Analysis of human-robot spatial behaviour applying a qualitative trajectory calculus

The analysis and understanding of human-robot joint spatial behaviour (JSB) such as guiding, approaching, departing, or coordinating movements in narrow spaces and its communicative and dynamic aspects are key requirements on the road towards more intuitive interaction, safe encounter, and appealing living with mobile robots. This endeavours demand for appropriate models and methodologies to represent JSB and facilitate its analysis. In this paper, we adopt a qualitative trajectory calculus (QTC) as a formal foundation for the analysis and representation of such spatial behaviour of a human and a robot based on a compact encoding of the relative trajectories of two interacting agents in a sequential model. We present this QTC together with a distance measure and a probabilistic behaviour model and outline its usage in an actual JSB study.We argue that the proposed QTC coding scheme and derived methodologies for analysis and modelling are flexible and extensible to be adapted for a variety of other scenarios and studies. I

Differences in instructional quality during the Covid-19 pandemic between Oman and Germany and the role of teacher competences

Introduction: School closures during the Covid-19 pandemic hit educational systems worldwide, forcing teachers to switch to digital learning settings. The presented study aims to (a) adapt and evaluate scales on instructional quality in digital settings, (b) describe instructional quality during the pandemic, and (c) to identify predictive teacher competences. Method: Data was assessed in a cross-sectional design via an online questionnaire conducted in Oman and Germany simultaneously. Results: Analyses of data from N = 284 teachers in Oman and Germany revealed mostly good psychometric parameters, differences in instructional quality between both countries, and positive relations between teachers’ competences and instructional quality. Conclusion: The present study contributes to instrument development and to the growing body of research, investigating teaching quality during the pandemic

Design optimization of soft pneumatic actuators using genetic algorithms

Recent trends in bioinspired robotic systems are paving the way for robots to become part of our daily lives. Soft robots, which are widely recognized as the next generation of human-friendly robots, are such a trend. Soft robots are generally more adaptable, more flexible, and safer than their rigid-link counterparts. Research in soft robotics has produced a broad variety of interesting solutions for all sorts of applications ranging from medical engineering and rehabilitation over exploration to industrial handling. This diversity together with a general lack of experience in designing with soft materials has contributed to a design flow that is highly empirical in nature. For soft robots to become mass-producible in the near future, more general design and modeling methods are needed. In this article, we present a method for the design optimization of soft robot modules that effectively combines finite element modeling and gradient-free optimization. To demonstrate the feasibility of the approach, a soft pneumatic actuator is designed and optimized. Performance analysis of the optimization scheme shows the robustness of the solution in the given case

Manganese-catalyzed dehydrogenative synthesis of urea derivatives and polyureas

A.K. thanks the Leverhulme Trust for an early career fellowship (ECF-2019-161). M.B. wishes to thank the School of Chemistry and EaStCHEM for their support. A.E.O. gratefully acknowledges a fellowship from the Akwa Ibom State University (TETFund).Urea derivatives have significant applications in the synthesis of resin precursors, dyes, agrochemicals, and pharmaceutical drugs. Furthermore, polyureas are useful plastics with applications in coating, adhesive, and biomedical industries. However, the conventional methods for the synthesis of urea derivatives and polyureas involve toxic reagents such as (di)isocyanates, phosgene, CO, and azides. We present here the synthesis of (poly)ureas using much less toxic reagents─(di)amines and methanol─via a catalytic dehydrogenative coupling process. The reaction is catalyzed by a pincer complex of an earth-abundant metal, manganese, and liberates H2 gas, valuable by itself, as the only byproduct, making the overall process highly atom-economic. A broad variety of symmetrical and unsymmetrical urea derivatives and polyureas have been synthesized in moderate to quantitative yields using this catalytic protocol. Mechanistic insights have also been provided using experiments and DFT computation, suggesting that the reaction proceeds via an isocyanate intermediate.Publisher PDFPeer reviewe

Unterrichtsqualität aus der Sicht von externen Raterinnen und Ratern – Analysen zum Reihenfolgeeffekt

