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1. Exploring ASR-Based Wav2Vec2 for Automated Speech Disorder Assessment: Insights and Analysis

Author

Nguyen, Tuan, Fredouille, Corinne, Ghio, Alain, Balaguer, Mathieu, and Woisard, Virginie

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Sound
Abstract

With the rise of SSL and ASR technologies, the Wav2Vec2 ASR-based model has been fine-tuned for automated speech disorder quality assessment tasks, yielding impressive results and setting a new baseline for Head and Neck Cancer speech contexts. This demonstrates that the ASR dimension from Wav2Vec2 closely aligns with assessment dimensions. Despite its effectiveness, this system remains a black box with no clear interpretation of the connection between the model ASR dimension and clinical assessments. This paper presents the first analysis of this baseline model for speech quality assessment, focusing on intelligibility and severity tasks. We conduct a layer-wise analysis to identify key layers and compare different SSL and ASR Wav2Vec2 models based on pre-trained data. Additionally, post-hoc XAI methods, including Canonical Correlation Analysis (CCA) and visualization techniques, are used to track model evolution and visualize embeddings for enhanced interpretability., Comment: Accepted at the Spoken Language Technology (SLT) Conference 2024

Published
2024

2. Integration of Structural Equation Modeling and Bayesian Networks in the Context of Causal Inference: A Case Study on Personal Positive Youth Development

Author

Benitez, Edgar and Balaguer, Alvaro

Subjects
Statistics - Methodology, 62H22, 62C10, 62P25, 62F15, G.3, I.2.6, I.6.5, I.6.4, H.4.2, H.2.8, J.4, J.1
Abstract

In this study, the combined use of structural equation modeling (SEM) and Bayesian network modeling (BNM) in causal inference analysis is revisited. The perspective highlights the debate between proponents of using BNM as either an exploratory phase or even as the sole phase in the definition of structural models, and those advocating for SEM as the superior alternative for exploratory analysis. The individual strengths and limitations of SEM and BNM are recognized, but this exploration evaluates the contention between utilizing SEM's robust structural inference capabilities and the dynamic probabilistic modeling offered by BNM. A case study of the work of, \citet{balaguer_2022} in a structural model for personal positive youth development (\textit{PYD}) as a function of positive parenting (\textit{PP}) and perception of the climate and functioning of the school (\textit{CFS}) is presented. The paper at last presents a clear stance on the analytical primacy of SEM in exploratory causal analysis, while acknowledging the potential of BNM in subsequent phases., Comment: 38 pages, 9 figures, 2 tables

Published
2024

3. Massive IIA flux compactifications with dynamical open strings

Author

Balaguer, Juan Ramón, Bevilacqua, Valentina, Dibitetto, Giuseppe, Fernández-Melgarejo, Jose J., and Sudano, Giuseppe

Subjects
High Energy Physics - Theory
Abstract

We consider massive type IIA compactifications down to 4 dimensions in presence of O6 planes and D6 branes parallel to them, in order to preserve half-maximal supersymmetry in 4D. The dynamics of open strings living on the spacetime filling branes is taken into account, in the gauged supergravity description, by adding extra vector multiplets and embedding tensor components. The scalar potential gets new terms that can be matched with contributions coming from dimensional reduction of the non-Abelian DBI and WZ brane actions. In this setting, we analyze the vacuum structure of the theory and find novel AdS$_4$ vacua, both supersymmetric and non-supersymmetric ones. Furthermore, we address their perturbative stability by computing their mass spectra. Some of the vacua are found to be perturbatively stable, despite their being non-supersymmetric. We conclude by discussing the reliability of our setup in terms of higher-derivative corrections., Comment: 39 pages

Published
2024

4. Automatic Modelling of Perceptual Judges in the Context of Head and Neck Cancer Speech Intelligibility

Author

Sebastião Quintas, Mathieu Balaguer, Julie Mauclair, Virginie Woisard, and Julien Pinquier

Abstract

Background: Perceptual measures such as speech intelligibility are known to be biased, variant and subjective, to which an automatic approach has been seen as a more reliable alternative. On the other hand, automatic approaches tend to lack explainability, an aspect that can prevent the widespread usage of these technologies clinically. Aims: In the present work, we aim to study the relationship between four perceptual parameters and speech intelligibility by automatically modelling the behaviour of six perceptual judges, in the context of head and neck cancer. From this evaluation we want to assess the different levels of relevance of each parameter as well as the different judge profiles that arise, both perceptually and automatically. Methods and Procedures: Based on a passage reading task from the Carcinologic Speech Severity Index (C2SI) corpus, six expert listeners assessed the voice quality, resonance, prosody and phonemic distortions, as well as the speech intelligibility of patients treated for oral or oropharyngeal cancer. A statistical analysis and an ensemble of automatic systems, one per judge, were devised, where speech intelligibility is predicted as a function of the four aforementioned perceptual parameters of voice quality, resonance, prosody and phonemic distortions. Outcomes and Results: The results suggest that we can automatically predict speech intelligibility as a function of the four aforementioned perceptual parameters, achieving a high correlation of 0.775 (Spearman's [rho]). Furthermore, different judge profiles were found perceptually that were successfully modelled automatically. Conclusions and Implications: The four investigated perceptual parameters influence the global rating of speech intelligibility, showing that different judge profiles emerge. The proposed automatic approach displayed a more uniform profile across all judges, displaying a more reliable, unbiased and objective prediction. The system also adds an extra layer of interpretability, since speech intelligibility is regressed as a direct function of the individual prediction of the four perceptual parameters, an improvement over more black box approaches.

Published
2024
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5. OCCASO V. Chemical-abundance trends with Galactocentric distance and age

Author

Carbajo-Hijarrubia, J., Casamiquela, L., Carrera, R., Balaguer-Núñez, L., Jordi, C., Anders, F., Gallart, C., Pancino, E., Drazdauskas, A., Stonkute, E., Tautvaišiene, G., Carrasco, J. M., Masana, E., Cantat-Gaudin, T., and Blanco-Cuaresma, S.

Subjects
Astrophysics - Astrophysics of Galaxies
Abstract

Context. Open clusters provide valuable information on stellar nucleosynthesis and the chemical evolution of the Galactic disc, as their age and distances can be measured more precisely with photometry than for field stars. Aims. Our aim is to study the chemical distribution of the Galactic disc using open clusters by analysing the existence of gradients with Galactocentric distance, azimuth or height from the plane and dependency with age. Methods. High-resolution spectra (R>60 000) of 194 stars belonging to 36 open clusters are used to determine atmospheric parameters and chemical abundances with two independent methods: equivalent widths and spectral synthesis. The sample has been complemented with 63 clusters with high-resolution spectroscopy from literature. Results. We measure local thermodynamic equilibrium abundances for 21 elements: {\alpha} (Mg, Si, Ca, and Ti), odd-Z (Na and Al), Fe-peak (Fe, Sc, V, Cr, Mn, Co, Ni, Cu, and Zn), and neutron-capture (Sr, Y, Zr, Ba, Ce, and Nd). We also provide non-local thermodynamic equilibrium abundances for elements when corrections are available. We find inner disc young clusters enhanced in [Mg/Fe] and [Si/Fe] compared to other clusters of their age. For [Ba/Fe] we report an age trend flattening for older clusters (age<2.5 Ga). The studied elements follow the expected radial gradients as a function of their nucleosynthesis groups, which are significantly steeper for the oldest systems. For the first time, we investigate the existence of an azimuthal gradient, finding some hints of its existence among the old clusters (age>2 Ga).

Published
2024
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6. Using deep reinforcement learning to promote sustainable human behaviour on a common pool resource problem

Author

Koster, Raphael, Pîslar, Miruna, Tacchetti, Andrea, Balaguer, Jan, Liu, Leqi, Elie, Romuald, Hauser, Oliver P., Tuyls, Karl, Botvinick, Matt, and Summerfield, Christopher

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computers and Society, Computer Science - Computer Science and Game Theory
Abstract

A canonical social dilemma arises when finite resources are allocated to a group of people, who can choose to either reciprocate with interest, or keep the proceeds for themselves. What resource allocation mechanisms will encourage levels of reciprocation that sustain the commons? Here, in an iterated multiplayer trust game, we use deep reinforcement learning (RL) to design an allocation mechanism that endogenously promotes sustainable contributions from human participants to a common pool resource. We first trained neural networks to behave like human players, creating a stimulated economy that allowed us to study how different mechanisms influenced the dynamics of receipt and reciprocation. We then used RL to train a social planner to maximise aggregate return to players. The social planner discovered a redistributive policy that led to a large surplus and an inclusive economy, in which players made roughly equal gains. The RL agent increased human surplus over baseline mechanisms based on unrestricted welfare or conditional cooperation, by conditioning its generosity on available resources and temporarily sanctioning defectors by allocating fewer resources to them. Examining the AI policy allowed us to develop an explainable mechanism that performed similarly and was more popular among players. Deep reinforcement learning can be used to discover mechanisms that promote sustainable human behaviour.

Published
2024

7. The longevity of the oldest open clusters: Structural parameters of NGC 188, NGC 2420, NGC 2425, NGC 2682, NGC 6791, NGC 6819

Author

Alvarez-Baena, N., Carrera, R., Thompson, H., Balaguer-Nuñez, L., Bragaglia, A., Jordi, C., Silva-Villa, E., and Vallenari, A.

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

Context: Open clusters' dynamical evolution is driven by stellar evolution, internal dynamics and external forces, which according to dynamical simulations, will evaporate them in a timescale of about 1 Ga. However, about 10\% of the known open clusters are older. They are special systems whose detailed properties are related to their dynamical evolution and the balance between mechanisms of cluster formation and dissolution. Aims:We investigate the spatial distribution and structural parameters of six open clusters older than 1 Ga in order to constrain their dynamical evolution, and longevity.} Methods: We identify members using Gaia EDR3 data up to a distance of 150 pc from each cluster's centre. We investigate the spatial distribution of stars inside each cluster to understand their degree of mass segregation. Finally, in order to interpret the obtained radial density profiles we reproduced them using the lowered isothermal model explorer with PYTHON Limepy and spherical potential escapers stitched SPES. Results: All the studied clusters seem more extended than previously reported in the literature. The spatial distributions of three of them show some structures aligned with their orbits. They may be related to the existence of extra tidal stars. In fact, we find that about 20 % of their members have enough energy to leave the systems or are already unbound. Together with their initial masses, their distances to the Galactic plane may play significant roles in their survival. We found clear evidences that the most dynamically evolved clusters do not fill their Roche volumes, appearing more concentrated than the others. Finally, we find a cusp-core dichotomy in the central regions of the studied clusters, which shows some similarities to the one observed among globular clusters., Comment: 16 pages, 11 figures, accepted for publication in A&A

Published
2024
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8. Discovery of a dormant 33 solar-mass black hole in pre-release Gaia astrometry

