An analytical step-by-step procedure to derive the flexural response of RC sections in compression

This paper proposes an analysis procedure able to determine the flexural response of rectangular symmetrically reinforced concrete sections subjected to axial load and uniaxial bending. With respect to the usual numerical approaches, based on the fibre decomposition method, this procedure is based on the use of analytical expressions of the contributions to the equilibrium given by the longitudinal reinforcement and the concrete region in compression, which depend on the neutral axis depth and the curvature at each analysis step. The formulation is developed in dimensionless terms, after a preliminary definition of the geometrical and mechanical parameters involved, so that the results are valid for classes of RC sections. The constitutive laws of the materials include confinement effect on the concrete and postyielding behaviour of the steel reinforcement, which can be assumed to be softening behaviour for buckled reinforcing bars. The strength and curvature domains at the first yielding of the reinforcement in tension and at the ultimate state are derived in the form of analytical curves depending on the compression level; therefore, the role of a single parameter on the shape of these curves can easily be deduced. The procedure is validated by comparing some results with those numerically obtained by other authors. © 2013 Piero Colajanni et al

A Review of Current Research on the Use of Geopolymer Recycled Aggregate Concrete for Structural Members

Geopolymer cement (GPC) is a sustainable alternative to ordinary Portland cement (OPC) that considerably cuts the emission of carbon dioxide linked to the building of concrete structures. Over the last few decades, while a large number of papers have been written concerning the use of GPC with natural aggregates and OPC with recycled aggregates, few papers have been devoted to investigating the use of Geopolymer Recycled Aggregate Concrete (GRAC) in structural members. Most of them show more interest in the mechanical strength of the material, rather than the structural behavior of RC members. This review critically compiles the present and past research on the behavior of structural members cast with different types and compositions of GRAC. The focus is on the few research studies investigating the structural behavior of GRAC elements, with an analysis of the load-bearing capacity, the load-deflection mechanism, shear behavior, tensile and flexural strength, and ductility of GRAC structural members. This review aims to indicate the research and experimental tests needed in the future for characterizing the behavior of structural members made up of GRAC

PBO textile embedded in FRCM for confinement of r.c. columns

Results of experimental tests on two reinforced concrete columns confined with PBO-FRCM jacketing subject to axial load and bending moments are presented, showing the effectiveness of the confinement system. Comparison of test results against theoretical results derived by a fiber model stress the ability of the confinement system to enhance both strength and deformation capacity of the confined concret

The digital girls response to pandemic: Impacts of in presence and online extracurricular activities on girls future academic choices

In the last few years, several initiatives based on extracurricular activities have been organized in many countries around the world, with the aim to reduce the digital gender gap in STEM (Science, Technology, Engineering, Math) fields. Among them, the Digital Girls summer camp, organized every year since 2014 by two Italian universities with the aim to attract female students to ICT (Information and Communication Technologies) disciplines, represents quite a unique initiative for its characteristics of long-duration (3–4 entire weeks) and complete gratuitousness for the participants. The COVID-19 emergency imposed severe changes to such activities, that had to be modified and carried out in the online mode as a consequence of social distancing. However, on one hand, the general lack of high-quality evaluations of these initiatives hinders the possibility to understand the actual impact of extracurricular activities on the future academic choices of the participants. On the other hand, the availability of data collected over different editions of Digital Girls has allowed us to analyze the summer camp impact and to evaluate the pros and cons of in-presence and online activities. The main contribution of this paper is twofold. First, we present an overview of existing experiences, at the national (Italian) and international levels, to increase female participation in integrated STEM and ICT fields. Second, we analyze how summer camp participation can influence girls’ future academic choices, with specific attention to ICT-related disciplines. In particular, the collection of a significant amount of data through anonymous surveys conducted before and after the camp activities over the two editions allowed us to evidence the different impacts of in-presence and online extracurricular activities

FRAMH: A Federated Learning Risk-Based Authorization Middleware for Healthcare

Modern healthcare systems operate in highly dy- namic environments requiring adaptable access control mecha- nisms. Access to sensitive data and medical equipment should be granted or denied according to the current health situation of the patient. To handle the need for adaptable access control of healthcare scenarios, we propose a novel model that allows dynamic access control decisions based on the context character- izing the source, type of access request, patient, and estimated risk corresponding to the conditions of the patient. Estimating patient status risk requires analyzing vital physiological data whose availability is growing thanks to the widespread diffusion of the Internet of Medical Things (IoMT) devices. Inferring the patient health status risk through Machine Learning (ML) techniques is possible, but to achieve better accuracy, the training phase requires the aggregation of vast amounts of data from different sources. This aggregation could be difficult or even impossible due to organization regulations and privacy laws. To address these issues, this paper proposes a novel Federated Learning Risk-based Authorization Middleware for Healthcare (FRAMH) that supports risk-based access control to deal with changing and unforeseen medical situations. Our solution infers the risk of health status through a federated learning (FL) approach enriched with blockchain to avoid the weaknesses of centralized servers. The implemented prototype and a large set of experimental results demonstrate the advantages of FL in estimating the risk in healthcare scenarios. Through this approach, even a medical institution with a limited dataset can achieve a satisfying risk estimation and efficient access control enforcement

