18 resultados para Variable Duty Cycle Control

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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The Notch signalling is a cellular pathway that results conserved from Drosophila to Homo sapiens controlling a wide range of cellular processes in development and in differentiated organs. It induces cell proliferation or differentiation, increased survival or apoptosis, and it is involved in stemness maintainance. These functions are conserved, but exerted with a high tissue and cellular context specificity. Signalling activation determs nuclear translocation of the receptor’s cytoplasmic domain and activation of target genes transcription. As many developmental pathway, Notch deregulation is involved in cancer, leading to oncogenic or tumour suppressive role depending on the functions exerted in normal tissue. Notch1 and Notch3 resulted aberrantly expressed in human hepatocellular carcinoma (HCC) that is the more frequent tumour of the liver and the sixth most common tumour worldwide. This thesis has the aim to investigate the role of the signalling in HCC, with particular attention to dissect common and uncommon regulatory pathways between Notch1 and Notch3 and to define the role of the signalling in HCC. Nocth1 and Notch3 were analysed on their regulation on Hes1 target and involvement in cell cycle control. They showed to regulate CDKN1C/p57kip2 expression through Hes1 target. CDKN1C/p57kip2 induces not only cell cycle arrest, but also senescence in HCC cell lines. Moreover, the involvement of Notch1 in cancer progression and epithelial to mesenchymal transition was investigated. Notch1 showed to induce invasion of HCC, regulating EMT and E- Cadherin expression. Moreover, Notch3 showed specific regulation on p53 at post translational levels. In vitro and ex vivo analysis on HCC samples suggests a complex role of both receptors in regulate HCC, with an oncogenic role but also showing tumour suppressive effects, suggesting a complex and deep involvement of this signalling in HCC.

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E2F-1 is a transcription factor that plays a key role in cell-cycle control at G1/S check-point level by regulating the timely expression of many target genes whose products are required for S phase entry and progression. In mammalian cells, E2F-1 is negatively regulated by hypo-phosphorylated Retinoblastoma protein (pRb) whereas it is protected against degradation by its binding to Mouse Double Minute 2 protein (MDM2). In this study we experimented a drug combination in order to obtain a strong down-regulation of E2F-1 by acting on two different mechanisms of E2F-1 regulation mentioned above. This was achieved by combining drugs inhibiting the phosphorylation of pRb with drugs inactivating the MDM2 binding capability. The mechanism of action of these drugs in down-regulating E2F-1 level and activity is p53 independent. As expected, when combined, these drugs strongly inhibits E2F-1 and hinder cell proliferation in p53-/- and p53-mutated cells by blocking them in G1 phase of cell cycle, suggesting that E2F-1 down-regulation may represent a valid chemotherapeutic approach to inhibit proliferation in tumors independently of p53 status.

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Diffuse radio emission in galaxy clusters has been observed with different size and properties. Giant radio halos (RH), Mpc-size sources found in merging clusters, and mini halos (MH), 0.1-0.5 Mpc size sources located in relaxed cool-core clusters, are thought to be distinct classes of objects with different formation mechanisms. However, recent observations have revealed the unexpected presence of diffuse emission on Mpc-scales in relaxed clusters that host a central MH and show no signs of major mergers. The study of these sources is still at the beginning and it is not yet clear what could be the origin of their unusual emission. The main goal of this thesis is to test the occurrence of these peculiar sources and investigate their properties using low frequency radio observations. This thesis consists in the study of a sample of 12 cool-core galaxy clusters which present some level of dynamical disturbances on large-scale. The heterogeneity of sources in the sample allowed me to investigate under which conditions a halo-type emission is present in MH clusters; and also to study the connection between AGN bubbles and the local environment. Using high sensitivity LOFAR observations, I have detected large-scale emission in four non-merging clusters, in addition to the central MH. I have constrained for the first time the spectral properties of diffuse emission in these double radio component galaxy clusters, and I have investigated the connection between their thermal and non-thermal emission for a better comprehension of the acceleration mechanism. Furthermore, I derived upper limits to the halo power for the other clusters in the sample, which could present large-scale diffuse emission under the detection threshold. Finally, I have reconstructed the duty-cycle of one of the most powerful AGN known, located at the centre of a galaxy cluster of the sample.

