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This paper proposes a data preparation process for managing real-world kinematic data and detecting fishing vessels. The solution is a binary classification that classifies ship trajectories into either fishing or non-fishing ships. The data used are characterized by the typical problems found in classic data mining applications using real-world data, such as noise and inconsistencies. The two classes are also clearly unbalanced in the data, a problem which is addressed using algorithms that resample the instances. For classification, a series of features are extracted from spatiotemporal data that represent the trajectories of the ships, available from sequences of Automatic Identification System (AIS) reports. These features are proposed for the modelling of ship behavior but, because they do not contain context-related information, the classification can be applied in other scenarios. Experimentation shows that the proposed data preparation process is useful for the presented classification problem. In addition, positive results are obtained using minimal information., Comment: Sensors 2020

This paper develops a smooth model identification and self-learning strategy for dynamic systems taking into account possible parameter variations and uncertainties. We have tried to solve the problem such that the model follows the changes and variations in the system on a continuous and smooth surface. Running the model to adaptively gain the optimum values of the parameters on a smooth surface would facilitate further improvements in the application of other derivative based optimization control algorithms such as MPC or robust control algorithms to achieve a combined modeling-control scheme. Compared to the earlier works on the smooth fuzzy modeling structures, we could reach a desired trade-off between the model optimality and the computational load. The proposed method has been evaluated on a test problem as well as the non-linear dynamic of a chemical process.

This work shows a study about the structure of the cycles contained in a Minimal Strong Digraph (MSD). The structure of a given cycle is determined by the strongly connected components (or strong components, SCs) that appear after suppressing the arcs of the cycle. By this process and by the contraction of all SCs into single vertices we obtain a Hasse diagram from the MSD. Among other properties, we show that any SC conformed by more than one vertex (non trivial SC) has at least one linear vertex (a vertex with indegree and outdegree equal to 1) in the MSD (Theorem 1); that in the Hasse diagram at least one linear vertex exists for each non trivial maximal (resp. minimal) vertex (Theorem 2); that if an SC contains a number $\lambda$ of vertices of the cycle then it contains at least $\lambda$ linear vertices in the MSD (Theorem 3); and, finally, that given a cycle of length $q$ contained in the MSD, the number $\alpha$ of linear vertices contained in the MSD satisfies $\alpha \geq \lfloor (q+1)/2 \rfloor$ (Theorem 4).

Cough is a protective reflex conveying information on the state of the respiratory system. Cough assessment has been limited so far to subjective measurement tools or uncomfortable (i.e., non-wearable) cough monitors. This limits the potential of real-time cough monitoring to improve respiratory care. Objective: This paper presents a machine hearing system for audio-based robust cough segmentation that can be easily deployed in mobile scenarios. Methods: Cough detection is performed in two steps. First, a short-term spectral feature set is separately computed in five predefined frequency bands: [0, 0.5), [0.5, 1), [1, 1.5), [1.5, 2), and [2, 5.5125] kHz. Feature selection and combination are then applied to make the short-term feature set robust enough in different noisy scenarios. Second, high-level data representation is achieved by computing the mean and standard deviation of short-term descriptors in 300 ms long-term frames. Finally, cough detection is carried out using a support vector machine trained with data from different noisy scenarios. The system is evaluated using a patient signal database which emulates three real-life scenarios in terms of noise content. Results: The system achieves 92.71% sensitivity, 88.58% specificity, and 90.69% Area Under Receiver Operating Characteristic (ROC) curve (AUC), outperforming state-of-the-art methods. Conclusion: Our research outcome paves the way to create a device for cough monitoring in real-life situations. Significance: Our proposal is aligned with a more comfortable and less disruptive patient monitoring, with benefits for patients (allows self-monitoring of cough symptoms), practitioners (e.g., assessment of treatments or better clinical understanding of cough patterns), and national health systems (by reducing hospitalizations)., Comment: 12 pages, 11 figures, 5 tables

Astronomers have found more than a dozen planets transiting 10-40 million year old stars, but even younger transiting planets have remained elusive. A possible reason for the lack of such discoveries is that newly formed planets are not yet in a configuration that would be recognized as a transiting planet or cannot exhibit transits because our view is blocked by a protoplanetary disk. However, we now know that many outer disks are warped; provided the inner disk is depleted, transiting planets may thus be visible. Here we report the observations of the transiting planet IRAS 04125+2902 b orbiting a 3 Myr, 0.7 M$_\odot$, pre-main sequence star in the Taurus Molecular Cloud. IRAS 04125+2902 hosts a nearly face-on (i $\sim$ 30$^\circ$) transitional disk and a wide binary companion. The planet has a period of 8.83 days, a radius of 10.9 R$_\oplus$ (0.97R$_J$), and a 95%-confidence upper limit on its mass of 90M$_\oplus$ (0.3M$_J$) from radial velocity measurements, making it a possible precursor of the super-Earths and sub-Neptunes that are commonly found around main-sequence stars. The rotational broadening of the star and the orbit of the wide (4", 635 AU) companion are both consistent with edge-on orientations. Thus, all components of the system appear to be aligned except the outer disk; the origin of this misalignment is unclear. Given the rare set of circumstances required to detect a transiting planet at ages when the disk is still present, IRAS 04125+2902 b likely provides a unique window into sub-Neptunes immediately following formation., Comment: Initial version submitted to Nature. Stellar, and hence planetary, parameters slightly differ from final version. Published version available at https://www.nature.com/articles/s41586-024-08123-3

