135 resultados para Crystal growth-theory and techniques

em CentAUR: Central Archive University of Reading - UK


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Vertically pointing Doppler radar has been used to study the evolution of ice particles as they sediment through a cirrus cloud. The measured Doppler fall speeds, together with radar-derived estimates for the altitude of cloud top, are used to estimate a characteristic fall time tc for the `average' ice particle. The change in radar reflectivity Z is studied as a function of tc, and is found to increase exponentially with fall time. We use the idea of dynamically scaling particle size distributions to show that this behaviour implies exponential growth of the average particle size, and argue that this exponential growth is a signature of ice crystal aggregation.

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The fundamental features of growth may be universal, because growth trajectories of most animals are very similar, but a unified mechanistic theory of growth remains elusive. Still needed is a synthetic explanation for how and why growth rates vary as body size changes, both within individuals over their ontogeny and between populations and species over their evolution. Here we use Bertalanffy growth equations to characterize growth of ray-finned fishes in terms of two parameters, the growth rate coefficient, K, and final body mass, m∞. We derive two alternative empirically testable hypotheses and test them by analyzing data from FishBase. Across 576 species, which vary in size at maturity by almost nine orders of magnitude, K scaled as m_∞^(-0.23). This supports our first hypothesis that growth rate scales as m_∞^(-0.25) as predicted by metabolic scaling theory; it implies that species which grow to larger mature sizes grow faster as juveniles. Within fish species, however, K scaled as m_∞^(-0.35). This supports our second hypothesis which predicts that growth rate scales as m_∞^(-0.33) when all juveniles grow at the same rate. The unexpected disparity between across- and within-species scaling challenges existing theoretical interpretations. We suggest that the similar ontogenetic programs of closely related populations constrain growth to m_∞^(-0.33) scaling, but as species diverge over evolutionary time they evolve the near-optimal m_∞^(-0.25) scaling predicted by metabolic scaling theory. Our findings have important practical implications because fish supply essential protein in human diets, and sustainable yields from wild harvests and aquaculture depend on growth rates.

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In a recent paper of Feng and Sidorov they show that for β∈(1,(1+5√)/2) the set of β-expansions grows exponentially for every x∈(0,1/(β−1)). In this paper we study this growth rate further. We also consider the set of β-expansions from a dimension theory perspective.

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1. The management of threatened species is an important practical way in which conservationists can intervene in the extinction process and reduce the loss of biodiversity. Understanding the causes of population declines (past, present and future) is pivotal to designing effective practical management. This is the declining-population paradigm identified by Caughley. 2. There are three broad classes of ecological tool used by conservationists to guide management decisions for threatened species: statistical models of habitat use, demographic models and behaviour-based models. Each of these is described here, illustrated with a case study and evaluated critically in terms of its practical application. 3. These tools are fundamentally different. Statistical models of habitat use and demographic models both use descriptions of patterns in abundance and demography, in relation to a range of factors, to inform management decisions. In contrast, behaviourbased models describe the evolutionary processes underlying these patterns, and derive such patterns from the strategies employed by individuals when competing for resources under a specific set of environmental conditions. 4. Statistical models of habitat use and demographic models have been used successfully to make management recommendations for declining populations. To do this, assumptions are made about population growth or vital rates that will apply when environmental conditions are restored, based on either past data collected under favourable environmental conditions or estimates of these parameters when the agent of decline is removed. As a result, they can only be used to make reliable quantitative predictions about future environments when a comparable environment has been experienced by the population of interest in the past. 5. Many future changes in the environment driven by management will not have been experienced by a population in the past. Under these circumstances, vital rates and their relationship with population density will change in the future in a way that is not predictable from past patterns. Reliable quantitative predictions about population-level responses then need to be based on an explicit consideration of the evolutionary processes operating at the individual level. 6. Synthesis and applications. It is argued that evolutionary theory underpins Caughley’s declining-population paradigm, and that it needs to become much more widely used within mainstream conservation biology. This will help conservationists examine critically the reliability of the tools they have traditionally used to aid management decision-making. It will also give them access to alternative tools, particularly when predictions are required for changes in the environment that have not been experienced by a population in the past.

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1. The management of threatened species is an important practical way in which conservationists can intervene in the extinction process and reduce the loss of biodiversity. Understanding the causes of population declines (past, present and future) is pivotal to designing effective practical management. This is the declining-population paradigm identified by Caughley. 2. There are three broad classes of ecological tool used by conservationists to guide management decisions for threatened species: statistical models of habitat use, demographic models and behaviour-based models. Each of these is described here, illustrated with a case study and evaluated critically in terms of its practical application. 3. These tools are fundamentally different. Statistical models of habitat use and demographic models both use descriptions of patterns in abundance and demography, in relation to a range of factors, to inform management decisions. In contrast, behaviour-based models describe the evolutionary processes underlying these patterns, and derive such patterns from the strategies employed by individuals when competing for resources under a specific set of environmental conditions. 4. Statistical models of habitat use and demographic models have been used successfully to make management recommendations for declining populations. To do this, assumptions are made about population growth or vital rates that will apply when environmental conditions are restored, based on either past data collected under favourable environmental conditions or estimates of these parameters when the agent of decline is removed. As a result, they can only be used to make reliable quantitative predictions about future environments when a comparable environment has been experienced by the population of interest in the past. 5. Many future changes in the environment driven by management will not have been experienced by a population in the past. Under these circumstances, vital rates and their relationship with population density will change in the future in a way that is not predictable from past patterns. Reliable quantitative predictions about population-level responses then need to be based on an explicit consideration of the evolutionary processes operating at the individual level. 6. Synthesis and applications. It is argued that evolutionary theory underpins Caughley's declining-population paradigm, and that it needs to become much more widely used within mainstream conservation biology. This will help conservationists examine critically the reliability of the tools they have traditionally used to aid management decision-making. It will also give them access to alternative tools, particularly when predictions are required for changes in the environment that have not been experienced by a population in the past.

