A multicenter study on the appropriateness of hospitalization in obstetric wards: application of Obstetric Appropriateness Evaluation Protocol (Obstetric AEP). Studio multicentrico sul protocollo di revisione dell’uso dell’ospedale in ostetricia: applicazione dello PRotocollo dell’Uso dell’Ospedale in Ostetricia (PRUO ostetrico)

Objectives This study has been based on the implementation of the Obstetric Appropriateness Evaluation Protocol in 7 Italian hospitals to determine inappropriate hospital admissions and days of stay. Design A cross-sectional study. Methods The outcomes examined were: appropriateness/inappropriateness of admission and "percentage of inappropriateness". Results A total number of 2196 clinical records were reviewed. The mean percentage of inappropriateness for a hospitalization was 22%. The percentage of inappropriateness for the first ten days of hospitalization peaked in correspondence of the 4th and 5th (42%). The emergency admission was a protective factor of inappropriated admission, OR= 0.23 95%CI (0.16-0.35). To be hospitalized in a Teaching Hospital, in a hospital with ≥30 beds and to be admitted during the Winter/Autumn and in the workweek were risk factors of inappropriateness, respectively with OR=3.50 95%CI(2.30-5.34), OR=2.04 95%CI(1.41-2.97), OR=2.14 95%CI(1.41-2.97), OR=1.85 95%CI(1.12-3.04). The linear regression model underlined that the "percentage of inappropriateness" significantly increased in inappropriate admission and in obstetric wards with ≥30 beds; the admission in a Teaching Hospital and the hospitalization in South Italy was inversely associated to the percentage of inappropriateness. The R2 model was 0.367. Conclusions The present study suggests that the percentage of inappropriate admission depends especially on the inappropriate admission and the large number of beds in obstetric wards. This suggests that the management of big hospitals, which is very complex, needs improving the processes of support and coordination of health professionals. The obstetric AEP tool seems to be an useful instrument for the decision makers to monitor and manage the obstetric wards

Forecasting the Spreading of Technologies in Research Communities

Technologies such as algorithms, applications and formats are an important part of the knowledge produced and reused in the research process. Typically, a technology is expected to originate in the context of a research area and then spread and contribute to several other fields. For example, Semantic Web technologies have been successfully adopted by a variety of fields, e.g., Information Retrieval, Human Computer Interaction, Biology, and many others. Unfortunately, the spreading of technologies across research areas may be a slow and inefficient process, since it is easy for researchers to be unaware of potentially relevant solutions produced by other research communities. In this paper, we hypothesise that it is possible to learn typical technology propagation patterns from historical data and to exploit this knowledge i) to anticipate where a technology may be adopted next and ii) to alert relevant stakeholders about emerging and relevant technologies in other fields. To do so, we propose the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model to forecast the propagation of technologies to research areas. A formal evaluation of the approach on a set of technologies in the Semantic Web and Artificial Intelligence areas has produced excellent results, confirming the validity of our solution

Forecasting Technology Migrations by means of the Technology-Topic Framework

Technologies such as algorithms, applications and formats usually originate in the context of a specific research area and then spread to several other fields, sometimes with transformative effects. However, this can be a slow and inefficient process, since it not easy for researchers to be aware of all interesting approaches produced by unfamiliar research communities. We address this issue by introducing the Technology-Topic Framework, a novel approach which uses a semantically enhanced technology-topic model and machine learning to forecast the propagation of technologies across research areas. The aim is to foster the knowledge flow by suggesting to scholars technologies that may become relevant to their research field. The system was evaluated on a manually curated set of 1,118 technologies in Semantic Web and Artificial Intelligence and the results of the evaluation confirmed the validity of our approach

2100 AI: Reflections on the mechanisation of scientific discovery

The pace of research is nowadays extremely intensive, with datasets and publications being published at an unprecedented rate. In this context data science, artificial intelligence, machine learning and big data analytics are providing researchers with new automatic techniques which not only help them to manage this flow of information but are also able to identify automatically interesting patterns and insights in this vast sea of information. However, the emergence of mechanised scientific discovery is likely to dramatically change the way we do science, thus introducing and amplifying serious societal implications on the role of researchers themselves, which need to be analysed thoroughly

A set of key questions to assess the stress among bank employees and its reliability: Bank Employee Stress Test (BEST8)

