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Workshop 1: Analysis of Food Waste
No full text• Introduction to the Food Waste problem
• Big questions on Food Losses and Food Waste
• Main impacts resulting from food waste
• Different issues that drive towards performance. Case examples
• The relevance of measurement
• Final thought
Three essays in consumption and social dynamics
No full textCotutelaThe Ph.D. thesis dissertation, “Three Essays in Consumption and Social Dynamics,” investigates the underlying determinants of consumer behavior and the influences arising from social norms through a rigorous exploration of social behaviour in distinct yet interconnected domains. The work is structured into three essays that together offer a comprehensive analysis of how individual decision rules, market interdependencies, and reference point drives certain economic, and social outcomes. In the first essay, “Interacting Cobweb Demands” (Co-Authored with Prof. Giorgio Ricchiuti) a dynamic two-good, two-market framework is developed to study consumer choice under uncertainty. Building on the classical cobweb model, the analysis introduces a novel heuristic that integrates the conventional price-minimization motive with an expectation-driven evaluation of intrinsic quality—referred to as the Reference Quality (RQ) price. By incorporating variable consumer quotas and exogenous tariffs, the model captures non-linearities in demand and illustrates how market interconnections can precipitate period-doubling and Hopf bifurcations. These results extend canonical models by demonstrating that the relative weighting between price and quality factors critically influences the stability of market equilibria. The second essay, “Misperception of Norms: Smartphone Use,” shifts the focus to digital consumption patterns. Here, the dissertation employs a randomized control trial (RCT) survey—conducted in collaboration with the European Commission’s Joint Research Center—to investigate how misperceptions about peer usage norms drive the overconsumption of digital devices. The findings reveal that individuals tend to overestimate the typical usage of smartphones while underestimating their own, a bias that reinforces excessive screen time. This evidence underscores the role of normative misperceptions in shaping consumption behavior and highlights the potential for informational interventions to realign individual behavior with actual social norms, thereby mitigating welfare losses associated with digital overuse, which is our main finding at this stage. The third essay, “Aspiration and Effort,” considers the persistence of inequality by linking individual aspirations with the broader structure of social networks. Employing both a historical review of seminal perspectives—from Parsons’ functional theory to Veblen’s emphasis on innate competitive drives (i.e. Pecuniary Emulation), and a novel network game model, this chapter argues that aspirations can be determined as an interplay between exogenous endowments but also by the social interactions. By formalizing this in a quadratic-cost pay-off function with effort effort choice, and network interactions, the analysis provides an early stage theoretical exploration on the enduring mechanisms of inequality, suggesting that both intrinsic motivations and extrinsic social influences jointly shape economic outcomes.Programa de Doctorat en Economia i Empres
Electrocatalytic systems for the synthesis of value-added products
No full textCompendi d'articles, Doctorat internacionalTo address the challenges posed by climate change and global warming, there is a pressing need to utilise renewable materials that can be obtained in a safe and environmentally friendly manner. The utilisation of biomass as a source of chemicals represents a revolutionary methodology with the potential to overcome humanity's reliance on fossil resources. Electrochemical technologies are advantageous in synthesising value-added products from biomass at atmospheric temperature and pressure, utilising water as a solvent and concurrently as a source of oxygen and hydrogen atoms and regulating chemical reactions through the application of electrical potential. In this study, inexpensive materials such as Cu and graphite, with slight modifications of catalytic metals such as Pd, Ag, Ni, were used for the electrochemical production of compounds that are used to produce polymeric materials, biofuels, pharmaceutical industry, etc.Programa de Doctorat en Cièncie
Estudio y modelado de la dispersión de contaminantes procedentes de fuentes pasivas con OpenFOAM
