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The JAGB method is a new way of measuring distances with use of AGB stars that are situated in a selected region in a J versus J-Ks CMD, using the fact that the absolute J magnitude is (nearly) constant. It is implicitly assumed in the method that the selected stars are carbon-rich AGB stars. However, as the sample selected to determine M_J is purely colour based there can also be contamination by oxygen-rich AGB stars. As the ratio of C to O-rich stars is known to depend on metallicity and initial mass, the star formation history and age-metallicity relation in a galaxy should influence the value of M_J. The aim of this paper is to look at mixed samples of O- and C-rich stars for the LMC, the SMC and Milky Way (MW), using the Gaia catalogue of long period variables as basis. We report the mean and median magnitudes and the results of fitting Gaussian and Lorentzian profiles to the luminosity function (LF) using different colour and magnitudes cuts. For the SMC and LMC we confirm the previous results in the literature. The LFs of the SMC and LMC JAGB stars are clearly different, yet the mean magnitude inside a selection box can be argued to agree at the 0.02~mag level. The analysis of the MW sample is less straightforward. The contamination by O-rich stars is substantial for a classical lower limit of (J-Ks)0= 1.3, and becomes less than 10% only for (J-Ks)0= 1.5. The sample of AGB stars is much smaller than for the MCs for two reasons. Nearby AGB stars tend to be absent as they saturate in the 2MASS catalogue, and the parallax errors of AGB stars tend to be larger compared to non-AGB stars. The mean and median magnitudes are fainter than for the MC samples by about 0.4~mag which is not predicted by theory. We do not confirm the claim in the literature that the absolute calibration of the JAGB method is independent of metallicity up to solar metallicity., Comment: Accepted for publication in Astronomy and Astrophysics

In this work, we propose a novel and efficient method for smoothing polylines in motion planning tasks. The algorithm applies to motion planning of vehicles with bounded curvature. In the paper, we show that the generated path: 1) has minimal length, 2) is $G^1$ continuous, and 3) is collision-free by construction, if the hypotheses are respected. We compare our solution with the state-of.the-art and show its convenience both in terms of computation time and of length of the compute path.

Real-time robot actuation is one of the main challenges to overcome in human-robot interaction. Most visual sensors are either too slow or their data are too complex to provide meaningful information and low latency input to a robotic system. Data output of an event camera is high-frequency and extremely lightweight, with only 8 bytes per event. To evaluate the hypothesis of using event cameras as data source for a real-time robotic system, the position of a waving hand is acquired from the event data and transmitted to a collaborative robot as a movement command. A total time delay of 110 ms was measured between the original movement and the robot movement, where much of the delay is caused by the robot dynamics., Comment: The 5th IFToMM ITALY Conference, IFIT 2024

This work is part of VESTALE, a project initiated within the Rubin-LSST Cadence Strategy Optimization Process . Its goal is to explore the potential of Rubin-LSST observations aimed at the Galaxy's bulge (Bulge) for studying RR Lyrae stars (RRL). Observation and analysis of RR Lyrae stars in the Bulge are crucial for tracing the old population of the central part of our galaxy and reconstructing the history of Bulge formation. Based on observations conducted with CTIO/DECam by Saha et al. 2019 towards the Baade Window, our simulations demonstrate that early Rubin-LSST observations will enable the recovery of RR Lyrae light curves at Galactic center distances with sufficient precision. This will allow us to utilize theoretical relations from Marconi et al. 2022 to determine their distances and/or metallicity, following the REDIME algorithm introduced in Bono et al. 2019. We show how reddening and crowding affect our simulations and highlight the importance of considering these effects when deriving pulsation parameters (luminosity amplitudes, mean magnitudes) based on the light curves especially if the goal is to explore the opposite side of the Bulge through the observation of its RRL. The simulations discussed in this investigation were conducted to support the SCOC's decision to observe this important sky region since it has only recently been decided to include part of the Bulge as a target within the LSST main survey., Comment: Accepted for publication in ApJS. 12 pages and 6 figures

