Moro Serrano, L.F. Iglesias Alonso, A. Grande Ruiz, J. Mercé Klein, J.R. Gonzalez Juanatey, G. Barón Esquivias, I. Monte Collado, H. Palacín Piquero, C. Brotons Cuixart, M. Rodríguez Morató, J. Bayo I Llibre, C. Corros Vicente, M. Vida Gutierrez, F. Epelde Gonzalo, C.A. Almeida Fernández, N. Del Val Plana, E. Escrivá Montserrat, J.J. Montero Alía, M. Barreda González, M.A. Moleiro Oliva, J. Iglesias Sanmartín, M. Jiménez González, M. Rodriguez Álvarez, J. Herreros Melenchon, T. Ripoll Vera, F. Ridocci Soriano, L. Garcia Riesco, M.D. Marco Macian, J. Quiles Granado, M. Jimenez Navarro, J. Cosin Sales, J.V. Vaquer Perez, M. Vazquez Caamano, M.F. Arcocha Torres, G. Marcos Gomez, A. Iñiguez Romo, M.A. Prieto Diaz, Carmela Alonso, Concepcion Alonso, D. Alvarez, M. Alvarez, M. Amaro, N. Andere, J. Aracil Villar, R. Armitano Ochoa, A. Austria, S. Barbeira, E. Barraquer Feu, A. Bartes, V. Becerra Munoz, F.J. Bermudez Jimenez, A. Branjovich Tijuan, J. Cabeza Ramirez, M. Cabrera Ramos, E. Calvo Martinez, M. Campo Moreno, G. Cancho Corchado, M. Casanova Gil, M. Castillo Orive, D. Castro Fernandez, M. Cebollada del Misterio, R. Codinachs Alsina, A. Cortada Cabrera, J. Costa Pinto Prego de Faria, S. Costas, M.I. Cotilla Marco, M. Dachs, C.M. Diaz Lopez, A. Domenech Borras, A. Elorriaga Madariaga, A. Espallargas, M. Fernandez, E. Fernandez Escobar, E. Fernandez Mas, A. Ferrer, J. Fosch, M. Garcia Bermudez, V. Garcia Millan, M. Gavira Saenz, C. Gines Garcia, C. Gomez, Y. Gomez Perez, A. Gonzales Segovia, P. Gonzalez, L. Grigorian, A. Guerrero Molina, M. del C. Gutierrez del Val, B. Herrero Maeso, E. Hevia Rodriguez, A. Iglesias Garcia, M.J. Jimenez Fernandez, B. Jimeno Besa, P. Juan Salvadores, M.B. Lage Bouzamayor, I. Lasuncion, L.E. Lezcano Gort, M. Llobet Molina, M. Lopez, A. Manzanal Rey, J. Mara Guerra, S. Marcus, A. Martin Vila, M. Martinez Mena, P. Mazon, F. Mendez Zurita, G. Millán, M. Molina, P. Montero Alia, D. Montes, M. Moure Gonzalez, R.B. Munoz Munoz, A. Negrete Palma, H.N. Orellana Figueroa, V.M. Ortega, C. Ortiz Cortes, D. Otero Tomera, N. Palomo Merchan, I. Pareja Ibar, E. Pena Garcia, M. Pereda Armayor, M. Perez Carasa, I. Prieto, V. Quintern, R. Renom, L.M. Rincon Diaz, V. Rios, L. Riquelme Sola, R. Rivera, X. Robiro Robiro, M. Roca, C. Roca Saumell, C. Rodrigo, E. Rodriguez, M. Rodriguez Garcia, S. Saez