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1. Sensitivity of $m$-ary functions and low degree partitions of Hamming graphs

Author: Asensio, Sara, García-Marco, Ignacio, and Knauer, Kolja
Subjects: Mathematics - Combinatorics, Computer Science - Discrete Mathematics
Abstract: The study of complexity measures of Boolean functions led Nisan and Szegedy to state the sensitivity conjecture in 1994, claiming a polynomial relation between degree and sensitivity. This problem remained unsolved until 2019, when Huang proved the conjecture via an equivalent graph theoretical reformulation due to Gotsman and Linial. We study $m$-ary functions, i.e., functions $f: T^n \rightarrow T$ where $T\subseteq \mathbb{C}$ is a finite alphabet of cardinality $|T| = m $ and extend the notions of degree $\mathrm{deg}(f)$ and sensitivity $s(f)$ to $m$-ary functions and show $s(f)\in O(\mathrm{deg}(f)^2)$. This generalizes results of Nisan and Szegedy. Conversely, we introduce the $m$-ary sensitivity conjecture, claiming a polynomial upper bound for $\mathrm{deg}(f)$ in terms of $s(f)$. Analogously to results of Gotsman and Linial, we provide a formulation of the conjecture in terms of imbalanced partitions of Hamming graphs into low degree subgraphs. Combining this with ideas of Chung, F\"uredi, Graham and Seymour, we show that for any prime $p$ the bound in the $p$-ary sensitivity conjecture has to be at least quadratic: there exist $p$-ary functions $f$ of arbitrarily large degree and $\mathrm{deg}(f)\in \Omega(s(f)^2)$., Comment: 17 pages, 7 figures
Published: 2024

2. Exploring spectropolarimetric inversions using neural fields. Solar chromospheric magnetic field under the weak-field approximation

Author: Baso, C. J. Díaz, Ramos, A. Asensio, Rodríguez, J. de la Cruz, Santos, J. M. da Silva, and van der Voort, L. Rouppe
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: Full-Stokes polarimetric datasets, originating from slit-spectrograph or narrow-band filtergrams, are routinely acquired nowadays. The data rate is increasing with the advent of bi-dimensional spectropolarimeters and observing techniques that allow long-time sequences of high-quality observations. There is a clear need to go beyond the traditional pixel-by-pixel strategy in spectropolarimetric inversions by exploiting the spatiotemporal coherence of the inferred physical quantities. We explore the potential of neural networks as a continuous representation of the physical quantities over time and space (also known as neural fields), for spectropolarimetric inversions. We have implemented and tested a neural field to perform the inference of the magnetic field vector (approach also known as physics-informed neural networks) under the weak-field approximation (WFA). By using a neural field to describe the magnetic field vector, we can regularize the solution in the spatial and temporal domain by assuming that the physical quantities are continuous functions of the coordinates. We investigated the results in synthetic and real observations of the Ca II 8542 A line. We also explored the impact of other explicit regularizations, such as using the information of an extrapolated magnetic field, or the orientation of the chromospheric fibrils. Compared to the traditional pixel-by-pixel inversion, the neural field approach improves the fidelity of the reconstruction of the magnetic field vector, especially the transverse component. This implicit regularization is a way of increasing the effective signal-to-noise of the observations. Although it is slower than the pixel-wise WFA estimation, this approach shows a promising potential for depth-stratified inversions, by reducing the number of free parameters and inducing spatio-temporal constraints in the solution., Comment: 12 pages, 7 figures, Appendix, Submitted to A&A
Published: 2024

3. Properties of sunspot light bridges on a geometric height scale

Author: Pozuelo, S. Esteban, Ramos, A. Asensio, Baso, C. J. Díaz, and Cobo, B. Ruiz
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Investigating light bridges (LBs) helps us comprehend key aspects of sunspots. However, few studies have analyzed the properties of LBs in terms of the geometric height, which is a more realistic perspective given the corrugation of the solar atmosphere. We aim to shed light on LBs by studying the variation in their physical properties with geometric height. We used the SICON code to infer the physical quantities in terms of the optical depth and the Wilson depression values of three LBs hosted by a sunspot observed with Hinode/SP in the Fe I 630 nm pair lines. We also used SIR inversions to cross-check the height variation of the field inclination in the LBs. In both output sets, we performed linear interpolation to convert the physical parameters from optical depth into a geometric height scale in each pixel. We classified each LB as filamentary, grainy, or umbral. They appear as ridges that reach different maximum heights, with the umbral LB being the deepest. While the filamentary LB hosts a plasma inflow from the penumbra, the results for the grainy LB are compatible with an injection of hot plasma through convective cells of reduced field strength. Only a few positions reveal hints suggesting a cusp-like magnetic canopy. Moreover, strong gradients in the magnetic field strength and inclination usually exhibit enhanced electric currents, with the filamentary LB having remarkably strong currents that appear to be related to chromospheric events. The height stratification in filamentary and grainy LBs differ, indicating diverse mechanisms at work. Our results are in general incompatible with a magnetic canopy scenario, and further analysis is needed to confirm whether it exists along the entire LB or only at specific locations. Furthermore, this work assesses the usefulness of SICON when determining the height stratification of solar structures., Comment: 13 pages, 12 figures. Accepted for publication in A&A. Abstract has been abridged
Published: 2024

4. Delivery of DART Impact Ejecta to Mars and Earth: Opportunity for Meteor Observations

Author: Peña-Asensio, Eloy, Küppers, Michael, Trigo-Rodríguez, Josep M., and Rimola, Albert
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: NASA's DART and ESA's Hera missions offer a unique opportunity to investigate the delivery of impact ejecta to other celestial bodies. We performed ejecta dynamical simulations using 3 million particles categorized into three size populations (10 cm, 0.5 cm, and 30 $\mu$m) and constrained by early post-impact LICIACube observations. The main simulation explored ejecta velocities ranging from 1 to 1,000 m/s, while a secondary simulation focused on faster ejecta with velocities from 1 to 2 km/s. We identified DART ejecta orbits compatible with the delivery of meteor-producing particles to Mars and Earth. Our results indicate the possibility of ejecta reaching the Mars Hill sphere in 13 years for launch velocities around 450 m/s, which is within the observed range. Some ejecta particles launched at 770 m/s could reach Mars's vicinity in 7 years. Faster ejecta resulted in a higher flux delivery towards Mars and particles impacting the Earth Hill sphere above 1.5 km/s. The delivery process is slightly sensitive to the initial observed cone range and driven by synodic periods. The launch locations for material delivery to Mars were predominantly northern the DART impact site, while they displayed a southwestern tendency for the Earth-Moon system. Larger particles exhibit a marginally greater likelihood of reaching Mars, while smaller particles favor delivery to Earth-Moon, although this effect is insignificant. To support observational campaigns for DART-created meteors, we provide comprehensive information on the encounter characteristics (orbital elements and radiants) and quantify the orbital decoherence degree of the released meteoroids., Comment: Accepted in Planetary Science Journal
Published: 2024
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5. On the compactness of the Weyl operator in $\mathcal{S}_{\omega}$

Author: Asensio, Vicente, Boiti, Chiara, Jornet, David, and Oliaro, Alessandro
Subjects: Mathematics - Functional Analysis, Primary 47B07, 42B35, Secondary 42C20, 46F12
Abstract: We characterize, using time-frequency analysis, the continuity and compactness of the Weyl operator in global classes of ultradifferentiable functions $\mathcal{S}_\omega$, for weight functions $\omega$ in the sense of Braun, Meise and Taylor. As a consequence, we give results about the compactness of the localization operator in $\mathcal{S}_\omega$, in relation with the spaces of $\omega$-multipliers and $\omega$-convolutors of $\mathcal{S}_\omega$. Moreover, we provide several examples that complement our investigation.
Published: 2024

6. Evaluating potential landing sites for the Artemis III mission using a multi-criteria decision making approach

Author: Peña-Asensio, Eloy, Neira-Acosta, Álvaro-Steve, and Sánchez-Lozano, Juan Miguel
Subjects: Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Geophysics
Abstract: The selection of a landing site within the Artemis Exploration Zone (AEZ) involves multiple factors and presents a complex problem. This study evaluates potential landing sites for the Artemis III mission using a combination of Geographic Information Systems (GIS) and Multi-Criteria Decision Making (MCDM) methodologies, specifically the TOPSIS algorithm. By integrating topographic, illumination, and mineralogy data of the Moon, we assess 1247 locations that meet the Human Landing System (HLS) requirements within 13 candidate regions and Site 004 near the lunar south pole. Criteria considered include surface visibility, HLS-astronaut line of sight, Permanently Shadowed Regions (PSRs), sunlight exposure, direct communication with Earth, geological units, and mafic mineral abundance. Site DM2 (Nobile Rim 2), particularly the point at latitude 84{\deg}12'5.61" S (-84.20156{\deg}) and longitude 60{\deg}41'59.61" E (60.69989{\deg}), is the optimal location for landing. Sensitivity analysis confirms the robustness of our approach, validating the suitability of the best location despite the MCDM method employed and variations in criteria weightings to prioritize illumination and PSRs. This research demonstrates the applicability of GIS-MCDM techniques for lunar exploration and the potential benefits they can bring to the Artemis program., Comment: Accepted for publication in Acta Astronautica
Published: 2024

7. High contrast at short separation with VLTI/GRAVITY: Bringing Gaia companions to light

Author: Pourré, N., Winterhalder, T. O., Bouquin, J. -B. Le, Lacour, S., Bidot, A., Nowak, M., Maire, A. -L., Mouillet, D., Babusiaux, C., Woillez, J., Abuter, R., Amorim, A., Asensio-Torres, R., Balmer, W. O., Benisty, M., Berger, J. -P., Beust, H., Blunt, S., Boccaletti, A., Bonnefoy, M., Bonnet, H., Bordoni, M. S., Bourdarot, G., Brandner, W., Cantalloube, F., Caselli, P., Charnay, B., Chauvin, G., Chavez, A., Choquet, E., Christiaens, V., Clénet, Y., Foresto, V. Coudé du, Cridland, A., Davies, R., Defrère, D., Dembet, R., Dexter, J., Drescher, A., Duvert, G., Eckart, A., Eisenhauer, F., Schreiber, N. M. Föster, Garcia, P., Lopez, R. Garcia, Gendron, E., Genzel, R., Gillessen, S., Girard, J. H., Gonte, F., Grant, S., Haubois, X., Heißel, G., Henning, Th., Hinkley, S., Hippler, S., Hönig, S. F., Houllé, M., Hubert, Z., Jocou, L., Kammerer, J., Kenworthy, M., Keppler, M., Kervella, P., Kreidberg, L., Kurtovic, N. T., Lagrange, A. -M., Lapeyrère, V., Lutz, D., Mang, F., Marleau, G. -D., Mérand, A., Millour, F., Mollière, P., Monnier, J. D., Mordasini, C., Nasedkin, E., Oberti, S., Ott, T., Otten, G. P. L., Paladini, C., Paumard, T., Perraut, K., Perrin, G., Pfuhl, O., Pueyo, L., Ribeiro, D. C., Rickman, E., Rustamkulov, Z., Shangguan, J., Shimizu, T., Sing, D., Soulez, F., Stadler, J., Stolker, T., Straub, O., Straubmeier, C., Sturm, E., Sykes, C., Tacconi, L. J., van Dishoeck, E. F., Vigan, A., Vincent, F., von Fellenberg, S. D., Wang, J., Widmann, F., Yazici, S., Collaboration, the GRAVITY, Abad, J. A., Carpentier, E. Aller, Alonso, J., Andolfato, L., Barriga, P., Beuzit, J. -L., Bourget, P., Brast, R., Caniguante, L., Cottalorda, E., Darré, P., Delabre, B., Delboulbé, A., Delplancke-Ströbele, F., Donaldson, R., Dorn, R., Dupuy, C., Egner, S., Fischer, G., Frank, C., Fuenteseca, E., Gitton, P., Guerlet, T., Guieu, S., Gutierrez, P., Haguenauer, P., Haimerl, A., Heritier, C. T., Huber, S., Hubin, N., Jolley, P., Kirchbauer, J. -P., Kolb, J., Kosmalski, J., Krempl, P., Louarn, M. Le, Lilley, P., Lopez, B., Magnard, Y., Mclay, S., Meilland, A., Meister, A., Moulin, T., Pasquini, L., Paufique, J., Percheron, I., Pettazzi, L., Phan, D., Pirani, W., Quentin, J., Rakich, A., Ridings, R., Reyes, J., Rochat, S., Schmid, C., Schuhler, N., Shchekaturov, P., Seidel, M., Soenke, C., Stadler, E., Stephan, C., Suárez, M., Todorovic, M., Valdes, G., Verinaud, C., Zins, G., Zúñiga-Fernández, S., and Collaboration, the NAOMI
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: Since 2019, GRAVITY has provided direct observations of giant planets and brown dwarfs at separations of down to 95 mas from the host star. Some of these observations have provided the first direct confirmation of companions previously detected by indirect techniques (astrometry and radial velocities). We want to improve the observing strategy and data reduction in order to lower the inner working angle of GRAVITY in dual-field on-axis mode. We also want to determine the current limitations of the instrument when observing faint companions with separations in the 30-150 mas range. To improve the inner working angle, we propose a fiber off-pointing strategy during the observations to maximize the ratio of companion-light-to-star-light coupling in the science fiber. We also tested a lower-order model for speckles to decouple the companion light from the star light. We then evaluated the detection limits of GRAVITY using planet injection and retrieval in representative archival data. We compare our results to theoretical expectations. We validate our observing and data-reduction strategy with on-sky observations; first in the context of brown dwarf follow-up on the auxiliary telescopes with HD 984 B, and second with the first confirmation of a substellar candidate around the star Gaia DR3 2728129004119806464. With synthetic companion injection, we demonstrate that the instrument can detect companions down to a contrast of $8\times 10^{-4}$ ($\Delta \mathrm{K}= 7.7$ mag) at a separation of 35 mas, and a contrast of $3\times 10^{-5}$ ($\Delta \mathrm{K}= 11$ mag) at 100 mas from a bright primary (K<6.5), for 30 min exposure time. With its inner working angle and astrometric precision, GRAVITY has a unique reach in direct observation parameter space. This study demonstrates the promising synergies between GRAVITY and Gaia for the confirmation and characterization of substellar companions., Comment: 16 pages, 14 figures. Submitted to A&A
Published: 2024

8. A fast neural emulator for interstellar chemistry

Author: Ramos, A. Asensio, Plaza, C. Westendorp, Navarro-Almaida, D., Rivière-Marichalar, P., Wakelam, V., and Fuente, A.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: Astrochemical models are important tools to interpret observations of molecular and atomic species in different environments. However, these models are time-consuming, precluding a thorough exploration of the parameter space, leading to uncertainties and biased results. Using neural networks to simulate the behavior of astrochemical models is a way to circumvent this problem, providing fast calculations that are based on real astrochemical models. In this paper, we present a fast neural emulator of the astrochemical code Nautilus based on conditional neural fields. The resulting model produces the abundance of 192 species for arbitrary times between 1 and 10$^7$ years. Uncertainties well below 0.2 dex are found for all species, while the computing time is of the order of 10$^4$ smaller than Nautilus. This will open up the possibility of performing much more complex forward models to better understand the physical properties of the interstellar medium. As an example of the power of these models, we ran a feature importance analysis on the electron abundance predicted by Nautilus. We found that the electron density is coupled to the initial sulphur abundance in a low density gas. Increasing the initial sulphur abundance from a depleted scenario to the cosmic abundance leads to an enhancement of an order of magnitude of the electron density. This enhancement can potentially influence the dynamics of the gas in star formation sites., Comment: 12 pages, 8 figures, accepted for publication in MNRAS
Published: 2024

9. Time-Series Foundation Models for Forecasting Soil Moisture Levels in Smart Agriculture

Author: Deforce, Boje, Baesens, Bart, and Asensio, Estefanía Serral
Subjects: Computer Science - Machine Learning
Abstract: The recent surge in foundation models for natural language processing and computer vision has fueled innovation across various domains. Inspired by this progress, we explore the potential of foundation models for time-series forecasting in smart agriculture, a field often plagued by limited data availability. Specifically, this work presents a novel application of $\texttt{TimeGPT}$, a state-of-the-art (SOTA) time-series foundation model, to predict soil water potential ($\psi_\mathrm{soil}$), a key indicator of field water status that is typically used for irrigation advice. Traditionally, this task relies on a wide array of input variables. We explore $\psi_\mathrm{soil}$'s ability to forecast $\psi_\mathrm{soil}$ in: ($i$) a zero-shot setting, ($ii$) a fine-tuned setting relying solely on historic $\psi_\mathrm{soil}$ measurements, and ($iii$) a fine-tuned setting where we also add exogenous variables to the model. We compare $\texttt{TimeGPT}$'s performance to established SOTA baseline models for forecasting $\psi_\mathrm{soil}$. Our results demonstrate that $\texttt{TimeGPT}$ achieves competitive forecasting accuracy using only historical $\psi_\mathrm{soil}$ data, highlighting its remarkable potential for agricultural applications. This research paves the way for foundation time-series models for sustainable development in agriculture by enabling forecasting tasks that were traditionally reliant on extensive data collection and domain expertise., Comment: 7 pages, accepted at KDD '24 - Fragile Earth Workshop https://openreview.net/forum?id=GZBGhi4JfE
Published: 2024

10. The 18 May 2024 Iberian superbolide from a sunskirting orbit: USG space sensors and ground-based independent observations

