Design, implementation and realization of an integrated platform dedicated to e-public health, for analysing health data and supporting the management control in healthcare companies.

In healthcare, the information is a fundamental aspect and the human body is the major source of every kind of data: the challenge is to benefit from this huge amount of unstructured data by applying technologic solutions, called Big Data Analysis, that allows the management of data and the extraction of information through informatic systems. This thesis aims to introduce a technologic solution made up of two open source platforms: Power BI and Knime Analytics Platform. First, the importance, the role and the processes of business intelligence and machine learning in healthcare will be discussed; secondly, the platforms will be described, particularly enhancing their feasibility and capacities. Then, the clinical specialties, where they have been applied, will be shown by highlighting the international literature that have been produced: neurology, cardiology, oncology, fetal-monitoring and others. An application in the current pandemic situation due to SARS-CoV-2 will be described by using more than 50000 records: a cascade of 3 platforms helping health facilities to deal with the current worldwide pandemic. Finally, the advantages, the disadvantages, the limitations and the future developments in this framework will be discussed while the architectural technologic solution containing a data warehouse, a platform to collect data, two platforms to analyse health and management data and the possible applications will be shown

Grid-graph modeling of emergent neuromorphic dynamics and heterosynaptic plasticity in memristive nanonetworks

Self-assembled memristive nanonetworks composed of many interacting nano objects have been recently exploited for neuromorphic-type data processing and for the implementation of unconventional computing paradigms, such as reservoir computing. In these networks, information processing and computing tasks are performed by exploiting the emergent network behaviour without the need of fine tuning its components. Here, we propose grid-graph modelling of the emergent behaviour of memristive nanonetworks, where the memristive behaviour is decoupled from the particular and detailed behaviour of each network element. In this model, the memristive behavior of each edge is regulated by an analytical potentiation-depression rate balance equation deduced from physical arguments. By comparing modelling and experimental results obtained on nanonetworks based on Ag NWs, the model is shown to be able to emulate the main features of the emergent memristive behaviour and spatio-temporal dynamics of the nanonetwork, including short-term plasticity, paired-pulse facilitation and heterosynaptic plasticity. These results show that the model represents a versatile platform for exploring the implementation of unconventional computing paradigms in nanonetworks

Modeling of Short-Term Synaptic Plasticity Effects in ZnO Nanowire-Based Memristors Using a Potentiation-Depression Rate Balance Equation

This letter deals with short-term plasticity (STP) effects in the conduction characteristics of single crystalline ZnO nanowires, including potentiation, depression and relaxation phenomena. The electrical behavior of the structures is modeled following Chua's approach for memristive systems, i.e. one equation for the electron transport and one equation for the memory state of the device. Linear conduction is assumed in the first case together with a voltage-controlled rate balance equation for the normalized conductance. The devices are subject to electrical stimuli such as ramped and pulsed voltages of both polarities with varying amplitude and frequency. In each case, the proposed model is able to account for the STP effects exhibited by ZnO highlighting its neuromorphic capabilities for bio-inspired circuits. An equivalent circuit representation and the SPICE implementation of the compact model is also provided

In materia implementation strategies of physical reservoir computing with memristive nanonetworks

Physical reservoir computing (RC) represents a computational framework that exploits information-processing capabilities of programmable matter, allowing the realization of energy-efficient neuromorphic hardware with fast learning and low training cost. Despite self-organized memristive networks have been demonstrated as physical reservoir able to extract relevant features from spatiotemporal input signals, multiterminal nanonetworks open the possibility for novel strategies of computing implementation. In this work, we report on implementation strategies of in materia RC with self-assembled memristive networks. Besides showing the spatiotemporal information processing capabilities of self-organized nanowire networks, we show through simulations that the emergent collective dynamics allows unconventional implementations of RC where the same electrodes can be used as both reservoir inputs and outputs. By comparing different implementation strategies on a digit recognition task, simulations show that the unconventional implementation allows a reduction of the hardware complexity without limiting computing capabilities, thus providing new insights for taking full advantage of in materia computing toward a rational design of neuromorphic systems

Multi-objective optimisation of constellation deployment using low-thrust propulsion

This work presents an analysis of the deployment of future constellations using a com-bination of low-thrust propulsion and natural dynamics. Different strategies to realise the transfer from the launcher injection orbit to the constellation operational orbit are investigated. The deployment of the constellation is formulated as a multi-objective optimisation problem that aims at minimising the maximum transfer ΔV, the launch cost and maximise at the same time the pay-off given by the service provided by the constellation. The paperwill consider the case of a typical constellation with 27 satellites in Medium Earth Orbit and the use of only two launchers, one of which can carry a single satellite. It will be demonstrated that some strategies and deployment sequences are dominant and provide the best trade-off between peak transfer ΔV and monetary pay-off

