Do Academic and Private Entrepreneurs differ? An empirical analysis of the Micro-Foundation of Entrepreneurial Orientation

This Doctoral Thesis focuses on the study of individual behaviours as a result of organizational affiliation. The objective is to assess the Entrepreneurial Orientation of individuals proving the existence of a set of antecedents to that measure returning a structural model of its micro-foundation. Relying on the developed measurement model, I address the issue whether some Entrepreneurs experience different behaviours as a result of their academic affiliation, comparing a sample of ‘Academic Entrepreneurs’ to a control sample of ‘Private Entrepreneurs’ affiliated to a matched sample of Academic Spin-offs and Private Start-ups. Building on the Theory of the Planned Behaviour, proposed by Ajzen (1991), I present a model of causal antecedents of Entrepreneurial Orientation on constructs extensively used and validated, both from a theoretical and empirical perspective, in sociological and psychological studies. I focus my investigation on five major domains: (a) Situationally Specific Motivation, (b) Personal Traits and Characteristics, (c) Individual Skills, (d) Perception of the Business Environment and (e) Entrepreneurial Orientation Related Dimensions. I rely on a sample of 200 Entrepreneurs, affiliated to a matched sample of 72 Academic Spin-offs and Private Start-ups. Firms are matched by Industry, Year of Establishment and Localization and they are all located in the Emilia Romagna region, in northern Italy. I’ve gathered data by face to face interviews and used a Structural Equation Modeling technique (Lisrel 8.80, Joreskog, K., & Sorbom, D. 2006) to perform the empirical analysis. The results show that Entrepreneurial Orientation is a multi-dimensional micro-founded construct which can be better represented by a Second-Order Model. The t-tests on the latent means reveal that the Academic Entrepreneurs differ in terms of: Risk taking, Passion, Procedural and Organizational Skills, Perception of the Government, Context and University Supports. The Structural models also reveal that the main differences between the two groups lay in the predicting power of Technical Skills, Perceived Context Support and Perceived University Support in explaining the Entrepreneurial Orientation Related Dimensions.

TiMMing: developing an innovative suite of bioinformatic tools to harmonize and track the origin of copy number alterations in the evolutive history of multiple myeloma

Multiple Myeloma (MM) is a hematologic cancer with heterogeneous and complex genomic landscape, where Copy Number Alterations (CNAs) play a key role in the disease's pathogenesis and prognosis. It is of biological and clinical interest to study the temporal occurrence of early alterations, as they play a disease "driver" function by deregulating key tumor pathways. This study presents an innovative bioinformatic tools suite created for harmonizing and tracing the origin of CNAs throughout the evolutionary history of MM. To this aim, large cohorts of newly-diagnosed MM (NDMM, N=1582) and Smoldering-MM (SMM, N=282) were aggregated. The tools developed in this study enable the harmonization of CNAs as obtained from different genomic platforms in such a way that a high statistical power can be obtained. By doing so, the high numerosity of those cohorts was harnessed for the identification of novel genes characterized as "driver" (NFKB2, NOTCH2, MAX, EVI5 and MYC-ME2-enhancer), and the generation of an innovative timing model, implemented with a statistical method to introduce confidence intervals in the CNAs-calls. By applying this model on both NDMM and SMM cohorts, it was possible to identify specific CNAs (1q(CKS1B)amp, 13q(RB1)del, 11q(CCND1)amp and 14q(MAX)del) and categorize them as "early"/ "driver" events. A high level of precision was guaranteed by the narrow confidence intervals in the timing estimates. These CNAs were proposed as critical MM alterations, which play a foundational role in the evolutionary history of both SMM and NDMM. Finally, a multivariate survival model was able to identify the independent genomic alterations with the greatest effect on patients’ survival, including RB1-del, CKS1B-amp, MYC-amp, NOTCH2-amp and TRAF3-del/mut. In conclusion, the alterations that were identified as both "early-drivers” and correlated with patients’ survival were proposed as biomarkers that, if included in wider survival models, could provide a better disease stratification and an improved prognosis definition.

