930 resultados para Domain-specific analysis
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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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This thesis provides a necessary and sufficient condition for asymptotic efficiency of a nonparametric estimator of the generalised autocovariance function of a Gaussian stationary random process. The generalised autocovariance function is the inverse Fourier transform of a power transformation of the spectral density, and encompasses the traditional and inverse autocovariance functions. Its nonparametric estimator is based on the inverse discrete Fourier transform of the same power transformation of the pooled periodogram. The general result is then applied to the class of Gaussian stationary ARMA processes and its implications are discussed. We illustrate that for a class of contrast functionals and spectral densities, the minimum contrast estimator of the spectral density satisfies a Yule-Walker system of equations in the generalised autocovariance estimator. Selection of the pooling parameter, which characterizes the nonparametric estimator of the generalised autocovariance, controlling its resolution, is addressed by using a multiplicative periodogram bootstrap to estimate the finite-sample distribution of the estimator. A multivariate extension of recently introduced spectral models for univariate time series is considered, and an algorithm for the coefficients of a power transformation of matrix polynomials is derived, which allows to obtain the Wold coefficients from the matrix coefficients characterizing the generalised matrix cepstral models. This algorithm also allows the definition of the matrix variance profile, providing important quantities for vector time series analysis. A nonparametric estimator based on a transformation of the smoothed periodogram is proposed for estimation of the matrix variance profile.
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Changing or creating an organisation means creating a new process. Each process involves many risks that need to be identified and managed. The main risks considered here are procedural and legal risks. The former are related to the risks of errors that may occur during processes, while the latter are related to the compliance of processes with regulations. Managing the risks implies proposing changes to the processes that allow the desired result: an optimised process. In order to manage a company and optimise it in the best possible way, not only should the organisational aspect, risk management and legal compliance be taken into account, but it is important that they are all analysed simultaneously with the aim of finding the right balance that satisfies them all. This is the aim of this thesis, to provide methods and tools to balance these three characteristics, and to enable this type of optimisation, ICT support is used. This work isn’t a thesis in computer science or law, but rather an interdisciplinary thesis. Most of the work done so far is vertical and in a specific domain. The particularity and aim of this thesis is not to carry out an in-depth analysis of a particular aspect, but rather to combine several important aspects, normally analysed separately, which however have an impact and influence each other. In order to carry out this kind of interdisciplinary analysis, the knowledge base of both areas was involved and the combination and collaboration of different experts in the various fields was necessary. Although the methodology described is generic and can be applied to all sectors, the case study considered is a new type of healthcare service that allows patients in acute disease to be hospitalised to their home. This provide the possibility to perform experiments using real hospital database.
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In recent decades, two prominent trends have influenced the data modeling field, namely network analysis and machine learning. This thesis explores the practical applications of these techniques within the domain of drug research, unveiling their multifaceted potential for advancing our comprehension of complex biological systems. The research undertaken during this PhD program is situated at the intersection of network theory, computational methods, and drug research. Across six projects presented herein, there is a gradual increase in model complexity. These projects traverse a diverse range of topics, with a specific emphasis on drug repurposing and safety in the context of neurological diseases. The aim of these projects is to leverage existing biomedical knowledge to develop innovative approaches that bolster drug research. The investigations have produced practical solutions, not only providing insights into the intricacies of biological systems, but also allowing the creation of valuable tools for their analysis. In short, the achievements are: • A novel computational algorithm to identify adverse events specific to fixed-dose drug combinations. • A web application that tracks the clinical drug research response to SARS-CoV-2. • A Python package for differential gene expression analysis and the identification of key regulatory "switch genes". • The identification of pivotal events causing drug-induced impulse control disorders linked to specific medications. • An automated pipeline for discovering potential drug repurposing opportunities. • The creation of a comprehensive knowledge graph and development of a graph machine learning model for predictions. Collectively, these projects illustrate diverse applications of data science and network-based methodologies, highlighting the profound impact they can have in supporting drug research activities.
