Filtern
Erscheinungsjahr
Dokumenttyp
- Wissenschaftlicher Artikel (212)
- Konferenzveröffentlichung (210)
- Teil eines Buches (Kapitel) (31)
- Sonstiges (29)
- Video (14)
- Buch (Monographie) (13)
- Preprint (9)
- Dissertation (4)
- Arbeitspapier (4)
- Bericht (3)
- Beitrag zu einer (nichtwissenschaftlichen) Zeitung oder Zeitschrift (2)
- Lehrmaterial (2)
- Masterarbeit (1)
Sprache
- Englisch (534) (entfernen)
Schlagworte
- Robotik (8)
- Flugkörper (7)
- UAV (7)
- Rettungsrobotik (5)
- Polymer-Elektrolytmembran-Brennstoffzelle (4)
- adhesion (4)
- Bionik (3)
- Erweiterte Realität <Informatik> (3)
- Gespenstschrecken (3)
- Haftorgan (3)
- OCSR (3)
- stick insects (3)
- Augmented Reality (2)
- CDK (2)
- Competency-Oriented Exams (2)
- Deep learning (2)
- Dissipative Particle Dynamics (2)
- Field measurement (2)
- Human-Robot Interaction (2)
- Solar modules (2)
- Twitter <Softwareplattform> (2)
- biomimicry (2)
- hydraulic compression (2)
- modular stack design (2)
- open quantum systems (2)
- social innovation (2)
- carbon nanofibers, platinum electrodeposition, ele ctrochemical surface area (1)
- 360 degree Feedback (1)
- 360° Panorama (1)
- AI (1)
- API 1130 (1)
- Aerosol (1)
- Aggregation-prone (1)
- Air handling unit (1)
- Alternative Geschäftsmodelle (1)
- Amylase, Enzymcharakterisierung (1)
- Anorganische Analyse (1)
- Artificial Intelligence (1)
- Assessment Center (1)
- Assisted living technologies (1)
- Assistive robotics (1)
- Augmented Three-Phase AC-Railgun (1)
- Autonomous Agents (1)
- Bildverarbeitung (1)
- Biomechanics (1)
- Biomedical monitoring, Hospitals, Electrocardiography, Wireless communication, Patient monitoring, Wireless sensor networks (1)
- Biomimetics (1)
- Bone morphogenetic protein 2 (1)
- Brand theory (1)
- COIL (1)
- CPM (1)
- Carboxylate (1)
- Case-Study (1)
- Cell-free implant (1)
- Chemical image depiction (1)
- Chemical space (1)
- Chemical structure depictions (1)
- Cheminformatics (1)
- Chemistry Development Kit (1)
- Chemistry Development Kit, CDK, Molecule fragmentation, In silico fragmentation, Scaffolds, Functional groups, Glycosidic moieties, Rich client, Graphical user interface, GUI (1)
- Chief Executive Officer (1)
- Climate change (1)
- Clustering (1)
- Codegenerierung (1)
- Communication management (1)
- Constructive Alignment (1)
- Continuous Assessment (1)
- Continuous Queries (1)
- Cookie <Internet> (1)
- Cr(VI) and Zn(II) cations (1)
- Crowdfunding (1)
- Data Collection (1)
- Data Journalism (1)
- Datalog (1)
- Datenjournalismus (1)
- Datensatz (1)
- Datenschutz (1)
- Deductive Databases (1)
- Deep Learning (1)
- Depiction generator image augmentation (1)
- Deutschland / Technische Regeln für brennbare Flüssigkeiten (1)
- Dissipative particle dynamics, DPD, Surfactant, Bilayer, Lamellar, Simulation, Mesoscopic (1)
- Distributed Software Development (1)
- E. coli SHuffle® T7 (1)
- Elastizitätsmodul (1)
- Elektrodenvorbereitung (1)
- Enterprise JavaBeans (1)
- Erneuerbare Energien (1)
- Europe (1)
- Evidence-based Management (1)
- Exams with Third-Party Applications (1)
- Fehlererkennung (1)
- Fehlerortung (1)
- Flipped Classroom (1)
- Flügelform (1)
- Formative Assessment (1)
- Fragmentation (1)
- Future capacity needs (1)
- Greek dept crisis (1)
- Hand-drawn images (1)
- Hands-free Interaction (1)
- Homogene Kühlung (1)
- Human-centered computing (1)
- Hydraulic cell compression (1)
- Hydraulic compression, Carbon Nano Fibers, PEM Fuel Cells, Catalyst utilization (1)
- Hydrogen evolution reaction (1)
- Hydrophilicity enhanced hBMP2 variant (1)
- ICP-Massenspektrometrie (1)
- Implantat (1)
- In-silico-design (1)
- Incremental Evaluation (1)
- Indigo (1)
- Interactive Voting Systems (1)
- Intercultural Collaboration (1)
- Journalismus (1)
- Juristenausbildung (1)
- Kalman filter (1)
- Kernspintomografie (1)
- Kohlenstoff (1)
- Kohlenstoff-Nanoröhre (1)
- Leadership Competencies (1)
- Leak detection (1)
- Leckerkennung (1)
- Leckortung (1)
- Lecksuchgerät (1)
- Lecküberwachung (1)
- Lüftungsanlage (1)
- MITRE (1)
- Machine Learning (1)
- Mapping (1)
- Maus (1)
- Media Brands (1)
- Media brand characteristics (1)
- Media positioning (1)
- Methodology (1)
- Middle-range Theory (1)
- Mikrofotografie (1)
- Mixed Reality (1)
- Molecule images (1)
- Multi-Agent System (1)
- Multiphase Rail Launcher (1)
- Mund-Nasen-Schutz (1)
- N,N,O Ligands (1)
- N,N′ Ligands (1)
- Nanofaser (1)
- Natural products (1)
- Naturstoff (1)
- NeRF (1)
- New Public Governance (1)
- New Public Management (1)
- New Work, Information and Communication Industry, Innovation, Organizational Goals, Survey (1)
- Normalisierung (1)
- OSINT (1)
- Object Recognition (1)
- Object-relational Mapping (1)
- Objektverfolgung (1)
- Ohrwurm (1)
- Online Programming Exams (1)
- Online Supervision (1)
- Online-Werbung (1)
- Optical Chemical Structure Recognition (1)
- Ortsbestimmung (1)
- PEM Electrolysis, Hydrogen, Hydraulic Compression, High Pressure (1)
- PEM electrolysis (1)
- PEM fuel cell (1)
- PEM fuel cell electrocatalysts, Carbon nanofibers, Oxygen plasma activation, Pulsed electroplating. (1)
- PEM fuel cells (1)
- PEM water electrolysis (1)
- PEM-Brennstoffzelle (1)
- Peer Assessment (1)
- Peer Instruction (1)
- People with disabilities (1)
- Performance prediction (1)
- Persistenz <Informatik> (1)
- Politische Berichterstattung (1)
- Polymere (1)
- Privatsphäre (1)
- Project-based Learning (1)
- PtCoMn (1)
- RDKit (1)
- RIS (1)
- Regeln der Technik (1)
- Rescue Robotics (1)
- Robot assistive drinking (1)
- Robot assistive eating (1)
- Rwanda (1)
- SARS-CoV-2 (1)
- Sauerstoffplasmaaktivierung (1)
- Scaffold (1)
- Scaffold network (1)
- Scaffold tree (1)
- Segmentation; Correlation; Diseases; Convolutional Neural Networks (1)
- Small UAVs (1)
- Smart Grid (1)
- Social Innovation (1)
- Social Learning (1)
- Social Media (1)
- Spondylodese (1)
- Stack <Brennstoffzelle> (1)
- Stellite 6; HVOF-spraying; Laser remelting; Cavitation erosion; Coatings (1)
- Student Activation (1)
- TRFL (1)
- Temperature coefficients (1)
- Ternary alloy catalyst preparation (1)
- Tetraplegie (1)
- Thermal Performance (1)
- Titanium; Al2O3–TiO2 coatings; Nanoindentation (1)
- Tracking (1)
- Transformative Teaching (1)
- Twitter (1)
- Update Propagation (1)
- Upscaling laboratory models (1)
- Urban heat island (1)
- Visual Monocular SLAM (1)
- Young´s modulus (1)
- Zinc (1)
- Zustandsmaschine (1)
- academic and job-related self-control demands (1)
- activated sludge (1)
- advanced persistent threats (1)
- aerosol (1)
- air hygiene (1)
- airborne infection (1)
- antecedents (1)
- artificial intelligence (1)
- assistive robotics (1)
- augmented reality (1)
- bacterial toxicity (1)
- balance (1)
- barrel cortex, cell types, multielectrode recordings, perception, psychophysics (1)
- bio-inspired functional surface (1)
- bioinspired (1)
- biomimetic (1)
- biomimetic materials (1)
- biomimetics; functional morphology; plant biomechanics; plant motion; strain analysis; structure–function relationship; 3D digital image correlation (3D-DIC); Hakea sericea; Hakea salicifolia (1)
- blockchain (1)
- bloxberg (1)
- carbon nano fibres (1)
- carbon nanofibers, platinum electrodeposition, electrocatalysts (1)
- cartilage defect (1)
- cartilage regeneration (1)
- chlorinated phenols (1)
- cluster (1)
- cobot (1)
- collaborative online international learning (COIL) (1)
- compassionate love (1)
- composition (1)
- conical intersection (1)
- consent banner (1)
- cookie banner (1)
- cookies (1)
- critical review (1)
- cyber kill chain (1)
- demagnetization cooling (1)
- design process (1)
- distributed software development (1)
- diversity (1)
- dlt (1)
- dynamic capabilities (1)
- efficiency of exciton transfer (1)
- electrode preparation (1)
- empowerment (1)
- entrepreneurial diversity (1)
- entrepreneurship (1)
- ethereum (1)
- ethics (1)
- excitation energy transfer (1)
- expert interviews (1)
- face mask (1)
- farming (1)
- gender stereotypes (1)
- gender-sensitive design (1)
- gender-specific design (1)
- human robot interaction (1)
- human-centered design (1)
- human-robot collaboration (1)
- hybrid sensor system (1)
- ingots (1)
- innovation (1)
- intercultural collaboration (1)
- interdisciplinary students project (1)
- international comparative study (1)
- intersectionality (1)
- irritation (1)
- leak locating (1)
- leak monitoring (1)
- long-term toxicity (1)
- luminescent bacteria (1)
- machine learning (1)
- managerial vs. non-managerial actors (1)
- measurement study (1)