Author: Peña-Asensio, Eloy, Grèbol-Tomàs, Pau, Trigo-Rodríguez, Josep M., Ramírez-Moreta, Pablo, and Kresken, Rainer
Subjects: Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Physics - Popular Physics
Abstract: On 18 May 2024, a superbolide traversed the western part of the Iberian Peninsula, culminating its flight over the Atlantic Ocean and generating significant media attention. This event was caused by a weak carbonaceous meteoroid of 1 m, entering the atmosphere at 40.4 km$\,$s$^{-1}$ with an average slope of 8.5$^\circ$. The luminous phase started at 133 km and ended at an altitude of 54 km. The meteoroid's heliocentric orbit had an inclination of 16.4$^\circ$, a high eccentricity of 0.952, a semi-major axis of 2.4 au, and a short perihelion distance of 0.12 au. The superbolide was recorded by multiple ground-based stations of the Spanish Meteor Network (SPMN) and the European Space Agency (ESA), as well as by the U.S. Government (USG) sensors from space. Due to the absence of observable deceleration, we successfully reconciled satellite radiometric data with a purely dynamic atmospheric flight model, constraining the meteoroid's mass and coherently fitting its velocity profile. Our analysis shows a good agreement with the radiant and velocity data reported by the Center for Near-Earth Object Studies (CNEOS), with a deviation of 0.56$^\circ$ and 0.1 km$\,$s$^{-1}$, respectively. The presence of detached fragments in the lower part of the luminous trajectory suggests that the meteoroid was a polymict carbonaceous chondrite, containing higher-strength macroscopic particles in its interior due to collisional gardening, or a thermally processed C-type asteroid. The orbital elements indicate that the most likely source is the Jupiter-Family Comet (JFC) region, aligning with the SOHO comet family, as its sunskirting orbit is decoupled from Jupiter. This event provides important information to characterize the disruption mechanism of near-Sun objects., Comment: Accepted in MNRAS Letters
Published: 2024
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11. SiO maser polarization and magnetic field in evolved cool stars

Author: Marinho, L., Herpin, F., Wiesemeyer, H., Ariste, A. López, Baudry, A., Ramos, A. Asensio, Lèbre, A., Mathias, P., and Montargès, M.
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Both magnetic fields and photospheric/atmospheric dynamics can be involved in triggering the important mass loss observed in evolved cool stars. Previous works have revealed that these objects exhibit a magnetic field extending beyond their surface. The origin of this magnetic field is still under debate with mechanisms involving a turbulent dynamo, convection, stellar pulsation, and cool spots. Our goal is to estimate the magnetic field strength in the inner circumstellar envelope of six evolved cool stars (five Miras and one Red Supergiant). Combining this work with previous studies, we tentatively constrain the global magnetic field type observed and shed light on the mechanisms at its origin. Using the XPOL polarimeter installed at the IRAM-30 m telescope, we observed the 28 SiO v = 1, J = 2-1 maser line emission and obtained simultaneous spectroscopic measurements of the four Stokes parameters. Applying a careful calibration method for Stokes Q, U, and V, we derive estimates of the magnetic field strength from the circular and linear polarization fractions considering the saturated and unsaturated maser cases under the Zeeman hypothesis. Magnetic field strengths from several Gauss up to several tens of Gauss are derived. These new and more accurate measurements constraining the field strength in the 2-5 stellar radii region better than previous studies and seem to exclude a global poloidal magnetic field type. A combination of a toroidal and a poloidal field is nevertheless not excluded. A variation of the magnetic field strength over a two-months timescale is observed in one Mira star which suggests a possible link to the stellar phase, i.e. with pulsation/photospheric activity., Comment: 18 pages, 12 figures, Accepted in A&A
Published: 2024
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12. Solar multi-object multi-frame blind deconvolution with a spatially variant convolution neural emulator

Author: Ramos, A. Asensio
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Computer Vision and Pattern Recognition
Abstract: The study of astronomical phenomena through ground-based observations is always challenged by the distorting effects of Earth's atmosphere. Traditional methods of post-facto image correction, essential for correcting these distortions, often rely on simplifying assumptions that limit their effectiveness, particularly in the presence of spatially variant atmospheric turbulence. Such cases are often solved by partitioning the field-of-view into small patches, deconvolving each patch independently, and merging all patches together. This approach is often inefficient and can produce artifacts. Recent advancements in computational techniques and the advent of deep learning offer new pathways to address these limitations. This paper introduces a novel framework leveraging a deep neural network to emulate spatially variant convolutions, offering a breakthrough in the efficiency and accuracy of astronomical image deconvolution. By training on a dataset of images convolved with spatially invariant point spread functions and validating its generalizability to spatially variant conditions, this approach presents a significant advancement over traditional methods. The convolution emulator is used as a forward model in a multi-object multi-frame blind deconvolution algorithm for solar images. The emulator enables the deconvolution of solar observations across large fields of view without resorting to patch-wise mosaicking, thus avoiding artifacts associated with such techniques. This method represents a significant computational advantage, reducing processing times by orders of magnitude., Comment: 15 pages, 14 figures, accepted for publication in A&A
Published: 2024
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13. From Internet of Things Data to Business Processes: Challenges and a Framework

Author: Mangler, Juergen, Seiger, Ronny, Benzin, Janik-Vasily, Grüger, Joscha, Kirikkayis, Yusuf, Gallik, Florian, Malburg, Lukas, Ehrendorfer, Matthias, Bertrand, Yannis, Franceschetti, Marco, Weber, Barbara, Rinderle-Ma, Stefanie, Bergmann, Ralph, Asensio, Estefanía Serral, and Reichert, Manfred
Subjects: Computer Science - Software Engineering, Computer Science - Artificial Intelligence, H.3.3, I.2.1
Abstract: The IoT and Business Process Management (BPM) communities co-exist in many shared application domains, such as manufacturing and healthcare. The IoT community has a strong focus on hardware, connectivity and data; the BPM community focuses mainly on finding, controlling, and enhancing the structured interactions among the IoT devices in processes. While the field of Process Mining deals with the extraction of process models and process analytics from process event logs, the data produced by IoT sensors often is at a lower granularity than these process-level events. The fundamental questions about extracting and abstracting process-related data from streams of IoT sensor values are: (1) Which sensor values can be clustered together as part of process events?, (2) Which sensor values signify the start and end of such events?, (3) Which sensor values are related but not essential? This work proposes a framework to semi-automatically perform a set of structured steps to convert low-level IoT sensor data into higher-level process events that are suitable for process mining. The framework is meant to provide a generic sequence of abstract steps to guide the event extraction, abstraction, and correlation, with variation points for plugging in specific analysis techniques and algorithms for each step. To assess the completeness of the framework, we present a set of challenges, how they can be tackled through the framework, and an example on how to instantiate the framework in a real-world demonstration from the field of smart manufacturing. Based on this framework, future research can be conducted in a structured manner through refining and improving individual steps.
Published: 2024

14. Statistical Equivalence of Metrics for Meteor Dynamical Association

Author: Peña-Asensio, Eloy and Sánchez-Lozano, Juan Miguel
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: We statistically evaluate and compare four orbital similarity criteria within five-dimensional parameter space ($D_{SH}$, $D_D$, $D_H$, and $\varrho_2$) to study dynamical associations using the already classified meteors (manually by a human) in CAMS database as a benchmark. In addition, we assess various distance metrics typically used in Machine Learning with two different vectors: ORBIT, grounded in heliocentric orbital elements, and GEO, predicated on geocentric observational parameters. Additionally, we compute the optimal cut-offs for all methods for distinguishing sporadic background events. Our findings demonstrate the superior performance of the sEuclidean metric in conjunction with the GEO vector. Within the scope of D-criteria, $D_{SH}$ emerged as the preeminent metric, closely followed by $\varrho_2$. $\varrho_2$ stands out as the most equivalence to the distance metrics when utilizing the GEO vector and the most compatible with GEO and ORBIT simultaneously, whereas $D_D$ aligns more closely when using the ORBIT vector. The stark contrast in $D_D$'s behavior compared to other D-criteria highlights potential inequivalence. Geocentric features provide a more robust basis than orbital elements for meteor dynamical association. Most distance metrics associated with the GEO vector surpass the D-criteria when differentiating the meteoroid background. Accuracy displayed a dependence on solar longitude with a pronounced decrease around 180$^\circ$ matching an apparent increase in the meteoroid background activity, tentatively associated with the transition from the Perseids to the Orionids. Considering lately identified meteor showers, $\sim$27\% of meteors in CAMS would have different associations. This work unveils that Machine Learning distance metrics can rival or even exceed the performance of tailored orbital similarity criteria for meteor dynamical association., Comment: Accepted for publication in Advances in Space Research
Published: 2024
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15. Power boundedness and related properties for weighted composition operators on $\mathscr{S}(\mathbb{R}^d)$

Author: Asensio, Vicente, Jordá, Enrique, and Kalmes, Thomas
Subjects: Mathematics - Functional Analysis, 47B33, 47A35
Abstract: We characterize those pairs $(\psi,\varphi)$ of smooth mappings $\psi:\mathbb{R}^d\rightarrow\mathbb{C},\varphi:\mathbb{R}^d\rightarrow\mathbb{R}^d$ for which the corresponding weighted composition operator $C_{\psi,\varphi}f=\psi\cdot(f\circ\varphi)$ acts continuously on $\mathscr{S}(\mathbb{R}^d)$. Additionally, we give several easy-to-check necessary and sufficient conditions of this property for interesting special cases. Moreover, we characterize power boundedness and topologizablity of $C_{\psi,\varphi}$ on $\mathscr{S}(\mathbb{R}^d)$ in terms of $\psi,\varphi$. Among other things, as an application of our results we show that for a univariate polynomial $\varphi$ with $\text{deg}(\varphi)\geq 2$, power boundedness of $C_{\psi,\varphi}$ on $\mathscr{S}(\mathbb{R})$ for every $\psi\in\mathscr{O}_M(\mathbb{R})$ only depends on $\varphi$ and that in this case power boundedness of $C_{\psi,\varphi}$ is equivalent to $(C_{\psi,\varphi}^n)_{n\in\mathbb{N}}$ converging to $0$ in $\mathcal{L}_b(\mathscr{S}(\mathbb{R}))$ as well as to the uniform mean ergodicity of $C_{\psi,\varphi}$. Additionally, we give an example of a power bounded and uniformly mean ergodic weighted composition operator $C_{\psi,\varphi}$ on $\mathscr{S}(\mathbb{R})$ for which neither the multiplication operator $f\mapsto \psi f$ nor the composition operator $f\mapsto f\circ\varphi$ acts on $\mathscr{S}(\mathbb{R})$. Our results complement and considerably extend various results of Fern\'andez, Galbis, and the second named author., Comment: 22 pages; comments welcome; minor editorial changes; accepted for publication in Journal of Functional Analysis
Published: 2024
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16. Magnetic properties of layered hybrid organic-inorganic metal-halide perovskites: transition metal, organic cation and perovskite phase effects

Author: Asensio, Yaiza, Marras, Sergio, Spirito, Davide, Gobbi, Marco, Ipatov, Mihail, Casanova, Fèlix, Mateo-Alonso, Aurelio, Hueso, Luis E., and Martín-García, Beatriz
Subjects: Condensed Matter - Materials Science, Physics - Chemical Physics
Abstract: Understanding the structural and magnetic properties in layered hybrid organic-inorganic metal halide perovskites (HOIPs) is key for their design and integration in spin-electronic devices. Here, we have conducted a systematic study on ten compounds to understand the effect of the transition metal (Cu$^{2+}$, Mn$^{2+}$, Co$^{2+}$), organic spacer (alkyl- and aryl-ammonium) and perovskite phase (Ruddlesden-Popper and Dion-Jacobson) on the properties of these materials. Temperature-dependent Raman measurements show that the crystals' structural phase transitions are triggered by the motional freedom of the organic cations as well as by the flexibility of the inorganic metal-halide lattice. In the case of Cu$^{2+}$ HOIPs, an increase of the in-plane anisotropy and a reduction of the octahedra interlayer distance is found to change the behavior of the HOIP from that of a 2D ferromagnet to that of a quasi-3D antiferromagnet. Mn$^{2+}$ HOIPs show inherent antiferromagnetic octahedra intralayer interactions and a phenomenologically rich magnetism, presenting spin-canting, spin-flop transitions and metamagnetism controlled by the crystal anisotropy. Co$^{2+}$ crystals with non-linked tetrahedra show a dominant paramagnetic behavior irrespective of the organic spacer and the perovskite phase. This work demonstrates that the chemical flexibility of HOIPs can be exploited to develop novel layered magnetic materials with tailored magnetic properties., Comment: 5 figures
Published: 2024
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17. Four-of-a-kind? Comprehensive atmospheric characterisation of the HR 8799 planets with VLTI/GRAVITY

Author: Nasedkin, E., Mollière, P., Lacour, S., Nowak, M., Kreidberg, L., Stolker, T., Wang, J. J., Balmer, W. O., Kammerer, J., Shangguan, J., Abuter, R., Amorim, A., Asensio-Torres, R., Benisty, M., Berger, J. -P., Beust, H., Blunt, S., Boccaletti, A., Bonnefoy, M., Bonnet, H., Bordoni, M. S., Bourdarot, G., Brandner, W., Cantalloube, F., Caselli, P., Charnay, B., Chauvin, G., Chavez, A., Choquet, E., Christiaens, V., Clénet, Y., Foresto, V. Coudé du, Cridland, A., Davies, R., Dembet, R., Dexter, J., Drescher, A., Duvert, G., Eckart, A., Eisenhauer, F., Schreiber, N. M. Förster, Garcia, P., Lopez, R. Garcia, Gendron, E., Genzel, R., Gillessen, S., Girard, J. H., Grant, S., Haubois, X., Heißel, G., Henning, Th., Hinkley, S., Hippler, S., Houllé, M., Hubert, Z., Jocou, L., Keppler, M., Kervella, P., Kurtovic, N. T., Lagrange, A. -M., Lapeyrère, V., Bouquin, J. -B. Le, Lutz, D., Maire, A. -L., Mang, F., Marleau, G. -D., Mérand, A., Monnier, J. D., Mordasini, C., Ott, T., Otten, G. P. P. L., Paladini, C., Paumard, T., Perraut, K., Perrin, G., Pfuhl, O., Pourré, N., Pueyo, L., Ribeiro, D. C., Rickman, E., Ruffio, J. B., Rustamkulov, Z., Shimizu, T., Sing, D., Stadler, J., Straub, O., Straubmeier, C., Sturm, E., Tacconi, L. J., van Dishoeck, E. F., Vigan, A., Vincent, F., von Fellenberg, S. D., Widmann, F., Winterhalder, T. O., Woillez, J., Yazici, S., and Collaboration, the GRAVITY
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: With four companions at separations from 16 to 71 au, HR 8799 is a unique target for direct imaging, presenting an opportunity for the comparative study of exoplanets with a shared formation history. Combining new VLTI/GRAVITY observations obtained within the ExoGRAVITY program with archival data, we perform a systematic atmospheric characterisation of all four planets. We explore different levels of model flexibility to understand the temperature structure, chemistry and clouds of each planet using both petitRADTRANS atmospheric retrievals and fits to self-consistent radiative-convective equilibrium models. Using Bayesian Model Averaging to combine multiple retrievals, we find that the HR 8799 planets are highly enriched in metals, with [M/H] $\gtrsim$1, and have stellar to super-stellar C/O ratios. The C/O ratio increases with increasing separation from $0.55^{+0.12}_{-0.10}$ for d to $0.78^{+0.03}_{-0.04}$ for b, with the exception of the innermost planet which has a C/O ratio of $0.87\pm0.03$. By retrieving a quench pressure and using a disequilibrium chemistry model we derive vertical mixing strengths compatible with predictions for high-metallicity, self-luminous atmospheres. Bayesian evidence comparisons strongly favour the presence of HCN in HR 8799 c and e, as well as CH$_{4}$ in HR 8799 c, with detections at $>5\sigma$ confidence. All of the planets are cloudy, with no evidence for patchiness. The clouds of c, d and e are best fit by silicate clouds lying above a deep iron cloud layer, while the clouds of the cooler HR 8799 b are more likely composed of Na$_{2}$S. With well defined atmospheric properties, future exploration of this system is well positioned to unveil further detail in these planets, extending our understanding of the composition, structure, and formation history of these siblings., Comment: 45 pages, 25 figures, accepted by Astronomy & Astrophysics
Published: 2024
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18. End-To-End Self-tuning Self-supervised Time Series Anomaly Detection

Author: Deforce, Boje, Lee, Meng-Chieh, Baesens, Bart, Asensio, Estefanía Serral, Yoo, Jaemin, and Akoglu, Leman
Subjects: Computer Science - Machine Learning
Abstract: Time series anomaly detection (TSAD) finds many applications such as monitoring environmental sensors, industry KPIs, patient biomarkers, etc. A two-fold challenge for TSAD is a versatile and unsupervised model that can detect various different types of time series anomalies (spikes, discontinuities, trend shifts, etc.) without any labeled data. Modern neural networks have outstanding ability in modeling complex time series. Self-supervised models in particular tackle unsupervised TSAD by transforming the input via various augmentations to create pseudo anomalies for training. However, their performance is sensitive to the choice of augmentation, which is hard to choose in practice, while there exists no effort in the literature on data augmentation tuning for TSAD without labels. Our work aims to fill this gap. We introduce TSAP for TSA "on autoPilot", which can (self-)tune augmentation hyperparameters end-to-end. It stands on two key components: a differentiable augmentation architecture and an unsupervised validation loss to effectively assess the alignment between augmentation type and anomaly type. Case studies show TSAP's ability to effectively select the (discrete) augmentation type and associated (continuous) hyperparameters. In turn, it outperforms established baselines, including SOTA self-supervised models, on diverse TSAD tasks exhibiting different anomaly types.
Published: 2024

