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Gatemons are superconducting qubits similar to transmons except that the Josephson element consists of a gate-tunable semiconducting weak link. Here, we report the realization of a gatemon device obtained by fabricating a microwave circuit in aluminium on a SiGe heterostructure embedding a Ge quantum well. Owing to the superconducting proximity effect, the high-mobility two-dimensional hole gas confined in this well provides a gate-tunable superconducting weak link between two Al contacts. We perform Rabi oscillation and Ramsey interference measurements, demonstrate the gate-voltage dependence of the qubit frequency, and measure the qubit anharmonicity. The reported proof-of-concept reproduces the results of a very recent work [Sagi et al., Nat. Commun. 15, 6400 (2024)] using similar SiGe heterostructures thereby validating a novel platform for the development of gatemons and parity-protected $\cos(2\phi)$ qubits.

In this study, we provide a full experimental characterization of the parametric longitudinal coupling between a CMOS charge qubit and an off-chip RF resonator. Following Corrigan et al, Phys. Rev. Applied 20, 064005 (2023), we activate parametric longitudinal coupling by driving the charge qubit at the resonator frequency. Managing the crosstalk between the drive applied to the qubit and the resonator allows for the systematic study of the dependence of the longitudinal and dispersive charge-photon couplings on the qubit-resonator detuning and the applied drive. Our experimental estimations of the charge-photon couplings are perfectly reproduced by theoretical simple formulas, without relying on any fitting parameter. We go further by showing a parametric displacement of the resonator's steady state, conditional on the qubit state, and the insensitivity of the longitudinal coupling constant on the photon population of the resonator. Our results open to the exploration of the photon-mediated longitudinal readout and coupling of multiple and distant spins, with long coherent times, in hybrid CMOS cQED architectures., Comment: 11 pages, 12 figures

Populations very often self-organize into regular spatial patterns with important ecological and evolutionary consequences. Yet, most existing models neglect the effect that external biophysical drivers might have both on pattern formation and the spatiotemporal population dynamics once patterns form. Here, we investigate the effect of environmental flows on pattern formation and population dynamics using a spatially nonlocal logistic model (or Fisher-Kolmogorov equation) coupled to a simple shear and a Rankine vortex flow. We find that, whereas population abundance generally decreases with increasing flow intensity, the effect of the flow on the pattern instability depends on the spatial structure of the flow velocity field. This result shows that the velocity field interacts with the spatial feedbacks responsible for pattern formation in non-trivial ways, leading to a variety of spatiotemporal population dynamics regimes in which the total population abundance can exhibit either regular oscillations with a characteristic frequency or more erratic dynamics without a well-defined period. More generally, the diversity of spatiotemporal population dynamics caused by the interplay between self-organizing feedbacks and environmental flows highlights the importance of incorporating environmental and biophysical processes when studying both ecological pattern formation and its consequences., Comment: 27 pages, 10 figures

Event extraction is an NLP task that commonly involves identifying the central word (trigger) for an event and its associated arguments in text. ACE-2005 is widely recognised as the standard corpus in this field. While other corpora, like PropBank, primarily focus on annotating predicate-argument structure, ACE-2005 provides comprehensive information about the overall event structure and semantics. However, its limited language coverage restricts its usability. This paper introduces ACE-2005-PT, a corpus created by translating ACE-2005 into Portuguese, with European and Brazilian variants. To speed up the process of obtaining ACE-2005-PT, we rely on automatic translators. This, however, poses some challenges related to automatically identifying the correct alignments between multi-word annotations in the original text and in the corresponding translated sentence. To achieve this, we developed an alignment pipeline that incorporates several alignment techniques: lemmatization, fuzzy matching, synonym matching, multiple translations and a BERT-based word aligner. To measure the alignment effectiveness, a subset of annotations from the ACE-2005-PT corpus was manually aligned by a linguist expert. This subset was then compared against our pipeline results which achieved exact and relaxed match scores of 70.55\% and 87.55\% respectively. As a result, we successfully generated a Portuguese version of the ACE-2005 corpus, which has been accepted for publication by LDC.

