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- Exceptional embeddings of N=2 minimal models(2026) Ros Camacho, Ana; Wasserman, Thomas A.Vafa and Warner observed that the Landau-Ginzburg model associated to the potential E6 (resp. E8) is a product of two other models, associated to the potentials A2 and A3 (resp. A2 and A4). We translate this along the LandauGinzburg / Conformal Field Theory correspondence to a conjecture about the unitary minimal quotients Md of the N = 2 superconformal algebra of central charge cd = 3−6 d : there should be a conformal embedding M12 → M3⊗M4 (resp. M30 → M3⊗M5) that exhibits the product as Ostrik's E6 (resp. E8) algebra in the Rep(su(2)10) (resp. Rep(su(2)28)) factor of the NS-sector of Rep(M12) (resp. Rep(M30)). We motivate, formulate, and prove this conjecture.
- Evaluating Distributed Communication Architectures for GPU-Accelerated Image Encoding(2026) Zheng, Haojie; Reaño, Carlos; Ariño-Sales, Juan F.Artificial intelligence (AI) has transformed how we engage with visual data, particularly within the context of enterprises. Multi-modal codification systems enable the creation of semantic connections between text and visual data using AI models. This opens new markets for businesses by enabling visual search engines, recommendation systems, and automatic tagging of visual data. However, implementing these systems presents significant technical challenges. The typical workflow involves encoding images using an AI model, converting these representations into semantic vectors, and inserting them into databases optimized for fast searches. This not only affects technical efficiency but also impacts the ability of companies to scale these systems to a commercial level. This paper presents a comprehensive comparative analysis of communication architectures for large-scale image encoding systems, evaluating gRPC, RabbitMQ, serverless Lambda, and SageMaker approaches across performance and resource efficiency dimensions. Through controlled experiments processing up to 18,000 images using the SigLIP model, we establish clear performance-architecture relationships that inform system design decisions for visual content-based search applications.
- Augmentation of singularities: quasi-homogeneity and good real images of map-germs(2026) Breva Ribes, Ignacio; Oset Sinha, Raúl; Escola de DoctoratWe study how the process of augmentation of singularities of map-germs preserves certain properties of the augmented map-germ and its augmenting function. In particular, we give sufficient criteria to determine when the simplicity of the latter two implies the simplicity of the augmentation, and we give two upper bounds on the codimension of the augmentation with respect to left-right equivalence. One of these bounds allows us to prove the Mond conjecture for augmentations of map-germs which satisfy the Mond conjecture, reducing the problem to non-augmentations. We give a characterization of when a map-germ is in the A -class of an augmentation, correcting a previous result by Houston. We also characterize simplicity in the case that the augmented map-germ has codimension 1 (in the left-right equivalence sense) or that the augmenting function is a Morse singularity. The problem of whether the A -class of an augmentation depends on the choice of 1-parameter stable unfolding is also tackled via two methods, one using an adaptation of Favaro and Mendes’ ϕ-equivalence, and another via comparison of the Ae -normal spaces of augmentations. In total, we conclude that when augmenting by quasi-homogeneous functions or by substantial unfoldings the choice of stable unfolding is irrelevant. This allows us to describe a full classification of simple augmentations of equidimensional map-germs in dimension 4. We generalize the concept of substantial 1-parameter stable unfoldings to stable unfoldings in any number of parameters, showing that substantiality of the stable unfolding is a necessary condition for a map-germ to be quasi-homogeneous in some coordinate system. This provides an easily computable method to discard the quasi-homogeneity of a given map-germ. Some partial results are obtained for the converse implication, showing that equidimensional map-germs with minimal stable unfolding or multiplicity 3 are equivalent to a quasi-homogeneous map-germ if and only if they admit a substantial unfolding. All of this leads us to conjecture that substantiality characterizes quasi-homogeneity in general. Finally, we give a necessary condition on when a map-germ admits a good real image, that is, when the image Milnor number of a complex map-germ can be realized by a real representative, for finitely determined map-germs with source dimension lower than target dimension. Concretely, we show that for corank 1 map-germs admitting a good real image, the non-empty, positive dimensional multiple point spaces must have Milnor number at most 1. Moreover, this condition gives clues on how to obtain such a perturbation if it exists. We show this with examples and provide context on how a classification of jets of map-germs can be obtained. A conjecture by Cooper and Mond is also solved, showing that the homotopy type of a good real perturbation is the same as that of its complexification, for map- germs parametrizing hypersurfaces. The proofs for this last part rely heavily on results from Smith theory, of which we give a description in the annex.
