Assuring measurement traceability to ATE systems for MEMS temperature sensors testing and calibration

In the framework of an EMPIR joint research project (MET4FoF - Metrology for Factory of Future), a facility is being developed to provide in-situ measurement traceability to next-generation of Automated Test Equipment (ATE) systems used in MEMS temperature sensors testing and calibration. The above measurement traceability concepts are demonstrated in a testbed developed by SPEA in collaboration with INRIM and IPQ. The experimental work comprises both the factory-side implementation and the laboratory-side developments of a special calibration facility, to cover the temperature range between approximately -60 °C and 200 °C. On the factory side, SPEA develops a novel ATE prototype system, based on the concepts of good metrology practice, with the possibility to calibrate/validate in-situ the electronic circuitry and the on-board reference temperature sensors. The novel ATE prototype implements: • An improved temperature control system, with a new design of heaters, temperature sensors and MEMS temperature conditioning features. • A CPU software/firmware improvements to store sensors’ calibration coefficients and allow a “one-touch calibration” feature (i.e. a fully automatic process able to perform a comparison calibration of the ATE on-board reference temperature sensors). • An assessment of thermal conditions (homogeneity, heat losses, boundary effects) to estimate temperature calibration uncertainty. • A so-called “reference fixture”, i.e. an instrumented sensor socket equipped with a network of laboratory-calibrated reference sensors. On the laboratory side, INRIM develops calibration facilities and measurements methods to provide traceable temperature and electrical measurements to the above ATE systems. A custom equipment is developed to accommodate the sensors belonging to the reference fixture in order to calibrate them by comparison in a thermostatic bath. IPQ deals with the numerical simulation, by means of a 3D model of the temperature uniformity of the thermal chuck i.e. the ATE component providing the thermal stimulus to the MEMS under test. The simulation data will be used to help the SPEA hardware designer to improve the type, number and position of reference sensors on the thermal chuck to provide a more reliable and metrologically characterized thermal stimulus. The final paper will describe how an ATE machine works and in which parts it consists and how it is modified to reach the final goal. Furthermore, simulation data will be cross-compared with experimental data coming from metrological characterization before and after the ATE improvements in order to demonstrate their effectiveness. Also the method to assure traceability in large-scale temperature MEMS testing will be detailed and an example of application will be reported. Finally, it is expected that the outcome of this work will impact the quality and reliability of the MEMS sensors largely used in consumer electronics and will extend the calibration capability provided by INRIM to such an expanding industrial sector

Outcomes of COVID-19 patients intubated after failure of non-invasive ventilation: a multicenter observational study

The efficacy of non-invasive ventilation (NIV) in acute respiratory failure secondary to SARS-CoV-2 infection remains controversial. Current literature mainly examined efficacy, safety and potential predictors of NIV failure provided out of the intensive care unit (ICU). On the contrary, the outcomes of ICU patients, intubated after NIV failure, remain to be explored. The aims of the present study are: (1) investigating in-hospital mortality in coronavirus disease 2019 (COVID-19) ICU patients receiving endotracheal intubation after NIV failure and (2) assessing whether the length of NIV application affects patient survival. This observational multicenter study included all consecutive COVID-19 adult patients, admitted into the twenty-five ICUs of the COVID-19 VENETO ICU network (February-April 2020), who underwent endotracheal intubation after NIV failure. Among the 704 patients admitted to ICU during the study period, 280 (40%) presented the inclusion criteria and were enrolled. The median age was 69 [60-76] years; 219 patients (78%) were male. In-hospital mortality was 43%. Only the length of NIV application before ICU admission (OR 2.03 (95% CI 1.06-4.98), p = 0.03) and age (OR 1.18 (95% CI 1.04-1.33), p < 0.01) were identified as independent risk factors of in-hospital mortality; whilst the length of NIV after ICU admission did not affect patient outcome. In-hospital mortality of ICU patients intubated after NIV failure was 43%. Days on NIV before ICU admission and age were assessed to be potential risk factors of greater in-hospital mortality

Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?

Background: The discovery of early, non-invasive biomarkers for the identification of “preclinical” or “pre-symptomatic” Alzheimer's disease and other dementias is a key issue in the field, especially for research purposes, the design of preventive clinical trials, and drafting population-based health care policies. Complex behaviors are natural candidates for this. In particular, recent studies have suggested that speech alterations might be one of the earliest signs of cognitive decline, frequently noticeable years before other cognitive deficits become apparent. Traditional neuropsychological language tests provide ambiguous results in this context. In contrast, the analysis of spoken language productions by Natural Language Processing (NLP) techniques can pinpoint language modifications in potential patients. This interdisciplinary study aimed at using NLP to identify early linguistic signs of cognitive decline in a population of elderly individuals.Methods: We enrolled 96 participants (age range 50–75): 48 healthy controls (CG) and 48 cognitively impaired participants: 16 participants with single domain amnestic Mild Cognitive Impairment (aMCI), 16 with multiple domain MCI (mdMCI) and 16 with early Dementia (eD). Each subject underwent a brief neuropsychological screening composed by MMSE, MoCA, GPCog, CDT, and verbal fluency (phonemic and semantic). The spontaneous speech during three tasks (describing a complex picture, a typical working day and recalling a last remembered dream) was then recorded, transcribed and annotated at various linguistic levels. A multidimensional parameter computation was performed by a quantitative analysis of spoken texts, computing rhythmic, acoustic, lexical, morpho-syntactic, and syntactic features.Results: Neuropsychological tests showed significant differences between controls and mdMCI, and between controls and eD participants; GPCog, MoCA, PF, and SF also discriminated between controls and aMCI. In the linguistic experiments, a number of features regarding lexical, acoustic and syntactic aspects were significant in differentiating between mdMCI, eD, and CG (non-parametric statistical analysis). Some features, mainly in the acoustic domain also discriminated between CG and aMCI.Conclusions: Linguistic features of spontaneous speech transcribed and analyzed by NLP techniques show significant differences between controls and pathological states (not only eD but also MCI) and seems to be a promising approach for the identification of preclinical stages of dementia. Long duration follow-up studies are needed to confirm this assumption

