967 resultados para Models, Theoretical
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Theoretical epidemiology aims to understand the dynamics of diseases in populations and communities. Biological and behavioral processes are abstracted into mathematical formulations which aim to reproduce epidemiological observations. In this thesis a new system for the self-reporting of syndromic data Influenzanet is introduced and assessed. The system is currently being extended to address greater challenges of monitoring the health and well-being of tropical communities.(...)
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In this work we provide a new mathematical model for the Pennes bioheat equation, assuming a fractional time derivative of single order. Alternative versions of the bioheat equation are studied and discussed, to take into account the temperature-dependent variability in the tissue perfusion, and both nite and innite speed of heat propagation. The proposed bioheat model is solved numerically using an implicit nite dierence scheme that we prove to be convergent and stable. The numerical method proposed can be applied to general reaction diusion equations, with a variable diusion coecient. The results obtained with the single order fractional model, are compared with the original models that use classical derivatives.
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El projecte exposat t com a propsit definir i implementar un model de simulaci basat en la coordinaci i assignaci dels serveis demergncia en accidents de trnsit. La definici del model sha realitzat amb ls de les Xarxes de Petri Acolorides i la implementaci amb el software Rockwell Arena 7.0. El modelatge de la primera simulaci ens mostra un model teric basat en cues mentre que el segon, mostra un model ms complet i real grcies a la connexi mitjanant la plataforma Corba a una base de dades amb informaci geogrfica de les flotes i de les rutes. Com a resultat de lestudi i amb lajuda de GoogleEarth, podem realitzar simulacions grfiques per veure els accidents generats, les flotes dels serveis i el moviment dels vehicles des de les bases fins als accidents.
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This work compares the structural/dynamics features of the wild-type alb-adrenergic receptor (AR) with those of the D142A active mutant and the agonist-bound state. The two active receptor forms were compared in their isolated states as well as in their ability to form homodimers and to recognize the G alpha q beta 1 gamma 2 heterotrimer. The analysis of the isolated structures revealed that, although the mutation- and agonist-induced active states of the alpha 1b-AR are different, they, however, share several structural peculiarities including (a) the release of some constraining interactions found in the wild-type receptor and (b) the opening of a cytosolic crevice formed by the second and third intracellular loops and the cytosolic extensions of helices 5 and 6. Accordingly, also their tendency to form homodimers shows commonalties and differences. In fact, in both the active receptor forms, helix 6 plays a crucial role in mediating homodimerization. However, the homodimeric models result from different interhelical assemblies. On the same line of evidence, in both of the active receptor forms, the cytosolic opened crevice recognizes similar domains on the G protein. However, the docking solutions are differently populated and the receptor-G protein preorientation models suggest that the final complexes should be characterized by different interaction patterns.
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Summary: Lipophilicity plays an important role in the determination and the comprehension of the pharmacokinetic behavior of drugs. It is usually expressed by the partition coefficient (log P) in the n-octanol/water system. The use of an additional solvent system (1,2-dichlorethane/water) is necessary to obtain complementary information, as the log Poct values alone are not sufficient to explain ail biological properties. The aim of this thesis is to develop tools allowing to predict lipophilicity of new drugs and to analyze the information yielded by those log P values. Part I presents the development of theoretical models used to predict lipophilicity. Chapter 2 shows the necessity to extend the existing solvatochromic analyses in order to predict correctly the lipophilicity of new and complex neutral compounds. In Chapter 3, solvatochromic analyses are used to develop a model for the prediction of the lipophilicity of ions. A global model was obtained allowing to estimate the lipophilicity of neutral, anionic and cationic solutes. Part II presents the detailed study of two physicochemical filters. Chapter 4 shows that the Discovery RP Amide C16 stationary phase allows to estimate lipophilicity of the neutral form of basic and acidic solutes, except of lipophilic acidic solutes. Those solutes present additional interactions with this particular stationary phase. In Chapter 5, 4 different IANI stationary phases are