Urban Invisibility: The Right to the City from a Feminine Perspective

The urban experience of women in São Paulo reflects the complexities of urban space and gender dynamics in Brazil's largest city. Women face significant challenges, from precarious mobility to unequal access to public services and unsafe urban spaces. Socioeconomic disparities exacerbate these difficulties, highlighting the intersectionality of their identities. Fully understanding these experiences is essential for developing more inclusive and equitable public policies. This article emphasizes the need for comprehensive analysis that recognizes the diverse realities of women in the City of São Paulo and promotes a safer, fairer, and more equal urban environment for all. Keywords: Feminist urbanism, right to the city, feminine right to the city, urban inequality. Topic: Public space and urban design in the contemporary metropolis.A vivência urbana feminina em São Paulo reflete as complexidades do espaço urbano e das dinâmicas de gênero na maior cidade do Brasil. Mulheres enfrentam desafios significativos, desde mobilidade precária até acesso desigual a serviços públicos e espaços urbanos inseguros. Disparidades socioeconômicas acentuam essas dificuldades, destacando a interseccionalidade de suas identidades. Compreender plenamente essas experiências é essencial para desenvolver políticas públicas mais inclusivas e equitativas. Este artigo destaca a necessidade de uma análise abrangente que reconheça as diversas realidades das mulheres na Cidade de São Paulo e promova um ambiente urbano mais seguro, justo e igualitário para todas. Palavras chave: Urbanismo feminista, direito a cidade, direito a cidade feminina, desigualdade urbana. Bloco temático: Espaço público e projeto urbano na metrópole contemporânea.Peer Reviewe

Instalación de sistemas de comunicaciones para la gestión de iluminación, seguridad y climatización en un hangar del Aeropuerto de Lleida-Alguaire

The main objective of this project is to optimize the communication system of a hangar for the management of lighting, security, and climate control systems at Lleida-Alguaire Airport. This will include the integration of all these functions into an intelligent management system, enabling real-time monitoring and control of each system, while also reducing energy consumption and long-term operational costs, in line with the airport's philosophy of sustainability and efficiency. To achieve these objectives, we will conduct a detailed study of all aspects of the installation, from lighting systems to access control mechanisms and climate control. We will compare the most current technologies available on the market to identify and evaluate those that best meet our needs. Additionally, we will prepare detailed plans of the installations, along with the specific calculations required for each system.El objetivo principal de este proyecto es optimizar el sistema de comunicaciones de un hangar para la gestión de los sistemas de iluminación, seguridad y climatización del Aeropuerto de Lleida- Alguaire. Esto incluirá la integración de todas estas funciones en un sistema de gestión inteligente. Que nos permitirá monitorizar y controlar cada sistema en tiempo real, además de reducir el consumo energético y los costes operativos a largo plazo, siguiendo siempre la filosofía del aeropuerto de sostenibilidad y eficiencia. Para conseguir estos objetivos, haremos un estudio detallado de todas las partes de la instalación, desde los sistemas de iluminación hasta los mecanismos de control de accesos y climatización. Compararemos las tecnologías más actuales del mercado, para identificar y valorar cuáles se ajustan mejor a nuestras necesidades. Además, elaboraremos planos detallados de las instalaciones, junto con los cálculos específicos necesarios para cada sistema.Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i Infraestructur

CIÈNCIA I TECNOLOGIA DELS MATERIALS (Examen final, 1r quadrimestre)

2024/20251r quadrimestr

A sliding-mode control in a new reference frame for three-phase UPFR with extended control range

This article presents a new switching strategy for a unity power factor rectifier (UPFR) using sliding-mode control (SMC). The traditional SMC in the natural frame suffers from a cross-coupling problem among controllers due to the neutral point voltage. To address this issue, a nonlinear transformation is applied to obtain the voltages and currents in a new 2-D reference frame. Based on the transformed variables, a nonlinear model is derived, and two different sliding-mode surfaces are designed using hysteresis band comparators. The nonlinear transformation is based on a switching strategy that not only avoids the cross-coupling problem but also injects a third harmonic in the control signal, providing an extended control range. As a result, a SMC is designed, providing relevant properties such as output voltage robustness, fast transient response against sudden load changes, and grid-voltage sags. Experimental results are provided to validate the theoretical contributions of this article.This work was supported in part by I+D+i PID2021-122835OB-C21 research project through MCIN/AEI/ 10.13039/501000011033 and FEDER “Una manera de hacer Europa.”Peer ReviewedPostprint (published version

