Refine
Year of publication
- 2023 (101) (remove)
Document Type
- Article (59)
- Conference Proceeding (30)
- Part of a Book (5)
- Preprint (2)
- Talk (2)
- Book (1)
- Contribution to a Periodical (1)
- Habilitation (1)
Language
- English (101) (remove)
Keywords
- Information extraction (3)
- Natural language processing (3)
- Associated liquids (2)
- Bacillaceae (2)
- Biotechnological application (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)
- 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)
- Broad pH spectrum (1)
- Building Automation (1)
- Business Process Intelligence (1)
- CFD (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)
- 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 nanoparticles (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)
- Lactobacillus rhamnosus GG (1)
- Latvia (1)
- LbL films (1)
- Leaderboard (1)
- Levulinic acid (1)
- Local path planning (1)
- Long COVID (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)
- 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)
- Obstacle avoidance (1)
- Ocean worlds (1)
- Open Source (1)
- Operational Design Domain (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)
- Sustainable engineering education (1)
- Tapered ends (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)
Institute
- Fachbereich Medizintechnik und Technomathematik (28)
- Fachbereich Elektrotechnik und Informationstechnik (18)
- ECSM European Center for Sustainable Mobility (16)
- Fachbereich Luft- und Raumfahrttechnik (16)
- Fachbereich Chemie und Biotechnologie (13)
- Fachbereich Energietechnik (13)
- INB - Institut für Nano- und Biotechnologien (11)
- IfB - Institut für Bioengineering (9)
- Fachbereich Wirtschaftswissenschaften (7)
- Fachbereich Maschinenbau und Mechatronik (6)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (6)
- Nowum-Energy (6)
- Kommission für Forschung und Entwicklung (3)
- Solar-Institut Jülich (3)
- Fachbereich Bauingenieurwesen (2)
- Institut fuer Angewandte Polymerchemie (2)
- Arbeitsstelle fuer Hochschuldidaktik und Studienberatung (1)
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.
The eVTOL industry is a rapidly growing mass market expected to start in 2024. eVTOL compete, caused by their predicted missions, with ground-based transportation modes, including mainly passenger cars. Therefore, the automotive and classical aircraft design process is reviewed and compared to highlight advantages for eVTOL development. A special focus is on ergonomic comfort and safety. The need for further investigation of eVTOL’s crashworthiness is outlined by, first, specifying the relevance of passive safety via accident statistics and customer perception analysis; second, comparing the current state of regulation and certification; and third, discussing the advantages of integral safety and applying the automotive safety approach for eVTOL development. Integral safety links active and passive safety, while the automotive safety approach means implementing standardized mandatory full-vehicle crash tests for future eVTOL. Subsequently, possible crash impact conditions are analyzed, and three full-vehicle crash load cases are presented.
Background
Aminoacylases are highly promising enzymes for the green synthesis of acyl-amino acids, potentially replacing the environmentally harmful Schotten-Baumann reaction. Long-chain acyl-amino acids can serve as strong surfactants and emulsifiers, with application in cosmetic industries. Heterologous expression of these enzymes, however, is often hampered, limiting their use in industrial processes.
Results
We identified a novel mycobacterial aminoacylase gene from Mycolicibacterium smegmatis MKD 8, cloned and expressed it in Escherichia coli and Vibrio natriegens using the T7 overexpression system. The recombinant enzyme was prone to aggregate as inclusion bodies, and while V. natriegens Vmax™ could produce soluble aminoacylase upon induction with isopropyl β-d-1-thiogalactopyranoside (IPTG), E. coli BL21 (DE3) needed autoinduction with lactose to produce soluble recombinant protein. We successfully conducted a chaperone co-expression study in both organisms to further enhance aminoacylase production and found that overexpression of chaperones GroEL/S enhanced aminoacylase activity in the cell-free extract 1.8-fold in V. natriegens and E. coli. Eventually, E. coli ArcticExpress™ (DE3), which co-expresses cold-adapted chaperonins Cpn60/10 from Oleispira antarctica, cultivated at 12 °C, rendered the most suitable expression system for this aminoacylase and exhibited twice the aminoacylase activity in the cell-free extract compared to E. coli BL21 (DE3) with GroEL/S co-expression at 20 °C. The purified aminoacylase was characterized based on hydrolytic activities, being most stable and active at pH 7.0, with a maximum activity at 70 °C, and stability at 40 °C and pH 7.0 for 5 days. The aminoacylase strongly prefers short-chain acyl-amino acids with smaller, hydrophobic amino acid residues. Several long-chain amino acids were fairly accepted in hydrolysis as well, especially N-lauroyl-L-methionine. To initially evaluate the relevance of this aminoacylase for the synthesis of N-acyl-amino acids, we demonstrated that lauroyl-methionine can be synthesized from lauric acid and methionine in an aqueous system.