The aims of the present study are: to realize a tool, clear and helpful, to assess the occupational distress level in bank employees in Italy; secondly to assess the reliability of the tool. Eight sentences were considered after a consensus meeting that involved different professional figures. 70 questionnaires were collected. The overall Cronbach’s alpha was 0.596, a sufficient reliability was found. The elimination of one sentences (“I haven’t time to dedicate myself to my hobbies/activities/stuff”) increases alpha’s value from 0.596 to 0.620, and thus reach fully sufficient score. The claim “The pace of change on work place exceeds my capacity for adaptation” maximises the change of the level of reliability (Inter item Correlation = 0.528)

Classifying Research Papers with the Computer Science Ontology

Ontologies of research areas are important tools for characterising, exploring and analysing the research landscape. We recently released the Computer Science Ontology (CSO), a large-scale, automatically generated ontology of research areas, which includes about 26K topics and 226K semantic relationships. CSO currently powers several tools adopted by the Springer Nature editorial team and has been used to enable a variety of solutions, such as classifying research publications, detecting research communities, and predicting research trends. As an effort to encourage the usage of CSO, we have developed the CSO Portal, a web application that enables users to download, explore, and provide granular feedbacks at different levels of the ontology. In this paper, we present the CSO Classifier, an application for automatically classifying academic papers according to the rich taxonomy of topics from CSO. The aim is to facilitate the adoption of CSO across the various communities engaged with scholarly data and to foster the development of new applications based on this knowledge base

Studio di variante alla SR 222 in localita' Grassina

Questo studio nasce dalla necessità oggettiva e dalla volontà da parte della Provincia di Firenze di migliorare i collegamenti tra il “Chianti Fiorentino” e l’area metropolitana del comune di Firenze. Attualmente le due aree sono raggiungibili percorrendo la SR 222 Chiantigiana, strada che si rivela inadeguata a sopportare gli elevati volumi di traffico che ormai l’attrattività di queste aree genera. La Chiantigiana è una via di comunicazione storica, che parte da Firenze sud e arriva fino a Siena, una delle poche alternative prima della realizzazione del raccordo autostradale, ed è una strada importante dal punto di vista turistico, per la bellezza e la fama dei territori che attraversa. Purtroppo proprio a causa del territorio collinare, il tracciato presenta repentini cambiamenti di pendenza, sezione molto variabile e un andamento planimetrico che limita fortemente la visibilità in curva. Il tratto più critico riguarda senza dubbio l’area di Grassina nel comune di Bagno a Ripoli; la strada infatti, non rimane tangente al paese come avviene in altri casi, ma attraversa l’abitato descrivendo numerose anse paragonabili a quelle di un torrente. Il flusso di attraversamento viene quindi a interagire con il traffico locale, creando una situazione insostenibile sotto tutti i punti di vista, da quello più ovvio dei tempi di percorrenza dilatati a quello più grave dell’inquinamento atmosferico; nelle ore di punta il centro di grassina viene attraversato da circa 2000 veicoli l’ora. Un adeguamento della SR 222 in questo tratto è per ovvi motivi, impensabile e comunque non alleggerirebbe l’abitato; l’unica soluzione è quella di bypassare la frazione di Grassina realizzando una nuova infrastruttura. Della “variante di grassina” si parla ormai da più di 40 anni, ad oggi di concreto nulla è stato fatto, esiste solo un progetto del nuovo tracciato redatto dalla provincia di Firenze nel 2006 che probabilmente andrà a breve in gara d’appalto. Il tracciato lungo circa 6.5 km, si articola da Ponte a Niccheri per circa due terzi in riva destra del Torrente Ema, sul versante opposto rispetto all’attuale tracciato della SR 222, a cui si ricongiunge risalendo il versante sinistro dell’Ema fra le località Capannuccia e Mortinete. L’intervento in progetto, che prevede per circa il 30% l’adeguamento della viabilità esistente, ricade nei comuni di Bagno a Ripoli (tratto Ponte a Niccheri – Capannuccia), Impruneta (tratto Capannuccia – Mortinete) e Greve in Chianti (intersezione in loc. Mortinete). Il compito di questo studio è fornire una valida alternativa al tracciato proposto dalla provincia, andando ad analizzare sia dal punto di vista prettamente geometrico che funzionale, le scelte effettuate. Dal punto di vista planimetrico il tracciato qui proposto ricalca quasi interamente quello della provincia, il territorio non lascia di fatto molte possibilità senza ovviamente coinvolgere opere d’arte di gran lunga più importanti ed onerose, si è scelto quindi di mantenere il più possibile l’occupazione prevista. Il lavoro si è invece concentrato molto sul profilo altimetrico; importanti modifiche fatte specialmente nel primo tratto (Ponte a Niccheri - Ghiacciaia) hanno infatti reso inutile la realizzazione di due gallerie artificiali preventivate dalla provincia. Molti cambiamenti riguardano poi le intersezioni, fra questi citiamo in località Mortinete, la ricollocazione della rotatoria sulla chiantigiana, a circa 400m in direzione l’Ugolino, e la completa riprogettazione dell’intersezione di Ponte a Niccheri, nodo nevralgico di tutto lo studio. A Ponte a Niccheri convergono infatti numerosi flussi provenienti dall’uscita autostradale Firenze Sud, da Ponte a Ema da Grassina, e dall’Antella; la provincia prevede di smaltire tutto il volume realizzando tre rotatorie di diametro esterno 33, 47 e 41 metri, distanziate tra loro rispettivamente 100 e 60 metri; inoltre tutta l’area che è soggetta a fenomeni di allagamento verrà rialzata di circa 2 metri rispetto alla quota attuale. La soluzione adottata in questo studio propone invece l’utilizzo di una sola rotatoria e il prolungamento del viadotto sul torrente Antella; come verrà spiegato dettagliatamente più avanti questa configurazione non necessita del rialzo dell’intera intersezione

