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96,939 results on '"Carles A"'

151. Topological Data Analysis for Neural Network Analysis: A Comprehensive Survey

Author

Ballester, Rubén, Casacuberta, Carles, and Escalera, Sergio

Subjects
Computer Science - Machine Learning, Mathematics - Algebraic Topology, 62R40, 55N31, 68T07, I.2.6
Abstract

This survey provides a comprehensive exploration of applications of Topological Data Analysis (TDA) within neural network analysis. Using TDA tools such as persistent homology and Mapper, we delve into the intricate structures and behaviors of neural networks and their datasets. We discuss different strategies to obtain topological information from data and neural networks by means of TDA. Additionally, we review how topological information can be leveraged to analyze properties of neural networks, such as their generalization capacity or expressivity. We explore practical implications of deep learning, specifically focusing on areas like adversarial detection and model selection. Our survey organizes the examined works into four broad domains: 1. Characterization of neural network architectures; 2. Analysis of decision regions and boundaries; 3. Study of internal representations, activations, and parameters; 4. Exploration of training dynamics and loss functions. Within each category, we discuss several articles, offering background information to aid in understanding the various methodologies. We conclude with a synthesis of key insights gained from our study, accompanied by a discussion of challenges and potential advancements in the field., Comment: 70 pages, 7 figures. 4 references added. Minor changes in the text. Part of generative models reestructured to improve generality and clarity of exposition

Published
2023

152. A look at the Kolmogorov complexity of finite groupoids and algebras

Author

Cardó, Carles

Subjects
Computer Science - Information Theory, 20N02, 68Q30, 03C05
Abstract

The incompressibility method is a counting argument in the framework of algorithmic complexity that permits discovering properties that are satisfied by most objects of a class. This paper gives a preliminary insight into Kolmogorov's complexity of groupoids and some algebras. The incompressibility method shows that almost all the groupoids are asymmetric and simple: Only trivial or constant homomorphisms are possible. However, highly random groupoids allow subgroupoids with interesting restrictions that reveal intrinsic structural properties. We also study the issue of the algebraic varieties and wonder which equational identities allow randomness., Comment: There is a lack of relevant literature. Some results are already known. The manuscript needs a significant revision

Published
2023

153. Stochastic Optimal Control Matching

Author

Domingo-Enrich, Carles, Han, Jiequn, Amos, Brandon, Bruna, Joan, and Chen, Ricky T. Q.

Subjects
Mathematics - Optimization and Control, Computer Science - Machine Learning, Mathematics - Numerical Analysis, Mathematics - Probability, Statistics - Machine Learning
Abstract

Stochastic optimal control, which has the goal of driving the behavior of noisy systems, is broadly applicable in science, engineering and artificial intelligence. Our work introduces Stochastic Optimal Control Matching (SOCM), a novel Iterative Diffusion Optimization (IDO) technique for stochastic optimal control that stems from the same philosophy as the conditional score matching loss for diffusion models. That is, the control is learned via a least squares problem by trying to fit a matching vector field. The training loss, which is closely connected to the cross-entropy loss, is optimized with respect to both the control function and a family of reparameterization matrices which appear in the matching vector field. The optimization with respect to the reparameterization matrices aims at minimizing the variance of the matching vector field. Experimentally, our algorithm achieves lower error than all the existing IDO techniques for stochastic optimal control for three out of four control problems, in some cases by an order of magnitude. The key idea underlying SOCM is the path-wise reparameterization trick, a novel technique that may be of independent interest. Code at https://github.com/facebookresearch/SOC-matching

Published
2023

154. Force Training Neural Network Potential Energy Surface Models

Author

Devereux, Christian, Yang, Yoona, Martí, Carles, Zádor, Judit, Eldred, Michael S., and Najm, Habib N.

Subjects
Physics - Chemical Physics
Abstract

Machine learned chemical potentials have shown great promise as alternatives to conventional computational chemistry methods to represent the potential energy of a given atomic or molecular system as a function of its geometry. However, such potentials are only as good as the data they are trained on, and building a comprehensive training set can be a costly process. Therefore, it is important to extract as much information from training data as possible without further increasing the computational cost. One way to accomplish this is by training on molecular forces in addition to energies. This allows for three additional labels per atom within the molecule. Here we develop a neural network potential energy surface for studying a hydrogen transfer reaction between two conformers of C5H5. We show that, for a much smaller training set, force training can greatly improve the accuracy of the model compared to only training to energies. We also demonstrate the importance of choosing the proper force to energy weight ratio for the loss function to minimize the model test error.

