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Early Exiting (EE) is a promising technique for speeding up inference by adaptively allocating compute resources to data points based on their difficulty. The approach enables predictions to exit at earlier layers for simpler samples while reserving more computation for challenging ones. In this study, we first present a novel perspective on the EE approach, showing that larger models deployed with EE can achieve higher performance than smaller models while maintaining similar computational costs. As existing EE approaches rely on confidence estimation at each exit point, we further study the impact of overconfidence on the controllability of the compute-performance trade-off. We introduce Performance Control Early Exiting (PCEE), a method that enables accuracy thresholding by basing decisions not on a data point's confidence but on the average accuracy of samples with similar confidence levels from a held-out validation set. In our experiments, we show that PCEE offers a simple yet computationally efficient approach that provides better control over performance than standard confidence-based approaches, and allows us to scale up model sizes to yield performance gain while reducing the computational cost., Comment: Appeared at ICML 2024 Workshop on Efficient Systems for Foundation Models (ES-FoMo-II)

Novel applications demand high throughput, low latency, and high reliability connectivity and still pose significant challenges to slicing orchestration architectures. The literature explores network slicing techniques that employ canonical methods, artificial intelligence, and combinatorial optimization to address errors and ensure throughput for network slice data plane. This paper introduces the Enhanced Mobile Broadband (eMBB)-Agent as a new approach that uses Reinforcement Learning (RL) in a vertical application to enhance network slicing throughput to fit Service-Level Agreements (SLAs). The eMBB-Agent analyzes application transmission variables and proposes actions within a discrete space to adjust the reception window using a Deep Q-Network (DQN). This paper also presents experimental results that examine the impact of factors such as the channel error rate, DQN model layers, and learning rate on model convergence and achieved throughput, providing insights on embedding intelligence in network slicing., Comment: Paper already published at Anais do XV Workshop de Pesquisa Experimental da Internet do Futuro (WPEIF)

We construct a nonlinear multiparametric Klein-Gordon for complex and real fields with mass dimension depending on a real parameter $\alpha$ as $\delta = 2/(1+\alpha)$ where $\delta$ is the mass dimension of the fields. We show that there are three classes of generalized models, one class for complex fields and two different classes for real fields. All models in these three classes have travelling-wave solutions and satisfy the relativistic dispersion relation. Moreover, all models of the complex class and models of only one class of the two real classes recover the standard Klein-Gordon model. We also build the Lagrangian and the Hamiltonian for the three classes of models. The fields in the models of these three classes could in principle have the mass dimension varying from zero to one and this can allow us to construct interaction terms, other than $\lambda \Phi^4$, with coupling constants with positive or zero mass dimensions. Furthermore, we also show that there is a subclass of equations in the complex class which has a Lorentzian soliton solution., Comment: 16 pages, 1 figure

Convergence spaces are a generalization of topological spaces. The category of convergence spaces is well-suited for Algebraic Topology, one of the reasons is the existence of exponential objects provided by continuous convergence. In this work, we use a net-theoretic approach to convergence spaces. The goal is to simplify the description of continuous convergence and apply it to problems related to homotopy theory. We present methods to develop the basis of homotopy theory in limit spaces, define the fundamental groupoid, and prove the groupoid version of the Seifert-van Kampen Theorem for limit spaces., Comment: I corrected the absence of a reference in the list of symbols and removed a repeated paragraph in the introduction of Chapter 3

The conjugation representation of a finite group $G$ is the complex permutation module defined by the action of $G$ on itself by conjugation. Addressing a problem raised by Hain motivated by the study of a Hecke action on iterated Shimura integrals, Tiep proved that for $G=\operatorname{SL}_{2}(\mathbb{Z}/p^{r})$, where $r\geq1$ and $p\geq5$ is a prime, any irreducible representation of $G$ that is trivial on the centre of $G$ is contained in the conjugation representation. Moreover, Tiep asked whether this can be generalised to $p=2$ or $3$. We answer the Hain--Tiep question in the affirmative and also prove analogous statements for $\operatorname{SL}_{2}$ and $\operatorname{GL}_{2}$ over any finite local principal ideal ring with residue field of odd characteristic., Comment: 40 pages

Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and summarizing reports. Code generation tasks that require long-structured outputs can also be enhanced by multimodality. Despite this, their use in commercial applications is often limited due to limited access to training data and restrictive licensing, which hinders open access. To address these limitations, we introduce BigDocs-7.5M, a high-quality, open-access dataset comprising 7.5 million multimodal documents across 30 tasks. We use an efficient data curation process to ensure our data is high-quality and license-permissive. Our process emphasizes accountability, responsibility, and transparency through filtering rules, traceable metadata, and careful content analysis. Additionally, we introduce BigDocs-Bench, a benchmark suite with 10 novel tasks where we create datasets that reflect real-world use cases involving reasoning over Graphical User Interfaces (GUI) and code generation from images. Our experiments show that training with BigDocs-Bench improves average performance up to 25.8% over closed-source GPT-4o in document reasoning and structured output tasks such as Screenshot2HTML or Image2Latex generation. Finally, human evaluations showed a preference for outputs from models trained on BigDocs over GPT-4o. This suggests that BigDocs can help both academics and the open-source community utilize and improve AI tools to enhance multimodal capabilities and document reasoning. The project is hosted at https://bigdocs.github.io ., Comment: The project is hosted at https://bigdocs.github.io

