9300 research outputs found
Sort by
Dataset of the work "UBU-Polymers Research Group 28032025"
No full textAntioxidants are used as markers of the functional potential of foods, making their accurate quantification essential for assessing bioactivity and possible health benefits. A smart polymer incorporating 2,2-diphenyl-1-picrylhydrazyl (DPPH) motifs (FDPPH) was synthesized via bulk polymerization of N-vinylpyrrolidone, methyl methacrylate, and a diphenylamine-functionalized monomer, followed by solid-phase reactions to introduce the DPPH functionality. FTIR and thermal analysis confirmed successful synthesis. The FDPPH sensor showed a colorimetric response consistent with DPPH in solution, demonstrating its reliability. Twenty-three beet samples were analyzed using both the conventional DPPH assay and the FDPPH method, where polymer discs were immersed and colour changes recorded via smartphone. The hue (H) parameter in the HSV colour-space showed the highest correlation. Calibration using beet samples was more accurate than with Trolox. The optimal response time was 3 hours, with a LOD and LOQ of 0.063 and 0.191 mmol Trolox/L, respectively.We gratefully acknowledge the financial support provided by all funders. Author S. Vallejos received Grant PID2023-147301OB-I00 and Grant 3101166576-166576-29-325 funded by MICIU/AEI /10.13039/501100011033 and FEDER, EU. The financial support provided by Fondo Europeo de Desarrollo Regional-European Regional Development Fund (FEDER, ERDF) and Regional Government of Castilla y León -Consejería de Educación, Junta de Castilla y León- (BU025P23) is gratefully acknowledged. This work was supported by the Regional Government of Castilla y León (Junta de Castilla y León) and by the Ministry of Science and Innovation MICIN and the European Union NextGenerationEU PRTR. Author Saul Vallejos received grant BG22/00086 funded by Spanish Ministerio de Universidades. J. L. Vallejo-García received the grant PRE2021-09812 funded by MCIN/AEI/ 10.13039/501100011033 and by “ESF Investing in your future”. Author María Gaona-Ruiz received a research assistant contract (UBU-08-B) funded by the Regional Government of Castilla y León
Monitorización de Virus y Resistencias a Antimicrobianos en Aguas Residuales como Estrategia para la Vigilancia en Salud Pública
No full textA lo largo de la historia, han sido numerosas las epidemias y pandemias que han
amenazado la salud del ser humano. A pesar del sentimiento generalizado de su control, hoy en
día las enfermedades infecciosas siguen siendo una de las principales causas de muerte a nivel
mundial, poniendo en riesgo la salud pública. El conocimiento y control de éstas es crucial no
solo desde el punto de vista sanitario, sino también por su impacto económico y social. En los
últimos años, la preocupación por las infecciones víricas se ha acrecentado, debido a las
diferentes situaciones de emergencia generadas por estos patógenos. Una alternativa que
permite el seguimiento continuado e incluso predictivo de agentes infecciosos es la
epidemiología basada en aguas residuales. Esta aproximación se caracteriza por su capacidad
para monitorizar poblaciones, y no individuos aislados, tanto sintomáticos como asintomáticos,
de una manera no invasiva, anónima, económica y rápida. Sin embargo, la ausencia de una
metodología estándar dificulta la comparación entre estudios, por lo que caracterizar las
diferentes alternativas es importante para tener un mayor conocimiento y poder establecer un
protocolo global. Las infecciones entéricas y respiratorias de origen vírico tienen un gran impacto
en nuestra sociedad. Las primeras han sido monitorizadas históricamente en matrices
alimentarias, y las segundas clínicamente. Sin embargo, el estudio de sus agentes etiológicos
mediante aguas residuales es más reciente, especialmente para los segundos. Junto a las
infecciones víricas, la resistencia a antimicrobianos es otra de las grandes amenazas de la
medicina moderna con un importante impacto económico.