investigated. For neutral solutes, linear data are obtained whatever the IANI column used. For the ionized solutes, their retention is due to a balance of electrostatic and hydrophobie interactions. Thus no discrimination is observed between different series of solutes bearing the same charge, from one column to an other. Part III presents two examples illustrating the information obtained thanks to Structure-Properties Relationships (SPR). Comparing graphically lipophilicity values obtained in two different solvent systems allows to reveal the presence of intramolecular effects .such as internai H-bond (Chapter 6). SPR is used to study the partitioning of ionizable groups encountered in Medicinal Chemistry (Chapter7). Rsum La lipophilie joue un .rle important dans la dtermination et la comprhension du comportement pharmacocintique des mdicaments. Elle est gnralement exprime par le coefficient de partage (log P) d'un compos dans le systme de solvants n-octanol/eau. L'utilisation d'un deuxime systme de solvants (1,2-dichlorothane/eau) s'est avre ncessaire afin d'obtenir des informations complmentaires, les valeurs de log Poct seules n'tant pas suffisantes pour expliquer toutes les proprits biologiques. Le but de cette thse est de dvelopper des outils permettant de prdire la lipophilie de nouveaux candidats mdicaments et d'analyser l'information fournie par les valeurs de log P. La Partie I prsente le dveloppement de modles thoriques utiliss pour prdire la lipophilie. Le chapitre 2 montre la ncessit de mettre jour les analyses solvatochromiques existantes mais inadaptes la prdiction de la lipophilie de nouveaux composs neutres. Dans le chapitre 3, la mme mthodologie des analyses solvatochromiques est utilise pour dvelopper un modle permettant de prdire la lipophilie des ions. Le modle global obtenu permet la prdiction de la lipophilie de composs neutres, anioniques et cationiques. La Partie II prsente l'tude approfondie de deux filtres physicochimiques. Le Chapitre 4 montre que la phase stationnaire Discovery RP Amide C16 permet la dtermination de la lipophilie de la forme neutre de composs basiques et acides, l'exception des acides trs lipophiles. Ces derniers prsentent des interactions supplmentaires avec cette phase stationnaire. Dans le Chapitre 5, 4 phases stationnaires IAM sont tudies. Pour les composs neutres tudis, des valeurs de rtention linaires sont obtenues, quelque que soit la colonne IAM utilise. Pour les composs ionisables, leur rtention est due une balance entre des interactions lectrostatiques et hydrophobes. Donc aucune discrimination n'est observe entre les diffrentes sries de composs portant la mme charge d'une colonne l'autre. La Partie III prsente deux exemples illustrant les informations obtenues par l'utilisation des relations structures-proprits. Comparer graphiquement la lipophilie mesure dans deux diffrents systmes de solvants permet de mettre en vidence la prsence d'effets intramolculaires tels que les liaisons hydrogne intramolculaires (Chapitre 6). Cette approche des relations structures-proprits est aussi applique l'tude du partage de fonctions ionisables rencontres en Chimie Thrapeutique (Chapitre 7) Rsum large public Pour exercer son effet thrapeutique, un mdicament doit atteindre son site d'action en quantit suffisante. La quantit effective de mdicament atteignant le site d'action dpend du nombre d'interactions entre le mdicament et de nombreux constituants de l'organisme comme, par exemple, les enzymes du mtabolisme ou les membranes biologiques. Le passage du mdicament travers ces membranes, appel permation, est un paramtre important optimiser pour dvelopper des mdicaments plus puissants. La lipophilie joue un rle cl dans la comprhension de la permation passive des mdicaments. La lipophilie est gnralement exprime par le coefficient de partage (log P) dans le systme de solvants (non miscibles) n-octanol/eau. Les valeurs de log Poct seules se sont avres insuffisantes pour expliquer la permation travers toutes les diffrentes membranes biologiques du corps humain. L'utilisation d'un systme de solvants additionnel (le systme 1,2-dichlorothane/eau) a permis d'obtenir les informations complmentaires indispensables une bonne comprhension du processus de permation. Un grand nombre d'outils exprimentaux et thoriques sont disposition pour tudier la lipophilie. Ce travail de thse se focalise principalement sur le dveloppement ou l'amlioration de certains de ces outils pour permettre leur application un champ plus large de composs. Voici une brve description de deux de ces outils: 1)La factorisation de la lipophilie en fonction de certaines proprits structurelles (telle que le volume) propres aux composs permet de dvelopper des modles thoriques utilisables pour la prdiction de la lipophilie de nouveaux composs ou mdicaments. Cette approche est applique l'analyse de la lipophilie de composs neutres ainsi qu' la lipophilie de composs chargs. 2)La chromatographie liquide haute pression sur phase inverse (RP-HPLC) est une mthode couramment utilise pour la dtermination exprimentale des valeurs de log Poct.
