Individual tracking of museum visitors based on portable radio beacons, an asset for behavioural analyses and comfort/performance improvements, is seeing increasing diffusion. Conceptually, this approach enables room-level localisation based on a network of small antennas (thus, without invasive modification of the existent structures). The antennas measure the intensity (RSSi) of self-advertising signals broadcasted by beacons individually assigned to the visitors. The signal intensity provides a proxy for the distance to the antennas and thus indicative positioning. However, RSSi signals are well-known to be noisy, even in ideal conditions (high antenna density, absence of obstacles, absence of crowd, ...). In this contribution, we present a method to perform accurate RSSi-based visitor tracking when the density of antennas is relatively low, e.g. due to technical constraints imposed by historic buildings. We combine an ensemble of "simple" localisers, trained based on ground-truth, with an encoding of the museum topology in terms of a total-coloured graph. This turns the localisation problem into a cascade process, from large to small scales, in space and in time. Our use case is visitors tracking in Galleria Borghese, Rome (Italy), for which our method manages >96% localisation accuracy, significantly improving on our previous work (J. Comput. Sci. 101357, 2021).

An early research in solid modeling led by Herbert Voelcker at the University of Rochester and later at Cornell suggested that every solid representation scheme corresponds to an algebra, where the elements of the algebra are solid representations constructed and edited using operations in the algebra. For example, every CSG representation describes an element in a finite Boolean algebra of closed regular sets, whereas every boundary representation describes an element of a vector space of 2-chains in an algebraic topological chain complex. In this paper, we elucidate the precise relationships (functors) between all algebras used for CSG and boundary representations of solids. Based on these properties, we show that many solid modeling operations, including boundary evaluation, reduce to straightforward algebraic operations or application of identified functors that are efficiently implemented using point membership tests and sparse matrix operations. To fully exploit the efficacy of the new algebraic approach to solid modeling, all algorithms are fully implemented in Julia, the modern language of choice for numerical and scientific computing.

The development of Boolean algebra based algorithms lied the foundation for a wide variety of cryptanalysis techniques based on the reformulation of a cryptosystem as a polynomial function over F2. Widely used approaches to solve multivariate system of equations include Gröbner bases (see [11]) and linearisation techniques like XL [4] and XSL [5]). Performances of these methodologies were however completely unfeasible for real problems’ size, making it impossible to directly find useful relations between cryptographic schemes’ input and output. At Eurocrypt’09 a new methodology settled in this environment, providing a feasible family of attacks able to retrieve useful in- put/output relations within feasible time: Dinur and Shamir Cube Attack [7]. The attack relied on the new concept of tweakable poly- nomials, polynomials in variables the attacker can set at will during the attack through which a black-box representation of the cipher is analysed. The resonance of this approach was unexpected, making it the forefather of many other approaches ranging from generic finite fields [1, 15] and non-linear [14] approaches to Meet-in-the- Middle [2, 13] and side channels [8] attacks. The idea of tweakable polynomials was also exploited to provide property (cube) testers which generated Conditional [12] and Dynamic [9] cube attacks. All of these approaches come with their own nomenclature, often making it unclear about their real contribute to the state of the art. The aim of this work is to introduce a novel notation to provide a global representation of the cube attacks family.

We describe studies undertaken in support of the Far-infrared Outgoing Radiation Understanding and Monitoring mission, European Space Agency's ninth Earth Explorer, designed to investigate whether airborne observations of far-infrared radiances can provide beneficial information on mid and upper tropospheric water vapor concentrations. Initially we perform a joint temperature and water vapor retrieval and show that the water vapor retrieval exploiting far-infrared measurements from the Tropospheric Airborne Fourier Transform Spectrometer (TAFTS) shows improvement over the a-priori Unified Model global forecast when compared to in situ dropsonde measurements. For this case the improvement is particularly noticeable in the mid-upper troposphere. Equivalent retrievals using mid-infrared radiances measured by the Airborne Research Interferometer Evaluation System (ARIES) show much reduced performance, with the degrees of freedom for signal (DFS), reduced by a factor of almost 2. Further sensitivity studies show that this advantage is decreased, but still present when the spectral resolution of the TAFTS measurements is reduced to match that of ARIES. The beneficial role of the far infrared for this case is further confirmed by performing water vapor only retrievals using ARIES and TAFTS individually, and then in combination. We find that the combined retrieval has a DFS value of 6.7 for water vapor, marginally larger than that obtained for the TAFTS retrieval and almost twice as large as that obtained for ARIES. These results provide observational support of theoretical studies highlighting the potential improvement that far-infrared observations could bring for the retrieval of tropospheric water vapor.