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The new social panorama resulting from aging of the Brazilian population is leading to significant transformations within healthcare. Through the cluster analysis strategy, it was sought to describe the specific care demands of the elderly population, using frailty components. Cross-sectional study based on reviewing medical records, conducted in the geriatric outpatient clinic, Hospital de Clínicas, Universidade Estadual de Campinas (Unicamp). Ninety-eight elderly users of this clinic were evaluated using cluster analysis and instruments for assessing their overall geriatric status and frailty characteristics. The variables that most strongly influenced the formation of clusters were age, functional capacities, cognitive capacity, presence of comorbidities and number of medications used. Three main groups of elderly people could be identified: one with good cognitive and functional performance but with high prevalence of comorbidities (mean age 77.9 years, cognitive impairment in 28.6% and mean of 7.4 comorbidities); a second with more advanced age, greater cognitive impairment and greater dependence (mean age 88.5 years old, cognitive impairment in 84.6% and mean of 7.1 comorbidities); and a third younger group with poor cognitive performance and greater number of comorbidities but functionally independent (mean age 78.5 years old, cognitive impairment in 89.6% and mean of 7.4 comorbidities). These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed at diminishing functional dependence, poor self-rated health and impaired quality of life.
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Health economic evaluations require estimates of expected survival from patients receiving different interventions, often over a lifetime. However, data on the patients of interest are typically only available for a much shorter follow-up time, from randomised trials or cohorts. Previous work showed how to use general population mortality to improve extrapolations of the short-term data, assuming a constant additive or multiplicative effect on the hazards for all-cause mortality for study patients relative to the general population. A more plausible assumption may be a constant effect on the hazard for the specific cause of death targeted by the treatments. To address this problem, we use independent parametric survival models for cause-specific mortality among the general population. Because causes of death are unobserved for the patients of interest, a polyhazard model is used to express their all-cause mortality as a sum of latent cause-specific hazards. Assuming proportional cause-specific hazards between the general and study populations then allows us to extrapolate mortality of the patients of interest to the long term. A Bayesian framework is used to jointly model all sources of data. By simulation, we show that ignoring cause-specific hazards leads to biased estimates of mean survival when the proportion of deaths due to the cause of interest changes through time. The methods are applied to an evaluation of implantable cardioverter defibrillators for the prevention of sudden cardiac death among patients with cardiac arrhythmia. After accounting for cause-specific mortality, substantial differences are seen in estimates of life years gained from implantable cardioverter defibrillators.
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Human Neks are a conserved protein kinase family related to cell cycle progression and cell division and are considered potential drug targets for the treatment of cancer and other pathologies. We screened the activation loop mutant kinases hNek1 and hNek2, wild-type hNek7, and five hNek6 variants in different activation/phosphorylation statesand compared them against 85 compounds using thermal shift denaturation. We identified three compounds with significant Tm shifts: JNK Inhibitor II for hNek1(Δ262-1258)-(T162A), Isogranulatimide for hNek6(S206A), andGSK-3 Inhibitor XIII for hNek7wt. Each one of these compounds was also validated by reducing the kinases activity by at least 25%. The binding sites for these compounds were identified by in silico docking at the ATP-binding site of the respective hNeks. Potential inhibitors were first screened by thermal shift assays, had their efficiency tested by a kinase assay, and were finally analyzed by molecular docking. Our findings corroborate the idea of ATP-competitive inhibition for hNek1 and hNek6 and suggest a novel non-competitive inhibition for hNek7 in regard to GSK-3 Inhibitor XIII. Our results demonstrate that our approach is useful for finding promising general and specific hNekscandidate inhibitors, which may also function as scaffolds to design more potent and selective inhibitors.
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The fungus Metarhizium anisopliae is used on a large scale in Brazil as a microbial control agent against the sugar cane spittlebugs, Mahanarva posticata and M. fimbriolata (Hemiptera., Cercopidae). We applied strain E9 of M. anisopliae in a bioassay on soil, with field doses of conidia to determine if it can cause infection, disease and mortality in immature stages of Anastrepha fraterculus, the South American fruit fly. All the events were studied histologically and at the molecular level during the disease cycle, using a novel histological technique, light green staining, associated with light microscopy, and by PCR, using a specific DNA primer developed for M. anisopliae capable to identify Brazilian strains like E9. The entire infection cycle, which starts by conidial adhesion to the cuticle of the host, followed by germination with or without the formation of an appressorium, penetration through the cuticle and colonisation, with development of a dimorphic phase, hyphal bodies in the hemocoel, and death of the host, lasted 96 hours under the bioassay conditions, similar to what occurs under field conditions. During the disease cycle, the propagules of the entomopathogenic fungus were detected by identifying DNA with the specific primer ITSMet: 5' TCTGAATTTTTTATAAGTAT 3' with ITS4 (5' TCCTCCGCTTATTGATATGC 3') as a reverse primer. This simple methodology permits in situ studies of the infective process, contributing to our understanding of the host-pathogen relationship and allowing monitoring of the efficacy and survival of this entomopathogenic fungus in large-scale applications in the field. It also facilitates monitoring the environmental impact of M. anisopliae on non-target insects.
