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As star-forming galaxies approach or exceed a stellar mass around $10^{11} M_\odot$, they are increasingly likely to be quenched in a process generically called mass quenching. Central galaxies, which are quenched via mass rather than environmental quenching, therefore accumulate in a peak around this characteristic mass. While a number of processes may influence the shape of the quenched central stellar mass function (QCSMF), we find that its low-mass slope is strongly affected by the scatter in the mass of black holes at a given stellar mass, with higher scatters in the black hole population yielding shallower slopes. Higher scatters in the black hole mass spread out the stellar mass range over which quenching occurs, leading to shallower slopes. This trend holds across a variety of semi-analytic models and cosmological hydrodynamic simulations. A comparison with observations provides indirect evidence for a large scatter in black hole mass $\sigma(\log_{10}(M_\mathrm{BH})|M_*) \gtrsim 0.5$ dex, and a joint constraint on AGN feedback physics and the co-evolution of galaxies and black holes., Comment: 13 pages, 6 figures

Many questions posed in the Astro2020 Decadal survey in both the New Messengers and New Physics and the Cosmic Ecosystems science themes require a gamma-ray mission with capabilities exceeding those of existing (e.g. Fermi, Swift) and planned (e.g. COSI) observatories. ComPair, the Compton Pair telescope, is a prototype of such a next-generation gamma-ray mission. It had its inaugural balloon flight from Ft. Sumner, New Mexico in August 2023. To continue the goals of the ComPair project to develop technologies that will enable a future gamma-ray mission, the next generation of ComPair (ComPair-2) will be upgraded to increase the sensitivity and low-energy transient capabilities of the instrument. These advancements are enabled by AstroPix, a silicon monolithic active pixel sensor, in the tracker and custom dual-gain silicon photomultipliers and front-end electronics in the calorimeter. This effort builds on design work for the All-sky Medium Energy Gamma-ray Observatory eXplorer (AMEGO-X) concept that was submitted the 2021 MIDEX Announcement of Opportunity. Here we describe the ComPair-2 prototype design and integration and testing plans to advance the readiness level of these novel technologies., Comment: 11 pages, 7 figures, SPIE Astronomical Telescopes and Instrumentation 2004 conference proceedings

In Concentrated Solar Power (CSP) plants based on Parabolic Trough Collectors (PTC), the Sun is tracked at discrete time intervals, with each interval representing a movement of the collector system. The act of moving heavy mechanical structures can lead to the development of cracks, bending, and/or displacements of components from their optimal optical positions. This, in turn, diminishes the overall performance of the entire system for energy capture. In this context, we introduce two combinatorial optimization problems to limit the number of tracking steps of the collector and hence the risk of failure incidents and contaminant leaks. On the one hand, the Minimum Tracking Motion (MTM)-Problem aims at detecting the minimum number of movements while maintaining the production within a given range. On the other hand, the Maximal Energy Collection (MEC)-Problem aims to achieve optimal energy production within a predetermined number of movements. Both problems are solved assuming scenarios where the energy collection function contains any number of local maximum/minimum due to optical errors of the elements in the PTCsystem. The MTM- and MEC-Problems are solved in O(n) time and O(n2mw*) time, respectively, being n the number of steps in the energy collection function, m the maximum number of movements of the solar structure, and w* the maximal amplitude angle that the structure can cover. The advantages of the solutions are shown in realistic experiments. While these problems can be solved in polynomial time, we establish the NP-hardness of a slightly modified version of the MEC-Problem. The proposed algorithms are generic and can be adapted to schedule solar tracking in other CSP systems.

Symmetry-breaking is pivotal for controlling ferroelectric, ferroelastic and/or ferromagnetic functions of materials, which enables applications in sensors, memories, transducers or actuators. Commonly, ferroic phases emerge from descending symmetry-breaking, as the laws of thermodynamics dictate that the ordered low entropy phases form at low temperature, which limits practical applications of many materials at room temperature. Rare examples of ascending symmetry-breakings have been observed, but the driving force remains often unclear. Here, we report on a ferroelastic symmetry-breaking occurring at high temperature in a spin-crossover material, studied by magnetic, DSC and X-ray diffraction measurements. Our DFT calculations and our model, based on the Landau theory of phase transitions, explain how the cooperative thermal switching of molecular spin state drives a ferroelastic symmetry breaking at high temperature, through a coupled Jahn-Teller distortion. Ferroelastic materials have rich properties, with important applications in memory, multifunctional and novel controllable devices. The electronic bistability in soft functional materials represents an important source of entropy gain, capable of overcoming the cost of symmetry-breaking entropy, which opens up new perspectives for stabilizing high-temperature and low-symmetry ferroic functions of advanced materials