Model selection and the vectorial misspecification-resistant information criterion in multivariate time series

The thesis deals with the problem of Model Selection (MS) motivated by information and prediction theory, focusing on parametric time series (TS) models. The main contribution of the thesis is the extension to the multivariate case of the Misspecification-Resistant Information Criterion (MRIC), a criterion introduced recently that solves Akaike’s original research problem posed 50 years ago, which led to the definition of the AIC. The importance of MS is witnessed by the huge amount of literature devoted to it and published in scientific journals of many different disciplines. Despite such a widespread treatment, the contributions that adopt a mathematically rigorous approach are not so numerous and one of the aims of this project is to review and assess them. Chapter 2 discusses methodological aspects of MS from information theory. Information criteria (IC) for the i.i.d. setting are surveyed along with their asymptotic properties; and the cases of small samples, misspecification, further estimators. Chapter 3 surveys criteria for TS. IC and prediction criteria are considered for: univariate models (AR, ARMA) in the time and frequency domain, parametric multivariate (VARMA, VAR); nonparametric nonlinear (NAR); and high-dimensional models. The MRIC answers Akaike’s original question on efficient criteria, for possibly-misspecified (PM) univariate TS models in multi-step prediction with high-dimensional data and nonlinear models. Chapter 4 extends the MRIC to PM multivariate TS models for multi-step prediction introducing the Vectorial MRIC (VMRIC). We show that the VMRIC is asymptotically efficient by proving the decomposition of the MSPE matrix and the consistency of its Method-of-Moments Estimator (MoME), for Least Squares multi-step prediction with univariate regressor. Chapter 5 extends the VMRIC to the general multiple regressor case, by showing that the MSPE matrix decomposition holds, obtaining consistency for its MoME, and proving its efficiency. The chapter concludes with a digression on the conditions for PM VARX models.

Development of human visual system analysis for the implementation of a new instrument for flicker measurement

Flicker is a power quality phenomenon that applies to cycle instability of light intensity resulting from supply voltage fluctuation, which, in turn can be caused by disturbances introduced during power generation, transmission or distribution. The standard EN 61000-4-15 which has been recently adopted also by the IEEE as IEEE Standard 1453 relies on the analysis of the supply voltage which is processed according to a suitable model of the lamp – human eye – brain chain. As for the lamp, an incandescent 60 W, 230 V, 50 Hz source is assumed. As far as the human eye – brain model is concerned, it is represented by the so-called flicker curve. Such a curve was determined several years ago by statistically analyzing the results of tests where people were subjected to flicker with different combinations of magnitude and frequency. The limitations of this standard approach to flicker evaluation are essentially two. First, the provided index of annoyance Pst can be related to an actual tiredness of the human visual system only if such an incandescent lamp is used. Moreover, the implemented response to flicker is “subjective” given that it relies on the people answers about their feelings. In the last 15 years, many scientific contributions have tackled these issues by investigating the possibility to develop a novel model of the eye-brain response to flicker and overcome the strict dependence of the standard on the kind of the light source. In this light of fact, this thesis is aimed at presenting an important contribution for a new Flickermeter. An improved visual system model using a physiological parameter that is the mean value of the pupil diameter, has been presented, thus allowing to get a more “objective” representation of the response to flicker. The system used to both generate flicker and measure the pupil diameter has been illustrated along with all the results of several experiments performed on the volunteers. The intent has been to demonstrate that the measurement of that geometrical parameter can give reliable information about the feeling of the human visual system to light flicker.

