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The integration of Semantic Communications (SemCom) and edge computing in space networks enables the optimal allocation of the scarce energy, computing, and communication resources for data-intensive applications. We use Earth Observation (EO) as a canonical functionality of satellites and review its main characteristics and challenges. We identify the potential of the space segment, represented by a low Earth orbit (LEO) satellite constellation, to serve as an edge layer for distributed intelligence. Based on that, propose a system architecture that supports semantic and goal-oriented applications for image reconstruction and object detection and localization. The simulation results show the intricate trade-offs among energy, time, and task-performance using a real dataset and State-of-the-Art (SoA) processing and communication parameters., Comment: Submitted for publication to IEEE Communications Magazine

A new system, called SELA -- Auditing Electronic System, has been developed to be applied to the Brazilian Electronic Voting Machine. The SELA was designed to use open hardware and software, making it widely known by society. The security of the auditing process is guaranteed by the application of a Fingerprint Algorithm, a Hash Function. This system is robust and requires minimal modifications to the Electronic Voting Machine. In this paper, SELA is described, and its use during the election process is analyzed. A comparison between SELA and the use of thermal printers as a secondary voting record system is also presented. The authors recommend a pilot implementation of SELA for the 2002 Brazilian Elections., Comment: 7 pages, in Portuguese language, 3 figures, prototype

Representation learning is an approach that allows to discover and extract the factors of variation from the data. Intuitively, a representation is said to be disentangled if it separates the different factors of variation in a way that is understandable to humans. Definitions of disentanglement and metrics to measure it usually assume that the factors of variation are independent of each other. However, this is generally false in the real world, which limits the use of these definitions and metrics to very specific and unrealistic scenarios. In this paper we give a definition of disentanglement based on information theory that is also valid when the factors of variation are not independent. Furthermore, we relate this definition to the Information Bottleneck Method. Finally, we propose a method to measure the degree of disentanglement from the given definition that works when the factors of variation are not independent. We show through different experiments that the method proposed in this paper correctly measures disentanglement with non-independent factors of variation, while other methods fail in this scenario.

Introduction. Here we reported the virological, entomological and epidemiological characteristics of the large autochthonous outbreak of dengue (DENV) occurred in a small village of the Lombardy region (Northern Italy) during summer 2023. Methods. After the diagnosis of the first autochthonous case on 18 August 2023, public health measures, including epidemiological investigation and vector control measures, were carried out. A serological screening for DENV antibodies detection was offered to the population. In the case of positive DENV IgM, a second sample was collected to detect DENV RNA and verify seroconversion. Entomological and epidemiological investigations were also performed. A modeling analysis was conducted to estimate the dengue generation time, transmission potential, distance of transmission, and assess diagnostic delays. Results. Overall, 416 subjects participated to the screening program and 20 were identified as DENV-1 cases (15 confirmed and 5 probable). In addition, DENV-1 infection was diagnosed in 24 symptomatic subjects referred to the local Emergency Room Department for suggestive symptoms and 1 case was identified through blood donation screening. The average generation time was estimated to be 18.3 days (95% CI: 13.1-23.5 days). R0 was estimated at 1.31 (95% CI: 0.76-1.98); 90% of transmission occurred within 500m. Entomological investigations performed in 46 pools of mosquitoes revealed the presence of only one positive pool for DENV-1. Discussion. This report highlights the importance of synergic surveillance, including virological, entomological and public health measures to control the spread of arboviral infections.

We construct deterministic particle solutions for linear and fast diffusion equations using a nonlocal approximation. We exploit the $2$-Wasserstein gradient flow structure of the equations in order to obtain the nonlocal approximating PDEs by regularising the corresponding internal energy with suitably chosen mollifying kernels, either compactly or globally supported. Weak solutions are obtained by the JKO scheme. From the technical point of view, we improve known commutator estimates, fundamental in the nonlocal-to-local limit, to include globally supported kernels which, in particular cases, allow us to justify the limit without any further perturbation needed. Furthermore, we prove geodesic convexity of the nonlocal energies in order to prove convergence of the particle solutions to the nonlocal equations towards weak solutions of the local equations. We overcome the crucial difficulty of dealing with the singularity of the first variation of the free energies at the origin. As a byproduct, we provide convergence rates expressed as a scaling relationship between the number of particles and the localisation parameter. The analysis we perform leverages the fact that globally supported kernels yield a better convergence rate compared to compactly supported kernels. Our result is relevant in statistics, more precisely in sampling Gibbs and heavy-tailed distributions.

