990 resultados para Dynamic nonlinear
Resumo:
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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The purpose of this study was to increase the understanding of the role and nature of trust in asymmetric technology partnership formation. In the knowledge-based "learning race" knowledge is considered as a primary source for competitive advantage. In the emerging ICT sector the high pace of technological change, the convergence of technologies and industries as well as the increasing complexity and uncertainty have forced even the largest players to seek cooperation for complementary knowledge and capabilities. Small technology firms need the complementary resources and legitimacy of the large firms to grow and compete in the global market place. Most of the earlier research indicates, however, that partnerships with asymmetric size, managerial resources and cultures have failed. A basic assumption supported by earlier research was that trust is a critical factor in asymmetric technology partnership formation. Asymmetric technology partnership formation is a dynamic and multi-dimensional process, and consequently a holistic research approach was selected. Research issue was approached from different levels: the individual decision-maker, the firm and the relationship between the parties. Also the impact of the dynamic environment and technology content was analyzed. A multitheoretical approach and a qualitative research method with in-depth interviews in five large ICT companies and eight small ICT companies enabled a holistic and rich view of the research issue. Study contributes on the scarce understanding on the nature and evolution of trust in asymmetric technology partnership formation. It sheds also light on the specific nature of asymmetric technology partnerships. The partnerships were found to be tentative and the diverse strategic intent of small and large technology firms appeared as a major challenge. The role of the boundary spanner was highlighted as a possibility to match the incompatible organizational cultures. A shared vision was found to be a pre-condition for individual-based fast trust leading to intuitive decision-making and experimentation. The relationships were tentative and they were continuously re-evaluated through the key actors' sense making of the technology content, asymmetry and the dynamic environment. A multi-dimensional conceptualization for trust was created and propositions on the role and nature of trust for further research are given. The purpose of this study was to increase the understanding of the role and nature of trust in asymmetric technology partnership formation. In the knowledge-based "learning race" knowledge is considered as a primary source for competitive advantage. In the emerging ICT sector the high pace of technological change, the convergence of technologies and industries as well as the increasing complexity and uncertainty have forced even the largest players to seek cooperation for complementary knowledge and capabilities. Small technology firms need the complementary resources and legitimacy of the large firms to grow and compete in the global market place. Most of the earlier research indicates, however, that partnerships with asymmetric size, managerial resources and cultures have failed. A basic assumption supported by earlier research was that trust is a critical factor in asymmetric technology partnership formation. Asymmetric technology partnership formation is a dynamic and multi-dimensional process, and consequently a holistic research approach was selected. Research issue was approached from different levels: the individual decision-maker, the firm and the relationship between the parties. Also the impact of the dynamic environment and technology content was analyzed. A multitheoretical approach and a qualitative research method with in-depth interviews in five large ICT companies and eight small ICT companies enabled a holistic and rich view of the research issue. Study contributes on the scarce understanding on the nature and evolution of trust in asymmetric technology partnership formation. It sheds also light on the specific nature of asymmetric technology partnerships. The partnerships were found to be tentative and the diverse strategic intent of small and large technology firms appeared as a major challenge. The role of the boundary spanner was highlighted as a possibility to match the incompatible organizational cultures. A shared vision was found to be a pre-condition for individual-based fast trust leading to intuitive decision-making and experimentation. The relationships were tentative and they were continuously re-evaluated through the key actors' sense making of the technology content, asymmetry and the dynamic environment. A multi-dimensional conceptualization for trust was created and propositions on the role and nature of trust for further research are given.
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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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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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PURPOSE: This study aims to identify which aspects of the pupil light reflex are most influenced by rods and cones independently by analyzing pupil recordings from different mouse models of photoreceptor deficiency. METHODS: One-month-old wild type (WT), rodless (Rho-/-), coneless (Cnga3-/-), or photoreceptor less (Cnga3-/-; Rho-/- or Gnat1-/-) mice were subjected to brief red and blue light stimuli of increasing intensity. To describe the initial dynamic response to light, the maximal pupillary constriction amplitudes and the derivative curve of the first 3 seconds were determined. To estimate the postillumination phase, the constriction amplitude at 9.5 seconds after light termination was related to the maximal constriction amplitude. RESULTS: Rho-/- mice showed decreased constriction amplitude but more prolonged pupilloconstriction to all blue and red light stimuli compared to wild type mice. Cnga3-/- mice had constriction amplitudes similar to WT however following maximal constriction, the early and rapid dilation to low intensity blue light was decreased. To high intensity blue light, the Cnga3-/- mice demonstrated marked prolongation of the pupillary constriction. Cnga3-/-; Rho-/- mice had no pupil response to red light of low and medium intensity. CONCLUSIONS: From specific gene defective mouse models which selectively voided the rod or cone function, we determined that mouse rod photoreceptors are highly contributing to the pupil response to blue light stimuli but also to low and medium red stimuli. We also observed that cone cells mainly drive the partial rapid dilation of the initial response to low blue light stimuli. Thus photoreceptor dysfunction can be derived from chromatic pupillometry in mouse models.