- Drone arc routing problems with multiple depots and other variants(2026) Corberán Fabra, Teresa; Plana Andani, Isaac; Sanchis Llopis, José María; Escola de DoctoratThe rapid development of unmanned aerial vehicles (drones) has created new opportunities for inspection, monitoring, and service operations along linear infrastructures such as power lines, pipelines, railway tracks, and road networks. These applications naturally lead to arc routing problems in which drones must traverse and service network elements. Unlike classical arc routing problems involving ground vehicles, drone-based routing allows vehicles to move freely in space and to enter and exit required lines at arbitrary points, which results in continuous optimization problems with an infinite set of feasible solutions. Solving such continuous problems directly is computationally challenging. A common approach consists of discretizing the continuous network by approximating each line with a polygonal chain and restricting drone entry and exit to a finite set of points, thus transforming the original problem into a large but finite combinatorial optimization problem. If the discretization is sufficiently fine, the solutions obtained for the discrete problem provide high-quality approximations of the continuous optimal solutions. Within this setting, this thesis studies several arc routing problems motivated by drone inspection and service applications. The problems considered combine features of classical arc routing and general routing problems with multiple depots, location decisions, and multiple trips, while explicitly incorporating drone-specific constraints such as limited flight duration and capacity. Although the original problems are continuous in nature, the thesis focuses on discrete formulations for which exact and heuristic methods are developed. The first problem addressed is the Multi-Depot drone General Routing Problem with duration and capacity constraints (MDdGRP). In this problem, a fleet of identical drones, each assigned to a predetermined depot, must jointly service a set of required lines and visit demand nodes while respecting flight duration and capacity limitations. A discrete formulation, the MDGRP, is proposed and strengthened through valid inequalities. A branch-and-cut algorithm is developed, together with two matheuristics specifically designed to handle the continuous nature of the original problem. The thesis then considers the Min Max Multi-Trip drone Location Arc Routing Problem (MM-MT-dLARP), which considers the interaction between drones and ground support vehicles. In this setting, trucks transport drones from a central depot to selected launching points, from which the drones perform multiple flights to service the required lines. A discretized version of the problem, the MM-MT-LARP, is formulated and its associated polyhedron is studied. Moreover, a branch-and-cut algorithm and a matheuristic method capable of obtaining high-quality solutions for large instances are developed. The MM-MT-LARP is a complex problem for which branch-and-cut methods struggle to obtain optimal solutions within short computational times. Since the solutions of this problem typically comprise a large number of trips, a column generation approach is particularly well suited to tackle it. Consequently, the last part of this thesis is devoted to a slight generalization of the MM-MT-LARP, for which a new formulation and an exact solution approach based on a branch-and-price algorithm are proposed. Unlike the previous problem, this new version is studied from a more general arc routing perspective and is no longer interpreted in a drone-specific context. Launching points are treated as potential depots with opening costs, and vehicles are considered in a generic way. The branch-and-price algorithm avoids imposing predefined limits on the number of trips and significantly improves computational performance, enabling the solution of instances that can not be solved with traditional branch-and-cut algorithms. The computational results obtained throughout the thesis clearly show that addressing drone arc routing problems requires the combination of different methodological approaches. Exact algorithms provide good results for small and medium-sized instances, while matheuristic procedures are essential to obtain high-quality solutions for larger and more realistic scenarios, as they can progressively refine the discretization by introducing intermediate points along required lines.
- La influencia de la comprensión lectora y del razonamiento verbal en el aprendizaje de la resolución aritmética de problemas verbales aritmético-algebraicos(2026) Pérez Buj, Gema; Arnau Vera, David; Diago Nebot, Pascual David; Departament de Didàctica de les MatematiquesLa resolución de problemas ocupa un lugar central en la educación matemática, aunque evaluaciones como PISA evidencian dificultades persistentes del alumnado en los problemas verbales. Estos requieren comprender el enunciado, establecer relaciones entre cantidades y traducirlas a una estructura matemática. La tesis analiza si una instrucción basada en los nombres de las cantidades, en lugar de sus valores numéricos, favorece una comprensión más profunda y la activación de esquemas conceptuales. Participaron 102 estudiantes de quinto de Primaria utilizando el sistema tutorial inteligente HINTS. Se compararon dos condiciones: una basada en representaciones numéricas y otra en descripciones escritas de las cantidades. Los resultados muestran relación entre resolución de problemas, comprensión lectora y capacidad de nombrar cantidades. Además, el análisis cualitativo permitió identificar distintas actuaciones y patrones cognitivos del alumnado durante la resolución de problemas.