Author

Gaia Collaboration, Panuzzo, P., Mazeh, T., Arenou, F., Holl, B., Caffau, E., Jorissen, A., Babusiaux, C., Gavras, P., Sahlmann, J., Bastian, U., Wyrzykowski, Ł., Eyer, L., Leclerc, N., Bauchet, N., Bombrun, A., Mowlavi, N., Seabroke, G. M., Teyssier, D., Balbinot, E., Helmi, A., Brown, A. G. A., Vallenari, A., Prusti, T., de Bruijne, J. H. J., Barbier, A., Biermann, M., Creevey, O. L., Ducourant, C., Evans, D. W., Guerra, R., Hutton, A., Jordi, C., Klioner, S. A., Lammers, U., Lindegren, L., Luri, X., Mignard, F., Nicolas, C., Randich, S., Sartoretti, P., Smiljanic, R., Tanga, P., Walton, N. A., Aerts, C., Bailer-Jones, C. A. L., Cropper, M., Drimmel, R., Jansen, F., Katz, D., Lattanzi, M. G., Soubiran, C., Thévenin, F., van Leeuwen, F., Andrae, R., Audard, M., Bakker, J., Blomme, R., Castañeda, J., De Angeli, F., Fabricius, C., Fouesneau, M., Frémat, Y., Galluccio, L., Guerrier, A., Heiter, U., Masana, E., Messineo, R., Nienartowicz, K., Pailler, F., Riclet, F., Roux, W., Sordo, R., Gracia-Abril, G., Portell, J., Altmann, M., Benson, K., Berthier, J., Burgess, P. W., Busonero, D., Busso, G., Cacciari, C., Cánovas, H., Carrasco, J. M., Carry, B., Cellino, A., Cheek, N., Clementini, G., Damerdji, Y., Davidson, M., de Teodoro, P., Delchambre, L., Dell'Oro, A., Garcia, E. Fraile, Garabato, D., García-Lario, P., Haigron, R., Hambly, N. C., Harrison, D. L., Hatzidimitriou, D., Hernández, J., Hestroffer, D., Hodgkin, S. T., Jamal, S., de Fombelle, G. Jevardat, Jordan, S., Krone-Martins, A., Lanzafame, A. C., Löffler, W., Lorca, A., Marchal, O., Marrese, P. M., Moitinho, A., Muinonen, K., Campos, M. Nuñez, Oreshina-Slezak, I., Osborne, P., Pancino, E., Pauwels, T., Recio-Blanco, A., Riello, M., Rimoldini, L., Robin, A. C., Roegiers, T., Sarro, L. M., Schultheis, M., Smith, M., Sozzetti, A., Utrilla, E., van Leeuwen, M., Weingrill, K., Abbas, U., Ábrahám, P., Aramburu, A. Abreu, Ahmed, S., Altavilla, G., Álvarez, M. A., Anders, F., Anderson, R. I., Varela, E. Anglada, Antoja, T., Baig, S., Baines, D., Baker, S. G., Balaguer-Núñez, L., Balog, Z., Barache, C., Barros, M., Barstow, M. A., Bartolomé, S., Bashi, D., Bassilana, J. -L., Baudeau, N., Becciani, U., Bedin, L. R., Bellas-Velidis, I., Bellazzini, M., Beordo, W., Bernet, M., Bertolotto, C., Bertone, S., Bianchi, L., Binnenfeld, A., Blanco-Cuaresma, S., Bland-Hawthorn, J., Blazere, A., Boch, T., Bossini, D., Bouquillon, S., Bragaglia, A., Braine, J., Bratsolis, E., Breedt, E., Bressan, A., Brouillet, N., Brugaletta, E., Bucciarelli, B., Butkevich, A. G., Buzzi, R., Camut, A., Cancelliere, R., Cantat-Gaudin, T., Guilarte, D. Capilla, Carballo, R., Carlucci, T., Carnerero, M. I., Carretero, J., Carton, S., Casamiquela, L., Casey, A., Castellani, M., Castro-Ginard, A., Ceraj, L., Cesare, V., Charlot, P., Chaudet, C., Chemin, L., Chiavassa, A., Chornay, N., Chosson, D., Cooper, W. J., Cornez, T., Cowell, S., Crosta, M., Crowley, C., Reyes, M. Cruz, Dafonte, C., Ponte, M. Dal, David, M., de Laverny, P., De Luise, F., De March, R., De Ridder, J., de Torres, A., del Peloso, E. F., Delbo, M., Delgado, A., Delisle, J. -B., Demouchy, C., Denis, E., Dharmawardena, T. E., Di Giacomo, F., Diener, C., Distefano, E., Dolding, C., Dsilva, K., Enke, H., Fabre, C., Fabrizio, M., Faigler, S., Fatović, M., Fedorets, G., Fernández-Hernández, J., Fernique, P., Figueras, F., Fouron, C., Fragkoudi, F., Gai, M., Galinier, M., Garcia-Serrano, A., García-Torres, M., Garofalo, A., Gerlach, E., Geyer, R., Giacobbe, P., Gilmore, G., Girona, S., Giuffrida, G., Gomboc, A., Gomez, A., González-Santamaría, I., Gosset, E., Granvik, M., Barrera, V. Gregori, Gutiérrez-Sánchez, R., Haywood, M., Helmer, A., Hidalgo, S. L., Hilger, T., Hobbs, D., Hottier, C., Huckle, H. E., Jiménez-Arranz, Ó., Campillo, J. Juaristi, Kaczmarek, Z., Kervella, P., Khanna, S., Kontizas, M., Kordopatis, G., Korn, A. J., Kóspál, Á, Kostrzewa-Rutkowska, Z., Kruszyńska, K., Kun, M., Lambert, S., Lanza, A. F., Lebreton, Y., Lebzelter, T., Leccia, S., Lecoutre, G., Liao, S., Liberato, L., Licata, E., Livanou, E., Lobel, A., López-Miralles, J., Loup, C., Madarász, M., Mahy, L., Mann, R. G., Manteiga, M., Marinoni, S., Marcellino, C. P., Marshall, D. J., Mascarenhas, D., Marchant, J. M., Lozano, J. Martín, Masip, A., Marconi, M., Pina, D. Marín, Polo, L. Martin, Martín-Fleitas, J. M., Mastrobuono-Battisti, A., McMillan, P. J., Meichsner, J. G. Marton, Merc, J., Messina, S., Millar, N. R., Mints, A., Mohamed, D., Molina, D., Molinaro, R., Monguió, M., Montegriffo, P., Monti, L., Mora, A., Morbidelli, R., Morris, D., Mudimadugula, R., Muraveva, T., Musella, I., Nagy, Z., Nardetto, N., Navarrete, C., Oh, S., Ordenovic, C., Orenstein, O., Pagani, C., Pagano, I., Palaversa, L., Palicio, P. A., Pallas-Quintela, L., Pawlak, M., Penttilä, A., Pesciullesi, P., Pinamonti, M., Plachy, E., Planquart, L., Plum, G., Poggio, E., Pourbaix, D., Price-Whelan, A. M., Pulone, L., Rabin, V., Rainer, M., Raiteri, C. M., Ramos, P., Ramos-Lerate, M., Ratajczak, M., Fiorentin, P. Re, Regibo, S., Reylé, C., Ripepi, V., Riva, A., Rix, H. -W., Rixon, G., Robert, G., Robichon, N., Robin, C., Romero-Gómez, M., Rowell, N., Mieres, D. Ruz, Rybicki, K. A., Sadowski, G., Sellés, A. Sagristà, Sanna, N., Santoveña, R., Sarasso, M., Sarmiento, M. H., Riera, C. Sarrate, Sciacca, E., Ségransan, D., Semczuk, M., Shahaf, S., Siebert, A., Slezak18, E., Smart, R. L., Snaith, O. N., Solano, E., Solitro, F., Souami, D., Souchay, J., Spitoni, E., Spoto, F., Squillante, L. A., Steele, I. A., Steidelmüller, H., Surdej, J., Szabados, L., Taris, F., Taylor, M. B., Teixeira, R., Tepper-Garcia, T., Thuillot, W., Tolomei, L., Tonello, N., Torra, F., Elipe, G. Torralba, Trabucchi, M., Trentin, E., Tsantaki, M., Turon, C., Ulla, A., Unger, N., Valtchanov, I., Vanel, O., Vecchiato, A., Vicente, D., Villar, E., Weiler, M., Zhao, H., Zorec, J., Zucker, S., Župić, A., and Zwitter, T.

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

Gravitational waves from black-hole merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models - and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive metal-poor stars. Gaia astrometry is expected to uncover many Galactic wide-binary systems containing dormant BHs, which may not have been detected before. The study of this population will provide new information on the BH-mass distribution in binaries and shed light on their formation mechanisms and progenitors. As part of the validation efforts in preparation for the fourth Gaia data release (DR4), we analysed the preliminary astrometric binary solutions, obtained by the Gaia Non-Single Star pipeline, to verify their significance and to minimise false-detection rates in high-mass-function orbital solutions. The astrometric binary solution of one source, Gaia BH3, implies the presence of a 32.70 \pm 0.82 M\odot BH in a binary system with a period of 11.6 yr. Gaia radial velocities independently validate the astrometric orbit. Broad-band photometric and spectroscopic data show that the visible component is an old, very metal-poor giant of the Galactic halo, at a distance of 590 pc. The BH in the Gaia BH3 system is more massive than any other Galactic stellar-origin BH known thus far. The low metallicity of the star companion supports the scenario that metal-poor massive stars are progenitors of the high-mass BHs detected by gravitational-wave telescopes. The Galactic orbit of the system and its metallicity indicate that it might belong to the Sequoia halo substructure. Alternatively, and more plausibly, it could belong to the ED-2 stream, which likely originated from a globular cluster that had been disrupted by the Milky Way., Comment: 23 pages, accepted fro publication in A&A Letters. New version with small fixes

Published
2024
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9. Exploring Pathological Speech Quality Assessment with ASR-Powered Wav2Vec2 in Data-Scarce Context

Author

Nguyen, Tuan, Fredouille, Corinne, Ghio, Alain, Balaguer, Mathieu, and Woisard, Virginie

Subjects
Electrical Engineering and Systems Science - Audio and Speech Processing, Computer Science - Computation and Language, Computer Science - Machine Learning, Computer Science - Sound
Abstract

Automatic speech quality assessment has raised more attention as an alternative or support to traditional perceptual clinical evaluation. However, most research so far only gains good results on simple tasks such as binary classification, largely due to data scarcity. To deal with this challenge, current works tend to segment patients' audio files into many samples to augment the datasets. Nevertheless, this approach has limitations, as it indirectly relates overall audio scores to individual segments. This paper introduces a novel approach where the system learns at the audio level instead of segments despite data scarcity. This paper proposes to use the pre-trained Wav2Vec2 architecture for both SSL, and ASR as feature extractor in speech assessment. Carried out on the HNC dataset, our ASR-driven approach established a new baseline compared with other approaches, obtaining average $MSE=0.73$ and $MSE=1.15$ for the prediction of intelligibility and severity scores respectively, using only 95 training samples. It shows that the ASR based Wav2Vec2 model brings the best results and may indicate a strong correlation between ASR and speech quality assessment. We also measure its ability on variable segment durations and speech content, exploring factors influencing its decision., Comment: Accepted at LREC-COLING 2024

Published
2024

10. Incidence, risk factors and therapy response of acute graft-versus-host disease after myeloablative hematopoietic stem cell transplantation with posttransplant cyclophosphamide

Author

Asensi Cantó, P., Gómez-Seguí, I., Montoro, J., Villalba Montaner, M., Chorão, P., Solves Alcaína, P., Santiago Balsera, M., Lloret Madrid, P., Solís Ruiz, J., Sopeña Pell-Ilderton, C., Martínez Campuzano, D., Granados Serrano, P., Eiris del Río, J., Louro, A., Rebollar, P., Perla, A., Benavente, R., De la Rubia Comos, J., Sanz, M. A., Balaguer, A., and Sanz, J.