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Understanding how Active Galactic Nuclei (AGN) shape galaxy evolution is a key challenge of modern astronomy. In the framework where black hole (BH) and galaxy growth are linked, AGN feedback must be tackled both at its “causes” (e.g. AGN-driven winds) and its “effects” (alteration of the gas reservoir in AGN hosts). The most informative cosmic time is z~1-3, at the peak of AGN activity and galaxy buildup, the so-called cosmic noon. The aim of this thesis is to provide new insights regarding some key questions that still remain open in this research field: i) What are the properties of AGN-driven sub-pc scale winds at z>1? ii) Are AGN-driven winds effective in influencing the life of galaxies? iii) Do AGN impact directly on star formation (SF) and gas content of their hosts? I first address AGN feedback as “caught in the act” by studying ultra-fast outflows (UFOs), X-ray AGN-driven winds, in gravitationally lensed quasars. I build the first statistically robust sample of high-z AGN, not preselected based on AGN-driven winds. I derive a first estimate of the high-z UFO detection fraction and measure the UFO duty cycle of a single high-z quasar for the first time. I also address the “effects” of AGN feedback on the life of host galaxies. If AGN influence galaxy growth, then they will reasonably impact the molecular gas reservoir first, and SF as a consequence. Through a comparative study of the molecular gas content in cosmic-noon AGN hosts and matched non-active galaxies (i.e., galaxies not hosting an AGN), we find that the host galaxies of more regular AGN (not selected to be the most luminous) are generally similar to non-active galaxies. However, we report on the possibility of a luminosity effect regulating the efficiency by which AGN might impact on galaxy growth.

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In the last decades, global food supply chains had to deal with the increasing awareness of the stakeholders and consumers about safety, quality, and sustainability. In order to address these new challenges for food supply chain systems, an integrated approach to design, control, and optimize product life cycle is required. Therefore, it is essential to introduce new models, methods, and decision-support platforms tailored to perishable products. This thesis aims to provide novel practice-ready decision-support models and methods to optimize the logistics of food items with an integrated and interdisciplinary approach. It proposes a comprehensive review of the main peculiarities of perishable products and the environmental stresses accelerating their quality decay. Then, it focuses on top-down strategies to optimize the supply chain system from the strategical to the operational decision level. Based on the criticality of the environmental conditions, the dissertation evaluates the main long-term logistics investment strategies to preserve products quality. Several models and methods are proposed to optimize the logistics decisions to enhance the sustainability of the supply chain system while guaranteeing adequate food preservation. The models and methods proposed in this dissertation promote a climate-driven approach integrating climate conditions and their consequences on the quality decay of products in innovative models supporting the logistics decisions. Given the uncertain nature of the environmental stresses affecting the product life cycle, an original stochastic model and solving method are proposed to support practitioners in controlling and optimizing the supply chain systems when facing uncertain scenarios. The application of the proposed decision-support methods to real case studies proved their effectiveness in increasing the sustainability of the perishable product life cycle. The dissertation also presents an industry application of a global food supply chain system, further demonstrating how the proposed models and tools can be integrated to provide significant savings and sustainability improvements.