We present an investigation of evolved stars in the nearby star-forming galaxy WLM, using NIRCam imaging from the JWST resolved stellar populations early-release science (ERS) program. We find that various combinations of the F090W, F150W, F250M, and F430M filters can effectively isolate red supergiants (RSGs) and thermally-pulsing asymptotic giant branch (TP-AGB) stars from one another, while also providing a reasonable separation of the primary TP-AGB subtypes: carbon-rich C-type stars and oxygen-rich M-type stars. The classification scheme we present here agrees very well with the well-established Hubble Space Telescope (HST) medium-band filter technique. The ratio of C to M-type stars (C/M) is 0.8$\pm$0.1 for both the new JWST and the HST classifications, which is within one sigma of empirical predictions from optical narrow-band CN and TiO filters. The evolved star colors show good agreement with the predictions from the PARSEC$+$COLIBRI stellar evolutionary models, and the models indicate a strong metallicity dependence that makes stellar identification even more effective at higher metallicity. However, the models also indicate that evolved star identification with NIRCam may be more difficult at lower metallicies. We test every combination of NIRCam filters using the models and present additional filters that are also useful for evolved star studies. We also find that $\approx$90\% of the dusty evolved stars are carbon-rich, suggesting that carbonaceous dust dominates the present-day dust production in WLM, similar to the findings in the Magellanic Clouds. These results demonstrate the usefulness of NIRCam in identifying and classifying dust-producing stars without the need for mid-infrared data., Comment: 15 page, 12 figures, submitted to AAS Journals

We present the first star formation history (SFH) and age-metallicity relation (AMR) derived from resolved stellar populations imaged with the JWST NIRCam instrument. The target is the Local Group star-forming galaxy WLM at 970 kpc. The depth of the color-magnitude diagram (CMD) reaches below the oldest main sequence turn-off with a SNR=10 at M_F090W=+4.6 mag; this is the deepest CMD for any galaxy that is not a satellite of the Milky Way. We use Hubble Space Telescope (HST) optical imaging that overlaps with the NIRCam observations to directly evaluate the SFHs derived based on data from the two great observatories. The JWST and HST-based SFHs are in excellent agreement. We use the metallicity distribution function measured from stellar spectra to confirm the trends in the AMRs based on the JWST data. Together, these results confirm the efficacy of recovering a SFH and AMR with the NIRCam F090W-F150W filter combination and provide validation of the sensitivity and accuracy of stellar evolution libraries in the near-infrared relative to the optical for SFH recovery work. From the JWST data, WLM shows an early onset to star formation, followed by an extended pause post-reionization before star formation re-ignites, which is qualitatively similar to what has been observed in the isolated galaxies Leo~A and Aquarius. Quantitatively, 15% of the stellar mass formed in the first Gyr, while only 10% formed over the next ~5 Gyr; the stellar mass then rapidly doubled in ~2.5 Gyr, followed by constant star formation over the last ~5 Gyr., Comment: 27 pages, 10 figures, 1 table

Mounting experimental evidence suggests that brain-state-specific neural mechanisms, supported by connectomic architectures, play a crucial role in integrating past and contextual knowledge with the current, incoming flow of evidence (e.g., from sensory systems). These mechanisms operate across multiple spatial and temporal scales, necessitating dedicated support at the levels of individual neurons and synapses. A notable feature within the neocortex is the structure of large, deep pyramidal neurons, which exhibit a distinctive separation between an apical dendritic compartment and a basal dendritic/perisomatic compartment. This separation is characterized by distinct patterns of incoming connections and brain-state-specific activation mechanisms, namely, apical amplification, isolation, and drive, which are associated with wakefulness, deeper NREM sleep stages, and REM sleep, respectively. The cognitive roles of apical mechanisms have been demonstrated in behaving animals. In contrast, classical models of learning in spiking networks are based on single-compartment neurons, lacking the ability to describe the integration of apical and basal/somatic information. This work aims to provide the computational community with a two-compartment spiking neuron model that incorporates features essential for supporting brain-state-specific learning. This model includes a piece-wise linear transfer function (ThetaPlanes) at the highest abstraction level, making it suitable for use in large-scale bio-inspired artificial intelligence systems. A machine learning evolutionary algorithm, guided by a set of fitness functions, selected the parameters that define neurons expressing the desired apical mechanisms., Comment: 23 pages, 9 figures (29 single images), 4 tables, paper