- media accountability (1)
- microfoundations (1)
- multi-level model of competence (1)
- narcissism (1)
- neutrality (1)
- nonadiabatic dynamics (1)
- noncommuting fluctuations (1)
- nonequilibrium quantum transport (1)
- normalisation (1)
- open science (1)
- optical chemical structure recognition (1)
- oxygen plasma activation (1)
- pH-shift elution (1)
- participatory design (1)
- phishing (1)
- photovoltaic power systems (1)
- poa (1)
- poe (1)
- policymakers (1)
- political journalism (1)
- privacy (1)
- product development (1)
- project-based learning (1)
- projection (1)
- public policy (1)
- quality standards (1)
- quantum dissipation (1)
- reconnaissance (1)
- relevance (1)
- respiration inhibition (1)
- risk management (1)
- role identity (1)
- sensor fusion (1)
- servant leadership (1)
- shared user control (1)
- silicon (1)
- solar cells (1)
- solution finding (1)
- spatial policy (1)
- state machine (1)
- study and working time per week (1)
- sustainable development (1)
- television news coverage (1)
- theorising (1)
- trait self-control (1)
- transport (1)
- tree frog (1)
- user acceptance (1)
- ventilation (1)
- vibronic coupling (1)
- virtual reality (1)
- visual cues (1)
- visualization techniques (1)
- watchblogs (1)
- web measurement (1)
- Änderung (1)
Institut
- Westfälisches Institut für Gesundheit (115)
- Institut für Internetsicherheit (56)
- Informatik und Kommunikation (51)
- Elektrotechnik und angewandte Naturwissenschaften (50)
- Wirtschaft und Informationstechnik Bocholt (46)
- Westfälisches Energieinstitut (44)
- Institut für biologische und chemische Informatik (37)
- Maschinenbau Bocholt (37)
- Institut Arbeit und Technik (15)
- Wirtschaftsingenieurwesen (15)
MFsim - An open Java all-in-one rich-client simulation environment for mesoscopic simulation
MFsim is an open Java all-in-one rich-client computing environment for mesoscopic simulation with Jdpd as its default simulation kernel for Molecular Fragment Dissipative Particle Dynamics (DPD). The environment integrates and supports the complete preparation-simulation-evaluation triad of a mesoscopic simulation task. Productive highlights are a SPICES molecular structure editor, a PDB-to-SPICES parser for particle-based peptide/protein representations, a support of polymer definitions, a compartment editor for complex simulation box start configurations, interactive and flexible simulation box views including analytics, simulation movie generation or animated diagrams. As an open project, MFsim enables customized extensions for different fields of research.
MFsim uses several open libraries (see MFSimVersionHistory.txt for details and references below) and is published as open source under the GNU General Public License version 3 (see LICENSE).
MFsim has been described in the scientific literature and used for DPD studies.
Jdpd - An open Java Simulation Kernel for Molecular Fragment Dissipative Particle Dynamics (DPD)
Jdpd is an open Java simulation kernel for Molecular Fragment Dissipative Particle Dynamics (DPD) with parallelizable force calculation, efficient caching options and fast property calculations. It is characterized by an interface and factory-pattern driven design for simple code changes and may help to avoid problems of polyglot programming. Detailed input/output communication, parallelization and process control as well as internal logging capabilities for debugging purposes are supported. The kernel may be utilized in different simulation environments ranging from flexible scripting solutions up to fully integrated “all-in-one” simulation systems like MFsim.
Since Jdpd version 1.6.1.0 Jdpd is available in a (basic) double-precision version and a (derived) single-precision version (= JdpdSP) for all numerical calculations, where the single precision version needs about half the memory of the double precision version.
Jdpd uses the Apache Commons Math and Apache Commons RNG libraries and is published as open source under the GNU General Public License version 3. This repository comprises the Java bytecode libraries (including the Apache Commons Math and RNG libraries), the Javadoc HTML documentation and the Netbeans source code packages including Unit tests.
Jdpd has been described in the scientific literature (the final manuscript 2018 - van den Broek - Jdpd - Final Manucsript.pdf is added to the repository) and used for DPD studies (see references below).
See text file JdpdVersionHistory.txt for a version history with more detailed information.
Stereo Camera Setup for 360° Digital Image Correlation to Reveal Smart Structures of Hakea Fruits
(2024)
About forty years after its first application, digital image correlation (DIC) has become an established method for measuring surface displacements and deformations of objects under stress. To date, DIC has been used in a variety of in vitro and in vivo studies to biomechanically characterise biological samples in order to reveal biomimetic principles. However, when surfaces of samples strongly deform or twist, they cannot be thoroughly traced. To overcome this challenge, different DIC setups have been developed to provide additional sensor perspectives and, thus, capture larger parts of an object’s surface. Herein, we discuss current solutions for this multi-perspective DIC, and we present our own approach to a 360 DIC system based on a single stereo-camera setup. Using this setup, we are able to characterise the desiccation-driven opening mechanism of two woody Hakea fruits over their entire surfaces. Both the breaking mechanism and the actuation of the two valves in predominantly dead plant material are models for smart materials. Based on these results, an evaluation of the setup for 360 DIC regarding its use in deducing biomimetic principles is given. Furthermore, we propose a way to improve and apply the method for future measurements.
An automated pipeline for comprehensive calculation of intermolecular interaction energies based on molecular force-fields using the Tinker molecular modelling package is presented. Starting with non-optimized chemically intuitive monomer structures, the pipeline allows the approximation of global minimum energy monomers and dimers, configuration sampling for various monomer-monomer distances, estimation of coordination numbers by molecular dynamics simulations, and the evaluation of differential pair interaction energies. The latter are used to derive Flory-Huggins parameters and isotropic particle-particle repulsions for Dissipative Particle Dynamics (DPD). The computational results for force fields MM3, MMFF94, OPLSAA and AMOEBA09 are analyzed with Density Functional Theory (DFT) calculations and DPD simulations for a mixture of the non-ionic polyoxyethylene alkyl ether surfactant C10E4 with water to demonstrate the usefulness of the approach.
n-type silicon modules
(2023)
The photovoltaic industry is facing an exponential growth in the recent years fostered by a dramatic decrease in installation prices. This cost reduction is achieved by means of several mechanisms. First, because of the optimization of the design and installation process of current PV projects, and second, by the optimization, in terms of performance, in the manufacturing techniques and material combinations within the modules, which also has an impact on both, the installation process, and the levelized cost of electricity (LCOE).
One popular trend is to increase the power delivered by photovoltaic modules, either by using larger wafer sizes or by combining more cells within the module unit. This solution means a significant increase in the size of these devices, but it implies an optimization in the design of photovoltaic plants. This results in an installation cost reduction which turns into a decrease in the LCOE.
However, this solution does not represent a breakthrough in addressing the real challenge of the technology which affects the module requirements. The innovation efforts must be focused on improving the modules capability to produce energy without enlarging the harvesting area. This challenge can be faced by approaching some of the module characteristics which are summarized in this chapter.
This paper reveals various approaches undertaken over more than two decades of teaching undergraduate programming classes at different Higher Education Institutions, in order to improve student activation and participation in class and consequently teaching and learning effectiveness.