- Methodology for microbiome data analysis: An overview(2025) Creus Martí, Irene; Moya Simarro, Andrés; Santonja Gómez, Francisco JoséIt is known that microbiome and health are related, in addition, recent research has found that microbiome has potential clinical uses. These facts highlight the importance of the microbiome in actual science. However, microbiome data has some characteristics that makes its statistical study challenging. In recent years, longitudinal and non-longitudinal methods have been designed to analyze the microbiota and knowing more about the bacterial behavior. In this article in the form of a review we summarize the characteristics of microbiome data and the statistical methods most widespread to analyze it. We have taken into account if the strategies are longitudinal or not. We also classify the methods based on their specific analytical objectives and based on their mathematical characteristics. The methods are structured according to their biological goals and mathematical features, ensuring that the insights provided are both relevant and accessible to professionals in biology and statistics. We present this review as a reference for the most widely used methods in microbiome data analysis and as a foundation for identifying potential areas for future research. We want to point out that this review can be particularly useful to remark the importance of the methodology designed in order to study microbiome longitudinal datasets.
- Scaling Computer Vision: A Comparative Analysis of Cloud Infrastructures for AI-Based Image Processing and Classification Applications(2026) Zheng, Haojie; Reaño, Carlos; Castillo, Alberto; Ariño-Sales, Juan F.; Igual, Álvaro; Igual, CarlesArtificial intelligence-driven computer vision has undergone rapid expansion in recent years, largely propelled by progress in deep learning techniques and the availability of extensive annotated datasets. Nevertheless, the large-scale adoption of such systems remains challenging for many organizations due to financial constraints and technological complexity. In this context, cloud computing has become an appealing alternative, as it offers elastic, on-demand resources under a pay-as-you-go model. Despite these advantages, the use of cloud platforms also introduces specific challenges for computer vision applications. One of the key open issues concerns the assessment of whether it is better to use classical Infrastructure (IaaS) or Containers (CaaS) to build applications. In this paper, we evaluated and compared these two models by using a real-world use case: an AI-based image processing and classification application. The best-performing model achieved speed-ups of up to 2.12× and reduced resource consumption and costs by up to 22% compared with the other evaluated alternatives.
- Enhancing PPE delivery and registration through augmented reality technology(2026) Riera, José V.; Reaño, Carlos; Romero, Verónica; Morillo Tena, Pedro; Casas Yrurzum, SergioIn most developed countries, legislation on personal protective equipment (PPE) requires employers not only to provide PPE to their workers but also to record the process in order to ensure adequate traceability. While employers are obligated to register the delivery of PPE, this process is often conducted manually, leading to mistakes and potential inaccuracies. This paper proposes an Augmented Reality (AR)-based system designed to streamline PPE delivery and registration by integrating marker-based recognition, mobile AR visualization, and interactive training modules. The system allows workers to scan PPE items using QR codes, ensuring automated tracking and digital record-keeping, while also providing on-demand safety training videos linked to each piece of equipment. A user study with 45 participants was conducted to evaluate the system's usability, cognitive workload, and user satisfaction. The results indicate a high usability rating, with a System Usability Scale (SUS) score of 83.5, placing the system in the 'excellent' category. The NASA Task Load Index (NASA-TLX) assessment revealed low mental and physical demand, confirming its accessibility for users with varying experience levels. Despite these positive outcomes, challenges such as technological adoption barriers, hardware ergonomics, and scalability concerns were identified. The findings suggest that AR-based PPE management ensures compliance and provides an efficient digital alternative to conventional PPE tracking in construction environments.