19. NLTE modelling of water-rich exoplanet atmospheres. Cooling and heating rates

Author: Muñoz, A. García, Ramos, A. Asensio, and Faure, A.
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: The hydrogen and water molecules respond very differently to the collisional-radiative processes taking place in planetary atmospheres. Naturally, the question arises whether H2O-rich atmospheres are more (or less) resilient to long-term mass loss than H2-dominated ones if they radiate away the incident stellar energy more (or less) efficiently. If confirmed, the finding would have implications on our understanding of the evolution of sub-Neptune exoplanets. As a key step towards answering this question, we present a non-local thermodynamic equilibrium (NLTE) model of H2O for the atmospheric region where the gas accelerates to escape the planet and conditions relevant to close-in sub-Neptunes. Our exploratory calculations for isothermal gas composed of H2, H2O and e- reveal that: 1) In the pressure region ~1e-2 - 1e-4 dyn cm-2 where the stellar extreme-ultraviolet (XUV) photons are typically deposited in the atmosphere, H2O is in rotational LTE but vibrational NLTE. Vibrational LTE is facilitated by high H2O abundances and fractional ionizations, and we report critical densities for the LTE-NLTE transition; 2) Vibrational cooling may locally dominate over rotational cooling, partly because of the comparatively small opacities of ro-vibrational lines; 3) Even low H2O abundances notably enhance the cooling, foreseeably offsetting some of the stellar heating; 4) Heating due to the deposition of stellar infrared (IR) photons is significant at pressures >=0.1 dyn cm-2. We estimate the contribution of H2O excitation to the internal energy of the gas and speculate on the photodissociation from the excited vibrational states. Ultimately, our findings motivate the consideration of NLTE in the mass loss rate calculations of H2O-rich atmospheres., Comment: Accepted for publication in Icarus
Published: 2024

20. Combining Gaia and GRAVITY: Characterising five new Directly Detected Substellar Companions

Author: Winterhalder, T. O., Lacour, S., Mérand, A., Maire, A. -L., Kammerer, J., Stolker, T., Pourré, N., Babusiaux, C., Abuter, R., Amorim, A., Asensio-Torres, R., Balmer, W. O., Benisty, M., Berger, J. -P., Beust, H., Blunt, S., Boccaletti, A., Bonnefoy, M., Bonnet, H., Bordoni, M. S., Bourdarot, G., Brandner, W., Cantalloube, F., Caselli, P., Charnay, B., Chauvin, G., Chavez, A., Choquet, E., Christiaens, V., Clénet, Y., Foresto, V. Coudé du, Cridland, A., Davies, R., Dembet, R., Dexter, J., Drescher, A., Duvert, G., Eckart, A., Eisenhauer, F., Schreiber, N. M. Förster, Garcia, P., Lopez, R. Garcia, Gardner, T., Gendron, E., Genzel, R., Gillessen, S., Girard, J. H., Grant, S., Haubois, X., Heißel, G., Henning, Th., Hinkley, S., Hippler, S., Houllé, M., Hubert, Z., Jocou, L., Keppler, M., Kervella, P., Kreidberg, L., Kurtovic, N. T., Lagrange, A. -M., Lapeyrère, V., Bouquin, J. -B. Le, Lutz, D., Mang, F., Marleau, G. -D., Mollière, P., Monnier, J. D., Mordasini, C., Mouillet, D., Nasedkin, E., Nowak, M., Ott, T., Otten, G. P. P. L., Paladini, C., Paumard, T., Perraut, K., Perrin, G., Pfuhl, O., Pueyo, L., Ribeiro, D. C., Rickman, E., Rustamkulov, Z., Shangguan, J., Shimizu, T., Sing, D., Stadler, J., Straub, O., Straubmeier, C., Sturm, E., Tacconi, L. J., van Dishoeck, E. F., Vigan, A., Vincent, F., von Fellenberg, S. D., Wang, J. J., Widmann, F., Woillez, J., and Yazıcı, Ş.
Subjects: Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: Precise mass constraints are vital for the characterisation of brown dwarfs and exoplanets. Here we present how the combination of data obtained by Gaia and GRAVITY can help enlarge the sample of substellar companions with measured dynamical masses. We show how the Non-Single-Star (NSS) two-body orbit catalogue contained in Gaia DR3 can be used to inform high-angular-resolution follow-up observations with GRAVITY. Applying the method presented in this work to eight Gaia candidate systems, we detect all eight predicted companions, seven of which were previously unknown and five are of a substellar nature. Among the sample is Gaia DR3 2728129004119806464 B, which - detected at an angular separation of (34.01 $\pm$ 0.15) mas from the host - is the closest substellar companion ever imaged. This translates to a semi-major axis of (0.938 $\pm$ 0.023) AU. WT 766 B, detected at a greater angular separation, was confirmed to be on an orbit exhibiting an even smaller semi-major axis of (0.676 $\pm$ 0.008) AU. The GRAVITY data were then used to break the host-companion mass degeneracy inherent to the Gaia NSS orbit solutions as well as to constrain the orbital solutions of the respective target systems. Knowledge of the companion masses enabled us to further characterise them in terms of their ages, effective temperatures, and radii via the application of evolutionary models. The inferred ages exhibit a distinct bias towards values younger than what is to be expected based on the literature. The results serve as an independent validation of the orbital solutions published in the NSS two-body orbit catalogue and show that the combination of astrometric survey missions and high-angular-resolution direct imaging holds great promise for efficiently increasing the sample of directly imaged companions in the future, especially in the light of Gaia's upcoming DR4 and the advent of GRAVITY+., Comment: Accepted for publication in Astronomy and Astrophysics
Published: 2024
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21. Fractionation in young cores: Direct determinations of nitrogen and carbon fractionation in HCN

Author: Jensen, S. S., Spezzano, S., Caselli, P., Sipilä, O., Redaelli, E., Giers, K., and Asensio, J. Ferrer
Subjects: Astrophysics - Astrophysics of Galaxies, Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: We aim to determine the $^{14}$N/$^{15}$N and $^{12}$C/$^{13}$C ratios for HCN in six starless and prestellar cores and compare the results between the direct method using radiative transfer modeling and the indirect double isotope method assuming a fixed $^{12}$C/$^{13}$C ratio. We present IRAM 30m observations of the HCN 1-0, HCN 3-2, HC15N 1-0 and H13CN 1-0 transitions toward six embedded cores. The ${}^{14}$N/${}^{15}$N ratio was derived using both the indirect double isotope method and directly through non-local thermodynamic equilibrium (NLTE) 1D radiative transfer modeling of the HCN emission. The latter also provides the ${}^{12}$C/${}^{13}$C ratio, which we compared to the local interstellar value. The derived ${}^{14}$N/${}^{15}$N ratios using the indirect method are generally in the range of 300-550. This result could suggest an evolutionary trend in the nitrogen fractionation of HCN between starless cores and later stages of the star formation process. However, the direct method reveals lower fractionation ratios of around $\sim$250, mainly resulting from a lower ${}^{12}$C/${}^{13}$C ratio in the range $\sim$20-40, as compared to the local interstellar medium value of 68. This study reveals a significant difference between the nitrogen fractionation ratio in HCN derived using direct and indirect methods. This can influence the interpretation of the chemical evolution and reveal the pitfalls of the indirect double isotope method for fractionation studies. However, the direct method is challenging, as it requires well-constrained source models to produce accurate results. No trend in the nitrogen fractionation of HCN between earlier and later stages of the star formation process is evident when the results of the direct method are considered., Comment: Accepted for publication in A&A
Published: 2024

22. Percolating Superconductivity in Air-Stable Organic-Ion Intercalated MoS2

Author: Pereira, Jose M., Tezze, Daniel, Niehues, Iris, Asensio, Yaiza, Yang, Haozhe, Mester, Lars, Chen, Shu, Casanova, Felix, Bittner, Alexander M., Ormaza, Maider, Schiller, Frederik, Martin-Garcia, Beatriz, Hillenbrand, Rainer, Hueso, Luis E., and Gobbi, Marco
Subjects: Condensed Matter - Superconductivity, Condensed Matter - Materials Science
Abstract: When doped into a certain range of charge carrier concentrations, MoS2 departs from its pristine semiconducting character to become a strongly correlated material characterized by exotic phenomena such as charge density waves or superconductivity. However, the required doping levels are typically achieved using ionic-liquid gating or air-sensitive alkali-ion intercalation, which are not compatible with standard device fabrication processes. Here, we report on the emergence of superconductivity and a charge density wave phase in air-stable organic cation intercalated MoS2 crystals. By selecting two different molecular guests, we show that these correlated electronic phases depend dramatically on the intercalated cation, demonstrating the potential of organic ion intercalation to finely tune the properties of 2D materials. Moreover, we find that a fully developed zero-resistance state is not reached in few-nm-thick flakes, indicating the presence of three-dimensional superconductive paths which are severed by the mechanical exfoliation. We ascribe this behavior to an inhomogeneous charge carrier distribution, which we probe at the nanoscale using scanning near-field optical microscopy. Our results establish organic-ion intercalated MoS2 as a platform to study the emergence and modulation of correlated electronic phases.
Published: 2024
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23. A catalogue of dual-field interferometric binary calibrators

Author: Nowak, M., Lacour, S., Abuter, R., Amorim, A., Asensio-Torres, R., Balmer, W. O., Benisty, M., Berger, J. -P., Beust, H., Blunt, S., Boccaletti, A., Bonnefoy, M., Bonnet, H., Bordoni, M. S., Bourdarot, G., Brandner, W., Cantalloube, F., Charnay, B., Chauvin, G., Chavez, A., Choquet, E., Christiaens, V., Clénet, Y., Foresto, V. Coudé du, Cridland, A., Davies, R., Dembet, R., Dexter, J., Drescher, A., Duvert, G., Eckart, A., Eisenhauer, F., Schreiber, N. M. Förster, Garcia, P., Lopez, R. Garcia, Gardner, T., Gendron, E., Genzel, R., Gillessen, S., Girard, J. H., Grant, S., Haubois, X., Heißel, G., Henning, T., Hinkley, S., Hippler, S., Houllé, M., Hubert, Z., Jocou, L., Kammerer, J., Keppler, M., Kervella, P., Kreidberg, L., Kurtovic, N. T., Lagrange, A. -M., Lapeyrère, V., Bouquin, J. -B. Le, Léna, P., Lutz, D., Maire, A. -L., Mang, F., Marleau, G. -D., Mérand, A., Monnier, J. D., Mordasini, C., Mouillet, D., Nasedkin, E., Ott, T., Otten, G. P. P. L., Paladini, C., Paumard, T., Perraut, K., Perrin, G., Pfuh, O., Pourré, N., Pueyo, L., Ribeiro, D. C., Rickman, E., Rustamkulov, Z., Shangguan, J., Shimizu, T., Sing, D., Stadler, J., Stolker, T., Straub, O., Straubmeier, C., Sturm, E., Subroweit, M., Tacconi, L. J., van Dishoeck, E. F., Vigan, A., Vincent, F., von Fellenberg, S. D., Wang, J. J., Widmann, F., Winterhalder, T. O., Woillez, J., Yazıcı, Ş., Young, A., and Collaboration, the GRAVITY
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract: Dual-field interferometric observations with VLTI/GRAVITY sometimes require the use of a "binary calibrator", a binary star whose individual components remain unresolved by the interferometer, with a separation between 400 and 2000 mas for observations with the Units Telescopes (UTs), or 1200 to 3000 mas for the Auxiliary Telescopes (ATs). The separation vector also needs to be predictable to within 10 mas for proper pointing of the instrument. Up until now, no list of properly vetted calibrators was available for dual-field observations with VLTI/GRAVITY on the UTs. Our objective is to compile such a list, and make it available to the community. We identify a list of candidates from the Washington Double Star (WDS) catalogue, all with appropriate separations and brightness, scattered over the Southern sky. We observe them as part of a dedicated calibration programme, and determine whether these objects are true binaries (excluding higher multiplicities resolved interferometrically but unseen by imaging), and extract measurements of the separation vectors. We combine these new measurements with those available in the WDS to determine updated orbital parameters for all our vetted calibrators. We compile a list of 13 vetted binary calibrators for observations with VLTI/GRAVITY on the UTs, and provide orbital estimates and astrometric predictions for each of them. We show that our list guarantees that there are always at least two binary calibrators at airmass < 2 in the sky over the Paranal observatory, at any point in time. Any Principal Investigator wishing to use the dual-field mode of VLTI/GRAVITY with the UTs can now refer to this list to select an appropriate calibrator. We encourage the use of "whereistheplanet" to predict the astrometry of these calibrators, which seamlessly integrates with "p2Gravity" for VLTI/GRAVITY dual-field observing material preparation., Comment: 16 pages, 6 figures. Submitted to A&A
Published: 2024
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24. Mechanical Properties of Minerals in Lunar and HED Meteorites from Nanoindentation Testing: Implications for Space Mining

Author: Peña-Asensio, Eloy, Rodríguez, Josep M. Trigo., Sort, Jordi, Ibáñez-Insa, Jordi, and Rimola, Albert
Subjects: Condensed Matter - Materials Science, Physics - Geophysics
Abstract: This study analyzes the mechanical and elemental properties of lunar meteorites DHOFAR 1084, JAH 838, NWA 11444, and HED meteorite NWA 6013. Utilizing microscale rock mechanics experiments, i.e., nanoindentation testing, this research reveals significant heterogeneity in both mechanical and elemental attributes across the minerals of the samples. Olivines, pyroxen, feldspar, and spinel demonstrate similar compositional and mechanical characteristics. Conversely, other silicate and oxide minerals display variations in their mechanical properties. Terrestrial olivines subjected to nanoindentation tests exhibit increased hardness and a higher Young's modulus compared to their lunar counterparts. A linear correlation is observed between the H/Er ratio and both plastic and elastic energies. Additionally, the alignment of mineral phases along a constant H/Er ratio suggests variations in local porosity. This study also highlights the need for further research focusing on porosity, phase insertions within the matrix, and structural orientations to refine our understanding of these mechanical characteristics. The findings have direct implications for in-situ resource utilization (ISRU) strategies and future state-of-the-art impact models. This comprehensive characterization serves as a foundational resource for future research efforts in space science and mining., Comment: Accepted for publication in Meteoritics & Planetary Science Journal
Published: 2024
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25. Deciding technosignature search strategies: Multi-criteria fuzzy logic to find extraterrestrial intelligence

Author: Sánchez-Lozano, Juan Miguel, Peña-Asensio, Eloy, and Socas-Navarro, Hector
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics
Abstract: This study presents the implementation of Multi-Criteria Decision-Making (MCDM) methodologies, particularly the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), in prioritizing technosignatures (TSs) for the Search for Extraterrestrial Intelligence (SETI). By incorporating expert opinions and weighted criteria based on the established Axes of Merit, our analysis offers insights into the relative importance of various TSs. Notably, radio and optical communications are emphasized, in contrast to dark side illumination and starshades in transit. We introduce a new axis, Scale Sensitivity, designed to assess the variability of TS metrics. A sensitivity analysis confirms the robustness of our approach. Our findings, especially the highlighted significance of artifacts orbiting Earth, the Moon, or the Sun, indicate a need to broaden evaluative criteria within SETI research. This suggests an enhancement of the Axes of Merit, with a focus on addressing the plausibility of TSs. As the quest to resolve the profound question of our solitude in the cosmos continues, SETI efforts would benefit from exploring innovative prioritization methodologies that effectively quantify TS search strategies., Comment: Accepted in MPDI Aerospace
Published: 2024
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26. Characterising the intra-cluster light in The Three Hundred simulations

Author: Contreras-Santos, Ana, Knebe, Alexander, Cui, Weiguang, Asensio, Isaac Alonso, Vecchia, Claudio Dalla, Cañas, Rodrigo, Haggar, Roan, Paun, Robert A. Mostoghiu, Pearce, Frazer, and Rasia, Elena
Subjects: Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies
Abstract: We characterise the intra-cluster light (ICL) in ensembles of full-physics cluster simulations from The Three Hundred project, a suite of 324 hydrodynamical resimulations of cluster-sized halos. We identify the ICL as those stellar particles bound to the potential of the cluster itself, but not to any of its substructures, and separate the brightest cluster galaxy (BCG) by means of a fixed 50 kpc aperture. We find the total BCG+ICL mass to be in agreement with state-of-the-art observations of galaxy clusters. The ICL mass fraction of our clusters is between 30 and 50 per cent of the total stellar mass within $R_{500}$, while the BCG represents around 10 percent. We further find no trend of the ICL fraction with cluster halo mass, at least not in the range $[0.2,3]\cdot10^{15}h^{-1}M_\odot$ considered here. For the dynamical state, characterised both by theoretical estimators and by the recent merging history of the cluster, there is a clear correlation, such that more relaxed clusters and those that have undergone fewer recent mergers have a higher ICL fraction. Finally, we investigate the possibility of using the ICL to explore the dark matter (DM) component of galaxy clusters. We compute the volumetric density profile for the DM and ICL components and show that, up to $R_{500}$, the ratio between the two can be described by a power law. Working with the velocity dispersion profiles instead, we show that the ratio can be fit by a straight line. Providing the parameters of these fits, we show how the ICL can be used to infer DM properties., Comment: 18 pages, 14 figures. Accepted for publication in Astronomy & Astrophysics
Published: 2024
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27. A deep search for large complex organic species toward IRAS16293-2422 B at 3 mm with ALMA

