Alberto Sols Biomedical Research Institute
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Exploring How Climate Change Scenarios Shape the Future of Alboran Sea Fisheries
No full textClimate change is disrupting marine ecosystems, necessitating a deeper understanding of
environmental and fishing-related impacts on exploited species. This study examines the
effects of physical factors (temperature, thermal anomalies, salinity, seabed conditions),
biogeochemical elements (pH, oxygen levels, nutrients, primary production), and fishing
pressure on the biomass of commercially important species in the Alboran Sea from 1999
to 2022. Data were sourced from the Copernicus observational program, focusing on the
geographical sub-area 1 (GSA-1) zone across three depth ranges. Generalized Additive
Models were applied for analysis. Rising temperatures and seasonal anomalies have
largely negative effects, disrupting species’ physiological balance. Changes in water quality,
including improved nutrient and oxygen concentrations, have yielded complex ecological
responses. Fishing indices highlight the vulnerability of small pelagic fish to climate change
and overfishing, underscoring their economic and ecological significance. These findings
stress the urgent need for ecosystem-based management strategies that integrate climate
change impacts to ensure sustainable marine resource managementThis work was supported by the Biodiversity Foundation (http://www.fundacionbiodiversidad.es/) of the Spanish Ministry Ecological Transition (Projects: “Evaluación y valoración de los servicios de los ecosistemas marinos de la Red Natura 2000 de España—LIFE15 IP
ES012—INTEMARES (FB2017APLI006)” and “Evaluación del impacto de la pesca sobre la biodiversidad marina: un análisisde la dinámica de sus redes tróficas en la Red Natura 2000 de España
(CA_BM_2019)
Propane dehydrogenation over Pt and Ga-containing MFI zeolites with modified acidity and textural properties
Get PDFA variety of oxides (titanium, tin, calcium, magnesium, and gallium) were supported over nano-crystalline ZSM-5 zeolite (n-ZSM-5) by wet impregnation, characterized and evaluated for propane dehydrogenation (PDH) reaction. To enhance the catalytic performance of the oxide-modified n-ZSM-5, Pt nanoparticles were also dispersed over the oxides-supported zeolite catalysts by wet impregnation. Finally, Ga-containing MFI zeolites were used as catalysts in the PDH. Ga was incorporated into the zeolite by two different methods, via hydrothermal synthesis and via wet impregnation. In the PDH reaction, Pt-containing samples exhibited a high initial catalytic activity although they suffered a fast deactivation by coke deposition. On the contrary, Ga-containing MFI catalysts showed a remarkable stability in the PDH reaction. In particular, the catalyst in which Ga was incorporated into the MFI structure by hydrothermal synthesis (Ga-MFI (nSH)) achieved the highest catalytic performance in PDH (9% conversion and 80% propylene selectivity) due to the synergy between the Brønsted and Lewis acid sites (BAS and LAS) and the optimal strength of its LAS sites. These results denote the great potential of Ga-MFI zeolites as catalysts in PDH reactionsAuthors gratefully acknowledge European Research Council Horizon 2020 research an innovation program TODENZE project (ERC-101021502). Adriana S. Oliveira thanks the Ministry of Universities; The Recovery, Transformation and Resilience Plan, and the Autonomous University of Madrid for a research grant (CA1/RSUE/2021–00836). MK and JC thank the Czech Science Foundation for funding this research through the ExPro project (19–27551X) and OP VVV “Excellent Research Teams”, project no. Z.02.1.01/0.0/0.0/15_003/0000417 − CUCAM from Ministerstvo Školství , Mládeže a Tělovýchovy. The work was also supported by ERDF/ESF project TECHSCALE (No. CZ.02.01.01/00/22_008/0004587) and Investigo Program (Nº Exp 09-PIN1-00006.5/2022) funded by European Union - Next Generation E
Improved transferability of self-supervised learning models through batch normalization finetuning
No full textThis version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10489-024-05758-7Abundance of unlabelled data and advances in Self-Supervised Learning (SSL) have made it the preferred choice in many transfer learning scenarios. Due to the rapid and ongoing development of SSL approaches, practitioners are now faced with an overwhelming amount of models trained for a specific task/domain, calling for a method to estimate transfer performance on novel tasks/domains. Typically, the role of such estimator is played by linear probing which trains a linear classifier on top of the frozen feature extractor. In this work we address a shortcoming of linear probing — it is not very strongly correlated with the performance of the models finetuned end-to-end— the latter often being the final objective in transfer learning— and, in some cases, catastrophically misestimates a model’s potential. We propose a way to obtain a significantly better proxy task by unfreezing and jointly finetuning batch normalization layers together with the classification head. At a cost of extra training of only 0.16% model parameters, in case of ResNet-50, we acquire a proxy task that (i) has a stronger correlation with end-to-end finetuned performance, (ii) improves the linear probing performance in the many- and few-shot learning regimes and (iii) in some cases, outperforms both linear probing and end-to-end finetuning, reaching the state-of-the-art performance on a pathology dataset. Finally, we analyze and discuss the changes batch normalization training introduces in the feature distributions that may be the reason for the improved performanceThis work was supported by the Ministerio de Ciencia e Innovación de España under projects TED2021-131643AI00 (SEGA-CV) and PID2021-125051OB-I00 (HVD
Advances in gene therapy for rare diseases: targeting functional haploinsufficiency through AAV and mRNA approaches
