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RV.S2.C1.V5 Modificar Emplazamiento
No full textVídeos docents de l'assignatura Representació Arquitectònica II (REVIT) impartida per Isidro Navarro, PDI de l'ETSA
Self-assembled charge-complementary hydrogel with sustained release of antimicrobial peptides for periodontitis treatment
No full textPeriodontitis is a pathogenic microbial-infected disease where immune dysregulation promotes chronic inflammation and excessive osteoclast activity, causing progressive tissue destruction. Current therapeutic approaches face challenges in achieving sustained drug release in periodontal pockets. In this study, we construct a self-assembled peptide hydrogel by combining negatively charged peptide amphiphile (PA) with positively charged antimicrobial peptide GL13K, namely PA/GL13K. GL13K electrostatically binds to self-assembled PA nanofibers, promoting PA self-assembly that yields a denser hydrogel network. This structural reinforcement enables sustained GL13K release. The PA/GL13K hydrogel demonstrates potent antibacterial effects and immunomodulatory properties, suppressing pro-inflammatory M1 macrophage polarization while promoting anti-inflammatory M2 macrophage activation. Moreover, the PA/GL13K hydrogel inhibits osteoclast differentiation in vitro. In an experimental periodontitis mouse model, local periodontal injection of the PA/GL13K hydrogel reduced inflammatory infiltration and osteoclast-mediated bone resorption, effectively mitigating periodontal tissue destruction. These findings suggest that the self-assembled peptide hydrogel system may represent a potential multifunctional therapeutic approach for periodontal treatment.Y.L. acknowledges support from the National Natural Science Foundation of China (NSFC, 82401109) and Seed Fund for PI Research of the University of Hong Kong. Z.Y. acknowledges support from the National Natural Science Foundation of China (NSFC, 82401187), the Innovation and Technology Fund (ITS/307/22), and the International Association for Dental Research (IADR) Innovation in Oral Care Awards. IBEC is a member of the CERCA Programme/Generalitat de Catalunya.Postprint (published version
Approccio tecnologico alla progettazione sostenibile del patrimonio ordinario
No full textThis paper presents a teaching experience carried out within the Architectural Technology course in the second year of the Architecture degree programme, focused on the energy and functional retrofitting of the Spirito Santo neighbourhood in Enna, considered as ordinary built heritage. The project activity aimed to promote a conscious and integrated design approach, combining technological, environmental and social aspects. Starting from a critical analysis of the existing buildings—marked by high thermal losses, obsolete construction solutions and limited passive performance—students developed multi-scale intervention strategies involving the building envelope, interior spatial organisation and outdoor spaces. Particular attention was paid to functional redistribution in relation to solar orientation, the reactivation of urban voids and the improvement of universal accessibility, with the goal of enhancing both energy performance and neighbourhood identity.Postprint (published version
Tema 2 (D): Passiu
No full textEn el passiu trobem les deutes a llarg termini de l'empresa que es comptabilitzaran en el passiu no corrent i les deutes a curt termini en el passiu corrent. En el passiu corrent trobarem els instruments financers i comptes que tinguin el seu origen en el tràfic de l'empresa, així com els comptes amb les administracions públiques
Data, statistics, and language: Exploring similarities in data processing and analysis for decision support on Unmanned Aerial Vehicle (UAV) and Care Unit Intensive (CUI) cases
No full textOne of the main language objectives is to decipher the information that is transmitted in order to be understood, interpreted, and react to the message. On the other hand, when talking about data analysis, algorithms are applied that manage to decipher the collected information making it possible to address almost all potential problems or situations that may have arisen in the world, either in the present or in the past. The main objective when deciphering this information is to create new opportunities to prevent or propose solutions to different types of situations. However, it can be argued that one’s perspective on a problem and its possible solution may be influenced by previous experiences or limited by a lack thereof. Consequently, data analysis is challenged to identify and recognize patterns and correlations (decipher) within data through algorithms like statistical/machine learning, among others. In this way, the idea that data analysis is also the language of data is introduced. The data has meaning and, depending on the context, can help to know the status of structures, patients, or processes with the primary objective to make predictions and/or forecasts. Two seemingly dissimilar fields are presented, but they converge on a common point in the pursuit of a solution. They are structural health monitoring (SHM) and decision support for medical staff in the intensive care unit (ICU). In SHM field, damage