This study presents a novel application of Graph Neural Networks (GNNs) to optimize dealership network planning for a luxury car manufacturer in the U.S. By conducting a comprehensive literature review on dealership location determinants, the study identifies 65 county-level explanatory variables, augmented by two additional measures of regional interconnectedness derived from social and mobility data. An ablation study involving 34 variable combinations and ten state-of-the-art GNN operators reveals key insights into the predictive power of various variables, particularly highlighting the significance of competition, demographic factors, and mobility patterns in influencing dealership location decisions. The analysis pinpoints seven specific counties as promising targets for network expansion. This research not only illustrates the effectiveness of GNNs in solving complex geospatial decision-making problems but also provides actionable recommendations and valuable methodological insights for industry practitioners., Comment: Accetped at IEEE BigData 2024, 10 pages, 4 figures, 6 tables, code and data are available at https://github.com/carocciluca/gnn-site-selection

The water entry at high horizontal speed of double-curvature specimens, reproducing the rear part of the fuselage that first gets in contact with the water during aircraft ditching, is investigated experimentally. Three shapes are analysed, representing different aircraft types. Pressure and load measurements are taken, supported by underwater high-speed visualization. The effects of different horizontal speeds, pitch angles, and curvatures are analysed, while keeping a constant vertical-to-horizontal velocity ratio. It is observed that the longitudinal curvature plays a significant role in the hydrodynamics, potentially leading to cavitation and ventilation in the rear part of the specimen at high speeds. The transverse curvature affects the pressures and loads both at the front and at the rear, since a lower transverse curvature increases the possibility of the fluid to escape from the sides. An increase in pitch angle results in an increased loading, in terms of both amplitude and distribution. Finally, an increased horizontal speed leads to higher loads at the front but also affects the cavitation and ventilation modalities at the rear. The load scaling for flat plates also applies to these specimens at the front, but the occurrence of cavitation and ventilation invalidates it at the rear. The time evolution of the cavitation region and of the wetted area are examined through advanced image processing techniques and pressure data analysis. The comparison with the geometric intersection area of the specimen with the still water surface provides further insight into the hydrodynamic phenomena during the water entry., Comment: 46 pages, 33 figures. Submitted to Journal of Fluid Mechanics

We calculate the form factors $F_{V}(q^2,q'^2)$ and $F_{TV}(q^2,q'^2)$ describing the $B_s\to \gamma^*$ transition induced by the vector and tensor weak currents in a broad range of values of $q^2$ and $q'^2$ far below the quark thresholds in both $q^2$ and $q'^2$ channels. These form factors are calculated via the distribution amplitudes of the $B_s$-meson. We then interpolate the obtained results by a formula that contains pole at $q'^2=M_\phi^2$ and extract the residue which gives the $B_s\to \phi$ transition form factors $V(q^2)$ and $T_1(q^2)$. In this way we obtain theoretical predictions for these form factors without invoking quark-hadron duality and QCD sum rules. Furthermore, we calculate the relationship between $V(0)$ and $T_1(0)$ and the parameter $\lambda_{B_s}(\mu)$, the inverse moment of the $B_s$-meson distribution amplitude. Using the available predictions for $V(0)$ and $T_1(0)$ coming from approaches not referring to the $B_s$-meson distribution amplitudes, we obtain the estimate $\lambda_{B_s}(\mu\simeq m_b)=(0.62\pm 0.10)$ GeV., Comment: 11 pages, small text changes, version to be published in PRD

Some properties of $m$-density points and density-degree functions are studied. Moreover the following main results are provided: \vskip2mm \begin{itemize} \item {\it Let $\lambda$ be a continuous differential form of degree $h$ in ${\mathbf R}^n$ (with $h\geq 0$) having the following property: There exists a continuous differential form $\Delta$ of degree $h+1$ in $\rn^n$ such that \begin{equation*} \int_{{\mathbf R}^n}\Delta\wedge\omega =\int_{{\mathbf R}^n}\lambda\wedge d\omega, \end{equation*} for every $C^\infty_c$ differential form $\omega$ of degree $n-h-1$ in ${\mathbf R}^n$. Moreover let $\mu$ be a $C^1$ differential form of degree $h+1$ in ${\mathbf R}^n$ and set $E:=\{y\in {\mathbf R}^n\,\vert\, \Delta (y)=\mu(y)\}$. Then $d\mu (x) = 0$ whenever $x$ is a $(n+1)$-density point of $E$.} \vskip2mm \item {\it Let $f:{\mathbf R}^n\to\overline {\mathbf R}$ be a measurable function such that $f(x)\in \{0\}\cup [n,+\infty]$ for a.e. $x\in {\mathbf R}^n$. Then there exists a countable family $\{F_k\}_{k=1}^\infty$ of closed subsets of ${\mathbf R}^n$ such that the corresponding sequence of density-degree functions $\{d_{F_k}\}_{k=1}^\infty$ converges almost everywhere to $f$. }

A property of weak stationarity of a matrix valued differential form at superdensity points of its vanishing set is proved. This result is then applied in the context of the Maurer-Cartan equation.

