106 resultados para output convergence


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In this paper, we consider a two-sided space-fractional diffusion equation with variable coefficients on a finite domain. Firstly, based on the nodal basis functions, we present a new fractional finite volume method for the two-sided space-fractional diffusion equation and derive the implicit scheme and solve it in matrix form. Secondly, we prove the stability and convergence of the implicit fractional finite volume method and conclude that the method is unconditionally stable and convergent. Finally, some numerical examples are given to show the effectiveness of the new numerical method, and the results are in excellent agreement with theoretical analysis.

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Purpose To investigate the frequency of convergence and accommodation anomalies in an optometric clinical setting in Mashhad, Iran, and to determine tests with highest accuracy in diagnosing these anomalies. Methods From 261 patients who came to the optometric clinics of Mashhad University of Medical Sciences during a month, 83 of them were included in the study based on the inclusion criteria. Near point of convergence (NPC), near and distance heterophoria, monocular and binocular accommodative facility (MAF and BAF, respectively), lag of accommodation, positive and negative fusional vergences (PFV and NFV, respectively), AC/A ratio, relative accommodation, and amplitude of accommodation (AA) were measured to diagnose the convergence and accommodation anomalies. The results were also compared between symptomatic and asymptomatic patients. The accuracy of these tests was explored using sensitivity (S), specificity (Sp), and positive and negative likelihood ratios (LR+, LR−). Results Mean age of the patients was 21.3 ± 3.5 years and 14.5% of them had specific binocular and accommodative symptoms. Convergence and accommodative anomalies were found in 19.3% of the patients; accommodative excess (4.8%) and convergence insufficiency (3.6%) were the most common accommodative and convergence disorders, respectively. Symptomatic patients showed lower values for BAF (p = .003), MAF (p = .001), as well as AA (p = .001) compared with asymptomatic patients. Moreover, BAF (S = 75%, Sp = 62%) and MAF (S = 62%, Sp = 89%) were the most accurate tests for detecting accommodative and convergence disorders in terms of both sensitivity and specificity. Conclusions Convergence and accommodative anomalies are the most common binocular disorders in optometric patients. Including tests of monocular and binocular accommodative facility in routine eye examinations as accurate tests to diagnose these anomalies requires further investigation.

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Research question / issue This paper frames the debate on corporate governance convergence in terms of the morality underlying corporate governance models. The claims and arguments of moral relativism are presented to provide theoretical structure to the moral aspects of corporate governance convergence, and ultimately the normative question of whether convergence should occur. Research findings / insights: The morality underlying different models of corporate governance has largely been ignored in the corporate governance convergence literature. A range of moral philosophies and principles that underlie the dominant corporate governance models are identified. This leads to a consideration of the claims and arguments of moral relativism relating to corporate governance. A research agenda around the claims of Descriptive and Metaethical moral relativism, and which ultimately informs the associated normative argument, is then suggested. Theoretical / Academic implications The application of moral relativism to the debate on corporate governance convergence presents a theoretical structure to the analysis and consideration of its moral aspects. This structure lends itself to further research, both empirical and conceptual. Practitioner / Policy implications The claims and arguments of moral relativism provide a means of analysing calls that are made for a culturally or nationally ‘appropriate’ model of corporate governance. This can assist in providing direction for corporate governance reforms and is of particular relevance for developing countries which have inherited Western corporate governance models through colonialism.

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Particle Swarm Optimization (PSO) is a biologically inspired computational search and optimization method based on the social behaviors of birds flocking or fish schooling. Although, PSO is represented in solving many well-known numerical test problems, but it suffers from the premature convergence. A number of basic variations have been developed due to solve the premature convergence problem and improve quality of solution founded by the PSO. This study presents a comprehensive survey of the various PSO-based algorithms. As part of this survey, the authors have included a classification of the approaches and they have identify the main features of each proposal. In the last part of the study, some of the topics within this field that are considered as promising areas of future research are listed.

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We describe a design and fabrication method to enable simpler manufacturing of more efficient organic solar cell modules using a modified flat panel deposition technique. Many mini-cell pixels are individually connected to each other in parallel forming a macro-scale solar cell array. The pixel size of each array is optimized through experimentation to maximize the efficiency of the whole array. We demonstrate that integrated organic solar cell modules with a scalable current output can be fabricated in this fashion and can also be connected in series to generate a scalable voltage output.

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Tourism plays an important role in the development of Cook Islands. In this paper we examine the nexus between tourism and growth using quarterly data over the period 2009Q1–2014Q2 using the recently upgraded ARDL bounds test to cointegration tool, Microfit 5.01, which provides sample adjusted bounds and hence is more reliable for small sample size studies. We perform the cointegration using the ARDL bounds test and examine the direction of causality. Using visitor arrival and output in per capita terms as respective proxy for tourism development and growth, we examine the long-run association and report the elasticity coefficient of tourism and causality nexus, accordingly. Using unit root break tests, we note that 2011Q1 and 2011Q2 are two structural break periods in the output series. However, we note that this period is not statistically significant in the ARDL model and hence excluded from the estimation. Subsequently, the regression results show the two series are cointegrated. The long-run elasticity coefficient of tourism is estimated to be 0.83 and the short-run is 0.73. A bidirectional causality between tourism and income is noted for Cook Islands which indicates that tourism development and income mutually reinforce each other. In light of this, socio-economic policies need to focus on broad-based, inclusive and income-generating tourism development projects which are expected to have feedback effect.