Manipulating the dynamics of open quantum systems is a crucial requirement for large-scale quantum computers. Finding ways to overcome or extend decoherence times is a challenging task. Already at the level of a single two-level atom, its reduced dynamics with respect to a larger environment can be very complex. Structured environments, for instance, can lead to various regimes other than memoryless Markovian spontaneous emission. Here, we consider an atom coupled to an array of coupled cavities in the presence of on-site correlated disorder. The correlation is long-ranged and associated with the trace of a fractional Brownian motion following a power-law spectrum. With the cavity modes playing the role of the environment, we study the dynamics of the spontaneous emission. We observe a change from non-Markovian to Markovian decay in the presence of disorder by tuning the correlation parameter. This is associated with a localization-delocalization transition involving the field modes. Two dissipative models that effectively reproduce the behavior of the non-Markovianity are discussed. The dissipation dynamics of the atom can thus be used to extract information about the phase of the environment. Our results provide a direction in the engineering of disordered quantum systems to function as controllable reservoirs., Comment: 9 pages, 5 figures

The concept of `proximity-based cities' has gained attention as a new urban organizational model. Most prominently, the 15-minute city contends that cities can function more effectively, equitably and sustainably if essential, everyday services and key amenities are within a 15-minute walk or cycle. However, focusing solely on travel time risks overlooking disparities in service quality, as the proximity paradigm tends to emphasize the mere presence of an element in a location rather than bringing up more complex questions of identity, diversity, quality, value or relationships. Transitioning to value-based cities by considering more than just proximity can enhance local identity, resilience and urban democracy. Fostering bottom-up initiatives can create a culture of local care and value, while predominantly top-down governing strategies can lead to large inequalities. Balancing these approaches can maximize resilience, health and sustainability. This equilibrium has the potential to accompany sustainable growth, by encouraging the creation of innovative urban solutions and reducing inequalities., Comment: This article is part of the theme issue 'Cocreating the future: participatory cities and digital governance', an opinion piece in Phil. Trans. R. Soc. A

The "miscentering effect," i.e., the offset between a galaxy cluster's optically-defined center and the center of its gravitational potential, is a significant systematic effect on brightest cluster galaxy (BCG) studies and cluster lensing analyses. We perform a cross-match between the optical cluster catalog from the Hyper Suprime-Cam (HSC) Survey S19A Data Release and the Sunyaev-Zeldovich cluster catalog from Data Release 5 of the Atacama Cosmology Telescope (ACT). We obtain a sample of 186 clusters in common in the redshift range $0.1 \leq z \leq 1.4$ over an area of 469 deg$^2$. By modeling the distribution of centering offsets in this fiducial sample, we find a miscentered fraction (corresponding to clusters offset by more than 330 kpc) of ~25%, a value consistent with previous miscentering studies. We examine the image of each miscentered cluster in our sample and identify one of several reasons to explain the miscentering. Some clusters show significant miscentering for astrophysical reasons, i.e., ongoing cluster mergers. Others are miscentered due to non-astrophysical, systematic effects in the HSC data or the cluster-finding algorithm. After removing all clusters with clear, non-astrophysical causes of miscentering from the sample, we find a considerably smaller miscentered fraction, ~10%. We show that the gravitational lensing signal within 1 Mpc of miscentered clusters is considerably smaller than that of well-centered clusters, and we suggest that the ACT SZ centers are a better estimate of the true cluster potential centroid., Comment: 20 pages, 15 figures. Accepted for publication in MNRAS

Self-dual Yang-Mills and Einstein gravity in Euclidean AdS$_4$ are useful toy models because they can be described by simple scalar Lagrangians exhibiting a new manifestation of the colour/kinematics duality, as recently shown by two of the authors. In this paper, we clarify how the self-dual sectors fit into the full theories. In particular, we explicitly construct the light-cone action for Yang-Mills theory and Einstein gravity in AdS$_4$ in terms of positive and negative helicity fields, where we are able to pinpoint the self-dual sector as expected. We then show that the boundary correlators of these theories take a remarkably simple form in terms of Feynman diagrams in half of flat space, acted on by certain differential operators. We also analyse their soft limits and show that they exhibit Weinberg-like soft factors, where the soft pole which appears in scattering amplitudes is replaced by a derivative with respect to the energy., Comment: 40 pages + 17 pages of appendix

Noble gas radiation detectors with optical readout are gaining popularity in fields like astrophysics and particle physics due to their ability to produce both ionization and scintillation signals in response to ionizing radiation interaction. In addition, the amplification of primary ionization signals can be achieved by promoting secondary scintillation in the gas. Noble gas purity, especially concerning impurities like H$_{2}$O, N$_{2}$, O$_{2}$, CO$_{2}$, and hydrocarbons, greatly influences its performance. These impurities can cause the loss of primary electrons and quench the scintillation signal. A very high purity level of the gas is required. In the early 90's, a simple method was developed for noble gas purification in sealed, small volume (up to few litters) gas radiation detectors. Gas purification is achieved promoting gas circulation through Zr-based hot getters, simply maintaining the gas circulation by convection. The effectiveness of this method has been only confirmed by the energy resolutions achieved in those detectors, which were similar to that achieved in other high-performance noble gas detectors. In this work, we used waveform analysis of the primary and secondary scintillation signals and we were able to evaluate the impact of the attachment and quenching caused by impurities in one of our detectors filled with pure Xe, and estimate upper values for the impurity content in the gas. The maximum overall impurity concentration was estimated to be below 4 ppm, considering nearly all the impurities, and below 82 ppm if N$_{2}$ is considered. The electron lifetime was measured to be 2.1 $\pm$ 0.1 ms, in line with those achieved in other high-performance optical detectors.

