Rapid Dual-Task Decrements After a Brief Period of Manual Tracking in Simulated Weightlessness by Water Submersion

Objective Investigating dual-task (DT) performance during simulated weightlessness by water submersion, using a manual tracking and a choice reaction task. In contrast to previous work, we focus on performance changes over time. Background Previous research showed motor tracking and choice reaction impairments under DT and single-task (ST) conditions in shallow water submersion. Recent research analyzed performance as average across task time, neglecting potential time-related changes or fluctuations of task-performance. Method An unstable tracking and a choice reaction task was performed for one minute under ST and DT conditions in 5 m water submersion and on dry land in 43 participants. Tracking and choice reaction time performance for both tasks were analyzed in blocks of 10 seconds. Results Tracking performance deteriorated underwater compared to dry land conditions during the second half while performing one minute in DT conditions. Choice reaction time increased underwater as well, but independent of task time and type. Conclusion Tracking error increased over time when performing unstable tracking and choice reaction together. Potentially, physiological and psychological alterations under shallow submersion further strain the human system during DT operations, exceeding available recourse capacities such that DT performance deteriorated over time. Application Humans operating in simulated weightlessness underwater should be aware of substantial performance declines that can occur within a short amount of time during DT situations that include continuous tracking.

Composition and decomposition of visuomotor maps during manual tracking

Adapting hand movements to changes in our body or the environment is essential for skilled motor behavior, as is the ability to flexibly combine experience gathered in separate contexts. However it has been shown that when adapting hand movements to two different visuomotor perturbations in succession, interference effects can occur. Here we investigate whether these interference effects compromise our ability to adapt to the superposition of the two perturbations. Participants tracked with a joystick a visual target that followed a smooth but unpredictable trajectory. Four separate groups of participants (total n = 83) completed one block of 50 trials under each of three mappings: one in which the cursor was rotated by 90° (ROTATION), one in which the cursor mimicked the behavior of a mass-spring system (SPRING), and one in which the SPRING and ROTATION mappings were superimposed (SPROT). The order of the blocks differed across groups. Although interference effects were found when switching between SPRING and ROTATION, participants who performed these blocks first performed better in SPROT than participants who had no prior experience with SPRING and ROTATION (i.e., composition). Moreover, participants who started with SPROT exhibited better performance under SPRING and ROTATION than participants who had no prior experience with each of these mappings (i.e., decomposition). Additional analyses confirmed that these effects resulted from components of learning that were specific to the rotational and spring perturbations. These results show that interference effects do not preclude the ability to compose/decompose various forms of visuomotor adaptation.

A Global Perspective of Tropical Cyclone Precipitation in Reanalyses

This study compares the spread in climatological tropical cyclone (TC) precipitation across eight different reanalysis datasets: NCEP-CFSR, ERA-20C, ERA-40, ERA5, ERA-Interim, JRA-55, MERRA-2 and NOAA-20C. TC precipitation is assigned using manual tracking via a fixed 500-km radius from each TC center. The reanalyses capture similar general spatial patterns of TC precipitation and TC precipitation fraction, defined as the fraction of annual precipitation assigned to TCs, and the spread in TC precipitation is larger than the spread in total precipitation across reanalyses. The spread in TC precipitation relative to the inter-reanalysis mean TC precipitation, or relative spread, is larger in the East Pacific than in the West Pacific. Partitioned by reanalysis intensity, the largest relative spread across reanalyses in TC precipitation is from high intensity TCs. Compared to satellite observations, reanalyses show lower climatological mean annual TC precipitation over most areas. A comparison of area-averaged precipitation rate in TCs composited over reanalysis intensity shows the spread across reanalyses is larger for higher intensity TCs. Testing the sensitivity of TC precipitation assignment to tracking method shows that climatological mean annual TC precipitation is systematically larger when assigned via manual tracking versus objective tracking. However, this tendency is minimized when TC precipitation is normalized by TC density. Overall, TC precipitation in reanalyses is not only affected by horizontal output resolution or any TC pre-processing, but also data assimilation and parameterization schemes. The results indicate that improvements in the representation of TCs and their precipitation in reanalyses are needed to improve overall precipitation.

