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An essential measure of autonomy in service robots designed to assist humans is adaptivity to the various contexts of human-oriented tasks. These robots may have to frequently execute the same action, but subject to subtle variations in task parameters that determine optimal behaviour. Such actions are traditionally executed by robots using pre-determined, generic motions, but a better approach could utilize robot arm maneuverability to learn and execute different trajectories that work best in each context.
In this project, we explore a robot skill acquisition procedure that allows incorporating contextual knowledge, adjusting executions according to context, and improvement through experience, as a step towards more adaptive service robots. We propose an apprenticeship learning approach to achieving context-aware action generalisation on the task of robot-to-human object hand-over. The procedure combines learning from demonstration, with which a robot learns to imitate a demonstrator’s execution of the task, and a reinforcement learning strategy, which enables subsequent experiential learning of contextualized policies, guided by information about context that is integrated into the learning process. By extending the initial, static hand-over policy to a contextually adaptive one, the robot derives and executes variants of the demonstrated action that most appropriately suit the current context. We use dynamic movement primitives (DMPs) as compact motion representations, and a model-based Contextual Relative Entropy Policy Search (C-REPS) algorithm for learning policies that can specify hand-over position, trajectory shape, and execution speed, conditioned on context variables. Policies are learned using simulated task executions, before transferring them to the robot and evaluating emergent behaviours.
We demonstrate the algorithm’s ability to learn context-dependent hand-over positions, and new trajectories, guided by suitable reward functions, and show that the current DMP implementation limits learning context-dependent execution speeds. We additionally conduct a user study involving participants assuming different postures and receiving an object from the robot, which executes hand-overs by either exclusively imitating a demonstrated motion, or selecting hand-over positions based on learned contextual policies and adapting its motion accordingly. The results confirm the hypothesized improvements in the robot’s perceived behaviour when it is context-aware and adaptive, and provide useful insights that can inform future developments.
An essential measure of autonomy in assistive service robots is adaptivity to the various contexts of human-oriented tasks, which are subject to subtle variations in task parameters that determine optimal behaviour. In this work, we propose an apprenticeship learning approach to achieving context-aware action generalization on the task of robot-to-human object hand-over. The procedure combines learning from demonstration and reinforcement learning: a robot first imitates a demonstrator’s execution of the task and then learns contextualized variants of the demonstrated action through experience. We use dynamic movement primitives as compact motion representations, and a model-based C-REPS algorithm for learning policies that can specify hand-over position, conditioned on context variables. Policies are learned using simulated task executions, before transferring them to the robot and evaluating emergent behaviours. We additionally conduct a user study involving participants assuming different postures and receiving an object from a robot, which executes hand-overs by either imitating a demonstrated motion, or adapting its motion to hand-over positions suggested by the learned policy. The results confirm the hypothesized improvements in the robot’s perceived behaviour when it is context-aware and adaptive, and provide useful insights that can inform future developments.
YAWL (Yet Another Workflow Language) is an open source Business Process Management System, first released in 2003. YAWL grew out of a university research environment to become a unique system that has been deployed worldwide as a laboratory environment for research in Business Process Management and as a productive system in other scientific domains.
