Anatomical trees are critical for clinical diagnosis and treatment planning, yet their complex and diverse geometry make accurate representation a significant challenge. Motivated by the latest advances in large language models, we introduce an autoregressive method for synthesizing anatomical trees. Our approach first embeds vessel structures into a learned discrete vocabulary using a VQ-VAE architecture, then models their generation autoregressively with a GPT-2 model. This method effectively captures intricate geometries and branching patterns, enabling realistic vascular tree synthesis. Comprehensive qualitative and quantitative evaluations reveal that our technique achieves high-fidelity tree reconstruction with compact discrete representations. Moreover, our B-spline representation of vessel cross-sections preserves critical morphological details that are often overlooked in previous' methods parameterizations. To the best of our knowledge, this work is the first to generate blood vessels in an autoregressive manner. Code is available at this https URL.

In a seminal work, K. Segerberg introduced a deontic logic called DAL to investigate normative reasoning over actions. DAL marked the beginning of a new area of research in Deontic Logic by shifting the focus from deontic operators on propositions to deontic operators on actions. In this work, we revisit DAL and provide a complete algebraization for it. In our algebraization we introduce deontic action algebras -- algebraic structures consisting of a Boolean algebra for interpreting actions, a Boolean algebra for interpreting formulas, and two mappings from one Boolean algebra to the other interpreting the deontic concepts of permission and prohibition. We elaborate on how the framework underpinning deontic action algebras enables the derivation of different deontic action logics by removing or imposing additional conditions over either of the Boolean algebras. We leverage this flexibility to demonstrate how we can capture in this framework several logics in the DAL family. Furthermore, we introduce four variations of DAL by: (a) enriching the algebra of formulas with propositions on states, (b) adopting a Heyting algebra for state propositions, (c) adopting a Heyting algebra for actions, and (d) adopting Heyting algebras for both. We illustrate these new deontic action logics with examples and establish their algebraic completeness.

We report on a search for sub-GeV dark matter (DM) particles interacting with electrons using the DAMIC-M prototype detector at the Modane Underground Laboratory. The data feature a significantly lower detector single $e^-$ rate (factor 50) compared to our previous search, while also accumulating a ten times larger exposure of $\sim$1.3 kg-day. DM interactions in the skipper charge-coupled devices (CCDs) are searched for as patterns of two or three consecutive pixels with a total charge between 2 and 4 $e^-$. We find 144 candidates of 2 $e^-$ and 1 candidate of 4 $e^-$, where 141.5 and 0.071, respectively, are expected from background. With no evidence of a DM signal, we place stringent constraints on DM particles with masses between 1 and 1000 MeV/$c^2$ interacting with electrons through an ultra-light or heavy mediator. For large ranges of DM masses below 1 GeV/c$^2$, we exclude theoretically-motivated benchmark scenarios where hidden-sector particles are produced as a major component of DM in the Universe through the freeze-in or freeze-out mechanisms.

Multifractal analysis studies signals, functions, images or fields via the fluctuations of their local regularity along time or space, which capture crucial features of their temporal/spatial dynamics. It has become a standard signal and image processing tool and is commonly used in numerous applications of different natures. In its common formulation, it relies on the H\"older exponent as a measure of local regularity, which is by nature restricted to positive values and can hence be used for locally bounded functions only. In this contribution, it is proposed to replace the H\"older exponent with a collection of novel exponents for measuring local regularity, the $p$-exponents. One of the major virtues of $p$-exponents is that they can potentially take negative values. The corresponding wavelet-based multiscale quantities, the $p$-leaders, are constructed and shown to permit the definition of a new multifractal formalism, yielding an accurate practical estimation of the multifractal properties of real-world data. Moreover, theoretical and practical connections to and comparisons against another multifractal formalism, referred to as multifractal detrended fluctuation analysis, are achieved. The performance of the proposed $p$-leader multifractal formalism is studied and compared to previous formalisms using synthetic multifractal signals and images, illustrating its theoretical and practical benefits. The present contribution is complemented by a companion article studying in depth the theoretical properties of $p$-exponents and the rich classification of local singularities it permits.

