Refine
Year of publication
- 2023 (114) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (28)
- Fachbereich Elektrotechnik und Informationstechnik (21)
- Fachbereich Luft- und Raumfahrttechnik (19)
- ECSM European Center for Sustainable Mobility (18)
- Fachbereich Chemie und Biotechnologie (16)
- Fachbereich Energietechnik (13)
- INB - Institut für Nano- und Biotechnologien (11)
- IfB - Institut für Bioengineering (9)
- Fachbereich Wirtschaftswissenschaften (8)
- Fachbereich Maschinenbau und Mechatronik (6)
Language
- English (114) (remove)
Document Type
- Article (64)
- Conference Proceeding (35)
- Part of a Book (6)
- Habilitation (2)
- Preprint (2)
- Talk (2)
- Book (1)
- Conference: Meeting Abstract (1)
- Contribution to a Periodical (1)
Keywords
- Information extraction (3)
- Natural language processing (3)
- Associated liquids (2)
- Bacillaceae (2)
- Biotechnological application (2)
- CFD (2)
- Diversity Management (2)
- Engineering Habitus (2)
- Future Skills (2)
- Interdisciplinarity (2)
- Organizational Culture (2)
- Power plants (2)
- Subtilases (2)
- Subtilisin (2)
- Sustainability (2)
- additive manufacturing (2)
- factory planning (2)
- manufacturing flexibility (2)
- ultrasound (2)
- (Poly)saccharides (1)
- (R)- or (S)- gamma-valerolactone (1)
- 197m/gHg (1)
- 4-hydroxy valeric acid (1)
- Academia (1)
- Active learning (1)
- Acyl-amino acids (1)
- Aeroelasticity (1)
- Agent-based simulation (1)
- Agile development (1)
- Aloe vera (1)
- Aminoacylase (1)
- Anammox (1)
- Android (1)
- Anomaly detection (1)
- Anti-Bias (1)
- Antibias (1)
- Architectural design (1)
- Asymptotic relative efficiency (1)
- Automation (1)
- Automotive safety approach (1)
- Autonomy (1)
- Bacillus atrophaeus spores (1)
- Bacterial cellulose (1)
- Best practice sharing (1)
- Bioabsorbable (1)
- Blade element method (1)
- Bragg peak (1)
- Brake set-up (1)
- Braking curves (1)
- Brands (1)
- Broad pH spectrum (1)
- Building Automation (1)
- Business Process Intelligence (1)
- CO2 (1)
- CO2 emission reduction targets (1)
- CRISPR/Cas9 (1)
- Capacitive field-effect sensor (1)
- Carbon Dioxide (1)
- Carbon sources (1)
- Cellulose nanostructure (1)
- Change (1)
- Chaperone co-expression (1)
- Charging station (1)
- Chiralidon-R (1)
- Chiralidon-S (1)
- Chondroitin sulfate (1)
- Clustering (1)
- Cognitive assistance system (1)
- Collagen fibrils (1)
- Competitiveness (1)
- Conductive Boundary Condition (1)
- Connected Automated Vehicle (1)
- Connective tissues (1)
- Control (1)
- Cost function (1)
- Cost-effectiveness (1)
- Cramér-von-Mises test (1)
- Crashworthiness (1)
- Cross border adjustment mechanism (1)
- Culture media (1)
- Cyclotron production (1)
- DPA (dipicolinic acid) (1)
- Datasets (1)
- Decision theory (1)
- Deep learning (1)
- Design Thinking (1)
- Dietary supplements (1)
- Digital leadership (1)
- Digital transformation (1)
- Digital triage (1)
- Digital twin (1)
- District data model (1)
- District energy planning platform (1)
- Drag estimation (1)
- Driver assistance system (1)
- Driving cycle recognition (1)
- E-Mobility (1)
- ECMS (1)
- Earthquake (1)
- Education (1)
- Electrocardiography (1)
- Electrochemistry (1)
- Electronic vehicle (1)
- Elicit (1)
- Endothelial dysfunction (1)
- Energy Disaggregation (1)
- Energy management strategies (1)
- Energy market design (1)
- Energy storage (1)
- Energy system planning (1)
- Energy-intensive industry (1)
- Enterprise information systems (1)
- Extracellular matrix (ECM) (1)
- Fault approximation (1)
- Fault detection (1)
- Finite element method (1)
- Finland (1)
- Floor prices (1)
- Freight rail (1)
- Full-vehicle crash test (1)
- Future skills (1)
- Ga-68 (1)
