968 resultados para dynamic measurement


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BACKGROUND: Mitogen activated protein kinases (MAPK) play an essential role in integrating extra-cellular signals and intra-cellular cues to allow cells to grow, adapt to stresses, or undergo apoptosis. Budding yeast serves as a powerful system to understand the fundamental regulatory mechanisms that allow these pathways to combine multiple signals and deliver an appropriate response. To fully comprehend the variability and dynamics of these signaling cascades, dynamic and quantitative single cell measurements are required. Microscopy is an ideal technique to obtain these data; however, novel assays have to be developed to measure the activity of these cascades. RESULTS: We have generated fluorescent biosensors that allow the real-time measurement of kinase activity at the single cell level. Here, synthetic MAPK substrates were engineered to undergo nuclear-to-cytoplasmic relocation upon phosphorylation of a nuclear localization sequence. Combination of fluorescence microscopy and automated image analysis allows the quantification of the dynamics of kinase activity in hundreds of single cells. A large heterogeneity in the dynamics of MAPK activity between individual cells was measured. The variability in the mating pathway can be accounted for by differences in cell cycle stage, while, in the cell wall integrity pathway, the response to cell wall stress is independent of cell cycle stage. CONCLUSIONS: These synthetic kinase activity relocation sensors allow the quantification of kinase activity in live single cells. The modularity of the architecture of these reporters will allow their application in many other signaling cascades. These measurements will allow to uncover new dynamic behaviour that previously could not be observed in population level measurements.

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The objective of this study is to show that bone strains due to dynamic mechanical loading during physical activity can be analysed using the flexible multibody simulation approach. Strains within the bone tissue play a major role in bone (re)modeling. Based on previous studies, it has been shown that dynamic loading seems to be more important for bone (re)modeling than static loading. The finite element method has been used previously to assess bone strains. However, the finite element method may be limited to static analysis of bone strains due to the expensive computation required for dynamic analysis, especially for a biomechanical system consisting of several bodies. Further, in vivo implementation of strain gauges on the surfaces of bone has been used previously in order to quantify the mechanical loading environment of the skeleton. However, in vivo strain measurement requires invasive methodology, which is challenging and limited to certain regions of superficial bones only, such as the anterior surface of the tibia. In this study, an alternative numerical approach to analyzing in vivo strains, based on the flexible multibody simulation approach, is proposed. In order to investigate the reliability of the proposed approach, three 3-dimensional musculoskeletal models where the right tibia is assumed to be flexible, are used as demonstration examples. The models are employed in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model is developed using the actual geometry of the subject’s tibia, which is obtained from 3 dimensional reconstruction of Magnetic Resonance Images. Inverse dynamics simulation based on motion capture data obtained from walking at a constant velocity is used to calculate the desired contraction trajectory for each muscle. In the forward dynamics simulation, a proportional derivative servo controller is used to calculate each muscle force required to reproduce the motion, based on the desired muscle contraction trajectory obtained from the inverse dynamics simulation. Experimental measurements are used to verify the models and check the accuracy of the models in replicating the realistic mechanical loading environment measured from the walking test. The predicted strain results by the models show consistency with literature-based in vivo strain measurements. In conclusion, the non-invasive flexible multibody simulation approach may be used as a surrogate for experimental bone strain measurement, and thus be of use in detailed strain estimation of bones in different applications. Consequently, the information obtained from the present approach might be useful in clinical applications, including optimizing implant design and devising exercises to prevent bone fragility, accelerate fracture healing and reduce osteoporotic bone loss.

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The present study investigates the usefulness of a multi-method approach to the measurement of reading motivation and achievement. A sample of 127 elementary and middle-school children aged 10 to 14 responded to measures of motivation, attributions, and achievement both longitudinally and in a challenging reading context. Novel measures of motivation and attributions were constructed, validated, and utilized to examine the relationship between ~ motivation, attributions, and achievement over a one-year period (Study I). The impact of classroom contexts and instructional practices was also explored through a study of the influence of topic interest and challenge on motivation, attributions, and persistence (Study II), as well as through interviews with children regarding motivation and reading in the classroom (Study III). Creation and validation of novel measures of motivation and attributions supported the use of a self-report measure of motivation in situation-specific contexts, and confirmed a three-factor structure of attributions for reading performance in both hypothetical and situation-specific contexts. A one-year follow up study of children's motivation and reading achievement demonstrated declines in all components of motivation beginning at age 10 through 12, and particularly strong decreases in motivation with the transition to middle school. Past perceived competence for reading predicted current achievement after controlling for past achievement, and showed the strongest relationships with reading-related skills in both elementary and middle school. Motivation and attributions were strongly related, and children with higher motivation Fulmer III displayed more adaptive attributions for reading success and failure. In the context of a developmentally inappropriate challenging reading task, children's motivation for reading, especially in terms of perceived competence, was threatened. However, interest in the story buffered some ofthe negative impacts of challenge, sustaining children's motivation, adaptive attributions, and reading persistence. Finally, children's responses during interviews outlined several emotions, perceptions, and aspects of reading tasks and contexts that influence reading motivation and achievement. Findings revealed that children with comparable motivation and achievement profiles respond in a similar way to particular reading situations, such as excessive challenge, but also that motivation is dynamic and individualistic and can change over time and across contexts. Overall, the present study outlines the importance of motivation and adaptive attributions for reading success, and the necessity of integrating various methodologies to study the dynamic construct of achievement motivation.