For decades, the theoretical understanding of planetary nebulae (PNe) has remained in tension with the observed universal bright-end cutoff of the PN luminosity function (PNLF). While the brightest younger PN populations are expected to be brighter in their [OIII] emission than observed, recent studies have proposed circumnebular extinction to be a key ingredient for bringing their brightness down to the observed bright end. In this work we use the recently introduced PICS (PNe In Cosmological Simulations) framework to investigate the impact of different circumnebular extinction treatments on the modeled PNe and their PNLF for a large range of stellar ages and metallicities. We test how different slopes in the observed relation of extinction versus central star mass modify the bright-end cutoffs of the PNLF, finding that steeper slopes lead to large changes for young stellar populations. In contrast, the differences for older PNe are much smaller. However, for individual PNe, the extinctions observed in nearby galaxies appear to be much higher than the models predict, showing that improvements on both the modeling and observational sides are needed to gain a better understanding of the brightest and strongly extincted PNe. These findings further advance the theoretical foundation for interpreting observed extragalactic PN populations coming from more complex composite stellar populations in the future.

Multicriteria decision-making methods exhibit critical dependence on the choice of normalization techniques, where different selections can alter 20-40% of the final rankings. Current practice is characterized by the ad-hoc selection of methods without systematic robustness evaluation. We present a framework that addresses this methodological uncertainty through automated exploration of the scaling transformation space. The implementation leverages the existing Scikit-Criteria infrastructure to automatically generate all possible methodological combinations and provide robust comparative analysis.

We present a comprehensive study of the X-ray binary system XTE~J1550-564, with the primary objective of analyzing the evolution of the black hole's spin parameter. To achieve this objective, we embarked on the necessary step of identifying a plausible progenitor for the system. Using a set of models covering various parameter combinations, we were able to replicate the system's observed characteristics within acceptable error margins, including fundamental parameters such as component masses, orbital period, donor luminosity, and effective temperature. The model results indicate the possibility of diverse evolutionary pathways for the system, highlighting the significant role played by the initial mass of the donor star and the efficiency of mass transfer episodes. While some models are well-aligned with estimates of the mass transfer rate, they all fall short of explaining the black hole's observed moderate spin ($a^* = 0.49$). We also explored alternative magnetic braking prescriptions, finding that only an extreme and fully conservative scenario, based on the convection and rotation boosted prescription, can reproduce the observed spin and only in a marginal way. Our study attempts to shed light on the complex dynamics of black hole X-ray binaries and the challenges of explaining their observed properties with theoretical models.

We present a data-driven generative framework for synthesizing blood vessel 3D geometry. This is a challenging task due to the complexity of vascular systems, which are highly variating in shape, size, and structure. Existing model-based methods provide some degree of control and variation in the structures produced, but fail to capture the diversity of actual anatomical data. We developed VesselVAE, a recursive variational Neural Network that fully exploits the hierarchical organization of the vessel and learns a low-dimensional manifold encoding branch connectivity along with geometry features describing the target surface. After training, the VesselVAE latent space can be sampled to generate new vessel geometries. To the best of our knowledge, this work is the first to utilize this technique for synthesizing blood vessels. We achieve similarities of synthetic and real data for radius (.97), length (.95), and tortuosity (.96). By leveraging the power of deep neural networks, we generate 3D models of blood vessels that are both accurate and diverse, which is crucial for medical and surgical training, hemodynamic simulations, and many other purposes.

