REGIONAL DISPARITIES IN ITALY OVER THE LONG RUN: THE ROLE OF HUMAN CAPITAL AND TRADE POLICY

The well known Italian dualism in terms of development disparities between the North and the South has been one of the most debated issues in economics over the last few decades. In the aftermath of the Unification of Italy, the gap between North and South in terms of human capital stock was more relevant than the dualism in terms of GDP per capita. In 1871 the percentage of population able to read and write was 57.7% in the North-West and only 15.9% in the South, while there is no evidence of income disparities. Interestingly, in 1951 income per capita in Southern regions was only about 50% of that of the North. Bearing this evidence in mind, and using a novel panel dataset, we in-vestigate the pattern of regional development focusing on the role of initial hu-man capital conditions as a major driver of growth over the period 1891–1951. We provide further empirical evidence on the impact of protectionist trade poli-cies in the late 19th century on long run development. We find that a numerical-ly large human capital stock in the North provided fertile soil for early industri-alization, while the protection of agriculture resulted in an incentive for the South to specialize further in the primary sector, which turned out to be harmful in the long run.REGIONAL DISPARITIES, HUMAN CAPITAL, TRADE POLICY

TuST: from Raw Data to Vehicular Traffic Simulation in Turin

Traffic simulations are becoming a standard way to study urban mobility patterns, to evaluate new traffic policies and to test modern vehicular technologies. For this reason, in recent years, mobility projects pushed towards an increase in the demand of traffic simulators and towards an extension of their area of investigation, aiming at covering a whole city and its suburbs. In this paper we describe the methodology we followed in the creation of a large-scale traffic simulation of a 400-Km^2 area around the Municipality of Turin. Our preliminary results demonstrate that a complete modeling of such a wide tool is possible at the expense of minor simplifications

Physical activity scale for the elderly: translation, cultural adaptation, and validation of the Italian version

Objective. The aim of the study was to translate and culturally adapt the Physical Activity Scale for the Elderly into Italian (PASE-I) and to evaluate its psychometric properties in the Italian older adults healthy population. Methods. For translation and cultural adaptation, the "Translation and Cultural Adaptation of Patient-Reported Outcomes Measures" guidelines have been followed. Participants included healthy individuals between 55 and 75 years old. The reliability and validity were assessed following the "Consensus-Based Standards for the Selection of Health Status Measurement Instruments" checklist. To evaluate internal consistency and test-retest reliability, Cronbach's α and Intraclass Correlation Coefficient (ICC) were, respectively, calculated. The Berg Balance Score (BBS) and the PASE-I were administered together, and Pearson's correlation coefficient was calculated for validity. Results. All the PASE-I items were identical or similar to the original version. The scale was administered twice within a week to 94 Italian healthy older people. The mean PASE-I score in this study was 159±77.88. Cronbach's α was 0.815 (p < 0.01) and ICC was 0.977 (p < 0.01). The correlation with the BBS was 0.817 (p < 0.01). Conclusions. The PASE-I showed positive results for reliability and validity. This scale will be of great use to clinicians and researchers in evaluating and managing physical activities in the Italian older adults population

Cognitive Theories of Concepts and Wittgenstein’s Rule-Following: Concept Updating, Category Extension, and Referring

In this article, the authors try to answer the following questions: How can an object/instance seen for the first time extend a category or update a concept? How is it possible to determine the reference of a concept that represents a behaviour? In the first case, the authors discuss the learning of inferential linguistic competence used to update a concept through an approach based on prototype theory. In the second case, the authors discuss the learning of referential linguistic competence used to determine the reference of a concept (i.e., determination of an actual behaviour) through an approach based on embodied cognition. The authors show how combining prototype-based and embodied categorization in Wittgenstein’s rule-following praxis (the individual and community dimension), linguistic learning of a concept (inferential competence), and determination of its reference (referential competence) can be traced back to the same model. Keywords Action, Categorization, Embodied Cognition, Embodiment, Linguistic Inferential Competence, Linguistic Referential Competence, Perception, Prototype Theory, Reference, Sign

Optimization models for computer data storage design: An application

In this paper we discuss a model being used to optimize the system design of the Computer Centre of one of the most important Italian banking groups. Data and transactions, processed by the system, are grouped respectively in data sets and by type, so it is possible to deal with the large dimensions of the corresponding optimization models. The transactions' arrivals are considered as stochastic variables and their probability values are estimated on the base of theoretical considerations. The solutions for two optimization problems, constructed and solved for different scenarios, are discussed in detail.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31307/1/0000215.pd

A machine learning approach to estimating preterm infants survival: development of the Preterm Infants Survival Assessment (PISA) predictor

