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We investigate the fermionic perturbations of the asymptotically AdS background known as holographic neutron star, which represents a highly degenerate state of strongly coupled fermions on a sphere at finite temperature. We calculate the two-point correlator of a fermionic operator and obtain its scaling properties as we approach the critical region of the phase diagram., Comment: 7 pages in the main text, 10 more pages of appendices containing the more detailed calculations, 5 figures

We utilized photometric data from the space telescope AKARI to identify potential planetary nebulae (PNe) and proto-planetary nebulae (PPNe) candidates. Using the colour-colour diagram, we found a region with a high concentration of established PNe and PPNe, comprising about 95% of the objects. Based on this, we identified 67 objects within this region that lack definitive classification in existing literature, suggesting they are promising candidates. We conducted Spectral Energy Distribution (SED) analysis and morphological investigations using imagery from various observatories and satellites. Finally, we present a list of 65 potential PNe and PPNe candidates., Comment: 26 pages, 19 figures, 1 table

Economic experiments offer a controlled setting for researchers to observe human decision-making and test diverse theories and hypotheses; however, substantial costs and efforts are incurred to gather many individuals as experimental participants. To address this, with the development of large language models (LLMs), some researchers have recently attempted to develop simulated economic experiments using LLMs-driven agents, called generative agents. If generative agents can replicate human-like decision-making in economic experiments, the cost problem of economic experiments can be alleviated. However, such a simulation framework has not been yet established. Considering the previous research and the current evolutionary stage of LLMs, this study focuses on the reasoning ability of generative agents as a key factor toward establishing a framework for such a new methodology. A multi-agent simulation, designed to improve the reasoning ability of generative agents through prompting methods, was developed to reproduce the result of an actual economic experiment on the ultimatum game. The results demonstrated that the higher the reasoning ability of the agents, the closer the results were to the theoretical solution than to the real experimental result. The results also suggest that setting the personas of the generative agents may be important for reproducing the results of real economic experiments. These findings are valuable for the future definition of a framework for replacing human participants with generative agents in economic experiments when LLMs are further developed., Comment: 10 pages, 5 figures

Sustainable artificial intelligence focuses on data, hardware, and algorithms to make machine learning models more environmentally responsible. In particular, machine learning models for speech representations are computationally expensive, generating environmental concerns because of their high energy consumption. Thus, we propose a sustainable self-supervised model to learn speech representation, combining optimizations in neural layers and training to reduce computing costs. The proposed model improves over a resource-efficient baseline, reducing both memory usage and computing cost estimations. It pretrains using a single GPU in less than a day. On top of that, it improves the error rate performance of the baseline in downstream task evaluations. When comparing it to large speech representation approaches, there is an order of magnitude reduction in memory usage, while computing cost reductions represent almost three orders of magnitude improvement.

The way heuristic optimizers are designed has evolved over the decades, as computing power has increased. Such has been the case for the Linear Ordering Problem (LOP), a field in which trajectory-based strategies led the way during the 1990s, but which have now been surpassed by memetic schemes.This paper focuses on understanding how the design of LOP optimizers will change in the future, as computing power continues to increase, yielding two main contributions.On the one hand, a metaheuristic was designed that is capable of effectively exploiting a large amount of computational resources, specifically, computing power equivalent to what a recent core can output during runs lasting over four months.Our analyses show that as the power of the computational resources increases, it will be necessary to boost the capacities of the intensification methods applied in the memetic algorithms to keep the population from stagnating.And on the other, the best-known results for today's most challenging set of instances (xLOLIB2) were significantly outperformed. New bounds were established in this benchmark, which provides a new frame of reference for future research.

We have learnt in the last decades that the majority of galaxies belong to high density regions interconnected in a sponge-like fashion. This large-scale structure is characterised by clusters, filaments, walls, where most galaxies concentrate, but also under-dense regions, called voids. The void regions and the galaxies within represent an ideal place for the study of galaxy formation and evolution as they are largely unaffected by the complex physical processes that transform galaxies in high-density environments. These void galaxies can hold the key as well to answer current challenges to the $\Lambda$CDM paradigm. The Calar Alto Void Integral-field Treasury surveY (CAVITY) is a Legacy project approved by the Calar Alto Observatory to obtain spatially resolved spectroscopic information of $\sim300$ void galaxies in the Local Universe (0.005 < z < 0.050) covering from -17.0 to -21.5 in $\rm r$ band absolute magnitude. It officially started in January 2021 and has been awarded 110 useful dark observing nights at the 3.5 m telescope using the PMAS spectrograph. Complementary follow-up projects including deep optical imaging, integrated, as well as resolved CO data, and integrated HI spectra, have joint the PMAS observations and naturally complete the scientific aim of characterising galaxies in cosmic voids. The extension data has been denominated CAVITY+. The data will be available to the whole community in different data releases, the first of which is planned for July 2024, and it will provide the community with PMAS data cubes for around 100 void galaxies through a user friendly, and well documented, database platform. We present here the survey, sample selection, data reduction, quality control schemes, science goals, and some examples of the scientific power of the CAVITY and CAVITY+ data., Comment: 19 pages, 11 figures. Accepted for publication in A&A - Replacement after A&A minor language edition

This study analyzes the spectrum of audio signals related to the work of "Pi\`eces de viole des Cinq Livres" based on the collaborative work between Marin Marais and Jordi Savall for the underlying musical information. In particular, we explore the identification of possible statistical signatures related to this musical work. Based on the complex systems approach, we compute the spectrum of audio signals, analyze and identify their best-fit statistical distributions, and plot their relative frequencies using the scientific pitch notation. Findings suggest that the collection of frequency components related to the spectrum of each of the books that form this audio work show highly skewed and associated statistical distributions. Therefore, the most frequent statistical distribution that best describes the collection of these audio data and may be associated with a singular statistical signature is the exponential.