Due to the use of fossil fuel resources, many environmental problems have been increasingly growing. Thus, the recent research focuses on the use of environment friendly materials from sustainable feedstocks for future fuels, chemicals, fibers and polymers. Lignocellulosic biomass has become the raw material of choice for these new materials. Recently, the research has focused on using lignin as a substitute material in many industrial applications. The antiradical and antimicrobial activity of lignin and lignin-based films are both of great interest for applications such as food packaging additives. DPPH assay was used to determine the antioxidant activity of Kraft lignin compared to Organosolv lignins from different biomasses. The purification procedure of Kraft lignin showed that double-fold selective extraction is the most efficient confirmed by UV-Vis, FTIR, HSQC, 31PNMR, SEC, and XRD. The antioxidant capacity was discussed regarding the biomass source, pulping process, and degree of purification. Lignin obtained from industrial black liquor are compared with beech wood samples: Biomass source influences the DPPH inhibition (softwood > grass) and the TPC (softwood < grass). DPPH inhibition affected by the polarity of the extraction solvent. Following the trend: ethanol > diethylether > acetone. Reduced polydispersity has positive influence on the DPPH inhibition. Storage decreased the DPPH inhibition but increased the TPC values. The DPPH assay was also used to discuss the antiradical activity of HPMC/lignin and HPMC/lignin/chitosan films. In both binary (HPMC/lignin) and ternary (HPMC/lignin/chitosan) systems the 5% addition showed the highest activity and the highest addition had the lowest. Both scavenging activity and antimicrobial activity are dependent on the biomass source; Organosolv of softwood > Kraft of softwood > Organosolv of grass. Lignins and lignin-containing films showed high antimicrobial activities against Gram-positive and Gram-negative bacteria at 35 °C and at low temperatures (0-7 °C). Purification of Kraft lignin has a negative effect on the antimicrobial activity while storage has positive effect. The lignin leaching in the produced films affected the activity positively and the chitosan addition enhances the activity for both Gram-positive and Gram-negative bacteria. Testing the films against food spoilage bacteria that grow at low temperatures revealed the activity of the 30% addition on HPMC/L1 film against both B. thermosphacta and P. fluorescens while L5 was active only against B. thermosphacta. In HPMC/lignin/chitosan films, the 5% addition exhibited activity against both food spoilage bacteria.
In 1991 the researchers at the center for the Learning Sciences of Carnegie Mellon University were confronted with the confusing question of “where is AI” from the users, who were interacting with AI but did not realize it. Three decades of research and we are still facing the same issue with the AItechnology users. In the lack of users’ awareness and mutual understanding of AI-enabled systems between designers and users, informal theories of the users about how a system works (“Folk theories”) become inevitable but can lead to misconceptions and ineffective interactions. To shape appropriate mental models of AI-based systems, explainable AI has been suggested by AI practitioners. However, a profound understanding of the current users’ perception of AI is still missing. In this study, we introduce the term “Perceived AI” as “AI defined from the perspective of its users”. We then present our preliminary results from deep-interviews with 50 AItechnology users, which provide a framework for our future research approach towards a better understanding of PAI and users’ folk theories.
In this paper we introduce the Perception for Autonomous Systems (PAZ) software library. PAZ is a hierarchical perception library that allow users to manipulate multiple levels of abstraction in accordance to their requirements or skill level. More specifically, PAZ is divided into three hierarchical levels which we refer to as pipelines, processors, and backends. These abstractions allows users to compose functions in a hierarchical modular scheme that can be applied for preprocessing, data-augmentation, prediction and postprocessing of inputs and outputs of machine learning (ML) models. PAZ uses these abstractions to build reusable training and prediction pipelines for multiple robot perception tasks such as: 2D keypoint estimation, 2D object detection, 3D keypoint discovery, 6D pose estimation, emotion classification, face recognition, instance segmentation, and attention mechanisms.
AErOmAt Abschlussbericht
(2020)
Das Projekt AErOmAt hatte zum Ziel, neue Methoden zu entwickeln, um einen erheblichen Teil aerodynamischer Simulationen bei rechenaufwändigen Optimierungsdomänen einzusparen. Die Hochschule Bonn-Rhein-Sieg (H-BRS) hat auf diesem Weg einen gesellschaftlich relevanten und gleichzeitig wirtschaftlich verwertbaren Beitrag zur Energieeffizienzforschung geleistet. Das Projekt führte außerdem zu einer schnelleren Integration der neuberufenen Antragsteller in die vorhandenen Forschungsstrukturen.