Author: Nazari, P., Cheung, J. S. Y., Asensio, J. Ferrer, Murillo, N. M., van Dishoeck, E. F., Jørgensen, J. K., Bourke, T. L., Chuang, K. -J., Drozdovskaya, M. N., Fedoseev, G., Garrod, R. T., Ioppolo, S., Linnartz, H., McGuire, B. A., Müller, H. S. P., Qasim, D., and Wampfler, S. F.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: Complex organic molecules (COMs) have been detected ubiquitously in protostellar systems. However, at shorter wavelengths (~0.8mm) it is more difficult to detect larger molecules than at longer wavelengths (~3mm) because of the increase of millimeter dust opacity, line confusion, and unfavorable partition function. We aim to search for large molecules (>8 atoms) in the ALMA Band 3 spectrum of IRAS 16293-2422 B. We search for more than 70 molecules and identify as many lines as possible in the spectrum. The spectral settings were set to specifically target three-carbon species such as propanol and glycerol. We identify lines of 31 molecules including many oxygen-bearing COMs such as CH3OH and c-C2H4O and a few nitrogen- and sulfur-bearing ones such as HOCH2CN and CH3SH. The largest detected molecules are gGg-(CH2OH)2 and CH3COCH3. We do not detect glycerol or propanol but provide upper limits for them which are in line with previous laboratory and observational studies. The line density in Band 3 is only ~2.5 times lower in frequency space than in Band 7. From the detected lines in Band 3 at a $\gtrsim 6\sigma$ level, ~25-30% of them could not be identified indicating the need for more laboratory data of rotational spectra. We find similar column densities and column density ratios of COMs (within a factor ~2) between Band 3 and Band 7. The effect of dust optical depth for IRAS 16293-2422 B at an off-source location on column densities and column density ratios is minimal. Moreover, for warm protostars, long wavelength spectra are not only crowded, but also take longer integration times to reach the same sensitivity limit. The 3mm search has not yet resulted in detection of larger and more complex molecules in warm sources. A full deep ALMA Band 2-3 (i.e., 3-4 mm) survey is needed to assess whether low frequency data have the potential to reveal more complex molecules in warm sources., Comment: Accepted for publication in A&A
Published: 2024
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28. VLTI/GRAVITY Provides Evidence the Young, Substellar Companion HD 136164 Ab formed like a 'Failed Star'

Author: Balmer, William O., Pueyo, L., Lacour, S., Wang, J. J., Stolker, T., Kammerer, J., Pourré, N., Nowak, M., Rickman, E., Blunt, S., Sivaramakrishnan, A., Sing, D., Wagner, K., Marleau, G. -D., Lagrange, A. -M., Abuter, R., Amorim, A., Asensio-Torres, R., Berger, J. -P., Beust, H., Boccaletti, A., Bohn, A., Bonnefoy, M., Bonnet, H., Bordoni, M. S., Bourdarot, G., Brandner, W., Cantalloube, F., Caselli, P., Charnay, B., Chauvin, G., Chavez, A., Choquet, E., Christiaens, V., Clénet, Y., Foresto, V. Coudé du, Cridland, A., Davies, R., Dembet, R., Drescher, A., Duvert, G., Eckart, A., Eisenhauer, F., Schreiber, N. M. F"orster, Garcia, P., Lopez, R. Garcia, Gendron, E., Genzel, R., Gillessen, S., Girard, J. H., Grant, S., Haubois, X., Heißel, G., Henning, Th., Hinkley, S., Hippler, S., Houllé, M., Hubert, Z., Jocou, L., Keppler, M., Kervella, P., Kreidberg, L., Kurtovic, N. T., Lapeyrère, V., Bouquin, J. -B. Le, Léna, P., Lutz, D., Maire, A. -L., Mang, F., Mérand, A., Mollière, P., Mordasini, C., Mouillet, D., Nasedkin, E., Ott, T., Otten, G. P. P. L., Paladini, C., Paumard, T., Perraut, K., Perrin, G., Pfuhl, O., Ribeiro, D. C., Rodet, L., Rustamkulov, Z., Shangguan, J., Shimizu, T., Straubmeier, C., Sturm, E., Tacconi, L. J., Vigan, A., Vincent, F., Ward-Duong, K., Widmann, F., Winterhalder, T., Woillez, J., and Yazici, S.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract: Young, low-mass Brown Dwarfs orbiting early-type stars, with low mass ratios ($q\lesssim0.01$), appear intrinsically rare and present a formation dilemma: could a handful of these objects be the highest mass outcomes of ``planetary" formation channels (bottom up within a protoplanetary disk), or are they more representative of the lowest mass ``failed binaries" (formed via disk fragmentation, or core fragmentation)? Additionally, their orbits can yield model-independent dynamical masses, and when paired with wide wavelength coverage and accurate system age estimates, can constrain evolutionary models in a regime where the models have a wide dispersion depending on initial conditions. We present new interferometric observations of the $16\,\mathrm{Myr}$ substellar companion HD~136164~Ab (HIP~75056~Ab) with VLTI/GRAVITY and an updated orbit fit including proper motion measurements from the Hipparcos-Gaia Catalogue of Accelerations. We estimate a dynamical mass of $35\pm10\,\mathrm{M_J}$ ($q\sim0.02$), making HD~136164~Ab the youngest substellar companion with a dynamical mass estimate. The new mass and newly constrained orbital eccentricity ($e=0.44\pm0.03$) and separation ($22.5\pm1\,\mathrm{au}$) could indicate that the companion formed via the low-mass tail of the Initial Mass Function. Our atmospheric fit to the \texttt{SPHINX} M-dwarf model grid suggests a sub-solar C/O ratio of $0.45$, and $3\times$ solar metallicity, which could indicate formation in the circumstellar disk via disk fragmentation. Either way, the revised mass estimate likely excludes ``bottom-up" formation via core accretion in the circumstellar disk. HD~136164~Ab joins a select group of young substellar objects with dynamical mass estimates; epoch astrometry from future \textit{Gaia} data releases will constrain the dynamical mass of this crucial object further., Comment: Accepted for publication in The Astronomical Journal. 9 figures, 3 tables
Published: 2023

29. The fluid mechanics of splat painting

Author: Ávila-García, Diego, Lacambra-Asensio, Lucía, Rodríguez-Rodríguez, Javier, Zenit, Roberto, and Champougny, Lorène
Subjects: Physics - Fluid Dynamics, Physics - Popular Physics
Abstract: In splat painting, a collection of liquid droplets is projected onto the substrate by imposing a controlled acceleration to a paint-loaded brush. To unravel the physical phenomena at play in this artistic technique, we perform a series of experiments where the amount of expelled liquid and the resulting patterns on the substrate are systematically characterized as a function of the liquid viscosity and brush acceleration. Experimental trends and orders of magnitude are rationalized by simple physical models, revealing the existence of an inertia-dominated flow in the anisotropic, porous tip of the brush. We argue that splat painting artists intuitively tune their parameters to work in this regime, which may also play a role in other pulsed flows, like violent expiratory events or sudden geophysical processes., Comment: 15 pages, 10 figures
Published: 2023

30. Deep machine learning for meteor monitoring: advances with transfer learning and gradient-weighted class activation mapping

Author: Peña-Asensio, Eloy, Trigo-Rodríguez, Josep M., Grèbol-Tomàs, Pau, Regordosa-Avellana, David, and Rimola, Albert
Subjects: Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract: In recent decades, the use of optical detection systems for meteor studies has increased dramatically, resulting in huge amounts of data being analyzed. Automated meteor detection tools are essential for studying the continuous meteoroid incoming flux, recovering fresh meteorites, and achieving a better understanding of our Solar System. Concerning meteor detection, distinguishing false positives between meteor and non-meteor images has traditionally been performed by hand, which is significantly time-consuming. To address this issue, we developed a fully automated pipeline that uses Convolutional Neural Networks (CNNs) to classify candidate meteor detections. Our new method is able to detect meteors even in images that contain static elements such as clouds, the Moon, and buildings. To accurately locate the meteor within each frame, we employ the Gradient-weighted Class Activation Mapping (Grad-CAM) technique. This method facilitates the identification of the region of interest by multiplying the activations from the last convolutional layer with the average of the gradients across the feature map of that layer. By combining these findings with the activation map derived from the first convolutional layer, we effectively pinpoint the most probable pixel location of the meteor. We trained and evaluated our model on a large dataset collected by the Spanish Meteor Network (SPMN) and achieved a precision of 98\%. Our new methodology presented here has the potential to reduce the workload of meteor scientists and station operators and improve the accuracy of meteor tracking and classification., Comment: Accepted in Planetary and Space Science
Published: 2023
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31. Oort cloud perturbations as a source of hyperbolic Earth impactors

Author: Peña-Asensio, Eloy, Visuri, Jaakko, Trigo-Rodríguez, Josep M., Socas-Navarro, Hector, Gritsevich, Maria, Siljama, Markku, and Rimola, Albert
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: The observation of interstellar objects 1I/'Oumuamua and 2I/Borisov suggests the existence of a larger population of smaller projectiles that impact our planet with unbound orbits. We analyze an asteroidal grazing meteor (FH1) recorded by the Finnish Fireball Network on October 23, 2022. FH1 displayed a likely hyperbolic orbit lying on the ecliptic plane with an estimated velocity excess of $\sim$0.7 km$\,$s$^{-1}$ at impact. FH1 may either be an interstellar object, indicating a high-strength bias in this population, or an Oort cloud object, which would reinforce migration-based solar system models. Furthermore, under the calculated uncertainties, FH1 could potentially be associated with the passage of Scholz's binary star system. Statistical evaluation of uncertainties in the CNEOS database and study of its hyperbolic fireballs reveals an anisotropic geocentric radiant distribution and low orbital inclinations, challenging the assumption of a randomly incoming interstellar population. Orbital integrations suggest that the event on March 9, 2017 (IM2) from CNEOS may have experienced gravitational perturbation during the Scholz fly-by, contingent upon velocity overestimation within the expected range. These findings suggest that apparent interstellar meteors may, in fact, be the result of accelerated meteoroid impacts caused by close encounters with massive objects within or passing through our solar system., Comment: Accepted for publication in Icarus
Published: 2023
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32. First VLTI/GRAVITY Observations of HIP 65426 b: Evidence for a Low or Moderate Orbital Eccentricity

Author: Blunt, S., Balmer, W. O., Wang, J. J., Lacour, S., Petrus, S., Bourdarot, G., Kammerer, J., Pourré, N., Rickman, E., Shangguan, J., Winterhalder, T., Abuter, R., Amorim, A., Asensio-Torres, R., Benisty, M., Berger, J. -P., Beust, H., Boccaletti, A., Bohn, A., Bonnefoy, M., Bonnet, H., Brandner, W., Cantalloube, F., Caselli, P., Charnay, B., Chauvin, G., Chavez, A., Choquet, E., Christiaens, V., Clénet, Y., Foresto, V. Coudé du, Cridland, A., Dembet, R., Drescher, A., Duvert, G., Eckart, A., Eisenhauer, F., Feuchtgruber, H., Garcia, P., Lopez, R. Garcia, Gendron, E., Genzel, R., Gillessen, S., Girard, J. H., Haubois, X., Heißel, G., Henning, Th., Hinkley, S., Hippler, S., Horrobin, M., Houllé, M., Hubert, Z., Jocou, L., Keppler, M., Kervella, P., Kreidberg, L., Lagrange, A. -M., Lapeyrère, V., Bouquin, J. -B. Le, Léna, P., Lutz, D., Maire, A. -L., Mang, F., Marleau, G. -D., Mérand, A., Mollière, P., Monnier, J. D., Mordasini, C., Mouillet, D., Nasedkin, E., Nowak, M., Ott, T., Otten, G. P. P. L., Paladini, C., Paumard, T., Perraut, K., Perrin, G., Pfuhl, O., Pueyo, L., Rameau, J., Rodet, L., Rustamkulov, Z., Shimizu, T., Sing, D., Stolker, T., Straubmeier, C., Sturm, E., Tacconi, L. J., van Dishoeck, E. F., Vigan, A., Vincent, F., Ward-Duong, K., Widmann, F., Wieprecht, E., Wiezorrek, E., Woillez, J., Yazici, S., and Young, A.
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: Giant exoplanets have been directly imaged over orders of magnitude of orbital separations, prompting theoretical and observational investigations of their formation pathways. In this paper, we present new VLTI/GRAVITY astrometric data of HIP 65426 b, a cold, giant exoplanet which is a particular challenge for most formation theories at a projected separation of 92 au from its primary. Leveraging GRAVITY's astrometric precision, we present an updated eccentricity posterior that disfavors large eccentricities. The eccentricity posterior is still prior-dependent, and we extensively interpret and discuss the limits of the posterior constraints presented here. We also perform updated spectral comparisons with self-consistent forward-modeled spectra, finding a best fit ExoREM model with solar metallicity and C/O=0.6. An important caveat is that it is difficult to estimate robust errors on these values, which are subject to interpolation errors as well as potentially missing model physics. Taken together, the orbital and atmospheric constraints paint a preliminary picture of formation inconsistent with scattering after disk dispersal. Further work is needed to validate this interpretation. Analysis code used to perform this work is available at https://github.com/sblunt/hip65426., Comment: 28 pages, 14 figures. Revised and resubmitted to AJ
Published: 2023

33. VLTI/GRAVITY Observations and Characterization of the Brown Dwarf Companion HD 72946 B

Author: Balmer, W. O., Pueyo, L., Stolker, T., Reggiani, H., Lacour, S., Maire, A. -L., Mollière, P., Nowak, M., Sing, D., Pourré, N., Blunt, S., Wang, J. J., Rickman, E., Henning, Th., Ward-Duong, K., Abuter, R., Amorim, A., Asensio-Torres, R., Benisty, M., Berger, J. -P., Beust, H., Boccaletti, A., Bohn, A., Bonnefoy, M., Bonnet, H., Bourdarot, G., Brandner, W., Cantalloube, F., Caselli, P., Charnay, B., Chauvin, G., Chavez, A., Choquet, E., Christiaens, V., Clénet, Y., Foresto, V. Coudé du, Cridland, A., Dembet, R., Drescher, A., Duvert, G., Eckart, A., Eisenhauer, F., Feuchtgruber, H., Garcia, P., Lopez, R. Garcia, Gardner, T., Gendron, E., Genzel, R., Gillessen, S., Girard, J. H., Haubois, X., Heißel, G., Hinkley, S., Hippler, S., Horrobin, M., Houllé, M., Hubert, Z., Jocou, L., Kammerer, J., Keppler, M., Kervella, P., Kreidberg, L., Lagrange, A. -M., Lapeyrère, V., Bouquin, J. -B. Le, Léna, P., Lutz, D., Mang, F., Marleau, G. -D., Mérand, A., Monnier, J. D., Mordasini, C., Mouillet, D., Nasedkin, E., Ott, T., Otten, G. P. P. L., Paladini, C., Paumard, T., Perraut, K., Perrin, G., Pfuhl, O., Rameau, J., Rodet, L., Rustamkulov, Z., Shangguan, J., Shimizu, T., Straubmeier, C., Sturm, E., Tacconi, L. J., van Dishoeck, E. F., Vigan, A., Vincent, F., Widmann, F., Wieprecht, E., Wiezorrek, E., Winterhalder, T., Woillez, J., Yazici, S., and Young, A.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract: Tension remains between the observed and modeled properties of substellar objects, but objects in binary orbits, with known dynamical masses can provide a way forward. HD 72946 B is a recently imaged brown dwarf companion to the nearby, solar type star. We achieve $\sim100~\mu\mathrm{as}$ relative astrometry of HD 72946 B in the K-band using VLTI/GRAVITY, unprecedented for a benchmark brown dwarf. We fit an ensemble of measurements of the orbit using orbitize! and derive a strong dynamical mass constraint $\mathrm{M_B}=69.5\pm0.5~\mathrm{M_{Jup}}$ assuming a strong prior on the host star mass $\mathrm{M_A}=0.97\pm0.01~\mathrm{M_\odot}$ from an updated stellar analysis. We fit the spectrum of the companion to a grid of self-consistent BT-Settl-CIFIST model atmospheres, and perform atmospheric retrievals using petitRADTRANS. A dynamical mass prior only marginally influences the sampled distribution on effective temperature, but has a large influence on the surface gravity and radius, as expected. The dynamical mass alone does not strongly influence retrieved pressure-temperature or cloud parameters within our current retrieval setup. Independent of cloud prescription and prior assumptions, we find agreement within $\pm2\,\sigma$ between the C/O ratio of the host ($0.52\pm0.05)$ and brown dwarf ($0.43$ to $0.63$), as expected from a molecular cloud collapse formation scenario, but our retrieved metallicities are implausibly high ($0.6-0.8$) in light of an excellent agreement of the data with the solar abundance model grid. Future work on our retrieval framework will seek to resolve this tension. Additional study of low surface-gravity objects is necessary to assess the influence of a dynamical mass prior on atmospheric analysis., Comment: Accepted for publication in the Astrophysical Journal. 32 pages, 14 figures, 7 tables. v2&3 correct errors in co-author's affiliations, figure rendering, and some grant acknowledgements
Published: 2023
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34. Magnetic field fluctuations in the shocked umbral chromosphere

