Object Manipulation in Virtual Reality Under Increasing Levels of Translational Gain

Room-scale Virtual Reality (VR) has become an affordable consumer reality, with applications ranging from entertainment to productivity. However, the limited physical space available for room-scale VR in the typical home or office environment poses a significant problem. To solve this, physical spaces can be extended by amplifying the mapping of physical to virtual movement (translational gain). Although amplified movement has been used since the earliest days of VR, little is known about how it influences reach-based interactions with virtual objects, now a standard feature of consumer VR. Consequently, this paper explores the picking and placing of virtual objects in VR for the first time, with translational gains of between 1x (a one-to-one mapping of a 3.5m*3.5m virtual space to the same sized physical space) and 3x (10.5m*10.5m virtual mapped to 3.5m*3.5m physical). Results show that reaching accuracy is maintained for up to 2x gain, however going beyond this diminishes accuracy and increases simulator sickness and perceived workload. We suggest gain levels of 1.5x to 1.75x can be utilized without compromising the usability of a VR task, significantly expanding the bounds of interactive room-scale VR

Fire Alters Plant Microbiome Assembly Patterns: Integrating the Plant and Soil Microbial Response to Disturbance

It is increasingly evident that the plant microbiome is a strong determinant of plant health. While the ability to manipulate the microbiome in plants and ecosystems recovering from disturbance may be useful, our understanding of the plant microbiome in regenerating plant communities is currently limited. Using 16S ribosomal RNA (rRNA) gene and internal transcribed spacer (ITS) region amplicon sequencing, we characterized the leaf, stem, fine root, rhizome, and rhizosphere microbiome of \u3c 1-yr-old aspen saplings and the associated bulk soil after a recent high-intensity prescribed fire across a burn severity gradient. Consistent with previous studies, we found that soil microbiomes are responsive to fire. We extend these findings by showing that certain plant tissue microbiomes also change in response to fire. Differences in soil microbiome compositions could be attributed to soil chemical characteristics, but, generally, plant tissue microbiomes were not related to plant tissue elemental concentrations. Using source tracking modeling, we also show that fire influences the relative dominance of microbial inoculum and the vertical inheritance of the sapling microbiome from the parent tree. Overall, our results demonstrate how fire impacts plant microbiome assembly, diversity, and composition and highlights potential for further research towards increasing plant fitness and ecosystem recovery after fire events

Methods for specifying the target difference in a randomised controlled trial : the Difference ELicitation in TriAls (DELTA) systematic review

Peer reviewedPublisher PD

Compared to conventional, ecological intensive management promotes beneficial proteolytic soil microbial communities for agro-ecosystem functioning under climate change-induced rain regimes

Projected climate change and rainfall variability will affect soil microbial communities, biogeochemical cycling and agriculture. Nitrogen (N) is the most limiting nutrient in agroecosystems and its cycling and availability is highly dependent on microbial driven processes. In agroecosystems, hydrolysis of organic nitrogen (N) is an important step in controlling soil N availability. We analyzed the effect of management (ecological intensive vs. conventional intensive) on N-cycling processes and involved microbial communities under climate change-induced rain regimes. Terrestrial model ecosystems originating from agroecosystems across Europe were subjected to four different rain regimes for 263 days. Using structural equation modelling we identified direct impacts of rain regimes on N-cycling processes, whereas N-related microbial communities were more resistant. In addition to rain regimes, management indirectly affected N-cycling processes via modifications of N-related microbial community composition. Ecological intensive management promoted a beneficial N-related microbial community composition involved in N-cycling processes under climate change-induced rain regimes. Exploratory analyses identified phosphorus-associated litter properties as possible drivers for the observed management effects on N-related microbial community composition. This work provides novel insights into mechanisms controlling agro-ecosystem functioning under climate change

Design of Experiments for Screening

The aim of this paper is to review methods of designing screening experiments, ranging from designs originally developed for physical experiments to those especially tailored to experiments on numerical models. The strengths and weaknesses of the various designs for screening variables in numerical models are discussed. First, classes of factorial designs for experiments to estimate main effects and interactions through a linear statistical model are described, specifically regular and nonregular fractional factorial designs, supersaturated designs and systematic fractional replicate designs. Generic issues of aliasing, bias and cancellation of factorial effects are discussed. Second, group screening experiments are considered including factorial group screening and sequential bifurcation. Third, random sampling plans are discussed including Latin hypercube sampling and sampling plans to estimate elementary effects. Fourth, a variety of modelling methods commonly employed with screening designs are briefly described. Finally, a novel study demonstrates six screening methods on two frequently-used exemplars, and their performances are compared