Unterrichtsqualität wird häufig über Urteile von Externen erfasst. Mit Blick auf die Güte dieser Urteile stellt sich die Frage, ob diese aufgrund von Darbietungsmodalitäten sowie individuellen Faktoren systematisch verzerrt sein können. In der vorliegenden Studie wurden daher der Einfluss der Reihenfolge von Unterrichtsvideos mit unterschiedlichen Qualitätsniveaus sowie von individuellen Faktoren wie Vorerfahrung und mentaler Zustand (Müdigkeit) auf Unterschiede in den Urteilen und Interaktionen untersucht. Hierfür wurden N = 69 Studierende zu drei Versuchsgruppen zugeordnet, die zwei zehnminütige Videos in variierender Reihenfolge der Qualitätsniveaus präsentiert bekamen: Gruppe A (niedrig/mittel), B (mittel/hoch) und C (hoch/mittel). Die Analysen zeigten Unterschiede in den mittleren Ratings aufgrund der Reihenfolge sowie der Vorerfahrung und der Müdigkeit. Überdies wurden Interaktionen zwischen der experimentellen Bedingung und der Müdigkeit identifiziert. Die Ergebnisse wiesen auf Verzerrungen der Urteile von Externen hin, besonders im Bereich Motivierung. Konsequenzen für die Interpretation und Durchführung von videogestützten Unterrichtsqualitätsstudien werden diskutiert.Ratings of external observers are often used for measuring instructional quality. These ratings can be influenced by the order of presentation and individual characteristics such as observers’ experience and mental state (tiredness). The present study examined the influence of the presentation order of videos with varying levels of teaching quality and of individual factors such as previous experience and mental state (tiredness) on differences in observer ratings and interactions. Therefore, N = 69 students were assigned to three experimental groups. In each group, two videos of ten minutes length were presented in varying order of teaching quality: group A (low/medium), B (medium/high), and C (high/medium). Analyses showed significant differences in the ratings, depending on the sequential order, the observers’ experience, and observers’ tiredness. An interaction was found between experimental condition and observers’ tiredness. Results suggest a bias of external judgements, especially concerning motivational quality. Consequences for interpretation and implementation of video-based studies measuring teaching quality are discussed

Unterrichtsqualität und intrinsische Lesemotivation im Kontext der Bund-Länder-Initiative „Bildung durch Sprache und Schrift“ (BiSS)

Lesekompetenz gilt als fächerübergreifende Schlüsselkompetenz für Bildungserfolg und ist damit ein zentrales Ziel des Grundschulunterrichts. Vor diesem Hintergrund zielte die Bund-Länder-Initiative „Bildung durch Sprache und Schrift“ unter anderem auf die Förderung lesebezogener Kompetenzen im Leseunterricht der Grundschule ab. Der intrinsischen Lesemotivation kommt aufgrund ihres eigenständigen Wertes und wegen ihrer Zusammenhänge mit der Lesekompetenz eine große Bedeutung zu. Der vorliegende Beitrag untersucht a) Zusammenhänge zwischen schulischer BiSS-Beteiligung und der Entwicklung der Qualität des Leseunterrichts in einem quasi-experimentellen Längsschnittdesign mit N = 1032 Schülerinnen und Schülern der vierten Klassenstufe und b) Zusammenhänge von Unterrichtsqualität und der Entwicklung intrinsischer Lesemotivation. Es wurden Mehrebenenstrukturgleichungsmodelle spezifiziert und analysiert, die einen kleinen positiven Effekt schulischer BiSS-Beteiligung auf die Differenzierung im Leseunterricht zeigten. Außerdem erwiesen sich Differenzierung, Störungen im Unterricht und Merkmale des unterstützenden Unterrichtsklimas als prädiktiv für intrinsische Lesemotivation auf Individualebene

Actuation and stiffening in fluid-driven soft robots using low-melting-point material

Soft material robots offer a number of advantages over traditional rigid robots in applications including human-robot interaction, rehabilitation and surgery. These robots can navigate around obstacles, elongate, squeeze through narrow openings or be squeezed - and they are considered to be inherently safe. The ability to stiffen compliant soft actuators has been achieved by embedding various mechanisms that are generally decoupled from the actuation principle. Miniaturisation becomes challenging due to space limitations which can in turn result in diminution of stiffening effects. Here, we propose to hydraulically actuate soft manipulators with low-melting-point material and, at the same time, be able to switch between a soft and stiff state. Instead of allocating an additional stiffening chamber within the soft robot, one chamber only is used for actuation and stiffening. Low Melting Point Alloy is integrated into the actuation chamber of a single-compartment soft robotic manipulator and the interfaced robotic syringe pump. Temperature change is enabled through embedded nichrome wires. Our experimental results show higher stiffness factors, from 9-12 opposing the motion of curvature, than those previously found for jamming mechanisms incorporated in separate additional chambers, in the range of 2-8 for the same motion

Experimental validation of 4D log file-based proton dose reconstruction for interplay assessment considering amplitude-sorted 4DCTs

