Il rapporto tra la professione contabile e l'armonizzazione contabile

l’obiettivo di questo lavoro è di meglio comprendere la relazione tra la professione contabile e il processo di regolamentazione contabile, che si sostanzia de facto in un’armonizzazione dei principi contabili internazionali su una base transnazionale. In questo modo, intendo contribuire da una parte alla letteratura sulla professione e dall’altra alla ricerca riguardante il processo di armonizzazione contabile e l’apporto dei vari attori nella sua definizione. Tale rapporto ha inevitabilmente ricadute anche sulla qualità della comunicazione economica finanziaria effettuata dalle aziende e, più in generale, sul sistema economico nel suo complesso

Human activity recognition on smartphones using a multiclass hardware-friendly support vector machine

Activity-Based Computing aims to capture the state of the user and its environment by exploiting heterogeneous sensors in order to provide adaptation to exogenous computing resources. When these sensors are attached to the subject’s body, they permit continuous monitoring of numerous physiological signals. This has appealing use in healthcare applications, e.g. the exploitation of Ambient Intelligence (AmI) in daily activity monitoring for elderly people. In this paper, we present a system for human physical Activity Recognition (AR) using smartphone inertial sensors. As these mobile phones are limited in terms of energy and computing power, we propose a novel hardware-friendly approach for multiclass classification. This method adapts the standard Support Vector Machine (SVM) and exploits fixed-point arithmetic for computational cost reduction. A comparison with the traditional SVM shows a significant improvement in terms of computational costs while maintaining similar accuracy, which can contribute to develop more sustainable systems for AmI.Peer ReviewedPostprint (author's final draft

Human activity recognition on smartphones for mobile context awareness

Activity-Based Computing [1] aims to capture the state of the user and its environment by exploiting heterogeneous sensors in order to provide adaptation to exogenous computing resources. When these sensors are attached to the subject’s body, they permit continuous monitoring of numerous physiological signals. This has appealing use in healthcare applications, e.g. the exploitation of Ambient Intelligence (AmI) in daily activity monitoring for elderly people. In this paper, we present a system for human physical Activity Recognition (AR) using smartphone inertial sensors. As these mobile phones are limited in terms of energy and computing power, we propose a novel hardware-friendly approach for multiclass classification. This method adapts the standard Support Vector Machine (SVM) and exploits fixed-point arithmetic. In addition to the clear computational advantages of fixed-point arithmetic, it is easy to show the regularization effect of the number of bits and then the connections with the Statistical Learning Theory. A comparison with the traditional SVM shows a significant improvement in terms of computational costs while maintaining similar accuracy, which can contribute to develop more sustainable systems for AmI.Peer ReviewedPostprint (published version

Energy efficient smartphone-based activity recognition using fixed-point arithmetic

In this paper we propose a novel energy efficient approach for the recognition of human activities using smartphones as wearable sensing devices, targeting assisted living applications such as remote patient activity monitoring for the disabled and the elderly. The method exploits fixed-point arithmetic to propose a modified multiclass Support Vector Machine (SVM) learning algorithm, allowing to better pre- serve the smartphone battery lifetime with respect to the conventional floating-point based formulation while maintaining comparable system accuracy levels. Experiments show comparative results between this approach and the traditional SVM in terms of recognition performance and battery consumption, highlighting the advantages of the proposed method.Peer ReviewedPostprint (published version

Structural and molecular dynamics investigations of ligand stabilization via secondary binding site interactions in Paenibacillus xylanivorans GH11 xylanase

