Dissertations / Theses on the topic 'Modelli causali'
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FALOTICO, ROSA. "Modelli ad Equazioni Strutturali e Reti Probabilistiche Bayesiane: due approcci a confronto nello studio di relazioni causali." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2011. http://hdl.handle.net/10281/19444.
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Causality is a concept extremely important in science, but its definition is quite controversial and its detection is not exempt from problems. There are different approaches to deal with causality. Two of them are the Structural Equation Models (SEMs) and the Probabilistic Bayesian Networks (PBNs). SEMs are confirmative models. Given a causal structure, they test if it is coherent with data. In this context they are estimated using the Partial Least Squares Path Modeling technique in order to obtain the scores of latent variables. PBNs are inductive methods. Their attempt is to extract the causal scheme deriving from data, without presupposing any knowledge. Both models presents advantages and disadvantages regardless of the causality approach they refer to. SEMs are best suited for quantitative data and when there is a solid theoretical knowledge on the subject of analysis. PBNs are preferable for nonlinear analysis or uncertain causal scheme.
In the thesis a possible integration of the two methods is proposed in the analysis of data deriving from a satisfaction and customer loyalty survey for “Customer American Satisfaction Index” (ACSI).
Results suggest that the SEMs are more suitable than the PBNs and that the integration of the two statistical models is advantageous only in part. This is related to the kind of data, since the ACSI survey is structured for a PLS-PM analysis. Thus, it could be very interesting repeat the comparison for different types of data.
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Brandano, Sergio. "Modelling causal reasoning." Thesis, Queen Mary, University of London, 2009. http://qmro.qmul.ac.uk/xmlui/handle/123456789/625.
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Although human causal reasoning is widely acknowledged as an object of scientific enquiry, there is little consensus on an appropriate measure of progress. Up-to-date evidence of the standard method of research in the field shows that this method has been rejected at the birth of modern science. We describe an instance of the standard scientific method for modelling causal reasoning (causal calculators). The method allows for uniform proofs of three relevant computational properties: correctness of the model with respect to the intended model, full abstraction of the model (function) with respect to the equivalence of reasoning scenarios (input), and formal relations of equivalence and subsumption between models. The method extends and exploits the systematic paradigm [Handbook of Logic in Artificial Intelligence and Logic Programming, volume IV, p. 439-498, Oxford 1995] to fit with our interpretation of it. Using the described method, we present results for some major models, with an updated summary spanning seventy-two years of research in the field.
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Faria, Rodrigo Cristino de. "Modelagem causal da astronomia antiga." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/8/8133/tde-07052015-141417/.
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Esta dissertação tem como objetivo apresentar a Modelagem Causal em História da Ciência (MCHC), e aplicá-la ao período da história da astronomia que vai dos primórdios ao século III AEC. Na primeira parte, exponho o método e discorro sobre algumas de suas implicações filosóficas especialmente aquelas relacionadas com a noção de avanço e historiográficas, ao mesmo tempo em que procuro inseri-lo no panorama da filosofia da ciência. Na segunda parte, que já é uma aplicação da MCHC, apresento uma pequena história da astronomia antiga, mostrando os principais avanços dos egípcios, babilônios e gregos, até Aristarco de Samos. Na última parte, utilizo os conceitos mobilizados na primeira parte e os avanços da segunda para apresentar o modelo causal da astronomia antiga e as conclusões dele derivadas.This thesis aims at presenting the Causal Modeling of the History of Science (MCHC), and applying it to the period of the history of astronomy comprising its beginning until the 3rd century BCE. In the first part, the method is discussed and some of its philosophical and historiographical implications are analyzed especially those related to the notion of advance. In the second part, an application of MCHC, a short history of ancient, is presented, showing the main advances of the Egyptians, Babylonians, and Greeks, up to Aristarchus of Samos. In the final part, I use the concepts deployed in the first part and the advances discussed in the second part to present a causal model of ancient astronomy and the conclusions therefrom derived.
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Lim, Bobby Ting Chuan. "Causal modelling construction project performance." Thesis, Heriot-Watt University, 1987. http://hdl.handle.net/10399/1011.
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Figueiredo, Garrido M. Isabel. "Causal modelling of evoked brain responses." Thesis, University College London (University of London), 2008. http://discovery.ucl.ac.uk/1444174/.
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The aim of this thesis was to test predictive coding as a model of cortical organization and function using a specific brain response, the mismatch negativity (MMN), and a novel tool for connectivity analysis, dynamic causal modelling (DCM). Predictive coding models state that the brain perceives and makes inferences about the world by recursively updating predictions about sensory input. Thus, perception would result from comparing bottom-up input from the environment with top-down predictions. The generation of the MMN, an event- related response elicited by violations in the regularity of a structured auditory sequence, has been discussed extensively in the literature. This thesis discusses the generation of the MMN in the light of predictive coding, in other words, the MMN could reflect prediction error, occurring whenever the current input does not match a previously learnt rule. This interpretation is tested using DCM, a methodological approach which assumes the activity in one cortical area is caused by the activity in another cortical area. In brief, this thesis assesses the validity of DCM, shows the usefulness of DCM in explaining how cortical activity is expressed at the scalp level and exploits the potential of DCM for testing hierarchical models underlying the MMN. The first part of this thesis is concerned with technical issues and establishing the validity of DCM. The second part addresses hierarchical cortical organization in MMN generation, plausible network models or mechanisms underlying the MMN, and finally, the effect of repetition or learning on the connectivity parameters of the causal model.
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Whittaker, Joseph. "A method of reducing model space for dynamic causal modelling." Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/a-method-of-reducing-model-space-for-dynamic-causal-modelling(41b3c338-4f1d-4d17-a0b8-58785d6a9f6e).html.
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An increasingly important concept in psychiatric neuroimaging is that of brai nconnectivity. Dynamic Causal Modelling (DCM) has been successfully usedto infer how spatially remote areas of the brain integrate to form functionalnetworks. A potential disadvantage to DCM is the need to predefine a modelbased on a hypothesis about the underlying connectivity. This requirementsmeans the results are dependent on the assumptions about model structure,and important features of the underlying network may be ignored. Here wepresent a method for identifying the model structure in a way t hat discardsthe a priori knowledge that is typically used to constrain model space. Thisallows DCM to be used in a more data-driven way, and allows the optimalmodel within a network of nodes to be identified. The thesis consists of 3studies that together provide a generic framework for a novel approach toDCM and validation that it works, and offers a significant computationaladvantage to traditional DCM.The first study demonstrates that the connectivity within a system of brainregions can be ascertained from inferring the connectivity within smallersystems, which consist of regions taken from the entire system. By analysingthe data in this fashion, we can effectively explore the entire networkstructure space, but estimate a much smaller number of models than wouldbe typical. The second study applies the method to a multicentre dataset andshows that Bayesian Model Selection (BMS) results are reproducible atdifferent centres and across different sessions. The findings show that DCMis robust enough to be used in multicentre studies and that our exploratoryapproach is just as effective as traditional approaches to DCM. The thirdstudy applies the method to a standard psychiatric imaging dataset; animplicit emotional processing face recognition task performed by patientswith major depressive disorder (MDD) vs healthy controls (HC). The MDDpatients perform a follow up scan having being treated with theantidepressant citalopram. The study shows that the developed method canbe used to identify the optimal model structure in order to make inferenceson effective connectivity parameters, and identify differences between patientand control groups, and before and after treatment.
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Mendes, Armando B. "Modelação das elasticidades de quotas de mercado para produtos de grande consumo." Master's thesis, Instituto Superior Técnico, 1997. http://hdl.handle.net/10400.3/2162.
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Dissertação de Mestrado em Investigação Operacional e Engenharia de Sistemas.As vendas de produtos ao nível da loja são habitualmente modeladas utilizando dados agregados no tempo ou no número de produtos. A agregação permite alisar a série, evitando a interferência de fenómenos como roturas de "stock", frequentes em muitas lojas de grande dimensão. Nesta tese são desenvolvidos modelos de vendas causais a serem utilizados em dados com elevado nível de desagregação e permitindo a análise do comportamento dos diferentes produtos perante roturas, promoções ou alterações de preço. Utiliza-se uma perspectiva descritiva ainda que os modelos possam ser utilizados previsionalmente. Introduz-se o conceito de variável relativizada tanto nos modelos clássicos como nos modelos de atracção. São deduzidas expressões tanto para as elasticidades directas como cruzadas, para cada modelo combinado com cada uma das expressões de relativização. Faz-se uma análise de robustez às expressões verificando-se que além dos modelos de atracção também alguns modelos clássicos conduzem a elasticidades robustas. Os modelos são posteriormente ajustados a dados relativos a uma subfamília com cinco marcas de arroz. Determinam-se e interpretam-se as elasticidades directas e cruzadas do preço nas quotas de mercado. Conclui-se que os modelos clássicos apresentam um maior poder explicativo fornecendo um maior número de parâmetros facilmente interpretáveis como os relacionados com roturas e promoções.
ABSTRACT: Retail product sales are usually modelled using data aggregated over time or by product group. Doing this is necessary in order to reduce bias effects such as stock-outs, very frequent in large stores. The present research develops causal sales models for daily item data, modelling sales price variability, promotions and stock-out substitution. The approach is essentially descriptive, but the developed models can be used for forecasting purposes. The relative marketing variable concept is introduced not only in classical causal models but also in attraction models. Direct and cross elasticity expressions are deduced for every model combined with seven relative variable expressions. These expressions are tested in extreme conditions for robustness. Not only the attraction models are found robust, but same classical models can bring robust elasticity expressions too. The models are then adjusted to any of five products belonging to a rice product group. Direct and cross elasticities are calculated and interpreted. Results from causal classical models and attraction models are compared. Classical models were found to have more descriptive power than attraction models providing several parameters, related with promotions and stock-outs, easier to interpret.
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Fewell, Zoe. "Causal modelling in epidemiology and health services research." Thesis, University of Bristol, 2007. http://hdl.handle.net/1983/f12fb11d-0826-46d6-a5ed-7a87fa582b63.
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Odondi, Lang'O. "Causal modelling of survival data with informative noncompliance." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/causal-modelling-of-survival-data-with-informative-noncompliance(74f40dc0-e5d1-46c0-ab2f-ac42a3425ac7).html.