Small robots that can operate under the plant canopy can enable new possibilities in agriculture. However, unlike larger autonomous tractors, autonomous navigation for such under canopy robots remains an open challenge because Global Navigation Satellite System (GNSS) is unreliable under the plant canopy. We present a hybrid navigation system that autonomously switches between different sets of sensing modalities to enable full field navigation, both inside and outside of crop. By choosing the appropriate path reference source, the robot can accommodate for loss of GNSS signal quality and leverage row-crop structure to autonomously navigate. However, such switching can be tricky and difficult to execute over scale. Our system provides a solution by automatically switching between an exteroceptive sensing based system, such as Light Detection And Ranging (LiDAR) row-following navigation and waypoints path tracking. In addition, we show how our system can detect when the navigate fails and recover automatically extending the autonomous time and mitigating the necessity of human intervention. Our system shows an improvement of about 750 m per intervention over GNSS-based navigation and 500 m over row following navigation., Comment: Presented in the 2023 IEEE International Conference on Robotics and Automation (ICRA)

The recent detection of extended $\gamma$-ray emission around middle-aged pulsars is interpreted as inverse-Compton scattering of ambient photons by electron-positron pairs escaping the pulsar wind nebula, which are confined near the system by unclear mechanisms. This emerging population of $\gamma$-ray sources was first discovered at TeV energies and remains underexplored in the GeV range. To address this, we conducted a systematic search for extended sources along the Galactic plane using 14 years of Fermi-LAT data above 10 GeV, aiming to identify a number of pulsar halo candidates and extend our view to lower energies. The search covered the inner Galactic plane ($\lvert l\rvert\leq$ 100$^{\circ}$, $\lvert b\rvert\leq$ 1$^{\circ}$) and the positions of known TeV sources and bright pulsars, yielding broader astrophysical interest. We found 40 such sources, forming the Second Fermi Galactic Extended Sources Catalog (2FGES), most with 68% containment radii smaller than 1.0$^{\circ}$ and relatively hard spectra with photon indices below 2.5. We assessed detection robustness using field-specific alternative interstellar emission models and by inspecting significance maps. Noting 13 sources previously known as extended in the 4FGL-DR3 catalog and five dubious sources from complex regions, we report 22 newly detected extended sources above 10 GeV. Of these, 13 coincide with H.E.S.S., HAWC, or LHAASO sources; six coincide with bright pulsars (including four also coincident with TeV sources); six are associated with 4FGL point sources only; and one has no association in the scanned catalogs. Notably, six to eight sources may be related to pulsars as classical pulsar wind nebulae or pulsar halos., Comment: 43 pages, 17 figures, 11 tables

Studies aiming to determine the astrophysical origins of nuclei produced by the rapid neutron capture process ($r$ process) rely on nuclear properties as inputs for simulations. The solar abundances can be used as a benchmark for such calculations, with the $r$-process rare-earth peak (REP) around mass number ($A$) 164 being of special interest due to its presently unknown origin. With the advancement of rare isotope beam production over the last decade and improvement in experimental sensitivities, many of these REP nuclides have become accessible for measurement. Masses are one of the most critical inputs as they impact multiple nuclear properties, namely the neutron-separation energies, neutron capture rates, $\beta$-decay rates, and $\beta$-delayed neutron emission probabilities. In this work, we report masses of 20 neutron-rich nuclides (along the Ba, La, Ce, Pr, Nd, Pm, Gd, Dy and Ho isotopic chains) produced at the CAlifornium Rare Isotope Breeder Upgrade (CARIBU) facility at Argonne National Laboratory. The masses were measured with the Canadian Penning trap (CPT) mass spectrometer using the Phase-Imaging Ion-Cyclotron-Resonance (PI-ICR) technique. We then use these new masses along with previously published CPT masses to inform predictions for a Markov Chain Monte Carlo (MCMC) procedure aiming to identify the astrophysical conditions consistent with both solar data and mass measurements. We show that the MCMC responds to this updated mass information, producing refined results for both mass predictions and REP abundances., Comment: 11 pages, 8 figures

