REM sleep deprivation during 5 hours leads to an immediate REM sleep rebound and to suppression of non-REM sleep intensity

Nine healthy male subjects were deprived of REM sleep during the first 5 h after sleep onset. Afterwards recovery sleep was undisturbed. During the deprivation period the non-REM EEG power spectrum was reduced when compared to baseline for the frequencies up to 7 Hz, despite the fact that non-REM sleep was not experimentally disturbed. During the recovery interval a significant rebound of REM sleep was observed, which was only accompanied by a very slight increase of power in the lower non-REM EEG frequencies. In order to control for intermittent wakefulness, the same subjects were subjected to non-REM sleep interruption during the first 5 h after sleep onset 2 weeks later. Again subsequent recovery sleep was undisturbed. The interventions resulted in a similar amount of wakefulness in both conditions. During the intervention period, the non-REM EEG power spectrum was only marginally reduced in the delta frequency range. REM sleep duration was only slightly reduced. During the recovery interval, however, a substantial increase in EEG power in the delta frequency range was noted, without notable changes in REM time. It is concluded that an increased pressure for REM sleep results in longer REM episodes and a reduced intensity of non-REM sleep.

Controlling the Gaze of Conversational Agents

We report on a pilot experiment that investigated the effects of different eye gaze behaviours of a cartoon-like talking face on the quality of human-agent dialogues. We compared a version of the talking face that roughly implements some patterns of human-like behaviour with\ud two other versions. In one of the other versions the shifts in gaze were kept minimal and in the other version the shifts would occur randomly. The talking face has a number of restrictions. There is no speech recognition, so questions and replies have to be typed in by the users\ud of the systems. Despite this restriction we found that participants that conversed with the agent that behaved according to the human-like patterns appreciated the agent better than participants that conversed with the other agents. Conversations with the optimal version also\ud proceeded more efficiently. Participants needed less time to complete their task

Experimenting with the Gaze of a Conversational Agent

We have carried out a pilot experiment to investigate the effects of different eye gaze behaviors of a cartoon-like talking face on the quality of human-agent dialogues. We compared a version of the talking face that roughly implements some patterns of humanlike behavior with two other versions. We called this the optimal version. In one of the other versions the shifts in gaze were kept minimal and in the other version the shifts would occur randomly. The talking face has a number of restrictions. There is no speech recognition, so questions and replies have to\ud be typed in by the users of the systems. Despite this restriction we found that participants that conversed with the optimal agent appreciated the agent more than participants that conversed with the other agents. Conversations with the optimal version proceeded more efficiently. Participants needed less time to complete their task

New Interactions with Workflow Systems

This paper describes the evaluation of our early design ideas of an ad-hoc of workflow system. Using the teach-back technique, we have performed a hermeneutic analysis of the mockup implementation named NIWS to get corrective and creative feedback at the functional, dialogue and representation level of the new workflow system

Sticks, balls or a ribbon? Results of a formative user study with bioinformaticians

User interfaces in modern bioinformatics tools are designed for experts. They are too complicated for\ud novice users such as bench biologists. This report presents the full results of a formative user study as part of a\ud domain and requirements analysis to enhance user interfaces and collaborative environments for\ud multidisciplinary teamwork. Contextual field observations, questionnaires and interviews with bioinformatics\ud researchers of different levels of expertise and various backgrounds were performed in order to gain insight into\ud their needs and working practices. The analysed results are presented as a user profile description and user\ud requirements for designing user interfaces that support the collaboration of multidisciplinary research teams in\ud scientific collaborative environments. Although the number of participants limits the generalisability of the\ud findings, the combination of recurrent observations with other user analysis techniques in real-life settings\ud makes the contribution of this user study novel

Climate and terrain factors explaining streamflow response and recession in Australian catchments

Daily streamflow data were analysed to assess which climate and terrain factors best explain streamflow response in 183 Australian catchments. Assessed descriptors of catchment response included the parameters of fitted baseflow models, and baseflow index (BFI), average quick flow and average baseflow derived by baseflow separation. The variation in response between catchments was compared with indicators of catchment climate, morphology, geology, soils and land use. Spatial coherence in the residual unexplained variation was investigated using semi-variogram techniques. A linear reservoir model (one parameter; recession coefficient) produced baseflow estimates as good as those obtained using a non-linear reservoir (two parameters) and for practical purposes was therefore considered an appropriate balance between simplicity and explanatory performance. About a third (27–34%) of the spatial variation in recession coefficients and BFI was explained by catchment climate indicators, with another 53% of variation being spatially correlated over distances of 100–150 km, probably indicative of substrate characteristics not captured by the available soil and geology data. The shortest recession half-times occurred in the driest catchments and were attributed to intermittent occurrence of fast-draining (possibly perched) groundwater. Most (70–84%) of the variation in average baseflow and quick flow was explained by rainfall and climate characteristics; another 20% of variation was spatially correlated over distances of 300–700 km, possibly reflecting a combination of terrain and climate factors. It is concluded that catchment streamflow response can be predicted quite well on the basis of catchment climate alone. The prediction of baseflow recession response should be improved further if relevant substrate properties were identified and measured

