DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY

• SALAS I BARENYS, BERNAT: Precision Agriculture in Fruit Orchards: Development and Evaluation of a Smart Sprayer for Variable Rate Pesticide Application in 3D crops
  
  Author: SALAS I BARENYS, BERNAT
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY
  Department: Department of Agri-Food Engineering and Biotechnology (DEAB)
  Mode: Article-based thesis
  Deposit date: 09/01/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: GIL MOYA, EMILIO | SALCEDO CIDONCHA, RAMON
  Committee:
       PRESIDENT: BAPTISTA, FÁTIMA DE JESUS FOLGÔA
       SECRETARI: CAMPOS TOBAJAS, JAVIER
       VOCAL: GIOELLI, FABRIZIO STEFANO
  Thesis abstract: European agriculture is currently experiencing an intense debate about the production model, linked to a growing social awareness regarding the use of agrochemicals in general, and plant protection products in particular. In this sense, there is a notable increasing focus on precision agriculture, which aims to optimize the use of these inputs by considering the intra-field variability among trees or plants. One example is the OPTIMA project (Optimised PesT Integrated MAnagement), funded by the EU under the H2020 program (http://optima-h2020.eu/en), within which this doctoral thesis has been developed. For the UMA-UPC research group, the goal was to design and integrate a novel system for applying plant protection products in a conventional hydropneumatic sprayer with constant flow for treatments in fruit trees. This system was designed to be able to adjust the amount of liquid sprayed based on the width and density of the tree canopies, thus avoiding excess or insufficient presence of pesticides on the target vegetation of the treatment. To achieve this, it uses a set of ultrasonic sensors to determine the size and leaf density of the canopy, sending this information to a computer that regulates a set of motorized valves to modify the flow rate in real time through the nozzles.With these premises, the present thesis encompasses, in the first part, the characterization of the sprayer, the design and implementation of the intelligent spraying system and the validation of the prototype conducted through field trials on apple applications. In these experiments, the coating and deposition of product on leaves were evaluated, both in terms of quantity and distribution uniformity, as well as the direct losses of plant protection product to the soil.The results of the sprayer characterization showed that the asymmetry of air velocities from the fan was accentuated as the airflow increased. Additionally, it was observed that the homogeneity of the coating on the tree canopies increased when working with larger droplet sizes along with higher airflow configurations in the fan. These results helped establish the configuration of the prototype during subsequent field trials (fan and nozzle parameters). Regarding the results of the second part, the prototype's ability to continuously modify the flow rate of the nozzles according to crop characteristics was successfully demonstrated, in terms of speed and precision level. The efficiency and robustness of the prototype and its components were successfully evaluated, including an in-depth analysis of the ultrasonic sensor configurations. All of this allowed for the selection of the appropriate configuration of both sensors and actuators as well as the parameters introduced into the algorithm for the final part of the thesis.The results obtained in this thesis demonstrate the success of the VRA system in achieving its fundamental objectives: reducing the volume of plant protection products applied and minimizing environmental impact. The intelligent spraying system allowed for a significant reduction of 45% in liquid use compared to conventional sprayers, maintaining optimal levels of leaf deposition. This optimization not only improves the efficiency of plant protection treatments but also reduces the direct losses of product to the soil, decreasing the risk of environmental contamination. Thus, the implementation of this technology contributes to more sustainable agriculture, aligning with the principles of the EU's Sustainable Use of Pesticides Directive and other regulatory frameworks that promote reducing dependence on chemical products in crop protection.
  

DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION

• GIL VIYUELA, OSCAR: Robot Navigation Issues and Human-Robot Collaborative Search using Deep Learning Methods
  
  Author: GIL VIYUELA, OSCAR
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Robotics and Industrial Informatics (IRI)
  Mode: Normal
  Deposit date: 13/01/2025
  Reading date: 27/02/2025
  Reading time: 11:00
  Reading place: Sala de Juntes de la Facultat de Matemàtiques i Estadística (FME),Campus Diagonal Sud, Carrer de Pau Gargallo, 14, 08028 Barcelona
  Thesis director: SANFELIU CORTES, ALBERTO
  Committee:
       PRESIDENT: MONTANO GELLA, LUIS ENRIQUE
       SECRETARI: ANDRADE CETTO, JUAN
       VOCAL: MERINO CABAÑAS, LUIS
  Thesis abstract: Currently, Social Robotics and Artificial Intelligence (AI) are two areas that are beginning to be explored together thanks to the great development they have undergone in the last decade. In particular, Deep Learning (DL) models, based on Artificial Neural Networks (ANNs), have advanced enormously in recent years. An advance that has allowed the use of these types of models in a large number of useful applications for people such as spam filters, detection and diagnosis in medicine, translators, text-to-speech methods or image generation models. In the last years, different applications of DL in Human-Robot Interaction and Human-Robot Collaboration have been developed in different fields such as assistive robotics, service robots, industrial robotics, Search and Rescue (SAR), educational robotics, domestic robotics, and others. Most of these applications require robust human-aware robot navigation. For this reason, this thesis explores different ways of applying DL and Deep Reinforcement Learning (DRL) methods to improve aspects of robot navigation in environments with humans. The main aspects of robot navigation that this thesis explores are human motion trajectory prediction and anticipation. Additionally, the Human-Robot Collaborative Search is studied taking into account people's preferences with a DL generative model. The simulations and experiments carried out have served to test the proposed methods, validate the hypotheses and check their limitations. In summary, this dissertation provides different ways to apply DL methods for robot navigation and Human-Robot Collaborative Search with a description of the current state of the art and explanations about the proposed approaches, the study tools used and the simulations or experiments performed. Finally, the conclusions are exposed.
  
• LOPES E SILVA, BRUNO MIGUEL: Artificial Intelligence to Improve Plastic Molding Processes
  
  Author: LOPES E SILVA, BRUNO MIGUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Robotics and Industrial Informatics (IRI)
  Mode: Normal
  Deposit date: 17/12/2024
  Reading date: 14/02/2025
  Reading time: 11:00
  Reading place: Sala d'Actes de la Facultat de Matemàtiques i Estadística (FME), Carrer de Pau Gargallo, 14, 08028 Barcelona
  Thesis director: ALENYÀ RIBAS, GUILLEM | CHARRUA DE SOUSA, JOÃO MIGUEL
  Committee:
       PRESIDENT: BRANCO SIMÕES DA SILVA, CATARINA HELENA
       SECRETARI: ÁLVAREZ NAPAGAO, SERGIO
       VOCAL: SORGATO, MARCO
  Thesis abstract: This thesis advances the field of production processes, specifically injection molding, toward the goal of Zero Defect Manufacturing (ZDM), with an emphasis on improving quality prediction methods through Artificial Intelligence (AI). It explores innovative strategies for improving the efficiency and quality of manufacturing processes, highlighting the importance of minimizing defects in industrial production.The research begins with an analysis of the current state of predictive quality systems in injection molding processes, identifying the critical need for advances to achieve ZDM. By collecting data from legacy and modern equipment, this work establishes a basis for a comprehensive analysis, using standard protocols and new methodologies for data collection. Central to this thesis is the application of feature selection algorithms, which employ a combination of filter, wrapper, embedded, and hybrid approaches. This framework is designed to accurately identify the key parameters that influence the quality of the injection molding process, thereby facilitating more effective and predictive modeling of manufacturing results. In addressing quality prediction, the thesis introduces both supervised and unsupervised models to predict manufacturing quality. It particularly focuses on enhancing these models with human knowledge, integrating expert insights into the predictive algorithms to better adapt to the complex dynamics of the manufacturing environment. This approach not only improves the accuracy of predictions but also enriches the models with practical, real-world applicability. Through a series of detailed use cases, the effectiveness of the proposed methodologies is demonstrated across various equipment and manufacturing scenarios. The results highlight significant improvements in process predictability, contributing to the reduction of defects and moving closer to the ideal of ZDM. The conclusion of this thesis reiterates the importance of its contributions to the field of AI used in production processes, with a focus on injection molding, providing a solid foundation for future research aimed at improving the integration of data-driven and human-centered approaches in manufacturing. The thesis outlines potential pathways for continued innovation in digitalization, feature selection, and quality prediction, emphasizing the ongoing pursuit of excellence in manufacturing processes.
  
