An X-ray diffraction pattern consists of relevant information (the signal) and noisy background. Under the assumption that they behave as the components of a two-dimensional mixture (bicomponent fluid) having slightly different physical properties related to the density gradients, a Lattice Boltzmann Method is applied to disentangle the two different diffusive dynamics. The solution is numerically stable, not computationally demanding, and, it also provides an efficient increase in the signal-to-noise ratio for patterns blurred by Poissonian noise and affected by collection data anomalies (fiber-like samples, experimental setup, etc.). The model is succesfully applied to different resolution images.

We present a comprehensive and automated methodology for processing two-dimensional X-ray diffraction (2D-XRD) patterns. The proposed workflow involves three sequential stages: (i) precise localization of the diffraction center, (ii) removal of high-frequency noise, and (iii) suppression of non-physical background signals. This method enables improved data quality for subsequent quantitative analysis such as radial integration, phase identification, and structural refinement. Application to experimental datasets from both the Synchrotron Radiation Facility and a table-top X-ray diffractometer demonstrates the method’s robustness, accuracy, and computational efficiency.

An X-ray Diffraction pattern consists of the relevant information (the signal) and the noisy background. Under the assumption that they behave as the components of a two-dimensional mixture (bicomponent fluid) having slightly different physical properties related to the density-gradients, a Lattice Boltzmann Method is applied to disentangle the two different diffusive dynamics. The solution is numerically stable, computationally not demanding and, moreover, it provides an efficient increase of the signal-to-noise ratio for patterns blurred by poissonian noise and affected by collection data anomalies (fiber-like samples, experimental setup, etc.). The model has been succesfully applied to different resolution images. Ke

We investigate rare semileptonic B -> K* l(+) l(-) by looking at a specific long distance contribution. Our analysis is limited to the very small values of physical accessible range of invariant mass of the leptonic couple q(2). We show that the light quarks loop has to be accounted for, along with the charming penguin contribution, in order to accurately compute the q(2)-spectrum in the Standard Model. Such a long distance contribution may also play a role in the analysis of the lepton flavor universality violation in this process. (c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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.

An unsupervised segmentation/clustering algorithm is a method for modeling the generation of directly observable visible variables from hidden sources. Each hidden source coop- erates in activating a subset of visible variables, or parts, which, in turn, additively generate the whole. This project aims at applying the versatility of such a method to the semantic analysis of text documents, namely patent applications.

We investigate rare semileptonic B->K*l+l- by looking at the long distance contributions. Our analysis is limited to the very small values of physical accessible range of invariant mass of the leptonic couple q2. We show that the light quarks loop has to be accounted for, along with the charming penguin contribution, in order to accurately compute the q2-spectrum in the Standard Model. Such a long distance contribution may also play a role in the analysis of the lepton flavour universality violation in this process.

A mm thick free-standing gel containing lipid vesicles made of 2-oleoyl-1-palmitoyl-sn-glycero-3-phosphocholine (POPC) was studied by scanning Small Angle X-ray Scattering (SAXS) and X-ray Transmission (XT) microscopies. Raster scanning relatively large volumes, besides reducing the risk of radiation damage, allows signal integration, improving the signal-to-noise ratio (SNR), as well as high statistical significance of the dataset. The persistence of lipid vesicles in gel was demonstrated, while mapping their spatial distribution and concentration gradients. Information about lipid aggregation and packing, as well as about gel density gradients, was obtained.A posterioriconfirmation of lipid presence in well-defined sample areas was obtained by studying the dried sample, featuring clear Bragg peaks from stacked bilayers. The comparison between wet and dry samples allowed it to be proved that lipids do not significantly migrate within the gel even upon drying, whereas bilayer curvature is lost by removing water, resulting in lipids packed in ordered lamellae. Suitable algorithms were successfully employed for enhancing transmission microscopy sensitivity to low absorbing objects, and allowing full SAXS intensity normalization as a general approach. In particular, data reduction includes normalization of the SAXS intensity against the local sample thickness derived from absorption contrast maps. The proposed study was demonstrated by a room-sized instrumentation, although equipped with a high brilliance X-ray micro-source, and is expected to be applicable to a wide variety of organic, inorganic, and multicomponent systems, including biomaterials. The employed routines for data reduction and microscopy, including Gaussian filter for contrast enhancement of low absorbing objects and a region growing segmentation algorithm to exclude no-sample regions, have been implemented and made freely available through the updated in-house developed software SUNBIM.

This work aims at studying the crystallization process of Hydroxyapatite samples in three different chemical environments (Cit, Glr, CitOH), as a function of time and temperature (25°C, 37°C or biomimetic temperature, 60°C and 80°C) . In particular non-crystalline and/or precursor states (SAXS) are expected to play a key-role in this analysis. Due to the huge amount of data collected at Synchrotron facilities, a preliminary correlation evaluation is needed in order to extract the most representative curves showing significant modification in shape and/or in the regions of interest. An algorithm based on Hierarchical Non-Negative Matrix Factorization (intensity SAXS profiles are positive) has been developed and applied in order to select 2^n profiles (n==number of bisections of the original data set). The comparison of the algorithm findings to the known particle morphologies (SAXS fitting) has spotted the HA crystallization dynamics (time resolved) beneath, both at different temperatures and chemical environments.