En esta tesis doctoral se abordan tres objetivos principales. En primer lugar, caracterizar
la metodología empleada, mediante el uso exhaustivo de controles, para avanzar en la búsqueda
de una metodología universal. En segundo lugar, evaluar la utilidad de la epidemiología basada
en aguas residuales a través del seguimiento de virus de interés para la salud pública, durante
cuatro años consecutivos en dos capitales de Castilla y León (España): Valladolid y Burgos. En
concreto, seis virus entéricos (norovirus pertenecientes a los genogrupos I y II, astrovirus
humano, rotavirus y virus de la hepatitis A y E) y cinco respiratorios (SARS-CoV-2, Virus
Respiratorio Sincitial A y B y Virus de la gripe A y B). Finalmente, se realizó un abordaje para la
identificación de la población bacteriana y los genes de resistencia a antibióticos presentes en
dichas poblaciones.
La metodología empleada para alcanzar los dos primeros objetivos consistió en la
concentración de los virus presentes en las muestras de agua residual, mediante una
precipitación con tricloruro de aluminio, y continuó con la extracción de los ácidos nucleicos para
finalizar con la cuantificación específica de los mismos por RT-qPCR. Para el estudio de la
población bacteriana y de los genes de resistencia a antimicrobianos se realizó un análisis
metagenómico en la Universidad Técnica de Dinamarca (DTU).Historically, several epidemics and pandemics have threatened human health. Despite
the general belief that they were under control, nowadays, infectious diseases continuous
being one of the main causes of death worldwide, setting public health at risk. Their
knowledge and control are crucial, not only from a clinical point of view, but also because
of their economic and social impact. Last years, the concern about viral infections has risen
because of the numerous emergence situations due to these pathogens. An alternative that
allows continuous, even predictive, monitoring of these microorganisms is wastewaterbased
epidemiology. This approach has been generally used to track the consumption of
illicit drugs or medicines, as well as for poliovirus detection. However, the use of this
approach has increased as can be used to detect the novel coronavirus, SARS-CoV-2, in
these types of matrixes. This tool is characterized by its ability to monitor population, not
isolated individuals, including symptomatic and non-symptomatic people, while being
non-invasive, anonymous, affordable and rapid. Nevertheless, the lack of a gold standard
methodology makes the inter-assay comparison still difficult. Consequently, the
characterization of different alternatives is necessary to gain knowledge and be able to
establish a universal protocol. Viral enteric and respiratory infections have a wide impact
on our society. The first has traditionally been monitored in food matrixes, while the
second clinically. However, the surveillance of these etiological agents in wastewater
samples is more recent, especially for respiratory viruses. Along with viral infections,
antimicrobial resistance is another important threat for modern medicine with a big
economic impact.
Three main objectives were addressed in this Ph.D. work. Firstly, the characterization
of the efficiency of the methodology assayed and the factors that can influence it via the
use of exhaustive controls, to foster the implementation of a universal protocol. Secondly,
the evaluation of the use of wastewater-based epidemiology for the surveillance of
different public health concern viruses, in two cities of Castilla y Leon (Spain), Valladolid
and Burgos. Specifically, six enteric (norovirus genogroups I and II, human astroviruses,
rotaviruses and hepatitis A and E viruses) and five respiratory viruses (SARS-CoV-2,
Respiratory Syncytial Virus A and B, and Influenza viruses A and B). Finally, a
characterization of the bacterial population and the antimicrobial resistance determinants