• ZHANG, SHUANG: STATE ESTIMATION, DIAGNOSIS AND CONTROL USING SET-BASED APPROACHES FOR LPV SYSTEMS
  
  Author: ZHANG, SHUANG
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AUTOMATIC CONTROL, ROBOTICS AND VISION
  Department: Institute of Industrial and Control Engineering (IOC)
  Mode: Normal
  Deposit date: 10/01/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: PUIG CAYUELA, VICENÇ | IFQIR, SARA
  Committee:
       PRESIDENT: MAMMAR, SAID
       SECRETARI: NEJJARI AKHI-ELARAB, FATIHA
       VOCAL: COMBASTEL, CHRISTOPHE
  Thesis abstract: Considering that Linear Parameter-Varying (LPV) technique has beendemonstrated as an effective way to represent nonlinear systems, results concerning the design of observers and controllers in LPV framework have been widely studied.This thesis contributes to the state-of-the-art in the field of robust state estimation, fault diagnosis and control for LPV systems, particularly in the presence of processing disturbances and measurement noise. The research is motivated by the safety-critical systems, such as autonomous vehicles, which require reliable fault diagnosis schemes for detecting and identifying potential actuator/sensor faults under uncertainties, and control strategies that are able to handle both the uncertainties and faults to achieve optimal and reliable performance. State estimation plays a crucial role in both fault diagnosis and controller design. To ensure robust performance, a set-membership state estimation method is developed for LPV systems subject to disturbances and measurement noises. These uncertainties are assumed to be unknown but bounded by zonotopes. The optimal state estimates are obtained by minimizing the radius of the bounding zonotope, formulated as an optimization problem in the form of Linear Matrix Inequalities (LMIs). Furthermore, the proposed method is extended to handle fault detection and estimation in more complex scenarios, including switched LPV systems and Nonlinear Parameter-Varying (NLPV) systems. In addition, Minimum Detectable Fault (MDF) and Minimum Isolable Fault (MIF) are characterized using zonotopic set-invariance approach. In the area of control, this thesis develops a Linear Quadratic Zonotopic (LQZ) control for the state feedback problem in the presence of uncertainties, in which the feedback loop is closed using the optimal estimates provided by a Zonotopic Kalman Filter (ZKF). The proposed LQZ control is less conservative, as it models uncertainties using zonotopic sets rather than Gaussian probability distributions. This formulation establishes the LQZ control as a zonotopic counterpart to the well-known Linear Quadratic Gaussian (LQG) control. Furthermore, in the presence of actuator fault, a Fault Tolerant Tracking Control (FTTC) strategy is developed. This strategy comprises a ZKF for state and fault estimation, a fault compensation mechanism and a state-feedback controller designed to achieve $\mathscr{H}_\infty$ performance.The above-mentioned contributions have been applied to state estimation, fault diagnosis and path-tracking control in vehicle lateral dynamics. Application to real data recorded with a prototype equipped vehicle demonstrates the relevance and efficiency of the proposed approaches.
  

DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS

• BENADOUDA IVARS, SALIM: Exploring dissipative systems with non-Hermitian modulations
  
  Author: BENADOUDA IVARS, SALIM
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN COMPUTATIONAL AND APPLIED PHYSICS
  Department: Department of Physics (FIS)
  Mode: Normal
  Deposit date: 10/01/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: HERRERO SIMON, RAMON | STALIUNAS, KESTUTIS
  Committee:
       PRESIDENT: V. GUREVICH, SVETLANA
       SECRETARI: ARTIGAS GARCIA, DAVID
       VOCAL: MAS ARABÍ, CARLOS
  Thesis abstract: The aim of this thesis is to explore the effect of non-Hermitian potentials in different nonlinear systems. Specifically, in the different sections of this work we focus on the stabilisation of various states. We consider mainly two systems due to their universality: the Gizburg Landau and the Lugiato Lefever equations. Both models correspond to generalisations of the nonlinear Schrödinger equation. The Ginzburg-Landau equation represents the dissipative extension of physical systems with active media. It has been extensively studied and praised as a foundational model for phenomena such as turbulence, lasers or Bose Einstein condensates. In contrast, the Lugiato-Lefever equation addresses dissipative systems with lossy media, where energy is injected. Recently, this model has gained renewed attention due to its accurate representation of fields in micro-resonators and the rapid advancements in mastering their fabrication. Through analytical and numerical studies we investigate how introducing non-Hermitian potentials leads to the stabilisation of different coherent structures. For laser-like models that exhibit strong and persistent turbulence regimes, this approach results in an effective stabilisation and control of the system. In turn, for micro-resonators, the stabilisation of periodic structures uncovers a novel and hybrid formation mechanism for solitons.
  

DOCTORAL DEGREE IN ELECTRONIC ENGINEERING

• GHODRATI, MOJTABA: NEGATIVE-SEQUENCE VIRTUAL CIRCUIT BREAKER
  
  Author: GHODRATI, MOJTABA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ELECTRONIC ENGINEERING
  Department: Department of Electronic Engineering (EEL)
  Mode: Normal
  Deposit date: 11/12/2024
  Reading date: 12/02/2025
  Reading time: 11:00
  Reading place: Defensa pública: Aula Master (VGA140), EPSEVG
  Thesis director: CASTILLA FERNANDEZ, MIGUEL | BORRELL SANZ, ÁNGEL
  Committee:
       PRESIDENT: GARCERÁ SANFELIU, GABRIEL
       SECRETARI: GARCIA DE VICUÑA MUÑOZ DE LA NAVA, JOSE LUIS
       VOCAL: FIGUERES AMORÓS, EMILIO
  Thesis abstract: Inverter-based microgrids are essential for integrating renewable energy sources and maintaining high power quality in distributed generation systems. However, unbalanced faults can induce negative-sequence currents and voltage imbalances, which significantly affect power stability and the operation of critical equipment. Conventional and solid-state circuit breakers, while capable of isolating faulted sections, face limitations in addressing these imbalances, especially in managing synchronization and power quality during disturbances.This thesis introduces a novel solution—the Negative-Sequence Virtual Circuit Breaker (NSVCB)—designed to prevent the propagation of negative-sequence components in islanded microgrids. Unlike traditional circuit breakers, the NSVCB eliminates negative-sequence currents and voltages at the point of common coupling (PCC) between microgrids without physically disconnecting sections of the grid, ensuring continuous power supply and frequency stability. The proposed NSVCB control scheme integrates advanced compensators with plug-and-play functionality, optimizing energy distribution and enhancing system resilience.This thesis is structured to comprehensively address the problem of negative-sequence currents and voltage imbalances in inverter-based microgrids, focusing on the development and validation of a Negative-Sequence Virtual Circuit Breaker (NSVCB). The document begins with an Introduction, which outlines the significance of power quality challenges in microgrids, particularly with respect to faults and imbalances, and reviews the limitations of conventional and solid-state circuit breakers.The next section, Modelling Asymmetrical Power Systems, presents a detailed methodology for analysing asymmetrical faults, using an illustrative example. Following this, the Control Proposal section defines three key control objectives—elimination of negative-sequence currents, improvement of power quality at the Point of Common Coupling, and maintaining power balance across inverters. A proposed control scheme for the NSVCB is also outlined here.In the Control Design section, the dynamic model of the closed-loop system is developed, with a focus on gain design and stability analysis, incorporating techniques such as the Nyquist criterion. The Experimental Results validate the proposed control system using a laboratory setup, comparing the NSVCB's performance with conventional circuit breakers, and demonstrating its advantages in mitigating negative-sequence currents without disconnection. The thesis concludes by summarizing the key findings and confirming the NSVCB's effectiveness in maintaining power quality and stability in microgrids.
  

DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION

• BERTOL GROS, ANA: Between rigor and imagination. Creativity in structures education
  
  Author: BERTOL GROS, ANA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENGINEERING, SCIENCES AND TECHNOLOGY EDUCATION
  Department: Institute of Education Sciences (ICE)
  Mode: Normal
  Deposit date: 13/12/2024
  Reading date: 07/03/2025
  Reading time: 12:00
  Reading place: Defensa pública Edifici C6 -E101
  Thesis director: LÓPEZ ÁLVAREZ, DAVID | BARDÍ MILÀ, BERTA
  Committee:
       PRESIDENT: COUSO LAGARÓN, DIGNA
       SECRETARI: ALIER FORMENT, MARC
       VOCAL: LLORENS LARGO, FARAÓN
  Thesis abstract: Creativity has been defined as a 21st century competence.In engineering, creativity is a vital component for the success and advancement of the profession. It enables engineers to view challenges from new perspectives, generate original and practical ideas, pose novel questions, and devise solutions to complex problems. This competence fosters interdisciplinarity, allowing professionals to collaborate within various fields to develop comprehensive projects that adhere to regulations and standards without sacrificing functionality or aesthetics. Teaching creativity to engineers is essential, as it equips them to devise innovative solutions, adapt to emerging technologies, enhance sustainability, and excel in a competitive job market.Traditionally, engineering education has been structured with methodologies centered on theoretical lectures and exercises with single answers. These studies, organized in silos with rigorous curricula, leave little room for exploration. Therefore, to promote creativity, educational methodologies must be adapted to the cognitive processes of university students and to the real demands of the profession and society.This doctoral thesis focuses on the field of structures, positioned at the intersection of engineering and architecture. This unique context presents an opportunity to explore creativity and contribute innovative ideas to enhance engineering education. The objective of this work is to analyze the theories, perspectives, and methodologies used in teaching structure courses to improve creativity in engineering education. By concentrating efforts in this area, the doctoral thesis aims to achieve reproducible and applicable results that can advance the field of engineering education.This work, based on a qualitative research paradigm, is structured on three pillars. The first is a literature review defining this thesis’s theoretical framework, synthesizing results from five areas relevant to creativity. Results show that, in higher education, effective creativity combines this innate skill with specific field knowledge. In engineering, this involves explaining the creative process to solve real problems. Research shows everyone has creative potential, but it must be fostered through education.The second pillar examines professional perspectives on creativity in engineering. Interviews with experts in structures reveal their opinions on integrating creativity in higher education. While there is agreement on general aspects of creativity, opinions diverge in the field of structures. Some professors question the need for creativity in their field, often due to time constraints that prevent the exploration of new teaching methodologies.The third pillar comprises field experiences. To understand the study environment, three research stays were conducted at European universities. In addition, two teaching innovation projects were carried out at the home institution. The results show that improving the design of the engineering curriculum requires collaboration and diverse teaching methodologies, the most recommended being thinking with your hands.Throughout this research, it has been discovered that there is a crucial need to provide accessible and adapted guidelines that can be applied by all educators in the discipline, regardless of their experience in creativity. The results of this research converge in the creation of nine practical guidelines to guide the development of creativity in structures. By implementing these results, engineering education can reshape the perception of creativity and demonstrate its tangible value in engineering practice. Creativity should not be seen as a separate entity but integrated throughout the curriculum, permeating all aspects of the student's educational itinerary. This requires a concerted effort by all staff involved in these teachings, where each person must play a fundamental role in fostering a culture of creativity.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• MO, YANGYANG: Modelling Hydro-Mechanical Coupled Gas Injection in Low Permeability Clay Materials
  
  Author: MO, YANGYANG
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 09/01/2025
  Reading date: 04/02/2025
  Reading time: 12:00
  Reading place: ETSECCPB. UPC, Campus Nord Building C1. Classroom: 002 C/Jordi Girona, 1-3 08034 Barcelona
  Thesis director: OLIVELLA PASTALLE, SEBASTIAN | RODRIGUEZ DONO, ALFONSO
  Committee:
       PRESIDENT: VILARRASA RIAÑO, VÍCTOR
       SECRETARI: PUIG DAMIANS, IVAN
       VOCAL: SONG, FEI
  Thesis abstract: This thesis investigates the hydro-mechanical (HM) coupled effects in geological media during gas injection, with a focus on various numerical strategies and modeling approaches. It is important to note that different types of elements and integration methods used in finite element simulations can influence the obtained results. The Heat and Gas Fracking model (HGFRAC), which consists of six different types of benchmark exercises, reveals that quadrilateral elements with bi-linear gradients produce more stable stress fields than linear triangle elements. Additionally, the use of selective integration method in quadrilateral elements enhances computational efficiency by mitigating convergence issues caused by locking effects. Sensitivity analyses were conducted on the fluidity parameter of the clay material, which controls the viscoplastic deformations. Further analysis of the response of quadrilateral elements, using the GTPT axisymmetric model, reveals that the integration method on Gauss points may cause convergence issues. These issues can be resolved by introducing the nodal point integration method, the selective integration method or a combination of both.Next, this thesis presents a comprehensive of three numerical strategies—Standard Finite Element Method (SFEM), SFEM with Selective Integration (SFEM+SI), and Mixed Finite Element Method (MFEM)—for simulating gas injection in clay-based geomaterials. The results indicate that the effective application of SFEM is heavily dependent on a high-precision mesh. Convergence issues may arise when dealing with relatively coarse meshes. Nevertheless, these convergence issues can be effectively mitigated by incorporating either the Selective Integration method or the MFEM formulations. In terms of computational efficiency, it is evident that the SFEM+SI method demonstrates higher efficiency than SFEM and MFEM. However, it is noteworthy that the computed gas flow patterns of SFEM and SFEM+SI can be affected by the alignment of the mesh. With MFEM, displacements and strains are calculated as independent unknowns, enhancing result accuracy and achieving mesh independence.And then, this thesis investigates gas injection processes using a three-dimensional (3D) HM coupled model to enhance understanding of gas transport in low-permeability geological formations. Conducted as part of the DECOVALEX 2023 project, the research focuses on in-situ gas injection tests in Callovo-Oxfordian (COx) clay, a crucial material for nuclear waste storage within the French concept for high-level radioactive waste disposal. The study underscores the limitations of 2D models in capturing the complexities of gas injection processes, highlighting the importance of using 3D models under HM coupled conditions for understanding gas breakthrough pressure and assessing the safety of geological repositories for nuclear waste storage. Various simulation strategies were applied to simulate the gas injection process, including the introduction of an Excavation Damage Zone (EDZ) around the borehole, the application of perfectly plastic contribution to the clay, and the further incorporation of softening behavior to the clay medium. Sensitivity analyses on EDZ permeability, test interval volume, and fracture spacing were also performed, alongside prolonged gas injection simulations, to provide deeper insights into the mechanisms governing gas flow and breakthrough pressure.
  