Changes in tumor stiffness for early prediction of tumor response to sorafenib: a proof-of-concept study with elastosonography in an animal model of Hepatocellular Carcinoma (HCC)

Background and aims: Sorafenib is the reference therapy for advanced Hepatocellular Carcinoma (HCC). No method exists to predict in the very early period subsequent individual response. Starting from the clinical experience in humans that subcutaneous metastases may rapidly change consistency under sorafenib and that elastosonography a new ultrasound based technique allows assessment of tissue stiffness, we investigated the role of elastonography in the very early prediction of tumor response to sorafenib in a HCC animal model. Methods: HCC (Huh7 cells) subcutaneous xenografting in mice was utilized. Mice were randomized to vehicle or treatment with sorafenib when tumor size was 5-10 mm. Elastosonography (Mylab 70XVG, Esaote, Genova, Italy) of the whole tumor mass on a sagittal plane with a 10 MHz linear transducer was performed at different time points from treatment start (day 0, +2, +4, +7 and +14) until mice were sacrified (day +14), with the operator blind to treatment. In order to overcome variability in absolute elasticity measurement when assessing changes over time, values were expressed in arbitrary units as relative stiffness of the tumor tissue in comparison to the stiffness of a standard reference stand-off pad lying on the skin over the tumor. Results: Sor-treated mice showed a smaller tumor size increase at day +14 in comparison to vehicle-treated (tumor volume increase +192.76% vs +747.56%, p=0.06). Among Sor-treated tumors, 6 mice showed a better response to treatment than the other 4 (increase in volume +177% vs +553%, p=0.011). At day +2, median tumor elasticity increased in Sor-treated group (+6.69%, range –30.17-+58.51%), while decreased in the vehicle group (-3.19%, range –53.32-+37.94%) leading to a significant difference in absolute values (p=0.034). From this time point onward, elasticity decreased in both groups, with similar speed over time, not being statistically different anymore. In Sor-treated mice all 6 best responders at day 14 showed an increase in elasticity at day +2 (ranging from +3.30% to +58.51%) in comparison to baseline, whereas 3 of the 4 poorer responders showed a decrease. Interestingly, these 3 tumours showed elasticity values higher than responder tumours at day 0. Conclusions: Elastosonography appears a promising non-invasive new technique for the early prediction of HCC tumor response to sorafenib. Indeed, we proved that responder tumours are characterized by an early increase in elasticity. The possibility to distinguish a priori between responders and non responders based on the higher elasticity of the latter needs to be validated in ad-hoc experiments as well as a confirmation of our results in humans is warranted.

Measurement of branching fractions and CP violation for charmless charged two-body B decays at LHCb

Charmless charged two-body B decays are sensitive probes of the CKM matrix, that parameterize CP violation in the Standard Model (SM), and have the potential to reveal the presence of New Physics. The framework of CP violation within the SM, the role of the CKM matrix, with its basic formalism, and the current experimental status are presented. The theoretical tools commonly used to deal with hadronic B decays and an overview of the phenomenology of charmless two-body B decays are outlined. LHCb is one of the four main experiments operating at the Large Hadron Collider (LHC), devoted to the measurement of CP violation and rare decays of charm and beauty hadrons. The LHCb detector is described, focusing on the technologies adopted for each sub-detector and summarizing their performances. The status-of-the-art of the LHCb measurements with charmless two-body B decays is then presented. Using the 37/pb of integrated luminosity collected at sqrt(s) = 7 TeV by LHCb during 2010, the direct CP asymmetries ACP(B0 -> Kpi) = −0.074 +/- 0.033 +/- 0.008 and ACP(Bs -> piK) = 0.15 +/- 0.19 +/- 0.02 are measured. Using 320/pb of integrated luminosity collected during 2011 these measurements are updated to ACP(B0 -> Kpi) = −0.088 +/- 0.011 +/- 0.008 and ACP(Bs -> piK) = 0.27 +/- 0.08 +/- 0.02. In addition, the branching ratios BR(B0 -> K+K-) = (0.13+0.06-0.05 +/- 0.07) x 10^-6 and BR(Bs -> pi+pi-) = (0.98+0.23-0.19 +/- 0.11) x 10^-6 are measured. Finally, using a sample of 370/pb of integrated luminosity collected during 2011, the relative branching ratios BR(B0 -> pi+pi-)/BR(B0 -> Kpi) = 0.262 +/- 0.009 +/- 0.017, (fs/fd)BR(Bs -> K+K-)/BR(B0 -> Kpi)=0.316 +/- 0.009 +/- 0.019, (fs/fd)BR(Bs -> piK)/BR(B0 -> Kpi) = 0.074 +/- 0.006 +/- 0.006 and BR(Lambda_b -> ppi)/BR(Lambda_b -> pK)=0.86 +/- 0.08 +/- 0.05 are determined.

