Two methodological approaches to assess the seismic vulnerability of masonry bridges

This work describes the seismic vulnerability assessment of a railway masonry arch bridge. Its conservation state is initially investigated by means of a thorough field and laboratory test campaign, comprising destructive and non-destructive tests. Two different methods are used to evaluate the bridge seismic vulnerability. The first method adopts a deterministic approach and corresponds to a single non-linear static analysis, performed as described in the Eurocodes. The second method employs a probabilistic approach and considers the variability of the involved mechanical parameters (structure geometry and properties of the building materials) and seismic parameters (intensity of the action and site conditions). This method associates the probabilistic values of ground acceleration exceedance to the estimated seismic vulnerability. This is shown by means of fragility curves, which allow to take into consideration the uncertainty of the various components involved in the definition of the seismic vulnerability and display the seismic damage scenarios. Currently no code requires to perform this calculation procedure. In addition, this work compares the values of masonry mechanical properties specified in the Eurocodes with those obtained in an extensive investigation campaign involving more than one hundred masonry bridges. Compressive strength and longitudinal elasticity modulus are the relevant mechanical parameters investigated. The outcomes of this research can contribute to the development of a more efficient maintenance system of the masonry bridges belonging to the railway network. This has an important role when it comes to establishing the priority order of assets intervention. Keywords: Railway masonry arch bridge, Bridge maintenance and conservation, Masonry mechanical parameters, Non-linear static analysis, Seismic fragility, Finite element analysi

Results of an A109 simulation validation and handling qualities study

The results for the validation of a mathematical model of the Agusta A109 helicopter, and subsequent use of the model as the baseline for a handling qualities study of cockpit centerstick requirements, are described. The technical approach included flight test, non-realtime analysis, and realtime piloted simulation. Results of the validation illustrate a time- and frequency-domain approach to the model and simulator issues. The final A109 model correlates well with the actual aircraft with the Stability Augmentation System (SAS) engaged, but is unacceptable without the SAS because of instability and response coupling at low speeds. Results of the centerstick study support the current U.S. Army handling qualities requirements for centerstick characteristics

A Survey Dataset Evaluating Perceptions of Civil Engineering Students about Building Information Modelling (BIM)

The implementation of Building Information Modelling (BIM) technologies has become increasingly central in the design, construction and maintenance of both civil structures and infrastructures. As more and more software houses develop new BIM software solutions and a wide range of private and public stakeholders employ them, several educational institutes across the globe strive to expand their teaching portfolio to encompass learning and teaching of BIM. This dataset deals with the perceptions expressed by all the civil engineering undergraduate students who attended an academic course specifically about BIM at University of Stavanger (UiS), Norway, during the second semester 2022. The survey was divided into five parts and collected information regarding as many overarching aspects: socio-demographic data, perceptions about BIM before and after course attendance, satisfaction about the academic course and the way it was conducted. Considering the very moderate sample size (28 students) and potential biases due to the specific context of the University of Stavanger, the dataset can provide a useful insight into teaching approaches and future curriculum development, rather than indicating major and generalized trends in BIM education. As the questionnaire responses shed light on the feedbacks and perceptions expressed by university students dealing with BIM for their first time, the formed dataset can offer a straightforward appreciation of students’ cognitive behaviour in BIM education.publishedVersio

Análisis de interrelación entre obesidad, c1q/tumour necrosis factor-related protein-1 y 3 y la progresión de la enfermedad renal crónica

Tesis Doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina, Departamento de Medicina. Fecha de Lectura: 04-12-202

Functional assessment of bidirectional cortical and peripheral neural control on heartbeat dynamics: A brain-heart study on thermal stress

The study of functional Brain-Heart Interplay (BHI) from non-invasive recordings has gained much interest in recent years. Previous endeavors aimed at understanding how the two dynamical systems exchange information, providing novel holistic biomarkers and important insights on essential cognitive aspects and neural system functioning. However, the interplay between cardiac sympathovagal and cortical oscillations still has much room for further investigation. In this study, we introduce a new computational framework for a functional BHI assessment, namely the Sympatho-Vagal Synthetic Data Generation Model, combining cortical (electroencephalography, EEG) and peripheral (cardiac sympathovagal) neural dynamics. The causal, bidirectional neural control on heartbeat dynamics was quantified on data gathered from 26 human volunteers undergoing a cold-pressor test. Results show that thermal stress induces heart-to-brain functional interplay sustained by EEG oscillations in the delta and gamma bands, primarily originating from sympathetic activity, whereas brain-to-heart interplay originates over central brain regions through sympathovagal control. The proposed methodology provides a viable computational tool for the functional assessment of the causal interplay between cortical and cardiac neural control

Reliability of Calculation of Dynamic Modulus for Asphalt Mixtures Using Different Master Curve Models and Shift Factor Equations