DOCTORAL DEGREE IN MARINE SCIENCES

• GONZÁLEZ ÁVALOS, RAÚL ALEXIS: High-Fidelity Modelling of Aquaculture Net Cages in Waves and Currents Using Smoothed Particle Hydrodynamics
  
  Author: GONZÁLEZ ÁVALOS, RAÚL ALEXIS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN MARINE SCIENCES
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Article-based thesis
  Deposit date: 13/01/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: ALTOMARE, CORRADO | GIRONELLA I COBOS, FRANCESC XAVIER
  Committee:
       PRESIDENT: CASTRO RODRÍGUEZ, MARIA TERESA
       SECRETARI: MARZEDDU, ANDREA
       VOCAL: ROMANO, ALESSANDRO
  Thesis abstract: As aquaculture expands into areas exposed to unfavourable climatic conditions, it becomes imperative to develop numerical models capable of predicting the behaviour of these systems under severe environmental scenarios. The complexity of aquaculture systems, which encompass nets, floating structures, and mooring lines, presents a significant challenge for traditional low- and medium-fidelity numerical approaches. These methods often rely on simplifying assumptions that are not applicable in such contexts. Modelling these systems in energetic seas necessitates solving multi-body problems subject to non-linear loads, wherein components such as nets undergo substantial deformations and exhibit non-linear behaviour. High-fidelity numerical models are therefore essential to accurately capture the intricate interactions between the fluid and the structuresThis thesis investigates the use of Computational Fluid Dynamics (CFD), based on the Smoothed Particle Hydrodynamics (SPH) method, as a high-fidelity tool for the numerical modelling of marine aquaculture systems in complex environmental settings. A methodology has been proposed and developed in which the net is represented as a set of fluid-driven elements connected through dynamic moorings. In this scheme, the particles that make up these elements interact directly with the particles that constitute the fluid, thereby establishing the fluid-structure interaction. This approach differs from other recent advances in the numerical modelling of these systems by integrating the net elements within the same simulation domain as the fluid, representing a significant advancement in the numerical modelling of these structures.This thesis is presented as a compendium of scientific articles organised into chapters, including conclusions and recommendations for future research. In Chapter 1, the context and relevance of the research problem are introduced. Chapter 2 presents the first article of the compendium, which describes the application and validation of the proposed methodology for the numerical modelling of aquaculture nets in currents. Chapter 3 includes the second article, which expands the approach by applying it to the modelling of an aquaculture cage with copper alloy nets at a 1:15 scale, subjected to current conditions representative of high-energy zones, and validates the results through comparison with experimental data. Chapter 4 presents a manuscript under review, which validates the modelling of the net cage under regular wave conditions and extends its application to a multi-component aquaculture system (cage and mooring system) subjected to the combined action of waves and currents. Finally, Chapter 5 presents the discussions and conclusions of this thesis. The results obtained demonstrate the effectiveness of the proposed approach as a high-fidelity tool for modelling aquaculture systems in challenging marine environments.
  

DOCTORAL DEGREE IN PHOTONICS

• ZARRAOA SARDÓN, LAURA: Photon counting with a single neutral atom: quantum efficiency, dark counts, and background rejection
  
  Author: ZARRAOA SARDÓN, LAURA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 05/12/2024
  Reading date: 27/02/2025
  Reading time: 10:00
  Reading place: ICFO, Mediterranean Technology Park, Avinguda Carl Friedrich Gauss, 3, 08860 Castelldefels, Barcelona
  Thesis director: MITCHELL, MORGAN | VEYRON, ROMAIN
  Committee:
       PRESIDENT: VON KLITZING, WOLF DIETRICH CARL
       SECRETARI: DE RIEDMATTEN, HUGUES
       VOCAL: HUGBART, MATHILDE
  Thesis abstract: This thesis studies the use of a single trapped neutral 87Rb atom as a photon counter. Detection of quantum jumps (QJs), i.e., abrupt changes between atomic states observable by a change in atomic fluorescence, is used to infer the arrival of single photons. This is referred to as the quantum jump photodetection (QJPD) technique.The thesis first situates QJPD in the context of photodetection. Compared to traditional detectors, QJPD technique has lower speed and quantum efficiency (QE), but has exceptional performance in other figures of merit: QJPD is intrinsically narrowband, has strong out-of-band rejection, and very low dark counts (DCs). These features make the QJPD interesting for applications that detect weak optical signals in the presence of a strong broadband background.Experimental methods to study QJPD are described. A 87Rb atom is loaded from a magneto-optical trap (MOT) into a far-off resonance trap (FORT) at the center of four orthogonal, co-focal, high numerical aperture lenses. These lenses create the FORT, couple probe light onto the atom and collect the atomic fluorescence, which is used to identify the atomic state. A typical QJPD sequence is presented, which consists of trapping and cooling an atom in the FORT, optically pumping it into the dark state, illuminating with probe light, illuminating with readout light and collecting fluorescence photons, and checking that the atom has not left the FORT during the sequence.Statistical methods for measurement of QE and DC contributions are introduced. These compare the observed fluorescence count distribution against measured hyperfine-state fluorescence distributions. A QE of (2.4±0.1)×e−3 is demonstrated, a record for single photon absorption by a single atom in free space.Dark count contributions are measured. To produce low DC, the QJPD technique is implemented in two time windows: an exposure time for the single photon absorption followed by a short fluorescence time to read out the atomic state. This implies distinct acquisition and readout DC contributions, similarly to CCD and CMOS detectors. A dark jump rate (analogous to CCD/CMOS dark current) is measured of (5 ± 10) × e−3 jumps/s, consistent with zero and limited by measurement statistics. The measured readout contribution is (4.0 ± 0.4) × e−3 jumps per ms of fluorescence readout. For a 1 Hz readout rate, with 1 ms readout pulses, a net dark count rate of (15 ± 10) × e−3 counts/acquisition is demonstrated, which is already competitive with any non-cryogenic detector.The background rejection capabilities of the system are tested by measuring quantum jump rates when the atom is illuminated with direct sunlight, and with light scattered by the atmosphere (skylight). A rate equation model is developed to describe QJ probabilities in the presence of both intense broadband background and weak resonant probe light. This model is used to interpret experiments in which a weak signal beam competes with strong broadband background and validated using direct sunlight. Measurements where the atom is illuminated with skylight show no observable background-induced QJs. Finally, measurements of sky brightness and its fluctuations are presented, showing large fluctuations even on mostly clear days, a factor that further increases the need for background rejection.A number of contemporary applications of extreme photodetection, including free-space quantum communication in daylight, classical optical communications in space, and fundamental physics experiments, are discussed as possible applications of the QJPD technique. A realistic scenario where the demonstrated QJPD capabilities surpass the current performance of commercial single photodetectors is presented.Finally, potential improvements are discussed. It is shown that existing atomic and optical technologies could be applied to reach different wavelength ranges, narrower bandwidths, higher quantum efficiency, and lower dark counts.
  

DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS

• NARAYANAN, SUBIN: Access Mechanisms for Massive Internet of Things in 5G and Beyond Networks
  
  Author: NARAYANAN, SUBIN
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SIGNAL THEORY AND COMMUNICATIONS
  Department: Department of Signal Theory and Communications (TSC)
  Mode: Normal
  Deposit date: 03/12/2024
  Reading date: 04/03/2025
  Reading time: 09:00
  Reading place: Aula C4-021B, EETAC, Castelldefels, Barcelona
  Thesis director: MERAKOS, LAZAROS | PASSAS, NIKOLAOS
  Committee:
       PRESIDENT: TRIANTAFYLLOPOULOU, DIONYSIA
       SECRETARI: RUIZ BOQUE, SILVIA
       VOCAL: LIOTOU, EIRINI
  Thesis abstract: The Massive Internet of Things (MIoT) characterizes a communication scenario where a massive number of battery-operated devices perform infrequent, primarily uplink-oriented small data transmissions to a network. The connectivity and management of a massive number of such devices pose challenges, and this thesis aims to tackle the issues related to the initial access mechanism of MIoT in the context of 5G and beyond networks. The thesis begins by conducting a thorough examination of both licensed and unlicensed spectrum technologies for the MIoT. Additionally, we investigate different test beds and simulators employed for the analysis. In the initial phase of the thesis, our focus is on examining existing standardized technologies in Massive IoT, with specific attention given to the Narrow-Band Internet of Things (NB-IoT) as a critical component for supporting MIoT in 5G networks. The performance of the NB-IoT access procedure is thoroughly analyzed under different network densities and combinations of configuration parameters. The findings lead to the development of an adaptive access mechanism that adjusts the access parameters based on the anticipated network density, improving the overall performance of the access procedure. In the subsequent stages of the study, we qualitatively analyzed network-based and User Equipment (UE) based relaying solutions for IoT applications, motivated by the fact that effective support of IoT requires cellular service in deep coverage areas. Relaying is a promising solution to extend the coverage while at the same time meeting the battery life requirements of IoT devices. While various relay-ing architectures and technologies have emerged in research and standardization, it is not yet clear which is best suited for IoT applications. Hence, we examine relay architectures and evaluate the suitability of UE-based relaying and network-based relaying solutions for IoT applications. We analyze the relaying solutions in terms of radio aspects, such as connection establishment, protocol architecture, and resource allocation. Our findings suggest that even though the standardized layer-2 network-based relaying solution (e.g., integrated access and backhaul networks) may be better suited to handle large numbers of low-complexity, low energy-consuming devices with better interference management, any optimizations aimed at supporting IoT traffic will directly affect existing networks, such as the introduction of new control plane signaling over the Uu interface. Conversely, the standardized layer-3 UE-based relaying solution can be optimized for handling massive IoT relaying with minimal impact on existing networks, since the optimizations can be made on the PC-5 interface with a subdued effect on the Uu interface. Based on the outcome of the qualitative study of relaying architecture, we analyze the suitability of layer-3 relaying over the New Radio (NR)-PC5 interface to support massive IoT applications. More precisely, we study the unicast connection establishment mechanism over the NR PC5 interface in a partial coverage scenario. Further, a set of optimizations on the NR-PC5 procedure to effectively support massive IoT applications are proposed and analyzed. The obtained performance evaluation results, which are presented in terms of data success probability, device power consumption, and signaling overhead, quantify how effectively the NR-PC5 interface can support the requirement of IoT in the 5G and beyond era. The proposed sidelink small data transmission and frame-level access provides the largest gain overall and can reduce the device power consumption by an average of 68 percent and signaling overhead by 15 percent while maintaining a data success probability of more than 90 percent in an International Mobile Telecommunications (IMT)-2020 defined IoT traffic scenario.
  

DOCTORAL DEGREE IN SUSTAINABILITY

• AGUDELO VALDERRAMA, VANESSA: Integración de la relación salud humana y cambio climático en el marco de la resiliencia urbana. Propuesta metodológica de evaluación y operacionalización en un contexto Latinoamericano
  
  Author: AGUDELO VALDERRAMA, VANESSA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 22/11/2024
  Reading date: 28/02/2025
  Reading time: 11:00
  Reading place: Defensa pública a l'Aula C1002 -Campus Nord- ETSECCPB
  Thesis director: MORATO FARRERAS, JORDI
  Committee:
       PRESIDENT: CORREIA GUEDES, MANUEL
       SECRETARI: ALVAREZ DEL CASTILLO, JAVIER
       VOCAL: MENA NIETO, ÁNGEL ISIDRO
  Thesis abstract: This study addresses the relationship between climate change and human health in the framework of urban resilience in a Latin American context. It sought to strengthen the climate and health components through conceptual harmonization and integration, as well as the identification of indicators within urban resilience measurement models. Thus, the first proposal of a model for measuring the urban resilience index adapted to Latin American cities is presented, specifically addressing the relationship between climate change and health. This model was validated and operationalized through a case study in two vulnerable communities in urban-rural transition areas in Santiago de Cali, Colombia.The approach included estimating five indicators of health, natural disasters, climate variability, socio-economic, governance, and satisfaction, where resilience negatively correlates with vulnerability. Given the limited monitoring and systematization of information in Latin American cities, much of the data was collected through structured interviews. The results revealed patterns characteristic of highly vulnerable Latino communities, such as a high degree of self-management to solve problems and improve quality of life. These findings provide elements to infer and prioritize communities with a strong sense of ownership, enabling the effective implementation of climate change adaptation and mitigation measures, given the high likelihood of ownership and continuity.
  
• YAZDIBAHRI, SEYEDEHSARA: Improving Thermal and Visual Comfort by Applying Parametric Design Panels on Adaptive Façade in Refurbishment Educational Building at Mediterranean Climate
  
  Author: YAZDIBAHRI, SEYEDEHSARA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN SUSTAINABILITY
  Department: University Research Institute for Sustainability Science and Technology (IS.UPC)
  Mode: Normal
  Deposit date: 14/01/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: ALIER FORMENT, MARC | SÁNCHEZ RIERA, ALBERTO
  Thesis abstract: This dissertation investigates the role of Double-Skin Façades (DSFs) in promoting sustainable building practices, focusing on their influence on energy efficiency, thermal and visual comfort, and social dynamics, particularly in urban settings. Given that buildings account for about 40% of global energy use, façades significantly impact energy performance, making their design a critical area for improving sustainability. This study employs a combination of empirical observations, advanced simulations, and parametric design tools such as Rhinoceros and Grasshopper to explore how DSFs can reduce energy consumption while enhancing the comfort and well-being of occupants.The research is structured around key performance indicators like Energy Use Intensity, Number of Hours in Thermal Comfort, and Spatial Glare Autonomy. The findings indicate that adaptive DSFs, when optimized, significantly improve building energy performance, reduce cooling and heating loads, and provide effective glare control—all while enhancing visual comfort. Moreover, DSFs help create socially dynamic environments by improving the aesthetic appeal of façades and fostering social interactions in urban areas.A case study in Barcelona highlights the broader applicability of these findings to Mediterranean climates, with implications for both new construction and retrofitting projects. By integrating advanced computational tools for multi-objective optimization, the study not only identifies façade configurations that balance energy efficiency and occupant comfort but also demonstrates how façades can enhance social engagement in densely populated urban spaces.In conclusion, the research provides architects and urban planners with actionable insights into the use of DSFs and parametric tools for sustainable building design, offering solutions that reduce energy consumption, improve occupant comfort, and encourage social interaction—key aspects of developing more sustainable urban environments.
  