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Noncompliance to treatment allocation is likely to complicate estimation of causal effects in clinical trials. The ubiquitous nonrandom phenomenon of noncompliance renders per-protocol and as- treated analyses or even simple regression adjustments for noncompliance inadequate for causal inference. For survival data, several specialist methods have been developed when noncompliance is related to risk. The Causal Accelerated Life Model (CALM) allows time-dependent departures from randomized treatment in either arm and relates each observed event time to a potential event time that would have been observed if the control treatment had been given throughout the trial. Alternatively, the structural Proportional Hazards (C-Prophet) model accounts for all-or-nothing noncompliance in the treatment arm only while the CHARM estimator allows time-dependent departures from randomized treatment by considering survival outcome as a sequence of binary outcomes to provide an 'approximate' overall hazard ratio estimate which is adjusted for compliance. The problem of efficacy estimation is compounded for two-active treatment trials (additional noncompliance) where the ITT estimate provides a biased estimator for the true hazard ratio even under homogeneous treatment effects assumption. Using plausible arm-specific predictors of compliance, principal stratification methods can be applied to obtain principal effects for each stratum. The present work applies the above methods to data from the Esprit trials study which was conducted to ascertain whether or not unopposed oestrogen (hormone replacement therapy - HRT) reduced the risk of further cardiac events in postmenopausal women who survive a first myocardial infarction. We use statistically designed simulation studies to evaluate the performance of these methods in terms of bias and 95% confidence interval coverage. We also apply a principal stratification method to adjust for noncompliance in two treatment arms trial originally developed for binary data for survival analysis in terms of causal risk ratio. In a Bayesian framework, we apply the method to Esprit data to account for noncompliance in both treatment arms and estimate principal effects. We apply statistically designed simulation studies to evaluate the performance of the method in terms of bias in the causal effect estimates for each stratum. ITT analysis of the Esprit data showed the effects of taking HRT tablets was not statistically significantly different from placebo for both all cause mortality and myocardial reinfarction outcomes. Average compliance rate for HRT treatment was 43% and compliance rate decreased as the study progressed. CHARM and C-Prophet methods produced similar results but CALM performed best for Esprit: suggesting HRT would reduce risk of death by 50%. Simulation studies comparing the methods suggested that while both C-Prophet and CHARM methods performed equally well in terms of bias, the CALM method performed best in terms of both bias and 95% confidence interval coverage albeit with the largest RMSE. The principal stratification method failed for the Esprit study possibly due to the strong distribution assumption implicit in the method and lack of adequate compliance information in the data which produced large 95% credible intervals for the principal effect estimates. For moderate value of sensitivity parameter, principal stratification results suggested compliance with HRT tablets relative to placebo would reduce risk of mortality by 43% among the most compliant. Simulation studies on performance of this method showed narrower corresponding mean 95% credible intervals corresponding to the the causal risk ratio estimates for this subgroup compared to other strata. However, the results were sensitive to the unknown sensitivity parameter.
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Rees, Stephen Edward. "Causal probabilistic network modelling of lipid and lipoprotein metabolism." Thesis, City University London, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241469.
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Chen, C. C. "Imaging the spatial-temporal neuronal dynamics using dynamic causal modelling." Thesis, University College London (University of London), 2009. http://discovery.ucl.ac.uk/18517/.
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Oscillatory brain activity is a ubiquitous feature of neuronal dynamics and the synchronous discharge of neurons is believed to facilitate integration both within functionally segregated brain areas and between areas engaged by the same task. There is growing interest in investigating the neural oscillatory networks in vivo. The aims of this thesis are to (1) develop an advanced method, Dynamic Causal Modelling for Induced Responses (DCM for IR), for modelling the brain network functions and (2) apply it to exploit the nonlinear coupling in the motor system during hand grips and the functional asymmetries during face perception. DCM for IR models the time-varying power over a range of frequencies of coupled electromagnetic sources. The model parameters encode coupling strength among areas and allows the differentiations between linear (within frequency) and nonlinear (between-frequency) coupling. I applied DCM for IR to show that, during hand grips, the nonlinear interactions among neuronal sources in motor system are essential while intrinsic coupling (within source) is very likely to be linear. Furthermore, the normal aging process alters both the network architecture and the frequency contents in the motor network. I then use the bilinear form of DCM for IR to model the experimental manipulations as the modulatory effects. I use MEG data to demonstrate functional asymmetries between forward and backward connections during face perception: Specifically, high (gamma) frequencies in higher cortical areas suppressed low (alpha) frequencies in lower areas. This finding provides direct evidence for functional asymmetries that is consistent with anatomical and physiological evidence from animal studies. Lastly, I generalize the bilinear form of DCM for IR to dissociate the induced responses from evoked ones in terms of their functional role. The backward modulatory effect is expressed as induced, but not evoked responses.
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CILIBERTI, NICOLA. "BIOLOGY, EPIDEMIOLOGY AND MODELLING OF BOTRYTIS CINEREA PERS.:FR., THE CAUSAL AGENT OF GREY MOULD IN GRAPEVINE." Doctoral thesis, Università Cattolica del Sacro Cuore, 2015. http://hdl.handle.net/10280/6067.
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Gli obbiettivi di questa tesi di dottorato erano: i) valutare l’effetto di differenti condizioni ambientali sulla biologia ed epidemiologia di isolati di B. cinerea appartenenti alle sub-popolazioni transposa e vacuma, e ii) sviluppare un nuovo modello previsionale per predire il rischio di muffa grigia nei vigneti tra le fasi fenologiche di sviluppo delle infiorescenze e maturazione dei grappoli.
Gli effetti della temperatura, durata di bagnatura e umidità relativa sulle infezioni di infiorescenze e bacche di Vitis vinifera sono stati valutati con inoculazioni artificiali di isolati di B. cinerea. Gli effetti della temperatura, attività dell’acqua, umidità relativa e composizione delle bacche di uva sulla germinazione dei conidi, crescita miceliale e produzione di conidi sono stati valutati su substrati artificiali. I risultati evidenziano che la capacità di causare infezioni varia con gli isolati indipendentemente dall’appartenenza alle sub-popolazioni transposa o vacuma. Inoltre, le risposte dei differenti isolati al variare delle condizioni ambientali risultano essere simili.
Basandosi sui risultati ottenuti sono state sviluppate equazioni matematiche per spiegare l’effetto dei fattori ambientali sull’incidenza delle infezioni di infiorescenze e bacche, germinazione dei conidi, crescita miceliale e produzione di conidi. Un nuovo modello previsionale è stato sviluppato per predire le infezioni di Botrytis cinerea nei vigneti utilizzando le equazioni sviluppate e seguendo un approccio meccanicistico. Il modello è stato validato per 6 anni (2009-2014) in 13 vigneti localizzati in Italia e Francia. Il nuovo modello risulta essere più completo di quelli proposti finora in letteratura e può essere utilizzato per migliorare le strategie di controllo della muffa grigia nei vigneti.The aims of this Doctoral work were: i) to investigate the effect of different environmental conditions on biology and epidemiology of B. cinerea strains belonging the two transposon types vacuma and transposa, and ii) develop a new weather-driven mechanistic model in order to predict risk of grey mould in vineyards from early growth of inflorescences to berry ripening. The effect of temperature, wetness duration and relative humidity on infection of Vitis vinifera inflorescences and berries was investigated by artificial inoculation of B. cinerea strains. The effect of temperature, water activity, relative humidity and grape berry composition on conidia germination, colony growth and conidial production was investigated in agar-medium. The results showed that the ability to cause infection was a strain rather than a transposon genotype attribute. Moreover, the general response to different environmental conditions is similar among different B. cinerea strains. Based on these data, equations were developed to account the combined effects of environmental factors on infection incidence, conidia germination, colony growth and conidial production. A new previsional model for Botrytis cinerea infections on grapevine was elaborated using the equations developed and following a mechanistic approach. The model was validated over a 6-year period (2009 to 2014) in 13 vineyards located in different grape-growing areas of Italy and France. The model is more complete than the others proposed in literature and represents an improvement to control grey mould in vineyards.
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CILIBERTI, NICOLA. "BIOLOGY, EPIDEMIOLOGY AND MODELLING OF BOTRYTIS CINEREA PERS.:FR., THE CAUSAL AGENT OF GREY MOULD IN GRAPEVINE." Doctoral thesis, Università Cattolica del Sacro Cuore, 2015. http://hdl.handle.net/10280/6067.
Full textAbstract:
Gli obbiettivi di questa tesi di dottorato erano: i) valutare l’effetto di differenti condizioni ambientali sulla biologia ed epidemiologia di isolati di B. cinerea appartenenti alle sub-popolazioni transposa e vacuma, e ii) sviluppare un nuovo modello previsionale per predire il rischio di muffa grigia nei vigneti tra le fasi fenologiche di sviluppo delle infiorescenze e maturazione dei grappoli.
Gli effetti della temperatura, durata di bagnatura e umidità relativa sulle infezioni di infiorescenze e bacche di Vitis vinifera sono stati valutati con inoculazioni artificiali di isolati di B. cinerea. Gli effetti della temperatura, attività dell’acqua, umidità relativa e composizione delle bacche di uva sulla germinazione dei conidi, crescita miceliale e produzione di conidi sono stati valutati su substrati artificiali. I risultati evidenziano che la capacità di causare infezioni varia con gli isolati indipendentemente dall’appartenenza alle sub-popolazioni transposa o vacuma. Inoltre, le risposte dei differenti isolati al variare delle condizioni ambientali risultano essere simili.
Basandosi sui risultati ottenuti sono state sviluppate equazioni matematiche per spiegare l’effetto dei fattori ambientali sull’incidenza delle infezioni di infiorescenze e bacche, germinazione dei conidi, crescita miceliale e produzione di conidi. Un nuovo modello previsionale è stato sviluppato per predire le infezioni di Botrytis cinerea nei vigneti utilizzando le equazioni sviluppate e seguendo un approccio meccanicistico. Il modello è stato validato per 6 anni (2009-2014) in 13 vigneti localizzati in Italia e Francia. Il nuovo modello risulta essere più completo di quelli proposti finora in letteratura e può essere utilizzato per migliorare le strategie di controllo della muffa grigia nei vigneti.The aims of this Doctoral work were: i) to investigate the effect of different environmental conditions on biology and epidemiology of B. cinerea strains belonging the two transposon types vacuma and transposa, and ii) develop a new weather-driven mechanistic model in order to predict risk of grey mould in vineyards from early growth of inflorescences to berry ripening. The effect of temperature, wetness duration and relative humidity on infection of Vitis vinifera inflorescences and berries was investigated by artificial inoculation of B. cinerea strains. The effect of temperature, water activity, relative humidity and grape berry composition on conidia germination, colony growth and conidial production was investigated in agar-medium. The results showed that the ability to cause infection was a strain rather than a transposon genotype attribute. Moreover, the general response to different environmental conditions is similar among different B. cinerea strains. Based on these data, equations were developed to account the combined effects of environmental factors on infection incidence, conidia germination, colony growth and conidial production. A new previsional model for Botrytis cinerea infections on grapevine was elaborated using the equations developed and following a mechanistic approach. The model was validated over a 6-year period (2009 to 2014) in 13 vineyards located in different grape-growing areas of Italy and France. The model is more complete than the others proposed in literature and represents an improvement to control grey mould in vineyards.
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YUM, YONG-SEOP. "Tests de causalite dans les modeles macroeconometriques dynamiques." Paris 1, 1994. http://www.theses.fr/1994PA010026.
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Cette these est conscaree a l'etude des tests de causalite a la granger. L'une des carateristiques importantes de ces tests est l'hypothese de stationnarite des series. Ce travail considere les series nonstationnaires (integrees d'ordre un), admettant une representation vectorielle autoregressive (var) finie dont les coefficients sont constants dans le temps. Dans ce cas, l'absence ou la presence de cointegration influence les tests de causalite. En presence de cointegration, toda et philips proposent une nouvelle methode, consistant a construire des statistiques dans un modele a correction d'erreur (ecm), cependant, les formules de leurs statistiques sont compliquees. Nous proposons alors des formules plus simples. Construites a partir du modele ecrm. Elles convergent vers une loi chi 2. Par ailleurs, cette these elargit la recherche a des series avec tendance deterministe de degre un. Cela conduit a proposer trois definitions de cointegration; cointegration stochastique, cointegration deterministe et cointegration globale. Notre travail considere trois formes ecm, derivees d'un modele var fini, selon le niveau de la prise en compte des contraintes sur le coefficient du terme temporel. Ce travail realise : (1) la comparaison de ces trois formes ecm sur le plan econometrique theorique, (2) l'etude des consequences de la mauvaise estimation du modele ecm de johansen (base sur la tendance deterministe specifique), (3) la proposition des statistiques du test de cointegration globale, (4) les modifications des formules des statistiques proposees concernant les tets de causalite. Diverses simulations sont aussi effectuees, afin de comparer les statistiques considerees.
