The PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral satellite, launched by the Italian Space Agency (ASI) is presently operational on a global scale. The mission includes the hyperspectral imager PRISMA working in the 400-2500 nm spectral range with 234 bands and a panchromatic (PAN) camera (400-750 nm). In the context of this work, we intend to determine the two noise components (photon and thermal noise) and assess SNR with an image based approach. Results show that the SNR evaluation assessed through the collected images is coherent with the mission requirements and that the PRISMA noise components, derived on the fragmented Pignola test site, in Southern Italy, are comparable to the ones derived on the Rail Road Valley calibration site.

MIPAS is a Fourier Transform spectrometer that measured the atmospheric limb emission spectra in the middle infrared on board the ENVISAT satellite. These measurements allowed the global monitoring of the three-dimensional (latitude, longitude and altitude) distribution of temperature and of the concentrations of many species, during both day and night, for 10 years, from July 2002 to April 2012. MIPAS measurements allowed to study the atmosphere from the upper troposphere to the stratosphere and above, up to the thermosphere. The interest in these measurements goes beyond the end of the mission, as they can be used in long time series of data to determine changes in atmospheric composition and in our planet's climate. Furthermore, if the Changing-Atmosphere Infra-Red Tomography Explorer (CAIRT) mission, one of four candidates for Earth Explorer 11, will be selected, MIPAS data will constitute a benchmark for these measurements. CAIRT exploits indeed the heritage of MIPAS on ENVISAT, but allows to measure the composition of the atmosphere with unprecedented three-dimensional resolution being the first imaging Fourier Transform spectrometer sounding the limb of the atmosphere from space. For the last reanalysis of the whole MIPAS mission, a significant effort was made by the MIPAS Quality Working Group, supported by ESA, to improve both L1 [1] and L2 processors, as well as spectroscopy and Level 2 Initial Guess profiles [2], with the objectives of obtaining L2 products with increased accuracy, better temporal stability, and a larger number of retrieved species. The main improvements of L1 processor were related to the radiometric calibration and pointing. With these new processors a MIPAS full mission reprocessing has been recently performed ([1] and [3]). The quality of this final operational data set has been assessed with comprehensive validation studies including comparisons to ground-based in-situ and balloon-borne measurements. The dataset containing the new version 8 of both L1 and L2 products and covering the entire MIPAS operational lifetime period (2002-2012) is available at ESA Earth Online web site.This paper will focus on the lessons learnt, on the quality of the reprocessed data, on the remaining problems, and on further improvements that could improve the quality of both MIPAS L1 and L2 datasets.[1] Kleinert et al. Kleinert, A., Birk, M., Perron, G., and Wagner, G.: Level 1b error budget for MIPAS on ENVISAT, Atmos. Meas. Tech., 11, 5657-5672,https://doi.org/10.5194/amt-11-5657-2018, 2018 [2] Raspollini, P., Arnone, E., Barbara, F., Bianchini, M., Carli, B., Ceccherini, S., Chipperfield, M. P., Dehn, A., Della Fera, S., Dinelli, B. M., Dudhia, A., Flaud, J.-M., Gai, M., Kiefer, M., López-Puertas, M., Moore, D. P., Piro, A., Remedios, J. J., Ridolfi, M., Sembhi, H., Sgheri, L., and Zoppetti, N.: Level 2 processor and auxiliary data for ESA Version 8 final full mission analysis of MIPAS measurements on ENVISAT, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2021-235, in review, 2021. [3] Dinelli, B. M., Raspollini, P., Gai, M., Sgheri, L., Ridolfi, M., Ceccherini, S., Barbara, F., Zoppetti, N., Castelli, E., Papandrea, E., Pettinari, P., Dehn, A., Dudhia, A., Kiefer, M., Piro, A., Flaud, J.-M., Lopez-Puertas, M., Moore, D., Remedios, J., and Bianchini, M.: The ESA MIPAS/ENVISAT Level2-v8 dataset: 10 years of measurements retrieved with ORM v8.22, Atmos. Meas. Tech. Discuss. [preprint], https://doi.org/10.5194/amt-2021-215, accepted, 2021.

