Tracking droplets in microfluidics is a challenging task. The difficulty arises in choosing a tool to analyze general microfluidic videos to infer physical quantities. The state-of-the-art object detector algorithm You Only Look Once (YOLO) and the object tracking algorithm Simple Online and Realtime Tracking with a Deep Association Metric (DeepSORT) are customizable for droplet identification and tracking. The customization includes training YOLO and DeepSORT networks to identify and track the objects of interest. We trained several YOLOv5 and YOLOv7 models and the DeepSORT network for droplet identification and tracking from microfluidic experimental videos. We compare the performance of the droplet tracking applications with YOLOv5 and YOLOv7 in terms of training time and time to analyze a given video across various hardware configurations. Despite the latest YOLOv7 being 10% faster, the real-time tracking is only achieved by lighter YOLO models on RTX 3070 Ti GPU machine due to additional significant droplet tracking costs arising from the DeepSORT algorithm. This work is a benchmark study for the YOLOv5 and YOLOv7 networks with DeepSORT in terms of the training time and inference time for a custom dataset of microfluidic droplets.

Mathematical models based on non-linear integral and integro-differential equations are gaining increasing attention in mathematical epidemiology due to their ability to incorporate the past infection dynamic into its current development. This property is particularly suitable to represent the evolution of diseases where the dependence of infectivity on the time since becoming infected plays a crucial role. These renewal equation models contain an integral term describing the contribution of the force of infection to the total infectivity and need, in general, numerical simulations for a complete understanding and quantitative description. For a general model which includes demographic effects [1, 2], we propose a non-standard approach [3] based on a non local discretization of the integral term characterizing the mathematical equations. We discuss classical problems related to the behaviour of this scheme and we prove the positivity invariance and the unconditional preservation of the stability nature of equilibria, with respect to the discretization parameter. These properties, together with the fact that the method can be put into an explicit form, actually make it a computationally attractive tool and, at the same time, a stand-alone discrete model describing the evolution of an epidemic. This is a joint work with Bruno Buonomo and Claudia Panico from University of Naples Federico II, and Antonia Vecchio from IAC-CNR, Naples.

We consider a discrete model of planar elasticity where the particles, in the reference configuration, sit on a regular triangular lattice and interact through nearest-neighbor pairwise potentials, with bonds modeled as linearized elastic springs. Within this framework, we introduce plastic slip fields, whose discrete circulation around each tri-angle detects the possible presence of an edge dislocation. We provide a gamma-convergence analysis, as the lattice spacing tends to zero, of the elastic energy induced by edge dislocations in the energy regime corresponding to a finite number of geometrically necessary dislocations.

This paper considers a Multiple Objective variant of the Critical Disruption Path problem to extend itssuitability in a range of security operations relying on path-based network interdiction, including flight patternoptimisation for surveillance. Given a pair of nodes s and t from the network to be monitored, the problemseeks for loopless s - t paths such that, within the induced subgraph obtained via deletion of the path, thesize of the largest connected component is minimised, the number of connected components is maximised,while concurrently reducing as much as possible the cost of such disruption path. These three objectives arepossibly in conflict with each other, and the scope of this work is to allow for an efficient and insightfulapproximation of the Pareto front, looking for a trade-off between costs and effectiveness to secure the mostconvenient paths for security and surveillance operations. We first introduce and formulate the Multi-ObjectiveCritical Disruption Path Problem (Multi-Objs-CDP) as a mixed integer programming formulation (MO-CDP),then we propose an original evolutionary metaheuristic algorithm hybridising modified-NSGA-II and VNS forfinding an approximation of the Pareto front, as well as a procedure securing the efficient generation of a highquality pool of initial solutions. The experimental performance of the proposed algorithm, as compared witha variety of competing approaches, proves to be fully satisfactory in terms of time efficiency and quality ofthe solutions obtained on a set of medium to large benchmark instances.

