The Effectiveness of Dynamically Processed Incremental Descriptions in Human Robot Interaction

We explore the effectiveness of a dynamically processed incremental referring description system using under-specified ambiguous descriptions that are then built upon using linguistic repair statements, which we refer to as a dynamic system. We build a dynamically processed incremental referring description generation system that is able to provide contextual navigational statements to describe an object in a potential real-world situation of nuclear waste sorting and maintenance. In a study of 31 participants, we test the dynamic system in a case where a user is remote operating a robot to sort nuclear waste, with the robot assisting them in identifying the correct barrels to be removed. We compare these against a static non-ambiguous description given in the same scenario. As well as looking at efficiency with time and distance measurements, we also look at user preference. Results show that our dynamic system was a much more efficient method—taking only 62% of the time on average—for finding the correct barrel. Participants also favoured our dynamic system.

Wild Type and Omicron SARS-CoV-2 Spike Receptor Binding Domains Bind Similarly to the Human ACE2 Receptor: An MM-GBSA Study

SARS-CoV-2 is a coronavirus that has created a global pandemic. The virus contains a spike protein which has been shown to bind to the ACE2 receptor on the surface of human cells. Vaccines have been developed that recognize elements of the SARS-CoV-2 spike protein and they have been successful in preventing infection. Recently, the omicron variant of the SARS-CoV-2 virus was reported and quickly became a variant of concern due to its transmissibility. This variant contained an unusually large number (32) of point mutations, of which 15 of those mutations are in the receptor binding domain of the spike protein. In order to assess the differential binding ability of the wild type and omicron variant of the RBD spike protein to human ACE2 receptors, we conducted 2 μs of molecular dynamics simulation to estimate the binding affinities and behaviors. Based upon MM-GBSA binding affinity, center of mass distance measurements, ensemble clustering, pairwise residue decomposition and hydrogen bonding analysis, we can conclude that the 15 point mutations in the receptor binding domain do not increase the affinity of the spike protein for the human ACE2 receptor. The MM-GBSA binding estimations over a 2 μs trajectory, suggest that the wild type binds to ACE2 with a value of -29.69 kcal/mol while the omicron mutant binds with an energy value of -26.67 kcal/mol. These values are within the error estimates of the MM-GBSA method. While some mutations increase binding, more mutations diminish binding, leading to an overall similar picture of binding.

Inter-team communication in large-scale co-located software engineering: a case study

Large-scale software engineering is a collaborative effort where teams need to communicate to develop software products. Managers face the challenge of how to organise work to facilitate necessary communication between teams and individuals. This includes a range of decisions from distributing work over teams located in multiple buildings and sites, through work processes and tools for coordinating work, to softer issues including ensuring well-functioning teams. In this case study, we focus on inter-team communication by considering geographical, cognitive and psychological distances between teams, and factors and strategies that can affect this communication. Data was collected for ten test teams within a large development organisation, in two main phases: (1) measuring cognitive and psychological distance between teams using interactive posters, and (2) five focus group sessions where the obtained distance measurements were discussed. We present ten factors and five strategies, and how these relate to inter-team communication. We see three types of arenas that facilitate inter-team communication, namely physical, virtual and organisational arenas. Our findings can support managers in assessing and improving communication within large development organisations. In addition, the findings can provide insights into factors that may explain the challenges of scaling development organisations, in particular agile organisations that place a large emphasis on direct communication over written documentation.

Heart Rate and Distance Measurement of Two Multisport Activity Trackers and a Cellphone App in Different Sports: A Cross-Sectional Validation and Comparison Field Study