A Framework for Automating Security Assessments with Deductive Reasoning

Proper testing of hardware and software infrastructure and applications has become mandatory. To this purpose, security researchers and software companies have released a plethora of domain specific tools, libraries and frameworks that assist human operators (penetration testers, red teamers, bug hunters) in finding and exploiting specific vulnerabilities, and orchestrating the activities of a security assessment. Most tools also require minor reconfigurations in order to operate properly with isomorphic systems, characterized by the same exploitation path even in presence of different configurations. In this paper we present a human-assisted framework that tries to overcome the aforementioned limitations. Our proposal is based on a Prolog-based expert system with facts and deductive rules that allow to infer new facts from existing ones. Rules are bound to actions whose results are fed back into the knowledge base as further facts. In this way, a security assessment is treated like a theorem that has to be proven. We have built an initial prototype and evaluated it in different security assessments of increasing complexity (jeopardy and boot-to-root machines). Our preliminary results show that the proposed approach can address the following challenges; (a) reaching non-standard goals (which would be missed by most tools and frameworks); (b) solving isomorphic systems without the need for reconfiguration; (c) identifying vulnerabilities from chained weaknesses and exposures

Practical Evaluation of Graph Neural Networks in Network Intrusion Detection

The most recent proposals of Machine and Deep Learning algorithms for Network Intrusion Detection Systems (NIDS) leverage Graph Neural Networks (GNN). These techniques create a graph representation of network traffic and analyze both network topology and netflow features to produce more accurate predictions. Although prior research shows promising results, they are biased by evaluation methodologies that are incompatible with real-world online intrusion detection. We are the first to identify these issues and to evaluate the performance of a state-of-the-art GNN-NIDS under real-world constraints. The experiments demonstrate that the literature overestimates the detection performance of GNN-based NIDS. Our results analyze and discuss the trade-off between detection delay and detection performance for different types of attacks, thus paving the way for the practical deployment of GNN-based NIDS

Strength and ductility of confined concrete columns under axial load and biaxial bending

The behaviour of prismatic reinforced concrete columns under increasing eccentric compression load was experimentally investigated and analytically modelled. Columns with distributed longitudinal reinforcement and closely spaced transverse reinforcement were tested up to failure, considering different values and directions of eccentricity. Preliminary tests were carried out under concentric compression in order to validate the choice of the stress-strain laws adopted for the confined concrete and the longitudinal steel bars in compression. In the paper, closed form expressions able to approximate the experimental results in the case of uniaxial bending are presented. Finally, a fibre numerical model is utilized for the cases of biaxial bending. The results show the reliability of the analytical models and suggest further studies to relate analytically the components of ultimate bending moment and curvature, in the cases of biaxial bending, to the values corresponding to two separate cases of uniaxial bending under the same level of compression.The behaviour of prismatic reinforced concrete columns under increasing eccentric compression load was experimentally investigated and analytically modelled. Columns with distributed longitudinal reinforcement and closely spaced transverse reinforcement were tested up to failure, considering different values and directions of eccentricity. Preliminary tests were carried out under concentric compression in order to validate the choice of the stress-strain laws adopted for the confined concrete and the longitudinal steel bars in compression. In the paper, closed form expressions able to approximate the experimental results in the case of uniaxial bending are presented. Finally, a fibre numerical model is utilized for the cases of biaxial bending. The results show the reliability of the analytical models and suggest further studies to relate analytically the components of ultimate bending moment and curvature, in the cases of biaxial bending, to the values corresponding to two separate cases of uniaxial bending under the same level of compression

Cultural Expertise and Socio-legal Studies: Introduction

International audienceEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services. Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation

The future of Cybersecurity in Italy: Strategic focus area

This volume has been created as a continuation of the previous one, with the aim of outlining a set of focus areas and actions that the Italian Nation research community considers essential. The book touches many aspects of cyber security, ranging from the definition of the infrastructure and controls needed to organize cyberdefence to the actions and technologies to be developed to be better protected, from the identification of the main technologies to be defended to the proposal of a set of horizontal actions for training, awareness raising, and risk management