The FlyEye design makes its debut in the ESA's NEOSTEL developed by OHB-Italia. This pioneering FlyEye telescope integrates a monolithic 1-meter class primary mirror feeding 16 CCD cameras for discovering Near-Earth Object (NEO) and any class of transient phenomena. OHB-Italia is the prime contractor, receiving extended support from the Italian National Institute for Astrophysics (INAF) in the ESA's NEOSTED program's integration and testing. The FlyEye distinctive design splits the Field of View into 16 channels, creating a unique multi-telescope system with a panoramic 44 square degree Field of View and a seeing-size pixel-scale, enabling NEOs detection down to apparent magnitudes 21.5 insisting on a 1m diameter spherical mirror. The scientific products of a similar FlyEye telescope can complement facilities such as Vera Rubin (former LSST) and ZTF. The FlyEye has the ability to survey two-thirds of the visible sky about three times per night can revolutionize time-domain astronomy, enabling comprehensive studies of transient phenomena, placing FlyEye in a new era of exploration of the dynamic universe. Efforts to develop automated calibration and testing procedures are keys to realizing this transformative potential., Comment: 9 pages, 1 figure, SPIE Astronomical Telescopes + Instrumentation, Ground-based and Airborne Instrumentation for Astronomy X, 16-21 June 2024

Let ${\mathcal D}$ and $T$ be, respectively, a $C^1$ distribution of $k$-planes and a normal $k$-current on ${\mathbf R}^n$. Then ${\mathcal D}$ has to be involutive at almost every superdensity point of the tangency set of $T$ with respect to ${\mathcal D}$.

We introduce and investigate superdensity and the density degree of sets with respect to a Radon measure on ${\mathbf R}^n$. Some applications are provided. In particular we prove a result on the approximability of a set by closed subsets of small density degree and a generalization of Schwarz's theorem on cross derivatives.

Step-counting has been widely implemented in wrist-worn devices and is accepted by end users as a quantitative indicator of everyday exercise. However, existing counting approach (mostly on wrist-worn setup) lacks robustness and thus introduces inaccuracy issues in certain scenarios like brief intermittent walking bouts and random arm motions or static arm status while walking (no clear correlation of motion pattern between arm and leg). This paper proposes a low-power step-counting solution utilizing the body area electric field acquired by a novel electrostatic sensing unit, consuming only 87.3 $\mu$W of power, hoping to strengthen the robustness of current dominant solution. We designed two wearable devices for on-the-wrist and in-the-ear deployment and collected body-area electric field-derived motion signals from ten volunteers. Four walking scenarios are considered: in the parking lot/shopping center with/without pushing the shopping trolley. The step-counting accuracy from the prototypes shows better accuracy than the commercial wrist-worn devices (e.g.,96% of the wrist- and ear-worn prototype vs. 66% of the Fitbit when walking in the shopping center while pushing a shopping trolley). We finally discussed the potential and limitations of sensing body-area electric fields for wrist-worn and ear-worn step-counting and beyond.

Random features are a powerful technique for rewriting positive-definite kernels as linear products. They bring linear tools to bear in important nonlinear domains like KNNs and attention. Unfortunately, practical implementations require approximating an expectation, usually via sampling. This has led to the development of increasingly elaborate representations with ever lower sample error. We resolve this arms race by deriving an optimal sampling policy. Under this policy all random features representations have the same approximation error, which we show is the lowest possible. This means that we are free to choose whatever representation we please, provided we sample optimally.

