A technique for the restoration of low resonance component and high res-onance component of K independently measured signals is presented. The definitionof low and high resonance component is given by the Rational Dilatation WaveletTransform (RADWT), a particular kind of finite frame that provides sparse repre-sentation of functions with different oscillations persistence. It is assumed that thesignals are measured simultaneously on several independent channels and in eachchannel the underlying signal is the sum of two components: the low resonancecomponent and the high resonance component, both sharing some common char-acteristic between the channels. Components restoration is performed by means ofthe lasso-type penalty and back-fitting algorithm. Numerical experiments show theperformance of the proposed method in different synthetic scenarios highlightingthe advantage of estimating the two components separately rather than together.

This book presents important recent applied mathematics research on environmental problems and impacts due to climate change. Although there are inherent difficulties in addressing phenomena that are part of such a complex system, exploration of the subject using mathematical modelling is especially suited to tackling poorly understood issues in the field. It is in this spirit that the book was conceived. It is an outcome of the International INDAM Workshop "Mathematical Approach to Climate Change Impacts - MAC2I", held in Rome in March 2017. The workshop comprised four sessions, on Ecosystems, Hydrology, Glaciology, and Monitoring. The book includes peer-reviewed contributions on research issues discussed during each of these sessions or generated by collaborations among the specialists involved. Accurate parameter determination techniques are explained and innovative mathematical modelling approaches, presented. The book also provides useful material and mathematical problem-solving tools for doctoral programs dealing with the complexities of climate change.

This work concerns the rock glacier flow model introduced, in its basic form, by Kannan and Rajagopal in [1] and extended with inclusion of temperature effects by Kannan, Rajagopal, Mansutti and Urbini in [2]. This one is based on the general conservation laws (momentum, mass and energy) and takes into account the effect of shear rate, pressure and rocks and sand grains volume fraction onto viscosity, also by implementing the effects of local pressure melting point variation. Here we present the results of a sensitivity analysis of the parameters developed by shooting the location of the internal sliding occurence, induced by the presence of rocks and sand grains trapped within the interstices of the glacier, and the value of the shear velocity. The case of the Murtel-Corvatsch glacier in Switzerland is considered for the availability of the detailed description based on measured data published by Arenson, Hoelzle and Springman in [3]. The numerical results obtained improve those ones presented in [1] and show clearly the contribution of each numerical and functional parameter of the model. They also exhibit a very good agreement with observations which makes this modelling approach very promising for general application. [1] Kannan, K., Rajagopal, K.R.: A model for the flow of rock glaciers. Int. J. Non-lin. Mech., 48, pp. 59– 64 (2013) [2] Kannan, K., Mansutti, D., Rajagopal, K.R. and Urbini, S.: Mathematical modeling of rock glacier flow with temperature effects, in Mathematical Approach to Climate Change and its Impacts (P. Cannarsa, D. Mansutti and A. Provenzale, eds.), pp. 137-148, Springer-INDAM series, vol.38 (2020) [3] Arenson, L., Hoeltzle, M. and Springman, S.: Borehole Deformation Measurements and Internal Structure of Some Rock Glaciers in Switzerland. Permafrost and Periglacial Processes, 13, pp. 117-135 (2002).

The paper concerns the weighted uniform approximation of a real function on the d-cube [-1, 1]^d, with d > 1, by means of some multivariate filtered polynomials. These polynomials have been deduced, via tensor product, from certain de la Vallée Poussin type means on [-1, 1], which generalize classical delayed arithmetic means of Fourier partial sums. They are based on arbitrary sequences of filter coefficients, not necessarily connected with a smooth filter function. Moreover, in the continuous case, they involve Jacobi-Fourier coefficients of the function, while in the discrete approximation, they use function's values at a grid of Jacobi zeros. In both the cases we state simple sufficient conditions on the filter coefficients and the underlying Jacobi weights, in order to get near-best approximation polynomials, having uniformly bounded Lebesgue constants in suitable spaces of locally continuous functions equipped with weighted uniform norm. The results can be useful in the construction of projection methods for solving Fredholm integral equations, whose solutions present singularities on the boundary. Some numerical experiments on the behavior of the Lebesgue constants and some trials on the attenuation of the Gibbs phenomenon are also shown.