detection problems will be addressed utilizing different types of signals collected from an unmanned aerial vehicle (UAV). In the context of the ICU, the main objective is to know if patients with Coronavirus Disease 2019 (COVID-19) should be intubated or to know the neurological prognosis of patients with subarachnoid hemorrhage pathology. In both fields, data are stored for further analysis, where concepts such as descriptive statistic, statistics, hypothesis testing, correlation analysis, resampling, and models based on statistical or machine learning methods, among others are employed. Many times, a simple solution using basic statistical concepts has enabled the development of data analysis techniques. Finally, the methods developed in each field have facilitated the creation of predictive models for decision-making processes. Along with these models, quality indices such as accuracy, precision, recall, specificity, among others allow the results to be objectively evaluated and compared, adjusting them
according to the required result. Data language deciphering in the field of SHM enables the early detection of damage. In the ICU context, it allows developing powerful decision support tools that permit experts to operate with greater ranges of reliability
and efficacy and with less uncertainty to identify and develop solutions. In conclusion, the objective of this work is to disseminate the fundamental aspects of these research and outline the nuances of decision-making associated with each specific case. In each of these fields, issues related to interpretability, the emergence of neologisms, and dialectal variations, along with basic statistical concepts and the help of
ML and SL methods, played a prominent role in solving real-world situations.Peer ReviewedPreprin
Enhancing hardwater treatment using ultra-loose nanofiltration membranes modified with novel MOF nanoparticles
No full textNanomaterial incorporation has emerged as a powerful strategy to tune membrane permeability, selectivity and durability. In this study, ultra-loose polyamide nanofiltration membranes were fabricated by interfacial polymerisation of m-phenylenediamine and trimesoyl chloride on a commercial polyacrylonitrile substrate. Different configurations of UiO-66-NH2 and ZIF-8-NH2 nanoparticles were incorporated. Before membrane fabrication, nanoparticles characterization techniques confirmed nanoparticle synthesis and polyamide formation, and evaluated how nanoparticle type, configuration, and concentration influenced morphology, hydrophilicity, pore size, and separation. The aim was to understand how these structural modifications affect water permeability and hardness removal from surface waters. Active layer morphology and roughness differed clearly between configurations: membranes with nanoparticles in the interlayer had more irregular, textured surfaces, while those with nanoparticles in the active layer were smoother with visible particle deposition. ZIF-8-NH2–modified membranes were more hydrophilic (contact angle 52°) than those with UiO-66-NH2 (71°). All membranes had similar zeta-potential behaviour with isoelectric point (IEP) near pH 4.7, except M5—which combined ZIF-8-NH2 in the active layer and UiO-66-NH2 in the interlayer—showing lower IEP (pH 3.7), more negative surface charge, and the best overall performance. In addition, M5 increased permeability from 0.16 to 3.20 L/m2·h·bar and substantially improved ion rejection—Mg2+ by 107%, Ca2+ by 137%, and SO42- by 101% compared with the control membrane. In addition, the average pore size was reduced by 26% and hydrophilicity was enhanced, lowering the contact angle from 86° to 40°. Overall, these improvements highlight the promise of modified NF membranes for efficient hardness removal in drinking water treatment.This research was supported by the Development of upcycling approaches in the agri-food and process industries to promote on-site and sustainable chemicals production (Upcycling) project (PID2023-147160OB-C21), financed by the Spanish Research Agency (AEI). This work is funded by the AGAUR-FI predoctoral program (2023 FI-100056) Joan Oró, supported by the Secretariat of Universities and Research under the Department of Research and Universities of the Generalitat de Catalunya. Additionally, the authors acknowledge the support of the Catalan Government through the R2EM group (2021-SGR-GRC-00596) and PSEP group (2021-SGR-01042). Moreover, this work was carried out within the framework of the Multiscale Center of Excellence, funded by the María de Maeztu Program for Units of Excellence (CEX2023-001300-M), supported by MCIN/AEI/Ministerio de Universidades, Spain. Finally, J.L. Cortina was also recognised through the “ICREA Academia” recognition for excellence in research funded by the Generalitat de Catalunya.Peer ReviewedPostprint (published version
Substepped and advected subdomain methods for part-scale LPBF modeling