The capability to simulate a two-way coupled interaction between a rarefied gas and an arbitrary-shaped colloidal particle is important for many practical applications, such as aerospace engineering, lung drug delivery, and semiconductor manufacturing. By means of numerical simulations based on the direct-simulation Monte Carlo (DSMC) method, we investigate the influence of the orientation of the particle and rarefaction on the drag and lift coefficients, in the case of prolate and oblate ellipsoidal particles immersed in a uniform ambient flow. This is done by modeling the solid particles using a cut-cell algorithm embedded within our DSMC solver. In this approach, the surface of the particle is described by its analytical expression and the microscopic gas-solid interactions are computed exactly using a ray-tracing technique. The measured drag and lift coefficients are used to extend the correlations, based on the sine-squared drag law, available in the continuum regime to the rarefied regime, focusing on the transitional and free-molecular regimes. The functional forms of the correlations for the ellipsoidal particles are chosen as a generalization from the spherical case. We show that the fits over the data from numerical simulations can be extended to regimes outside the simulated range of Kn. Our approach allows to achieve a higher precision when compared with existing predictive models from the literature. Finally, we underline the importance of this work in providing correlations for nonspherical particles that can be used for point-particle Euler-Lagrangian simulations to address the problem of contamination from finite-size particles in high-tech mechanical systems.

Stabilised dense emulsions display a rich phenomenology connecting microstructure and rheology. In this work, we study how an emulsion with a finite yield stress can be built via large-scale stirring. By gradually increasing the volume fraction of the dispersed minority phase, under the constant action of a stirring force, we are able to achieve a volume fraction close to 80%. Despite the fact that our system is highly concentrated and not yet turbulent we observe a droplet size distribution consistent with the -10/3 scaling, often associated with inertial range droplets breakup. We report that the polydispersity of droplet sizes correlates with the dynamics of the emulsion formation process. Additionally, we quantify the visco-elastic properties of the dense emulsion finally obtained and we demonstrate the presence of a finite yield stress. The approach reported can pave the way to a quantitative understanding of the complex interplay between the dynamics of mesoscale constituents and the large-scale flow properties of yield stress fluids.

The growth and evolution of microbial populations is often subjected to advection by fluid flows in spatially extended environments, with immediate consequences for questions of spatial population genetics in marine ecology, planktonic diversity and origin of life scenarios. Here, we review recent progress made in understanding this rich problem in the simplified setting of two competing genetic microbial strains subjected to fluid flows. As a pedagogical example we focus on antagonsim, i.e., two killer microorganism strains, each secreting toxins that impede the growth of their competitors (competitive exclusion), in the presence of stationary fluid flows. By solving two coupled reaction-diffusion equations that include advection by simple steady cellular flows composed of characteristic flow motifs in two dimensions (2D), we show how local flow shear and compressibility effects can interact with selective advantage to have a dramatic influence on genetic competition and fixation in spatially distributed populations. We analyze several 1D and 2D flow geometries including sources, sinks, vortices and saddles, and show how simple analytical models of the dynamics of the genetic interface can be used to shed light on the nucleation, coexistence and flow-driven instabilities of genetic drops. By exploiting an analogy with phase separation with nonconserved order parameters, we uncover how these genetic drops harness fluid flows for novel evolutionary strategies, even in the presence of number fluctuations, as confirmed by agent-based simulations as well.

The development of turbulence closure models, parametrizing the influence of small nonresolved scales on the dynamics of large resolved ones, is an outstanding theoretical challenge with vast applicative relevance. We present a closure, based on deep recur- rent neural networks, that quantitatively reproduces, within statistical errors, Eulerian and Lagrangian structure functions and the intermittent statistics of the energy cascade, including those of subgrid fluxes. To achieve high-order statistical accuracy, and thus a stringent statistical test, we employ shell models of turbulence. Our results encourage the development of similar approaches for three-dimensional Navier-Stokes turbulence.