Among the celestial bodies in the Solar System, Mars currently represents the main target for the search for life beyond Earth. However, its surface is constantly exposed to high doses of cosmic rays (CRs) that may pose a threat to any biological system. For this reason, investigations into the limits of resistance of life to space relevant radiation is fundamental to speculate on the chance of finding extraterrestrial organisms on Mars. In the present work, as part of the STARLIFE project, the responses of dried colonies of the black fungus Cryomyces antarcticus Culture Collection of Fungi from Extreme Environments (CCFEE) 515 to the exposure to accelerated iron (LET: 200 keV/μm) ions, which mimic part of CRs spectrum, were investigated. Samples were exposed to the iron ions up to 1000 Gy in the presence of Martian regolith analogues. Our results showed an extraordinary resistance of the fungus in terms of survival, recovery of metabolic activity and DNA integrity. These experiments give new insights into the survival probability of possible terrestrial-like life forms on the present or past Martian surface and shallow subsurface environments.
The general method of topological reduction for the network problems is presented on example of gas transport networks. The method is based on a contraction of series, parallel and tree-like subgraphs for the element equations of quadratic, power law and general monotone dependencies. The method allows to reduce significantly the complexity of the graph and to accelerate the solution procedure for stationary network problems. The method has been tested on a large set of realistic network scenarios. Possible extensions of the method have been described, including triangulated element equations, continuation of the equations at infinity, providing uniqueness of solution, a choice of Newtonian stabilizer for nearly degenerated systems. The method is applicable for various sectors in the field of energetics, including gas networks, water networks, electric networks, as well as for coupling of different sectors.
With increasing life expectancy, demands for dental tissue and whole-tooth regeneration are becoming more significant. Despite great progress in medicine, including regenerative therapies, the complex structure of dental tissues introduces several challenges to the field of regenerative dentistry. Interdisciplinary efforts from cellular biologists, material scientists, and clinical odontologists are being made to establish strategies and find the solutions for dental tissue regeneration and/or whole-tooth regeneration. In recent years, many significant discoveries were done regarding signaling pathways and factors shaping calcified tissue genesis, including those of tooth. Novel biocompatible scaffolds and polymer-based drug release systems are under development and may soon result in clinically applicable biomaterials with the potential to modulate signaling cascades involved in dental tissue genesis and regeneration. Approaches for whole-tooth regeneration utilizing adult stem cells, induced pluripotent stem cells, or tooth germ cells transplantation are emerging as promising alternatives to overcome existing in vitro tissue generation hurdles. In this interdisciplinary review, most recent advances in cellular signaling guiding dental tissue genesis, novel functionalized scaffolds and drug release material, various odontogenic cell sources, and methods for tooth regeneration are discussed thus providing a multi-faceted, up-to-date, and illustrative overview on the tooth regeneration matter, alongside hints for future directions in the challenging field of regenerative dentistry.
The temperature of photovoltaic modules is modelled as a dynamic function of ambient temperature, shortwave and longwave irradiance and wind speed, in order to allow for a more accurate characterisation of their efficiency. A simple dynamic thermal model is developed by extending an existing parametric steady-state model using an exponential smoothing kernel to include the effect of the heat capacity of the system. The four parameters of the model are fitted to measured data from three photovoltaic systems in the Allgäu region in Germany using non-linear optimisation. The dynamic model reduces the root-mean-square error between measured and modelled module temperature to 1.58 K on average, compared to 3.03 K for the steady-state model, whereas the maximum instantaneous error is reduced from 20.02 to 6.58 K.
This dataset contains data from two measurement campaigns in autumn 2018 and summer 2019 that were part of the BMWi project "MetPVNet", and serve as a supplement to the paper "Dynamic model of photovoltaic module temperature as a function of atmospheric conditions", published in the special edition of "Advances in Science and Research", the proceedings of the 19th EMS Annual Meeting: European Conference for Applied Meteorology and Climatology 2019.
Data are resampled to one minute, and include:
PV module temperature
Ambient temperature
Plane-of-array irradiance
Windspeed
Atmospheric thermal emission
The data were used for the dynamic temperature model, as presented in the paper
Telepresence robots allow users to be spatially and socially present in remote environments. Yet, it can be challenging to remotely operate telepresence robots, especially in dense environments such as academic conferences or workplaces. In this paper, we primarily focus on the effect that a speed control method, which automatically slows the telepresence robot down when getting closer to obstacles, has on user behaviors. In our first user study, participants drove the robot through a static obstacle course with narrow sections. Results indicate that the automatic speed control method significantly decreases the number of collisions. For the second study we designed a more naturalistic, conference-like experimental environment with tasks that require social interaction, and collected subjective responses from the participants when they were asked to navigate through the environment. While about half of the participants preferred automatic speed control because it allowed for smoother and safer navigation, others did not want to be influenced by an automatic mechanism. Overall, the results suggest that automatic speed control simplifies the user interface for telepresence robots in static dense environments, but should be considered as optionally available, especially in situations involving social interactions.
Miscanthus crops possess very attractive properties such as high photosynthesis yield and carbon fixation rate. Because of these properties, it is currently considered for use in second-generation biorefineries. Here we analyze the differences in chemical composition between M. x giganteus, a commonly studied Miscanthus genotype, and M. nagara, which is relatively understudied but has useful properties such as increased frost resistance and higher stem stability. Samples of M. x giganteus (Gig35) and M. nagara (NagG10) have been separated by plant portion (leaves and stems) in order to isolate the corresponding lignins. The organosolv process was used for biomass pulping (80% ethanol solution, 170 °C, 15 bar). Biomass composition and lignin structure analysis were performed using composition analysis, Fourier-transform infrared (FTIR), ultraviolet-visible (UV-Vis) and nuclear magnetic resonance (NMR) spectroscopy, thermogravimetric analysis (TGA), size exclusion chromatography (SEC) and pyrolysis gas-chromatography/mass spectrometry (Py-GC/MS) to determine the 3D structure of the isolated lignins, monolignol ratio and most abundant linkages depending on genotype and harvesting season. SEC data showed significant differences in the molecular weight and polydispersity indices for stem versus leaf-derived lignins. Py-GC/MS and hetero-nuclear single quantum correlation (HSQC) NMR revealed different monolignol compositions for the two genotypes (Gig35, NagG10). The monolignol ratio is slightly influenced by the time of harvest: stem-derived lignins of M. nagara showed increasing H and decreasing G unit content over the studied harvesting period (December–April).
Abschlussbericht zum BMBF-Fördervorhaben Enabling Infrastructure for HPC-Applications (EI-HPC)
(2020)
Intelligente Dialogsysteme – Chatbots – werden immer häufiger als virtuelle Ansprechpartner von Unternehmen und Institutionen eingesetzt. Auf Basis einer Wissensdatenbank können Chatbots einen größeren Anteil von Kundenanfragen automatisiert beantworten. Analog ist der Einsatz von Chatbots als digitaler Ansprechpartner öffentlicher Verwaltungen denkbar. Sie könnten Bürgern helfen, sich innerhalb der behördlichen Strukturen zu orientieren und Verwaltungsleistungen effizient und effektiv in Anspruch zu nehmen.
Diese Arbeit überprüft den Einsatz eines Chatbots in der öffentlichen Verwaltung hinsichtlich der entstehenden Kosten und des erwartbaren Nutzens. Auf Basis einer umfangreichen Literaturauswertung und der prototypischen Realisierung eines Chatbots für ein Stadtportal werden dabei Herausforderungen dieser Anwendungsdomäne herausgearbeitet, konkrete Funktionsweise und Implementierungsstrategien von Chatbots erörtert und einige Erfolgsfaktoren formuliert, die den Kern einer Handlungsempfehlung für Entscheidungsträger öffentlicher Verwaltungen bilden.
Failure prognostic builds up on constant data acquisition and processing and fault diagnosis and is an essential part of predictive maintenance of smart manufacturing systems enabling condition based maintenance, optimised use of plant equipment, improved uptime and yield and to prevent safety problems. Given known control inputs into a plant and real sensor outputs or simulated measurements, the model-based part of the proposed hybrid method provides numerical values of unknown parameter degradation functions at sampling time points by the evaluation of equations that have been derived offline from a bicausal diagnostic bond graph. These numerical values are computed concurrently to the constant monitoring of a system and are stored in a buffer of fixed length. The data-driven part of the method provides a sequence of remaining useful life estimates by repeated projection of the parameter degradation into the future based on the use of values in a sliding time window. Existing software can be used to determine the best fitting function and can account for its random parameters. The continuous parameter estimation and their projection into the future can be performed in parallel for multiple isolated simultaneous parametric faults on a multicore, multiprocessor computer.
