X-ray Small and Wide Scattering scanning microscopies have been adopted to inspect morphological and structural properties of collagen-based tissues at the atomic and nano scale 1 . Examples will be discussed on specific pathologies: o osteoarthritis of the hip, also named osteoarthrosis of the hip or coxarthrosis, which is a chronic degenerative disorder of the hip joint, causing growing articular pain that can bring the patient to lifestyle limitations until surgical intervention is needed 2 o keratoconus, a pathology affecting cornea, which causes progressive thinning of the stroma and consequently abnormal curvature, inducing irregular astigmatism and myopia, corneal fibrosis, and distortion of vision, due to the modification in the organization of the corneal collagen 3 o abdominal aortic aneurysm, that occurs in the major artery from the hearth that supplies blood to the abdomen, and popliteal aneurysm, that takes place in the legs, behind the knees, characterized by alteration of collagen structure into vessel's wall of the aneurysm tissues, heterogeneous grade of inflammation related to infiltrating cells and extracellular matrix changes, in particular disruption of elastic fibers, fibrosis and calcifications 4 o diabetes mellitus, a metabolic disorder characterized by high blood sugar levels over a prolonged period due to defects in insulin action or secretion, which causes collagen to have a fixed orientation, stiffen the tissue and is likely to disrupt the normal cell interactions.

Spectral emissivity is a key property of the Earth surface of which only very few measurements exist so far in the far-infrared (FIR) spectral region, even though recent work has shown its FIR contribution is important for accurate modelling of global climate. The European Space Agency's 9th Earth Explorer, FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) will provide the first global spectrally resolved measurements of the Earth's top-of-the-atmosphere (TOA) spectrum in the FIR. In clear-sky conditions with low water vapour content, these measurements will provide a unique opportunity to retrieve spectrally resolved FIR surface emissivity. In preparation for the FORUM mission with an expected launch in 2026, this study takes the first steps towards the development of an operational emissivity retrieval for FORUM by investigating the sensitivity of the emissivity product of a full spectrum optimal estimation retrieval method to different physical and operational parameters. The tool used for the sensitivity tests is the FORUM mission's end-to-end simulator. These tests show that spectral emissivity of most surface types can be retrieved for dry scenes in the 350-600 cm-1 region with an uncertainty ranging from 0.005 to 0.01. In addition, the quality of retrieval is quantified with respect to the precipitable water vapour content of the scene, and the uncertainty caused by the correlation of emissivity with surface temperature is investigated. Two main recommendations are made based on these investigations: (1) As the extent of TOA sensitivity to the surface in the FIR depends on the atmospheric state, the spectral region of the emissivity product should be decided using a so-called information quantifier, calculated from the ratio of the retrieval uncertainty to the a-priori uncertainty. (2) Depending on retrieval input parameters, the correlation of emissivity with surface temperature allows for retrieved emissivities within a small range around the true emissivity. Thus the impact of this correlation on the uncertainty estimates of the product should be quantified in detail during further development of the operational retrieval.

We present mesoscale numerical simulations of Rayleigh-Bénard (RB) convection in a two-dimensional model emulsion. The systems under study are constituted of finite-size droplets, whose concentration is systematically varied from small (Newtonian emulsions) to large values (non-Newtonian emulsions). We focus on the characterisation of the heat transfer properties close to the transition from conductive to convective states, where it is well known that a homogeneous Newtonian system exhibits a steady flow and a time-independent heat flux. In marked contrast, emulsions exhibit non-steady dynamics with fluctuations in the heat flux. In this paper, we aim at the characterisation of such non-steady dynamics via detailed studies on the time-averaged heat flux and its fluctuations. To quantitatively understand the time-averaged heat flux, we propose a side-by-side comparison between the emulsion system and a single-phase (SP) system, whose viscosity is suitably constructed from the shear rheology of the emulsion. We show that such local closure works well only when a suitable degree of coarse-graining (at the droplet scale) is introduced in the local viscosity. To delve deeper into the fluctuations in the heat flux, we furthermore propose a side-by-side comparison between a Newtonian emulsion (i.e., with a small droplet concentration) and a non-Newtonian emulsion (i.e., with a large droplet concentration), at fixed time-averaged heat flux. This comparison elucidates that finite-size droplets and the non-Newtonian rheology cooperate to trigger enhanced heat-flux fluctuations at the droplet scales. These enhanced fluctuations are rooted in the emergence of space correlations among distant droplets, which we highlight via direct measurements of the droplets displacement and the characterisation of the associated correlation function. The observed findings offer insights on heat transfer properties for confined systems possessing finite-size constituents.