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In pursuit of aligning with the European Union's ambitious target of achieving a carbon-neutral economy by 2050, researchers, vehicle manufacturers, and original equipment manufacturers have been at the forefront of exploring cutting-edge technologies for internal combustion engines. The introduction of these technologies has significantly increased the effort required to calibrate the models implemented in the engine control units. Consequently the development of tools that reduce costs and the time required during the experimental phases, has become imperative. Additionally, to comply with ever-stricter limits on 〖"CO" 〗_"2" emissions, it is crucial to develop advanced control systems that enhance traditional engine management systems in order to reduce fuel consumption. Furthermore, the introduction of new homologation cycles, such as the real driving emissions cycle, compels manufacturers to bridge the gap between engine operation in laboratory tests and real-world conditions. Within this context, this thesis showcases the performance and cost benefits achievable through the implementation of an auto-adaptive closed-loop control system, leveraging in-cylinder pressure sensors in a heavy-duty diesel engine designed for mining applications. Additionally, the thesis explores the promising prospect of real-time self-adaptive machine learning models, particularly neural networks, to develop an automatic system, using in-cylinder pressure sensors for the precise calibration of the target combustion phase and optimal spark advance in a spark-ignition engines. To facilitate the application of these combustion process feedback-based algorithms in production applications, the thesis discusses the results obtained from the development of a cost-effective sensor for indirect cylinder pressure measurement. Finally, to ensure the quality control of the proposed affordable sensor, the thesis provides a comprehensive account of the design and validation process for a piezoelectric washer test system.

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The world of communication has changed quickly in the last decade resulting in the the rapid increase in the pace of peoples’ lives. This is due to the explosion of mobile communication and the internet which has now reached all levels of society. With such pressure for access to communication there is increased demand for bandwidth. Photonic technology is the right solution for high speed networks that have to supply wide bandwidth to new communication service providers. In particular this Ph.D. dissertation deals with DWDM optical packet-switched networks. The issue introduces a huge quantity of problems from physical layer up to transport layer. Here this subject is tackled from the network level perspective. The long term solution represented by optical packet switching has been fully explored in this years together with the Network Research Group at the department of Electronics, Computer Science and System of the University of Bologna. Some national as well as international projects supported this research like the Network of Excellence (NoE) e-Photon/ONe, funded by the European Commission in the Sixth Framework Programme and INTREPIDO project (End-to-end Traffic Engineering and Protection for IP over DWDM Optical Networks) funded by the Italian Ministry of Education, University and Scientific Research. Optical packet switching for DWDM networks is studied at single node level as well as at network level. In particular the techniques discussed are thought to be implemented for a long-haul transport network that connects local and metropolitan networks around the world. The main issues faced are contention resolution in a asynchronous variable packet length environment, adaptive routing, wavelength conversion and node architecture. Characteristics that a network must assure as quality of service and resilience are also explored at both node and network level. Results are mainly evaluated via simulation and through analysis.