Electronic fluids can display exciting dynamical properties. In particular, due to Landau damping, the collective modes spectrum of an electronic system with multipolar interactions is non-hermitian, and can present non-hermitian degeneracies called $\textit{exceptional points}$. In this work, we want to explore the dynamical properties of these degeneracies using laser control. We show that by using a light pulse, we can control the collective mode spectrum and tune a non-hermitian $\mathcal{PT}$ phase transition in which two exceptional points anhilate each other. At this transition, the gap closes with a cubic root signature, what defines a third order exceptional point., Comment: 7 pages, 4 figures

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

Scene coordinate regression (SCR) methods are a family of visual localization methods that directly regress 2D-3D matches for camera pose estimation. They are effective in small-scale scenes but face significant challenges in large-scale scenes that are further amplified in the absence of ground truth 3D point clouds for supervision. Here, the model can only rely on reprojection constraints and needs to implicitly triangulate the points. The challenges stem from a fundamental dilemma: The network has to be invariant to observations of the same landmark at different viewpoints and lighting conditions, etc., but at the same time discriminate unrelated but similar observations. The latter becomes more relevant and severe in larger scenes. In this work, we tackle this problem by introducing the concept of co-visibility to the network. We propose GLACE, which integrates pre-trained global and local encodings and enables SCR to scale to large scenes with only a single small-sized network. Specifically, we propose a novel feature diffusion technique that implicitly groups the reprojection constraints with co-visibility and avoids overfitting to trivial solutions. Additionally, our position decoder parameterizes the output positions for large-scale scenes more effectively. Without using 3D models or depth maps for supervision, our method achieves state-of-the-art results on large-scale scenes with a low-map-size model. On Cambridge landmarks, with a single model, we achieve 17% lower median position error than Poker, the ensemble variant of the state-of-the-art SCR method ACE. Code is available at: https://github.com/cvg/glace., Comment: Large-scale visual localization with a single optimizable MLP. CVPR 2024. Code: https://github.com/cvg/glace. Project page: https://xjiangan.github.io/glace

We investigate a system of two-dimensional interacting Brownian particles at finite density. In the continuum limit, we uncover a hidden symmetry under area-preserving diffeomorphism transformations. This symmetry leads to the conservation of local vorticity. By calculating the generating functional within the saddle-point plus Gaussian fluctuations approximation, we reveal the emergence of a $U(1)$ gauge symmetry. This emergent symmetry enables us to describe the dynamics of density fluctuations as a gauge theory. We solve the corresponding equations of motion for various local and non-local two-body potentials, demonstrating the presence of multiple dynamical regimes and associated dynamical phase transitions., Comment: 10 pages, 1 figure

Hybrid superconductor-semiconductor Josephson field-effect transistors (JoFETs) function as Josephson junctions with a gate-tunable critical current. Additionally, they can feature a non-sinusoidal current-phase relation (CPR) containing multiple harmonics of the superconducting phase difference, a so-far underutilized property. In this work, we exploit this multi-harmonicity to create a Josephson circuit element with an almost perfectly $\pi$-periodic CPR, indicative of a largely dominant charge-4e supercurrent transport. Such a Josephson element was recently proposed as the basic building block of a protected superconducting qubit. Here, it is realized using a superconducting quantum interference device (SQUID) with low-inductance aluminum arms and two nominally identical JoFETs. The latter are fabricated from a SiGe/Ge/SiGe quantum-well heterostructure embedding a high-mobility two-dimensional hole gas. By carefully adjusting the JoFET gate voltages and finely tuning the magnetic flux through the SQUID close to half a flux quantum, we achieve a regime where the $\sin(2\varphi)$ component accounts for more than \SI{95}{\percent} of the total supercurrent. This result demonstrates a new promising route for the realization of superconducting qubits with enhanced coherence properties.

In this paper, we consider the recently introduced application of the Deck of Cards Method (DCM) to ordinal regression proposing an extension to Robust Ordinal Regression and Stochastic Multiattribute Acceptability Analysis. In Multiple Criteria Decision Aiding context, the proposed methodology permits to assign a value to each alternative evaluated on a set of criteria hierarchically structured. The Decision Maker can provide precise or imprecise information at different levels of the hierarchy of criteria using the classical DCM framework. This information is therefore used to infer a value function compatible with it. The compatible value function can be a simple weighted sum, a piecewise linear value function, a general monotonic value function, or a Choquet integral. To provide robust recommendations to the Decision Maker, we consider the Robust Ordinal Regression and the Stochastic Multicriteria Acceptability Analysis because, even if in different ways, both of them take into account the whole set of models compatible with the preference information provided by the Decision Maker. The applicability of the proposed methodology is shown by a didactic example in which Italian regions are evaluated on criteria representing Circular Economy, Innovation Driven Development and Smart Specialization Strategies.