In this work we present the results of a measurement campaign carried out in the Mediterranean sea aimed at characterizing the underwater acoustic channel in a wideband at ultrasonic frequencies centered at 80 kHz with a width of 96 kHz, covering two octaves from 32 to 128 kHz. So far, these type of wideband measurements are not found in the literature. Periodic orthogonal frequency division multiplexing (OFMD) sounding signals using Zadoff-Chu sequences have been specially designed for this purpose. The collected data has been post-processed to estimate the time-variant impulse and frequency responses and relevant parameters for system design like the time coherence, bandwidth coherence, delay spread and Doppler bandwidth. The statistical behavior of the channel gain random fluctuation has also been analyzed. This information has been extracted for both the global channel and each path separately. The wide bandwidth of the measurements have allowed the characterization of the channel in a scarcely explored ultrasonic band with an accuracy that is far beyond what is reported in previous works., Comment: 13 pages, 15 figures

The aim of this study is to implement a method to remove ambient noise in biomedical sounds captured in auscultation. We propose an incremental approach based on multichannel non-negative matrix partial co-factorization (NMPCF) for ambient denoising focusing on high noisy environment with a Signal-to-Noise Ratio (SNR) <= -5 dB. The first contribution applies NMPCF assuming that ambient noise can be modelled as repetitive sound events simultaneously found in two single-channel inputs captured by means of different recording devices. The second contribution proposes an incremental algorithm, based on the previous multichannel NMPCF, that refines the estimated biomedical spectrogram throughout a set of incremental stages by eliminating most of the ambient noise that was not removed in the previous stage at the expense of preserving most of the biomedical spectral content. The ambient denoising performance of the proposed method, compared to some of the most relevant state-of-the-art methods, has been evaluated using a set of recordings composed of biomedical sounds mixed with ambient noise that typically surrounds a medical consultation room to simulate high noisy environments with a SNR from -20 dB to -5 dB. Experimental results report that: (i) the performance drop suffered by the proposed method is lower compared to MSS and NLMS; (ii) unlike what happens with MSS and NLMS, the proposed method shows a stable trend of the average SDR and SIR results regardless of the type of ambient noise and the SNR level evaluated; and (iii) a remarkable advantage is the high robustness of the estimated biomedical sounds when the two single-channel inputs suffer from a delay between them.

Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. Experiments have tested a variety of accuracy and beyond accuracy quality measures, including prediction, recommendation of ordered and unordered lists, novelty, and diversity. Results show each convenient matrix factorization model attending to their simplicity, the required prediction quality, the necessary recommendation quality, the desired recommendation novelty and diversity, the need to explain recommendations, the adequacy of assigning semantic interpretations to hidden factors, the advisability of recommending to groups of users, and the need to obtain reliability values. To ensure the reproducibility of the experiments, an open framework has been used, and the implementation code is provided., Comment: 14 pages, 5 figures, 3 tables

Neural collaborative filtering is the state of art field in the recommender systems area; it provides some models that obtain accurate predictions and recommendations. These models are regression-based, and they just return rating predictions. This paper proposes the use of a classification-based approach, returning both rating predictions and their reliabilities. The extra information (prediction reliabilities) can be used in a variety of relevant collaborative filtering areas such as detection of shilling attacks, recommendations explanation or navigational tools to show users and items dependences. Additionally, recommendation reliabilities can be gracefully provided to users: "probably you will like this film", "almost certainly you will like this song", etc. This paper provides the proposed neural architecture; it also tests that the quality of its recommendation results is as good as the state of art baselines. Remarkably, individual rating predictions are improved by using the proposed architecture compared to baselines. Experiments have been performed making use of four popular public datasets, showing generalizable quality results. Overall, the proposed architecture improves individual rating predictions quality, maintains recommendation results and opens the doors to a set of relevant collaborative filtering fields., Comment: 9 pages, 7 figures

This paper has taken into advantage the relationship between Fuzzy Relation Equations (FRE) and Concept Lattices in order to introduce a procedure to reduce a FRE, without losing information. Specifically, attribute reduction theory in property-oriented and object-oriented concept lattices has been considered in order to present a mechanism for detecting redundant equations. As a first consequence, the computation of the whole solution set of a solvable FRE is reduced. Moreover, we will also introduce a novel method for computing approximate solutions of unsolvable FRE related to a (real) dataset with uncertainty/imprecision data.

