Complex delay dynamics on railway networks from universal laws to realistic modelling

This is the final version. Available from EDP Sciences via the DOI in this record.The datasets supporting the conclusions of this article are included within the article (and its additional files).Railways are a key infrastructure for any modern country. The reliability and resilience of this peculiar transportation system may be challenged by different shocks such as disruptions, strikes and adverse weather conditions. These events compromise the correct functioning of the system and trigger the spreading of delays into the railway network on a daily basis. Despite their importance, a general theoretical understanding of the underlying causes of these disruptions is still lacking. In this work, we analyse the Italian and German railway networks by leveraging on the train schedules and actual delay data retrieved during the year 2015. We use these data to infer simple statistical laws ruling the emergence of localized delays in different areas of the network and we model the spreading of these delays throughout the network by exploiting a framework inspired by epidemic spreading models. Our model offers a fast and easy tool for the preliminary assessment of the effectiveness of traffic handling policies, and of the railway network criticalities.John Templeton FoundationAustrian Research Promotion Agency FFGNewton International FellowshipThe Royal SocietyThe British AcademyAcademy of Medical Science

Clinical and genetic characterization of patients with hypertrophic cardiomyopathy and right atrial enlargement

AIMS: Prevalence and clinical significance of right atrial enlargement (RAE) has been poorly characterized in hypertrophic cardiomyopathy. METHODS: One hundred and sixty consecutive patients with hypertrophic cardiomyopathy (35.5 ± 20 years; 64% men) were studied. They underwent clinical examination, standard ECG, M-mode, 2D and Doppler echocardiography, stress test and ECG Holter monitoring. Major adverse cardiac events were considered: cardiac death (sudden death, heart failure death); cardiac transplant; resuscitated cardiac arrest or appropriate implantable cardioverter defibrillator discharge. Genetic analysis of eight sarcomeric genes was performed using Sanger sequencing. RESULTS: RAE was observed in 22 patients (14%), associated with left atrial enlargement in all cases. Patients with RAE were likely to have restrictive mitral pattern (P < 0.001) and had higher New York Heart Association (P < 0.001), N-terminal prohormone of brain natriuretic peptide (P < 0.001), left atrial volume index (P < 0.001), lateral (P = 0.04) and septal (P = 0.002) E/e', systolic pulmonary artery pressure (P < 0.001) and lower ejection fraction (all P < 0.001). On cardiopulmonary exercise testing, peak VO2 was lower and VE/VCO2 higher in patients with RAE (P < 0.001). During a mean follow-up of 4 ± 2.1 years, 30 major adverse cardiac events in 24 patients (15%) were observed. Cox proportional hazards regression analysis identified RAE as an independent predictor of major adverse cardiac events (odds ratio = 2.6; confidence interval 1.5-4.6; P = 0.001). In patients with RAE who were genetically tested, there was a higher prevalence of sarcomeric gene mutations (68%), double mutations (16%) and troponin T mutations (21%). CONCLUSION: RAE is present in a small subset of patients with hypertrophic cardiomyopathy, and largely reflects increased pulmonary pressures because of severe diastolic and/or systolic left ventricular dysfunction. Patients with RAE had a higher prevalence of sarcomeric gene mutations, troponin T mutations and complex genotypes. In conclusion, RAE may serve as a very useful marker of disease progression and adverse outcome in patients with sarcomeric hypertrophic cardiomyopathy

Left atrial volume during stress is associated with increased risk of arrhythmias in patients with hypertrophic cardiomyopathy

