Technische Universität Dresden: Qucosa
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The regulation of insulin secretory granule protein production by hnRNP A2/B1: Final Report DFG Grant SO 818/10-1
No full textThis DFG-funded project investigated how pancreatic β-cells regulate insulin biosynthesis in response to glucose fluctuations. β-cells uniquely produce and secrete insulin, the hormone enabling glucose uptake and lowering blood sugar. While insulin synthesis is known to rise rapidly after glucose stimulation, the speed of this response cannot be explained by transcription alone. Our studies uncovered a missing mechanism: insulin mRNA is stored in membrane-less cytosolic condensates that release it when metabolic energy becomes available. These condensates, organised by RNA-binding proteins, keep insulin mRNA protected but untranslated in resting β-cells and dissolve upon stimulation, allowing rapid initiation of insulin translation.
In Vasiljević et al., 2021, we showed that mRNAs encoding insulin and other β-cell secretory granule cargoes bind to hnRNP A2/B1 and localise to stress-granule-like particles that disassemble after glucose stimulation. In Quezada et al., EMBO J 2025, we identified G3BP1 and G3BP2 as main structural components of these condensates. Under low glucose, G3BP1/2 cluster with insulin mRNA, translation factors and AMPK; their dissolution by glucose, GLP-1 stimulation or palmitate enables translation. Depolarisation by high KCl, which triggers secretion but not biosynthesis, does not dissolve condensates, uncoupling insulin production from release.
Aldolase activity proved essential for condensate dynamics. Its inhibition blocked ATP generation and dissolution even in the presence of pyruvate, revealing glycolysis as a control point for translation upstream of oxidative phosphorylation. Deletion of G3BP1 reduced insulin mRNA and secretion. These findings are intriguing based on our previous evidence indicating that in islets from living donors with type 2 diabetes, aldolase B is increased and G3BP1 decreased (Wigger et al., Nat Metab 2021*), suggesting impaired regulation of insulin translation.
Together, these findings define a new principle of β-cell control: insulin mRNA is stored and released for translation through a glycolysis-coupled, energy-sensing mechanism. The dissolution of insulin-mRNA-containing condensates is a physico-chemical process occurring within minutes—much faster than transcription—allowing β-cells to adjust insulin production swiftly to metabolic demand. This is especially relevant in view of the evidence indicating that newly-synthesized insulin is preferentially released
Energy Optimal Flight Path Planning for Unmanned Aerial Vehicles in Urban Environments
No full textThis PhD thesis presents a comprehensive approach to calculating energy-efficient flight paths for unmanned aerial vehicles (UAVs) operating in urban environments. The primary objective is to minimize their energy consumption by exploiting local wind phenomena, such as upwind and tailwind generated by the airflow around buildings.
To achieve this, a realistic wind field for a typical continental European urban setting is generated using PALM, a Large Eddy Simulation (LES) tool, and validated through wind tunnel experiments. Both simulations and experiments are based on a generic city model designed to represent the characteristics of such urban environments. The validation uses a 1:100-scale model of the benchmark city model, where velocity profiles are measured via hot-wire probes and particle image velocimetry (PIV) at several positions.
A novel A-star-based algorithm, enhanced with path smoothing techniques and accounting for the UAV turning constraints, is applied to optimize the flight trajectories. The cost function integrates the generated wind field to reduce energy consumption. Additionally, a new energy-distance map forms the basis of the A-star heuristic, incorporating key factors affecting required energy.
The environmental conditions under which the UAV will operate are inherently uncertain. To address the optimization sensitivity to uncertainties, a specialized cost function is integrated into the A-star algorithm. Three distinct uncertainties are considered independently for optimization: local position drift, reduced up-wind due to vortices, and turbulence avoidance. The strategies applied address these uncertainties to achieve energy-efficient and robust flight paths.