While new technologies and the ubiquity of smartphones and internet access has brought new tools to the classroom and opened new didactic approaches, lessons learned from this personal long-term study show that neither technology itself nor any single new and often hyped didactic approach ensured sustained improvement of student activation. Rather it needs an integrated yet open approach towards a participative learning space supported but not created by new tools, technology and innovative teaching methods.
This paper presents a pragmatic approach for stepwise introduction of peer assessment elements in undergraduate programming classes, discusses some lessons learned so far and directions for further work. Students are invited to challenge their peers with their own programming exercises to be submitted through Moodle and evaluated by other students according to a predefined rubric and supervised by teaching assistants. Preliminary results show an increased activation and motivation of students leading to a better performance in the final programming exams.
In this work a mathematical approach to calculate solar panel temperature based on measured irradiance, temperature and wind speed is applied. With the calculated module temperature, the electrical solar module characteristics is determined. A program developed in MatLab App Designer allows to import measurement data from a weather station and calculates the module temperature based on the mathematical NOCT and stationary approach with a time step between the measurements of 5 minutes. Three commercially available solar panels with different cell and interconnection technologies are used for the verification of the established models. The results show a strong correlation between the measured and by the stationary model predicted module temperature with a coefficient of determination R2 close to 1 and a root mean square deviation (RMSE) of ≤ 2.5 K for a time period of three months. Based on the predicted temperature, measured irradiance in module plane and specific module information the program models the electrical data as time series in 5-minute steps. Predicted to measured power for a time period of three months shows a linear correlation with an R2 of 0.99 and a mean absolute error (MAE) of 3.5, 2.7 and 4.8 for module ID 1, 2 and 3. The calculated energy (exemplarily for module ID 2) based on the measured, calculated by the NOCT and stationary model for this time period is 118.4 kWh, resp. 116.7 kWh and 117.8 kWh. This is equivalent to an uncertainty of 1.4% for the NOCT and 0.5% for the stationary model.
Advanced Determination of Temperature Coefficients of Photovoltaic Modules by Field Measurements
(2023)
In this work data from outdoor measurements, acquired over the course of up to three years on commercially available solar panels, is used to determine the temperature coefficients and compare these to the information as stated by the producer in the data sheets. A program developed in MatLab App Designer allows to import the electrical and ambient measurement data. Filter algorithms for solar irradiance narrow the irradiance level down to ~1000 W/m2 before linear regression methods are applied to obtain the temperature coefficients. A repeatability investigation proves the accuracy of the determined temperature coefficients which are in good agreement to the supplier specification if the specified values for power are not larger than -0.3%/K. Further optimization is achieved by applying wind filter techniques and days with clear sky condition. With the big (measurement) data on hand it was possible to determine the change of the temperature coefficients for varying irradiance. As stated in literature we see an increase of the temperature coefficient of voltage and a decline for the temperature coefficient of power with increasing irradiance.
As a rule, an experiment carried out at school or in undergraduate study
courses is rather simple and not very informative. However, when the experiments
are to be performed using modern methods, they are often abstract and
difficult to understand. Here, we describe a quick and simple experiment,
namely the enzymatic characterization of ptyalin (human salivary amylase)
using a starch degradation assay. With the experimental setup presented here,
enzyme parameters, such as pH optimum, temperature optimum, chloride
dependence, and sensitivity to certain chemicals can be easily determined. This
experiment can serve as a good model for enzyme characterization in general,
as modern methods usually follow the same principle: determination of the
activity of the enzyme under different conditions. As different alleles occur in
humans, a random selection of test subjects will be quite different with regard
to ptyalin activities. Therefore, when the students measure their own ptyalin
activity, significant differences will emerge, and this will give them an idea of
the genetic diversity in human populations. The evaluation has shown that the
pupils have gained a solid understanding of the topic through this experiment.
With ongoing developments in the field of smart cities and digitalization in general, data is becoming a driving factor and value stream for new and existing economies alike. However, there exists an increasing centralization and monopolization of data holders and service providers, especially in the form of the big US-based technology companies in the western world and central technology providers with close ties to the government in the Asian regions. Self Sovereign Identity (SSI) provides the technical building blocks to create decentralized data-driven systems, which bring data autonomy back to the users. In this paper we propose a system in which the combination of SSI and token economy based incentivisation strategies makes it possible to unlock the potential value of data-pools without compromising the data autonomy of the users.
The European General Data Protection Regulation (GDPR), which went into effect in May 2018, brought new rules for the processing of personal data that affect many business models, including online advertising. The regulation’s definition of personal data applies to every company that collects data from European Internet users. This includes tracking services that, until then, argued that they were collecting anonymous information and data protection requirements would not apply to their businesses.
Previous studies have analyzed the impact of the GDPR on the prevalence of online tracking, with mixed results. In this paper, we go beyond the analysis of the number of third parties and focus on the underlying information sharing networks between online advertising companies in terms of client-side cookie syncing. Using graph analysis, our measurement shows that the number of ID syncing connections decreased by around 40 % around the time the GDPR went into effect, but a long-term analysis shows a slight rebound since then. While we can show a decrease in information sharing between third parties, which is likely related to the legislation, the data also shows that the amount of tracking, as well as the general structure of cooperation, was not affected. Consolidation in the ecosystem led to a more centralized infrastructure that might actually have negative effects on user privacy, as fewer companies perform tracking on more sites.
In the modern Web, service providers often rely heavily on third parties to run their services. For example, they make use of ad networks to finance their services, externally hosted libraries to develop features quickly, and analytics providers to gain insights into visitor behavior.
For security and privacy, website owners need to be aware of the content they provide their users. However, in reality, they often do not know which third parties are embedded, for example, when these third parties request additional content as it is common in real-time ad auctions.
In this paper, we present a large-scale measurement study to analyze the magnitude of these new challenges. To better reflect the connectedness of third parties, we measured their relations in a model we call third party trees, which reflects an approximation of the loading dependencies of all third parties embedded into a given website. Using this concept, we show that including a single third party can lead to subsequent requests from up to eight additional services. Furthermore, our findings indicate that the third parties embedded on a page load are not always deterministic, as 50 % of the branches in the third party trees change between repeated visits. In addition, we found that 93 % of the analyzed websites embedded third parties that are located in regions that might not be in line with the current legal framework. Our study also replicates previous work that mostly focused on landing pages of websites. We show that this method is only able to measure a lower bound as subsites show a significant increase of privacy-invasive techniques. For example, our results show an increase of used cookies by about 36 % when crawling websites more deeply.
Advanced Persistent Threats (APTs) are one of the main challenges in modern computer security. They are planned and performed by well-funded, highly-trained and often state-based actors. The first step of such an attack is the reconnaissance of the target. In this phase, the adversary tries to gather as much intelligence on the victim as possible to prepare further actions. An essential part of this initial data collection phase is the identification of possible gateways to intrude the target.
In this paper, we aim to analyze the data that threat actors can use to plan their attacks. To do so, we analyze in a first step 93 APT reports and find that most (80 %) of them begin by sending phishing emails to their victims. Based on this analysis, we measure the extent of data openly available of 30 entities to understand if and how much data they leak that can potentially be used by an adversary to craft sophisticated spear phishing emails. We then use this data to quantify how many employees are potential targets for such attacks. We show that 83 % of the analyzed entities leak several attributes of uses, which can all be used to craft sophisticated phishing emails.
The set of transactions that occurs on the public ledger of an Ethereum network in a specific time frame can be represented as a directed graph, with vertices representing addresses and an edge indicating the interaction between two addresses.
While there exists preliminary research on analyzing an Ethereum network by the means of graph analysis, most existing work is focused on either the public Ethereum Mainnet or on analyzing the different semantic transaction layers using static graph analysis in order to carve out the different network properties (such as interconnectivity, degrees of centrality, etc.) needed to characterize a blockchain network. By analyzing the consortium-run bloxberg Proof-of-Authority (PoA) Ethereum network, we show that we can identify suspicious and potentially malicious behaviour of network participants by employing statistical graph analysis. We thereby show that it is possible to identify the potentially malicious
exploitation of an unmetered and weakly secured blockchain network resource. In addition, we show that Temporal Network Analysis is a promising technique to identify the occurrence of anomalies in a PoA Ethereum network.
Software updates take an essential role in keeping IT environments secure. If service providers delay or do not install updates, it can cause unwanted security implications for their environments. This paper conducts a large-scale measurement study of the update behavior of websites and their utilized software stacks. Across 18 months, we analyze over 5.6M websites and 246 distinct client- and server-side software distributions. We found that almost all analyzed sites use outdated software. To understand the possible security implications of outdated software, we analyze the potential vulnerabilities that affect the utilized software. We show that software components are getting older and more vulnerable because they are not updated. We find that 95 % of the analyzed websites use at least one product for which a vulnerability existed.