DOCTORAL DEGREE IN THERMAL ENGINEERING

• VERA I FERNÁNDEZ, JORDI: Development of Algorithms for Enhancing Numerical Simulations in CFD & HT: Conjugate Heat Transfer, Moving Bodies, Indoor Air Quality, and Thermal Energy Storage
  
  Author: VERA I FERNÁNDEZ, JORDI
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN THERMAL ENGINEERING
  Department: Department of Heat Engines (MMT)
  Mode: Normal
  Deposit date: 09/01/2025
  Reading date: pending
  Reading time: pending
  Reading place: pending
  Thesis director: OLIVA LLENA, ASENSIO | PEREZ SEGARRA, CARLOS DAVID
  Committee:
       PRESIDENT: CORTÉS GRACIA, CRISTÓBAL
       SECRETARI: TRIAS MIQUEL, FRANCESC XAVIER
       VOCAL: FERNÁNDEZ SEARA, JOSÉ
  Thesis abstract: This thesis consists of the enhancement of numerical simulations in CFD \& HT (Computational Fluid Dynamics and Heat Transfer). The contents are divided into three blocks: CFD numerical methods, indoor air quality, and thermal energy storage (TES).The first block focuses on simulation methods for moving bodies. A new approach is introduced to enhance Conjugate Heat Transfer (CHT) simulations using the Immersed Boundary Method (IBM). This algorithm uses a two-mesh system to eliminate numerical errors in the solid energy equation caused by convective schemes that transport the solid's temperature field when using a single mesh.For rotating bodies, the Sliding Mesh Method (SMM) is applied, and an improvement to the face intersection algorithm is proposed. Additionally, a comparison between the IBM and the SMM is made using both a reference case and a newly proposed testing case.The second block studies the infection probability and air quality in indoor domains using CFD tools. A new methodology based on the Wells-Riley model is proposed to assess infection risk. The novel approach assesses various scenarios by performing a permutation for all possible locations of both infectious and susceptible individuals, generating an infection probability matrix that helps identify airflow patterns with either positive or negative impacts on infection rates.Finally, the new methodology, along with other air quality studies, is applied in a practical case involving an urban bus.The third block presents an advanced numerical simulation of a structured thermocline thermal energy storage system integrated with Concentrated Solar Power (CSP) plants. This storage system employs a single-tank configuration with a packed bed of ceramic filler materials, featuring channels for circulation of the Heat Transfer Fluid (HTF), a molten salt, to reduce costs and enhance thermal performance.A detailed mathematical model is developed to solve the unsteady 3D heat equation within the solid domain, coupled with 1D models for the HTC flow. This numerical model is then used for a parametric study to assess the impacts of geometric configurations, operational conditions, and cycle durations on the system's performance.In addition to the previously mentioned sections, two appendixes are included. The first appendix is closely related to the third block, focusing on the design of an experimental unit to validate the numerical models presented in that section. It provides a detailed description of the necessary components, including their operational and functional conditions. Preliminary experimental tests are conducted to assess the compatibility of filler materials and the properties of molten salts.Certain components, such as the heat exchanger, are analyzed in more detail using the methodology outlined in the second appendix. This second appendix compares the results of different CHT methodologies, including a 1D coupled model and a multidimensional CFD approach, to evaluate the behavior of heat exchangers under both steady and transient conditions. A new heat exchanger design is proposed and analyzed using this methodology. Finally, an experimental setup for the proposed design has been developed and prepared for testing.
  

DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY

• COLLANTES VELIZ, RUBEN DARIO: DESARROLLO DE UN SISTEMA DE APOYO A LA TOMA DE DECISIÓN PARA LA EVALUACIÓN CUANTITATIVA DE LOS EQUIPOS DE APLICACIÓN DE PRODUCTOS FITOSANITARIOS EN FUNCIÓN DEL RIESGO MEDIOAMBIENTAL
  
  Author: COLLANTES VELIZ, RUBEN DARIO
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN AGRI-FOOD TECHNOLOGY AND BIOTECHNOLOGY
  Department: Department of Agri-Food Engineering and Biotechnology (DEAB)
  Mode: Change of supervisor
  Deposit date: 24/01/2025
  Deposit END date: 06/02/2025
  Thesis director: GIL MOYA, EMILIO | SCHLOSSER, JOSE FERNANDO
  Thesis abstract: Since the adoption of the Machinery Directive 2009/127/EC and theimplementation of the new Machinery Regulation (EU) 2023/1230, which willbe mandatory from 2027, manufacturers of agricultural sprayers have beenrequired to ensure that their equipment is technologically sound and suitablefor sustainable use. Technology is a key resource that can significantlycontribute to increasing agricultural production while enabling the safe andsustainable use of crop protection products to protect human health and theenvironment. Machinery for applying crop protection products plays a crucialrole in the agricultural sector. However, despite the availability of advancedtechnology, many machines still do not meet the design standards required bylegislation. Additionally, manufacturers often face difficulties in accessing these regulations, which affects the production process. In some cases,performing the necessary tests to certify the compliance of their equipment presents an additional challenge. In this context, the aim of this work was todevelop a decision support system for quantifying and classifying pesticide application equipment based on the risk of contamination and the degree ofcompliance with European regulations. This system takes into consideration the technical criteria established in the ISO 16119 and ISO 16122 standardsfor evaluating and classifying application equipment. Another aim is also to promote this support in Latin American countries where it is not yet fullymandatory to test application equipment, nor are they required to be designed or manufactured with the protection of human health and the environment inmind. The system has been validated on boom sprayers and airblast sprayers manufactured in Spain, Brazil and Peru. The results indicate specific areas forimprovement, mainly in the cleaning systems and in the information provided in the instruction manual. This system can be a valuable tool formanufacturers, helping them optimize their products while ensuring the protection of crops, the environment and human health.
  

DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE

• PITARCH ABAIGAR, CARLA: Advances towards a robust AI-based glioma grading system
  
  Author: PITARCH ABAIGAR, CARLA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ARTIFICIAL INTELLIGENCE
  Department: Department of Computer Science (CS)
  Mode: Normal
  Deposit date: 24/01/2025
  Deposit END date: 06/02/2025
  Thesis director: VELLIDO ALCACENA, ALFREDO | RIBAS RIPOLL, VICENTE JORGE
  Thesis abstract: Gliomas represent the most common and aggressive form of primary brain tumors in adults, posing significant diagnostic challenges due to their heterogeneous molecular, histological, and radiological characteristics. The World Health Organization (WHO) classifies gliomas on a four-stage scale, ranging from the most benign to the most malignant. The latest WHO Central Nervous System (CNS) diagnostic criteria releases incorporate molecular and histological features for subtyping and grading. However, this process is complex, time-consuming, and prone to inter-observer variability. While histological assessment remains the standard method for glioma characterization, it is invasive and limited in cases where tissue extraction is not feasible, highlighting the need for non-invasive alternatives. This dissertation investigates the application of deep learning algorithms to multi-sequence Magnetic Resonance Imaging (MRI) for the automatic grading of gliomas. First, we integrated and homogenized MRI data from three well-known publicly available datasets resulting in a collective database exceeding one thousand cases. Initial efforts focused on understanding the multi-sequence MRI data, assessing artifacts, and evaluating techniques such as data normalization, data augmentation, transfer learning, and tumor patching, to enhance the classification between lower- and high-grade gliomas, benchmarking with the state-of-the-art. In the second phase, we extend the classification to glioma grades as defined by the WHO CNS 2016 criteria. We developed and compared different Convolutional Neural Networks (CNNs) architectures based on 2D slices from single anatomical planes, multi-planar integrations, and entire 3D volumes. Recognizing the strong association between glioma aggressiveness and genetic features like IDH mutations and 1p/19q co-deletions, we developed a multi-task framework capable of classifying the glioma grade and these molecular features simultaneously, allowing the network to learn contextual relationships among variables. To prevent healthcare disparities and foster the reliability and transparency of our findings, we evaluated model performance across different demographic and clinical populations, including sex, age, and molecular subgroups.Our results reveal consistent challenges in accurately classifying grade 3 gliomas, underscoring the need for further research, as well as more diverse and up-to-date data that aligns with current guidelines. While Artificial Intelligence (AI) holds immense potential to assist in medical diagnosis, prognosis, and therapy planning, its full adoption in the medical field remains limited largely due to a lack of trust and widespread acceptance among healthcare professionals and patients. The ultimate goal of this thesis is to explore the implications and limitations of integrating AI algorithms in healthcare and foster collaboration among clinicians and technologists to achieve patient-centric, reliable AI within clinical practice.
  