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An indirect estimate of consumable food and probability of acquiring food in a blowfly species, Chrysomya putoria, is presented. This alternative procedure combines three distinct models to estimate consumable food in the context of the exploitative competition experienced by immature individuals in blowfly populations. The relevant parameters are derived from data for pupal weight and survival and estimates of density-independent larval mortality in twenty different larval densities. As part of this procedure, the probability of acquiring food per unit of time and the time taken to exhaust the food supply are also calculated. The procedure employed here may be valuable for estimations in insects whose immature stages develop inside the food substrate, where it is difficult to partial out confounding effects such as separation of faeces. This procedure also has the advantage of taking into account the population dynamics of immatures living under crowded conditions, which are particularly characteristic of blowflies and other insects as well.
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The evolution of a quantitative phenotype is often envisioned as a trait substitution sequence where mutant alleles repeatedly replace resident ones. In infinite populations, the invasion fitness of a mutant in this two-allele representation of the evolutionary process is used to characterize features about long-term phenotypic evolution, such as singular points, convergence stability (established from first-order effects of selection), branching points, and evolutionary stability (established from second-order effects of selection). Here, we try to characterize long-term phenotypic evolution in finite populations from this two-allele representation of the evolutionary process. We construct a stochastic model describing evolutionary dynamics at non-rare mutant allele frequency. We then derive stability conditions based on stationary average mutant frequencies in the presence of vanishing mutation rates. We find that the second-order stability condition obtained from second-order effects of selection is identical to convergence stability. Thus, in two-allele systems in finite populations, convergence stability is enough to characterize long-term evolution under the trait substitution sequence assumption. We perform individual-based simulations to confirm our analytic results.
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BACKGROUND: In vitro aggregating brain cell cultures containing all types of brain cells have been shown to be useful for neurotoxicological investigations. The cultures are used for the detection of nervous system-specific effects of compounds by measuring multiple endpoints, including changes in enzyme activities. Concentration-dependent neurotoxicity is determined at several time points. METHODS: A Markov model was set up to describe the dynamics of brain cell populations exposed to potentially neurotoxic compounds. Brain cells were assumed to be either in a healthy or stressed state, with only stressed cells being susceptible to cell death. Cells may have switched between these states or died with concentration-dependent transition rates. Since cell numbers were not directly measurable, intracellular lactate dehydrogenase (LDH) activity was used as a surrogate. Assuming that changes in cell numbers are proportional to changes in intracellular LDH activity, stochastic enzyme activity models were derived. Maximum likelihood and least squares regression techniques were applied for estimation of the transition rates. Likelihood ratio tests were performed to test hypotheses about the transition rates. Simulation studies were used to investigate the performance of the transition rate estimators and to analyze the error rates of the likelihood ratio tests. The stochastic time-concentration activity model was applied to intracellular LDH activity measurements after 7 and 14 days of continuous exposure to propofol. The model describes transitions from healthy to stressed cells and from stressed cells to death. RESULTS: The model predicted that propofol would affect stressed cells more than healthy cells. Increasing propofol concentration from 10 to 100 μM reduced the mean waiting time for transition to the stressed state by 50%, from 14 to 7 days, whereas the mean duration to cellular death reduced more dramatically from 2.7 days to 6.5 hours. CONCLUSION: The proposed stochastic modeling approach can be used to discriminate between different biological hypotheses regarding the effect of a compound on the transition rates. The effects of different compounds on the transition rate estimates can be quantitatively compared. Data can be extrapolated at late measurement time points to investigate whether costs and time-consuming long-term experiments could possibly be eliminated.