Radiology report generation (RRG) aims to create free-text radiology reports from clinical imaging. Grounded radiology report generation (GRRG) extends RRG by including the localisation of individual findings on the image. Currently, there are no manually annotated chest X-ray (CXR) datasets to train GRRG models. In this work, we present a dataset called PadChest-GR (Grounded-Reporting) derived from PadChest aimed at training GRRG models for CXR images. We curate a public bi-lingual dataset of 4,555 CXR studies with grounded reports (3,099 abnormal and 1,456 normal), each containing complete lists of sentences describing individual present (positive) and absent (negative) findings in English and Spanish. In total, PadChest-GR contains 7,037 positive and 3,422 negative finding sentences. Every positive finding sentence is associated with up to two independent sets of bounding boxes labelled by different readers and has categorical labels for finding type, locations, and progression. To the best of our knowledge, PadChest-GR is the first manually curated dataset designed to train GRRG models for understanding and interpreting radiological images and generated text. By including detailed localization and comprehensive annotations of all clinically relevant findings, it provides a valuable resource for developing and evaluating GRRG models from CXR images. PadChest-GR can be downloaded under request from https://bimcv.cipf.es/bimcv-projects/padchest-gr/

RNA is a vital biomolecule with numerous roles and functions within cells, and interest in targeting it for therapeutic purposes has grown significantly in recent years. However, fully understanding and predicting RNA behavior, particularly for applications in drug discovery, remains a challenge due to the complexity of RNA structures and interactions. While foundational models in biology have demonstrated success in modeling several biomolecules, especially proteins, achieving similar breakthroughs for RNA has proven more difficult. Current RNA models have yet to match the performance observed in the protein domain, leaving an important gap in computational biology. In this work, we present ChaRNABERT, a suite of sample and parameter-efficient RNA foundational models, that through a learnable tokenization process, are able to reach state-of-the-art performance on several tasks in established benchmarks. We extend its testing in relevant downstream tasks such as RNA-protein and aptamer-protein interaction prediction. Weights and inference code for ChaRNABERT-8M will be provided for academic research use. The other models will be available upon request., Comment: First version. Work in progress

In this paper, we consider Dirichlet boundary value problem involving the anisotropic $p(x)$-Laplacian, where $p(x)= (p_1(x), ..., p_n(x))$, with $p_i(x)> 1$ in $\overline{\Omega}$. Using the topological degree constructed by Berkovits, we prove, under appropriate assumptions on the data, the existence of weak solutions for the given problem. An important contribution is that we are considering the degenerate and the singular cases in the discussion. Finally, according to the compact embedding for anisotropic Sobolev spaces, we point out that the considered boundaru value problem may be critical in some region of $\Omega$.

Understanding the origins of complexity is a fundamental challenge with implications for biological and technological systems. Network theory emerges as a powerful tool to model complex systems. Networks are an intuitive framework to represent inter-dependencies among many system components, facilitating the study of both local and global properties. However, it is unclear whether we can define a universal theoretical framework for evolving networks. While basic growth mechanisms, like preferential attachment, recapitulate common properties such as the power-law degree distribution, they fall short in capturing other system-specific properties. Tinkering, on the other hand, has shown to be very successful in generating modular or nested structures "for-free", highlighting the role of internal, non-adaptive mechanisms in the evolution of complexity. Different network extensions, like hypergraphs, have been recently developed to integrate exogenous factors in evolutionary models, as pairwise interactions are insufficient to capture environmentally-mediated species associations. As we confront global societal and climatic challenges, the study of network and hypergraphs provides valuable insights, emphasizing the importance of scientific exploration in understanding and managing complexity., Comment: Contributed chapter to "Nonlinear Dynamics for Biological Systems", M. Stich, J. Carballido-Landeira (Eds), Springer, Switzerland (submitted, 2024)