- Gamification (1)
- Geriatric (1)
- Germany (1)
- Glucosamine (1)
- Gold nanoparticle (AuNP) (1)
- Gold nanoparticles (1)
- Guide Tube (1)
- Halotolerant protease (1)
- High-field NMR (1)
- Hip fractures (1)
- Home Assistant (1)
- Home Automation Platform (1)
- Human factors (1)
- Human-centered work design (1)
- Human-robot collaboration (1)
- Ice melting probe (1)
- Ice penetration (1)
- Icy moons (1)
- Inclusion bodies (1)
- Incomplete data (1)
- Instagram store (1)
- Interculturality (1)
- Inverse Scattering (1)
- Inverse scattering problem (1)
- Key competences (1)
- Label-free detection (1)
- Labyfrinth weirs (1)
- Lactobacillus rhamnosus GG (1)
- Large Eddy Simulation (1)
- Latvia (1)
- LbL films (1)
- Leaderboard (1)
- Levulinic acid (1)
- Local path planning (1)
- Long COVID (1)
- Luxury (1)
- MCDA (1)
- Machine Learning (1)
- Mainstream (1)
- Marginal homogeneity (1)
- Market modeling (1)
- Mars (1)
- Masonry partition walls (1)
- Mechanical stability (1)
- Medical radionuclide production (1)
- Medusomyces gisevi (1)
- Meitner-Auger-electron (MAE) (1)
- Metal contaminants (1)
- Microfluidic solvent extraction (1)
- Micromix (1)
- Minimum Risk Manoeuvre (1)
- Minor chemistry (1)
- Mobility transition (1)
- Model-driven software engineering (1)
- Mpc (1)
- Multi-criteria decision analysis (1)
- Multi-objective optimization (1)
- Multicell (1)
- Multiplexing (1)
- Multirotor UAS (1)
- Natural Language Processing (1)
- Natural language understanding (1)
- Navigation (1)
- Neural networks (1)
- Nitrogen removal (1)
- Nozzle (1)
- Obstacle avoidance (1)
- Ocean worlds (1)
- Open Source (1)
- Operational Design Domain (1)
- Operations (1)
- Organic acids (1)
- Out-of-plane capacity (1)
- PLS (1)
- Paired sample (1)
- Parking (1)
- Partial nitritation (1)
- Path planning (1)
- Path-following (1)
- Performance (1)
- Personality (1)
- Physical chemistry (1)
- Physical chemistry basics (1)
- Physical chemistry starters (1)
- Polylactide acid (1)
- Polysaccharides (1)
- Post-COVID-19 syndrome (1)
- Predictive battery discharge (1)
- Preference assessment (1)
- Prevention (1)
- Privacy (1)
- Process Model Extraction (1)
- Process optimization (1)
- Profile extraction (1)
- Propeller (1)
- Propeller elasticity (1)
- Prophylaxis (1)
- Prototype (1)
- Quality control (1)
- Query learning (1)
- Raman spectroscopy (1)
- Regionalization (1)
- Relation classification (1)
- Renewable energy integration (1)
- Reproducible research (1)
- Reservation system (1)
- Resistive temperature detector (1)
- Responsibility (1)
- Rotary encoder (1)
- SOA (1)
- Sensors comparison (1)
- Shunting (1)
- Silk fibroin (1)
- Simulation (1)
- Slab deflection (1)
- Smart Building (1)
- Sn₃O₄ (1)
- Social impact measurement (1)
- Society (1)
- Software (1)
- Software and systems modeling (1)
- Software development (1)
- Software testing (1)
- Spectroscopy (1)
- Steel industry (1)
- Streptomyces griseus (1)
- Streptomyces lividans (1)
- Stress testing (1)
- Suction (1)
- Sustainable engineering education (1)
- TICTOP (1)
- Tapered ends (1)
- Targeted radionuclide therapy (TRT) (1)
- Teamwork (1)
- Text Mining (1)
- Text mining (1)
- Thermodynamics as minor (1)
- Time-series synchronization (1)
- Transdisciplinarity (1)
- Transformative Competencies (1)
- Transiton of Control (1)
- Transmission Eigenvalues (1)
- Triage-app (1)
- Trustworthy artificial intelligence (1)
- UAV (1)
- Utilization improvement (1)
- V2X (1)
- Vibrio natriegens (1)
- Volumes of confidence regions (1)
- Wastewater (1)
- Wearable electronic device (1)
- Wiegand sensor (1)
- Wind milling (1)
- Wind tunnel experiments (1)
- active learning (1)
- adaptive systems (1)
- aircraft engine (1)
