Bare-handed 3D drawing in augmented reality

Head-mounted augmented reality (AR) enables embodied in situ drawing in three dimensions (3D).We explore 3D drawing interactions based on uninstrumented, unencumbered (bare) hands that preserve the user’s ability to freely navigate and interact with the physical environment. We derive three alternative interaction techniques supporting bare-handed drawing in AR from the literature and by analysing several envisaged use cases. The three interaction techniques are evaluated in a controlled user study examining three distinct drawing tasks: planar drawing, path description, and 3D object reconstruction. The results indicate that continuous freehand drawing supports faster line creation than the control point-based alternatives, although with reduced accuracy. User preferences for the different techniques are mixed and vary considerably between the different tasks, highlighting the value of diverse and flexible interactions. The combined effectiveness of these three drawing techniques is illustrated in an example application of 3D AR drawing

Crowdsourcing interface feature design with Bayesian optimization

Designing novel interfaces is challenging. Designers typically rely on experience or subjective judgment in the absence of analytical or objective means for selecting interface parameters. We demonstrate Bayesian optimization as an efficient tool for objective interface feature refinement. Specifically, we show that crowdsourcing paired with Bayesian optimization can rapidly and effectively assist interface design across diverse deployment environments. Experiment 1 evaluates the approach on a familiar 2D interface design problem: a map search and review use case. Adding a degree of complexity, Experiment 2 extends Experiment 1 by switching the deployment environment to mobile-based virtual reality. The approach is then demonstrated as a case study for a fundamentally new and unfamiliar interaction design problem: web-based augmented reality. Finally, we show how the model generated as an outcome of the refinement process can be used for user simulation and queried to deliver various design insights

Fast and precise touch-based text entry for head-mounted augmented reality with variable occlusion

We present the VISAR keyboard: An augmented reality (AR) head-mounted display (HMD) system that supports text entry via a virtualised input surface. Users select keys on the virtual keyboard by imitating the process of single-hand typing on a physical touchscreen display. Our system uses a statistical decoder to infer users’ intended text and to provide error-tolerant predictions. There is also a high-precision fall-back mechanism to support users in indicating which keys should be unmodified by the auto-correction process. A unique advantage of leveraging the well-established touch input paradigm is that our system enables text entry with minimal visual clutter on the see-through display, thus preserving the user’s field-of-view. We iteratively designed and evaluated our system and show that the final iteration of the system supports a mean entry rate of 17.75wpm with a mean character error rate less than 1%. This performance represents a 19.6% improvement relative to the state-of-the-art baseline investigated: A gaze-then-gesture text entry technique derived from the system keyboard on the Microsoft HoloLens. Finally, we validate that the system is effective in supporting text entry in a fully mobile usage scenario likely to be encountered in industrial applications of AR HMDs.Per Ola Kristensson was supported in part by a Google Faculty research award and EPSRC grants EP/N010558/1 and EP/N014278/1. Keith Vertanen was supported in part by a Google Faculty research award. John Dudley was supported by the Trimble Fund

Performance Envelopes of In-Air Direct and Smartwatch Indirect Control for Head-Mounted Augmented Reality

The scarcity of established input methods for augmented reality (AR) head-mounted displays (HMD) motivates us to investigate the performance envelopes of two easily realisable solutions: indirect cursor control via a smartwatch and direct control by in-air touch. Indirect cursor control via a smartwatch has not been previously investigated for AR HMDs. We evaluate these two techniques in three fundamental user interface actions: target acquisition, goal crossing, and circular steering. We find that in-air is faster than smartwatch (p<0.001) for target acquisition and circular steering. We observe, however, that in-air selection can lead to discomfort after extended use and suggest that smartwatch control offers a complementary alternative.This work was supported by EPSRC (grant number EP/N010558/1) and the Trimble Fund. Part of this work was conducted within the Transregional Collaborative Research Centre SFB/TRR 62 Companion-Technology of Cognitive Technical Systems funded by the German Research Foundation (DFG)

A Review of User Interface Design for Interactive Machine Learning

Interactive Machine Learning (IML) seeks to complement human perception and intelligence by tightly integrating these strengths with the computational power and speed of computers. The interactive process is designed to involve input from the user but does not require the background knowledge or experience that might be necessary to work with more traditional machine learning techniques. Under the IML process, non-experts can apply their domain knowledge and insight over otherwise unwieldy datasets to find patterns of interest or develop complex data driven applications. This process is co-adaptive in nature and relies on careful management of the interaction between human and machine. User interface design is fundamental to the success of this approach, yet there is a lack of consolidated principles on how such an interface should be implemented. This article presents a detailed review and characterisation of Interactive Machine Learning from an interactive systems perspective. We propose and describe a structural and behavioural model of a generalised IML system and identify solution principles for building effective interfaces for IML. Where possible, these emergent solution principles are contextualised by reference to the broader human-computer interaction literature. Finally, we identify strands of user interface research key to unlocking more efficient and productive non-expert interactive machine learning applications

