Consorzio di Bioingegneria e Informatica Medica

During the summer of 1791, in anticipation of the opening of a midwifery school in Pavia, near Milan, Vincenzo Malacarne requested a full-sized obstetrical machine and a number of additional wax anatomical preparations from the Florentine wax workshop of Felice Fontana. 1 Fontana's wax workshop was renowned in Italy and abroad for its lifelike anatomical models. 2Midwifery instructors like Malacarne often employed a variety of three-dimensional obstetrical representations to help students, both midwives and surgeons, coordinate their visualization of internal structures with their tactile sense of the female body and the position and movement of the fetus in utero.On models and machines, midwives, who often lacked formal training, could practice manual skills and become familiar 1Parts of this chapter were previously published as "Modelling Authority:

This paper addresses the monitoring and continual learning of data-based dynamical models. Throughout the lifespan of any process, many changes can occur. In an indirect control design framework, in order to maintain an effective control system, it is crucial to monitor the modelling performance and adapt the existing model to possible system variations while preserving previously acquired information. A comprehensive methodology is hence proposed to detect a system-model mismatch and its cause, and to update the model accordingly. The proposed idea consists in leveraging control charts constructed on operational data to spot an anomaly and to determine its cause (endogenous or exogenous). The procedure then provides an adaptation algorithm based on the type of change detected: if endogenous, the model is 'partially' updated by means of a Moving Horizon Estimation (MHE) algorithm, if exogenous, the model is 'incrementally' updated by means of a model uncertainty estimation algorithm. The proposed methodology is tested in simulation on a district heating system benchmark, showing promising results from the monitoring and continual learning perspective.

Organ motion is one of the main challenges to account for in particle therapy to plan and deliver an accurate treatment. In this chapter, we will explain the concept of organ motion in terms of inter- and intra-fraction variations. The current inter- and intra-fraction motion compensation techniques demanding for imaging will be also reported.

Bell inequalities are one of the cornerstones of quantum foundations, and fundamental tools for quantum technologies. Recently, the scientific community worldwide has put a lot of effort towards them, which culminated with loophole-free experiments. Nonetheless, none of the experimental tests so far was able to extract information on the full inequality from each entangled pair, since the wave function collapse forbids performing, on the same quantum state, all the measurements needed for evaluating the entire Bell parameter. We present here the first single-pair Bell inequality test, able to obtain a Bell parameter value for every entangled pair detected. This is made possible by exploiting sequential weak measurements, allowing to measure non-commuting observables in sequence on the same state, on each entangled particle. Such an approach not only grants unprecedented measurement capability, but also removes the need to choose between different measurement bases, intrinsically eliminating the freedom-of-choice loophole and stretching the concept of counterfactual-definiteness (since it allows measuring in the otherwise not-chosen bases). We also demonstrate how, after the Bell parameter measurement, the pair under test still presents a noteworthy amount of entanglement, providing evidence of the absence of (complete) wave function collapse and allowing to exploit this quantum resource for further protocols.

General practitioner (GP) training programme involves a complex process. In Italy, unlike in other European countries, there is no national core curriculum for the training of GPs and the three-year specific training course in General Medicine (CSFMG) is not equated as a proper specialty. Furthermore, the quality of the CFSMGs is poorly investigated and data are difficult to find/fragment. The aim of this study is to describe and compare GP tranining from two pilot regions (Lombardy and Lazio). The study analysed the white and grey literature. For data collection a descriptive grid was created using the characteristics foreseen by current legislation as comparison indicators; the information came exclusively from official and public written data. The analysis reports indicators: structural-organisational; theoretical activity; practical activity; research/guided study; final thesis. The most evident fact that emerges is the lack of available (show the gap), public and official information on the GP training, therefore the description and comparison of the basic indicators in the pilot Regions suffers. A learning model based more on minimum time requirements (time-based learning) than on competences to be acquired (competencies-based learning) is evident. Furthermore, the professional/academic profiles of the lecturers are not available and thus comparable; finally, no information on the training methodologies of the frontal/research sessions can be found. The limitation to only two Regions and the lack of available data do not allow a comprehensive assessment and it would be useful to extend the study on a national scale. However, there is a clear need for improved transparency and evaluation within the GP's training in different Regions through a periodic monitoring system with specific indicators (quantitative and qualitative). The re-establishment/establishment of an independent national observatory on Training in General Practice would be desirable.