- allocation (1)
- amperometric biosensors (1)
- anammox (1)
- artificial intelligence (1)
- aspergillus (1)
- assistance system (1)
- bacterial cellulose (1)
- bio-methane (1)
- biocompatible (1)
- biodegradabl (1)
- biofilms (1)
- biological dosimeter (1)
- biomechanics (1)
- biosensor (1)
- bubble column (1)
- central symmetry test (1)
- climate change (1)
- combustion (1)
- compression behavior (1)
- conditional excess distribution (1)
- conditional expectation principle (1)
- confidence interval (1)
- connective tissue (1)
- covariance principle (1)
- deficit irrigation (1)
- distribution grid simulation (1)
- e-mobility (1)
- eVTOL development (1)
- eVTOL safety (1)
- electromyography (1)
- emission index (1)
- encapsulation materials (1)
- energy efficiency (1)
- entrepreneurship education (1)
- enzyme cascade (1)
- exchangeability test (1)
- fibroin (1)
- field-effect sensor (1)
- filamentous fungi (1)
- forecast (1)
- fuel cell vehicle (1)
- fused filament fabrication (1)
- gamification (1)
- genome engineering (1)
- glucose oxidase (GOx) (1)
- goodness-of-fit test (1)
- heavy metals (1)
- horseradish peroxidase (HRP) (1)
- hydrogel (1)
- hydrogen (1)
- immobilization (1)
- independence test (1)
- infill strategy (1)
- intelligent control (1)
- intelligent energy management (1)
- lab work (1)
- locomotion (1)
- machine learning (1)
- mainstream deammonification (1)
- manufacturing (1)
- manufacturing data model (1)
- methanation (1)
- mix flexibility (1)
- nanobelts (1)
- neutrons (1)
- nitric oxides (1)
- nitrogen elimination (1)
- not identically distributed (1)
- onion (1)
- optical fibers (1)
- optical sensor setup (1)
- optical trapping (1)
- optimization system (1)
- overload (1)
- physiology (1)
- plug flow reactor (1)
- polyetheretherketone (PEEK) (1)
- portfolio risk (1)
- power-to-gas (1)
- prebiotic (1)
- production planning and control (1)
- professional skills (1)
- proton therapy (1)
- protons (1)
- purchase factor (1)
- qNMR (1)
- random effects (1)
- rapid tooling (1)
- recombinant expression (1)
- relative dosimetry (1)
- retinal microvasculature (1)
- service-oriented architectures (1)
- shopping behavior (1)
- smart-charging (1)
- sterilization (1)
- stretch-shortening cycle (1)
- structural equation model (1)
- technology planning (1)
- tobacco mosaic virus (TMV) (1)
- turnip vein clearing virus (TVCV) (1)
- volume flexibility (1)
- wastewater (1)
- water economy (1)
- yield (1)
- α-aminoacylase (1)
- ε-lysine acylase (1)
Meitner-Auger-electron emitters have a promising potential for targeted radionuclide therapy of cancer because of their short range and the high linear energy transfer of Meitner-Auger-electrons (MAE). One promising MAE candidate is 197m/gHg with its half-life of 23.8 h and 64.1 h, respectively, and high MAE yield. Gold nanoparticles (AuNPs) that are labelled with 197m/gHg could be a helpful tool for radiation treatment of glioblastoma multiforme when infused into the surgical cavity after resection to prevent recurrence. To produce such AuNPs, 197m/gHg was embedded into pristine AuNPs. Two different syntheses were tested starting from irradiated gold containing trace amounts of 197m/gHg. When sodium citrate was used as reducing agent, no 197m/gHg labelled AuNPs were formed, but with tannic acid, 197m/gHg labeled AuNPs were produced. The method was optimized by neutralizing the pH (pH = 7) of the Au/197m/gHg solution, which led to labelled AuNPs with a size of 12.3 ± 2.0 nm as measured by transmission electron microscopy. The labelled AuNPs had a concentration of 50 μg (gold)/mL with an activity of 151 ± 93 kBq/mL (197gHg, time corrected to the end of bombardment).
