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Most existing traffic video datasets including Waymo are structured, focusing predominantly on Western traffic, which hinders global applicability. Specifically, most Asian scenarios are far more complex, involving numerous objects with distinct motions and behaviors. Addressing this gap, we present a new dataset, DAVE, designed for evaluating perception methods with high representation of Vulnerable Road Users (VRUs: e.g. pedestrians, animals, motorbikes, and bicycles) in complex and unpredictable environments. DAVE is a manually annotated dataset encompassing 16 diverse actor categories (spanning animals, humans, vehicles, etc.) and 16 action types (complex and rare cases like cut-ins, zigzag movement, U-turn, etc.), which require high reasoning ability. DAVE densely annotates over 13 million bounding boxes (bboxes) actors with identification, and more than 1.6 million boxes are annotated with both actor identification and action/behavior details. The videos within DAVE are collected based on a broad spectrum of factors, such as weather conditions, the time of day, road scenarios, and traffic density. DAVE can benchmark video tasks like Tracking, Detection, Spatiotemporal Action Localization, Language-Visual Moment retrieval, and Multi-label Video Action Recognition. Given the critical importance of accurately identifying VRUs to prevent accidents and ensure road safety, in DAVE, vulnerable road users constitute 41.13% of instances, compared to 23.71% in Waymo. DAVE provides an invaluable resource for the development of more sensitive and accurate visual perception algorithms in the complex real world. Our experiments show that existing methods suffer degradation in performance when evaluated on DAVE, highlighting its benefit for future video recognition research.

Robotic telescope networks play an important role in capturing early and bright optical afterglows, providing critical insights into the energetics and emission mechanisms of GRBs. In this study, we analyze GRB 230204B, an exceptionally energetic and multi-pulsed long GRB, detected by the Fermi GBM and MAXI detectors, with an isotropic equivalent gamma-ray energy exceeding 10$^{54}$ erg. Time-resolved spectral analysis reveals a transition in the prompt emission from hard (sub-photospheric dominated) spectra during early pulses to softer (synchrotron radiation dominated) spectra in later pulses, indicative of a hybrid jet composition. We report the discovery and characterization of the optical afterglow using the MASTER and BOOTES robotic telescope networks, alongside long-term radio observations extending to 335 days post-burst with the ATCA. At ~1.3 ks post-burst, the optical luminosity was exceptionally high, surpassing even other bright GRBs, such as GRB 221009A (the ``BOAT"). Multi-wavelength modeling, incorporating data from MASTER, BOOTES, DOT, Swift/XRT, and radio observations, was conducted using an external ISM forward-shock top-hat jet model with afterglowpy. The results reveal a narrow and highly collimated jet with a circumburst density of n$_{0}$ ~ 28.12 cm$^{-3}$, kinetic energy E$_{K}$ ~ 4.18 x 10$^{55}$ erg, and a relatively low value of $\epsilon_{B}$ = 2.14 x 10$^{-6}$, indicating shock-compression of the magnetic field in the surrounding interstellar medium. We constrained a low radiative efficiency of ~ 4.3 %. This study highlights the indispensable contribution of robotic networks to early afterglow observations and advances our understanding of GRB 230204B unique characteristics and underlying jet physics., Comment: 27 pages, 12 figures, 8 tables, submitted

We use granular regulatory data on euro interest rate swap trades between January 2021 and June 2023 to assess whether derivative positions of Italian banks can offset losses on their debt securities holdings should interest rates rise unexpectedly. At the aggregate level of the banking system, we find that a 100-basis-point upward shift of the yield curve increases on average the value of swaps by 3.65% of Common Equity Tier 1 (CET1), compensating in part for the losses of 2.64% and 5.98% of CET1 recorded on debt securities valued at fair value and amortised cost. Variation exists across institutions, with some bank swap positions playing an offsetting role and some exacerbating bond market exposures to interest rate risk. Nevertheless, we conclude that, on aggregate, Italian banks use swaps as hedging instruments to reduce their interest rate exposures, which improves their ability to cope with the recent tightening of monetary policy. Finally, we draw on our swap pricing model to conduct an extensive data quality analysis of the transaction-level information available to authorities, and we show that the errors in fitting value changes over time are significantly lower compared to those in fitting the values themselves.

A numerical algorithm (implemented in Matlab) for computing the zeros of the parabolic cylinder function $U(a,z)$ in domains of the complex plane is presented. The algorithm uses accurate approximations to the first zero plus a highly efficient method based on a fourth-order fixed point method with the parabolic cylinder functions computed by Taylor series and carefully selected steps, to compute the rest of the zeros. For $|a|$ small, the asymptotic approximations are complemented with a few fixed point iterations requiring the evaluation of $U(a,z)$ and $U'(a,z)$ in the region where the complex zeros are located. Liouville-Green expansions are derived to enhance the performance of a computational scheme to evaluate $U(a,z)$ and $U'(a,z)$ in that region. Several tests show the accuracy and efficiency of the numerical algorithm.