Starting from the Gaia DR3 HR diagram, we derive the star formation history (SFH) as a function of distance from the Galactic Plane within a cylinder centred on the Sun with a 200~pc radius and spanning 1.3~kpc above and below the Galaxy's midplane. We quantify both the concentration of the more recent star formation in the Galactic Plane, and the age-related increase in the scale height of the Galactic Disc stellar component, which is well-described by power-laws with indices ranging from $1/2$ to $2/3$. The vertically-integrated star formation rate falls from $(1.147 \pm 0.039)\times10^{-8}\, \text{M}_{\odot} \text{yr}^{-1} \text{pc}^{-2}$ at earlier times down to $(6.2 \pm 3.0) \times10^{-9}\, \text{M}_{\odot} \text{yr}^{-1} \text{pc}^{-2}$ at present times, but we find a significant peak of star formation in the 2 to 3 Gyr age bin. The total mass of stars formed per unit area over time is $118.7 \pm 6.2\, \text{M}_{\odot} \text{pc}^{-2}$, which is nearly twice the present stellar mass derived from kinematics within 1~kpc from the Galactic Plane, implying a high degree of matter recycling in successive generations of stars. The method is then modified by adopting an age-dependent correlation between the SFH across the different slices, which results in less noisy and more symmetrical results without significantly changing the previously mentioned quantities. This appears to be a promising way to improve SFH recovery in external galaxies., Comment: Accepted for publication in MNRAS

The Chinese Space Station Telescope (CSST) is a cutting-edge two-meter astronomical space telescope currently under construction. Its primary Survey Camera (SC) is designed to conduct large-area imaging sky surveys using a sophisticated seven-band photometric system. The resulting data will provide unprecedented data for studying the structure and stellar populations of the Milky Way. To support the CSST development and scientific projects related to its survey data, we generate the first comprehensive Milky Way stellar mock catalogue for the CSST SC photometric system using the TRILEGAL stellar population synthesis tool. The catalogue includes approximately 12.6 billion stars, covering a wide range of stellar parameters, photometry, astrometry, and kinematics, with magnitude reaching down to $g\,=\,27.5$ mag in the AB magnitude system. The catalogue represents our benchmark understanding of the stellar populations in the Milky Way, enabling a direct comparison with the future CSST survey data. Particularly, it sheds light on faint stars that are hidden from current sky surveys. Our crowding limit analysis based on this catalogue provides compelling evidence for the extension of the CSST Optical Survey (OS) to cover low Galactic latitude regions. The strategic extension of the CSST-OS coverage, combined with this comprehensive mock catalogue, will enable transformative science with the CSST., Comment: Accepted by Sci. China Phys. Mech. Astron, catalogue at https://nadc.china-vo.org/data/data/csst-trilegal/f, 16 pages, 9 figures

Simulation speed matters for neuroscientific research: this includes not only how quickly the simulated model time of a large-scale spiking neuronal network progresses, but also how long it takes to instantiate the network model in computer memory. On the hardware side, acceleration via highly parallel GPUs is being increasingly utilized. On the software side, code generation approaches ensure highly optimized code, at the expense of repeated code regeneration and recompilation after modifications to the network model. Aiming for a greater flexibility with respect to iterative model changes, here we propose a new method for creating network connections interactively, dynamically, and directly in GPU memory through a set of commonly used high-level connection rules. We validate the simulation performance with both consumer and data center GPUs on two neuroscientifically relevant models: a cortical microcircuit of about 77,000 leaky-integrate-and-fire neuron models and 300 million static synapses, and a two-population network recurrently connected using a variety of connection rules. With our proposed ad hoc network instantiation, both network construction and simulation times are comparable or shorter than those obtained with other state-of-the-art simulation technologies, while still meeting the flexibility demands of explorative network modeling., Comment: 29 pages, 9 figures