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Djordjilovic, Vera. "Graphical modelling of biological pathways." Doctoral thesis, Università degli studi di Padova, 2015. http://hdl.handle.net/11577/3424702.
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Biological pathways underlie the basic functions of a living cell. They are complex diagrams featuring genes, proteins and other small molecules, showing how they work together to achieve a particular biological effect. From a technical point of view, they are networks represented through a graph where genes and their connections are, respectively, nodes and edges of a graph.
The main research objective of this thesis is to develop a framework for simulating effects of gene silencing.
To this end, we propose a three step approach. First, we refine the structure of a pathway via our CK2 algorithm. Next, we assess the uncertainty in the refined structure. Finally, we simulate gene silencing through intervention analysis in causal graphical models. The proposed approach showed promising results when applied to the problem of predicting the effect of the knockdown of the nkd gene in Drosophila Melanogaster.I pathway biologici sono alla base del funzionamento delle cellule viventi. Tali pathway sono diagrammi complessi che coinvolgono geni, proteine e altre piccole molecole, mostrando come essi svolgano un ruolo congiunto nel raggiungimento di uno specifico effetto biologico. Da un punto di vista tecnico, questi network sono rappresentati mediante diagrammi dove i geni e le loro connessioni sono, rispettivamente, nodi e archi. Il principale obiettivo di questa ricerca è sviluppare una tecnica per simulare gli effetti del silenziamento genico. A tal fine, proponiamo un approccio basato su tre passi. Nel primo passo, raffiniamo la struttura di un pathway attraverso il nostro algoritmo CK2. In seguito, nel secondo passo, valutiamo l'incertezza nella struttura raffinata. Infine, nel terzo passo, simuliamo il silenziamento genico tramite intervention analysis nei modelli grafici causali. L'approccio proposto mostra risultati promettenti se applicato al problema della previsione dell'effetto del silenziamento del gene nkd della Drosophila Melanogaster.
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O'Keeffe, Aidan Gerard. "Causal inference and dynamic modelling in the analysis of longitudinal data." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609903.
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Saengphueng, Sompop. "EXPLORATION OF CAUSAL AND CORRELATIONAL MODELLING IN CANCER : GLIOBLASTOMA CASE STUDY." Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1428074720.
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Orozco, de la Paz Sebastián. "Análisis comparativo y causal de modelos de volatilidad para activos financieros." Tesis, Universidad de Chile, 2014. http://www.repositorio.uchile.cl/handle/2250/129900.
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Ingeniero Civil IndustrialDentro del trabajo de memoria, se analizaron los modelos de volatilidad de Desviación Estándar, Alisamiento Exponencial de la Varianza, GARCH con distribución Normal y Normal Inversa Gaussiana y el GJR GARCH, los cuales se aplicaron al precio del cobre, al tipo de cambio dólar-peso observado, al precio de la acción de Copec, al IPSA y a la TIR de un BCP a 10 años, buscando establecer las ventajas y desventajas de cada uno con la finalidad de generar una métrica que permita, al tomador de decisión, escoger el mejor modelo de volatilidad a usar bajo sus requerimientos y recursos. Además, se estudiarán efectos causales de la volatilidad en los activos escogidos para entender de mejor forma las causas que la originan. Se observó que los modelos GARCH están por sobre los otros dos modelos en todos los criterios escogidos, exceptuando el costo computacional. Además, los resultados de estos modelos son consistentes con la literatura en cuanto a determinar las características de la volatilidad (sensibilidad al corto plazo, persistencia y velocidad de reversión) y que cuando los retornos distribuyen cercanos a una Normal, los modelos GARCH entregan valores similares, los cuales difieren al cambiar la distribución por otra con asimetría o colas más gruesas, donde los modelos NIG y GJR son capaces de capturar información que el otro no puede. Además se observa que existe una relación fuerte entre el riesgo del cobre con el tipo de cambio dólar-peso, donde el metal genera cambios en el valor de la moneda norteamericana. Adicional a ésta se encontraron otras relaciones débiles. Se concluye que la volatilidad es causada por tres principales factores, la persistencia, el retorno del activo y el contagio de riesgo con otros activos de la economía. Finalmente, se concluye que una adecuada medición de la volatilidad es de suma importancia, ya que tal como se observó para el caso del tipo de cambio dólar-peso, sin necesariamente cambiar la forma de estimar la provisión, sino utilizando una diferente forma de medir la volatilidad, se puede ahorrar una significativa cantidad de dinero.
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Panchenko, Valentyn. "Nonparametric methods in economics and finance: dependence, causality and prediction." [S.l. : Amsterdam : s.n.] ; Universiteit van Amsterdam [Host], 2006. http://dare.uva.nl/document/30844.
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Burda, Maike M. "Testing for causality with Wald tests under nonregular conditions." Doctoral thesis, [S.l.] : [s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=968852432.
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Guerrero, Alejandro. "Strategy realisation process : a modelling enabling approach." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/8190.
Full textAbstract:
Changing conditions within an organisation's environment necessitate enactment of the strategy realisation process to produce relevant coping strategic intents to successfully reconfigure current, or potential, process networks to better exploit potential opportunities or minimise impacts of a potential threats. Literature regarding strategy realisation has not produced a coherent approach to describe and decompose the subprocesses of the strategy realisation, i.e., several different approaches have been taken to enact some components however there is no formal decomposition of such process. A revision of the strategy realisation literature was conducted and a formal decomposition model for the strategy realisation process was conceived. Various modelling tools, methods and techniques were surveyed to enable the underpinning of the proposed strategy realisation conceptualisation. Utilising a combination of static, causal and simulation modelling methods and tools, a research methodology was proposed to underpin aspects of the enterprise which would facilitate the decision making process of the strategy realisation process. Two case studies were identified in which the proposed methodology could be implemented. In the first case study, two differing strategic intents were analysed within the same organisation under opposing economic conditions. The second case study observed the implementation of a different system configuration to achieve a strategic intent. The strategy realisation process was studied using the described conceptualisation and the enterprise was modelled. Key variables, set by senior management were observed and quantitative analysis was undertaken and reported. It was concluded that the use of modelling methods providing quantitative and qualitative analysis facilitated the decision process within an organisation. A new conceptualisation of the strategy realisation process and the integration of modelling methods, tools and techniques were devised.
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Mashamhanda, Tendai. "Modelling the causality between FDI and Zimbabwe’s economic growth." Thesis, Rhodes University, 2017. http://hdl.handle.net/10962/50260.
Full textAbstract:
The study investigates the causal nexus between economic growth and FDI in Zimbabwe for the period spanning 1976 to 2011. The bounds testing approach to cointegration and Granger causality methodology was applied and results suggest a bi-directional causal relationship between FDI and economic growth in the long run. However, the causal effect from economic growth to FDI was weak. Domestic investment, human capital and trade openness were also found to be crucial determinants of economic growth in Zimbabwe. Implementing policies that promote inflow of FDI into Zimbabwe are recommended.
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Meurk, Carla Siobhan. "Causally Appropriate Graphical Modelling for Time Series with Applications to Economics, Ecology and Environmental Science." Thesis, University of Canterbury. Mathematics and Statistics, 2005. http://hdl.handle.net/10092/1152.
Full textAbstract:
I apply the GMTS approach to graphical modelling of time series to data sets from economics, ecology and environmental science. This approach improves on traditional approaches to modelling insofar as it selects the most parsimonius model. I improve on this approach by removing some redundancies in the GMTS approach. However, a bias in terms of which links are selected means that it is unlikely that this model will select the best causal model.
24
Renwick, Alan. "Complex causal modelling : institutional choice in Hungary, Czechoslovakia and Poland, 1989-1990." Thesis, University of Oxford, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402248.
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Santi, Maria Grazia. "Analisi di sensibilità di un modello matematico per la causal inference e le interazioni multisensoriali." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/19372/.
Full textAbstract:
La percezione del mondo esterno è basata sulla integrazione sensoriale di numerosi input differenti. Tale integrazione tende a migliorare le prestazioni umane, riducendo le ambiguità percettive e migliorando l’individuazione degli stimoli.
Non è però ancora chiaro come il cervello organizzi tutti questi aspetti sensoriali in un concetto coerente. È quindi fondamentale studiare l’integrazione multi-sensoriale al fine di comprendere come il nostro cervello riesca a collegare le molteplici fonti di informazione permettendoci di interagire con l’ambiente che ci circonda.
Tale studio può essere condotto utilizzando differenti approcci. In particolare, questo lavoro è basato sull'utilizzo di un modello di ispirazione biologica utile alla risoluzione del problema della causal inference e della integrazione multi-sensoriale di stimoli uditivi e visivi.
Obiettivo centrale di questa tesi è stato svolgere una analisi di sensibilità del modello utilizzato. Nello specifico tale ricerca è stata incentrata nella individuazione di parametri utili al corretto funzionamento della rete neurale, in modo da permettere a questa di emulare il comportamento del cervello umano se sottoposto a stimoli audio-visivi. La peculiarità di questo lavoro è stata riuscire a riprodurre nel modello considerato gli effetti illusori del ventriloquismo spaziale e temporale quando sottoposto a condizioni simili a quelle in cui hanno luogo tali fenomeni nell'essere umano.
Riuscire ad emulare attraverso un modello di ispirazione biologica fenomeni illusori di questo tipo può giocare un ruolo molto importante nel fornire una più profonda comprensione dei meccanismi che partecipano al processo di integrazione multi-sensoriale, oltre che nell'intuire la topologia delle connessioni neurali tra differenti aree del cervello.
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ROMIO, SILVANA ANTONIETTA. "Modelli marginali strutturali per lo studio dell'effetto causale di fattori di rischio in presenza di confondenti tempo dipendenti." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2010. http://hdl.handle.net/10281/8048.
Full textAbstract:
Uno degli obiettivi piu importanti della ricerca epidemiologica è quello di analizzare la relazione tra uno o più fattori di rischio ed un evento. Tali relazioni sono spesso complicate dalla presenza di confondenti, il cui concetto è estremamente complesso da formalizzare.
Dal punto di vista dell'analisi causale, si dice che esiste confondimento quando la misura di associazione non coincide con quella di effetto corrispondente, cioè quando ad esempio il rischio relativo non coincide con il rischio relativo causale. Il problema è quindi quello di individuare i disegni e le ipotesi sulla base delle quali è possibile calcolare l'effetto causale oggetto di studio. Ad esempio, gli studi clinici controllati randomizzati sono nati con lo scopo di minimizzare l'influenza di errori sistematici nella misurazione dell'effetto di un fattore di rischio su di un outcome. Inoltre in questi studi le misure di associazione risultano essere uguali a quelle di effetto (causali). Negli studi osservazionali lo scenario diventa più complesso per la presenza di una o più variabili che possono alterare o 'confondere' la relazione d'interesse poichè lo sperimentatore non può in alcun modo intervenire sulle covariate osservate né sull'outcome. Di particolare interesse risulta quindi l'identificazione di metodi che permettano di risolvere il problema del confondimento.
