106 resultados para Dynamic Calibration
Resumo:
Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.
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We show that the quasifission paths predicted by the one-body dissipation dynamics, in the slowest phase of a binary reaction, follow a quasistatic path, which represents a sequence of states of thermal equilibrium at a fixed value of the deformation coordinate. This establishes the use of the statistical particle-evaporation model in the case of dynamical time-evolving systems. Pre- and post-scission multiplicities of neutrons and total multiplicities of protons and α particles in fission reactions of 63Cu+92Mo, 60Ni+100Mo, 63Cu+100Mo at 10 MeV/u and 20Ne+144,148,154Sm at 20 MeV/u are reproduced reasonably well with statistical model calculations performed along dynamic trajectories whose slow stage (from the most compact configuration up to the point where the neck starts to develop) lasts some 35×10−21 s.
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This paper describes the fluctuations of temporal criteria dynamics in the context of professional sport. Specifically, we try to verify the underlying deterministic patterns in the outcomes of professional basketball players. We use a longitudinal approach based on the analysis of the outcomes of 94 basketball players over ten years, covering practically players" entire career development. Time series were analyzed with techniques derived from nonlinear dynamical systems theory. These techniques analyze the underlying patterns in outcomes without previous shape assumptions (linear or nonlinear). These techniques are capable of detecting an intermediate situation between randomness and determinism, called chaos. So they are very useful for the study of dynamic criteria in organizations. We have found most players (88.30%) have a deterministic pattern in their outcomes, and most cases are chaotic (81.92%). Players with chaotic patterns have higher outcomes than players with linear patterns. Moreover, players with power forward and center positions achieve better results than other players. The high number of chaotic patterns found suggests caution when appraising individual outcomes, when coaches try to find the appropriate combination of players to design a competitive team, and other personnel decisions. Management efforts must be made to assume this uncertainty.
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We present molecular dynamics simulations of a simple model for polymer melts with intramolecular barriers. We investigate structural relaxation as a function of the barrier strength. Dynamic correlators can be consistently analyzed within the framework of the mode coupling theory of the glass transition. Control parameters are tuned in order to induce a competition between general packing effects and polymer-specific intramolecular barriers as mechanisms for dynamic arrest. This competition yields unusually large values of the so-called mode coupling theory exponent parameter and rationalizes qualitatively different observations for simple bead-spring and realistic polymers. The systematic study of the effect of intramolecular barriers presented here also establishes a fundamental difference between the nature of the glass transition in polymers and in simple glass formers.
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The silicon photomultiplier (SiPM) is a novel detector technology that has undergone a fast development in the last few years, owing to its single-photon resolution and ultra-fast response time. However, the typical high dark count rates of the sensor may prevent the detection of low intensity radiation fluxes. In this article, the time-gated operation with short active periods in the nanosecond range is proposed as a solution to reduce the number of cells fired due to noise and thus increase the dynamic range. The technique is aimed at application fields that function under a trigger command, such as gated fluorescence lifetime imaging microscopy.
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Intravascular brachytherapy with beta sources has become a useful technique to prevent restenosis after cardiovascular intervention. In particular, the Beta-Cath high-dose-rate system, manufactured by Novoste Corporation, is a commercially available 90Sr 90Y source for intravascular brachytherapy that is achieving widespread use. Its dosimetric characterization has attracted considerable attention in recent years. Unfortunately, the short ranges of the emitted beta particles and the associated large dose gradients make experimental measurements particularly difficult. This circumstance has motivated the appearance of a number of papers addressing the characterization of this source by means of Monte Carlo simulation techniques.
Resumo:
Chemical analysis is a well-established procedure for the provenancing of archaeological ceramics. Various analytical techniques are routinely used and large amounts of data have been accumulated so far in data banks. However, in order to exchange results obtained by different laboratories, the respective analytical procedures need to be tested in terms of their inter-comparability. In this study, the schemes of analysis used in four laboratories that are involved in archaeological pottery studies on a routine basis were compared. The techniques investigated were neutron activation analysis (NAA), X-ray fluorescence analysis (XRF), inductively coupled plasma optical emission spectrometry (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS). For this comparison series of measurements on different geological standard reference materials (SRM) were carried out and the results were statistically evaluated. An attempt was also made towards the establishment of calibration factors between pairs of analytical setups in order to smooth the systematic differences among the results.