Author: Felipe, T., Manrique, S. J. González, Sangeetha, C. R., and Ramos, A. Asensio
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Several studies have reported magnetic field fluctuations associated with umbral shock waves. We aim to study the properties and origin of magnetic field fluctuations in the umbral chromosphere. Temporal series of spectropolarimetric observations were acquired with the GREGOR telescope. The chromospheric and photospheric conditions were derived from simultaneous inversions of the He I 10830 \AA\ triplet and the Si I 10827 \AA\ line using HAZEL2. The oscillations are interpreted using wavelet analysis and context information from UV observations acquired with SDO/AIA and IRIS. The chromospheric magnetic field shows strong fluctuations in the sunspot umbra, with peak field strengths up to 2900 G. Magnetic field and velocity umbral oscillations exhibit a strong coherence, with the magnetic field lagging the shock fronts detected in the velocity fluctuations. This points to a common origin of the fluctuations in both parameters, whereas the analysis of the phase shift between photospheric and chromospheric velocity is consistent with upwards wave propagation. These results suggest that the strong inferred magnetic field fluctuations are caused by changes in the response height of the He I 10830 \AA\ line to the magnetic field, which is sensitive to high photospheric layers after the shock fronts. The coronal activity seen in EUV data could possibly have some impact on the inferred fluctuations, but it is not the main driver of the magnetic field oscillations since they are found before EUV events take place. Chromospheric magnetic field fluctuations measured with the He I 10830 \AA\ triplet arise due to variations in the opacity of the line. After shocks produced by slow magnetoacoustic waves, the response of the line to the magnetic field can be shifted down to the upper photosphere. This is seen as remarkably large fluctuations in the line of sight magnetic field strength., Comment: Accepted for publication in A&A. Abstract abridged due to arXiv's 1920 character limit
Published: 2023
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35. Machine learning in solar physics

Author: Ramos, A. Asensio, Cheung, M. C. M., Chifu, I., and Gafeira, R.
Subjects: Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Computer Vision and Pattern Recognition
Abstract: The application of machine learning in solar physics has the potential to greatly enhance our understanding of the complex processes that take place in the atmosphere of the Sun. By using techniques such as deep learning, we are now in the position to analyze large amounts of data from solar observations and identify patterns and trends that may not have been apparent using traditional methods. This can help us improve our understanding of explosive events like solar flares, which can have a strong effect on the Earth environment. Predicting hazardous events on Earth becomes crucial for our technological society. Machine learning can also improve our understanding of the inner workings of the sun itself by allowing us to go deeper into the data and to propose more complex models to explain them. Additionally, the use of machine learning can help to automate the analysis of solar data, reducing the need for manual labor and increasing the efficiency of research in this field., Comment: 100 pages, 13 figures, 286 references, accepted for publication as a Living Review in Solar Physics (LRSP)
Published: 2023

36. Accelerating Multiframe Blind Deconvolution via Deep Learning

Author: Ramos, A. Asensio, Pozuelo, S. Esteban, and Kuckein, C.
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Computer Science - Computer Vision and Pattern Recognition
Abstract: Ground-based solar image restoration is a computationally expensive procedure that involves nonlinear optimization techniques. The presence of atmospheric turbulence produces perturbations in individual images that make it necessary to apply blind deconvolution techniques. These techniques rely on the observation of many short exposure frames that are used to simultaneously infer the instantaneous state of the atmosphere and the unperturbed object. We have recently explored the use of machine learning to accelerate this process, with promising results. We build upon this previous work to propose several interesting improvements that lead to better models. As well, we propose a new method to accelerate the restoration based on algorithm unrolling. In this method, the image restoration problem is solved with a gradient descent method that is unrolled and accelerated aided by a few small neural networks. The role of the neural networks is to correct the estimation of the solution at each iterative step. The model is trained to perform the optimization in a small fixed number of steps with a curated dataset. Our findings demonstrate that both methods significantly reduce the restoration time compared to the standard optimization procedure. Furthermore, we showcase that these models can be trained in an unsupervised manner using observed images from three different instruments. Remarkably, they also exhibit robust generalization capabilities when applied to new datasets. To foster further research and collaboration, we openly provide the trained models, along with the corresponding training and evaluation code, as well as the training dataset, to the scientific community., Comment: 26 pages, 9 figures, accepted for publication in Solar Physics
Published: 2023
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37. High-precision interpolation of stellar atmospheres with a deep neural network using a 1D convolutional auto encoder for feature extraction

Author: Plaza, C. Westendorp, Ramos, A. Asensio, and Prieto, C. Allende
Subjects: Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics, Statistics - Machine Learning
Abstract: Given the widespread availability of grids of models for stellar atmospheres, it is necessary to recover intermediate atmospheric models by means of accurate techniques that go beyond simple linear interpolation and capture the intricacies of the data. Our goal is to establish a reliable, precise, lightweight, and fast method for recovering stellar model atmospheres, that is to say the stratification of mass column, temperature, gas pressure, and electronic density with optical depth given any combination of the defining atmospheric specific parameters: metallicity, effective temperature, and surface gravity, as well as the abundances of other key chemical elements. We employed a fully connected deep neural network which in turn uses a 1D convolutional auto-encoder to extract the nonlinearities of a grid using the ATLAS9 and MARCS model atmospheres. This new method we call iNNterpol effectively takes into account the nonlinearities in the relationships of the data as opposed to traditional machine-learning methods, such as the light gradient boosting method (LightGBM), that are repeatedly used for their speed in well-known competitions with reduced datasets. We show a higher precision with a convolutional auto-encoder than using principal component analysis as a feature extractor.We believe it constitutes a useful tool for generating fast and precise stellar model atmospheres, mitigating convergence issues, as well as a framework for future developments. The code and data for both training and direct interpolation are available online at https://github.com/cwestend/iNNterpol for full reproducibility and to serve as a practical starting point for other continuous 1D data in the field and elsewhere., Comment: Accepted for publication in Astronomy and Astrophysics, 11 pages, 27 figures, 3 tables
Published: 2023
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38. Economic and Resilience Improvement for Radial and Meshed Grids

Author: Rosales-Asensio, Enrique, de Simón-Martín, Miguel, Blanes-Peiró, Jorge, González-Martínez, Alberto, Colmenar-Santos, Antonio, Borge-Diez, David, editor, and Rosales-Asensio, Enrique, editor
Published: 2024
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39. Resilience Improvement in Office Buildings with Critical Loads

Author: Rosales-Asensio, Enrique, de Simón-Martín, Miguel, Borge-Diez, David, Blanes-Peiró, Jorge Juan, Colmenar-Santos, Antonio, Borge-Diez, David, editor, and Rosales-Asensio, Enrique, editor
Published: 2024
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40. Peak Load Reduction and Resilience Benefits in Critical Microgrids

Author: Rosales-Asensio, Enrique, Icaza, Daniel, González-Cobos, Noemi, Borge-Diez, David, Borge-Diez, David, editor, and Rosales-Asensio, Enrique, editor
Published: 2024
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41. Resilience Improvement in PreCOVID-19 Medical Centers

Author: Lagrange, Alexis, de Simón-Martín, Miguel, González-Martínez, Alberto, Bracco, Stefano, Rosales-Asensio, Enrique, Borge-Diez, David, editor, and Rosales-Asensio, Enrique, editor
Published: 2024
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42. Resilience Improvement in PostCOVID-19 Medical Centers

Author: Hervás-Zaragoza, Josep, Colmenar-Santos, Antonio, Rosales-Asensio, Enrique, Colmenar-Fernández, Lucía, Borge-Diez, David, editor, and Rosales-Asensio, Enrique, editor
Published: 2024
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43. Self-Supervised Anomaly Detection of Rogue Soil Moisture Sensors

Author: Deforce, Boje, Baesens, Bart, Diels, Jan, and Asensio, Estefanía Serral
Subjects: Computer Science - Machine Learning
Abstract: IoT data is a central element in the successful digital transformation of agriculture. However, IoT data comes with its own set of challenges. E.g., the risk of data contamination due to rogue sensors. A sensor is considered rogue when it provides incorrect measurements over time. To ensure correct analytical results, an essential preprocessing step when working with IoT data is the detection of such rogue sensors. Existing methods assume that well-behaving sensors are known or that a large majority of the sensors is well-behaving. However, real-world data is often completely unlabeled and voluminous, calling for self-supervised methods that can detect rogue sensors without prior information. We present a self-supervised anomalous sensor detector based on a neural network with a contrastive loss, followed by DBSCAN. A core contribution of our paper is the use of Dynamic Time Warping in the negative sampling for the triplet loss. This novelty makes the use of triplet networks feasible for anomalous sensor detection. Our method shows promising results on a challenging dataset of soil moisture sensors deployed in multiple pear orchards.
Published: 2023

44. Estimating the longitudinal magnetic field in the chromosphere of quiet-Sun magnetic concentrations

Author: Pozuelo, S. Esteban, Ramos, A. Asensio, Rodríguez, J. de la Cruz, Bueno, J. Trujillo, and González, M. J. Martínez
Subjects: Astrophysics - Solar and Stellar Astrophysics
Abstract: Details of the magnetic field in the quiet Sun chromosphere are key to our understanding of essential aspects of the solar atmosphere. We aim to determine the longitudinal magnetic field component (B_lon) of quiet Sun regions depending on their size. We estimated B_lon by applying the weak-field approximation (WFA) to high-spatial-resolution Ca II 854.2 nm data taken with the Swedish 1m Solar Telescope. Specifically, we analyzed the estimates inferred for different spectral ranges using the data at the original cadence and temporally integrated signals. The longitudinal magnetic field in each considered plasma structure correlates with its size. Using a spectral range restricted to the line core leads to chromospheric longitudinal fields varying from 50 G at the edges to 150-500 G at the center of the structure. These values increase as the spectral range widens due to the photospheric contribution. However, the difference between this contribution and the chromospheric one is not uniform for all structures. Small and medium-sized concentrations show a steeper height gradient in B_lon compared to their chromospheric values, so estimates for wider ranges are less trustworthy. Signal addition does not alleviate this situation as the height gradients in B_lon are consistent with time. Finally, despite the amplified noise levels that deconvolving processes may cause, data restored with the destretching technique show similar results, though are affected by smearing. We obtained B_lon estimates similar to those previously found, except for large concentrations and wide spectral ranges. In addition, we report a correlation between the height variation of B_lon compared to the chromospheric estimates and the concentration size. This correlation affects the difference between the photospheric and chromospheric magnetic flux values and the reliability of the estimates for wider spectral ranges., Comment: 14 pages, 14 figures. Accepted for publication in Astronomy & Astrophysics; abstract has been abridged
Published: 2023
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45. Data augmentation for battery materials using lattice scaling

Author: Abenza, Eduardo, Alonso, César, Sobrados, Isabel, Amarilla, José M., Rodríguez, Javier L., Alonso, José A., Martín, Roberto G. E., and Asensio, Maria C.
Subjects: Condensed Matter - Materials Science
Abstract: A significant step forward in Lithium-ion batteries (LIBs) developments can only be achieved by proposing mold-breaking research based on selecting the best materials for the cell components, optimizing cell manufacture, anticipating the degradation mechanisms of the LIBs, and consolidating the regeneration processes of damaged batteries. LIBs with longer recycling life, better safety, and the ability to be reused will establish sustainable state-of-the-art batteries with maximum energy efficiency, low costs, and minimal CO2 emissions within a circular economy, promoting sustainability in areas as relevant as electromobility and portable electronics. Recently, there has been increasing interest in applying Artificial Intelligence (AI) techniques and their subclasses to better predict novel materials with designed properties. This collection of methods has already obtained considerable success, having been used to predict numerous physical properties of materials. However, compared to other fields, the materials data are typically much smaller and sometimes more diverse, which undoubtedly affects the construction and effectiveness of AI models. At present, several Data Augmentation (DA) methods have been proposed in materials science based on flipping, rotating, and distorting the unit cells of materials, which have been demonstrated to be very efficient in increasing the size and quality of data. Here we present an even more effective new method of Data Augmentation based on the lattice scaling of crystal structures. In the lattice scaling DA method, the unit cell is perturbed, undergoing an increase and decrease of the unit cell volume in an isotropic or anisotropic way. This transformation is particularly pertinent for battery components since volume changes of up to 5% have been reported for the insertion-based LIBs during cycling.
Published: 2023

46. Millimetre and sub-millimetre spectroscopy of doubly deuterated acetaldehyde (CHD2CHO) and first detection towards IRAS 16293-2422

Author: Asensio, J. Ferrer, Spezzano, S., Coudert, L. H., Lattanzi, V., Endres, C. P., Jørgensen, J. K., and Caselli, P.
Subjects: Astrophysics - Astrophysics of Galaxies
Abstract: The abundances of deuterated molecules with respect to their main isotopologue counterparts have been determined to be orders of magnitude higher than expected from the cosmic abundance of deuterium relative to hydrogen. The increasing number of singly and multi-deuterated species detections helps us to constrain the interplay between gas-phase and solid-state chemistry and to understand better deuterium fractionation in the early stages of star formation. Acetaldehyde is one of the most abundant complex organic molecules (COMs) in star-forming regions and its singly deuterated isotopologues have already been observed towards protostars. A spectroscopic catalogue for astrophysical purposes is built for doubly deuterated acetaldehyde CHD2CHO from measurements in the laboratory. Submillimetre wave transitions were measured for the non-rigid doubly deuterated acetaldehyde CHD2CHO displaying hindered internal rotation of its asymmetrical CHD2 methyl group. A line position analysis is carried out allowing us to reproduce 853 transition frequencies with a weighted root mean square standard deviation of 1.7, varying 40 spectroscopic constants. A spectroscopic catalogue for astrophysical purposes is built from the analysis results. Using this catalogue we were able to detect for the first time CHD2CHO towards the low-mass protostellar system IRAS 16293-2422 utilizing data from the ALMA Protostellar Interferometric Line Survey. The first detection of the CHD2CHO species allows for the derivation of its column density with a value of 1.3x10^15 cm^-2 and an uncertainty of 10-20%. The resulting D2/D ratio of ~20% is found to be coincident with D2/D ratios derived for other complex organic molecules towards IRAS~16293-2422, pointing at a common formation environment with enhanced deuterium fractionation.
Published: 2023
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47. Identifying meteorite droppers among the population of bright 'sporadic' bolides imaged by the Spanish Meteor Network during the spring of 2022

Author: Peña-Asensio, Eloy, Trigo-Rodríguez, Josep M., Rimola, Albert, Corretgé-Gilart, Marc, and Koschny, Detlef
Subjects: Astrophysics - Earth and Planetary Astrophysics
Abstract: The extraordinary weather conditions available between February and March 2022 over Spain have allowed us to analyze the brightest fireballs recorded by the monitoring stations of the Spanish Meteor Network (SPMN). We study the atmospheric flight of 15 large meteoroids to determine if they are meteorite dropper events to prepare campaigns to search for freshly fallen extraterrestrial material. We investigate their origins in the Solar System and their dynamic association with parent bodies and meteoroid streams. Employing our Python pipeline 3D-FireTOC, we reconstruct the atmospheric trajectory utilizing ground-based multi-station observations and compute the heliocentric orbit. In addition, we apply an ablation model to estimate the initial and terminal mass of each event. Using a dissimilarity criterion and propagating backward in time, we check the connection of these meteoroids with known complexes and near-Earth objects. We also calculate if the orbits are compatible with recent meteoroid ejections. We find that ~27% of these fireballs are dynamically associated with minor meteoroid streams and exhibit physical properties of cometary bodies, as well as one associated with a near-Earth asteroid. We identify two meteorite-producing events; however, the on-site search was unsuccessful. By considering that these fireballs are mostly produced by cm-sized rocks that might be the fragmentation product of much larger meteoroids, our findings emphasize the idea that the population of near-Earth objects is a source of near-term impact hazards, existing large Earth-colliding meteoroids in the known complexes., Comment: Accepted in MNRAS
Published: 2023
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48. Access to and quality of elective care: a prospective cohort study using hernia surgery as a tracer condition in 83 countries