Work and Family: a complex interplay. An Italian application of the DISC Model on health care workers

The present thesis investigates the issue of work-family conflict and facilitation in a sanitarian contest, using the DISC Model (De Jonge and Dormann, 2003, 2006). The general aim has been declined in two empirical studies reported in this dissertation chapters. Chapter 1 reporting the psychometric properties of the Demand-Induced Strain Compensation Questionnaire. Although the empirical evidence on the DISC Model has received a fair amount of attention in literature both for the theoretical principles and for the instrument developed to display them (DISQ; De Jonge, Dormann, Van Vegchel, Von Nordheim, Dollard, Cotton and Van den Tooren, 2007) there are no studies based solely on psychometric investigation of the instrument. In addition, no previous studies have ever used the DISC as a model or measurement instrument in an Italian context. Thus the first chapter of the present dissertation was based on psychometric investigation of the DISQ. Chapter 2 reporting a longitudinal study contribution. The purpose was to examine, using the DISC model, the relationship between emotional job characteristics, work-family interface and emotional exhaustion among a health care population. We started testing the Triple Match Principle of the DISC Model using solely the emotional dimension of the strain-stress process (i.e. emotional demands, emotional resources and emotional exhaustion). Then we investigated the mediator role played by w-f conflict and w-f facilitation in relation to emotional job characteristics and emotional exhaustion. Finally we compared the mediator model across workers involved in chronic illness home demands and workers who are not involved. Finally, a general conclusion, integrated and discussed the main findings of the studies reported in this dissertation.

General effective medium model for the complex permittivity extraction with an open-ended coaxial probe in presence of a multilayer material under test

The work presented in this thesis is focused on the open-ended coaxial-probe frequency-domain reflectometry technique for complex permittivity measurement at microwave frequencies of dispersive dielectric multilayer materials. An effective dielectric model is introduced and validated to extend the applicability of this technique to multilayer materials in on-line system context. In addition, the thesis presents: 1) a numerical study regarding the imperfectness of the contact at the probe-material interface, 2) a review of the available models and techniques, 3) a new classification of the extraction schemes with guidelines on how they can be used to improve the overall performance of the probe according to the problem requirements.

Parameter estimation in a growth model for a biological population

The motivating problem concerns the estimation of the growth curve of solitary corals that follow the nonlinear Von Bertalanffy Growth Function (VBGF). The most common parameterization of the VBGF for corals is based on two parameters: the ultimate length L∞ and the growth rate k. One aim was to find a more reliable method for estimating these parameters, which can capture the influence of environmental covariates. The main issue with current methods is that they force the linearization of VBGF and neglect intra-individual variability. The idea was to use the hierarchical nonlinear model which has the appealing features of taking into account the influence of collection sites, possible intra-site measurement correlation and variance heterogeneity, and that can handle the influence of environmental factors and all the reliable information that might influence coral growth. This method was used on two databases of different solitary corals i.e. Balanophyllia europaea and Leptopsammia pruvoti, collected in six different sites in different environmental conditions, which introduced a decisive improvement in the results. Nevertheless, the theory of the energy balance in growth ascertains the linear correlation of the two parameters and the independence of the ultimate length L∞ from the influence of environmental covariates, so a further aim of the thesis was to propose a new parameterization based on the ultimate length and parameter c which explicitly describes the part of growth ascribable to site-specific conditions such as environmental factors. We explored the possibility of estimating these parameters characterizing the VBGF new parameterization via the nonlinear hierarchical model. Again there was a general improvement with respect to traditional methods. The results of the two parameterizations were similar, although a very slight improvement was observed in the new one. This is, nevertheless, more suitable from a theoretical point of view when considering environmental covariates.