was performed by a metagenomic strategy.Doctorado en Avances en Ciencia y Biotecnología Alimentaria
Low-Strength Concrete with Raw-Crushed Wind Turbine Blade and Coarse Recycled Aggregate
No full textNonselective crushing of wind turbine blades results in raw-crushed wind turbine blade (RCWTB), a material that can be used in concrete production. Wind farm decommissioning can also generate coarse recycled aggregate (CRA) from the demolition of wind turbine concrete footings. This paper proposes a first approach for the joint management of both wastes through their simultaneous use in low-strength concrete, with a target compressive strength of 25 MPa. Mixes with 50% and 100% CRA, and 0% and 10% RCWTB as a cement addition, were designed, with the effect of CRA content not being statistically significant, to analyze its interaction with RCWTB. The results showed that, on the one hand, RCWTB reduced strength and stiffness under compression by a maximum of 9%–15%, although the target strength was achieved in all mixes; the presence of balsa wood and polymer particles in RCWTB, with high flexibility, could explain these reductions. On the other hand, the stitching effect of the glass fiber–reinforced polymer fibers present in RCWTB largely improved the bending-tensile mechanical properties. For example, flexural strength was almost doubled (from 2.51 to 4.99 MPa) when RCWTB was combined with 50% CRA. Additionally, RCWTB reduced both the embodied carbon and cost of low-strength concrete, resulting in doubled flexural-strength efficiency (flexural strength per unit of embodied carbon and cost), regardless of the CRA content. Overall, the best interaction was observed with 10% RCWTB and 50% RCA. Therefore, this study opens the possibility of simultaneously using RCWTB and CRA in low-strength concrete for applications where bending stresses predominate.This research work was supported by the Ministerio de Ciencia, Innovación y Universidades (MICIU), Agencia Estatal de Investigación (AEI), European Union (EU), European Regional Development Fund (ERDF), and NextGenerationEU/PRTR (Grant Nos. PID2020-113837RB-I00, PID2023-146642OB-I00, 10.13039/501100011033, TED2021-129715B-I00, and FPU21/04364); the Junta de Castilla y León (Regional Government) and ERDF (Grant Nos. UIC-231, BU033P23, and BU066-22), and, finally, the University of Burgos (Grant No. SUCONS, Y135.GI). Authors Nerea Hurtado-Alonso and Javier Manso-Morato contributed equally to this paper
Herramientas de comunicación de Zara: diferencias y similitudes entre los mercados de España y México
No full textZara, la principal marca del Grupo Inditex, se ha consolidado como una de las marcas lideres en el sector de la moda rápida a nivel global. Este prestigio es resultado de un desarrollo constante desde su creación, desde sus inicios, se observó la importancia de atender las necesidades de los clientes lo más rápidamente posible, dando así origen a la moda rápida y cimentando el éxito de Zara.
El trabajo investiga, a través de un enfoque comparativo entre España y México y, con la participación de una muestra de 102 compradores de la marca, las diversas herramientas de comunicación que Zara utiliza para comunicar sus productos y servicios. A través de este estudio podemos observar cómo en determinados aspectos, la marca actúa de forma similar en ambos países. Sin embargo, también se observa como Zara se adapta específicamente según el contexto, dejando en evidencia que la marca se adecua según la cultura del país en el que comercializa sus productos.The main brand of the Inditex group, Zara, has been established as one of the globally leading brands in the fast fashion market. Its reputation is due to a permanent evolution since its creation when the importance of attending the customer needs as soon as possible was observed, giving rise to this kind of fashion and fortifying Zara’s success.