Introduction: In patients affected by hypertrophic cardiomyopathy (HCM), left atrial volume index (LAVi) is associated with an increased risk of tachyarrhythmias and major clinical events. To date, the clinical meaning of LAVi measured during exercise (stress LAVi [sLAVi]) has not yet been investigated in HCM. This study sought to evaluate the correlation between LAVi/sLAVi and clinical outcome (risk of arrhythmias and heart failure [HF]) in patients with HCM. Methods and Results: We enrolled a total of 51 consecutive patients with HCM (39 men; mean age: 39.41 ± 17.9 years) who underwent standard and stress echocardiography, following a common protocol. During follow-up (median follow-up was 1.82 years), the following composite endpoints were collected: ARRHYT endpoint (atrial fibrillation, paroxysmal supraventricular tachycardia, nonsustained ventricular tachycardia (VT), sustained VT, ventricular fibrillation, syncope of likely cardiogenic nature, and sudden cardiac death) and HF endpoint (worsening of functional class and left ventricular ejection fraction, hospitalization, and death for end-stage HF). Eight patients were lost at follow-up. ARRHYT endpoint occurred in 13 (30.2%) patients (8, 18.6%, supraventricular and 10, 23.2%, ventricular arrhythmias), whereas HF endpoint occurred in 5 (11.6%) patients. sLAVi (mean value of 31.16 ± 10.15 mL/m2) performed better than rLAVi as a predictor of ARRHYT endpoint (Akaike Information Criterion: 48.37 vs. 50.37, if dichotomized according to the median values). A sLAVi value of 30 mL/m2 showed a predictive accuracy of 72.1% (C-statistics of 0.7346), with a high negative predictive value (87.5%). Conclusion: These findings encourage future studies on sLAVi, as a potential predictor of arrhythmias and adverse outcome in patients with HCM

Prevalence and clinical significance of red flags in patients with hypertrophic cardiomyopathy

Introduction: We sought to determine prevalence and predictive accuracy of clinical markers (red flags, RF), known to be associated with specific systemic disease in a consecutive cohort of patients with hypertrophic cardiomyopathy (HCM). / Methods: We studied 129 consecutive patients (23.7 ± 20.9 years, range 0–74 years; male/female 68%/32%). Pre-specified RF were categorized into five domains: family history; signs/symptoms; electrocardiography; imaging; and laboratory. Sensitivity (Se), specificity (Sp), negative predictive value (NPV), positive predictive value (PPV), and predictive accuracy of RF were analyzed in the genotyped population. / Results: In the overall cohort of 129 patients, 169 RF were identified in 62 patients (48%). Prevalence of RF was higher in infants (78%) and in adults >55 years old (58%). Following targeted genetic and clinical evaluation, 94 patients (74%) had a definite diagnosis (sarcomeric HCM or specific causes of HCM). We observed 14 RF in 13 patients (21%) with sarcomeric gene disease, 129 RF in 34 patients (97%) with other specific causes of HCM, and 26 RF in 15 patients (45%) with idiopathic HCM (p  55yo. Se, Sp, PPV, NPV and PA of RF were 97%, 70%, 55%, 98% and 77%, respectively. Single and clinical combination of RF (clusters) had an high specificity, NPV and predictive accuracy for the specific etiologies (syndromes/metabolic/infiltrative disorders associated with HCM). / Conclusions: An extensive diagnostic work up, focused on analysis of specific diagnostic RF in patients with unexplained LVH facilitates a clinical diagnosis in 74% of patients with HCM

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning

Using Project-Based-Learning in a mobile application development course-An experience report

In this paper, we report the experience gained in a Mobile Application Development course. We involved students in Computer Science at the University of Salerno, who in teams had to conduct a project. The goal of this project was to design and develop applications (or simply app) for Android-based devices. The adopted teaching approach was based on Project-Based-Learning and enhanced collaboration and competition. Collaboration took place among members of the same team (intra-team), while competition among different teams of students (extra-team). To allow intra-team collaboration, students used GitHub as Computer-Supported-Collaborative-Learning tool. It provided support for implicit and explicit communication among members in each team and for distributed revision control and management of software artifacts (e.g., source code and requirements models). Developed apps underwent a final public competition prized by IT managers of national and international software companies. This is how we implemented extra-team competition. IT managers expressed a positive judgment on both students׳ competition and developed apps. Also, students provided very good feedback on used teaching approach and support GitHub provided