DOCTORAL DEGREE IN BIOINFORMATICS

• FLORES MUÑOZ, PABLO JAVIER: Functional Similarity Between Feature Lists Based on the Joint Enrichment of the Gene Ontology Terms.
  
  Author: FLORES MUÑOZ, PABLO JAVIER
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN BIOINFORMATICS
  Department: School of Mathematics and Statistics (FME)
  Mode: Normal
  Deposit date: 24/01/2025
  Deposit END date: 06/02/2025
  Thesis director: SÁNCHEZ PLA, ÀLEX | OCAÑA REBULL, JORDI
  Thesis abstract: The advent of omics technologies, such as high-throughput experiments, has revolutionized modern biology. They allow the study of the behavior of hundreds of features (such as genes, proteins, or metabolites) under different experimental conditions. While obtaining feature lists from these experiments suggests substantial progress, it is more relevant to provide functional meaning to these lists, that is, to understand and evaluate the biological significance of their elements.This work concentrates on developing a method to identify the functional similarity between a set of feature lists. The method is based on the premise that two or more feature lists reveal biological similarity if they share a significant proportion of enriched GO terms.The metric selected to assess this proportion is obtained from the Sorensen-Dice index, which we proved follows an asymptotically normal distribution; however, in cases of low enrichment, a distribution based on the Bootstrap approach is more suitable.This asymptotic analysis has led to the development of a statistic hypothesis test based on the equivalence approach, enabling the inference of biological similarity between two or more lists when the Sorensen dissimilarity is null, except for an irrelevant deviation, which is defined by an irrelevance limit developed according to the geometric bioavailability ratio, which prevents using an arbitrary irrelevance limit, typically associated with most tests using this equivalence approach.This hypothesis test has been tested through a simulation study, which proves that it works effectively, maintaining a controlled type I error probability and acceptable power. In addition, a dissimilarity matrix has been developed based on the irrelevance limit that makes the compared lists equivalent. The values of this matrix measure the degree of functional similarity between the compared lists. Their graphical representation allows for observing a grouping structure according to the degree of biological similarity. From this, detecting the biological functions associated with these clusterings has been possible.The R-package goSorensen, hosted on Bioconductor, is a validated computational tool for effectively managing this analysis's extensive inputs and outputs. This R-package has been built to apply the method proposed in this thesis.The method has been implemented on real gene lists. The results facilitated the visualisation of outputs and enabled a comparison of the method's consistency and efficacy against alternative methods employed for analogous purposes.
  

DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING

• BELLVER CATALÁ, MARTA: Phycobiliprotein production with cyanobacteria-rich cultures and microbiomes
  
  Author: BELLVER CATALÁ, MARTA
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 22/01/2025
  Deposit END date: 04/02/2025
  Thesis director: FERRER MARTI, IVET
  Thesis abstract: Phycobiliproteins are pigments found in cyanobacteria, which are exploited in the food, cosmetic, and pharmaceutical industries. However, the large-scale production of these bio-based products has high production costs. To address this issue, various strategies have been explored, nutrient recovery from wastewaters being among the most studied. However, due to the potential presence of contaminants in waste streams, the market application and social acceptance of these products would be limited. Recently, the use of photosynthetic microbiomes for valuable compounds production, has shown promising stability and productivity in comparison with monocultures. Hence, the first objective was to couple phycobiliprotein production with tertiary wastewater treatment using cyanobacteria monocultures. The second one, was to optimize and scale-up of phycobiliprotein production by cyanobacteria-rich consortia. The last objective, was to provide an example for the application of these pigments: the formulation of biomaterials.Firstly, the assessment of the pigment production potential of two wastewater-borne cyanobacteria genera (namely Synechocystis sp. and Synechococcus sp.) was approached in synthetic medium. Next, their ability to grow on and remove nutrients upon tertiary wastewater treatment, and their pigment production capacity was evaluated in semi-continuous photobioreactors. The presence of contaminants of emerging concern (CEC) was analyzed, in view of the potential application of the pigments recovered. Finally, the pigment-extracted biomass was used for the production of biogas within a biorefinery concept. This study demonstrated that both Synechococcus sp. and Synechocystis sp. removed the nutrients from secondary effluent, achieving nutrient removal efficiencies of up to 83% for N-NH₄+ and 97% for P-PO₄³-, along with stable biomass concentrations around 500 mg VSS L⁻¹. Regarding phycobiliprotein recovery, Synechococcus sp. exhibited a notably high pigment production potential, reaching up to 214 mg total phycobiliproteins gDW⁻¹ in secondary effluent. In contrast, Synechocystis sp. maintained steady pigment concentrations around 70 mg total phycobiliproteins gDW⁻¹ throughout the whole cultivation period. Moreover, out of 22 contaminants detected in the secondary effluent, only 3 were present in the phycobiliprotein extracts. Finally, the anaerobic digestion of phycobiliprotein-extracted biomass produced 222 NL CH₄ kg VS⁻¹.Afterwards, the optimization of pigment production in 6 cyanobacteria-rich microbiomes was developed, through their irradiation with different light qualities (white, green, blue and red) during 4 and 6 days. Next, the process was scaled-up under the optimal conditions, the pigments content quantified, and the antioxidant bioactivity of harvested biomass analyzed. At the same time, a preliminary model to predict the phycobiliprotein content from hyperspectral data was developed. According to the results, green light irradiation significantly increased the phycobiliprotein content in all the tested microbiomes, and a 4-day exposure period was the optimum in 5 of the microbiomes. The highest total phycobiliprotein content reached was 145.5 mg gDW⁻¹. When the process was scaled-up, the phycobiliprotein production was maintained over a period of 69 days, and promising antioxidant activities and phenolic contents were detected in harvested biomass. The model generated from hyperspectral images showed a good training performance for phycocyanin and allophycocyanin estimation, but future work should focus on producing a large pool of hyperspectral images to validate it.Finally, the addition of phycobiliprotein-rich extracts into biomaterials, evidenced how people out of academia were eager to learn about cyanobacteria and their potential applications in everyday processes. Social acceptance is vital for shaping a future based on pigments.
  