Digital Simulations (DS) provide safe environments where users interact with an agent through conversational prompts, providing engaging learning experiences that can be used to train teacher candidates in realistic classroom scenarios. These simulations usually include open-ended questions, allowing teacher candidates to express their thoughts but complicating an automatic response analysis. To address this issue, we have evaluated Large Language Models (LLMs) to identify characteristics (user behaviors) in the responses of DS for teacher education. We evaluated the performance of DeBERTaV3 and Llama 3, combined with zero-shot, few-shot, and fine-tuning. Our experiments discovered a significant variation in the LLMs' performance depending on the characteristic to identify. Additionally, we noted that DeBERTaV3 significantly reduced its performance when it had to identify new characteristics. In contrast, Llama 3 performed better than DeBERTaV3 in detecting new characteristics and showing more stable performance. Therefore, in DS where teacher educators need to introduce new characteristics because they change depending on the simulation or the educational objectives, it is more recommended to use Llama 3. These results can guide other researchers in introducing LLMs to provide the highly demanded automatic evaluations in DS.

Ultrasound follicle tracking is an important part of cycle monitoring. OSIS Ovary (Online System for Image Segmentation for the Ovary) has been conceived aiming to aid the management of the workflow in follicle tracking, one of the most iterative procedures in cycle monitoring during ovarian stimulation. In the present study, we compared OSIS Ovary (as three-dimensional ultrasound-based automated system) with the two-dimensional manual standard measurement method, in order to assess the reliability of the main measurements obtained to track follicle growth during ovarian stimulation cycles, the follicle size and count. Based on the mean follicle diameter and follicle count values obtained, the Pearson/intraclass correlation coefficients were 0.976/0.987 and 0.804/0.889 in >=10mm follicles, 0.989/0.994 and 0.809/0.867 in >=13mm follicles and 0.995/0.997 and 0.791/0.840 in >=16mm follicles. The mean difference (MnD) for the mean diameter and follicle count was, respectively, 0.759/0.161 in >=10mm follicles, 0.486/1.033 in >=13mm follicles and 0.784/0.486 in >=16mm follicles. The upper and lower limits of agreement (ULA and LLA) were 3.641/2.123 and 5.392/3.070 in >=10mm follicles, 3.496/2.522 and 4.285/2.218 in >=13mm follicles, and 3.723/2.153 and 2.432/1.459 in >=16mm follicles. The limits of agreement range (LoAR) were 5.764/8.462 in >=10mm follicles, 6.048/6.503 in >=13mm follicles and 5.876/3.891 in >=16mm follicles. P<0.05 was considered for all calculations. As three-dimensional ultrasound-based automated system in comparison with two-dimensional manual method standard, we found OSIS Ovary as a reliable tool to track follicle growth during ovarian stimulation cycles, Comment: 21 pages, 4 figures, 2 tables

The Son Of X-Shooter (SOXS) is a single object spectrograph, built by an international consortium for the 3.58-m ESO New Technology Telescope at the La Silla Observatory [1]. It offers a simultaneous spectral coverage over 350-2000 nm, with two separate spectrographs. In this paper we present the status of the Near InfraRed (NIR) cryogenic echelle cross-dispersed spectrograph [1], in the range 0.80-2.00 {\mu}m with 15 orders, equipped with an 2k x 2k Hawaii H2RG IR array from Teledyne, working at 40K, that is currently assembled and tested on the SOXS instrument, in the premises of INAF in Padova. We describe the different tests and results of the cryo, vacuum, opto-mechanics and detector subsystems that finally will be part of the PAE by ESO., Comment: 8 Pages, 7 Figures, Astronomical Telescopes and Instrumentation, SPIE Proceedings 2024