This paper develops a parameter-free adaptive proximal bundle method with two important features: 1) adaptive choice of variable prox stepsizes that "closely fits" the instance under consideration; and 2) adaptive criterion for making the occurrence of serious steps easier. Computational experiments show that our method performs substantially fewer consecutive null steps (i.e., a shorter cycle) while maintaining the number of serious steps under control. As a result, our method performs significantly less number of iterations than its counterparts based on a constant prox stepsize choice and a non-adaptive cycle termination criterion. Moreover, our method is very robust relative to the user-provided initial stepsize., Comment: 24 pages

We find a direct map that determines moduli-space integrands for one-loop superstring amplitudes in terms of field-theory loop integrands in the BCJ form. The latter can be computed using efficient unitarity methods, so our map provides an alternative to worldsheet CFT techniques. This construction is a one-loop higher-point analogue of a recent conjecture for the three-loop four-point superstring amplitude. Based on the one-loop chiral-splitting representation, we show how all coefficients of an ansatz for the superstring can be identified with field-theory BCJ numerators, up to at least 7-point amplitudes. Moreover, we obtain partial results for all higher-point amplitudes. The monodromy constraints associated to chiral splitting play a crucial role in determining coefficients of the ansatz that, naively, are not fixed by the field-theory limit. Taking a field-theory perspective, our ansatz for the superstring implies by construction the existence of one-loop BCJ numerators at any multiplicity., Comment: 33 pages, 3 figures

This paper uses a net-theoretic approach to convergence spaces, aimed to simplify the description of continuous convergence in order to apply it in problems concerning Homotopy Theory. We present methods for handling homotopies of limit spaces, define fundamental groupoids, and prove a generalized version of the Seifert-van Kampen Theorem for limit spaces., Comment: Minor typos corrected in Example 3.6. Remarks 3.7 and 5.1 were added

The XLZD collaboration is developing a two-phase xenon time projection chamber with an active mass of 60 to 80 t capable of probing the remaining WIMP-nucleon interaction parameter space down to the so-called neutrino fog. In this work we show that, based on the performance of currently operating detectors using the same technology and a realistic reduction of radioactivity in detector materials, such an experiment will also be able to competitively search for neutrinoless double beta decay in $^{136}$Xe using a natural-abundance xenon target. XLZD can reach a 3$\sigma$ discovery potential half-life of 5.7$\times$10$^{27}$ yr (and a 90% CL exclusion of 1.3$\times$10$^{28}$ yr) with 10 years of data taking, corresponding to a Majorana mass range of 7.3-31.3 meV (4.8-20.5 meV). XLZD will thus exclude the inverted neutrino mass ordering parameter space and will start to probe the normal ordering region for most of the nuclear matrix elements commonly considered by the community., Comment: 29 pages, 7 figures

This report describes the experimental strategy and technologies for a next-generation xenon observatory sensitive to dark matter and neutrino physics. The detector will have an active liquid xenon target mass of 60-80 tonnes and is proposed by the XENON-LUX-ZEPLIN-DARWIN (XLZD) collaboration. The design is based on the mature liquid xenon time projection chamber technology of the current-generation experiments, LZ and XENONnT. A baseline design and opportunities for further optimization of the individual detector components are discussed. The experiment envisaged here has the capability to explore parameter space for Weakly Interacting Massive Particle (WIMP) dark matter down to the neutrino fog, with a 3$\sigma$ evidence potential for the spin-independent WIMP-nucleon cross sections as low as $3\times10^{-49}\rm cm^2$ (at 40 GeV/c$^2$ WIMP mass). The observatory is also projected to have a 3$\sigma$ observation potential of neutrinoless double-beta decay of $^{136}$Xe at a half-life of up to $5.7\times 10^{27}$ years. Additionally, it is sensitive to astrophysical neutrinos from the atmosphere, sun, and galactic supernovae., Comment: 32 pages, 14 figures

Autism Spectrum Disorder (ASD) is a neurodivergent condition with a wide range of characteristics and support levels. Individuals with ASD can exhibit various combinations of traits such as difficulties in social interaction, communication, and language, alongside restricted interests and repetitive activities. Many adults with ASD live independently due to increased awareness and late diagnoses, which help them manage long-standing challenges. Predictability, clarity, and minimized sensory stimuli are crucial for the daily comfort of autistic individuals. In mobile applications, autistic users face significant cognitive overload compared to neurotypicals, resulting in higher effort and time to complete tasks. Urban mobility apps, essential for daily routines, often overlook the needs of autistic users, leading to cognitive overload issues. This study investigates the accessibility of urban mobility apps for autistic individuals using the Interfaces Accessibility Guide for Autism (GAIA). By evaluating various apps, we have identified a common gap regarding accessibility for people with Autism Spectrum Disorder (ASD). This limitation relates to the absence of a functionality that allows users on the autism spectrum to customize the characteristics of the textual and visual elements of the software, such as changing the text font, altering the font type, and adjusting text colors, as well as native audio guidance within the applications themselves. Currently, the only function in this context is for visually impaired people, which completely changes the user experience in terms of navigation., Comment: Author pre-print of article published in the XXIII Brazilian Symposium on Human Factors in Computing Systems (IHC'24)

This paper develops an adaptive generic proximal bundle method, shows its complexity, and presents numerical experiments comparing this method with two bundle methods on a set of optimization problems.