Jimenez, P. Sanchez Calderon, L. Sanchez Mendez, S. Sanchez Parra, C. Santolaya, M.R. Senan Sanz, A. Seoane Blanco, E. Serralvo, N. Sierra, C. Simon Valero, J. Sorribes Lopez, M. Teixido Fontanillas, M. Terns Riera, G. Tobajas, C. Torres, J. Torres Marques, M. Ubeda Pastor, M. Rosenqvist, A. Wirdby, J. Linden, K. Henriksson, M. Elmersson, A. Egilsson, U. Börjesson, G. Svärd, B. Liu, A. Lindh, L.-B. Olsson, M. Gustavsson, Lars Andersson, Lisbeth Andersson, L. Benson, C. Bothin, A. Hajimirsadeghi, K. Kadir, M. Ericsson, A. Ohlsson, H. Lindvall, P. Svensson, K. Thorne, H. Handel, P. Platonov, B. Eriksson, I. Timberg, K. Romberg, M. Crisby, J.-E. Karlsson, S.A. Jensen, A. Andersson, L. Malmqvist, B. Martinsson, F. Bernsten, J. Engdahl, J. Thulin, A. Hot-Bjelac, P. Stalby, H. Aaröe, E. Ahbeck, H. Ahlmark, F. Al-Khalili, G. Bonkowski, S. Dzeletovic, A.-B. Ekstrand, G.-B. Eriksson, K. Floren, C. Grässjö, S. Hahn, P. Jaensson, B. Jansson, J.-H. Jansson, R.-M. Kangert, A. Koch, D. Kusiak, A. Lettenström, A. Lindberg, C.-J. Lindholm, A. Mannermyr, K. Mansson, M. Millborg, C. Nilsson, A.-M. Ohlin, A. Olofsson, A. Osberg, A. Pedersen, K. Risbecker, K. Rosenberg, J. Samuelsson, M. Shayesteh, K. Skoglund, M. Stjernberg, C. Thorsen, J. Steffel, J.H. Beer, J. Debrunner, D. Amstutz, J. Bruegger, G. Elise, A. Grau, A. Guinand, I. Henriette, E. Saga, S. Winnik, A. Parkhomenko, I. Rudyk, V. Tseluyko, O. Karpenko, S. Zhurba, I. Kraiz, I. Kupnovytska, N. Serediuk, Y. Mostovoy, O. Ushakov, O. Koval, I. Kovalskyi, Y. Svyshchenko, O. Sychov, M. Stanislavchuk, O. Kraydashenko, A. Yagensky, S. Tykhonova, I. Fushtey, R. Belegai, G. Berko, L. Burdeuna, O. Chabanna, I. Daniuk, A. Ivanov, E. Kamenska, P. Kaplan, O. Khyzhnyak, S. Kizim, O. Matova, O. Medentseva, V. Mochonyi, M. Mospan, V. Nemtsova, T. Ovdiienko, O. Palamarchuk, M. Pavelko, R. Petrovskyy, D. Plevak, O. Proshak, S. Pyvovar, L. Rasputina, O. Romanenko, O. Romanova, A. Sapatyi, O. Shumakov, R. Stets, L. Todoriuk, V. Varenov, D. Fitzmaurice, N. Chauhan, D. Goodwin, P. Saunders, R. Evans, J. Leese, P.S. Jhittay, A. Ross, M.S. Kainth, G. Pickavance, J. McDonnell, A. Williams, T. Gooding, H. Wagner, S. Suryani, A. Singal, S. Sircar, R. Bilas, P. Hutchinson, A. Wakeman, M. Stokes, N. Paul, M. Aziz, C. Ramesh, P. Wilson, S. Franklin, S. Fairhead, J. Thompson, V. St