We study the co-evolution of black holes (BHs) and their host galaxies in the ASTRID and Illustris-TNG300 cosmological simulations and the Dark Sage Semi-Analytic Model (SAM), focusing on the evolution of the BH mass - stellar mass ($M_{\rm BH}-M_*$) relation. Due to differences in the adopted sub-grid modeling of BH seeding, dynamics, and feedback, the models differ in their predicted redshift evolution of the $M_{\rm BH}-M_*$ relation. We find that it is the interplay between the star formation rate (SFR) and the black hole accretion rate (BHAR) which drives the evolution of the mean relation. We define a quantity $\mathcal{R}$, the ratio between the specific BHAR and SFR (i.e. $\mathcal{R} \equiv\ $sBHAR/sSFR), and demonstrate that it is $\mathcal{R}$ that governs the evolution of individual sources in the $M_{\rm BH}-M_*$ plane. The efficiency of BH growth versus stellar mass growth in the sSFR-sBHAR plane reflects the partitioning of gas between fueling star formation versus BH accretion. This partitioning depends on the implementation of BH dynamics and the nature of how AGN feedback quenches galaxies. In the cosmological simulations (ASTRID and Illustris-TNG300), the BHAR and SFR are intrinsically linked, resulting in a tight $M_{\rm BH}-M_*$ correlation, while the Dark Sage SAM produces a significantly larger scatter. We discuss these results in the context of recently discovered over-massive BHs and massive quenched galaxies at high redshift by the James Webb Space Telescope., Comment: 17 pages, 8 figures. Submitted to ApJ. Comments welcome

Mangroves are dynamic coastal ecosystems that are crucial to environmental health, economic stability, and climate resilience. The monitoring and preservation of mangroves are of global importance, with remote sensing technologies playing a pivotal role in these efforts. The integration of cutting-edge artificial intelligence with satellite data opens new avenues for ecological monitoring, potentially revolutionizing conservation strategies at a time when the protection of natural resources is more crucial than ever. The objective of this work is to provide a comprehensive evaluation of recent deep-learning models on the task of mangrove segmentation. We first introduce and make available a novel open-source dataset, MagSet-2, incorporating mangrove annotations from the Global Mangrove Watch and satellite images from Sentinel-2, from mangrove positions all over the world. We then benchmark three architectural groups, namely convolutional, transformer, and mamba models, using the created dataset. The experimental outcomes further validate the deep learning community's interest in the Mamba model, which surpasses other architectures in all metrics., Comment: 12 pages, accepted to the MACLEAN workshop of ECML/PKDD 2024

As a step towards the ultimate goal of a high-precision mass measurement of doubly-magic $^{100}$Sn, the mass of $^{103}$Sn was measured at the Low Energy Beam and Ion Trap (LEBIT) located at the Facility for Rare Isotope Beams (FRIB). Utilizing the time-of-flight ion cyclotron resonance (ToF-ICR) technique, a mass uncertainty of 3.7~keV was achieved, an improvement by more than an order of magnitude compared to a recent measurement performed in 2023 at the Cooler Storage Ring (CSRe) in Lanzhou. Although the LEBIT and CSRe mass measurements of $^{103}$Sn are in agreement, they diverge from the experimental mass value reported in the 2016 version of the Atomic Mass Evaluation (AME2016), which was derived from the measured $Q_{\beta^+}$ value and the mass of $^{103}$In. In AME2020, this indirectly measured $^{103}$Sn mass was classified as a `seriously irregular mass' and replaced with an extrapolated value, which aligns with the most recent measured values from CSRe and LEBIT. As such, the smoothness of the mass surface is confidently reestablished for $^{103}$Sn. Furthermore, LEBIT's mass measurement of $^{103}$Sn enabled a significant reduction in the mass uncertainties of five parent isotopes which are now dominated by uncertainties in their respective $Q$-values.

The ComPair balloon instrument is a prototype gamma-ray telescope that aims to further develop technology for observing the gamma-ray sky in the MeV regime. ComPair combines four detector subsystems to enable parallel Compton scattering and pair-production detection, critical for observing in this energy range. This includes a 10 layer double-sided silicon strip detector tracker, a virtual Frisch grid low energy CZT calorimeter, a high energy CsI calorimeter, and a plastic scintillator anti-coincidence detector. The inaugural balloon flight successfully launched from the Columbia Scientific Balloon Facility site in Fort Sumner, New Mexico, in late August 2023, lasting approximately 6.5 hours in duration. In this proceeding, we discuss the development of the ComPair Since balloon payload, the performance during flight, and early results., Comment: 13 pages, 12 figures

Precise mass measurements of the odd-odd $^{108, 110, 112, 114, 116}$Rh ground and isomeric states were performed using the Canadian Penning Trap at Argonne National Laboratory, showing a good agreement with recent JYFLTRAP measurements. A new possible isomeric state of $^{114}$Rh was also observed. These isotopes are part of the longest odd-odd chain of identical ground state spin-parity assignment, of 1$^+$, spanning $^{104-118}$Rh, despite being in a region of deformation. Realistic phenomenological mean-field calculations using ``universal'' Wood-Saxon Hamiltonian were performed, explaining this phenomenon for the first time. In addition, multi-quasiparticle blocking calculations were conducted to study the configuration of low-lying states in the odd-odd Rh nuclei and elucidate the observed anomalous isomeric yield ratio of $^{114}$Rh.

