Direct data-driven control of constrained linear parameter-varying systems: A hierarchical approach

In many nonlinear control problems, the plant can be accurately described by a linear model whose operating point depends on some measurable variables, called scheduling signals. When such a linear parameter-varying (LPV) model of the open-loop plant needs to be derived from a set of data, several issues arise in terms of parameterization, estimation, and validation of the model before designing the controller. Moreover, the way modeling errors affect the closed-loop performance is still largely unknown in the LPV context. In this paper, a direct data-driven control method is proposed to design LPV controllers directly from data without deriving a model of the plant. The main idea of the approach is to use a hierarchical control architecture, where the inner controller is designed to match a simple and a-priori specified closed-loop behavior. Then, an outer model predictive controller is synthesized to handle input/output constraints and to enhance the performance of the inner loop. The effectiveness of the approach is illustrated by means of a simulation and an experimental example. Practical implementation issues are also discussed.Comment: Preliminary version of the paper "Direct data-driven control of constrained systems" published in the IEEE Transactions on Control Systems Technolog

Direct learning ofLPVcontrollers from data

In many control applications, it is attractive to describe nonlinear (NL) and time-varying (TV) plants by linear parametervarying (LPV) models and design controllers based on such representations to regulate the behaviour of the system. The LPV system class offers the representation of NL and TV phenomena as a linear dynamic relationship between input and output signals, which relationship is dependent on some measurable signals, e.g., operating conditions, often called as scheduling variables. For such models, powerful control synthesis tools are available, but the way how to systematically convert available first principles models to LPV descriptions of the plant, to efficiently identify LPV models for control from data and to understand how modeling errors affect the control performance are still subject of undergoing research. Therefore, it is attractive to synthesize the controller directly from data without the need of modeling the plant and addressing the underlying difficulties. Hence, in this paper, a novel data-driven synthesis scheme is proposed in a stochastic framework to provide a practically applicable solution for synthesizing LPV controllers directly from data. Both the cases of fixed order controller tuning and controller structure learning are discussed and two different design approaches are provided. The effectiveness of the proposed methods is also illustrated by means of an academic example and a real application based simulation case study

ESA ESRIN'S VALUE FOR ITALY

The report presents an overview of the evolution of ESA's ESRIN stablishment. The programs and activities carried out by ESRIN are then analyzed, with particular attention to the Earth Observation and VEGA programs. We then moved on to assessing the economic and strategic impact of ESRIN for Italy. In particular, an estimate was made of the direct and indirect economic impact and of the scientific value developed by ESRIN on the Italian territory

Split-Boost Neural Networks

The calibration and training of a neural network is a complex and time-consuming procedure that requires significant computational resources to achieve satisfactory results. Key obstacles are a large number of hyperparameters to select and the onset of overfitting in the face of a small amount of data. In this framework, we propose an innovative training strategy for feed-forward architectures - called split-boost - that improves performance and automatically includes a regularizing behaviour without modeling it explicitly. Such a novel approach ultimately allows us to avoid explicitly modeling the regularization term, decreasing the total number of hyperparameters and speeding up the tuning phase. The proposed strategy is tested on a real-world (anonymized) dataset within a benchmark medical insurance design problem

Linguistic adaptation and validation of Italian version of OSA-18, a quality of life questionnaire for evaluation of children with obstructive sleep apnea-hypopnea syndrome (OSAS).

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Glucorticoid receptor in human cutaneous melanoma: immunohistochemical and immunofluorescence study

GR is a nuclear receptor which, when activated by its specific ligand, can act as a transcription factor that binds to glucocorticoid response elements (GRE) or negative GRE. It affects inflammatory responses, differentiation and cell proliferation. The ligand activated glucocorticoid receptor induces a G1 cell cycle arrest or apoptosis in immature thymocytes and impairs proliferation of fibroblasts of undifferentiated mammary epithelial cells. It impairs proliferation and differentiation of neural progenitor cells in vivo and in vitro. Glucocorticoids are widely used in cancer therapy and have cell type-specific pro- or antiapoptotic effects. In melanoma, however, the antitumor activity of glucocorticoids remains an open question. A recent report demonstrated that in mouse embryo tissue and in human undifferentiated cells, cytoplasmic accumulation of GR is determined by nestin in conjunction with vimentin, copolymerised into an intermediate filament system, and that this anchoring of GR to the nestin/vimentin etheromeric complex is related to the maintenance of a high proliferation rate. The aim of this study was to analyse the expression of subcellular GR in cutaneous melanoma by immunofluorescence, immunohistochemistry and laser scanning confocal microscopy and to evaluate any effect in melanoma progression. The results will be discussed

Course and Lethality of SARS-CoV2 Epidemic in Nursing Homes after Vaccination in Florence, Italy

