5 resultados para factor analytic model
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
Questa tesi riguarda l'analisi delle trasmissioni ad ingranaggi e delle ruote dentate in generale, nell'ottica della minimizzazione delle perdite di energia. È stato messo a punto un modello per il calcolo della energia e del calore dissipati in un riduttore, sia ad assi paralleli sia epicicloidale. Tale modello consente di stimare la temperatura di equilibrio dell'olio al variare delle condizioni di funzionamento. Il calcolo termico è ancora poco diffuso nel progetto di riduttori, ma si è visto essere importante soprattutto per riduttori compatti, come i riduttori epicicloidali, per i quali la massima potenza trasmissibile è solitamente determinata proprio da considerazioni termiche. Il modello è stato implementato in un sistema di calcolo automatizzato, che può essere adattato a varie tipologie di riduttore. Tale sistema di calcolo consente, inoltre, di stimare l'energia dissipata in varie condizioni di lubrificazione ed è stato utilizzato per valutare le differenze tra lubrificazione tradizionale in bagno d'olio e lubrificazione a “carter secco” o a “carter umido”. Il modello è stato applicato al caso particolare di un riduttore ad ingranaggi a due stadi: il primo ad assi paralleli ed il secondo epicicloidale. Nell'ambito di un contratto di ricerca tra il DIEM e la Brevini S.p.A. di Reggio Emilia, sono state condotte prove sperimentali su un prototipo di tale riduttore, prove che hanno consentito di tarare il modello proposto [1]. Un ulteriore campo di indagine è stato lo studio dell’energia dissipata per ingranamento tra due ruote dentate utilizzando modelli che prevedano il calcolo di un coefficiente d'attrito variabile lungo il segmento di contatto. I modelli più comuni, al contrario, si basano su un coefficiente di attrito medio, mentre si può constatare che esso varia sensibilmente durante l’ingranamento. In particolare, non trovando in letteratura come varia il rendimento nel caso di ruote corrette, ci si è concentrati sul valore dell'energia dissipata negli ingranaggi al variare dello spostamento del profilo. Questo studio è riportato in [2]. È stata condotta una ricerca sul funzionamento di attuatori lineari vite-madrevite. Si sono studiati i meccanismi che determinano le condizioni di usura dell'accoppiamento vite-madrevite in attuatori lineari, con particolare riferimento agli aspetti termici del fenomeno. Si è visto, infatti, che la temperatura di contatto tra vite e chiocciola è il parametro più critico nel funzionamento di questi attuatori. Mediante una prova sperimentale, è stata trovata una legge che, data pressione, velocità e fattore di servizio, stima la temperatura di esercizio. Di tale legge sperimentale è stata data un'interpretazione sulla base dei modelli teorici noti. Questo studio è stato condotto nell'ambito di un contratto di ricerca tra il DIEM e la Ognibene Meccanica S.r.l. di Bologna ed è pubblicato in [3].
Resumo:
In this work, we explore and demonstrate the potential for modeling and classification using quantile-based distributions, which are random variables defined by their quantile function. In the first part we formalize a least squares estimation framework for the class of linear quantile functions, leading to unbiased and asymptotically normal estimators. Among the distributions with a linear quantile function, we focus on the flattened generalized logistic distribution (fgld), which offers a wide range of distributional shapes. A novel naïve-Bayes classifier is proposed that utilizes the fgld estimated via least squares, and through simulations and applications, we demonstrate its competitiveness against state-of-the-art alternatives. In the second part we consider the Bayesian estimation of quantile-based distributions. We introduce a factor model with independent latent variables, which are distributed according to the fgld. Similar to the independent factor analysis model, this approach accommodates flexible factor distributions while using fewer parameters. The model is presented within a Bayesian framework, an MCMC algorithm for its estimation is developed, and its effectiveness is illustrated with data coming from the European Social Survey. The third part focuses on depth functions, which extend the concept of quantiles to multivariate data by imposing a center-outward ordering in the multivariate space. We investigate the recently introduced integrated rank-weighted (IRW) depth function, which is based on the distribution of random spherical projections of the multivariate data. This depth function proves to be computationally efficient and to increase its flexibility we propose different methods to explicitly model the projected univariate distributions. Its usefulness is shown in classification tasks: the maximum depth classifier based on the IRW depth is proven to be asymptotically optimal under certain conditions, and classifiers based on the IRW depth are shown to perform well in simulated and real data experiments.