The outermost structure of the bacterial flagellar motor is a long helicoidal filament, whose protein building blocks are produced and injected from the base, progressively elongating the filament and regenerating it in case it breaks. Here, we study the evolution of flagellar filaments in the soil bacterium $\textit{Bradyrhizobium diazoefficiens}$ after being exposed to shear flows, for shear rates between 1 s$^{-1}$ and $10^5$ s$^{-1}$, and for durations between tens of milliseconds and minutes. We demonstrate that the average swimming speed and fraction of swimming cells decrease after exposition to shear, but both parameters can recover, at least partially, with time. These observations support the hypothesis that flagellar filaments are cut by shear flows, but that reversibly damaged flagellar motors can be restored thanks to filament regeneration. By fitting our observations with phenomenological expressions, we obtain the individual growth rates of the two different flagellar filaments that $\textit{B. diazoefficiens}$ possesses, showing that the lateral filaments have a recovery time of about 40 min while the subpolar one requires more than 4.5 h to regrow. Our work demonstrates that a simple monitoring of bacterial motility after exposition to shear can be used to characterise the process of flagellar filament growth., Comment: 21 pages, 5 figures

Sloshing of cryogenic liquid propellants can significantly impact a spacecraft's mission safety and performance by unpredictably altering the center of mass and producing large pressure fluctuations due to the increased heat and mass transfer within the tanks. This study, conducted as part of the NT-SPARGE (Non-isoThermal Sloshing PARabolic FliGht Experiment) project, provides a detailed experimental investigation of the thermodynamic evolution of a partially filled upright cylindrical tank undergoing non-isothermal sloshing in microgravity. Sloshing was induced by a step reduction in gravity during the 83rd European Space Agency (ESA) parabolic flight, resulting in a chaotic reorientation of the free surface under inertia-dominated conditions. To investigate the impact of heat and mass transfer on the sloshing dynamics, two identical test cells operating with a representative fluid, HFE-7000, in single-species were considered simultaneously. One cell was maintained in isothermal conditions, while the other started with initially thermally stratified conditions. Flow visualization, pressure, and temperature measurements were acquired for both cells. The results highlight the impact of thermal mixing on liquid dynamics coupled with the significant pressure and temperature fluctuations produced by the destratification. The comprehensive experimental data gathered provide a unique opportunity to validate numerical simulations and simplified models for non-isothermal sloshing in microgravity, thus contributing to improved cryogenic fluid management technologies.

This paper develops a new parameter-free restarted method, namely RPF-SFISTA, and a new parameter-free aggressive regularization method, namely A-REG, for solving strongly convex and convex composite optimization problems, respectively. RPF-SFISTA has the major advantage that it requires no knowledge of both the strong convexity parameter of the entire composite objective and the Lipschitz constant of the gradient. Unlike several other restarted first-order methods which restart an accelerated composite gradient (ACG) method after a predetermined number of ACG iterations have been performed, RPF-SFISTA checks a key inequality at each of iterations to determine when to restart. Extensive computational experiments show that RPF-SFISTA is roughly 3 to 15 times faster than other state-of-the-art restarted methods on four important classes of problems. The A-REG method, developed for convex composite optimization, solves each of its strongly convex regularized subproblems according to a stationarity criterion by using the RPF-SFISTA method with a possibly aggressive choice of initial strong convexity estimate. This scheme is thus more aggressive than several other regularization methods which solve their subproblems by running a standard ACG method for a predetermined number of iterations.

The Internet of Things (IoT) empowers small devices to sense, react, and communicate, with applications ranging from smart ordinary household objects to complex industrial processes. To provide access to an increasing number of IoT devices, particularly in long-distance communication scenarios, a robust low-power wide area network (LPWAN) protocol becomes essential. A widely adopted protocol for this purpose is 6TiSCH, which builds upon the IEEE 802.15.4 standard. It introduces time-slotted channel hopping (TSCH) mode as a new medium access control (MAC) layer operating mode, in conjunction with IEEE 802.15.4g, which also defines both MAC and physical layer (PHY) layers and provides IPv6 connectivity for LPWAN. Notably, 6TiSCH has gained adoption in significant standards such as Wireless Intelligent Ubiquitous Networks (Wi-SUN). This study evaluates the scalability of 6TiSCH, with a focus on key parameters such as queue size, the maximum number of single-hop retries, and the slotframe length. Computational simulations were performed using an open-source simulator and obtained the following results: increasing the transmission queue size, along with adjusting the number of retries and slotframe length, leads to a reduction in the packet error rate (PER). Notably, the impact of the number of retries is particularly pronounced. Furthermore, the effect on latency varies based on the specific combination of these parameters as the network scales.