While the search of high Tc superconductivity was driven mostly by trial and error methodology searching for novel materials, here we provide a quasi-first-principle quantum theory for engineering superconductivity in artificial high-Tc superlattices (AHTS) with period d, ranging from 5.28 down to 3 nanometers, made of superconducting quantum wells of variable thickness L. An important feature of our quantum design is the key role of the interface internal electric field giving Rashba spin-orbit coupling (SOC) in the nanoscale quantum superconducting building blocks. By tuning the geometrical conformational parameter L/d around its magic ratio 2/3 we predict the superconducting dome of Tc versus doping characteristic of unconventional superconductors. Quantum size effects, controlled by L/d, change the energy width and splitting of two quantum subbands formed by the electronic space charge confined in superconducting nano-layers. The theoretical superconducting dome Tc versus charge density controlled by the Fano-Feshbach resonance between two superconducting gaps has been able to predict experimental results on cuprate AHTS by tuning the geometry of superlattices of quantum wells made of superconducting layers (S) of thickness L of modulation doped stoichiometric Mott insulator La2CuO4 with no chemical dopants, with interface space charge confined within normal metal (N) overdoped cuprate layers, Comment: 12 pages, 12 figures. arXiv admin note: text overlap with arXiv:2211.11547

Recently, the quest for high-Tc superconductivity has evolved from the trial-and-error methodology to the growth of nanostructured artificial high-Tc superlattices (AHTS) with tailor-made superconducting functional properties by quantum design. Superlattices are composed of nanoscale superconducting units of modulation doped Mott insulator La2CuO4 with thickness L intercalated by metallic overdoped La1.55Sr0.45CuO4 and period d. Quantum design based on the multi-gap Bogoliubov theory including spin-orbit coupling (SOC). has been employed for prediction of the amplification of the critical temperature as a function of the conformational parameter L/d. At the top of the superconducting dome, at the magic ratio L/d=2/3, the heterostructures are tuned at the Fano-Feshbach resonance and the normal phase exhibits the Planckian T-linear resistivity. Here, we report experimental evidence that the Kondo proximity effect competes with the Fano-Feshbach resonance suppressing Tc on both sides of the superconducting dome. The Kondo proximity effect is expected in electrical resistance of AHTS nanoscale heterostructures following a Kondo universal scaling obtained by numerical renormalization group theory. We show the vanishing Kondo temperature TK and Kondo scattering amplitude R0K at L/d=2/3, while TK and R0K increase on the underdoped (L/d>2/3) and overdoped (L/d<2/3) side of the superconducting dome., Comment: 11 pages, 3 figures

This paper analyzes the dynamics of a level-dependent quasi-birth-death process ${\cal X}=\{(I(t),J(t)): t\geq 0\}$, i.e., a bi-variate Markov chain defined on the countable state space $\cup_{i=0}^{\infty} l(i)$ with $l(i)=\{(i,j) : j\in\{0,...,M_i\}\}$, for integers $M_i\in\mathbb{N}_0$ and $i\in\mathbb{N}_0$, which has the special property that its $q$-matrix has a block-tridiagonal form. Under the assumption that the first passage to the subset $l(0)$ occurs in a finite time with certainty, we characterize the probability law of $(\tau_{\max},I_{\max},J(\tau_{\max}))$, where $I_{\max}$ is the running maximum level attained by process ${\cal X}$ before its first visit to states in $l(0)$, $\tau_{\max}$ is the first time that the level process $\{I(t): t\geq 0\}$ reaches the running maximum $I_{\max}$, and $J(\tau_{\max})$ is the phase at time $\tau_{\max}$. Our methods rely on the use of restricted Laplace-Stieltjes transforms of $\tau_{\max}$ on the set of sample paths $\{I_{\max}=i,J(\tau_{\max})=j\}$, and related processes under taboo of certain subsets of states. The utility of the resulting computational algorithms is demonstrated in two epidemic models: the SIS model for horizontally and vertically transmitted diseases; and the SIR model with constant population size., Comment: 28 pages, 5 figures