To develop a mechanistic-empirical pavement design system for Norwegian conditions, this paper evaluates the influence of the adoption of different models and shifting techniques on the determination of dynamic modulus master curves of asphalt mixtures. Two asphalt mixture types commonly used in Norway, namely Asphalt Concrete (AC) and Stone Mastic Asphalt (SMA) containing neat bitumen and polymer-modified bitumen, were prepared by the roller compactor, and their dynamic moduli were determined by the cyclic indirect tensile test. The dynamic modulus master curves were constructed using the standard logistic sigmoidal model, a generalized logistic sigmoidal model and the Christensen–Anderson–Marasteanu model. The shifting techniques consisted of log-linear, quadratic polynomial function, Arrhenius, William–Landel–Ferry and Kaelble methods. The absolute error, normalised square error and goodness-of-fit statistics encompassing standard error ratio and coefficient of determination were used to appraise the models and shifting methods. The results showed that the standard logistic sigmoidal model and the Williams–Landel–Ferry equation had the most suitable fits for the specimens tested. The asphalt mixtures containing neat bitumen had a better fit than the ones containing polymer-modified bitumen. The Kaelble equation and log-linear equation led to similar results. These findings provide a relevant recommendation for the mechanistic-empirical pavement design system.publishedVersio

A survey dataset to evaluate the changes in mobility and transportation due to COVID-19 travel restrictions in Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa, United States

COVID-19 pandemic has heavily impacted the global community. To curb the viral transmission, travel restrictions have been enforced across the world. The dataset documents the mobility disruptions and the modal shifts that have occurred as a consequence of the restrictive measures implemented in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online questionnaire was distributed during the period from the 11st to the 31st of May 2020, with a total of 9 394 respondents. The first part of the survey has characterized the frequency of use of all transport modes before and during the enforcement of the restrictions, while the second part of the survey has dealt with perceived risks of contracting COVID-19 from different transport modes and perceived effectiveness of travel mitigation measures. Overall, the dataset (stored in a repository publicly available) can be conveniently used to quantify and understand the modal shifts and people's cognitive behavior towards travel due to COVID-19. The collected responses can be further analysed by considering other demographic and socioeconomic covariates. © 2020 The Author(s). *Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Louisa Lam” is provided in this record

An Environmental Resource within the Job Demands-Resources Model: The Mediating Role of Self-Efficacy between Properties of the Learning Environment and Academic Engagement

The characteristics of learning environments are relevant for promoting academic engagement and learning achievement. Thus, this study seeks to identify whether perceived characteristics of the learning environment, and specifically, the sub-dimensions of Perceived Restorativeness (compatibility, being away, extent, fascination), can promote academic Engagement and self-efficacy using the Job Demands-Resources Model as the underlying conceptual framework. Further, we tested the mediating effect of self-efficacy on the relationship between Perceived Restorativeness and academic engagement. Data were collected from a sample of 188 Italian university students. Hierarchical multivariate regression analysis indicated that a restorative quality of the learning environment (i.e., compatibility and fascination) was positively correlated with academic engagement, but that there was a non-significant relationship between being Away and academic engagement and between extent and academic engagement. Regression analyses showed significant indirect effects of compatibility and extent through students’ self-Efficacy. Further, self-efficacy was a complete mediator between extent and academic engagement. Furthermore, self-efficacy was found to play a partially mediating role between compatibility and academic engagement. The results of this study provide important information that students, teachers and designers should pay attention to levels of restorative quality in the environment for improving engagement and self-efficacy

Impact of COVID-19 pandemic on mobility in ten countries and associated perceived risk for all transport modes

The restrictive measures implemented in response to the COVID-19 pandemic have triggered sudden massive changes to travel behaviors of people all around the world. This study examines the individual mobility patterns for all transport modes (walk, bicycle, motorcycle, car driven alone, car driven in company, bus, subway, tram, train, airplane) before and during the restrictions adopted in ten countries on six continents: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. This cross-country study also aims at understanding the predictors of protective behaviors related to the transport sector and COVID-19. Findings hinge upon an online survey conducted in May 2020 (N = 9,394). The empirical results quantify tremendous disruptions for both commuting and non-commuting travels, highlighting substantial reductions in the frequency of all types of trips and use of all modes. In terms of potential virus spread, airplanes and buses are perceived to be the riskiest transport modes, while avoidance of public transport is consistently found across the countries. According to the Protection Motivation Theory, the study sheds new light on the fact that two indicators, namely income inequality, expressed as Gini index, and the reported number of deaths due to COVID-19 per 100,000 inhabitants, aggravate respondents’ perceptions. This research indicates that socio-economic inequality and morbidity are not only related to actual health risks, as well documented in the relevant literature, but also to the perceived risks. These findings document the global impact of the COVID-19 crisis as well as provide guidance for transportation practitioners in developing future strategies. © 2021 Barbieri et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. *Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Louisa Lam” is provided in this record*

Measures of fine tuning

Fine-tuning criteria are frequently used to place upper limits on the masses of superpartners in supersymmetric extensions of the standard model. However, commonly used prescriptions for quantifying naturalness have some important shortcomings. Motivated by this, we propose new criteria for quantifying fine tuning that can be used to place upper limits on superpartner masses with greater fidelity. In addition, our analysis attempts to make explicit the assumptions implicit in quantifications of naturalness. We apply our criteria to the minimal supersymmetric extension of the standard model, and we find that the scale of supersymmetry breaking can be larger than previous methods indicate.Comment: 15 pages, LaTex, 5 figures uuencoded, gz-compressed file. Minor revisions bring the archived manuscript into agreement with published versio