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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Universidade Estadual de Campinas . Faculdade de Educação Física
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Universidade Estadual de Campinas. Faculdade de Educação Física
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RATIONALE: Benign focal seizures of adolescence (BFSA) described by Loiseau et al in 1972, is considered a rare entity, but maybe underdiagnosed. Although mild neuropsychological deficits have been reported in patients with benign epilepsies of childhood, these evaluations have not so far been described in BFSA. The aim of this study is to evaluate neuropsychological functions in BFSA with new onset seizures (<12 months). METHODS: Eight patients with BFSA (according to Loiseau et al, 1972, focal or secondarily tonic clonic generalized seizures between the ages of 10-18 yrs., normal neurologic examination, normal EEG or with mild focal abnormalities) initiated in the last 12 months were studied between July 2008 to May 2009. They were referred from the Pediatric Emergency Section of the Hospital Universitário of the University of Sao Paulo, a secondary care regionalized facility located in a district of middle-low income in Sao Paulo city, Brazil. The study was approved by the Ethics Committee of the Institution. All patients performed neurological, EEG, brain CT and neuropsychological evaluation which consisted of Raven's Special Progressive Matrices - General and Special Scale (according to different ages), Wechsler Children Intelligence Scale-WISC III with ACID Profile, Trail Making Test A/B, Stroop Test, Bender Visuo-Motor Test, Rey Complex Figure, Rey Auditory Verbal Learning Test-RAVLT, Boston Naming Test, Fluency Verbal for phonological and also conceptual patterns - FAS/Animals and Hooper Visual Organization Test. For academic achievement, we used a Brazilian test for named "Teste do Desempenho Escolar", which evaluates abilities to read, write and calculate according to school grade. RESULTS: There were 2 boys and 6 girls, with ages ranging from 10 yrs. 9 m to 14 yrs. 3 m. Most (7/8) of the patients presented one to two seizures and only three of them received antiepileptic drugs (AEDs). Six had mild EEG focal abnormalities and all had normal brain CT. All were literate, attended regular public schools and scored in a median range for IQ, and seven showed discrete higher scores for the verbal subtests. There were low scores for attention in different modalities in six patients, mainly in alternated attention as well as inhibitory subtests (Stroop test and Trail Making Test part B). Four of the latter cases who showed impairment both in alternated and inhibitory attention were not taking AEDs. Visual memory was impaired in five patients (Rey Complex Figure). Executive functions analysis showed deficits in working memory in five, mostly observed in Digits Indirect Order and Arithmetic tests (WISC III). Reading and writing skills were below the expected average for school grade in six patients according to the achievement scholar performance test utilized. One patient of this series who had the best scores in all tests was taking phenobarbital. CONCLUSIONS: Neuropsychological imbalance between normal IQ and mild dysfunctions such as in attention domain and in some executive abilities like working memory and planning, as well as difficulties in visual memory and in reading and writing, were described in this group of patients with BFSA from community. This may reflect mild higher level neurological dysfunctions in adolescence idiopathic focal seizures probably caused by an underlying dysmaturative epileptogenic process. Although academic problems often have multiple causes, a specific educational approach may be necessary in these adolescents, in order to improve their scholastic achievements, helping in this way, to decrease the stigma associated to epileptic seizures in the community.
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The aim of the present work was to characterize changes in the protein profile throughout seed development in O. catharinensis, a recalcitrant species, by two-dimensional gel electrophoresis. Protein extraction was undertaken by using a thiourea/urea buffer, followed by a precipitation step with 10% TCA. Comparative analysis during seed development showed that a large number of proteins were exclusively detected in each developmental stage. The cotyledonary stage, which represents the transition phase between embryogenesis and the beginning of metabolism related to maturation, presents the highest number of stage-specific spots. Protein identification, through MS/MS analysis, resulted in the identification of proteins mainly related to oxidative metabolism and storage synthesis. These findings contribute to a better understanding of protein metabolism during seed development in recalcitrant seeds, besides providing information on established markers that could be useful in defining and improving somatic embryogenesis protocols, besides monitoring the development of somatic embryos in this species.