The proposed hybrid bond graph model-based, data-driven method is verified by an offline simulation case study of a typical power electronic circuit. It can be used to implement embedded systems that enable cooperating machines in smart manufacturing to perform prognostic themselves.
Trust is the lubricant of the sharing economy. This is true especially in peer-to-peer carsharing, in which one leaves a highly valuable good to a stranger in the hope of getting it back unscathed. Nowadays, ratings of other users are major mechanisms for establishing trust. To foster uptake of peer-to-peer carsharing, connected car technology opens new possibilities to support trust-building, e.g., by adding driving behavior statistics to users' profiles. However, collecting such data intrudes into rentees' privacy. To explore the tension between the need for trust and privacy demands, we conducted three focus group and eight individual interviews. Our results show that connected car technologies can increase trust for car owners and rentees not only before but also during and after rentals. The design of such systems must allow a differentiation between information in terms of type, the context, and the negotiability of information disclosure.
Bei genauer Betrachtung heutiger Sharing Plattformen wie AirBnB, Uber, Drivy oder Fairleihen fällt auf, dass diese eines gemein haben. Als Plattformökonomien basieren sie auf mindestens zwei Nutzergruppen, Anbietern und Nachfragern für Güter oder Dienstleistungen. Ein Problem solcher zweioder mehrseitigen Märkte ist jedoch häufig, dass der Wertezuwachs, der durch die Nutzer generiert wird, nicht gleichmäßig unter der Plattform und den aktiven Nutzern verteilt wird, sondern meist ausschließlich als Gewinn an die Plattformen geht. Mit der Blockchain-Technologie könnte dieses Problem gelöst werden, indem der Informations- und Wertetransfer sicher und dezentral organisiert wird und viele Funktionen traditioneller Intermediäre dadurch obsolet werden. Diese Arbeit bietet einen Überblick über Anwendungsfelder und das Grundkonzept der Sharing Economy. Wir zeigen auf, wie sich Geschäftsmodelle und Infrastrukturen in einer Blockchain abbilden lassen, welche Potentiale eine Blockchain-basierte Infrastruktur bietet, wann diese in der Sharing Economy sinnvoll sein kann und welche Probleme dadurch gelöst werden können.
Die Motive für die Einführung von Public Cloud Services liegen oft im Bereich der Kosteneinsparung und Qualitätsverbesserung. Vielfach werden bei der erstmaligen Einführung vermeidbare Fehler gemacht, die im Nachhinein den Erfolg des Vorhabens schmälern. Der Beitrag beschreibt ein aus Sicht der Beratungspraxis bewährtes Vorgehensmodell für die Einführung und Nutzung von Public Cloud Services unter besonderer Berücksichtigung von Microsoft Cloud Services.
Coumarin as a structural component of substrates and probes for serine and cysteine proteases
(2020)
Im Rahmen dieser Forschungsarbeit wurde eine praxisorientierte Methode entwickelt, die es ermöglicht, Bodenproben nach ihrer Entnahme auf dem Feld aufzubereiten und hinsichtlich ihres Mikroplastikgehaltes analysieren zu können. Die Extraktionsmethode wurde bereits für zwei Polymere, PA 12 und PE (Mulchfolienpartikel), mit Wiederfindungsraten von je 100 % für Partikel größer als 0,5 mm validiert. Für Partikel größer als 63 μm liegt die Wiederfindungsrate für PE-Mulchfolienpartikel bei 97 % beziehungs-weise für PA-Partikel bei 86 %. Weiterhin wurden verschiedene spektroskopische Detektions-methoden untersucht und hinsichtlich ihrer Potentiale und Grenzen miteinander verglichen. Dabei wurde festgestellt, dass die Digitalmikroskopie zwar sehr gut geeignet ist, die Farbe, Größe, Form und Anzahl der Partikel zu bestimmen, jedoch stark von der subjektiven Einschätzung abhängig ist. Sie sollte daher in jedem Fall mit einer weiteren Detektionsmethode kombiniert werden. In dieser Arbeit wurde hierzu die ATR-FTIR-Spektroskopie verwendet. Diese ermöglicht zusätzlich die Bestimmung des Polymertyps einzelner Partikel mit einer unteren Nachweisgrenze von 500 μm. Die Methode konnte auf insgesamt fünf landwirtschaftlich genutzten Flächen angewendet werden, wovon zwei konventionell und drei ökologisch bewirtschaftet werden. Um einen ersten Eindruck über die aktuelle Mikroplastik-Belastung von Agrarböden zu erhalten, wurden die mit Hilfe der in dieser Forschungsarbeit entwickelten Methode erhaltenen Ergebnisse extrapoliert und als Emissionskoeffizienten in verschiedenen Einheiten angegeben.
In der heutigen Zeit nimmt die Bedeutung schlanker und effektiver Prozesse in Unternehmen vor dem Hintergrund des Wettbewerbs sowie Kostendrucks stetig zu. Um dieser Herausforderung entgegenzuwirken, fokussieren sich Unternehmen auf die Identifikation neuer innovativer Potenziale. Aufgrund der Tatsache, dass monotone und regelbasierte Prozesse durch Softwareroboter automatisiert werden können, ist das Interesse an Robotic Process Automation (RPA) in den letzten Jahren stetig gestiegen. Bevor sich Unternehmen allerdings für oder gegen den Einsatz von RPA entscheiden, ist es zunächst notwendig, dass die Entscheidungsträger ein Verständnis von RPA erlangen sowie die entsprechenden Einsatzpotenziale und Risiken einschätzen können. Dieser Artikel trägt diesem Bedürfnis Rechnung, indem es diese auf Basis einer Literaturrecherche ermittelt und bewertet. Im Ausblick wird das zukünftige Potenzial von RPA eingeschätzt.
Surface-enhanced Raman spectroscopy (SERS) with subsequent chemometric evaluation was performed for the rapid and non-destructive differentiation of seven important meat-associated microorganisms, namely Brochothrix thermosphacta DSM 20171, Pseudomonas fluorescens DSM 4358, Salmonella enterica subsp. enterica sv. Enteritidis DSM 14221, Listeria monocytogenes DSM 19094, Micrococcus luteus DSM 20030, Escherichia coli HB101 and Bacillus thuringiensis sv. israelensis DSM 5724. A simple method for collecting spectra from commercial paper-based SERS substrates without any laborious pre-treatments was used. In order to prepare the spectroscopic data for classification at genera level with a subsequent chemometric evaluation consisting of principal component analysis and discriminant analysis, a pre-processing method with spike correction and sum normalisation was performed. Because of the spike correction rather than exclusion, and therefore the use of a balanced data set, the multivariate analysis of the data is significantly resilient and meaningful. The analysis showed that the differentiation of meat-associated microorganisms and thereby the detection of important meat-related pathogenic bacteria was successful on genera level and a cross-validation as well as a classification of ungrouped data showed promising results, with 99.5 % and 97.5 %, respectively.
The present thesis elucidates the development of (i) a series of small molecule inhibitors reacting in a covalent-irreversible manner with the targeted proteases and (ii) a fluorescently labeled activity-based probe as a pharmacological tool compound for investigation of specific functions of the mentioned enzymes in vitro. Herein, the rational design, organic synthesis and quantitative structure-activity-relationships are described extensively.