By varying the oil volume fraction, the microscopic droplet size and the macroscopic rheology of emulsions are investigated in a Taylor-Couette turbulent shear flow. Although here oil and water in the emulsions have almost the same physical properties (density and viscosity), unexpectedly, we find that oil-in-water (O/W) and water-in-oil (W/O) emulsions have very distinct hydrodynamic behaviours, i.e. the system is clearly asymmetric. By looking at the micro-scales, the average droplet diameter hardly changes with the oil volume fraction for O/W or for W/O. However, for W/O it is about 50% larger than that of O/W. At the macro-scales, the effective viscosity of O/W is higher when compared to that of W/O. These asymmetric behaviours are expected to be caused by the presence of surface-active contaminants from the walls of the system. By introducing an oil-soluble surfactant at high concentration, remarkably, we recover the symmetry (droplet size and effective viscosity) between O/W and W/O emulsions. Based on this, we suggest a possible mechanism responsible for the initial asymmetry and reach conclusions on emulsions where interfaces are fully covered by the surfactant. Next, we discuss what sets the droplet size in turbulent emulsions. We uncover a -6/5 scaling dependence of the droplet size on the Reynolds number of the flow. Combining the scaling dependence and the droplet Weber number, we conclude that the droplet fragmentation, which determines the droplet size, occurs within the boundary layer and is controlled by the dynamic pressure caused by the gradient of the mean flow, as proposed by Levich (Physicochemical Hydrodynamics, Prentice-Hall, 1962), instead of the dynamic pressure due to turbulent fluctuations, as proposed by Kolmogorov (Dokl. Akad. Nauk. SSSR, vol. 66, 1949, pp. 825-828). The present findings provide an understanding of both the microscopic droplet formation and the macroscopic rheological behaviours in dynamic emulsification, and connects them.

We introduce a novel mesoscopic computational model based on a multiphase-multicomponent lattice Boltzmann method for the simulation of self-phoretic particles in the presence of liquid-liquid interfaces. Our model features fully resolved solvent hydrodynamics, and, thanks to its versatility, it can handle important aspects of the multiphysics of the problem, including particle wettability and differential solubility of the product in the two liquid phases. The method is extensively validated in simple numerical experiments, whose outcome is theoretically predictable, and then applied to the study of the behavior of active particles next to and trapped at interfaces. We show that their motion can be variously steered by tuning relevant control parameters, such as the phoretic mobilities, the contact angle, and the product solubility.

Electrostimulation is the object of the study of a variety of clinical approaches, ranging from bioelectronic medicine where the aim is to elicit the activity of the autonomic nervous system (ANS), to electroacupuncture with the general objective to restore homeostasis, to transcutaneous electrical nerve stimulation (TENS) to control pain and degeneration, to name a few. Among the numerous obstacles preventing from a clear adoption or rejection of these approaches in mainstream clinical practice, is the difficulty in standardizing experimental systems for testing and validation. Consequently, indications on the appropriate magnitude of an effective stimulus (duration, frequency, intensity) remain unclear. To approach this issue we present preliminary results on the differential molecular activity elicited in a 3D bioprinted construct containing fibroblasts and keratinocytes in a collagen matrix, by two diverse types of electrical stimulation (direct and alternate current). Two conditions, physiology and inflammation induced by TNF? perfusion were tested with anelectrobiomedical device. The system mimics a simplified model of skin, the largest and most accessible of our organs, in inflamed or physiological states, treated by electrostimulation. The bioprinted sample is constructed to yield an appropriate number of cell enabling high-throughput screens. We report here our preliminary results on RNA-seq differential expression comparing direct and alternate current stimuli, with a focus on wound healing and inflammation as part of the greater inflammatory pathway. Our construct offer reproducibility of the experience, and direct comparison among potentially numerous conditions and types of stimulation. Our preliminary results shows that electrostimulation offers differential elicitation of biological functions. In particular, direct and alternate current provoke differential activation of proliferation and development associated functions.