The major advantage of labyrinth weirs over linear weirs is hydraulic efficiency. In hydraulic modeling efforts, this strength contrasts with limited pump capacity as well as limited computational power for CFD simulations. For the latter, reducing the number of investigated cycles can significantly reduce necessary computational time. In this study, a labyrinth weir with different cycle numbers was investigated. The simulations were conducted in FLOW-3D HYDRO as a Large Eddy Simulation. With a mean deviation of 1.75 % between simulated discharge coefficients and literature design equations, a reasonable agreement was found. For downstream conditions, overall consistent results were observed as well. However, the orientation of labyrinth weirs with a single cycle should be chosen carefully under consideration of the individual research purpose.
Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.
The concept of energy conversion into platform chemicals using bioelectrochemical systems (BES) has gained increasing attention in recent years, as the technology simultaneously provides an opportunity for sustainable chemical production and tackles the challenge of Power-to-X technologies. There are many approaches to realize the industrial scale of BES. One concept is to equip standard bioreactors with static electrodes. However, large installations resulted in a negative influence on various reactor parameters. In this study, we present a new single-chamber BES based on a stirred tank reactor in which the stirrer was replaced by a carbon fiber brush, performing the functions of the working electrode and the stirrer. The reactor is characterized in abiotic studies and electro-fermentations with Clostridium acetobutylicum. Compared to standard reactors an increase in butanol production of 20.14±3.66 % shows that the new BES can be efficiently used for bioelectrochemical processes.
Research on robotic lunar exploration has seen a broad revival, especially since the Google Lunar X-Prize increasingly brought private endeavors into play. This development is supported by national agencies with the aim of enabling long-term lunar infrastructure for in-situ operations and the establishment of a moon village. One challenge for effective exploration missions is developing a compact and lightweight robotic rover to reduce launch costs and open the possibility for secondary payload options. Existing micro rovers for exploration missions are clearly limited by their design for one day of sunlight and their low level of autonomy. For expanding the potential mission applications and range of use, an extension of lifetime could be reached by surviving the lunar night and providing a higher level of autonomy. To address this objective, the paper presents a system design concept for a lightweight micro rover with long-term mission duration capabilities, derived from a multi-day lunar mission scenario at equatorial regions. Technical solution approaches are described, analyzed, and evaluated, with emphasis put on the harmonization of hardware selection due to a strictly limited budget in dimensions and power.
In Europe, efforts are underway to develop key technologies that can be used to explore the Moon and to exploit the resources available. This includes technologies for in-situ resource utilization (ISRU), facilitating the possibility of a future Moon Village. The Moon is the next step for humans and robots to exploit the use of available resources for longer term missions, but also for further exploration of the solar system. A challenge for effective exploration missions is to achieve a compact and lightweight robot to reduce launch costs and open up the possibility of secondary payload options. Current micro rover concepts are primarily designed to last for one day of solar illumination and show a low level of autonomy. Extending the lifetime of the system by enabling survival of the lunar night and implementing a high level of autonomy will significantly increase potential mission applications and the operational range. As a reference mission, the deployment of a micro rover in the equatorial region of the Moon is being considered. An overview of mission parameters and a detailed example mission sequence is given in this paper. The mission parameters are based on an in-depth study of current space agency roadmaps, scientific goals, and upcoming flight opportunities. Furthermore, concepts of the ongoing international micro rover developments are analyzed along with technology solutions identified for survival of lunar nights and a high system autonomy. The results provide a basis of a concise requirements set-up to allow dedicated system developments and qualification measures in the future.