We analyze the concept of virtuosity as a collective attribute in music and its relationship with the entropy based on an experiment that compares two sets of digital signals played by composer-performer electric guitarists. Based on an interdisciplinary approach related to the complex systems, we computed the spectrum of signals, identified statistical distributions that best describe them, and measured the Shannon entropy to establish their diversity. Findings suggested that virtuosity might be related to a range of entropy values that identify levels of diversity of the frequency components of audio signals. Despite the presence of different values of entropy in the two sets of signals, they are statistically similar. Therefore, entropy values can be interpreted as levels of virtuosity in music.

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

Textureless object recognition has become a significant task in Computer Vision with the advent of Robotics and its applications in manufacturing sector. It has been challenging to obtain good accuracy in real time because of its lack of discriminative features and reflectance properties which makes the techniques for textured object recognition insufficient for textureless objects. A lot of work has been done in the last 20 years, especially in the recent 5 years after the TLess and other textureless dataset were introduced. In this project, by applying image processing techniques we created a robust augmented dataset from initial imbalanced smaller dataset. We extracted edge features, feature combinations and RGB images enhanced with feature/feature combinations to create 15 datasets, each with a size of ~340,000. We then trained four classifiers on these 15 datasets to arrive at a conclusion as to which dataset performs the best overall and whether edge features are important for textureless objects. Based on our experiments and analysis, RGB images enhanced with combination of 3 edge features performed the best compared to all others. Model performance on dataset with HED edges performed comparatively better than other edge detectors like Canny or Prewitt., Comment: arXiv admin note: text overlap with arXiv:1910.14255

We present a catalog of $\sim$52,000 extragalactic HII regions and their spectroscopic properties obtained using Integral Field Spectroscopy (IFS) from MUSE observations. The sample analyzed in this study contains 678 galaxies within the nearby Universe (0.004 < z < 0.06) covering different morphological types and a wide range of stellar masses (6 < log(M$_{*}$/M$_{\odot}$) < 13). Each galaxy was analyzed using the Pipe3D and pyHIIextractor codes to obtain information of the ionized gas and underlying stellar populations. Specifically, the fluxes, equivalent widths, velocities and velocity dispersions of 30 emission lines covering the wavelength range between $\lambda$4750A to $\lambda$9300A, were extracted and were used to estimate luminosity weighted ages and metallicities of the underlying stellar populations from each HII region (of the original sample we detect HII regions in 539 galaxies). In addition, we introduce and apply a novel method and independent of any intrinsic physical property to estimate and decontaminate the contribution of the diffuse ionized gas. Using the final catalog, we explore the dependence of properties of the HII regions on different local and global galaxy parameters: (i) Hubble type, (ii) stellar mass, (iii) galactocentric distance, and (iv) the age and metallicity of the underlying/neighbour stellar populations. We confirm known relations between properties of the HII regions and the underlying stellar populations (in particular with the age) uncovered using data of lower spatial and spectral resolution. Furthermore, we describe the existence of two main families of diffuse ionized gas different for galaxies host or not of HII region, Comment: Submitted for publishing in MNRAS, 2O pages, 13 figures

Self-supervised learning enables the training of large neural models without the need for large, labeled datasets. It has been generating breakthroughs in several fields, including computer vision, natural language processing, biology, and speech. In particular, the state-of-the-art in several speech processing applications, such as automatic speech recognition or speaker identification, are models where the latent representation is learned using self-supervised approaches. Several configurations exist in self-supervised learning for speech, including contrastive, predictive, and multilingual approaches. There is, however, a crucial limitation in most existing approaches: their high computational costs. These costs limit the deployment of models, the size of the training dataset, and the number of research groups that can afford research with large self-supervised models. Likewise, we should consider the environmental costs that high energy consumption implies. Efforts in this direction comprise optimization of existing models, neural architecture efficiency, improvements in finetuning for speech processing tasks, and data efficiency. But despite current efforts, more work could be done to address high computational costs in self-supervised representation learning., Comment: 16 pages, 3 figures

The usual approach to classify the ionizing source using optical spectroscopy is based on the use of diagnostic diagrams that compares the relative strength of pairs of collisitional metallic lines (e.g., [O iii] and [N ii]) with respect to recombination hydrogen lines (e.g., H{\beta} and H{\alpha}). Despite of being accepted as the standard procedure, it present known problems, including confusion regimes and/or limitations related to the required signal-to-noise of the involved emission lines. These problems affect not only our intrinsic understanding of inter-stellar medium and its poroperties, but also fundamental galaxy properties, such as the star-formation rate and the oxygen abundance, and key questions just as the fraction of active galactic nuclei, among several others. We explore the existing alternatives in the literature to minimize the confusion among different ionizing sources and proposed a new simple diagram that uses the equivalent width and the velocity dispersion from one single emission line, H{\alpha}, to classify the ionizing sources. We use aperture limited and spatial resolved spectroscopic data in the nearby Universe (z{\sim}0.01) to demonstrate that the new diagram, that we called WHaD, segregates the different ionizing sources in a more efficient way that previously adopted procedures. A new set of regions are defined in this diagram to select betweeen different ionizing sources. The new proposed diagram is well placed to determine the ionizing source when only H{\alpha} is available, or when the signal-to-noise of the emission lines involved in the classical diagnostic diagrams (e.g., H{\beta})., Comment: 10 pages, 5 figures, accepted for publishing in A&A