Extended multi-adjoint logic programming arises as an extension of multi-adjoint normal logic programming where constraints and a special type of aggregator operator have been included. The use of this general aggregator operator permits to consider, for example, different negation operators in the body of the rules of a logic program. We have introduced the syntax and the semantics of this new paradigm, as well as an interesting mechanism for obtaining a multi-adjoint normal logic program from an extended multi-adjoint logic program. This mechanism will allow us to establish technical properties relating the different stable models of both logic programming frameworks. Moreover, it makes possible that the already developed and future theory associated with stable models of multi-adjoint normal logic programs can be applied to extended multi-adjoint logic programs.

The current accelerated expansion of the Universe remains ones of the most intriguing topics in modern cosmology, driving the search for innovative statistical techniques. Recent advancements in machine learning have significantly enhanced its application across various scientific fields, including physics, and particularly cosmology, where data analysis plays a crucial role in problem-solving. In this work, a non-parametric regression method with Gaussian processes is presented along with several applications to reconstruct some cosmological observables, such as the deceleration parameter and the dark energy equation of state, in order to contribute with some information that helps to clarify the behavior of the Universe. It was found that the results are consistent with $\Lambda$CDM and the predicted value of the Hubble parameter at redshift zero is $H_{0}=68.798\pm 6.340(1\sigma) \text{ km}\text{ s}^{-1}\text{ Mpc}^{-1}$., Comment: 21 pages, 19 figures, Universe 10 (2024) 12

This paper studies the solvability of the max-product fuzzy relation equations in which a negation operator is considered. Specifically, the residuated negation of the product t-norm has been introduced in these equations in order to increase the flexibility of the standard fuzzy relation equations introduced by Sanchez in 1976. The solvability and the set of solutions of these bipolar equations have been studied in different scenarios, depending on the considered number of variables and equations.

Bipolar fuzzy relation equations arise when unknown variables together with their logical negations appear simultaneously in fuzzy relation equations. This paper gives a characterization of the solvability of bipolar max product fuzzy (relation) equations with the standard negation. In addition, some properties associated with the existence of the greatest/least solution or maximal/minimal solutions are shown, when these (relation) equations are solvable. Different examples are included in order to clarify the developed theory.

Bipolar fuzzy relation equations arise as a generalization of fuzzy relation equations considering unknown variables together with their logical connective negations. The occurrence of a variable and the occurrence of its negation simultaneously can give very useful information for certain frameworks where the human reasoning plays a key role. Hence, the resolution of bipolar fuzzy relation equations systems is a research topic of great interest. This paper focuses on the study of bipolar fuzzy relation equations systems based on the max-product t-norm composition. Specifically, the solvability and the algebraic structure of the set of solutions of these bipolar equations systems will be studied, including the case in which such systems are composed of equations whose independent term be equal to zero. As a consequence, this paper complements the contribution carried out by the authors on the solvability of bipolar max-product fuzzy relation equations.

A fundamental issue about installation of photovoltaic solar power stations is the optimization of the energy generation and the fault detection, for which different techniques and methodologies have already been developed considering meteorological conditions. This fact implies the use of unstable and difficult predictable variables which may give rise to a possible problem for the plausibility of the proposed techniques and methodologies in particular conditions. In this line, our goal is to provide a decision support system for photovoltaic fault detection avoiding meteorological conditions. This paper has developed a mathematical mechanism based on fuzzy sets in order to optimize the energy production in the photovoltaic facilities, detecting anomalous behaviors in the energy generated by the facilities over time. Specifically, the incorrect and correct behaviors of the photovoltaic facilities have been modeled through the use of different membership mappings. From these mappings, a decision support system based on OWA operators informs of the performances of the facilities per day, by using natural language. Moreover, a state machine is also designed to determine the stage of each facility based on the stages and the performances from previous days. The main advantage of the designed system is that it solves the problem of "constant loss of energy production", without the consideration of meteorological conditions and being able to be more profitable. Moreover, the system is also scalable and portable, and complements previous works in energy production optimization. Finally, the proposed mechanism has been tested with real data, provided by Grupo Energ\'etico de Puerto Real S.A. which is an enterprise in charge of the management of six photovoltaic facilities in Puerto Real, C\'adiz, Spain, and good results have been obtained for faulting detection.

Formal concept analysis (FCA) is a useful mathematical tool for obtaining information from relational datasets. One of the most interesting research goals in FCA is the selection of the most representative variables of the dataset, which is called attribute reduction. Recently, the attribute reduction mechanism has been complemented with the use of local congruences in order to obtain robust clusters of concepts, which form convex sublattices of the original concept lattice. Since the application of such local congruences modifies the quotient set associated with the attribute reduction, it is fundamental to know how the original context (attributes, objects and relationship) has been modified in order to understand the impact of the application of the local congruence in the attribute reduction.