Published
2024
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13. Real Evaluations Tractability using Continuous Goal-Directed Actions in Smart City Applications

Author

Fernandez-Fernandez, Raul, Victores, Juan G., Estevez, David, and Balaguer, Carlos

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

One of the most important challenges of Smart City Applications is to adapt the system to interact with non-expert users. Robot imitation frameworks aim to simplify and reduce times of robot programming by allowing users to program directly through demonstrations. In classical frameworks, actions are modeled using joint or Cartesian space trajectories. Other features, such as visual ones, are not always well represented with these pure geometrical approaches. Continuous Goal-Directed Actions (CGDA) is an alternative to these methods, as it encodes actions as changes of any feature that can be extracted from the environment. As a consequence of this, the robot joint trajectories for execution must be fully computed to comply with this feature-agnostic encoding. This is achieved using Evolutionary Algorithms (EA), which usually requires too many evaluations to perform this evolution step in the actual robot. Current strategies involve performing evaluations in a simulation, transferring the final joint trajectory to the actual robot. Smart City applications involve working in highly dynamic and complex environments, where having a precise model is not always achievable. Our goal is to study the tractability of performing these evaluations directly in a real-world scenario. Two different approaches to reduce the number of evaluations using EA, are proposed and compared. In the first approach, Particle Swarm Optimization (PSO)-based methods have been studied and compared within CGDA: naive PSO, Fitness Inheritance PSO (FI-PSO), and Adaptive Fuzzy Fitness Granulation with PSO (AFFG-PSO). The second approach studied the introduction of geometrical and velocity constraints within CGDA. The effects of both approaches were analyzed and compared in the wax and paint actions, two CGDA commonly studied use cases. Results from this paper depict an important reduction in the number of evaluations.

Published
2024
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14. Neural Policy Style Transfer

Author

Fernandez-Fernandez, Raul, Victores, Juan G., Gago, Jennifer J., Estevez, David, and Balaguer, Carlos

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

Style Transfer has been proposed in a number of fields: fine arts, natural language processing, and fixed trajectories. We scale this concept up to control policies within a Deep Reinforcement Learning infrastructure. Each network is trained to maximize the expected reward, which typically encodes the goal of an action, and can be described as the content. The expressive power of deep neural networks enables encoding a secondary task, which can be described as the style. The Neural Policy Style Transfer (NPST) algorithm is proposed to transfer the style of one policy to another, while maintaining the content of the latter. Different policies are defined via Deep Q-Network architectures. These models are trained using demonstrations through Inverse Reinforcement Learning. Two different sets of user demonstrations are performed, one for content and other for style. Different styles are encoded as defined by user demonstrations. The generated policy is the result of feeding a content policy and a style policy to the NPST algorithm. Experiments are performed in a catch-ball game inspired by the Deep Reinforcement Learning classical Atari games; and a real-world painting scenario with a full-sized humanoid robot, based on previous works of the authors. The implementation of three different Q-Network architectures (Shallow, Deep and Deep Recurrent Q-Network) to encode the policies within the NPST framework is proposed and the results obtained in the experiments with each of these architectures compared.

Published
2024
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15. Deep Robot Sketching: An application of Deep Q-Learning Networks for human-like sketching

Author

Fernandez-Fernandez, Raul, Victores, Juan G., and Balaguer, Carlos

Subjects
Computer Science - Robotics, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning, Computer Science - Neural and Evolutionary Computing
Abstract

The current success of Reinforcement Learning algorithms for its performance in complex environments has inspired many recent theoretical approaches to cognitive science. Artistic environments are studied within the cognitive science community as rich, natural, multi-sensory, multi-cultural environments. In this work, we propose the introduction of Reinforcement Learning for improving the control of artistic robot applications. Deep Q-learning Neural Networks (DQN) is one of the most successful algorithms for the implementation of Reinforcement Learning in robotics. DQN methods generate complex control policies for the execution of complex robot applications in a wide set of environments. Current art painting robot applications use simple control laws that limits the adaptability of the frameworks to a set of simple environments. In this work, the introduction of DQN within an art painting robot application is proposed. The goal is to study how the introduction of a complex control policy impacts the performance of a basic art painting robot application. The main expected contribution of this work is to serve as a first baseline for future works introducing DQN methods for complex art painting robot frameworks. Experiments consist of real world executions of human drawn sketches using the DQN generated policy and TEO, the humanoid robot. Results are compared in terms of similarity and obtained reward with respect to the reference inputs

Published
2024
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16. RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture

Author

Balaguer, Angels, Benara, Vinamra, Cunha, Renato Luiz de Freitas, Filho, Roberto de M. Estevão, Hendry, Todd, Holstein, Daniel, Marsman, Jennifer, Mecklenburg, Nick, Malvar, Sara, Nunes, Leonardo O., Padilha, Rafael, Sharp, Morris, Silva, Bruno, Sharma, Swati, Aski, Vijay, and Chandra, Ranveer

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

There are two common ways in which developers are incorporating proprietary and domain-specific data when building applications of Large Language Models (LLMs): Retrieval-Augmented Generation (RAG) and Fine-Tuning. RAG augments the prompt with the external data, while fine-Tuning incorporates the additional knowledge into the model itself. However, the pros and cons of both approaches are not well understood. In this paper, we propose a pipeline for fine-tuning and RAG, and present the tradeoffs of both for multiple popular LLMs, including Llama2-13B, GPT-3.5, and GPT-4. Our pipeline consists of multiple stages, including extracting information from PDFs, generating questions and answers, using them for fine-tuning, and leveraging GPT-4 for evaluating the results. We propose metrics to assess the performance of different stages of the RAG and fine-Tuning pipeline. We conduct an in-depth study on an agricultural dataset. Agriculture as an industry has not seen much penetration of AI, and we study a potentially disruptive application - what if we could provide location-specific insights to a farmer? Our results show the effectiveness of our dataset generation pipeline in capturing geographic-specific knowledge, and the quantitative and qualitative benefits of RAG and fine-tuning. We see an accuracy increase of over 6 p.p. when fine-tuning the model and this is cumulative with RAG, which increases accuracy by 5 p.p. further. In one particular experiment, we also demonstrate that the fine-tuned model leverages information from across geographies to answer specific questions, increasing answer similarity from 47% to 72%. Overall, the results point to how systems built using LLMs can be adapted to respond and incorporate knowledge across a dimension that is critical for a specific industry, paving the way for further applications of LLMs in other industrial domains.

Published
2024

17. Gemini: A Family of Highly Capable Multimodal Models

Author

Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.

Published
2023

19. CTNND1 is involved in germline predisposition to early-onset gastric cancer by affecting cell-to-cell interactions

Author

Herrera-Pariente, Cristina, Bonjoch, Laia, Muñoz, Jenifer, Fernàndez, Guerau, Soares de Lima, Yasmin, Mahmood, Romesa, Cuatrecasas, Miriam, Ocaña, Teresa, Lopez-Prades, Sandra, Llargués-Sistac, Gemma, Domínguez-Rovira, Xavier, Llach, Joan, Luzko, Irina, Díaz-Gay, Marcos, Lazaro, Conxi, Brunet, Joan, Castillo-Manzano, Carmen, García-González, María Asunción, Lanas, Angel, Carrillo, Marta, Hernández San Gil, Raquel, Quintero, Enrique, Sala, Nuria, Llort, Gemma, Aguilera, Lara, Carot, Laura, Diez-Redondo, Pilar, Jover, Rodrigo, Ramon y Cajal, Teresa, Cubiella, Joaquín, Castells, Antoni, Balaguer, Francesc, Bujanda, Luis, Castellví-Bel, Sergi, and Moreira, Leticia

Published
2024
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20. Immune reconstitution after single-unit umbilical cord blood transplantation using anti-thymoglobulin and myeloablative conditioning in adults with hematological malignancies

Author

Cordón, Lourdes, Chorão, Pedro, Martín-Herreros, Beatriz, Montoro, Juan, Balaguer, Aitana, Guerreiro, Manuel, Villalba, Marta, Facal, Ana, Asensi, Pedro, Solves, Pilar, Gómez, Inés, Santiago, Marta, Lamas, Brais, Bataller, Ana, Granados, Pablo, Sempere, Amparo, Sanz, Guillermo F., Sanz, Miguel A., and Sanz, Jaime

Published
2024
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21. Real-world evaluation of a QCM-based biosensor for exhaled air

Author

Juste-Dolz, Augusto, Teixeira, William, Pallás-Tamarit, Yeray, Carballido-Fernández, Mario, Carrascosa, Javier, Morán-Porcar, Ángela, Redón-Badenas, María Ángeles, Pla-Roses, María Gracia, Tirado-Balaguer, María Dolores, Remolar-Quintana, María José, Ortiz-Carrera, Jon, Ibañez-Echevarría, Ethel, Maquieira, Angel, and Giménez-Romero, David

Published
2024
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23. Barriers and facilitators to implementation of the interoperable Survivorship Passport (SurPass) v2.0 in 6 European countries: a PanCareSurPass online survey study

Author

van den Oever, Selina R., de Beijer, Ismay A. E., Kremer, Leontien C. M., Alfes, Marie, Balaguer, Julia, Bardi, Edit, Nieto, Adela Cañete, Cangioli, Giorgio, Charalambous, Eliana, Chronaki, Catherine, Costa, Tiago, Degelsegger, Alexander, Düster, Vanessa, Filbert, Anna-Liesa, Grabow, Desiree, Gredinger, Gerald, Gsell, Hannah, Haupt, Riccardo, van Helvoirt, Maria, Ladenstein, Ruth, Langer, Thorsten, Laschkolnig, Anja, Muraca, Monica, Rascon, Jelena, Schreier, Günter, Tomasikova, Zuzana, Tormo, Maria Teresa, Trinkunas, Justas, Trollip, Jessica, Trunner, Kathrin, Uyttebroeck, Anne, van der Pal, Helena J. H., and Pluijm, Saskia M. F.

