971 resultados para Linear quadratic Gaussian


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In the present study survival responses were determined in cells with differing radiosensitivity, specifically primary fibroblast (AG0-1522B), human breast cancer (MDA-MB-231), human prostate cancer (DU-145) and human glioma (T98G) cells, after exposure to modulated radiation fields delivered by shielding 50% of the tissue culture flask. A significant decrease (P < 0.05) in cell survival was observed in the shielded area, outside the primary treatment field (out-of-field), that was lower than predicted when compared to uniform exposures fitted to the linear-quadratic model. Cellular radiosensitivity was demonstrated to be an important factor in the level of response for both the in- and out-of-field regions. These responses were shown to be dependent on secretion-mediated intercellular communication, because inhibition of cellular secreted factors between the in- and out-of-field regions abrogated the response. Out-of-field cell survival was shown to increase after pretreatment of cells with agents known to inhibit factors involved in mediating radiation-induced bystander signaling (aminoguanidine, DMSO or cPTIO). These data illustrate a significant decrease in survival out-of-field, dependent upon intercellular communication, in several cell lines with varying radiosensitivity after exposure to a modulated radiation field. This study provides further evidence for the importance of intercellular signaling in modulated exposures, where dose gradients are present, and may inform the refinement of established radiobiological models to facilitate the optimization of advanced radiotherapy treatment plans.

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Radiation biophysics has sought to understand at a molecular level, the mechanisms through which ionizing radiations damage DNA, and other molecules within living cells. The complexity of lesions produced in the DNA by ionizing radiations is thought to depend on the amount of energy deposited at the site of each lesion. To study the relationship between the energy deposited and the damage produced, we have developed novel techniques for irradiating dry prasmid DNA, partially re-hydrated DNA and DNA in solution using monochromatic vacuum-UV synchrotron radiation. We have used photons in the energy range 7-150 eV, corresponding to the range of energies typically involved in the efficient production of DNA single-strand (SSB), and double-strand breaks (DSB) by ionizing radiation. The data show that both types of breaks are produced at all energies investigated (with, or without water present). Also, the energy dependence for DSB induction follows a similar trend to SSB induction but at a 20-30-fold reduced incidence, suggesting a common precursor for both types of damage. Preliminary studies where DNA has been irradiated in solution indicate a change in the shape of the dose-effect curve (from linear, to linear-quadratic for double-strand break induction) and a large increase in sensitivity due to the presence of water.

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Low-dose hyper-radiosensitivity (HRS) is the phenomenon whereby cells exposed to radiation doses of less than approximately 0.5 Gy exhibit increased cell killing relative to that predicted from back-extrapolating high-dose survival data using a linear-quadratic model. While the exact mechanism remains to be elucidated, the involvement of several molecular repair pathways has been documented. These processes in turn are also associated with the response of cells to O6-methylguanine (O6MeG) lesions. We propose a model in which the level of low-dose cell killing is determined by the efficiency of both pre-replicative repair by the DNA repair enzyme O6-methylguanine methyltransferase (MGMT) and post-replicative repair by the DNA mismatch repair (MMR) system. We therefore hypothesized that the response of cells to low doses of radiation is dependent on the expression status of MGMT and MMR proteins. MMR (MSH2, MSH6, MLH1, PMS1, PMS2) and MGMT protein expression signatures were determined in a panel of normal (PWR1E, RWPE1) and malignant (22RV1, DU145, PC3) prostate cell lines and correlated with clonogenic survival and cell cycle analysis. PC3 and RWPE1 cells (HRS positive) were associated with MGMT and MMR proficiency, whereas HRS negative cell lines lacked expression of at least one (MGMT or MMR) protein. MGMT inactivation had no significant effect on cell survival. These results indicate a possible role for MMR-dependent processing of damage produced by low doses of radiation.

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Purpose: To investigate the clinical implications of a variable relative biological effectiveness (RBE) on proton dose fractionation. Using acute exposures, the current clinical adoption of a generic, constant cell killing RBE has been shown to underestimate the effect of the sharp increase in linear energy transfer (LET) in the distal regions of the spread-out Bragg peak (SOBP). However, experimental data for the impact of dose fractionation in such scenarios are still limited.

Methods and Materials: Human fibroblasts (AG01522) at 4 key depth positions on a clinical SOBP of maximum energy 219.65 MeV were subjected to various fractionation regimens with an interfraction period of 24 hours at Proton Therapy Center in Prague, Czech Republic. Cell killing RBE variations were measured using standard clonogenic assays and were further validated using Monte Carlo simulations and parameterized using a linear quadratic formalism.