Estimation of mortality risk of very preterm neonates is carried out in clinical and research settings. We aimed at elaborating a prediction tool using machine learning methods. We developed models on a cohort of 23747 neonates &lt;30 weeks gestational age, or &lt;1501 g birth weight, enrolled in the Italian Neonatal Network in 2008–2014 (development set), using 12 easily collected perinatal variables. We used a cohort from 2015–2016 (N = 5810) as a test set. Among several machine learning methods we chose artificial Neural Networks (NN). The resulting predictor was compared with logistic regression models. In the test cohort, NN had a slightly better discrimination than logistic regression (P &lt; 0.002). The differences were greater in subgroups of neonates (at various gestational age or birth weight intervals, singletons). Using a cutoff of death probability of 0.5, logistic regression misclassified 67/5810 neonates (1.2 percent) more than NN. In conclusion our study – the largest published so far – shows that even in this very simplified scenario, using only limited information available up to 5 minutes after birth, a NN approach had a small but significant advantage over current approaches. The software implementing the predictor is made freely available to the community

Repeated TACE in HCC after Fontan surgery and situs viscerum inversus: A case report

We describe the case of a 32-year-old man who developed a liver neoplasm due to previous Fontan surgery (FS) for a single ventricle anomaly and situs viscerum inversus. He was admitted to our hospital for suspected hepatocellular carcinoma during an Ultrasound (US) follow up. Computed tomography (CT) showed features of chronic liver disease and 7 cm hepatic nodule with arterial enhancement. Laboratory analyses documented preserved liver function and increased levels of alpha-fetoprotein. Trans-arterial-chemoembolization (TACE) was performed obtaining complete necrosis at 4 weeks of follow up and significant reduction of alpha-fetoprotein. The patient is currently in follow-up, being evaluated for further treatments and/or combined liver-heart transplantation. TACE is a therapeutic option for the treatment of patients with unresectable hepatocellular carcinoma (HCC) and with severe heart disease, like those submitted to FS and with also other vascular abnormalities like those correlated to situs viscerum inversus

PM10 and PM2.5 Qualitative Source Apportionment Using Selective Wind Direction Sampling in a Port-Industrial Area in Civitavecchia, Italy

The possibility to discriminate between different emission sources and between natural and anthropogenic contributions is a key issue for planning efficient air pollution reduction and mitigation strategies. Moreover, the knowledge of the particulate matter (PM) chemical composition for the different size fractions is recognized as increasingly important, in particular with respect to health effects of exposed population. This study is focused on the characterization of PM10 and PM2.5 main sources located in the Civitavecchia harbor-industrial area (Central Italy), namely a large coal-fired power plant, a natural gas power plant, the harbor area, the vehicular traffic (due to both the local traffic and the highway crossing the area) and small industrial activities. The approach was based on PM10/PM2.5 samples monthly collected for one year and a further relative chemical characterization of organic and inorganic fractions. Wind-select sensors, allowing a selective PM10 and PM2.5 sampling downwind to specific emission sources, were used for the overall sampling. This methodology manages to explain specific emission patterns and to assess the concentration levels of the micro pollutants emitted by local sources and particularly toxic for health. A descriptive statistical analysis of data was performed, also verifying the occurrence of legislative threshold exceedances. Moreover, in order to highlight the contribution of specific sources, the differences in the measured micro pollutants concentrations between wind directions, PM size fractions and sampling sites have been investigated, as well as the seasonal trends of pollutants concentrations. These results allow to highlight that the applied methodology represents a valid support in source apportionment studies

Aldo-keto reductases protect metastatic melanoma from ER stress-independent ferroptosis

The incidence of melanoma is increasing over the years with a still poor prognosis and the lack of a cure able to guarantee an adequate survival of patients. Although the new immuno-based coupled to target therapeutic strategy is encouraging, the appearance of targeted/cross-resistance and/or side effects such as autoimmune disorders could limit its clinical use. Alternative therapeutic strategies are therefore urgently needed to efficiently kill melanoma cells. Ferroptosis induction and execution were evaluated in metastasis-derived wild-type and oncogenic BRAF melanoma cells, and the process responsible for the resistance has been dissected at molecular level. Although efficiently induced in all cells, in an oncogenic BRAF- and ER stress-independent way, most cells were resistant to ferroptosis execution. At molecular level we found that: resistant cells efficiently activate NRF2 which in turn upregulates the early ferroptotic marker CHAC1, in an ER stress-independent manner, and the aldo-keto reductases AKR1C1\u2009\uf7\u20093 which degrades the 12/15-LOX-generated lipid peroxides thus resulting in ferroptotic cell death resistance. However, inhibiting AKRs activity/expression completely resensitizes resistant melanoma cells to ferroptosis execution. Finally, we found that the ferroptotic susceptibility associated with the differentiation of melanoma cells cannot be applied to metastatic-derived cells, due to the EMT-associated gene expression reprogramming process. However, we identified SCL7A11 as a valuable marker to predict the susceptibility of metastatic melanoma cells to ferroptosis. Our results identify the use of pro-ferroptotic drugs coupled to AKRs inhibitors as a new valuable strategy to efficiently kill human skin melanoma cells