Published
2024
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24. Gaia Focused Product Release: Sources from Service Interface Function image analysis -- Half a million new sources in omega Centauri

Author

Gaia Collaboration, Weingrill, K., Mints, A., Castañeda, J., Kostrzewa-Rutkowska, Z., Davidson, M., De Angeli, F., Hernández, J., Torra, F., Ramos-Lerate, M., Babusiaux, C., Biermann, M., Crowley, C., Evans, D. W., Lindegren, L., Martín-Fleitas, J. M., Palaversa, L., Mieres, D. Ruz, Tisanić, K., Brown, A. G. A., Vallenari, A., Prusti, T., de Bruijne, J. H. J., Arenou, F., Barbier, A., Creevey, O. L., Ducourant, C., Eyer, L., Guerra, R., Hutton, A., Jordi, C., Klioner, S. A., Lammers, U., Luri, X., Mignard, F., Randich, S., Sartoretti, P., Smiljanic, R., Tanga, P., Walton, N. A., Bailer-Jones, C. A. L., Bastian, U., Cropper, M., Drimmel, R., Katz, D., Soubiran, C., van Leeuwen, F., Audard, M., Bakker, J., Blomme, R., Fabricius, C., Fouesneau, M., Frémat, Y., Galluccio, L., Guerrier, A., Masana, E., Messineo, R., Nicolas, C., Nienartowicz, K., Pailler, F., Panuzzo, P., Riclet, F., Roux, W., Seabroke, G. M., Sordo, R., Thévenin, F., Gracia-Abril, G., Portell, J., Teyssier, D., Altmann, M., Benson, K., Berthier, J., Burgess, P. W., Busonero, D., Busso, G., Cánovas, H., Carry, B., Cheek, N., Clementini, G., Damerdji, Y., de Teodoro, P., Delchambre, L., DellÓro, A., Garcia, E. Fraile, Garabato, D., García-Lario, P., Torres, N. Garralda, Gavras, P., Haigron, R., Hambly, N. C., Harrison, D. L., Hatzidimitriou, D., Hodgkin, S. T., Holl, B., Jamal, S., Jordan, S., Krone-Martins, A., Lanzafame, A. C., Löffler, W., Lorca, A., Marchal, O., Marrese, P. M., Moitinho, A., Muinonen, K., Campos, M. Nuñez, Oreshina-Slezak, I., Osborne, P., Pancino, E., Pauwels, T., Recio-Blanco, A., Riello, M., Rimoldini, L., Robin, A. C., Roegiers, T., Sarro, L. M., Schultheis, M., Siopis, C., Smith, M., Sozzetti, A., Utrilla, E., van Leeuwen, M., Abbas, U., Ábrahám, P., Aramburu, A. Abreu, Aerts, C., Altavilla, G., Álvarez, M. A., Alves, J., Anders, F., Anderson, R. I., Antoja, T., Baines, D., Baker, S. G., Balog, Z., Barache, C., Barbato, D., Barros, M., Barstow, M. A., Bartolomé, S., Bashi, D., Bauchet, N., Baudeau, N., Becciani, U., Bedin, L. R., Bellas-Velidis, I., Bellazzini, M., Beordo, W., Berihuete, A., Bernet, M., Bertolotto, C., Bertone, S., Bianchi, L., Binnenfeld, A., Blazere, A., Boch, T., Bombrun, A., Bouquillon, S., Bragaglia, A., Braine, J., Bramante, L., Breedt, E., Bressan, A., Brouillet, N., Brugaletta, E., Bucciarelli, B., Butkevich, A. G., Buzzi, R., Caffau, E., Cancelliere, R., Cannizzo, S., Cantat-Gaudin, T., Carballo, R., Carlucci, T., Carnerero, M. I., Carrasco, J. M., Carretero, J., Carton, S., Casamiquela, L., Castellani, M., Castro-Ginard, A., Cesare, V., Charlot, P., Chemin, L., Chiaramida, V., Chiavassa, A., Chornay, N., Collins, R., Contursi, G., Cooper, W. J., Cornez, T., Crosta, M., Dafonte, C., de Laverny, P., De Luise, F., De March, R., de Souza, R., de Torres, A., del Peloso, E. F., Delbo, M., Delgado, A., Dharmawardena, T. E., Diakite, S., Diener, C., Distefano, E., Dolding, C., Dsilva, K., Durán, J., Enke, H., Esquej, P., Fabre, C., Fabrizio, M., Faigler, S., Fatović, M., Fedorets, G., Fernández-Hernández, J., Fernique, P., Figueras, F., Fournier, Y., Fouron, C., Gai, M., Galinier, M., Garcia-Gutierrez, A., García-Torres, M., Garofalo, A., Gerlach, E., Geyer, R., Giacobbe, P., Gilmore, G., Girona, S., Giuffrida, G., Gomel, R., Gomez, A., González-Núñez, J., González-Santamaría, I., Gosset, E., Granvik, M., Barrera, V. Gregori, Gutiérrez-Sánchez, R., Haywood, M., Helmer, A., Helmi, A., Henares, K., Hidalgo, S. L., Hilger, T., Hobbs, D., Hottier, C., Huckle, H. E., Jabłońska, M., Jansen, F., Jiménez-Arranz, Ó., Campillo, J. Juaristi, Khanna, S., Kordopatis, G., Kóspál, Á, Kun, M., Lambert, S., Lanza, A. F., Campion, J. -F. Le, Lebreton, Y., Lebzelter, T., Leccia, S., Lecoeur-Taibi, I., Lecoutre, G., Liao, S., Liberato, L., Licata, E., Lindstrøm, H. E. P., Lister, T. A., Livanou, E., Lobel, A., Loup, C., Mahy, L., Mann, R. G., Manteiga, M., Marchant, J. M., Marconi, M., Pina, D. Marín, Marinoni, S., Marshall, D. J., Lozano, J. Martín, Marton, G., Mary, N., Masip, A., Massari, D., Mastrobuono-Battisti, A., Mazeh, T., McMillan, P. J., Meichsner, J., Messina, S., Michalik, D., Millar, N. R., Molina, D., Molinaro, R., Molnár, L., Monari, G., Monguió, M., Montegriffo, P., Montero, A., Mor, R., Mora, A., Morbidelli, R., Morel, T., Morris, D., Mowlavi, N., Munoz, D., Muraveva, T., Murphy, C. P., Musella, I., Nagy, Z., Nieto, S., Noval, L., Ogden, A., Ordenovic, C., Pagani, C., Pagano, I., Palicio, P. A., Pallas-Quintela, L., Panahi, A., Panem, C., Payne-Wardenaar, S., Pegoraro, L., Penttilä, A., Pesciullesi, P., Piersimoni, A. M., Pinamonti, M., Pineau, F. -X., Plachy, E., Plum, G., Poggio, E., Pourbaix, D., Prša, A., Pulone, L., Racero, E., Rainer, M., Raiteri, C. M., Ramos, P., Ratajczak, M., Fiorentin, P. Re, Regibo, S., Reylé, C., Ripepi, V., Riva, A., Rix, H. -W., Rixon, G., Robichon, N., Robin, C., Romero-Gómez, M., Rowell, N., Royer, F., Rybicki, K. A., Sadowski, G., Núñez, A. Sáez, Sellés, A. Sagristà, Sahlmann, J., Gimenez, V. Sanchez, Sanna, N., Santoveña, R., Sarasso, M., Riera, C. Sarrate, Sciacca, E., Segovia, J. C., Ségransan, D., Shahaf, S., Siebert, A., Siltala, L., Slezak, E., Smart, R. L., Snaith, O. N., Solano, E., Solitro, F., Souami, D., Souchay, J., Spina, L., Spitoni, E., Spoto, F., Squillante, L. A., Steele, I. A., Steidelmüller, H., Surdej, J., Szabados, L., Taris, F., Taylor, M. B., Teixeira, R., Tolomei, L., Elipe, G. Torralba, Trabucchi, M., Tsantaki, M., Ulla, A., Unger, N., Vanel, O., Vecchiato, A., Vicente, D., Voutsinas, S., Weiler, M., Wyrzykowski, Ł., Zhao, H., Zorec, J., Zwitter, T., Balaguer-Núñez, L., Leclerc, N., Morgenthaler, S., Robert, G., and Zucker, S.

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

Gaia's readout window strategy is challenged by very dense fields in the sky. Therefore, in addition to standard Gaia observations, full Sky Mapper (SM) images were recorded for nine selected regions in the sky. A new software pipeline exploits these Service Interface Function (SIF) images of crowded fields (CFs), making use of the availability of the full two-dimensional (2D) information. This new pipeline produced half a million additional Gaia sources in the region of the omega Centauri ($\omega$ Cen) cluster, which are published with this Focused Product Release. We discuss the dedicated SIF CF data reduction pipeline, validate its data products, and introduce their Gaia archive table. Our aim is to improve the completeness of the {\it Gaia} source inventory in a very dense region in the sky, $\omega$ Cen. An adapted version of {\it Gaia}'s Source Detection and Image Parameter Determination software located sources in the 2D SIF CF images. We validated the results by comparing them to the public {\it Gaia} DR3 catalogue and external Hubble Space Telescope data. With this Focused Product Release, 526\,587 new sources have been added to the {\it Gaia} catalogue in $\omega$ Cen. Apart from positions and brightnesses, the additional catalogue contains parallaxes and proper motions, but no meaningful colour information. While SIF CF source parameters generally have a lower precision than nominal {\it Gaia} sources, in the cluster centre they increase the depth of the combined catalogue by three magnitudes and improve the source density by a factor of ten. This first SIF CF data publication already adds great value to the {\it Gaia} catalogue. It demonstrates what to expect for the fourth {\it Gaia} catalogue, which will contain additional sources for all nine SIF CF regions.

Published
2023
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25. Gaia Focused Product Release: A catalogue of sources around quasars to search for strongly lensed quasars

Author

Gaia Collaboration, Krone-Martins, A., Ducourant, C., Galluccio, L., Delchambre, L., Oreshina-Slezak, I., Teixeira, R., Braine, J., Campion, J. -F. Le, Mignard, F., Roux, W., Blazere, A., Pegoraro, L., Brown, A. G. A., Vallenari, A., Prusti, T., de Bruijne, J. H. J., Arenou, F., Babusiaux, C., Barbier, A., Biermann, M., Creevey, O. L., Evans, D. W., Eyer, L., Guerra, R., Hutton, A., Jordi, C., Klioner, S. A., Lammers, U., Lindegren, L., Luri, X., Randich, S., Sartoretti, P., Smiljanic, R., Tanga, P., Walton, N. A., Bailer-Jones, C. A. L., Bastian, U., Cropper, M., Drimmel, R., Katz, D., Soubiran, C., van Leeuwen, F., Audard, M., Bakker, J., Blomme, R., Castaneda, J., De Angeli, F., Fabricius, C., Fouesneau, M., Fremat, Y., Guerrier, A., Masana, E., Messineo, R., Nicolas, C., Nienartowicz, K., Pailler, F., Panuzzo, P., Riclet, F., Seabroke, G. M., Sordo, R., Thevenin, F., Gracia-Abril, G., Portell, J., Teyssier, D., Altmann, M., Benson, K., Berthier, J., Burgess, P. W., Busonero, D., Busso, G., Canovas, H., Carry, B., Cheek, N., Clementini, G., Damerdji, Y., Davidson, M., de Teodoro, P., Dell'Oro, A., Garcia, E. Fraile, Garabato, D., Garcia-Lario, P., Torres, N. Garralda, Gavras, P., Haigron, R., Hambly, N. C., Harrison, D. L., Hatzidimitriou, D., Hernandez, J., Hodgkin, S. T., Holl, B., Jamal, S., Jordan, S., Lanzafame, A. C., Loffler, W., Lorca, A., Marchal, O., Marrese, P. M., Moitinho, A., Muinonen, K., Campos, M. Nunez, Osborne, P., Pancino, E., Pauwels, T., Recio-Blanco, A., Riello, M., Rimoldini, L., Robin, A. C., Roegiers, T., Sarro, L. M., Schultheis, M., Siopis, C., Smith, M., Sozzetti, A., Utrilla, E., van Leeuwen, M., Weingrill, K., Abbas, U., Abraham, P., Aramburu, A. Abreu, Aerts, C., Altavilla, G., Alvarez, M. A., Alves, J., Anderson, R. I., Antoja, T., Baines, D., Baker, S. G., Balog, Z., Barache, C., Barbato, D., Barros, M., Barstow, M. A., Bartolome, S., Bashi, D., Bauchet, N., Baudeau, N., Becciani, U., Bedin, L. R., Bellas-Velidis, I., Bellazzini, M., Beordo, W., Berihuete, A., Bernet, M., Bertolotto, C., Bertone, S., Bianchi, L., Binnenfeld, A., Boch, T., Bombrun, A., Bouquillon, S., Bragaglia, A., Bramante, L., Breedt, E., Bressan, A., Brouillet, N., Brugaletta, E., Bucciarelli, B., Butkevich, A. G., Buzzi, R., Caffau, E., Cancelliere, R., Cannizzo, S., Carballo, R., Carlucci, T., Carnerero, M. I., Carrasco, J. M., Carretero, J., Carton, S., Casamiquela, L., Castellani, M., Castro-Ginard, A., Cesare, V., Charlot, P., Chemin, L., Chiaramida, V., Chiavassa, A., Chornay, N., Collins, R., Contursi, G., Cooper, W. J., Cornez, T., Crosta, M., Crowley, C., Dafonte, C., de Laverny, P., De Luise, F., De March, R., de Souza, R., de Torres, A., del Peloso, E. F., Delbo, M., Delgado, A., Dharmawardena, T. E., Diakite, S., Diener, C., Distefano, E., Dolding, C., Dsilva, K., Duran, J., Enke, H., Esquej, P., Fabre, C., Fabrizio, M., Faigler, S., Fatovic, M., Fedorets, G., Fernandez-Hernandez, J., Fernique, P., Figueras, F., Fournier, Y., Fouron, C., Gai, M., Galinier, M., Garcia-Gutierrez, A., Garcia-Torres, M., Garofalo, A., Gerlach, E., Geyer, R., Giacobbe, P., Gilmore, G., Girona, S., Giuffrida, G., Gomel, R., Gomez, A., Gonzalez-Nunez, J., Gonzalez-Santamaria, I., Gosset, E., Granvik, M., Barrera, V. Gregori, Gutierrez-Sanchez, R., Haywood, M., Helmer, A., Helmi, A., Henares, K., Hidalgo, S. L., Hilger, T., Hobbs, D., Hottier, C., Huckle, H. E., Jablonska, M., Jansen, F., Jimenez-Arranz, O., Campillo, J. Juaristi, Khanna, S., Kordopatis, G., Kospal, A., Kostrzewa-Rutkowska, Z., Kun, M., Lambert, S., Lanza, A. F., Lebreton, Y., Lebzelter, T., Leccia, S., Lecoeur-Taibi, I., Lecoutre, G., Liao, S., Liberato, L., Licata, E., Lindstrom, H. E. P., Lister, T. A., Livanou, E., Lobel, A., Loup, C., Mahy, L., Mann, R. G., Manteiga, M., Marchant, J. M., Marconi, M., Pina, D. Marin, Marinoni, S., Marshall, D. J., Lozano, J. Martin, Martin-Fleitas, J. M., Marton, G., Mary, N., Masip, A., Massari, D., Mastrobuono-Battisti, A., Mazeh, T., McMillan, P. J., Meichsner, J., Messina, S., Michalik, D., Millar, N. R., Mints, A., Molina, D., Molinaro, R., Molnar, L., Monari, G., Monguio, M., Montegriffo, P., Montero, A., Mor, R., Mora, A., Morbidelli, R., Morel, T., Morris, D., Mowlavi, N., Munoz, D., Muraveva, T., Murphy, C. P., Musella, I., Nagy, Z., Nieto, S., Noval, L., Ogden, A., Ordenovic, C., Pagani, C., Pagano, I., Palaversa, L., Palicio, P. A., Pallas-Quintela, L., Panahi, A., Panem, C., Payne-Wardenaar, S., Penttila, A., Pesciullesi, P., Piersimoni, A. M., Pinamonti, M., Pineau, F. -X., Plachy, E., Plum, G., Poggio, E., Pourbaix, D., Prsa, A., Pulone, L., Racero, E., Rainer, M., Raiteri, C. M., Ramos, P., Ramos-Lerate, M., Ratajczak, M., Fiorentin, P. Re, Regibo, S., Reyle, C., Ripepi, V., Riva, A., Rix, H. -W., Rixon, G., Robichon, N., Robin, C., Romero-Gomez, M., Rowell, N., Royer, F., Mieres, D. Ruz, Rybicki, K. A., Sadowski, G., Nunez, A. Saez, Selles, A. Sagrista, Sahlmann, J., Gimenez, V. Sanchez, Sanna, N., Santovena, R., Sarasso, M., Riera, C. Sarrate, Sciacca, E., Segovia, J. C., Segransan, D., Shahaf, S., Siebert, A., Siltala, L., Slezak, E., Smart, R. L., Snaith, O. N., Solano, E., Solitro, F., Souami, D., Souchay, J., Spina, L., Spitoni, E., Spoto, F., Squillante, L. A., Steele, I. A., Steidelmuller, H., Surdej, J., Szabados, L., Taris, F., Taylor, M. B., Tisanic, K., Tolomei, L., Torra, F., Elipe, G. Torralba, Trabucchi, M., Tsantaki, M., Ulla, A., Unger, N., Vanel, O., Vecchiato, A., Vicente, D., Voutsinas, S., Weiler, M., Wyrzykowski, L., Zhao, H., Zorec, J., Zwitter, T., Balaguer-Nunez, L., Leclerc, N., Morgenthaler, S., Robert, G., and Zucker, S.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

Context. Strongly lensed quasars are fundamental sources for cosmology. The Gaia space mission covers the entire sky with the unprecedented resolution of $0.18$" in the optical, making it an ideal instrument to search for gravitational lenses down to the limiting magnitude of 21. Nevertheless, the previous Gaia Data Releases are known to be incomplete for small angular separations such as those expected for most lenses. Aims. We present the Data Processing and Analysis Consortium GravLens pipeline, which was built to analyse all Gaia detections around quasars and to cluster them into sources, thus producing a catalogue of secondary sources around each quasar. We analysed the resulting catalogue to produce scores that indicate source configurations that are compatible with strongly lensed quasars. Methods. GravLens uses the DBSCAN unsupervised clustering algorithm to detect sources around quasars. The resulting catalogue of multiplets is then analysed with several methods to identify potential gravitational lenses. We developed and applied an outlier scoring method, a comparison between the average BP and RP spectra of the components, and we also used an extremely randomised tree algorithm. These methods produce scores to identify the most probable configurations and to establish a list of lens candidates. Results. We analysed the environment of 3 760 032 quasars. A total of 4 760 920 sources, including the quasars, were found within 6" of the quasar positions. This list is given in the Gaia archive. In 87\% of cases, the quasar remains a single source, and in 501 385 cases neighbouring sources were detected. We propose a list of 381 lensed candidates, of which we identified 49 as the most promising. Beyond these candidates, the associate tables in this Focused Product Release allow the entire community to explore the unique Gaia data for strong lensing studies further., Comment: 35 pages, 60 figures, accepted for publication by Astronomy and Astrophysics

Published
2023
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26. Gaia Focused Product Release: Radial velocity time series of long-period variables

