Article
Refine
Year of publication
- 2023 (64) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (22)
- Fachbereich Chemie und Biotechnologie (14)
- Fachbereich Luft- und Raumfahrttechnik (11)
- INB - Institut für Nano- und Biotechnologien (11)
- ECSM European Center for Sustainable Mobility (9)
- IfB - Institut für Bioengineering (7)
- Fachbereich Energietechnik (5)
- Fachbereich Maschinenbau und Mechatronik (5)
- Nowum-Energy (4)
- Fachbereich Elektrotechnik und Informationstechnik (3)
Language
- English (64) (remove)
Document Type
- Article (64) (remove)
Keywords
- Bacillaceae (2)
- Biotechnological application (2)
- Subtilases (2)
- Subtilisin (2)
- additive manufacturing (2)
- factory planning (2)
- manufacturing flexibility (2)
- ultrasound (2)
- (Poly)saccharides (1)
- 197m/gHg (1)
- Acyl-amino acids (1)
- Aeroelasticity (1)
- Aloe vera (1)
- Aminoacylase (1)
- Anammox (1)
- Antibias (1)
- Architectural design (1)
- Automotive safety approach (1)
- Autonomy (1)
- Bacillus atrophaeus spores (1)
- Bacterial cellulose (1)
- Bioabsorbable (1)
- Blade element method (1)
- Bragg peak (1)
- Brake set-up (1)
- Braking curves (1)
- Brands (1)
- Broad pH spectrum (1)
- CFD (1)
- CO2 emission reduction targets (1)
- CRISPR/Cas9 (1)
- Capacitive field-effect sensor (1)
- Carbon sources (1)
- Cellulose nanostructure (1)
- Change (1)
- Chaperone co-expression (1)
- Charging station (1)
- Chondroitin sulfate (1)
- Competitiveness (1)
- Conductive Boundary Condition (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)
- Dietary supplements (1)
- Diversity Management (1)
- Drag estimation (1)
- Driver assistance system (1)
- Driving cycle recognition (1)
- E-Mobility (1)
- ECMS (1)
- Earthquake (1)
- Electronic vehicle (1)
- Endothelial dysfunction (1)
- Energy management strategies (1)
- Energy-intensive industry (1)
- Engineering Habitus (1)
- Enterprise information systems (1)
- Fault approximation (1)
- Fault detection (1)
- Finite element method (1)
- Finland (1)
- Floor prices (1)
- Freight rail (1)
- Full-vehicle crash test (1)
- Ga-68 (1)
- Geriatric (1)
- Germany (1)
- Glucosamine (1)
- Gold nanoparticle (AuNP) (1)
- Gold nanoparticles (1)
- Halotolerant protease (1)
- High-field NMR (1)
- Hip fractures (1)
- Human factors (1)
- Inclusion bodies (1)
- Information extraction (1)
- Inverse Scattering (1)
- Inverse scattering problem (1)
- Label-free detection (1)
- Lactobacillus rhamnosus GG (1)
- Latvia (1)
- LbL films (1)
- Local path planning (1)
- Long COVID (1)
- Luxury (1)
- MCDA (1)
- Mainstream (1)
- Masonry partition walls (1)
- Medical radionuclide production (1)
- Medusomyces gisevi (1)
- Meitner-Auger-electron (MAE) (1)
- Metal contaminants (1)
- Microfluidic solvent extraction (1)
- Mobility transition (1)
- Model-driven software engineering (1)
- Multi-criteria decision analysis (1)
- Multi-objective optimization (1)
- Multicell (1)
- Multiplexing (1)
- Multirotor UAS (1)
- Nitrogen removal (1)
- Obstacle avoidance (1)
- Operations (1)
- Organic acids (1)
- Organizational Culture (1)
- Out-of-plane capacity (1)
- Parking (1)
- Partial nitritation (1)
- Path planning (1)
- Polylactide acid (1)
- Polysaccharides (1)
- Post-COVID-19 syndrome (1)
- Predictive battery discharge (1)
- Preference assessment (1)
- Prevention (1)
- Propeller (1)
- Propeller elasticity (1)
- Prophylaxis (1)
- Raman spectroscopy (1)
- Regionalization (1)
- Reservation system (1)
- Resistive temperature detector (1)
- Rotary encoder (1)
- SOA (1)
- Shunting (1)
- Silk fibroin (1)
- Simulation (1)
- Slab deflection (1)
- Sn₃O₄ (1)
- Software and systems modeling (1)
- Spectroscopy (1)
- Steel industry (1)
- Streptomyces griseus (1)
- Streptomyces lividans (1)
- Targeted radionuclide therapy (TRT) (1)
- Transmission Eigenvalues (1)
- UAV (1)
- Utilization improvement (1)
- Vibrio natriegens (1)
- Wastewater (1)
- Wiegand sensor (1)
- Wind milling (1)
- Wind tunnel experiments (1)
- adaptive systems (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)
- 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)
- 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)
- immobilization (1)
- independence test (1)
- infill strategy (1)
- intelligent control (1)
- intelligent energy management (1)
- locomotion (1)
- machine learning (1)
- mainstream deammonification (1)
- manufacturing (1)
- manufacturing data model (1)
- methanation (1)
- mix flexibility (1)
- nanobelts (1)