Il problema è particolarmente complesso nello studio dell'effetto causale di un fattore di rischio in presenza di confondenti tempo dipendenti e cioè una variabile che, condizionatamente alla storia di esposizione pregressa è un predittore sia dell'outcome che dell'esposizione successiva. Nel presente lavoro è stato studiato un importante problema di sanità pubblica come quello di esplorare l'esistenza di una relazione causale tra abitudine al fumo e diminuzione dell'indice di massa corporea (body mass index - BMI) considerando come confondente tempo dipendente lo stesso BMI misurato al tempo precedente, utilizzando un modello marginale strutturale per misure ripetute avendo a disposizione i dati relativi ad una coorte di studenti svedesi (coorte BROMS). L'elevata numerosita di tale coorte e l'accuratezza e tipologia dei dati raccolti la rendono particolarente adatta allo studio di fenomeni dinamici comportamentali caratteristici dell'adolescenza.
Dallo studio emerge come l'effetto causale cumulato del fumo di sigaretta sulla riduzione del BMI è significativo solo nelle donne, con una stima del parametro relativo all'interazione tra l'esposizione al fumo e genere pari a 0.322 (p-value < 0.001) mentre la stima del parametro relativo al consumo cumulato di sigarette nei maschi è non signicativo e pari a 0.053 (p-value pari a 0.464). I risultati ottenuti sono consistenti con quanto riportato in studi precedenti.
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Kasperskaya, Yulia. "Essays on causal performance measurement models." Doctoral thesis, Universitat Pompeu Fabra, 2007. http://hdl.handle.net/10803/7348.
Full textAbstract:
La tesis trata de los modelos de gestión modernos de naturaleza causal, entre los que destaca el Cuadro de Mando Integral (CMI). En primer lugar, se presenta un análisis conceptual su supuesto central, las relaciones causa-efecto. En segundo lugar, se ofrece un análisis estadístico de los supuestos del CMI. En tercer lugar, a partir dos casos de estudio de ayuntamientos, se compara y analiza la implementación del CMI en las organizaciones. El análisis conceptual indica que la complejidad, la incertidumbre y el carácter dinámico del entorno pueden obstaculizar la elaboración de modelos válidos de causa-efecto. Los resultados del análisis estadístico no permiten confirmar la hipótesis de existencia de relaciones estables en el CMI. Finalmente, el análisis de los casos sugiere que las organizaciones pueden recurrir a diversas tácticas y escenarios para implementar el CMI y enfatiza la influencia que las rutinas y normas establecidas en las organizaciones ejercen en ello.This dissertation address a number of research questions related to causal performance measurement models, such as the Balanced Scorecard (BSC). First, we provide an analytical discussion on the topic of the cause-and-effect relationships in these models. Second, we test of the BSC assumptions on empirical data coming from the dynamic enterprises. Third, we compare and analyze the BSC adoption by two city councils. The conceptual analysis indicates that dynamic, complex and uncertain environment and the cognitive limitations of managers may greatly challenge the elaboration of valid causal models. Our statistical results give little support to the existence of stable BSC links. Our case studies findings show diverse organizational rationalities behind the BSC adoption in organizations and the importance of the existing rules and routines.
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Obeid, Abdul. "Modelling contextuality amidst causal influences by means of a computationally tractable combinatorial approach." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/226105/1/Abdul_Obeid_Thesis.pdf.
Full textAbstract:
This thesis is concerned with modelling contextuality in the fields of Quantum Information Science and Quantum Cognition. It extends the combinatorial approach by contributing computational tractable variants of the Foulis-Randall product and Weighted Fractional Packing Number for arbitrarily large contextuality experiments. The thesis also presents a set of techniques that allow contextuality to be differentiated between causal influences and noise.
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CASTALDELLO, Cosetta. "LA PARTECIPAZIONE MORALE AL REATO. IL TORMENTATO RAPPORTO TRA MODELLO CAUSALE E INTERAZIONI PSICHICHE NEL DIRITTO PENALE." Doctoral thesis, Università degli studi di Ferrara, 2015. http://hdl.handle.net/11392/2388978.
Full textAbstract:
This thesis concerns the issue related to the assessment of a causal connection (which represents, according to the legal literature and to Italian jurisprudence, one of the most important requirements to establish the criminal relevance of the conduct of those who participate in the commission of a crime) between a conduct of participation in a crime and the offence actually realized. In particular, this problem is related to psychological assistances, that is to the cases in which a person assists in the commission of the crime by “counseling” “commanding” or “encouraging” the material executor in the commission of the criminal offense. In fact, in these cases the difficulties connected to the judicial assessment of causality depend on absence of scientific evidences about the existence of regular connections between these kinds of conducts and psychological events. The same problem exists with regard to different cases. Indeed, what we could translate as “psychic interaction” constitutes an important element of several kind of crimes (e.g. stalking). Therefore, it is necessary to verify if the ordinary parameters of causality assessment could be applied to the cases in which a human action involves a psychological effect.
30
Koen, Hildegarde Suzanne. "Predictive policing in an endangered species context : combating rhino poaching in the Kruger National Park." Thesis, University of Pretoria, 2017. http://hdl.handle.net/2263/61301.
Full textAbstract:
Approximately three rhinos are poached daily in South Africa. Rhino poaching is a serious problem
that a ects not only the rhino population of South Africa, but also the rhino population of the world.
South Africa has the largest rhino population and of those rhinos the largest number can be found in
the Kruger National Park (KNP). The KNP has been hit the hardest by the poaching epidemic, losing
1,175 rhinos in 2015 alone. Two big challenges are the size of the park and the unknown locations
of both the poachers and new poaching events. The KNP is the size of a small country and there are
simply not enough rangers to patrol this area e ectively. A costly solution would be to employ more
rangers, but a proposed alternative is to reduce the search space and thus ensure that the rangers are
allocated to the high risk areas first. A mathematical model was developed in the form of a Bayesian
network (BN) to infer the most important factors contributing to poaching events and to model the
rhino poaching problem. This model can be used to predict the area in which a future poaching attack
could take place and thereby reduce the search area of rangers. The model also serves as a vehicle to
enhance the understanding of the problem and encourage reasoning and discussion amongst decision
makers. The map of the KNP is divided into cells and each cell is given a poaching probability, based
on the outcome of the BN. This probability map forms a heat map that can be shown to the control
centre and rangers can then be sent to the respective hotspots on the map. This is a proactive approach,
which is in stark contrast to the numerous reactive approaches attempted thus far. This is the first BN
modelling approach to the rhino poaching problem, and it is also the first BN application to wildlife
crime. Previous applications of BN have only gone so far as environmental modelling, but not wildlife
crimes. In this study the rhino poaching problem was shifted from a complex, ill-structured space to a
position where researchers can begin to address the underlying problems by using a causal model as the
vehicle for understanding the complex interplay between the factors a ecting poaching events.Ongeveer drie renosters word daagliks in Suid-Afrika gestroop. Renosterstroping is 'n ernstige probleem wat nie net die renosterbevolking van Suid-Afrika raak nie, maar ook die res van die wêreld. Suid-Afrika het die grootste renoster bevolking in die wêreld, en die grootste getal van dié renosters word in die Kruger Nasionale Park (KNP) aangetref. Die KNP word die ergste geraak deur die stropings epidemie en 1,175 renosters is in 2015 gestroop. Twee groot uitdagings is die grootte van die park, asook die onbekende posisies van beide die stropers en die nuwe stropingsaanvalle. Die KNP is die grootte van 'n klein land en daar is eenvoudig nie genoeg veldwagters om hierdie area e ektief te patrolleer nie. 'n Duur oplossing sou wees om meer veldwagters aan te stel, maar 'n alternatief is om die soekarea van die veldwagters te verklein en sodoende te verseker dat die veldwagters die hoë-risiko areas eerste, en meer gereeld, patrolleer. 'n Wiskundige model in die vorm van 'n Bayesiese netwerk (BN) is ontwikkel om die belangrikste faktore te bepaal wat bydra tot stropingsaanvalle en uiteindelik die probleem te modelleer. Hierdie model kan gebruik word om die area te voorspel waar 'n stropingsaanval moontlik kan plaasvind en die soekarea van die veldwagters te verminder. Dit dien ook as 'n kanaal om die begrip van die probleem te verbeter en redenasie en bespreking onder besluitnemers aan te moedig. Die kaart van die KNP word in selle verdeel en aan elke sel word 'n stropingswaarskynlikheid toegeken gebaseer op die uitkoms van die BN. Hierdie waarskynlikheidskaart vorm 'n "hittekaart" wat aan die kontrolesentrum gewys kan word, en veldwagters kan dan na die onderskeie responskolle op die kaart gestuur word. Hierdie pro-aktiewe benadering is in teenstelling met huidige reaktiewe benaderings. Hierdie is die eerste BN modellering benadering tot die renosterstropingsprobleem, en dit is ook die eerste BN toepassing tot natuurlewe-misdaad. Vorige toepassings van BNs het omgewingsmodellering aangespreek, maar nie natuurlewe-misdade nie. In hierdie studie word aangetoon hoe die renosterstropings probleem geskuif is vanaf 'n komplekse, swak gestruktureerde probleemruimte na 'n omgewing waar navorsers kan begin om die onderliggende probleme aan te spreek deur gebruik te maak van 'n kausale model as die voertuig van begrip om die komplekse wisselwerking tussen faktore wat 'n stropingsaanval beïnvloed, te verstaan.
Thesis (PhD)--University of Pretoria, 2017.
Electrical, Electronic and Computer Engineering
PhD
Unrestricted
31
COSTANTINI, ROSSELLA. "generazione e caratterizzazione di due differenti modelli murini di condrodisplasie causate da difetti nella biosintesi dei proteoglicani." Doctoral thesis, Università degli studi di Pavia, 2019. http://hdl.handle.net/11571/1248469.
Full textAbstract:
Among the recent classification of genetic skeletal disorders, there is a cluster of diseases such as, Desbuquois dysplasia, diastrophic dysplasia that display common features including short stature, dysplasia of skeletal elements, and congenital joint dislocations. At biochemical level all these disorders are characterized by defects in proteoglycans (PGs) that represent one of the most important components of the cartilage extracellular matrix. alterations of PG synthesis, due to mutations in genes encoding for enzymes or proteins involved in the process, lead to the onset of genetic diseases affecting cartilage.The molecular basis of many skeletal disorders are poorly understood, thus mechanistic studies using an in vivo approach is necessary to investigate the role of the disease gene in the disorder.Among this scenario, this work has been focused, using in vivo models, on the study of two chondrodysplasias in which proteoglycan synthesis is impaired: Chondrodysplasia with joint dislocation gPAPP type and Desbuquois dysplasia type 1. Chondrodysplasia with joint dislocation gPAPP type is a recessive osteochondrodysplasia caused by mutations in IMPAD1 gene that encodes for a Golgi resident adenosine 3‟,5‟-bisphosphate phosphatase crucial for proteoglycan sulfation. Desbuquois dysplasia type 1 is a rare chondrodysplasia caused by mutations in the CANT1 gene encoding for calcium-activated nucleotidase 1, a Golgi protein that preferentially hydrolyzes UDP.The molecular knowledge of the two disorders is different; thus, in this thesis the two models have been used to pursue different objectives: I) the generation and characterization of a conditional knock-in mouse as model for the study of the chondrodysplasia with joint dislocations gPAPP type, II) the validation of a Cant1 knock-out mouse (dbqd mouse) as an animal model of Desbuquois dysplasia type 1 and the study of Cant1 role in PG biosynthesis.