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COD discharges out of processes have increased in line with elevating brightness demands for mechanical pulp and papers. The share of lignin-like substances in COD discharges is on average 75%. In this thesis, a plant dynamic model was created and validated as a means to predict COD loading and discharges out of a mill. The assays were carried out in one paper mill integrate producing mechanical printing papers. The objective in the modeling of plant dynamics was to predict day averages of COD load and discharges out of mills. This means that online data, like 1) the level of large storage towers of pulp and white water 2) pulp dosages, 3) production rates and 4) internal white water flows and discharges were used to create transients into the balances of solids and white water, referred to as “plant dynamics”. A conversion coefficient was verified between TOC and COD. The conversion coefficient was used for predicting the flows from TOC to COD to the waste water treatment plant. The COD load was modeled with similar uncertainty as in reference TOC sampling. The water balance of waste water treatment was validated by the reference concentration of COD. The difference of COD predictions against references was within the same deviation of TOC-predictions. The modeled yield losses and retention values of TOC in pulping and bleaching processes and the modeled fixing of colloidal TOC to solids between the pulping plant and the aeration basin in the waste water treatment plant were similar to references presented in literature. The valid water balances of the waste water treatment plant and the reduction model of lignin-like substances produced a valid prediction of COD discharges out of the mill. A 30% increase in the release of lignin-like substances in the form of production problems was observed in pulping and bleaching processes. The same increase was observed in COD discharges out of waste water treatment. In the prediction of annual COD discharge, it was noticed that the reduction of lignin has a wide deviation from year to year and from one mill to another. This made it difficult to compare the parameters of COD discharges validated in plant dynamic simulation with another mill producing mechanical printing papers. However, a trend of moving from unbleached towards high-brightness TMP in COD discharges was valid.
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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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Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD.
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This paper is a literature review which describes the construction of state of the art of permanent magnet generators and motors constructing and discusses the current and possible application of these machines in industry. Permanent magnet machines are a well-know class of rotating and linear electric machines used for many years in industrial applications. A particular interest for permanent magnet generators is connected with wind mills, which seem to be becoming increasingly popular nowadays. Geared and direct-driven permanent magnet generators are described. A classification of direct-driven permanent magnet generators is given. Design aspects of permanent magnet generators are presented. Permanent magnet generators for wind turbines designs are highlighted. Dynamics and vibration problems of permanent magnet generators covered in literature are presented. The application of the Finite Element Method for mechanical problems solution in the field of permanent magnet generators is discussed.
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Technical analysis of Low Voltage Direct Current (LVDC) distribution systems shows that in LVDC transmission the customer voltage quality is higher. One of the problems in LVDC distribution networks that converters both ends of the DC line are required. Because of the converters produce not pure DC voltage, but some fluctuations as well, the huge electrolytic capacitors are required to reduce voltage distortions in the DC-side. This thesis master’s thesis is focused on calculating required DC-link capacitance for LVDC transmission and estimation of the influence of different parameters on the voltage quality. The goal is to investigate the methods of the DC-link capacitance estimation and location in the transmission line.
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In this work we consider the nonlinear equivalent representation form of oscillators that exhibit nonlinearities in both the elastic and the damping terms. The nonlinear damping effects are considered to be described by fractional power velocity terms which provide better predictions of the dissipative effects observed in some physical systems. It is shown that their effects on the system dynamics response are equivalent to a shift in the coefficient of the linear damping term of a Duffing oscillator. Then, its numerical integration predictions, based on its equivalent representation form given by the well-known forced, damped Duffing equation, are compared to the numerical integration values of its original equations of motion. The applicability of the proposed procedure is evaluated by studying the dynamics response of four nonlinear oscillators that arise in some engineering applications such as nanoresonators, microresonators, human wrist movements, structural engineering design, and chain dynamics of polymeric materials at high extensibility, among others
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Electron scattering on a thin layer where the potential depends self-consistently on the wave function has been studied. When the amplitude of the incident wave exceeds a certain threshold, a soliton-shaped brightening (darkening) appears on the layer causing diffraction of the wave. Thus the spontaneously formed transverse pattern can be viewed as a self-induced nonlinear quantum screen. Attractive or repulsive nonlinearities result in different phase shifts of the wave function on the screen, which give rise to quite different diffraction patterns. Among others, the nonlinearity can cause self-focusing of the incident wave into a beam, splitting in two "beams," single or double traces with suppressed reflection or transmission, etc.
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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.