"Innovating Workforce Education: Community Colleges at the Forefront of Registered Apprenticeship" explores Registered Apprenticeships in the United States, examining their increasing relevance to community colleges and the broader workforce development landscape. At its core, the apprenticeship model integrates paid employment with progressive learning, characterized by on-the-job training, classroom instruction, and mentorship, culminating in an industry recognized credential. This blend of practical and academic learning is pivotal for skill acquisition and provides a pathway to gainful employment. The paper will emphasize the versatility of apprenticeships while clarifying misconceptions. Apprenticeships are not limited to pre-employment training or entry-level positions but encompass diverse career stages and occupational scopes. Additionally, apprenticeships are adaptable in instructional delivery and flexible learning, making them suitable for various learning styles and job roles. In exploring types of apprenticeships, the paper identifies time-based, competency-based, and hybrid models and explores efforts like pre-apprenticeship and youth apprenticeship. Also, the paper closes by proposing future research and practice areas for ACCT, focusing on evaluating apprenticeship models, examining policy impacts, exploring digital learning's role in related instruction, and analyzing the financial models linked to apprenticeship sustainability and expansion.

This paper studies moving 180-degree N\'eel walls in ferromagnetic thin films under the reduced model for the in-plane magnetization proposed by Capella, Melcher and Otto [5], in the case when a sufficiently weak external magnetic field is applied. It is shown that the linearization around the moving N\'eel wall's phase determines a spectral problem that is a relatively bounded perturbation of the linearization around the static N\'eel wall, which is the solution when the external magnetic field is set to zero and which is spectrally stable. Uniform resolvent-type estimates for the linearized operator around the static wall are established in order to prove the spectral stability of the moving wall upon application of perturbation theory for linear operators. The spectral analysis is the basis to prove, in turn, both the decaying properties of the generated semigroup and the nonlinear stability of the moving N\'eel wall under small perturbations, in the case of a sufficiently weak external magnetic field. The stability of the static N\'eel wall, which was established in a companion paper [4], plays a key role to obtain the main result., Comment: 40 pages, 4 figures

We introduce a novel uncertainty principle for generalized graph signals that extends classical time-frequency and graph uncertainty principles into a unified framework. By defining joint vertex-time and spectral-frequency spreads, we quantify signal localization across these domains, revealing a trade-off between them. This framework allows us to identify a class of signals with maximal energy concentration in both domains, forming the fundamental atoms for a new joint vertex-time dictionary. This dictionary enhances signal reconstruction under practical constraints, such as incomplete or intermittent data, commonly encountered in sensor and social networks. Numerical experiments on real-world datasets demonstrate the effectiveness of the proposed approach, showing improved reconstruction accuracy and noise robustness compared to existing methods.

Circuit knitting emerges as a promising technique to overcome the limitation of the few physical qubits in near-term quantum hardware by cutting large quantum circuits into smaller subcircuits. Recent research in this area has been primarily oriented towards reducing subcircuit sampling overhead. Unfortunately, these works neglect hardware information during circuit cutting, thus posing significant challenges to the follow on stages. In fact, direct compilation and execution of these partitioned subcircuits yields low-fidelity results, highlighting the need for a more holistic optimization strategy. In this work, we propose a hardware-aware framework aiming to advance the practicability of circuit knitting. Drawing a contrast with prior methodologies, the presented framework designs a cutting scheme that concurrently optimizes the number of gate cuttings and SWAP insertions during circuit cutting. In particular, we leverage the graph similarity between qubits interactions and chip layout as a heuristic guide to reduces potential SWAPs in the subsequent step of qubit routing. Building upon this, the circuit knitting framework we developed has been evaluated on several quantum algorithms, leading to reduction of total subcircuits depth by up to 64% (48% on average) compared to the state-of-the-art approach, and enhancing the relative fidelity up to 2.7$\times$., Comment: Accepted to the 2024 IEEE/ACM International Conference on Computer-Aided Design (ICCAD '24)

We study the dynamics of phonon-mediated qubit-qubit interactions between trapped ions in the presence of an ultracold atomic gas. By deriving and solving a master equation to describe the combined system, we show that the presence of the atoms causes the quantum gate quality to reduce because of motional decoherence. On the other hand, we calculate that the gas may be used to keep the ion crystal cold in the presence of external heating due to electric field noise. We show that tuning the atom-ion scattering length allows to tune the cooling rate of the ions and would make it possible to temporarily reduce the effects of the gas during a quantum gate while keeping the ions cold over long timescales. In this way, the trapped ion quantum computer may be buffer gas cooled. The system may also be used for quantum-enhanced measurements of the atom-ion interactions or properties of the atomic bath., Comment: 10 pages, 4 figures

This paper focuses on studying a model for molecular motors responsible for the bending of the axoneme in the flagella of microorganisms. The model is a coupled system of partial differential equations inspired by J\"ulicher et al. or Camalet, incorporating two rows of molecular motors between microtubules filaments. Existence and uniqueness of a solution is proved, together with the presence of a supercritical Hopf bifurcation. Additionally, numerical simulations are provided to illustrate the theoretical results. A brief study on the generalization to N-rows is also included.