The Středa formula establishes a fundamental connection between the topological invariants characterizing the bulk of topological matter and the presence of gapless edge modes. In this work, we extend the Středa formula to periodically driven systems, providing a rigorous framework to elucidate the unconventional bulk-boundary correspondence of Floquet systems, while offering a link between Floquet winding numbers and tractable response functions. Using the Sambe representation of periodically driven systems, we analyze the response of the unbounded Floquet density of states to a magnetic perturbation. This Floquet-Středa response is regularized through Cesàro summation, yielding a well-defined, quantized result within spectral gaps. The response features two physically distinct contributions: a quantized charge flow between edge and bulk, and an anomalous energy flow between the system and the drive, offering new insight into the nature of anomalous edge states. This result rigorously connects Floquet winding numbers to the orbital magnetization density of Floquet states and holds broadly, from clean to disordered and inhomogeneous systems. This is further supported by providing a real-space formulation of the Floquet-Středa response, which introduces a local topological marker suited for periodically driven settings. In translationally-invariant systems, the framework yields a remarkably simple expression for Floquet winding numbers involving geometric properties of Floquet-Bloch bands. A concrete experimental protocol is proposed to extract the Floquet-Středa response via particle-density measurements in systems coupled to engineered baths. Finally, by expressing the topological invariants through the magnetic response of the Floquet density of states, this approach opens a promising route toward the topological characterization of interacting driven phases.

We analyse deep images from the VISTA survey of the Magellanic Clouds in the YJKs filters, covering 14 sqrdeg (10 tiles), split into 120 subregions, and comprising the main body and Wing of the Small Magellanic Cloud (SMC). We apply a colour--magnitude diagram reconstruction method that returns their best-fitting star formation rate SFR(t), age-metallicity relation (AMR), distance and mean reddening, together with 68% confidence intervals. The distance data can be approximated by a plane tilted in the East-West direction with a mean inclination of 39 deg, although deviations of up to 3 kpc suggest a distorted and warped disk. After assigning to every observed star a probability of belonging to a given age-metallicity interval, we build high-resolution population maps. These dramatically reveal the flocculent nature of the young star-forming regions and the nearly smooth features traced by older stellar generations. They document the formation of the SMC Wing at ages <0.2 Gyr and the peak of star formation in the SMC Bar at 40 Myr. We clearly detect periods of enhanced star formation at 1.5 Gyr and 5 Gyr. The former is possibly related to a new feature found in the AMR, which suggests ingestion of metal-poor gas at ages slightly larger than 1 Gyr. The latter constitutes a major period of stellar mass formation. We confirm that the SFR(t) was moderately low at even older ages.

The Neumann Equation of State (EQS) allows obtaining the value of the surface free energy of a solid ${\gamma}_{SV}$ from the contact angle $({\theta})$ of a probe liquid with known surface tension ${\gamma}_{LV}$. The value of ${\gamma}_{SV}$ is obtained by numerical methods solving the corresponding EQS. In this work, we analyzed the discrepancies between the values of ${\gamma}_{SV}$ obtained using the three versions of the EQS reported in the literature. The condition number of the different EQS was used to analyze their sensitivity to the uncertainty in the ${\theta}$ values. Polynomials fit to one of these versions of EQS are proposed to obtain values of ${\gamma}_{SV}$ directly from contact angles $({\gamma}_{SV} ({\theta}))$ of particular probe liquids. Finally, a general adjusted polynomial is presented to obtain the values of ${\gamma}_{SV}$ not restricted to a particular probe liquid $({\gamma}_{SV}({\theta},{\gamma}_{LV}))$. Results showed that the three versions of EQS present non-negligible discrepancies, especially at high values of ${\theta}$. The sensitivity of the EQS to the uncertainty in the values of ${\theta}$ is very similar in the three versions and depends on the probe liquid used (greater sensitivity at higher ${\gamma}_{LV})$ and on the value of ${\gamma}_{SV}$ of the solid (greater sensitivity at lower ${\gamma}_{SV})$. The discrepancy of the values obtained by numerical resolution of both the fifth-order fit polynomials and the general fit polynomial was low, no larger than ${\pm}0.40\,mJ/m^{2}$. The polynomials obtained allow the analysis and propagation of the uncertainty of the input variables in the determination of ${\gamma}_{SV}$ in a simple and fast way.