The approach is demonstrated on a delivery UAV benchmark scenario. Energy optimal flight paths are compared to shortest way trajectories for 12 different scenarios. The results demonstrate significant energy saving potential when flying in urban areas by exploiting knowledge of the current wind conditions and minimizing the effects of uncertainties.:1 Introduction
2 Urban Logistic Scenario
3 Wind Field Prediction within Urban Environments
3.1 State of the art
3.2 Modelling the Wind Field Using Large Eddy Simulation
3.2.1 Geometry
3.2.2 Boundary Conditions
3.2.3 Adjustment
3.2.4 Simulation
3.3 Wind Tunnel Experiment for Validation
3.3.1 Low-Speed Wind Tunnel at TU Dresden
3.3.2 Experimental Setup
3.4 Results and Comparison to LES
3.4.1 Wake Area downstream the Single Building
3.4.2 Horizontal Wind Velocity Component Profiles in the City Model
3.4.3 Vertical Wind Velocity Component Profiles in the City Model
4 Trajectory Optimization
4.1 State of the art
4.2 Model Area Discretization
4.3 Extended A-star Algorithm
4.4 Cost Function for Exact Energy Identification
4.5 Heuristic Function for Energy Identification
4.6 Trajectory Sensitivity
4.6.1 Cost Function for Local Drift
4.6.2 Cost Function for turbulent Up- and Downwind
4.6.3 Cost Function for Turbulence Avoidance
4.6.4 Combinations of Cost Functions
5 Trajectory Optimization Results
5.1 Results of Nominal Trajectory Optimization
5.2 Results of Trajectory Optimization Including Uncertainties
5.2.1 Results of South-North-Track
5.2.2 Results of East-West-Track
5.3 Results of URBANSens scenario
6.1 Conclusion
6.2 Outlook
BibliographyIn dieser Dissertation wird ein übergreifender Ansatz für die Berechnung energieeffizienter Flugpfade von unbemannten Luftfahrzeugen (UAVs) in einem städtischen Umfeld verfolgt. Das übergeordnete Ziel ist die Minimierung des Energieverbrauchs durch die Ausnutzung lokaler Windphänomene, wie z.B. Auf- und Rückenwind, die durch die Gebäudeumströmung entstehen.
Dafür wird ein realistisches Windfeld für eine typische kontinentaleuropäische städtische Umgebung durch eine Large Eddy Simulation (LES) mit dem Programm PALM erzeugt und durch Windkanalversuche validiert. Das für die Simulationen und Versuche verwendete generische Stadtmodell wird im Rahmen dieser Arbeit entworfen. Der Maßstab des Referenz-Stadtmodells im Windkanal beträgt 1:100. Es werden an mehreren Positionen über die Höhe Geschwindigkeitsprofile mit Hitzedraht-Sonden und dem Particle Image Velocimetry (PIV)-Verfahren aufgenommen.
In der Optimierung der Flugbahnen wird ein neuartiger A-Star-basierender Algorithmus entwickelt, welcher kontinuierlich-differenzierbare Flugwege enthält und die Wendigkeit des UAVs berücksichtigt. Die verwendete Kostenfunktion basiert auf dem Energiebedarf dieser Flugbahnen, der unter Berücksichtigung der Windkomponenten des ermittelten Windfelds berechnet wird, um diesen zu minimieren. Außerdem wird für die benötigte Heuristik des A-Stern Algorithmus eine neuartige verzerrte Karte entwickelt, die anstatt Entfernungen den Energiebedarf aufzeigt.
Während eines UAV Fluges können aufgrund verschiedener Umwelteinflüsse ungeplante Störungen auftreten. Um diese Einwirkungen zu berücksichtigen enthält die Kostenfunktion des Algorithmus als Erweiterung eine Abwägung der Sensitivität der Optimierung. Bei der Optimierung werden schließlich drei verschiedene Unsicherheiten unabhängig voneinander betrachtet: lokale Positionsabweichungen, reduzierter Aufwind durch Strömungswirbel und die Vermeidung von Turbulenzgebieten. Die Berücksichtigung dieser Störgrößen ermöglicht sowohl energieeffiziente als auch robuste Flugpfade.