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This paper employs the one-sector Real Business Cycle model as a testing ground for four different procedures to estimate Dynamic Stochastic General Equilibrium (DSGE) models. The procedures are: 1 ) Maximum Likelihood, with and without measurement errors and incorporating Bayesian priors, 2) Generalized Method of Moments, 3) Simulated Method of Moments, and 4) Indirect Inference. Monte Carlo analysis indicates that all procedures deliver reasonably good estimates under the null hypothesis. However, there are substantial differences in statistical and computational efficiency in the small samples currently available to estimate DSGE models. GMM and SMM appear to be more robust to misspecification than the alternative procedures. The implications of the stochastic singularity of DSGE models for each estimation method are fully discussed.

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En opération depuis 2008, l’expérience ATLAS est la plus grande de toutes les expériences au LHC. Les détecteurs ATLAS- MPX (MPX) installés dans ATLAS sont basés sur le détecteur au silicium à pixels Medipix2 qui a été développé par la collaboration Medipix au CERN pour faire de l’imagerie en temps réel. Les détecteurs MPX peuvent être utilisés pour mesurer la luminosité. Ils ont été installés à seize différents endroits dans les zones expérimentale et technique d’ATLAS en 2008. Le réseau MPX a recueilli avec succès des données indépendamment de la chaîne d’enregistrement des données ATLAS de 2008 à 2013. Chaque détecteur MPX fournit des mesures de la luminosité intégrée du LHC. Ce mémoire décrit la méthode d’étalonnage de la luminosité absolue mesurée avec les détectors MPX et la performance des détecteurs MPX pour les données de luminosité en 2012. Une constante d’étalonnage de la luminosité a été déterminée. L’étalonnage est basé sur technique de van der Meer (vdM). Cette technique permet la mesure de la taille des deux faisceaux en recouvrement dans le plan vertical et horizontal au point d’interaction d’ATLAS (IP1). La détermination de la luminosité absolue nécessite la connaissance précise de l’intensité des faisceaux et du nombre de trains de particules. Les trois balayages d’étalonnage ont été analysés et les résultats obtenus par les détecteurs MPX ont été comparés aux autres détecteurs d’ATLAS dédiés spécifiquement à la mesure de la luminosité. La luminosité obtenue à partir des balayages vdM a été comparée à la luminosité des collisions proton- proton avant et après les balayages vdM. Le réseau des détecteurs MPX donne des informations fiables pour la détermination de la luminosité de l’expérience ATLAS sur un large intervalle (luminosité de 5 × 10^29 cm−2 s−1 jusqu’à 7 × 10^33 cm−2 s−1 .

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The use of data reconciliation techniques can considerably reduce the inaccuracy of process data due to measurement errors. This in turn results in improved control system performance and process knowledge. Dynamic data reconciliation techniques are applied to a model-based predictive control scheme. It is shown through simulations on a chemical reactor system that the overall performance of the model-based predictive controller is enhanced considerably when data reconciliation is applied. The dynamic data reconciliation techniques used include a combined strategy for the simultaneous identification of outliers and systematic bias.

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Models for water transfer in the crop-soil system are key components of agro-hydrological models for irrigation, fertilizer and pesticide practices. Many of the hydrological models for water transfer in the crop-soil system are either too approximate due to oversimplified algorithms or employ complex numerical schemes. In this paper we developed a simple and sufficiently accurate algorithm which can be easily adopted in agro-hydrological models for the simulation of water dynamics. We used a dual crop coefficient approach proposed by the FAO for estimating potential evaporation and transpiration, and a dynamic model for calculating relative root length distribution on a daily basis. In a small time step of 0.001 d, we implemented algorithms separately for actual evaporation, root water uptake and soil water content redistribution by decoupling these processes. The Richards equation describing soil water movement was solved using an integration strategy over the soil layers instead of complex numerical schemes. This drastically simplified the procedures of modeling soil water and led to much shorter computer codes. The validity of the proposed model was tested against data from field experiments on two contrasting soils cropped with wheat. Good agreement was achieved between measurement and simulation of soil water content in various depths collected at intervals during crop growth. This indicates that the model is satisfactory in simulating water transfer in the crop-soil system, and therefore can reliably be adopted in agro-hydrological models. Finally we demonstrated how the developed model could be used to study the effect of changes in the environment such as lowering the groundwater table caused by the construction of a motorway on crop transpiration. (c) 2009 Elsevier B.V. All rights reserved.