Measuring outcomes and impact from the BioHackathon Europe

One of the recurring questions when it comes to BioHackathons is how to measure their impact, especially when funded and/or supported by the public purse (e.g., research agencies, research infrastructures, grants). In order to do so, we first need to understand the outcomes from a BioHackathon, which can include software, code, publications, new or strengthened collaborations, along with more intangible effects such as accelerated progress and professional and personal outcomes. In this manuscript, we report on three complementary approaches to assess outcomes of three BioHackathon Europe events: survey-based, publication-based and GitHub-based measures. We found that post-event surveys bring very useful insights into what participants feel they achieved during the hackathon, including progressing much faster on their hacking projects, broadening their professional network and improving their understanding of other technical fields and specialties. With regards to published outcomes, manual tracking of publications from specific servers is straightforward and useful to highlight the scientific legacy of the event, though there is much scope to automate this via text-mining. Finally, GitHub-based measures bring insights on some of the software and data best practices (e.g., license usage) but also on how the hacking activities evolve in time (e.g., activities observed in GitHub repositories prior, during and after the event). Altogether, these three approaches were found to provide insightful preliminary evidence of outcomes, thereby supporting the value of financing such large-scale events with public funds.

Measuring the double-drift illusion with hand tracking

If a gabor pattern drifts in one direction while its internal texture drifts in the orthogonal direction, its perceived position deviates further and further away from its true path. We first evaluated the illusion using manual tracking. Participants followed the gabor with a stylus on a drawing tablet that coincided optically with the horizontal monitor surface. Their hand and the stylus were not visible during the tracking. The magnitude of the tracking illusion corresponded closely to previous perceptual and pointing measures indicating that manual tracking is a valid measure for the illusion. This allowed us to use it in a second experiment to capture the behavior of the illusion as it eventually degrades and breaks down in single trials. Specifically, the deviation of the gabor stops accumulating at some point and either stays at a fixed offset or resets toward the veridical position. To report the perceived trajectory of the gabor, participants drew it after the gabor was removed from the monitor. Resets were detected and analyzed and they suggest that there is a spatial limit beyond which the illusion saturates or resets.

De novo learning versus adaptation of continuous control in a manual tracking task

How do people learn to perform tasks that require continuous adjustments of motor output, like riding a bicycle? People rely heavily on cognitive strategies when learning discrete movement tasks, but such time-consuming strategies are infeasible in continuous control tasks that demand rapid responses to ongoing sensory feedback. To understand how people can learn to perform such tasks without the benefit of cognitive strategies, we imposed a rotation/mirror reversal of visual feedback while participants performed a continuous tracking task. We analyzed behavior using a system identification approach which revealed two qualitatively different components of learning: adaptation of a baseline controller and formation of a new, task-specific continuous controller. These components exhibited different signatures in the frequency domain and were differentially engaged under the rotation/mirror reversal. Our results demonstrate that people can rapidly build a new continuous controller de novo and can simultaneously deploy this process with adaptation of an existing controller.

Experimental Investigation on Novel Parabolic Trough Collector

With the increase in demand of the cleaner energy, the use of renewable sources of energy is increasing day by day and solar energy is the answer to it. Several methods are used to harness solar thermal energy among them Concentrating Parabolic Collectors (CPC) are widely used. In this paper, A novel CPC is made, and an experimental study is carried out to find out its efficiency in manual and automated single axis tracking mode using water as working fluid. It was observed that the automated tracking method outperforms the manual tracking method with efficiency reaching up to 48% as compared to 42% in the later. Methods to improve efficiency of the CPC are not used in this study. CPC was found suitable for domestic use.

Extracting Crowd Velocities at High Density

Velocity is a fundamental property of foot traffic flow. Monitoring the change of velocity patterns at high pedestrian densities may provide valuable insights on foot traffic dynamics. In this paper, a closer look is taken to explore the capability of the Particle Image Velocimetry (PIV) technique on extracting crowd velocities from surveillance camera images. Experiments are performed to report the accuracy of pedestrian velocity extraction with PIV. Quantitative accuracy is reported with manual tracking of pedestrians, surveying correlation misses at different window sizes and compute times. The results indicate that the PIV algorithm can be a good candidate for velocity extraction in real-time.