Investigation on the Stabilizing Effect of Titanium in HfO2-Based Resistive Switching Devices With Tungsten Electrode

Resistive switching (RS) devices, also referred to as resistive random access memories (ReRAMs), rely on a working principle based on the change of electrical resistance following proper external electrical stimuli. Since the demonstration of the first resistive memory based on a binary transition metal oxide (TMO) enclosed in a metal–insulator–metal (MIM) structure, this class of devices has been considered a key player for simple and low-cost memories. However, successful large-scale integration with standard complementary metal–oxide–semiconductor (CMOS) technologies still needs systematic investigations. In this work, we examine the beneficial effect titanium has when employed as a buffer layer between CMOS-compatible materials like hafnium dioxide and tungsten. Hindering the tungsten oxidation, Ti provides RS stabilization and allows getting faster responses from the devices. Through an extensive comparative study, the effect of both thickness and composition of Ti-based buffer layers is investigated. The reported results show how titanium can be effectively employed to stabilize and tailor the RS behavior of the devices, and they may open the way to the definition of new design rules for ReRAM–CMOS integration. Moreover, the gradual switching and the response speed tunability observed employing titanium might also extend the domain of interest of these results to brain-inspired computing applications

The relationship between medical ethics and the legal system in Italy: food for thought

Relations between ethics in general – and medical ethics in particular – and legal systems are complex and have been extensively examined in the literature. The topic is important not only for ethicists and jurists, but also for members of the public, who benefit from the services offered by the professions. While the Italian Institute of Health does not claim to propose new avenues for exploration of the relations between ethics and legal systems, it offers some food for thought in the ongoing debate

General principles and practice of the ethics of public health surveillance: comments on the situation in Italy

The “WHO guidelines on ethical issues in public health surveillance” were ublished shortly after the Italian Presidency of the Council of Ministers published a Decree (3rd March, 2017) regarding surveillance systems and registries. The WHO document is a comprehensive framework of international import that forms a compendium of ethical principles to underlie public health surveillance. Although the Italian Decree is in line with the guidelines it contains no reference to mechanisms to ensure ethical surveillance, which instead are recommended in the WHO document. Ethics Committees would appear the most suitable candidates to fill this role

Research on biological materials of human origin. Jurists and scientists face to face

On 3rd October 2016 a convention was held in the Aldo Moro room of the Chamber of Deputies on “Research on biological materials of human origin. Jurists and scientists face to face”.  The convention was organised by the Bioethics Unit of the Istituto Superiore di Sanità (ISS, Italian National Institute of Health) in conjunction with the Italian Academy of the Internet Code (IAIC) and the Fondazione Centro di Iniziativa Giuridica Piero Calamandrei.  The present contribution reports the topics discussed and the key conclusions reached. As a follow-up to the discussion, the scientists, jurists and institutions concerned are resolved to take further steps towards the formulation of operational proposals intended to facilitate research using human biological materials within a framework of precise and strict regulations

Experimental and Modeling Study of Metal–Insulator Interfaces to Control the Electronic Transport in Single Nanowire Memristive Devices

Memristive devices relying on redox-based resistive switching mechanisms represent promising candidates for the development of novel computing paradigms beyond von Neumann architecture. Recent advancements in understanding physicochemical phenomena underlying resistive switching have shed new light on the importance of an appropriate selection of material properties required to optimize the performance of devices. However, despite great attention has been devoted to unveiling the role of doping concentration, impurity type, adsorbed moisture, and catalytic activity at the interfaces, specific studies concerning the effect of the counter electrode in regulating the electronic flow in memristive cells are scarce. In this work, the influence of the metal-insulator Schottky interfaces in electrochemical metallization memory (ECM) memristive cell model systems based on single-crystalline ZnO nanowires (NWs) is investigated following a combined experimental and modeling approach. By comparing and simulating the electrical characteristics of single NW devices with different contact configurations and by considering Ag and Pt electrodes as representative of electrochemically active and inert electrodes, respectively, we highlight the importance of an appropriate choice of electrode materials by taking into account the Schottky barrier height and interface chemistry at the metal-insulator interfaces. In particular, we show that a clever choice of metal-insulator interfaces allows to reshape the hysteretic conduction characteristics of the device and to increase the device performance by tuning its resistance window. These results obtained from single NW-based devices provide new insights into the selection criteria for materials and interfaces in connection with the design of advanced ECM cells