Im Rahmen der Arbeit wurde Kraft-Lignin mit Natriumsulfit demethyliert, um den Gehalt an aromatischen Hydroxygruppen zu erhöhen und damit die Reaktivität des Lignins in Bezug auf Polyurethan-Synthesen zu erhöhen. Variiert wurden die Demethylierungstemperatur (72°C, 90°C) sowie der pH-Wert zur Isolierung des Kraft-Lignins (pH 2, 3, 4 und 5). Die Analyse der demethylierten Proben erfolgte mittels differentieller UV-Spektroskopie und der OH-Gehaltbestimmung via automatischer Titration (angelehnt an ISO 14900:2001(E)). Weitere Untersuchungen umfassten Löslichkeitstests sowie Strukturanalysen via FTIR- und UV/Vis-Spektroskopie.
Validierung einer Web-Applikation zum Fern-Monitoring von Belastungs- und Erholungsparametern
(2020)
Simultan zur agilen Entwicklung einer Web-Applikation, die Parameter der Belastungs- und Beanspruchungssteuerung erfasst, wurden die implementierten Belastungs- und Erholungs-parameter an freiwilligen Testern/innen in der Praxis überprüft. Um sowohl die Applikation als auch die z.T. selbst entwickelten Kenngrößen auf ihre externe Validität hin zu bewerten, werden diese regressionsanalytisch bearbeitet.
OSC data
(2020)
An internal model of self-motion provides a fundamental basis for action in our daily lives, yet little is known about its development. The ability to control self-motion develops in youth and often deteriorates with advanced age. Self-motion generates relative motion between the viewer and the environment. Thus, the smoothness of the visual motion created will vary as control improves. Here, we study the influence of the smoothness of visually simulated self-motion on an observer's ability to judge how far they have travelled over a wide range of ages. Previous studies were typically highly controlled and concentrated on university students. But are such populations representative of the general public? And are there developmental and sex effects? Here, estimates of distance travelled (visual odometry) during visually induced self-motion were obtained from 466 participants drawn from visitors to a public science museum. Participants were presented with visual motion that simulated forward linear self-motion through a field of lollipops using a head-mounted virtual reality display. They judged the distance of their simulated motion by indicating when they had reached the position of a previously presented target. The simulated visual motion was presented with or without horizontal or vertical sinusoidal jitter. Participants' responses indicated that they felt they travelled further in the presence of vertical jitter. The effectiveness of the display increased with age over all jitter conditions. The estimated time for participants to feel that they had started to move also increased slightly with age. There were no differences between the sexes. These results suggest that age should be taken into account when generating motion in a virtual reality environment. Citizen science studies like this can provide a unique and valuable insight into perceptual processes in a truly representative sample of people.
Digital Business
(2020)
Digital Business behandelt die Besonderheiten digitaler Geschäftsmodelle, den Umgang mit Daten, erläutert die Funktionsweise digitaler Märkte und deren Auswirkungen auf Servicefunktionen wie HR, Kommunikation, Finanzierung und Marketing. Zudem werden wesentliche Erfolgsfaktoren wie agiles Management und Customer Experience behandelt. Insgesamt haben 30 Experten mit ihrem spezifischem Know How an der Erstellung des praxisorientierten Litello-eBook mitgearbeitet, dass sich auch gut als Basis für einschlägige Lehrveranstaltung anbietet.
Multiwalled carbon nanotubes (MWCNTs) were easily and efficiently functionalised with highly cross-linked polyamines. The radical polymerisation of two bis-vinylimidazolium salts in the presence of pristine MWCNTs and azobisisobutyronitrile (AIBN) as a radical initiator led to the formation of materials with a high functionalisation degree. The subsequent treatment with sodium borohydride gave rise to the reduction of imidazolium moieties with the concomitant formation of secondary and tertiary amino groups. The obtained materials were characterised by thermogravimetric analysis (TGA), elemental analysis, solid state 13C-NMR, Fourier-transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), potentiometric titration, and temperature programmed desorption of carbon dioxide (CO2-TPD). One of the prepared materials was tested as a heterogeneous base catalyst in C–C bond forming reactions such as the Knoevenagel condensation and Henry reaction. Furthermore, two examples concerning a sequential one-pot approach involving two consecutive reactions, namely Knoevenagel and Michael reactions, were reported.