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An amorphous, catechol-based analogue of PEEK ("o-PEEK") has been prepared by a classical step-growth polymerization reaction between catechol and 4,4'-difluorobenzophenone and shown to be readily soluble in a range of organic solvents. Copolymers with p-PEEK have been investigated, including an amorphous 50: 50 composition and a semicrystalline though still organic-soluble material comprising 70% p-PEEK. o-PEEK has also been obtained by entropy-driven ring-opening polymerization of the macrocyclic oligomers (MCO's) formed by cyclo-condensation of catechol with 4,4'-difluorobenzophenone under pseudo-high-dilution conditions. The principal products of this latter reaction were the cyclic dimer 3a (20 wt %), cyclic trimer 3b (16%) cyclic tetramer 3c (14%), cyclic pentamer 3d (13%) and cyclic hexamer 3e (12%). Macrocycles 3a-c were isolated as pure compounds by gradient column chromatography, and the structures of the cyclic dimer 3a and cyclic tetramer 3c were analyzed by single-crystal X-ray diffraction. A mixture of MCO's, 3, of similar composition, was obtained by cyclodepolymerization of high molar mass o-PEEK in dilute soluion.

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Real estate development appraisal is a quantification of future expectations. The appraisal model relies upon the valuer/developer having an understanding of the future in terms of the future marketability of the completed development and the future cost of development. In some cases the developer has some degree of control over the possible variation in the variables, as with the cost of construction through the choice of specification. However, other variables, such as the sale price of the final product, are totally dependent upon the vagaries of the market at the completion date. To try to address the risk of a different outcome to the one expected (modelled) the developer will often carry out a sensitivity analysis on the development. However, traditional sensitivity analysis has generally only looked at the best and worst scenarios and has focused on the anticipated or expected outcomes. This does not take into account uncertainty and the range of outcomes that can happen. A fuller analysis should include examination of the uncertainties in each of the components of the appraisal and account for the appropriate distributions of the variables. Similarly, as many of the variables in the model are not independent, the variables need to be correlated. This requires a standardised approach and we suggest that the use of a generic forecasting software package, in this case Crystal Ball, allows the analyst to work with an existing development appraisal model set up in Excel (or other spreadsheet) and to work with a predetermined set of probability distributions. Without a full knowledge of risk, developers are unable to determine the anticipated level of return that should be sought to compensate for the risk. This model allows the user a better understanding of the possible outcomes for the development. Ultimately the final decision will be made relative to current expectations and current business constraints, but by assessing the upside and downside risks more appropriately, the decision maker should be better placed to make a more informed and “better”.

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Within the literature, many authors have argued that the rapid growth of the field of Information and Communication Technologies for Development (ICT4D) has resulted in an emphasis on the applications rather than on theory. However, it is clear that it is not theories, rather the integration of theory and practice, that is often lacking. To address this gap, the authors begin by exploring some of the popular theoretical approaches to ICT4D with a view to identifying those theories relevant to shared impacts: development, delivery and communication. To unify practice and theory, we offer a framework to directly assess the impact of ICT4D on development.

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Replacing grass silage with maize silage results in a fundamental change in the ratio of structural to non-structural carbohydrates with commensurate changes in rumen fermentation patterns and nutrient utilisation. This study investigated the effects of feeding four forage mixtures, namely grass silage (G); 67 g/100 g grass silage133 g/100 g maize silage (GGM); 67 g/100 g maize silage133/100 g grass silage (MMG); maize silage (M) to four ruminally and duodenally canulated Holstein Friesian steers. All diets were formulated to be isonitrogenous (22.4 g N/kg DM) using a concentrate mixture. Dietary dry matter (DM) and organic matter (OM) digestibility increased with ascending maize silage inclusion (P,0.1) whereas starch and neutral detergent fibre digestibility declined (P,0.05). Ratio of non-glucogenic to glucogenic precursors in the rumen fluid increased with maize silage inclusion (P,0.01) with a commensurate reduction in rumen pH (P,0.05). Mean circulating concentrations of insulin were greatest and similar in diets MMG and GGM, lower in diet M and lowest in diet G (P,0.01). There were no effects of diet on the mean circulating concentration of growth hormone (GH), or the frequency, amplitude and duration of GH pulses, or the mean circulating concentrations of IGF-1. Increasing levels of DM, OM and starch intakes with the substitution of grass silage with maize silage affected overall digestion, nutrient partitioning and subsequent circulating concentrations of insulin.