In this note, we consider generalizations of the Cucker-Smale dynamical system and we derive rigorously in Wasserstein's type topologies the mean-field limit (and propagation of chaos) to the Vlasov-type equation introduced in [13]. Unlike previous results on the Cucker-Smale model, our approach is not based on the empirical measures, but, using an Eulerian point of view introduced in [9] in the Hamiltonian setting, we show the limit providing explicit constants. Moreover, for non strictly Cucker-Smale particles dynamics, we also give an insight on what induces a flocking behavior of the solution to the Vlasov equation to the - unknown a priori - flocking properties of the original particle system.

Mass currents in astrophysics generate gravitomagnetic fields of enormous complexity. Gravitomagnetichelicity, in direct analogy with magnetic helicity, is a measure of entwining of the gravitomagnetic fieldlines. We discuss gravitomagnetic helicity within the gravitoelectromagnetic (GEM) framework oflinearized general relativity. Furthermore, we employ the spacetime curvature approach to GEM in orderto determine the gravitomagnetic helicity for static observers in Kerr spacetime.

In the description of the relativistic two-body interaction, together with the effects of energy andangular momentum losses due to the emission of gravitational radiation, one has to take into account alsothe loss of linear momentum, which is responsible for the recoil of the center-of-mass of the system. Wecompute higher-order tail (i.e., tail-of-tail and tail-squared) contributions to the linear momentum fluxfor a nonspinning binary system either along hyperboliclike or ellipticlike orbits. The correspondingorbital averages are evaluated at their leading post-Newtonian approximation, using harmoniccoordinates and working in the Fourier domain. The final expressions are given in a large-eccentricity(or large-angular momentum) expansion along hyperboliclike orbits and in a small-eccentricityexpansion along ellipticlike orbits. We thus complete a previous analysis focusing on both energyand angular momentum losses [Phys. Rev. D 104, 104020 (2021)], providing brick-type results whichwill be useful, e.g., in the high-accurate determination of the radiated impulses of the two bodiesundergoing a scattering process.

Gravitational radiation can be decomposed as an infinite sum of radiative multipole moments, which parametrize the waveform at infinity. The multipolar-post-Minkowskian formalism provides a connection between these multipoles and the source multipole moments, known as explicit integrals over the matter source. The gravitational wave energy, angular momentum, and linear momentum fluxes are then expressed as multipolar expansions containing certain combinations of the source moments. We compute several gauge-invariant quantities as "building blocks"entering the multipolar expansion of both radiated energy and angular momentum at the 2.5 post-Newtonian (PN) level of accuracy in the case of hyperboliclike motion, by completing previous studies through the calculation of tail effects up to the fractional 1PN order. We express such multipolar invariants in terms of certain eccentricity enhancement factor functions, which are the counterpart of the well-known enhancement functions already introduced in the literature for ellipticlike motion. Finally, we use the complete 2.5PN-accurate averaged energy and angular momentum fluxes to study the associated adiabatic evolution of orbital elements under gravitational radiation reaction.

We briefly review the known properties of Melvin's magnetic universe and study the propagation of test charged matter waves in this static spacetime. Moreover, the possible correspondence between the wave perturbations on the background Melvin universe and the motion of charged test particles is discussed. Next, we explore a simple scenario for turning Melvin's static universe into one that undergoes gravitational collapse. In the resulting dynamic gravitational field, the formation of cosmic double-jet configurations is emphasized.

We compute the metric fluctuations induced by a turbulent energy-matter tensor within the first orderpost-Minkowskian approximation. It is found that the turbulent energy cascade can in principle interferewith the process of black hole formation, leading to a potentially strong coupling between these two highlynonlinear phenomena. It is further found that a power-law turbulent energy spectrum EðkÞ ~ k-n generatesmetric fluctuations scaling as xn-2, where x is the four-dimensional spacelike distance from an arbitraryorigin in Minkowski spacetime, highlighting the onset of metric singularities whenever n < 2. Finally, theeffect of metric fluctuations on the geodesic motion of test particles is also discussed as a potentialtechnique to extract information on the spectral characteristics of fluctuating spacetime.

