I fondi pensione in Italia. Un confronto con il sistema statunitense.

Analisi della normativa, degli aspetti gestionali e dello stato dell'arte dei fondi pensione italiani. Breve analisi del sistema statunitense e confronto dei principali indicatori con quelli italiani

Empowered or engaged employees? A fuzzy set analysis on knowledge transfer professionals

Purpose This paper combines the literature on knowledge transfer and that on organizational behavior to analyze how perceived empowerment and perceived engagement affect knowledge transfer offices’ (KTOs’) performance, measured in terms of the number of license agreements. Design/methodology/approach The authors measured the cognitions which constitute perceived empowerment and perceived engagement through a survey sent to Italian KTOs’ professionals. The authors performed “fuzzy set qualitative analysis” to investigate if this cognition, together or in isolation, may influence KTOs’ management performance, measured by the number of license agreements. Findings The results highlight the role of individual cognitions in influencing KTOs’ performance. Furthermore, an important finding from the analysis of the main configurations is that the co-presence of perceived engagement and perceived empowerment leads to more license agreements only in the presence of specific individual cognitions. More precisely, the level of organizational citizenship behavior, the degree to which an individual influences results at work (degree of impact) and the value of a work goal (degree of meaning) are the cognitions which lead to a higher number of license agreements. Originality/value Despite the growing interest in the investigation of the determinants of KTOs’ performance, a relevant research gap still concerns the explanation of KTOs’ performance considering individual cognitions such as attitudes, norms, perceived behavioral control and intentions. This study looks at the combined effect of the individual cognition of perceived engagement and perceived empowerment on KTOs’ performances

Not just numbers! Improving TTO performance by balancing the soft sides of the TQM

Purpose: This study investigates the role of “soft” factors of total quality management – in terms of empowerment and engagement of employees – in facilitating or hindering organizational performance of the university technology transfer offices. Design/methodology/approach: The authors developed an Ordinary Least Squares (OLS), multiple regression model to test if empowerment and engagement affect organizational performance of the university technology transfer offices. Findings: The authors found that “soft” factors of total quality management – in terms of empowerment and engagement – facilitate the improvement of organizational performance in university technology transfer offices. Practical implications: The authors’ analysis shows that soft total quality management practices create the conditions for improving organizational performance. This study provides practical implications by showing that, in the evaluation of the technology transfer office, not only the “hard” variables (e.g. number of employees and employee experience) but also the “soft” one (e.g. empowerment and engagement) matter. Therefore, university technology transfer managers or university technology transfer delegates should take actions to promote not only empowering employees but also create a climate conducive to employees' engagement in the university technology transfer offices. Originality/value: With regards to the differences in organizational performances of university technology transfer offices, several studies have focused their attention on technology transfer professionals in technology transfer offices, but only a few of them have examined the “soft side” of total quality management. Thus, this study examines the organizational goals of technology transfer offices through “soft” factors of total quality management in terms of empowerment and engagement employees

Localization of anatomical changes in patients during proton therapy with in-beam PET monitoring: a voxel-based morphometry approach exploiting Monte Carlo simulations

Purpose: In-beam positron emission tomography (PET) is one of the modalities that can be used for in vivo noninvasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy-to-interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in-beam PET monitoring images that can be used to locate, quantify, and visualize regions with possible morphological changes occurring over the course of treatment. Methods: We selected a patient treated for squamous cell carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel-wise two-tailed statistical tests of the simulated PET images, resembling the voxel-based morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the change. Results: The VBM resembling method has been successfully applied to the simulated in-beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify interfractional morphological changes and to visualize them superimposed on the computed tomography (CT) scan. In particular, the characteristic color patterns resulting from the two-tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of treatment. Conclusions: The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal interfractional morphological changes in patients, occurring over the course of treatment. Based on simulated in-beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments

In-vivo range verification analysis with in-beam PET data for patients treated with proton therapy at CNAO

Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam's Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5 mm with the MLS method and 2.3 mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan