923 resultados para variable power, cycle-run, stochastic cycling


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Bond graph is an apt modelling tool for any system working across multiple energy domains. Power electronics system modelling is usually the study of the interplay of energy in the domains of electrical, mechanical, magnetic and thermal. The usefulness of bond graph modelling in power electronic field has been realised by researchers. Consequently in the last couple of decades, there has been a steadily increasing effort in developing simulation tools for bond graph modelling that are specially suited for power electronic study. For modelling rotating magnetic fields in electromagnetic machine models, a support for vector variables is essential. Unfortunately, all bond graph simulation tools presently provide support only for scalar variables. We propose an approach to provide complex variable and vector support to bond graph such that it will enable modelling of polyphase electromagnetic and spatial vector systems. We also introduced a rotary gyrator element and use it along with the switched junction for developing the complex/vector variable's toolbox. This approach is implemented by developing a complex S-function tool box in Simulink inside a MATLAB environment This choice has been made so as to synthesise the speed of S-function, the user friendliness of Simulink and the popularity of MATLAB.

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Pseudo-marginal methods such as the grouped independence Metropolis-Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms have been introduced in the literature as an approach to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but suffers from poor mixing if it is too computationally intensive to obtain high-precision likelihood estimates. The MCWM algorithm has better mixing properties, but less theoretical support. In this paper we propose to use Gaussian processes (GP) to accelerate the GIMH method, whilst using a short pilot run of MCWM to train the GP. Our new method, GP-GIMH, is illustrated on simulated data from a stochastic volatility and a gene network model.

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1. Many organisms inhabit strongly fluctuating environments but their demography and population dynamics are often analysed using deterministic models and elasticity analysis, where elasticity is defined as the proportional change in population growth rate caused by a proportional change in a vital rate. Deterministic analyses may not necessarily be informative because large variation in a vital rate with a small deterministic elasticity may affect the population growth rate more than a small change in a less variable vital rate having high deterministic elasticity. 2. We analyse a stochastic environment model of the red kangaroo (Macropus rufus), a species inhabiting an environment characterized by unpredictable and highly variable rainfall, and calculate the elasticity of the stochastic growth rate with respect to the mean and variability in vital rates. 3. Juvenile survival is the most variable vital rate but a proportional change in the mean adult survival rate has a much stronger effect on the stochastic growth rate. 4. Even if changes in average rainfall have a larger impact on population growth rate, increased variability in rainfall may still be important also in long-lived species. The elasticity with respect to the standard deviation of rainfall is comparable to the mean elasticities of all vital rates but the survival in age class 3 because increased variation in rainfall affects both the mean and variability of vital rates. 5. Red kangaroos are harvested and, under the current rainfall pattern, an annual harvest fraction of c. 20% would yield a stochastic growth rate about unity. However, if average rainfall drops by more than c. 10%, any level of harvesting may be unsustainable, emphasizing the need for integrating climate change predictions in population management and increase our understanding of how environmental stochasticity translates into population growth rate.

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This paper demonstrates the application of inverse filtering technique for power systems. In order to implement this method, the control objective should be based on a system variable that needs to be set on a specific value for each sampling time. A control input is calculated to generate the desired output of the plant and the relationship between the two is used design an auto-regressive model. The auto-regressive model is converted to a moving average model to calculate the control input based on the future values of the desired output. Therefore, required future values to construct the output are predicted to generate the appropriate control input for the next sampling time.

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Seeds in the field experience wet-dry cycling that is akin to the well-studied commercial process of seed priming in which seeds are hydrated and then re-dried to standardise their germination characteristics. To investigate whether the persistence (defined as in situ longevity) and antioxidant capacity of seeds are influenced by wet-dry cycling, seeds of the global agronomic weed Avena sterilis ssp. ludoviciana were subjected to (1) controlled ageing at 60% relative humidity and 53.5°C for 31 days, (2) controlled ageing then priming, or (3) ageing in the field in three soils for 21 months. Changes in seed viability (total germination), mean germination time, seedling vigour (mean seedling length), and the concentrations of the glutathione (GSH) / glutathione disulphide (GSSG) redox couple were recorded over time. As controlled-aged seeds lost viability, GSH levels declined and the relative proportion of GSSG contributing to total glutathione increased, indicative of a failing antioxidant capacity. Subjecting seeds that were aged under controlled conditions to a wet-dry cycle (to −1 MPa) prevented viability loss and increased GSH levels. Field-aged seeds that underwent numerous wet-dry cycles due to natural rainfall maintained high viability and high GSH levels. Thus wet-dry cycles in the field may enhance seed longevity and persistence coincident with re-synthesis of protective compounds such as GSH.