In this work, we have tested an innovative strategy called “the Cre-mediated genetic switch” in vivo, with the aim to generate a Impad1 conditional knock-in mouse for a missense mutation.The Cre-mediated genetic switch combines the ability of Cre recombinase to stably invert or excise a DNA fragment depending upon the orientation of flanking mutant loxP sites. Targeting constructs were generated in which the Impad1 exon 2 and an inverted exon 2* containing the point mutations, were flanked by mutant loxP sites in a head-to-head orientation. When the Cre recombinase is present, the DNA flanked by the mutant loxP sites is expected to be stably inverted leading to the activation of the mutated exon.The targeting vectors were used to generate heterozygous floxed mice in which inversion of the wild-type with the mutant exon has not occurred yet. To generate Impad1 knock-in mice, floxed animals were mated to a global Cre-deleter mouse strain for stable inversion and activation of the mutation.Unexpectedly the phenotype of homozygous Impad1 knock-in animals overlaps with the lethal phenotype described previously in Impad1 knock-out mice. Expression studies demonstrated that mutant mRNA underwent abnormal splicing leading to the synthesis of non-functional proteins. the skeletal phenotypes were not caused by the missense mutations, but by aberrant splicing.The dbqd mouse, an animal model of human Desbuquois dysplasia type I, was previously generated by our research group.
The clinical phenotype of Cant1 knock-out mice showed the same typical features of patients with Desbuquois dysplasia type 1 confirming the dbqd mouse as an animal model of the human disorder. Biochemical studies highlighted the contribution of CANT1 in PG synthesis. GAG synthesis was reduced and chains were shorter and oversulfated
32
COSTANTINI, ROSSELLA. "generazione e caratterizzazione di due differenti modelli murini di condrodisplasie causate da difetti nella biosintesi dei proteoglicani." Doctoral thesis, Università degli studi di Pavia, 2019. http://hdl.handle.net/11571/1248449.
Full textAbstract:
Among the recent classification of genetic skeletal disorders, there is a cluster of diseases such as, Desbuquois dysplasia, diastrophic dysplasia that display common features including short stature, dysplasia of skeletal elements, and congenital joint dislocations. At biochemical level all these disorders are characterized by defects in proteoglycans (PGs) that represent one of the most important components of the cartilage extracellular matrix. alterations of PG synthesis, due to mutations in genes encoding for enzymes or proteins involved in the process, lead to the onset of genetic diseases affecting cartilage.The molecular basis of many skeletal disorders are poorly understood, thus mechanistic studies using an in vivo approach is necessary to investigate the role of the disease gene in the disorder.Among this scenario, this work has been focused, using in vivo models, on the study of two chondrodysplasias in which proteoglycan synthesis is impaired: Chondrodysplasia with joint dislocation gPAPP type and Desbuquois dysplasia type 1. Chondrodysplasia with joint dislocation gPAPP type is a recessive osteochondrodysplasia caused by mutations in IMPAD1 gene that encodes for a Golgi resident adenosine 3‟,5‟-bisphosphate phosphatase crucial for proteoglycan sulfation. Desbuquois dysplasia type 1 is a rare chondrodysplasia caused by mutations in the CANT1 gene encoding for calcium-activated nucleotidase 1, a Golgi protein that preferentially hydrolyzes UDP.The molecular knowledge of the two disorders is different; thus, in this thesis the two models have been used to pursue different objectives: I) the generation and characterization of a conditional knock-in mouse as model for the study of the chondrodysplasia with joint dislocations gPAPP type, II) the validation of a Cant1 knock-out mouse (dbqd mouse) as an animal model of Desbuquois dysplasia type 1 and the study of Cant1 role in PG biosynthesis.
In this work, we have tested an innovative strategy called “the Cre-mediated genetic switch” in vivo, with the aim to generate a Impad1 conditional knock-in mouse for a missense mutation.The Cre-mediated genetic switch combines the ability of Cre recombinase to stably invert or excise a DNA fragment depending upon the orientation of flanking mutant loxP sites. Targeting constructs were generated in which the Impad1 exon 2 and an inverted exon 2* containing the point mutations, were flanked by mutant loxP sites in a head-to-head orientation. When the Cre recombinase is present, the DNA flanked by the mutant loxP sites is expected to be stably inverted leading to the activation of the mutated exon.The targeting vectors were used to generate heterozygous floxed mice in which inversion of the wild-type with the mutant exon has not occurred yet. To generate Impad1 knock-in mice, floxed animals were mated to a global Cre-deleter mouse strain for stable inversion and activation of the mutation.Unexpectedly the phenotype of homozygous Impad1 knock-in animals overlaps with the lethal phenotype described previously in Impad1 knock-out mice. Expression studies demonstrated that mutant mRNA underwent abnormal splicing leading to the synthesis of non-functional proteins. the skeletal phenotypes were not caused by the missense mutations, but by aberrant splicing.The dbqd mouse, an animal model of human Desbuquois dysplasia type I, was previously generated by our research group.
The clinical phenotype of Cant1 knock-out mice showed the same typical features of patients with Desbuquois dysplasia type 1 confirming the dbqd mouse as an animal model of the human disorder. Biochemical studies highlighted the contribution of CANT1 in PG synthesis. GAG synthesis was reduced and chains were shorter and oversulfated
33
COSTANTINI, ROSSELLA. "generazione e caratterizzazione di due differenti modelli murini di condrodisplasie causate da difetti nella biosintesi dei proteoglicani." Doctoral thesis, Università degli studi di Pavia, 2019. http://hdl.handle.net/11571/1248390.
Full textAbstract:
Among the recent classification of genetic skeletal disorders, there is a cluster of diseases such as, Desbuquois dysplasia, diastrophic dysplasia that display common features including short stature, dysplasia of skeletal elements, and congenital joint dislocations. At biochemical level all these disorders are characterized by defects in proteoglycans (PGs) that represent one of the most important components of the cartilage extracellular matrix. alterations of PG synthesis, due to mutations in genes encoding for enzymes or proteins involved in the process, lead to the onset of genetic diseases affecting cartilage.The molecular basis of many skeletal disorders are poorly understood, thus mechanistic studies using an in vivo approach is necessary to investigate the role of the disease gene in the disorder.Among this scenario, this work has been focused, using in vivo models, on the study of two chondrodysplasias in which proteoglycan synthesis is impaired: Chondrodysplasia with joint dislocation gPAPP type and Desbuquois dysplasia type 1. Chondrodysplasia with joint dislocation gPAPP type is a recessive osteochondrodysplasia caused by mutations in IMPAD1 gene that encodes for a Golgi resident adenosine 3‟,5‟-bisphosphate phosphatase crucial for proteoglycan sulfation. Desbuquois dysplasia type 1 is a rare chondrodysplasia caused by mutations in the CANT1 gene encoding for calcium-activated nucleotidase 1, a Golgi protein that preferentially hydrolyzes UDP.The molecular knowledge of the two disorders is different; thus, in this thesis the two models have been used to pursue different objectives: I) the generation and characterization of a conditional knock-in mouse as model for the study of the chondrodysplasia with joint dislocations gPAPP type, II) the validation of a Cant1 knock-out mouse (dbqd mouse) as an animal model of Desbuquois dysplasia type 1 and the study of Cant1 role in PG biosynthesis.
In this work, we have tested an innovative strategy called “the Cre-mediated genetic switch” in vivo, with the aim to generate a Impad1 conditional knock-in mouse for a missense mutation.The Cre-mediated genetic switch combines the ability of Cre recombinase to stably invert or excise a DNA fragment depending upon the orientation of flanking mutant loxP sites. Targeting constructs were generated in which the Impad1 exon 2 and an inverted exon 2* containing the point mutations, were flanked by mutant loxP sites in a head-to-head orientation. When the Cre recombinase is present, the DNA flanked by the mutant loxP sites is expected to be stably inverted leading to the activation of the mutated exon.The targeting vectors were used to generate heterozygous floxed mice in which inversion of the wild-type with the mutant exon has not occurred yet. To generate Impad1 knock-in mice, floxed animals were mated to a global Cre-deleter mouse strain for stable inversion and activation of the mutation.Unexpectedly the phenotype of homozygous Impad1 knock-in animals overlaps with the lethal phenotype described previously in Impad1 knock-out mice. Expression studies demonstrated that mutant mRNA underwent abnormal splicing leading to the synthesis of non-functional proteins. the skeletal phenotypes were not caused by the missense mutations, but by aberrant splicing.The dbqd mouse, an animal model of human Desbuquois dysplasia type I, was previously generated by our research group.
The clinical phenotype of Cant1 knock-out mice showed the same typical features of patients with Desbuquois dysplasia type 1 confirming the dbqd mouse as an animal model of the human disorder. Biochemical studies highlighted the contribution of CANT1 in PG synthesis. GAG synthesis was reduced and chains were shorter and oversulfated
34
Hewitt, Anthea. "Causal modelling of the relationship between attribution style, coping and suicidal behaviour : a comparative study." Thesis, University of Portsmouth, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.271446.
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Carter, Matthew Edward. "Setting location priors using beamforming improves model comparison in MEG-DCM." Thesis, Virginia Tech, 2014. http://hdl.handle.net/10919/50418.
Full textAbstract:
Modelling neuronal interactions using a directed network can be used to provide insight into
the activity of the brain during experimental tasks. Magnetoencephalography (MEG) allows
for the observation of the fast neuronal dynamics necessary to characterize the activity of
sources and their interactions. A network representation of these sources and their con-
nections can be formed by mapping them to nodes and their connection strengths to edge
weights. Dynamic Causal Modelling (DCM) presents a Bayesian framework to estimate the
parameters of these networks, as well as the ability to test hypotheses on the structure of
the network itself using Bayesian model comparison. DCM uses a neurologically-informed
representation of the active neural sources, which leads to an underdetermined system and
increased complexity in estimating the network parameters. This work shows that inform-
ing the MEG DCM source location with prior distributions defined using a MEG source
localization algorithm improves model selection accuracy. DCM inversion of a group of can-
didate models shows an enhanced ability to identify a ground-truth network structure when
source-localized prior means are used.Master of Science
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Dauvermann, Maria Regina. "Investigation into functional large-scale networks in individuals with schizophrenia using fMRI data and Dynamic Causal Modelling." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/10022.
