957 resultados para TIME EVOLUTION
Resumo:
Niobium pentoxide reacts actively with concentrate NaOH solution under hydrothermal conditions at as low as 120 degrees C. The reaction ruptures the corner-sharing of NbO7 decahedra and NbO6 octahedra in the reactant Nb2O5, yielding various niobates, and the structure and composition of the niobates depend on the reaction temperature and time. The morphological evolution of the solid products in the reaction at 180 degrees C is monitored via SEM: the fine Nb2O5 powder aggregates first to irregular bars, and then niobate fibers with an aspect ratio of hundreds form. The fibers are microporous molecular sieve with a monoclinic lattice, Na2Nb2O6 center dot(2)/3H2O. The fibers are a metastable intermediate of this reaction, and they completely convert to the final product NaNbO3 Cubes in the prolonged reaction of 1 h. This study demonstrates that by carefully optimizing the reaction condition, we can selectively fabricate niobate structures of high purity, including the delicate microporous fibers, through a direct reaction between concentrated NaOH solution and Nb2O5. This synthesis route is simple and suitable for the large-scale production of the fibers. The reaction first yields poorly crystallized niobates consisting of edge-sharing NbO6 octahedra, and then the microporous fibers crystallize and grow by assembling NbO6 octahedra or clusters of NbO6 octahedra and NaO6 units. Thus, the selection of the fibril or cubic product is achieved by control of reaction kinetics. Finally, niobates with different structures exhibit remarkable differences in light absorption and photoluminescence properties. Therefore, this study is of importance for developing new functional materials by the wet-chemistry process.
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Quantitative genetics provides a powerful framework for studying phenotypic evolution and the evolution of adaptive genetic variation. Central to the approach is G, the matrix of additive genetic variances and covariances. G summarizes the genetic basis of the traits and can be used to predict the phenotypic response to multivariate selection or to drift. Recent analytical and computational advances have improved both the power and the accessibility of the necessary multivariate statistics. It is now possible to study the relationships between G and other evolutionary parameters, such as those describing the mutational input, the shape and orientation of the adaptive landscape, and the phenotypic divergence among populations. At the same time, we are moving towards a greater understanding of how the genetic variation summarized by G evolves. Computer simulations of the evolution of G, innovations in matrix comparison methods, and rapid development of powerful molecular genetic tools have all opened the way for dissecting the interaction between allelic variation and evolutionary process. Here I discuss some current uses of G, problems with the application of these approaches, and identify avenues for future research.
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Enterovirus 71 (EV71) is one of the main causative agents of hand, foot and mouth disease (HFMD) in young children. Infections caused by EV71 could lead to many complications, ranging from brainstem encephalitis to pulmonary oedema, resulting in high mortality. Thus, rapid detection of the virus is required to enable measures to be implemented in preventing widespread transmission. Based on primers and probes targeting at the VP1 region, a real-time reverse-transcriptase polymerase chain reaction (RT-PCR) hybridization probe assay was developed for specific detection of EV71 from clinical specimens. Quantitative analysis showed that the assay was able to detect as low as 5 EV71 viral copies and EV71 was detected from 46 of the 55 clinical specimens obtained from pediatric patients suffering from HFMD during the period from 2000 to 2003 in Singapore. This study showed that the single tube real-time RT-PCR assay developed in this study can be applied as a rapid and sensitive method for specific detection of EV71 directly from clinical specimens. (c) 2005 Elsevier Ltd. All rights reserved.
Resumo:
Weathering profiles overlying the Sapecado, Pico and Andaime iron ore deposits, Quadrilátero Ferrífero (QF), Minas Gerais, Brazil, reach depths of 150–400 m and host world-class supergene iron orebodies. In addition to hosting supergene ore bodies of global economic significance, weathered banded iron-formations at the Quadrilátero Ferrífero and elsewhere (e.g., Carajás, Hamersley) are postulated to underlie some of the most ancient continuously exposed weathering profiles on earth. Laser incremental-heating 40Ar/39Ar results for 69 grains of hollandite-group manganese oxides extracted from 23 samples collected at depths ranging from 5 to 150 m at the Sapecado, Pico and Andaime deposits reveal ages ranging from ca. 62 to 14 Ma. Older Mn-oxides occur near the surface, while younger Mn-oxides occur at depth. However, many samples collected at the weathering–bedrock interface yield ages in the 51–41 Ma range, suggesting that the weathering profiles in the Quadrilátero Ferrífero had already reached their present depth in the Paleogene. The antiquity of the weathering profiles in the Quadrilátero Ferrífero is comparable to the antiquity of dated weathering profiles on banded iron-formations in the Carajás Region (Brazil) and the Hamersley Province, Western Australia. The age versus depth distributions obtained in this study, but not available for other regions containing similar supergene iron deposits, suggest that little further advance of the weathering front has occurred in the Quadrilátero Ferrífero lateritic profiles during the Neogene. The results suggest that weathering in some of these ancient landscapes is not controlled by the steady-state advance of weathering fronts through time, but may reflect climatic and geomorphological conditions prevailing in a remote past. The geochronological results also confirm that the ancient landsurfaces in the Quadrilátero Ferrífero probably remained immune to erosion for tens of millions of years. Deep weathering, mostly in the Paleogene, combined with low erosion rates, account for the abundance and widespread distribution of supergene iron, manganese, and aluminum orebodies in this region.