Rocket engine test facilities and launch pads are typically equipped with a guide tube. Its purpose is to ensure the controlled and safe routing of the hot exhaust gases. In addition, the guide tube induces a suction that effects the nozzle flow, namely the flow separation during transient start-up and shut-down of the engine. A cold flow subscale nozzle in combination with a set of guide tubes was studied experimentally
to determine the main influencing parameters.
The growing body of political texts opens up new opportunities for rich insights into political dynamics and ideologies but also increases the workload for manual analysis. Automated speaker attribution, which detects who said what to whom in a speech event and is closely related to semantic role labeling, is an important processing step for computational text analysis. We study the potential of the large language model family Llama 2 to automate speaker attribution in German parliamentary debates from 2017-2021. We fine-tune Llama 2 with QLoRA, an efficient training strategy, and observe our approach to achieve competitive performance in the GermEval 2023 Shared Task On Speaker Attribution in German News Articles and Parliamentary Debates. Our results shed light on the capabilities of large language models in automating speaker attribution, revealing a promising avenue for computational analysis of political discourse and the development of semantic role labeling systems.
Background
Hip fractures are a common and costly health problem, resulting in significant morbidity and mortality, as well as high costs for healthcare systems, especially for the elderly. Implementing surgical preventive strategies has the potential to improve the quality of life and reduce the burden on healthcare resources, particularly in the long term. However, there are currently limited guidelines for standardizing hip fracture prophylaxis practices.
Methods
This study used a cost-effectiveness analysis with a finite-state Markov model and cohort simulation to evaluate the primary and secondary surgical prevention of hip fractures in the elderly. Patients aged 60 to 90 years were simulated in two different models (A and B) to assess prevention at different levels. Model A assumed prophylaxis was performed during the fracture operation on the contralateral side, while Model B included individuals with high fracture risk factors. Costs were obtained from the Centers for Medicare & Medicaid Services, and transition probabilities and health state utilities were derived from available literature. The baseline assumption was a 10% reduction in fracture risk after prophylaxis. A sensitivity analysis was also conducted to assess the reliability and variability of the results.
Results
With a 10% fracture risk reduction, model A costs between $8,850 and $46,940 per quality-adjusted life-year ($/QALY). Additionally, it proved most cost-effective in the age range between 61 and 81 years. The sensitivity analysis established that a reduction of ≥ 2.8% is needed for prophylaxis to be definitely cost-effective. The cost-effectiveness at the secondary prevention level was most sensitive to the cost of the contralateral side’s prophylaxis, the patient’s age, and fracture treatment cost. For high-risk patients with no fracture history, the cost-effectiveness of a preventive strategy depends on their risk profile. In the baseline analysis, the incremental cost-effectiveness ratio at the primary prevention level varied between $11,000/QALY and $74,000/QALY, which is below the defined willingness to pay threshold.
Conclusion
Due to the high cost of hip fracture treatment and its increased morbidity, surgical prophylaxis strategies have demonstrated that they can significantly relieve the healthcare system. Various key assumptions facilitated the modeling, allowing for adequate room for uncertainty. Further research is needed to evaluate health-state-associated risks.
Background
Post-COVID-19 syndrome (PCS) is a lingering disease with ongoing symptoms such as fatigue and cognitive impairment resulting in a high impact on the daily life of patients. Understanding the pathophysiology of PCS is a public health priority, as it still poses a diagnostic and treatment challenge for physicians.
Methods
In this prospective observational cohort study, we analyzed the retinal microcirculation using Retinal Vessel Analysis (RVA) in a cohort of patients with PCS and compared it to an age- and gender-matched healthy cohort (n = 41, matched out of n = 204).