The Optional Public Goods Game is a three-strategy game in which an individual can play as a cooperator or defector or decide not to participate. Despite its simplicity, this model can effectively represent many human social dilemmas, such as those found in the use of public services, environmental concerns, or other activities related to society. In this contribution, we present a comprehensive analysis of the conditions under which spontaneous, sustained cooperation emerges and the characteristics of these cooperative states. Through simulations, we demonstrate the conditions leading to the coexistence of the three strategies in a steady equilibrium or the alternate dominance of each strategy in a rock-paper-scissors fashion. The results identify each of the possible scenarios in terms of two key parameters: the multiplication rate of the public good game (reward) and the size of the group of potential players. We also discuss other details of the game that may influence the appearance of cycles, along with relevant characteristics of these cycles, such as the prevalence of cooperation., Comment: 8 pages, 6 figures

Atomic masses are a foundational quantity in our understanding of nuclear structure, astrophysics and fundamental symmetries. The long-standing goal of creating a predictive global model for the binding energy of a nucleus remains a significant challenge, however, and prompts the need for precise measurements of atomic masses to serve as anchor points for model developments. We present precise mass measurements of neutron-rich Ru and Pd isotopes performed at the Californium Rare Isotope Breeder Upgrade facility at Argonne National Laboratory using the Canadian Penning Trap mass spectrometer. The masses of $^{108}$Ru, $^{110}$Ru and $^{116}$Pd were measured to a relative mass precision $\delta m/m \approx 10^{-8}$ via the phase-imaging ion-cyclotron-resonance technique, and represent an improvement of approximately an order of magnitude over previous measurements. These mass data were used in conjunction with the physically interpretable machine learning (PIML) model, which uses a mixture density neural network to model mass excesses via a mixture of Gaussian distributions. The effects of our new mass data on a Bayesian-updating of a PIML model are presented., Comment: 6 pages, 4 figures

The topics of interest are location analysis and related problems. This includes location models, networks, transportation, logistics, exact and heuristic solution methods, and computational geometry, among many others., Comment: The proceedings book of the previous editions can be found at arXiv:2002.08287 arXiv:2002.08293 arXiv:2002.08300 arXiv:2002.01702 arXiv:2202.13878 . arXiv:2309.08337 . The XIII International Workshop on Locational Analysis and Related Problems will take place during September 4--6, 2024 in Granada (Spain). It is organized by the Spanish Location Network, REDLOCA, and the Location Group, GELOCA, from the Spanish Society of Statistics and Operations Research (SEIO). The Spanish Location Network is a group of 100+ researchers from several Spanish universities organized into 7 thematic groups. The Network has been funded by the Spanish Government since 2003

We present a complete analysis of Fermi Large Area Telescope (LAT) data of GRB 221009A, the brightest Gamma-Ray Burst (GRB) ever detected. The burst emission above 30 MeV detected by the LAT preceded by 1 s the low-energy (< 10 MeV) pulse that triggered the Fermi Gamma-Ray Burst Monitor (GBM), as has been observed in other GRBs. The prompt phase of GRB 221009A lasted a few hundred seconds. It was so bright that we identify a Bad Time Interval (BTI) of 64 seconds caused by the extremely high flux of hard X-rays and soft gamma rays, during which the event reconstruction efficiency was poor and the dead time fraction quite high. The late-time emission decayed as a power law, but the extrapolation of the late-time emission during the first 450 seconds suggests that the afterglow started during the prompt emission. We also found that high-energy events observed by the LAT are incompatible with synchrotron origin, and, during the prompt emission, are more likely related to an extra component identified as synchrotron self-Compton (SSC). A remarkable 400 GeV photon, detected by the LAT 33 ks after the GBM trigger and directionally consistent with the location of GRB 221009A, is hard to explain as a product of SSC or TeV electromagnetic cascades, and the process responsible for its origin is uncertain. Because of its proximity and energetic nature, GRB 221009A is an extremely rare event., Comment: 60 pages, 38 figures, 9 tables

