Conceptual Design and Workspace Analysis of an Exechon-inspired Parallel Kinematic Machine

Inspired by the commercial application of the Exechon machine, this paper proposed a novel parallel kinematic machine (PKM) named Exe-Variant. By exchanging the sequence of kinematic pairs in each limb of the Exechon machine, the Exe-Variant PKM claims an arrangement of 2UPR/1SPR topology and consists of two identical UPR limbs and one SPR limb. The inverse kinematics of the 2UPR/1SPR parallel mechanism was firstly analyzed based on which a conceptual design of the Exe-Variant was carried out. Then an algorithm of reachable workspace searching for the Exe-Variant and the Exchon was proposed. Finally, the workspaces of two example systems of the Exechon and the Exe-Variant with approximate dimensions were numerically simulated and compared. The comparison shows that the Exe-Variant possesses a competitive workspace with the Exechon machine, indicating it can be used as a promising reconfigurable module in a hybrid 5-DOF machine tool system.

Stiffness Analysis and Experiment of a Novel 5-DoF Parallel Kinematic Machine Considering Gravitational Effects

In order to carry out high-precision machining of aerospace structural components with large size, thin wall and complex surface, this paper proposes a novel parallel kinematic machine (PKM) and formulates its semi-analytical theoretical stiffness model considering gravitational effects that is verified by stiffness experiments. From the viewpoint of topology structure, the novel PKM consists of two substructures in terms of the redundant and overconstrained parallel mechanisms that are connected by two interlinked revolute joints. The theoretical stiffness model of the novel PKM is established based upon the virtual work principle and deformation superposition principle after mapping the stiffness models of substructures from joint space to operated space by Jacobian matrices and considering the deformation contributions of interlinked revolute joints to two substructures. Meanwhile, the component gravities are treated as external payloads exerting on the end reference point of the novel PKM resorting to static equivalence principle. This approach is proved by comparing the theoretical stiffness values with experimental stiffness values in the same configurations, which also indicates equivalent gravity can be employed to describe the actual distributed gravities in an acceptable accuracy manner. Finally, on the basis of the verified theoretical stiffness model, the stiffness distributions of the novel PKM are illustrated and the contributions of component gravities to the stiffness of the novel PKM are discussed.

Ab initio diffusional potential energy surface for CO chemisorption on Pd{110} at high coverage:Coupled translation and rotation

The ground state potential energy surface for CO chemisorption across Pd{110} has been calculated using density functional theory with gradient corrections at monolayer coverage. The most stable site corresponds well with the experimental adsorption heat, and it is found that the strength of binding to sites is in the following order: pseudo-short-bridge>atop>long-bridge>hollow. Pathways and transition states for CO surface diffusion, involving a correlation between translation and orientation, are proposed and discussed. (C) 1997 American Institute of Physics.

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 paper 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 paper addresses the question of the impact of audience reception on the translation process.

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.