5 resultados para relevance model
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
One important metaphor, referred to biological theories, used to investigate on organizational and business strategy issues is the metaphor about heredity; an area requiring further investigation is the extent to which the characteristics of blueprints inherited from the parent, helps in explaining subsequent development of the spawned ventures. In order to shed a light on the tension between inherited patterns and the new trajectory that may characterize spawned ventures’ development we propose a model aimed at investigating which blueprints elements might exert an effect on business model design choices and to which extent their persistence (or abandonment) determines subsequent business model innovation. Under the assumption that academic and corporate institutions transmit different genes to their spin-offs, we hence expect to have heterogeneity in elements that affect business model design choices and its subsequent evolution. This is the reason why we carry on a twofold analysis in the biotech (meta)industry: under a multiple-case research design, business model and especially its fundamental design elements and themes scholars individuated to decompose the construct, have been thoroughly analysed. Our purpose is to isolate the dimensions of business model that may have been the object of legacy and the ones along which an experimentation and learning process is more likely to happen, bearing in mind that differences between academic and corporate might not be that evident as expected, especially considering that business model innovation may occur.
Resumo:
MultiProcessor Systems-on-Chip (MPSoC) are the core of nowadays and next generation computing platforms. Their relevance in the global market continuously increase, occupying an important role both in everydaylife products (e.g. smartphones, tablets, laptops, cars) and in strategical market sectors as aviation, defense, robotics, medicine. Despite of the incredible performance improvements in the recent years processors manufacturers have had to deal with issues, commonly called “Walls”, that have hindered the processors development. After the famous “Power Wall”, that limited the maximum frequency of a single core and marked the birth of the modern multiprocessors system-on-chip, the “Thermal Wall” and the “Utilization Wall” are the actual key limiter for performance improvements. The former concerns the damaging effects of the high temperature on the chip caused by the large power densities dissipation, whereas the second refers to the impossibility of fully exploiting the computing power of the processor due to the limitations on power and temperature budgets. In this thesis we faced these challenges by developing efficient and reliable solutions able to maximize performance while limiting the maximum temperature below a fixed critical threshold and saving energy. This has been possible by exploiting the Model Predictive Controller (MPC) paradigm that solves an optimization problem subject to constraints in order to find the optimal control decisions for the future interval. A fully-distributedMPC-based thermal controller with a far lower complexity respect to a centralized one has been developed. The control feasibility and interesting properties for the simplification of the control design has been proved by studying a partial differential equation thermal model. Finally, the controller has been efficiently included in more complex control schemes able to minimize energy consumption and deal with mixed-criticalities tasks
Resumo:
Spatial prediction of hourly rainfall via radar calibration is addressed. The change of support problem (COSP), arising when the spatial supports of different data sources do not coincide, is faced in a non-Gaussian setting; in fact, hourly rainfall in Emilia-Romagna region, in Italy, is characterized by abundance of zero values and right-skeweness of the distribution of positive amounts. Rain gauge direct measurements on sparsely distributed locations and hourly cumulated radar grids are provided by the ARPA-SIMC Emilia-Romagna. We propose a three-stage Bayesian hierarchical model for radar calibration, exploiting rain gauges as reference measure. Rain probability and amounts are modeled via linear relationships with radar in the log scale; spatial correlated Gaussian effects capture the residual information. We employ a probit link for rainfall probability and Gamma distribution for rainfall positive amounts; the two steps are joined via a two-part semicontinuous model. Three model specifications differently addressing COSP are presented; in particular, a stochastic weighting of all radar pixels, driven by a latent Gaussian process defined on the grid, is employed. Estimation is performed via MCMC procedures implemented in C, linked to R software. Communication and evaluation of probabilistic, point and interval predictions is investigated. A non-randomized PIT histogram is proposed for correctly assessing calibration and coverage of two-part semicontinuous models. Predictions obtained with the different model specifications are evaluated via graphical tools (Reliability Plot, Sharpness Histogram, PIT Histogram, Brier Score Plot and Quantile Decomposition Plot), proper scoring rules (Brier Score, Continuous Rank Probability Score) and consistent scoring functions (Root Mean Square Error and Mean Absolute Error addressing the predictive mean and median, respectively). Calibration is reached and the inclusion of neighbouring information slightly improves predictions. All specifications outperform a benchmark model with incorrelated effects, confirming the relevance of spatial correlation for modeling rainfall probability and accumulation.
Resumo:
Purpose. Despite work-related stress is one of the most studied topic in organizational psychology, many aspects as for example the use of different measures (e.g. subjective and objective, qualitative and quantitative) are still under debate. According to this, in order to enhance knowledge concerning which factors and processes contribute to create healthy workplaces, this thesis is composed by four different studies aiming to understand: a) the role of relevant antecedents (e.g. leadership, job demands, work-family conflict, social support etc.) and outcomes (e.g. workplace phobia, absenteeism etc.) of work-related stress; and b) how to manage psychosocial risk factors in the workplace. The studies. The first study focused on how disagreement between supervisors and their employees on leadership style (transformational and transactional) could affect workers well-being and work team variables. The second and third study used both subjective and objective data in order to increase the quality of the reliability of the results gained. Particularly, the second study focused on job demand and its relationship with objective sickness leave. Findings showed that despite there is no direct relationship between these two variables, job demand affects work-family conflict, which in turn affect exhaustion, which leads to absenteeism. The third study analysed the role of a new concept never studied before in organizational settings (workplace phobia), as a health outcome in the JD-R model, demonstrating also its relationship with absenteeism. The last study highlighted the added value of using the mixed methods research approach in order to detect and analyse context-specific job demands which could affects workers’ health. Conclusion. The findings of this thesis answered both to open questions in the scientific literature and to the social request of managing psychosocial risk factors in the workplace in order to enhance workers well-being.
Resumo:
Lipid peroxidation is a complex mechanism that causes the degradation of lipid material of both industrial and biological significance. During processing, it is known that thermal stress produces oxidation and polymerization of oils. Additionally, biological lipids with both structural and bioactive roles are prone to peroxidation, which can have pathogenic effects including cancer and long-term degenerative disorders. To create innovative strategies to slow down the deterioration of lipids, it is crucial to improve our understanding of oxidation reactions and kinetics. To this purpose, Chapter II of this thesis focuses on the kinetic study of the oxidation reactions that take place during the thermal processing of bio-oils for industrial application. Through a new method it was possible to evaluate the kinetic parameters of oxidation of various lipid materials. This allowed us to distinguish between the different lipid materials based on their intrinsic properties. The effect of 18 antioxidants from the major families of natural and synthetic phenols were studied using the same methodology in order to acquire crucial data for enhancing the antioxidant activity of phenols based on structure-activity at high temperatures. Finally, it has been described how the antioxidant activity of α-tocopherol, revealed to be scarce in our conditions, can be improved in the presence of gamma-terpinene, through a synergistic action. Chapter III describes the synthesis and study of the antioxidant activity of polydopamine nanoparticles, in order to clarify the unclear mechanism of action of this material. Finally, in Chapter IV it was reported how the gamma-terpinene strongly inhibits the peroxidation of unsaturated lipids in heterogeneous model systems (micelles and liposomes) by forming hydroperoxyl radicals which diffuse outside the lipid nucleus, blocking the propagation of the chain radical. Furthermore, gamma-terpinene shows a very potent protective activity against ferroptosis being effective in the nanomolar range in the human neuroblastoma cell model.