We present updated estimates of $\vert V_{cb} \vert$ and $R(D^{(*)})$ based on all the available theoretical and experimental data on semileptonic $B \to D^{(*)} \ell \nu_\ell$ decays. These values have been obtained by using the Dispersive Matrix method to describe the hadronic form factors. By analysing all the lattice data we get the theoretical values $R^{\rm th}(D) = 0.296 \pm 0.008$ and $R^{\rm th}(D^*) = 0.262 \pm 0.009$, which are consistent with the corresponding HFLAV averages at the $\simeq 2.0\,\sigma$ and the $\simeq 1.5\,\sigma$ level, respectively. Moreover, from a bin-per-bin study of the experimental data we obtain the values $\vert V_{cb} \vert = (41.0 \pm 1.2) \cdot10^{-3}$ from $B \to D$ decay and $\vert V_{cb} \vert = (39.92 \pm 0.64) \cdot10^{-3}$ from $B \to D^*$ one, whose differences with the latest inclusive determinations never exceed the $\simeq 2.5\,\sigma$ level., Comment: 6 pages, 2 figures. Presented at the 12th Workshop on the CKM Unitarity Triangle, 18-22 September 2023, Santiago de Compostela

This study addresses the prediction of geomagnetic disturbances by exploiting machine learning techniques. Specifically, the Long-Short Term Memory recurrent neural network, which is particularly suited for application over long time series, is employed in the analysis of in-situ measurements of solar wind plasma and magnetic field acquired over more than one solar cycle, from $2005$ to $2019$, at the Lagrangian point L$1$. The problem is approached as a binary classification aiming to predict one hour in advance a decrease in the SYM-H geomagnetic activity index below the threshold of $-50$ nT, which is generally regarded as indicative of magnetospheric perturbations. The strong class imbalance issue is tackled by using an appropriate loss function tailored to optimize appropriate skill scores in the training phase of the neural network. Beside classical skill scores, value-weighted skill scores are then employed to evaluate predictions, suitable in the study of problems, such as the one faced here, characterized by strong temporal variability. For the first time, the content of magnetic helicity and energy carried by solar transients, associated with their detection and likelihood of geo-effectiveness, were considered as input features of the network architecture. Their predictive capabilities are demonstrated through a correlation-driven feature selection method to rank the most relevant characteristics involved in the neural network prediction model. The optimal performance of the adopted neural network in properly forecasting the onset of geomagnetic storms, which is a crucial point for giving real warnings in an operational setting, is finally showed.

The scalability of spin qubit devices is conditioned by qubit-to-qubit variability. Disorder in the host materials indeed affects the wave functions of the confined carriers, which leads to variations in their charge and spin properties. Charge disorder in the amorphous oxides is particularly detrimental owing to its long-range influence. Here we analyze the effects of charge traps at the semiconductor/oxide interface, which are generally believed to play a dominant role in variability. We consider multiple random distributions of these interface traps and numerically calculate their impact on the chemical potentials, detuning and tunnel coupling of two adjacent quantum dots in SiGe heterostructure. Our results highlight the beneficial screening effect of the metal gates. The surface of the heterostructure shall, therefore, be covered as much as possible by the gates in order to limit variability. We propose an alternative layout with tip-shaped gates that maximizes the coverage of the semiconductor/oxide interface and outperforms the usual planar layout in some regimes. This highlights the importance of design in the management of device-to-device variability.

We perform three-dimensional numerical simulations of magnetized relativistic jets propagating in a uniform density environment in order to study the effect of the entrainment and the consequent deceleration, extending a previous work in which magnetic effects were not present. As in previous papers, our aim is to understand the connection between the jet properties and the resulting Fanaroff-Riley classification. We consider jets with different low densities, and therefore low power, and different magnetizations. We find that lower magnetization jets effectively decelerate to sub-relativistic velocities and may then result in an FR~I morphology on larger scales. At the opposite, in the higher magnetization cases, the entrainment and consequent deceleration are substantially reduced. }, Comment: 13 pages, 11 figures, accepted in A&A

We propose a method for checking generalized reachability properties in Petri nets that takes advantage of structural reductions and that can be used, transparently, as a pre-processing step of existing model-checkers. Our approach is based on a new procedure that can project a property, about an initial Petri net, into an equivalent formula that only refers to the reduced version of this net. Our projection is defined as a variable elimination procedure for linear integer arithmetic tailored to the specific kind of constraints we handle. It has linear complexity, is guaranteed to return a sound property, and makes use of a simple condition to detect when the result is exact. Experimental results show that our approach works well in practice and that it can be useful even when there is only a limited amount of reductions.