In this article, we deal with the model selection problem for estimating a Gaussian Graphical Model (GGM) by regression based techniques. In fact, although regression based techniques are well understood and have good theoretical properties, it is still not clear which criterion is more appropriate for model selection. In this work we do a comparative study between CV and BIC, obtaining important conclusions that can be of practical interest in different contexts of data analysis. In this article, we deal with the model selection problem for estimating a Gaussian Graphical Model (GGM) by regression based techniques. In fact, although regression based techniques are well understood and have good theoretical properties, it is still not clear which criterion is more appropriate for model selection. In this work we do a comparative study between CV and BIC, obtaining important conclusions that can be of practical interest in different contexts of data analysis.

In this paper, we propose two models describing the dynamics of heavy and light vehicles on a road network, taking into account the interactions between the two classes. The models are tailored for two-lane highways where heavy vehicles cannot overtake. This means that heavy vehicles cannot saturate the whole road space, while light vehicles can. In these conditions, the creeping phenomenon can appear, i.e., one class of vehicles can proceed even if the other class has reached the maximal density. The first model we propose couples two first-order macroscopic LWR models, while the second model couples a second-order microscopic follow-the-leader model with a first-order macroscopic LWR model. Numerical results show that both models are able to catch some second-order (inertial) phenomena such as stop and go waves. Models are calibrated by means of real data measured by fixed sensors placed along the A4 Italian highway Trieste-Venice and its branches, provided by Autovie Venete S.p.A.

A new immersed boundary approach for high order Weighted Essentially non-Oscillatory (WENO) schemes is proposed. The schemes is based on the main ideas from both the general immersed boundary algorithms and the level-set approach and can be easily applied to both finite difference and finite volume formulation. Although formally only second order accurate, numerical tests prove that the use of higher order approximation for the Eulerian fluxes can be very convenient to capture flow details and to obtain low uncertainty also with very coarse grids.

The observations acquired during the full mission of the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) instrument, aboard the European Space Agency Environmental Satellite (Envisat), have been analysed with version 8.22 of the Optimised Retrieval Model (ORM), originally developed as the scientific prototype of the ESA level-2 processor for MIPAS observations. The results of the analyses have been included into the MI- PAS level-2 version 8 (level2-v8) database containing atmospheric fields of pressure, temperature, and volume mixing ratio (VMR) of MIPAS main targets H2 O, O3 , HNO3 , CH4 , N2 O, and NO2 , along with the minor gases CFC- 11, ClONO2 , N2 O5 , CFC-12, COF2 , CCl4 , CF4 , HCFC-22, C2 H2 , CH3 Cl, COCl2 , C2 H6 , OCS, and HDO. The database covers all the measurements acquired by MIPAS in the nominal measurement mode of the full resolution (FR) part of the mission (from July 2002 to March 2004) and all the observation modes of the optimised resolution (OR) part (from January 2005 to April 2012). The number of species included in the MIPAS level2-v8 dataset makes it of particular importance for the studies of stratospheric chemistry. The database is considered by ESA the final release of the MIPAS level-2 products.The ORM algorithm is operated at the vertical grid coincident to the tangent altitudes of the observations or to a subset of them, spanning (in the nominal mode) the alti- tude range from 6 to 68km in the FR phase and from 6 to 70 km in the OR period. In the latitude domain, FR profiles are spaced by about 4.7o, while the OR profiles are spaced by about 3.7o. For each retrieved species, the auxiliary data and the retrieval choices are described. Each product is characterised in terms of the retrieval error, spatial resolution, and "useful" vertical range in both phases of the MIPAS mission. These depend on the characteristics of the measurements (spectral and vertical resolution of the measurements), the retrieval choices (number of spectral points in- cluded in the analyses, number of altitudes included in the vertical retrieval grid), and the information content of the measurements for each trace species. For temperature, water vapour, ozone, and nitric acid, the number of degrees of freedom is significantly larger in the OR phase than in the FR one, mainly due to the finer vertical measurement grid. In the FR phase, some trace species are characterised by a smaller retrieval error with respect to the OR phase, mainly due to the larger number of spectral points used in the analyses, along with the reduced vertical resolution. The way of handling possible caveats (negative VMR, vertical grid representation) is discussed. The quality of the retrieved profiles is assessed through four criteria, two providing information on the successful convergence of the retrieval iterations, one on the capability of the retrieval to reproduce the measurements, and one on the presence of outliers. An easy way to identify and filter the problematic profiles with the informa- tion contained in the output files is provided. MIPAS level2- v8 data are available to the scientific community through the ESA portal (https://doi.org/10.5270/EN1-c8hgqx4).