Understanding what is normal is a key aspect of protecting a domain. Other domains invest heavily in observational science to develop models of normal behavior to better detect anomalies. Recent advances in high performance graph libraries, such as the GraphBLAS, coupled with supercomputers enables processing of the trillions of observations required. We leverage this approach to synthesize low-parameter observational models of anonymized Internet traffic with a high regard for privacy., Comment: Accepted to IEEE HPEC, 7 pages, 6 figures, 1 table, 41 references

The optical manipulation of magnetism enabled by rare earth-transition metal ferrimagnets holds the promise of ultrafast, energy efficient spintronic technologies. This work investigates laser-induced picosecond spin currents generated by ferrimagnetic GdCo via terahertz emission spectroscopy. A suppression of the THz emission and spin current is observed at magnetization compensation when varying the temperature or alloy composition in the presence of a magnetic field. It is demonstrated that this is due to the formation of domains in the GdCo equilibrium magnetic configuration. Without an applied magnetic field, the picosecond spin current persists at the compensation point. The experimental findings support the model for THz spin current generation based on transport of hot spin-polarized electrons, which is dominated by the Co sublattice at room temperature. Only at low temperature a comparable contribution from Gd is detected but with slower dynamics. Finally, spectral analysis reveals a blueshift of the THz emission related to the formation of magnetic domains close to magnetization compensation.

Understanding the thermodynamic properties of many-body quantum systems and their emergence from microscopic laws is a topic of great significance due to its profound fundamental implications and extensive practical applications. Recent advances in experimental techniques for controlling and preparing these systems have increased interest in this area, as they have the potential to drive the development of quantum technologies. In this study, we present a density-functional theory approach to extract detailed information about the statistics of work and the irreversible entropy associated with quantum quenches at finite temperature. Specifically, we demonstrate that these quantities can be expressed as functionals of thermal and out-of-equilibrium densities, which may serve as fundamental variables for understanding finite-temperature many-body processes. We, then, apply our method to the case of the inhomogeneous Hubbard model, showing that our density functional theory based approach can be usefully employed to unveil the distinctive roles of interaction and external potential on the thermodynamic properties of such a system.

Proximity operations to small bodies, such as asteroids and comets, demand high levels of autonomy to achieve cost-effective, safe, and reliable Guidance, Navigation and Control (GNC) solutions. Enabling autonomous GNC capabilities in the vicinity of these targets is thus vital for future space applications. However, the highly non-linear and uncertain environment characterizing their vicinity poses unique challenges that need to be assessed to grant robustness against unknown shapes and gravity fields. In this paper, a pipeline designed to generate variable density gravity field models is proposed, allowing the generation of a coherent set of scenarios that can be used for design, validation, and testing of GNC algorithms. The proposed approach consists in processing a polyhedral shape model of the body with a given density distribution to compute the coefficients of the spherical harmonics expansion associated with the gravity field. To validate the approach, several comparison are conducted against analytical solutions, literature results, and higher fidelity models, across a diverse set of targets with varying morphological and physical properties. Simulation results demonstrate the effectiveness of the methodology, showing good performances in terms of modeling accuracy and computational efficiency. This research presents a faster and more robust framework for generating environmental models to be used in simulation and hardware-in-the-loop testing of onboard GNC algorithms.