We present a lattice determination of the hadronic susceptibilities that, thanks to unitarity and analyticity, constrain the form factors entering the semileptonic $b\rightarrow c$ transitions. We evaluate the transverse and longitudinal susceptibilities of the vector and axial polarization functions at zero momentum transfer from the moments of appropriate two-point correlation functions. The latter are obtained on the lattice employing gauge ensembles of the Extended Twisted Mass Collaboration (ETMC) with $N_f$=2+1+1 flavors of Wilson-clover twisted-mass quarks with masses of all the dynamical quark flavors tuned close to their physical values. The simulations are carried out at four values of the lattice spacing, $a \simeq (0.057,0.068, 0.080, 0.091)$ fm, with spatial lattice sizes up to $L \simeq 7.6$ fm. Heavy-quark masses up to $\approx 3.5$ times the physical charm mass are employed, allowing for a smooth extrapolation to the physical b-quark mass., Comment: 7 pages, 4 figures, proceeding of Lattice 2023

Accurate and low-power indoor localization is becoming more and more of a necessity to empower novel consumer and industrial applications. In this field, the most promising technology is based on UWB modulation; however, current UWB positioning systems do not reach centimeter accuracy in general deployments due to multipath and nonisotropic antennas, still necessitating several fixed anchors to estimate an object's position in space. This article presents an in-depth study and assessment of angle of arrival (AoA) UWB measurements using a compact, low-power solution integrating a novel commercial module with phase difference of arrival (PDoA) estimation as integrated feature. Results demonstrate the possibility of reaching centimeter distance precision and ang 2.4 average angular accuracy in many operative conditions, e.g., in a ang 90 range around the center. Moreover, integrating the channel impulse response, the phase differential of arrival, and the point-to-point distance, an error correction model is discussed to compensate for reflections, multipaths, and front-back ambiguity., Comment: This article has been accepted for publication in the IEEE Transactions on Instrumentation and Measurement journal. DOI: https://doi.org/10.1109/TIM.2023.3282289

We investigate a two-dimensional system of interacting Active Brownian Particles. Using the Martin-Siggia-Rose-Janssen-de Dominicis formalism, we built up the generating functional for correlation functions. We study in detail the hydrodynamic regime with a constant density stationary state. Our findings reveal that, within a small density fluctuations regime, an emergent $U(1)$ gauge symmetry arises, originated from the conservation of fluid vorticity. Consequently, the interaction between the orientational order parameter and density fluctuations can be cast into a gauge theory, where the concept of ``electric charge density" aligns with the local vorticity of the original fluid. We study in detail the case of a microscopic local two-body interaction. We show that, upon integrating out the gauge fields, the stationary states of the rotational degrees of freedom satisfy a non-local Frank free energy for a nematic fluid. We give explicit expressions for the splay and bend elastic constants as a function of the P\'eclet number (${\rm Pe}$) and the diffusion interaction constant ($k_d$)., Comment: 15 pages, final version accepted to publish in Phys. Rev. E

This paper tackles the intricate challenge of improving the quality of nighttime images under hazy and low-light conditions. Overcoming issues including nonuniform illumination glows, texture blurring, glow effects, color distortion, noise disturbance, and overall, low light have proven daunting. Despite the inherent difficulties, this paper introduces a pioneering solution named Nighttime Dehazing, Low-Light Enhancement, and Light Suppression (NDELS). NDELS utilizes a unique network that combines three essential processes to enhance visibility, brighten low-light regions, and effectively suppress glare from bright light sources. In contrast to limited progress in nighttime dehazing, unlike its daytime counterpart, NDELS presents a comprehensive and innovative approach. The efficacy of NDELS is rigorously validated through extensive comparisons with eight state-of-the-art algorithms across four diverse datasets. Experimental results showcase the superior performance of our method, demonstrating its outperformance in terms of overall image quality, including color and edge enhancement. Quantitative (PSNR, SSIM) and qualitative metrics (CLIPIQA, MANIQA, TRES), measure these results.