• CEBOLLA ALEMANY, JOAQUIM: Nanoparticle modeling in industrial settings
  
  Author: CEBOLLA ALEMANY, JOAQUIM
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN ENVIRONMENTAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 24/01/2025
  Deposit END date: 06/02/2025
  Thesis director: MACARULLA MARTÍ, MARCEL | VIANA RODRIGUEZ, MARIA DEL MAR
  Thesis abstract: Nanoparticles (NPs) are incidentally generated in the industry by multiple material transformation processes, especially by highly energetic activities. This type of aerosol, due to its small size, poses a significant threat to human health. This circumstance is particularly relevant for workers in industrial settings due to the elevated concentrations present in these spaces. Therefore, prediction, estimation, and control of environmental NPs have become issues of growing concern. However, NP concentration simulation and emission estimation for industrial indoor air quality applications still present problems derived from uncertainty quantification, the effect of unmodeled activities functioning as disturbances for the system, and computationally efficient simulations that can be used in industrial management and optimization algorithms.This PhD thesis addresses these issues through five main objectives: (I) to evaluate and optimize size ranges in sectional models; (II) to simulate industrial concentration through stochastic modeling; (III) to design a method to quantify industrial incidental NP emission rates; (IV) to deploy deterministic concentration simulations in multidomain problems to enable easy-to-use risk management application for non-expert users; (V) to propose a framework to coordinate indoor air quality and industrial management for energy optimization of mechanical ventilation systems.For this purpose, the research is structured in four parts. First, size-resolved data processing was conducted through a k-means clustering algorithm applied to combustion NPs from a laboratory experiment. This analysis showed a modal cluster containing more than 80% of particle number concentrations in three different experiments, pointing towards effective deployment of total concentration models for NP simulation and indicating a potential accuracy of these models above the instruments’ tolerance.Consequently, total particle number concentration reduced-order models were evaluated through stochastic and derived deterministic approaches in different industrial scenarios with pulsing and continuous activities. The stochastic method allowed the parameterization, calibration, and validation of model parameters, which enabled their translation into deterministic models, showing Pearson correlation coefficients above 0.9 and average accuracy above 80% for different simulated points, respectively.Then, based on the validated stochastic method, a systematic approach for industrial emission rate determination was designed and applied based on the literature to 7 datasets involving a total of 16 concentration time series in four scenarios, testing 79 models for high-velocity oxy-fuel spraying, atmospheric plasma spraying, and ceramic tile firing. This method was applied first for confined NP sources, and then to non-confined activities, showing estimations consistent with previous studies and between datasets, requiring major efforts and complexity for non-confined sources’ application, with a slight decrease in correlation from 0.9 to 0.8 for some of the simulated points. Additionally, this research emphasized the significance of emission and mechanical transport processes, while deposition and aggregation were found non-statistically significant in the monitored scenarios.Finally, a new framework using artificial intelligence algorithms and multidomain simulations was conceptualized to improve building energy management in industrial production contexts using reduced-order models. Their application was exemplified and evaluated in thermal spraying case studies, showing flexibility to adapt to multiple scenarios considering photovoltaic energy self-consumption, energy flexibility, and cost minimization.
  

DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING

• GARCIA NUÑEZ, LUIS MIGUEL: Evaluación de la resistencia residual. Efecto de la velocidad de corte, temperatura e interacción termo-hidro-mecánica (THM)
  
  Author: GARCIA NUÑEZ, LUIS MIGUEL
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN GEOTECHNICAL ENGINEERING
  Department: Department of Civil and Environmental Engineering (DECA)
  Mode: Normal
  Deposit date: 03/02/2025
  Deposit END date: 14/02/2025
  Thesis director: LLORET MORANCHO, ANTONIO | PINYOL PUIGMARTI, NURIA MERCE
  Thesis abstract: The study of residual soil strength and its dependence on intrinsic, external, and coupled effects has gained significant scientific interest due to its relevance in geotechnical field. This doctoral thesis experimentally analyzes the shear behavior of soils under residual conditions, focusing on the effects of shear rate, temperature, and coupled thermo-hydro-mechanical (THM) processes.To investigate shear rate and temperature effects, 26 tests with progressive shear rate increments and 70 tests under controlled temperature conditions were conducted on various fine-grained soils. A modified Bromhead ring shear apparatus was used to test shear rates from 0.089 mm/min to 45 mm/min and temperatures from 0 °C to 60 °C under normal stresses of 100, 200, and 300 kPa. The results were analyzed using the rate-, state-, and temperature-dependent friction (RSTF) model. Additionally, scanning electron microscopy (SEM) and interferometric imaging were used to examine shear surfaces.For coupled THM effects, 15 rapid shear tests were performed on Canelles clay, a low-permeability material, using a high-speed ring shear prototype developed at UPC. This device was modified to record temperature and pore pressure during shearing. The results were interpreted using a deformation compatibility model, which successfully reproduced observed deformations and pore pressure changes.The results indicate that heating reduces friction, while cooling increases resistance. At a constant temperature (~20 °C) and normal stress (100–300 kPa), increasing the shear rate generally increased resistance, except in Barcelona silty clay (the least plastic soil), where resistance decreased under 100 kPa normal stress. Other influencing factors include normal stress, clay fraction, plasticity index, specific surface area, activity, and smectite fraction.For rapid shear tests on Canelles clay, thermal dilation effects were significant at shear rates above 0.5 km/h. Pore pressure increased by approximately 2 kPa/°C for temperature rises below 20 °C and 5 kPa/°C for rises above 25 °C. If the soil volume had remained constant, frictional heating would have caused even higher pore pressure increases, reducing effective confining stress and shear strength.In conclusion, residual soil strength is influenced by shear rate, temperature, and THM effects, which are critical for understanding soil behavior in stability assessments.
  

DOCTORAL DEGREE IN PHOTONICS

• PASCUAL GARCÍA, CARLOS: Continuous Variable Quantum Communications: Technologies and Security
  
  Author: PASCUAL GARCÍA, CARLOS
  Thesis file: (contact the Doctoral School to confirm you have a valid doctoral degree and to get the link to the thesis)
  Programme: DOCTORAL DEGREE IN PHOTONICS
  Department: Institute of Photonic Sciences (ICFO)
  Mode: Normal
  Deposit date: 03/02/2025
  Deposit END date: 14/02/2025
  Thesis director: ACÍN DAL MASCHIO, ANTONIO | BÄUML, STEFAN MARKUS GEORG
  Thesis abstract: With this Thesis, we will focus on diverse technologies as well as techniques relevant for the development of secure communication systems based on Quantum Mechanics. This theoretical analysis involves the application of diverse methodologies, which represent formidable challenges from a purely analytical perspective, as well as from a numerical stance. The contents of this manuscript are divided according to the nature of the particular technology under scrutiny.As a first step, we will provide a study of Quantum Key Distribution based on continuous variable states and coarse-grained measurements. This inquiry is split according to two chapters. In the first one, a thorough description of our approach will be provided, as well as diverse outcomes regarding the addition of postselection techniques for an improved perfomance; a study of optimization in infinite dimensions, as well as results in the finite regime under collective attacks. In the second part, we will observe how performing a full discretization on the measurements grants not only full security against any adversary allowed by Quantum Mechanics, but also a new formalism via entropy accumulation approaches that permits the analysis of the statistical fluctuations that emerge when only finite statistics are accessible.This discussion will be followed by a study of Quantum Random Number Generation according to a semi Device Independent perspective where the assumptions on the experimental setups are limited. Our discussion will be based on using a trusted measurement and imposing a bound on the corresponding expectation value -- which requires an adaption from the well-known asymptotic limit to the the finite case in order to prevent emerging security pitfalls. This examination is completed with a thorough security proof against general attacks and diverse results in the finite regime. To conclude, this Thesis finishes with an assessment of Quantum Key Distribution for large networks based on classical Internet models, which provides insights on the scalability and optimality conditions of Quantum Communications according to the density of users and their connections. In particular, this indagation is mainly based on continuous variable systems, albeit another approach grounded on discrete variables is also added to the model in order to enhance its performance.