Multidimensional Measures of Firm Competitiveness: a Model-Based Approach

The concept of competitiveness, for a long time considered as strictly connected to economic and financial performances, evolved, above all in recent years, toward new, wider interpretations disclosing its multidimensional nature. The shift to a multidimensional view of the phenomenon has excited an intense debate involving theoretical reflections on the features characterizing it, as well as methodological considerations on its assessment and measurement. The present research has a twofold objective: going in depth with the study of tangible and intangible aspect characterizing multidimensional competitive phenomena by assuming a micro-level point of view, and measuring competitiveness through a model-based approach. Specifically, we propose a non-parametric approach to Structural Equation Models techniques for the computation of multidimensional composite measures. Structural Equation Models tools will be used for the development of the empirical application on the italian case: a model based micro-level competitiveness indicator for the measurement of the phenomenon on a large sample of Italian small and medium enterprises will be constructed.

Measurement of the ZZ production cross section and limits on anomalous neutral triple gauge couplings with ATLAS

The main work of this thesis concerns the measurement of the production cross section using LHC 2011 data collected at a center-of-mass energy equal to 7 TeV by the ATLAS detector and resulting in a total integrated luminosity of 4.6 inverse fb. The ZZ total cross section is finally compared with the NLO prediction calculated with modern Monte Carlo generators. In addition, the three differential distributions (∆φ(l,l), ZpT and M4l) are shown unfolded back to the underlying distributions using a Bayesian iterative algorithm. Finally, the transverse momentum of the leading Z is used to provide limits on anoumalus triple gauge couplings forbidden in the Standard Model.

Measurement of the differential cross section of tt pairs in pp collision at sqrt(s) = 7TeV with the ATLAS detector at the LHC

In this thesis three measurements of top-antitop differential cross section at an energy in the center of mass of 7 TeV will be shown, as a function of the transverse momentum, the mass and the rapidity of the top-antitop system. The analysis has been carried over a data sample of about 5/fb recorded with the ATLAS detector. The events have been selected with a cut based approach in the "one lepton plus jets" channel, where the lepton can be either an electron or a muon. The most relevant backgrounds (multi-jet QCD and W+jets) have been extracted using data driven methods; the others (Z+ jets, diboson and single top) have been simulated with Monte Carlo techniques. The final, background-subtracted, distributions have been corrected, using unfolding methods, for the detector and selection effects. At the end, the results have been compared with the theoretical predictions. The measurements are dominated by the systematic uncertainties and show no relevant deviation from the Standard Model predictions.

Preharvest factors affecting quality and antioxidant levels on Abate Fétel pears: study of superficial scald with a multivariate statistical approach and neural networks

There are only a few insights concerning the influence that agronomic and management variability may have on superficial scald (SS) in pears. Abate Fétel pears were picked during three seasons (2018, 2019 and 2020) from thirty commercial orchards in the Emilia Romagna region, Italy. Using a multivariate statistical approach, high heterogeneity between farms for SS development after cold storage with regular atmosphere was demonstrated. Indeed, some factors seem to affect SS in all growing seasons: high yields, soil texture, improper irrigation and Nitrogen management, use of plant growth regulators, late harvest, precipitations, Calcium and cow manure, presence of nets, orchard age, training system and rootstock. Afterwards, we explored the spatio/temporal variability of fruit attributes in two pear orchards. Environmental and physiological spatial variables were recorded by a portable RTK GPS. High spatial variability of the SS index was observed. Through a geostatistical approach, some characteristics, including soil electrical conductivity and fruit size, have been shown to be negatively correlated with SS. Moreover, regression tree analyses were applied suggesting the presence of threshold values of antioxidant capacity, total phenolic content, and acidity against SS. High pulp firmness and IAD values before storage, denoting a more immature fruit, appeared to be correlated with low SS. Finally, a convolution neural networks (CNN) was tested to detect SS and the starch pattern index (SPI) in pears for portable device applications. Preliminary statistics showed that the model for SS had low accuracy but good precision, and the CNN for SPI denoted good performances compared to the Ctifl and Laimburg scales. The major conclusion is that Abate Fétel pears can potentially be stored in different cold rooms, according to their origin and quality features, ensuring the best fruit quality for the final consumers. These results might lead to a substantial improvement in the Italian pear industry.