Alkaline methanol oxidation is an important electrochemical process in the design of efficient fuel cells. Typically, a system of ordinary differential equations is used to model the kinetics of this process. The fitting of the parameters of the underlying mathematical model is performed on the basis of different types of experiments, characterizing the fuel cell. In this paper, we describe generic methods for creation of a mathematical model of electrochemical kinetics from a given reaction network, as well as for identification of parameters of this model. We also describe methods for model reduction, based on a combination of steady-state and dynamical descriptions of the process. The methods are tested on a range of experiments, including different concentrations of the reagents and different voltage range.
Digitale Güter
(2020)
Fundamental hydrogen storage properties of TiFe-alloy with partial substitution of Fe by Ti and Mn
(2020)
TiFe intermetallic compound has been extensively studied, owing to its low cost, good volumetric hydrogen density, and easy tailoring of hydrogenation thermodynamics by elemental substitution. All these positive aspects make this material promising for large-scale applications of solid-state hydrogen storage. On the other hand, activation and kinetic issues should be amended and the role of elemental substitution should be further understood. This work investigates the thermodynamic changes induced by the variation of Ti content along the homogeneity range of the TiFe phase (Ti:Fe ratio from 1:1 to 1:0.9) and of the substitution of Mn for Fe between 0 and 5 at.%. In all considered alloys, the major phase is TiFe-type together with minor amounts of TiFe2 or \b{eta}-Ti-type and Ti4Fe2O-type at the Ti-poor and rich side of the TiFe phase domain, respectively. Thermodynamic data agree with the available literature but offer here a comprehensive picture of hydrogenation properties over an extended Ti and Mn compositional range. Moreover, it is demonstrated that Ti-rich alloys display enhanced storage capacities, as long as a limited amount of \b{eta}-Ti is formed. Both Mn and Ti substitutions increase the cell parameter by possibly substituting Fe, lowering the plateau pressures and decreasing the hysteresis of the isotherms. A full picture of the dependence of hydrogen storage properties as a function of the composition will be discussed, together with some observed correlations.
In dieser vorliegenden Arbeit wurde der photolytische und photokatalytische Abbau von Lignin untersucht. Eine Charakterisierung des verwendeten Photoreaktors wurde mittels Kalium-Ferrioxalat-Aktinometrie durchgeführt. Zur Analyse der abgebauten Lignine wurde eine Optimierung einer bereits bestehenden Methode zur Bestimmung des Hydroxylgehaltes erarbeitet. Die Bestimmung der Hydroxylgehalte erfolgte demnach bei Raumtemperatur nach einer Acetylierungsdauer von 72 h und zeigte eine Abnahme der Hydroxylgehalte mit andauernder UV-Bestrahlung. Selbige Beobachtung konnte mit Hilfe der ATR-IR-Spektroskopie gemacht werden. Zusätzlich konnte die Bildung von Carbonsäuren und der Abbau von aromatischen Strukturen detektiert werden. Der Abbau aromatischer Strukturen konnte ebenfalls durch UV-VIS-Spektroskopie gezeigt werden. Eine Vermutung, dass es sich bei dem Abbauprozess um einen oxidativen Mechanismus handelt, konnte mit dem Abbau von Hydroxylgruppen über eine Bildung von Carbonsäuren zu Kohlenstoffdioxid bestätigt werden. Eine Freisetzung von Kohlenstoffdioxid konnte durch eine Bestimmung des IC festgestellt werden. Die Ergebnisse der Gel-Permeations-Chromatographie zusammen mit einer TOC-Analyse zeigen einen Abbau der molaren Masse des Lignins auf. Es konnten Fragmente mit einer Molmasse ähnlich der Monomere des Lignins gefunden werden. Der eingesetzte Photokatalysator wurde via Röntgenbeugung untersucht und konnte als das hoch photokatalytisch aktive P25 von Degussa identifiziert werden. Trotz des Einsatzes verschiedener Katalysatorkonzentrationen in einem Bereich von 0-0,5 g L^(-1) konnte kein Einfluss des Photokatalysators auf den Abbauprozess des Lignins beobachtet werden.