Purpose The unpredictable interplay between dynamic proton therapy delivery and target motion in the thorax can lead to severe dose distortions. A fraction-wise four-dimensional (4D) dose reconstruction workflow allows for the assessment of the applied dose after patient treatment while considering the actual beam delivery sequence extracted from machine log files, the recorded breathing pattern and the geometric information from a 4D computed tomography scan (4DCT). Such an algorithm capable of accounting for amplitude-sorted 4DCTs was implemented and its accuracy as well as its sensitivity to input parameter variations was experimentally evaluated. Methods An anthropomorphic thorax phantom with a movable insert containing a target surrogate and a radiochromic film was irradiated with a monoenergetic field for various 1D target motion forms (sin, sin(4)) and peak-to-peak amplitudes (5/10/15/20/30 mm). The measured characteristic film dose distributions were compared to the respective sections in the 4D reconstructed doses using a 2D gamma-analysis (3 mm, 3%); gamma-pass rates were derived for different dose grid resolutions (1 mm/3 mm) and deformable image registrations (DIR, automatic/manual) applied during the 4D dose reconstruction process. In an additional analysis, the sensitivity of reconstructed dose distributions against potential asynchronous timing of the motion and machine log files was investigated for both a monoenergetic field and more realistic 4D robustly optimized fields by artificially introduced offsets of +/- 1/5/25/50/250 ms. The resulting dose distributions with asynchronized log files were compared to those with synchronized log files by means of a 3D gamma-analysis (1 mm, 1%) and the evaluation of absolute dose differences. Results The induced characteristic interplay patterns on the films were well reproduced by the 4D dose reconstruction with 2D gamma-pass rates >= 95% for almost all cases with motion magnitude

Primary care practice-based care management for chronically ill patients (PraCMan): study protocol for a cluster randomized controlled trial [ISRCTN56104508]

Background: Care management programmes are an effective approach to care for high risk patients with complex care needs resulting from multiple co-occurring medical and non-medical conditions. These patients are likely to be hospitalized for a potentially "avoidable" cause. Nurse-led care management programmes for high risk elderly patients showed promising results. Care management programmes based on health care assistants (HCAs) targeting adult patients with a high risk of hospitalisation may be an innovative approach to deliver cost-efficient intensified care to patients most in need. Methods: PraCMan is a cluster randomized controlled trial with primary care practices as unit of randomisation. The study evaluates a complex primary care practice-based care management of patients at high risk for future hospitalizations. Eligible patients either suffer from type 2 diabetes mellitus, chronic obstructive pulmonary disease, chronic heart failure or any combination. Patients with a high likelihood of hospitalization within the following 12 months (based on insurance data) will be included in the trial. During 12 months of intervention patients of the care management group receive comprehensive assessment of medical and non-medical needs and resources as well as regular structured monitoring of symptoms. Assessment and monitoring will be performed by trained HCAs from the participating practices. Additionally, patients will receive written information, symptom diaries, action plans and a medication plan to improve self-management capabilities. This intervention is addition to usual care. Patients from the control group receive usual care. Primary outcome is the number of all-cause hospitalizations at 12 months follow-up, assessed by insurance claims data. Secondary outcomes are health-related quality of life (SF12, EQ5D), quality of chronic illness care (PACIC), health care utilisation and costs, medication adherence (MARS), depression status and severity (PHQ-9), self-management capabilities and clinical parameters. Data collection will be performed at baseline, 12 and 24 months (12 months post-intervention). Discussion: Practice-based care management for high risk individuals involving trained HCAs appears to be a promising approach to face the needs of an aging population with increasing care demands. Trial registration: Current Controlled Trials ISRCTN5610450

Trajectory Based Flight Phase Identification with Machine Learning for Digital Twins

Analysis of aircraft trajectory data is used in different applications of aviation research. Areas such as Maintenance, Repair and Overhaul (MRO) and Air Traffic Management (ATM) benefit from a more detailed understanding of the trajectory, thus requiring the trajectory to be divided into the different flight phases. Flight phases are mostly computed from the aircraft’s internal sensor parameters, which are very sensitive and have scarce availability to the public. This is why identification on publicly available data such as Automatic Dependent Surveillance Broadcast (ADS-B) trajectory data is essential. Some of the flight phases required for these applications are not covered by state-of-the-art flight phase identification on ADS-B trajectory data. This paper presents a novel machine learning approach for more detailed flight phase identification. We generate a training dataset with supervised simulation data obtained with the X-plane simulator. The model combines K-means clustering with a Long Short-Term Memory (LSTM) network, the former allows the segmentation to capture transitions between phases more closely, and the latter learns the dynamics of a flight. We are able to identify a larger variety of phases compared to state of the art and adhere to the International Civil Aviation Organisation (ICAO) standard