Analytical approaches for the measurement of sulfide in biological and pharmaceutical fields

Hydrogen sulfide (H2S) is a widely recognized gasotransmitter, with key roles in physiological and pathological processes. The accurate quantification of H2S and reactive sulfur species (RSS) may hold important implications for the diagnosis and prognosis of various diseases. However, H2S species quantification in biological matrices is still a challenge. Among the sulfide detection methods, monobromobimane (MBB) derivatization coupled with reversed phase high-performance liquid chromatography (RP-HPLC) is one of the most reported. However, it is characterized by a complex preparation and time-consuming process, which may alter the actual H2S level. Moreover, quantitative validation has still not been described based on a survey of previously published works. In this study, we developed and validated an improved analytical protocol for the MBB RP-HPLC method. Main parameters like MBB concentration, temperature, reaction time, and sample handling were optimized, and the calibration method was further validated using leave-one-out cross-validation (CV) and tested in a clinical setting. The method shows high sensitivity and allows the quantification of H2S species, with a limit of detection (LOD) of 0.5 µM and a limit of quantification (LOQ) of 0.9 µM. Additionally, this model was successfully applied in measurements of H2S levels in the serum of patients subjected to inhalation with vapors rich in H2S. In addition, a properly procedure was established for H2S release with the modified MBB HPLC-FLD method. The proposed analytical approach demonstrated the slow-release kinetics of H2S from the multilayer Silk-Fibroin scaffolds with the combination of different H2S donor’s concentration with respect to the weight of PLGA nanofiber. In the end, some efforts were made on sulfide measurements by using size exclusion chromatography fluorescence/ultraviolet detection and inductively coupled plasma-mass spectrometry (SEC-FLD/UV-ICP/MS). It’s intended as a preliminary study in order to define the feasibility of a separation-detection-quantification platform to analyze biological samples and quantify sulfur species.

Design and testing of innovative, artificial intelligence-based techniques to model and control the combustion process and to reduce the Co2 emissions in modern, high-performance, gasoline direct injection engines

This work deals with the development of calibration procedures and control systems to improve the performance and efficiency of modern spark ignition turbocharged engines. The algorithms developed are used to optimize and manage the spark advance and the air-to-fuel ratio to control the knock and the exhaust gas temperature at the turbine inlet. The described work falls within the activity that the research group started in the previous years with the industrial partner Ferrari S.p.a. . The first chapter deals with the development of a control-oriented engine simulator based on a neural network approach, with which the main combustion indexes can be simulated. The second chapter deals with the development of a procedure to calibrate offline the spark advance and the air-to-fuel ratio to run the engine under knock-limited conditions and with the maximum admissible exhaust gas temperature at the turbine inlet. This procedure is then converted into a model-based control system and validated with a Software in the Loop approach using the engine simulator developed in the first chapter. Finally, it is implemented in a rapid control prototyping hardware to manage the combustion in steady-state and transient operating conditions at the test bench. The third chapter deals with the study of an innovative and cheap sensor for the in-cylinder pressure measurement, which is a piezoelectric washer that can be installed between the spark plug and the engine head. The signal generated by this kind of sensor is studied, developing a specific algorithm to adjust the value of the knock index in real-time. Finally, with the engine simulator developed in the first chapter, it is demonstrated that the innovative sensor can be coupled with the control system described in the second chapter and that the performance obtained could be the same reachable with the standard in-cylinder pressure sensors.