The study investigates, through a comparative approach between Spain and Mexico and with the participation of a sample of 102 brand buyers, the various communication tools that Zara uses to convey its products and services. Through this study, we can observe how the brand acts similarly in certain aspects in both countries. However, it is also observed how Zara specifically adapts according to the context, highlighting that the brand adjusts according to the country's culture in which it markets its products
Dimensional stability and water transport behavior of concrete with high contents of wind‐turbine blade waste
No full textFiber addition is a common strategy to enhance concrete's durability, avoiding cracks and reducing penetration of harmful agents. In this research, a sustainable fiber-like material obtained from mechanical recycling of dismantled wind-turbine blades and made up of glass fiber-reinforced polymer (GFRP) fibers and microfibers, balsa wood, and polymeric particles, named raw-crushed wind-turbine blade (RCWTB), was added into concrete in high quantities. For studying dimensional stability and water transport behavior of concrete containing this waste, 11 mixes were manufactured with RCWTB contents up to 10 vol.% as aggregate replacement. Dimensional stability was enhanced by RCWTB incorporation, as shrinkage and linear coefficient of thermal expansion were reduced up to 47% and 17%, respectively. Furthermore, when tested for accelerated aging, RCWTB mixes experienced similar or slightly lower thermal strains compared to the reference mix. RCWTB also reduced the variations in the mechanical properties after accelerated aging and even led to improved flexural (+9.75%) and compressive (+11.14%) strengths, partly thanks to the proper stitching of the matrix by the GFRP fibers, as scanning electron microscope images and energy dispersive x-ray spectra demonstrated. Concrete porosity in both full-immersion and capillarity terms increased up to 70%–75% following RCWTB addition due to higher air entrainment and the porous particles of balsa wood in RCWTB acting as water-storage points, yet porosity was always within structural standards. Overall, mixes with proven proper performance regarding both concrete dimensions were produced with high proportions of RCWTB, being therefore suitable for applications in which such performance is of utmost relevance.This research work was supported by the MICIU, AEI, EU, ERDF and NextGenerationEU/PRTR (grant numbers PID2023-146642OB-I00; 10.13039/501100011033; TED2021-129715B-I00; FPU21/04364); the Junta de Castilla y León (Regional Government) and ERDF (grant number UIC-231; BU033P23; BU066-22); and, finally, the University of Burgos (grant number SUCONS, Y135. GI)
Identifying users of immersive virtual-reality serious games through machine-learning techniques
No full textUser identification is currently an open issue in immersive Virtual Reality (iVR) environments. Three main goals are
usually associated with the use of tracking-data and Machine-Learning (ML) techniques: safeguarding privacy, user
authentication, and user-experience customization. However, research to date has only involved very limited recordings
of user data (e.g., on a single session and for low-interactive situations), rare in real iVR environments. So, the research
gap between real iVR data and ML techniques for user identification is addressed in this paper. To do so, a 3-session
iVR experience of operating a bridge crane is considered. In this simple yet highly interactive learning action, the
dataset records of user performance show rapid changes between one experience and another. Eye, head, and hand
movements of 64 users of similar age and with comparable previous experience were all recorded while engaged with
the experience. The final raw dataset had a size of approximately 50M data points with 25 attributes that were mainly
temporal series values. Secondly, different ML algorithms were used for user identification: Decision Tree, Random
Forest, XGBoost, k-Nearest Neighbors, Support Vector Machines, and Multilayer Perceptron. The results showed that
ML ensemble learning techniques, particularly Random Forest, were the most suitable solutions on the basis of different
measures for the prediction of user identity. Additionally, the inclusion of stress and no-stress conditions significantly
enhanced model performance, highlighting the importance of data diversity. Temporal segmentation revealed that user
identification during later phases of the exercise was slightly more effective, due to increased individual variability.