Author

Gaia Collaboration, Trabucchi, M., Mowlavi, N., Lebzelter, T., Lecoeur-Taibi, I., Audard, M., Eyer, L., García-Lario, P., Gavras, P., Holl, B., de Fombelle, G. Jevardat, Nienartowicz, K., Rimoldini, L., Sartoretti, P., Blomme, R., Frémat, Y., Marchal, O., Damerdji, Y., Brown, A. G. A., Guerrier, A., Panuzzo, P., Katz, D., Seabroke, G. M., Benson, K., Haigron, R., Smith, M., Lobel, A., Vallenari, A., Prusti, T., de Bruijne, J. H. J., Arenou, F., Babusiaux, C., Barbier, A., Biermann, M., Creevey, O. L., Ducourant, C., Evans, D. W., Guerra, R., Hutton, A., Jordi, C., Klioner, S. A., Lammers, U., Lindegren, L., Luri, X., Mignard, F., Randich, S., Smiljanic, R., Tanga, P., Walton, N. A., Bailer-Jones, C. A. L., Bastian, U., Cropper, M., Drimmel, R., Lattanzi, M. G., Soubiran, C., van Leeuwen, F., Bakker, J., Castañeda, J., De Angeli, F., Fabricius, C., Fouesneau, M., Galluccio, L., Masana, E., Messineo, R., Nicolas, C., Pailler, F., Riclet, F., Roux, W., Sordo, R., Thévenin, F., Gracia-Abril, G., Portell, J., Teyssier, D., Altmann, M., Berthier, J., Burgess, P. W., Busonero, D., Busso, G., Cánovas, H., Carry, B., Cheek, N., Clementini, G., Davidson, M., de Teodoro, P., Delchambre, L., Dell'Oro, A., Garcia, E. Fraile, Garabato, D., Torres, N. Garralda, Hambly, N. C., Harrison, D. L., Hatzidimitriou, D., Hernández, J., Hodgkin, S. T., Jamal, S., Jordan, S., Krone-Martins, A., Lanzafame, A. C., Löffler, W., Lorca, A., Marrese, P. M., Moitinho, A., Muinonen, K., Campos, M. Nuñez, Oreshina-Slezak, I., Osborne, P., Pancino, E., Pauwels, T., Recio-Blanco, A., Riello, M., Robin, A. C., Roegiers, T., Sarro, L. M., Schultheis, M., Siopis, C., Sozzetti, A., Utrilla, E., van Leeuwen, M., Weingrill, K., Abbas, U., Ábrahám, P., Aramburu, A. Abreu, Aerts, C., Altavilla, G., Álvarez, M. A., Alves, J., Anders, F., Anderson, R. I., Antoja, T., Baines, D., Baker, S. G., Balog, Z., Barache, C., Barbato, D., Barros, M., Barstow, M. A., Bartolomé, S., Bashi, D., Bauchet, N., Baudeau, N., Becciani, U., Bedin, L. R., Bellas-Velidis, I., Bellazzini, M., Beordo, W., Berihuete, A., Bernet, M., Bertolotto, C., Bertone, S., Bianchi, L., Binnenfeld, A., Blazere, A., Boch, T., Bombrun, A., Bouquillon, S., Bragaglia, A., Braine, J., Bramante, L., Breedt, E., Bressan, A., Brouillet, N., Brugaletta, E., Bucciarelli, B., Butkevich, A. G., Buzzi, R., Caffau, E., Cancelliere, R., Cannizzo, S., Carballo, R., Carlucci, T., Carnerero, M. I., Carrasco, J. M., Carretero, J., Carton, S., Casamiquela, L., Castellani, M., Castro-Ginard, A., Cesare, V., Charlot, P., Chemin, L., Chiaramida, V., Chiavassa, A., Chornay, N., Collins, R., Contursi, G., Cooper, W. J., Cornez, T., Crosta, M., Crowley, C., Dafonte, C., David, M., de Laverny, P., De Luise, F., De March, R., De Ridder, J., de Souza, R., de Torres, A., del Peloso, E. F., Delbo, M., Delgado, A., Dharmawardena, T. E., Diakite, S., Diener, C., Distefano, E., Dolding, C., Dsilva, K., Durán, J., Enke, H., Esquej, P., Fabre, C., Fabrizio, M., Faigler, S., Fatović, M., Fedorets, G., Fernández-Hernández, J., Fernique, P., Figueras, F., Fournier, Y., Fouron, C., Gai, M., Galinier, M., Garcia-Gutierrez, A., García-Torres, M., Garofalo, A., Gerlach, E., Geyer, R., Giacobbe, P., Gilmore, G., Girona, S., Giuffrida, G., Gomel, R., Gomez, A., González-Núñez, J., González-Santamaría, I., Gosset, E., Granvik, M., Barrera, V. Gregori, Gutiérrez-Sánchez, R., Haywood, M., Helmer, A., Helmi, A., Henares, K., Hidalgo, S. L., Hilger, T., Hobbs, D., Hottier, C., Huckle, H. E., Jabłońska, M., Jansen, F., Jiménez-Arranz, Ó., Campillo, J. Juaristi, Khanna, S., Kordopatis, G., Kóspál, Á, Kostrzewa-Rutkowska, Z., Kun, M., Lambert, S., Lanza, A. F., Campion, J. -F. Le, Lebreton, Y., Leccia, S., Lecoutre, G., Liao, S., Liberato, L., Licata, E., Lindstrøm, H. E. P., Lister, T. A., Livanou, E., Loup, C., Mahy, L., Mann, R. G., Manteiga, M., Marchant, J. M., Marconi, M., Pina, D. Marín, Marinoni, S., Marshall, D. J., Lozano, J. Martín, Martín-Fleitas, J. M., Marton, G., Mary, N., Masip, A., Massari, D., Mastrobuono-Battisti, A., Mazeh, T., McMillan, P. J., Meichsner, J., Messina, S., Michalik, D., Millar, N. R., Mints, A., Molina, D., Molinaro, R., Molnár, L., Monari, G., Monguió, M., Montegriffo, P., Montero, A., Mor, R., Mora, A., Morbidelli, R., Morel, T., Morris, D., Munoz, D., Muraveva, T., Murphy, C. P., Musella, I., Nagy, Z., Nieto, S., Noval, L., Ogden, A., Ordenovic, C., Pagani, C., Pagano, I., Palaversa, L., Palicio, P. A., Pallas-Quintela, L., Panahi, A., Panem, C., Payne-Wardenaar, S., Pegoraro, L., Penttilä, A., Pesciullesi, P., Piersimoni, A. M., Pinamonti, M., Pineau, F. -X., Plachy, E., Plum, G., Poggio, E., Pourbaix, D., Prša, A., Pulone, L., Racero, E., Rainer, M., Raiteri, C. M., Ramos, P., Ramos-Lerate, M., Ratajczak, M., Fiorentin, P. Re, Regibo, S., Reylé, C., Ripepi, V., Riva, A., Rix, H. -W., Rixon, G., Robichon, N., Robin, C., Romero-Gómez, M., Rowell, N., Royer, F., Mieres, D. Ruz, Rybicki, K. A., Sadowski, G., Núñez, A. Sáez, Sellés, A. Sagristà, Sahlmann, J., Gimenez, V. Sanchez, Sanna, N., Santoveña, R., Sarasso, M., Riera, C. Sarrate, Sciacca, E., Segovia, J. C., Ségransan, D., Shahaf, S., Siebert, A., Siltala, L., Slezak, E., Smart, R. L., Snaith, O. N., Solano, E., Solitro, F., Souami, D., Souchay, J., Spina, L., Spitoni, E., Spoto, F., Squillante, L. A., Steele, I. A., Steidelmüller, H., Surdej, J., Szabados, L., Taris, F., Taylor, M. B., Teixeira, R., Tisanić, K., Tolomei, L., Torra, F., Elipe, G. Torralba, Tsantaki, M., Ulla, A., Unger, N., Vanel, O., Vecchiato, A., Vicente, D., Voutsinas, S., Weiler, M., Wyrzykowski, Ł., Zhao, H., Zorec, J., Zwitter, T., Balaguer-Núñez, L., Leclerc, N., Morgenthaler, S., Robert, G., and Zucker, S.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity (RV) in DR4, this Focused Product Release (FPR) provides RV time series for a selection of LPVs with high-quality observations. We describe the production and content of the Gaia catalog of LPV RV time series, and the methods used to compute variability parameters published in the Gaia FPR. Starting from the DR3 LPVs catalog, we applied filters to construct a sample of sources with high-quality RV measurements. We modeled their RV and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the RV period and at least one of the $G$, $G_{\rm BP}$, or $G_{\rm RP}$ photometric periods. The catalog includes RV time series and variability parameters for 9\,614 sources in the magnitude range $6\lesssim G/{\rm mag}\lesssim 14$, including a flagged top-quality subsample of 6\,093 stars whose RV periods are fully compatible with the values derived from the $G$, $G_{\rm BP}$, and $G_{\rm RP}$ photometric time series. The RV time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great most sources (88%) as genuine LPVs, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% consists of candidate ellipsoidal binaries. Quality checks against RVs available in the literature show excellent agreement. We provide illustrative examples and cautionary remarks. The publication of RV time series for almost 10\,000 LPVs constitutes, by far, the largest such database available to date in the literature. The availability of simultaneous photometric measurements gives a unique added value to the Gaia catalog (abridged), Comment: 36 pages, 38 figures

Published
2023

27. Reconstruction of total solar irradiance variability as simultaneously apparent from Solar Orbiter and Solar Dynamics Observatory

Author

Yeo, K. L., Krivova, N. A., Solanki, S. K., Hirzberger, J., Suárez, D. Orozco, Albert, K., Jorge, N. Albelo, Appourchaux, T., Alvarez-Herrero, A., Rodríguez, J. Blanco, Gandorfer, A., Gutierrez-Marques, P., Kahil, F., Kolleck, M., Iniesta, J. C. del Toro, Volkmer, R., Woch, J., Fiethe, B., Pérez-Grande, I., Kilders, E. Sanchis, Jiménez, M. Balaguer, Rubio, L. R. Bellot, Calchetti, D., Carmona, M., Feller, A., Fernandez-Rico, G., Fernández-Medina, A., Parejo, P. García, Blesa, J. L. Gasent, Gizon, L., Grauf, B., Heerlein, K., Korpi-Lagg, A., Maue, T., Meller, R., Vacas, A. Moreno, Müller, R., Nakai, E., Schmidt, W., Schou, J., Sinjan, J., Staub, J., Strecker, H., Torralbo, I., and Valori, G.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

Solar irradiance variability has been monitored almost exclusively from the Earth's perspective. {We present a method to combine the unprecedented observations of the photospheric magnetic field and continuum intensity from outside the Sun-Earth line, which is being recorded by the Polarimetric and Helioseismic Imager on board the Solar Orbiter mission (SO/PHI), with solar observations recorded from the Earth's perspective to examine the solar irradiance variability from both perspectives simultaneously.} Taking SO/PHI magnetograms and continuum intensity images from the cruise phase of the Solar Orbiter mission and concurrent observations from the Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) as input into the SATIRE-S model, we successfully reconstructed the total solar irradiance variability as apparent from both perspectives. In later stages of the SO mission, the orbital plane will tilt in such a way as to bring the spacecraft away from the ecliptic to heliographic latitudes of up to $33^{\circ}$. The current study sets the template for the reconstruction of solar irradiance variability as seen from outside the ecliptic from data that SO/PHI is expected to collect from such positions. {Such a reconstruction will be beneficial to factoring inclination into how the brightness variations of the Sun compare to those of other cool stars, whose rotation axes are randomly inclined.

Published
2023
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28. Coronal voids and their magnetic nature

Author

Nölke, J. D., Solanki, S. K., Hirzberger, J., Peter, H., Chitta, L. P., Kahil, F., Valori, G., Wiegelmann, T., Suárez, D. Orozco, Albert, K., Jorge, N. Albelo, Appourchaux, T., Alvarez-Herrero, A., Rodríguez, J. Blanco, Gandorfer, A., Germerott, D., Guerrero, L., Gutierrez-Marques, P., Kolleck, M., Iniesta, J. C. del Toro, Volkmer, R., Woch, J., Fiethe, B., Cama, J. M. Gómez, Pérez-Grande, I., Kilders, E. Sanchis, Jiménez, M. Balaguer, Rubio, L. R. Bellot, Calchetti, D., Carmona, M., Deutsch, W., Feller, A., Fernandez-Rico, G., Fernández-Medina, A., Parejo, P. García, Blesa, J. L. Gasent, Gizon, L., Grauf, B., Heerlein, K., Korpi-Lagg, A., Lange, T., Jiménez, A. López, Maue, T., Meller, R., Vacas, A. Moreno, Müller, R., Nakai, E., Schmidt, W., Schou, J., Schühle, U., Sinjan, J., Staub, J., Strecker, H., Torralbo, I., Berghmans, D., Kraaikamp, E., Rodriguez, L., Verbeeck, C., Zhukov, A. N., Auchere, F., Buchlin, E., Parenti, S., Janvier, M., Barczynski, K., Harra, L., Schwanitz, C., Cuadrado, R. Aznar, Mandal, S., Teriaca, L., Long, D., and Smith, P.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

Extreme ultraviolet (EUV) observations of the quiet solar atmosphere reveal extended regions of weak emission compared to the ambient quiescent corona. The magnetic nature of these coronal features is not well understood. We study the magnetic properties of the weakly emitting extended regions, which we name coronal voids. In particular, we aim to understand whether these voids result from a reduced heat input into the corona or if they are associated with mainly unipolar and possibly open magnetic fields, similar to coronal holes. We defined the coronal voids via an intensity threshold of 75% of the mean quiet-Sun (QS) EUV intensity observed by the high-resolution EUV channel (HRIEUV) of the Extreme Ultraviolet Imager on Solar Orbiter. The line-of-sight magnetograms of the same solar region recorded by the High Resolution Telescope of the Polarimetric and Helioseismic Imager allowed us to compare the photospheric magnetic field beneath the coronal voids with that in other parts of the QS. The coronal voids studied here range in size from a few granules to a few supergranules and on average exhibit a reduced intensity of 67% of the mean value of the entire field of view. The magnetic flux density in the photosphere below the voids is 76% (or more) lower than in the surrounding QS. Specifically, the coronal voids show much weaker or no network structures. The detected flux imbalances fall in the range of imbalances found in QS areas of the same size. Conclusions. We conclude that coronal voids form because of locally reduced heating of the corona due to reduced magnetic flux density in the photosphere. This makes them a distinct class of (dark) structure, different from coronal holes., Comment: 10 pages, 11 figures

Published
2023
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29. Intensity contrast of solar network and faculae close to the solar limb, observed from two vantage points

Author

Albert, K., Krivova, N. A., Hirzberger, J., Solanki, S. K., Vacas, A. Moreno, Suárez, D. Orozco, Jorge, N. Albelo, Appourchaux, T., Alvarez-Herrero, A., Rodríguez, J. Blanco, Gandorfer, A., Gutierrez-Marques, P., Kahil, F., Kolleck, M., Volkmer, R., Iniesta, J. C. del Toro, Woch, J., Fiethe, B., Pérez-Grande, I., Kilders, E. Sanchis, Jiménez, M. Balaguer, Rubio, L. R. Bellot, Calchetti, D., Carmona, M., Feller, A., Fernandez-Rico, G., Fernández-Medina, A., Parejo, P. García, Blesa, J. L. Gasent, Gizon, L., Grauf, B., Heerlein, K., Korpi-Lagg, A., Lange, T., Jiménez, A. López, Maue, T., Meller, R., Müller, R., Nakai, E., Schmidt, W., Schou, J., Sinjan, J., Staub, J., Strecker, H., Torralbo, I., and Valori, G.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