- Singularities of Frontal Map Germs(2026) Muñoz Cabello, Christian; Nuño Ballesteros, Juan José; Oset Sinha, Raúl; Departament de Geometria i TopologiaA smooth map f: N^n -> Z^{n+1} is a wave front if it can be lifted onto an integral immersion i: N -> W^{2n+1}, with target on a contact manifold W, via a Legendrian fibration W -> Z. The problem of classifying wave fronts under A-equivalence (smooth changes of coordinates in the source and target) dates back to the 1970s, where Arnold and his colleagues from the Russian school of singularities prove that every wave front can be written in terms of a family of functions g: R^d x R^n -> R, which they call a Morse family of hypersurfaces (see Arnold et al, 2012, S 20.7). This allows them to apply Arnold's ADE classification of smooth functions (Arnold, 1972) in order to establish a classification of stable wave fronts up to dimension 10 in (Zakalyukin, 1976) (later corrected in Arnold et al, 2012, S 21.7). (Ishikawa, 2005) extends these results by defining a theory of Legendrian equivalence for integral maps N -> W (not necessarily immersive), establishing a notion of Legendrian codimension similar to Mather's A-codimension, that characterises Legendrian stable integral maps in several different ways and gives a method to construct a versal deformation of a generic integral map, similar to Martinet's theorem (Martinet, 1976); see also (Mond and Nuño-Ballesteros, 2020, Theorem 5.1). (Fujimori et al., 2008) define the notion of frontal maps f: N -> Z. For us, a map N -> Z is frontal if it can be lifted onto an integral map N -> W via a Legendrian fibration W -> Z. In this work, we define a theory of equivalence on the level of frontal map germs that is equivalent to Ishikawa’s theory of Legendre equivalence. We show that the Mather-Gaffney criterion (see Mond and Nuño-Ballesteros, 2020, S 4.5) for smooth map germs has a frontal counterpart, and give a method to compute stable and versal frontal unfolding of corank 1 frontal map germs. We investigate the double point set of a corank 1 frontal map germ and define the source transverse double point set, giving formulas that parallel the Marar-Mond formula from (Marar and Mond, 1989). We study the vanishing cycles of a frontal map germ following the work of Mond (Mond, 1985; Mond, 1991) defining the notion of frontal Milnor number and giving a formula to compute it in terms of the Samuel multiplicity. We also prove that wave fronts verify the Mond conjecture and give an expression for the frontal Milnor number of a corank 1 frontal surface. Finally, we use the methods previously developed to classify the corank 1 stable frontal map germs (C^3,S) -> (C^4,0), and give a complete intersection ring that allows to compute the number of D4 singularities in a generic perturbation of a wave front.
- Evidence of the cooperative response of Blattella germanica gut microbiota to antibiotic treatment(2023) Creus Martí, Irene; Marín Miret, Jesús; Moya Simarro, Andrés; Santonja Gómez, Francisco JoséGut microbiota plays a key role in host health under normal conditions. However, bacterial composition can be altered by external factors such as antibiotic (AB) intake. While there are many descriptive publications about the effects of AB on gut microbiota composition after treatment, the dynamics and interactions among the bacterial taxa are still poorly understood. In this work, we performed a longitudinal study of gut microbiome dynamics in B. germanica treated with kanamycin. The AB was supplied in three separate periods, giving the microbiota time to recover between each antibiotic intake. We applied two new statistical models, not focusing on pair-wise interactions, to more realistically study the interactions between groups of bacterial taxa and how some groups affect a single taxon. The first model provides information on the importance of a given genus, and the rest of the community, to define the abundance of that genus. The second model, on the other hand, provides details about the relationship between groups of bacteria, focusing on which community groups affect the taxa. These models help us to identify which bacteria are community-dependent in stress conditions, which taxa might be better adapted than the rest of the community, and which bacteria might be working together within the community to overcome the antibiotic. In addition, these models enable us to identify different bacterial groups that were separated in control conditions but were found together in treated conditions, suggesting that when the environment is more hostile (as it is under antibiotic treatment), the whole community tends to work together.