Published
2023

155. Low regularity solutions to the logarithmic Schrodinger equation

Author

Carles, Rémi, Hayashi, Masayuki, and Ozawa, Tohru

Subjects
Mathematics - Analysis of PDEs
Abstract

We consider the logarithmic Schr{\"o}dinger equation, in various geometric settings. We show that the flow map can be uniquely extended from H^1 to L^2 , and that this extension is Lipschitz continuous. Moreover, we prove the regularity of the flow map in intermediate Sobolev spaces., Comment: Some typos fixed. A flaw corrected in Section 4

Published
2023

156. Using two point correlation functions to understand the assembly histories of Milky Way-like galaxies

Author

Zhang, Yike, Wang, Wenting, Han, Jiaxin, Yang, Xiaohu, Rodriguez-Gomez, Vicente, Palau, Carles G., and Tan, Zhenlin

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Solar and Stellar Astrophysics
Abstract

The two point correlation function (2PCF) is a powerful statistical tool to measure galaxy clustering. Although 2PCF has also been used to study the clustering of stars on parsec and sub-parsec scales, its physical implication is not clear on such non-linear scales. In this study, we use the Illustris-TNG50 simulation to study the connection between the 2PCF signals of accreted halo stars and the assembly histories of Milky Way-mass galaxies. We find, in general, the 2PCF signal increases with the increase in galactocentric radii, $r$, and with the decrease in the pair separations. Galaxies which assemble late on average have stronger 2PCF signals. With $z_{1/4}$, $z_{1/2}$ and $z_{3/4}$ defined as the redshifts when galaxies accreted one-fourth, half and three-fourths of their ex-situ stellar mass at today, we find all of them show the strongest correlations with the 2PCF signals at $r\sim0.2R_{200}$. $z_{3/4}$ shows the strongest correlations at all radii than those of $z_{1/4}$ or $z_{1/2}$, as later accreted stars preserve better clusterings. However, the correlations between the 2PCF signals at different radii and the galaxy formation times all have large scatters. The 2PCFs in velocity space show weaker correlations with the galaxy formation times within $0.38R_{200}$ than real space 2PCFs, and the scatter is considerably large. Both the real and velocity space 2PCFs correlate with the assembly histories of the host dark matter halos as well. Within $0.38R_{200}$, the real space 2PCF shows stronger correlations with the galaxy formation histories than with the halo formation histories, while the velocity space 2PCFs do not show large differences. We conclude that it is difficult to use 2PCF alone to precisely predict the formation times or assembly histories of galaxies., Comment: accepted by ApJ

Published
2023
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157. A contextuality witness inspired by optimal state discrimination

Author

Carceller, Carles Roch i and Brask, Jonatan Bohr

Subjects
Quantum Physics
Abstract

Many protocols and tasks in quantum information science rely inherently on the fundamental notion of contextuality to provide advantages over their classical counterparts, and contextuality represents one of the main differences between quantum and classical physics. In this work we present a witness for preparation contextuality inspired by optimal two-state discrimination. The main idea is based on finding the accessible averaged success and error probabilities in both classical and quantum models. We can then construct a noncontextuality inequality and associated witness which we find to be robust against depolarising noise and loss in the form of inconclusive events., Comment: 5 pages main text, 3 figures, 3 pages supplemental material

Published
2023
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158. On the use of Vision-Language models for Visual Sentiment Analysis: a study on CLIP

Author

Bustos, Cristina, Civit, Carles, Du, Brian, Sole-Ribalta, Albert, and Lapedriza, Agata

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

This work presents a study on how to exploit the CLIP embedding space to perform Visual Sentiment Analysis. We experiment with two architectures built on top of the CLIP embedding space, which we denote by CLIP-E. We train the CLIP-E models with WEBEmo, the largest publicly available and manually labeled benchmark for Visual Sentiment Analysis, and perform two sets of experiments. First, we test on WEBEmo and compare the CLIP-E architectures with state-of-the-art (SOTA) models and with CLIP Zero-Shot. Second, we perform cross dataset evaluation, and test the CLIP-E architectures trained with WEBEmo on other Visual Sentiment Analysis benchmarks. Our results show that the CLIP-E approaches outperform SOTA models in WEBEmo fine grained categorization, and they also generalize better when tested on datasets that have not been seen during training. Interestingly, we observed that for the FI dataset, CLIP Zero-Shot produces better accuracies than SOTA models and CLIP-E trained on WEBEmo. These results motivate several questions that we discuss in this paper, such as how we should design new benchmarks and evaluate Visual Sentiment Analysis, and whether we should keep designing tailored Deep Learning models for Visual Sentiment Analysis or focus our efforts on better using the knowledge encoded in large vision-language models such as CLIP for this task.