Si mostrano le condizioni sufficienti per avere costanti di Lebesgue ottimali (anche pesate) per l'approssimazione polinomiale discreta di una funzione di due variabili, nota su una griglia di zeri di Jacobi. Si considera sia l'interpolazione bivariata di Lagrange che l'approssimazione generalizzata di tipo de la Vallée Poussin, ottenuta mediante una generica funzione filtro. **

A full ODE model for the transmission of cholera is investigated, includ- ing both direct and indirect transmission and a nonlinear growth for pathogens. The direct problem is preliminarily studied and characterized in terms of reproduction number, endemic and disease free equilibria. The inverse problem is then discussed in view of parameter estimation and model identification via a Least Squares Approximation approach. The procedure is applied to real data coming from the recent Yemen cholera outbreak of 2017-2018.

The rheology of pressure-driven flows of two-dimensional dense monodisperse emulsions in neutral wetting microchannels is investigated by means of mesoscopic lattice Boltzmann simulations, capable of handling large collections of droplets, in the order of several hundreds. The simulations reveal that the fluidization of the emulsion proceeds through a sequence of discrete steps, characterized by yielding events whereby layers of droplets start rolling over each other, thus leading to sudden drops of the relative effective viscosity. It is shown that such discrete fluidization is robust against loss of confinement, namely it persists also in the regime of small ratios of the droplet diameter over the microchannel width. We also develop a simple phenomenological model which predicts a linear relation between the relative effective viscosity of the emulsion and the product of the confinement parameter (global size of the device over droplet radius) and the viscosity ratio between the disperse and continuous phases. The model shows excellent agreement with the numerical simulations. The present work offers new insights to enable the design of microfluidic scaffolds for tissue engineering applications and paves the way to detailed rheological studies of soft-glassy materials in complex geometries.

We present a mathematical model describing the evolution ofsea ice andmeltwater during summer. The system is described by two coupled partial differential equations for the ice thickness h and pond depth w fields. We test the sensitivity of the model to variations of parameters controlling fluid-dynamic processes at the pond level, namely the variation of turbulent heat flux with pond depth and the lateral melting of ice enclosing a pond. We observe that different heat flux scalings determine different rates of total surface ablations, while the system is relatively robust in terms of probability distributions of pond surface areas. Finally, we study pond morphology in terms of fractal dimensions, showing that the role of lateral melting is minor, whereas there is evidence of an impact from the initial sea ice topography.

A Round Robin exercise was implemented by ESA to compare different classification methods in detecting clouds from images taken by the PROBA-V sensor. A high-quality dataset of 1350 reflectances and Clear/Cloudy corresponding labels had been prepared by ESA in the framework of the exercise. Motivated by both the experience acquired by one of the authors in this exercise and the availability of such a reliable annotated dataset, we present a full assessment of the methodology proposed therein. Our objective is also to investigate specific issues related to cloud detection when remotely sensed images comprise only a few spectral bands in the visible and near-infrared. For this purpose, we consider a bunch of well-known classification methods. First, we demonstrate the feasibility of using a training dataset semi-automatically obtained from other accurate algorithms. In addition, we investigate the effect of ancillary information, e.g., surface type or climate, on accuracy. Then we compare the different classification methods using the same training dataset under different configurations. We also perform a consensus analysis aimed at estimating the degree of mutual agreement among classification methods in detecting Clear or Cloudy sky conditions.

The paper proposes an approach to deal with the day by day dynamic behaviour of Oil & Gas assets, providing support for optimized decisions on wells and facilities. The approach is based on: o A set of software agents, trained with a machine learning approach to understand the health status of the components of the reservoir/well/plant system and capable of proposing optimization actions for the corresponding subsystem; o An inter-agent negotiation approach, capable of evaluating the optimization actions of the single agents in the wider picture of the overall optimization of the producing asset. The paper will describe how this approach has been implemented, as well as an example application.