Spatial and contextual awareness has the potential to revolutionize sensor nodes, enabling spatially augmented data collection and location-based services. With its high bandwidth, superior energy efficiency, and precise time-of-flight measurements, ultra-wideband (UWB) technology emerges as an ideal solution for such devices. This paper presents an evaluation and comparison of a non-coherent UWB transceiver within the context of highly energy-constrained wireless sensing nodes and pervasive Internet of Things (IoT) devices. Experimental results highlight the unique properties of UWB transceivers, showcasing efficient data transfer ranging from 2 kbit/s to 7.2 Mbit/s while reaching an energy consumption of 0.29 nJ/bit and 1.39 nJ/bit for transmitting and receiving, respectively. Notably, a ranging accuracy of up to +/-25 cm can be achieved. Moreover, the peak power consumption of the UWB transceiver is with 6.7 mW in TX and 23 mW in RX significantly lower than that of other commercial UWB transceivers., Comment: This article has been accepted for publication in the Proceedings of the 2023 IEEE SENSORS conference. DOI: https://doi.org/10.1109/SENSORS56945.2023.10325219

In this contribution we describe a recent study focused on the lattice calculation of inclusive decay rates of heavy mesons. We show how the inclusive calculation can be achieved starting from four-point lattice correlation functions normalised appropriately. The correlators used in this project come from gauge ensembles provided by the JLQCD and ETM collaborations. An essential point of this method is the extraction of spectral densities from lattice correlators which is obtained using two of the most recent approaches in the literature. Our results are in remarkable agreement with analytical predictions from the operator-product expansion. This study represents the first step towards a full lattice QCD study of heavy mesons inclusive semileptonic decays., Comment: 6 pages, 2 figures, contribution to IFAE 2023, Catania (Italy), 12-14 April 2023

Connected and Automated Vehicles (CAVs) can have a profound influence on transport systems. However, most levels of automation and connectivity require support from the road infrastructure. Additional support such as Cooperative Intelligent Transport Systems (C-ITS) services can facilitate safe and efficient traffic, and alleviate the environmental impacts of road surface vehicles. However, due to the rapidly evolving technology, C-ITS service deployment requirements are not always clear. Furthermore, the costs and benefits of infrastructure investments are subject to tremendous uncertainty. This study articulates the requirements using a structured approach to propose a CAV-Readiness Framework (CRF). The main purpose of the CRF is allowing road authorities to assess their physical and digital infrastructure readiness, define requirements for C-ITS services, and identify future development paths to reach higher levels of readiness to support CAVs by enabling C-ITS services. The CRF is intended to guide and support road authorities' investment decisions on infrastructure.

In the ever-growing Internet of Things (IoT) landscape, smart power management algorithms combined with energy harvesting solutions are crucial to obtain self-sustainability. This paper presents an energy-aware adaptive sampling rate algorithm designed for embedded deployment in resource-constrained, battery-powered IoT devices. The algorithm, based on a finite state machine (FSM) and inspired by Transmission Control Protocol (TCP) Reno's additive increase and multiplicative decrease, maximizes sensor sampling rates, ensuring power self-sustainability without risking battery depletion. Moreover, we characterized our solar cell with data acquired over 48 days and used the model created to obtain energy data from an open-source world-wide dataset. To validate our approach, we introduce the EcoTrack device, a versatile device with global navigation satellite system (GNSS) capabilities and Long-Term Evolution Machine Type Communication (LTE-M) connectivity, supporting MQTT protocol for cloud data relay. This multi-purpose device can be used, for instance, as a health and safety wearable, remote hazard monitoring system, or as a global asset tracker. The results, validated on data from three different European cities, show that the proposed algorithm enables self-sustainability while maximizing sampled locations per day. In experiments conducted with a 3000 mAh battery capacity, the algorithm consistently maintained a minimum of 24 localizations per day and achieved peaks of up to 3000., Comment: This article has been accepted for publication in the Proceedings of the 11th International Workshop on Energy Harvesting and Energy-Neutral Sensing Systems (ENSSys '23). DOI: https://doi.org/10.1145/3628353.3628545