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Syntheses of protein molecules in a cell are carried out by ribosomes.A ribosome can be regarded as a molecular motor which utilizes the input chemical energy to move on a messenger RNA (mRNA) track that also serves as a template for the polymerization of the corresponding protein. The forward movement, however, is characterized by an alternating sequence of translocation and pause. Using a quantitative model, which captures the mechanochemical cycle of an individual ribosome, we derive an exact analytical expression for the distribution of its dwell times at the successive positions on the mRNA track. Inverse of the average dwell time satisfies a Michaelis-Menten-type'' equation and is consistent with the general formula for the average velocity of a molecular motor with an unbranched mechanochemical cycle. Extending this formula appropriately, we also derive the exact force-velocity relation for a ribosome. Often many ribosomes each synthesizes a copy of the same protein. We extend the model of a single ribosome by incorporating steric exclusion of different individuals on the same track. We draw the phase diagram of this model of ribosome traffic in three-dimensional spaces spanned by experimentally controllable parameters. We suggest new experimental tests of our theoretical predictions.

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Enzyme is a dynamic entity with diverse time scales, ranging from picoseconds to seconds or even longer. Here we develop a rate theory for enzyme catalysis that includes conformational dynamics as cycling on a two-dimensional (2D) reaction free energy surface involving an intrinsic reaction coordinate (X) and an enzyme conformational coordinate (Q). The validity of Michaelis-Menten (MM) equation, i.e., substrate concentration dependence of enzymatic velocity, is examined under a nonequilibrium steady state. Under certain conditions, the classic MM equation holds but with generalized microscopic interpretations of kinetic parameters. However, under other conditions, our rate theory predicts either positive (sigmoidal-like) or negative (biphasic-like) kinetic cooperativity due to the modified effective 2D reaction pathway on X-Q surface, which can explain non-MM dependence previously observed on many monomeric enzymes that involve slow or hysteretic conformational transitions. Furthermore, we find that a slow conformational relaxation during product release could retain the enzyme in a favorable configuration, such that enzymatic turnover is dynamically accelerated at high substrate concentrations. The effect of such conformation retainment in a nonequilibrium steady state is evaluated.

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Inter-annual rainfall variability is a major challenge to sustainable and productive grazing management on rangelands. In Australia, rainfall variability is particularly pronounced and failure to manage appropriately leads to major economic loss and environmental degradation. Recommended strategies to manage sustainably include stocking at long-term carrying capacity (LTCC) or varying stock numbers with forage availability. These strategies are conceptually simple but difficult to implement, given the scale and spatial heterogeneity of grazing properties and the uncertainty of the climate. This paper presents learnings and insights from northern Australia gained from research and modelling on managing for rainfall variability. A method to objectively estimate LTCC in large, heterogeneous paddocks is discussed, and guidelines and tools to tactically adjust stocking rates are presented. The possible use of seasonal climate forecasts (SCF) in management is also considered. Results from a 13-year grazing trial in Queensland show that constant stocking at LTCC was far more profitable and largely maintained land condition compared with heavy stocking (HSR). Variable stocking (VAR) with or without the use of SCF was marginally more profitable, but income variability was greater and land condition poorer than constant stocking at LTCC. Two commercial scale trials in the Northern Territory with breeder cows highlighted the practical difficulties of variable stocking and provided evidence that heavier pasture utilisation rates depress reproductive performance. Simulation modelling across a range of regions in northern Australia also showed a decline in resource condition and profitability under heavy stocking rates. Modelling further suggested that the relative value of variable v. constant stocking depends on stocking rate and land condition. Importantly, variable stocking may possibly allow slightly higher stocking rates without pasture degradation. Enterprise-level simulations run for breeder herds nevertheless show that poor economic performance can occur under constant stocking and even under variable stocking in some circumstances. Modelling and research results both suggest that a form of constrained flexible stocking should be applied to manage for climate variability. Active adaptive management and research will be required as future climate changes make managing for rainfall variability increasingly challenging.