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A plethora of process modeling techniques has been proposed over the years. One way of evaluating and comparing the scope and completeness of techniques is by way of representational analysis. The purpose of this paper is to examine how process modeling techniques have developed over the last four decades. The basis of the comparison is the Bunge-Wand-Weber representation model, a benchmark used for the analysis of grammars that purport to model the real world and the interactions within it. This paper presents a comparison of representational analyses of several popular process modeling techniques and has two main outcomes. First, it provides insights, within the boundaries of a representational analysis, into the extent to which process modeling techniques have developed over time. Second, the findings also indicate areas in which the underlying theory seems to be over-engineered or lacking in specialization.
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Operationalising and measuring the concept of globalisation is important, as the extent to which the international economy is integrated has a direct impact on industrial dynamics, national trade policies and firm strategies. Using complex systems network analysis with longitudinal trade data from 1938 to 2003, this paper presents a new way to measure globalisation. It demonstrates that some important aspects of the international trade network have been remarkably stable over this period. However, several network measures have changed substantially over the same time frame. Taken together, these analyses provide a novel measure of globalisation.
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We present in this paper ideas to tackle the problem of analysing and forecasting nonstationary time series within the financial domain. Accepting the stochastic nature of the underlying data generator we assume that the evolution of the generator's parameters is restricted on a deterministic manifold. Therefore we propose methods for determining the characteristics of the time-localised distribution. Starting with the assumption of a static normal distribution we refine this hypothesis according to the empirical results obtained with the methods anc conclude with the indication of a dynamic non-Gaussian behaviour with varying dependency for the time series under consideration.
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The paper examines the capital structure adjustment dynamics of listed non-financial corporations in seven east Asian countries before, during and after the crisis of 1997–1998. Our methodology allows for speeds of adjustment to vary, not only among firms, but also over time, distinguishing between cases of sudden and smooth adjustment.Whereas, compared with firms in the least affected countries, average leverages were much higher, generalized method-ofmoments analysis of the Worldscope panel data suggests that average speeds of adjustment were lower in the worst affected countries. This holds also for the severely financially distressed firms in some worst affected countries, though the trend reversed in the post-crisis period. These findings have important implications for the regulatory environment as well as access to market finance.
Resumo:
Purpose - This paper provides a deeper examination of the fundamentals of commonly-used techniques - such as coefficient alpha and factor analysis - in order to more strongly link the techniques used by marketing and social researchers to their underlying psychometric and statistical rationale. Design/methodology approach - A wide-ranging review and synthesis of psychometric and other measurement literature both within and outside the marketing field is used to illuminate and reconsider a number of misconceptions which seem to have evolved in marketing research. Findings - The research finds that marketing scholars have generally concentrated on reporting what are essentially arbitrary figures such as coefficient alpha, without fully understanding what these figures imply. It is argued that, if the link between theory and technique is not clearly understood, use of psychometric measure development tools actually runs the risk of detracting from the validity of the measures rather than enhancing it. Research limitations/implications - The focus on one stage of a particular form of measure development could be seen as rather specialised. The paper also runs the risk of increasing the amount of dogma surrounding measurement, which runs contrary to the spirit of this paper. Practical implications - This paper shows that researchers may need to spend more time interpreting measurement results. Rather than simply referring to precedence, one needs to understand the link between measurement theory and actual technique. Originality/value - This paper presents psychometric measurement and item analysis theory in easily understandable format, and offers an important set of conceptual tools for researchers in many fields. © Emerald Group Publishing Limited.
Resumo:
The aim of this thesis is to present numerical investigations of the polarisation mode dispersion (PMD) effect. Outstanding issues on the side of the numerical implementations of PMD are resolved and the proposed methods are further optimized for computational efficiency and physical accuracy. Methods for the mitigation of the PMD effect are taken into account and simulations of transmission system with added PMD are presented. The basic outline of the work focusing on PMD can be divided as follows. At first the widely-used coarse-step method for simulating the PMD phenomenon as well as a method derived from the Manakov-PMD equation are implemented and investigated separately through the distribution of a state of polarisation on the Poincaré sphere, and the evolution of the dispersion of a signal. Next these two methods are statistically examined and compared to well-known analytical models of the probability distribution function (PDF) and the autocorrelation function (ACF) of the PMD phenomenon. Important optimisations are achieved, for each of the aforementioned implementations in the computational level. In addition the ACF of the coarse-step method is considered separately, based on the result which indicates that the numerically produced ACF, exaggerates the value of the correlation between different frequencies. Moreover the mitigation of the PMD phenomenon is considered, in the form of numerically implementing Low-PMD spun fibres. Finally, all the above are combined in simulations that demonstrate the impact of the PMD on the quality factor (Q=factor) of different transmission systems. For this a numerical solver based on the coupled nonlinear Schrödinger equation is created which is otherwise tested against the most important transmission impairments in the early chapters of this thesis.
