994 resultados para predictive compensation


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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.

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Traditional morphological examinations are not anymore sufficient for a complete evaluation of tumoral tissue and the use of neoplastic markers is of utmost importance. Neoplastic markers can be classified in: diagnostic, prognostic and predictive markers. Three markers were analyzed. 1) Insulin-like growth factor binding protein 2 (IGFBP2) was immunohistochemically examined in prostatic tissues: 40 radical prostatectomies from hormonally untreated patients with their preoperative biopsies, 10 radical prostatectomies from patients under complete androgen ablation before surgery and 10 simple prostatectomies from patients with bladder outlet obstruction. Results were compared with α-methylacyl-CoA racemase (AMACR). IGFBP2 was expressed in the cytoplasm of untreated adenocarcinomas and, to a lesser extent, in HG-PIN; the expression was markedly lower in patients after complete androgen ablation. AMACR was similarly expressed in both adenocarcinoma and HG-PIN, the level being similar in both lesions; the expression was slightly lower in patients after complete androgen ablation. IGFBP2 may be used a diagnostic marker of prostatic adenocarcinomas. 2) Heparan surface proteoglycan immunohistochemical expression was examined in 150 oral squamous cell carcinomas. Follow up information was available in 93 patients (range: 6-34 months, mean: 19±7). After surgery, chemotherapy was performed in 8 patients and radiotherapy in 61 patients. Multivariate and univariate overall survival analyses showed that high expression of syndecan-1 (SYN-1) was associated with a poor prognosis. In patients treated with radiotherapy, such association was higher. SYN-1 is a prognostic marker in oral squamous cell carcinomas; it may also represent a predictive factor for responsiveness to radiotherapy. 3) EGFR was studied in 33 pulmonary adenocarcinomas with traditional DNA sequencing methods and with two mutation-specific antibodies. Overall, the two antibodies had 61.1% sensitivity and 100% specificity in detecting EGFR mutations. EGFR mutation-specific antibodies may represent a predictive marker to identify patients candidate to tyrosine kinase inhibitors therapy.

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Introduction. Neutrophil Gelatinase-Associated Lipocalin (NGAL) belongs to the family of lipocalins and it is produced by several cell types, including renal tubular epithelium. In the kidney its production increases during acute damage and this is reflected by the increase in serum and urine levels. In animal studies and clinical trials, NGAL was found to be a sensitive and specific indicator of acute kidney injury (AKI). Purpose. The aim of this work was to investigate, in a prospective manner, whether urine NGAL can be used as a marker in preeclampsia, kidney transplantation, VLBI and diabetic nephropathy. Materials and methods. The study involved 44 consecutive patients who received renal transplantation; 18 women affected by preeclampsia (PE); a total of 55 infants weighing ≤1500 g and 80 patients with Type 1 diabetes. Results. A positive correlation was found between urinary NGAL and 24 hours proteinuria within the PE group. The detection of higher uNGAL values in case of severe PE, even in absence of statistical significance, confirms that these women suffer from an initial renal damage. In our population of VLBW infants, we found a positive correlation of uNGAL values at birth with differences in sCreat and eGFR values from birth to day 21, but no correlation was found between uNGAL values at birth and sCreat and eGFR at day 7. systolic an diastolic blood pressure decreased with increasing levels of uNGAL. The patients with uNGAL <25 ng/ml had significantly higher levels of systolic blood pressure compared with the patients with uNGAL >50 ng/ml ( p<0.005). Our results indicate the ability of NGAL to predict the delay in functional recovery of the graft. Conclusions. In acute renal pathology, urinary NGAL confirms to be a valuable predictive marker of the progress and status of acute injury.