Knowledge, attitude and behaviours towards recommended vaccinations among healthcare workers

Healthcare workers (HCWs) are an important group of professionals exposed to biological risk during their work activities. So, the aim of this study is to perform a survey on the knowledge, attitude and behaviour of Italian HCWs towards the vaccinations recommended by the Ministry of Health. A cross-sectional study was carried out during the period September 2014-August 2015 in the Lazio region. The study was conducted by recruiting HCWs and biomedical students. The sample was comprised of 571 responders, of whom 12.4% were physicians, 18.9% were nurses, 34.3% were other HCW, and 34.3% were biomedical students (medical and nurses students). Hepatitis B virus (HBV) is perceived as a risk for personal health by 457 (80%) participants; TB is also worrying (434; 76%). Moreover, HBV (70.9%) and tuberculosis (TB) (79.2%) are perceived as a risk for health, while influenza is not considered so by most participants (46.2%). There is an underestimation of the role of influenza, perceived as a risk for 137 respondents (24%). The vaccination rate among these HCWs is highest for Hepatitis B virus (HBV) (82%), and lowest for influenza (28.5%) and varicella (40.3%). The vast majority of responders are in favour of HBV (77.8%) and TB (64.8%) vaccines. For other vaccinations there is less interest (between 33% and 40% for measles, mumps, rubella, pertussis and influenza). This study shows that knowledge of recommended occupational vaccinations is insufficient in HCWs, with few exceptions represented by HBV and TB. There is a need for novel approaches in this field, with the aim of enhancing vaccine coverage among HCW

Passive smoking indicators in Italy: does the gross domestic product matter?

BACKGROUND: The aim of this study is to analyse the correlation between regional values of Gross Domestic Product (GDP) and passive smoking in Italy. METHODS: The outcome measures were smoking ban respect in public places, workplaces and at home, derived from the PASSI surveillance for the period 2011⁻2017. The explanatory variable was GDP per capita. The statistical analysis was carried out using bivariate and linear regression analyses, taking into consideration two different periods, Years 2011⁻2014 and 2014⁻2017. RESULTS: GDP is showed to be positively correlated with smoking ban respect in public places (r = 0.779 p < 0.001; r = 0.723 p < 0.001 in the two periods, respectively), as well as smoking ban respect in the workplace (r = 0.662 p = 0.001; r = 0.603 p = 0.004) and no smoking at home adherence (r = 0.424 p = 0.056; r = 0.362 p = 0.107). In multiple linear regression GDP is significantly associated to smoking ban respect in public places (adjusted β = 0.730 p < 0.001; β = 0.698 p < 0.001 in the two periods, respectively), smoking ban in workplaces (adjusted β = 0.525 p = 0.020; β = 0.570 p = 0.009) and no smoking at home (adjusted β = 0.332 p = 0.070; β = 0.362 p = 0.052). CONCLUSIONS: Smoking ban is more respected in Regions with higher GDP. For a better health promotion, systematic vigilance and sanctions should be maintained and strengthened, particularly in regions with low compliance with smoking bans