Published
2023

159. Efficient Representation of Lattice Path Matroids

Author

Padró, Carles

Subjects
Mathematics - Combinatorics, 05B35 (Primary) 94A62 (Secondary)
Abstract

Efficient deterministic algorithms to construct representations of lattice path matroids over finite fields are presented. They are built on known constructions of hierarchical secret sharing schemes, a recent characterization of hierarchical matroid ports, and the existence of isolating weight functions for lattice path matroids whose values are polynomial on the size of the ground set.

Published
2023

160. SpectAcLE: An Improved Method for Modeling Light Echo Spectra

Author

Partoush, Roee, Rest, Armin, Jencson, Jacob E., Poznanski, Dovi, Foley, Ryan J., Kilpatrick, Charles D., Andrews, Jennifer E., Angulo, Rodrigo, Badenes, Carles, Bianco, Federica B., Filippenko, Alexei V., Ridden-Harper, Ryan, Li, Xiaolong, Margheim, Steve, Matheson, Thomas, Olsen, Knut A. G., Siebert, Matthew R., Smith, Nathan, Welch, Douglas L., and Zenteno, A.

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - High Energy Astrophysical Phenomena, Astrophysics - Solar and Stellar Astrophysics
Abstract

Light echoes give us a unique perspective on the nature of supernovae and non-terminal stellar explosions. Spectroscopy of light echoes can reveal details on the kinematics of the ejecta, probe asymmetry, and reveal details on its interaction with circumstellar matter, thus expanding our understanding of these transient events. However, the spectral features arise from a complex interplay between the source photons, the reflecting dust geometry, and the instrumental setup and observing conditions. In this work we present an improved method for modeling these effects in light echo spectra, one that relaxes the simplifying assumption of a light curve weighted sum, and instead estimates the true relative contribution of each phase. We discuss our logic, the gains we obtain over light echo analysis method(s) used in the past, and prospects for further improvements. Lastly, we show how the new method improves our analysis of echoes from Tycho's supernova (SN 1572) as an example.

Published
2023

161. Cosmology with imaging galaxy surveys: the impact of evolving galaxy bias and magnification

Author

Pandey, Shivam, Sánchez, Carles, Jain, Bhuvnesh, and Collaboration, The LSST Dark Energy Science

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract

The joint analysis of galaxy clustering and galaxy-shear cross-correlations (galaxy-galaxy lensing) in imaging surveys constitutes one of the main avenues to obtain cosmological information. Analyses from Stage III surveys have assumed constant galaxy bias and weak lensing magnification coefficients within redshift bins. We use simple models of bias and magnification evolution to show that plausible levels of evolution impact cosmological parameter inference significantly for Stage IV surveys and possibly for current datasets as well. The distance weighting factors in galaxy-galaxy lensing cause it to have a different effective mean redshift within a lens bin than galaxy clustering. If the evolution is not included carefully in the theory modeling, this produces an apparent de-correlation of clustering and lensing even on large scales and leads to biased cosmological constraints. The level of bias is sensitive to the redshift and the width of the lens redshift distributions: for magnitude-limited-like samples it is comparable to the statistical precision even for the full DES survey, and exceeds it for Rubin-LSST. We find that ignoring the evolution can lead to approximately $1\sigma$ biases in the cosmological constraints in future Rubin-LSST analyses. We describe how these effects can be mitigated from the modeling and data sides, in particular by using cross-correlations to constrain the evolution parameters. We also demonstrate that the combination of galaxy clustering and CMB lensing does not suffer from this problem, due to the different distance weighting., Comment: 12 pages, 11 figures