Helichrysum microphyllum subsp. tyrrhenicum, Its Root-Associated Microorganisms, and Wood Chips Represent an Integrated Green Technology for the Remediation of Petroleum Hydrocarbon-Contaminated Soils

Phytoremediation and the use of suitable amendments are well-known technologies for the mitigation of petroleum hydrocarbon (PHC) contaminations in terrestrial ecosystems. Our study is aimed at combining these two approaches to maximize their favorable effects. To this purpose, Helichrysum microphyllum subsp. tyrrhenicum, a Mediterranean shrub growing on sandy and semiarid soils, was selected. The weathered PHC-polluted matrix (3.3 ± 0.8 g kg−1 dry weight) from a disused industrial site was employed as the cultivation substrate with (WCAM) or without (UNAM) the addition and mixing of wood chips. Under the greenhouse conditions, the species showed a survival rate higher than 90% in the UNAM while the amendment administration restored the totality of the plant survival. At the end of the greenhouse test (nine months), the treatment with the wood chips significantly increased the moisture, dehydrogenase activity and abundance of the microbial populations of the PHC degraders in the substrate. Cogently, the residual amount of PHCs was significantly lower in the UNAM (3–92% of the initial quantity) than in the WCAM (3–14% of the initial quantity). Moreover, the crown diameter was significantly higher in the WCAM plants. Overall, the results establish the combined technology as a novel approach for landscaping and the bioremediation of sites chronically injured by PHC-weathered contaminations

Static compliance and driving pressure are associated with ICU mortality in intubated COVID-19 ARDS

Background Pathophysiological features of coronavirus disease 2019-associated acute respiratory distress syndrome (COVID-19 ARDS) were indicated to be somewhat different from those described in nonCOVID-19 ARDS, because of relatively preserved compliance of the respiratory system despite marked hypoxemia. We aim ascertaining whether respiratory system static compliance (Crs), driving pressure (DP), and tidal volume normalized for ideal body weight (VT/kg IBW) at the 1st day of controlled mechanical ventilation are associated with intensive care unit (ICU) mortality in COVID-19 ARDS. Methods Observational multicenter cohort study. All consecutive COVID-19 adult patients admitted to 25 ICUs belonging to the COVID-19 VENETO ICU network (February 28th-April 28th, 2020), who received controlled mechanical ventilation, were screened. Only patients fulfilling ARDS criteria and with complete records of Crs, DP and VT/kg IBW within the 1st day of controlled mechanical ventilation were included. Crs, DP and VT/kg IBW were collected in sedated, paralyzed and supine patients. Results A total of 704 COVID-19 patients were screened and 241 enrolled. Seventy-one patients (29%) died in ICU. The logistic regression analysis showed that: (1) Crs was not linearly associated with ICU mortality (p value for nonlinearity = 0.01), with a greater risk of death for values < 48 ml/cmH(2)O; (2) the association between DP and ICU mortality was linear (p value for nonlinearity = 0.68), and increasing DP from 10 to 14 cmH(2)O caused significant higher odds of in-ICU death (OR 1.45, 95% CI 1.06-1.99); (3) VT/kg IBW was not associated with a significant increase of the risk of death (OR 0.92, 95% CI 0.55-1.52). Multivariable analysis confirmed these findings. Conclusions Crs < 48 ml/cmH(2)O was associated with ICU mortality, while DP was linearly associated with mortality. DP should be kept as low as possible, even in the case of relatively preserved Crs, irrespective of VT/kg IBW, to reduce the risk of death

ARIANNA: A research environment for neuroimaging studies in autism spectrum disorders