Selection of an appropriately simple storm runoff model

An appropriately simple event runoff model for catchment hydrological studies was derived. The model was selected from several variants as having the optimum balance between simplicity and the ability to explain daily observations of streamflow from 260 Australian catchments (23–1902 km<sup>2</sup>). Event rainfall and runoff were estimated from the observations through a combination of baseflow separation and storm flow recession analysis, producing a storm flow recession coefficient (<i>k</i><sub>QF</sub>). Various model structures with up to six free parameters were investigated, covering most of the equations applied in existing lumped catchment models. The performance of alternative structures and free parameters were expressed in Aikake's Final Prediction Error Criterion (FPEC) and corresponding Nash-Sutcliffe model efficiencies (NSME) for event runoff totals. For each model variant, the number of free parameters was reduced in steps based on calculated parameter sensitivity. The resulting optimal model structure had two or three free parameters; the first describing the non-linear relationship between event rainfall and runoff (<i>S</i><sub>max</sub>), the second relating runoff to antecedent groundwater storage (<i>C</i><sub>Sg</sub>), and a third that described initial rainfall losses (<i>L</i><sub>i</sub>), but which could be set at 8 mm without affecting model performance too much. The best three parameter model produced a median NSME of 0.64 and outperformed, for example, the Soil Conservation Service Curve Number technique (median NSME 0.30–0.41). Parameter estimation in ungauged catchments is likely to be challenging: 64% of the variance in <i>k</i><sub>QF</sub> among stations could be explained by catchment climate indicators and spatial correlation, but corresponding numbers were a modest 45% for <i>C</i><sub>Sg</sub>, 21% for <i>S</i><sub>max</sub> and none for <i>L</i><sub>i</sub>, respectively. In gauged catchments, better estimates of event rainfall depth and intensity are likely prerequisites to further improve model performance

Self-rated health and employment status in patients with multiple sclerosis

Purpose. The aim is to explore the association between self-rated health and employment status in patients with multiple sclerosis (MS) when controlling for age, gender, functional disability, disease duration, anxiety and depression. Method. One hundred eighty-four people with MS completed a sociodemographic questionnaire that included questions on employment status, the first item of the Short Form-36 Health Survey and the Hospital Anxiety and Depression Scale. Functional disability was assessed using the Expanded Disability Status Scale. The probability of good self-rated health in employed persons was investigated using stepwise logistic regression analyses. Results. Patients with MS who reported good self-rated health were 2.46 times more likely to be employed (95% confidence interval [CI]: 1.08-5.59). Patients without anxiety were 2.64 times more likely to be employed (95% CI: 1.23-5.67). Patients with higher EDSS scores were 0.49 times less likely to be employed (95% CI: 0.33-0.70). Age, gender, disease duration and the presence of depression did not show an increased chance of patient employment. Conclusions. Patients with MS with good self-rated health are more likely to be employed, even after adjusting for age, gender, education, functional disability, disease duration, depression and anxiety. Dependent on the findings of longitudinal studies unravelling the relevant causal pahways, self-rated health might be used as a quick and cheap prognostic marker, which could warn about the possible loss of employment, or changes in functional disability

Computing Storyline Visualizations with Few Block Crossings

Storyline visualizations show the structure of a story, by depicting the interactions of the characters over time. Each character is represented by an x-monotone curve from left to right, and a meeting is represented by having the curves of the participating characters run close together for some time. There have been various approaches to drawing storyline visualizations in an automated way. In order to keep the visual complexity low, rather than minimizing pairwise crossings of curves, we count block crossings, that is, pairs of intersecting bundles of lines. Partly inspired by the ILP-based approach of Gronemann et al. [GD 2016] for minimizing the number of pairwise crossings, we model the problem as a satisfiability problem (since the straightforward ILP formulation becomes more complicated and harder to solve). Having restricted ourselves to a decision problem, we can apply powerful SAT solvers to find optimal drawings in reasonable time. We compare this SAT-based approach with two exact algorithms for block crossing minimization, using both the benchmark instances of Gronemann et al. and random instances. We show that the SAT approach is suitable for real-world instances and identify cases where the other algorithms are preferable.Comment: Appears in the Proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017