The digital healthcare workforce is usually composed of two major types of professionals: the healthcare workers, who are the users of eHealth, and the health informatics developers, who are usually computer scientists, biomedical engineers, or other technical experts. Health informatics educators have the responsibility to develop the appropriate skills for both, acting within their specific curricula. Here we present the experience of the Italian Society of Biomedical Informatics (SIBIM) and show that, whereas the technical curricula are widely covered with a large range of topics, the eHealth education in medical curricula is often limited to simple bioengineering and informatics skills, thus suggesting that eHealth associations and organizations at the national level should focus their efforts towards increasing the level of eHealth contents in medical schools.

Electric vehicles are becoming widely adopted; besides environmental advantages, electric power trains present peculiar characteristics that pave the way for reconsidering classical vehicle dynamics control (e.g. ABS, TC) and improving their performance. In this paper, we propose an ABS/TC system for full electric vehicles with 4-wheel drive. The regulator is derived from a nonlinear brake-based slip control. We modelled the wheel dynamics with an augmented single-corner model that includes the transmission, a crucial element. The controller has been tuned in simulation on the identified grey-box model and validated with an instrumented vehicle on ice and snow. It shows good performance relieving the driver of limiting the slips. The wheels are kept controlled and the magnitude of the average acceleration is increased with respect to professional driver performance.

Smart gird is intelligent and interactive among its power devices using the communication network running a protocol for reliable transfer of messages from one device to another or with the system operator for critical operation and control of the substation. Employing protocol such as IEC61850 globally in the electrical substation need to be well tested for time critical operations, physical security of the substation with proper logic implementation for power flow in case of an event. If the substation is connected to the internet then the problem gets more complex with respect to cyber security challenges faced over this protocol.In this work, Hardware-in-the-loop simulation methodology of Smart grid including the physical IEC61850 communication net-work layer using Intelligent electronic devices of circuit breakers is presented. GOOSE messages and MMS server communication using IEC61850 in the smart grids are investigated inside the real-time simulation boundaries. The unique aspect of this work is the logic implementation among the protection devices are tested with real communication delays over the protocol that can occur between them, and these results are more realistic matching the real world scenario.

The Smart Aging Serious Game (SASG) is an ecologically-based digital platform used in mild neurocognitive disorders. Considering the higher risk of developing dementia for mild cognitive impairment (MCI) and vascular cognitive impairment (VCI), their digital phenotyping is crucial. A new understanding of MCI and VCI aided by digital phenotyping with SASG will challenge current differential diagnosis and open the perspective of tailoring more personalized interventions. To confirm the validity of SASG in detecting MCI from healthy controls (HC) and to evaluate its diagnostic validity in differentiating between VCI and HC. 161 subjects (74 HC: 37 males, 75.47±2.66 mean age; 60 MCI: 26 males, 74.20±5.02; 27 VCI: 13 males, 74.22±3.43) underwent a SASG session and a neuropsychological assessment (Montreal Cognitive Assessment (MoCA), Free and Cued Selective Reminding Test, Trail Making Test). A multi-modal statistical approach was used: receiver operating characteristic (ROC) curves comparison, random forest (RF), and logistic regression (LR) analysis. SASG well captured the specific cognitive profiles of MCI and VCI, in line with the standard neuropsychological measures. ROC analyses revealed high diagnostic sensitivity and specificity of SASG and MoCA (AUCs > 0.800) in detecting VCI versus HC and MCI versus HC conditions. An acceptable to excellent classification accuracy was found for MCI and VCI (HC versus VCI; RF: 90%, LR: 91%. HC versus MCI; RF: 75%; LR: 87%). SASG allows the early assessment of cognitive impairment through ecological tasks and potentially in a self-administered way. These features make this platform suitable for being considered a useful digital phenotyping tool, allowing a non-invasive and valid neuropsychological evaluation, with evident implications for future digital-health trails and rehabilitation.

The use of high-resolution Numerical Weather Prediction (NWP) data for electromagnetic wave propagation analysis along Extremely High Frequencies (EHF) is the focus of this work. The Weather Research and Forecast (WRF) model is coupled with the ERA5 meteorological data to produce NWP data, hence the link attenuation, at resolutions never explored for propagation purposes, i.e. 1 minute and 1 km x 1 km. By comparison with the Alphasat propagation data collected in Milan, light is shed on the best compromise between space-time resolution and computation time. Also, a statistical approach is proposed exploiting in a more reliable way the link attenuation forecasts to dynamically adapt the link parameters (e.g. modulation and coding scheme) and thus meet the target quality requirements (e.g. Bit Error Rate) in different weather conditions.