Author: Dönmez, A Eylül, Goswami, Aakansha Giri, Raheja, Aashna, Bhadani, Aayush, El Kady, Abd Elrahman Safwat, Alniemi, Abdalaziz, Awad, Abdalkarim, Aladl, Abdalla, Younis, Abdalla, Alwali, Abdallah, Khalil, Abdallah, Mansour, Abdallah, Elkhouly, Abdallah Mohamed, Rashad Temerik, Abdallah, Hasan, Abdallatef, Chied, Abdelhafid, Abdraba, Abdelhamid, Hrora, Abdelmalek, Abdelshafi, Abdelrahman, Alwali, Abdelrahman, Maraqa, Abdelrahman, Ghaffar, Abdul, Chekfa, Abdul Jabar, Al Balushi, Abdul Majeed, Quddus, Abdul, Hammadieh, Abdul Rahman, Muntaka, Abdul-Jalilu Mohammed, Asekun, Abdulazeez, Alshahrani, Abdulaziz, Jowharji, Abdulaziz, Alshukre, Abdulbaset, Khair Etareig, Abdulhafid, Abubakar Abdulkarim, Abdulhafiz, Ashiru, Abdulhafiz, Alailesh, Abdulhamid, Al-Mallah, Abdullah, Baydoun, Abdullah, Chaudhry, Abdullah, Askin, Abdullah Emre, Almutairi, Abdulmjeed, Belkhair, Abdulmunem, Abdllah, Abdulrahman, Alhammali, Abdulrahman, Basalim, Abdulrahman, Abouelnagah, Abdulrahman Galal Mohamed Mostafa, Ghazal, Abdulrahman, Mohammed, Abdulrahman, Qasem, Abdulrahman, Anadani, Abdulrazak, Jimoh, Abdulrazaq, Lawal, Abdulrazzaq Oluwagbemiga, Khaity, Abdulrhman, Lawal, Abdulwahab, Elzoubi, Abdurrahim Esseid, Sheshe, Abdurrahman Abba, Cetişli, Abdurrahman Furkan, Oyedele, Abeeb, Aljahdali, Abeer, Aboelnasr, Abeer Gamal Elsyed, Demessie, Abel, Bhargava, Abhilasha, Sonkar, Abhinav Arun, Bavaharan, Abhirame, Khan, Abid, Campbell, Abigail, Oyelekan, Abimbola Adeola Akintunde, Okunlola, Abiodun Idowu, Ojewuyi, Abiodun, Ekerin, Abiola, Saleh, Abobakr, Khairy, Abouelatta, Muthunayagam, Abraham Benjamin, Botha, Abraham, Teshome Sahilemariam, Abraham, Nawawi, Abrar, Muhammad, Abubakar Bala, Dahiru, Abubakar, Yahaya, Abubakar, Abdelmalik, Abubaker, Anuar, Abul Akmal Arif, Ousseini, Adakal, Leon -Del- Angel, Adalberto, Frankel, Adam, Gyedu, Adam, Lim, Adam, Lukáč, Adam, Peckham-Cooper, Adam, Sabbah, Adam, Varga, Adam, Sanou, Adama, Issaka, Adamu, Ningi, Adamu, Yeshitila, Addis, Yingess, Addisu, Olugbami, Adebayo, Moses, Damola-Okesiji, Adebola, Lawal, Adedayo, Ojo, Adedoyin, Hashmi, Adeel, Fakoya, Adegbolahan, Ishola, Adegoke, Abiodun, Adekunle, Ajayi, Adekunle, Mouffokes, Adel, Bonelli, Adele, Adekoya, Adeleke, Akeem Aderogba, Adeleke, Özcan, Adem, Ayoade, Ademidun, Adeyeye, Ademola, Agbaje, Ademola, Talabi, Ademola, Ademuyiwa, Adesoji, Adewumiya, Adesoji, Ademuyiwa, Adesoji O, Aderounmu, Adewale, Adisa, Adewale, Oke, Adewale, Ragab, Adham, Alzadjali, Adil, Baksi, Aditya, Jayapalan, Aditya, Md Yunos, Adnan, Pisanu, Adolfo, Salazar, Adolfo, Salinas Barragan, Adrian Alberto, Fox, Adrian, Stollberg, Adrian, Franco, Adriana, Neves, Adriana, Vricheva, Adriana, Hodonou, Adrien Montcho, Aghayeva, Afag, Liaquat, Affifa, Alsultan, Afnan, Morad, Afnan, Kalidis, Afroditi Angella, Gkouniaroudi, Agathi, Karakosta, Agathi, Lovi, Agbenya, Yevide, Agossou Barthélémy, Duro, Agustin, Rodriguez Gonzalez, Agustin, Tariq, Ahbala, Abaidalla, Ahmad, Abuhammad, Ahmad, Abuhantash, Ahmad, Mansour, Ahmad Adel, Ahmad Zaidi, Ahmad Al Hafeez, Alahmad Alismael, Ahmad, Alayed, Ahmad, Alfarwan, Ahmad, Alhaj, Ahmad, Ali, Ahmad, Alroobi, Ahmad, Alsheikh, Ahmad, Alusef, Ahmad, Alzu'Bi, Ahmad, Kayali, Ahmad Amir, Bouhuwaish, Ahmad, Doghaim, Ahmad, El-Sherbiney, Ahmad, Ghazal, Ahmad, Ramly, Ahmad Nasir, Raza, Ahmad, Qureshi, Ahmad Uzair, Arnaout, Ahmad Yamen, Abdelhamid, Ahmed, Abuthaher, Ahmed, Adel, Ahmed, Ahmayda, Ahmed, Al-Mouahhed, Ahmed, Alagha, Ahmed, Albalawi, Ahmed, Albhaisi, Ahmed, Alrifaee, Ahmed, Azam, Ahmed, Barakat, Ahmed, Al-Hajjaj, Ahmed Basim Abed, Dawoud, Ahmed, El Shamarka, Ahmed, El-Bastwesy, Ahmed, Elghrieb, Ahmed, Elkhalifa, Ahmed, Elmosalamy, Ahmed, Elshazli Mahmoud, Ahmed, Montaser, Ahmed G., Gbeadese, Ahmed, Haty, Ahmed, K. 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Daniel, Montwedi, Daniel, Muñoz, Daniel, Patterson, Daniel, Reim, Daniel, Agbley, Daniel Yao Dodzie, Patiño García, Daniela Cristina, Di Pietrantonio, Daniela, Pais, Daniela, Rosado, Daniela, Tavares, Daniela, Alberti, Daniele, Fusario, Daniele, Massaro, Daniele, Paglione, Daniele, Pironi, Daniele, Kurochka, Daniil, Centonze, Danilo Corrado, Hackner, Danilo, Herrera, Danilo, Amangaliyev, Daniyar, Silva-Cano, Danny Wladimir, Chaudhry, Daoud, Palmisano, Dario, Ribero, Dario, Vukosav, Dario, Misca, Darius, Lowen, Darren, Rattray, Darren, Walia, Darshanjit Singh, Maan, Darvesh, Muyenzi, Daryle, Verdi, Daunia, Bardsley, David, Reyes Rodríguez, David Estuardo, Fra Corral, David, Garcia López De Goicoechea, David, Gavit, David, Gómez, David, Idowu, David, Konkin, David, Labadah, David Kplorla Kekeli, Liu, David, Merlini, David, Mitchell, David, Moro-Valdezate, David, Osifo, David, Proud, David, Ridder, David, Gobatti, Davide, Muschitiello, Davide, Pertile, Davide, Zulian, Davide, Mengiste, Dawit, Mikami, Dean, Mohanty, Debajyoti, Chatterjee, Debarghya, Komolafe, Deborah Olaitan, Scotto Di Carlo, Deborah, Wright, Deborah, Rahme, Deema, Talreja, Deep Parkash, Jain, Deepak, Rajput, Deepak, Singh, Deepak, Anbu, Deepika, Ibrahim, Dena, Phom, Denchu, Hili, Denise, Osei, Dennis Broni, Daary, Dennis, Kyeremeh, Dennis, Shen, Dennis, Uymaz, Derya Salim, Cianflocca, Desiree, Ashitey, Desmond, Evripidou, Despo, Papageorgouli, Despoina, Kaushal, Devesh, Abeysirigunawardana, Dewmi, Dugar, Dharmendra, Mallik, Dhiraj, Ghosh, Dhruva, Houmran, Diaa, Abdulrahman, Diala, Pantoja Pachajoa, Diana Alejandra, Cardona Gomez, Diana Catalina, Fenner, Diana, Gonzalez, Diana Samantha, Siriwardena, Diana, Garcés Palacios, Diana Sofía, Stoian, Diana, Zuikyte, Diana, Sosa Méndez, Dianne Alitzá, Wickramarathna, Dickson, Mutter, Didier, Palma Portillo, Diego Andrés, Chavez Fernandez, Diego, Córdova García, Diego, Enjuto, Diego, Giulitti, Diego, Sasia, Diego, Visconti, Diego, Yiğit, Dilara, George, Dilip, Rabaia, Dima, Georgiev, Dimitar, Hadzhiev, Dimitar, Alexandrou, Dimitrios, Balalis, Dimitrios, Giakoustidis, Dimitrios, Manatakis, Dimitrios K., Korkolis, Dimitrios, Lytras, Dimitrios, Massaras, Dimitrios, Moris, Dimitrios, Politis, Dimitrios, Sampanis, Dimitrios, Schizas, Dimitrios, Tsiardas, Dimitrios, Vardakostas, Dimitrios, Kotsaris, Dimitris, Khattab, Dina Hesham, M. Awad, Dina, Alrokh, Dina Sami, Schippers, Dina, Waleed, Dina, Salinovic, Dinko, Gonçalves Múrias Gomes, Diogo Miguel, Silva, Diogo, Vaz Acosta, Diogo, Morton, Dion, Panagopoulos, Dionisios, Kelgiorgi, Dionysia, Dellaportas, Dionysios, Prevezanos, Dionysios, Joshi, Dipti, Ozal, Direm, Yigit, Direnc, Chimkaomasiri, Divine, Jabbar, Diya, Nepogodiev, Dmitri, Belekar, Dnyanesh, Abdalaziz, Doaa, Abunemer, Doaa, Attia, Doaa, Elkafrawy, Doaa, Dimitrov, Dobromir, Pignatelli, Domenica, Merlicco, Domenico, Soriero, Domenico, Zerbo, Domenico, Atouguia, Domingas, Fairbrass, Dominic, T. Enti, Donald, Venskutonis, Donatas, Rukavina, Dora, Caruso, Dorena, Herappe, Dorihela, Lee, Dorinda Norbetha, Ofosuhene, Doris, Hajela, Apoorva, Badwan, Basem, Kulkarni, Datta, Dhawan, Deep, Dhillon, Jeevanjit, Mehmood, Manzer, Mahmood, Namrah, Nikam, Narendra, Ramchandani, Radhakrishna, Thind, Ravinder Singh, Riazhussain, D Hafiz, Maqsood, Saliha, Alalawi, Yousef, Tyagi, Harshdeep, Kshirsagar, Shivani, Ahmed, Hisham, Juan Carlos, Luna Cydejko, Kone, Dramane, Omar, Duaa, Alves, Duarte Gil, Subasinghe, Duminda, Ommi, Durgesh, Joshiba, Durshney, Chakarov, Dzhevdet, Arkoh, Ebenezer Ameyaw, Frimpong-Manso, Ebenezer, Ada, Ece, Lincango, Eddy P., Lozada Hernandez, Edgard Efren, Hodžić, Edin, Di Marco, Edith, Baccalini, Edoardo Andrea, Baldini, Edoardo, González Marín, Eduardo, Gutierrez, Eduardo, Sepúlveda, Eduardo, Dainius, Edvinas, Zhang, Edward, Yenli, Edwin Mwintiereh Ta-Ang, Antoniou, Efstathios, Kapasakis, Efstathios, Baili, Efstratia, Poulios, Efthymios, Kubiliute, Egle, Osaze, Ehioghae, Afeikhena, Ehis, Elshennawy, Eiad, Athanasopoulou, Eirini, Synekidou, Eirini, Ekaladze, Eka, Tampaki, Ekaterini Christina, Adam, Elaf, Adel Hamdoun Aziz, Elaf, Yousuf, Elamin, Gialamas, Eleftherios, Spartalis, Eleftherios, Bedzhanyan, Elen, Toma, Elena Adelina, Daukšaitė, Elena, Desiato, Elena, Dvivedi, Elena, Hadzhieva, Elena, Martí Cuñat, Elena, Montalbán Martínez, Elena, Montanari, Elena, Signaroli, Elenasofia, Efremidou, Eleni, Gavriil, Eleni, Karakeke, Eleni, Mavrodimitraki, Eleni, Papamattheou, Eleni, Jose, Elenza, Cianci, Eleonora, Ciccioli, Eleonora, Daleva, Eleonora, Locci, Eleonora, Lori, Eleonora, Silanos, Eleonora, Ayala, Elí, Bankart, Eliana, Brolese, Eliane, Efstathiou, Elias, Salloum, Elias, Colak, Elif, Terzi, Elif Didem, Ametefe, Elikem, Cagigal Ortega, Elima Pilar, Donnarumma, Elio, Mina, Elisa, Reitano, Elisa, Wallner, Elisabeth, Moggia, Elisabetta, Betz, Elise, Kontis, Elissaios, Anestiadou, Elissavet, Gimson, Eliza, Lun, Elizabeth, Fraser, Elizabeth, Li, Elizabeth, Torres De Anda, Elizabeth Magaly, Murphy, Elizabeth Mary Ann, O'Connell, Elizabeth, Redondo, Elizabeth, Lun, Elizabeth Weng Yan, Francis, Ella, Haiden, Elmar, Hamed, Elmonzir, Alkhalifa, Elmustafa, Dexter, Eloise, Daketsey, Elorm, Setsoafia, Elorm, Mohamed, Elsagad, Mohammed, Elsamoual, Hegab, Elsayed, Ay, Elvin, Adinolfi, Elvira, Mbanzabugabo, Elvis, Chin, Elynn, Ahmed, Emad Ali, Younes, Eman, Basile, Emanuela, Gessa, Emanuela, Pontecorvi, Emanuele, Romairone, Emanuele, Hatangimana, Eméry, Ndizeye, Emile, Ciofic, Emilia, Dijan, Emilio, López-Negrete Cueto, Emilio, Baker, Emily, Reid, Emily, Schmidt, Emily, Alić, Emir, Bičakčić, Emir, Agbowada, Emma, Colton, Emma, Downing, Emma, Haege, Emma, O'Neill, Emma, Roussos, Emmanouel, Nachelleh, Emmanuel Aadereyir, Adebunmi, Emmanuel, Obiesie, Emmanuel Ahuizechukwu, Akakpo, Emmanuel Bismark, Konlan, Emmanuel Dammigu Francis, Nwangwu, Emmanuel Ifeanyi, Kafui Ayodeji, Emmanuel, Ofori, Emmanuel Owusu, Spanoudakis, Emmanuel, Abate, Emmanuele, Balik, Emre, Bozdağ, Emre, Bozkurt, Emre, Karabulut, Emre Cagri, Ozoran, Emre, Tunçcan, Emre, Tuzuner, Emre, Halilović, Emsad, Alabed, Enaam, Zidan, Enas, Hodžić, Enes, Aybar, Engin, Yildirim, Engin Okan, Wong, Enoch, Yhoshu, Enono, Bisogno, Enrica, Andolfi, Enrico, Ferri, Enrico, Potenza, Enrico, Spalice, Enrico, Volpin, Enrico, González, Enrique, Downes, Eoin, Gallo, Erdachew, Kamer, Erdinc, Naidoo, Eressa, Erginöz, Ergin, Bara, Eric, Irungu, Eric, García-Villegas, Eric Yusif, Mazzotta, Erica, Monati, Erica, Chan, Erick, Gómez Mejía, Erika, Dylja, Eris, Somuncu, Erkan, Yavuz, Erkan, Begunić, Ernes, Margelis, Ernest, Osei, Ernest Owusu, Saitoglou, Ertzan, Agastra, Ervis, Mazumdar, Eshan, Soyer Güldoğan, Esra, Abu Siam, Esra'A, Abdelbaset, Esraa, Abdu, Esraa, Adel Mahmod Sultan, Esraa, Nubi Mohamed, Esraa Gamal, Abuobaida Banaga Hag El Tayeb, Essam Eldien, Ali, Essraa, Page-Taylor, Estelle, Marra, Ester, Garcia Santos, Esther Pilar, Elsheikh, Ethar, Unal, Ethem, Tan, Eugene, De Leo, Eugenio, Borges, Eva, Gáspár, Éva, Ruiz-Daum, Eva, Apostolopoulos, Evaggelos, Samara, Evangelia, Barkolias, Evangelos, Fradelos, Evangelos, Hopping, Eve, Romo Ascencio, Evelia Veronica, Sosa Ferreira, Ever David, Shestakov, Evgenii, Tyurina, Evgenya, Hristova, Evguenia, Efthymiou, Evripidis, Tokidis, Evripidis, Harrison, Ewen, Dontoh, Ewurama Akroma, Mansour, Eyad, Yeshialem, Eyosiyas, Dabbagh, Ezeddin, Amer, Ezzeldin, Manasci, Fabiana, Gomes, Fabio, Medas, Fabio, d'Acapito, Fabrizio, Vassallo, Fabrizio, Haddad, Fadi, Elhabishi, Fadwa, Akhtar, Fahad, Tauheed, Fahad, Al Abbood, Fahd, Gareb, Fahed, Ghazali, Fairuz, Alnazawi, Faisal, Ondago, Faith, Rasoaherinomenjanahary, Fanjandrainy, Wiese, Fanny, González Ponce, Fanny Yesenia, Georgiades, Fanourios, Ali, Farah, Galley, Fareeda, Huda, Farhanul, Amir, Farhat Naaz, Ashraf, Fariha, Alfarsi, Faris, Ayasra, Faris, Ali, Farman, Mahmoud, Faten, Aliskander, Fater, Tahir Lwdie, Fathea, Buyuker, Fatih, Aguilar Del Castillo, Fátima, Mohammed Daoud, Fatima Ahmed, Alowjaly, Fatima, Oni, Fatima, Rauf, Fatima, Elkhafeefi, Fatimah, Hourri, Fatine, Monib, Fatma A., Alshreef, Fatma, Benghalbon, Fatma, Ntirenganya, Faustin, Ashraf, Fauziyah, Chahrour, Fayez, Ahmad, Fazal, Parray, Fazlul Qadir, Philips, Febi, Campus, Federica, Di Marco, Federica, Ferraina, Federica, Frongia, Federica, Maffeis, Federica, Natali, Federica, Pederiva, Federica, Scolari, Federica, Tofani, Federica, Marin, Federico Alberto