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.

The use of a mathematical model is proposed in order to denoise X-ray two-dimensional patterns. The method relies on a generalized diffusion equation whose diffusion constant depends on the image gradients. The numerical solution of the diffusion equation provides an efficient reduction of pattern noise as witnessed by the computed peak of signal-to-noise ratio. The use of experimental data with different inherent levels of noise allows us to show the success of the method even in the case, experimentally relevant, when patterns are blurred by Poissonian noise. The corresponding MatLab code for the numerical method is made available.

SUNBIM (Supramolecular and sUbmolecular Nano- and Biomaterials X-ray IMaging) is a computer suite of integrated programs which, through a user-friendly graphical interface, is able to perform a number of functions for (GI)SAXS-(GI)WAXS data analysis [1] such as: centering, q-scale calibration, two-dimensional to one-dimensional folding of small- and wide-angle X-ray scattering (SAXS/WAXS) data, also in grazing-incidence (GISAXS/GIWAXS); indexing of two-dimensional GISAXS frames and extraction of one-dimensional GISAXS profiles along specific cuts; quantitative scanning microscopy in absorption and SAXS contrast. SUNBIM consists of five main programs: (1) Calibration package, a set of functions allow one to find all of the geometrical parameters needed to extract a one-dimensional profile out of a two-dimensional image; (2) Batch Script & 2D Mesh Composite, to prepare batch script files (ASCII files) to run a sequential acquisition of two-dimensional frames (in scanning mode) and to perform a composite of the as-collected two-dimensional SAXS frames into a single image; (3) Single-scan (GI)SAXS and (GI)WAXS data analysis, to calibrate and fold the two-dimensional data, in order to extract relevant information from the experimental data and to fold 2D data into 1D profiles; (4) Multi-scan SAXS and WAXS data analysis, to fold each two-dimensional frame of the mesh into a one-dimensional profile and extract scattering features of the sample with a multi-modal imaging approach; (5) One-D Data Analysis Manager, a package that in addition to basic operations on one dimensional profiles (such as change of the plot representation from pixels to q, change from linear scale to logarithmic scale of the axes, choice of colors and plot thickness, inserting the legend, etc. as well as import, trigger, save and export plots) gives the possibility to denoise the folded profile and/or to deconvolute the primary beam angular divergence from the SAXS/WAXS profiles, particularly useful for a complete data analysis. SUNBIM combines in the same package both originally developed algorithms (i.e denoising, beam centering etc.) and reliable methods documented in the literature (multi-modal imaging [2], GIXAXS three-dimensional frame indexing [3]). New tools have been developed to enrich SUNBIM suite. The main novelty is the possibility to perform a deeper data reduction including dark current subtraction, background evaluation and subtraction, normalization of the SAXS intensity against the local sample thickness derived from absorption contrast maps. The advances of the new release with respect to previous one include also an automatic background subtraction from the 1D profile of the azimuthal integration to enhance peak visibility at large scattering angles (WAXS), to correct geometric aberration for small sample-to-detector distance. The previous release of the software has already been used successfully to analyse several nano-structured samples [4][5][6]. We are confident that the new features will allow a more correct and extensive analysis of the (GI)SAXS/(GI)WAXS data. SUNBIM is developed in the MATLAB language and it is distributed free of charge to the academic user (downloadable after a valid registration from http://www.ba.ic.cnr.it/softwareic/sunbimweb/)

We propose the use of a mathematical model in order to denoise X-ray twodimensional patterns. The model, which makes use of a generalized diffusion equation whose diffusion constant depends on the image gradients, enables to obtain an efficient reduction of pattern noise as witnessed by the computed peak of signal to noise ratio. The corresponding MATLAB code is made available.

In this article a nonnegative blind source separation technique, known as nonnegative matrix factorization, is applied to microdiffraction data in order to extract characteristic patterns and to determine their spatial distribution in tissue typing problems occurring in bone-tissue engineering. In contrast to other blind source separation methods, nonnegative matrix factorization only requires nonnegative constraints on the extracted sources and corresponding weights, which makes it suitable for the analysis of data occurring in a variety of applications. In particular, here nonnegative matrix factorization is hierarchically applied to two-dimensional meshes of X-ray diffraction data measured in bone samples with implanted tissue. Such data are characterized by nonnegative profiles and their analysis provides significant information about the structure of possibly new deposited bone tissue. A simulation and real data studies show that the proposed method is able to retrieve the patterns of interest and to provide a reliable and accurate segmentation of the given X-ray diffraction data.

We present two possible approaches to calculate the momentum distribution n(p) and the Compton profile within the framework of the ab initio GW approximation on the self-energy. The approaches are based on integration of the Green's function along either the real or the imaginary axes. Examples will be presented on the jellium model and on real bulk sodium. Advantages and drawbacks of both methods are discussed in comparison with accurate quantum Monte Carlo calculations and x-ray Compton scattering experiments. We illustrate the effect of many-body correlations and disentangle them from band-structure and anisotropy effects by a comparison with density functional theory in the local density approximation. Our results suggest the use of G0W0 momentum distributions as reference for future experiments and theory developments.