In this paper, we consider the problem of estimating the graphs of conditional dependencies between variables (i.e., graphical models) from multiple datasets under Gaussian settings. We present jewel 2.0, which improves our previous method jewel 1.0 by modeling commonality and class-specific differences in the graph structures and better estimating graphs with hubs, making this new approach more appealing for biological data applications. We introduce these two improvements by modifying the regression-based problem formulation and the corresponding minimization algorithm. We also present, for the first time in the multiple graphs setting, a stability selection procedure to reduce the number of false positives in the estimated graphs. Finally, we illustrate the performance of jewel 2.0 through simulated and real data examples. The method is implemented in the new version of the R package jewel

Mathematical models have the potential to contribute to design and evaluate the infectivity spreading and growth of human immunodeficiency virus (HIV). Providing a better understanding of the dynamics of HIV infection in vivo and the immune system interactions with the virus can improve the classification of the infected cells and drive to an early diagnosis of the disease and drug evaluations. We analyze a two-dimensional environment HIV model from a new perspective, in terms of a multi-objective optimization problem, by introducing a linear modeling approach and providing numerical evidence for its suitability by introducing a general Instantaneous Control Algorithm.

In this paper we propose a modeling setting and a numerical Riemann problem solver at the junction of one dimensional shallow-water channel networks. The junction conditions take into account the angles with which the channels intersect and include the possibility of channels with different sections. The solver is illustrated with several numerical tests which underline the importance of the angle dependence to obtain reliable solutions.

The societal impact of traffic is a long-standing and complex problem. We focus on the estimation of ground-level ozone production due to vehicular traffic. We propose a comprehensive computational approach combining four consecutive modules: a traffic simulation module, an emission module, a module for the main chemical reactions leading to ozone production, and a module for the diffusion of gases in the atmosphere. The traffic module is based on a second-order traffic flow model, obtained by choosing a special velocity function for the Collapsed Generalized Aw-Rascle-Zhang model. A general emission module is taken from literature, and tuned on NGSIM data together with the traffic module. Last two modules are based on reaction-diffusion partial differential equations. The system of partial differential equations describing the main chemical reactions of nitrogen oxides presents a source term given by the general emission module applied to the output of the traffic module. We use the proposed approach to analyze the ozone impact of various traffic scenarios and describe the effect of traffic light timing. The numerical tests show the negative effect of vehicles restarts on emissions, and the consequent increase in pollutants in the air, suggesting to increase the length of the green phase of traffic lights.

Nonparametric univariate regression via wavelets is usually implemented under the assumptions of dyadic sample size, equally spaced fixed sample points, and i.i.d. normal errors. In this work, we propose, study and compare some wavelet based nonparametric estimation methods designed to recover a one-dimensional regression function for data that not necessary possess the above requirements. These methods use appropriate regularizations by penalizing the decomposition of the unknown regression function on a wavelet basis of functions evaluated on the sampling design. Exploiting the sparsity of wavelet decompositions for signals belonging to homogeneous Besov spaces, we use some efficient proximal gradient descent algorithms, available in recent literature, for computing the estimates with fast computation times. Our wavelet based procedures, in both the standard and the robust regression case have favorable theoretical properties, thanks in large part to the separability nature of the (non convex) regularization they are based on. We establish asymptotic global optimal rates of convergence under weak conditions. It is known that such rates are, in general, unattainable by smoothing splines or other linear nonparametric smoothers. Lastly, we present several experiments to examine the empirical performance of our procedures and their comparisons with other proposals available in the literature. An interesting regression analysis of some real data applications using these procedures unambiguously demonstrate their effectiveness.