This paper introduces an effective solution for retrofitting construction power tools with low-power IoT to enable accurate activity classification. We address the challenge of distinguishing between when a power tool is being moved and when it is actually being used. To achieve classification accuracy and power consumption preservation a newly released algorithm called MiniRocket was employed. Known for its accuracy, scalability, and fast training for time-series classification, in this paper, it is proposed as a TinyML algorithm for inference on resource-constrained IoT devices. The paper demonstrates the portability and performance of MiniRocket on a resource-constrained, ultra-low power sensor node for floating-point and fixed-point arithmetic, matching up to 1% of the floating-point accuracy. The hyperparameters of the algorithm have been optimized for the task at hand to find a Pareto point that balances memory usage, accuracy and energy consumption. For the classification problem, we rely on an accelerometer as the sole sensor source, and BLE for data transmission. Extensive real-world construction data, using 16 different power tools, were collected, labeled, and used to validate the algorithm's performance directly embedded in the IoT device. Experimental results demonstrate that the proposed solution achieves an accuracy of 96.9% in distinguishing between real usage status and other motion statuses while consuming only 7kB of flash and 3kB of RAM. The final application exhibits an average current consumption of less than 15{\mu}W for the whole system, resulting in battery life performance ranging from 3 to 9 years depending on the battery capacity (250-500mAh) and the number of power tool usage hours (100-1500h).

Indoor Positioning System (IPS) is a crucial technology that enables medical staff and hospital managements to accurately locate and track persons or assets inside the medical buildings. Among other technologies, Bluetooth Low Energy (BLE) can be exploited for achieving an energy-efficient and low-cost solution. This work presents the design and implementation of an received signal strength indicator (RSSI)-based indoor localization system. The paper shows the implementation of a low complex weighted k-Nearest Neighbors algorithm that processes raw RSSI data from connection-less iBeacon's. The designed hardware and firmware are implemented around the low-power and low-cost nRF52832 from Nordic Semiconductor. Experimental evaluation with the real-time data processing has been evaluated and presented in a 7.2 m by 7.2 m room with furniture and 5 beacon nodes. The experimental results show an average error of only 0.72 m in realistic conditions. Finally, the overall power consumption of the fixed beacon with a periodic advertisement of 100 ms is only 50 uA at 3 V, which leads to a long-lasting solution of over one year with a 500 mAh coin battery., Comment: This article has been accepted for publication in the proceedings of the 2021 IEEE International Conference on Wireless and Mobile Computing, Networking And Communications (WiMob). DOI: 10.1109/WiMob52687.2021.9606272

The rapid growth of the Internet of Things paradigm is pushing the need to connect billions of batteryoperated devices to the internet and among them. To address this need, the introduction of energy-efficient wireless mesh networks based on Bluetooth provides an effective solution. This paper proposes a testbed setup to accurately evaluate and compare the standard Bluetooth Mesh 5.0 and the emerging energy-efficient Wirepas protocol that promises better performance. The paper presents the evaluation in terms of power consumption, energy efficiency, and transmission latency which are the most crucial features, in a controlled and reproducible test setup consisting of 10 nodes. Experimental results demonstrated that Wirepas has a median latency of 2.83 ms in Low-Latency mode respectively around 2 s in the Low-Energy mode. The corresponding power consumption is 6.2 mA in Low-Latency mode and 38.9 uA in Low-Energy mode. For Bluetooth Mesh the median latency is 4.54 ms with a power consumption of 6.2 mA at 3.3 V. Based on this comparison, conclusions about the advantages and disadvantages of both technologies can be drawn., Comment: This article has been accepted for publication in the proceedings of the 2023 IEEE International Conference on Wireless and Mobile Computing, Networking And Communications (WiMob). DOI: 10.1109/WiMob58348.2023.10187799

Radial velocity surveys suggest that the Solar System may be unusual and that Jupiter-like planets have a frequency <20% around solar-type stars. However, they may be much more common in one of the closest associations in the solar neighbourhood. Young moving stellar groups are the best targets for direct imaging of exoplanets and four massive Jupiter-like planets have been already discovered in the nearby young beta Pic Moving Group (BPMG) via high-contrast imaging, and four others were suggested via high precision astrometry by the European Space Agency's Gaia satellite. Here we analyze 30 stars in BPMG and show that 20 of them might potentially host a Jupiter-like planet as their orbits would be stable. Considering incompleteness in observations, our results suggest that Jupiter-like planets may be more common than previously found. The next Gaia data release will likely confirm our prediction., Comment: 21 pages. Final edited version published on Nature Communications available at URL: https://www.nature.com/articles/s41467-023-41665-0