In this work we have studied in situ the formation and growth of calcium phosphate (CaP) nanoparticles (NPs) in the presence of three calcium-binding carboxylate molecules having different affinities for Ca2+ ions: citrate (Cit), hydroxycitrate (CitOH), and glutarate (Glr). The formation of CaP NPs at several reaction temperatures ranging from 25 °C to 80 °C was monitored in situ through simultaneous Small and Wide X-ray Scattering (SAXS/WAXS) using synchrotron light. SAXS was used to investigate the first stages of NP formation where a crystalline order is not yet formed. In this regard we have developed a new bivariate mesh data analysis method for identifying the SAXS curves associated with the most relevant timeframes for performing curve modeling. WAXS was used to study the formation of crystalline phases and their evolution over time. The combined SAXS/WAXS data allowed us to track NP nucleation, their size and morphology, and their evolution up to mature hydroxyapatite (HA) nanocrystals. We have assessed that in the first stages of reaction (80 seconds) amorphous, elongated primary NPs nucleate whose size and morphology depend on the temperature and type of carboxylate molecule. The temperature controls the release of Ca2+ ions from carboxylate molecules, and thus induces the formation of a higher amount of amorphous particles and increases their size and aspect ratio. As the reaction time progresses, amorphous particles evolve into crystalline ones, whose kinetics of crystal growth are controlled by temperature and carboxylate ions. Stronger Ca-binding carboxylates (CitOH > Cit > Glr) have a more pronounced inhibiting effect on HA crystallization, retarding the formation and growth of crystalline domains, while a rise of temperature promotes crystallization. This work allowed us to shed more light on the formation of HA in the presence of growth-controlling molecules, as well as present the potential of combined SAXS/WAXS for studying the formation of highly relevant NPs for different applications.

The appearance of AC72 foiling catamarans in the scenario of sailing yacht competitions in 2013 raised attention to this ship design concept, although not brand new in the yacht design history. The drastic drag reduction connected with the elevation of the ship hull outside the water is obtained by the use of a foil, or a system of foils, acting as the wings of a plane, providing a lift force balancing the weight of the ship. Since this lift is proportional (non-linearly) to the ship hull speed, the take-off speed of the hull cannot be low. As a result, since we are travelling in water at high speeds, the occurrence of the phenomenon of cavitation cannot be completely avoided, and the performance of the ship undergoes deterioration. Shaping of the foil profile must consider this peculiar situation, so the design tools commonly adopted for the aero-hydrodynamic hull design optimization are no longer adequate. In this paper, we are considering the optimization of the 2D profile of a foil in three different physical conditions: single fluid, two fluids and two fluids with cavitation. The first is typical of aeronautic wing design, the second of the appendages of a displacement ship, and the third of a foiling ship. Results give evidence of the different requirements for the three different conditions.

The importance of the immune system (IS) in tuberculosis (TB) drug development is often underestimated because of the intricate nature of experiments and the specialized knowledge needed. In vitro and animal studies fall short in replicating the intricate reactions of the human IS to drugs and infections. In this study, we present our initial efforts in employing an in silico approach to comprehend how an individual’s IS impacts the efficacy of therapy, particularly in managing mycobacterium tuberculosis (Mtb) infection and minimizing the risk of relapse. We employed a well-established agent-based IS simulator called C-IMMSIM. We conducted simulations to investigate the long-term outcomes of TB disease in a virtual cohort infected with Mtb over a 50-year period. Our simulations revealed that individuals with competent IS showed a high success rate in containing Mtb infection. Furthermore, to better understand the dynamic interactions between Mtb and the IS, we deliberately introduced specific IS deficiencies, thus successfully inducing short-term relapses and mortality. These results confirm the model’s ability to elucidate the mechanisms underlying the interactions between Mtb and the IS.

Algebraic Cryptanalysis is a widely used technique that tackles the problem of breaking ciphers mainly relying on the ability to express a cryptosystem as a solvable polynomial system. Each output bit/word can be expressed as a polynomial equation in the cipher’s inputs—namely the key and the plaintext or the initialisation vector bits/words. A part of research in this area consists in finding suitable algebraic structures where polynomial systems can be effectively solved, e.g., by computing Gröbner bases. In 2009, Dinur and Shamir proposed the cube attack, a chosen plaintext algebraic cryptanalysis technique for the offline acquisition of an equivalent system by means of monomial reduction; interpolation on cubes in the space of variables enables retrieving a linear polynomial system, hence making it exploitable in the online phase to recover the secret key. Since its introduction, this attack has received both many criticisms and endorsements from the crypto community; this work aims at providing, under a unified notation, a complete state-of-the-art review of recent developments by categorising contributions in five classes. We conclude the work with an in-depth description of the kite attack framework, a cipher-independent tool that implements cube attacks on GPUs. Mickey2.0 is adopted as a showcase.