Evidence on the effectiveness of SARS-CoV-2 vaccines in nursing home (NHs) residents is limited. We examined the impact of the BNT162b2 mRNA SARS-CoV-2 vaccine on the course of the epidemic in NHs in the Florence Health District, Italy, before and after vaccination. Moreover, we assessed survival and hospitalization by vaccination status in SARS-CoV-2-positive cases occurring during the post-vaccination period. We calculated the weekly infection rates during the pre-vaccination (1 October–26 December 2020) and post-vaccination period (27 December 2020–31 March 2021). Cox analysis was used to analyze survival by vaccination status. The study involved 3730 residents (mean age 84, 69% female). Weekly infection rates fluctuated during the pre-vaccination period (1.8%–6.5%) and dropped to zero during the post-vaccination period. Nine unvaccinated (UN), 56 partially vaccinated (PV) and 35 fully vaccinated (FV) residents tested SARS-CoV-2+ during the post-vaccination period. FV showed significantly lower hospitalization and mortality rates than PV and UV (hospitalization: FV 3%, PV 14%, UV 33%; mortality: FV 6%, PV 18%, UV 56%). The death risk was 84% and 96% lower in PV (HR 0.157, 95%CI 0.049–0.491) and FV (HR 0.037, 95%CI 0.006–0.223) versus UV. SARS-CoV-2 vaccination was followed by a marked decline in infection rates and was associated with lower morbidity and mortality among infected NH residents

Staff perceptions of Family-Centered Care in Italian Neonatal Intensive Care Units: A multicenter cross-sectional study

Family Centered Care (FCC) in Neonatal Intensive Care Units (NICUs) included family involvement in the care process of newborns and infants. Staff perceptions of FCC may influence clinical practice and management strategies in NICUs, with an impact on quality and humanization of the care. The Family-Centred Care Questionnaire-Revised (FCCQ-R) was adapted for the NICU setting, therefore the FCCQ-R@it-NICU was developed and used for the present study in 32 Italian NICUs. We calculated internal consistency using Cronbach's alpha correlation between Current and Necessary dimensions of the scale using the Pearson correlation coefficient. Furthermore, we investigated which characteristics could influence staff perceptions of FCC in NICUs. 921 NICU professionals participated in the study. The FCCQ-R@it-NICU revealed good internal consistency (0.96) and good correlation between dimensions (p < 0.05). Statistical and significant differences in Current and Necessary dimensions were found and some demographic characteristics were found predictable on FCC practice. The FCCQ-R@it-NICU is a valid tool to investigate staff perceptions about FCC in NICU settings. Profession, education level and work experience seem to positively influence the perception of what is required for FCC practice within NICUs

Shedding light on typical species: Implications for habitat monitoring

Habitat monitoring in Europe is regulated by Article 17 of the Habitats Directive, which suggests the use of typical species to assess habitat conservation status. Yet, the Directive uses the term “typical” species but does not provide a definition, either for its use in reporting or for its use in impact assessments. To address the issue, an online workshop was organized by the Italian Society for Vegetation Science (SISV) to shed light on the diversity of perspectives regarding the different concepts of typical species, and to discuss the possible im-plications for habitat monitoring. To this aim, we inquired 73 people with a very different degree of expertise in the field of vegetation science by means of a tailored survey composed of six questions. We analysed the data using Pearson's Chi-squared test to verify that the answers diverged from a random distribution and checked the effect of the degree of experience of the surveyees on the results. We found that most of the surveyees agreed on the use of the phytosociological method for habitat monitoring and of the diagnostic and characteristic species to evaluate the structural and functional conservation status of habitats. With this contribution, we shed light on the meaning of “typical” species in the context of habitat monitoring

Shedding light on typical species : implications for habitat monitoring

Habitat monitoring in Europe is regulated by Article 17 of the Habitats Directive, which suggests the use of typical species to assess habitat conservation status. Yet, the Directive uses the term “typical” species but does not provide a definition, either for its use in reporting or for its use in impact assessments. To address the issue, an online workshop was organized by the Italian Society for Vegetation Science (SISV) to shed light on the diversity of perspectives regarding the different concepts of typical species, and to discuss the possible implications for habitat monitoring. To this aim, we inquired 73 people with a very different degree of expertise in the field of vegetation science by means of a tailored survey composed of six questions. We analysed the data using Pearson's Chi-squared test to verify that the answers diverged from a random distribution and checked the effect of the degree of experience of the surveyees on the results. We found that most of the surveyees agreed on the use of the phytosociological method for habitat monitoring and of the diagnostic and characteristic species to evaluate the structural and functional conservation status of habitats. With this contribution, we shed light on the meaning of “typical” species in the context of habitat monitoring