Symmetry in European Regional Folk Dress: A Multidisciplinary Analysis

Leonardo ◽  
2020 ◽  
Vol 53 (2) ◽  
pp. 157-166
Author(s):  
David A. James ◽  
Alice V. James

Designs on folk dress form an expression of artistic import within a culture. A 2017 ethnomathematics paper to which the authors contributed concludes that the designs on European regional folk dress are highly symmetric and analyzes the symmetry in the costume designs of 73 European cultures. Also examined are which symmetries are favored by, for instance, Catholic cultures or mountain cultures. In this article, two of the study's coauthors summarize its key points and go on to explore the neurophysiologic, aesthetic and ethnographic reasons why humans display symmetry on their regional dress.

Author(s):  
Laura S. DeThorne ◽  
Kelly Searsmith

Purpose The purpose of this article is to address some common concerns associated with the neurodiversity paradigm and to offer related implications for service provision to school-age autistic students. In particular, we highlight the need to (a) view first-person autistic perspectives as an integral component of evidence-based practice, (b) use the individualized education plan as a means to actively address environmental contributions to communicative competence, and (c) center intervention around respect for autistic sociality and self-expression. We support these points with cross-disciplinary scholarship and writings from autistic individuals. Conclusions We recognize that school-based speech-language pathologists are bound by institutional constraints, such as eligibility determination and Individualized Education Program processes that are not inherently consistent with the neurodiversity paradigm. Consequently, we offer examples for implementing the neurodiversity paradigm while working within these existing structures. In sum, this article addresses key points of tension related to the neurodiversity paradigm in a way that we hope will directly translate into improved service provision for autistic students. Supplemental Material https://doi.org/10.23641/asha.13345727


Author(s):  
Michael O’Toole

In this article I examine aspects of the relationship between mothers and sons from an attachment perspective in an Irish context. Through the works of Irish writers such as Seamus Heaney, John McGahern, and Colm Tóibín, I focus on particular aspects of this relationship, which fails to support the developmental processes of separation and individuation in the many men who come to me for psychotherapy. I illustrate key points concerning this attachment dynamic through the use of clinical examples of my work with two men from my practice. While acknowledging that many other cultural factors play a significant role in the emotional development of children, integrating the work of our poets, novelists, and scholars with an attachment perspective


2007 ◽  
Vol 23 (2) ◽  
pp. 283-316 ◽  

This article examines some of the key points attributed to the Liberal Reform of 1857 as they appeared in the debate over immigration policy in Mexico from 1836 to 1855. It argues that many of the key provisions of reform that are attributed to the radical Liberals of 1857 were, in fact, part of a more broad-ranging and moderate debate for decades before. In this manner, immigration policy debates often served as a ““test balloon““for what would later be defined as the essential points of liberalism.


2020 ◽  
Vol 2020 (10) ◽  
pp. 181-1-181-7
Author(s):  
Takahiro Kudo ◽  
Takanori Fujisawa ◽  
Takuro Yamaguchi ◽  
Masaaki Ikehara

Image deconvolution has been an important issue recently. It has two kinds of approaches: non-blind and blind. Non-blind deconvolution is a classic problem of image deblurring, which assumes that the PSF is known and does not change universally in space. Recently, Convolutional Neural Network (CNN) has been used for non-blind deconvolution. Though CNNs can deal with complex changes for unknown images, some CNN-based conventional methods can only handle small PSFs and does not consider the use of large PSFs in the real world. In this paper we propose a non-blind deconvolution framework based on a CNN that can remove large scale ringing in a deblurred image. Our method has three key points. The first is that our network architecture is able to preserve both large and small features in the image. The second is that the training dataset is created to preserve the details. The third is that we extend the images to minimize the effects of large ringing on the image borders. In our experiments, we used three kinds of large PSFs and were able to observe high-precision results from our method both quantitatively and qualitatively.


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