We present a standalone Matlab software platform complete with visualization for the reconstruction of the neural activity in the brain from MEG or EEG data. The underlying inversion combines hierarchical Bayesian models and Krylov subspace iterative least squares solvers. The Bayesian framework of the underlying inversion algorithm allows to account for anatomical information and possible a priori belief about the focality of the reconstruction. The computational efficiency makes the software suitable for the reconstruction of lengthy time series on standard computing equipment. The algorithm requires minimal user provided input parameters, although the user can express the desired focality and accuracy of the solution. The code has been designed so as to favor the parallelization performed automatically by Matlab, according to the resources of the host computer. We demonstrate the flexibility of the platform by reconstructing activity patterns with supports of different sizes from MEG and EEG data. Moreover, we show that the software reconstructs well activity patches located either in the subcortical brain structures or on the cortex. The inverse solver and visualization modules can be used either individually or in combination. We also provide a version of the inverse solver that can be used within Brainstorm toolbox. All the software is available online by Github, including the Brainstorm plugin, with accompanying documentation and test data.

An experimental setup operating in transmission mode in the frequency range between 18 and 40 GHz is described. This study shows how the system is able to distinguish healthy and rotten hazelnuts. In addition, a Self-Organizing Map (SOM) trained with the Kohonen algorithm was used to classify the hazelnuts according to their quality.

Employing numerical simulations, we provide an accurate insight into the heat transfer mechanism in the Rayleigh-Bénard convection of concentrated emulsions with finite-size droplets. We focus on the unsteady dynamics characterizing the thermal convection of these complex fluids close to the transition from conductive to convective states, where the heat transfer phenomenon, expressed in terms of the Nusselt number Nu, is characterized by pronounced fluctuations triggered by collective droplet motion [F. Pelusi et al., Soft Matter, 2021, 17(13), 3709-3721]. By systematically increasing the droplet concentration, we show how these fluctuations emerge along with the segregation of “extreme events” in the boundary layers, causing intermittent bursts in the heat flux fluctuations. Furthermore, we quantify the extension S and the duration of the coherent droplet motion accompanying these extreme events via a suitable statistical analysis involving the droplet displacements. We show how the increase in droplet concentration results in a power-law behaviour of the probability distribution function of S and and how this outcome is robust at changing the analysis protocol. Our work offers a comprehensive picture, linking macroscopic heat transfer fluctuations with the statistics of droplets at the mesoscale.

Since long time THz-TDS techniques have been seen as a good option for the measurements of plasma parameters [1]. This becomes a particularly interesting option for nuclear fusion experiments where Far Infrared and microwave diagnostics, in the frequency range 0.1-4000 THz, are one of the most important measurement tool [2] [3]. The application of THz-TDS techniques can potentially provide important plasma parameters, such as density, temperature and fluctuations, by using a multi-functional device with relatively small access requirements [4].

Wood is a hygroscopic material that is subject to phenomena of water exchange with the external environment. These exchanges can cause dimensional variations and cracks to appear on a macroscopic level. In recent years, the use of terahertz technologies in the field of diagnostics applied to cultural heritage has increased considerably. One of the most important characteristics of terahertz radiation is its sensitivity to water content; this polar liquid strongly absorbs and reflects this radiation. The subject of this study will be the detection of moisture in pine wood samples using a 97 GHz terahertz imaging system.

In Deuterium Plasmas differences were detected in JET between electron temperature measurements (Te) made by Electron Cyclotron Emission - Te_ECE - and Thomson Scattering diagnostics systems (Te_TS) [1]. Similar behaviour was found in TFTR [2]. Plasmas heated by ECRH (Electron Cyclotron Heating) in Deuterium on FTU showed T_ECE < T_TS for 8 KeV ≤ Te ≤ 14 keV [3]. These differences can be due to the non-Maxwellian nature of the Electron velocity Distribution Function (EDF) [5,6]. The radiation temperature (Trad) measured by ECE is equal to the Te only for a Maxwellian plasma: being Trad dependent on the derivative of the EDF with respect to perpendicular velocity [5]. This paper describes differences of Te measured by ECE (ECE_MP, Martin-Puplett interferometer) and High-Resolution Thomson Scattering (HRTS) diagnostic. HRTS gives independent information on these differences, having shorter space resolution (2 cm), and faster repetition rate (20 Hz) on a different line of sight (16 cm from the magnetic centre): HRTS measurements confirm the trends observed using LIDAR TS [4,5]. Comparison between HRTS and ECE radiometer measurements is also reported (see sec.3).