Full textAbstract:
Schizophrenia is a complex and severe psychiatric disorder with positive symptoms, negative symptoms and cognitive deficits. Preclinical neurobiological studies showed that alterations of dopaminergic and glutamatergic neurotransmitter circuits involving the prefrontal cortex resulted in cognitive impairment such as working memory. Functional activation and functional connectivity findings of functional Magnetic Resonance Imaging (fMRI) data provided support for prefrontal dysfunction during fMRI working memory tasks in individuals with schizophrenia. However, these findings do not offer a neurobiological interpretation of the fMRI data. Biophysical modelling of functional large-scale networks has been designed for the analysis of fMRI data, which can be interpreted in a mechanistic way. This approach may enable the interpretation of fMRI data in terms of altered synaptic plasticity processes found in schizophrenia. One such process is gating mechanism, which has been shown to be altered for the thalamo-cortical and meso-cortical connection in schizophrenia. The primary aim of the thesis was to investigate altered synaptic plasticity and gating mechanisms with Dynamic Causal Modelling (DCM) within functional large-scale networks during two fMRI tasks in individuals with schizophrenia. Applying nonlinear DCM to the verbal fluency fMRI task of the Edinburgh High Risk Study, we showed that the connection strengths with nonlinear modulation for the thalamo-cortical connection was reduced in subjects at high familial risk of schizophrenia when compared to healthy controls. These results suggest that nonlinear DCM enables the investigation of altered synaptic plasticity and gating mechanism from fMRI data. For the Scottish Family Mental Health Study, we reported two different optimal linear models for individuals with established schizophrenia (EST) and healthy controls during working memory function. We suggested that this result may indicate that EST and healthy controls used different functional large-scale networks. The results of nonlinear DCM analyses may suggest that gating mechanism was intact in EST and healthy controls. In conclusion, the results presented in this thesis give evidence for the role of synaptic plasticity processes as assessed in functional large-scale networks during cognitive tasks in individuals with schizophrenia.
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Strikholm, Birgit. "Essays on nonlinear time series modelling och hypothesis testing." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-535.
Full textAbstract:
There seems to be a common understanding nowadays that the economy is nonlinear. Economic theory suggests features that can not be incorporated into linear frameworks, and over the decades a solid body of empirical evidence of nonlinearities in economic time series has been gathered. This thesis consists of four essays that have to do with various forms of nonlinear statistical inference. In the first chapter the problem of determining the number regimes in a threshold autoregressive (TAR) model is considered. Typically, the number of regimes (or thresholds) is assumed unknown and has to be determined from the data. The solution provided in the chapter first uses the smooth transition autoregressive (STAR) model with a fixed and rapid transition to approximate the TAR model. The number of thresholds is then determined using sequential misspecification tests developed for the STAR model. The main characteristic of the proposed method is that only standard statistical inference is used, as opposed to non-standard inference or computation intensive bootstrap-based methods. In the second chapter a similar idea is employed and the structural break model is approximated with a smoothly time-varying autoregressive model. By making the smooth changes in parameters rapid, the model is able to closely approximate the corresponding model with breaks in the parameter structure. This approximation makes the misspecification tests developed for the STR modelling framework available and they can be used for sequentially determining the number of breaks. Again, the method is computationally simple as all tests rely on standard statistical inference. There exists literature suggesting that business cycle fluctuations affect the pattern of seasonality in macroeconomic series. A question asked in the third chapter is whether other factors such as changes in institutions or technological change may have this effect as well. The time-varying smooth transition autoregressive (TV- STAR) models that can incorporate both types of change are used to model the (possible) changes in seasonal patterns and shed light on the hypothesis that institutional and technological changes (proxied by time) may have a stronger effect on seasonal patterns than business cycle. The TV-STAR testing framework is applied to nine quarterly industrial production series from the G7 countries, Finland and Sweden. These series display strong seasonal patterns and also contain the business cycle fluctuations. The empirical results of the chapter suggest that seasonal patterns in these series have been changing over time and, furthermore, that the business cycle fluctuations do not seem to be the main cause for this change. The last chapter of the thesis considers the possibility of testing for Granger causality in bivariate nonlinear systems when the exact form of the nonlinear relationship between variables is not known. The idea is to linearize the testing problem by approximating the nonlinear system by its Taylor expansion. The expansion is linear in parameters and one gets round the difficulty caused by the unknown functional form of the relationship under investigation.Diss. Stockholm : Handelshögskolan, 2004
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ONESTI, GIOVANNI. "Studi sulle dinamiche dell'inoculo di Guignardia bidwellii, agente causale del marciume nero della vite." Doctoral thesis, Università Cattolica del Sacro Cuore, 2016. http://hdl.handle.net/10280/10799.
Full textAbstract:
L’ascomicete Guignardia bidwellii, agente causale del marciume nero della vite, è un patogeno economicamente importante in alcuni areali viticoli. La conoscenza, disponibile sul marciume nero dell’uva, è stata recuperata dalla letteratura, analizzata e sintetizzata per sviluppare un modello meccanicistico del ciclo di vita del patogeno, guidata dalle variabili meteorologiche e dalla fenologia della vite, e basata sull'analisi dei sistemi. Il modello è stato poi valutato per la sua capacità di rappresentare il sistema reale e la sua utilità per la comprensione di epidemie di marciume nero su foglie e grappoli in un vigneto del Nord Italia, nel 2013 al 2015. Successivamente, le mancanze di conoscenza sono state analizzate, studiate e quindi colmate attraverso specifici esperimenti. In un primo passo, le dinamiche dell’inoculo primario e dei modelli di dispersione (di entrambi ascospore e conidi) da mummie svernate sono state studiate in un vigneto sperimentale per tre anni. In un secondo passo, l'effetto della temperatura e dell'umidità sulla formazione di picnidi di G. bidwellii e la successiva estrusione di cirri, nelle lesioni su foglia, la produzione e la germinazione dei conidi (inoculo secondario), e la lunghezza del periodo di latenza sono stati studiati sia in condizioni di campo che in ambiente controllato. In un terzo passo, sono stati condotti studi in ambiente controllato per studiare la produzione di conidi di G. bidwellii sulle lesioni di foglie, influenzata da lavaggi ripetuti e alternando periodi di secco ed umido. Il modello epidemiologico sviluppato in questa tesi può essere utilizzata da viticoltori come strumento predittivo per la pianificazione di trattamenti fungicidi nei vigneti.The ascomycete Guignardia bidwellii, causal agent of black-rot on grapevines, is an economically important pathogen in some viticultural areas. The available knowledge on black-rot of grape was retrieved from literature, analyzed, and synthesized to develop a mechanistic model of the life cycle of the pathogen, driven by weather and vine phenology, and based on the systems analysis. The model was then evaluated for its ability to represent the real system and its usefulness for understanding black-rot epidemics on leaves and bunches in a vineyard of north Italy, in 2013 to 2015. Thereafter, weaknesses in our knowledge were analysed and studied through specific experiments. In a first step, dynamics of primary inoculum and dispersal patterns (both ascospores and conidia) from overwintered grape mummies were investigated in an experimental vineyard during three years. In a second step, the effect of temperature and humidity on the formation of G. bidwellii pycnidia and the extrusion of cirri in grape leaf lesions, production and germination of conidia (secondary inoculum), and the length of the latency period were studied under both environmental and controlled conditions. In a third step, environmental-controlled studies were conducted to investigate the production course of G. bidwellii conidia on grape leaf lesions as influenced by repeated washing events and alternate dry and wet periods. The model developed in this thesis can be used by vinegrowers as a predictive tool for scheduling fungicide sprays in the vineyards.
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ONESTI, GIOVANNI. "Studi sulle dinamiche dell'inoculo di Guignardia bidwellii, agente causale del marciume nero della vite." Doctoral thesis, Università Cattolica del Sacro Cuore, 2016. http://hdl.handle.net/10280/10799.
Full textAbstract:
L’ascomicete Guignardia bidwellii, agente causale del marciume nero della vite, è un patogeno economicamente importante in alcuni areali viticoli. La conoscenza, disponibile sul marciume nero dell’uva, è stata recuperata dalla letteratura, analizzata e sintetizzata per sviluppare un modello meccanicistico del ciclo di vita del patogeno, guidata dalle variabili meteorologiche e dalla fenologia della vite, e basata sull'analisi dei sistemi. Il modello è stato poi valutato per la sua capacità di rappresentare il sistema reale e la sua utilità per la comprensione di epidemie di marciume nero su foglie e grappoli in un vigneto del Nord Italia, nel 2013 al 2015. Successivamente, le mancanze di conoscenza sono state analizzate, studiate e quindi colmate attraverso specifici esperimenti. In un primo passo, le dinamiche dell’inoculo primario e dei modelli di dispersione (di entrambi ascospore e conidi) da mummie svernate sono state studiate in un vigneto sperimentale per tre anni. In un secondo passo, l'effetto della temperatura e dell'umidità sulla formazione di picnidi di G. bidwellii e la successiva estrusione di cirri, nelle lesioni su foglia, la produzione e la germinazione dei conidi (inoculo secondario), e la lunghezza del periodo di latenza sono stati studiati sia in condizioni di campo che in ambiente controllato. In un terzo passo, sono stati condotti studi in ambiente controllato per studiare la produzione di conidi di G. bidwellii sulle lesioni di foglie, influenzata da lavaggi ripetuti e alternando periodi di secco ed umido. Il modello epidemiologico sviluppato in questa tesi può essere utilizzata da viticoltori come strumento predittivo per la pianificazione di trattamenti fungicidi nei vigneti.The ascomycete Guignardia bidwellii, causal agent of black-rot on grapevines, is an economically important pathogen in some viticultural areas. The available knowledge on black-rot of grape was retrieved from literature, analyzed, and synthesized to develop a mechanistic model of the life cycle of the pathogen, driven by weather and vine phenology, and based on the systems analysis. The model was then evaluated for its ability to represent the real system and its usefulness for understanding black-rot epidemics on leaves and bunches in a vineyard of north Italy, in 2013 to 2015. Thereafter, weaknesses in our knowledge were analysed and studied through specific experiments. In a first step, dynamics of primary inoculum and dispersal patterns (both ascospores and conidia) from overwintered grape mummies were investigated in an experimental vineyard during three years. In a second step, the effect of temperature and humidity on the formation of G. bidwellii pycnidia and the extrusion of cirri in grape leaf lesions, production and germination of conidia (secondary inoculum), and the length of the latency period were studied under both environmental and controlled conditions. In a third step, environmental-controlled studies were conducted to investigate the production course of G. bidwellii conidia on grape leaf lesions as influenced by repeated washing events and alternate dry and wet periods. The model developed in this thesis can be used by vinegrowers as a predictive tool for scheduling fungicide sprays in the vineyards.
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Bernigau, Holger. "Causal Models over Infinite Graphs and their Application to the Sensorimotor Loop." Doctoral thesis, Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-164734.
Full textAbstract:
Motivation and background
The enormous amount of capabilities that every human learns throughout his life, is probably among the most remarkable and fascinating aspects of life. Learning has therefore drawn lots of interest from scientists working in very different fields like philosophy, biology, sociology, educational sciences, computer sciences and mathematics. This thesis focuses on the information theoretical and mathematical aspects of learning.
We are interested in the learning process of an agent (which can be for example a human, an animal, a robot, an economical institution or a state) that interacts with its environment. Common models for this interaction are Markov decision processes (MDPs) and partially observable Markov decision processes (POMDPs). Learning is then considered to be the maximization of the expectation of a predefined reward function. In order to formulate general principles (like a formal definition of curiosity-driven learning or avoidance of unpleasant situation) in a rigorous way, it might be desirable to have a theoretical framework for the optimization of more complex functionals of the underlying process law. This might include the entropy of certain sensor values or their mutual information. An optimization of the latter quantity (also known as predictive information) has been investigated intensively both theoretically and experimentally using computer simulations by N. Ay, R. Der, K Zahedi and G. Martius. In this thesis, we develop a mathematical theory for learning in the sensorimotor loop beyond expected reward maximization.
Approaches and results
This thesis covers four different topics related to the theory of learning in the sensorimotor loop.