Results: Significant variations in the cell killing RBE for fractionated exposures along the proton dose profile were observed. RBE increased sharply toward the distal position, corresponding to a reduction in cell sparing effectiveness of fractionated proton exposures at higher LET. The effect was more pronounced at smaller doses per fraction. Experimental survival fractions were adequately predicted using a linear quadratic formalism assuming full repair between fractions. Data were also used to validate a parameterized variable RBE model based on linear α parameter response with LET that showed considerable deviations from clinically predicted isoeffective fractionation regimens.

Conclusions: The RBE-weighted absorbed dose calculated using the clinically adopted generic RBE of 1.1 significantly underestimates the biological effective dose from variable RBE, particularly in fractionation regimens with low doses per fraction. Coupled with an increase in effective range in fractionated exposures, our study provides an RBE dataset that can be used by the modeling community for the optimization of fractionated proton therapy.

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RESUMO: Este trabalho teve como objetivo a determinação de esquemas de tratamento alternativos para o carcinoma da próstata com radioterapia externa (EBRT) e braquiterapia de baixa taxa de dose (LDRBT) com implantes permanentes de Iodo-125, biologicamente equivalentes aos convencionalmente usados na prática clínica, com recurso a modelos teóricos e a métodos de Monte Carlo (MC). Os conceitos de dose biológica efetiva (BED) e de dose uniforme equivalente (EUD) foram utilizados, com o modelo linear-quadrático (LQ), para a determinação de regimes de tratamento equivalentes. Numa primeira abordagem, utilizou-se a BED para determinar: 1) esquemas hipofracionados de EBRT mantendo as complicações retais tardias de regimes convencionais com doses totais de 75,6 Gy, 77,4 Gy, 79,2 Gy e 81,0 Gy; e 2) a relação entre as doses totais de EBRT e LDRBT de modo a manter a BED do regime convencional de 45 Gy de EBRT e 110 Gy de LDRBT. Numa segunda abordagem, recorreu-se ao código de MC MCNPX para a simulação de distribuições de dose de EBRT e LDRBT em dois fantomas de voxel segmentados a partir das imagens de tomografia computorizada de pacientes com carcinoma da próstata. Os resultados das simulações de EBRT e LDRBT foram somados e determinada uma EUD total de forma a obterem-se: 1) esquemas equivalentes ao tratamento convencional de 25 frações de 1,8 Gy de EBRT em combinação com 110 Gy de LDRBT; e 2) esquemas equivalentes a EUD na próstata de 67 Gy, 72 Gy, 80 Gy, 90 Gy, 100 Gy e 110 Gy. Em todos os resultados nota-se um ganho terapêutico teórico na utilização de esquemas hipofracionados de EBRT. Para uma BED no reto equivalente ao esquema convencional, tem-se um aumento de 2% na BED da próstata com menos 5 frações. Este incremento dá-se de forma cada vez mais visível à medida que se reduz o número de frações, sendo da ordem dos 10-11% com menos 20 frações e dos 35-45% com menos 40 frações. Considerando os resultados das simulações de EBRT, obteve-se uma EUD média de 107 Gy para a próstata e de 42 Gy para o reto, com o esquema convencional de 110 Gy de LDRBT, seguidos de 25 frações de 1,8 Gy de EBRT. Em termos de probabilidade de controlo tumoral (igual EUD), é equivalente a este tratamento a administração de EBRT em 66 frações de 1,8 Gy, 56 de 2 Gy, 40 de 2,5 Gy, 31 de 3 Gy, 20 de 4 Gy ou 13 de 5 Gy. Relativamente à administração de 66 frações de 1,8 Gy, a EUD generalizada no reto reduz em 6% com o recurso a frações de 2,5 Gy e em 10% com frações de 4 Gy. Determinou-se uma BED total de 162 Gy para a administração de 25 frações de 1,8 Gy de EBRT em combinação com 110 Gy de LDRBT. Variando-se a dose total de LDRBT (TDLDRBT) em função da dose total de EBRT (TDEBRT), de modo a garantir uma BED de 162 Gy, obteve-se a seguinte relação:.......... Os resultados das simulações mostram que a EUD no reto diminui com o aumento da dose total de LDRBT para dose por fração de EBRT (dEBRT) inferiores a 2, Gy e aumenta para dEBRT a partir dos 3 Gy. Para quantidades de TDLDRBT mais baixas (<50 Gy), o reto beneficia de frações maiores de EBRT. À medida que se aumenta a TDLDRBT, a EUD generalizada no reto torna-se menos dependente da dEBRT. Este trabalho