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Joint-stability in interindustry models relates to the mutual simultaneous consistency of the demand-driven and supply-driven models of Leontief and Ghosh, respectively. Previous work has claimed joint-stability to be an acceptable assumption from the empirical viewpoint, provided only small changes in exogenous variables are considered. We show in this note, however, that the issue has deeper theoretical roots and offer an analytical demonstration that shows the impossibility of consistency between demand-driven and supply-driven models.
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This study proposes a theoretical model describing the electrostatically driven step of the alpha 1 b-adrenergic receptor (AR)-G protein recognition. The comparative analysis of the structural-dynamics features of functionally different receptor forms, i.e., the wild type (ground state) and its constitutively active mutants D142A and A293E, was instrumental to gain insight on the receptor-G protein electrostatic and steric complementarity. Rigid body docking simulations between the different forms of the alpha 1 b-AR and the heterotrimeric G alpha q, G alpha s, G alpha i1, and G alpha t suggest that the cytosolic crevice shared by the active receptor and including the second and the third intracellular loops as well as the cytosolic extension of helices 5 and 6, represents the receptor surface with docking complementarity with the G protein. On the other hand, the G protein solvent-exposed portions that recognize the intracellular loops of the activated receptors are the N-terminal portion of alpha 3, alpha G, the alpha G/alpha 4 loop, alpha 4, the alpha 4/beta 6 loop, alpha 5, and the C-terminus. Docking simulations suggest that the two constitutively active mutants D142A and A293E recognize different G proteins with similar selectivity orders, i.e., G alpha q approximately equal to G alpha s > G alpha i > G alpha t. The theoretical models herein proposed might provide useful suggestions for new experiments aiming at exploring the receptor-G protein interface.
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Cette thse s'intresse tudier les proprits extrmales de certains modles de risque d'intrt dans diverses applications de l'assurance, de la finance et des statistiques. Cette thse se dveloppe selon deux axes principaux, savoir: Dans la premire partie, nous nous concentrons sur deux modles de risques univaris, c'est-- dire, un modle de risque de dflation et un modle de risque de rassurance. Nous tudions le dveloppement des queues de distribution sous certaines conditions des risques communs. Les principaux rsultats sont ainsi illustrs par des exemples typiques et des simulations numriques. Enfin, les rsultats sont appliqus aux domaines des assurances, par exemple, les approximations de Value-at-Risk, d'esprance conditionnelle unilatrale etc. La deuxime partie de cette thse est consacre trois modles deux variables: Le premier modle concerne la censure deux variables des vnements extrme. Pour ce modle, nous proposons tout d'abord une classe d'estimateurs pour les coefficients de dpendance et la probabilit des queues de distributions. Ces estimateurs sont flexibles en raison d'un paramtre de rglage. Leurs distributions asymptotiques sont obtenues sous certaines conditions lentes bivaries de second ordre. Ensuite, nous donnons quelques exemples et prsentons une petite tude de simulations de Monte Carlo, suivie par une application sur un ensemble de donnes relles d'assurance. L'objectif de notre deuxime modle de risque deux variables est l'tude de coefficients de dpendance des queues de distributions obliques et asymtriques deux variables. Ces distributions obliques et asymtriques sont largement utiles dans les applications statistiques. Elles sont gnres principalement par le mlange moyenne-variance de lois normales et le mlange de lois normales asymtriques d'chelles, qui distinguent la structure de dpendance de queue comme indiqu par nos principaux rsultats. Le troisime modle de risque deux variables concerne le rapprochement des maxima de sries triangulaires elliptiques obliques. Les rsultats thoriques sont fonds sur certaines hypothses concernant le primtre alatoire sous-jacent des queues de distributions. -- This thesis aims to investigate the extremal properties of certain risk models of interest in various applications from insurance, finance and statistics. This thesis develops along two principal lines, namely: In the first part, we focus on two univariate risk models, i.e., deflated risk and reinsurance risk models. Therein we investigate their tail expansions under certain tail conditions of the common risks. Our main results are illustrated by some typical examples and numerical simulations as well. Finally, the findings are formulated into some applications in insurance fields, for instance, the approximations of Value-at-Risk, conditional tail expectations etc. The second