INFORMÀTICA | FINAL

Final2424-20251r quadrimestr

FONAMENTS DE LA MATEMÀTICA | FINAL

FinalResolved2424-20251r quadrimestr

SPANISH

Theoretical and operational research, of guidelines development, instruments and projective devices for the organization, projection and sustainable management of the territory, at three different scales (macro, meso, micro) emerging from the analytical studies of characterization and assessment of Landscape Units, registered through landscape catalogs to develop a Green Infrastructure Program that provides ecosystem services and improves risk management, urban resilience and the restoration of degraded ecosystems due to the advance of new urbanizations that have altered the City Landscape of Rio Ceballos, weakening its natural, cultural and heritage values, hidden by the dynamic of transformation of the territory, putting the ecological and social structure at risk. Finally, projective operations of new operational landscapes are tested, as a hybridization between ecology and technique that reorganize and conduct energy and matter, leading to new combinations and territorial potentials.Investigación teórica y operativa, de elaboración de lineamientos, instrumentos y dispositivos proyectuales para el ordenamiento, proyectación y gestión sostenible del territorio, en tres diferentes escalas, (macro, meso, micro) emergentes de los estudios analíticos de caracterización y valoración de Unidades de Paisaje, registrados a través de los catálogos de paisajes para elaborar un Programa de Infraestructura Verde que brinde servicios ecosistémicos y mejoren la gestión de riesgos, la resiliencia urbana y la restauración de ecosistemas degradados debido al avance de nuevas urbanizaciones que ha alterado el Paisaje de la Ciudad de Rio Ceballos, debilitando sus valores naturales, culturales y que hacen a su patrimonio, ocultos por la dinámica de transformación del territorio, poniendo en riesgo la estructura ecológica y social, Finalmente se ensayan operaciones proyectuales de nuevos paisajes operativos, como una hibridación entre ecología y técnica que reorganizan y conducen energía y materia, dando lugar a nuevas combinaciones y potencialidades territoriales.Peer Reviewe

On many-objective feature selection and the need for interpretability

Big data comes with the challenge of containing irrelevant and redundant information (i.e., features). Given that a single objective cannot fully capture a feature’s relevance, a Many-Objective Feature Selection (MOFS) approach able to accommodate various relevant perspectives is preferred for identifying the most appropriate features in a given context. However, MOFS produces a large set of solutions whose interpretability has been largely overlooked. First, we demonstrate the relevance of MOFS and establish its necessity by considering up to six objectives using a genetic algorithm and Naive Bayes on ten datasets for classification tasks. Then, we propose a novel methodology to improve the interpretability of MOFS results in order to support the data scientist in selecting the subset of features pertinent to their use case. Our methodology is instantiated as an intuitive and interactive dashboard that provides insights into the results beyond the pure numerical representation of the objectives being considered and evaluated with 50 participants. The outcome shows that it addresses the need for a methodological approach and comprehensive visualization to achieve interoperability.The project leading to this publication has received funding from the European Commission under the European Union’s Horizon 2020 research and innovation program (grant agreement No. 955895). Moreover, A. Abelló and B. Bilalli are funded by the Spanish Ministerio de Ciencia e Innovación under project PID2020-117191RB-I00, funding scheme AEI/10.13039/501100011033. G. Bontempi is supported by the Service Public de Wallonie Recherche under grant nr 2010235–ARIAC by DigitalWallonia4.ai. Computational resources have been provided by the Consortium des Équipements de Calcul Intensif, funded by the Fonds de la Recherche Scientifique de Belgique (G.A. No. 2.5020.11) and Walloon Region.Peer ReviewedPostprint (published version

Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing

The Joint Laboratory on Extreme-Scale Computing (JLESC) was initiated at the same time lossy compression for scientific data became an important topic for the scientific communities. The teams involved in the JLESC played and are still playing an important role in developing the research, techniques, methods, and technologies making lossy compression for scientific data a key tool for scientists and engineers. In this paper, we present the evolution of lossy compression for scientific data from 2015, describing the situation before the JLESC started, the evolution of this discipline in the past 8 years (until 2023) through the prism of the JLESC collaborations on this topic and some of the remaining open research questions.This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC , a collaborative effort of two DOE organizations – the Office of Science and the National Nuclear Security Administration, responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, to support the nation’s exascale computing imperative. The material was supported by the U.S. Department of Energy, Office of Science, Advanced Scientific Computing Research (ASCR), under contract DE-AC02-06CH11357 , and supported by the National Science Foundation under Grant OAC-2003709/2303064 , OAC-2104023/2247080 , OAC-2311875/2311876/2311877 , OAC-2312673 , and OAC-2034169 . We acknowledge the computing resources provided on Bebop (operated by the Laboratory Computing Resource Center at Argonne). Some of the experiments presented in this paper were carried out using the PlaFRIM experimental testbed, supported by Inria, CNRS (LABRI and IMB), Université de Bordeaux, Bordeaux INP and Conseil Régional d’Aquitaine (see https://www.plafrim.fr ). TEZip - This work has been supported by the COE research grant in computational science from Hyogo Prefecture and Kobe City through the Foundation for Computational Science. XIOS-SZ - Mario Acosta and Xavier Yepes-Arbós have received co-funding from the State Research Agency through OEMES ( PID2020-116324RA-I00 ).Peer ReviewedArticle signat per 20 autors/es: Franck Cappello (a), Sheng Di (a), Robert Underwood (a), Dingwen Tao (b), Jon Calhoun (c), Yoshii Kazutomo (a), Kento Sato (d), Amarjit Singh (d), Luc Giraud (e), Emmanuel Agullo (e), Xavier Yepes (f), Mario Acosta (f), Sian Jin (b), Jiannan Tian (b), Frédéric Vivien (e), Boyuan Zhang (b), Kentaro Sano (d), Tomohiro Ueno (d), Thomas Grützmacher (g), Hartwig Anzt (g) / (a) Argonne National Laboratory, United States of America; (b) Indiana University, Bloomington, United States of America; (c) Clemson University, United States of America; (d) RIKEN Center for Computational Science, Japan; (e) National Research Institute for Computing and Automation, France; (f) Barcelona Supercomputing Center, Spain; (g) Karlsruhe Institute of Technology, GermanyPostprint (author's final draft