A Crypto-Token Based Charging Incentivization
Scheme for Sustainable Light Electric Vehicle
Sharing
(2021)
The ecological impact of shared light electric vehicles (LEV) such as kick scooters is still widely discussed. Especially the fact that the vehicles and batteries are collected using diesel vans in order to charge empty batteries with electricity of unclear origin is perceived as unsustainable. A better option could be to let the users charge the vehicles themselves whenever it is necessary. For this, a decentralized,flexible and easy to install network of off-grid solar charging stations could bring renewable electricity where it is needed without sacrificing the convenience of a free float sharing system. Since the charging stations are powered by solar energy the most efficient way to utilize them would be to charge the vehicles when the sun is shining. In order to make users charge the vehicle it is necessary to provide some form of benefit for
them doing so. This could be either a discount or free rides. A
particularly robust and well-established mechanism is controlling incentives via means of blockchain-based cryptotokens. This paper demonstrates a crypto-token based scheme for incentivizing users to charge sharing vehicles during times of considerable solar irradiation in order to contribute to more sustainable mobility services.
Third-party tracking is a common and broadly used technique on the Web. Different defense mechanisms have emerged to counter these practices (e.g. browser vendors that ban all third-party cookies). However, these countermeasures only target third-party trackers and ignore the first party because the narrative is that such monitoring is mostly used to improve the utilized service (e.g. analytical services). In this paper, we present a large-scale measurement study that analyzes tracking performed by the first party but utilized by a third party to circumvent standard tracking preventing techniques. We visit the top 15,000 websites to analyze first-party cookies used to track users and a technique called “DNS CNAME cloaking”, which can be used by a third party to place first-party cookies. Using this data, we show that 76% of sites effectively utilize such tracking techniques. In a long-running analysis, we show that the usage of such cookies increased by more than 50% over 2021.
Measurement studies are essential for research and industry alike to understand the Web’s inner workings better and help quantify specific phenomena. Performing such studies is demanding due to the dynamic nature and size of the Web. An experiment’s careful design and setup are complex, and many factors might affect the results. However, while several works have independently observed differences in
the outcome of an experiment (e.g., the number of observed trackers) based on the measurement setup, it is unclear what causes such deviations. This work investigates the reasons for these differences by visiting 1.7M webpages with five different measurement setups. Based on this, we build ‘dependency trees’ for each page and cross-compare the nodes in the trees. The results show that the measured trees differ considerably, that the cause of differences can be attributed to specific nodes, and that even identical measurement setups can produce different results.
Proof of Existence as a blockchain service has first been published in 2013 as a public notary service on the Bitcoin network and can be used to verify the existence of a particular file in a specific point of time without sharing the file or its content itself. This service is also available on the Ethereum based bloxberg network, a decentralized research infrastructure that is governed, operated and developed by an international consortium of research facilities. Since it is desirable to integrate the creation of this proof tightly into the research workflow, namely the acquisition and processing of research data, we show a simple to integrate MATLAB extension based solution with the concept being applicable to other programming languages and environments as well.
The number of publications describing chemical structures has increased steadily over the last decades. However, the majority of published chemical information is currently not available in machine-readable form in public databases. It remains a challenge to automate the process of information extraction in a way that requires less manual intervention - especially the mining of chemical structure depictions. As an open-source platform that leverages recent advancements in deep learning, computer vision, and natural language processing, DECIMER.ai (Deep lEarning for Chemical IMagE Recognition) strives to automatically segment, classify, and translate chemical structure depictions from the printed literature. The segmentation and classification tools are the only openly available packages of their kind, and the optical chemical structure recognition (OCSR) core application yields outstanding performance on all benchmark datasets. The source code, the trained models and the datasets developed in this work have been published under permissive licences. An instance of the DECIMER web application is available at https://decimer.ai.
Cookie notices (or cookie banners) are a popular mechanism for websites to provide (European) Internet users a tool to choose which cookies the site may set. Banner implementations range from merely providing information that a site uses cookies over offering the choice to accepting or denying all cookies to allowing fine-grained control of cookie usage. Users frequently get annoyed by the banner’s pervasiveness as they interrupt “natural” browsing on the Web. As a remedy, different browser extensions have been developed to automate the interaction with cookie banners.
In this work, we perform a large-scale measurement study comparing the effectiveness of extensions for “cookie banner interaction.” We configured the extensions to express different privacy choices (e.g., accepting all cookies, accepting functional cookies, or rejecting all cookies) to understand their capabilities to execute a user’s preferences. The results show statistically significant differences in which cookies are set, how many of them are set, and which types are set—even for extensions that aim to implement the same cookie choice. Extensions for “cookie banner interaction” can effectively reduce the number of set cookies compared to no interaction with the banners. However, all extensions increase the
tracking requests significantly except when rejecting all cookies.
To address the question which neocortical layers and cell types are important for the perception of a sensory stimulus, we performed multielectrode recordings in the barrel cortex of head-fixed mice performing a single-whisker go/no-go detection task with vibrotactile stimuli of differing intensities. We found that behavioral detection probability decreased gradually over the course of each session, which was well explained by a signal detection theory-based model that posits stable psychometric sensitivity and a variable decision criterion updated after each reinforcement, reflecting decreasing motivation. Analysis of multiunit activity demonstrated highest neurometric sensitivity in layer 4, which was achieved within only 30 ms after stimulus onset. At the level of single neurons, we observed substantial heterogeneity of neurometric sensitivity within and across layers, ranging from nonresponsiveness to approaching or even exceeding psychometric sensitivity. In all cortical layers, putative inhibitory interneurons on average proffered higher neurometric sensitivity than putative excitatory neurons. In infragranular layers, neurons increasing firing rate in response to stimulation featured higher sensitivities than neurons decreasing firing rate. Offline machine-learning-based analysis of videos of behavioral sessions showed that mice performed better when not moving, which at the neuronal level, was reflected by increased stimulus-evoked firing rates.
Moderating Role of Self-control Strength with Transformational Leadership and Adaptive Performance
(2013)
Based on a longitudinal sample of employees from the U.S. financial services industry (N=121), the present research examined the impact of transformational leadership on followers’ adaptive performance in change processes. Follower personality was taken into account as boundary condition by testing, if follower self-control strength as an individual trait moderated the relationship between transformational leadership and adaptive performance. In line with the developed hypothesis, results from a latent moderated structural equation model showed that followers’ self-control strength attenuated the relationship between transformational leadership and adaptive performance. Implications for research and practice are discussed.
Psychological Capital as Mediator between Transformational Leadership and Adaptive Performance
(2013)
In the realm of digital situational awareness during disaster situations, accurate digital representations,
like 3D models, play an indispensable role. To ensure the
safety of rescue teams, robotic platforms are often deployed
to generate these models. In this paper, we introduce an
innovative approach that synergizes the capabilities of compact Unmaned Arial Vehicles (UAVs), smaller than 30 cm, equipped with 360° cameras and the advances of Neural Radiance Fields (NeRFs). A NeRF, a specialized neural network, can deduce a 3D representation of any scene using 2D images and then synthesize it from various angles upon request. This method is especially tailored for urban environments which have experienced significant destruction, where the structural integrity of buildings is compromised to the point of barring entry—commonly observed post-earthquakes and after severe fires. We have tested our approach through recent post-fire scenario, underlining the efficacy of NeRFs even in challenging outdoor environments characterized by water, snow, varying light conditions, and reflective surfaces.
In this paper, we present a method for detecting objects of interest, including cars, humans, and fire, in aerial images captured by unmanned aerial vehicles (UAVs) usually during vegetation fires. To achieve this, we use artificial neural networks and create a dataset for supervised learning. We accomplish the assisted labeling of the dataset through the implementation of an object detection pipeline that combines classic image processing techniques with pretrained neural networks. In addition, we develop a data augmentation pipeline to augment the dataset with utomatically labeled images. Finally, we evaluate the performance of different neural networks.
The video shows a very high resolution 3D point cloud !!! of the outdoor area of the German Rescue Robotics Center. For the recording, a 25-second POI flight was performed with a Mavic 3. From the 4K video footage captured during this flight, 77 images were cropped and localized within 4 minutes using colmap and processed using Neural Radiance Fields (NeRF). The nerfacto model of Nerfstudio was trained on an Nvidia RTX 4090 for 8 minutes. In summary, a top 3D model is available to task forces after about 13 minutes. The calculation is performed locally on site by the RobLW of the DRZ. The video shown here shows a free camera path rendered at 60 hz (Full HD).
In this paper, we investigate the influence of different disease groups on the size of different 1 anatomical structures. To this end, we first modify and improve an existing anatomical segmentation 2 model. Then, we use this model to segment 104 anatomical structures from computed tomography 3 (CT) scans and compute their volumes from the segmentation. After correlating the results with each 4 other, we find no new significant correlations. After correlating the volume data with known diseases 5 for each case, we find two weak correlations, one of which has not been described before and for 6 which we present a possible explanation.
