3,549 research outputs found

    Author Attributions in Medieval Text Collections: An Exploration

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    This article examines the role and function of author attributions in multi-text manuscripts containing Dutch, English, French or German short verse narratives. The findings represent one strand of the investigations undertaken by the cross-European project ‘The Dynamics of the Medieval Manuscript’, which analysed the dissemination of short verse narratives and the principles of organisation underlying the compilation of text collections. Whilst short verse narratives are more commonly disseminated anonymously, there are manuscripts in which authorship is repeatedly attributed to a text or corpus. Through six case studies, this article explores medieval concepts of authorship and how they relate to constructions of authority, whether regarding an empirical figure or a literary construction. In addition, it looks at how authorship plays a role in manuscript compilation, and at the effects of attributions (by author and/or compiler) on reception. The case studies include manuscripts from the thirteenth to fifteenth centuries, produced in a range of social and cultural contexts, and featuring some of the most important European authors of short verse narratives: Rutebeuf, Baudouin de Condé, Der Striker, Konrad von Würzberg, Willem of Hildegaersberch, and Geoffrey Chaucer. The preliminary findings contribute to our understanding of author attributions in text collections from across northern Europe and point towards future lines of enquiry into the role of authorship in medieval textual dissemination

    Neuroprotection against apoptosis of SK-N-MC cells using RMP-7- and lactoferrin-grafted liposomes carrying quercetin

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    Yung-Chih Kuo, Chien-Wei Tsao Department of Chemical Engineering, National Chung Cheng University, Chia-Yi, Taiwan, Republic of China Abstract: A drug delivery system of quercetin (QU)-encapsulated liposomes (LS) grafted with RMP-7, a bradykinin analog, and lactoferrin (Lf) was developed to permeate the blood–brain barrier (BBB) and rescue degenerated neurons, acting as an Alzheimer’s disease (AD) pharmacotherapy. This colloidal formulation of QU-encapsulated LS grafted with RMP-7 and Lf (RMP-7-Lf-QU-LS) was used to traverse human brain microvascular endothelial cells (HBMECs) regulated by human astrocytes (HAs) and to treat SK-N-MC cells after an insult with cytotoxic β-amyloid (Aβ) fibrils. We found that surface RMP-7 and Lf enhanced the ability of QU to cross the BBB without inducing strong toxicity and damaging the tight junction. In addition, RMP-7-Lf-QU-LS significantly reduced Aβ-induced neurotoxicity and improved the viability of SK-N-MC cells. Compared with free QU, RMP-7-Lf-QU-LS could also significantly inhibit the expression of phosphorylated c-Jun N terminal kinase, phosphorylated p38, and phosphorylated tau protein at serine 202 by SK-N-MC cells, indicating an important role of RMP-7, Lf, and LS in protecting neurons against apoptosis. RMP-7-Lf-QU-LS is a promising carrier targeting the BBB to prevent Aβ-insulted neurodegeneration and may have potential in managing AD in future clinical applications. Keywords: Alzheimer’s disease, blood–brain barrier, β-amyloid, drug targeting, neurodegeneration, pharmacotherap

    Batch Bayesian Learning of Large-Scale LS-SVMs Based on Low-rank Tensor Networks

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    Least Squares Support Vector Machines (LS-SVMs) are state-of-the-art learning algorithms that have been widely used for pattern recognition. The solution for an LS-SVM is found by solving a system of linear equations, which involves the computational complexity of O(N^3). When datasets get larger, solving LS-SVM problems with standard methods becomes burdensome or even unfeasible. The Tensor Train (TT) decomposition provides an approach to representing data in highly compressed formats without loss of accuracy. By converting vectors and matrices in the TT format, the storage and computational requirements can be greatly reduced. In this thesis, we develop a Bayesian learning method in the TT format to solve large-scale LS-SVM problems, which involves the computation of a matrix inverse. This method allows us to include the information we know about the model parameters in the prior distribution. As a result, we are able to obtain a probability distribution of the parameters, which enables us to construct confidence levels of the predictions. In the numerical experiment, we show that the developed method performs competitively with the current methods.Mechanical Engineering | Systems and Contro