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 concentrations of many species, during both day and night, for 10 years, from July 2002 to April 2012. Being a limb sounding instrument, the focus of MIPAS measurements was the study of the atmosphere from the upper troposphere to the stratosphere and above, up to the mesosphere. 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 our planet's climate. To this purpose, it is therefore important to continue improving their quality. The quality of MIPAS L2 products depends on the quality of the L1 products, on the L2 model accuracy, on the quality of auxiliary data, particularly on spectroscopic data. 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 and L2 processors, as well as spectroscopy, with the objectives of obtaining L2 products with increased accuracy, better temporal stability, and a larger number of retrieved species. Here we present the full mission dataset, including vertical profiles of 21 trace species plus temperature, obtained by applying the latest version of ESA L2 processor (ORM V8) to the MIPAS L1 data obtained with version 8 of the L1 processor. The impact of the improvements of both L1 and L2 processors on the quality of the L2 products is presented, as well as results of the validation against independent correlative measurements.

The reverse mortgage market has been expanding rapidly in developed economies in recent years. Reverse mortgages provide an alternative source of funding for retirement income and health care costs. Increase in life expectancies and decrease in the real income at retirement continue to worry those who are retired or close to retirement. Therefore, financial products that help to alleviate the "risk of living longer" continue to be attractive among the retirees. Reverse mortgage contracts involve a range of risks from the insurer's perspective. When the outstanding balance exceeds the housing value before the loan is settled, the insurer suffers an exposure to crossover risk induced by three risk factors: interest rates, house prices and mortality rates. We analyse the combined impact of these risks on pricing and the risk profile of reverse mortgage loans in a stochastic interest-mortality-house pricing model. Our results show that pricing of reverse mortgages loans does not accurately assess the risks underwritten by reverse mortgages lenders.In particular, it fails to take into account mortality improvements substantially underestimating the longevity risk involved in reverse mortgage loans.

The containment of the invasive species is a widespread problem in the environmental management, with a significant economic impact. We analyze an optimal control model which aims to find the best temporal resource allocation strategy for the removal of an invasive species. We derive the optimality system in the state and control variables and we use the phase-space analysis to provide qualitative insights about the behavior of the optimal solution. Finally, for the state-costate variables which satisfy a boundary-valued nearly-Hamiltonian system, we propose exponential Lawson symplectic approximations applied in the forward-backward form. The numerical results related to an example of invasive plant considered in Baker, et al. (Nat Resour Model 31(4):e12190, 2018), confirm the qualitative findings provided by the state-control analysis.

The daily exposure of social media users to propaganda and disinformation campaigns has reinvigorated the need to investigate the local and global patterns of diffusion of different (mis)information content on social media. Echo chambers and influencers are often deemed responsible of both the polarization of users in online social networks and the success of propaganda and disinformation campaigns. This article adopts a data-driven approach to investigate the structuration of communities and propaganda networks on Twitter in order to assess the correctness of these imputations. In particular, the work aims at characterizing networks of propaganda extracted from a Twitter dataset by combining the information gained by three different classification approaches, focused respectively on (i) using Tweets content to infer the "polarization" of users around a specific topic, (ii) identifying users having an active role in the diffusion of different propaganda and disinformation items, and (iii) analyzing social ties to identify topological clusters and users playing a "central" role in the network. The work identifies highly partisan community structures along political alignments; furthermore, centrality metrics proved to be very informative to detect the most active users in the network and to distinguish users playing different roles; finally, polarization and clustering structure of the retweet graphs provided useful insights about relevant properties of users exposure, interactions, and participation to different propaganda items.

Service literature has recognized the important role of customers' characteristics for successful innovation and is increasingly emphasizing the contribution of lead users. However, few studies have analyzed this issue with reference to advertising and other creative services, especially because of the difficulties in defining innovation in these industries, by capturing its complex nature. Through a large-scale survey on European advertising agencies, we provide empirical evidence of a multidimensional nature of innovation in these services, which can be better promoted by clients embodying some attributes rather than others. Indeed, our results identify three clusters, which differ for the clients' innovation enabling characteristics and their potential roles in promoting agency's innovation: the Dominant lead users; the Expert lead users; the Ordinary clients. We acknowledge the role of lead users in advertising and contribute to literature highlighting when they can be conducive to agency's innovation or be detrimental to it.