No full textLas emisiones odoríferas de las estaciones depuradoras de aguas residuales (EDARs) constituyen un importante desafío ambiental debido a su impacto en la calidad de vida de las comunidades cercanas. Estas emisiones, originadas principalmente en fuentes pasivas superficiales como tanques abiertos, incluyen compuestos como el sulfuro de hidrógeno y amoníaco, los cuales son detectables incluso a bajas concentraciones. El presente estudio aborda el modelado de la dispersión de contaminantes mediante Dinámica de Fluidos Computacional (CFD), empleando el software OpenFOAM. Se modelan las fuentes pasivas mediante la analogía con cavidades bidimensionales, con el objetivo de desarrollar un modelo analítico que pueda integrarse en simulaciones de microescala urbana, reduciendo el coste computacional al simplificar la representación de las fuentes emisoras. Además, se incluye el uso de redes neuronales entrenadas con resultados CFD para predicciones rápidas, lo que permite realizar estudios paramétricos extensos y optimizar la gestión de las emisiones odoríferas.Odorous emissions from wastewater treatment plants (WWTPs) have low detection thresholds, causing discomfort in nearby communities. These emissions mainly originate from passive surface sources, whose volatilization depends on environmental factors. This study models pollutant dispersion using Computational Fluid Dynamics (CFD) in OpenFOAM, representing passive sources as two-dimensional cavities. The emission rate is analyzed based on geometric and physical variables to develop an analytical model that optimizes microscale simulations. To reduce computational cost, neural networks trained with CFD results are employed, enabling efficient predictions of wind fields and pollutant concentrations. The combination of physical models and Deep Learning enhances the assessment of environmental impact and optimizes emission management in urban and industrial environments.Programa de Doctorat en Tecnologies Industrials i Material
Digital violence against women as gender-based violence. Characterization, types, and analy
No full textTreball final de Màster Universitari en Igualtat i Gènere en l'Àmbit Públic i Privat (Pla de 2013). Codi: SRM042. Curs acadèmic 2024-2025El trabajo académico consiste en la caracterización y análisis de la violencia digital hacia las mujeres en el entorno online. A tal efecto, mediante este breve trabajo, se pretende obtener mayor conocimiento del fenómeno a través de una visión más amplia de la violencia machista digital hacia el colectivo de mujeres jóvenes. En virtud de lo expuesto, se proponen medidas de intervención social para contribuir a la eliminación de la violencia digital, y de ese modo lograr la igualdad efectiva entre mujeres y hombres. Del mismo modo, es relevante abordar desde una prisma ética feminista los retos presentes para conseguir que dicha problemática no sea normalizada y aumente exponencialmente, afectando a los derechos fundamentales del colectivo de mujeres.This academic work consists of the characterization and analysis of digital violence against women in the online environment. To this end, this brief study aims to gain a greater understanding of the phenomenon through a broader view of digital gender-based violence against young women. In light of the above, social intervention measures are proposed to contribute to the elimination of digital violence and thus achieve effective equality between women and men. Similarly, it is important to address the current challenges from a feminist ethical perspective to ensure that this problem does not become normalized and increase exponentially, affecting the fundamental rights of women as a grou
Autopercepción de competencias y entorno de prácticas en estudiantes de enfermería en el este de Inglaterra
No full textLa experiencia práctico-clínica tiene un papel esencial en la formación universitaria de las enfermeras. La percepción de los estudiantes de su entorno de prácticas y la autopercepción de su preparación para desenvolverse en dicho entorno aparecen destacados en la literatura. Se llevó a cabo un estudio descriptivo y transversal de tipo correlacional en estudiantes del Grado de Enfermería en una universidad del este de Inglaterra para analizar la relación entre el entorno en las prácticas clínicas y el nivel de competencia percibido por los participantes. Se encontró una asociación positiva entre el entorno y el nivel de competencia y diferencias significativas de competencia autopercibida entre los grupos. Los estudiantes del grado de Enfermería valoran de forma favorable su entorno de prácticas, lo cual influye en una autopercepción general positiva de su nivel de competencia. Sería recomendable explorar en mayor profundidad a los diferentes grupos de estudiantes.Practice experience plays an essential role in the undergraduate education of nurses. Students' perceptions of their practice environment and the self-perception of their preparedness to work in that environment are highlighted in the literature as relevant factors. A descriptive, cross-sectional, correlational study of undergraduate nursing students at a university in the East of England was conducted to examine participants' perceived level of competence and its relationship to the clinical practice environment. A positive association was found between environment and level of competence. There were significant differences in self-perceived competence between the groups. Nursing students rate their practice environment favourably, and this influences their overall positive perception of their level of competence. Further exploration of these findings in different groups of students would be advisable.Programa de Doctorat en Ciències de la Infermeri