As minimum area SRAM bit-cells are obtained when using cell ratio and pull-up ratio of 1, we analyze the possibility of decreasing the cell ratio from the conventional values comprised between 1.5-2.5 to 1. The impact of this option on area, power, performance and stability is analyzed showing that the most affected parameter is read stability, although this impact can be overcome using some of the read assist circuits proposed in the literature. The main benefits are layout regularity enhancement, with its consequent higher tolerance to variability, cell area reduction by 25% (with respect to a cell having a cell ratio of 2), leakage current improvement by a 35%, as well as energy dissipation reduction and a soft error rate per bit improvement of around 30%., Comment: 9 pages, 13 figures

Analyzing large datasets and summarizing it into useful information is the heart of the data mining process. In healthcare, information can be converted into knowledge about patient historical patterns and possible future trends. During the COVID-19 pandemic, data mining COVID-19 patient information poses an opportunity to discover patterns that may signal that the patient is at high risk for death. COVID-19 patients die from sepsis, a complex disease process involving multiple organ systems. We extracted the variables physicians are most concerned about regarding viral septic infections. With the aim of distinguishing COVID-19 patients who survive their hospital stay and those COVID-19 who do not, the authors of this study utilize the Support Vector Machine (SVM) and the Random Forest (RF) classification techniques to classify patients according to their demographics, laboratory test results, and preexisting health conditions. After conducting a 10-fold validation procedure, we assessed the performance of the classification through a Receiver Operating Characteristic (ROC) curve, and a Confusion Matrix was used to determine the accuracy of the classifiers. We also performed a cluster analysis on the binary factors, such as if the patient had a preexisting condition and if sepsis was identified, and the numeric values from patient demographics and laboratory test results as predictors.

We present experimental results of the cross-section related to cosmic-ray irradiation at ground level for minimum-sized six-transistors (6T) and eight-transistors (8T) bit-cells SRAM memories implemented on a 65 nm CMOS standard technology. Results were obtained from accelerated irradiation tests performed in the mixed-field irradiation facility of the CERN High-energy Accelerator test facility (CHARM) at the European Organization for Nuclear Research in Geneva, Switzerland. A 1.45x higher SEU cross-section was observed for 6T-cell designs despite the larger area occupied by the 8T cells (1.5x for MCU). Moreover, the trend for events affecting multiple bits was higher in 6T-cells. The cross-section obtained values show that the memories have enough sensitivity to be used as a radiation monitors in high energy physics experiments., Comment: 18 pages, 8 figures

We report the discovery of three ultracompact binary white dwarf systems hosting accretion disks, with orbital periods of 7.95, 8.68, and 13.15 minutes. This significantly augments the population of mass-transferring binaries at the shortest periods, and provides the first evidence that accretors in ultracompacts can be dense enough to host accretion disks even below 10 minutes (where previously only direct-impact accretors were known). In the two shortest-period systems, we measured changes in the orbital periods driven by the combined effect of gravitational wave emission and mass transfer; we find $\dot{P}$ is negative in one case, and positive in the other. This is only the second system measured with a positive $\dot{P}$, and it the most compact binary known that has survived a period minimum. Using these systems as examples, we show how the measurement of $\dot{P}$ is a powerful tool in constraining the physical properties of binaries, e.g. the mass and mass-radius relation of the donor stars. We find that the chirp masses of ultracompact binaries at these periods seem to cluster around $\mathcal{M}_c \sim 0.3 M_\odot$, perhaps suggesting a common origin for these systems or a selection bias in electromagnetic discoveries. Our new systems are among the highest-amplitude known gravitational wave sources in the millihertz regime, providing exquisite opportunity for multi-messenger study with future space-based observatories such as \textit{LISA} and TianQin; we discuss how such systems provide fascinating laboratories to study the unique regime where the accretion process is mediated by gravitational waves., Comment: Accepted for publication in ApJ