Die Wirksamkeit des Ansatzes wird schließlich anhand eines Referenzszenarios demonstriert. Energieeffiziente Flugpfade werden für 12 verschiedene Missionsszenarien mit Trajektorien für den kürzesten Weges verglichen. Diese Szenarien umfassen Kombinationen unterschiedlicher Routen und Windgeschwindigkeiten. Die Ergebnisse zeigen ein erhebliches Energieeinsparungspotenzial beim Fliegen in städtischen Gebieten auf, indem das Wissen über die aktuellen Windbedingungen genutzt und die Auswirkungen von Unsicherheiten minimiert werden.:1 Introduction
2 Urban Logistic Scenario
3 Wind Field Prediction within Urban Environments
3.1 State of the art
3.2 Modelling the Wind Field Using Large Eddy Simulation
3.2.1 Geometry
3.2.2 Boundary Conditions
3.2.3 Adjustment
3.2.4 Simulation
3.3 Wind Tunnel Experiment for Validation
3.3.1 Low-Speed Wind Tunnel at TU Dresden
3.3.2 Experimental Setup
3.4 Results and Comparison to LES
3.4.1 Wake Area downstream the Single Building
3.4.2 Horizontal Wind Velocity Component Profiles in the City Model
3.4.3 Vertical Wind Velocity Component Profiles in the City Model
4 Trajectory Optimization
4.1 State of the art
4.2 Model Area Discretization
4.3 Extended A-star Algorithm
4.4 Cost Function for Exact Energy Identification
4.5 Heuristic Function for Energy Identification
4.6 Trajectory Sensitivity
4.6.1 Cost Function for Local Drift
4.6.2 Cost Function for turbulent Up- and Downwind
4.6.3 Cost Function for Turbulence Avoidance
4.6.4 Combinations of Cost Functions
5 Trajectory Optimization Results
5.1 Results of Nominal Trajectory Optimization
5.2 Results of Trajectory Optimization Including Uncertainties
5.2.1 Results of South-North-Track
5.2.2 Results of East-West-Track
5.3 Results of URBANSens scenario
6.1 Conclusion
6.2 Outlook
Bibliograph
Data-driven approaches to identify isolated group members: A systematic literature review
No full textDigital CommunicationFrom the Introduction: Group work is a central component of modern working environments and better results are achieved through the synergy of the members than through individual work. This is equally emphasised by Wellhöfer (2018, p. 65): „If the group did not exist, we would have to invent it, as it can achieve results that are superior to the individual performance of the group members“. In modern working environments, characterised by the principles of New Work and globalisation, effective group dynamics are increasingly important. Isolated group members can significantly impair the functionality and success of teams. It is therefore crucial to understand the causes and effects of isolation in groups and to develop solutions
Determinants of Psychomotor Ability through the Utilization of Digital Media in Vocational Learning
No full textThis study aims to reveal (1) determinant factors of the psychomotor ability to building design through the utilization of digital media in vocational teaching, (2) the effect of digital media utilization on the formation of the psychomotor ability to building design in vocational teaching, and (3) the composition of digital media use instruments to form the psychomotor ability to building design in the vocational teaching.
This study uses a mixed-method approach with an exploratory sequential research design. It was conducted at the Civil Engineering and Planning Education Study Program, Faculty of Engineering, UNY. The data sources are lecturers and students. The qualitative data were collected through literature study, focus group discussions (FGD), and the quantitative data were collected through interviews and by using a questionnaire. The FGD involved experts in the field of vocational teaching, digital media for learning, and stakeholders. The results of the FGD are components of the formation of psychomotor abilities in designing a building using digital media. The population of this study was 608 respondents. The samples of the research uses the table of Krejcie and Morgan with error 5%, a total of 235 respondents were obtained, and were taken using the simple random sampling technique. The instrument was validated through expert judgment. Validity and reliability analysis were carried out using Confirmatory Factor Analysis (CFA). The data analysis used Structural Equation Modelling (SEM) and descriptive statistical analysis.