We characterize massive stars (M>8 M_sun) in the nearby (D~0.8 Mpc) extremely metal-poor (Z~5% Z_sun) galaxy Leo A using Hubble Space Telescope ultra-violet (UV), optical, and near-infrared (NIR) imaging along with Keck/LRIS and MMT/Binospec optical spectroscopy for 18 main sequence OB stars. We find that: (a) 12 of our 18 stars show emission lines, despite not being associated with an H II region, suggestive of stellar activity (e.g., mass loss, accretion, binary star interaction), which is consistent with previous predictions of enhanced activity at low metallicity; (b) 6 are Be stars, which are the first to be spectroscopically studied at such low metallicity -- these Be stars have unusual panchromatic SEDs; (c) for stars well-fit by the TLUSTY non-local thermodynamic equilibrium (non-LTE) models, the photometric and spectroscopic values of T_eff and log(g) agree to within ~0.01 dex and ~0.18 dex, respectively, indicating that NUV/optical/NIR imaging can be used to reliably characterize massive (M ~ 8-30 M_sun) main sequence star properties relative to optical spectroscopy; (d) the properties of the most massive stars in H II regions are consistent with constraints from previous nebular emission line studies; and (e) 13 stars with M>8 M_sun are >40 pc from a known star cluster or H II region. Our sample comprises ~50% of all known massive stars at Z < 10% Z_sun with derived stellar parameters, high-quality optical spectra, and panchromatic photometry., Comment: 35 pages, 18 figures

Neuroscience is moving towards a more integrative discipline, where understanding brain function requires consolidating the accumulated evidence seen across experiments, species, and measurement techniques. A remaining challenge on that path is integrating such heterogeneous data into analysis workflows such that consistent and comparable conclusions can be distilled as an experimental basis for models and theories. Here, we propose a solution in the context of slow wave activity ($<1$ Hz), which occurs during unconscious brain states like sleep and general anesthesia, and is observed across diverse experimental approaches. We address the issue of integrating and comparing heterogeneous data by conceptualizing a general pipeline design that is adaptable to a variety of inputs and applications. Furthermore, we present the Collaborative Brain Wave Analysis Pipeline (Cobrawap) as a concrete, reusable software implementation to perform broad, detailed, and rigorous comparisons of slow wave characteristics across multiple, openly available ECoG and calcium imaging datasets.

Sleep is essential for learning and cognition, but the mechanisms by which it stabilizes learning, supports creativity, and manages the energy consumption of networks engaged in post-sleep task have not been yet modelled. During sleep, the brain cycles between non-rapid eye movement (NREM), a mainly unconscious state characterized by collective oscillations, and rapid eye movement (REM), associated with the integrated experience of dreaming. We propose a biologically grounded two-area thalamo-cortical plastic spiking neural network model and investigate the role of NREM - REM cycles on its awake performance. We demonstrate that sleep has a positive effect on energy consumption and cognitive performance during the post-sleep awake classification task of handwritten digits. NREM and REM simulated dynamics modify the synaptic structure into a sharper representation of training experiences. Sleep-induced synaptic modifications reduce firing rates and synaptic activity without reducing cognitive performance. Also, it creates novel multi-area associations. The model leverages the apical amplification, isolation and drive experimentally grounded principles and the combination of contextual and perceptual information. In summary, the main novelty is the proposal of a multi-area plastic model that also expresses REM and integrates information during a plastic dream-like state, with cognitive and energetic benefits during post-sleep awake classification., Comment: 22 pages, 9 figures

We describe a large simulation of the stars to be observed by the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). The simulation is based on the TRILEGAL code, which resorts to large databases of stellar evolutionary tracks, synthetic spectra, and pulsation models, added to simple prescriptions for the stellar density and star formation histories of the main structures of the Galaxy, to generate mock stellar samples through a population synthesis approach. The main bodies of the Magellanic Clouds are also included. A complete simulation is provided for single stars, down to the $r=27.5$ mag depth of the co-added wide-fast-deep survey images. A second simulation is provided for a fraction of the binaries, including the interacting ones, as derived with the BinaPSE module of TRILEGAL. We illustrate the main properties and numbers derived from these simulations, including: comparisons with real star counts; the expected numbers of Cepheids, long-period variables and eclipsing binaries; the crowding limits as a function of seeing and filter; the star-to-galaxy ratios, etc. Complete catalogs are accessible through the NOIRLab Astro Data Lab, while the stellar density maps are incorporated in the LSST metrics analysis framework (MAF)., Comment: Accepted for publication in the LSST focused ApJS issue