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The cardiovascular regulation undergoes wide changes in the different states of sleepwake cycle. In particular, the relationship between spontaneous fluctuations in heart period and arterial pressure clearly shows differences between the two sleep states. In non rapid-eye-movement sleep, heart rhythm is under prevalent baroreflex control, whereas in rapid-eye-movement sleep central autonomic commands prevail (Zoccoli et al., 2001). Moreover, during rapid-eye-movement sleep the cardiovascular variables show wide fluctuations around their mean value. In particular, during rapid-eyemovement sleep, the arterial pressure shows phasic hypertensive events which are superimposed upon the tonic level of arterial pressure. These phasic increases in arterial pressure are accompanied by an increase in heart rate (Sei & Morita, 1996; Silvani et al., 2005). Thus, rapid-eye-movement sleep may represent an “autonomic stress test” for the cardiovascular system, able to unmask pathological patterns of cardiovascular regulation (Verrier et al. 2005), but this hypothesis has never been tested experimentally. The aim of this study was to investigate whether rapid-eye-movement sleep may reveal derangements in central autonomic cardiovascular control in an experimental model of essential hypertension. The study was performed in Spontaneously Hypertensive Rats, which represent the most widely used model of essential hypertension, and allow full control of genetic and environmental confounding factors. In particular, we analyzed the cardiovascular, electroencephalogram, and electromyogram changes associated with phasic hypertensive events during rapid-eyemovement sleep in Spontaneously Hypertensive Rats and in their genetic Wistar Kyoto control strain. Moreover, we studied also a group of Spontaneously Hypertensive Rats made phenotypically normotensive by means of a chronic treatment with an angiotensin converting enzyme inhibitor, the Enalapril maleate, from the age of four weeks to the end of the experiment. All rats were implanted with electrodes for electroencephalographic and electromyographic recordings and with an arterial catheter for arterial pressure measurement. After six days for postoperative recovery, the rats were studied for five days, at an age of ten weeks.The study indicated that the peak of mean arterial pressure increase during the phasic hypertensive events in rapid-eye-movement sleep did not differ significantly between Spontaneously Hypertensive Rats and Wistar Kyoto rats, while on the other hand Spontaneously Hypertensive Rats showed a reduced increase in the frequency of theta rhythm and a reduced tachicardia with respect to Wistar Kyoto rats. The same pattern of changes in mean arterial pressure, heart period, and theta frequency was observed between Spontaneously Hypertensive Rats and Spontaneously Hypertensive Rats treated with Enalapril maleate. Spontaneously Hypertensive Rats do not differ from Wistar Kyoto rats only in terms of arterial hypertension, but also due to multiple unknown genetic differences. Spontaneously Hypertensive Rats were developed by selective breeding of Wistar Kyoto rats based only on the level of arterial pressure. However, in this process, multiple genes possibly unrelated to hypertension may have been selected together with the genetic determinants of hypertension (Carley et al., 2000). This study indicated that Spontaneously Hypertensive Rats differ from Wistar Kyoto rats, but not from Spontaneously Hypertensive Rats treated with Enalapril maleate, in terms of arterial pH and theta frequency. This feature may be due to genetic determinants unrelated to hypertension. In sharp contrast, the persistence of differences in the peak of heart period decrease and the peak of theta frequency increase during phasic hypertensive events between Spontaneously Hypertensive Rats and Spontaneously Hypertensive Rats treated with Enalapril maleate demonstrates that the observed reduction in central autonomic control of the cardiovascular system in Spontaneously Hypertensive Rats is not an irreversible consequence of inherited genetic determinants. Rather, the comparison between Spontaneously Hypertensive Rats and Spontaneously Hypertensive Rats treated with Enalapril maleate indicates that the observed differences in central autonomic control are the result of the hypertension per se. This work supports the view that the study of cardiovascular regulation in sleep provides fundamental insight on the pathophysiology of hypertension, and may thus contribute to the understanding of this disease, which is a major health problem in European countries (Wolf-Maier et al., 2003) with its burden of cardiac, vascular, and renal complications.

