Cross-cultural Theatre Education: Rehearsals and Performance. English as Lingua Franca, rewriting process, and poly-glottal text in psycho-physical acting practice

At Copenhagen International School of Performing Arts, English is the Lingua Franca (ELF) of artistic exploration. With a non-conformist approach to the use of ELF, highlighting a body-mind insight into the language over correctness, a latent, expressive potential of ELF is explored through a psycho-physical training. The predominant technique is Movement Psychology (Laban/Malmgren), which examines the interdependence between, on the one hand, text, language, and narrative and, on the other, the embodiment of the Jungian unconscious.The paper analyses the process and the methods of staging the production entitled Re: ORESTES, based on Mee’s play Orestes 2.0, applying the described methodological exploration. The play was rewritten and remoulded by the performers throughout a rehearsal process, which focused on interlacing the performers’ highly diverse cultural horizons (Gadamer) in a common mega-text, in an attempt to fuse the familiar with the alien, the personal with the collective, and to channel, shape and articulate the material within ELF.The paper details two different examples of this transformative remoulding process. One actor wrote a completely new text, which was performed in the heightened style of "the Queen’s English". Another actor performed a part in a poly-glottal combination of Ancient and Modern Greek (her mother tongue) and ELF. In this process, both performers sought to transcend the preconceived limitations of their individual cultural horizons as well as of the English language

If it looks like a duck, swims like a duck, and quacks like a duck — does it have to be a duck?

[Extract] Case Presentation On 2nd July 2013, a 29-year-old HIV-positive woman presented herself to the outpatient clinic at the Infectious Diseases Institute in Kampala, Uganda. Her weight had decreased from 46 kg to 42 kg in the past few weeks. In addition, she complained about abdominal pain, diarrhea, vomiting, and evening fevers during the week leading up to her visit (see Table 1 and Fig 1 for patient characteristics). Her CD4 T cell count in June 2013 was 34 cells/μl, and she had documented second-line antiretroviral treatment (tenofovir disoproxil fumarate, emtricitabine, and lopinavir-ritonavir) failure. She admitted to taking her medications irregularly and was on trimethoprim-sulfamethoxazole prophylaxis. Her last HIV-1 RNA viral load in June 2013 was 199,994 copies/ml. Based on her immunosuppression and symptoms, we screened her for tuberculosis (TB). At the time of screening, she could not produce sputum, but an abdominal ultrasound in late June 2013 showed a lymphadenopathy. A chest X-ray was not carried out at baseline, as it would not have changed the clinical decision to treat the presumptive diagnosis of extrapulmonary TB. Her glomerular filtration rate (GFR) was 55 mL/min, the liver enzyme alanine aminotransferase was 33 IU/L (normal range 0–35 IU/L), and her albumin level was slightly decreased (35.5 g/L; normal range 38–47 g/L)

Autoencoder Based Iterative Modeling and Multivariate Time-Series Subsequence Clustering Algorithm

This paper introduces an algorithm for the detection of change-points and the identification of the corresponding subsequences in transient multivariate time-series data (MTSD). The analysis of such data has become more and more important due to the increase of availability in many industrial fields. Labeling, sorting or filtering highly transient measurement data for training condition based maintenance (CbM) models is cumbersome and error-prone. For some applications it can be sufficient to filter measurements by simple thresholds or finding change-points based on changes in mean value and variation. But a robust diagnosis of a component within a component group for example, which has a complex non-linear correlation between multiple sensor values, a simple approach would not be feasible. No meaningful and coherent measurement data which could be used for training a CbM model would emerge. Therefore, we introduce an algorithm which uses a recurrent neural network (RNN) based Autoencoder (AE) which is iteratively trained on incoming data. The scoring function uses the reconstruction error and latent space information. A model of the identified subsequence is saved and used for recognition of repeating subsequences as well as fast offline clustering. For evaluation, we propose a new similarity measure based on the curvature for a more intuitive time-series subsequence clustering metric. A comparison with seven other state-of-the-art algorithms and eight datasets shows the capability and the increased performance of our algorithm to cluster MTSD online and offline in conjunction with mechatronic systems.Comment: 26 pages, 11 figures, for associated python code repositories see https://github.com/Jokonu/mt3scm and https://github.com/Jokonu/abimca; Minor spelling and grammar corrections, fixed wrong bibtex entry for SOStream, some improvements and corrections in formulas of section

Who Needs Agglomeration? Varying Agglomeration Externalities and the Industry Life Cycle

