Environmental impacts of cement production. A statistical analysis

The attention to environmental impacts of cement production has grown fast in recent decades. The cement industry is a significant greenhouse gases emitter mainly due to the calcinations of raw materials and the combustions of fuels. This paper investigates on the environmental performances of cement production and on the identification of factors driving emissions. For this purpose, a sample of 193 different recipes of gray cement produced in Italy from 2014 to 2019 according to the European standard EN 197-1. This paper identifies the consumption impact categories (e.g., fossil fuels, renewable and non-renewable secondary fuels) that explain the assessment of the Global Warming Potential, one of the most crucial impacts of cement production. Having regard to the overall examined dataset and each cement type, a set of predictive models is implemented and evaluated. A similar approach has been adopted to produce accurate predictive models for further environmental impact categories that quantify emissions to air. The obtained results provide important information that can support cement producers to develop low-impacting cement recipes

Parametric estimation for functional autoregressive processes on the sphere

The aim of this paper is to define a nonlinear least squares estimator for the spectral parameters of a spherical autoregressive process of order 1 in a parametric setting. Furthermore, we investigate on its asymptotic properties, such as weak consistency and asymptotic normalit

Adaptive Density Estimation on the Circle by Nearly-Tight Frames

This work is concerned with the study of asymptotic properties of nonparametric density estimates in the framework of circular data. The estimation procedure here applied is based on wavelet thresholding methods: the wavelets used are the so-called Mexican needlets, which describe a nearly-tight frame on the circle. We study the asymptotic behaviour of the $L^{2}$-risk function for these estimates, in particular its adaptivity, proving that its rate of convergence is nearly optimal.Comment: 30 pages, 3 figure

LASSO estimation for spherical autoregressive processes

The purpose of the present paper is to investigate a class of spherical functional autoregressive processes in order to introduce and study LASSO (Least Absolute Shrinkage and Selection Operator) type estimators for the corresponding autoregressive kernels, defined in the harmonic domain by means of their spectral decompositions. Some crucial properties for these estimators are proved, in particular, consistency and oracle inequalities

Localisation of directional scale-discretised wavelets on the sphere

Scale-discretised wavelets yield a directional wavelet framework on the sphere where a signal can be probed not only in scale and position but also in orientation. Furthermore, a signal can be synthesised from its wavelet coefficients exactly, in theory and practice (to machine precision). Scale-discretised wavelets are closely related to spherical needlets (both were developed independently at about the same time) but relax the axisymmetric property of needlets so that directional signal content can be probed. Needlets have been shown to satisfy important quasi-exponential localisation and asymptotic uncorrelation properties. We show that these properties also hold for directional scale-discretised wavelets on the sphere and derive similar localisation and uncorrelation bounds in both the scalar and spin settings. Scale-discretised wavelets can thus be considered as directional needlets

A new ligament-compatible patient-specific 3D-printed implant and instrumentation for total ankle arthroplasty: from biomechanical studies to clinical cases

Background: Computer navigation and patient-specific instrumentation for total ankle arthroplasty have still to demonstrate their theoretical ability to improve implant positioning and functional outcomes. The purpose of this paper is to present a new and complete total ankle arthroplasty customization process for severe posttraumatic ankle joint arthritis, consisting of patient-specific 3D-printed implant and instrumentation, starting from a ligament-compatible design. Case presentation: The new customization process was proposed in a 57-year-old male patient and involved image analysis, joint modeling, prosthesis design, patient-specific implant and instrumentation development, relevant prototyping, manufacturing, and implantation. Images obtained from a CT scan were processed for a 3D model of the ankle, and the BOX ankle prosthesis (MatOrtho, UK) geometries were customized to best fit the model. Virtual in silico, i.e., at the computer, implantation was performed to optimize positioning of these components. Corresponding patient-specific cutting guides for bone preparation were designed. The obtained models were printed in ABS by additive manufacturing for a final check. Once the planning procedure was approved, the models were sent to final state-of-the-art additive manufacturing (the metal components using cobalt-chromium-molybdenum powders, and the guides using polyamide). The custom-made prosthesis was then implanted using the cutting guides. The design, manufacturing, and implantation procedures were completed successfully and consistently, and final dimensions and location for the implant corresponded with the preoperative plan. Immediate post-op X-rays showed good implant positioning and alignment. After 4 months, clinical scores and functional abilities were excellent. Gait analysis showed satisfactory joint moment at the ankle complex and muscle activation timing within normality. Conclusions: The complete customization process for total ankle arthroplasty provided accurate and reliable implant positioning, with satisfactory short-term clinical outcomes. However, further studies are needed to confirm the potential benefits of this complete customization process. Level of evidence: 5. Case report

Accessible opera : overcoming linguistic and sensorial barriers

The desire to make media available for all has been rapidly accepted and implemented by most European countries. Opera, as one of the many audiovisual representations, also falls under the category of production which needs to be made accessible and this article aims to analyse how opera has gone through a complete transformation to become a cultural event for all, overcoming not only linguistic but also sensorial barriers. The first part of the article analyses the various forms of translation associated with opera and the main challenges they entail. The second presents different systems used to make opera accessible to the sensorially challenged, highlighting their main difficulties. Examples from research carried out at the Barcelona's Liceu opera house are presented to illustrate various modalities, especially audio description. All in all, it is our aim to show how translated-related processes have made it possible to open opera to a wider audience despite some initial reluctance

Adaptive nonparametric regression on spin fiber bundles

AbstractThe construction of adaptive nonparametric procedures by means of wavelet thresholding techniques is now a classical topic in modern mathematical statistics. In this paper, we extend this framework to the analysis of nonparametric regression on sections of spin fiber bundles defined on the sphere. This can be viewed as a regression problem where the function to be estimated takes as its values algebraic curves (for instance, ellipses) rather than scalars, as usual. The problem is motivated by many important astrophysical applications, concerning, for instance, the analysis of the weak gravitational lensing effect, i.e. the distortion effect of gravity on the images of distant galaxies. We propose a thresholding procedure based upon the (mixed) spin needlets construction recently advocated by Geller and Marinucci (2008, 2010) and Geller et al. (2008, 2009), and we investigate their rates of convergence and their adaptive properties over spin Besov balls

Simple proposal for radial 3D needlets

We present here a simple construction of a wavelet system for the three-dimensional ball, which we label radial 3D needlets. The construction envisages a data collection environment in which an observer located at the center of the ball is surrounded by concentric spheres with the same pixelization at different radial distances, for any given resolution. The system is then obtained by weighting the projector operator built on the corresponding set of eigenfunctions and performing a discretization step which turns out to be computationally very convenient. The resulting wavelets can be shown to have very good localization properties in the real and harmonic domain; their implementation is computationally very convenient, and they allow for exact reconstruction as they form a tight frame system. Our theoretical results are supported by an extensive numerical analysis