- neutrons (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)
- proton therapy (1)
- protons (1)
- qNMR (1)
- random effects (1)
- rapid tooling (1)
- recombinant expression (1)
- relative dosimetry (1)
- retinal microvasculature (1)
- service-oriented architectures (1)
- smart-charging (1)
- sterilization (1)
- stretch-shortening cycle (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)
Obstacle avoidance is critical for unmanned aerial vehicles (UAVs) operating autonomously. Obstacle avoidance algorithms either rely on global environment data or local sensor data. Local path planners react to unforeseen objects and plan purely on local sensor information. Similarly, animals need to find feasible paths based on local information about their surroundings. Therefore, their behavior is a valuable source of inspiration for path planning. Bumblebees tend to fly vertically over far-away obstacles and horizontally around close ones, implying two zones for different flight strategies depending on the distance to obstacles. This work enhances the local path planner 3DVFH* with this bio-inspired strategy. The algorithm alters the goal-driven function of the 3DVFH* to climb-preferring if obstacles are far away. Prior experiments with bumblebees led to two definitions of flight zone limits depending on the distance to obstacles, leading to two algorithm variants. Both variants reduce the probability of not reaching the goal of a 3DVFH* implementation in Matlab/Simulink. The best variant, 3DVFH*b-b, reduces this probability from 70.7 to 18.6% in city-like worlds using a strong vertical evasion strategy. Energy consumption is higher, and flight paths are longer compared to the algorithm version with pronounced horizontal evasion tendency. A parameter study analyzes the effect of different weighting factors in the cost function. The best parameter combination shows a failure probability of 6.9% in city-like worlds and reduces energy consumption by 28%. Our findings demonstrate the potential of bio-inspired approaches for improving the performance of local path planning algorithms for UAV.
Companies often build their businesses based on product information and therefore try to automate the process of information extraction (IE). Since the information source is usually heterogeneous and non-standardized, classic extract, transform, load techniques reach their limits. Hence, companies must implement the newest findings from research to tackle the challenges of process automation. They require a flexible and robust system that is extendable and ensures the optimal processing of the different document types. This paper provides a distributed microservice architecture pattern that enables the automated generation of IE pipelines. Since their optimal design is individual for each input document, the system ensures the ad-hoc generation of pipelines depending on specific document characteristics at runtime. Furthermore, it introduces the automated quality determination of each available pipeline and controls the integration of new microservices based on their impact on the business value. The introduced system enables fast prototyping of the newest approaches from research and supports companies in automating their IE processes. Based on the automated quality determination, it ensures that the generated pipelines always meet defined business requirements when they come into productive use.
In this work, the bioabsorbable materials, namely fibroin, polylactide acid (PLA), magnesium and magnesium oxide are investigated for their application as transient, resistive temperature detectors (RTD). For this purpose, a thin-film magnesium-based meander-like electrode is deposited onto a flexible, bioabsorbable substrate (fibroin or PLA) and encapsulated (passivated) by additional magnesium oxide layers on top and below the magnesium-based electrode. The morphology of different layered RTDs is analyzed by scanning electron microscopy. The sensor performance and lifetime of the RTD is characterized both under ambient atmospheric conditions between 30°C and 43°C, and wet tissue-like conditions with a constant temperature regime of 37°C. The latter triggers the degradation process of the magnesium-based layers. The 3-layers RTDs on a PLA substrate could achieve a lifetime of 8.5 h. These sensors also show the best sensor performance under ambient atmospheric conditions with a mean sensitivity of 0.48 Ω/°C ± 0.01 Ω/°C.