Joseph, G. Taylor, D. Tragen, D. Seamark, C. Paul, M. Richardson, A. Jefferies, H. Sharp, H. Jones, C. Giles, M. Page, O. Oginni, J. Aldegather, S. Wetherwell, W. Lumb, P. Evans, F. Scouller, N. Macey, Y. Stipp, R. West, S. Thurston, P. Wadeson, J. Matthews, P. Pandya, A. Gallagher, T. Railton, B. Sinha, D. Russell, J.A. Davies, P. Ainsworth, C.P. Jones, P. Weeks, J. Eden, D. Kernick, W. Murdoch, L. Lumley, R.P. Patel, S.W. Wong, M. Saigol, K. Ladha, K. Douglas, D.F. Cumberlidge, C. Bradshaw, G. Van Zon, K.P. Jones, M.J. Thomas, E. Watson, B. Sarai, N. Ahmad, W. Willcock, J. Cairns, S. Sathananthan, N. de Kare-Silver, A. Gilliland, E. Strieder, A. Howitt, B. Vishwanathan, N. Bird, D. Gray, M. Clark, J. Bisatt, J. Litchfield, E. Fisher, T. Fooks, A.R. Kelsall, E. Alborough, J. Wakeling, M. Parfitt, K. Milne, S. Rogers, R. Priyadharshan, J.L. Oliver, E. Davies, S. Abushal, M. Jacobs, C. Hutton, N.I. Walls, R. Thompson, C. Chigbo, S.M.A. Zaidi, M. Howard, K.C. Butter, S. Barrow, H. Little, I.U. Haq, L. Gibbons, S. Glencross, A.J. McLeod, K. Poland, C. Mulholland, A. Warke, P. Conn, G. Burns, R.N. Smith, S. Lowe, R. Kamath, H.S. Dau, J. Webster, I. Hodgins, S. Vercoe, P.C. Roome, H. Pinnock, J.R.A. Patel, A. Ali, N. Hart, R. Davies, E. Stuart, C.A. Neden, M. Danielsen, R. Heath, P. Sharma, S. Galloway, C. Hawkins, R. Oliver, M. Aylward, S. Mannion, M. Braddick, D. Edwards, A.C. Rothwell, A. Sabir, F. Choudhary, S. Khalaque, A. Wilson, S. Peters, W. Coulson, N. Roberts, A. Heer, S. Coates, B. Ward, D. Jackson, S. Walton, D. Shepherd, M. Sterry, T. Wong, M. Boon, R. Bunney, R. Haria-Shah, R.T. Baron, S. Davies, T. Schatzberger, N. Hargreaves, T. Stephenson, H. Choi, R. Batson, L. Lucraft, T. Myhill, S. Estifano, D. Geatch, J. Wilkinson, R. Veale, K. Forshaw, T. Davies, K. Zaman, P. Vinson, C. Liley, M. Bandrapalli, P. McGinty, R. Wastling, P. McEleny, A. Beattie, P. Cooke, M. Wong, J. Gunasegaram, M. Pugsley, S. Ahmad, C. A'Court, J. Ayers, J. Bennett, S. Cartwright, S. Dobson, C. Dooldeniya, A. Flynn, R. Fox, J. Goram, A. Halpin, A. Hay, P. Jacobs, L. Jeffers, L. Lomax, I. Munro, R. Muvva, M. Nadaph, K. Powell, S. Randfield, D. Redpath, R. Reed, M. Rickenbach, G. Rogers, P.B. Saunders, C. Seamark, J. Shewring, P. Simmons, H. Simper, H. Stoddart, A. Sword, N. Thomas, A. Thomson, H. Gibbs, A. Blenkhorn, B. Singh, W. Van