Published
2023

162. Neglecting the fallow season can significantly underestimate annual methane emissions in Mediterranean rice fields.

Author

Maite Martínez-Eixarch, Carles Alcaraz, Marc Viñas, Joan Noguerol, Xavier Aranda, Francesc Xavier Prenafeta-Boldú, Jesús Antonio Saldaña-De la Vega, Maria Del Mar Català, and Carles Ibáñez

Subjects
Medicine, Science
Abstract

Paddy rice fields are one of the most important sources of anthropogenic methane. Improving the accuracy in the CH4 budget is fundamental to identify strategies to mitigate climate change. Such improvement requires a mechanistic understanding of the complex interactions between environmental and agronomic factors determining CH4 emissions, and also the characterization of the annual temporal CH4 emissions pattern in the whole crop cycle. Hence, both the growing and fallow seasons must be included. However, most of the previous research has been based on single-factor analyses that are focused on the growing season. In order to fill this gap, a study was conducted in a Mediterranean rice agrosystem (Ebre Delta, Catalonia) following a farm-to-farm approach with the purpose of 1) evaluating the cumulative and temporal pattern of CH4 emission, and 2) conducting a multi-variate analyses to assess the associative pattern, relative contribution and temporal variation of the main explanatory variables concerning the observed CH4 emissions. Measurements of CH4 emissions and agronomic and environmental parameters in 15 commercial rice fields were monitored monthly, during a whole crop field cycle. The temporal pattern of CH4 emission followed a bi-modal distribution peaking in August and October. The cumulative annual CH4 emissions from rice fields amounted 314 kg CH4 kg ha-1, of which ca. 70% were emitted during the fallow season. The main controlling factors of the CH4 emission rate in the growing season were positive related to water level and plant cover, while soil redox was negatively related. The main controlling factors in the fallow season were water level (negatively related, conversely to the growing season), as well as straw incorporation and soil temperature (positively related). The results of this study highlight the importance of the often neglected fallow season in the accurate estimation of CH4 emissions and, thus, the necessity of measurement programs that cover the whole crop field cycle. This information is the first step for setting effective mitigation strategies based on straw and water management.

Published
2018
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164. Cell-Free UAV Networks With Wireless Fronthaul: Analysis and Optimization

Author

Diaz-Vilor, Carles, Lozano, Angel, and Jafarkhani, Hamid

Subjects
Theory Of Computation, Information and Computing Sciences, Communications Engineering, Engineering, Affordable and Clean Energy, Cell-free, UAV, fronthaul, FDMA, SDMA, deployment optimization, power optimization, Distributed Computing, Electrical and Electronic Engineering, Communications Technologies, Networking & Telecommunications, Communications engineering, Electrical engineering, Distributed computing and systems software
Abstract

The use of uncrewed aerial vehicles (UAVs) in cell-free networks is poised to unleash a number of new opportunities to further improve wireless networks. However, cell-free UAV networks present major challenges related to the wireless nature of access and fronthaul links. This manuscript studies the uplink of cell-free systems where users connect to UAVs, the latter devices forwarding the information to a processing point through imperfect wireless fronthaul links. Three multiple access alternatives are considered for the fronthaul, namely frequency division multiples access, spatial division multiple access, and combinations thereof. Deterministic equivalent expressions for the spectral efficiency under these fronthaul schemes and minimum mean-square error reception are derived. Then, the optimization subproblems of (a) the 3D deployment of the UAVs, (b) the user transmit powers, and (c) the UAV transmit powers, are investigated. The joint optimization of these subproblems yields superior performance, with the 3D deployment being the main source of improvement.