Core-collapse supernovae are explosions of massive stars at the end of their evolution. They are responsible for metal production and for halting star formation, having a significant impact on galaxy evolution. The details of these processes depend on the nature of supernova progenitors, but it is unclear if Type Ic supernovae (without hydrogen or helium lines in their spectra) originate from core-collapses of very massive stars (> 30 Msun) or from less massive stars in binary systems. Here we show that Type II (with hydrogen lines) and Ic supernovae are located in environments with similar molecular gas densities, therefore their progenitors have comparable lifetimes and initial masses. This supports a binary interaction for most Type Ic supernova progenitors, which explains the lack of hydrogen and helium lines. This finding can be implemented in sub-grid prescriptions in numerical cosmological simulations to improve the feedback and chemical mixing., Comment: 9 pages, 3 figures, published in Nature Communications

While numerous methods achieving remarkable performance exist in the Object Detection literature, addressing data distribution shifts remains challenging. Continual Learning (CL) offers solutions to this issue, enabling models to adapt to new data while maintaining performance on previous data. This is particularly pertinent for edge devices, common in dynamic environments like automotive and robotics. In this work, we address the memory and computation constraints of edge devices in the Continual Learning for Object Detection (CLOD) scenario. Specifically, (i) we investigate the suitability of an open-source, lightweight, and fast detector, namely NanoDet, for CLOD on edge devices, improving upon larger architectures used in the literature. Moreover, (ii) we propose a novel CL method, called Latent Distillation~(LD), that reduces the number of operations and the memory required by state-of-the-art CL approaches without significantly compromising detection performance. Our approach is validated using the well-known VOC and COCO benchmarks, reducing the distillation parameter overhead by 74\% and the Floating Points Operations~(FLOPs) by 56\% per model update compared to other distillation methods., Comment: ECCV workshops, Computational Aspects of Deep Learning (CADL) 2024

The thermodynamic interpretation of the Stephani Universes is studied in detail. The general expression of the speed of sound and of the thermodynamic schemes associated with a thermodynamic solution is obtained. The constraints imposed on the solutions by considering some significant physical properties are analyzed. We focus on the models where the cosmological observer measures isotropic radiation. We consider some examples, and a solution that models an ultrarelativistic gas is analyzed in detail., Comment: 16 pages, 7 figures

This work presents a three-dimensional geometric resolution method to calculate the complete inverse kinematics of a 7-degree-of-freedom articulated arm, including the hand itself. The method is classified as an analytical method with geometric solution, since it obtains a precise solution in a closed number of steps, converting the inverse kinematic problem into a three-dimensional geometric model. To simplify the problem, the kinematic decoupling method is used, so that the position of the wrist is calculated independently on one hand with information on the orientation of the hand, and the angles of the rest of the arm are calculated from the wrist., Comment: in Spanish language

SAPPO is a high-precision, low-cost and highly scalable indoor localization system. The system is designed using modified HC-SR04 ultrasound transducers as a base to be used as distance meters between beacons and mobile robots. Additionally, it has a very unusual arrangement of its elements, such that the beacons and the array of transmitters of the mobile robot are located in very close planes, in a horizontal emission arrangement, parallel to the ground, achieving a range per transducer of almost 12 meters. SAPPO represents a significant leap forward in ultrasound localization systems, in terms of reducing the density of beacons while maintaining average precision in the millimeter range., Comment: in Spanish language

Let $E$ be an elliptic curve defined over $\mathbb{Q}$, and let $K$ be an imaginary quadratic field. Consider an odd prime $p$ at which $E$ has good supersingular reduction with $a_p(E)=0$ and which is inert in $K$. Under the assumption that the signed Selmer groups are cotorsion modules over the corresponding Iwasawa algebra, we prove that the Mordell-Weil ranks of $E$ are bounded over any subextensions of the anticyclotomic $\mathbb{Z}_p$-extension of $K$. Additionally, we provide an asymptotic formula for the growth of the $p$-parts of the Tate-Shafarevich groups of $E$ over these extensions.

In the following report, we describe the solution we propose for the AI Olympics competition held at IROS 2024. Our solution is based on a Model-free Deep Reinforcement Learning approach combined with an evolutionary strategy. We will briefly describe the algorithms that have been used and then provide details of the approach

Acoustoplasmonic resonators, such as nanobars and crosses, are efficient acousto-optical transducers. The excitation of mechanical modes in these structures strongly depends on the spatial profile of the eigenmodes of the resonator. Using a system of two identical gold elongated bars placed on a silicon dioxide substrate, we examine how breaking mirror symmetries affects the optical and acoustic properties to provide insights in the design of acoustoplasmonic metasurfaces for nonsymmetric acousto-optical transducers. Our findings show that, the absence of mirror symmetries affects differently the optical and nanomechanical response. Broken mirror symmetries not only couple nanomechanical modes existing in single bars, but introduces new torsional resonant modes.