The Coherent Neutrino-Nucleus Interaction Experiment (CONNIE) is taking data at the Angra 2 nuclear reactor with the aim of detecting the coherent elastic scattering of reactor antineutrinos with silicon nuclei using charge-coupled devices (CCDs). In 2019 the experiment operated with a hardware binning applied to the readout stage, leading to lower levels of readout noise and improving the detection threshold down to 50 eV. The results of the analysis of 2019 data are reported here, corresponding to the detector array of 8 CCDs with a fiducial mass of 36.2 g and a total exposure of 2.2 kg-days. The difference between the reactor-on and reactor-off spectra shows no excess at low energies and yields upper limits at 95% confidence level for the neutrino interaction rates. In the lowest-energy range, 50-180 eV, the expected limit stands at 34 (39) times the standard model prediction, while the observed limit is 66 (75) times the standard model prediction with Sarkis (Chavarria) quenching factors.

Amortization systems are used widely in economy to generate payment schedules to repaid an initial debt with its interest. We present a generalization of these amortization systems by introducing the mathematical formalism of quantum mechanics based on vector spaces. Operators are defined for debt, amortization, interest and periodic payment and their mean values are computed in different orthonormal basis. The vector space of the amortization system will have dimension M, where M is the loan maturity and the vectors will have a SO(M) symmetry, yielding the possibility of rotating the basis of the vector space while preserving the distance among vectors. The results obtained are useful to add degrees of freedom to the usual amortization systems without affecting the interest profits of the lender while also benefitting the borrower who is able to alter the payment schedules. Furthermore, using the tensor product of algebras, we introduce loans entanglement in which two borrowers can correlate the payment schedules without altering the total repaid.

Speaker verification (SV) systems are currently being used to make sensitive decisions like giving access to bank accounts or deciding whether the voice of a suspect coincides with that of the perpetrator of a crime. Ensuring that these systems are fair and do not disfavor any particular group is crucial. In this work, we analyze the performance of several state-of-the-art SV systems across groups defined by the accent of the speakers when speaking English. To this end, we curated a new dataset based on the VoxCeleb corpus where we carefully selected samples from speakers with accents from different countries. We use this dataset to evaluate system performance for several SV systems trained with VoxCeleb data. We show that, while discrimination performance is reasonably robust across accent groups, calibration performance degrades dramatically on some accents that are not well represented in the training data. Finally, we show that a simple data balancing approach mitigates this undesirable bias, being particularly effective when applied to our recently-proposed discriminative condition-aware backend.

The Red-Giant Branch Bump (RGBB) is one of the most noteworthy features in the red-giant luminosity function of stellar clusters. It is caused by the passage of the hydrogen-burning shell through the composition discontinuity left at the point of the deepest penetration by the convective envelope. When crossing the discontinuity the usual trend in increasing luminosity reverses for a short time before it increases again, causing a zig-zag in the evolutionary track. In spite of its apparent simplicity the actual physical reason behind the decrease in luminosity is not well understood and several different explanations have been offered. Here we use a recently proposed simple toy-model for the structure of low-mass red giants, together with previous results, to show beyond reasonable doubt that the change in luminosity at the RGBB can be traced to the change in the mean molecular weight of the layers on top of the burning shell. And that these changes happen on a nuclear timescale. The change in the effective mean molecular weight, as the burning shell approaches the discontinuity, causes a drop in the temperature of the burning shell which is attenuated by the consequent feedback contraction of the layers immediately below the burning shell. Our work shows that, when applied correctly, including the feedback on the structure of the core together with of the increase in the mass of the core, shell-source homology relations do a great quantitative job in explaining the properties of full evolutionary models at the RGBB.

Data processing pipelines represent an important slice of the astronomical software library that include chains of processes that transform raw data into valuable information via data reduction and analysis. In this work we present Corral, a Python framework for astronomical pipeline generation. Corral features a Model-View-Controller design pattern on top of an SQL Relational Database capable of handling: custom data models; processing stages; and communication alerts, and also provides automatic quality and structural metrics based on unit testing. The Model-View-Controller provides concept separation between the user logic and the data models, delivering at the same time multi-processing and distributed computing capabilities. Corral represents an improvement over commonly found data processing pipelines in Astronomy since the design pattern eases the programmer from dealing with processing flow and parallelization issues, allowing them to focus on the specific algorithms needed for the successive data transformations and at the same time provides a broad measure of quality over the created pipeline. Corral and working examples of pipelines that use it are available to the community at this https URL.