Measurements and main results
PCS patients exhibit persistent endothelial dysfunction (ED), as indicated by significantly lower venular flicker-induced dilation (vFID; 3.42% ± 1.77% vs. 4.64% ± 2.59%; p = 0.02), narrower central retinal artery equivalent (CRAE; 178.1 [167.5–190.2] vs. 189.1 [179.4–197.2], p = 0.01) and lower arteriolar-venular ratio (AVR; (0.84 [0.8–0.9] vs. 0.88 [0.8–0.9], p = 0.007). When combining AVR and vFID, predicted scores reached good ability to discriminate groups (area under the curve: 0.75). Higher PCS severity scores correlated with lower AVR (R = − 0.37 p = 0.017). The association of microvascular changes with PCS severity were amplified in PCS patients exhibiting higher levels of inflammatory parameters.
Conclusion
Our results demonstrate that prolonged endothelial dysfunction is a hallmark of PCS, and impairments of the microcirculation seem to explain ongoing symptoms in patients. As potential therapies for PCS emerge, RVA parameters may become relevant as clinical biomarkers for diagnosis and therapy management.
Environmental emissions, global warming, and energy-related concerns have accelerated the advancements in conventional vehicles that primarily use internal combustion engines. Among the existing technologies, hydrogen fuel cell electric vehicles and fuel cell hybrid electric vehicles may have minimal contributions to greenhouse gas emissions and thus are the prime choices for environmental concerns. However, energy management in fuel cell electric vehicles and fuel cell hybrid electric vehicles is a major challenge. Appropriate control strategies should be used for effective energy management in these vehicles. On the other hand, there has been significant progress in artificial intelligence, machine learning, and designing data-driven intelligent controllers. These techniques have found much attention within the community, and state-of-the-art energy management technologies have been developed based on them. This manuscript reviews the application of machine learning and intelligent controllers for prediction, control, energy management, and vehicle to everything (V2X) in hydrogen fuel cell vehicles. The effectiveness of data-driven control and optimization systems are investigated to evolve, classify, and compare, and future trends and directions for sustainability are discussed.
There is a growing demand for more flexibility in manufacturing to counter the volatility and unpredictability of the markets and provide more individualization for customers. However, the design and implementation of flexibility within manufacturing systems are costly and only economically viable if applicable to actual demand fluctuations. To this end, companies are considering additive manufacturing (AM) to make production more flexible. This paper develops a conceptual model for the impact quantification of AM on volume and mix flexibility within production systems in the early stages of the factory-planning process. Together with the model, an application guideline is presented to help planners with the flexibility quantification and the factory design process. Following the development of the model and guideline, a case study is presented to indicate the potential impact additive technologies can have on manufacturing flexibility Within the case study, various scenarios with different production system configurations and production programs are analyzed, and the impact of the additive technologies on volume and mix flexibility is calculated. This work will allow factory planners to determine the potential impacts of AM on manufacturing flexibility in an early planning stage and design their production systems accordingly.
Traditional vulcanization mold manufacturing is complex, costly, and under pressure due to shorter product lifecycles and diverse variations. Additive manufacturing using Fused Filament Fabrication and high-performance polymers like PEEK offer a promising future in this industry. This study assesses the compressive strength of various infill structures (honeycomb, grid, triangle, cubic, and gyroid) when considering two distinct build directions (Z, XY) to enhance PEEK’s economic and resource efficiency in rapid tooling. A comparison with PETG samples shows the behavior of the infill strategies. Additionally, a proof of concept illustrates the application of a PEEK mold in vulcanization. A peak compressive strength of 135.6 MPa was attained in specimens that were 100% solid and subjected to thermal post-treatment. This corresponds to a 20% strength improvement in the Z direction. In terms of time and mechanical properties, the anisotropic grid and isotropic cubic infill have emerged for use in rapid tooling. Furthermore, the study highlights that reducing the layer thickness from 0.15 mm to 0.1 mm can result in a 15% strength increase. The study unveils the successful utilization of a room-temperature FFF-printed PEEK mold in vulcanization injection molding. The parameters and infill strategies identified in this research enable the resource-efficient FFF printing of PEEK without compromising its strength properties. Using PEEK in rapid tooling allows a cost reduction of up to 70% in tool production.