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National meteorological offices are largely concerned with synoptic-scale forecasting where weather predictions are produced for a whole country for 24 hours ahead. In practice, many local organisations (such as emergency services, construction industries, forestry, farming, and sports) require only local short-term, bespoke, weather predictions and warnings. This thesis shows that the less-demanding requirements do not require exceptional computing power and can be met by a modern, desk-top system which monitors site-specific ground conditions (such as temperature, pressure, wind speed and direction, etc) augmented with above ground information from satellite images to produce `nowcasts'. The emphasis in this thesis has been towards the design of such a real-time system for nowcasting. Local site-specific conditions are monitored using a custom-built, stand alone, Motorola 6809 based sub-system. Above ground information is received from the METEOSAT 4 geo-stationary satellite using a sub-system based on a commercially available equipment. The information is ephemeral and must be captured in real-time. The real-time nowcasting system for localised weather handles the data as a transparent task using the limited capabilities of the PC system. Ground data produces a time series of measurements at a specific location which represents the past-to-present atmospheric conditions of the particular site from which much information can be extracted. The novel approach adopted in this thesis is one of constructing stochastic models based on the AutoRegressive Integrated Moving Average (ARIMA) technique. The satellite images contain features (such as cloud formations) which evolve dynamically and may be subject to movement, growth, distortion, bifurcation, superposition, or elimination between images. The process of extracting a weather feature, following its motion and predicting its future evolution involves algorithms for normalisation, partitioning, filtering, image enhancement, and correlation of multi-dimensional signals in different domains. To limit the processing requirements, the analysis in this thesis concentrates on an `area of interest'. By this rationale, only a small fraction of the total image needs to be processed, leading to a major saving in time. The thesis also proposes an extention to an existing manual cloud classification technique for its implementation in automatically classifying a cloud feature over the `area of interest' for nowcasting using the multi-dimensional signals.
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Studies of political dynamics between multinational enterprise (MNE) parents and subsidiaries during subsidiary role evolution have focused largely on control and resistance. This paper adopts a critical discursive approach to enable an exploration of subtle dynamics in the way that both headquarters and subsidiaries subjectively reconstruct their independent-interdependent relationships with each other during change. We draw from a real-time qualitative study of a revealing case of charter change in an important European subsidiary of an MNE attempting to build closer integration across European country operations. Our results illustrate the role of three discourses – selling, resistance and reconciliation – in the reconstruction of the subsidiary–parent relationship. From this analysis we develop a process framework that elucidates the important role of these three discourses in the reconstruction of subsidiary roles, showing how resistance is not simply subversive but an important part of integration. Our findings contribute to a better understanding of the micro-level political dynamics in subsidiary role evolution, and of how voice is exercised in MNEs. This study also provides a rare example of discourse-based analysis in an MNE context, advancing our knowledge of how discursive methods can help to advance international business research more generally.
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Last year (2009) marked the bicentenary of Charles Darwin's birth and the sesquicentenary of The Origin of Species. This article examines the influence of Erasmus Darwin on Charles's evolutionary thought and shows how, in many ways, Erasmus anticipated his much better-known grandson. It discusses the similarity in the mindsets of the two Darwins, asks how far the younger Darwin was exposed to the elder's evolutionary thought, examines the similarities and differences in their theories of evolution, and ends by showing the surprising similarity between their theories of inheritance. Erasmus's influence on Charles is greater than customarily acknowledged, and now is an opportune time to bring the grandfather out from behind the glare of his stellar grandson.
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We present a mean-field model of cloud evolution that describes droplet growth due to condensation and collisions and droplet loss due to fallout. The model accounts for the effects of cloud turbulence both in a large-scale turbulent mixing and in a microphysical enhancement of condensation and collisions. The model allows for an effective numerical simulation by a scheme that is conservative in water mass and keeps accurate count of the number of droplets. We first study the homogeneous situation and determine how the rain-initiation time depends on the concentration of cloud condensation nuclei (CCN) and turbulence level. We then consider clouds with an inhomogeneous concentration of CCN and evaluate how the rain initiation time and the effective optical depth vary in space and time. We argue that over-seeding even a part of a cloud by small hygroscopic nuclei, one can substantially delay the onset and increase the amount of precipitation.
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The spreading time of liquid binder droplet on the surface a primary particle is analyzed for Fluidized Bed Melt Granulation (FBMG). As discussed in the first paper of this series (Chua et al., in press) the droplet spreading rate has been identified as one of the important parameters affecting the probability of particles aggregation in FBMG. In this paper, the binder droplet spreading time has been estimated using Computational Fluid Dynamic modeling (CFD) based on Volume of Fluid approach (VOF). A simplified analytical solution has been developed and tested to explore its validity for predicting the spreading time. For the purpose of models validation, the droplet spreading evolution was recorded using a high speed video camera. Based on the validated model, a generalized correlative equation for binder spreading time is proposed. For the operating conditions considered here, the spreading time for Polyethylene Glycol (PEG1500) binder was found to fall within the range of 10-2 to 10-5 s. The study also included a number of other common binders used in FBMG. The results obtained here will be further used in paper III, where the binder solidification rate is discussed.