Niccolò, Biolchini, Federico, Cappellacci, Federico, Corronca, Federico, Mazzola, Federico, Suldrup, Federico, Nyarko, Felicia, Casas J, Felipe, Zapata, Felipe, Aigner, Felix, Alakaloko, Felix, Amoako, Felix, Camacho, Felix, Hammett, Felix, Kuubetersob B. N, Felix, Alahmad, Feras, Alnimri, Feras, Haddad, Feras, Gool, Ferhana, Castro, Fernanda, Diaz, Fernanda, Lucero, Fernanda, Vovola, Fernanda, Mahnic, Fernando, Mercado Sanchez, Fernando, Prieto La Noire, Fernando, Soggiu, Fiammetta, Tsige, Fikreab, Brzeszczyński, Filip, Rudisch, Filip, Valente Costa Pinto, Filipa, Ramalho De Almeida, Filipe, Banchini, Filippo, Palomino Escalante, Fiorella, Fadzlullah, Fitri, Terefe, Fitsum, Sulo, Fjorenta, Ciccarone, Flavia, Tirelli, Flavio, Krämer, Florian, Grama, Florin, Spanos, Foivos, Solimene, Folco, Akinwande, Foluso, Osman, Forzia, Stefou, Foteini, Kyramargios, Fotios, Stavratis, Fotios, Alassani, Fousseni, Ascari, Francesca, Cammelli, Francesca, D'Agostino, Francesca, Tropeano, Francesca Paola, Peters, Francesca, Ré, Francesca, Brucchi, Francesco, Casti, Francesco, Coratti, Francesco, Ferrara, Francesco, Floris, Francesco, Izzo, Francesco, Maffei, Francesco, Palmieri, Francesco, Pata, Francesco, Porcelli, Francesco, Selvaggi, Francesco, Velluti, Francesco, Mulita, Francesk, Bello, Francis, Caiquo, Francis, Dossou, Francis, Eshun, Francis Junior, Opoku Twene, Francis, Tierenye, Francis, Quayson, Francis William, Romo Rosales, Francisco David, Ibañez Ortiz, Francisco, León Frutos, Francisco Javier, Redondo Calvo, Francisco Javier, Silva Rivera, Francisco Javier, Barbosa Camacho, Francisco José, Bujalance Cabrera, Francisco Manuel, Ruescas, Francisco, Irakiza, Franck Fanon, Corvatta, Franco, Pascual, Franco Raúl, Roviello, Franco, Roodt, Francois, Gyamfi, Frank Enoch, Olaniru, Frank, Owusu, Frank, Bader, Franz G., Anzinger, Franz-Xaver, Agbodo, Fred David Anku, Ris, Frederic, Agbemafoh, Frederick Mawuli, Afonso, Frederico, Nazareth, Frederico, Berrevoet, Frederik, Hounde, Fréjus, Demiral, Furkan, Hassooni, Furqan Ridha Hassooni, Kafa, Gabi, Cárdenas Rivera, Gabriel, Ntwari, Gabriel, Szydlo Shein, Gabriel, Ambriz González, Gabriela, Nita, Gabriela Elisa, Bellio, Gabriele, Moitzi, Gabriele, Urdang, Gabriella, Marom, Gad, Gallo, Gaetano, Luglio, Gaetano, Poillucci, Gaetano, Singh, Gagandeep, Saletta, Gaia, Abouelnagah, Galal, Yarovenko, Galina, Kazobinka, Gallina, Ahmed, Gamal Mutwakil Gamal, Rahman, Ganiyu Adebisi, Smith, Garett, Pillai, Gargi, Saxena, Garima, Gbessi, Gaspard, Nkunguzi, Gaston, Jalal, Gaurav, Chillarge, Gauri, Singh, Gautam, Mevognon, Gedeon, Getachew, Gedion, George, Gejoe, De La Peña González, Gema, Martínez Izquierdo, Gema, Grande, Gennaro, Birikorang, Geoffrey, Weber, Georg F., Singer, Georg, Ansong, George, Bashour, George, Brown, George Darko, Hneino, George, Kavalieratos, George, Kenchadze, George, Nagy, George, Pappas Gogos, George, Skroubis, George, Waiyaki, George, Cox, Georgia, Zeringa, Georgia, De Wee, Georgin, Hart, Georgina, Bekakos, Georgios, Fragulidis, Georgios, Kapogiannatos, Georgios, Karakaidos, Georgios, Kokkinos, Georgios, Kostoulas, Georgios, Koukoulis, Georgios, Peros, Georgios, Rados, Georgios, Tsoulfas, Georgios, Verras, Georgios-Ioannis, Berger, Geraint, Adoro, Gerard Ayuka, Chamoso Mialdea, Gerardo, Palmieri, Gerardo, Procaccini, Gerardo, Steenkamp, Gerhard, Viscido, Germán Rodrigo, Dajti, Gerti, Alemayehu, Getachew, Seyfu, Gezachew, Birqeeq, Ghada, Alsheikh, Ghadeer, Alrayyes, Ghaith, El Hunjul, Ghalib Nashaat, Zaza, Ghayath, Matroud, Ghazlah, Alhadwah, Ghena, Maltinti, Gherardo, Awais, Ghina, Shamsi, Ghina, Calini, Giacomo, Carganico, Giacomo, Zanus, Giacomo, Canu, Gian Luigi, Mendiola, Gian, Ibero Casadiego, Giana Pamela, Cocorullo, Gianfranco, Baronio, Gianluca, Pellino, Gianluca, Zanni, Gianluca, Poto, Gianmario Edoardo, Gravante, Gianpiero, Aduroja, Gideon, Almogy, Gidon, Bond-Smith, Giles, Natchagande, Gilles, Bechara, Gio, Brachini, Gioia, Riccioli, Giordana, Ercolani, Giorgio, Farris, Giorgio, Giraudo, Giorgio, Mammolo, Giovanna, Pavone, Giovanna, Sgarzini, Giovanna, Aprea, Giovanni, Fonsi, Giovanni Battista, Boroni, Giovanni, De Angeli, Giovanni, De Palma, Giovanni Domenico, Emiliani, Giovanni, Grava, Giovanni, Guercio, Giovanni, De Carlo, Giulia, Del Corpo, Giulia, Duranti, Giulia, Galatioto, Giulia, Grassi, Giulia, Graziano, Giulia, Marini, Giulia Maria Francesca, Munzi, Giulia, Tarantino, Giulia, Borda-Luque, Giuliano, Pellicano', Giuseppe Antonino, Canonico, Giuseppe, Carollo, Giuseppe, Ietto, Giuseppe, Palomba, Giuseppe, Pascarella, Giuseppe, Salamone, Giuseppe, Sica, Giuseppe, Sorrentino, Giuseppe, Orlando, Giuseppina, Pignata, Giusto, Pisarevi, Givi, Akcakoca, Gizem, Owusu, Godfred, Yohanna Abrak, Godwin, Kurtoglu, Gokalp Kagan, Kurtoglugk, Gokalp Kagan, Alıcı, Gökhan, Kurtoglu, Goktug Mert, Delgado Hernandez, Gonzalo, Augustin, Goran, Bhat, Gowhar Aziz, Sundaram Venkatesan, Gowtham, Chang, Grace, Eke, Grace, Lee, Grace, Massarra, Grace, Travaglini, Grazia, Scialandrone, Grazisa, Stavrou, Gregor A., Di Franco, Gregorio, Charalambous, Gregory, Christodoulidis, Gregory, Kouraklis, Gregory, Goodwin, Gregory Richard, Devidze, Grigol, Fialho, Guilherme, Santos, Guilherme, Cabezudo, Guillermo, García-Santos, Guillermo, Pou, Guillermo, Romero Reyna, Guillermo, Yanowsky-Reyes, Guillermo, Ozyuksel, Gul, Karadeniz Cakmak, Guldeniz, Kucuk, Gultekin Ozan, Bulbuloglu, Guney Cem, Sarp, Guray, Kaur, Gurleen, Nibogora, Guy Darcy, Hamdan, Gymar, Ogundipe, Habeeb, Yunes, Habib, Ayesh, Hadeel, Al Atassi, Hadi, Jalilehvand, Hadis, Masalma, Hafez, Jafarkhan, Hafis, Shahid, Hafiz Huzaifa, Younus, Hafsa, Al-Derume, Hail, Shames, Haitam, Mimouni, Haithem Ahmed, Aldare, Hajar, Odah Bashi, Hajar Omar, Abusnina, Hajer, Altounsi, Hajir, Qayum, Hajra, Baysal, Hakan, Bolukbasi, Hakan, Yigitbas, Hakan, Alkhatib, Hala, Afzal, Haleema, Mftah, Halima, Oyinlola, Halimah, Tümer, Haluk, Dolo, Hamadoun, Braham, Hamdi, Ozsahin, Hamdi, Abu-Arish, Hamdoon, Al-Aamri, Hamed, Fadlalmola, Hammad Ali, Abu Obead, Hamza, Al-Fahel, Hamza, Al-Zoubi, Hamza, Asaad, Hamza, Ejaz, Hamza, Jaber, Hamza, Bhatti, Hamza Waqar, Mohammadi Sardoo, Hamzeh, Farhat, Hana, Idheiraj, Hanadi, Zwaraa, Hanady, Al Sohabi, Hanan, Basharat, Hanan, Said, Hanan, Al-Abdallat, Haneen, Foad, Haneen, Daaboul, Hanen, Al Qadhi, Hani, Elhallaq, Hani, Alhusaini, Hanin, Lidbetter, Hannah, Reilly, Hannah, Moya- Ambriz, Hannia Betzabeth, Lederhuber, Hans, Fehrer, Hans-Jörg, Xiao, Haotian, Iswariah, Harish, Kaur, Harmeena, Cheema, Harnoor Kaur, Foda, Haroun, Chauhan, Harpreet, Kaur, Harpreet, Sagar, Harry, Unwin, Harry, Kaur, Harsharan, Panga, Harshavardhan, Gupta, Harshit, Prabhakar, Harshit Kumar, Anand, Harshitha, Pahwa, Harvinder Singh, Abbadi, Hasan, Amoudi, Hasan, Zaini, Hasan Hadi Zaini, Škiljo, Hasan, Miyasika, Hasangi, Altabbaa, Hashem, Haj Freej, Hasn, Abdelazim, Hassan, Habiba, Hassan, Kamal, Hassan, Sabir, Hassan, Zaigham, Hassan, Pehlivan, Hatice, Telci, Hatice, Abuobaida, Hayat, Tetley, Heather, Taher, Heba, Aguado López, Héctor, Askarpour, Hedyeh, Sherif Farouk Ahmed Hassan, Heidi, Devesa, Helena, Arbogast, Helmut, Nuñez Del Barrio, Henar, Abiyere, Henry, Delacave, Henry, Rice, Henry E., Pleass, Henry, Bradly, Hera, 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Rugambwa, Jean Paul, Jordaan, Jean- Jacques, Razafindrahita, Jeannie Ba, Do, Jee Eun, Senavirathna, Jeewantha, Kalyanapu, Jeffrey A, Chan, Jeffrey, Ofori, Jeffrey, Otote, Jeffrey, Akiely, Jehad, Cassiano Neves, Jelena, Gillingham, Jemima, Herrera Batres, Jenifer Olga María, Ezeh, Jennifer, Okei, Jennifer, Vu, Jennifer, Guevara, Jenny, Siu, Jenny, Rolinger, Jens, Skaff, Jeolle, Uys, Jernelle, Makama, Jerry Godfrey, Barklimore, Jessica, Dei-Asamoa, Jessica, Jahjah, Jessica, Jones, Jessica, Ng, Jessica, Ricardo, Jéssica, Schembri Higgans, Jessica, You, Jessica, Annan, Jessie, Aguilar, Jesus Antonio, Pizarro Lozano, Jesús, Lim, Jia Hui, Zhu, Jiang, Wang, Jianxue, Abbasy, Jibran, Ugwu, Jideofor, Rathod, Jignesh, Albalushi, Jihan, Najajra, Jinan, Fu, Jing Hui, Tefay, Joan Sia Tan, Domingues, Joana Cristina, Simoes, Joana FF, Figueiredo, Joana, Fontaínhas, Joana, Frazão, Joana, Marques Antunes, Joana, Simoes, Joana, Marx, Joanna Naemi, Dias-Ferreira, João, Fernandes, João, Mendes, João, Pinho, João, Ribeiro, João, Vaz, João, Dominguez, Joaquina, Abutu John, Job, Chen, Joe Jun Qiao, Enaholo, Joel, Alaji, Joelle, Miller, Johanna, Binder, Johannes, Daleku, John, Katogiritis, John, Khoury, John, Anyorigiya, John Noah, Reilly, John, Abebrese, John Tabiri, Ahale, Johnny Lordson, Tabora-Zepeda, Johnny, Barrutia Leonardo, Jon, Demma, Jonathan Abraham, Hong, Jonathan, Chejfec-Ciociano, Jonathan Matias, Oppong, Jonathan, Quansah, Jonathan, Sutcliffe, Jonathan, Taiwo, Jones, Nyamekye - Baidoo, Joojo, Prat-Ortells, Jordi, Dongmo, Jordy, Kleeff, Jorg, Jimenez Flores, Jorge Alberto, Pellecer Cano, Jorge Bernardo, Chóliz, Jorge, Giubi Bobeda, Jorge Eduardo, Escartin, Jorge, Febré, Jorge, Gass, Jörn-Markus, Calvache, Jose A, Guzman Barba, Jose Aldo, Gutiérrez Gómez, José Alonso, Calvache, Jose Andres, Acevedo Parrales, José Danilo, Orozco Navarro, José Esteban, Viñas, José Federico, Gomez, José, Goncalves-Nobre, Jose Guilherme, Valenzuela, José Ignacio, Garcia Galocha, Jose Luis, 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Marcella, Pisano, Marcello, Doniquian, Marcelo Alejandro, Martínez Bareiro, Marcelo Nicolás, Pagani, Marcelo, Scortechini, Marcelo, Carvalho, Márcia, Sánchez Audelo, Marco Antonio, Brizzolari, Marco, Ceresoli, Marco, De Prizio, Marco, Amisano, Marco Francesco, Gramellini, Marco, Marcianò, Marco, Mariani, Marco, Milone, Marco, Montagna, Marco, Piccino, Marco, Santos, Marco, Dyer, Marcus, Kang, Marcus, Mahadi, Mardhiana, Zawadzki, Marek, Yinusa, Margaret, Bernardo, Margarida, Nunes Luís, Margarida, Gambelli, Margherita, Flint, Margot, Aggelidou, Maria, Bequis, Maria Agustina, Sotiriou, Maria Aikaterini, Ñañez, Maria Alejandra, Tahir, Maria Ambreen, Gascón Domínguez, María Ángeles, Asimakidou, Maria, Mourato, Maria Beatriz, Blanco, Maria, Christou, Maria, Coronas Soucheiron, Maria, Pignanelli, Maria Costanza, Kalaydjian, María Cristina, Martí-Ejarque, Maria del Mar, Olmedo Reinoso, María Del Mar, Cebollero, María Del Pilar, Derattani, Maria, Gama Caldeira, Maria Do Carmo, Drogouti, Maria, Gonzalez-Gonzalez, Maria Elena, Muñoz Fernández, María Elena, Muriel, María Emilia, Duran, María Eugenia, Zarate Casas, María Fernanda, Florou, Maria, Piacentini, Maria Gaia, Seixo, Maria Inês, Bellini, Maria Irene, Peña Soria, Maria Jesús, Martínez, María José, Medina, Maria José, Rueda Medécigo, María José, Karakeke, Maria, Kausar, Maria, Kyriazi, Maria, Marqueta De Salas, Maria, Modolo, Maria Marta, Mateu, Maria, Mavri, Maria, El Ghoul Miliotou, Maria Melina, Moreno Gijon, Maria, Papadoliopoulou, Maria, Proclamà, Maria Pia, Picciochi, Maria, Reis, Maria, Rennis, Maria, D'Anna, Maria Rosa, Ruffoli, Maria, Ruiz Soriano, María, Sánchez Ramirez, Maria, Sánchez-Rubio, María, Schüler, Maria, Sotiropoulou, Maria, Barrio Renteria, Maria Teresa, Tsopozidi, Maria, Vasconcelos, Maria, Facchino, Maria Vittoria, Wikar, Maria, Aguilera-Arevalo, Maria-Lorena, Abdu, Mariam, Asarbakhsh, Mariam, Elmiesiry, Mariam, Ashong, Marian Esi, Gomes, Mariana, Capuano, Marianna, Lill, Marianne, Nieto Galvan, 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Nathan, Michael, Maclean, Michael, Nortey, Michael, Pellen, Michael, Pham, Michael, Pitiakoudis, Michael, Singh, Michael Prodip, Spartalis, Michael, Van Der Colf, Michael, Wilson, Michael, Billis, Michail, Karanikas, Michail, Papamichail, Michail, Vailas, Michail, Kisielewski, Michał, Kusiński, Michał, Nycz, Michał, Święch, Michał, Fagbayimu, Micheal, Adamina, Michel, Fiogbe, Michel, Prudhomme, Michel, Angelucci, Michela, Campanelli, Michela, Cricrì, Michele, Grande, Michele, Manigrasso, Michele, Scopelliti, Michele, George, Michelle, Mozel, Michelle, Galasyuk, Mick, Chevallay, Mickael, Giuliano, Micol, Dobón Rascón, Miguel Ángel, Fernandez Romero, Miguel Angel, García Ureña, Miguel Ángel, Zaragoza Mendieta, Miguel Ángel, Bejarano Serrano, Miguel, Brito, Miguel, Calderon, Miguel, Jurado Román, Miguel, Palas, Miguel, Li Valencia, Miguel