Attribute and size reductions are key issues in formal concept analysis. In this paper, we consider a special kind of equivalence relation to reduce concept lattices, which will be called local congruence. This equivalence relation is based on the notion of congruence on lattices, with the goal of losing as less information as possible and being suitable for the reduction of concept lattices. We analyze how the equivalence classes obtained from a local congruence can be ordered. Moreover, different properties related to the algebraic structure of the whole set of local congruences are also presented. Finally, a procedure to reduce concept lattices by the new weaker notion of congruence is introduced. This procedure can be applied to the classical and fuzzy formal concept analysis frameworks.

Multi-adjoint logic programming is a general framework with interesting features, which involves other positive logic programming frameworks such as monotonic and residuated logic programming, generalized annotated logic programs, fuzzy logic programming and possibilistic logic programming. One of the most interesting extensions of this framework is the possibility of considering a negation operator in the logic programs, which will improve its flexibility and the range of real applications. This paper introduces multi-adjoint normal logic programming, which is an extension of multi-adjoint logic programming including a negation operator in the underlying lattice. Beside the introduction of the syntax and semantics of this paradigm, we will provide sufficient conditions for the existence of stable models defined on a convex compact set of a euclidean space. Finally, we will consider a particular algebraic structure in which sufficient conditions can be given in order to ensure the unicity of stable models of multi-adjoint normal logic programs.

We investigate the effect of pressure on the carbon dioxide (CO$_{2}$) hydrate-water interfacial free energy along its dissociation line using advanced computer simulation techniques. In previous works, we have determined the interfacial energy of the hydrate at $400 \,\text{bar}$ using the TIP4P/ice and TraPPE molecular models for water and CO$_{2}$, respectively, in combination with two different extensions of the Mold Integration technique [J. Chem. Phys. 141, 134709 (2014)]. Results obtained from computer simulation, $29(2)$ and $30(2)\,\text{mJ/m}^{2}$, are found to be in excellent agreement with the only two measurements that exist in the literature, $28(6)\,\text{mJ/m}^{2}$ determined by Uchida et al. [J. Phys. Chem. B 106, 8202 (2002)] and $30(3)\,\text{mJ/m}^{2}$ by Anderson et al. [J. Phys. Chem. B 107, 3507 (2002)]. Since the experiments do not allow to obtain the variation of the interfacial energy along the dissociation line of the hydrate, we extend our previous studies to quantify the effect of pressure on the interfacial energy at different pressures. Our results suggest that there exists a correlation between the interfacial free energy values and the pressure, i.e., it decreases with the pressure between $100$ and $1000\,\text{bar}$. We expect that the combination of reliable molecular models and advanced simulation techniques could help to improve our knowledge of the thermodynamic parameters that control the interfacial free energy of hydrates from a molecular perspective., Comment: 7 pages, 4 figures

Obtaining accurate forecasts for the evolution of epidemic outbreaks from deterministic compartmental models represents a major theoretical challenge. Recently, it has been shown that these models typically exhibit trajectories' degeneracy, as different sets of epidemiological parameters yield comparable predictions at early stages of the outbreak but disparate future epidemic scenarios. Here we use the Doi-Peliti approach and extend the classical deterministic SIS and SIR models to a quantum-like formalism to explore whether the uncertainty of epidemic forecasts is also shaped by the stochastic nature of epidemic processes. This approach allows getting a probabilistic ensemble of trajectories, revealing that epidemic uncertainty is not uniform across time, being maximal around the epidemic peak and vanishing at both early and very late stages of the outbreak. Our results therefore show that, independently of the models' complexity, the stochasticity of contagion and recover processes poses a natural constraint for the uncertainty of epidemic forecasts.

In this paper, the solubility of carbon dioxide (CO$_{2}$) in water along the isobar of 400 bar is determined by computer simulations using the well-known TIP4P/Ice force field for water and TraPPE model for CO$_{2}$. In particular, the solubility of CO$_{2}$ in water when in contact with the CO$_{2}$ liquid phase, and the solubility of CO$_{2}$ in water when in contact with the hydrate have been determined. The solubility of CO$_{2}$ in a liquid-liquid system decreases as temperature increases. The solubility of CO$_{2}$ in a hydrate-liquid system increases with temperature. The two curves intersect at a certain temperature that determines the dissociation temperature of the hydrate at 400 bar ($T_{3}$). We compare the predictions with the $T_{3}$ obtained using the direct coexistence technique in a previous work. The results of both methods agree and we suggest 290(2)K as the value of $T_{3}$ for this system using the same cutoff distance for dispersive interactions. We also propose a novel and alternative route to evaluate the change in chemical potential for the formation of hydrate along the isobar. The new approach is based on the use of the solubility curve of CO$_{2}$ when the aqueous solution is in contact with the hydrate phase. It considers rigorously the non-ideality of the aqueous solution of CO$_{2}$, providing reliable values for driving force for nucleation of hydrates in good agreement with other thermodynamic routes used. It is shown that the driving force for hydrate nucleation at 400 bar is larger for the methane hydrate than for the carbon dioxide hydrate when compared at the same supercooling. We have also analyzed and discussed the effect of the cutoff distance of the dispersive interactions and the occupancy of CO$_{2}$ on the driving force for nucleation of the hydrate., Comment: 25 pages, 19 figures