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The first part of my thesis presents an overview of the different approaches used in the past two decades in the attempt to forecast epileptic seizure on the basis of intracranial and scalp EEG. Past research could reveal some value of linear and nonlinear algorithms to detect EEG features changing over different phases of the epileptic cycle. However, their exact value for seizure prediction, in terms of sensitivity and specificity, is still discussed and has to be evaluated. In particular, the monitored EEG features may fluctuate with the vigilance state and lead to false alarms. Recently, such a dependency on vigilance states has been reported for some seizure prediction methods, suggesting a reduced reliability. An additional factor limiting application and validation of most seizure-prediction techniques is their computational load. For the first time, the reliability of permutation entropy [PE] was verified in seizure prediction on scalp EEG data, contemporarily controlling for its dependency on different vigilance states. PE was recently introduced as an extremely fast and robust complexity measure for chaotic time series and thus suitable for online application even in portable systems. The capability of PE to distinguish between preictal and interictal state has been demonstrated using Receiver Operating Characteristics (ROC) analysis. Correlation analysis was used to assess dependency of PE on vigilance states. Scalp EEG-Data from two right temporal epileptic lobe (RTLE) patients and from one patient with right frontal lobe epilepsy were analysed. The last patient was included only in the correlation analysis, since no datasets including seizures have been available for him. The ROC analysis showed a good separability of interictal and preictal phases for both RTLE patients, suggesting that PE could be sensitive to EEG modifications, not visible on visual inspection, that might occur well in advance respect to the EEG and clinical onset of seizures. However, the simultaneous assessment of the changes in vigilance showed that: a) all seizures occurred in association with the transition of vigilance states; b) PE was sensitive in detecting different vigilance states, independently of seizure occurrences. Due to the limitations of the datasets, these results cannot rule out the capability of PE to detect preictal states. However, the good separability between pre- and interictal phases might depend exclusively on the coincidence of epileptic seizure onset with a transition from a state of low vigilance to a state of increased vigilance. The finding of a dependency of PE on vigilance state is an original finding, not reported in literature, and suggesting the possibility to classify vigilance states by means of PE in an authomatic and objectic way. The second part of my thesis provides the description of a novel behavioral task based on motor imagery skills, firstly introduced (Bruzzo et al. 2007), in order to study mental simulation of biological and non-biological movement in paranoid schizophrenics (PS). Immediately after the presentation of a real movement, participants had to imagine or re-enact the very same movement. By key release and key press respectively, participants had to indicate when they started and ended the mental simulation or the re-enactment, making it feasible to measure the duration of the simulated or re-enacted movements. The proportional error between duration of the re-enacted/simulated movement and the template movement were compared between different conditions, as well as between PS and healthy subjects. Results revealed a double dissociation between the mechanisms of mental simulation involved in biological and non-biologial movement simulation. While for PS were found large errors for simulation of biological movements, while being more acurate than healthy subjects during simulation of non-biological movements. Healthy subjects showed the opposite relationship, making errors during simulation of non-biological movements, but being most accurate during simulation of non-biological movements. However, the good timing precision during re-enactment of the movements in all conditions and in both groups of participants suggests that perception, memory and attention, as well as motor control processes were not affected. Based upon a long history of literature reporting the existence of psychotic episodes in epileptic patients, a longitudinal study, using a slightly modified behavioral paradigm, was carried out with two RTLE patients, one patient with idiopathic generalized epilepsy and one patient with extratemporal lobe epilepsy. Results provide strong evidence for a possibility to predict upcoming seizures in RTLE patients behaviorally. In the last part of the thesis it has been validated a behavioural strategy based on neurobiofeedback training, to voluntarily control seizures and to reduce there frequency. Three epileptic patients were included in this study. The biofeedback was based on monitoring of slow cortical potentials (SCPs) extracted online from scalp EEG. Patients were trained to produce positive shifts of SCPs. After a training phase patients were monitored for 6 months in order to validate the ability of the learned strategy to reduce seizure frequency. Two of the three refractory epileptic patients recruited for this study showed improvements in self-management and reduction of ictal episodes, even six months after the last training session.

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Several diagnostic techniques are presented for the detection of electrical fault in induction motor variable speed drives. These techinques are developed taking into account the impact of the control system on machine variables and non stationary operating conditions.