In this paper, we introduce peridynamic theory and its application to Richards’ equation with a piecewise smooth initial condition. Peridynamic theory is a non-local continuum theory that models the deformation and failure of materials. Richards’ equation describes the unsaturated flow of water through porous media, and it plays an essential role in many applications, such as groundwater management, soil science, and environmental engineering. We develop a peridynamic formulation of Richards’ equation that includes the effect of peridynamic forces and a piecewise smooth initial condition, further introducing a non-standard symmetric influence function to describe such peridynamic interactions, which turns out to provide beneficial effects from a numerical point of view. Moreover, we implement a numerical scheme based on Chebyshev polynomials and symmetric Gauss–Lobatto nodes, providing a powerful spectral method able to capture singularities and critical issues of Richards’ equation with piecewise smooth initial conditions. We also present numerical simulations that illustrate the performance of the proposed approach. In particular, we perform a computational investigation into the spatial order of convergence, showing that, despite the discontinuity in the initial condition, the order of convergence is retained.

The aim of this chapter is to device a computationally effective procedure for numerically solving fractional-time-space differential equations with the spectral fractional Laplacian. A truncated spectral representation of the solution in terms of the eigenfunctions of the usual integer-order Laplacian is considered. Time-dependent coefficients in this representation, which are solutions to some linear fractional differential equations, are evaluated by means of a generalized exponential time-differencing method, with some advantages in terms of accuracy and computational effectiveness. Rigorous a priori error estimates are derived, and they are verified by means of some numerical experiments.

Membrane viscosity is known to play a central role in the transient dynamics of isolated viscoelastic capsules by decreasing their deformation, inducing shape oscillations and reducing the loading time, that is, the time required to reach the steady-state deformation. However, for dense suspensions of capsules, our understanding of the influence of the membrane viscosity is minimal. In this work, we perform a systematic numerical investigation based on coupled immersed boundary-lattice Boltzmann (IB-LB) simulations of viscoelastic spherical capsule suspensions in the non-inertial regime. We show the effect of the membrane viscosity on the transient dynamics as a function of volume fraction and capillary number. Our results indicate that the influence of membrane viscosity on both deformation and loading time strongly depends on the volume fraction in a non-trivial manner: dense suspensions with large surface viscosity are more resistant to deformation but attain loading times that are characteristic of capsules with no surface viscosity, thus opening the possibility to obtain richer combinations of mechanical features.

Let 1 < p < ∞, ε0 ∈]0, p − 1], Ω ⊂ Rn be a Lebesgue measurable set of positive, finite measure, and let δ : (0, p − 1] → (0, ∞) be such that δb(·):= δ(·) p−·1 is nondecreasing and bounded. We show that the linear set of functions 5 f Lebesgue measurable on Ω: 0<ε sup ≤ε0(δ(ε) k − |f(x)|p−εdx ) p−1 ε < ∞ 5 Ω does not depend on small values of ε0 if and only if δb ∈ ∆2(0+) (i.e., δb(2ε) ≤ cδb(ε) for ε small, for some c > 1), which is equivalent to say that δ ∈ ∆2(0+). This means that in the case δb ∈/ ∆2(0+), the parameter ε0 plays a crucial role in the definition of a generalized grand Lebesgue space, namely, different values of ε0 define different Banach function spaces.

Some recent results on the theory of fractional Orlicz–Sobolev spaces are surveyed. They concern Sobolev type embeddings for these spaces with an optimal Orlicz target, related Hardy type inequalities, and criteria for compact embeddings. The limits of these spaces when the smoothness parameter s ∈ (0, 1) tends to either of the endpoints of its range are also discussed. This note is based on recent papers of ours, where additional material and proofs can be found.