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In irrigated cropping, as with any other industry, profit and risk are inter-dependent. An increase in profit would normally coincide with an increase in risk, and this means that risk can be traded for profit. It is desirable to manage a farm so that it achieves the maximum possible profit for the desired level of risk. This paper identifies risk-efficient cropping strategies that allocate land and water between crop enterprises for a case study of an irrigated farm in Southern Queensland, Australia. This is achieved by applying stochastic frontier analysis to the output of a simulation experiment. The simulation experiment involved changes to the levels of business risk by systematically varying the crop sowing rules in a bioeconomic model of the case study farm. This model utilises the multi-field capability of the process based Agricultural Production System Simulator (APSIM) and is parameterised using data collected from interviews with a collaborating farmer. We found sowing rules that increased the farm area sown to cotton caused the greatest increase in risk-efficiency. Increasing maize area also improved risk-efficiency but to a lesser extent than cotton. Sowing rules that increased the areas sown to wheat reduced the risk-efficiency of the farm business. Sowing rules were identified that had the potential to improve the expected farm profit by ca. $50,000 Annually, without significantly increasing risk. The concept of the shadow price of risk is discussed and an expression is derived from the estimated frontier equation that quantifies the trade-off between profit and risk.

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This paper investigates the short-run effects of economic growth on carbon dioxide emissions from the combustion of fossil fuels and the manufacture of cement for 189 countries over the period 1961-2010. Contrary to what has previously been reported, we conclude that there is no strong evidence that the emissions-income elasticity is larger during individual years of economic expansion as compared to recession. Significant evidence of asymmetry emerges when effects over longer periods are considered. We find that economic growth tends to increase emissions not only in the same year, but also in subsequent years. Delayed effects - especially noticeable in the road transport sector - mean that emissions tend to grow more quickly after booms and more slowly after recessions. Emissions are more sensitive to fluctuations in industrial value added than agricultural value added, with services being an intermediate case. On the expenditure side, growth in consumption and growth in investment have similar implications for national emissions. External shocks have a relatively large emissions impact, and the short-run emissions-income elasticity does not appear to decline as incomes increase. Economic growth and emissions have been more tightly linked in fossil-fuel rich countries.

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The following problem is considered. Given the locations of the Central Processing Unit (ar;the terminals which have to communicate with it, to determine the number and locations of the concentrators and to assign the terminals to the concentrators in such a way that the total cost is minimized. There is alao a fixed cost associated with each concentrator. There is ail upper limit to the number of terminals which can be connected to a concentrator. The terminals can be connected directly to the CPU also In this paper it is assumed that the concentrators can bo located anywhere in the area A containing the CPU and the terminals. Then this becomes a multimodal optimization problem. In the proposed algorithm a stochastic automaton is used as a search device to locate the minimum of the multimodal cost function . The proposed algorithm involves the following. The area A containing the CPU and the terminals is divided into an arbitrary number of regions (say K). An approximate value for the number of concentrators is assumed (say m). The optimum number is determined by iteration later The m concentrators can be assigned to the K regions in (mk) ways (m > K) or (km) ways (K>m).(All possible assignments are feasible, i.e. a region can contain 0,1,…, to concentrators). Each possible assignment is assumed to represent a state of the stochastic variable structure automaton. To start with, all the states are assigned equal probabilities. At each stage of the search the automaton visits a state according to the current probability distribution. At each visit the automaton selects a 'point' inside that state with uniform probability. The cost associated with that point is calculated and the average cost of that state is updated. Then the probabilities of all the states are updated. The probabilities are taken to bo inversely proportional to the average cost of the states After a certain number of searches the search probabilities become stationary and the automaton visits a particular state again and again. Then the automaton is said to have converged to that state Then by conducting a local gradient search within that state the exact locations of the concentrators are determined This algorithm was applied to a set of test problems and the results were compared with those given by Cooper's (1964, 1967) EAC algorithm and on the average it was found that the proposed algorithm performs better.