In this paper we establish an higher integrability result for second derivatives of the local solution of elliptic equation div(A(x,Du))=0in?where ? ? R, n>= 2 and A(x, ?) has linear growth with respect to ? variable. Concerning the dependence on the x-variable, we shall assume that, for the map x-> A(x, ?) , there exists a non negative function k(x), such that |DxA(x,?)|?k(x)(1+|?|)for every ?? R and a.e. x? ?. It is well known that there exists a relationship between this condition and the regularity of the solutions of the equation. Our pourpose is to establish an higher integrability result for second derivatives of the local solution, by assuming k(x) in a suitable Zygmund class.

In this paper we establish the boundedness and the higher differentiability of solutions to the {div(A(x,Du))+b(x)|u(x)|u(x)=fin ?u=0on ?? under a Sobolev assumption on the partial map x->A(x,?). The novelty here is that we deal with degenerate elliptic operator A(x,?) with p-growth, p>=2, with respect to the gradient variable, in presence of lower order terms. The interplay between b(x) and f(x), introduced in ([1]), gives a regularizing effect also in the degenerate elliptic setting.

Meditation practices have been claimed to have a positive effect on the regulation of mood and emotions for quite some time by practitioners, and in recent times there has been a sustained effort to provide a more precise description of the influence of meditation on the human brain. Longitudinal studies have reported morphological changes in cortical thickness and volume in selected brain regions due to meditation practice, which is interpreted as an evidence its effectiveness beyond the subjective self reporting. Using magnetoencephalography (MEG) or electroencephalography to quantify the changes in brain activity during meditation practice represents a challenge, as no clear hypothesis about the spatial or temporal pattern of such changes is available to date. In this article we consider MEG data collected during meditation sessions of experienced Buddhist monks practicing focused attention (Samatha) and open monitoring (Vipassana) meditation, contrasted by resting state with eyes closed. The MEG data are first mapped to time series of brain activity averaged over brain regions corresponding to a standard Destrieux brain atlas. Next, by bootstrapping and spectral analysis, the data are mapped to matrices representing random samples of power spectral densities in ?, ?, ?, and ? frequency bands. We use linear discriminant analysis to demonstrate that the samples corresponding to different meditative or resting states contain enough fingerprints of the brain state to allow a separation between different states, and we identify the brain regions that appear to contribute to the separation. Our findings suggest that the cingulate cortex, insular cortex and some of the internal structures, most notably the accumbens, the caudate and the putamen nuclei, the thalamus and the amygdalae stand out as separating regions, which seems to correlate well with earlier findings based on longitudinal studies.

Neural oscillations contribute to speech parsing via cortical tracking of hierarchical linguistic structures, including syllable rate. While the properties of neural entrainment have been largely probed with speech stimuli at either normal or artificially accelerated rates, the important case of natural fast speech has been largely overlooked. Using magnetoencephalography, we found that listening to naturally-produced speech was associated with cortico-acoustic coupling, both at normal (~6 syllables/s) and fast (~9 syllables/s) rates, with a corresponding shift in peak entrainment frequency. Interestingly, time-compressed sentences did not yield such coupling, despite being generated at the same rate as the natural fast sentences. Additionally, neural activity in right motor cortex exhibited stronger tuning to natural fast rather than to artificially accelerated speech, and showed evidence for stronger phase-coupling with left temporo-parietal and motor areas. These findings are highly relevant for our understanding of the role played by auditory and motor cortex oscillations in the perception of naturally produced speech.

MagnetoEncephaloGraphy (MEG) and ElectroEncephaloGraphy (EEG) are the most common non-invasive brain imaging techniques for monitoring the electrical brain activity with millisecond resolution. Due to their high, millisecond, temporal resolution, these techniques are also the most suitable for studying the dynamic interplay of between brain regions during information processing. In clinical settings, MEG and EEG are valuable methods for the pre-surgical evaluation of patients with pharmaco-resistant epilepsy. The localization of epileptogenic zone (EZ) provided by these techniques can avoid or guide invasive intracranial recordings. More recently, there is has been a growing interest in exploiting leveraging these techniques as a crucial tool to advance our understanding of the pathophysiological mechanisms of major neuropsychiatric disorders and neurological diseases. This symposium offers an overview of very recent studies on the use ofwhich employed MEG and EEG as valid tools to investigate brain disorders. In particularSpecifically, the five talks will provide important insights on new methodological approaches to characterize brain dysfunctions in different pathological conditions. We will focus on : (1) emerging tool to characterize irritative zones in epileptic patients and to detect in a semi automatic way epileptiform abnormalities during EEG sleep recordings ina semi-automatic way; (2) two different methodological approaches to evaluate frequency specific alterations of brain activity and connectivity in schizoprenia and glioma patients; and (3) using machine-learning methods for identificationto identify EEG predictors of dementia in Parkinson.