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In order to progress beyond currently available medical devices and implants, the concept of tissue engineering has moved into the centre of biomedical research worldwide. The aim of this approach is not to replace damaged tissue with an implant or device but rather to prompt the patient's own tissue to enact a regenerative response by using a tissue-engineered construct to assemble new functional and healthy tissue. More recently, it has been suggested that the combination of Synthetic Biology and translational tissue-engineering techniques could enhance the field of personalized medicine, not only from a regenerative medicine perspective, but also to provide frontier technologies for building and transforming the research landscape in the field of in vitro and in vivo disease models.

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We propose an iterative estimating equations procedure for analysis of longitudinal data. We show that, under very mild conditions, the probability that the procedure converges at an exponential rate tends to one as the sample size increases to infinity. Furthermore, we show that the limiting estimator is consistent and asymptotically efficient, as expected. The method applies to semiparametric regression models with unspecified covariances among the observations. In the special case of linear models, the procedure reduces to iterative reweighted least squares. Finite sample performance of the procedure is studied by simulations, and compared with other methods. A numerical example from a medical study is considered to illustrate the application of the method.

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In this paper, we describe our investigation of the cointegration and causal relationships between energy consumption and economic output in Australia over a period of five decades. The framework used in this paper is the single-sector aggregate production function, which is the first comprehensive approach used in an Australian study of this type to include energy, capital and labour as separate inputs of production. The empirical evidence points to a cointegration relationship between energy and output and implies that energy is an important variable in the cointegration space, as are conventional inputs capital and labour. We also find some evidence of bidirectional causality between GDP and energy use. Although the evidence of causality from energy use to GDP was relatively weak when using the thermal aggregate of energy use, once energy consumption was adjusted for energy quality, we found strong evidence of Granger causality from energy use to GDP in Australia over the investigated period. The results are robust, irrespective of the assumptions of linear trends in the cointegration models, and are applicable for different econometric approaches.

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This paper investigates the cointegration and causal relationships between Information and Communication Technology (ICT) and economic output in Australia using data for about five decades. The framework used in this paper is the single-sector aggregate production function, which is the first comprehensive approach of this kind to include ICT and non-ICT capital and other factors to examine long-run Granger causality. The empirical evidence points to a cointegration relationship between ICT capital and output, and implies that ICT capital Granger causes economic output and multifactor productivity, as does non-ICT capital.

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The study investigates the long-run and dynamic relationships between energy consumption and output in Australia using a multivariate cointegration and causality framework. Using both Engle-Granger and Johansen cointegration approaches, the study finds that energy consumption and real Gross Domestic Product are cointegrated. The Granger causality tests suggest bidirectional Granger causality between energy consumption and real GDP, and Granger endogeineity in the system. Since the energy sector largely contributes to carbon emissions in Australia, we suggest that direct measures to reduce carbon by putting constraints on the energy consumption would pose significant economic costs for the Australian economy.

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This paper addresses an output feedback control problem for a class of networked control systems (NCSs) with a stochastic communication protocol. Under the scenario that only one sensor is allowed to obtain the communication access at each transmission instant, a stochastic communication protocol is first defined, where the communication access is modelled by a discrete-time Markov chain with partly unknown transition probabilities. Secondly, by use of a network-based output feedback control strategy and a time-delay division method, the closed-loop system is modeled as a stochastic system with multi time-varying delays, where the inherent characteristic of the network delay is well considered to improve the control performance. Then, based on the above constructed stochastic model, two sufficient conditions are derived for ensuring the mean-square stability and stabilization of the system under consideration. Finally, two examples are given to show the effectiveness of the proposed method.

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"The book brings together experts from Media and Communication Studies with Postcolonial Studies scholars to illustrate how the two fields may challenge and enrich each other. Its essays introduce readers to selected topics including »Media Convergence«, »Transcultural Subjectivity«, »Hegemony«, »Piracy« and »Media History and Colonialism«. Drawing on examples from film, literature, music, TV and the internet, the contributors investigate the transnational dimensions in today's media, engage with local and global media politics and discuss media outlets as economic agents, thus illustrating mechanisms of power in postcolonial and neo-colonial mediascapes."--Publisher website

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Despite positive testing in animal studies, more than 80% of novel drug candidates fail to proof their efficacy when tested in humans. This is primarily due to the use of preclinical models that are not able to recapitulate the physiological or pathological processes in humans. Hence, one of the key challenges in the field of translational medicine is to “make the model organism mouse more human.” To get answers to questions that would be prognostic of outcomes in human medicine, the mouse's genome can be altered in order to create a more permissive host that allows the engraftment of human cell systems. It has been shown in the past that these strategies can improve our understanding of tumor immunology. However, the translational benefits of these platforms have still to be proven. In the 21st century, several research groups and consortia around the world take up the challenge to improve our understanding of how to humanize the animal's genetic code, its cells and, based on tissue engineering principles, its extracellular microenvironment, its tissues, or entire organs with the ultimate goal to foster the translation of new therapeutic strategies from bench to bedside. This article provides an overview of the state of the art of humanized models of tumor immunology and highlights future developments in the field such as the application of tissue engineering and regenerative medicine strategies to further enhance humanized murine model systems.