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Iberia underwent intraplate deformation during the Mesozoic and Cenozoic. In eastem Ibena, compression took place during the Palaeogene and early Miocene, giving rise to the Iberian Chain, and extension started during the early Miocene in the coastal areas and the Valencia trough; during early Miocene compression continued in the western Iberian Chain whereas extension had started in the eastern Iberian Chain. From the kinematic data obtained from the major compressional and extensional structures formed dunng the Cenozoic, a simple dynamic model using Bott's (1959) formula is presented. The results show that both extension and compression may have been produced assuming a main horizontal stress-axis approximately N-S, in a similar direction that the convergence between Europe, Ibena and Afnca dunng the Cenozoic.
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Our research aims to analyze the causal relationships in the behavior of public debt issued by peripheral member countries of the European Economic and Monetary Union -EMU-, with special emphasis on the recent episodes of crisis triggered in the eurozone sovereign debt markets since 2009. With this goal in mind, we make use of a database of daily frequency of yields on 10-year government bonds issued by five EMU countries -Greece, Ireland, Italy, Portugal and Spain-, covering the entire history of the EMU from its inception on 1 January 1999 until 31 December 2010. In the first step, we explore the pair-wise causal relationship between yields, both for the whole sample and for changing subsamples of the data, in order to capture the possible time-varying causal relationship. This approach allows us to detect episodes of contagion between yields on bonds issued by different countries. In the second step, we study the determinants of these contagion episodes, analyzing the role played by different factors, paying special attention to instruments that capture the total national debt -domestic and foreign- in each country.
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Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.
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Needle trap devices (NTDs) are a relatively new and promising tool for headspace (HS) analysis. In this study, a dynamic HS sampling procedure is evaluated for the determination of volatile organic compounds (VOCs) in whole blood samples. A full factorial design was used to evaluate the influence of the number of cycles and incubation time and it is demonstrated that the controlling factor in the process is the number of cycles. A mathematical model can be used to determine the most appropriate number of cycles required to adsorb a prefixed amount of VOCs present in the HS phase whenever quantitative adsorption is reached in each cycle. Matrix effect is of great importance when complex biological samples, such as blood, are analyzed. The evaluation of the salting out effect showed a significant improvement in the volatilization of VOCs to the HS in this type of matrices. Moreover, a 1:4 (blood:water) dilution is required to obtain quantitative recoveries of the target analytes when external calibration is used. The method developed gives detection limits in the 0.020–0.080 μg L−1 range (0.1–0.4 μg L−1 range for undiluted blood samples) with appropriate repeatability values (RSD < 15% at high level and <23% at LOQ level). Figure of merits of the method can be improved by using a smaller phase ratio (i.e., an increase in the blood volume and a decrease in the HS volume), which lead to lower detection limits, better repeatability values and greater sensibility. Twenty-eight blood samples have been evaluated with the proposed method and the results agree with those indicated in other studies. Benzene was the only target compound that gave significant differences between blood levels detected in volunteer non-smokers and smokers
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As a result of the growing interest in studying employee well-being as a complex process that portrays high levels of within-individual variability and evolves over time, this present study considers the experience of flow in the workplace from a nonlinear dynamical systems approach. Our goal is to offer new ways to move the study of employee well-being beyond linear approaches. With nonlinear dynamical systems theory as the backdrop, we conducted a longitudinal study using the experience sampling method and qualitative semi-structured interviews for data collection; 6981 registers of data were collected from a sample of 60 employees. The obtained time series were analyzed using various techniques derived from the nonlinear dynamical systems theory (i.e., recurrence analysis and surrogate data) and multiple correspondence analyses. The results revealed the following: 1) flow in the workplace presents a high degree of within-individual variability; this variability is characterized as chaotic for most of the cases (75%); 2) high levels of flow are associated with chaos; and 3) different dimensions of the flow experience (e.g., merging of action and awareness) as well as individual (e.g., age) and job characteristics (e.g., job tenure) are associated with the emergence of different dynamic patterns (chaotic, linear and random).
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Available empirical evidence regarding the degree of symmetry between European economies in the context of Monetary Unification is not conclusive. This paper offers new empirical evidence concerning this issue related to the manufacturing sector. Instead of using a static approach as most empirical studies do, we analyse the dynamic evolution of shock symmetry using a state-space model. The results show a clear reduction of asymmetries in terms of demand shocks between 1975 and 1996, with an increase in terms of supply shocks at the end of the period.
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We present the implementation of dynamic electrostatic force microscopy in liquid media. This implementation enables the quantitative imaging of local dielectric properties of materials in electrolyte solutions with nanoscale spatial resolution. Local imaging capabilities are obtained by probing the frequency-dependent and ionic concentration-dependent electrostatic forces at high frequency (>1 MHz), while quantification of the interaction forces is obtained with finite-element numerical calculations. The results presented open a wide range of possibilities in a number of fields where the dielectric properties of materials need to be probed at the nanoscale and in a liquid environment.