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The Myc oncoproteins belong to a family of transcription factors composed by Myc, N-Myc and L-Myc. The most studied components of this family are Myc and N-Myc because their expressions are frequently deregulated in a wide range of cancers. These oncoproteins can act both as activators or repressors of gene transcription. As activators, they heterodimerize with Max (Myc associated X-factor) and the heterodimer recognizes and binds a specific sequence elements (E-Box) onto gene promoters recruiting histone acetylase and inducing transcriptional activation. Myc-mediated transcriptional repression is a quite debated issue. One of the first mechanisms defined for the Myc-mediated transcriptional repression consisted in the interaction of Myc-Max complex Sp1 and/or Miz1 transcription factors already bound to gene promoters. This interaction may interfere with their activation functions by recruiting co-repressors such as Dnmt3 or HDACs. Moreover, in the absence of , Myc may interfere with the Sp1 activation function by direct interaction and subsequent recruitment of HDACs. More recently the Myc/Max complex was also shown to mediate transcriptional repression by direct binding to peculiar E-box. In this study we analyzed the role of Myc overexpression in Osteosarcoma and Neuroblastoma oncogenesis and the mechanisms underling to Myc function. Myc overexpression is known to correlate with chemoresistance in Osteosarcoma cells. We extended this study by demonstrating that c-Myc induces transcription of a panel of ABC drug transporter genes. ABCs are a large family trans-membrane transporter deeply involved in multi drug resistance. Furthermore expression levels of Myc, ABCC1, ABCC4 and ABCF1 were proved to be important prognostic tool to predict conventional therapy failure. N-Myc amplification/overexpression is the most important prognostic factor for Neuroblastoma. Cyclin G2 and Clusterin are two genes often down regulated in neuroblastoma cells. Cyclin G2 is an atypical member of Cyclin family and its expression is associated with terminal differentiation and apoptosis. Moreover it blocks cell cycle progression and induces cell growth arrest. Instead, CLU is a multifunctional protein involved in many physiological and pathological processes. Several lines of evidences support the view that CLU may act as a tumour suppressor in Neuroblastoma. In this thesis I showed that N-Myc represses CCNG2 and CLU transcription by different mechanisms. • N-Myc represses CCNG2 transcription by directly interacting with Sp1 bound in CCNG2 promoter and recruiting HDAC2. Importantly, reactivation of CCNG2 expression through epigenetic drugs partially reduces N-Myc and HDAC2 mediated cell proliferation. • N-Myc/Max complex represses CLU expression by direct binding to a peculiar E-box element on CLU promoter and by recruitment of HDACs and Polycomb Complexes, to the CLU promoter. Overall our findings strongly support the model in which Myc overexpression/amplification may contribute to some aspects of oncogenesis by a dual action: i) transcription activation of genes that confer a multidrug resistant phenotype to cancer cells; ii), transcription repression of genes involved in cell cycle inhibition and cellular differentiation.

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The main objective of this work was to investigate the impact of different hybridization concepts and levels of hybridization on fuel economy of a standard road vehicle where both conventional and non-conventional hybrid architectures are treated exactly in the same way from the point of view of overall energy flow optimization. Hybrid component models were developed and presented in detail as well as the simulations results mainly for NEDC cycle. The analysis was performed on four different parallel hybrid powertrain concepts: Hybrid Electric Vehicle (HEV), High Speed Flywheel Hybrid Vehicle (HSF-HV), Hydraulic Hybrid Vehicle (HHV) and Pneumatic Hybrid Vehicle (PHV). In order to perform equitable analysis of different hybrid systems, comparison was performed also on the basis of the same usable system energy storage capacity (i.e. 625kJ for HEV, HSF and the HHV) but in the case of pneumatic hybrid systems maximal storage capacity was limited by the size of the systems in order to comply with the packaging requirements of the vehicle. The simulations were performed within the IAV Gmbh - VeLoDyn software simulator based on Matlab / Simulink software package. Advanced cycle independent control strategy (ECMS) was implemented into the hybrid supervisory control unit in order to solve power management problem for all hybrid powertrain solutions. In order to maintain State of Charge within desired boundaries during different cycles and to facilitate easy implementation and recalibration of the control strategy for very different hybrid systems, Charge Sustaining Algorithm was added into the ECMS framework. Also, a Variable Shift Pattern VSP-ECMS algorithm was proposed as an extension of ECMS capabilities so as to include gear selection into the determination of minimal (energy) cost function of the hybrid system. Further, cycle-based energetic analysis was performed in all the simulated cases, and the results have been reported in the corresponding chapters.