Integrated access and backhaul (IAB) technology is a flexible solution for network densification. IAB nodes can also be deployed in moving nodes such as buses and trains, i.e., mobile IAB (mIAB). As mIAB nodes can move around the coverage area, the connection between mIAB nodes and their parent macro base stations (BSs), IAB donor, is sometimes required to change in order to keep an acceptable backhaul link, the so called topology adaptation (TA). The change from one IAB donor to another may strongly impact the system load distribution, possibly causing unsatisfactory backhaul service due to the lack of radio resources. Based on this, TA should consider both backhaul link quality and traffic load. In this work, we propose a load balancing algorithm based on TA for IAB networks, and compare it with an approach in which TA is triggered based on reference signal received power (RSRP) only. The results show that our proposed algorithm improves the passengers worst connections throughput in uplink (UL) and, more modestly, also in downlink (DL), without impairing the pedestrian quality of service (QoS) significantly., Comment: Paper submitted to Journal of Communication and Information Systems (JCIS)

As the number of user equipments increases in fifth generation (5G) and beyond, it is desired to densify the cellular network with auxiliary nodes assisting the base stations. Examples of these nodes are integrated access and backhaul (IAB) nodes, network-controlled repeaters (NCRs) and reconfigurable intelligent surfaces (RISs). In this context, this work presents a system level overview of these three nodes. Moreover, this work evaluates through simulations the impact of network planning aiming at enhancing the performance of a network used to cover an outdoor sport event. We show that, in the considered scenario, in general, IAB nodes provide an improved signal to interference-plus-noise ratio and throughput, compared to NCRs and RISs. However, there are situations where NCR outperforms IAB due to higher level of interference caused by the latter. Finally, we show that the deployment of these nodes in unmanned aerial vehicles (UAVs) also achieves performance gains due to their aerial mobility. However, UAV constraints related to aerial deployment may prevent these nodes from reaching results as good as the ones achieved by their stationary deployment., Comment: Paper submitted to IEEE Systems Journal

In this work, we show that the edge dynamics of the Laughlin state in the weakly nonlinear regime is governed by the Korteweg-de Vries (KdV) equation. Our starting point is the Chern-Simons-Ginzburg-Landau theory in the lower half-plane, where the effective edge dynamics are encoded in anomaly-compatible boundary conditions. The saddle point bulk dynamics and the corresponding boundary conditions of this action can be reformulated as two-dimensional compressible fluid dynamic equations, subject to a quantum Hall constraint that links the superfluid vorticity to its density fluctuations. The boundary conditions in this hydrodynamic framework consist of no-penetration and no-stress conditions. We then apply the method of multiple scales to this hydrodynamic system and derive the KdV equation for the edge dynamics in the weakly nonlinear regime. By employing the Hamiltonian framework for the KdV equation, we show that we can recover the chiral Luttinger liquid theory in the linearized regime and provide a pathway for canonically quantizing the edge dynamics in the weakly non-linear limit., Comment: 33 pages, 1 figure

We present a novel deep learning pipeline to perform a model-independent, likelihood-free search for anomalous (i.e., non-background) events in the proposed next generation multi-ton scale liquid Xenon-based direct detection experiment, DARWIN. We train an anomaly detector comprising a variational autoencoder and a classifier on extensive, high-dimensional simulated detector response data and construct a one-dimensional anomaly score optimised to reject the background only hypothesis in the presence of an excess of non-background-like events. We benchmark the procedure with a sensitivity study that determines its power to reject the background-only hypothesis in the presence of an injected WIMP dark matter signal, outperforming the classical, likelihood-based background rejection test. We show that our neural networks learn relevant energy features of the events from low-level, high-dimensional detector outputs, without the need to compress this data into lower-dimensional observables, thus reducing computational effort and information loss. For the future, our approach lays the foundation for an efficient end-to-end pipeline that eliminates the need for many of the corrections and cuts that are traditionally part of the analysis chain, with the potential of achieving higher accuracy and significant reduction of analysis time., Comment: 10 Figures, 3 Tables, 23 Pages (incl. references)

Marine robots must maintain precise control and ensure safety during tasks like ocean monitoring, even when encountering unpredictable disturbances that affect performance. Designing algorithms for uncrewed surface vehicles (USVs) requires accounting for these disturbances to control the vehicle and ensure it avoids obstacles. While adaptive control has addressed USV control challenges, real-world applications are limited, and certifying USV safety amidst unexpected disturbances remains difficult. To tackle control issues, we employ a model reference adaptive controller (MRAC) to stabilize the USV along a desired trajectory. For safety certification, we developed a reachability module with a moving horizon estimator (MHE) to estimate disturbances affecting the USV. This estimate is propagated through a forward reachable set calculation, predicting future states and enabling real-time safety certification. We tested our safe autonomy pipeline on a Clearpath Heron USV in the Charles River, near MIT. Our experiments demonstrated that the USV's MRAC controller and reachability module could adapt to disturbances like thruster failures and drag forces. The MRAC controller outperformed a PID baseline, showing a 45%-81% reduction in RMSE position error. Additionally, the reachability module provided real-time safety certification, ensuring the USV's safety. We further validated our pipeline's effectiveness in underway replenishment and canal scenarios, simulating relevant marine tasks., Comment: 35 pages, 23 figures, 6 tables

Let $W_{r}(\mathbb{F}_{q})$ be the ring of Witt vectors of length $r$ with residue field $\mathbb{F}_{q}$ of characteristic $p$. In this paper, we study the defining characteristic case of the representations of $\mathrm{GL}_{n}$ and $\mathrm{SL}_{n}$ over the principal ideal local rings $W_{r}(\mathbb{F}_{q})$ and $\mathbb{F}_{q}[t]/t^{r}$. Let ${\mathbf{G}}$ be either $\mathrm{GL}_{n}$ or $\mathrm{SL}_{n}$ and $F$ a perfect field of characteristic $p$, we prove that for most $p$ the group algebras $F[{\mathbf{G}}(W_{r}(\mathbb{F}_{q}))]$ and $F[{\mathbf{G}}(\mathbb{F}_{q}[t]/t^{r})]$ are not stably equivalent of Morita type. Thus, the group algebras $F[{\mathbf{G}}(W_{r}(\mathbb{F}_{q}))]$ and $F[{\mathbf{G}}(\mathbb{F}_{q}[t]/t^{r})]$ are not isomorphic in the defining characteristic case., Comment: 10 pages, comments are welcome!