Options for monitoring sports have been continuously developed by using activity trackers to determine almost all vital and movement parameters. The aim of this study was to validate heart rate and distance measurements of two activity trackers (Polar Ignite; Garmin Forerunner 945) and a cellphone app (Polar Beat app using iPhone 7 as a hardware platform) in a cross-sectional field study. Thirty-six moderate endurance-trained adults (20 males/16 females) completed a test battery consisting of walking and running 3 km, a 1.6 km interval run (standard 400 m outdoor stadium), 3 km forest run (outdoor), 500/1000 m swim and 4.3/31.5 km cycling tests. Heart rate was recorded via a Polar H10 chest strap and distance was controlled via a map, 400 m stadium or 50 m pool. For all tests except swimming, strong correlation values of r > 0.90 were calculated with moderate exercise intensity and a mean absolute percentage error of 2.85%. During the interval run, several significant deviations (p < 0.049) were observed. The swim disciplines showed significant differences (p < 0.001), with the 500 m test having a mean absolute percentage error of 8.61%, and the 1000 m test of 55.32%. In most tests, significant deviations (p < 0.001) were calculated for distance measurement. However, a maximum mean absolute percentage error of 4.74% and small mean absolute error based on the total route lengths were calculated. This study showed that the accuracy of heart rate measurements could be rated as good, except for rapid changing heart rate during interval training and swimming. Distance measurement differences were rated as non-relevant in practice for use in sports.

Janus

Proximity detection is at the core of several mobile and ubiquitous computing applications. These include reactive use cases, e.g., alerting individuals of hazards or interaction opportunities, and others concerned only with logging proximity data, e.g., for offline analysis and modeling. Common approaches rely on Bluetooth Low Energy (BLE) or ultra-wideband (UWB) radios. Nevertheless, these strike opposite tradeoffs between the accuracy of distance estimates quantifying proximity and the energy efficiency affecting system lifetime, effectively forcing a choice between the two and ultimately constraining applicability. Janus reconciles these dimensions in a dual-radio protocol enabling accurate and energy-efficient proximity detection, where the energy-savvy BLE is exploited to discover devices and coordinate their distance measurements, acquired via the energy-hungry UWB. A model supports domain experts in configuring Janus for their use cases with predictable performance. The latency, reliability, and accuracy of Janus are evaluated experimentally, including realistic scenarios endowed with the mm-level ground truth provided by a motion capture system. Energy measurements show that Janus achieves weeks to months of autonomous operation, depending on the use case configuration. Finally, several large-scale campaigns exemplify its practical usefulness in real-world contexts.

In situ distance measurements in a membrane transporter using maleimide functionalized orthogonal spin labels and 5-pulse electron double resonance spectroscopy

Spectroscopic investigation of membrane proteins in their native environment is a challenging task. Earlier we demonstrated the feasibility to measure precise distances within outer membrane proteins in E. coli and native membranes using methanethiosulfonate (MTS) functionalized labels combined with pulsed electron double resonance spectroscopy. Here we show the application of maleimide functionalized Gd(III), nitroxide, and trityl labels for in situ distance measurement using the cobalamin transporter BtuB. These labels enabled distance measurements for BtuB in E. coli and native outer membranes and in the membranes maleimide-Gd-DOTA also is effective. Further, we show that the observable dipolar evolution time can be significantly prolonged in the native environments using the Carr-Purcell 5-pulse electron double resonance sequence. For a nitroxide-nitroxide pair, application of sech/tanh inversion pulses substantially suppressed the 4-pulse artifact at the Q- band frequency. In the case of a nitroxide-trityl pair, Gaussian pump pulses of varying amplitude are sufficient to suppress the artifact to the typical noise level. The feasibility of a range of bioresistant spin labels and the 5-pulse electron double resonance offers promising tools for investigating heterooligomeric membrane protein complexes in their native environment.

Practical And Robust Approach For A Neural Networks Based Indoor Positioning System Using Ultrawide Band

With the increasing widespread of sensor technology, new solutions for indoor positioning systems are continuously being developed and with them, new services requiring accurate positioning data have seen a great rise in popularity. In this thesis, a new design technique and deployment methodology for an indoor positioning system using neural networks is proposed to offer more flexibility and simplicity in the development of such a system which is currently very context-bound. The usage of battery-powered tags implies also that systems should not require excessive power consumption and the large number of targets to position requires a method that is not only accurate but also scalable. The proposed positioning system utilizes a small “swarm” of neural networks tasked to position targets based on distance measurements from Ultrawide Band sensors and requires shorter fingerprint collection campaigns and enables more flexibility in system deployment and alterations. Instead of relying solely on real data collected on the field for the training of neural networks, synthetic data is used for an initial training phase. Together, these propositions allow flexibility in terms of adding, removing or altering positions of reference nodes and simplifies offline deployment operations of an indoor positioning system. This thesis presents a system operating in a laboratory-workshop environment capable of good positioning accuracies and maintains robust performances in poor signal propagation.