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Hybrid vehicles (HV), comprising a conventional ICE-based powertrain and a secondary energy source, to be converted into mechanical power as well, represent a well-established alternative to substantially reduce both fuel consumption and tailpipe emissions of passenger cars. Several HV architectures are either being studied or already available on market, e.g. Mechanical, Electric, Hydraulic and Pneumatic Hybrid Vehicles. Among the others, Electric (HEV) and Mechanical (HSF-HV) parallel Hybrid configurations are examined throughout this Thesis. To fully exploit the HVs potential, an optimal choice of the hybrid components to be installed must be properly designed, while an effective Supervisory Control must be adopted to coordinate the way the different power sources are managed and how they interact. Real-time controllers can be derived starting from the obtained optimal benchmark results. However, the application of these powerful instruments require a simplified and yet reliable and accurate model of the hybrid vehicle system. This can be a complex task, especially when the complexity of the system grows, i.e. a HSF-HV system assessed in this Thesis. The first task of the following dissertation is to establish the optimal modeling approach for an innovative and promising mechanical hybrid vehicle architecture. It will be shown how the chosen modeling paradigm can affect the goodness and the amount of computational effort of the solution, using an optimization technique based on Dynamic Programming. The second goal concerns the control of pollutant emissions in a parallel Diesel-HEV. The emissions level obtained under real world driving conditions is substantially higher than the usual result obtained in a homologation cycle. For this reason, an on-line control strategy capable of guaranteeing the respect of the desired emissions level, while minimizing fuel consumption and avoiding excessive battery depletion is the target of the corresponding section of the Thesis.

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Engine developers are putting more and more emphasis on the research of maximum thermal and mechanical efficiency in the recent years. Research advances have proven the effectiveness of downsized, turbocharged and direct injection concepts, applied to gasoline combustion systems, to reduce the overall fuel consumption while respecting exhaust emissions limits. These new technologies require more complex engine control units. The sound emitted from a mechanical system encloses many information related to its operating condition and it can be used for control and diagnostic purposes. The thesis shows how the functions carried out from different and specific sensors usually present on-board, can be executed, at the same time, using only one multifunction sensor based on low-cost microphone technology. A theoretical background about sound and signal processing is provided in chapter 1. In modern turbocharged downsized GDI engines, the achievement of maximum thermal efficiency is precluded by the occurrence of knock. Knock emits an unmistakable sound perceived by the human ear like a clink. In chapter 2, the possibility of using this characteristic sound for knock control propose, starting from first experimental assessment tests, to the implementation in a real, production-type engine control unit will be shown. Chapter 3 focus is on misfire detection. Putting emphasis on the low frequency domain of the engine sound spectrum, features related to each combustion cycle of each cylinder can be identified and isolated. An innovative approach to misfire detection, which presents the advantage of not being affected by the road and driveline conditions is introduced. A preliminary study of air path leak detection techniques based on acoustic emissions analysis has been developed, and the first experimental results are shown in chapter 4. Finally, in chapter 5, an innovative detection methodology, based on engine vibration analysis, that can provide useful information about combustion phase is reported.

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Gait analysis allows to characterize motor function, highlighting deviations from normal motor behavior related to an underlying pathology. The widespread use of wearable inertial sensors has opened the way to the evaluation of ecological gait, and a variety of methodological approaches and algorithms have been proposed for the characterization of gait from inertial measures (e.g. for temporal parameters, motor stability and variability, specific pathological alterations). However, no comparative analysis of their performance (i.e. accuracy, repeatability) was available yet, in particular, analysing how this performance is affected by extrinsic (i.e. sensor location, computational approach, analysed variable, testing environmental constraints) and intrinsic (i.e. functional alterations resulting from pathology) factors. The aim of the present project was to comparatively analyze the influence of intrinsic and extrinsic factors on the performance of the numerous algorithms proposed in the literature for the quantification of specific characteristics (i.e. timing, variability/stability) and alterations (i.e. freezing) of gait. Considering extrinsic factors, the influence of sensor location, analyzed variable, and computational approach on the performance of a selection of gait segmentation algorithms from a literature review was analysed in different environmental conditions (e.g. solid ground, sand, in water). Moreover, the influence of altered environmental conditions (i.e. in water) was analyzed as referred to the minimum number of stride necessary to obtain reliable estimates of gait variability and stability metrics, integrating what already available in the literature for over ground gait in healthy subjects. Considering intrinsic factors, the influence of specific pathological conditions (i.e. Parkinson’s Disease) was analyzed as affecting the performance of segmentation algorithms, with and without freezing. Finally, the analysis of the performance of algorithms for the detection of gait freezing showed how results depend on the domain of implementation and IMU position.