First of all, we need to specify the model of an agent interacting with the environment, either with learning or without learning. This interaction naturally results in complex causal dependencies. Since we are interested in asymptotic properties of learning algorithms, it is necessary to consider infinite time horizons. It turns out that the well-understood theory of causal networks known from the machine learning literature is not powerful enough for our purpose. Therefore we extend important theorems on causal networks to infinite graphs and general state spaces using analytical methods from measure theoretic probability theory and the theory of discrete time stochastic processes. Furthermore, we prove a generalization of the strong Markov property from Markov processes to infinite causal networks.
Secondly, we develop a new idea for a projected stochastic constraint optimization algorithm. Generally a discrete gradient ascent algorithm can be used to generate an iterative sequence that converges to the stationary points of a given optimization problem. Whenever the optimization takes place over a compact subset of a vector space, it is possible that the iterative sequence leaves the constraint set. One possibility to cope with this problem is to project all points to the constraint set using Euclidean best-approximation. The latter is
sometimes difficult to calculate. A concrete example is an optimization over the unit ball in a matrix space equipped with operator norm. Our idea consists of a back-projection using quasi-projectors different from the Euclidean best-approximation. In the matrix example, there is another canonical way to force the iterative sequence to stay in the constraint set:
Whenever a point leaves the unit ball, it is divided by its norm. For a given target function, this procedure might introduce spurious stationary points on the boundary. We show that this problem can be circumvented by using a gradient that is tailored to the quasi-projector used for back-projection. We state a general technical compatibility condition between a quasi-projector and a metric used for gradient ascent, prove convergence of stochastic iterative sequences and provide an appropriate metric for the unit-ball example.
Thirdly, a class of learning problems in the sensorimotor loop is defined and motivated. This class of problems is more general than the usual expected reward maximization and is illustrated by numerous examples (like expected reward maximization, maximization of the predictive information, maximization of the entropy and minimization of the variance of a given reward function). We also provide stationarity conditions together with appropriate gradient formulas.
Last but not least, we prove convergence of a stochastic optimization algorithm (as considered in the second topic) applied to a general learning problem (as considered in the third topic). It is shown that the learning algorithm converges to the set of stationary points. Among others, the proof covers the convergence of an improved version of an algorithm for the maximization of the predictive information as proposed by N. Ay, R. Der and K. Zahedi. We also investigate an application to a linear Gaussian dynamic, where the policies are encoded by the unit-ball in a space of matrices equipped with operator norm.
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Canavan, Shane. "Performance modelling of urban metro rail systems : an application of frontiers, regression, and causal inference techniques." Thesis, Imperial College London, 2015. http://hdl.handle.net/10044/1/27051.
Full textAbstract:
Metro rail provides a vital role towards facilitating the travel needs of major urban economies, and has contributed substantially in transporting the population within cities. However, implementing a safe service to meet with the statutory requirements of operation is fraught with difficulties. Due to high capital expenditures and need for public money, metros are politically sensitive and are subject to scrutiny. Consequently, understanding variation in metro performance continues to be a major research objective. This has proven to be far from straightforward due to the complex nature of the industry and that metro operators are generally monopolistic in nature, with no source of performance comparisons in the same region. This emphasises the need for an international comparison. This thesis focuses on technical efficiency, which concerns the use of input factors (such as capital and labour) to produce metro services. The study is bolstered by using a high quality panel dataset, consisting of 27 metro systems for the period 2004 to 2012. Additional insight into the variation of metro performance is provided as shortcomings in the literature include the lack of appropriate data and insufficient application of statistical techniques. Three empirical contributions are provided. Firstly, by assessing the relative performance of a group of metro systems by calculating technical efficiency scores using Stochastic Frontier Analysis, the study reveals a number of drivers of performance that affect output efficiency. Secondly, the study identifies reliability to be a key influence, and this is subsequently investigated further. Count data regression models are estimated to reveal determinants of incidents which cause a delay to service and provide a means for carrying out future forecasting of incident rates. Finally, given the growing capacity restrictions experienced by metros, the study investigates the causal impact of introducing a technological treatment (in this case, moving block signalling) on technical efficiency using a Propensity Score Matching approach.
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Xiang, Wentao. "Modélisation causale dynamique dans l'inférence de changements en connectivité cérébrale." Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S083.
Full textAbstract:
Nos travaux portent sur la connectivité cérébrale entre des populations neuronales distantes impliquées dans les crises d'épilepsie, et ce à partir de la modélisation causale dynamique (DCM : dynamic causal modelling) dans sa version spectrale. Celle-ci est basée sur deux instances, (i) le modèle neuronal pour interpréter les signaux observés et leurs densités spectrales de puissance, (ii) l'inversion du modèle basée sur l'algorithme d'estimation-maximisation (EM) variationnel pour identifier les paramètres du modèle. L'approche DCM s'avérant sensible à l'initialisation des paramètres, une mauvaise estimation peut s'ensuivre. Pour y pallier, nous proposons deux variantes de l'algorithme DCM spectral, l'algorithme L-DCM basé sur un ajustement local de l'estimation à chaque initialisation et l'algorithme D-DCM basé sur un schéma de type recuit-simulé. Les trois approches sont évaluées à l'aide de deux types de modèle, un modèle basé sur la physiologie (PBM) et un modèle plus affiné en termes de liaisons entre sous-populations neuronales (cPBM), et sont comparées sur des signaux simulés et des signaux stéréoélectroencéphalographiques réels. Nos résultats prouvent non seulement l'efficacité des nouvelles approches mais confirment également l’avantage du cPBM par rapport au PBM en termes de complexité de calcul et de précision d'estimation. Dans un dernier temps, nous nous focalisons sur la lenteur de l'algorithme EM variationnel liée à la méthode de Gauss-Newton employée. Une technique de recherche linéaire optimale (ELS : exact line search) est proposée, consistant à calculer, à chaque itération de l’algorithme itératif, le pas optimal à réaliser dans la direction de plus grande pente. La faisabilité de cette approche est envisagée dans le contexte de mélanges de gaussiennes. Les résultats obtenus sur signaux simulés et réels attestent l'efficacité du schéma proposé lorsqu'il est appliqué à l'algorithme EM conventionnel, mais aussi à d'autres techniques comme l'algorithme du gradient conjugué. Ces résultats préliminaires sont une perspective pour une future extension de l'approche DCMOur work mainly focuses on inferring effective connectivity in distant neural populations involved in epileptic seizures using a model-based technique, the spectral dynamic causal modelling (DCM). A neural mass model (NMM) is used to describe the observed epileptic intracerebral signals and their power spectral densities. DCM includes mainly two steps (i) model inversion based on the maximization of the free energy concept using the variational estimation-maximization (EM) algorithm to identify the parameters of the model and (ii) model comparison where the best model structure in terms of the maximized free energy is identified among other possible structures as the one underlying the observed data. As spectral DCM reveals some sensitivity to the initialization during the variational EM process, a misestimation of the model structure may arise. To cope with this issue, we propose two variants of spectral DCM, the L-DCM and the D-DCM algorithms. While L-DCM is based on a local adjustment of the initial guess, D-DCM relies on a deterministic annealing scheme. The performance of the proposed strategies in terms of effective connectivity inference is assessed using simulated and real human epileptic SEEG (stereoelectroencephalographic) signals. Regarding simulated and real signals, two kinds of NMM are investigated, the physiology-based model (PBM) and the complete physiology-based model (cPBM). Our experiments show the efficiency of the proposed approaches compared to the standard spectral DCM using either PBM or cPBM. The reported results also confirm that cPBM offers lower computational complexity and better estimation quality of the model parameters compared to PBM. Besides, in order to cope with the complexity of spectral DCM which is essentially related to the Gauss-Newton method used in the variational EM algorithm, a simpler ascent gradient method based on an exact line search (ELS) scheme can be employed. It allows for an optimal computation of the gradient step size to be used at each iteration towards the final solution in the given search direction. The feasibility of the ELS scheme in a probabilistic framework is not straightforward and, in this work, the ELS scheme is considered in the context of Gaussian mixture models (GMM) to accelerate the standard EM algorithm. Numerical results using both simulated and real datasets show the efficiency of the proposed ELS scheme when applied to the standard EM algorithm as well as to anti-annealing-based acceleration techniques derived from either the EM algorithm or the expectation conjugate gradient one. The ELS feasibility being proved, its applicability on spectral DCM will be an extension of the present work
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Cadman, Lee. "Exploitation of image sequence causality and temporality in passive 3D metric object modelling." Thesis, University of Warwick, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.400096.
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Danishvar, Morad. "Modelling and design of the eco-system of causality for real-time systems." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/12105.
Full textAbstract:
The purpose of this research work is to propose an improved method for real-time sensitivity analysis (SA) applicable to large-scale complex systems. Borrowed from the EventTracker principle of the interrelation of causal events, it deploys the Rank Order Clustering (ROC) method to automatically group every relevant system input to parameters that represent the system state (i.e. output). The fundamental principle of event modelling is that the state of a given system is a function of every acquirable piece of knowledge or data (input) of events that occur within the system and its wider operational environment unless proven otherwise. It therefore strives to build the theoretical and practical foundation for the engineering of input data. The event modelling platform proposed attempts to filter unwanted data, and more importantly, include information that was thought to be irrelevant at the outset of the design process. The underpinning logic of the proposed Event Clustering technique (EventiC) is to build causal relationship between the events that trigger the inputs and outputs of the system. EventiC groups inputs with relevant corresponding outputs and measures the impact of each input variable on the output variables in short spans of time (relative real-time). It is believed that this grouping of relevant input-output event data by order of its importance in real-time is the key contribution to knowledge in this subject area. Our motivation is that components of current complex and organised systems are capable of generating and sharing information within their network of interrelated devices and systems. In addition to being an intelligent recorder of events, EventiC could also be a platform for preliminary data and knowledge construction. This improvement in the quality, and at times the quantity of input data, may lead to improved higher level mathematical formalism. It is hoped that better models will translate into superior controls and decision making. It is therefore believed that the projected outcome of this research work can be used to predict, stabilize (control), and optimize (operational research) the work of complex systems in the shortest possible time. For proof of concept, EventiC was designed using the MATLAB package and implemented using real-time data from the monitoring and control system of a typical cement manufacturing plant. The purpose for this deployment was to test and validate the concept, and to demonstrate whether the clusters of input data and their levels of importance against system performance indicators could be approved by industry experts. EventiC was used as an input variable selection tool for improving the existing fuzzy controller of the plant. Finally, EventiC was compared with its predecessor EventTracker using the same case study. The results revealed improvements in both computational efficiency and the quality of input variable selection.
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Feyeux, Maxime. "Utilisation des cellules souches embryonnaires humaines porteuses de la mutation causale de la maladie de Huntington en tant que nouveau modèle pathologique." Thesis, Evry-Val d'Essonne, 2011. http://www.theses.fr/2011EVRY0035/document.