In this paper, the changing roles of agglomeration externalities during different stages of the industry life cycle are investigated. A central argument is that agglomeration externalities vary with mode of competition, innovation intensity, and characteristics of learning opportunities in industries. Following the Industry Life Cycle perspective, we distinguish between young and mature industries, and investigate how these benefit from MAR, Jacobs’ and Urbanization externalities. The empirical analysis builds on a Swedish plant level dataset that covers the period of 1974-2004.The outcomes of panel data regression models show that the benefits industries derive from their local environment are strongly associated with their stage in the industry life cycle. Whereas MAR externalities increase with the maturity of industries, Jacobs’ externalities decline when industries are more mature. This is in line with the hypothesis that young industries operate in an environment dominated by rapid product innovation and low levels of standardization. Hence, it pays off when knowledge can be sourced locally from many different sources, but there is still little scope for specialization benefits. Mature industries, in contrast, are associated with lower innovation intensities and a focus on cost saving process innovations. Therefore, there are major benefits to be derived from specialization, whereas knowledge spillovers from different industries are less relevant. The distinction between the product competition in young industries and price competition in mature industries is reflected in our finding that high regional factor costs are detrimental to mature industries, but not to young industries. This can also be related to the finding that high quality living environments, attractive for highly paid employees, are important to young industries. Overall, the outcomes stress that industrial life cycles have to be taken into account in the analysis of agglomeration externalities.agglomeration externalities, industry life cycle, urbanization, Sweden

Development of an instrument to assess early number concept development in four South African languages

A recently published interview-based test, known by its partly German acronym, MARKO-D SA, is introduced in this article by way of a narrative of its development through various cycles of research. The 48-item test, in 4 South African languages, captures number concept development of children in the 6 to 8-year age group. The authors present their argument for the South African versioning and translation of the test for this country, where there is a dearth of suitable assessment instruments for gauging young children’s mathematical concept development. We also present the findings of the research that was conducted to standardise and norm the local version of the test, along with our reasoning about the theoretical strength of the conceptual model that undergirds the test

Correspondence problems in computer vision : novel models, numerics, and applications

Correspondence problems like optic flow belong to the fundamental problems in computer vision. Here, one aims at finding correspondences between the pixels in two (or more) images. The correspondences are described by a displacement vector field that is often found by minimising an energy (cost) function. In this thesis, we present several contributions to the energy-based solution of correspondence problems: (i) We start by developing a robust data term with a high degree of invariance under illumination changes. Then, we design an anisotropic smoothness term that works complementary to the data term, thereby avoiding undesirable interference. Additionally, we propose a simple method for determining the optimal balance between the two terms. (ii) When discretising image derivatives that occur in our continuous models, we show that adapting one-sided upwind discretisations from the field of hyperbolic differential equations can be beneficial. To ensure a fast solution of the nonlinear system of equations that arises when minimising the energy, we use the recent fast explicit diffusion (FED) solver in an explicit gradient descent scheme. (iii) Finally, we present a novel application of modern optic flow methods where we align exposure series used in high dynamic range (HDR) imaging. Furthermore, we show how the alignment information can be used in a joint super-resolution and HDR method.Korrespondenzprobleme wie der optische Fluß, gehören zu den fundamentalen Problemen im Bereich des maschinellen Sehens (Computer Vision). Hierbei ist das Ziel, Korrespondenzen zwischen den Pixeln in zwei (oder mehreren) Bildern zu finden. Die Korrespondenzen werden durch ein Verschiebungsvektorfeld beschrieben, welches oft durch Minimierung einer Energiefunktion (Kostenfunktion) gefunden wird. In dieser Arbeit stellen wir mehrere Beiträge zur energiebasierten Lösung von Korrespondenzproblemen vor: (i) Wir beginnen mit der Entwicklung eines robusten Datenterms, der ein hohes Maß an Invarianz unter Beleuchtungsänderungen aufweißt. Danach entwickeln wir einen anisotropen Glattheitsterm, der komplementär zu dem Datenterm wirkt und deshalb keine unerwünschten Interferenzen erzeugt. Zusätzlich schlagen wir eine einfache Methode vor, die es erlaubt die optimale Balance zwischen den beiden Termen zu bestimmen. (ii) Im Zuge der Diskretisierung von Bildableitungen, die in unseren kontinuierlichen Modellen auftauchen, zeigen wir dass es hilfreich sein kann, einseitige upwind Diskretisierungen aus dem Bereich hyperbolischer Differentialgleichungen zu übernehmen. Um eine schnelle Lösung des nichtlinearen Gleichungssystems, dass bei der Minimierung der Energie auftaucht, zu gewährleisten, nutzen wir den kürzlich vorgestellten fast explicit diffusion (FED) Löser im Rahmen eines expliziten Gradientenabstiegsschemas. (iii) Schließlich stellen wir eine neue Anwendung von modernen optischen Flußmethoden vor, bei der Belichtungsreihen für high dynamic range (HDR) Bildgebung registriert werden. Außerdem zeigen wir, wie diese Registrierungsinformation in einer kombinierten super-resolution und HDR Methode genutzt werden kann

Can momentum correlations proof kinetic equilibration in heavy ion collisions at 160/A-GeV?

We perform an event-by-event analysis of the transverse momentum distribution of final state particles in central Pb(160AGeV)+Pb collisions within a microscopic non-equilibrium transport model (UrQMD). Strong influence of rescattering is found. The extracted momentum distributions show less fluctuations in A+A collisions than in p+p reactions. This is in contrast to simplified p+p extrapolations and random walk models