Problem
- How to effectively use aerial robots to support rescue forces?
- How to achieve good flight characteristics and long flight times?
- How to enable simple and intuitive control?
- How to efficiently record image data of the environment?
- How to generate flight and image data for rescue forces?
Implementation:
The flying robot was designed in Autodesk Fusion360. In order to achieve high stability as well as low weight, the frame was milled from carbon. Mounts such as for GPS and 360° camera were 3D printed. A special feature is that the flying robot is not visible in the panoramic view of the 360° camera. The flight controller of the robot was set up using Ardupilot. The communication with the robot is done via MAVLink (UDP).To support different platforms, a software was realized as a web application. The front end was created using HTML, CSS and Javascript.
The back end is based on Flask-Socket-IO (Python). For the intelligent recognition of motor vehicles a micro controller with an integrated camera is used. For the post-processing of flight and video data a pipeline was implemented for automation.
Purpose
So far, there are several approaches of measuring the Dark Triad traits, but still all of them are
personality questionnaires with at least questionable usability for applied contexts such as Human
Resource Management.
The purpose of the study is the development of a structured interview with the aim of measuring the Dark Triad in a rather qualitative way that increases social validity for the respondents.
Design/Methodology/Approach/Intervention
In the present study, 15 executives from the telecommunications industry were interviewed on their personal evaluation of management success and derailment. Afterwards, their personality traits of the Dark Triad were measured with the help of the Short Dark Triad Scale. Subsequently, the data from qualitative and quantitative research were examined for correlations using the mixed-method approach.
Results
The results of the mixed-method approach showed a statistically significant correlation between the Short Dark Triad Scale and the ratings for narcissism, Machiavellianism and subclinical psychopathy in the Dark Triad interview.
Limitations
Replicating the results in a bigger sample and a deeper investigation of the criterion-related validity as well as an integration of multiple raters can provide more confidence in our results.
Research/Practical Implications
Structured interviews allow the measurement of personality traits in a more convenient way especially in personnel selection and development processes. Identifying subclinical traits in leadership candidates can, e.g. prevent management derailment.
Originality/Value
The present study advances the measurement methods of the Dark Triad.
Purpose
Although the systemic approach to the leadership concept seems to fit well into our modern complex and dynamic work environment, only little research has been conducted to define and assess systemic leadership. In this study we therefore developed and assessed criterion validity of the
multidimensional systemic leadership inventory (SLI, Sülzenbrück & Externbrink, 2017).
Methodology
We conducted two cross-sectional survey among managers and employees of various organizations (N = 143 and N = 150).
Results
We found a robust five-factor structure of the SLI, comprising systemic thinking, self-knowledge, solution-oriented communication, creating meaning and delegation. Regarding criterion validity, a significant positive correlation of systemic leadership was found with affective commitment, while a significant negative correlation with emotional strain in occupational contexts occurred. These overall positive outcomes for employees were not undermined by negative personality traits of the employee (Machiavellianism), while strong growth need strength further enhanced positive effects on affective commitment.
Limitations
Since all variables were measured as self-reports, common method variance could limit our findings.
Practical Implications
Systemic leadership is a very promising new approach for leaders to ensure committed and less strained employees.
Value
Systemic leadership, especially in terms of a leaders’ understanding of organizational and private systems influencing work behaviour of all members of an organization, is a promising novel leadership model suitable to address challenges of complex and dynamic work environments.
Purpose
Although courage has generally been understood as a powerful virtue, research to establish it as a psychological construct is in its infancy. We examined courage in organizations against the backdrop of positive psychology with a design in the Grounded Theory tradition that connects Positive Organizational Behavior and Positive Organizational Scholarship.
Method
The sample consists of organizations that define courage in their mission statement and organizations without such a definition. It includes employees and executives, exploring workplace courage on the macro as well as the micro level. Eleven organizations and 23 participants contributed to the interview study.
Results
Applying Glaser's theoretical coding, specifically the C-family, we propose that courage arises from a decisional conflict in three major domains: the self, social interaction, and performance. It is located on a continuum between apathy and foolhardiness and can take on reactive, proactive, or autonomous forms. Whether and to what extent courage manifests, is a dynamic process contingent upon organizational structure, culture, and communication climate as well as individual cognitiveaffective personality systems.
Limitations
The model depicts the complexity of the phenomenon, rather than details of its individual components. It goes beyond pre-defined categories and prevailing definitions.
Implications
Modern organizations are characterized by volatility, uncertainty, complexity, and ambiguity (VUCA).
Courage is crucial in such an environment and can be systematically fostered across the whole human
resource management cycle.
Value
The study advances theory building on courage in the workplace and highlights its potential to be
measured, developed and managed for more effective work performance.
Design and Development of a Bioreactor System for Mechanical Stimulation of Musculoskeletal Tissue
(2023)
We report on the development of a bioreactor system for mechanical stimulation of musculoskeletal tissues. The ultimate object is to improve the quality of medical treatment following injuries of the enthesis tissue. To this end, the tissue formation process through the effect of mechanical stimulation is investigated. A six-well system was designed, 3D printed and tested. An integrated actuator creates strain by applying a force. A contactless position sensor monitors the travels. An electronic circuit controls the bioreactor using a microcontroller. An IoT platform connects the microcontroller to a smartphone, enabling the user to alter variables, trigger actions and monitor the system. The system was stabilised by implementing two PID controllers and safety measures. The results show that the bioreactor design is suited to execute mechanical stimulation and to investigate the tissue formation and regeneration process …
Impact of Team Members’ Competence on the Development of Team Mental Models and Team Performance
(2011)
We argue that effective leadership development should be evidence-based, i.e. that it combines the best available scientific evidence with
research in the specific organizational context. To illustrate our proposition, we report findings from a case study in a multinational organization. The goal was to examine which rater source in the company’s 360 degree feedback would provide the most valid information about leadership competencies. Therefore, we explored relationships between 360 degree ratings and assessment center (AC) ratings of the same leadership competencies (N=151). It was predicted that AC ratings show higher overlap with 360 degree ratings for behaviors that specific rating
sources can more easily observe in the ratees’ work life. Results showed that peers were the most accurate observers of leadership competencies in 360 degree assessments, compared to managers and subordinates. This corroborates our argument for an evidence-based instead of an
intuitive handling of 360 degree feedback results. Practical implications and avenues for future research are discussed.
This paper makes a contribution to the discussion on microfoundations of dynamic capabilities – actions and interactions in organizations that enable continuous organizational renewal. More specifically, we propose the idea that dynamic capabilities of an organization
are a positive function of corresponding dynamic capabilities of individual and collective actors in the organization. Further, we develop the assumption that not only individual acts of managers but also of individuals and teams without managerial responsibility relate to dynamic capabilities of the organization. Following a holistic view, we also take into consideration empowering working conditions as enhancing factor of this function. To
examine these roots of dynamic capabilities, we use a multi level model of competence provided by Wilkens, Keller and Schmette (2006) that operationalizes the concept of dynamic
capabilities provided by Teece (2007) on a concisely behavioural base. We investigated our hypotheses with a standardized questionnaire in a case study of a German plant engineering company with 112 participants and found first support for our assumptions. Our results show an impact of individual dynamic capabilities on dynamic capabilities of the organization which is mediated by team dynamic capabilities. Psychological and social-structural empowerment moderated this relationship. A case-specific interpretation and implications for future research and practice are discussed.
Dephasing in quantum systems is typically the result of their interaction with environmental degrees of freedom. We investigate within a spin-boson model the influence of a super-Ohmic environment on the dynamics of a quantum two-state system. A super-Ohmic environment thereby models typical bulk phonons which are a common disturbance for solid state quantum systems as, for example, nitrogen-vacancy centers. By applying the numerically exact quasiadiabatic path-integral approach we show that for strong system-bath coupling, pseudocoherent dynamics emerges, i.e., oscillatory dynamics at short times due to slaving of the quantum system to the bath dynamics. We extend the phase diagram known for sub-Ohmic and Ohmic environments into the super-Ohmic regime and observe a pronounced nonmonotonous behavior. Super-Ohmic purely dephasing fluctuations strongly suppress the amplitude of coherent dynamics at very short times with no subsequent further decay at later times. Nevertheless, they render the dynamics overdamped. The corresponding phase separation line shows also a nonmonotonous behavior, very similar to the pseudocoherent dynamics.