Get PDFMost rare diseases (RDs) encompass a diverse group of inherited disorders that affect millions of people worldwide. A significant proportion of these diseases are driven by functional haploinsufficiency, which is caused by pathogenic genetic variants. Currently, most treatments for RDs are limited to symptom management, emphasizing the need for therapies that directly address genetic deficiencies. Recent advancements in gene therapy, particularly with adeno-associated viruses (AAVs) and lipid nanoparticle-encapsulated messenger RNA (mRNA), have introduced promising therapeutic approaches. AAV vectors offer durable gene expression, extensive tissue tropism, and a safety profile that makes them a leading choice for gene delivery; however, limitations remain, including packaging size and immune response. In contrast, mRNA therapeutics, formulated in LNPs, facilitate transient protein expression without the risk of genomic integration, supporting repeated dosing and pharmacokinetic control, though with less long-term expression than AAVs. This review analyzes the latest developments in AAV and mRNA technologies for rare monogenic disorders, focusing on preclinical and clinical outcomes, vector design, and delivery challenges. We also address key regulatory and immunological considerations impacting therapeutic success. Together, these advancements in AAV and mRNA technology underscore a new era in RD treatment, providing innovative tools to target the genetic root of these diseases and expanding therapeutic approaches for patients who currently face limited medical option
Mitochondrial DNA Structure in Trypanosoma cruzi
Get PDFKinetoplastids display a single, large mitochondrion per cell, with their mitochondrial DNA referred to as the kinetoplast. This kinetoplast is a network of concatenated circular molecules comprising a maxicircle (20–64 kb) and up to thousands of minicircles varying in size depending on the species (0.5–10 kb). In Trypanosoma cruzi, maxicircles contain typical mitochondrial genes found in other eukaryotes. They consist of coding and divergent/variable regions, complicating their assembly due to repetitive elements. However, next-generation sequencing (NGS) methods have resolved these issues, enabling the complete sequencing of maxicircles from different strains. Furthermore, several insertions and deletions in the maxicircle sequences have been identified among strains, affecting specific genes. Unique to kinetoplastids, minicircles play a crucial role in a particular U-insertion/deletion RNA editing system by encoding guide RNAs (gRNAs). These gRNAs are essential for editing and maturing maxicircle mRNAs. I
Función y características de los organismos nacionales de normalización contable en la Unión Europea: un análisis comparativo
Get PDFThis paper examines the persistence of national/local institutions in accounting settings, where standards are global/international (or convergent). This poses the question of how these institutions adapt to a changing environment and what factors shape their structure. We provide updated information on 17 National Accounting Standard Setters (NASS) from 15 EU countries plus Australia and USA. The results reveal the four most relevant dimensions of each NASS (nature, organization, financing, and transparency) and identify two main models of NASS (public and private). The paper also discusses potential applications of this data, mainly to examine whether (and how) certain institutional factors could enhance the quality of financial reportingThe authors acknowledge the financial contribution ofthe Resolución convocatoria ICAC-ASEPUC de informes-dictámenes técnicos 2018. They are grateful to theSpanish Ministry of Science and Innovation (PID 2019-104163RA100) and the Government of Madrid (within theframework of the multi-year agreement with the UAM onLine 3: Excellence for University Staff - PRICIT). They wouldlike to thank Jacobo Gómez, Salvador Ortiz, Beatriz Garcíaand the participants of the 44th EAA Conference for theirhelpful comments on an earlier version of the paper
Boundedness properties of modified averaging operators and geometrically doubling metric spaces
Get PDFWe characterize the geometrically doubling condition of a metric space in terms of the uniform L1 -boundedness of super averaging operators, where uniform refers to the existence of bounds independent of the measure being consideredJesús Munárriz Aldaz was partially supported by Grant PID2019-106870GB-I00 of the MICINN of Spain, by V PRICIT (Comunidad de Madrid – Spain), and also by ICMAT Severo Ochoa project CEX2019-000904-S (MICINN
Advanced discovery mechanisms in model repositories
No full textAs model-driven engineering gains traction and poses as the new paradigm for software engineering, it raises a need for efficient approaches and tools to manage, discover, and retrieve relevant modeling artifacts. Hence, industry and academia are conceiving effective ways to store, search, and retrieve heteroge neous model artifacts that employ advanced discovery mechanisms. This paper presents MDEForge-Search, a novel approach to discovering heterogeneous model artifacts over MDEForge, a distributed cloud-based model repository. We designed advanced discovery mechanisms that retrieve heterogeneous artifacts within their context (megamodel) and reuse them across model management services. In addition, a domain-specific approach has been proposed to formu late queries in terms of keywords, search tags, conditional operators, quality model assessment services and a transformation chain discoverer. Finally, the applicability of our approach was assessed in a recommender system modeling framework, which, thanks to the operated integration, can rely on the avail ability of more than 5000 model artifacts currently persisted in our cloud-based model repositoryThis work is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie
Skłodowska-Curie–ITN grant agreement no 81388