Considering the concept of attainable sets for differential inclusions, we introduce the isochronous manifolds relative to a piecewise smooth dynamical systems in R2 and R3, and study how analytical and topological properties of such manifolds are related to sliding motion and to partially nodal attractivity conditions on the discontinuity manifolds. We also investigate what happens to isochronous manifolds at tangential exit points, where attractivity conditions cease to hold. In particular, we find that isochronous curves in R2, which are closed simple curves under attractivity regime, become open curves at such points.

Introduction. In high-contact sport athletes, repetitive head trauma might be linked to permanent brain damage. In particular, findings in professional American football players indicate that brain injury is often associated with long-term cognitive slowing. In this context, hemp extracts might have beneficial effects. Methods. Forty-two former professional American football players were recruited (age = 49.6 ± 9.8 years). Before or immediately after the oral administration of a THC-free hemp extract, the following measures were acquired: 1) the median theta/beta ratio and posterior peak alpha frequency (PAF) during resting state; 2) P200 and P300b latencies as well as reaction times (RT) during performance of a Go/NoGo task. Results. After treatment, a smaller median theta/beta ratio (p < .01) was detected. An onset latency reduction was also found for the P200 (p < .01) and P300b (p < .05) measures, which was accompanied by smaller RT variances (p < .05). Finally, a positive correlation between RT measures and P300b latencies was found only after treatment. Conclusion. The administration of THC-free hemp extracts in former professional high-impact athletes might have beneficial effects on both cognitive performance and emotion regulation. Also, recent technological advances in EEG detection and analysis could play an important role in the management of patients with sport-related brain injuries.

In this paper, we present TLBfind, a GPU code for simulating the hydrodynamics of droplets along with a dynamic temperature field. TLBfind hinges on a two-dimensional multi-component lattice Boltzmann (LB) model simulating a concentrated emulsion with finite-size droplets evolving in a thermal convective state, just above the transition from conduction to convection. The droplet concentration of the emulsion system is tunable and at the core of the code lies the possibility to measure a large number of physical observables characterising the flow and droplets. Furthermore, TLBfind includes a parallel implementation on GPU of the Delaunay triangulation useful for the detection of droplets' plastic rearrangements, and several types of boundary conditions, supporting simulations of channels with structured rough walls. Program summary: Program Title: TLBfind CPC Library link to program files: https://doi.org/10.17632/hbk45696nf.1 Developer's repository link: https://github.com/FrancescaPelusi/TLBfind Licensing provisions: MIT Programming language: CUDA-C Nature of problem: Hydrodynamics of concentrated emulsions with finite-size droplets in a thermal convective state. Solution method: Single relaxation time Lattice Boltzmann method to solve Navier-Stokes equations for fluids, coupled with the temperature field dynamics. The output describes the dynamics of finite-size droplets of concentrated emulsions in presence of a temperature field. The temperature field obeys the advection-diffusion equation. Additional comments including restrictions and unusual features: Plastic rearrangements of droplets are detected via the parallel implementation of the Delaunay triangulation, and boundary conditions are tunable.

Under the condition of partial surface wettability, thin liquid films can be destabilized by small perturbations and rupture into droplets. As successfully predicted by the thin film equation (TFE), the rupture dynamics are dictated by the liquid-solid interaction. The theory describes the latter using the disjoining pressure or, equivalently, the contact angle. The introduction of a secondary fluid can lead to a richer phenomenology, thanks to the presence of different fluid/surface interaction energies but has so far not been investigated. In this work, we study the rupture of liquid films with different heights immersed in a secondary fluid using a multi-component lattice Boltzmann (LB) approach. We investigate a wide range of surface interaction energies, equilibrium contact angles, and film thicknesses. We found that the rupture time can differ by about one order of magnitude for identical equilibrium contact angles but different surface free energies. Interestingly, the TFE describes the observed breakup dynamics qualitatively well, up to equilibrium contact angles as large as 130°. A small film thickness is a much stricter requirement for the validity of the TFE, and agreement with LB results is found only for ratios ε = h / L of the film height h and lateral system size L, such as ε≲ × 10 - 3.

The problem of choosing appropriate values for missing data is often encountered in the data science. We describe a novel method containing both traditional mathematics and machine learning elements for prediction (imputation) of missing data. This method is based on the notion of distance between shifted linear subspaces representing the existing data and candidate sets. The existing data set is represented by the subspace spanned by its first principal components. Solutions for the case of the Euclidean metric are given.

Let X = {X-1, X-2,..., X-m} be a system of smooth vector fields in R-n satisfying the Hormander's finite rank condition. We prove the following Sobolev inequality with reciprocal weights in Carnot-Caratheodory space G associated to system X(1/integral(BR) K(x) dx integral(BR) vertical bar u vertical bar(t) K (x) dx)(1/t) <= C R (1/integral(BR) 1/K(x) dx integral(BR) vertical bar Xu vertical bar(2)/K(x) dx)(1/2),where Xu denotes the horizontal gradient of u with respect to X. We assume that the weight K belongs to Muckenhoupt's class A(2) and Gehring's class G tau, where tau is a suitable exponent related to the homogeneous dimension.