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This thesis focuses on how elevated CO2 and/or O3 affect the below-ground processes in semi-natural vegetation, with an emphasis on greenhouse gases, N cycling and microbial communities. Meadow mesocosms mimicking lowland hay meadows in Jokioinen, SW Finland, were enclosed in open-top chambers and exposed to ambient and elevated levels of O3 (40-50 ppb) and/or CO2 (+100 ppm) for three consecutive growing season, while chamberless plots were used as chamber controls. Chemical and microbiological analyses as well as laboratory incubations of the mesocosm soils under different treatments were used to study the effects of O3 and/or CO2. Artificially constructed mesocosms were also compared with natural meadows with regards to GHG fluxes and soil characteristics. In addition to research conducted at the ecosystem level (i.e. the mesocosm study), soil microbial communities were also examined in a pot experiment with monocultures of individual species. By comparing mesocosms with similar natural plant assemblage, it was possible to demonstrate that artificial mesocosms simulated natural habitats, even though some differences were found in the CH4 oxidation rate, soil mineral N, and total C and N concentrations in the soil. After three growing seasons of fumigations, the fluxes of N2O, CH4, and CO2 were decreased in the NF+O3 treatment, and the soil NH4+-N and mineral N concentrations were lower in the NF+O3 treatment than in the NF control treatment. The mesocosm soil microbial communities were affected negatively by the NF+O3 treatment, as the total, bacterial, actinobacterial, and fungal PLFA biomasses as well as the fungal:bacterial biomass ratio decreased under elevated O3. In the pot survey, O3 decreased the total, bacterial, actinobacterial, and mycorrhizal PLFA biomasses in the bulk soil and affected the microbial community structure in the rhizosphere of L. pratensis, whereas the bulk soil and rhizosphere of the other monoculture, A. capillaris, remained unaffected by O3. Elevated CO2 caused only minor and insignificant changes in the GHG fluxes, N cycling, and the microbial community structure. In the present study, the below-ground processes were modified after three years of moderate O3 enhancement. A tentative conclusion is that a decrease in N availability may have feedback effects on plant growth and competition and affect the N cycling of the whole meadow ecosystem. Ecosystem level changes occur slowly, and multiplication of the responses might be expected in the long run.

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Boreal peatlands represent a considerable portion of the global carbon (C) pool. Water-level drawdown (WLD) causes peatland drying and induces a vegetation change, which affects the decomposition of soil organic matter and the release of greenhouse gases (CO2 and CH4). The objective of this thesis was to study the microbial communities related to the C cycle and their response to WLD in two boreal peatlands. Both sampling depth and site type had a strong impact on all microbial communities. In general, bacteria dominated the deeper layers of the nutrient-rich fen and the wettest surfaces of the nutrient-poor bog sites, whereas fungi seemed more abundant in the drier surfaces of the bog. WLD clearly affected the microbial communities but the effect was dependent on site type. The fungal and methane-oxidizing bacteria (MOB) community composition changed at all sites but the actinobacterial community response was apparent only in the fen after WLD. Microbial communities became more similar among sites after long-term WLD. Litter quality had a large impact on community composition, whereas the effects of site type and WLD were relatively minor. The decomposition rate of fresh organic matter was influenced slightly by actinobacteria, but not at all by fungi. Field respiration measurements in the northern fen indicated that WLD accelerates the decomposition of soil organic matter. In addition, a correlation between activity and certain fungal sequences indicated that community composition affects the decomposition of older organic matter in deeper peat layers. WLD had a negative impact on CH4 oxidation, especially in the oligotrophic fen. Fungal sequences were matched to taxa capable of utilizing a broad range of substrates. Most of the actinobacterial sequences could not be matched to characterized taxa in reference databases. This thesis represents the first investigation of microbial communities and their response to WLD among a variety of boreal peatland habitats. The results indicate that microbial community responses to WLD are complex but dependent on peatland type, litter quality, depth, and variable among microbes.