Roberto, Sebastián-Mendoza, Miguel-Julián, Muresan, Mihai-Stefan, Slavchev, Mihail, Agapov, Mikhail, Milentijević, Milica, Catterall, Millie, 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Abosedra, Mohammed, Sarker, Mohammed Abu Kawsar, Abudabbous, Mohammed, Abuwarda, Mohammed, Elgak, Mohammed Ahmed, Al Hinai, Mohammed, Al Zebda, Mohammed, Al-Shehari, Mohammed, Alharthi, Mohammed, Ali, Mohammed, Ismael Alamin, Mohammed Ali, Alqadasi, Mohammed, Alshanwani, Mohammed, Alshehri, Mohammed, Asaad, Mohammed, Bashir, Mohammed, Bohlala, Mohammed, Meghaizerou, Mohammed El Amine, Albanna, Mohammed Emad Hashem, Ghunaim, Mohammed, Goga, Mohammed, Hajhamad, Mohammed, Hamada Takrouney, Mohammed, Hammoda, Mohammed, Hamoud Almahly, Mohammed, Muragi, Mohammed, Mohammed, Mohammed Mustafa Hassan, Obaid, Mohammed, Omar, Mohammed, Said, Mohammed, Salah, Mohammed, Saleh Khatab, Mohammed, Aliyu, Mohammed Salele, Shakhshir, Mohammed, Sheriff, Mohammed, Tageldin, Mohammed, Abdelfattah, Mohanad, Daher, Mohanad, Lotfy, Mohanad, Alqedrh, Mohannad, Nasani, Mohannad, Mohd Shah, Mohd Shahrulsalam, Madany, Mohie El-Din Mostafa, Mobolaji-Ojibara, Mojisola, Nkogatse, Moleseng, Alazabi, Mona, Gupta, 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López, Sara, Giovampietro, Sara, Ismail, Sara, Kamari, Sara, Lauricella, Sara, Marzorati, Sara, Mohammed, Sara, Moschella, Sara, Mostafa Yassin, Sara, Patrocínio, Sara, Massa, Sara Tiziana, Vertaldi, Sara, Abdelmohsen, Sarah, Al Sharie, Sarah, Barbosa Castelo Branco, Sarah, Bowman, Sarah, Condron, Sarah, Elfurdag, Sarah, Ellouzy, Sarah, Fennelly, Sarah, Mansour, Sarah, Molfino, Sarah, Qwyder, Sarah, Rennie, Sarah, Robinson, Sarah, Segnitome, Sarah, Staight, Sarah, Yassin, Sarah, Alsibai, Sareyah, Khan, Sarfaraz, Khurana, Sarita, Rafiq, Sarmad, Malhi, Sarvpreet Singh, Dognia, Satchmo, D A, Sathiafrey, Babu, Satia, Subbiah Nagaraj, Satish, Meena, Satya Prakash, Vasquez, Saul, Bradulskis, Saulius, Mikalauskas, Saulius, Laura, Saura García, Verhage, Savannah Skye, Simeonidis, Savvas, Sarwary, Sayed Haschmatullah, Naidu, Sayuri, Schimpke, Scott, Davis, Sean, Stevens, Sean, Sierra, Sebastian, Dos Santos, Sebastiano, Strachan, Sebastien, Bektas, Sebnem, Atupra, Sedinam Adjoa Asiedua, Kreid, Sedra, Bugren, Seeraj, Saudí-Moro, Sef, Ashini, Sehar, Aboseif, Seif, Abdul Rahman, Seif-Aldin, Karim, Seiver, Öztürk, Selen, Akuffo, Selma, Awad, Selmy, Srishankar, Selvaratnam, Tobome, Sèmèvo Romaric, Malek, Sepand, Quartarone, Serafino, Grimaldi, Serena, Guarriello, Serena, Kalenga, Serge, Katorkin, Sergei, Trujillo Ponce, Sergio Adrian, Villeda, Sergio Alejandro, Intini, Sergio Giuseppe, Vázquez-Sánchez, Sergio Jiram, Salido, Sergio, Valeri, Sergio, Yilmaz, Serhan, Meriç, Serhat, Bensalem, Serien, Sucu, Serkan, Yılmaz, Serkan, Uludağ, Server Sezgin, Torres Rodríguez, Servio Tulio, Ooi, Sett, Luciano, Severino, Houndji, Sèwou Francklin Albert, Agordjor, Seyram, Ward, Sezar, Samardali, Shaden, Altoume, Shadi, Mahfoud, Shafik, Razaq, Shahad, Khan, Shahbano, Husanov, Shahboz, Ahmed, Shaheer, Islam, Shahnoor, Waqar, Shahzad Hussain, Kumaran, Shairashree, Magrhi, Shamsa, Zhang, Shane, Kashyap, Shankarsai, Karandikar, Sharad, Sundaramurthy, Sharada, Chowdhury, Sharfuddin, Jayasekara, Sharitha, Laura, Sharon, Shanker, Shashwat, Ababneh, Shatha, Gilbert, Shaun, Kenworthy, Shaunna, Ng, Shawn Hong Ming, Mackenzie, Shawn, Salindera, Shehnarz, Khattak, Shehrbano, Loke, Sheih Nee, Manzoor, Sheikh Viqar, Alwardi, Sheikha, Allam, Shereen, Tawfik, Sherifa, Francis, Shikha, Cai, Shirley, Dindyal, Shiva, Pandya, Shivangi, Chopra, Shreya, Ingley, Shreya, Kulkarni, Shrirang, Kosna, Shuba, Nayak, Shubhalaxmi, Ahuja, Shubham, Hariharan, Shubhang, Karuppusamy Krishnasamy, Shyam, Khare, Siddhant, Handa, Siddhartha, Amin Omar Alsiddig, Siddig, Alqurashi, Siddiga, Al-Tahayneh, Sief-Addeen, Sibiya, Silindokuhle, Perretta, Silvana, Ibarra Camargo, Silvia Alejandra, Montisci, Silvia, Mungo, Silvia, Puddu, Silvia, Severi, Silvia, Agudelo Mendoza, Silvia Valentina, Makkai-Popa, Silviu Tiberiu, Boyes, Simon, Monkhouse, Simon, Stock, simon, Alberti, Simona, Meneghini, Simona, Giudici, Simone, Guadagni, Simone, Birolo, Simone Lorenzo, Novello, Simone, Oliveira, Simone, Gumede, Simphiwe, Dhole, Simran, Budhwani, Simran Saleem, Ramjit, Sinead, Yumurtacilar, Sinem, Mahendra, Sirigi Naga, Abeykoon, Sithira, Moh Pauzi, Siti Farhan, Rajendra, Sittampalam, Sundararajan, Siva, Gananadha, Sivakumar, Kamarajah, Sivesh K, Marawu, Siyasanga, Basu, Sk, Hassan, Sleman, Reddy, Snigdha Mettu, Anaya Sanchez, Sofia, Gaspar Reis, Sofia, Gomez, Sofía, Gamba, Sofia Lucia, Pimentel Morais, Sofia, Ashry, Soha, Abdullateef, Sohaila, Bandyopadhyay, Soham, Samadi, Soheil, Pathan, Sohilkhan R., Lakew, Solomon, Basu, Somprakas, Ohri, Sonali, Alonso Marcos, Sonia, Amoza Pais, Sonia, Fortuna Martins, Sónia, Gill, Sonia, Matthiess, Sonia, Sabbatini, Sonia, Soto Schütte, Sonia, Engel, Sophie, Eam, Sothseyhakmonique, Botaitis, Sotirios, Lawani, Souliath, Jamil, Soumaya, Kondpan, Sourav, Oum, Sovannarith, Govender, Sovishnee, Christodoulou, Spyridon, Davakis, Spyridon, Vernadakis, Spyridon, Gkogkos, Spyros, Gobishangar, Sreekanthan, Suresh, Sreelakshmi, Vembar, Sridhar, M, Srikanth, Abdelrasoul Elnour 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Abubasheer, Tareq, Alhusban, Tariq, Yılmaz, Tarık Emre, Aloqaili, Tasneem, Aldirawi, Tayef, Karahasanoğlu, Tayfun, Gülşen, Taygun, Jemal, Tebarek, Nadeem, Tehmina, Singh, Tejinder Paul, Alinger, Temsula, Longkumer, Temsutoshi, Lo, Terence, Gimenez Maurel, Teresa, Uprak, Tevfik Kıvılcım, Petropoulou, Thalia, Rawther, Thampi, Techapongsatorn, Thawin, Manickam, Thendral, Padioti, Theodora, Kozonis, Theodoros, Sidiropoulos, Theodoros, Tsirlis, Theodoros, Theodosopoulos, Theodosios, Hessou, Thierry Kinnongni, Uiyapat, Thitapon, Agyen, Thomas, Harris, Thomas, Hugh, Thomas J, Jorgensen, Thomas W., Theivendrampillai, Thrshegan, Pham, Thuy Vy, Branco, Tiago, Nagwamutse, Tijjani Nasiru, Tony V, Tina, Devabalan Koil, Titus, Pilia, Tiziana, Abdulmola, Tmador Mahmed Ali, Oyeyemi, Tobiloba, Kebede, Tolera, Ibarra-Hurtado, Tomás Ramón, Reichelt, Tomas, Gach, Tomasz, Stefura, Tomasz, Wojewoda, Tomasz, Soric, Tomislav, Risteski, Toni, Tridip, Tridip Dutta Baruah, Yotsov, Tsanko, Doma Bhutia, Tshering, Girma, Tsion, Kwan, Tsun Yu, Ivanov, Tsvetomir, Iahmo, TT, Ashkar, Tuleen, Mabogoane, Tumi, Olobatoke, Tunde, Sholadoye, Tunde T., Mishra, Tushar Subhadarshan, Parker, Tyla, Ezomike, Uchechukwu, Dilibe, Uchenna, Kumbhar, Uday, Una, Uduak-Abasi, Grossi, Ugo, Ezidiegwu, Ugochukwu, Edith, Ugwuoke, Daspal, Ujjwal, Kalu, Ukoha Agwu, Dietz, Ulrich, Ronellenfitsch, Ulrich, Wirth, Ulrich, Abdullah, Umar, Rivolta, Umberto, Jayarajah, Umesh, Kanyan Kassim, Umu-Hera, Govindan, Unnikrishnan, Fernandes, Urânia, Akram, Usman, Mohammed Bello, Usman, Omara, Usra, Naidoo, Uvarasen, Mahendravarman, Vaishnaivy, Negoita, Valentina Madalina, Mariottini, Valentina, Murzi, Valentina, Zucchini, Valentina, Agbakwuru, Valentine, Armenta Tapia, Valeria Estefania, Gentilino, Valerio, Borgogni, Vanessa, Ng, Vanessa, Wolfschluckner, Vanessa, Silvestri, Vania, Žufić, Vanja, Gunasaegaram, Varman, Kamalathevan, Vasan, Pillay, Vasanthan, Neykov, Vasil, Kalles, Vasileios, Mousafeiris, Vasileios, Papadopoulos, Vasileios, Tsaousis, Vasileios, Tselepidis, Vasileios, Vougas, Vasileios, Georgilaki, Vasiliki, Nikolaou, Vasiliki, Themelidi, Vasiliki, Manchev, Vassil, Ioannou, Veatriki, Jha, Vedant Shekhar, Dragisic, Vedran, Sutharshan, Vengadasalam, Alonso, Veronica, Brocco, Veronica, Ongil Rodríguez, Verónica, Schirinzi, Veronica, Budyakova, Veronika, Naunova, Vesna, Panduro-Correa, Vicky, Ruiz López, Víctor Andrés, Bill, Victor, Dassah, Victor, Gonzabay, Víctor Eduardo, Etwire, Victor, Modekwe, Victor, Serna-Alarcon, Victor, De Donato, Victor Ugo, Duque Mallén, Victoria, Liu, Victoria, Sharma, Vidushi, Kumar, Vijaya, Muralidharan, Vijayaragavan, Kakotkin, Viktor, Enemuo, Vincent, Kudoh, Vincent, Osoka, Vincent, Siepaal, Vincent, Granata, Vincenza, Dinuzzi, Vincenza Paola, Lizzi, Vincenzo, Ricchiuti, Vincenzo, Mosca, Vinicio, Kanna D, Vinoth, Nair, Vipin Venugopal, Ledda, Virginia, Michael, Vishal, Singh, Vishavdeep, Govindasamy, Vishendran, Kollengode, Viswanathan V, Giordano, Vittoria, Morinelli, Vittoria, Lin, Vivian, Cuk, Vladica, Cijan, Vladimir, Çalik, Volkan, Bakshi, Vrushank, Ten, Vyacheslav, Ratheesh, Vysakh, Alsado, Wael, Mayo, Wafik, Yang, Wah, Rehman, Wajeeh Ur, Abbas, Walaa, Al-Khyatt, Waleed, Mabood, Waleed, Santucci, Walter, Yew, Wan Ting, Tahir, Warda, De Silva, Warusha Dhammika Dulantha, Wijenayake, Wasantha, Almadhoun, Waseem J.N., Alhroub, Wasef, Ebrahim, Wesam, Jabłoński, Wiktor, Krawczyk, Wiktor, Bhatti, William, Lai, William Kwan Ho, Petrushnko, Wilson, Afedo, Wisdom, Kasetsermwiriya, Wisit, Serednicki, Wojciech, Wysocki, Wojciech, Zerefa, Wondwossen Amtataw, Vagena, Xanthoula, Tarrado, Xavier, Papazarkadas, Xenofon, Po, Xiang Yuen, Ouadi, Yacine, Myla, Yacob, Haido, Yacoub, Hasan, Yafea, Karataş, Yağmur, Carpio Colmenares, Yahaira, Galvañ Félix, Yaiza, Balogun, Yakub Lekan, Maktabi, Yaman, Nerabani, Yaman, Fulgence, Yamuremye, De Silva, Yannick, Asar, Yara, Samer Morsy, Yara, Ghaleb, Yasameen Saif Saeed Mohammed, Vashishth, Yash, M S, Yashas, Manickchund, Yashoda, Sakaray, Yashwant, Kara, Yasin, Tosun, Yasin, Zwain, Yasir, Farag, Yasmeen, Jedidi, Yasmine, Seada, Yasmine, Aldebasi, Yasser, Ashour, Yasser, Badr, Yassin, Sarpong, Yaw, Alawneh, Yazan, Aung, Yee Lay, Orabi, Yehia, Lam, Yick Ho, Şen, Yigit Kaan, Koyluoglu, Yilmaz Onat, Huang, Yining, Mintz, Yoav, Perez, Yocarli, Chamara, Yohan, Melkamu, Yohannes, Maestre González, Yolanda, Dean, Yomna, Metaferia, Yonas Yilma, Malki, Yosra, Mohamed, Younis, A. Omar, Yousef, Alhammoud, Yousef, Allaoua, Yousef, Tanas, Yousef, El Okazy, Youssef, Kerolous, Youssef, Mohamed, Youssef, Al-Junaidi, Youssuf, Lakdawala, Yousuf, Lu, Yuann, Asano, Yukio, Altinel, Yuksel, Aktimur, Yunus Emre, Fishman, Yuri, Kudryavcev, Yurii, Tandoğan, Yusuf Iskender, Razafimandimby, Yves Michaël, Adofo-Asamoah, Yvonne, Şenol, Zafer, Odeh, Zahra, Benamrouche, Zahra Rayane, Alkhaier, Zahraa, Al-Sheikh Ali, Zaid, Zaher, Zain Aldin, Alnajjar, Zaina, Al-Balushi, Zainab, Alkhuzaie, Zainab, Khraim, Zakaria, Toutounji, Zakaria, Djama, Zakarya, Farraj, Zamil, Shah, Zamir Ahmad, Khan, Zara, Khan, Zarnigar, Abo Alarous, Zayn Alabden, Asaad, Zaynab, Demetrashvili, Zaza, Lorenc, Zbigniew, Brekalo, Zdrinko, Hannouneh, Zein Alabdin, Robertson, Zelda, Bady, Zeyad, Durna, Zeynep, Wong, Zhen Yu, Fozo, Zien Alabdin, Klib, Zienab, Chin, Ziling, Tamou, Zime Farid, Johnson, Zina, Shabello, Ziyad, Orzeszko, Zofia, Aljalabi, Zohal, Al-Azher El-Hamel, Zohour, Karampotaki, Zoi Rafaila, Valera Sanchez, Zoraida, Matkovic, Zoran, Azhar, Zubair, Qureshi, Zubaria, Correa López, Zulema Margarita, Balciscueta, Zutoia, Musilová, Zuzana, Katusic, Zvonimir, Osama, Zyad, and Dauksa, Zygimantas
Published: 2024
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49. A Historical Perspective to Decrypt AMR in Mycobacterium: From Classic Discoveries to Genomics Approaches

Author: Calvet-Seral, Juan, Crespo-Yuste, Estefanía, Mendoza-Losana, Alfonso, Gonzalo-Asensio, Jesús, Soni, Vijay, editor, and Akhade, Ajay Suresh, editor
Published: 2024
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50. Identifying Missing Sensor Values in IoT Time Series Data: A Weight-Based Extension of Similarity Measures for Smart Manufacturing

Author: Schultheis, Alexander, Malburg, Lukas, Grüger, Joscha, Weich, Justin, Bertrand, Yannis, Bergmann, Ralph, Serral Asensio, Estefanía, Hartmanis, Juris, Founding Editor, van Leeuwen, Jan, Series Editor, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Kobsa, Alfred, Series Editor, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Nierstrasz, Oscar, Series Editor, Pandu Rangan, C., Editorial Board Member, Sudan, Madhu, Series Editor, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Weikum, Gerhard, Series Editor, Vardi, Moshe Y, Series Editor, Goos, Gerhard, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Recio-Garcia, Juan A., editor, Orozco-del-Castillo, Mauricio G., editor, and Bridge, Derek, editor
Published: 2024
Full Text: View/download PDF

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