Unicam Activity Framework (UAF)

This presentation illustrates the framework of processing performance of the faculty of the University of Camerino. The evaluation criteria are explained and the technological structure that allows automatic performance assessment available online anywhere and anytime. The designed framework is usually applied to the performance evaluation of staff working for Università di Camerino (ITALY). It has provided excellent results which were positively judged by those who underwent the assessment, who also found that it portrayed their work quite properly

Resistance of sugarcane commercials cultivars to causal agent of ratoon stunting disease

O raquitismo-da-soqueira (RSD), causado pela bactéria Leifsonia xyli subsp. xyli, é uma das mais importantes doenças da cana-de-açúcar nas regiões produtoras do mundo. O presente trabalho teve como objetivo avaliar o grau de resistência de 10 variedades comerciais RB de cana-de-açúcar mais a variedade CB 49-260, a qual foi incluída como padrão suscetível. O trabalho visou avaliar os danos amostrados em campo pelo peso das parcelas em função da relação entre a produtividade de parcelas inoculadas e não inoculadas artificialmente com a bactéria. Os resultados mostraram que as variedades RB 72 454, RB 83 5486, RB 86 7515, RB 92 5211, RB 92 5268, RB 92 5345, RB 92 8064 e a variedade padrão CB 49-260 comportaram-se como variedades suscetíveis. A variedade RB 85 5156 comportou-se como de resistência intermediária e apenas as variedades RB 85 5453 e RB 85 5536 comportaram-se como tolerantes.Ratoon stunting disease (RSD) caused by bacteria Leifsonia xyli subsp. xyli is one of the most economically important disease of sugarcane worldwide. The present survey had objective to evaluate the resistance of 10 RB commercial cultivars of sugarcane including CB 49-260 as a susceptible standard. The study evaluated the correlating the damages presented for overhauls productivity of inoculate and non inoculate parcels with the bacteria. The results showed that varieties RB 72 454, RB 83 5486, RB 86 7515, RB 92 8064, RB 92 5211, RB 92 5345 and RB 92 5268 were susceptible. RB 85 5156 had a intermediary resistance and varieties RB 85 5453 and RB 85 5536 both showed tolerant behavior

Cloud for eGov: the state of the art

Specifically, the paper provides a detailed analysis of the state of the art regarding technological, regulatory and interoperability aspects, devoting particular attention to those projects (and related experience) in the field of cloud and distributed computing. The paper's aim is to evaluate benefits and risks of the applicability of solutions that are already in place for the specified areas of interest. The key factors that determine relevant regulations, with particular emphasis on the European target, have been listed in the paper. Finally, the main Italian projects and the situation in some European countries have also been mentioned

Work environment, volume of activity and staffing in neonatal intensive care units in Italy: results of the SONAR-nurse study

Neonatal units' volume of activity, and other quantitative and qualitative variables, such as staffing, workload, work environment, care organization and geographical location, may influence the outcome of high risk newborns. Data about the distribution of these variables and their relationships among Italian neonatal units are lacking

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 <30 weeks gestational age, or <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 < 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

Development and In Vivo Evaluation of Multidrug Ultradeformable Vesicles for the Treatment of Skin Inflammation

The aim of this work was to evaluate the effect of two chemically different edge activators, i.e., Tween® 80 and sodium deoxycholate, on (i) the physical, mechanical, and biological properties of ultradeformable vesicles, and (ii) the administration of naproxen sodium-loaded multidrug ultradeformable vesicles for the transdermal route in order to obtain therapeutically meaningful drug concentrations in the target tissues and to potentiate its anti-inflammatory effect by association with the antioxidant drug idebenone. The results obtained in this investigation highlighted a synergistic action between naproxen and idebenone in the treatment of inflammatory disease with a more pronounced anti-inflammatory effect in multidrug ultradeformable vesicles compared to the commercial formulation of Naprosyn® gel. Systems made up of Tween® 80 appeared to be the most suitable in terms of percutaneous permeation and anti-inflammatory activity due to the greater deformability of these vesicles compared to multidrug ultradeformable vesicles with sodium deoxycholate. Our findings are very encouraging and suggest the use of these carriers in the topical treatment of inflammatory diseases

Cell wall-associated alpha-glucan is instrumental for Mycobacterium tuberculosis to block CD1 molecule expression and disable the function of dendritic cell derived from infected monocyte.

Summary We previously described an escape mechanism exploited by Mycobacterium tuberculosis (Mtb) to prevent the generation of fully competent dendritic cells (DC). We have now tested the effect of isolated mycobacterial components on human monocyte dif- ferentiation into DC and demonstrated that cell wall (CW)-associated alpha-glucan induces monocytes to differentiate into DC (Glu-MoDC) with the same altered phenotype and functional behaviour of DC derived from Mtb-infected monocytes (Mt-MoDC). In fact, Glu- MoDC lack CD1 molecule expression, fail to upregu- late CD80 and produce IL-10 but not IL-12. We also showed that Glu-MoDC are not able to prime effector T cells or present lipid antigens to CD1-restricted T-cell clones. Thus, we propose a mechanism of Mtb- monocyte interaction mediated by CW-associated alpha-glucan, which allows the bacterium to evade both innate and acquired immune responses

A novel strategy for balancing the workload of industrial lines based on a genetic algorithm

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksOne major problem in industrial automation is the workload balancing problem. It consists of making the robots or, more generally, the machines, involved in the assembly process to work exactly the same, either by picking and placing the same number of pieces or by having the same number of operational cycles. This paper presents a novel strategy for solving such a problem by means of an evolutionary algorithm. The specific application of this strategy is to balance the workload of a pick-and-place process developed in the facilities of the industrial company Fameccanica Spa Data within the framework of an industrial project between the company and our research group. The novelties concerning the state-of-the-art contributions are: (1) instead of using an explicit fitness function, the candidate solutions at each iteration are evaluated by using a simulation of the entire process; (2) the parameters optimized are the velocity and acceleration of the robots involved in the line and (3) the strategy includes an algorithm for distributing the workload between the robots during the process.Peer ReviewedPostprint (author's final draft