part of this thesis is devoted to the following three bivariate models: The first model is concerned with bivariate censoring of extreme events. For this model, we first propose a class of estimators for both tail dependence coefficient and tail probability. These estimators are flexible due to a tuning parameter and their asymptotic distributions are obtained under some second order bivariate slowly varying conditions of the model. Then, we give some examples and present a small Monte Carlo simulation study followed by an application on a real-data set from insurance. The objective of our second bivariate risk model is the investigation of tail dependence coefficient of bivariate skew slash distributions. Such skew slash distributions are extensively useful in statistical applications and they are generated mainly by normal mean-variance mixture and scaled skew-normal mixture, which distinguish the tail dependence structure as shown by our principle results. The third bivariate risk model is concerned with the approximation of the component-wise maxima of skew elliptical triangular arrays. The theoretical results are based on certain tail assumptions on the underlying random radius.
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Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.
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The recent wave of upheavals and revolts in Northern Africa and the Middle East goes back to an old question often raised by theories of collective action: does repression act as a negative or positive incentive for further mobilization? Through a review of the vast literature devoted to this question, this article aims to go beyond theoretical and methodological dead-ends. The article moves on to non-Western settings in order to better understand, via a macro-sociological and dynamic approach, the causal effects between mobilizations and repression. It pleads for a meso- and micro-level approach to this issue: an approach that puts analytical emphasis both on protest organizations and on individual activists' careers.
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Cultural variation in a population is affected by the rate of occurrence of cultural innovations, whether such innovations are preferred or eschewed, how they are transmitted between individuals in the population, and the size of the population. An innovation, such as a modification in an attribute of a handaxe, may be lost or may become a property of all handaxes, which we call "fixation of the innovation." Alternatively, several innovations may attain appreciable frequencies, in which case properties of the frequency distribution-for example, of handaxe measurements-is important. Here we apply the Moran model from the stochastic theory of population genetics to study the evolution of cultural innovations. We obtain the probability that an initially rare innovation becomes fixed, and the expected time this takes. When variation in cultural traits is due to recurrent innovation, copy error, and sampling from generation to generation, we describe properties of this variation, such as the level of heterogeneity expected in the population. For all of these, we determine the effect of the mode of social transmission: conformist, where there is a tendency for each nave newborn to copy the most popular variant; pro-novelty bias, where the newborn prefers a specific variant if it exists among those it samples; one-to-many transmission, where the variant one individual carries is copied by all newborns while that individual remains alive. We compare our findings with those predicted by prevailing theories for rates of cultural change and the distribution of cultural variation.
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Two different approaches currently prevail for predicting spatial patterns of species assemblages. The first approach (macroecological modelling, MEM) focuses directly on realised properties of species assemblages, whereas the second approach (stacked species distribution modelling, S-SDM) starts with constituent species to approximate assemblage properties. Here, we propose to unify the two approaches in a single 'spatially-explicit species assemblage modelling' (SESAM) framework. This framework uses relevant species source pool designations, macroecological factors, and ecological assembly rules to constrain predictions of the richness and composition of species assemblages obtained by stacking predictions of individual species distributions. We believe that such a framework could prove useful in many theoretical and applied disciplines of ecology and evolution, both for improving our basic understanding of species assembly across spatio-temporal scales and for anticipating expected consequences of local, regional or global environmental changes. In this paper, we propose such a framework and call for further developments and testing across a broad range of community types in a variety of environments.
