931 resultados para Generalized Shift Operator
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The performance of La(2-x)M(x)CuO(4) perovskites (where M = Ce, Ca or Sr) as catalysts for the water-gas shift reaction was investigated at 290 degrees C and 360 degrees C. The catalysts were characterized by EDS, XRD, N(2) adsorption-desorption, XPS and XANES. The XRD results showed that all the perovskites exhibited a single phase (the presence of perovskite structure), suggesting the incorporation of metals in the perovskite structure. The XPS and XANES results showed the presence of Cu(2+) on the surface. The perovskites that exhibited the best catalytic performance were La(2-x)Ce(x)CuO(4) perovslcites, with CO conversions of 85%-90%. Moreover, these perovskites have higher surface areas and larger amounts of Cu on the surface. And Ce has a higher filled energy level than the other metals, increasing the energy of the valence band of Ce and providing more electrons for the reaction. Besides, the La(1.80)Ca(0.20)CuO(4) perovskite showed a good catalytic performance.
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This paper describes an investigation on CuO and CuO-ZnO catalysts supported on CeO(2) and CeO(2)-La(2)O(3) oxides, which were designed for the low temperature water-gas shift reaction (WGSR). Bulk catalysts were prepared by co-precipitation of metal nitrates and characterized by energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD), surface area (by the BET method), X-ray photoelectron spectroscopy (XPS), and in situ X-ray absorption near edge structure (XANES). The catalysts` activities were tested in the forward WGSR, and the CuO/CeO(2) catalyst presented the best catalytic performance. The reasons for this are twofold: (1) the presence of Zn inhibits the interaction between Cu and Ce ions, and (2) lanthanum oxide forms a solid solution with cerium oxide, which will cause a decrease in the surface area of the catalysts. Also the CuO/CeO(2) catalyst presented the highest Cu content on the surface, which could influence its catalytic behavior. Additionally, the Cu and Cu(1+) species could influence the catalytic activity via a reduction-oxidation mechanism, corroborating to the best catalytic performance of the Cu/Ce catalyst. (c) 2010 Elsevier B.V. All rights reserved.
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This essay has investigated the question of an ongoing language shift from Plattdeutsch and German to Spanish among the Mennonites in Paraguay and the role of the school in this process. The aims of the study were to compare the use of languages among the Mennonites in Asuncion and in the Menno colony and to identify the importance that parents give to the languages and to compare this with a school leader perspective. The aim was also to identify factors that influence the language shift and identify the influence that the shift excerpts on Mennonite values and identity. The results are based on my own observations, interviews with Mennonite women and interviews with key informants who have insight into the school policy issues. The outcome may be used as a basis for educational and language planning. There is a need to consciously sit down and re-define the Mennonite identity and to make the community and the school aware of their responsibility in language maintenance.
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Detecting both the majors genes that control the phenotypic mean and those controlling phenotypic variance has been raised in quantitative trait loci analysis. In order to mapping both kinds of genes, we applied the idea of the classic Haley-Knott regression to double generalized linear models. We performed both kinds of quantitative trait loci detection for a Red Jungle Fowl x White Leghorn F2 intercross using double generalized linear models. It is shown that double generalized linear model is a proper and efficient approach for localizing variance-controlling genes. We compared two models with or without fixed sex effect and prefer including the sex effect in order to reduce the residual variances. We found that different genes might take effect on the body weight at different time as the chicken grows.
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The objective of this study has been to describe and analyse existing forms of organisation in heating plants using wood fuels, regarding work tasks, organisational structure, skill demands, crew recruitment, working hours and wage conditions. Sixteen plants ranging from 10 to 120 MW have been studied by means of interviews, work place observations and written material. The job of the operator of heating plants is fairly qualified, independent and varied. The most negative factor is shift work. Some of the bigger plants (enterprises) have a relatively hierarchic, segmented and perhaps also an oversized organisation. However, modern concepts of organisation, such as customer orientation, ”flat organisation”, integration of production and maintenance etc, are gaining ground. Blue collar and white collar tasks are increasingly being integrated. Some of the medium sized enterprises have reached very far and may serve as models for bigger enterprises.