The brightness of faculae and network depends on the angle at which they are observed and the magnetic flux density. Close to the limb, assessment of this relationship has until now been hindered by the increasingly lower signal in magnetograms. This preliminary study aims at highlighting the potential of using simultaneous observations from different vantage points to better determine the properties of faculae close to the limb. We use data from the Solar Orbiter/Polarimetric and Helioseismic Imager (SO/PHI), and the Solar Dynamics Observatory/Helioseismic and Magnetic Imager (SDO/HMI), recorded at $\sim60^\circ$ angular separation of their lines of sight at the Sun. We use continuum intensity observed close to the limb by SO/PHI and complement it with the co-observed $B_{\rm LOS}$ from SDO/HMI, originating closer to disc centre (as seen by SDO/HMI), thus avoiding the degradation of the magnetic field signal near the limb. We derived the dependence of facular brightness in the continuum on disc position and magnetic flux density from the combined observations of SO/PHI and SDO/HMI. Compared with a single point of view, we were able to obtain contrast values reaching closer to the limb and to lower field strengths. We find the general dependence of the limb distance at which the contrast is maximum on the flux density to be at large in line with single viewpoint observations, in that the higher the flux density is, the closer the turning point lies to the limb. There is a tendency, however, for the maximum to be reached closer to the limb when determined from two vantage points. We note that due to the preliminary nature of this study, these results must be taken with caution. Our analysis shows that studies involving two viewpoints can significantly improve the detection of faculae near the solar limb and the determination of their brightness contrast relative to the quiet Sun.

Published
2023
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30. Potentiation of cortico-spinal output via targeted electrical stimulation of the motor thalamus

Author

Jonathan C. Ho, Erinn M. Grigsby, Arianna Damiani, Lucy Liang, Josep-Maria Balaguer, Sridula Kallakuri, Lilly W. Tang, Jessica Barrios-Martinez, Vahagn Karapetyan, Daryl Fields, Peter C. Gerszten, T. Kevin Hitchens, Theodora Constantine, Gregory M. Adams, Donald J. Crammond, Marco Capogrosso, Jorge A. Gonzalez-Martinez, and Elvira Pirondini

Subjects
Science
Abstract

Abstract Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for therapies aimed at improving volitional muscle activation. Here we hypothesize that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby immediately potentiating motor output. To test this hypothesis, we identify optimal thalamic targets and stimulation parameters that enhance upper-limb motor-evoked potentials and grip forces in anesthetized monkeys. This potentiation persists after white matter lesions. We replicate these results in humans during intra-operative testing. We then design a stimulation protocol that immediately improves strength and force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.

Published
2024
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31. High-speed data processing onboard sunrise chromospheric infrared spectropolarimeter for the SUNRISE III balloon telescope

Author

Kubo, Masahito, Katsukawa, Yukio, Expósito, David Hernández, Gómez, Antonio Sánchez, Jimenéz, María Balaguer, Suárez, David Orozco, Fernández, José M. Morales, del Moral, Beatriz Aparicio, Mantas, Antonio J. Moreno, Martínez, Eduardo Bailón, Iniesta, Jose Carlos del Toro, Kawabata, Yusuke, Noda, Carlos Quintero, Oba, Takayoshi, Ishikawa, Ryohtaroh T., and Shimizu, Toshifumi

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

The Sunrise Chromospheric Infrared spectroPolarimeter (SCIP) has been developed for the third flight of the SUNRISE balloon-borne stratospheric solar observatory. The aim of SCIP is to reveal the evolution of three-dimensional magnetic fields in the solar photosphere and chromosphere using spectropolarimetric measurements with a polarimetric precision of 0.03\% (1$\sigma$). Multiple lines in the 770 and 850 nm wavelength bands are simultaneously observed with two 2k$\times$2k CMOS cameras at a frame rate of 31.25 Hz. Stokes profiles are calculated onboard by accumulating the images modulated by a polarization modulation unit, and then compression processes are applied to the two-dimensional maps of the Stokes profiles. This onboard data processing effectively reduces the data rate. SCIP electronics can handle large data formats at high speed. Before the implementation into the flight SCIP electronics, a performance verification of the onboard data processing was performed with synthetic SCIP data that were produced with a numerical simulation modeling the solar atmospheres. Finally, we verified that the high-speed onboard data processing was realized on ground with the flight hardware by using images illuminated by natural sunlight or an LED., Comment: 31 pages, 11 figures, accepted for publication in JATIS

Published
2023

32. Potentiation of cortico-spinal output via targeted electrical stimulation of the motor thalamus

Author

Ho, Jonathan C., Grigsby, Erinn M., Damiani, Arianna, Liang, Lucy, Balaguer, Josep-Maria, Kallakuri, Sridula, Tang, Lilly W., Barrios-Martinez, Jessica, Karapetyan, Vahagn, Fields, Daryl, Gerszten, Peter C., Hitchens, T. Kevin, Constantine, Theodora, Adams, Gregory M., Crammond, Donald J., Capogrosso, Marco, Gonzalez-Martinez, Jorge A., and Pirondini, Elvira

Published
2024
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42. Discovering Causal Relations and Equations from Data

Author

Camps-Valls, Gustau, Gerhardus, Andreas, Ninad, Urmi, Varando, Gherardo, Martius, Georg, Balaguer-Ballester, Emili, Vinuesa, Ricardo, Diaz, Emiliano, Zanna, Laure, and Runge, Jakob

Subjects
Physics - Data Analysis, Statistics and Probability, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Statistics - Methodology
Abstract

Physics is a field of science that has traditionally used the scientific method to answer questions about why natural phenomena occur and to make testable models that explain the phenomena. Discovering equations, laws and principles that are invariant, robust and causal explanations of the world has been fundamental in physical sciences throughout the centuries. Discoveries emerge from observing the world and, when possible, performing interventional studies in the system under study. With the advent of big data and the use of data-driven methods, causal and equation discovery fields have grown and made progress in computer science, physics, statistics, philosophy, and many applied fields. All these domains are intertwined and can be used to discover causal relations, physical laws, and equations from observational data. This paper reviews the concepts, methods, and relevant works on causal and equation discovery in the broad field of Physics and outlines the most important challenges and promising future lines of research. We also provide a taxonomy for observational causal and equation discovery, point out connections, and showcase a complete set of case studies in Earth and climate sciences, fluid dynamics and mechanics, and the neurosciences. This review demonstrates that discovering fundamental laws and causal relations by observing natural phenomena is being revolutionised with the efficient exploitation of observational data, modern machine learning algorithms and the interaction with domain knowledge. Exciting times are ahead with many challenges and opportunities to improve our understanding of complex systems., Comment: 137 pages

Published
2023

43. Direct assessment of SDO/HMI helioseismology of active regions on the Sun's far side using SO/PHI magnetograms

Author

Yang, D., Gizon, L., Barucq, H., Hirzberger, J., Suárez, D. Orozco, Albert, K., Jorge, N. Albelo, Appourchaux, T., Alvarez-Herrero, A., Rodríguez, J. Blanco, Gandorfer, A., Germerott, D., Guerrero, L., Gutierrez-Marques, P., Kahil, F., Kolleck, M., Solanki, S. K., Iniesta, J. C. del Toro, Volkmer, R., Woch, J., Pérez-Grande, I., Kilders, E. Sanchis, Jiménez, M. Balaguer, Rubio, L. R. Bellot, Calchetti, D., Carmona, M., Deutsch, W., Feller, A., Fernandez-Rico, G., Fernández-Medina, A., Parejo, P. García, Blesa, J. L. Gasent, Grauf, B., Heerlein, K., Korpi-Lagg, A., Lange, T., Jiménez, A. López, Maue, T., Meller, R., Vacas, A. Moreno, Müller, R., Nakai, E., Schmidt, W., Schou, J., Schühle, U., Sinjan, J., Staub, J., Strecker, H., Torralbo, I., and Valori, G.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

Earth-side observations of solar p modes can be used to image and monitor magnetic activity on the Sun's far side. Here we use magnetograms of the far side obtained by the Polarimetric and Helioseismic Imager (PHI) onboard Solar Orbiter (SO) to directly assess -- for the first time -- the validity of far-side helioseismic holography. We wish to co-locate the positions of active regions in helioseismic images and magnetograms, and to calibrate the helioseismic measurements in terms of magnetic field strength. We identify three magnetograms on 18 November 2020, 3 October 2021, and 3 February 2022 displaying a total of six active regions on the far side. The first two dates are from SO's cruise phase, the third from the beginning of the nominal operation phase. We compute contemporaneous seismic phase maps for these three dates using helioseismic holography applied to time series of Dopplergrams from the Helioseismic and Magnetic Imager (HMI) on the Solar Dynamics Observatory (SDO). Among the six active regions seen in SO/PHI magnetograms, five active regions are identified on the seismic maps at almost the same positions as on the magnetograms. One region is too weak to be detected above the seismic noise. To calibrate the seismic maps, we fit a linear relationship between the seismic phase shifts and the unsigned line-of-sight magnetic field averaged over the active region areas extracted from the SO/PHI magnetograms. SO/PHI provides the strongest evidence so far that helioseismic imaging provides reliable information about active regions on the far side, including their positions, areas, and mean unsigned magnetic field., Comment: 10 pages, 9 figures

Published
2023
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44. Spectropolarimetric investigation of magnetohydrodynamic wave modes in the photosphere: First results from PHI on board Solar Orbiter

Author

Calchetti, D., Stangalini, M., Jafarzadeh, S., Valori, G., Albert, K., Jorge, N. Albelo, Alvarez-Herrero, A., Appourchaux, T., Jiménez, M. Balaguer, Rubio, L. R. Bellot, Rodríguez, J. Blanco, Feller, A., Gandorfer, A., Germerott, D., Gizon, L., Guerrero, L., Gutierrez-Marques, P., Hirzberger, J., Kahil, F., Kolleck, M., Korpi-Lagg, A., Vacas, A. Moreno, Suárez, D. Orozco, Pérez-Grande, I., Kilders, E. Sanchis, Schou, J., Schühle, U., Sinjan, J., Solanki, S. K., Staub, J., Strecker, H., Iniesta, J. C. del Toro, Volkmer, R., and Woch, J.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

In November 2021, Solar Orbiter started its nominal mission phase. The remote-sensing instruments on board the spacecraft acquired scientific data during three observing windows surrounding the perihelion of the first orbit of this phase. The aim of the analysis is the detection of magnetohydrodynamic (MHD) wave modes in an active region by exploiting the capabilities of spectropolarimetric measurements. The High Resolution Telescope (HRT) of the Polarimetric and Helioseismic Imager (SO/PHI) on board the Solar Orbiter acquired a high-cadence data set of an active region. This is studied in the paper. B-$\omega$ and phase-difference analyses are applied on line-of-sight velocity and circular polarization maps and other averaged quantities. We find that several MHD modes at different frequencies are excited in all analysed structures. The leading sunspot shows a linear dependence of the phase lag on the angle between the magnetic field and the line of sight of the observer in its penumbra. The magnetic pore exhibits global resonances at several frequencies, which are also excited by different wave modes. The SO/PHI measurements clearly confirm the presence of magnetic and velocity oscillations that are compatible with one or more MHD wave modes in pores and a sunspot. Improvements in modelling are still necessary to interpret the relation between the fluctuations of different diagnostics.

