Study of innovative methods of control in the cereal productive chain for the production of beer and spirits

Researches performed during the PhD course intended to assess innovative applications of near-infrared spectroscopy in reflectance (NIR) in the production chain of beer. The purpose is to measure by NIR the "malting quality" (MQ) parameter of barley, to monitor the malting process and to know if a certain type of barley is suitable for the production of beer and spirits. Moreover, NIR will be applied to monitor the brewing process. First of all, it was possible to check the quality of the raw materials like barley, maize and barley malt using a rapid, non-destructive and reliable method, with a low error of prediction. The more interesting result obtained at this level was that the repeatability of the NIR calibration models developed was comparable with the one of the reference method. Moreover, about malt, new kinds of validation were used in order to estimate the real predictive power of the proposed calibration models and to understand the long-term effects. Furthermore, the precision of all the calibration models developed for malt evaluation was estimated and statistically compared with the reference methods, with good results. Then, new calibration models were developed for monitoring the malting process, measuring the moisture content and other malt quality parameters during germination. Moreover it was possible to obtain by NIR an estimate of the "malting quality" (MQ) of barley and to predict whether if its germination will be rapid and uniform and if a certain type of barley is suitable for the production of beer and spirits. Finally, the NIR technique was applied to monitor the brewing process, using correlations between NIR spectra of beer and analytical parameters, and to assess beer quality. These innovative results are potentially very useful for the actors involved in the beer production chain, especially the calibration models suitable for the control of the malting process and for the assessment of the “malting quality” of barley, which need to be deepened in future studies.

Ruolo dell'elettrocardiogramma standard nella stratificazione prognostica della cardiomiopatia ipertrofica. Studio multicentrico

Lo scopo di questo studio è di valutare il significato prognostico dell'elettrocardiogramma standard in un'ampia casistica di pazienti affetti da cardiomiopatia ipertrofica. In questo studio multicentrico sono stati considerati 841 pazienti con cardiomiopatia ipertrofica (66% uomini, età media 48±17 anni) per un follow-up di 7.1±7.1 anni, per ognuno è stato analizzato il primo elettrocardiogramma disponibile. I risultati hanno dimostrato come fattori indipendentemente correlati a morte cardiaca improvvisa la sincope inspiegata (p 0.004), il sopraslivellamento del tratto ST e/o la presenza di onde T positive giganti (p 0.048), la durata del QRS >= 120 ms (p 0.017). Sono stati costruiti due modelli per predire il rischio di morte improvvisa: il primo basato sui fattori di rischio universalmente riconosciuti (spessore parietale >= 30 mm, tachicardie ventricolari non sostenute all'ECG Holter 24 ore, sincope e storia familiare di morte improvvisa) e il secondo con l'aggiunta delle variabili sopraslivellamento del tratto ST/onde T positive giganti e durata del QRS >= 120 ms. Entrambi i modelli stratificano i pazienti in base al numero dei fattori di rischio, ma il secondo modello risulta avere un valore predittivo maggiore (chi-square da 12 a 22, p 0.002). In conclusione nella cardiomiopatia ipertrofica l'elettrocardiogramma standard risulta avere un valore prognostico e migliora l'attuale modello di stratificazione per il rischio di morte improvvisa.

Computational modeling of human atrial cardiomyocytes: integration of electro-mechanical & mechano-electric feedback pathways

The cardiomyocytes are very complex consisting of many interlinked non-linear regulatory mechanisms between electrical excitation and mechanical contraction. Thus given a integrated electromechanically coupled system it becomes hard to understand the individual contributor of cardiac electrics and mechanics under both physiological and pathological conditions. Hence, to identify the causal relationship or to predict the responses in a integrated system the use of computational modeling can be beneficial. Computational modeling is a powerful tool that provides complete control of parameters along with the visibility of all the individual components of the integrated system. The advancement of computational power has made it possible to simulate the models in a short timeframe, providing the possibility of increased predictive power of the integrated system. My doctoral thesis is focused on the development of electromechanically integrated human atrial cardiomyocyte model with proper consideration of feedforward and feedback pathways.

Model predictive flight control systems for rotorcraft UAS

Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the development of a model predictive control system for small scale rotorcraft UAS. Several different predictive architectures have been evaluated and tested by means of simulation, as a result of this analysis the most promising one has been used to implement three different control systems: a Stability and Control Augmentation System, a trajectory tracking and a path following system. The systems have been compared with a corresponding baseline controller and showed several advantages in terms of performance, stability and robustness.

Essays On CEO Compensation: New Evidence On The Managerial-Power Vs. Optimal Contracting Debate

This dissertation analyzes the effect of market analysts’ expectations of share prices (price targets) on executive compensation. It examines how well the estimated effects of price targets on compensation fit with two competing views on determining executive compensation: the arm’s length bargaining model, which assumes that a board seeks to maximize shareholders’ interests, and the managerial power model, which assumes that a board seeks to maximize managers’ compensation (Bebchuk et al. 2005). The first chapter documents the pattern of CEO pay from fiscal year 1996 to 2010. The second chapter analyzes the Institutional Broker Estimate System Detail History Price Target data file, which that reports analysts’ price targets for firms. I show that the number of price target announcements is positively associated with company share price’s volatility, that price targets are predictive of changes in the value of stocks, and that when analysts announce positive (negative) expectations of future stock price, share prices change in the same direction in the short run. The third chapter analyzes the effect of price targets on executive compensation. I find that analysts' price targets alter the composition of executive pay between cash-based compensation and stock-based compensation. When analysts forecast a rise (fall) in the share price for a firm, the compensation package tilts toward stock-based (cash-based) compensation. The substitution effect is stronger in companies that have weaker corporate governance. The fourth chapter explores the effect of the introduction of the Sarbanes-Oxley Act (SOX) in 2002 and its reinforcement in 2006 on the options granting process. I show that the introduction of SOX and its reinforcement eliminated the practice of backdating options but increased “spring-loading” of option grants around price targets announcements. Overall, the dissertation shows that price targets provide insights into the determinants of executive pay in favor of the managerial power model.

Model predictive control in thermal management of multiprocessor systems-on-chip

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