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Lakes are an important component of ecosystem carbon cycle through both organic carbon sequestration and carbon dioxide and methane emissions, although they cover only a small fraction of the Earth's surface area. Lake sediments are considered to be one of rather perma-nent sinks of carbon in boreal regions and furthermore, freshwater ecosystems process large amounts of carbon originating from terrestrial sources. These carbon fluxes are highly uncer-tain especially in the changing climate. -- The present study provides a large-scale view on carbon sources and fluxes in boreal lakes situated in different landscapes. We present carbon concentrations in water, pools in lake se-diments, and carbon gas (CO2 and CH4) fluxes from lakes. The study is based on spatially extensive and randomly selected Nordic Lake Survey (NLS) database with 874 lakes. The large database allows the identification of the various factors (lake size, climate, and catchment land use) determining lake water carbon concentrations, pools and gas fluxes in different types of lakes along a latitudinal gradient from 60oN to 69oN. Lakes in different landscapes vary in their carbon quantity and quality. Carbon (C) content (total organic and inorganic carbon) in lakes is highest in agriculture and peatland dominated areas. In peatland rich areas organic carbon dominated in lakes but in agricultural areas both organic and inorganic C concentrations were high. Total inorganic carbon in the lake water was strongly dependent on the bedrock and soil quality in the catchment, especially in areas where human influence in the catchment is low. In inhabited areas both agriculture and habitation in the catchment increase lake TIC concentrations, since in the disturbed soils both weathering and leaching are presumably more efficient than in pristine areas. TOC concentrations in lakes were related to either catchment sources, mainly peatlands, or to retention in the upper watercourses. Retention as a regulator of the TOC concentrations dominated in southern Finland, whereas the peatland sources were important in northern Finland. The homogeneous land use in the north and the restricted catchment sources of TOC contribute to the close relationship between peatlands and the TOC concentrations in the northern lakes. In southern Finland the more favorable climate for degradation and the multiple sources of TOC in the mixed land use highlight the importance of retention. Carbon processing was intensive in the small lakes. Both CO2 emission and the Holocene C pool in sediments per square meter of the lake area were highest in the smallest lakes. How-ever, because the total area of the small lakes on the areal level is limited, the large lakes are important units in C processing in the landscape. Both CO2 and CH4 concentrations and emissions were high in eutrophic lakes. High availability of nutrients and the fresh organic matter enhance degradation in these lakes. Eutrophic lakes are often small and shallow, enabling high contact between the water column and the sediment. At the landscape level, the lakes in agricultural areas are often eutrophic due to fertile soils and fertilization of the catchments, and therefore they also showed the highest CO2 and CH4 concentrations. Export from the catchments and in-lake degradation were suggested to be equally important sources of CO2 and CH4 in fall when the lake water column was intensively mixed and the transport of sub-stances from the catchment was high due to the rainy season. In the stagnant periods, especially in the winter, in-lake degradation as a gas source was highlighted due to minimal mixing and limited transport of C from the catchment. The strong relationship between the annual CO2 level of lakes and the annual precipitation suggests that climate change can have a major impact on C cycling in the catchments. Increase in precipitation enhances DOC export from the catchments and leads to increasing greenhouse gas emissions from lakes. The total annual CO2 emission from Finnish lakes was estimated to be 1400 Gg C a-1. The total lake sediment C pool in Finland was estimated to be 0.62 Pg, giving an annual sink in Finnish lakes of 65 Gg C a-1.

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Molecular motors are proteins that convert chemical energy into mechanical work. The viral packaging ATPase P4 is a hexameric molecular motor that translocates RNA into preformed viral capsids. P4 belongs to the ubiquitous class of hexameric helicases. Although its structure is known, the mechanism of RNA translocation remains elusive. Here we present a detailed kinetic study of nucleotide binding, hydrolysis, and product release by P4. We propose a stochastic-sequential cooperative model to describe the coordination of ATP hydrolysis within the hexamer. In this model the apparent cooperativity is a result of hydrolysis stimulation by ATP and RNA binding to neighboring subunits rather than cooperative nucleotide binding. Simultaneous interaction of neighboring subunits with RNA makes the otherwise random hydrolysis sequential and processive. Further, we use hydrogen/deuterium exchange detected by high resolution mass spectrometry to visualize P4 conformational dynamics during the catalytic cycle. Concerted changes of exchange kinetics reveal a cooperative unit that dynamically links ATP binding sites and the central RNA binding channel. The cooperative unit is compatible with the structure-based model in which translocation is effected by conformational changes of a limited protein region. Deuterium labeling also discloses the transition state associated with RNA loading which proceeds via opening of the hexameric ring. Hydrogen/deuterium exchange is further used to delineate the interactions of the P4 hexamer with the viral procapsid. P4 associates with the procapsid via its C-terminal face. The interactions stabilize subunit interfaces within the hexamer. The conformation of the virus-bound hexamer is more stable than the hexamer in solution, which is prone to spontaneous ring openings. We propose that the stabilization within the viral capsid increases the packaging processivity and confers selectivity during RNA loading. Finally, we use single molecule techniques to characterize P4 translocation along RNA. While the P4 hexamer encloses RNA topologically within the central channel, it diffuses randomly along the RNA. In the presence of ATP, unidirectional net movement is discernible in addition to the stochastic motion. The diffusion is hindered by activation energy barriers that depend on the nucleotide binding state. The results suggest that P4 employs an electrostatic clutch instead of cycling through stable, discrete, RNA binding states during translocation. Conformational changes coupled to ATP hydrolysis modify the electrostatic potential inside the central channel, which in turn biases RNA motion in one direction. Implications of the P4 model for other hexameric molecular motors are discussed.