The results of this study are as follows. (1) Determinant factors of the psychomotor abilities in designing a building using digital media in vocational teaching consist of the quality of digital media, acceptance of technology, and digital learning environment. (2) The effect of variables of digital media utilization on the formation of psychomotor abilities in designing a building in vocational learning is in the high category, with a value of 86.92 (sig<0.05). (3) The composition of the instrument for utilizing digital media to form psychomotor abilities in designing a building in the vocational teaching is: 43% (digital media), 18% (digital learning environment), 7% (level of technology acceptance by users), and 17% (resources support), while the remaining 12% (learning strategies) and 3% by other factors.:ABSTRACT
CHAPTER I. INTRODUCTION
A. Background
B. Identification of problems
C. Limitation the problem
D. Problem Formulation
E. Goals of Research
F. Benefits of research
CHAPTER II. THEORETICAL FRAMEWORK
A. Theoretical Analysis
1. Implementation of Vocational Education in Indonesia
2. Vocational Learning
3. Bloom's Taxonomy
4. Distance Learning
5. Digital Media
6. Technology Acceptance Model (TAM)
7. Digital Media Assessment Instrument
8. The Nature of Determinants
B. Related Research
C. Thinking Framework
D. Hypothesis
E. Research Questions
CHAPTER III. RESEARCH METHODS
A. Qualitative Methods
1. Research Place
2. Data source
3. Data collection technique
4. Data analysis
5. Data Credibility Testing
6. Data Transferability Testing
7. Formulation of Initial Findings
B. Quantitative Methods
1. Population and Sample
2. Data collection technique
3. Research Instruments
4. Prerequisite Test
5. Data Analysis Techniques
C. Qualitative and Quantitative Research Data Analysis
CHAPTER IV. RESEARCH RESULTS AND DISCUSSION
A. Research result
1. Determinant factors of psychomotor abilities using digital media in vocational learning
2. The influence of digital media review aspects on the formation of psychomotor abilities in vocational learning
3. Composition of the use of digital media to form psychomotor abilities in vocational learning
4. Research Result Novelty
B. Discussion of Research Results
1. Review aspects of psychomotor abilities in designing a building
2. Aspects of reviewing the quality of digital media learning
3. Aspects of technology acceptance review
4. Aspects of digital learning environment review
5. Resource support review aspects
C. Research Limitations
BAB V. CONCLUSION AND RECOMMENDATIONS
A. Conclusion
B. Implications
C. Recommendations
REFERENCE
Fachspezifische digitalisierungsbezogene Lehr-Lern-Szenarien: Innovationen durch multiprofessionelle Zusammenarbeit
No full textDigital Education: Vocational TrainingAus dem Text: Der Beitrag präsentiert den Ansatz, passgenaue Angebote für die Zielgruppe der Seiteneinsteiger:innen in multiprofessionellen Teams zu konzipieren, um den Erwerb fachspezifischer digitalisierungsbezogener Kompetenzen zu fördern
AI-Enhanced Personalized Learning in Higher Research Education: Tracing a Path to Tailored Support
No full textDigital Education: AI IIFrom the Text: Education is undergoing significant changes due to the emergence of generative AI (West, 2018; Luckin, 2018). Traditional one-size-fits-all methods are being replaced by more individualized learning practices designed to meet the unique needs of each student (Holmes et al., 2019; Hummel & Donner, 2024; Bartok et al., 2023; Hummel et al., 2023; Hummel & Donner, 2023). Personalized learning, which tailors educational content, pacing, and learning plans to individual learners needs and preferences, has emerged as a crucial component of modern education (Zhou & Brown, 2015; Egger & Hummel, 2020; Hummel, 2020; Hummel et al., 2024). Initially rooted in theories about diverse learning styles and early computer-assisted teaching, personalized learning now incorporates advanced AI-driven methods such as recommender systems, learning analytics, and adaptive learning technologies to create highly responsive and effective educational environments (Truong, 2020; Hummel & Donner, 2023; Bohlinger & Hummel, 2024). To enhance positive impacts of personalized learning on education, there is a critical need to integrate existing policies, technologies, and frameworks into a cohesive approach that can adapt to the evolving educational landscape. While research has progressed, a comprehensive understanding that unifies these innovations is still lacking
Digitale Gesundheitsanwendungen (DiGA) im Spannungsfeld von Fortschritt und Kritik: Diskussionsbeitrag der Fachgruppe „Digital Health“ der Gesellschaft für Informatik e. V.