In comparison to single-analyte devices, multiplexed systems for a multianalyte detection offer a reduced assay time and sample volume, low cost, and high throughput. Herein, a multiplexing platform for an automated quasi-simultaneous characterization of multiple (up to 16) capacitive field-effect sensors by the capacitive–voltage (C–V) and the constant-capacitance (ConCap) mode is presented. The sensors are mounted in a newly designed multicell arrangement with one common reference electrode and are electrically connected to the impedance analyzer via the base station. A Python script for the automated characterization of the sensors executes the user-defined measurement protocol. The developed multiplexing system is tested for pH measurements and the label-free detection of ligand-stabilized, charged gold nanoparticles.
Throughout the last decade, and particularly in 2022, water scarcity has become a critical concern in Morocco and other Mediterranean countries. The lack of rainfall during spring was worsened by a succession of heat waves during the summer. To address this drought, innovative solutions, including the use of new technologies such as hydrogels, will be essential to transform agriculture. This paper presents the findings of a study that evaluated the impact of hydrogel application on onion (Allium cepa) cultivation in Meknes, Morocco. The treatments investigated in this study comprised two different types of hydrogel-based soil additives (Arbovit® polyacrylate and Huminsorb® polyacrylate), applied at two rates (30 and 20 kg/ha), and irrigated at two levels of water supply (100% and 50% of daily crop evapotranspiration; ETc). Two control treatments were included, without hydrogel application and with both water amounts. The experiment was conducted in an open field using a completely randomized design. The results indicated a significant impact of both hydrogel-type dose and water dose on onion plant growth, as evidenced by various vegetation parameters. Among the hydrogels tested, Huminsorb® Polyacrylate produced the most favorable outcomes, with treatment T9 (100%, HP, 30 kg/ha) yielding 70.55 t/ha; this represented an increase of 11 t/ha as compared to the 100% ETc treatment without hydrogel application. Moreover, the combination of hydrogel application with 50% ETc water stress showed promising results, with treatment T4 (HP, 30 kg, 50%) producing almost the same yield as the 100% ETc treatment without hydrogel while saving 208 mm of water.
Manufacturing companies across multiple industries face an increasingly dynamic and unpredictable environment. This development can be seen on both the market and supply side. To respond to these challenges, manufacturing companies must implement smart manufacturing systems and become more flexible and agile. The flexibility in operational planning regarding the scheduling and sequencing of customer orders needs to be increased and new structures must be implemented in manufacturing systems’ fundamental design as they constitute much of the operational flexibility available. To this end, smart and more flexible solutions for production planning and control (PPC) are developed. However, scheduling or sequencing is often only considered isolated in a predefined stable environment. Moreover, their orientation on the fundamental logic of the existing IT solutions and their applicability in a dynamic environment is limited. This paper presents a conceptual model for a task-based description logic that can be applied to factory planning, technology planning, and operational control. By using service-oriented architectures, the goal is to generate smart manufacturing systems. The logic is designed to allow for easy and automated maintenance. It is compatible with the existing resource and process allocation logic across operational and strategic factory and production planning.
Melting probes are a proven tool for the exploration of thick ice layers and clean sampling of subglacial water on Earth. Their compact size and ease of operation also make them a key technology for the future exploration of icy moons in our Solar System, most prominently Europa and Enceladus. For both mission planning and hardware engineering, metrics such as efficiency and expected performance in terms of achievable speed, power requirements, and necessary heating power have to be known.