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The objective of this study has been to describe and analyse existing forms of organisation in wood fuel plants regarding work tasks, organisational structure, work content, skill demands, crew recruitment, working hours and wage conditions. The study has been introductory, con¬sisting of 2-3 hour visits to 12 plants.The production of refined wood fuels is carried out in rather small plants. The number of employees ranges from 6 to 15 persons in the factories producing between 20 and 100 thousand tons per year. Generally one shift crew consists of only two persons. The operator job requires multiskill capacity, dexterity and autonomous problem-solving.The job can be considered as qualified, responsible, autonomous, meaningful and variable. It was generally considered that it takes about a year to become a good operator. And even after that, one is still learning. Negative factors are shift work, partly poor physical working environment (dust and noise) and, occasionally, mental pressure and overtime.Modern organisation concepts are, to a large extent, applied in the wood fuel plants. The organisation is flat, lean and customer-oriented.
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Igiogbe cultural heritage has existed since the founding of Bini kingdom without any controversy; however since the Supreme Court decision in Idehen v Idehen the issue of Igiogbe has assumed new dimensions. Igiogbe - the house in which a Benin man lived and died devolves on his first son absolutely; but since the beginning of 20th century litigation as to the real meaning of Igiogbe and who is entitled to inheritance thereof began to increase. Controversies and increase in litigation over Igiogbe has occasioned a shift in the practice, the Bini’s are not conscious of some of these changes, most of them (Bini’s) still claim Igiogbe practices is rigidly adhered to. This study on Igiogbe inheritance in Bini kingdom is therefore carried out with a view to bringing out the changes in Igiogbe cultural practice using legal and anthropological tools to examine the changes. While laying the foundation for the discussion on the main research object the researcher examined the origin and status of customary law in Nigeria. There after I examined Igiogbe inheritance in Bini kingdom. Igiogbe and the issue of first son were critically analyzed with the aid of the research questions bringing out the changes in Igiogbe concept from traditional practice to modern practice. Study shows Igiogbe practice is still relevant in modern Bini kingdom, however, the shift and changes in practice of this cultural milieu has lead me to ask some fundamental questions which I intend to answer in the broader research work in future.
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The Sustainability revolution: A societal paradigm shift – ethos, innovation, governance transformation This paper identifies several key mechanisms that underlie major paradigm shifts. After identifying four such mechanisms, the article focuses on one type of transformation which has a prominent place in the sustainability revolution that the article argues is now taking place. The transformation is piecemeal, incremental, diffuse – in earlier writings referred to as ”organic”. This is a more encompassing notion than grassroots, since the innovation and transformation processes may be launched and developed at multiple levels through diverse mechanisms of discovery and development. Major features of the sustainability revolution are identified and comparisons made to the industrial revolution.
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This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.
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Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.
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BACKGROUND AND OBJECTIVE: To a large extent, people who have suffered a stroke report unmet needs for rehabilitation. The purpose of this study was to explore aspects of rehabilitation provision that potentially contribute to self-reported met needs for rehabilitation 12 months after stroke with consideration also to severity of stroke. METHODS: The participants (n = 173) received care at the stroke units at the Karolinska University Hospital, Sweden. Using a questionnaire, the dependent variable, self-reported met needs for rehabilitation, was collected at 12 months after stroke. The independent variables were four aspects of rehabilitation provision based on data retrieved from registers and structured according to four aspects: amount of rehabilitation, service level (day care rehabilitation, primary care rehabilitation and home-based rehabilitation), operator level (physiotherapist, occupational therapist, speech therapist) and time after stroke onset. Multivariate logistic regression analyses regarding the aspects of rehabilitation were performed for the participants who were divided into three groups based on stroke severity at onset. RESULTS: Participants with moderate/severe stroke who had seen a physiotherapist at least once during each of the 1st, 2nd and 3rd-4th quarters of the first year (OR 8.36, CI 1.40-49.88 P = 0.020) were more likely to report met rehabilitation needs. CONCLUSION: For people with moderate/severe stroke, continuity in rehabilitation (preferably physiotherapy) during the first year after stroke seems to be associated with self-reported met needs for rehabilitation.
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We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.
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Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.