Flares from M-dwarf stars can attain energies up to $10^4$ times larger than solar flares but are generally thought to result from similar processes of magnetic energy release and particle acceleration. Larger heating rates in the low atmosphere are needed to reproduce the shape and strength of the observed continua in stellar flares, which are often simplified to a blackbody model from the optical to the far-ultraviolet (FUV). The near-ultraviolet (NUV) has been woefully undersampled in spectral observations despite this being where the blackbody radiation should peak. We present Hubble Space Telescope NUV spectra in the impulsive phase of a flare with $E_{\rm{TESS}} \approx 7.5 \times 10^{33}$ erg and a flare with $E_{\rm{TESS}} \approx 10^{35}$ erg and the largest NUV flare luminosity observed to date from an M star. The composite NUV spectra are not well represented by a single blackbody that is commonly assumed in the literature. Rather, continuum flux rises toward shorter wavelengths into the FUV, and we calculate that an optical $T=10^4$ K blackbody underestimates the short wavelength NUV flux by a factor of $\approx 6$. We show that rising NUV continuum spectra can be reproduced by collisionally heating the lower atmosphere with beams of $E \gtrsim 10$ MeV protons or $E \gtrsim 500$ keV electrons and flux densities of $10^{13}$ erg cm$^{-2}$ s$^{-1}$. These are much larger than canonical values describing accelerated particles in solar flares., Comment: Accepted for publication in the Astrophysical Journal

This article presents the latest results of our ALMA program to study circumstellar disk characteristics as a function of orbital and stellar properties in a sample of young binary star systems known to host at least one disk. Optical and infrared observations of the eccentric, ~48-year period binary DF Tau indicated the presence of only one disk around the brighter component. However, our 1.3 mm ALMA thermal continuum maps show two nearly-equal brightness components in this system. We present these observations within the context of updated stellar and orbital properties which indicate that the inner disk of the secondary is absent. Because the two stars likely formed together, with the same composition, in the same environment, and at the same time, we expect their disks to be co-eval. However the absence of an inner disk around the secondary suggests uneven dissipation. We consider several processes which have the potential to accelerate inner disk evolution. Rapid inner disk dissipation has important implications for planet formation, particularly in the terrestrial-planet-forming region., Comment: 18 pages, 8 figures, accepted to AJ

Maxwell's demon (MD) has proven an instructive vehicle by which to explore the relationship between information theory and thermodynamics, fueling the possibility of information driven machines. A long standing debate has been the concern of entropy violation, now resolved by the introduction of a quantum MD, but this theoretical suggestion has proven experimentally challenging. Here, we use classical vectorially structured light that is non-separable in spin and orbital angular momentum to emulate a quantum MD experiment. Our classically entangled light fields have all the salient properties necessary of their quantum counterparts but without the experimental complexity of controlling quantum entangled states. We use our experiment to show that the demon's entropy increases during the process while the system's entropy decreases, so that the total entropy is conserved through an exchange of information, confirming the theoretical prediction. We show that our MD is able to extract useful work from the system in the form of orbital angular momentum, opening a path to information driven optical spanners for the mechanical rotation of objects with light. Our synthetic dimensions of angular momentum can easily be extrapolated to other degrees of freedom, for scalable and robust implementations of MDs at both the classical and quantum realms, enlightening the role of a structured light MD and its capability to control and measure information., Comment: 14 pages, 6 Figures

The neutron star low-mass X-ray binary, EXO 0748--676, recently returned to outburst after a $\sim$ 16 year-long quiescence. Since its return, there has been a global effort to capture the previously unseen rise of the source and to understand its somewhat early return to outburst, as it is typical for a source to spend longer in quiescence than in outburst. Here, we report on the simultaneous optical and X-ray detection of a type I X-ray burst, captured by XMM-Newton during a DDT observation on 30th June 2024. The data show 3 X-ray eclipses consistent with the known ephemeris and one type I X-ray burst at 60492.309 MJD. The X-ray burst is reprocessed into the optical band and captured by XMM-Newton's Optical Monitor during a 4399 s exposure with the B filter in image + fast mode. We determine that the optical peak lags the X-ray peak by 4.46 $\pm$ 1.71s. The optical and X-ray rise times are similar, but the optical decay timescale is shorter than the X-ray decay timescale. The reprocessing site is likely within a few light seconds of the X-ray emitting region, so the companion star, accretion disc and ablated material are all plausible., Comment: 6 Pages, 3 Figures, Accepted for Publication in MNRAS Letters

The construction of large datasets for deep learning has raised concerns regarding unauthorized use of online data, leading to increased interest in protecting data from third-parties who want to use it for training. The Convolution-based Unlearnable DAtaset (CUDA) method aims to make data unlearnable by applying class-wise blurs to every image in the dataset so that neural networks learn relations between blur kernels and labels, as opposed to informative features for classifying clean data. In this work, we evaluate whether CUDA data remains unlearnable after image sharpening and frequency filtering, finding that this combination of simple transforms improves the utility of CUDA data for training. In particular, we observe a substantial increase in test accuracy over adversarial training for models trained with CUDA unlearnable data from CIFAR-10, CIFAR-100, and ImageNet-100. In training models to high accuracy using unlearnable data, we underscore the need for ongoing refinement in data poisoning techniques to ensure data privacy. Our method opens new avenues for enhancing the robustness of unlearnable datasets by highlighting that simple methods such as sharpening and frequency filtering are capable of breaking convolution-based unlearnable datasets.