We propose a quantum-mechanical model to calculate the current through a single molecular junction immersed in a solvent and surrounded by a thin shell of bound water under an applied ac voltage. The solvent plus hydration shell are captured by a dielectric continuum model for which the resulting spectral density is determined. Here the dielectric properties, e.g., the Debye relaxation time and the dielectric constant, of the bulk solvent and the hydration shell as well as the shell thickness directly enter. We determine the charge current through the molecular junction under an ac voltage in the sequential tunneling regime where we solve a quantum master equation by a real-time diagrammatic technique. Interestingly, the Fourier components of the charge current show an exponential-like decline when the hydration shell thickness increases. Finally, we apply our findings to binary solvent mixtures with varying volume fractions and find that the current is highly sensitive to both the hydration shell thickness as well as the volume fraction of the solvent mixture, giving rise to possible applications as shell and concentration sensors on the molecular scale.
We propose a quantum-mechanical model to calculate the nonlinear differential conductance of a single molecular junction immersed in a solvent, either in pure form or as a binary mixture with varying volume fraction. The solvent mixture is captured by a dielectric continuum model for which the resulting spectral density is determined within the Gladstone-Dale approach. The conductance of the molecular junction is calculated by a real-time diagrammatic technique. We find a strong variation of the conductance maximum for varying volume fraction of the solvent mixture. Importantly, the calculated molecular nonlinear conductance shows a very good agreement with experimentally measured data for common molecular junctions in various polar solvent mixtures.
We study the dynamics of a quantum two-state system driven through an avoided crossing under the influence of a super-Ohmic environment. We determine the Landau–Zener probability employing the numerical exact quasi-adiabatic path integral and a Markovian weak coupling approach. Increasing the driving time in the numerical protocol, we find converged results which shows that super-Ohmic environments only influence the Landau Zener probability within a finite crossing time window. This crossing time is qualitatively determined by the environmental cut-off energy. At weak coupling, we show that the Markovian weak coupling approach provides an accurate description. Since pure dephasing of a super-Ohmic bath is non-Markovian, this highlights that pure dephasing hardly influences the Landau–Zener probability. The finite crossing time window, thus, results from the suppression of relaxation once the energy splitting exceeds the environmental cut-off energy.
Leadership Beyond Narcissism: On the Role of Compassionate Love as Antecedent of Servant Leadership
(2020)
While we already know a lot about the outcomes and boundary conditions of servant leadership, there is still a need for research on its antecedents. Building on the theory of purposeful work behavior and further theorizing by van Dierendonck and Patterson (2015), we examine if leaders’ propensity for compassionate love will evoke servant leadership behavior. At the same time, we contrast compassionate love to leaders’ narcissism as psychological counterpart to compassionate love, because narcissism is not associated with leader effectiveness, but with leader emergence instead. We collected data from 170 leader-follower-dyads in a field study in Germany, while measuring leaders’ compassionate love and narcissism, and followers’ perceptions of servant leadership. We found a positive association between leaders’ compassionate love and servant leadership behavior, while narcissism was negatively associated with servant leadership. Theoretical and practical implications, as well as pathways for future research are discussed.
The purpose of the paper is to contribute to the inner workings of transformational leadership in the context of organizational change. According to the organizational role theory, role conflict is proposed as a mediator between transformational leadership and affective commitment to change and irritation. Cross-sectional data were collected in a German company in the textiles sector, undergoing a pervasive IT-related change. Confirmatory factor analysis and structural equation modeling was performed for validity and hypothesis testing. The findings suggest that role conflict acts as a full mediator in the relationship between transformational leadership and affective commitment to change, as well as irritation. Transformational leadership is often discussed in terms of change-oriented leadership. Surprisingly, only a few studies have examined the specific impact of transformational leadership on attitudinal outcomes during change processes, yet. Consequently, research on the underlying psychological mechanisms of the relationship is scarce, too.
A quantum two-level system immersed in a sub-Ohmic bath experiences enhanced low-frequency quantum statistical fluctuations which render the nonequilibrium quantum dynamics highly non-Markovian. Upon using the numerically exact time-evolving matrix product operator approach, we investigate the phase diagram of the polarization dynamics. In addition to the known phases of damped coherent oscillatory dynamics and overdamped decay, we identify a new third region in the phase diagram for strong coupling showing an aperiodic behavior. We determine the corresponding phase boundaries. The dynamics of the quantum two-state system herein is not coherent by itself but slaved to the oscillatory bath dynamics.
This chapter is a commentary on Principle 21 of the United Nations Guiding Principles on Business and Human Rights (UNGPs). The UNGPs, endorsed by the United Nations Human Rights Council in 2011, are the first universally accepted framework for addressing business responsibilities for human rights. They outline State obligations to protect human rights, businesses’ responsibility to respect human rights, and the importance of both States and businesses offering adequate remedies for human rights breaches.
Article 135 TFEU
(2023)
Article 134 TFEU
(2023)
This chapter is a commentary on Principle 20 of the United Nations Guiding Principles on Business and Human Rights (UNGPs). The UNGPs, endorsed by the United Nations Human Rights Council in 2011, are the first universally accepted framework for addressing business responsibilities for human rights. They outline State obligations to protect human rights, businesses’ responsibility to respect human rights, and the importance of both States and businesses offering adequate remedies for human rights breaches.
The German supply chain law ( Lieferkettensorgfaltspflichtengesetz, abbreviated: LkSG) which enters into force on 1 January 2023 is part of the developing legal framework for human rights in global supply chains. Like the French vigilance law, it represents a new generation of supply chain laws which impose mandatory human rights due diligence obligations. The LkSG requires enterprises to exercise a number of due diligence obligations – from conducting risk analysis to undertaking preventive measures or remedial actions. The law is based on public enforcement via a competent authority, the Federal Office for Economic Affairs and Export Control (BAFA). The BAFA monitors and enforces compliance with the due diligence obligations. Non-compliant enterprises can be fined with up to 800,000 Euros and, in some cases, up to 2% of the annual turnover. Whilst the LkSG is an important step towards achieving greater corporate sustainability, it also has limitations. It was a political compromise and, as such, it does not include a new civil liability for non-compliance. Moreover, by default, it only applies to the enterprise’s own business area and its direct suppliers, whereas indirect suppliers are only included where the enterprise has substantiated knowledge that an obligation has been violated.
The concept of “Internationalisation at Home“ has gained momentum with the increasing digitalization of education and limitations on mobility. Collaborative Online International Learning (COIL) is an innovative, cost-effective instructional method that promotes intercul-tural learning through online collaboration between faculty and students from different countries or locations. The benefits of using COIL courses have been widely recognized, with learners developing intercultural competencies, digital skills, international education experi-ence, and global awareness.
However, multicultural communication in project environments can be complex and demand awareness of cultural variations . The creation and development of effective cross-cultural collectivism, trust, communication, and empathy in leadership is an important ingredient for remote project collaborations success. This is an area that has been least explored in re-search on communication in virtual teams.
The GIPE projects are mainly carried out as so-called Collaborative Online International Learning (COIL) events. However, to gain a “real world“ experience abroad in an intercultural team, students from all partner universities can participate in the Spring School being held for two weeks in Germany and the Germany students present and hand-over the results in the country of the partner university. The main objective of this research was to examine the experiences of students participating in the GIPE project and to evaluate the effectiveness of the project in enhancing intercultural competencies and fostering collaboration among stu-dents from different continents. This paper will also explore the implications of the GIPE project for Education 2.0 considering the COVID-19 pandemic and the future of education delivery and administration transformation.
The disruptive nature of the changing media landscape and technology-driven advances in communication have led to innovative ways of organizing work in the information and communication industry. This reorganization of work is reflected in the concept of New Work, which rethinks working concepts, styles, and employee behavior. Based on a survey among staff in the information and communication industry (n = 380), this study investigates the status quo of the implementation of New Work measures and their effectiveness in helping companies reach organizational goals. The results show that New Work measures are widely adopted although there is still unused potential. Moreover, the study demonstrates that the implementation of New Work measures supports companies in achieving New Work goals as well as overall organizational goals in the contexts of agile management, change management, internal communication, and evaluation.
The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data is an important factor for the generation of deep learning systems that generalise well and are not overfit to a specific type of input. In the case of chemical structure depictions, these features are defined by the depiction parameters such as bond length, line thickness, label font style and many others. Here we present RanDepict, a toolkit for the creation of diverse sets of chemical structure depictions. The diversity of the image features is generated by making use of all available depiction parameters in the depiction functionalities of the CDK, RDKit, and Indigo. Furthermore, there is the option to enhance and augment the image with features such as curved arrows, chemical labels around the structure, or other kinds of distortions. Using depiction feature fingerprints, RanDepict ensures diversely picked image features. Here, the depiction and augmentation features are summarised in binary vectors and the MaxMin algorithm is used to pick diverse samples out of all valid options. By making all resources described herein publicly available, we hope to contribute to the development of deep learning-based OCSR systems.