The advent of large integral field spectroscopic surveys has found that elliptical galaxies (EGs) can be classified into two classes: the fast rotators (whose kinematics are dominated by rotation) and the slow rotators (which exhibit slow or no rotation pattern). It is often suggested that while the slow rotators typically have boxy isophotal shapes, have a high $\alpha$-to-iron abundance ratio, and are quite massive, the fast rotators often exhibit the opposite properties (that is, having disky isophotes, lower $\alpha$-to-iron ratio, and of typical masses). Whether the EGs consist of two distinct populations (i.e., a dichotomy exists), remains an unsolved issue. To examine the existence of the dichotomy, we used a sample of 1,895 EGs from the SDSS-IV MaNGA survey, and measured robustly the stellar kinematics, isophotal shapes, and [Mg/Fe] ratio. We confirmed the previous finding that the bulk of the EGs are disky (65%) and fast rotators (67%), but found no evidence supporting a dichotomy, based on a principal component analysis. The different classes (boxy/disky and slow/fast rotators) of EGs occupy slightly different loci in the principal component space. This may explain the observed trends that led to the premature support of a dichotomy based on small samples of galaxies., Comment: 27 pages, 19 figures, 5 tables. Submitted to ApJ. Comments are welcome!

The 15-minute city concept, advocating for cities where essential services are accessible within 15 minutes on foot and by bike, has gained significant attention in recent years. However, despite being celebrated for promoting sustainability, there is an ongoing debate regarding its effectiveness in reducing car usage and, subsequently, emissions in cities. In particular, large-scale evaluations of the effectiveness of the 15-minute concept in reducing emissions are lacking. To address this gap, we investigate whether cities with better walking accessibility, like 15-minute cities, are associated with lower transportation emissions. Comparing 700 cities worldwide, we find that cities with better walking accessibility to services emit less CO$_2$ per capita for transport. Moreover, we observe that among cities with similar average accessibility, cities spreading over larger areas tend to emit more. Our findings highlight the effectiveness of decentralised urban planning, especially the proximity-based 15-minute city, in promoting sustainable mobility. However, they also emphasise the need to integrate local accessibility with urban compactness and efficient public transit, which are vital in large cities.

We report the first spatially resolved detection of the near-infrared [C I] $\lambda$8727 emission from the outer pair of low-ionization structures in the planetary nebula NGC 7009 from data obtained by the Multi Unit Spectroscopic Explorer integral field unit. This atomic carbon emission marks the transition zone between ionized and neutral gas, and for the first time offers direct evidence that LISs are photodominated regions. The outer LIS pair exhibits intense [C I] $\lambda$8727 emission, but He I $\lambda$8733 is absent. Conversely, the inner pair of knots shows both lines, likely due to the host nebula emission. Furthermore, the [C I] $\lambda$8727 line is absent in the host nebula emission, but He I $\lambda$8733 is present. Although the origin of the [C I] $\lambda$8727 line is still debated, its detection supports the scenario of photoevaporated dense molecular clumps., Comment: 9 pages, 5 figures, 3 tables

Structural Health Monitoring (SHM) aims to monitor in real time the health state of engineering structures. For thin structures, Lamb Waves (LW) are very efficient for SHM purposes. A bonded piezoelectric transducer (PZT) emits LW in the structure in the form of a short tone burst. This initial wave packet (IWP) propagates in the structure and interacts with its boundaries and discontinuities and with eventual damages generating additional wave packets. The main issues with LW based SHM are that at least two LW modes are simultaneously excited and that those modes are dispersive. Matching Pursuit Method (MPM), which consists of approximating a signal as a sum of different delayed and scaled atoms taken from an a priori known learning dictionary, seems very appealing in such a context, however is limited to nondispersive signals and relies on a priori known dictionary. An improved version of MPM called the Single Atom Convolutional Matching Pursuit method (SACMPM), which addresses the dispersion phenomena by decomposing a measured signal as delayed and dispersed atoms and limits the learning dictionary to only one atom, is proposed here. Its performances are illustrated when dealing with numerical and experimental signals as well as its usage for damage detection. Although the signal approximation method proposed in this paper finds an original application in the context of SHM, this method remains completely general and can be easily applied to any signal processing problem.