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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

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Background. Neoangiogenesis is crucial in plaque progression and instability. Previous data from our group demonstrated that intra-plaque neovessels show both a Nestin+/WT+ and a Nestin+/WT1- phenotype, the latter being correlated with complications and plaque instability. Aims. The aims of the present thesis are: (i) to confirm our previous results on Nestin/WT1 phenotype in a larger series of carotid atheromatous plaques, (ii) to evaluate the relationship between the Nestin+/WT1- neoangiogenesis phenotype and plaque morphology, (iii) to evaluate the relationship between the immunohistochemical and histopathological characteristics and the clinical instability of the plaques. Materials and Methods. Seventy-three patients (53 males, 20 females, mean age 71 years) were consecutively enrolled. Symptoms, brain CT scan, 14 histological variables, including intraplaque hemorrhage and diffuse calcifications, were collected. Immunohistochemistry for CD34, Nestin and WT1 was performed. RT-PCR was performed to evaluate Nestin and WT1 mRNA (including 5 healthy arteries as controls). Results. Diffusely calcified plaques (13 out of 73) were found predominantly in females (P=0.017), with a significantly lower incidence of symptoms (TIA/stroke) and brain focal lesions (P=0.019 and P=0.013 respectively) than not-calcified plaques, but with the same incidence of intraplaque complications (P=0.156). Accordingly, both calcified and not calcified plaques showed similar mean densities of positivity for CD34, Nestin and WT1. The density of Nestin and WT1 correlated with the occurrence of intra-plaque hemorrhage in all cases, while the density of CD34 correlated only in not-calcified plaques. Conclusions. We confirmed that the Nestin+/WT1- phenotype characterizes the neovessels of instable plaques, regardless the real amount of CD34-positive neoangiogenesis. The calcified plaques show the same incidence of histological complications, albeit they do not influence symptomatology and plaque vulnerability. Female patients show a much higher incidence of not-complicated or calcified plaques, receiving de facto a sort of protection compared to male patients.

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Falls are common and burdensome accidents among the elderly. About one third of the population aged 65 years or more experience at least one fall each year. Fall risk assessment is believed to be beneficial for fall prevention. This thesis is about prognostic tools for falls for community-dwelling older adults. We provide an overview of the state of the art. We then take different approaches: we propose a theoretical probabilistic model to investigate some properties of prognostic tools for falls; we present a tool whose parameters were derived from data of the literature; we train and test a data-driven prognostic tool. Finally, we present some preliminary results on prediction of falls through features extracted from wearable inertial sensors. Heterogeneity in validation results are expected from theoretical considerations and are observed from empirical data. Differences in studies design hinder comparability and collaborative research. According to the multifactorial etiology of falls, assessment on multiple risk factors is needed in order to achieve good predictive accuracy.

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In the field of computer assisted orthopedic surgery (CAOS) the anterior pelvic plane (APP) is a common concept to determine the pelvic orientation by digitizing distinct pelvic landmarks. As percutaneous palpation is - especially for obese patients - known to be error-prone, B-mode ultrasound (US) imaging could provide an alternative means. Several concepts of using ultrasound imaging to determine the APP landmarks have been introduced. In this paper we present a novel technique, which uses local patch statistical shape models (SSMs) and a hierarchical speed of sound compensation strategy for an accurate determination of the APP. These patches are independently matched and instantiated with respect to associated point clouds derived from the acquired ultrasound images. Potential inaccuracies due to the assumption of a constant speed of sound are compensated by an extended reconstruction scheme. We validated our method with in-vitro studies using a plastic bone covered with a soft-tissue simulation phantom and with a preliminary cadaver trial.

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After trans-catheter aortic valve implantation (TAVI), the need for postinterventional pacemaker (PM) implantation can occur in as many as 10-50% of cases, but it is not yet clear, how this need can be predicted. The aim of this study was to assess the possible predictive factors of post TAVI PM implantation based on Computed Tomography (CT) measured aortic valve calcification and its distribution.

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This paper aims at the development and evaluation of a personalized insulin infusion advisory system (IIAS), able to provide real-time estimations of the appropriate insulin infusion rate for type 1 diabetes mellitus (T1DM) patients using continuous glucose monitors and insulin pumps. The system is based on a nonlinear model-predictive controller (NMPC) that uses a personalized glucose-insulin metabolism model, consisting of two compartmental models and a recurrent neural network. The model takes as input patient's information regarding meal intake, glucose measurements, and insulin infusion rates, and provides glucose predictions. The predictions are fed to the NMPC, in order for the latter to estimate the optimum insulin infusion rates. An algorithm based on fuzzy logic has been developed for the on-line adaptation of the NMPC control parameters. The IIAS has been in silico evaluated using an appropriate simulation environment (UVa T1DM simulator). The IIAS was able to handle various meal profiles, fasting conditions, interpatient variability, intraday variation in physiological parameters, and errors in meal amount estimations.