Recent years have seen a sharp increase in the development of deep learning and artificial intelligence-based molecular informatics. There has been a growing interest in applying deep learning to several subfields, including the digital transformation of synthetic chemistry, extraction of chemical information from the scientific literature, and AI in natural product-based drug discovery. The application of AI to molecular informatics is still constrained by the fact that most of the data used for training and testing deep learning models are not available as FAIR and open data. As open science practices continue to grow in popularity, initiatives which support FAIR and open data as well as open-source software have emerged. It is becoming increasingly important for researchers in the field of molecular informatics to embrace open science and to submit data and software in open repositories. With the advent of open-source deep learning frameworks and cloud computing platforms, academic researchers are now able to deploy and test their own deep learning models with ease. With the development of new and faster hardware for deep learning and the increasing number of initiatives towards digital research data management infrastructures, as well as a culture promoting open data, open source, and open science, AI-driven molecular informatics will continue to grow. This review examines the current state of open data and open algorithms in molecular informatics, as well as ways in which they could be improved in future.
The influence of molecular fragmentation and parameter settings on a mesoscopic dissipative particle dynamics (DPD) simulation of lamellar bilayer formation for a C10E4/water mixture is studied. A “bottom-up” decomposition of C10E4 into the smallest fragment molecules (particles) that satisfy chemical intuition leads to convincing simulation results which agree with experimental findings for bilayer formation and thickness. For integration of the equations of motion Shardlow’s S1 scheme proves to be a favorable choice with best overall performance. Increasing the integration time steps above the common setting of 0.04 DPD units leads to increasingly unphysical temperature drifts, but also to increasingly rapid formation of bilayer superstructures without significantly distorted particle distributions up to an integration time step of 0.12. A scaling of the mutual particle–particle repulsions that guide the dynamics has negligible influence within a considerable range of values but exhibits apparent lower thresholds beyond which a simulation fails. Repulsion parameter scaling and molecular particle decomposition show a mutual dependence. For mapping of concentrations to molecule numbers in the simulation box particle volume scaling should be taken into account. A repulsion parameter morphing investigation suggests to not overstretch repulsion parameter accuracy considerations.
Developing and implementing computational algorithms for the extraction of specific substructures from molecular graphs (in silico molecule fragmentation) is an iterative process. It involves repeated sequences of implementing a rule set, applying it to relevant structural data, checking the results, and adjusting the rules. This requires a computational workflow with data import, fragmentation algorithm integration, and result visualisation. The described workflow is normally unavailable for a new algorithm and must be set up individually. This work presents an open Java rich client Graphical User Interface (GUI) application to support the development of new in silico molecule fragmentation algorithms and make them readily available upon release. The MORTAR (MOlecule fRagmenTAtion fRamework) application visualises fragmentation results of a set of molecules in various ways and provides basic analysis features. Fragmentation algorithms can be integrated and developed within MORTAR by using a specific wrapper class. In addition, fragmentation pipelines with any combination of the available fragmentation methods can be executed. Upon release, three fragmentation algorithms are already integrated: ErtlFunctionalGroupsFinder, Sugar Removal Utility, and Scaffold Generator. These algorithms, as well as all cheminformatics functionalities in MORTAR, are implemented based on the Chemistry Development Kit (CDK).
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT (COlleCtion of Open Natural prodUcTs) database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day.
This chapter describes a new concept and experiences of a distributed interdisciplinary learning program for students across continents. The aim is to provide students with a truly Global Intercultural Project Experience (GIPE) by working together with peers from around the world and solving real-life client’s problems. We have received seed-funding for four annual projects to engage students from Germany (Europe), Namibia (Africa), Indonesia (Asia), and Peru (South America). In 2020 and 2021, 28 and 44 students from four continents engaged in a one-semester distributed interdisciplinary project for a Namibian and Indonesian client, respectively. Despite Covid-19 they successfully completed the project expressing deep appreciation for the learning opportunities overcoming challenges of working across widespread time zones, cultures, changing requirements, and various technical difficulties. Considering the vast learning benefits, we suggest incorporating such projects in all tertiary education curricula across the globe, while streamlining organizational efforts based on lessons learned.
Air Handling units (AHU) are designed to guarantee a high indoor air quality for any time and outdoor condition all over the year. To do so, the AHU removes particle matter like dust or pollen and adapts the thermophysical properties of air to the desired, seasonal indoor comfort conditions. AHU have a robust design and thus operate for more than fifteen years, sometimes even for decades. An AHU designed today must consider and anticipate the change of user needs as well as outdoor air conditions for the next twenty years. To anticipate the outdoor air condition of coming decades, scientific models exist, which allow the design of peak performance and capacities of the air treatment components. It is most likely, that the ongoing climate change will lead to higher temperatures as well as higher humidity, while the comfort zone of human beings will remain at today’s values. Next to the impact of global warming with average rise of mean air temperature local effects will influence the operation of AHU. On effect investigated here is the steep temperature increase in city centres called urban heat islands. Heating and cooling capacities as well as water consumption for humidification are investigated for a reference AHU for fifteen regional locations in Germany. These regions represent all climate zones within the country. Additionally, the urban heat island effect was investigated for Berlin Alexanderplatz compared a rural area close by. The AHU was chosen to operate in an intensive care unit of a hospital. The set-up leads to 24/7 operation with 8760 hours per year. The article presents the modelling of current and future weather data as well as the unit set up. The calculated hourly performance and capacity parameters for current (reference year 2012) and future weather data (reference year 2045) yield energy consumption and peak loads of the unit for heating, cooling and humidification. The results are displayed by relative comparisons of each performance value.
Media Brand Management
(2022)
The management of media brands faces challenges. In order to be able to point out possible solutions, this article first explains the concept and the nature of “media brands.” Subsequently, various theoretical approaches to the explanation of media brands and their management are presented. Regardless of theoretical preferences, it is important to keep in mind the brand-strategic complexity of media management that is subsequently described. Due to their specificity, special attention is paid to the basic strategic positioning options and to the communication management of media brands. In this way, the special features of media brand management become clear in comparison with other products and services.
The concept of molecular scaffolds as defining core structures of organic molecules is utilised in many areas of chemistry and cheminformatics, e.g. drug design, chemical classification, or the analysis of high-throughput screening data. Here, we present Scaffold Generator, a comprehensive open library for the generation, handling, and display of molecular scaffolds, scaffold trees and networks. The new library is based on the Chemistry Development Kit (CDK) and highly customisable through multiple settings, e.g. five different structural framework definitions are available. For display of scaffold hierarchies, the open GraphStream Java library is utilised. Performance snapshots with natural products (NP) from the COCONUT database and drug molecules from DrugBank are reported. The generation of a scaffold network from more than 450,000 NP can be achieved within a single day.
The development of deep learning-based optical chemical structure recognition (OCSR) systems has led to a need for datasets of chemical structure depictions. The diversity of the features in the training data is an important factor for the generation of deep learning systems that generalise well and are not overfit to a specific type of input. In the case of chemical structure depictions, these features are defined by the depiction parameters such as bond length, line thickness, label font style and many others. Here we present RanDepict, a toolkit for the creation of diverse sets of chemical structure depictions. The diversity of the image features is generated by making use of all available depiction parameters in the depiction functionalities of the CDK, RDKit, and Indigo. Furthermore, there is the option to enhance and augment the image with features such as curved arrows, chemical labels around the structure, or other kinds of distortions. Using depiction feature fingerprints, RanDepict ensures diversely picked image features. Here, the depiction and augmentation features are summarised in binary vectors and the MaxMin algorithm is used to pick diverse samples out of all valid options. By making all resources described herein publicly available, we hope to contribute to the development of deep learning-based OCSR systems.
The use of molecular string representations for deep learning in chemistry has been steadily increasing in recent years. The complexity of existing string representations, and the difficulty in creating meaningful tokens from them, lead to the development of new string representations for chemical structures. In this study, the translation of chemical structure depictions in the form of bitmap images to corresponding molecular string representations was examined. An analysis of the recently developed DeepSMILES and SELFIES representations in comparison with the most commonly used SMILES representation is presented where the ability to translate image features into string representations with transformer models was specifically tested. The SMILES representation exhibits the best overall performance whereas SELFIES guarantee valid chemical structures. DeepSMILES perform in between SMILES and SELFIES, InChIs are not appropriate for the learning task. All investigations were performed using publicly available datasets and the code used to train and evaluate the models has been made available to the public.
The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over the last three decades in this field, but the development of systems for the recognition of complex hand-drawn structure depictions is still at the beginning. Currently, there is no data for the systematic evaluation of OCSR methods on hand-drawn structures available. Here we present DECIMER — Hand-drawn molecule images, a standardised, openly available benchmark dataset of 5088 hand-drawn depictions of diversely picked chemical structures. Every structure depiction in the dataset is mapped to a machine-readable representation of the underlying molecule. The dataset is openly available and published under the CC-BY 4.0 licence which applies very few limitations. We hope that it will contribute to the further development of the field.