The well-known Cornell quark-antiquark potential in momentum space contains singularities both in its one-gluon-exchange (OGE) and linear confining parts, which prevents a direct use of the convenient Nystr\"om method to solve the corresponding bound-state integral equation for the meson masses. While it has been known for a long time how the Coulomb-type singularity in the OGE potential can be treated with a subtraction technique, only very complicated methods have been developed to deal with the stronger singularity in the linear potential. In this work, we present a simple subtraction method to remove this singularity from the kernel, such that the Nystr\"om method becomes applicable. Derivatives of the wave function, that appear as a result of the subtraction, are represented by means of interpolating functions, for which we found Lagrange polynomials to be very efficient. Test calculations show excellent agreement with exactly known energy eigenvalues. By increasing the number of integration points and the order of the Lagrange interpolation polynomials, extremely high accuracy can be achieved. This method can also be extended to relativistic Bethe-Salpeter type equations with singular kernels., Comment: 14 pages; revised text in Abstract, Introduction, and Summary and Conclusions; some typos in equations corrected and incorrectly rounded figures in Table 1 corrected; References updated

The Canadian Penning Trap mass spectrometer (CPT) has conducted precision mass measurements of neutron-rich nuclides from the CAlifornia Rare Isotope Breeder Upgrade (CARIBU) of the Argonne Tandem Linac Accelerator System (ATLAS) facility at Argonne National Laboratory using the Phase-Imaging Ion-Cyclotron-Resonance (PI-ICR) technique for over half a decade. Here we discuss the CPT system, and methods to improve accuracy and precision in mass measurement using PI-ICR including some optimization techniques and recently studied systematic effects., Comment: 14 pages, 7 figures

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

Between 2001 and 2023, we obtained high spectral resolution mid-infrared observations of Io using the TEXES instrument at NASA's Infrared Telescope Facility. These observations were centered at 529.8 cm-1 (18.88 {\mu}m) and include several SO2 absorption lines. By modeling the shapes and strengths of these absorption lines, we are able to determine how Io's SO2 atmospheric density varies over the 22-year time period, covering nearly two Jovian years. Previous analysis has shown that the density of Io's atmosphere on the anti-Jovian hemisphere exhibits clear seasonal temporal variability, which can be modeled as the sum of a seasonally-varying frost sublimation component and a constant component, assumed to be volcanic. The new data show that the seasonal pattern repeats during the second Jovian year, confirming the importance of sublimation support. The considerable longitudinal variability in Io's atmospheric density found in previous work is also stable over the second Jovian year with the SO2 column density on the Jupiter-facing hemisphere being 5--8 times lower than the anti-Jovian hemisphere. For the first time, we detect seasonal variability on the Jupiter-facing hemisphere as well. This can also be modeled as a combination of sublimation and a small constant source. The lower atmospheric density on the Jupiter-facing hemisphere can plausibly be explained by the daily Jupiter eclipses, which decrease the surface temperature and therefore reduce the sublimation-driven component of the atmosphere, combined with a lower level of volcanic activity directly emitting SO2 into the atmosphere., Comment: Accepted in Icarus

The ComPair gamma-ray telescope is a technology demonstrator for a future gamma-ray telescope called the All-sky Medium Energy Gamma-ray Observatory (AMEGO). The instrument is composed of four subsystems, a double-sided silicon strip detector, a virtual Frisch grid CdZnTe calorimeter, a CsI:Tl based calorimeter, and an anti-coincidence detector (ACD). The CsI calorimeter's goal is to measure the position and energy deposited from high-energy events. To demonstrate the technological readiness, the calorimeter has flown onboard a NASA scientific balloon as part of the GRAPE-ComPair mission and accumulated around 3 hours of float time at an altitude of 40 km. During the flight, the CsI calorimeter observed background radiation, Regener-Pfotzer Maximum, and several gamma-ray activation lines originating from aluminum.