Averaged local bond order parameters based on spherical harmonics, also known as Lechner and Dellago order parameters, are routinely used to determine crystal structures in molecular simulations. Among different options, the combination of the $\overline{q}_{4}$ and $\overline{q}_{6}$ parameters is one of the best choices in the literature since allows one to distinguish, not only between solid- and liquid-like particles but also between different crystallographic phases, including cubic and hexagonal phases. Recently, Algaba et al. [J. Colloid Interface Sci. 623, 354, (2022)] have used the Lechner and Dellago order parameters to distinguish hydrate- and liquid-like water molecules in the context of determining the carbon dioxide hydrate-water interfacial free energy. According to the results, the preferred combination previously mentioned is not the best option to differentiate between hydrate- and liquid-like water molecules. In this work, we revisit and extend the use of these parameters to deal with systems in which clathrate hydrates phases coexist with liquid phases of water. We consider carbon dioxide, methane, tetrahydrofuran, nitrogen, and hydrogen hydrates that exhibit sI and sII crystallographic structures. We find that the $\overline{q}_{3}$ and $\overline{q}_{12}$ combination is the best option possible between a large number of possible different pairs to distinguish between hydrate- and liquid-like water molecules in all cases., Comment: 18 pages, 8 figures

In this work, we determine the dissociation line of the nitrogen (N$_2$) hydrate by computer simulation using the TIP4P/Ice model for water and the TraPPE force field for N$_2$. We use the solubility method proposed recently by some of us to evaluate the dissociation temperature of the hydrate at different pressures, from 500 to 1500 bar. Particularly, we calculate the solubility of N$_2$ in the aqueous solution when it is in contact with a N$_2$-rich liquid phase and when in contact with the hydrate phase via planar interfaces as functions of temperature. Since the solubility of N$_2$ decreases with temperature in the first case and increases with temperature in the second case, both curves intersect at a certain temperature that determines the dissociation temperature at a given pressure. We find a good agreement between the predictions obtained in this work and the experimental data taken from the literature in the range of pressures considered in this work. From our knowledge of the solubility curves of N$_2$ in the aqueous solution, we also determine the driving force for nucleation of the hydrate, as a function of temperature, at different pressures. In particular, we use two different thermodynamic routes to evaluate the change in chemical potential for hydrate formation. Although the driving force for nucleation slightly decreases (in absolute value) when the pressure is increased, our results indicate that the effect of pressure can be considered negligible in the range of pressures studied in this work. To the best of our knowledge, this is the first time the driving force for nucleation of a hydrate that exhibits crystallographic structure sII, along its dissociation line, is studied from computer simulation., Comment: 15 pages, 9 figures. arXiv admin note: text overlap with arXiv:2408.03257

In this work, the tetrahydrofuran (THF) hydrate-water interfacial free energy is determined at $500\,\text{bar}$, at one point of the univariant two-phase coexistence line of the THF hydrate, by molecular dynamics simulation. The Mold Integration-Host methodology, an extension of the original Mold Integration technique to deal with hydrate-fluid interfaces, is used to calculate the interfacial energy. Water is described using the well-known TIP4P/Ice model and THF is described using a rigid version of the TraPPE model. We have recently used the combination of these two models to accurately describe the univariant two-phase dissociation line of the THF hydrate, in a wide range of pressures, from computer simulation [J. Chem. Phys. 160, 164718 (2024)]. The THF hydrate-water interfacial free energy predicted in this work is compared with the only experimental data available in the literature. The value obtained, $27(2)\,\text{mJ/m}^{2}$, is in excellent agreement with the experimental data taken from the literature, $24(8)\,\text{mJ/m}^{2}$. To the best of our knowledge, this is the first time that the THF hydrate-water interfacial free energy is predicted from computer simulation. This work confirms that the Mold Integration technique can be used with confidence to predict solid-fluid interfaces of complex structures, including hydrates that exhibit sI and sII crystallographic structures., Comment: 11 pages, 6 figures