Finally, a minimum duration of the iVR experience was identified as a requirement to assure high identification rates.This study was partially funded through the ACIS project (Reference Number: INVESTUN/21/BU/0002) of the Consejería de Empleo e Industria of the Junta de Castilla y León (Spain); the REMAR Project (Reference Number: CPP2022-
009724) supported by the Ministry of Science and Innovation of Spain (MCIN/AEI/10.13039/501100011033) and
through “ERDF A way of making Europe” or European Union NextGenerationEU/PRTR funding; the HumanAid
Project (Reference Number: TED2021-129485B-C43) funded through the Spanish Ministry of Science and Innovation
and the Ministry of Science, Innovation and Universities (FPU21/01978)
Identifying users of immersive virtual-reality serious games through machine-learning techniques
No full textUser identification is currently an open issue in immersive Virtual Reality (iVR) environments. Three main goals are usually associated with the use of tracking-data and Machine-Learning (ML) techniques: safeguarding privacy, user authentication, and user-experience customization. However, research to date has only involved very limited recordings of user data (e.g., on a single session and for low-interactive situations), rare in real iVR environments. So, the research gap between real iVR data and ML techniques for user identification is addressed in this paper. To do so, a 3-session iVR experience of operating a bridge crane is considered. In this simple yet highly interactive learning action, the dataset records of user performance show rapid changes between one experience and another. Eye, head, and hand movements of 64 users of similar age and with comparable previous experience were all recorded while engaged with the experience. The final raw dataset had a size of approximately 50M data points with 25 attributes that were mainly temporal series values. Secondly, different ML algorithms were used for user identification: Decision Tree, Random Forest, XGBoost, k-Nearest Neighbors, Support Vector Machines, and Multilayer Perceptron. The results showed that ML ensemble learning techniques, particularly Random Forest, were the most suitable solutions on the basis of different measures for the prediction of user identity. Additionally, the inclusion of stress and no-stress conditions significantly enhanced model performance, highlighting the importance of data diversity. Temporal segmentation revealed that user identification during later phases of the exercise was slightly more effective, due to increased individual variability. Finally, a minimum duration of the iVR experience was identified as a requirement to assure high identification rates.his study was partially funded through the ACIS project (Reference Number: INVESTUN/21/BU/0002) of the Consejería de Empleo e Industria of the Junta de Castilla y León (Spain); the REMAR Project (Reference Number: CPP2022-
009724) supported by the Ministry of Science and Innovation of Spain (MCIN/AEI/10.13039/501100011033) and
through “ERDF A way of making Europe” or European Union NextGenerationEU/PRTR funding; the HumanAid
Project (Reference Number: TED2021-129485B-C43) funded through the Spanish Ministry of Science and Innovation
and the Ministry of Science, Innovation and Universities (FPU21/01978)
Multifunctional smart polymers and citizen science for a comprehensive approach to nitrate pollution: Curative and preventive strategies
No full textThis work presents the development and evaluation of a multifunctional smart polymer (FNO₃)
for the extraction and detection of nitrates in drinking water. A total of 250 tap water samples
from various localities were analyzed, revealing nitrate concentrations that in some cases doubled
the legal limit (up to 100 mg⋅L⁻¹). FNO₃, composed of 49.75 mol% NNZA monomer with high
anion-exchange capacity, exhibited a maximum nitrate adsorption capacity (qmax) of
164 ± 5 mg⋅g⁻¹ , which is 3.6 times greater than that of commercial resins. The polymer
demonstrated significant swelling in water (~2014 ± 152 %) and incorporated a sensing functionality
via a fluorometric monomer, enabling visual detection when saturation occurs. Fluorescence
response studies yielded a limit of detection (LOD) of 4.26 mg⋅L⁻¹ and a limit of
quantification (LOQ) of 12.92 mg⋅L⁻¹ , values that are below the regulatory thresholds established
by European and Spanish legislation for nitrates in drinking water. The material was tested
through multiple adsorption-regeneration cycles using domestic saline solutions, maintaining
stable efficiency. Interference studies indicated that carbonates present in hard water partially
reduce adsorption effectiveness. Life Cycle Assessment (LCA) identified the structural materials and
functional monomers as the main contributors to environmental impact, while reuse and polymer
application offer environmental benefits due to nitrate recovery. Additionally, in vitro toxicological
assays with HepG2 cells confirmed the absence of cytotoxicity, supporting the polymer’s
