Evaluation of the masonry and timber structures of San Francisco Church in Santiago de Cuba through nondestructive diagnostic methods

Recently, due to a renewed interest in the religious architectural heritage of the Caribbean island of Cuba, some important interventions for the restoration and reinforcement of the colonial churches of the island were carried out. The authors, collaborating with the Archdiocese of Santiago de Cuba in a project concerning the protection of Cuban churches, applied some nondestructive and noninvasive destructive tests for an in-depth study of the main characteristics of those structures. The diagnostic method, developed mainly for the historical buildings or monuments of Europe and North America, was used to study some peculiarities of the building construction traditions of this area. The proposed techniques revealed the existence of several original solutions, for example, defenses for seismic mitigation, developed to resist the earthquakes that frequently affect the area

La storia di Firenze tra tarda antichità e medioevo. Nuovi dati dallo scavo di via de’ Castellani

Il nostro recente progetto è finalizzato alla conoscenza della risorsa archeologica di Firenze. In particolare la nostra attenzione si è concentrata sugli aspetti legati alle trasformazioni della città tra tarda antichità e medioevo: i cambiamenti nell’economia cittadina, le forme urbanistiche che Florentia assunse nella lunga transizione tra III e vIII secolo, la riurbanizzazione bassomedievale e le ancor più significative vicende che portarono alla formazione della città del Rinascimento. L’obiettivo consiste nel riscrivere, sulla base di nuove fonti, processi ancora non messi a fuoco, contribuendo a ridefinire lo sviluppo contemporaneo della città sulla base dei segni materiali della storia

Block size estimation for data partitioning in HPC applications using machine learning techniques

The extensive use of HPC infrastructures and frameworks for running data-intensive applications has led to a growing interest in data partitioning techniques and strategies. In fact, finding an effective partitioning, i.e. a suitable size for data blocks, is a key strategy to speed-up parallel data-intensive applications and increase scalability. This paper describes a methodology for data block size estimation in HPC applications, which relies on supervised machine learning techniques. The implementation of the proposed methodology was evaluated using as a testbed dislib, a distributed computing library highly focused on machine learning algorithms built on top of the PyCOMPSs framework. We assessed the effectiveness of our solution through an extensive experimental evaluation considering different algorithms, datasets, and infrastructures, including the MareNostrum 4 supercomputer. The results we obtained show that the methodology is able to efficiently determine a suitable way to split a given dataset, thus enabling the efficient execution of data-parallel applications in high performance environments

Seroprevalence of SARS-CoV-2–Specific Antibodies in Cancer Patients Undergoing Active Systemic Treatment: A Single-Center Experience from the Marche Region, Italy

none13noSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in cancer patients may vary widely dependent on the geographic area and this has significant implications for oncological care. The aim of this observational, prospective study was to assess the seroprevalence of SARS-CoV-2 IgM/IgG antibodies in solid cancer patients referred to the academic institution of the Marche Region, Italy, between 1 July and 26 October 2020 and to determine the accuracy of the rapid serological test. After performing 3767 GCCOV-402a rapid serological tests on a total of 949 patients, seroconversion was initially observed in 13 patients (1.4%). Ten (77% of the total positive) were IgG-positive, 1 (8%) were IgM-positive and 2 (15%) IgM-positive/IgG-positive. However, only 7 out of 13 were confirmed as positive at the reference serological test (true positives), thus seroprevalence after cross-checking was 0.7%. No false negatives were reported. The kappa value of the consistency analysis was 0.71. Due to rapid serological test high false positive rate, its role in assessing seroconversion rate is limited, and the standard serological tests should remain the gold standard. However, as rapid test negative predictive value is high, GCCOV-402a may instead be useful to monitor patient immunity over time, thus helping to assist ongoing vaccination programsopenCantini, Luca; Bastianelli, Lucia; Lupi, Alessio; Pinterpe, Giada; Pecci, Federica; Belletti, Giovanni; Stoico, Rosa; Vitarelli, Francesca; Moretti, Marco; Onori, Nicoletta; Giampieri, Riccardo; Rocchi, Marco Bruno Luigi; Berardi, RossanaCantini, Luca; Bastianelli, Lucia; Lupi, Alessio; Pinterpe, Giada; Pecci, Federica; Belletti, Giovanni; Stoico, Rosa; Vitarelli, Francesca; Moretti, Marco; Onori, Nicoletta; Giampieri, Riccardo; Rocchi, Marco Bruno Luigi; Berardi, Rossan

SARS-CoV-2 omicron (B.1.1.529)-related COVID-19 sequelae in vaccinated and unvaccinated patients with cancer: results from the OnCovid registry