The Parametric Inverse Problem in Transient Scattering

Scattering problems in many areas of applied physics are governed by the wave equation. In the most usual situation, we are given the incident wave (input) and the scatterer(s) and attempt, through analytical, experimental, or numerical methods, to produce the scattered waves (output). Such procedures can be carried out in either the frequency domain or the time domain and are categorized under the general heading of “forward problems.” In a less usual, but no less important situation, we are given the incident wave (input) and the scattered waves (output) and attempt to find the scatterer(s) that produced the output. In this case, we call the procedures “inverse” problems

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

Drilling their own graves:How the European oil and gas supermajors avoid sustainability tensions through mythmaking

This study explores how paradoxical tensions between economic growth and environmental protection are avoided through organizational mythmaking. By examining the European oil and gas supermajors’ ‘‘CEOspeak’’ about climate change, we show how mythmaking facilitates the disregarding, diverting, and/or displacing of sustainability tensions. In doing so, our findings further illustrate how certain defensive responses are employed: (1) regression, or retreating to the comforts of past familiarities, (2) fantasy, or escaping the harsh reality that fossil fuels and climate change are indeed irreconcilable, and (3) projecting, or shifting blame to external actors for failing to address climate change. By highlighting the discursive effects of enacting these responses, we illustrate how the European oil and gas supermajors self-determine their inability to substantively address the complexities of climate change. We thus argue that defensive responses are not merely a form of mismanagement as the paradox and corporate sustainability literature commonly suggests, but a strategic resource that poses serious ethical concerns given the imminent danger of issues such as climate change

Tocolytic effect of a selective FP receptor antagonist in rodent models reveals an innovative approach to the treatment of preterm labor

<p>Abstract</p> <p>Background</p> <p>Management of preterm labor by tocolysis remains an unmet medical need. Prostaglandins play a major role in regulation of uterine activity and in molecular mechanisms of human labor and parturition. There is some circumstantial evidence that prostaglandin F2α by action through the prostaglandin receptor subtype FP is effective in key events during labor uterine contraction, rupture of membranes and cervical dilation. This role of FP is briefly reviewed. In this study, we tested the hypothesis that an orally active and selective FP antagonist may arrest labor and delay parturition in animal models.</p> <p>Methods</p> <p>We examined the effects of a small molecule selective antagonist of the FP receptor (AS604872) in inhibition of spontaneous uterine contraction in pregnant rat near term. We tested AS604872 for its ability to delay preterm birth in a mouse model in which the anti-progestin agent RU486 triggered parturition.</p> <p>Results</p> <p>By oral or intravenous dosing AS604872 reduced markedly and dose-dependently the spontaneous uterine contractions in late-term pregnant rats at gestational days 19–21. In pregnant mice, AS604872 delayed the preterm birth caused by RU486 administration. The effect was dose-dependent with a significant increase in the mean delivery time of 16 and 33 hours at oral doses of 30 mg/kg and 100 mg/kg, respectively, in the case of labor triggered at gestational day 14. In both models AS604872 appeared more effective than the β-agonist ritodrine.</p> <p>Conclusion</p> <p>The tocolytic activity displayed by a selective FP receptor antagonist supports a key role for the FP receptor in the pathophysiology of premature birth and demonstrates the therapeutic potential of an FP antagonist for the treatment of preterm labor cases in which uterine hyperactivity plays a dominant role.</p

Single Gene Deletions of Orexin, Leptin, Neuropeptide Y, and Ghrelin Do Not Appreciably Alter Food Anticipatory Activity in Mice

Timing activity to match resource availability is a widely conserved ability in nature. Scheduled feeding of a limited amount of food induces increased activity prior to feeding time in animals as diverse as fish and rodents. Typically, food anticipatory activity (FAA) involves temporally restricting unlimited food access (RF) to several hours in the middle of the light cycle, which is a time of day when rodents are not normally active. We compared this model to calorie restriction (CR), giving the mice 60% of their normal daily calorie intake at the same time each day. Measurement of body temperature and home cage behaviors suggests that the RF and CR models are very similar but CR has the advantage of a clearly defined food intake and more stable mean body temperature. Using the CR model, we then attempted to verify the published result that orexin deletion diminishes food anticipatory activity (FAA) but observed little to no diminution in the response to CR and, surprisingly, that orexin KO mice are refractory to body weight loss on a CR diet. Next we tested the orexigenic neuropeptide Y (NPY) and ghrelin and the anorexigenic hormone, leptin, using mouse mutants. NPY deletion did not alter the behavior or physiological response to CR. Leptin deletion impaired FAA in terms of some activity measures, such as walking and rearing, but did not substantially diminish hanging behavior preceding feeding time, suggesting that leptin knockout mice do anticipate daily meal time but do not manifest the full spectrum of activities that typify FAA. Ghrelin knockout mice do not have impaired FAA on a CR diet. Collectively, these results suggest that the individual hormones and neuropepetides tested do not regulate FAA by acting individually but this does not rule out the possibility of their concerted action in mediating FAA