Recent research shows reductions in the VLF signal noise amplitude that begin before particular earthquakes whose epicentres are more than 100 km away from the signal propagation path. In this paper, we extend this research to studying the noise amplitude during periods of intense seismic activity in a localized area. We analyse variations in the VLF signal noise amplitude over a period of 10 days (25 October-3 November 2016) when 981 earthquakes with the minimum magnitude of 2 occurred in Central Italy. Out of these events, 31 had the magnitude equal or greater than 4, while the strongest one had the magnitude of 6.5. We observe the VLF signal emitted by the ICV transmitter located in Sardinia (Italy) and recorded in Belgrade (Serbia). Bearing in mind that the trajectory of this signal crosses the area in which the observed earthquakes occurred, we extend the existing research to study of variations in the noise amplitude of the signal propagating at short distances from the epicentres of the considered earthquakes. In addition, we analyse the impact of a large number earthquakes on characteristics of the noise amplitude and its reductions before particular events. In order to examine the localization of the recorded changes, we additionally analysed the noise amplitude of two reference signals emitted in Germany and Norway. The obtained results show the existence of the noise amplitude reduction preceding individual strong or relatively strong earthquakes, and earthquakes followed by others that occurred in a shorter time interval. However, the additional noise amplitude reductions are either not pronounced or they do not exist before the considered events in periods of the reduced noise amplitude remain from previous earthquakes. Reductions in noise amplitudes for all observed signals indicate a larger perturbed area through which they spread or its closer location to the receiver. The analysis of daily values of parameters describing the noise amplitude reveals their variations start up to 2 weeks before the seismically active period occurs.

The method of simulated quantiles is extended to a general multivariate framework and to provide sparse estimation of the scaling matrix. The method is based on the minimisation of a distance between appropriate statistics evaluated on the true and synthetic data simulated from the postulated model. Those statistics are functions of the quantiles providing an effective way to deal with distributions that do not admit moments of any order like the α–Stable or the Tukey lambda distribution. The lack of a natural ordering represents the major challenge for the extension of the method to the multivariate framework, which is addressed by considering the notion of projectional quantile. The SCAD 1–penalty is then introduced in order to achieve sparse estimation of the scaling matrix which is mostly responsible for the curse of dimensionality. The asymptotic properties of the proposed estimator have been discussed and the method is illustrated and tested on several synthetic datasets simulated from the Elliptical Stable distribution for which alternative methods are recognised to perform poorly.

How can Science be told in, and with comics, if ever? In recent years, the CNR Edizioni Comics&Science label tried to answer this question with a variety of projects, all spawned by the all-time classic comic book format. Let us recapitulate, with an open eye on future developments.

We consider a variational model analyzed in March and Riey (Inverse Probl Imag 11(6): 997-1025, 2017) for simultaneous video inpainting and motion estimation. The model has applications in the field of recovery of missing data in archive film materials. A gray-value video content is reconstructed in a spatiotemporal region where the video data is lost. A variational method for motion compensated video inpainting is used, which is based on the simultaneous estimation of apparent motion in the video data. Apparent motion is mathematically described by a vector field of velocity, denoted optical flow, which is estimated through gray-value variations of the video data. The functional to be minimized is defined on a space of vector valued functions of bounded variation and the relaxation method of the Calculus of Variations is used. We introduce in the functional analyzed in March and Riey(Inverse Probl Imag 11(6): 997-1025, 2017) a suitable positive weight, and we show that diagonal minimizing sequences of the functional converge, up to subsequences as the weight tends to infinity, to minimizers of an appropriate limit functional. Such a limit functional is the relaxed version of a functional, modified with suitable improvements, proposed by Lauze and Nielsen (2004) and which permits an accurate joint reconstruction both of the optical flow and of the video content.

In this paper, we discuss the convergence of an Algebraic MultiGrid (AMG) method for general symmetric positive-definite matrices. The method relies on an aggregation algorithm, named coarsening based on compatible weighted matching, which exploits the interplay between the principle of compatible relaxation and the maximum product matching in undirected weighted graphs. The results are based on a general convergence analysis theory applied to the class of AMG methods employing unsmoothed aggregation and identifying a quality measure for the coarsening; similar quality measures were originally introduced and applied to other methods as tools to obtain good quality aggregates leading to optimal convergence for M-matrices. The analysis, as well as the coarsening procedure, is purely algebraic and, in our case, allows an a posteriori evaluation of the quality of the aggregation procedure which we apply to analyze the impact of approximate algorithms for matching computation and the definition of graph edge weights. We also explore the connection between the choice of the aggregates and the compatible relaxation convergence, confirming the consistency between theories for designing coarsening procedures in purely algebraic multigrid methods and the effectiveness of the coarsening based on compatible weighted matching. We discuss various completely automatic algorithmic approaches to obtain aggregates for which good convergence properties are achieved on various test cases.