mostra que é possível a utilização de diferentes regimes de tratamento para o carcinoma da próstata com radioterapia que possibilitem um ganho terapêutico, quer seja administrando uma maior dose biológica com efeitos tardios constantes, quer mantendo a dose no tumor e diminuindo a toxicidade retal. A utilização com precaução de esquemas hipofracionados de EBRT, para além do benefício terapêutico, pode trazer vantagens ao nível da conveniência para o paciente e economia de custos. Os resultados das simulações deste estudo e conversão para doses de efeito biológico para o tratamento do carcinoma da próstata apresentam linhas de orientação teórica de interesse para novos ensaios clínicos. --------------------------------------------------ABSTRACT: The purpose of this work was to determine alternative radiotherapy regimens for the treatment of prostate cancer using external beam radiotherapy (EBRT) and low dose-rate brachytherapy (LDRBT) with Iodine-125 permanent implants which are biologically equivalent to conventional clinical treatments, by the use of theoretical models and Monte Carlo techniques. The concepts of biological effective dose (BED) and equivalent uniform dose (EUD), together with the linear-quadratic model (LQ), were used for determining equivalent treatment regimens. In a first approach, the BED concept was used to determine: 1) hypofractionated schemes of EBRT maintaining late rectal complications as with the conventional regimens with total doses of 75.6 Gy, 77.4 Gy, 79.2 Gy and 81.0 Gy; and 2) the relationship between total doses of EBRT and LDRBT in order to keep the BED of the conventional treatment of 45 Gy of EBRT and 110 Gy of LDRBT. In a second approach, the MC code MCNPX was used for simulating dose distributions of EBRT and LDRBT in two voxel phantoms segmented from the computed tomography of patients with prostate cancer. The results of the simulations of EBRT and LDRBT were added up and given an overall EUD in order to obtain: 1) equivalent to conventional treatment regimens of 25 fraction of 1.8 Gy of EBRT in combination with 110Gy of LDRBT; and 2) equivalent schemes of EUD of 67 Gy, 72 Gy, 80 Gy, 90 Gy, 100 Gy, and 110Gy to the prostate. In all the results it is noted a therapeutic gain using hypofractionated EBRT schemes. For a rectal BED equivalent to the conventional regimen, an increment of 2% in the prostate BED was achieved with less 5 fractions. This increase is visibly higher as the number of fractions decrease, amounting 10-11% with less 20 fractions and 35-45% with less 20 fractions. Considering the results of the EBRT simulations an average EUD of 107 Gy was achieved for the prostate and of 42 Gy for the rectum with the conventional scheme of 110 Gy of LDRBT followed by 25 fractions of 1.8 Gy of EBRT. In terms of tumor control probability (same EUD) it is equivalent to this treatment, for example, delivering the EBRT in 66 fractions of 1.8 Gy, 56 fractions of 2 Gy, 40 fractions of 2.5 Gy, 31 fractions of 3 Gy, 20 fractions of 4 Gy or 13 fractions of 5 Gy. Regarding the use of 66 fractions of 1.8 Gy, the rectum EUD is reduced to 6% with 2.5 Gy per fraction and to 10% with 4 Gy. A total BED of 162 Gy was achieved for the delivery of 25 fractions of 1.8 Gy of EBRT in combination with 110 Gy of LDRBT. By varying the total dose of LDRBT (TDLDRBT) with the total dose of EBRT (TDEBRT) so as to ensure a BED of 162 Gy, the following relationship was obtained: ....... The simulation results show that the rectum EUD decreases with the increase of the TDLDRBT, for EBRT dose per fracion (dEBRT) less than 2.5 Gy and increases for dEBRT above 3 Gy. For lower amounts of TDLDRBT (< 50Gy), the rectum benefits of larger EBRT fractions. As the TDLDRBT increases, the rectum gEUD becomes less dependent on the dEBRT. The use of different regimens which enable a therapeutic gain, whether deivering a higher dose with the same late biological effects or maintaining the dose to the tumor and reducing rectal toxicity is possible. The use with precaution of hypofractionated regimens, in addition to the therapeutic benefit, can bring advantages in terms of convenience for the patient and cost savings. The simulation results of this study together with the biological dose conversion for the treatment of prostate cancer serve as guidelines of interest for new clinical trials.