Electrical source imaging (ESI) aims at reconstructing the electrical brain activity from measurements of the electric field on the scalp. ESI is a key element in the analysis of EEG data, in both research and clinical settings. In the last twenty years several algorithms have been applied for solving the ill- posed EEG inverse problem. Most of these popular methods can be derived within a Bayesian statistical framework in which all variables can be modelled as random variables with associated probability density functions (pdf) and the solution of the inverse problem is the posterior pdf for the unknown primary current distribution conditioned on the measurements. The different methods mainly differ from each other by the quality and quantity of a priori information they use in order to solve the EEG inverse problem. In this study [1] we validate and compare ten different ESI methods (wMNE, dSPM, sLORETA, eLORETA, LCMV, dipole fitting, RAP-MUSIC, MxNE, gamma map and Sesame) "in vivo", by exploiting a recently published EEG dataset [2] for which the ground truth is known. We compare the different inverse methods under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of the parameters on the localization performance

The poles of the heart and branchiomeric muscles of the face and neck are formed from the cardiopharyngeal mesoderm within the pharyngeal apparatus. They are disrupted in patients with 22q11.2 deletion syndrome, due to haploinsufficiency of TBX1, encoding a T-box transcription factor. Here, using single cell RNA-sequencing, we now identify a multilineage primed population within the cardiopharyngeal mesoderm, marked by Tbx1, which has bipotent properties to form cardiac and branchiomeric muscle cells. The multilineage primed cells are localized within the nascent mesoderm of the caudal lateral pharyngeal apparatus and provide a continuous source of cardiopharyngeal mesoderm progenitors. Tbx1 regulates the maturation of multilineage primed progenitor cells to cardiopharyngeal mesoderm derivatives while restricting ectopic non-mesodermal gene expression. We further show that TBX1 confers this balance of gene expression by direct and indirect regulation of enriched genes in multilineage primed progenitors and downstream pathways, partly through altering chromatin accessibility, the perturbation of which can lead to congenital defects in individuals with 22q11.2 deletion syndrome.

A recently proposed mesoscale approach for the simulation of multicomponent flows with near-contact interactions is employed to investigate the early stage formation and clustering statistics of soft flowing crystals in microfluidic channels. Specifically, we first demonstrate the ability of the aforementioned mesoscale model to accurately reproduce main mechanisms leading to the formation of two basic droplet patterns (triangular and hexagonal), in close agreement with experimental evidence. Next, we quantitatively evaluate the device-scale clustering efficiency of the crystal formation process by introducing a new orientational order parameter, based on the Delaunay triangulation and Voronoi diagrams analysis of the droplet patterns. The mesoscale computational approach employed in this work proves to be an efficient tool to shed new light on the complex dynamics of dense emulsions, from short-scale thin-film hydrodynamics, all the way up to global structure formation and statistics of the resulting droplets ensembles.

Purpose A recursive scheme for the ALIENOR method is proposed as a remedy for the difficulties induced by the method. A progressive focusing on the most promising region, in combination with a variation of the density of the alpha-dense curve, is proposed. Design/methodology/approach ALIENOR method is aimed at reducing the space dimensions of an optimization problem by spanning it by using a single alpha-dense curve: the curvilinear abscissa along the curve becomes the only design parameter for any design space. As a counterpart, the transformation of the objective function in the projected space is much more difficult to tackle. Findings A fine tuning of the procedure has been performed in order to identity the correct balance between the different elements of the procedure. The proposed approach has been tested by using a set of algebraic functions with up to 1,024 design variables, demonstrating the ability of the method in solving large scale optimization problem. Also an industrial application is presented. Originality/value In the knowledge of the author there is not a similar paper in the current literature.

Differential models, numerical methods and computer simulations play a fundamental rolein applied sciences. Since most of the differential models inspired by real world applications have noanalytical solutions, the development of numerical methods and efficient simulation algorithms playa key role in the computation of the solutions to many relevant problems. Moreover, since the modelparameters in mathematical models have interesting scientific interpretations and their values areoften unknown, estimation techniques need to be developed for parameter identification against themeasured data of observed phenomena. In this respect, this Special Issue collects some importantdevelopments in different areas of application.

Questo documento riassume l'attività svolta nei vari WP, le azioni completate e lo stato di del progetto per il periodo di attività dal 16 giugno 2020 (RA2) al 9 giugno 2021 (RA3).

Given the definition of Software Unit (SU) as a computer program, which takes some input data and processesthem producing output data, this Technical Note (TN) provides some general guidelines to prepare the scientificand technical documentation of the different SUs developed and shared by the partners of the "FORUM Scienza"project.