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The suggestion is discussed that characteristic particle and field signatures at the dayside magnetopause, termed “flux transfer events” (FTEs), are, in at least some cases, due to transient solar wind and/or magnetosheath dynamic pressure increases, rather than time-dependent magnetic reconnection. It is found that most individual cases of FTEs observed by a single spacecraft can, at least qualitatively, be explained by the pressure pulse model, provided a few rather unsatisfactory features of the predictions are explained in terms of measurement uncertainties. The most notable exceptions to this are some “two-regime” observations made by two satellites simultaneously, one on either side of the magnetopause. However, this configuration has not been frequently achieved for sufficient time, such observations are rare, and the relevant tests are still not conclusive. The strongest evidence that FTEs are produced by magnetic reconnection is the dependence of their occurrence on the north-south component of the interplanetary magnetic field (IMF) or of the magnetosheath field. The pressure pulse model provides an explanation for this dependence (albeit qualitative) in the case of magnetosheath FTEs, but this does not apply to magnetosphere FTEs. The only surveys of magnetosphere FTEs have not employed the simultaneous IMF, but have shown that their occurrence is strongly dependent on the north-south component of the magnetosheath field, as observed earlier/later on the same magnetopause crossing (for inbound/outbound passes, respectively). This paper employs statistics on the variability of the IMF orientation to investigate the effects of IMF changes between the times of the magnetosheath and FTE observations. It is shown that the previously published results are consistent with magnetospheric FTEs being entirely absent when the magnetosheath field is northward: all crossings with magnetosphere FTEs and a northward field can be attributed to the field changing sense while the satellite was within the magnetosphere (but close enough to the magnetopause to detect an FTE). Allowance for the IMF variability also makes the occurrence frequency of magnetosphere FTEs during southward magnetosheath fields very similar to that observed for magnetosheath FTEs. Conversely, the probability of attaining the observed occurrence frequencies for the pressure pulse model is 10−14. In addition, it is argued that some magnetosheath FTEs should, for the pressure pulse model, have been observed for northward IMF: the probability that the number is as low as actually observed is estimated to be 10−10. It is concluded that although the pressure model can be invoked to qualitatively explain a large number of individual FTE observations, the observed occurrence statistics are in gross disagreement with this model.

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A structure-dynamic approach to cortical systems is reported which is based on the number of paths and the accessibility of each node. The latter measurement is obtained by performing self-avoiding random walks in the respective networks, so as to simulate dynamics, and then calculating the entropies of the transition probabilities for walks starting from each node. Cortical networks of three species, namely cat, macaque and humans, are studied considering structural and dynamical aspects. It is verified that the human cortical network presents the highest accessibility and number of paths (in terms of z-scores). The correlation between the number of paths and accessibility is also investigated as a mean to quantify the level of independence between paths connecting pairs of nodes in cortical networks. By comparing the cortical networks of cat, macaque and humans, it is verified that the human cortical network tends to present the largest number of independent paths of length larger than four. These results suggest that the human cortical network is potentially the most resilient to brain injures. (C) 2009 Elsevier B.V. All rights reserved.

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Objectives: Studies of the viscoelastic properties of the vocal folds are normally performed with rheometers that use parallel assigned a fixed value. In tissues subject to variation of thickness plates whose interplate space is usually at between samples, fixed gaps could result in different compressions, compromising the comparison among them. We performed,in experimental study to determine whether different compressions call lead to different results in measurements of dynamic viscosity (DV) of vocal fold samples. Methods: We Measured the DV of vocal fold samples of 10 larynges of cadavers under 3 different compression levels, corresponding to 0.2, 0.5, and 10 N on an 8-mm-diameter parallel-plate rheometer. Results: The DV directly varied with compression. We observed statistically significant differences between the results of 0.2 and 10 N (p = 0.0396) and 0.5 and 10 N (p = 0.0442). Conclusions: The study demonstrated that the level of compression influences the DV measure and Suggests that a defined compression level should be used in rheometric studies of biological tissues.

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Reviewing the de nition and measurement of speculative bubbles in context of contagion, this paper analyses the DotCom bubble in American and European equity markets using the dynamic conditional correlation (DCC) model proposed by (Engle and Sheppard 2001) as on one hand as an econometrics explanation and on the other hand the behavioral nance as an psychological explanation. Contagion is de ned in this context as the statistical break in the computed DCCs as measured by the shifts in their means and medians. Even it is astonishing, that the contagion is lower during price bubbles, the main nding indicates the presence of contagion in the di¤erent indices among those two continents and proves the presence of structural changes during nancial crisis

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.