Full textAbstract:
La maladie de Huntington (MH) est une maladie neurodégénérative héréditaire. Elle est causée par l'expansion d'un motif CAG qui codant une séquence de poly-glutamine (polyQ) dans le gène huntingtine (HTT). La survenue des symptômes de la maladie est tardive. Pour étudier la MH, un grand nombre de modèles génétiques animaux et cellulaires ont été utilisés au cours des 15 dernières années sans se traduire en traitements bénéfiques de façon durable pour les patients. Les médicaments disponibles servent actuellement à gérer les symptômes de la maladie, et n’ont pas d’effet sur le pronostic létal. Les modèles existants semblent incapables de répliquer pleinement les premières anomalies transcriptionnelles intervenant dans la MH. J’ai tiré profit de la disponibilité de lignées de cellules hESC-MH et émis l'hypothèse qu’elles sont adaptées au déchiffrement des mécanismes pathologiques ou correcteurs impliqués dans la phase pré-symptomatique de la MH, du développement embryonnaire à la vie adulte. J'ai développé des protocoles et des outils cellulaires et moléculaires pour établir les hESC mutantes et normales comme modèle cellulaire de la MH. Puis j’ai utilisé ces cultures pour explorer par une approche transcriptomique la dérégulation transcriptionnelle dans les cellules neurales immatures porteuses de la mutation causale de la MH. J’ai identifié de nouveaux biomarqueurs cellulaires précoces associés à la mutation causale de la MH. Ces résultats suggèrent l’existence de mécanismes moléculaires encore inconnus et spécifiques des phases les plus précoces de la maladie. Ces découvertes pourraient fournir des cibles originales pour une intervention pharmacologique pré-symptomatiqueHuntington’s Disease (HD) is a neurodegenerative inherited disease. It is caused by the extension of a CAG motif coding for a poly-glutamine (polyQ) tract within huntingtin gene (HTT). Symptoms declaration occurs late in life. In order to better understand HD a wealth of cellular and animal genetic models both have fuelled 15 years of studies, but never transduced into truely lasting and beneficial pharmacological treatment. Avalaible drugs are used to handle symptomatology, but don’t address the lethal prognosis. Existing models seems to fail at replicating fully the first steps of transcriptionnal alterations occurring in HD. I took advantage of the recent disponibility of hESC naturally carrying HD mutation to investigate the hypothesis that they can yield insight into early presymptomatic mechanisms of HD from embryonic development to adulthood. I developed protocols, cellular and molecular tools to establish HD and normal hESC as HD cellular models. Then I used these tools to investigate transcriptomic dysregulation in immature neural cells carrying the HD causing mutation. I identified new early cellular biomarkers associated to the mutation. These results suggest the existence of previously unknown molecular mécanisms spécific to the earliest stages of the disease. These new biomarkers could be very interesting targets for pre-symptomatic pharmacological intervention
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Hazan, Amaury. "Musical expectation modelling from audio : a causal mid-level approach to predictive representation and learning of spectro-temporal events." Doctoral thesis, Universitat Pompeu Fabra, 2010. http://hdl.handle.net/10803/22721.
Full textAbstract:
We develop in this thesis a computational model of music expectation, which may be one of the most important aspects in music listening. Many phenomenons related to music listening such as preference, surprise or emo- tions are linked to the anticipatory behaviour of listeners. In this thesis, we concentrate on a statistical account to music expectation, by modelling the processes of learning and predicting spectro-temporal regularities in a causal fashion.
The principle of statistical modelling of expectation can be applied to several music representations, from symbolic notation to audio signals. We first show that computational learning architectures can be used and evaluated to account behavioral data concerning auditory perception and learning. We then propose a what/when representation of musical events which enables to sequentially describe and learn the structure of acoustic units in musical audio signals.
The proposed representation is applied to describe and anticipate timbre features and musical rhythms. We suggest ways to exploit the properties of the expectation model in music analysis tasks such as structural segmentation. We finally explore the implications of our model for interactive music applications in the context of real-time transcription, concatenative synthesis, and visualization.Esta tesis presenta un modelo computacional de expectativa musical, que es un aspecto muy importante de como procesamos la música que oímos. Muchos fenómenos relacionados con el procesamiento de la música están vinculados a una capacidad para anticipar la continuación de una pieza de música. Nos enfocaremos en un acercamiento estadístico de la expectativa musical, modelando los procesos de aprendizaje y de predicción de las regularidades espectro-temporales de forma causal. El principio de modelado estadístico de la expectativa se puede aplicar a varias representaciones de estructuras musicales, desde las notaciones simbólicas a la señales de audio. Primero demostramos que ciertos algoritmos de aprendizaje de secuencias se pueden usar y evaluar en el contexto de la percepción y el aprendizaje de secuencias auditivas. Luego, proponemos una representación, denominada qué/cuándo, para representar eventos musicales de una forma que permite describir y aprender la estructura secuencial de unidades acústicas en señales de audio musical. Aplicamos esta representación para describir y anticipar características tímbricas y ritmos. Sugerimos que se pueden explotar las propiedades del modelo de expectativa para resolver tareas de análisis como la segmentación estructural de piezas musicales. Finalmente, exploramos las implicaciones de nuestro modelo a la hora de definir nuevas aplicaciones en el contexto de la transcripción en tiempo real, la síntesis concatenativa y la visualización.
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Bhatt, Mrudul B. "Computational modelling of laminar dynamics in human primary motor cortex (M1) : a dynamic causal modelling study of the healthy and post-stroke brain." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10042817/.
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Background: Oscillatory activity in the beta range, in human primary motor cortex (M1), shows interesting dynamics that are tied to behaviour and change systematically in disease. To investigate the pathophysiology underlying these changes, we must first understand how changes in beta activity are caused in healthy subjects. We used the Dynamic Causal Modelling framework to develop a microcircuit model to explain mesoscopic dynamics in motor cortex. This model was applied to explain differences in measured oscillatory characteristics between healthy controls and stroke patients. The model was tested for robustness of use in EEG, and applied to pharmacological datasets to investigate differences in effective connectivity at the mesoscopic level under different pharmacological conditions. Aims: To investigate the laminar interaction underpinning beta-oscillatory dynamics in humans, in vivo, non-invasively. To this apply methodology to stroke patients to elucidate any differences at the mesoscopic level between these two key groups. To investigate whether such a technique was clinically feasible with more readily available research tools such as EEG. To investigate mesoscopic motor cortical dynamics under pharmacological influence, in humans, in vivo. Data acquisition and analysis: Most data acquisition was performed using a 275 CTF MEG scanner, with some data acquisition being performed using a standard 32 lead EEG headset. These data were taken and subject to rigorous analysis, that utilised dynamic causal modelling, Bayesian model comparison, as well as several signal processing and head modelling procedures that is outlined in detail in chapter 2. All analysis was done using the SPM 12 suite designed for neuroimaging analysis in MATLAB. Conclusions: We were able to develop a canonical microcircuit model for M1, and show it had significantly more model evidence than previous CMC models in explaining data from motor cortex. We applied this model to healthy controls to show the laminar interactions underpinning beta-oscillations in humans, in vivo. We were then able to apply this model and characterise laminar differences between healthy controls and stroke patients, as well as propose a novel mechanism for the origins of movement related beta desynchronization. We were able to show that our technique remained robust when applied to more clinically appropriate EEG. We were able to show significant differences in effective connectivity in different pharmacological states, that corresponded to differences observed in measured oscillatory data between groups who were given tiagabine and controls.
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Weidenfeld, Andrea. "Interpretation of and reasoning with conditionals probabilities, mental models, and causality /." Phd thesis, [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=975653652.
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Goldsmith, Kimberley. "Instrumental variable and longitudinal structural equation modelling methods for causal mediation : the PACE trial of treatments for chronic fatigue syndrome." Thesis, King's College London (University of London), 2014. https://kclpure.kcl.ac.uk/portal/en/theses/instrumental-variable-and-longitudinal-structural-equation-modelling-methods-for-causal-mediation-the-pace-trial-of-treatments-for-chronic-fatigue-syndrome(413e5fb0-03b9-40bc-b993-0465b1bcbdee).html.
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Background: Understanding complex psychological treatment mechanisms is important in order to refine and improve treatment. Mechanistic theories can be evaluated using mediation analysis methods. The Pacing, Graded Activity, and Cognitive Behaviour Therapy: A Randomised Evaluation (PACE) trial studied complex therapies for the treatment of chronic fatigue syndrome. The aim of the project was to study different mediation analysis methods using PACE trial data, and to make trial design recommendations based upon the findings. Methods: PACE trial data were described using summary statistics and correlation analyses. Mediation estimates were derived using: the product of coefficients approach, instrumental variable (IV) methods with randomisation by baseline variables interactions as IVs, and dual process longitudinal structural equation models (SEM). Monte Carlo simulation studies were done to further explore the behaviour of IV estimators and to examine aspects of the SEM. Results: Cognitive and behavioural measures were mediators of the cognitive behavioural and graded exercise therapies in PACE. Results were robust when accounting for correlated measurement error and different SEM structures. Randomisation by baseline IVs were weak, giving imprecise and sometimes extreme estimates, leaving their utility unclear. A flexible version of a latent change SEM with contemporaneous mediation effects and contemporaneous correlated measurement errors was the most appropriate longitudinal model. Conclusions: IV methods using interaction IVs are unlikely to be useful; designs with randomised IV might be more suitable. Longitudinal SEM for mediation in clinical trials seems a promising approach. Mediation estimates from SEM were generally robust when allowing for correlated measurement error and for different model classes. Mediation analysis in trials should be longitudinal and should consider the number and timing of measures at the design stage. Using appropriate methods for studying mediation in trials will help clarify treatment mechanisms of action and allow for their refinement, which would maximize the information gained from trials and benefit patients.
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Jonasson, Torbjörn. "General Causality Orientation och Myers-Briggs Type Indicator: En studie av sambandet mellan två modeller för att mäta motivationsorientering och personlighetstyp." Thesis, Malmö högskola, Fakulteten för kultur och samhälle (KS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-23006.
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Varje år genomförs ungefär 3,5 miljoner personlighetsprofileringar med Myers-Briggs Type Indicator®, MBTI ®. Det gör instrumentet till ett av de mest använda psykologiska testen i världen och det innebär att lika många människor får en etikett på sin personlighetstyp som kan användas på olika sätt. Det finns studier, till exempel av Carlyn, som talar för att MBTI är ett pålitligt instrument, men det finns också studier, till exempel av Pittenger, som hävdar motsatsen. James Michael menar att enbart MBTI ger en alltför inkomplett bild av en ledares beteende. Kanske är det klokt att komplettera MBTI med andra testinstrument för att få en komplettare bild av en individ.En modell som skulle kunna komplettera MBTI är motivationsteorin Self-Determination Theory, SDT, och tillhörande delteori General Causality Orientation, GCO. I denna studie jämförs MBTI med GCO och resultatet indikerar att autonomi orientation i GCO saknar kausala samband med MBTI medan controlled orientation och impersonal orientation har viss överlappning. Slutsatsen blir att de två modellerna mäter olika aspekter av personlighet och att de därför kan komplettera varandra.Every year about 3.5 million personality profiles are made with the Myers-Briggs Type Indicator ®, MBTI ®. This should make the instrument one of the most widely used psychological tests in the world and it means that a lot of people get a description of their personality type that can be used in different ways. Some studies, for example by Carlyn, suggest that the MBTI is a reliable instrument, but there are also studies, for example by Pittenger, that claim otherwise. James Michael says that MBTI alone give an incomplete assessment of a leader's behavior. Perhaps it is wise to complete the MBTI with other test instruments to get a more complete profile of an individual.A model that could complement MBTI is Self-Determination Theory, SDT, and the related sub theory General Causality Orientation, GCO. This study compares MBTI with GCO and the results indicate that autonomy orientation in GCO has no causality with MBTI whereas controlled orientation and impersonal orientation has some overlapping. The conclusion is that the two models measure different aspects of personality and therefore they can complement each other.