Opening Eyes to Opera: the process of translation for blind and partially-sighted audiences

In today’s rapidly developing digital age and increasingly socially-aware society, the notion of media accessibility is evolving in response to shifting audience expectations. Performing arts and media, such as opera, are called upon to include all audiences, and related audiovisual translation methods are progressing in this direction. These comprise audio description and touch tours for the blind and partially-sighted, two relatively new translation modalities which are consumer-oriented and require an original research design for the analysis of the translation processes involved. This research design follows two fundamental principles: (1) audience reception studies should be an integral part of the investigation into the translation process; and (2) the translation process is regarded as a network. Therefore, this chapter explores the unique translation processes of audio description and touch tours within the context of live opera from the perspective of actor-network theory and by providing an overview of a reception project. Through discussion of the methodology and findings, this chapter addresses the question of the impact of audience reception on the translation process.

Machine learning for transient discovery in Pan-STARRS1 difference imaging

Efficient identification and follow-up of astronomical transients is hindered by the need for humans to manually select promising candidates from data streams that contain many false positives. These artefacts arise in the difference images that are produced by most major ground-based time-domain surveys with large format CCD cameras. This dependence on humans to reject bogus detections is unsustainable for next generation all-sky surveys and significant effort is now being invested to solve the problem computationally. In this paper, we explore a simple machine learning approach to real-bogus classification by constructing a training set from the image data of similar to 32 000 real astrophysical transients and bogus detections from the Pan-STARRS1 Medium Deep Survey. We derive our feature representation from the pixel intensity values of a 20 x 20 pixel stamp around the centre of the candidates. This differs from previous work in that it works directly on the pixels rather than catalogued domain knowledge for feature design or selection. Three machine learning algorithms are trained (artificial neural networks, support vector machines and random forests) and their performances are tested on a held-out subset of 25 per cent of the training data. We find the best results from the random forest classifier and demonstrate that by accepting a false positive rate of 1 per cent, the classifier initially suggests a missed detection rate of around 10 per cent. However, we also find that a combination of bright star variability, nuclear transients and uncertainty in human labelling means that our best estimate of the missed detection rate is approximately 6 per cent.

Paediatricians' opinions of microneedle-mediated monitoring: a key stage in the translation of microneedle technology from laboratory into clinical practice

Microneedle (MN) arrays could offer an alternative method to traditional drug delivery and blood sampling methods. However, acceptance among key end-users is critical for new technologies to succeed. MNs have been advocated for use in children and so, paediatricians are key potential end-users. However, the opinions of paediatricians on MN use have been previously unexplored. The aim of this study was to investigate the views of UK paediatricians on the use of MN technology within neonatal and paediatric care. An online survey was developed and distributed among UK paediatricians to gain their opinions of MN technology and its use in the neonatal and paediatric care settings, particularly for MN-mediated monitoring. A total of 145 responses were obtained, with a completion response rate of 13.7 %. Respondents believed an alternative monitoring technique to blood sampling in children was required. Furthermore, 83 % of paediatricians believed there was a particular need in premature neonates. Overall, this potential end-user group approved of the MN technology and a MN-mediated monitoring approach. Minimal pain and the perceived ease of use were important elements in gaining favour. Concerns included the need for confirmation of correct application and the potential for skin irritation. The findings of this study provide an initial indication of MN acceptability among a key potential end-user group. Furthermore, the concerns identified present a challenge to those working within the MN field to provide solutions to further improve this technology. The work strengthens the rationale behind MN technology and facilitates the translation of MN technology from lab bench into the clinical setting.

Poem translation: 'How Many Shady Abodes'. Host publication: 'Il filo della vita-The thread of life-Snáithe na beatha' (ed. A. Gentili)

Poem

Slow Release Drug Dissolution Profile Prediction in Pharmaceutical Manufacturing: a Multivariate and Machine Learning Approach

Slow release drugs must be manufactured to meet target specifications with respect to dissolution curve profiles. In this paper we consider the problem of identifying the drivers of dissolution curve variability of a drug from historical manufacturing data. Several data sources are considered: raw material parameters, coating data, loss on drying and pellet size statistics. The methodology employed is to develop predictive models using LASSO, a powerful machine learning algorithm for regression with high-dimensional datasets. LASSO provides sparse solutions facilitating the identification of the most important causes of variability in the drug fabrication process. The proposed methodology is illustrated using manufacturing data for a slow release drug.

(223)Ra and other bone-targeting radiopharmaceuticals-the translation of radiation biology into clinical practice

Osseous metastases are a source of significant morbidity for patients with a variety of cancers. Radiotherapy is well established as an effective means of palliating symptoms associated with such metastases. The role of external beam radiotherapy is limited where sites of metastases are numerous and widespread. Low linear energy transfer (LET) radionuclides have been utilized to allow targeted delivery of radiotherapy to disparate sites of disease, with evidence of palliative benefit. More recently, the bone targeting, high LET radionuclide (223)Ra has been shown to not only have a palliative effect but also a survival prolonging effect in metastatic, castration-resistant prostate cancer with bone metastases. This article reviews the different radionuclide-based approaches for targeting bone metastases, with an emphasis on (223)Ra, and key elements of the underlying radiobiology of these that will impact their clinical effectiveness. Consideration is given to the remaining unknowns of both the basic radiobiological and applied clinical effects of (223)Ra as targets for future research.