Gaal, W. Abhayaratna, R. Lehman, P. Roberts-Thomson, J. Kilian, D. Coulshed, A. Catanchin, D. Colquhoun, H. Kiat, D. Eccleston, J. French, L. Zimmett, B. Ayres, T. Phan, P. Blombery, D. Crimmins, D. O'Donnell, A. Choi, P. Astridge, M. Arstall, N. Jepson, M. Binnekamp, A. Lee, J. Rogers, G. Starmer, P. Carroll, J. Faunt, A. Aggarwala, L. Barry, C. Batta, R. Beveridge, A. Black, M. Bonner, J. Boys, E. Buckley, M. Campo, L. Carlton, A. Connelly, B. Conway, D. Cresp, H. Dimitri, S. Dixon, M. Dolman, M. Duroux, M. Eskandari, R. Eslick, A. Ferreira-Jardim, T. Fetahovic, D. Fitzpatrick, R. Geraghty, J. Gibbs, T. Grabek, M.H. Modi, K. Hayes, M.P. Hegde, L. Hesketh, B. Hoffmann, B. Jacobson, K. Johnson, C. Juergens, I. Kassam, V. Lawlor, M. Lehman, S. Lehman, D. Leung, S. Mackay, M. MacKenzie, C. McCarthy, C. McIntosh, L. McKeon, H. Morrison, C. Mussap, J.-D. Myers, V. Nagalingam, G. Oldfield, V. O'May, J. Palmer, L. Parsons, K. Patching, T. Patching, V. Paul, M. Plotz, S. Preston, H. Rashad, M. Ratcliffe, S. Raynes, J. Rose, L. Sanders, M. Seremetkoska, H. Setio, S. Shone, P. Shrestha, C. Singh, C. Singleton, N. Stoyanov, S. Sutcliffe, K. Swaraj, J. Tarrant, S. Thompson, I.M. Tsay, M. Vorster, A. Waldman, L. Wallis, E. Wilford, K. Wong, S.J. Connolly, A. Spyropoulos, J. Eikelboom, R. Luton, M. Gupta, A.S. Pandey, S. Cheung, R. Leader, P. Beaudry, F. Ayala-Paredes, J. Berlingieri, J. Heath, G. Poirier, M. Du Preez, R. Nadeau, G. Dresser, R. Dhillon, T. Hruczkowski, B. Schweitzer, B. Coutu, P. Angaran, P. MacDonald, S. Vizel, S. Fikry, R. Parkash, A. Lavoie, J. Cha, B. Ramjattan, J. Bonet, K. Ahmad, L. Aro, T. Aves, K. Beaudry, C. Bergeron, J. Bigcanoe, N. Bignell, L. Breakwell, E. Burke, L. Carroll, B. Clarke, T. Cleveland, S. Daheb, P. Dehghani, I. Denis, Z. Djaidani, P. Dorian, S. Douglass, J. Dunnigan, A. Ewert, D. Farquhar, A. Fearon, L. Ferleyko, D. Fournier, B. Fox, M.-C. Grenier, W. Gulliver, K. Haveman, C. Hines, K. Hines, A.M. Jackson, C. Jean, G. Jethoo, R. Kahlon, S. Kelly, R. Kim, V. Korley, J. Kornder, L. Kwan, J. Largy, C. Lewis, S. Lewis, I. Mangat, R. Moor, J. Navratil, I. Neas, J. Otis, R. Otis, M. Pandey, F. Petrie, A. Pinter, M. Raines, P. Roberts, M. Robinson, G. Sas, S. Schulman, L. Snell, S. Spearson, J. Stevenson, T. Trahey, S. Wong, D. Wright, H. Ragy, A. Abd El-Aziz, S.K. Abou Seif, M.G. El Din, S. El