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

Developing RPC-Net: leveraging high-density electromyography and machine learning for improved hand position estimation

Objective: The purpose of this study was to develop and evaluate the performance of RPC-Net (Recursive Prosthetic Control Network), a novel method using simple neural network architectures to translate electromyographic activity into hand position with high accuracy and computational efficiency. Methods: RPC-Net uses a regression-based approach to convert forearm electromyographic signals into hand kinematics. We tested the adaptability of the algorithm to different conditions and compared its performance with that of solutions from the academic literature. Results: RPC-Net demonstrated a high degree of accuracy in predicting hand position from electromyographic activity, outperforming other solutions with the same computational cost. Including previous position data consistently improved results across subjects and conditions. RPC-Net showed robustness against a reduction in the number of electromyography electrodes used and shorter input signals, indicating potential for further reduction in computational cost. Conclusion: The results demonstrate that RPC-Net is capable of accurately translating forearm electromyographic activity into hand position, offering a practical and adaptable tool that may be accessible in clinical settings. Significance: The development of RPC-Net represents a significant advancement. In clinical settings, its application could enable prosthetic devices to be controlled in a way that feels more natural, improving the quality of life for individuals with limb loss

Chitosan Micro-Grooved Membranes with Increased Asymmetry for the Improvement of the Schwann Cell Response in Nerve Regeneration

Peripheral nerve injuries are a common condition in which a nerve is damaged, affecting more than one million people every year. There are still no efficient therapeutic treatments for these injuries. Artificial scaffolds can offer new opportunities for nerve regeneration applications; in this framework, chitosan is emerging as a promising biomaterial. Here, we set up a simple and effective method for the production of micro-structured chitosan films by solvent casting, with high fidelity in the micro-pattern reproducibility. Three types of chitosan directional micro-grooved patterns, presenting different levels of symmetricity, were developed for application in nerve regenerative medicine: gratings (GR), isosceles triangles (ISO) and scalene triangles (SCA). The directional patterns were tested with a Schwann cell line. The most asymmetric topography (SCA), although it polarized the cell shaping less efficiently, promoted higher cell proliferation and a faster cell migration, both individually and collectively, with a higher directional persistence of motion. Overall, the use of micro-structured asymmetrical directional topographies may be exploited to enhance the nerve regeneration process mediated by chitosan scaffolds