viability for safe water treatment applications.We gratefully acknowledge the financial support provided by all funders. Author S. Vallejos received Grant PID2023–147301OB-I00 and Grant 8138165958–165958–57–425 funded by MICIU/AEI /10.13039/501100011033 and FEDER, EU. The financial support provided by Fondo Europeo de Desarrollo Regional-European Regional Development Fund (FEDER, ERDF) and Regional Government of Castilla y León -Consejería de Educación, Junta de Castilla y León- (BU025P23) is gratefully acknowledged. This work was supported by the Regional Government of Castilla y León (Junta de Castilla y León) and by the Ministry of Science and Innovation MICIN and the European Union NextGenerationEU PRTR. This project has received funding from the LIFE Programme of the European Union under Grant Agreement Nº 101215633 - LIFE NITRAZENS. J. L. Vallejo-García received the grant PRE2021–09812 funded by MCIN/AEI/ 10.13039/501100011033 and by “ESF Investing in your future”. Author Saul Vallejos received grant BG22/00086 funded by Spanish Ministerio de Universidades
Parodias deepfakes, espectáculo tecnológico y catarsis digital: el caso de Iberian Son
No full textThis study examines 1,919 user comments on 57 deepfakes created by Iberian Son and posted on TikTok, which parody the Spanish Prime Minister, Pedro Sánchez. Content analysis and textual analysis are applied to explore whether the use of AI motivates viewing, what kind of responses they generate, and whether users infer implicit meanings not directly expressed in the videos. The results show that AI not only increases the appeal of the content but also acts as a tool for digital catharsis. The comments reveal that these videos provoke visceral reactions and reactivate latent political hate speech. In addition, they project broader ideological readings, some of which are linked to narratives typical of the far right.Este estudio examina 1.919 comentarios de usuarios sobre 57 Deepfakes creados por Iberian Son y publicados en TikTok, que parodian al presidente del Gobierno español, Pedro Sánchez. Se aplica un análisis de contenido y un análisis textual para explorar si el uso de IA motiva el visionado, qué tipo de respuestas generan y si los usuarios infieren significados implícitos no expresados directamente en los vídeos. Los resultados muestran que IAno solo incrementa el atractivo del contenido, sino que también actúa como herramienta de catarsis digital. Los comentarios revelan que estos vídeos provocan reacciones viscerales y reactivan discursos de odio político latente. Además, los proyectan lecturas ideológicas más amplias, algunas de las cuales se vinculan con narrativas propias de la extrema derecha.This research was conducted within the framework of the project Challenging Online Narratives of Political Hatred and Misogyny (ref. PID2023-147506OB-I00), within the 2021 State Programme for Research, Development, and Innovation for Knowledge Generation Projects, funded by the Ministry of Science and Innovation and the Spanish Research Agency (AEI) of the Government of Spain
Bystander behaviour online and anti-cyberbullying self-efficacy among a post primary school aged sample In Ireland
No full textEmerging research suggests that the dynamics of bystander behaviour online is complex and nuanced. Some of this research has identified differences between online bystanders and non bystanders in intervening in online bullying when it is witnessed online. However, little research has investigated the extent to which self-efficacy beliefs could predict whether or not online bystanders are more likely to carry out cyberdefending or cyberpassive behaviours. 225 post primary students in Ireland completed an online survey during the Safer Internet Day (SID) campaign which included questions about their use of Internet devices, behaviour when witnessing cyberbullying incidences, and anti-cyberbullying self-efficacy beliefs. The study considered 45.3% of the sample to be online bystanders who reported to have witnessed cyberbullying at least once over the last number of months. Online bystanders reported to use Internet devices significantly more often than non bystanders and also present as a bully-victim cyberbullying involvement role. Compared to non bystanders, online bystanders were found to be less confident when noticing, interpreting, and knowing what actions to take when cyberbullying happens to them. For online bystanders, prior victimisation was found to be a common predictor of both cyberdefending and cyberpassive bystander behaviour. However, having higher self-rated confidence to intervene in a direct cyberbullying incident was a significant predictor of cyberdefending bystander behaviour only. Implications of the study results are discussed in the context of interventions and research that addresses young people’s social norms online that can be considerably detrimental for effective intervention.Derek A. Laffan is in receipt of a funded bursary awarded from the National Educational Psychology Service (NEPS) in the Department of Education in Ireland to undertake his doctoral studies in educational and child psychology (DECPsy) at Mary Immaculate College, Limerick, Ireland. Contributory funding for this research was also provided by META and the Vodafone Foundation Ireland