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Les avancés dans le domaine de l’intelligence artificielle, permettent à des systèmes informatiques de résoudre des tâches de plus en plus complexes liées par exemple à la vision, à la compréhension de signaux sonores ou au traitement de la langue. Parmi les modèles existants, on retrouve les Réseaux de Neurones Artificiels (RNA), dont la popularité a fait un grand bond en avant avec la découverte de Hinton et al. [22], soit l’utilisation de Machines de Boltzmann Restreintes (RBM) pour un pré-entraînement non-supervisé couche après couche, facilitant grandement l’entraînement supervisé du réseau à plusieurs couches cachées (DBN), entraînement qui s’avérait jusqu’alors très difficile à réussir. Depuis cette découverte, des chercheurs ont étudié l’efficacité de nouvelles stratégies de pré-entraînement, telles que l’empilement d’auto-encodeurs traditionnels(SAE) [5, 38], et l’empilement d’auto-encodeur débruiteur (SDAE) [44]. C’est dans ce contexte qu’a débuté la présente étude. Après un bref passage en revue des notions de base du domaine de l’apprentissage machine et des méthodes de pré-entraînement employées jusqu’à présent avec les modules RBM, AE et DAE, nous avons approfondi notre compréhension du pré-entraînement de type SDAE, exploré ses différentes propriétés et étudié des variantes de SDAE comme stratégie d’initialisation d’architecture profonde. Nous avons ainsi pu, entre autres choses, mettre en lumière l’influence du niveau de bruit, du nombre de couches et du nombre d’unités cachées sur l’erreur de généralisation du SDAE. Nous avons constaté une amélioration de la performance sur la tâche supervisée avec l’utilisation des bruits poivre et sel (PS) et gaussien (GS), bruits s’avérant mieux justifiés que celui utilisé jusqu’à présent, soit le masque à zéro (MN). De plus, nous avons démontré que la performance profitait d’une emphase imposée sur la reconstruction des données corrompues durant l’entraînement des différents DAE. Nos travaux ont aussi permis de révéler que le DAE était en mesure d’apprendre, sur des images naturelles, des filtres semblables à ceux retrouvés dans les cellules V1 du cortex visuel, soit des filtres détecteurs de bordures. Nous aurons par ailleurs pu montrer que les représentations apprises du SDAE, composées des caractéristiques ainsi extraites, s’avéraient fort utiles à l’apprentissage d’une machine à vecteurs de support (SVM) linéaire ou à noyau gaussien, améliorant grandement sa performance de généralisation. Aussi, nous aurons observé que similairement au DBN, et contrairement au SAE, le SDAE possédait une bonne capacité en tant que modèle générateur. Nous avons également ouvert la porte à de nouvelles stratégies de pré-entraînement et découvert le potentiel de l’une d’entre elles, soit l’empilement d’auto-encodeurs rebruiteurs (SRAE).

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Un modèle de croissance et de réponse à la radiothérapie pour le glioblastome multiforme (GBM) basé le formalisme du modèle de prolifération-invasion (PI) et du modèle linéaire-quadratique a été développé et implémenté. La géométrie spécifique au patient est considérée en modélisant, d'une part, les voies d'invasion possibles des GBM avec l'imagerie du tenseur de diffusion (DTI) et, d'autre part, les barrières à la propagation à partir des images anatomiques disponibles. La distribution de dose réelle reçue par un patient donné est appliquée telle quelle dans les simulations, en respectant l'horaire de traitement. Les paramètres libres du modèle (taux de prolifération, coefficient de diffusion, paramètres radiobiologiques) sont choisis aléatoirement à partir de distributions de valeurs plausibles. Un total de 400 ensembles de valeurs pour les paramètres libres sont ainsi choisis pour tous les patients, et une simulation de la croissance et de la réponse au traitement est effectuée pour chaque patient et chaque ensemble de paramètres. Un critère de récidive est appliqué sur les résultats de chaque simulation pour identifier un lieu probable de récidive (SPR). La superposition de tous les SPR obtenus pour un patient donné permet de définir la probabilité d'occurrence (OP). Il est démontré qu'il existe des valeurs de OP élevées pour tous les patients, impliquant que les résultats du modèle PI ne sont pas très sensibles aux valeurs des paramètres utilisés. Il est également démontré comment le formalisme développé dans cet ouvrage pourrait permettre de définir un volume cible personnalisé pour les traitements de radiothérapie du GBM.