Published
2024

165. Population genomics of post-glacial western Eurasia

Author

Allentoft, Morten E, Sikora, Martin, Refoyo-Martínez, Alba, Irving-Pease, Evan K, Fischer, Anders, Barrie, William, Ingason, Andrés, Stenderup, Jesper, Sjögren, Karl-Göran, Pearson, Alice, Sousa da Mota, Bárbara, Schulz Paulsson, Bettina, Halgren, Alma, Macleod, Ruairidh, Jørkov, Marie Louise Schjellerup, Demeter, Fabrice, Sørensen, Lasse, Nielsen, Poul Otto, Henriksen, Rasmus A, Vimala, Tharsika, McColl, Hugh, Margaryan, Ashot, Ilardo, Melissa, Vaughn, Andrew, Fischer Mortensen, Morten, Nielsen, Anne Birgitte, Ulfeldt Hede, Mikkel, Johannsen, Niels Nørkjær, Rasmussen, Peter, Vinner, Lasse, Renaud, Gabriel, Stern, Aaron, Jensen, Theis Zetner Trolle, Scorrano, Gabriele, Schroeder, Hannes, Lysdahl, Per, Ramsøe, Abigail Daisy, Skorobogatov, Andrei, Schork, Andrew Joseph, Rosengren, Anders, Ruter, Anthony, Outram, Alan, Timoshenko, Aleksey A, Buzhilova, Alexandra, Coppa, Alfredo, Zubova, Alisa, Silva, Ana Maria, Hansen, Anders J, Gromov, Andrey, Logvin, Andrey, Gotfredsen, Anne Birgitte, Henning Nielsen, Bjarne, González-Rabanal, Borja, Lalueza-Fox, Carles, McKenzie, Catriona J, Gaunitz, Charleen, Blasco, Concepción, Liesau, Corina, Martinez-Labarga, Cristina, Pozdnyakov, Dmitri V, Cuenca-Solana, David, Lordkipanidze, David O, En’shin, Dmitri, Salazar-García, Domingo C, Price, T Douglas, Borić, Dušan, Kostyleva, Elena, Veselovskaya, Elizaveta V, Usmanova, Emma R, Cappellini, Enrico, Brinch Petersen, Erik, Kannegaard, Esben, Radina, Francesca, Eylem Yediay, Fulya, Duday, Henri, Gutiérrez-Zugasti, Igor, Merts, Ilya, Potekhina, Inna, Shevnina, Irina, Altinkaya, Isin, Guilaine, Jean, Hansen, Jesper, Aura Tortosa, Joan Emili, Zilhão, João, Vega, Jorge, Buck Pedersen, Kristoffer, Tunia, Krzysztof, Zhao, Lei, Mylnikova, Liudmila N, Larsson, Lars, Metz, Laure, Yepiskoposyan, Levon, Pedersen, Lisbeth, Sarti, Lucia, Orlando, Ludovic, Slimak, Ludovic, Klassen, Lutz, Blank, Malou, González-Morales, Manuel, and Silvestrini, Mara

Subjects
Biological Sciences, Genetics, History, Heritage and Archaeology, Human Society, Historical Studies, Anthropology, Biotechnology, Humans, Genomics, Diploidy, Agriculture, Europe, Metagenomics, General Science & Technology
Abstract

Western Eurasia witnessed several large-scale human migrations during the Holocene1-5. Here, to investigate the cross-continental effects of these migrations, we shotgun-sequenced 317 genomes-mainly from the Mesolithic and Neolithic periods-from across northern and western Eurasia. These were imputed alongside published data to obtain diploid genotypes from more than 1,600 ancient humans. Our analyses revealed a 'great divide' genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers were highly genetically differentiated east and west of this zone, and the effect of the neolithization was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacement of hunter-gatherers in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, whereas, east of the Urals, relatedness remained high until around 4,000 BP, consistent with the persistence of localized groups of hunter-gatherers. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP, resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive, but we show that hunter-gatherers from the Middle Don region contributed ancestry to them. Yamnaya groups later admixed with individuals associated with the Globular Amphora culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a 'Neolithic steppe' cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.

Published
2024

166. Multi-UAV Reinforcement Learning for Data Collection in Cellular MIMO Networks

Author

Diaz-Vilor, Carles, Abdelhady, Amr M, Eltawil, Ahmed M, and Jafarkhani, Hamid

Subjects
Information and Computing Sciences, Artificial Intelligence, Data Management and Data Science, Distributed Computing and Systems Software, Machine Learning, Distributed Computing, Electrical and Electronic Engineering, Communications Technologies, Networking & Telecommunications, Communications engineering, Electrical engineering, Distributed computing and systems software
Abstract

Uncrewed Aerial Vehicles (UAVs) provide a compelling solution for data collection in Internet of Things (IoT) networks due to their mobility and adaptability. However, the line-of-sight dominance in their channels may result in severe interference to ground users during UAV operations. To address this, we present an optimization framework that concurrently optimizes UAV trajectories and transmit powers. Our approach efficiently results in the collection of data from a variety of IoT sensors while (a) minimizing the UAVs flying time and (b) mitigating interference with terrestrial networks. Given the complex nature of such an optimization problem, this paper leverages reinforcement learning, specifically the twin delayed deep deterministic policy gradient algorithm, where a distributed learning algorithm is presented. Experimental results validate the efficacy of our proposed approach, demonstrating its capability to significantly enhance data collection in IoT networks while minimizing UAV flight time and interference with ground user links.