No full textIm Dezember 2019 wurden in Deutschland Digitale Gesundheitsanwendungen (DiGA) in die Regelversorgung aufgenommen und können somit durch die gesetzlichen Krankenkassen erstattet werden, um PatientInnen bei der Behandlung von Erkrankungen oder Beeinträchtigungen zu unterstützen. Inzwischen gibt es 48 DiGA (Stand: Oktober 2023) im Verzeichnis des Bundesinstituts für Arzneimittel und Medizinprodukte (BfArM), die vor allem in den Bereichen mentale Gesundheit, Hormone und Stoffwechsel sowie Muskeln, Knochen und Gelenke eingesetzt werden. In diesem Artikel beschreibt die Fachgruppe „Digital Health“ der Gesellschaft für Informatik e. V. (GI) die aktuellen Entwicklungen rund um die DiGA sowie das derzeitige Stimmungsbild zu Themen wie Nutzerzentrierung, Akzeptanz von PatientInnen und Behandelnden sowie Innovationspotenzial. Zusammenfassend haben DiGA in den letzten 3 Jahren eine positive Entwicklung in Form eines langsam steigenden Angebots verschiedener DiGA und Leistungsbereiche erfahren. Nichtsdestotrotz sind in einigen Bereichen noch erhebliche regulatorische Weichenstellungen notwendig, um DiGA langfristig in der Regelversorgung zu etablieren. Zentrale Herausforderungen bestehen u. a. in der Nutzerzentrierung oder in der nachhaltigen Verwendung der Anwendungen.Since December 2019, digital health applications (DiGA) have been included in standard care in Germany and are therefore reimbursed by the statutory health insurance funds to support patients in the treatment of diseases or impairments. There are 48 registered DiGA listed in the directory of the Federal Institute of Drugs and Medical Devices (BfArM), mainly in the areas of mental health; hormones and metabolism; and muscles, bones, and joints. In this article, the “Digital Health” specialist group of the German Informatics Society describes the current developments around DiGA as well as the current sentiment on topics such as user-centricity, patient and practitioner acceptance, and innovation potential. In summary, over the past three years, DiGA have experienced a positive development, characterized by a gradually increasing availability of various DiGA and coverage areas as well as prescription numbers. Nevertheless, significant regulatory adjustments are still required in some areas to establish DiGA as a well-established instrument in long-term routine healthcare. Key challenges include user-centeredness and the sustainable use of the applications
Direct handling between vessels and trucks: skipping storage of containers at seaport terminals
No full textContainer yards are increasingly becoming bottlenecks at the terminals. To address this, new approaches are needed. One way to redesign processes at the terminal is the direct handling of containers on the seaside. This study employs a discrete-event simulation model to analyse the effects of delayed truck arrivals on quay crane productivity during direct handling between vessels and trucks. In this context, direct handling of containers refers to the loading and unloading of containers between vessels and trucks without intermediate storage in the container yard. A simulation model using Tecnomatix Plant Simulation replicates a terminal employing both conventional and direct handling, examining various truck delay scenarios. Results indicate that minor truck delays mildly affect quay crane productivity, whereas significant delays considerably diminish productivity, especially when a larger share of containers is handled directly. Although direct handling offers efficiency potential, delayed trucks pose significant planning challenges. Future research will aim to develop strategies to mitigate these impacts, such as flexible export container loading sequences
Development of a Simulation Library for Material Flow Modelling in Special Machine Construction
No full textThe machinery building industry designs and constructs customized production lines, relying on simulation tools for design, validation, and project acquisition. However, a lack of standardized, detailed simulation libraries tailored to this sector causes modelling inefficiencies. This paper presents a structured methodology for developing such libraries, using software engineering principles and specialized system analysis. A simulation library focusing on transfer systems was developed using this methodology within Siemens Plant Simulation for Robert Bosch Manufacturing Solutions GmbH (BMG). Evaluation of the library via a complex industrial use case demonstrated a significant reduction in modelling effort, saving approximately 65 hours (90%) per layout iteration compared to traditional model development. While implemented on a specific platform, the methodology and
architectural concepts offer a transferable framework for improving simulation efficiency and fidelity in this industry
Simulation-based Reinforcement Learning for Production Job Control
No full textThis paper explores simulation-based reinforcement learning for production job control in a single-machine environment with stochastic demand. A SimPy-based discrete-event simulation implements inventory dynamics, while a Gym-compatible interface enables training of reinforcement learning agents. Using Q-learning as a baseline, the study highlights the challenges of applying learning algorithms in such settings, including the need for careful reward shaping, discretization, and environment simplification. Results show that even in simplified scenarios, convergence is slow and sensitive to design choices. The approach offers potential but requires further refinement before it can support complex, real-world production planning tasks