The Exame Nacional do Ensino M\'edio (ENEM) is a pivotal test for Brazilian students, required for admission to a significant number of universities in Brazil. The test consists of four objective high-school level tests on Math, Humanities, Natural Sciences and Languages, and one writing essay. Students' answers to the test and to the accompanying socioeconomic status questionnaire are made public every year (albeit anonymized) due to transparency policies from the Brazilian Government. In the context of large language models (LLMs), these data lend themselves nicely to comparing different groups of humans with AI, as we can have access to human and machine answer distributions. We leverage these characteristics of the ENEM dataset and compare GPT-3.5 and 4, and MariTalk, a model trained using Portuguese data, to humans, aiming to ascertain how their answers relate to real societal groups and what that may reveal about the model biases. We divide the human groups by using socioeconomic status (SES), and compare their answer distribution with LLMs for each question and for the essay. We find no significant biases when comparing LLM performance to humans on the multiple-choice Brazilian Portuguese tests, as the distance between model and human answers is mostly determined by the human accuracy. A similar conclusion is found by looking at the generated text as, when analyzing the essays, we observe that human and LLM essays differ in a few key factors, one being the choice of words where model essays were easily separable from human ones. The texts also differ syntactically, with LLM generated essays exhibiting, on average, smaller sentences and less thought units, among other differences. These results suggest that, for Brazilian Portuguese in the ENEM context, LLM outputs represent no group of humans, being significantly different from the answers from Brazilian students across all tests., Comment: Accepted at the Seventh AAAI/ACM Conference on AI, Ethics and Society (AIES 2024). 14 pages, 4 figures

Counting fish larvae is an important, yet demanding and time consuming, task in aquaculture. In order to address this problem, in this work, we evaluate four neural network architectures, including convolutional neural networks and transformers, in different sizes, in the task of fish larvae counting. For the evaluation, we present a new annotated image dataset with less data collection requirements than preceding works, with images of spotted sorubim and dourado larvae. By using image tiling techniques, we achieve a MAPE of 4.46% ($\pm 4.70$) with an extra large real time detection transformer, and 4.71% ($\pm 4.98$) with a medium-sized YOLOv8.

A random walk-based method is proposed to efficiently compute the solution of a large class of fractional in time linear systems of differential equations (linear F-ODE systems), along with the derivatives with respect to the system parameters. Such a method is unbiased and unconditionally stable, and can therefore be used to provide an unbiased estimation of individual entries of the solution, or the full solution. By using stochastic differentiation techniques, it can be used as well to provide unbiased estimators of the sensitivities of the solution with respect to the problem parameters without any additional computational cost. The time complexity of the algorithm is discussed here, along with suitable variance bounds, which prove in practice the convergence of the algorithm. Finally, several test cases were run to assess the validity of the algorithm.

Proximity-based cities have attracted much attention in recent years. The 15-minute city, in particular, heralded a new vision for cities where essential services must be easily accessible. Despite its undoubted merit in stimulating discussion on new organisations of cities, the 15-minute city cannot be applicable everywhere, and its very definition raises a few concerns. Here, we tackle the feasibility and practicability of the '15-minute city' model in many cities worldwide. We provide a worldwide quantification of how close cities are to the ideal of the 15-minute city. To this end, we measure the accessibility times to resources and services, and we reveal strong heterogeneity of accessibility within and across cities, with a significant role played by local population densities. We provide an online platform (\href{whatif.sonycsl.it/15mincity}{whatif.sonycsl.it/15mincity}) to access and visualise accessibility scores for virtually all cities worldwide. The heterogeneity of accessibility within cities is one of the sources of inequality. We thus simulate how much a better redistribution of resources and services could heal inequity by keeping the same resources and services or by allowing for virtually infinite resources. We highlight pronounced discrepancies among cities in the minimum number of additional services needed to comply with the 15-minute city concept. We conclude that the proximity-based paradigm must be generalised to work on a wide range of local population densities. Finally, socio-economic and cultural factors should be included to shift from time-based to value-based cities.

Let $B$ be a block algebra of a group algebra $FG$ of a finite group $G$ over a field $F$ of characteristic $p>0$. This paper studies ring theoretic properties of the representation ring $T^\Delta(B,B)$ of perfect $p$-permutation $(B,B)$-bimodules and properties of the $k$-algebra $k\otimes_\mathbb{Z} T^\Delta(B,B)$, for a field $k$. We show that if the Cartan matrix of $B$ has $1$ as an elementary divisor then $[B]$ is not primitive in $T^\Delta(B,B)$. If $B$ has cyclic defect groups we determine a primitive decomposition of $[B]$ in $T^\Delta(B,B)$. Moreover, if $k$ is a field of characteristic different from $p$ and $B$ has cyclic defect groups of order $p^n$ we describe $k\otimes_\mathbb{Z} T^\Delta(B,B)$ explicitly as a direct product of a matrix algebra and $n$ group algebras., Comment: 16 pages

In quantitative finance, machine learning methods are essential for alpha generation. This study introduces a new approach that combines Hidden Markov Models (HMM) and neural networks, integrated with Black-Litterman portfolio optimization. During the COVID period (2019-2022), this dual-model approach achieved a 83% return with a Sharpe ratio of 0.77. It incorporates two risk models to enhance risk management, showing efficiency during volatile periods. The methodology was implemented on the QuantConnect platform, which was chosen for its robust framework and experimental reproducibility. The system, which predicts future price movements, includes a three-year warm-up to ensure proper algorithm function. It targets highly liquid, large-cap energy stocks to ensure stable and predictable performance while also considering broker payments. The dual-model alpha system utilizes log returns to select the optimal state based on the historical performance. It combines state predictions with neural network outputs, which are based on historical data, to generate trading signals. This study examined the architecture of the trading system, data pre-processing, training, and performance. The full code and backtesting data are available under the QuantConnect terms., Comment: 14 pages, 4 figures, 2 tables