Quantum Communications is a field that promises advances in cryptography, quantum computing and clock synchronisation, among other potential applications. However, communication based on quantum phenomena requires an extreme level of isolation from external disturbances, making the transmission of quantum signals together with classical ones difficult. A range of techniques has been tested to introduce quantum communications in already deployed optical networks which also carry legacy traffic. This comes with challenges, not only at the physical layer but also at the operations and management layer. To achieve a broad acceptance among network operators, the joint management and operation of quantum and classical resources, compliance with standards, and quality and legal assurance need to be addressed. This article presents a detailed account of solutions to the above issues, deployed and evaluated in the MadQCI (Madrid Quantum Communication Infrastructure) testbed. This network is designed to integrate quantum communications in the telecommunications ecosystem by installing quantum-key-distribution modules from multiple providers in production nodes of two different operators. The modules were connected through an optical-switched network with more than 130 km of deployed optical fibre. The tests were done in compliance with strict service level agreements that protected the legacy traffic of the pre-existing classical network. The goal was to achieve full quantum-classical compatibility at all levels, while limiting the modifications of optical transport and encryption and complying with as many standards as possible. This effort was intended to serve as a blueprint, which can be used as the foundation of large-scale quantum network deployments. To demonstrate the capabilities of MadQCI, end-to-end encryption services were deployed and a variety of use-cases were showcased., Comment: 16 pages

Fault-tolerant quantum computers must be designed in conjunction with classical co-processors that decode quantum error correction measurement information in real-time. In this work, we introduce the belief propagation plus ordered Tanner forest (BP+OTF) algorithm as an almost-linear time decoder for quantum low-density parity-check codes. The OTF post-processing stage removes qubits from the decoding graph until it has a tree-like structure. Provided that the resultant loop-free OTF graph supports a subset of qubits that can generate the syndrome, BP decoding is then guaranteed to converge. To enhance performance under circuit-level noise, we introduce a technique for sparsifying detector error models. This method uses a transfer matrix to map soft information from the full detector graph to the sparsified graph, preserving critical error propagation information from the syndrome extraction circuit. Our BP+OTF implementation first applies standard BP to the full detector graph, followed by BP+OTF post-processing on the sparsified graph. Numerical simulations show that the BP+OTF decoder achieves logical error suppression within an order of magnitude of state-of-the-art inversion-based decoders while maintaining almost-linear runtime complexity across all stages., Comment: 13 pages, 3 figures

In this paper, we address the challenge of clustering mixed-type data with temporal evolution by introducing the statistical jump model for mixed-type data. This novel framework incorporates regime persistence, enhancing interpretability and reducing the frequency of state switches, and efficiently handles missing data. The model is easily interpretable through its state-conditional means and modes, making it accessible to practitioners and policymakers. We validate our approach through extensive simulation studies and an empirical application to air quality data, demonstrating its superiority in inferring persistent air quality regimes compared to the traditional air quality index. Our contributions include a robust method for mixed-type temporal clustering, effective missing data management, and practical insights for environmental monitoring., Comment: 25 pages, 5 figures, 9 tables

MEIGA is a module specially designed for people with tetraplegia or anyone who has very limited movement capacity in their upper limbs. MEIGA converts the user's head movements into mouse movements. To simulate keystrokes, it uses blinking, reading the movement of the cheek that occurs with it. The performance, speed of movement of the mouse and its precision are practically equivalent to their respective measurements using the hand., Comment: in Spanish language

Within the Standard Model Effective Field Theory framework, we set indirect constraints on top quark operators that violate baryon number by one unit above the TeV scale. We find that these constraints are typically many orders of magnitude more stringent than the recently derived direct bounds from collider experiments. Therefore, direct observation of baryon number violation in top-quark observables at the TeV scale would imply a large fine-tuning among operators across different energy scales. This possibility is not protected under universal radiative corrections or any known symmetry principles., Comment: 8 pages, 2 tables, 2 figures