Understanding users and their needs

Gaze-control enables people to control a computer by using eye-gaze to select items on screen. Gaze-control is a necessity for people who have lost all motor control of their body and only have control over eye movements. In addition, gaze-control can be the quickest and least tiring option for a far broader group of people with varying disabilities. This paper reports findings from gaze-control user trials involving users from both groups: people who are totally paralyzed, as well as people with a wide range of complex disabilities. The trials conducted involved four different centres supporting people with disabilities in three different European countries. Several gaze-control systems were trialled by a large number of users with varying needs and abilities. The perceived benefits of gaze-control are described, and recommendations for successful assessment and implementation of gaze-control are provided.     

Multi-Stage Phase-Segregation of Mixed Halide Perovskites under Illumination: A Quantitative Comparison of Experimental Observations and Thermodynamic Models

Photo- and charge-carrier-induced ion migration is a major challenge when utilizing metal halide perovskite semiconductors for optoelectronic applications. For mixed iodide/bromide perovskites, the compositional instability due to light- or electrical bias induced phase-segregation restricts the exploitation of the entire bandgap range. Previous experimental and theoretical work suggests that excited states or charge carriers trigger the process, but the exact mechanism is still under debate. To identify the mechanism and cause of light-induced phase-segregation phenomena, the full compositional range of methylammonium lead bromide/iodide samples are investigated, MAPb(Br_xI_1-x)₃ with x = 0…1, by simultaneous in situ X-ray diffraction (XRD) and photoluminescence (PL) spectroscopy during illumination. The quantitative comparison of composition-dependent in situ XRD and PL shows that at excitation densities of 1 sun, only the initial stage of photo-segregation is rationalized with the previously established thermodynamic models. However, a progression of the phase segregation is observed that is rationalized by considering long-lived accumulative photo-induced material alterations. It is suggested that (additional) photo-induced defects, possibly halide vacancies and interstitials, need to be considered to fully rationalize light-induced phase segregation and anticipate the findings to provide crucial insight for the development of more sophisticated models.     

Covalent Adaptable Microstructures via Combining Two-Photon Laser Printing and Alkoxyamine Chemistry: Toward Living 3D Microstructures

Manufacturing programmable materials, whose mechanical properties can be adapted on demand, is highly desired for their application in areas ranging from robotics, to biomedicine, or microfluidics. Herein, the inclusion of dynamic and living bonds, such as alkoxyamines, in a printable formulation suitable for two-photon 3D laser printing is exploited. On one hand, taking advantage of the dynamic covalent character of alkoxyamines, the nitroxide exchange reaction is investigated. As a consequence, a reduction of the Young´s Modulus by 50%, is measured by nanoindentation. On the other hand, due to its “living” characteristic, the chain extension becomes possible via nitroxide mediated polymerization. In particular, living nitroxide mediated polymerization of styrene results not only in a dramatic increase of the volume (≈8 times) of the 3D printed microstructure but also an increase of the Young's Modulus by two orders of magnitude (from 14 MPa to 2.7 GPa), while maintaining the shape including fine structural details. Thus, the approach introduces a new dimension by enabling to create microstructures with dynamically tunable size and mechanical properties.     

Distance-based local linear regression for functional predictors

The problem of nonparametrically predicting a scalar response variable from a functional predictor is considered. A sample of pairs (functional predictor and response) is observed. When predicting the response for a new functional predictor value, a semi-metric is used to compute the distances between the new and the previously observed functional predictors. Then each pair in the original sample is weighted according to a decreasing function of these distances. A Weighted (Linear) Distance-Based Regression is fitted, where the weights are as above and the distances are given by a possibly different semi-metric. This approach can be extended to nonparametric predictions from other kinds of explanatory variables (e.g., data of mixed type) in a natural way.     

Simultaneous algorithm for trajectory planning

This paper addresses the solution of smooth trajectory planning for industrial robots in environments with obstacles using a direct method, creating the trajectory gradually as the robot moves. The presented method deals with the uncertainties associated with the lack of knowledge of kinematic properties of intermediate via‐points since they are generated as the algorithm evolves looking for the solution. Several cost functions are also proposed, which use the time that has been calculated to guide the robot motion. The method has been applied successfully to a PUMA 560 robot and four operational parameters (execution time, computational time, distance travelled and number of configurations) have been computed to study the properties and influence of each cost function on the trajectory obtained. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

To Score or Not to Score? Tripling Insights for Participatory Design

For evaluating visual-analytics tools, many studies confine to scoring user insights into data. For participatory design of those tools, we propose a three-level methodology to make more out of users' insights. The Relational Insight Organizer (RIO) helps to understand how insights emerge and build on one each other.     

Semantics-driven annotation of patient-specific 3D data: a step to assist diagnosis and treatment of rheumatoid arthritis

In the digital era, patient-specific 3D models (3D-PSMs) are becoming increasingly relevant in computer-assisted diagnosis, surgery training on digital models, or implant design. While advanced imaging and reconstruction techniques can create accurate and detailed 3D models of patients’ anatomy, software tools that are able to fully exploit the potential of 3D-PSMs are still far from being satisfactory. In particular, there is still a lack of integrated approaches for extracting, coding, sharing and retrieving medically relevant information from 3D-PSMs and use it concretely as a support to diagnosis and treatment. In this article, we propose the SemAnatomy3D framework, which demonstrates how the ontology-driven annotation of 3D-PSMs and of their anatomically relevant features (parts of relevance) can assist clinicians to document more effectively pathologies and their evolution. We exemplify the idea in the context of the diagnosis of rheumatoid arthritis of the hand district, and show how feature extraction tools and semantic 3D annotation can provide a rich characterization of anatomical landmarks (e.g., articular facets, prominent features, ligament attachments) and pathological markers (erosions, bone loss). The core contributions are an ontology-driven part-based annotation method for the 3D-PSMs and a novel automatic localization of erosion and quantification of the OMERACT RAMRIS erosion score. Finally, our results have been compared against a medical ground truth.