We present our numerical simulation approach for the End-to-End (E2E) model applied to various astronomical spectrographs, such as SOXS (ESO-NTT), CUBES (ESO-VLT), and ANDES (ESO-ELT), covering multiple wavelength regions. The E2E model aim at simulating the expected astronomical observations starting from the radiation of the scientific sources (or calibration sources) up to the raw-frame data produced by the detectors. The comprehensive description includes E2E architecture, computational models, and tools for rendering the simulated frames. Collaboration with Data Reduction Software (DRS) teams is discussed, along with efforts to meet instrument requirements. The contribution to the cross-correlation algorithm for the Active Flexure Compensation (AFC) system of CUBES is detailed., Comment: 19 pages, 17 figures, SPIE Astronomical Telescopes + Instrumentation, Yokohama 2024. arXiv admin note: text overlap with arXiv:2209.07185, arXiv:2012.12684

The first generation of ELT instruments includes an optical-infrared high-resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs ([U]BV, RIZ, YJH) providing a spectral resolution of $\sim$100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 $\mu$m with the goal of extending it to 0.35-2.4 $\mu$m with the addition of a U arm to the BV spectrograph and a separate K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Modularity and fibre-feeding allow ANDES to be placed partly on the ELT Nasmyth platform and partly in the Coud\'e room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases, there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of almost 300 scientists and engineers which include the majority of the scientific and technical expertise in the field that can be found in ESO member states., Comment: SPIE astronomical telescope and instrumentation 2024, in press

We measure the magnetic field produced by a linear octupole formed by four magnets placed in such a way that both their magnetic moments and their quadrupole moments cancel each other. The magnetic field is measured with the magnetic sensor of a smartphone together with a suitable app, using the Android operating system. The main objective is to determine the dependence of the x-component of the magnetic field with distance and compare with the theoretical result that tells us that this dependence is a quintic decrease., Comment: 4 pages, 4 figs

In the symposium contributions we discuss research in physics education and the consequences of its results for physics teaching. The symposium presents four different aspects of physics teaching and learning, but all of them have research-based problem analysis in common. The problems analysed cover different aspects of the physics teaching-learning process. Innovative aspects such as the effect on learning of the integration of engineering projects in the science teaching process, the influence on the learning process of conceptions about science and attitudes, and aspects related to teaching contents and students' learning difficulties. Its conclusions are not merely intuitive proposals based on teaching experience, but on a careful planning of data collection, analysis of results and empirical basis, Comment: Symposium Organized by GTG Physics Education Research at University-PERU

This paper develops two parameter-free methods for solving convex and strongly convex hybrid composite optimization problems, namely, a composite subgradient type method and a proximal bundle type method. Both functional and stationary complexity bounds for the two methods are established in terms of the unknown strong convexity parameter. To the best of our knowledge, the two proposed methods are the first universal methods for solving hybrid strongly convex composite optimization problems that do not rely on any restart scheme nor require the knowledge of the optimal value., Comment: 24 pages

This paper develops an adaptive Proximal Alternating Direction Method of Multipliers (P-ADMM) for solving linearly-constrained, weakly convex, composite optimization problems. This method is adaptive to all problem parameters, including smoothness and weak convexity constants. It is assumed that the smooth component of the objective is weakly convex and possibly nonseparable, while the non-smooth component is convex and block-separable. The proposed method is tolerant to the inexact solution of its block proximal subproblem so it does not require that the non-smooth component has easily computable block proximal maps. Each iteration of our adaptive P-ADMM consists of two steps: (1) the sequential solution of each block proximal subproblem, and (2) adaptive tests to decide whether to perform a full Lagrange multiplier and/or penalty parameter update(s). Without any rank assumptions on the constraint matrices, it is shown that the adaptive P-ADMM obtains an approximate first-order stationary point of the constrained problem in a number of iterations that matches the state-of-the-art complexity for the class of P-ADMMs. The two proof-of-concept numerical experiments that conclude the paper suggest our adaptive P-ADMM enjoys significant computational benefits.

This paper presents "Emotion Talk," a system designed to provide continuous emotional support through audio messages for psychological assistance. The primary objective is to offer consistent support to patients outside traditional therapy sessions by analyzing audio messages to detect emotions and generate appropriate responses. The solution focuses on Portuguese-speaking users, ensuring that the system is linguistically and culturally relevant. This system aims to complement and enhance the psychological follow-up process conducted by therapists, providing immediate and accessible assistance, especially in emergency situations where rapid response is crucial. Experimental results demonstrate the effectiveness of the proposed system, highlighting its potential in applications of psychological support.

Image search and retrieval tasks can perpetuate harmful stereotypes, erase cultural identities, and amplify social disparities. Current approaches to mitigate these representational harms balance the number of retrieved items across population groups defined by a small number of (often binary) attributes. However, most existing methods overlook intersectional groups determined by combinations of group attributes, such as gender, race, and ethnicity. We introduce Multi-Group Proportional Representation (MPR), a novel metric that measures representation across intersectional groups. We develop practical methods for estimating MPR, provide theoretical guarantees, and propose optimization algorithms to ensure MPR in retrieval. We demonstrate that existing methods optimizing for equal and proportional representation metrics may fail to promote MPR. Crucially, our work shows that optimizing MPR yields more proportional representation across multiple intersectional groups specified by a rich function class, often with minimal compromise in retrieval accuracy., Comment: 48 pages, 33 figures. Accepted as poster at NeurIPS 2024. Code can be found at https://github.com/alex-oesterling/multigroup-proportional-representation