- Bayesian Hierarchical Compositional Models for Analysing Longitudinal Abundance Data from Microbiome Studies(2022) Creus Martí, Irene; Moya Simarro, Andrés; Santonja Gómez, Francisco JoséGut microbiome plays a significant role in defining the health status of subjects, and recent studies highlight the importance of using time series strategies to analyse microbiome dynamics. In this paper, we develop a Bayesian model for microbiota longitudinal data, based on Dirichlet distribution with time-varying parameters, that take into account the compositional paradigm and consider principal balances. The proposed model can be effective for predicting the future dynamics of a microbial community in the short term and for analysing the microbial interactions using the value of the estimated parameters. The usefulness of the proposed model is illustrated with six different datasets, and a comparison study with four alternative models is provided.
- A Dirichlet Autoregressive Model for the Analysis of Microbiota Time-Series Data(2021) Creus Martí, Irene; Moya Simarro, Andrés; Santonja Gómez, Francisco JoséGrowing interest in understanding microbiota dynamics has motivated the development of different strategies to model microbiota time series data. However, all of them must tackle the fact that the available data are high-dimensional, posing strong statistical and computational challenges. In order to address this challenge, we propose a Dirichlet autoregressive model with time-varying parameters, which can be directly adapted to explain the effect of groups of taxa, thus reducing the number of parameters estimated by maximum likelihood. A strategy has been implemented which speeds up this estimation. The usefulness of the proposed model is illustrated by application to a case study.
- Utilizing Mobile Health Technology to Enhance Brace Compliance: Feasibility and Effectiveness of an App-Based Monitoring System for Adolescents with Idiopathic Scoliosis(2025) Sánchez Raya, Judith; Salat Batlle, Judith; Castilla López, Diana Virginia; Zaragozá Álvarez, Irene; García Palacios, Azucena; Suso Ribera, CarlosBackground/Objectives: Adolescent idiopathic scoliosis (AIS) often requires prolonged brace use to prevent curve progression. However, adherence is challenging due to discomfort, mobility restrictions, and psychosocial stressors. This study evaluated the feasibility and clinical utility of a mobile health (mHealth) system for real-time tracking of brace adherence and treatment-related experiences in adolescents with AIS. Methods: Thirty adolescents with AIS (mean age = 12.9, SD = 1.8) undergoing brace treatment at a tertiary care center used a custom app for 90 days. The app collected daily self-reports on brace wear duration, discomfort, movement limitations, emotional distress, and social challenges. A clinical alarm system alerted providers when patient input indicated potential concerns. Primary outcomes were feasibility (adherence to daily use and usability ratings) and brace adherence. Secondary outcomes included the app's capacity to identify treatment-related challenges and its association with changes in stress, quality of life, anxiety, and depression. Results: Participants reported meeting recommended brace wear time (≥16 h/day) on 84.8% of days. The app triggered 186 clinical alarms, with the most frequent related to emotional distress (23.1%) and pain (15.6%). Alarm frequency declined over time. Improvements of ≥20% in psychological outcomes were observed in 20-26.7% of participants, while group-level changes were nonsignificant. Conclusions: mHealth-based monitoring appears feasible and acceptable for digitally engaged adolescents with AIS. The app supported early detection of treatment barriers and prompted timely clinical responses. Despite limitations, it shows promise as a tool to improve treatment engagement and address psychosocial challenges in scoliosis care.
- Unveiling Common Transcriptomic Features between Melanoma Brain Metastases and Neurodegenerative Diseases(2025) Soler Saéz, Irene; Hidalgo, Marta R.; Gómez Cabañes, Borja; López-Cerdán, Adolfo; Català-Senent, José Francisco; De la Iglesia-Vayá, María; Hernando, Eva; García García, FranciscoMelanoma represents a critical clinical challenge owing to its unfavorable outcomes. This type of skin cancer exhibits unique adaptability to the brain microenvironment, but its underlying molecular mechanisms are poorly understood. Recent findings have suggested that melanoma brain metastases may share biological processes similar to those found in various neurodegenerative diseases. To further characterize melanoma brain metastasis development, we explore the relationship between the transcriptional profiles of melanoma brain metastases and the neurodegenerative diseases Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We take an in silico approach to unveil a neurodegenerative signature of melanoma brain metastases compared with those of melanoma nonbrain metastasis (53 dysregulated genes were enriched in 11 functional terms, such as associated terms to the extracellular matrix and development) and with those of nontumor-bearing brain controls (195 dysregulated genes, mostly involved in development and cell differentiation, chromatin remodeling and nucleosome organization, and translation). Two genes, ITGA10 and DNAJC6, emerged as key potential markers being dysregulated in both scenarios. Finally, we developed an open-source, user-friendly web tool (https://bioinfo.cipf.es/metafun-mbm/) that allows interactive exploration of the complete results.