Colorectal Cancer Video for the Deaf Community: A Randomized Control Trial

The Deaf community experiences multiple barriers to accessing cancer information. Deaf participants (n = 144) were randomly assigned to view a colorectal cancer education video or another program in American Sign Language. They completed surveys pre- and post-intervention and at 2 months post-intervention. By using a crossover model, control group participants were offered the option of seeing the intervention video. The experimental group gained and retained significantly more colorectal cancer knowledge than the control group, and the control group demonstrated the greatest knowledge gain after crossing into the experimental arm. This video effectively informed the Deaf community about colorectal cancer

Children's vomiting following posterior fossa surgery: A retrospective study

<p>Abstract</p> <p>Background</p> <p>Nausea and vomiting is a problem for children after neurosurgery and those requiring posterior fossa procedures appear to have a high incidence. This clinical observation has not been quantified nor have risk factors unique to this group of children been elucidated.</p> <p>Methods</p> <p>A six year retrospective chart audit at two Canadian children's hospitals was conducted. The incidence of nausea and vomiting was extracted. Hierarchical multivariable logistic regression was used to quantify risk and protective factors at 120 hours after surgery and early vs. late vomiting.</p> <p>Results</p> <p>The incidence of vomiting over a ten day postoperative period was 76.7%. Documented vomiting ranged from single events to greater than 20 over the same period. In the final multivariable model: adolescents (age 12 to <17) were less likely to vomit by 120 hours after surgery than other age groups; those who received desflurane, when compared to all other volatile anesthetics, were more likely to vomit, yet the use of ondansetron with desflurane decre kelihood. Children who had intraoperative ondansetron were more likely to vomit in the final multivariable model (perhaps because of its use, in the clinical judgment of the anesthesiologist, for children considered at risk). Children who started vomiting in the first 24 hours were more likely to be school age (groups 4 to <7 and 7 to <12) and receive desflurane. Nausea was not well documented and was therefore not analyzed.</p> <p>Conclusion</p> <p>The incidence of vomiting in children after posterior fossa surgery is sufficient to consider all children requiring these procedures to be at high risk for POV. Nausea requires better assessment and documentation.</p

Speaker Sex Perception from Spontaneous and Volitional Nonverbal Vocalizations.

In two experiments, we explore how speaker sex recognition is affected by vocal flexibility, introduced by volitional and spontaneous vocalizations. In Experiment 1, participants judged speaker sex from two spontaneous vocalizations, laughter and crying, and volitionally produced vowels. Striking effects of speaker sex emerged: For male vocalizations, listeners' performance was significantly impaired for spontaneous vocalizations (laughter and crying) compared to a volitional baseline (repeated vowels), a pattern that was also reflected in longer reaction times for spontaneous vocalizations. Further, performance was less accurate for laughter than crying. For female vocalizations, a different pattern emerged. In Experiment 2, we largely replicated the findings of Experiment 1 using spontaneous laughter, volitional laughter and (volitional) vowels: here, performance for male vocalizations was impaired for spontaneous laughter compared to both volitional laughter and vowels, providing further evidence that differences in volitional control over vocal production may modulate our ability to accurately perceive speaker sex from vocal signals. For both experiments, acoustic analyses showed relationships between stimulus fundamental frequency (F0) and the participants' responses. The higher the F0 of a vocal signal, the more likely listeners were to perceive a vocalization as being produced by a female speaker, an effect that was more pronounced for vocalizations produced by males. We discuss the results in terms of the availability of salient acoustic cues across different vocalizations

Effect of within-session breaks in play on responsible gambling behaviour during sustained monetary losses

Rapid, continuous gambling formats are associated with higher risks for gambling-related harm in terms of excessive monetary and time expenditure. The current study investigated the effect on gambling response latency and persistence, of a new form of within-game intervention that required players to actively engage in response inhibition via monitoring for stop signals. Seventy-four experienced electronic gaming machine gamblers, with a mean age of 35.28 years, were recruited to participate in a rapid, continuous gambling task where real money could be won and lost. Participants were randomly allocated to either the control condition where no intervention was presented, or either a condition with a passive three minute break in play or a condition with a three minute intervention that required participants to engage in response inhibition. Although there was no main effect for experimental condition on gambling persistence, both interventions were effective in elevating response latency during a period of sustained losses. It was concluded that within-game interventions that create an enforced break in play are effective in increasing response latency between bets during periods of sustained losses. Furthermore, within-game interventions that require active involvement appear to be more effective in increasing response latency than standard, passive breaks in play

Predicting sample size required for classification performance

<p>Abstract</p> <p>Background</p> <p>Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target.</p> <p>Methods</p> <p>We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method.</p> <p>Results</p> <p>A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p < 0.05).</p> <p>Conclusions</p> <p>This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.</p