Published
2024

167. Laser-Empowered UAVs for Aerial Data Aggregation in Passive IoT Networks

Author

Abdelhady, Amr M, Celik, Abdulkadir, Diaz-Vilor, Carles, Jafarkhani, Hamid, and Eltawil, Ahmed M

Subjects
Communications Engineering, Engineering, Laser-powered UAVs, trajectory optimization, backscatter communications, resource allocation, Communications engineering
Abstract

This paper investigates the maximization of data harvested by an uncrewed aerial vehicle (UAV) that supports Internet of Things (IoT) deployment scenarios. The novelty of the paper is that we study the feasibility of battery-free UAV and IoT device deployment where the UAV is powered by a ground laser source, and the IoT devices are powered by a power beacon via bistatic backscattering. We aim to optimize the UAV trajectory while minimizing the laser energy consumption throughout the entire flight by tuning the laser power and the power beacon radiated temporal power profiles. Upon considering an unspecified flying time, we adopt path discretization and resort to the single-block successive convex approximation (SCA) to solve the data collection maximization problem. In addition to considering the UAV dynamics and power budget, two novel SCA-compatible bounds are introduced for the product of positive mixed convex/concave functions. Finally, the simulation results show that the proposed algorithm increases the data collected under different operation conditions by approximately 90%.

Published
2024

171. Long-term survival following anti-PD-(L)1 monotherapy in advanced urothelial cancer and an assessment of potential prognostic clinical factors: a multicentre observational study

Author

Stockem, Chantal F., Einerhand, Sarah M. H., Rodríguez, Isabel Miras, Salhi, Youssra, Pérez, Esther, Bakaloudi, Dimitra R., Talukder, Rafee, Caramelo, Belen, Morales-Barrera, Rafael, De Meulenaere, Astrid, Rametta, Alessandro, Bottelli, Andrea, Lefort, Felix, Giannatempo, Patrizia, Vulsteke, Christof, Carles, Joan, Duran, Ignacio, Grivas, Petros, de Liaño, Alfonso Gómez, Robbrecht, Debbie G. J., Valderrama, Begoña P., van der Noort, Vincent, and van der Heijden, Michiel S.

Published
2024
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174. Neuropathological spectrum of anti-IgLON5 disease and stages of brainstem tau pathology: updated neuropathological research criteria of the disease-related tauopathy

Author

Gelpi, Ellen, Reinecke, Raphael, Gaig, Carles, Iranzo, Alex, Sabater, Lidia, Molina-Porcel, Laura, Aldecoa, Iban, Endmayr, Verena, Högl, Birgit, Schmutzhard, Erich, Poewe, Werner, Pfausler, Bettina, Popovic, Mara, Pretnar-Oblak, Janja, Leypoldt, Frank, Matschke, Jakob, Glatzel, Markus, Erro, Elena Maria, Jerico, Ivonne, Caballero, Maria Cristina, Zelaya, Maria Victoria, Mariotto, Sara, Heidbreder, Anna, Kalev, Ognian, Weis, Serge, Macher, Stefan, Berger-Sieczkowski, Evelyn, Ferrari, Julia, Reisinger, Christoph, Klupp, Nikolaus, Tienari, Pentti, Rautila, Osma, Niemelä, Marja, Yilmazer-Hanke, Deniz, Guasp, Mar, Bloem, Bas, Van Gaalen, Judith, Kusters, Benno, Titulaer, Maarten, Fransen, Nina L., Santamaria, Joan, Dawson, Thimoty, Holton, Janice L., Ling, Helen, Revesz, Tamas, Myllykangas, Liisa, Budka, Herbert, Kovacs, Gabor G., Lewerenz, Jan, Dalmau, Josep, Graus, Francesc, Koneczny, Inga, and Höftberger, Romana

Published
2024
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178. Real-time PCR for malaria diagnosis and identification of Plasmodium species in febrile patients in Cubal, Angola