In this work, we determine the dissociation line of the nitrogen (N$_{2}$) hydrate by computer simulation using the TIP4P/Ice model for water and the TraPPE force field for N$_{2}$. This work is the natural extension of our previous paper in which the dissociation temperature of the N$_2$ hydrate has been obtained at $500$, $1000$, and $1500\,\text{bar}$ [\emph{J. Chem. Phys.} \textbf{159}, 224707 (2023)] using the solubility method and assuming single occupancy. We extend our previous study and determine the dissociation temperature of the N$_2$ hydrate at different pressures, from $500$ to $4500\,\text{bar}$, taking into account single and double occupancy of the N$_{2}$ molecules in the hydrate structure. We calculate the solubility of N$_2$ in the aqueous solution, as a function of temperature, when it is in contact with a N$_{2}$-rich liquid phase and when in contact with the hydrate phase with single and double occupancy via planar interfaces. Both curves intersect at a certain temperature that determines the dissociation temperature at a given pressure. We observe a negligible effect of the occupancy on the dissociation temperature. Our findings are in very good agreement with the experimental data taken from the literature. We have also obtained the driving force for nucleation of the hydrate as a function of the temperature and occupancy at several pressures. As in the case of the dissociation line, the effect of the occupancy on the driving force for nucleation is negligible. To the best of our knowledge, this is the first time that the effect of the occupancy on the driving force for nucleation of a hydrate that exhibits sII crystallographic structure is studied from computer simulation., Comment: 15 pages, 13 figures

The Universe is shaped as a web-like structure, formed by clusters, filaments, and walls that leave large volumes in between named voids. Galaxies in voids have been found to be of a later type, bluer, less massive, and to have a slower evolution than galaxies in denser environments (filaments and walls). However, the effect of the void environment on their stellar population properties is still unclear. We aim to address this question using 118 optical integral field unit datacubes from the Calar Alto Void Integral-field Treasury surveY (CAVITY), observed with the PMAS/PPaK spectrograph at the 3.5m telescope at the Calar Alto Observatory (Almer\'ia, Spain). We used the non-parametric full spectral fitting code STARLIGHT to estimate their stellar population properties: stellar mass, stellar mass surface density, age, star formation rate (SFR), and specific star formation rate (sSFR). We analysed the results through the global and spatially resolved properties. Then, we compared them with a control sample of galaxies in filaments and walls from the CALIFA survey, matched in stellar mass and morphological type. Key findings include void galaxies having a slightly higher half-light radius (HLR), lower stellar mass surface density, and younger ages across all morphological types, and slightly elevated SFR and sSFR (only significant enough for Sas). Many of these differences appear in the outer parts of spiral galaxies in voids (HLR > 1), which are younger and exhibit a higher sSFR, indicative of less evolved discs. This trend is also found for early-type spirals, suggesting a slower transition from star-forming to quiescent states in voids. Our analysis indicates that void galaxies, influenced by their surroundings, undergo a more gradual evolution, especially in their outer regions, with a more pronounced effect for low-mass galaxies., Comment: 24 pages, 22 figures, 5 tables. Accepted for publication in A&A. Updated references list

Acoustic local positioning systems (ALPSs) are an interesting alternative for indoor positioning due to certain advantages over other approaches, including their relatively high accuracy, low cost, and room-level signal propagation. Centimeter-level or fine-grained indoor positioning can be an asset for robot navigation, guiding a person to, for instance, a particular piece in a museum or to a specific product in a shop, targeted advertising, or augmented reality. In airborne system applications, acoustic positioning can be based on using opportunistic signals or sounds produced by the person or object to be located (e.g., noise from appliances or the speech from a speaker) or from encoded emission beacons (or anchors) specifically designed for this purpose. This work presents a review of the different challenges that designers of systems based on encoded emission beacons must address in order to achieve suitable performance. At low-level processing, the waveform design (coding and modulation) and the processing of the received signal are key factors to address such drawbacks as multipath propagation, multiple-access interference, nearfar effect, or Doppler shifting. With regards to high-level system design, the issues to be addressed are related to the distribution of beacons, ease of deployment, and calibration and positioning algorithms, including the possible fusion of information. Apart from theoretical discussions, this work also includes the description of an ALPS that was implemented, installed in a large area and tested for mobile robot navigation. In addition to practical interest for real applications, airborne ALPSs can also be used as an excellent platform to test complex algorithms, which can be subsequently adapted for other positioning systems, such as underwater acoustic systems or ultrawideband radiofrequency (UWB RF) systems.

Significant research work has been undertaken related to the game-based learning approach over the last years. However, a closer look at this work reveals that further research is needed to examine some types of game-based learning approaches such as virtual reality serious games and LEGO Serious Play. This article examines and compares the effectiveness for learning Scrum and related agile practices of a serious game based on virtual reality and a learning activity based on the LEGO Serious Play methodology. The presented study used a quasi-experimental design with two groups, pre- and post-tests, and a perceptions questionnaire. The sample was composed of 59 software engineering students, 22 of which belonged to group A, while the other 37 were part of group B. The students in group A played the virtual reality serious game, whereas the students in group B conducted the LEGO Serious Play activity. The results show that both game-based learning approaches were effective for learning Scrum and related agile practices in terms of learning performance and motivation, but they also show that the students who played the virtual reality serious game outperformed their peers from the other group in terms of learning performance., Comment: 15 pages, 4 figures. Journal article published in Applied Sciences