A reaction-diffusion system governing the prey-predator interaction with Allee effect on the predators, already introduced by the authors in a previous work is reconsidered with the aim of showing destabilization mechanisms of the biologically meaning equilibrium and detecting some aspects for the eventual oscillatory pattern formation. Extensive numerical simulations, depicting such complex dynamics, are shown. In order to complete the stability analysis of the coexistence equilibrium, a nonlinear stability result is shown.

In this study, we computationally corroborate the flow of rock glaciers against borehole measurements, within the context of a model previously developed (2020). The model is, here, tested against the simulation of the sliding motion of the Murtel-Corvatsch alpine glacier, which is characterized in detail in the literature with internal structure description and borehole deformations measurement. The capability of the model to take into account the composition of the rock glacier, as a mixture of ice and rock and sand grains with the local impact of pressure and heat transfer, results in the accurate detection of the internal sliding. With careful calibration of the model parameters, the computed numerical solution of the model reports a relative error of 1.8% and of 0.3% in the reproduction of the measured shear zone velocity and of the ratio of measured shear zone deformation over top surface deformation, respectively. Furthermore a deeper understanding of the role of the model parameters involved in the simulation of such a process is also gained and we discuss the same in detail.

The Fokker--Planck approximation for an elementary linear, two-dimensional kinetic model endowed with a mass-preserving integral collision process is numerically studied, along with its diffusive limit. In order to set up a well-balanced discretization relying on an $S$-matrix, exact steady states of the continuous equation are derived. The ability of the scheme to keep these stationary solutions invariant produces the discretization of the local differential operator which mimics the collision process. The aforementioned scheme can be reformulated as an implicit-explicit one, which is proved to be both well-balanced and asymptotic-preserving in the diffusion limit. Several numerical benchmarks, computed on coarse grids, are displayed so as to illustrate the results.

First-degree relatives (FDRs) of type 2 diabetics (T2D) feature dysfunction of subcutaneous adipose tissue (SAT) long before T2D onset. miRNAs have a role in adipocyte precursor cells (APC) differentiation and in adipocyte identity. Thus, impaired miRNA expression may contribute to SAT dysfunction in FDRs. In the present work, we have explored changes in miRNA expression associated with T2D family history which may affect gene expression in SAT APCs from FDRs. Small RNA-seq was performed in APCs from healthy FDRs and matched controls and omics data were validated by qPCR. Integrative analyses of APC miRNome and transcriptome from FDRs revealed down-regulated hsa-miR-23a-5p, -193a-5p and -193b-5p accompanied by up-regulated Insulin-like Growth Factor 2 (IGF2) gene which proved to be their direct target. The expression changes in these marks were associated with SAT adipocyte hypertrophy in FDRs. APCs from FDRs further demonstrated reduced capability to differentiate into adipocytes. Treatment with IGF2 protein decreased APC adipogenesis, while over-expression of hsa-miR-23a-5p, -193a-5p and -193b-5p enhanced adipogenesis by IGF2 targeting. Indeed, IGF2 increased the Wnt Family Member 10B gene expression in APCs. Down-regulation of the three miRNAs and IGF2 up-regulation was also observed in Peripheral Blood Leukocytes (PBLs) from FDRs. In conclusion, APCs from FDRs feature a specific miRNA/gene profile, which associates with SAT adipocyte hypertrophy and appears to contribute to impaired adipogenesis. PBL detection of this profile may help in identifying adipocyte hypertrophy in individuals at high risk of T2D.

Mass spectrometry is a widely applied technology with a strong impact in the proteomics field. MALDI-TOF is a combined technology in mass spectrometry with many applications in characterizing biological samples from different sources, such as the identification of cancer biomarkers, the detection of food frauds, the identification of doping substances in athletes' fluids, and so on. The massive quantity of data, in the form of mass spectra, are often biased and altered by different sources of noise. Therefore, extracting the most relevant features that characterize the samples is often challenging and requires combining several computational methods. Here, we present GeenaR, a novel web tool that provides a complete workflow for pre-processing, analyzing, visualizing, and comparing MALDI-TOF mass spectra. GeenaR is user-friendly, provides many different functionalities for the analysis of the mass spectra, and supports reproducible research since it produces a human-readable report that contains function parameters, results, and the code used for processing the mass spectra. First, we illustrate the features available in GeenaR. Then, we describe its internal structure. Finally, we prove its capabilities in analyzing oncological datasets by presenting two case studies related to ovarian cancer and colorectal cancer. GeenaR is available at http://proteomics.hsanmartino.it/geenar/.