Discrete Conditional Phase-type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a rare disease in which retinal blood vessels of premature infants fail to develop normally, and is one of the major causes of childhood blindness throughout the world. The Discrete Conditional Phase-type (DC-Ph) model consists of two components, the conditional component measuring the inter-relationships between covariates and the survival component which models the survival distribution using a Coxian phase-type distribution. This paper expands the DC-Ph models by introducing a support vector machine (SVM), in the role of the conditional component. The SVM is capable of classifying multiple outcomes and is used to identify the infant's risk of developing ROP. Class imbalance makes predicting rare events difficult. A new class decomposition technique, which deals with the problem of multiclass imbalance, is introduced. Based on the SVM classification, the length of stay in the neonatal ward is modelled using a 5, 8 or 9 phase Coxian distribution.

Translation as an Evaluative Concept

Testing the hypothesis that the concept of translation is evaluative rather than merely descriptive, Blumczyński analyses its increasingly popular use in three areas: political discourse, life writing and biomedical publications. He argues that translation as an evaluative concept is concerned with profound rather than superficial issues: to translate something is to assert its significance and value. At the same time, translation brings to the surface real and authentic things, producing its therapeutic value: it makes us more visible to ourselves, exposes pretences and thus brings relief. Finally, translation delivers on its own ethical imperative by breaking the spell of proverbial good intentions and bringing things to completion.

Translating Values:Evaluative Concepts in Translation

This collection explores the central importance of values and evaluative concepts in cross-cultural translational encounters. Written by a group of international scholars from a diverse range of linguistic and cultural backgrounds, the chapters in this book consider what it means to translate cultures by examining core values and their relationship to key evaluative concepts (such as authenticity, clarity, home, honour, or justice) and how they influence the complex multidimensional process of translation. This book will be of interest to academics studying cross-cultural and inter-linguistic interactions, to translators and interpreters, students of translation and of modern languages, and all those dealing with multilingual and multicultural settings.

Ubiquitous Translation

In this book, Piotr Blumczynski explores the central role of translation as a key epistemological concept as well as a hermeneutic, ethical, linguistic and interpersonal practice. His argument is three-fold: (1) that translation provides a basis for genuine, exciting, serious, innovative and meaningful exchange between various areas of the humanities through both a concept (the WHAT) and a method (the HOW); (2) that, in doing so, it questions and challenges many of the traditional boundaries and offers a transdisciplinary epistemological paradigm, leading to a new understanding of quality, and thus also meaning, truth, and knowledge; and (3) that translational phenomena are studied by a broad range of disciplines in the humanities (including philosophy, theology, linguistics, and anthropology) using various, often seemingly unrelated concepts which nevertheless display a considerable degree of qualitative proximity. The common thread running through all these convictions and binding them together is the insistence that translational phenomena are ubiquitous. Because of its unconventional and innovative approach, this book will be of interest to translation studies scholars looking to situate their research within a broader transdisciplinary model, as well as to students of translation programs and practicing translators who seek a fuller understanding of why and how translation matters.

The idea, the machine, and the art: word and image in the 21st century

Taking in recent advances in neuroscience and digital technology, Gander and Garland assess the state of the inter-arts in America and the Western world, exploring and questioning the primacy of affect in an increasingly hypertextual everyday environment. In this analysis they signal a move beyond W. J. T. Mitchell’s coinage of the ‘imagetext’ to an approach that centres the reader-viewer in a recognition, after John Dewey, of ‘art as experience’. New thinking in cognitive and computer sciences about the relationship between the body and the mind challenges any established definitions of ‘embodiment’, ‘materiality’, ‘virtuality’ and even ‘intelligence, they argue, whilst ‘Extended Mind Theory’, they note, marries our cognitive processes with the material forms with which we engage, confirming and complicating Marshall McLuhan’s insight, decades ago, that ‘all media are “extensions of man”’. In this chapter, Gander and Garland open paths and suggest directions into understandings and critical interpretations of new and emerging imagetext worlds and experiences.

Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine

The peptides derived from envelope proteins have been shown to inhibit the protein-protein interactions in the virus membrane fusion process and thus have a great potential to be developed into effective antiviral therapies. There are three types of envelope proteins each exhibiting distinct structure folds. Although the exact fusion mechanism remains elusive, it was suggested that the three classes of viral fusion proteins share a similar mechanism of membrane fusion. The common mechanism of action makes it possible to correlate the properties of self-derived peptide inhibitors with their activities. Here we developed a support vector machine model using sequence-based statistical scores of self-derived peptide inhibitors as input features to correlate with their activities. The model displayed 92% prediction accuracy with the Matthew’s correlation coefficient of 0.84, obviously superior to those using physicochemical properties and amino acid decomposition as input. The predictive support vector machine model for self- derived peptides of envelope proteins would be useful in development of antiviral peptide inhibitors targeting the virus fusion process.

Elastodynamic Modeling and Analysis for an Exechon Parallel Kinematic Machine

As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.