The APEnet+ board delivers a point-to-point, low-latency, 3D torus network interface card. In this paper we describe the latest generation of APEnet NIC, APEnet v5, integrated in a PCIe Gen3 board based on a state-of-the-art, 28 nm Altera Stratix V FPGA. The NIC features a network architecture designed following the Remote DMA paradigm and tailored to tightly bind the computing power of modern GPUs to the communication fabric. For the APEnet v5 board we show characterizing figures as achieved bandwidth and BER obtained by exploiting new high performance ALTERA transceivers and PCIe Gen3 compliancy.

Benefiting from the GAIA second and early third releases of photometric and astrometric data we examine the population of asymptotic giant branch (AGB) stars that appear in the fields of intermediate-age and young open star clusters. We identify 49 AGB star candidates, brighter than the tip of the red giant branch, with a good-to-high cluster membership probability. Among them we find 19 TP-AGB stars with known spectral type: 4 M stars, 3 MS/S stars and 12 C stars. By combining observations, stellar models, and radiative transfer calculations that include the effect of circumstellar dust, we characterize each star in terms of initial mass, luminosity, mass-loss rate, core mass, period and mode of pulsation. The information collected helps us shed light on the TP-AGB evolution at solar-like metallicity, placing constraints on the third dredge-up process, the initial masses of carbon stars, stellar winds, and the initial-final mass relation (IFMR). In particular, we find that two bright carbon stars, MSB 75 and BM IV 90, members of the clusters NGC 7789 and NGC 2660 (with similar ages of $\simeq 1.2-1.6$ Gyr and initial masses $ 2.1 \ge M_{\rm i}/M_{\odot} \ge 1.9$), have unusually high core masses, $M_{\rm c} \approx 0.67-0.7\,M_{\odot}$. These results support the findings of a recent work (Marigo et al. 2020) that identified a kink in the IFMR, which interrupts its monotonic trend just at the same initial masses. Finally, we investigate two competing scenarios to explain the $M_{\rm c}$ data: the role of stellar winds in single-star evolution, and binary interactions through the blue-straggler channel., Comment: Article accepted for publication in ApJS (46 pages, 11 figures, 10 tables)

We derive the spatially-resolved star formation history (SFH) for a $96$ deg$^2$ area across the main body of the Large Magellanic Cloud (LMC), using the near-infrared photometry from the VISTA survey of the Magellanic Clouds (VMC). The data and analyses are characterised by a great degree of homogeneity and a low sensitivity to the interstellar extinction. 756 subregions of size $0.125$ deg$^2$ -- corresponding to projected sizes of about $296\times322\,\mathrm{pc}^{2}$ in the LMC -- are analysed. The resulting SFH maps, with typical resolution of $0.2$--$0.3$ dex in logarithm of age, reveal main features in the LMC disc at different ages: the patchy star formation at recent ages, the concentration of star formation on three spiral arms and on the Bar up to ages of $\sim\!1.6$ Gyr, and the wider and smoother distribution of older populations. The period of most intense star formation occurred roughly between 4 and 0.5 Gyr ago, at rates of $\sim\!0.3\,\mathrm{M}_{\odot}\mathrm{yr}^{-1}$. We compare young and old star formation rates with the observed numbers of RR Lyrae and Cepheids. We also derive a mean extinction and mean distance for every subregion, and the plane that best describes the spatial distribution of the mean distances. Our results cover an area about 50 per cent larger than the classical SFH maps derived from optical data by Harris & Zaritsky (2009). Main differences with respect to those maps are lower star formation rates at young ages, and a main peak of star formation being identified at ages slightly younger than $1$ Gyr., Comment: Accepted for publication in MNRAS