More than twenty years ago the reverse vaccinology paradigm came to light trying todesign new vaccines based on the analysis of genomic information in order to selectthose pathogen peptides able to trigger an immune response. In this context, focusingon the proteome of Trypanosoma cruzi, we investigated the link between theprobabilities for pathogen peptides to be presented on a cell surface and their distancefrom human self. We found a reasonable but, as far as we know, undiscoveredproperty: the farther the distance between a peptide and the human-self the higherthe probability for that peptide to be presented on a cell surface. We also found thatthe most distant peptides from human self bind, on average, a broader collection ofHLAs than expected, implying a potential immunological role in a large portion ofindividuals. Finally, introducing a novel quantitative indicator for a peptide tomeasure its potential immunological role, we proposed a pool of peptides that could bepotential epitopes and that can be suitable for experimental testing. The software tocompute peptide classes according to the distance from human self is free available athttp://www.iasi.cnr.it/~dsantoni/nullomers.

The post-Minkowskian approach to gravitationally interacting binary systems (i.e., perturbation theory in G, without assuming small velocities) is extended to the computation of the dynamical effects induced by the tidal deformations of two extended bodies, such as neutron stars. Our derivation applies general properties of perturbed actions to the effective field theory description of tidally interacting bodies. We compute several tidal invariants (notably the integrated quadrupolar and octupolar actions) at the fast post-Minkowskian order. The corresponding contributions to the scattering angle are derived.

TEOBResumS and SEOBNRv4 are the two existing semianalytical gravitational waveform models for spin-aligned coalescing black hole binaries based on the effective-one-body (EOB) approach. They are informed by numerical relativity simulations and provide the relative dynamics and waveforms from early inspiral to plunge, merger, and ringdown. The central building block of each model is the EOB resummed Hamiltonian. The two models implement different Hamiltonians that are both deformations of the Hamiltonian of a test spinning black hole moving around a Kerr black hole. Here we analytically compare, clement by clement, the two Hamiltonians. In particular: we illustrate that one can introduce a centrifiigal radius in SEOBNRv4, so to rewrite the Hamiltonian in a more compact form that is analogous to the one of TEOBResumS. The latter centrifugal radius cannot, however, be identified with the one used in TEOBResumS because the two models differ in their ways of incorporating spin effects in their respective deformations of the background Kerr Hamiltonian. We performed extensive comparisons between the energetics corresponding to the two Hamiltonians using gauge-invariant quantities. Finally, as an exploratory investigation, we apply the postadiabatic approximation to the newly rewritten SEOBNRv4 Hamiltonian, illustrating that it is possible to generate long-inspiral waveforms with negligible computational cost.

An Ermakov-Pinney-like equation associated with the scalar wave equation in curved space-time is here studied. The example of Schwarzschild space-time considered in the present work shows that this equation can be viewed more as a "model equation," with interesting applications in black hole physics. Other applications studied involve cosmological space-times (de Sitter) and pulse of plane gravitational waves: in all these cases the evolution of the Ermakov-Pinney field seems to be consistent with a rapid blow-up, unlike the Schwarzschild case where spatially damped oscillations are allowed. Eventually, the phase function is also evaluated in many of the above space-time models.

We compute the first-order self-force contribution to Detweiler's redshift invariant for extended bodies endowed with both dipolar and quadrupolar structure (with spin-induced quadrupole moment) moving along circular orbits on a Schwarzschild background. Our analysis includes effects which arc second order in spin, generalizing previous results for purely spinning particles. The perturbing body is assumed to move on the equatorial plane, the associated spin vector being orthogonal to it. The metric perturbations are obtained by using a standard gravitational self-force approach in a radiation gauge. Our results are accurate through the 6.5 post-Newtonian order, and arc shown to reproduce the corresponding post-Newtonian expression for the same quantity computed by using the available Hamiltonian from an effective field theory approach for the dynamics of spinning binaries.