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The experimental variogram computed in the usual way by the method of moments and the Haar wavelet transform are similar in that they filter data and yield informative summaries that may be interpreted. The variogram filters out constant values; wavelets can filter variation at several spatial scales and thereby provide a richer repertoire for analysis and demand no assumptions other than that of finite variance. This paper compares the two functions, identifying that part of the Haar wavelet transform that gives it its advantages. It goes on to show that the generalized variogram of order k=1, 2, and 3 filters linear, quadratic, and cubic polynomials from the data, respectively, which correspond with more complex wavelets in Daubechies's family. The additional filter coefficients of the latter can reveal features of the data that are not evident in its usual form. Three examples in which data recorded at regular intervals on transects are analyzed illustrate the extended form of the variogram. The apparent periodicity of gilgais in Australia seems to be accentuated as filter coefficients are added, but otherwise the analysis provides no new insight. Analysis of hyerpsectral data with a strong linear trend showed that the wavelet-based variograms filtered it out. Adding filter coefficients in the analysis of the topsoil across the Jurassic scarplands of England changed the upper bound of the variogram; it then resembled the within-class variogram computed by the method of moments. To elucidate these results, we simulated several series of data to represent a random process with values fluctuating about a mean, data with long-range linear trend, data with local trend, and data with stepped transitions. The results suggest that the wavelet variogram can filter out the effects of long-range trend, but not local trend, and of transitions from one class to another, as across boundaries.

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An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

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In this paper, a discrete time dynamic integrated system optimisation and parameter estimation algorithm is applied to the solution of the nonlinear tracking optimal control problem. A version of the algorithm with a linear-quadratic model-based problem is developed and implemented in software. The algorithm implemented is tested with simulation examples.

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Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

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A novel iterative procedure is described for solving nonlinear optimal control problems subject to differential algebraic equations. The procedure iterates on an integrated modified linear quadratic model based problem with parameter updating in such a manner that the correct solution of the original non-linear problem is achieved. The resulting algorithm has a particular advantage in that the solution is achieved without the need to solve the differential algebraic equations . Convergence aspects are discussed and a simulation example is described which illustrates the performance of the technique. 1. Introduction When modelling industrial processes often the resulting equations consist of coupled differential and algebraic equations (DAEs). In many situations these equations are nonlinear and cannot readily be directly reduced to ordinary differential equations.

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This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

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This study aimed to optimize the rheological properties of probiotic yoghurts supplemented with skimmed milk powder (SMP) whey protein concentrate (WPC) and sodium caseinate (Na-Cn) by using an experimental design type simplex-centroid for mixture modeling It Included seven batches/trials three were supplemented with each type of the dairy protein used three corresponding to the binary mixtures and one to the ternary one in order to increase protein concentration in 1 g 100 g(-1) of final product A control experiment was prepared without supplementing the milk base Processed milk bases were fermented at 42 C until pH 4 5 by using a starter culture blend that consisted of Streptococcus thermophilus Lactobacillus delbrueckii subsp bulgaricus and Bifidobacterium (Humans subsp lactis The kinetics of acidification was followed during the fermentation period as well the physico-chemical analyses enumeration of viable bacteria and theological characteristics of the yoghurts Models were adjusted to the results (kinetic responses counts of viable bacteria and theological parameters) through three regression models (linear quadratic and cubic special) applied to mixtures The results showed that the addition of milk proteins affected slightly acidification profile and counts of S thermophilus and B animal`s subsp lactis but it was significant for L delbrueckii subsp bulgaricus Partially-replacing SMP (45 g/100 g) with WPC or Na-Cn simultaneously enhanced the theological properties of probiotic yoghurts taking into account the kinetics of acidification and enumeration of viable bacteria (C) 2010 Elsevier Ltd All rights reserved

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In this paper we present a technique based on precision guidance approach for the sensor delivery and reception problem between two mobile robots. A slave robot is employed to collect sensors and slack them on a tray carried by the mobile master robot. We define the terminal attitude of the slave robot with respect to the master and present a LQR control approach to solving the problem of achieving a desired terminal approach angle necessary for the appropriate sensor delivery. The approach criteria is defined in terms of both minimizing the miss distance and controlling the slave robot's body attitude with respect to the master robot at the terminal point.