We investigate the collective behavior of a system of social agents subject to the competition between two mass media influences considered as external fields. We study under what conditions either of two mass media with different intensities can impose its message to the majority. In addition to a collective state dominated by the stronger mass media and a disordered phase, we characterize two nontrivial effects as the parameters of the system are varied: (i) the appearance of a majority sharing the state of the weaker mass media, and (ii) the emergence of an alternative ordering in a state different from those of either media. We explore the dependence of both phenomena on the topology of the network of interactions. We show that the presence of long-range interactions rather than random connections is essential for the occurrence of both effects. The model can be extended to include multiple mass media and we illustrate it by considering three mass media fields acting on the system. Nontrivial collective behaviors persist for some ranges of parameters: the weakest mass media can convince the majority, and the system can spontaneously order against all applied fields., Comment: 8 pages, 15 figures, sent to Physical Review E

A mathematical model is developed to describe column adsorption when the contaminant constitutes a significant amount of the fluid. This requires modelling the variation of pressure and velocity, in addition to the usual advection-diffusion-adsorption and kinetic equations describing concentration and adsorption rates. The model builds on previous work based on a linear kinetic equation, to include both physical and chemical adsorption. A semi-analytical solution is developed and validated against a numerical solution. The model is tested against experimental data for the adsorption of large quantities of CO$_2$ from a helium mixture, with a CO$_2$ volume fraction ranging from 14% to 69%, and a N$_2$ mixture with 16% to 33% CO$_2$ volume fraction. Our results show a significant improvement with respect to models for the removal of trace amounts of contaminant., Comment: 30 pages, 9 figures, 6 tables. Contains Supplementary Material (8 pages,2 figures, 2 tables)

Tuberculosis (TB) remains a significant global health challenge, with pediatric cases posing a major concern. The World Health Organization (WHO) advocates for chest X-rays (CXRs) for TB screening. However, visual interpretation by radiologists can be subjective, time-consuming and prone to error, especially in pediatric TB. Artificial intelligence (AI)-driven computer-aided detection (CAD) tools, especially those utilizing deep learning, show promise in enhancing lung disease detection. However, challenges include data scarcity and lack of generalizability. In this context, we propose a novel self-supervised paradigm leveraging Vision Transformers (ViT) for improved TB detection in CXR, enabling zero-shot pediatric TB detection. We demonstrate improvements in TB detection performance ($\sim$12.7% and $\sim$13.4% top AUC/AUPR gains in adults and children, respectively) when conducting self-supervised pre-training when compared to fully-supervised (i.e., non pre-trained) ViT models, achieving top performances of 0.959 AUC and 0.962 AUPR in adult TB detection, and 0.697 AUC and 0.607 AUPR in zero-shot pediatric TB detection. As a result, this work demonstrates that self-supervised learning on adult CXRs effectively extends to challenging downstream tasks such as pediatric TB detection, where data are scarce., Comment: 5 pages, 3 figures, 2 tables. This paper has been accepted at IEEE ISBI 2024

Accurate and robust navigation in unstructured environments requires fusing data from multiple sensors. Such fusion ensures that the robot is better aware of its surroundings, including areas of the environment that are not immediately visible but were visible at a different time. To solve this problem, we propose a method for traversability prediction in challenging outdoor environments using a sequence of RGB and depth images fused with pose estimations. Our method, termed WayFASTER (Waypoints-Free Autonomous System for Traversability with Enhanced Robustness), uses experience data recorded from a receding horizon estimator to train a self-supervised neural network for traversability prediction, eliminating the need for heuristics. Our experiments demonstrate that our method excels at avoiding obstacles, and correctly detects that traversable terrains, such as tall grass, can be navigable. By using a sequence of images, WayFASTER significantly enhances the robot's awareness of its surroundings, enabling it to predict the traversability of terrains that are not immediately visible. This enhanced awareness contributes to better navigation performance in environments where such predictive capabilities are essential., Comment: Accepted for the 2024 IEEE International Conference on Robotics and Automation (ICRA 2024)

We propose a mathematical model for describing column adsorption processes where large amounts of contaminant are removed from a carrier gas. The large mass loss causes velocity and pressure to be variables which must then be determined along with the contaminant and gas concentrations and adsorbed quantity. The adsorption rate is described using a Langmuir sink, which is physically more sensible than the linear sink used in a previous study. The proposed model is solved numerically and using a traveling wave approach. The analytical solutions are consistent with previous models with fixed gas velocity and provide excellent agreement when validated against experimental data., Comment: 10 pages, 3 figures, 1 table