Author

Mediavilla, Alejandro, Silgado, Aroa, Febrer-Sendra, Begoña, Crego-Vicente, Beatriz, Martínez-Vallejo, Patricia, Maturana, Carles Rubio, Goterris, Lidia, Nindia, Arlette, Martínez-Campreciós, Joan, Aixut, Sandra, Aznar-Ruiz-de-Alegría, María Luisa, Fernández-Soto, Pedro, Muro, Antonio, Salvador, Fernando, Molina, Israel, Berzosa, Pedro, Oliveira-Souto, Inés, and Sulleiro, Elena

Published
2024
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181. Identification of novel small molecule-based strategies of COL7A1 upregulation and readthrough activity for the treatment of recessive dystrophic epidermolysis bullosa

Author

Jover, Irene, Ramos, Maria C., Escámez, María José, Lozoya, Estrella, Tormo, José R., de Prado-Verdún, Diana, Mencía, Ángeles, Pont, Mercè, Puig, Carles, Larraufie, Marie-Helene, Gutiérrez-Caballero, Cristina, Reyes, Fernando, Trincado, Juan Luis, García-González, Vicente, Cerrato, Rosario, Andrés, Miriam, Crespo, Maribel, Vicente, Francisca, Godessart, Nuria, Genilloud, Olga, Larcher, Fernando, and Nueda, Arsenio

Published
2024
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183. Precarious work on the rise

Author

Perri, Melissa, O’Campo, Patricia, Gill, Paneet, Gunn, Virginia, Ma, Rachel W, Buhariwala, Pearl, Rasoulian, Elham, Lewchuk, Wayne, Baron, Sherry, Bodin, Theo, and Muntaner, Carles

Published
2024
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184. Correction: ENDOLUNG trial. A phase 1/2 study of the Akt/mTOR inhibitor and autophagy inducer Ibrilatazar (ABTL0812) in combination with paclitaxel/carboplatin in patients with advanced/recurrent endometrial cancer: Alexandra Leary

Author

Leary, Alexandra, Estévez-García, Purificación, Sabatier, Renaud, Ray-Coquard, Isabelle, Romeo, Margarita, Barretina-Ginesta, Pilar, Gil-Martin, Marta, Garralda, Elena, Bosch-Barrera, Joaquim, Morán, Teresa, Martin-Martorell, Paloma, Nadal, Ernest, Gascón, Pere, Rodon, Jordi, Lizcano, Jose M, Muñoz-Guardiola, Pau, Fierro-Durán, Gemma, Pedrós-Gámez, Oriol, Pérez-Montoyo, Héctor, Yeste-Velasco, Marc, Cortal, Marc, Pérez-Campos, Antonio, Alfon, Jose, Domenech, Carles, Pérez-Fidalgo, Alejandro, and Oaknin, Ana

Published
2024
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185. ENDOLUNG trial. A phase 1/2 study of the Akt/mTOR inhibitor and autophagy inducer Ibrilatazar (ABTL0812) in combination with paclitaxel/carboplatin in patients with advanced/recurrent endometrial cancer

Author

Leary, Alexandra, Estévez-García, Purificación, Sabatier, Renaud, Ray-Coquard, Isabelle, Romeo, Margarita, Barretina-Ginesta, Pilar, Gil-Martin, Marta, Garralda, Elena, Bosch-Barrera, Joaquim, Morán, Teresa, Martin-Martorell, Paloma, Nadal, Ernest, Gascón, Pere, Rodon, Jordi, Lizcano, Jose M, Muñoz-Guardiola, Pau, Fierro-Durán, Gemma, Pedrós-Gámez, Oriol, Pérez-Montoyo, Héctor, Yeste-Velasco, Marc, Cortal, Marc, Pérez-Campos, Antonio, Alfon, Jose, Domenech, Carles, Pérez-Fidalgo, Alejandro, and Oaknin, Ana

Published
2024
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186. Effect of lung volume preservation during spontaneous breathing trial on successful extubation in patients receiving mechanical ventilation: protocol for a multicenter clinical trial