Resumo:
Animal models have been relevant to study the molecular mechanisms of cancer and to develop new antitumor agents. Anyway, the huge divergence in mouse and human evolution made difficult the translation of the gained achievements in preclinical mouse based studies. The generation of clinically relevant murine models requires their humanization both concerning the creation of transgenic models and the generation of humanized mice in which to engraft a functional human immune system, and reproduce the physiological effects and molecular mechanisms of growth and metastasization of human tumors. In particular, the availability of genotypically stable immunodepressed mice able to accept tumor injection and allow human tumor growth and metastasization would be important to develop anti-tumor and anti-metastatic strategies. Recently, Rag2-/-;gammac-/- mice, double knockout for genes involved in lymphocyte differentiation, had been developed (CIEA, Central Institute for Experimental Animals, Kawasaki, Japan). Studies of human sarcoma metastasization in Rag2-/-; gammac-/- mice (lacking B, T and NK functionality) revealed their high metastatic efficiency and allowed the expression of human metastatic phenotypes not detectable in the conventionally used nude murine model. In vitro analysis to investigate the molecular mechanisms involved in the specific pattern of human sarcomas metastasization revealed the importance of liver-produced growth and motility factors, in particular the insulin-like growth factors (IGFs). The involvement of this growth factor was then demonstrated in vivo through inhibition of IGF signalling pathway. Due to the high growth and metastatic propensity of tumor cells, Rag2-/-;gammac-/- mice were used as model to investigate the metastatic behavior of rhabdomyosarcoma cells engineered to improve the differentiation. It has been recently shown that this immunodeficient model can be reconstituted with a human immune system through the injection of human cord blood progenitor cells. The work illustrated in this thesis revealed that the injection of different human progenitor cells (CD34+ or CD133+) showed peculiar engraftment and differentiation abilities. Experiments of cell vaccination were performed to investigate the functionality of the engrafted human immune system and the induction of specific human immune responses. Results from such experiments will allow to collect informations about human immune responses activated during cell vaccination and to define the best reconstitution and experimental conditions to create a humanized model in which to study, in a preclinical setting, immunological antitumor strategies.
Resumo:
Down syndrome (DS) is a genetic pathology characterized by brain hypotrophy and severe cognitive disability. Although defective neurogenesis is an important determinant of cognitive impairment, a severe dendritic pathology appears to be an equally important factor. It is well established that serotonin plays a pivotal role both on neurogenesis and dendritic maturation. Since the serotonergic system is profoundly altered in the DS brain, we wondered whether defects in the hippocampal development can be rescued by treatment with fluoxetine, a selective serotonin reuptake inhibitor and a widely used antidepressant drug. A previous study of our group showed that fluoxetine fully restores neurogenesis in the Ts65Dn mouse model of DS and that this effect is accompanied by a recovery of memory functions. The goal of the current study was to establish whether fluoxetine also restores dendritic development and maturation. In mice aged 45 days, treated with fluoxetine in the postnatal period P3-P15, we examined the dendritic arbor of newborn and mature granule cells of the dentate gyrus (DG). The granule cells of trisomic mice had a severely hypotrophic dendritic arbor, fewer spines and a reduced innervation than euploid mice. Treatment with fluoxetine fully restored all these defects. Moreover the impairment of excitatory and inhibitory inputs to CA3 pyramidal neurons was fully normalized in treated trisomic mice, indicating that fluoxetine can rescue functional connectivity between the DG and CA3. The widespread beneficial effects of fluoxetine on the hippocampal formation suggest that early treatment with fluoxetine can be a suitable therapy, possibly usable in humans, to restore the physiology of the hippocampal networks and, hence, memory functions. These findings may open the way for future clinical trials in children and adolescents with DS.
Resumo:
The instability of river bank can result in considerable human and land losses. The Po river is the most important in Italy, characterized by main banks of significant and constantly increasing height. This study presents multilayer perceptron of artificial neural network (ANN) to construct prediction models for the stability analysis of river banks along the Po River, under various river and groundwater boundary conditions. For this aim, a number of networks of threshold logic unit are tested using different combinations of the input parameters. Factor of safety (FS), as an index of slope stability, is formulated in terms of several influencing geometrical and geotechnical parameters. In order to obtain a comprehensive geotechnical database, several cone penetration tests from the study site have been interpreted. The proposed models are developed upon stability analyses using finite element code over different representative sections of river embankments. For the validity verification, the ANN models are employed to predict the FS values of a part of the database beyond the calibration data domain. The results indicate that the proposed ANN models are effective tools for evaluating the slope stability. The ANN models notably outperform the derived multiple linear regression models.