Theoretical studies aim at describing thermal losses on the one hand, while laboratory experiments and field tests allow an empirical investigation of the true performance on the other hand. To investigate the practical value of a performance model for the operational performance in extraterrestrial environments, we first contrast measured data from terrestrial field tests on temperate and polythermal glaciers with results from basic heat loss models and a melt trajectory model. For this purpose, we propose conventions for the determination of two different efficiencies that can be applied to both measured data and models. One definition of efficiency is related to the melting head only, while the other definition considers the melting probe as a whole. We also present methods to combine several sources of heat loss for probes with a circular cross-section, and to translate the geometry of probes with a non-circular cross-section to analyse them in the same way. The models were selected in a way that minimizes the need to make assumptions about unknown parameters of the probe or the ice environment.
The results indicate that currently used models do not yet reliably reproduce the performance of a probe under realistic conditions. Melting velocities and efficiencies are constantly overestimated by 15 to 50 % in the models, but qualitatively agree with the field test data. Hence, losses are observed, that are not yet covered and quantified by the available loss models. We find that the deviation increases with decreasing ice temperature. We suspect that this mismatch is mainly due to the too restrictive idealization of the probe model and the fact that the probe was not operated in an efficiency-optimized manner during the field tests. With respect to space mission engineering, we find that performance and efficiency models must be used with caution in unknown ice environments, as various ice parameters have a significant effect on the melting process. Some of these are difficult to estimate from afar.
Antibias training is increasingly demanded and practiced in academia and industry to increase employees’ sensitivity to discrimination, racism, and diversity. Under the heading of “Diversity Management,” antibias trainings are mainly offered as one-off workshops intending to raise awareness of unconscious biases, create a diversity-affirming corporate culture, promote awareness of the potential of
diversity, and ultimately enable the reflection of diversity in development processes. However, coming from childhood education, research and scientific articles on the sustainable effectiveness of antibias in adulthood, especially in academia, are very scarce. In order to fill this research gap, the article aims to explore how sustainable the effects of individual antibias trainings on participants’ behavior are. In order to investigate this, participant observation in a qualitative pre–post setting was conducted, analyzing antibias training in an academic context. Two observers actively participated in the training sessions and documented the activities and reflection processes of the participants. Overall, the results question the effectiveness of single antibias trainings and show that a target-group adaptive approach is mandatory owing to the background of the approach in early childhood education. Therefore, antibias work needs to be adapted to the target group’s needs and realities of life. Furthermore, the study reveals that single antibias trainings must be embedded in a holistic diversity management approach to stimulate sustainable reflection processes among the target group. This article is one of the first to scientifically evaluate antibias training effectiveness, especially in engineering sciences and the university context.
In this paper, we provide an analytical study of the transmission eigenvalue problem with two conductivity parameters. We will assume that the underlying physical model is given by the scattering of a plane wave for an isotropic scatterer. In previous studies, this eigenvalue problem was analyzed with one conductive boundary parameter whereas we will consider the case of two parameters. We prove the existence and discreteness of the transmission eigenvalues as well as study the dependence on the physical parameters. We are able to prove monotonicity of the first transmission eigenvalue with respect to the parameters and consider the limiting procedure as the second boundary parameter vanishes. Lastly, we provide extensive numerical experiments to validate the theoretical work.
New European Union (EU) regulations for UAS operations require an operational risk analysis, which includes an estimation of the potential danger of the UAS crashing. A key parameter for the potential ground risk is the kinetic impact energy of the UAS. The kinetic energy depends on the impact velocity of the UAS and, therefore, on the aerodynamic drag and the weight during free fall. Hence, estimating the impact energy of a UAS requires an accurate drag estimation of the UAS in that state. The paper at hand presents the aerodynamic drag estimation of small-scale multirotor UAS. Multirotor UAS of various sizes and configurations were analysed with a fully unsteady Reynolds-averaged Navier–Stokes approach. These simulations included different velocities and various fuselage pitch angles of the UAS. The results were compared against force measurements performed in a subsonic wind tunnel and provided good consistency. Furthermore, the influence of the UAS`s fuselage pitch angle as well as the influence of fixed and free spinning propellers on the aerodynamic drag was analysed. Free spinning propellers may increase the drag by up to 110%, depending on the fuselage pitch angle. Increasing the fuselage pitch angle of the UAS lowers the drag by 40% up to 85%, depending on the UAS. The data presented in this paper allow for increased accuracy of ground risk assessments.