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by an expanded CAG repeat in the coding sequence of the huntingtin protein. Initially, it predominantly affects medium-sized spiny neurons (MSSNs) of the corpus striatum. No effective treatment is available, thus urging the identification of potential therapeutic targets. While evidence of mitochondrial structural alterations in HD exists, previous studies mainly employed 2D approaches and were performed outside the strictly native brain context. In this study, we adopted a novel multiscale approach to conduct a comprehensive 3D in situ structural analysis of mitochondrial disturbances in a mouse model of HD. We investigated MSSNs within brain tissue under optimal structural conditions utilizing state-of-the-art 3D imaging technologies, specifically FIB/SEM for the complete imaging of neuronal somas and Electron Tomography for detailed morphological examination and image processing-based quantitative analysis. Our findings suggest a disruption of the mitochondrial network towards fragmentation in HD. The network of interlaced, slim, and long mitochondria observed in healthy conditions transforms into isolated, swollen, and short entities, with internal cristae disorganization, cavities, and abnormally large matrix granules., Comment: 31 pages 5 figures

Gravimeters fabricated with MEMS suffer from temperature-dependent drifts in their long-term stability. We analyze the thermal contributions to the signal, and we propose three mechanisms to mitigate their effects. The first one uses materials that fulfill the condition $\alpha_E=-2 \alpha$, where the thermal expansion is canceled by the temperature variation of the Young's modulus. The second one uses the thermal expansion to introduce a compression that compensates the variation in the force of the spring. In the third one, the expansion compensates the displacement of the proof mass in the sensor, rather than the force. The three mechanisms are robust since they only depend on the temperature of the sensor itself.

In this paper we demonstrate a sufficient condition for blowup of the nonlinear Klein-Gordon equation with arbitrarily positive initial energy in Friedmann-Lema\^itre-Robertson-Walker spacetimes. This is accomplished using an established concavity method that has been employed for similar PDEs in Minkowski space. This proof relies on the energy inequality associated with this equation, $E(t_0)\geq E(t)$, also proved herein using a geometric method., Comment: 15 pages. 1 figure

Located at the bottom of the main sequence, ultracool dwarf stars are widespread in the solar neighbourhood. Nevertheless, their extremely low luminosity has left their planetary population largely unexplored, and only one of them, TRAPPIST-1, has so far been found to host a transiting planetary system. In this context, we present the SPECULOOS project's detection of an Earth-sized planet in a 17 h orbit around an ultracool dwarf of M6.5 spectral type located 16.8 pc away. The planet's high irradiation (16 times that of Earth) combined with the infrared luminosity and Jupiter-like size of its host star make it one of the most promising rocky exoplanet targets for detailed emission spectroscopy characterization with JWST. Indeed, our sensitivity study shows that just ten secondary eclipse observations with the Mid-InfraRed Instrument/Low-Resolution Spectrometer on board JWST should provide strong constraints on its atmospheric composition and/or surface mineralogy.

Background: Human Emotion Recognition (HER) has been a popular field of study in the past years. Despite the great progresses made so far, relatively little attention has been paid to the use of HER in autism. People with autism are known to face problems with daily social communication and the prototypical interpretation of emotional responses, which are most frequently exerted via facial expressions. This poses significant practical challenges to the application of regular HER systems, which are normally developed for and by neurotypical people. Objective: This study reviews the literature on the use of HER systems in autism, particularly with respect to sensing technologies and machine learning methods, as to identify existing barriers and possible future directions. Methods: We conducted a systematic review of articles published between January 2011 and June 2023 according to the 2020 PRISMA guidelines. Manuscripts were identified through searching Web of Science and Scopus databases. Manuscripts were included when related to emotion recognition, used sensors and machine learning techniques, and involved children with autism, young, or adults. Results: The search yielded 346 articles. A total of 65 publications met the eligibility criteria and were included in the review. Conclusions: Studies predominantly used facial expression techniques as the emotion recognition method. Consequently, video cameras were the most widely used devices across studies, although a growing trend in the use of physiological sensors was observed lately. Happiness, sadness, anger, fear, disgust, and surprise were most frequently addressed. Classical supervised machine learning techniques were primarily used at the expense of unsupervised approaches or more recent deep learning models., Comment: 21 pages, 9 figures