Background COVID-19 sequelae can affect about 15% of patients with cancer who survive the acute phase of SARS-CoV-2 infection and can substantially impair their survival and continuity of oncological care. We aimed to investigate whether previous immunisation affects long-term sequelae in the context of evolving variants of concern of SARS-CoV-2. Methods OnCovid is an active registry that includes patients aged 18 years or older from 37 institutions across Belgium, France, Germany, Italy, Spain, and the UK with a laboratory-confirmed diagnosis of COVID-19 and a history of solid or haematological malignancy, either active or in remission, followed up from COVID-19 diagnosis until death. We evaluated the prevalence of COVID-19 sequelae in patients who survived COVID-19 and underwent a formal clinical reassessment, categorising infection according to the date of diagnosis as the omicron (B.1.1.529) phase from Dec 15, 2021, to Jan 31, 2022; the alpha (B.1.1.7)-delta (B.1.617.2) phase from Dec 1, 2020, to Dec 14, 2021; and the pre-vaccination phase from Feb 27 to Nov 30, 2020. The prevalence of overall COVID-19 sequelae was compared according to SARS-CoV-2 immunisation status and in relation to post-COVID-19 survival and resumption of systemic anticancer therapy. This study is registered with ClinicalTrials.gov, NCT04393974. Findings At the follow-up update on June 20, 2022, 1909 eligible patients, evaluated after a median of 39 days (IQR 24-68) from COVID-19 diagnosis, were included (964 [ 50 center dot 7%] of 1902 patients with sex data were female and 938 [49 center dot 3%] were male). Overall, 317 (16 center dot 6%; 95% CI 14 center dot 8-18 center dot 5) of 1909 patients had at least one sequela from COVID-19 at the first oncological reassessment. The prevalence of COVID-19 sequelae was highest in the prevaccination phase (191 [19 center dot 1%; 95% CI 16 center dot 4-22 center dot 0] of 1000 patients). The prevalence was similar in the alpha-delta phase (110 [16 center dot 8%; 13 center dot 8- 20 center dot 3] of 653 patients, p=0 center dot 24), but significantly lower in the omicron phase (16 [6 center dot 2%; 3 center dot 5-10 center dot 2] of 256 patients, p<0 center dot 0001). In the alpha- delta phase, 84 (18 center dot 3%; 95% CI 14 center dot 6-22 center dot 7) of 458 unvaccinated patients and three (9 center dot 4%; 1 center dot 9- 27 center dot 3) of 32 unvaccinated patients in the omicron phase had sequelae. Patients who received a booster and those who received two vaccine doses had a significantly lower prevalence of overall COVID-19 sequelae than unvaccinated or partially vaccinated patients (ten [7 center dot 4%; 95% CI 3 center dot 5-13 center dot 5] of 136 boosted patients, 18 [9 center dot 8%; 5 center dot 8-15 center dot 5] of 183 patients who had two vaccine doses vs 277 [ 18 center dot 5%; 16 center dot 5-20 center dot 9] of 1489 unvaccinated patients, p=0 center dot 0001), respiratory sequelae (six [4 center dot 4%; 1 center dot 6-9 center dot 6], 11 [6 center dot 0%; 3 center dot 0-10 center dot 7] vs 148 [9 center dot 9%; 8 center dot 4- 11 center dot 6], p= 0 center dot 030), and prolonged fatigue (three [2 center dot 2%; 0 center dot 1-6 center dot 4], ten [5 center dot 4%; 2 center dot 6-10 center dot 0] vs 115 [7 center dot 7%; 6 center dot 3-9 center dot 3], p=0 center dot 037)

Analyzing Political Polarization on Social Media by Deleting Bot Spamming

Social media platforms are part of everyday life, allowing the interconnection of people around the world in large discussion groups relating to every topic, including important social or political issues. Therefore, social media have become a valuable source of information-rich data, commonly referred to as Social Big Data, effectively exploitable to study the behavior of people, their opinions, moods, interests and activities. However, these powerful communication platforms can be also used to manipulate conversation, polluting online content and altering the popularity of users, through spamming activities and misinformation spreading. Recent studies have shown the use on social media of automatic entities, defined as social bots, that appear as legitimate users by imitating human behavior aimed at influencing discussions of any kind, including political issues. In this paper we present a new methodology, namely TIMBRE (Time-aware opInion Mining via Bot REmoval), aimed at discovering the polarity of social media users during election campaigns characterized by the rivalry of political factions. This methodology is temporally aware and relies on a keyword-based classification of posts and users. Moreover, it recognizes and filters out data produced by social media bots, which aim to alter public opinion about political candidates, thus avoiding heavily biased information. The proposed methodology has been applied to a case study that analyzes the polarization of a large number of Twitter users during the 2016 US presidential election. The achieved results show the benefits brought by both removing bots and taking into account temporal aspects in the forecasting process, revealing the high accuracy and effectiveness of the proposed approach. Finally, we investigated how the presence of social bots may affect political discussion by studying the 2016 US presidential election. Specifically, we analyzed the main differences between human and artificial political support, estimating also the influence of social bots on legitimate users

Tarsie in marmo e serpentino dallo scavo della pieve di San Genesio (San Miniato, Pisa)

Nel contributo sono presentate le tarsie in marmo e serpentino rinvenute nello scavo della pieve di San Genesio (San Miniato-Pi), contestualizzate rispetto alla stratigrafia archeologica per meglio definirne funzione e cronologia (seconda metà XII-inizio XIII secolo). Un parte è dedicata anche alle tecniche di esecuzione dei manufatti analizzati