The eRisk laboratory aims to address issues related to early risk detection on the Web. In this year's edition, three tasks were proposed, where Task 2 was about early detection of signs of anorexia. Early risk detection is a problem where precision and speed are two crucial objectives. Our research group solved Task 2 by defining a CPI+DMC approach, addressing both objectives independently, and a time-aware approach, where precision and speed are considered a combined single-objective. We implemented the last approach by explicitly integrating time during the learning process, considering the ERDE{\theta} metric as the training objective. It also allowed us to incorporate temporal metrics to validate and select the optimal models. We achieved outstanding results for the ERDE50 metric and ranking-based metrics, demonstrating consistency in solving ERD problems.

Viruses and their hosts are involved in an 'arms race' where they continually evolve mechanisms to overcome each other. It has long been proposed that intrinsic disorder provides a substrate for the evolution of viral hijack functions and that short linear motifs (SLiMs) are important players in this process. Here, we review evidence in support of this tenet from two model systems: the papillomavirus E7 protein and the adenovirus E1A protein. Phylogenetic reconstructions reveal that SLiMs appear and disappear multiple times across evolution, providing evidence of convergent evolution within individual viral phylogenies. Multiple functionally related SLiMs show strong co-evolution signals that persist across long distances in the primary sequence and occur in unrelated viral proteins. Moreover, changes in SLiMs are associated with changes in phenotypic traits such as host range and tropism. Tracking viral evolutionary events reveals that host switch events are associated with the loss of several SLiMs, suggesting that SLiMs are under functional selection and that changes in SLiMs support viral adaptation. Fine-tuning of viral SLiM sequences can improve affinity, allowing them to outcompete host counterparts. However, viral SLiMs are not always competitive by themselves, and tethering of two suboptimal SLiMs by a disordered linker may instead enable viral hijack. Coevolution between the SLiMs and the linker indicates that the evolution of disordered regions may be more constrained than previously thought. In summary, experimental and computational studies support a role for SLiMs and intrinsic disorder in viral hijack functions and in viral adaptive evolution.

By constructing a model of spacetime having a strong curvature singularity in which causal geodesics are complete, but more generic causal curves are not, we explicitly show that some electrostatic field configurations on that background are bounded on every open punctured neighborhood of the curvature singularity. Our calculations are performed using the analog gravity description provided by Plebanski and Tamm, according to which the characterization of the electromagnetic field on a generic curved background is equivalent to solving Maxwell's equations in flat space with a matter content verifying certain nontrivial constitutive relations. The regularity of the electric field as it approaches what could be considered the worst conceivable physical condition, opens the door to further investigation into the possibility of propagating signals capable of crossing a spacetime singularity.

Symbiotic stars are binaries in which a cool and evolved star of luminosity class I-III accretes onto a smaller companion. However, direct accretion signatures like disc flickering and boundary layer X-rays are typically outshone or suppressed by the luminous giant, shell burning on the accreting white dwarf, and the illuminated wind nebula. We present a new way to find symbiotics that is less biased against directly-detectable accretion discs than methods based on narrow-band H$\alpha$ photometry or objective prism plate surveys. We identified outliers in SkyMapper survey photometry, using reconstructed uvg snapshot colours and rapid variability among the three exposures of each 20-minute SkyMapper Main Survey filter sequence, from a sample of 366,721 luminous red objects. We found that SkyMapper catalog colours of large-amplitude pulsating giants must be corrected for variability, and that flickering is detectable with only three data points. Our methods probed a different region of parameter space than a recent search for accreting-only symbiotics in the GALAH survey, while being surprisingly concordant with another survey's infrared detection algorithm. We discovered 12 new symbiotics, including four with optical accretion disc flickering. Two of the optical flickerers exhibited boundary-layer hard X-rays. We also identified 10 symbiotic candidates, and discovered likely optical flickering in the known symbiotic V1044 Cen (CD-36 8436). We conclude that at least 20% of the true population of symbiotics exhibit detectable optical flickering from the inner accretion disc, the majority of which do not meet the H$\alpha$ detection thresholds used to find symbiotics in typical narrow-band surveys.