Etriby, A. Elbahry, A. El-Etreby, M. Elkhadem, A. Katta, T. Khairy, A. Mowafy, M. Nawar, A. Ohanissian, A. Reda, M. Reda, H. Salem, N. Sami, S. Samir, M. Setiha, M. Sobhy, A. Soliman, N. Taha, M. Tawfik, E. Zaatout, D. Kettles, J. Bayat, H. Siebert, A. Horak, Y. Kelfkens, R. Garda, T. Pillay, M. Guerra, L. van Zyl, H. Theron, A. Murray, R. Louw, D. Greyling, P. Mntla, V. Ueckermann, R. Loghdey, S. Ismail, F. Ahmed, J. Engelbrecht, A. Ramdass, S. Maharajh, W. Oosthuysen, G. Angel, C. Bester, M. Booysen, C. Boshoff, C. Cannon, S. Cassimjee, C. Chami, G. Conway, A. Davids, L. de Meyer, G. Du Plessis, T. Ellis, L. Henley, M. Karsten, E. Loyd, J. Marks, L. Mavhusa, M. Mostert, A. Page, L. Rikhotso, M. Salie, J. Sasto, F. Shaik, A. Skein, L. Smith, G. Tarr, T. Tau, F. van Zyl, W. Al Mahmeed, G. Yousef, A. Agrawal, M. Nathani, M. Ibrahim, E.M. Esheiba, R. Singh, A. Naguib, M. Abu-Mahfouz, M. Al Omairi, A. Al Naeemi, R. Maruthanayagam, N. Bazargani, A. Wassef, R. Gupta, M. Khan, B. Subbaraman, A. Abdul, A. Al Mulla, S. El Bardisy, P. Haridas, S. Jadhav, K. Magdaluyo, M. Makdad, I. Maqsood, R. Mohamed, N. Sharma, R. Sharma, M. Thanzeel, S.Z. Goldhaber, R. Canosa, P. Rama, E. Blumberg, J. Garcia, P. Mullen, V. Wilson, A. Quick, K. Ferrick, W.M. Kutayli, M. Cox, M. Franco, S. Falkowski, R. Mendelson, M. Williams, S. Miller, S. Beach, A. Alfieri, T. Gutowski, I. Haque, R. Reddy, W. Ahmed, P. Delafontaine, D. Diercks, D. Theodoro, K. Remmel, M. Alberts, R. Ison, H. Noveck, P. Duffy, S. Pitta, D. Nishijima, C. Treasure, N. Asafu-Adjaye, K. Ball, M. Bartlett, M. Bentley, S. Bowers, A. Brown, A. Browne, J. Cameron-Watts, M. Canova, D. Cassidy, K. Cervellione, S. Congal, J. DePauw, A. Dickerson, M. Eley, L. Evans, S. Felpel, K. Ferdinand, D. Fielder, P. Gentry, A. Haideri, F. Hakimi, T. Harbour, E. Hartranft, B. Hawkins, M. Headlee, L. Henson, C. Herrick, T. Hicks, S. Jasinski, A. Jones, L. Jones, P. Jones, S. Karl, M. Keeling, J. Kerr, P. Knowles, J. Langdon, M. Lay, J.A. Lee, T. Lincoln, E. Malone, A. Merliss, D. Merritt, J. Minardo, B. Mooso, C. Orosco, V. Palumbo, M. Parker, T. Parrott, S. Paserchia, G. Pearl, J. Peterson, N. Pickelsimer, T. Purcell, J. Raynor, S. Raziano, C. Richard, T. Richardson, C. Robertson, A. Sage, T. Sanghera, P. Shaw, J. Shoemaker, K. Smith, B. Stephanie, A. Thatcher, H. Theobald, N. Thompson, L. Treasure, T. Tripti, C. Verdi, and V. Worthy