No full textThis work presents substepping schemes for part-scale Laser Powder Bed Fusion (LPBF) modeling where the computational domain is divided into a fast partition with a small time-step and a slow one using a large time-step. These schemes are of special interest due to the disparity of time scales present in LPBF applications, which renders simulation prohibitively expensive unless simplifications are made. A Robin–Robin substepper is proposed and compared to the scheme proposed by Hodge (2021). Additionally, the introduction of an advected subdomain in the fast partition is proposed. This approach was first presented in Slimani et al. (2024) and allows for larger time-steps, as the problem in the Heat Affected Zone (HAZ) is posed in the moving reference frame of the laser, where the thermal field is significantly steadier than in the fixed frame. These methods are used in combination to obtain a computationally efficient scheme for LPBF thermal simulations. The proposed methods are implemented in FEniCSx. Their strengths and weaknesses are evaluated through 2D benchmarks, comparison with experimental melt pool data, and 3D LPBF simulations.Michele Chiumenti gratefully acknowledges financial support from the Spanish Ministry of Science, Innovation and Universities through the R+D project ‘‘Desarrollo de un gemelo digital para monitorización el control activo del proceso de fabricación aditiva DED (DIGITAM)’’ (Ref. CPP2023-010440), as well as from the Center for Technological Development and Innovation (CDTI) through the R+D project ‘‘Machine Learning Driven Metal Additive Manufacturing By Direct Energy Deposition For Repairing Operations (MALE4RAM)’’. Mehdi Slimani is grateful to the FEniCSx project and its community for providing an actively developed open-source FEM platform and for their consistently helpful and responsive support.Peer ReviewedPostprint (published version
Implementació en Raspberry Pi d'un sistema de predicció de paraules per a pacients neurodegeneratius basat en xarxes neuronals
No full textL’ús de sistemes de predicció de veu en pacients que han perdut part de la parla degut a una malaltia neurodegenerativa pot suposar una millora significativa de la seva comunicació. Ara bé, el disseny i implementació d’aquest tipus de predictors sovint implica construir solucions costoses a nivell computacional i econòmic. En aquest Treball de Final de Màster es presenta la implementació d’un predictor de paraules individuals basat en xarxes neuronals sobre un mini-ordinador Raspberry Pi. L’algorisme de predicció va ser desenvolupat prèviament com a part d’un Treball de Final de Grau, i en aquest projecte s’ha adaptat i optimitzat per a ser executat eficientment en un sistema embegut de baix cost. El sistema està dissenyat per a ser emprat en un entorn domèstic per part de persones de suport (familiars o cuidadors). La persona afectada disposa d’un micròfon de solapa instal·lat sobre la roba, mentre que la captura d’àudio i l’inici de la predicció es controla mitjançant una API local accessible des d’un dispositiu extern. Un cop enregistrat l’àudio, el processament i la inferència es duen a terme localment a la Raspberry Pi, i la paraula predita s’envia a la interfície de l’API per poder ser visualitzada. Després d’una fase d’optimització, s’ha aconseguit reduir la latència de predicció fins els 90 ± 20 ms, demostrant així que és possible implementar un predictor funcional i eficient en un dispositiu de baix cost, apte per al seu ús en un context pràctic
Modelat de sistemes tipus Mecanoviga MVH i MVV pels reforços de forjats: comportament global i unions crítiques
No full textAquest Treball de Fi de Grau se centra en el desenvolupament d’una eina de càlcul estructural orientada a l’anàlisi dels sistemes Mecanoviga, utilitzats habitualment en el reforç d’estructures existents. Aquests sistemes modulars permeten una adaptació flexible a diferents configuracions geomètriques i estats de càrrega, però presenten particularitats estructurals que requereixen una anàlisi acurada tant del comportament global com del comportament local de les unions. En una primera fase del treball s’ha desenvolupat una eina pròpia de càlcul global basada en Python i Excel, que permet automatitzar l’avaluació d’esforços interns, deformacions i verificacions normatives segons la teoria de la resistència de materials. Aquesta eina facilita l’anàlisi sistemàtica de diferents configuracions de bigues, llums i càrregues, reduint considerablement el temps necessari respecte a un procés de càlcul manual. Tanmateix, el càlcul global no és suficient per descriure amb precisió el comportament estructural complet del sistema, ja que no permet capturar els mecanismes resistents locals que es produeixen a les unions singulars. Per aquest motiu, el treball incorpora una segona fase d’anàlisi basada en la simulació avançada de les unions mitjançant el programari IdeaStatiCa, que utilitza el mètode CBFEM per modelitzar plaques, cargols pretensats i ancoratges. L’anàlisi conjunta del càlcul global i de la simulació local permet identificar quins elements governen realment el disseny del sistema. Els resultats mostren que, per als casos analitzats, el dimensionament no està controlat per la resistència del perfil metàl·lic, sinó pel comportament de les unions, especialment les unions de solapament, fet que justifica plenament l’ús d’eines de simulació específiques. Finalment, el treball conclou que la combinació d’un càlcul global automatitzat amb una anàlisi local detallada constitueix un enfocament adequat i eficient per a l’estudi dels sistemes Mecanoviga. L’eina desenvolupada presenta una aplicabilitat directa en l’àmbit professional del càlcul estructural i estableix una base sòlida per a futures ampliacions i millores