Educar para transformar conflictos. Valoración de los conocimientos, habilidades y recursos para hacer las paces en la formación de grado en psicología social en Venezuela
No full textEsta investigación analiza el currículo formativo en psicología social impartido en el Grado en Psicología de la Universidad Central de Venezuela usando el marco analítico de la Educación Crítica para la Paz (ECpP). Para ello, establece un conjunto de conocimientos, habilidades y recursos para hacer las paces con la literatura especializada y realiza un estudio de casos intrínseco de corte cualitativo. Se conformó un corpus informativo constituido por 20 programas de asignaturas dictadas por el Departamento de Psicología Social de la Escuela de Psicología de la UCV y se entrevistó en profundidad a 23 estudiantes del Ciclo Aplicado de Psicología Social de las cohortes que comenzaron dicho ciclo entre 2015 y 2018. Los programas analizados presentan amplias referencias interdisciplinares y oportunidades de mejora en la sinergia pedagógica. El reporte del estudiantado señala la promoción de un habitus socio-reflexivo y crítico como recurso principal para la construcción de paz en Venezuela.This research analyses the curriculum of social psychology taught in the undergraduate Psychology program at the Universidad Central de Venezuela, using the analytical framework of Critical Peace Education (CPE). To do so, it establishes a set of knowledge, skills, and resources for making peace based on specialized literature and conducts an intrinsic case study with a qualitative approach. The information corpus was composed of 20 course syllabi from the Department of Social Psychology at the UCV School of Psychology, and in-depth interviews were conducted with 23 students from the Applied Cycle of Social Psychology who began the cycle between 2015 and 2018. The analysed syllabi present broad interdisciplinary references and opportunities for improvement in pedagogical synergy. The students' report highlights the promotion of a socio-reflective and critical habitus as the main resource for peacebuilding in Venezuela.Programa de Doctorat en Estudis Internacionals de Pau, Conflictes i Desenvolupamen
Fuel–Load Mapping in Mediterranean Maquis via UAV LiDAR & Deep-Learning Semantic Segmentation
No full textTreball de Final de Màster Universitari Erasmus Mundus en Robòtica Intel·ligent Marina i Marítima (Pla de 2024). Codi: SJO053. Curs acadèmic 2024-2025In the context of climate change, vegetation fires have become a major risk for many countries around the world, with their frequency and intensity increasing in recent years.
The characteristics of vegetation, particularly shrub height and surface fuel load, are key parameters that determine the propagation and intensity of wildfires. They also serve as essential inputs to fire behavior models used for fire suppression and land management planning. Traditional methods for estimating these parameters are labour-intensive, destructive, and costly, and are impractical for widespread or repeated monitoring. There is therefore a pressing need for rapid, non-destructive, and scalable approaches to fuel load estimation.
This thesis focuses on the estimation of surface fuel load and vegetation height for Mediterranean Maquis shrubs, with particular emphasis on the genus Cistus. The work builds on existing reference studies in the field [1], adapting and applying them to this specific ecosystem. By combining drone-based remote sensing technologies, including LiDAR and optical imagery (RGB and multispectral), with deep learning techniques for semantic segmentation, the methodology is tailored to the structural and ecological characteristics of the study site. A critical analysis and adaptation of existing approaches were carried out to ensure their suitability for Maquis shrubland conditions.
Comprehensive datasets were collected over three months in Bistugliu, near Corte, Corsica, incorporating LiDAR point clouds, RGB and multispectral orthomosaics, and detailed ground-truth data (including fuel load and shrub heights). Semantic segmentation models trained on the orthomosaics effectively delineated Cistus shrubs, while processed LiDAR data enabled precise vegetation measurements. By integrating these results, optimal LiDAR-derived metrics for fuel load prediction were identified, leading to reliable estimations across the entire study area.