- A comprehensive transcriptional reference for severity and progression in spinal cord injury reveals novel translational biomarker genes(2025) Grillo Risco, Rubén; Hidalgo, Marta R.; Martínez Rojas, Beatriz; Moreno-Manzano, Victoria; García García, FranciscoSpinal cord injury (SCI) is a devastating condition that leads to motor, sensory, and autonomic dysfunction. Current therapeutic options remain limited, emphasizing the need for a comprehensive understanding of the underlying SCI-associated molecular mechanisms. This study characterized distinct SCI phases and severities at the gene and functional levels, focusing on biomarker gene identification. Our approach involved a systematic review, individual transcriptomic analysis, gene meta-analysis, and functional characterization. We compiled a total of fourteen studies with 273 samples, leading to the identification of severity- and phase-specific biomarker genes that allow the precise classification of transcriptomic profiles. We investigated the potential transferability of severity-specific biomarkers and identified a twelve-gene signature that predicted injury prognosis from human blood samples. We also report the development of MetaSCI-app - an interactive web application designed for researchers - that allows the exploration and visualization of all generated results (https://metasci-cbl.shinyapps.io/metaSCI). Overall, we present a transcriptomic reference and provide a comprehensive framework for assessing SCI considering severity and time perspectives, all integrated into a user-friendly tool.
- On various diametral notions of points in the unit ball of some vector-valued function spaces(2025) Lee, Han Ju; Roldán Blay, Óscar; Tag, Hyung JoonIn this article, we study the ccs-Daugavet, ccs-$\Delta$, super-Daugavet, super-$\Delta$, Daugavet, $\Delta$, and $\nabla$ points in the unit balls of vector-valued function spaces $C_0(L, X)$, $A(K, X)$, $L_\infty(\mu, X)$, and $L_1(\mu, X)$. To partially or fully characterize these diametral points, we first provide improvements of several stability results under $\oplus_\infty$ and $\oplus_1$-sums shown in the literature. For complex Banach spaces, $\nabla$ points are identical to Daugavet points, and so the study of $\nabla$ points only makes sense when a Banach space is real. Consequently, we obtain that the seven notions of diametral points are equivalent for $L_\infty(\mu)$ and uniform algebra when $K$ is infinite.
- Developing epidemiological preparedness for a plant disease invasion: Modelling citrus huánglóngbìng in the European Union(2025) Ellis, John; Lázaro Hervás, Elena; Vicent, Antonio; Cunniffe, Nik J.Societal Impact Statement Huánglóngbìng (HLB) is a bacterial disease of citrus that has significantly impacted Brazil and the United States, although citrus production in the Mediterranean Basin remains unaffected. By developing a mathematical model of spread in Spain, we tested surveillance and control strategies before any future HLB entry in the EU. We found while some citrus production might be maintained by roguing, this requires extensive surveillance and significant chemical control, perhaps also including testing of psyllids (which spread the pathogen) for bacterial DNA. Our work highlights the key importance of early detection (including asymptomatic infection) and vector control for HLB management. Summary Huánglóngbìng (HLB; citrus greening) is the most damaging disease of citrus worldwide. While citrus production in the United States and Brazil have been affected for decades, HLB has not been reported in the European Union (EU). However, a HLB vector, the African citrus psyllid, is already in Portugal and Spain. In 2023, the major vector, the Asian citrus psyllid, was first reported in Cyprus. We develop a landscape-scale, epidemiological model, accounting for heterogeneous citrus cultivation and vector dispersal, as well as climate and disease management. We use our model to predict HLB dynamics for an epidemic vectored by the African citrus psyllid in high-density citrus areas in Spain, assessing detection and control strategies. Without disease management, we predict large areas infected within 10-20 years. Even with significant visual surveillance, any epidemic will be widespread on first detection, making eradication unlikely. Nevertheless, increased inspection and roguing following first detection, particularly if coupled with intensive insecticide use, could sustain some citriculture for a decade or more, albeit with reduced production. However, effective control may require chemical application rates and/or active substances no longer authorised in the EU. Strategies targeting asymptomatic infection will be more successful. Detection of bacteriliferous vectors sometimes possible long before plants show symptoms could reduce lags before disease management commences. If detection of HLB-positive vectors were followed by intensive insecticide sprays, this may greatly improve outcomes. Our work highlights modelling as a key component of developing epidemiological preparedness for a pathogen invasion that is, at least somewhat, predictable in advance.