Subjects
Surgery, RD1-811, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background: The Global Anticoagulant Registry in the FIELD–Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. Methods and results: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012–2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P

Published
2018
Full Text
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46. Mapping Literacies in the Tourism Labor Market: A Cross-Database Comparison

Author

Leyva, Eddy Soria, Mateu, Aida Valls, and Lara, Ana Beatriz Hernandez

Subjects
Computer Science - Digital Libraries
Abstract

This book chapter conducts a comparative bibliometric analysis of literacies in the tourism labor market, drawing from the Web of Science (WoS) and Scopus databases. The objective is to assess scientific outputs and identify key patterns of scientific collaboration. Findings suggest a statistically significant difference between the two databases with an overlap level of 35.71%. However, there is a gradual and correlated increase in the number of publications over time. Scopus stands out for its broader impact and enduring citation relevance, suggesting its academic contributions have a longer-lasting effect. Conversely, WoS is characterized by a focus on more recent influential publications and exhibits a marginally more intense collaboration network.

Published
2024

47. A fuzzy framework for unraveling experiential tourism value

Author

Leyva, Eddy Soria, Lara, Ana Beatriz Hernández, Mateu, Aïda Valls, and Vivar, Jorge Luis Mariño

Subjects
Mathematics - General Mathematics
Abstract

There is currently a growing interest in the study of sustainable tourism experiences. Although the main dimensions of tourism experiences are known, the assessment of attractions as a key component in sustainable tourism design has seen little research. This gap stems from two primary challenges: firstly, the complexity of each tourism destination, which makes use of heterogeneous scales of evaluation; and secondly, the subjective nature of tourism experiences that requires qualitative measurement scales and assessment. To overcome these shortcomings, a new methodology based on fuzzy numbers is proposed, consisting of a scale normalization stage, followed by an aggregation of the fuzzy numbers that can be integrated into a Geographical Information System. This technique is tested on the quantification of the tourism value of attractions for sustainable experience in Santiago de Cuba.

Published
2024

48. Capillary imbibition in lubricant coated channels

Author

Leyva, Sergi G., Pagonabarraga, Ignacio, Hernández-Machado, Aurora, and Ledesma-Aguilar, Rodrigo

Subjects
Physics - Fluid Dynamics, Condensed Matter - Soft Condensed Matter
Abstract

Capillary imbibition underpins many processes of fundamental and applied relevance in fluid mechanics. A limitation to the flow is the coupling to the confining solid, which induces friction forces. Our work proposes a general theoretical framework for the modeling of the transport of liquids in lubricant impregnated surfaces. We show that for sufficiently small lubricant viscosity, dissipation entirely occurs in the lubricant layer, resulting in a linear growth of the advancing front. As a result, an external force gives rise to an exponential front growth. This new capacity to control multiphase flows sets new experimental challenges that can be determinant for micro and nanofluidic devices.

Published
2024

49. Regressing Transformers for Data-efficient Visual Place Recognition

Author

Leyva-Vallina, María, Strisciuglio, Nicola, and Petkov, Nicolai

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Visual place recognition is a critical task in computer vision, especially for localization and navigation systems. Existing methods often rely on contrastive learning: image descriptors are trained to have small distance for similar images and larger distance for dissimilar ones in a latent space. However, this approach struggles to ensure accurate distance-based image similarity representation, particularly when training with binary pairwise labels, and complex re-ranking strategies are required. This work introduces a fresh perspective by framing place recognition as a regression problem, using camera field-of-view overlap as similarity ground truth for learning. By optimizing image descriptors to align directly with graded similarity labels, this approach enhances ranking capabilities without expensive re-ranking, offering data-efficient training and strong generalization across several benchmark datasets., Comment: Accepted for publication in ICRA 2024

Published
2024

50. A taxonomy for generalized synchronization between flat-coupled systems

Author

Letellier, Christophe, Minati, Ludovico, Sendina-Nadal, Irene, and Leyva, I.

Subjects
Nonlinear Sciences - Chaotic Dynamics
Abstract

Generalized synchronization is plausibly the most complex form of synchronization. Previous studies have revealed the existence of weak or strong forms of generalized synchronization depending on the multi- or mono-valued nature of the mapping between the attractors of two unidirectionally-coupled systems. Generalized synchronization is here obtained by coupling two systems with a flat control law. Here, we demonstrate that the corresponding first-return maps can be topologically conjugate in some cases. Conversely, the response map can foliated while the drive map is not. We describe the corresponding types of generalized synchronization, explicitly focusing on the influence of the coupling strength when significantly different dimensions or dissipation properties characterize the coupled systems. A taxonomy of generalized synchronization based on these properties is proposed., Comment: 17 pages, 19 figures, submitted to PRE

Published
2024

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