In high-energy physics (HEP), both the exclusion and discovery of new theories depend not only on the acquisition of high-quality experimental data but also on the rigorous application of statistical methods. These methods provide probabilistic criteria (such as p-values) to compare experimental data with theoretical models, aiming to describe the data as accurately as possible. Hypothesis testing plays a central role in this process, as it enables comparisons between established theories and potential new explanations for the observed data. This report reviews key statistical methods currently employed in particle physics, using synthetic data and numerical comparisons to illustrate the concepts in a clear and accessible way. Our results highlight the practical significance of these statistical tools in enhancing the experimental sensitivity and model exclusion capabilities in HEP. All numerical results are estimated using Python and RooFit, a high-level statistical modeling package used by the ATLAS and CMS collaborations at CERN to model and report results from experimental data., Comment: 28 pages, 25 figures. Comments and suggestions are welcome

Context. The formation of stars has been subject to extensive studies in the past decades from molecular cloud to protoplanetary disk scales. It is still not fully understood how the surrounding material in a protostellar system, that often shows asymmetric structures with complex kinematic properties, feeds the central protostar(s) and their disk(s). Aims. We study the spatial morphology and kinematic properties of the molecular gas surrounding the IRS3A and IRS3B protostellar systems in the L1448N region located in the Perseus molecular cloud. Methods. We present 1 mm NOEMA observations of the PRODIGE large program and analyze the kinematic properties of molecular lines. Given the complexity of the spectral profiles, the lines are fitted with up to three Gaussian velocity components. The clustering algorithm DBSCAN is used to disentangle the velocity components into the underlying physical structure. Results. We discover an extended gas bridge (~3000 au) surrounding both the IRS3A and IRS3B systems in six molecular line tracers (C18O, SO, DCN, H2CO, HC3N, and CH3OH). This gas bridge is oriented along the northeast-southwest direction and shows clear velocity gradients on the order of 100 km/s/pc towards the IRS3A system. We find that the observed velocity profile is consistent with analytical streamline models of gravitational infall towards IRS3A. The high-velocity C18O (2-1) emission towards IRS3A indicates a protostellar mass of ~1.2 Msun. Conclusions. While high angular resolution continuum data often show IRS3A and IRS3B in isolation, molecular gas observations reveal that these systems are still embedded within a large-scale mass reservoir with a complex spatial morphology as well as velocity profiles. The kinematic properties of the extended gas bridge are consistent with gravitational infall toward the IRS3A protostar., Comment: 16 pages, 10 figures; accepted for publication in A&A

Advancements in Natural Language Processing (NLP), have led to the emergence of Large Language Models (LLMs) such as GPT, Llama, Claude, and Gemini, which excel across a range of tasks but require extensive fine-tuning to align their outputs with human expectations. A widely used method for achieving this alignment is Reinforcement Learning from Human Feedback (RLHF), which, despite its success, faces challenges in accurately modelling human preferences. In this paper, we introduce GazeReward, a novel framework that integrates implicit feedback -- and specifically eye-tracking (ET) data -- into the Reward Model (RM). In addition, we explore how ET-based features can provide insights into user preferences. Through ablation studies we test our framework with different integration methods, LLMs, and ET generator models, demonstrating that our approach significantly improves the accuracy of the RM on established human preference datasets. This work advances the ongoing discussion on optimizing AI alignment with human values, exploring the potential of cognitive data for shaping future NLP research.

Almost all accreting black hole and neutron star X-ray binary systems (XRBs) exhibit prominent brightness variations on a few characteristic time-scales and their harmonics. These quasi-periodic oscillations (QPOs) are thought to be associated with the precession of a warped accretion disc, but the physical mechanism that generates the precessing warp remains uncertain. Relativistic frame dragging (Lense-Thirring precession) is one promising candidate, but a misaligned magnetic field is an alternative, especially for neutron star XRBs. Here, we report the discovery of 5 accreting white dwarf systems (AWDs) that display strong optical QPOs with characteristic frequencies and harmonic structures that suggest they are the counterpart of the QPOs seen in XRBs. Since AWDs are firmly in the classical (non-relativistic) regime, Lense-Thirring precession cannot account for these QPOs. By contrast, a weak magnetic field associated with the white dwarf can drive disc warping and precession in these systems, similar to what has been proposed for neutron star XRBs. Our observations confirm that magnetically driven warping is a viable mechanism for generating QPOs in disc-accreting astrophysical systems, certainly in AWDs and possibly also in (neutron star) XRBs. Additionally, they establish a new way to estimate magnetic field strengths, even in relatively weak-field systems where other methods are not available., Comment: 16 pages, 9 figures, accepted for publication in MNRAS