- Biology and epidemiology of Diaporthe amygdali: understanding how environmental factors influence fungal growth, sporulation, infection and lesion development on almond(2025) Francia, Carolina; Lázaro Hervás, Elena; Novellón, Maite; Ramón Albalat, Antonio; Beluzán, Francisco; Berbegal, Mónica; Armengol, JosepIntroduction: Diaporthe amygdali is a major pathogen causing twig canker and shoot blight disease on almond crops. Knowledge about the influence of environmental factors on the biology and epidemiology of this pathogen has mainly been obtained on peach, but there is scarce information on almond. Thus, the main objective of this research was to better understand how environmental factors, such as temperature and wetness periods, determine the cycle of this disease on almond crops in Mediterranean conditions.Methods: Several experiments were conducted to obtain information about mycelial growth, sporulation, plant infection and lesion development using almond isolates of D. amygdali.Results: Our results showed that the temperature ranges for both α-conidia germination and almond infection are broad and overlap (between 5 and 35°C), potentially allowing infections to occur year-round. Nevertheless, the highest infection of almond plants was observed after 72 h of wetness period, while the lowest occurred after 6 h, explaining why D. amygdali is a prevalent disease in spring and autumn when rain events are more frequent.Discussion: Mycelial growth of D. amygdali and lesion development were promoted by warm temperatures. The production of mature pycnidia on cankers had lower and narrower temperature requirements, thus suggesting an adaptation to late winter and early spring conditions. Moreover, the optimum temperature for α-conidia production in pycnidia was around 22°C. All this information could be used to develop a mechanistic model for almond twig canker and shoot blight disease management to enhance the timeliness and effectiveness of control strategies, while reducing both economic costs and environmental impacts.
- fmmpy: a Python module for frequency-modulated Möbius signal decomposition(2026) Canedo, Christian; Carratalá-Sáez, Rocío; Rueda, CristinaWe present fmmpy, an open-source Python library that implements the Frequency Modulated Möbius (FMM) model for robust decomposition of oscillatory signals into interpretable components. Beyond addressing the computational limitations of earlier implementations, fmmpy provides a significantly more flexible and general framework for applying the FMM model in diverse real-world scenarios. The package incorporates optimized algorithms and robust parameter constraint handling, showing how its improved flexibility and efficiency make it feasible to address problems that were previously too complex or slow to solve. This makes the FMM model more accessible and adaptable for diverse applications in biomedical, engineering, and other signal processing fields. To demonstrate its practical utility, we present two representative use cases: ECG analysis and signal spectrography, showing how the enhanced algorithms enable novel insights and solutions in these domains.
- On the development of high-performance, multi-GPU applications on heterogeneous systems leveraging SYCL(2026) Andújar, Francisco J.; Carratalá-Sáez, Rocío; Torres, Yuri; Gonzalez-Escribano, Arturo; Llanos, Diego R.Computational platforms for high-performance scientific applications are increasingly heterogeneous, incorporating multiple GPU accelerators. However, differences in GPU vendors, architectures, and programming models challenge performance portability and ease of development. SYCL provides a unified programming approach, enabling applications to target NVIDIA and AMD GPUs simultaneously while offering higher-level abstractions for data and task management. This paper evaluates SYCL's performance and development effort using the Finite Time Lyapunov Exponent (FTLE) calculation as a case study. We compare SYCL's AdaptiveCpp (Ahead-Of-Time and Just-In-Time) and Intel oneAPI compilers, along with different data management strategies (Unified Shared Memory and buffers), against equivalent CUDA and HIP implementations. Our analysis considers single and multi-GPU execution, including heterogeneous setups with GPUs from different vendors. Results show that, while SYCL introduces additional development effort compared to native CUDA and HIP implementations, it enables multi-vendor portability with minimal performance overhead when using specific design options. Based on our findings, we provide development guidelines to help programmers decide when to use SYCL versus vendor-specific alternatives.