Glycoside hydrolases (GHs) are essential for plant biomass deconstruction. GH11 family consist of endo-β-1,4-xylanases which hydrolyze xylan, the second most abundant cell wall biopolymer after cellulose, into small bioavailable oligomers. Structural requirements for enzymatic mechanism of xylan hydrolysis is well described for GH11 members. However, over the last years, it has been discovered that some enzymes from GH11 family have a secondary binding sites (SBS), which modulate the enzymes activities, but mechanistic details of the molecular communication between the active site and SBS of the enzymes remain a conundrum. In the present work we structurally characterized GH11 xylanase from Paenibacillus xylanivorans A57 (PxXyn11B), a microorganism of agricultural importance, using protein crystallography and molecular dynamics simulations. The PxXyn11B structure was solved to 2.5 Å resolution and different substrates (xylo-oligosaccharides from X3 to X6), were modelled in its active and SBS sites. Molecular Dynamics (MD) simulations revealed an important role of SBS in the activity and conformational mobility of PxXyn11B, demonstrating that binding of the reaction products to the SBS of the enzyme stabilizes the N-terminal region and, consequently, the active site. Furthermore, MD simulations showed that the longer the ligand, the better is the stabilization within active site, and the positive subsites contribute less to the stabilization of the substrates than the negative ones. These findings provide rationale for the observed enzyme kinetics, shedding light on the conformational modulation of the GH11 enzymes via their SBS mediated by the positive molecular feedback loop which involve the products of the enzymatic reaction.Instituto de BiotecnologíaFil: Briganti, Lorenzo. Universidade de São Paulo. Instituto de Física de São Carlos; BrasilFil: Capetti, Caio. Universidade de São Paulo. Instituto de Física de São Carlos; BrasilFil: Pellegrini, Vanessa O. A. Universidade de São Paulo. Instituto de Física de São Carlos; BrasilFil: Ghio, Silvina. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Ghio, Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Campos, Eleonora. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Agrobiotecnología y Biología Molecular; ArgentinaFil: Campos, Eleonora. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Nascimento, Alessandro S. Universidade de São Paulo. Instituto de Física de São Carlos; BrasilFil: Polikarpov, Igor. Universidade de São Paulo. Instituto de Física de São Carlos; Brasi

Pregnancy and neonatal outcomes of SARS-CoV-2 infection discovered at the time of delivery: a tertiary center experience in North Italy

Objectives: Although the knowledge on SARS-CoV-2 infection in pregnancy has greatly improved, there is still a lack of information on its role in the later stages of gestation. The aim of this study is to investigate whether SARS-CoV-2 discovered at delivery is associated with any obstetric or neonatal complications. Methods: A retrospective case-control study was conducted at Department of Obstetrics, University Hospital Maggiore della Carità, Novara, Italy, from March 2020 to March 2023. Pregnant women admitted were tested for SARS-CoV-2. 168 women resulted positive at the time of delivery; the women were asymptomatic or paucisymptomatic. 170 negative women were selected as controls, selecting, for each SARS-CoV-2 positive patient, the patient who gave birth right before, if negative. Demographic and anamnestic characteristics, pregnancy, labor, and neonatal outcomes were evaluated. Results: SARS-CoV-2 positive patients were more likely to have gestational diabetes (13.7 vs. 5.3 %) and required less frequently intrapartum analgesia (11.3 vs. 27 %) and labor augmentation (7.3 vs. 16.5 %). Post-partum hemorrhage rate was lower (13.7 vs. 22.9 %) and a shorter length of first and second stage of labor occurred. There were no statistically significant differences between the two groups regarding the mode of delivery and neonatal outcomes. Conclusions: SARS-CoV-2 positive patients have shorter labor length and a lower incidence of postpartum hemorrhage. Fewer obstetric interventions, as well as less use of intrapartum analgesia and oxytocin, could explain these findings. Moreover, gestational diabetes could increase susceptibility to infection. SARS-CoV-2 infection discovered at the time of delivery in asymptomatic or paucisymptomatic patients does not appear to increase the rate of cesarean delivery or other obstetric complications, and neonatal outcomes have not worsened

Results from the kaonic hydrogen X-ray measurement at DAFNE and outlook to future experiments

The $\overline{K}N$ system at rest plays a key role for the understanding of strong interaction of hadrons with strangeness involved. The experiment SIDDHARTA used X-ray spectroscopy of kaonic atoms to measure the strong interaction induced shift and width of the ground state. It was the first experiment on kaonic He3 and deuterium ever, kaonic hydrogen was measured with improved precision resulting in \epsilon_{1s} = -283 \pm 36 \mbox{(stat)} \pm 6 \mbox{(syst)} eV and \Gamma_{1s} = 541 \pm 89 \mbox{(stat)} \pm 22 \mbox{(syst)} eV. Additionally a scheme for an improved future experiment on kaonic deuterium is introduced in this contribution