    Additive Manufacturing: Polymers Applicable for Laser Sintering (LS)

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    AbstractAdditive Manufacturing (AM) is close to become a production technique changing the way of part fabrication in future. Enhanced complexity and personalized features are aimed. The expectations in AM for the future are enormous and betimes it is considered as kind of the next industrial revolution. Laser Sintering (LS) of polymer powders is one component of the AM production techniques. However materials successfully applicable to Laser Sintering (LS) are very limited today. The presentation picks up this topic and gives a short introduction on the material available today. Important factors of polymer powders, their significance for effective LS processing and analytical approaches to access those values are presented in the main part. Concurrently the exceptional position of polyamide 12 powders is this connection is outlined

    The Social Cost-of-Living: Welfare Foundations and Estimation

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    We present a new class of social cost-of-living indices and a nonparametric framework for estimating these and other social cost-of- living indices. Common social cost-of-living indices can be understood as aggregator functions of approximations of individual cost-of-living indices. The Consumer Price Index (CPI) is the expenditure-weighted average of first-order approximations of each individual’s cost-of-living index. This is troubling for three reasons. First, it has not been shown to have a welfare economic foundation for the case where agents are heterogeneous (as they clearly are.) Second, it uses an expenditure-weighted average which downweights the experience of poor households relative to rich households. Finally, it uses only first-order approximations of each individual’s cost-of-living index, and thus ignores substitution effects. We propose a “common-scaling” social cost-of-living index, which is defined as the single scaling to everyone’s expenditure which holds social welfare constant across a price change. Our approach has an explicit social welfare foundation and allows us to choose the weights on the costs of rich and poor households. We also give a unique solution for the welfare function for the case where the weights are independent of household expenditure. A first order approximation of our social cost-of- living index nests as special cases commonly used indices such as the CPI. We also provide a nonparametric method for estimating second- order approximations (which account for substitution effects).Inflation, Social cost-of-living, Demand, Average Derivatives

    The Social Cost-of-Living: Welfare Foundations and Estimation

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    We present a new class of social cost-of-living indices and a nonparametric framework for estimating these and other social cost-of-living indices. Common social cost-of-living indices can be understood as aggregator functions of approximations of individual cost-of-living indices. The Consumer Price Index (CPI) is the expenditure-weighted average of first-order approximations of each individual’s cost-of-living index. This is troubling for three reasons. First, it has not been shown to have a welfare economic foundation for the case where agents are heterogeneous (as they clearly are.) Second, it uses an expenditure-weighted average which downweights the experience of poor households relative to rich households. Finally, it uses only first-order approximations of each individual’s cost-of-living index, and thus ignores substitution effects. We propose a “common-scaling” social cost-of-living index, which is defined as the single scaling to everyone’s expenditure which holds social welfare constant across a price change. Our approach has an explicit social welfare foundation and allows us to choose the weights on the costs of rich and poor households. We also give a unique solution for the welfare function for the case where the weights are independent of household expenditure. A first order approximation of our social cost-of-living index nests as special cases commonly used indices such as the CPI. We also provide a nonparametric method for estimating second-order approximations (which account for substitution effects).Inflation, Social cost-of-living, Demand, Average derivatives

    Tell us our story: Understanding 'religion and violence' in multiple contexts of learning

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    This article raises the question about how definitions of religion and violence can be understood as links to the context in which they are formulated. The focus is on the context of academic learning. Understanding a definition as a micro-narrative that reflects the cultural 'archive', the author uses two academic contexts (i.e. Utrecht, The Netherlands and Jakarta, Indonesia) to show how religion and violence are differently understood. These differences are taken as significant information for understanding how the topic of 'religion and violence' is related to cultural understandings of the place of religion in society. The question is raised how 'narrative learning' can help as a strategy to raise awareness about the preconditioning of (academic) definitions of 'religion and violence'
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