The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over the last three decades in this field, but the development of systems for the recognition of complex hand-drawn structure depictions is still at the beginning. Currently, there is no data for the systematic evaluation of OCSR methods on hand-drawn structures available. Here we present DECIMER - Hand-drawn molecule images, a standardised, openly available benchmark dataset of 5088 hand-drawn depictions of diversely picked chemical structures. Every structure depiction in the dataset is mapped to a machine-readable representation of the underlying molecule. The dataset is openly available and published under the CC-BY 4.0 licence which applies very few limitations. We hope that it will contribute to the further development of the field.
We investigated the formation of Artemia franciscana swarms of freshly hatched instar I nauplii larvae. Nauplii were released into light gradients but then interrupted by light-direction changes, small obstacles, or long barriers. All experiments were carried out horizontally. Each experiment used independent replicates. Freshly produced Artemia broods were harvested from independent incubators thus providing true replicate cohorts of Artemia subjected as replicates to the experimental treatments.
We discovered that Artemia nauplii swarms can: 1. repeatedly react to non-obstructed light gradients that undergo repeated direction-changes and do so in a consistent way, 2. find their way to a light source within maze-like arrangements made from small transparent obstacles, 3. move as a swarm around extended transparent barriers, following a light gradient. This paper focuses on the recognition of whole-swarm behaviors, the description thereof and the recognition of differences in whole-swarm movements comparing non-obstructed swarming with swarms encountering obstacles. Investigations of the within-swarm behaviors of individual Artemia nauplii and their interactions with neighboring nauplii are in progress, e.g. in order to discover the underlying swarming algorithms and differences
thereof comparing non-obstructed vs. obstructed pathways.
Different charge treatment approaches are examined for cyclotide-induced plasma membrane disruption by lipid extraction studied with dissipative particle dynamics. A pure Coulomb approach with truncated forces tuned to avoid individual strong ion pairing still reveals hidden statistical pairing effects that may lead to artificial membrane stabilization or distortion of cyclotide activity depending on the cyclotide’s charge state. While qualitative behavior is not affected in an apparent manner, more sensitive quantitative evaluations can be systematically biased. The findings suggest a charge smearing of point charges by an adequate charge distribution. For large mesoscopic simulation boxes, approximations for the Ewald sum to account for mirror charges due to periodic boundary conditions are of negligible influence.
Biomimetics is a well-known approach for technical innovation. However, most of its influence remains in the academic field. One option for increasing its application in the practice of technical design is to enhance the use of the biomimetic process with a step-by-step standard, building a bridge to common engineering procedures. This article presents the endeavor of an interdisciplinary expert panel from the fields of biology, engineering science, and industry to develop a standard that links biomimetics to the classical processes of product development and engineering design. This new standard, VDI 6220 Part 2, proposes a process description that is compatible and connectable to classical approaches in engineering design. The standard encompasses both the solution-based and the problem-driven process of biomimetics. It is intended to be used in any product development process for more biomimetic applications in the future.
Fruits (follicles) of Hakea salicifolia and Hakea sericea (Proteaceae) are characterised by pronounced lignification and open via a ventral suture and the dorsal side. The opening along both sides is unique within the Proteaceae. Both serotinous species are obligate seeders, whose spreading benefits from bush fire events. The different tissues and the course of the vascular bundles must allow the opening mechanism. While their 2D-arrangements are known to some extent from light-microscopy images of cross-sections, this work presents their three-dimensional structures and discusses their contribution to the opening of Hakea fruits. For this purpose, 3D greyscale images, reconstructed from µCT-projection data of both fruits are segmented, assisted by a deep learning algorithm (AI algorithm). 3D renderings from these segmentations show strongly interconnected vascular bundles that build a double-dome shaped network in each valve of H. salicifolia and a dome shaped honeycomb-structure in each valve of H. sericea. However, the vascular bundles of both species show no interconnection between the two lateral valves of the fruit but leave gaps for predetermined fracture tissues on the ventral and dorsal side. The opening of the fruits after a fire or after separation from the mother plant can be explained by the anisotropic shrinkage in the two valves of the fruit.
Robot arms are one of many assistive technologies used by people with motor impairments. Assistive robot arms can allow people to perform activities of daily living (ADL) involving grasping and manipulating objects in their environment without the assistance of caregivers. Suitable input devices (e.g., joysticks) mostly have two Degrees of Freedom (DoF), while most assistive robot arms have six or more. This results in time-consuming and cognitively demanding mode switches to change the mapping of DoFs to control the robot. One option to decrease the difficulty of controlling a high-DoF assistive robot arm using a low-DoF input device is to assign different combinations of movement-DoFs to the device’s input DoFs depending on the current situation (adaptive control). To explore this method of control, we designed two adaptive control methods for a realistic virtual 3D environment. We evaluated our methods against a commonly used non-adaptive control method that requires the user to switch controls manually. This was conducted in a simulated remote study that used Virtual Reality and involved 39 non-disabled participants. Our results show that the number of mode switches necessary to complete a simple pick-and-place task decreases significantl when using an adaptive control type. In contrast, the task completion time and workload stay the same. A thematic analysis of qualitative feedback of our participants suggests that a longer period of training could further improve the performance of adaptive control methods.
Nowadays, robots are found in a growing number of areas where they collaborate closely with humans. Enabled by lightweight materials and safety sensors, these cobots are gaining increasing popularity in domestic care, where they support people with physical impairments in their everyday lives. However, when cobots perform actions autonomously, it remains challenging for human collaborators to understand and predict their behavior, which is crucial for achieving trust and user acceptance. One significant aspect of predicting cobot behavior is understanding their perception and comprehending how they “see” the world. To tackle this challenge, we compared three different visualization techniques for Spatial Augmented Reality. All of these communicate cobot perception by visually indicating which objects in the cobot’s surrounding have been identified by their sensors. We compared the well-established visualizations Wedge and Halo against our proposed visualization Line in a remote user experiment with participants suffering from physical impairments. In a second remote experiment, we validated these findings with a broader non-specific user base. Our findings show that Line, a lower complexity visualization, results in significantly faster reaction times compared to Halo, and lower task load compared to both Wedge and Halo. Overall, users prefer Line as a more straightforward visualization. In Spatial Augmented Reality, with its known disadvantage of limited projection area size, established off-screen visualizations are not effective in communicating cobot perception and Line presents an easy-to-understand alternative.
This paper describes a new concept and experiences of a distributed interdisciplinary learning programme for students across continents. The aim is to provide students with a truly Global Intercultural Project Experience (GIPE) by working together with peers from around the world, and solving real-life client’s problems. We have received seed-funding for four annual projects to engage students from Germany (Europe), Namibia (Africa), Indonesia (Asia), and Peru (Latin-America). In 2020, 30 students from four continents engaged in a one-semester distributed software development project for a Namibian client. Despite Covid-19 they successfully completed the project expressing deep appreciation for the learning opportunities overcoming challenges of working across wide-spread time zones, cultures, changing requirements, and various technical challenges. Considering the vast learning benefits, we suggest to incorporate such projects in all tertiary education curricula across the globe.
Competency-oriented exams offer a wide range of advantages, especially where the use and mastery of third-party applications and tools play an important role. Therefore, we developed a competency-oriented setup for both our programming classes and exams ensuring their constructive alignment.
Exams were moved to the computer lab and designed to test both conceptional skills as well as the use of state-of-the-art programming tools. At the peak of the COVID-19 pandemic, when exams had to be moved from lab to online, we needed to design an online setup for our practical programming exams preserving the competency-oriented approach and its constructive alignment as well as the validity, reliability and fairness of the exams. The key was to use the same online tools that have been introduced
for running lectures and practical classes offering almost the same learning experience as before the pandemic. However, to ensure the validity and fairness of the exams, some kind of online supervision needed to be implemented as technical solutions were found to be either unusable or not working
properly in our case. This paper discusses the driving factors, the resulting technical and organizational setup as well as students’ feedback and lessons learned for further improvements. Therefore, COVID-19 has not been able to ruin our competency-oriented programming exams.
We study the nonequilibrium dynamics of a quantum system under the influence of two noncommuting fluctuation sources, i.e., purely dephasing fluctuations and relaxational fluctuations. We find that increasing purely dephasing fluctuations suppress increasing relaxation in the quantum system. This effect is further enhanced when both fluctuation sources are fully correlated. These effects arise for medium to strong primary fluctuations already when the secondary fluctuations are weak due to their noncommuting coupling to the quantum system. Dephasing, in contrast, is increased by increasing any of the two fluctuations. Fully correlated fluctuations result in overdamping at much lower system-bath coupling than uncorrelated noncommuting fluctuations. In total, we observe that treating subdominant secondary environmental fluctuations perturbatively leads, as neglecting them, to erroneous conclusions.
360° Camera at a small UAV
(2021)