The developed methodology provides a reliable estimation of surface fuel load and vegetation height for the Cistus species, and demonstrates the potential of this ap proach for the broader characterization of Mediterranean Maquis shrubs. This work shows how drone-based remote sensing combined with deep learning can deliver replica ble, non-destructive solutions that support effective land management and wildfire risk assessment
Selective chemical recycling of polyhydroxybutyrate into high-value hydroxy acid using the taurine organocatalyst
No full textPolyhydroxyalkanoates (PHAs) are receiving significant attention due to their biobased origin, biodegradability, and excellent barrier properties. However, their high cost compared to traditional plastics necessitates the development of recycling technologies to retain their value post-use. Despite being thermoplastics, PHAs are difficult to recycle mechanically due to their narrow processing window, particularly for polyhydroxybutyrate (PHB), and conventional chemical recycling routes often lead to non-selective degradation and dehydration to crotonic acid, yielding complex product mixtures with limited valorization potential. In contrast, this study presents a selective chemical recycling method for PHB that suppresses dehydration pathways by using naturally occurring taurine as an organocatalyst. Taurine outperforms other catalyst families, such as Brønsted acids and bases, in terms of depolymerization yield and selectivity, achieving 98% enantiomerically pure 3-hydroxybutyric acid (HBA) in the optimized process. Density functional theory (DFT) calculations provided insights into the pH-dependent HBA elimination mechanisms demonstrating that taurine does not play a role in this process under very basic nor acidic conditions. A liquid-liquid extraction technique was developed to separate HBA from by-product crotonic acid, successfully maintaining the R-enantiomeric form of the recovered HBA. This method is applicable to both synthetic PHB and biological PHB samples, including copolymers and blends. Overall, this taurine-catalyzed PHB depolymerization approach inhibits the formation of dehydrated by-products and offers a promising solution for selective recycling of PHB into valuable chiral building blocks.The authors acknowledge the Spanish Ministry of Science and Innovation: PID2022-138199NB-I00 funded by MCIU/AEI/10.13039/501100011033, as well as the funding of the State Research Agency (AEI) with numbers TED2021-129852B-C21 and TED2021-129852B-C22 and the Basque Government with number GC IT-1667-22. EG thanks the Basque Government for the Postdoctoral fellowship (POS_2022_1_0040). VM gratefully acknowledges financial support from grant PGC2018-094852-B-C21 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, and from grant PROMETEO CIPROM/2021/079 of Generalitat Valenciana. KŚ thanks the Spanish Ministerio de Ciencia, Innovación y Universidades for the Ramon y Cajal fellowship (RYC2020-030596-I) and Grant to Encourage Research Consolidation (CNS2024-154238). The authors acknowledge ERC-Co (METACELL-818089), IKERBASQUE for sponsoring him. DAS thanks the Basque Government's Predoctoral Programme (PRE_2022_2_0138). The work done at Colorado State University was supported by the U.S. National Science Foundation (NSF-1955482)
A geometric approach to general relativity and rotationally symmetric solutions of the Einstein Field equation for the vacuum
No full textTreball Final de Grau en Matemàtica Computacional. Codi: MT1054. Curs 2024-2025This thesis explores the mathematical foundations of general relativity by reconstructing the differential geometry required to understand Einstein’s feld equations and by deriving the Schwarzschild metric. Motivated by a deep curiosity about the nature of spacetime and gravity, the project develops the geometric tools from frst principles, emphasizing the role of tensors, curvature, and connections in describing gravitational phenomena. Through a careful bibliographic study and the implementation of a Python-based computational tool, the work derives the Schwarzschild solution under vacuum and spherical symmetry assumptions, verifying its consistency with established literature. The results also provide insight into the physical implications of general relativity, such as gravitational time dilation and the emergence of black holes. This work not only bridges mathematical rigor with physical intuition but also aims to provide an accessible framework for future explorations of relativistic geometry