The complexity and heterogeneity of Autism Spectrum Disorders (ASD) require the implementation of dedicated analysis techniques to obtain the maximum from the interrelationship among many variables that describe affected individuals, spanning from clinical phenotypic characterization and genetic profile to structural and functional brain images. The ARIANNA project has developed a collaborative interdisciplinary research environment that is easily accessible to the community of researchers working on ASD (https://arianna.pi.infn.it). The main goals of the project are: to analyze neuroimaging data acquired in multiple sites with multivariate approaches based on machine learning; to detect structural and functional brain characteristics that allow the distinguishing of individuals with ASD from control subjects; to identify neuroimaging-based criteria to stratify the population with ASD to support the future development of personalized treatments. Secure data handling and storage are guaranteed within the project, as well as the access to fast grid/cloud-based computational resources. This paper outlines the web-based architecture, the computing infrastructure and the collaborative analysis workflows at the basis of the ARIANNA interdisciplinary working environment. It also demonstrates the full functionality of the research platform. The availability of this innovative working environment for analyzing clinical and neuroimaging information of individuals with ASD is expected to support researchers in disentangling complex data thus facilitating their interpretation

Climate and landscape composition explain agronomic practices, pesticide use and grape yield in vineyards across Italy

Context Worldwide, organic farming is being promoted as one of the main alternatives to intensive conventional farming. However, the benefits of organic agriculture are still controversial and need to be tested across wide environmental gradients. Objective Here, we carried out an observational study to test how agronomic practices, pest management, environmental impact and yield of conventional and organic vineyards changed along wide climatic and landscape gradients across Italy. Methods We used a block design with 38 pairs of conventional and organic vineyards across Italy. Results and conclusions Most agronomic practices did not differ between conventional and organic vineyards. By contrast, landscape composition and climate were strong predictors of management in both systems. First, increasing semi-natural areas around the vineyards reduced pesticide pressure and related environmental impacts, but was also associated with lower yield. Second, irrespective of the farming system, a warm and dry climate was associated with reduced fungicide pressure. Conventional farming had a yield gain of 40% in cold and wet climate compared to organic but the yield gap disappeared in the warmest regions. Significance In both farming systems, we observed a large variability in management practices that was mainly explained by climate and landscape composition. This large variability should be considered when evaluating the benefits and drawbacks of different farming systems under contrasting environmental contexts

Proceedings of the Fifth Italian Conference on Computational Linguistics CLiC-it 2018

On behalf of the Program Committee, a very warm welcome to the Fifth Italian Conference on Computational Linguistics (CLiC-­‐it 2018). This edition of the conference is held in Torino. The conference is locally organised by the University of Torino and hosted into its prestigious main lecture hall “Cavallerizza Reale”. The CLiC-­‐it conference series is an initiative of the Italian Association for Computational Linguistics (AILC) which, after five years of activity, has clearly established itself as the premier national forum for research and development in the fields of Computational Linguistics and Natural Language Processing, where leading researchers and practitioners from academia and industry meet to share their research results, experiences, and challenges

Economic consequences of investing in anti-HCV antiviral treatment from the Italian NHS perspective : a real-world-based analysis of PITER data

OBJECTIVE: We estimated the cost consequence of Italian National Health System (NHS) investment in direct-acting antiviral (DAA) therapy according to hepatitis C virus (HCV) treatment access policies in Italy. METHODS: A multistate, 20-year time horizon Markov model of HCV liver disease progression was developed. Fibrosis stage, age and genotype distributions were derived from the Italian Platform for the Study of Viral Hepatitis Therapies (PITER) cohort. The treatment efficacy, disease progression probabilities and direct costs in each health state were obtained from the literature. The break-even point in time (BPT) was defined as the period of time required for the cumulative costs saved to recover the Italian NHS investment in DAA treatment. Three different PITER enrolment periods, which covered the full DAA access evolution in Italy, were considered. RESULTS: The disease stages of 2657 patients who consecutively underwent DAA therapy from January 2015 to December 2017 at 30 PITER clinical centres were standardized for 1000 patients. The investment in DAAs was considered to equal €25 million, €15 million, and €9 million in 2015, 2016, and 2017, respectively. For patients treated in 2015, the BPT was not achieved, because of the disease severity of the treated patients and high DAA prices. For 2016 and 2017, the estimated BPTs were 6.6 and 6.2 years, respectively. The total cost savings after 20 years were €50.13 and €55.50 million for 1000 patients treated in 2016 and 2017, respectively. CONCLUSIONS: This study may be a useful tool for public decision makers to understand how HCV clinical and epidemiological profiles influence the economic burden of HCV

Optimization and mechanical-physical characterization of geopolymers with construction and demolition waste (CDW) aggregates for construction products

The paper presents the mechanical and physical characterization of a metakaolin-slag-fly ash-potassium silicate geopolymer mortar embedding inorganic recycled aggregates from Construction and Demolition Waste (CDW). The binder was holistically optimized to comply with the pilot plant requirements for producing architectural panels of satisfactory quality, among them: reduced viscosity, minimum open time of 1 h, use of commercial reagents, sufficient strength and limited shrinkage. Size and aspect ratio of small scale cylindrical specimens were investigated in compression, comparing the performance of tested geopolymers to available provisions for natural rocks, cement concrete and mortars. Empirical correlations between compressive and splitting tensile strength were calibrated through the results of about 130 geopolymer mixtures produced in former and current activities. Lastly, the suitability of reusing geopolymers at their end-of-life as recycled aggregates in a new geopolymer production was preliminarily assessed to explore the feasibility of a closed-loop process