Author

Subirà, Carles, Rognoni, Gina, Baquerizo, Herbert, García, Carolina, Cabañes, Sara, de la Torre, Maria, Quevedo, Beatriz, Pedrós, Cristina, Tizón, Ana I., Murillo, Natalia, Parro, Laura, Eiras, Fernando, Rialp, Gemma, Altaba, Susana, González-Castro, Alejandro, Pacheco, Andrés F., Bayoumi, Pablo, Gómez-Medrano, Norma, Vallverdú, Imma, Higón, Áurea, Navarro, María D., Falcón, Alirio, Keough, Elena, Arizo, David, Martínez, Juan F., Durán, Núria, Rodríguez, Raquel, Popoviciu-Koborzan, Melinda R., Guerrero, Isabel, Concha, Pablo, Barral, Patricia, Batlle, Montserrat, Cano, Sílvia, Garcia-Castrillon, Silvia, Andorrà, Xavier, Tua, Yenifher, Arnau, Anna, and Fernández, Rafael

Published
2024
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192. Comparative characterization of the infant gut microbiome and their maternal lineage by a multi-omics approach

Author

Barker-Tejeda, Tomás Clive, Zubeldia-Varela, Elisa, Macías-Camero, Andrea, Alonso, Lola, Martín-Antoniano, Isabel Adoración, Rey-Stolle, María Fernanda, Mera-Berriatua, Leticia, Bazire, Raphaëlle, Cabrera-Freitag, Paula, Shanmuganathan, Meera, Britz-McKibbin, Philip, Ubeda, Carles, Francino, M. Pilar, Barber, Domingo, Ibáñez-Sandín, María Dolores, Barbas, Coral, Pérez-Gordo, Marina, and Villaseñor, Alma

Published
2024
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193. Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Author

Ceccato, Adrian, Forne, Carles, Bos, Lieuwe D., Camprubí-Rimblas, Marta, Areny-Balagueró, Aina, Campaña-Duel, Elena, Quero, Sara, Diaz, Emili, Roca, Oriol, De Gonzalo-Calvo, David, Fernández-Barat, Laia, Motos, Anna, Ferrer, Ricard, Riera, Jordi, Lorente, Jose A., Peñuelas, Oscar, Menendez, Rosario, Amaya-Villar, Rosario, Añón, José M., Balan-Mariño, Ana, Barberà, Carme, Barberán, José, Blandino-Ortiz, Aaron, Boado, Maria Victoria, Bustamante-Munguira, Elena, Caballero, Jesús, Carbajales, Cristina, Carbonell, Nieves, Catalán-González, Mercedes, Franco, Nieves, Galbán, Cristóbal, Gumucio-Sanguino, Víctor D., de la Torre, Maria del Carmen, Estella, Ángel, Gallego, Elena, García-Garmendia, José Luis, Garnacho-Montero, José, Gómez, José M., Huerta, Arturo, Jorge-García, Ruth Noemí, Loza-Vázquez, Ana, Marin-Corral, Judith, Martínez de la Gándara, Amalia, Martin-Delgado, María Cruz, Martínez-Varela, Ignacio, Messa, Juan Lopez, Muñiz-Albaiceta, Guillermo, Nieto, María Teresa, Novo, Mariana Andrea, Peñasco, Yhivian, Pozo-Laderas, Juan Carlos, Pérez-García, Felipe, Ricart, Pilar, Roche-Campo, Ferran, Rodríguez, Alejandro, Sagredo, Victor, Sánchez-Miralles, Angel, Sancho-Chinesta, Susana, Socias, Lorenzo, Solé-Violan, Jordi, Suarez-Sipmann, Fernando, Tamayo-Lomas, Luis, Trenado, José, Úbeda, Alejandro, Valdivia, Luis Jorge, Vidal, Pablo, Bermejo, Jesus, Gonzalez, Jesica, Barbe, Ferran, Calfee, Carolyn S., Artigas, Antonio, and Torres, Antoni

Published
2024
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194. Flow starvation during square-flow assisted ventilation detected by supervised deep learning techniques

Author

de Haro, Candelaria, Santos-Pulpón, Verónica, Telías, Irene, Xifra-Porxas, Alba, Subirà, Carles, Batlle, Montserrat, Fernández, Rafael, Murias, Gastón, Albaiceta, Guillermo M., Fernández-Gonzalo, Sol, Godoy-González, Marta, Gomà, Gemma, Nogales, Sara, Roca, Oriol, Pham, Tai, López-Aguilar, Josefina, Magrans, Rudys, Brochard, Laurent, Blanch, Lluís, and Sarlabous, Leonardo

Published
2024
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