Published
2023
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45. The ratio of horizontal to vertical displacement in solar oscillations estimated from combined SO/PHI and SDO/HMI observations

Author

Schou, J., Hirzberger, J., Suárez, D. Orozco, Albert, K., Jorge, N. Albelo, Appourchaux, T., Alvarez-Herrero, A., Rodríguez, J. Blanco, Gandorfer, A., Germerott, D., Guerrero, L., Gutierrez-Marques, P., Kahil, F., Kolleck, M., Solanki, S. K., Iniesta, J. C. del Toro, Volkmer, R., Woch, J., Fiethe, B., Pérez-Grande, I., Kilders, E. Sanchis, Jiménez, M. Balaguer, Rubio, L. R. Bellot, Calchetti, D., Carmona, M., Deutsch, W., Feller, A., Fernandez-Rico, G., Fernández-Medina, A., Parejo, P. García, Blesa, J. L. Gasent, Gizon, L., Grauf, B., Heerlein, K., Korpi-Lagg, A., Jiménez, A. López, Maue, T., Meller, R., Vacas, A. Moreno, Müller, R., Nakai, E., Schmidt, W., Sinjan, J., Staub, J., Strecker, H., Torralbo, I., and Valori, G.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

In order to make accurate inferences about the solar interior using helioseismology, it is essential to understand all the relevant physical effects on the observations. One effect to understand is the (complex-valued) ratio of the horizontal to vertical displacement of the p- and f-modes at the height at which they are observed. Unfortunately, it is impossible to measure this ratio directly from a single vantage point, and it has been difficult to disentangle observationally from other effects. In this paper we attempt to measure the ratio directly using 7.5 hours of simultaneous observations from the Polarimetric and Helioseismic Imager on board Solar Orbiter and the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory. While image geometry problems make it difficult to determine the exact ratio, it appears to agree well with that expected from adiabatic oscillations in a standard solar model. On the other hand it does not agree with a commonly used approximation, indicating that this approximation should not be used in helioseismic analyses. In addition, the ratio appears to be real-valued., Comment: Accepted for publication in Astronomy & Astrophysics. 8 pages, 8 figures

Published
2023
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46. Magnetic fields inferred by Solar Orbiter: A comparison between SO/PHI-HRT and SDO/HMI

Author

Sinjan, J., Calchetti, D., Hirzberger, J., Kahil, F., Valori, G., Solanki, S. K., Albert, K., Jorge, N. Albelo, Alvarez-Herrero, A., Appourchaux, T., Rubio, L. R. Bellot, Rodríguez, J. Blanco, Feller, A., Gandorfer, A., Germerott, D., Gizon, L., Cama, J. M. Gómez, Guerrero, L., Gutierrez-Marques, P., Kolleck, M., Korpi-Lagg, A., Michalik, H., Vacas, A. Moreno, Suárez, D. Orozco, Pérez-Grande, I., Kilders, E. Sanchis, Jiménez, M. Balaguer, Schou, J., Schühle, U., Staub, J., Strecker, H., Iniesta, J. C. del Toro, Volkmer, R., and Woch, J.

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Physics - Space Physics
Abstract

The High Resolution Telescope (HRT) of the Polarimetric and Helioseismic Imager on board the Solar Orbiter spacecraft (SO/PHI) and the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) both infer the photospheric magnetic field from polarised light images. SO/PHI is the first magnetograph to move out of the Sun--Earth line and will provide unprecedented access to the Sun's poles. This provides excellent opportunities for new research wherein the magnetic field maps from both instruments are used simultaneously. We aim to compare the magnetic field maps from these two instruments and discuss any possible differences between them. We used data from both instruments obtained during Solar Orbiter's inferior conjunction on 7 March 2022. The HRT data were additionally treated for geometric distortion and degraded to the same resolution as HMI. The HMI data were re-projected to correct for the $3^{\circ}$ separation between the two observatories. SO/PHI-HRT and HMI produce remarkably similar line-of-sight magnetograms, with a slope coefficient of $0.97$, an offset below $1$ G, and a Pearson correlation coefficient of $0.97$. However, SO/PHI-HRT infers weaker line-of-sight fields for the strongest fields. As for the vector magnetic field, SO/PHI-HRT was compared to both the $720$-second and $90$-second HMI vector magnetic field: SO/PHI-HRT has a closer alignment with the $90$-second HMI vector. In the weak signal regime ($< 600$ G), SO/PHI-HRT measures stronger and more horizontal fields than HMI, very likely due to the greater noise in the SO/PHI-HRT data. In the strong field regime ($\gtrsim 600$ G), HRT infers lower field strengths but with similar inclinations (a slope of $0.92$) and azimuths (a slope of $1.02$). The slope values are from the comparison with the HMI $90$-second vector., Comment: 10 pages, 5 figures, accepted for publication in A&A; manuscript is a part of Astronomy & Astrophysics special issue: Solar Orbiter First Results (Nominal Mission Phase)

Published
2023
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47. Open Strings in IIB Orientifold Reductions

Author

Balaguer, Juan R., Dibitetto, Giuseppe, Fernandez-Melgarejo, Jose J., and Ruiperez, Alejandro

Subjects
High Energy Physics - Theory
Abstract

We consider type IIB compactifications on a general 4D group manifold with different types of possible spacetime filling O-planes and the corresponding D-branes parallel to them. Once fluxes allowed by the associated orientifold projection are included, a 6D $\mathcal{N}=(1,1)$ gauged supergravity is obtained. In this paper we show how the consistent coupling to dynamical open strings living on the spacetime filling D-branes may be captured by the inclusion of extra vector multiplets and extra embedding tensor deformations on the gauged supergravity side. As a result, the quadratic constraints on the embedding tensor consistently reproduce the source corrected 10D Bianchi identities. Furthermore, the field strength modifications induced by the open string sector could potentially be understood as U-dual versions of the Green-Schwarz terms. Finally, the entire scalar potential of the theory exactly matches the one obtained from reduction of the bulk action plus the source contributions., Comment: 45 pages, 1 figure

Published
2023
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48. Plasma lipidomics in early APP/PS1 female mouse model and its relationship with brain: Is it affected by the estrous cycle?

Author

Laura Ferré-González, Ángel Balaguer, Marta Roca, Artemis Ftara, Ana Lloret, and Consuelo Cháfer-Pericás

Subjects
Plasma, Brain, Lipid, Early, Alzheimer, Mouse model, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Background Alzheimer's disease (AD) is the most prevalent dementia, showing higher incidence in women. Besides, lipids play an essential role in brain, and they could be dysregulated in neurodegeneration. Specifically, impaired plasma lipid levels could predict early AD diagnosis. This work aims to identify the main plasma lipids altered in early AD female mouse model and evaluate their relationship with brain lipidome. Also, the possible involvement of the estrous cycle in lipid metabolism has been evaluated. Methods Plasma samples of wild-type (n = 10) and APP/PS1 (n = 10) female mice of 5 months of age were collected, processed, and analysed using a lipidomic mass spectrometry-based method. A statistical analysis involving univariate and multivariate approaches was performed to identify significant lipid differences related to AD between groups. Also, cytology tests were conducted to confirm estrous cycle phases. Results Three hundred thirty lipids were detected in plasma, 18 of them showed significant differences between groups; specifically, some triacylglycerols, cholesteryl esters, lysophosphatidylcholines, phosphatidylcholines, and ether-linked phosphatidylcholines, increased in early AD; while other phosphatidylcholines, phosphatidylethanolamines, ceramides, and ether-linked phosphatidylethanolamines decreased in early AD. A multivariate approach was developed from some lipid variables, showing high diagnostic indexes (70% sensitivity, 90% specificity, 80% accuracy). From brain and plasma lipidome, some significant correlations were observed, mainly in the glycerophospholipid family. Also, some differences were found in both plasma and brain lipids, according to the estrous cycle phase. Conclusions Therefore, lipid alterations can be identified in plasma at early AD stages in mice females, with a relationship with brain lipid metabolism for most of the lipid subfamilies, suggesting some lipids as potential AD biomarkers. In addition, the estrous cycle monitoring could be relevant in female studies.

Published
2024
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49. Endoscopic management of patients with familial adenomatous polyposis after prophylactic colectomy or restorative proctocolectomy – systematic review of the literature

Author

Gavric Aleksandar, Sanchez Liseth Rivero, Brunori Angelo, Bravo Raquel, Balaguer Francesc, and Pellisé Maria

Subjects
familial adenomatous polyposis, ileorectal anastomosis, ileal pouch-anal anastomosis, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Patients with familial adenomatous polyposis (FAP) develop early colorectal adenomas and if left untreated, progression to cancer is an inevitable event. Prophylactic surgery does not prevent further development of cancer in the rectal remnant, rectal cuff in patients with ileal pouch anal anastomosis (IPAA) and even on the ileal mucosa of the pouch body. The aim of this review is to assess long-term rates of cancer and adenoma development in patients with FAP after prophylactic surgery and to summarise current recommendations for endoscopic management and surveillance of these patients.

Published
2024
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50. Motor skill learning modulates striatal extracellular vesicles’ content in a mouse model of Huntington’s disease

Author

Júlia Solana-Balaguer, Pol Garcia-Segura, Genís Campoy-Campos, Almudena Chicote-González, Joaquín Fernández-Irigoyen, Enrique Santamaría, Esther Pérez-Navarro, Mercè Masana, Jordi Alberch, and Cristina Malagelada

Subjects
Extracellular vesicles, Motor learning, Huntington’s disease, Cortico-striatal activation, Striatum, Proteomics, Medicine, Cytology, QH573-671
Abstract

Abstract Huntington’s disease (HD) is a neurological disorder caused by a CAG expansion in the Huntingtin gene (HTT). HD pathology mostly affects striatal medium-sized spiny neurons and results in an altered cortico-striatal function. Recent studies report that motor skill learning, and cortico-striatal stimulation attenuate the neuropathology in HD, resulting in an amelioration of some motor and cognitive functions. During physical training, extracellular vesicles (EVs) are released in many tissues, including the brain, as a potential means for inter-tissue communication. To investigate how motor skill learning, involving acute physical training, modulates EVs crosstalk between cells in the striatum, we trained wild-type (WT) and R6/1 mice, the latter with motor and cognitive deficits, on the accelerating rotarod test, and we isolated their striatal EVs. EVs from R6/1 mice presented alterations in the small exosome population when compared to WT. Proteomic analyses revealed that striatal R6/1 EVs recapitulated signaling and energy deficiencies present in HD. Motor skill learning in R6/1 mice restored the amount of EVs and their protein content in comparison to naïve R6/1 mice. Furthermore, motor skill learning modulated crucial pathways in metabolism and neurodegeneration. All these data provide new insights into the pathogenesis of HD and put striatal EVs in the spotlight to understand the signaling and metabolic alterations in neurodegenerative diseases. Moreover, our results suggest that motor learning is a crucial modulator of cell-to-cell communication in the striatum.

Published
2024
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