Recurrent neural networks (RNNs) hold immense potential for computations due to their Turing completeness and sequential processing capabilities, yet existing methods for their training encounter efficiency challenges. Backpropagation through time (BPTT), the prevailing method, extends the backpropagation (BP) algorithm by unrolling the RNN over time. However, this approach suffers from significant drawbacks, including the need to interleave forward and backward phases and store exact gradient information. Furthermore, BPTT has been shown to struggle to propagate gradient information for long sequences, leading to vanishing gradients. An alternative strategy to using gradient-based methods like BPTT involves stochastically approximating gradients through perturbation-based methods. This learning approach is exceptionally simple, necessitating only forward passes in the network and a global reinforcement signal as feedback. Despite its simplicity, the random nature of its updates typically leads to inefficient optimization, limiting its effectiveness in training neural networks. In this study, we present a new approach to perturbation-based learning in RNNs whose performance is competitive with BPTT, while maintaining the inherent advantages over gradient-based learning. To this end, we extend the recently introduced activity-based node perturbation (ANP) method to operate in the time domain, leading to more efficient learning and generalization. We subsequently conduct a range of experiments to validate our approach. Our results show similar performance, convergence time and scalability compared to BPTT, strongly outperforming standard node and weight perturbation methods. These findings suggest that perturbation-based learning methods offer a versatile alternative to gradient-based methods for training RNNs which can be ideally suited for neuromorphic computing applications

We propose a method for reducing the spatial discretization error of coarse computational fluid dynamics (CFD) problems by enhancing the quality of low-resolution simulations using deep learning. We feed the model with fine-grid data after projecting it to the coarse-grid discretization. We substitute the default differencing scheme for the convection term by a feed-forward neural network that interpolates velocities from cell centers to face values to produce velocities that approximate the down-sampled fine-grid data well. The deep learning framework incorporates the open-source CFD code OpenFOAM, resulting in an end-to-end differentiable model. We automatically differentiate the CFD physics using a discrete adjoint code version. We present a fast communication method between TensorFlow (Python) and OpenFOAM (c++) that accelerates the training process. We applied the model to the flow past a square cylinder problem, reducing the error from 120% to 25% in the velocity for simulations inside the training distribution compared to the traditional solver using an x8 coarser mesh. For simulations outside the training distribution, the error reduction in the velocities was about 50%. The training is affordable in terms of time and data samples since the architecture exploits the local features of the physics.

We study the impact of black hole nuclear activity on both the global and radial star formation rate (SFR) profiles in X-ray-selected active galactic nuclei (AGN) in the field of miniJPAS, the precursor of the much wider J-PAS project. Our sample includes 32 AGN with z < 0.3 detected via the XMM-Newton and Chandra surveys. For comparison, we assembled a control sample of 71 star-forming (SF) galaxies with similar magnitudes, sizes, and redshifts. To derive the global properties of both the AGN and the control SF sample, we used CIGALE to fit the spectral energy distributions derived from the 56 narrowband and 4 broadband filters from miniJPAS. We find that AGN tend to reside in more massive galaxies than their SF counterparts. After matching samples based on stellar mass and comparing their SFRs and specific SFRs (sSFRs), no significant differences appear. This suggests that the presence of AGN does not strongly influence overall star formation. However, when we used miniJPAS as an integral field unit (IFU) to dissect galaxies along their position angle, a different picture emerges. We find that AGN tend to be more centrally concentrated in mass with respect to SF galaxies. Moreover, we find a suppression of the sSFR up to 1Re and then an enhancement beyond 1Re , strongly contrasting with the decreasing radial profile of sSFRs in SF galaxies. This could point to an inside-out quenching of AGN host galaxies. These findings suggest that the reason we do not see differences on a global scale is because star formation is suppressed in the central regions and enhanced in the outer regions of AGN host galaxies. While limited in terms of sample size, this work highlights the potential of the upcoming J-PAS as a wide-field low-resolution IFU for thousands of nearby galaxies and AGN., Comment: 21 pages, 20 figures, Accepted for Publication in A&A

In this work, the univariant two-phase coexistence line of the hydrate of tetrahydrofuran (THF) is determined from 100 to 1000 bar by molecular dynamics simulations. The study is carried out by putting in contact a THF hydrate phase with a stoichiometric aqueous solution phase. Following the direct coexistence technique, the pressure has been fixed, and the coexistence line has been determined by analyzing if the hydrate phase grows or melts at different values of temperature. The model of water used is the well-known TIP4P/Ice model. We have used two different models of THF based on the transferable parameters for phase equilibria-united atom approach (TraPPE-UA), the original (flexible) TraPPe-UA model as well as a rigid and planar version of it. Overall, at high pressures, small differences have been observed in the results obtained by both models. Also, large differences have been observed in the computational efforts required by the simulations performed using both models, being the rigid and planar version much faster than the original one. The effect of the unlike dispersive interactions between the water and THF molecules has been also analyzed at 250 bar using the rigid and planar THF model. In particular, we have modified the Berthelot combining rule by adding a factor ({\xi}O-THF) that modifies the unlike water-THF dispersive interactions and we have analyzed the effect on the dissociation temperature when {\xi}O-THF is modified from 1.0 (original Berthelot combining rule) to 1.4 (modified Berthelot combining rule). We have extended the study using {\xi}O-THF = 1.4 and the rigid THF model to the rest of the pressures considered in this work, finding an excellent agreement with the scarce experimental data taken from the literature., Comment: 10 pages, 5 figures