Conclusion
Our results suggest that the recombinant enzyme is well suited for synthesis reactions and will thus be further investigated.
Several species of (poly)saccharides and organic acids can be found often simultaneously in various biological matrices, e.g., fruits, plant materials, and biological fluids. The analysis of such matrices sometimes represents a challenging task. Using Aloe vera (A. vera) plant materials as an example, the performance of several spectro-scopic methods (80 MHz benchtop NMR, NIR, ATR-FTIR and UV–vis) for the simultaneous analysis of quality parameters of this plant material was compared. The determined parameters include (poly)saccharides such as aloverose, fructose and glucose as well as organic acids (malic, lactic, citric, isocitric, acetic, fumaric, benzoic and sorbic acids). 500 MHz NMR and high-performance liquid chromatography (HPLC) were used as the reference methods.
UV–vis data can be used only for identification of added preservatives (benzoic and sorbic acids) and drying agent (maltodextrin) and semiquantitative analysis of malic acid. NIR and MIR spectroscopies combined with multivariate regression can deliver more informative overview of A. vera extracts being able to additionally quantify glucose, aloverose, citric, isocitric, malic, lactic acids and fructose. Low-field NMR measurements can be used for the quantification of aloverose, glucose, malic, lactic, acetic, and benzoic acids. The benchtop NMR method was successfully validated in terms of robustness, stability, precision, reproducibility and limit of detection (LOD) and quantification (LOQ), respectively. All spectroscopic techniques are useful for the screening of (poly)saccharides and organic acids in plant extracts and should be applied according to its availability as well as information and confidence required for the specific analytical goal. Benchtop NMR spectroscopy seems to be the most feasible solution for quality control of A. vera products.
Using scenarios is vital in identifying and specifying measures for successfully transforming the energy system. Such transformations can be particularly challenging and require the support of a broader set of stakeholders. Otherwise, there will be opposition in the form of reluctance to adopt the necessary technologies. Usually, processes for considering stakeholders' perspectives are very time-consuming and costly. In particular, there are uncertainties about how to deal with modifications in the scenarios. In principle, new consulting processes will be required. In our study, we show how multi-criteria decision analysis can be used to analyze stakeholders' attitudes toward transition paths. Since stakeholders differ regarding their preferences and time horizons, we employ a multi-criteria decision analysis approach to identify which stakeholders will support or oppose a transition path. We provide a flexible template for analyzing stakeholder preferences toward transition paths. This flexibility comes from the fact that our multi-criteria decision aid-based approach does not involve intensive empirical work with stakeholders. Instead, it involves subjecting assumptions to robustness analysis, which can help identify options to influence stakeholders' attitudes toward transitions.
The connective tissues such as tendons contain an extracellular matrix (ECM) comprising collagen fibrils scattered within the ground substance. These fibrils are instrumental in lending mechanical stability to tissues. Unfortunately, our understanding of how collagen fibrils reinforce the ECM remains limited, with no direct experimental evidence substantiating current theories. Earlier theoretical studies on collagen fibril reinforcement in the ECM have relied predominantly on the assumption of uniform cylindrical fibers, which is inadequate for modelling collagen fibrils, which possessed tapered ends. Recently, Topçu and colleagues published a paper in the International Journal of Solids and Structures, presenting a generalized shear-lag theory for the transfer of elastic stress between the matrix and fibers with tapered ends. This paper is a positive step towards comprehending the mechanics of the ECM and makes a valuable contribution to formulating a complete theory of collagen fibril reinforcement in the ECM.
To fulfil the CO2 emission reduction targets of the European Union (EU), heavy-duty (HD) trucks need to operate 15% more efficiently by 2025 and 30% by 2030. Their electrification is necessary as conventional HD trucks are already optimized for the long-haul application. The resulting hybrid electric vehicle (HEV) truck gains most of the fuel saving potential by the recuperation of potential energy and its consecutive utilization. The key to utilizing the full potential of HEV-HD trucks is to maximize the amount of recuperated energy and ensure its intelligent usage while keeping the operating point of the internal combustion engine as efficient as possible. To achieve this goal, an intelligent energy management strategy (EMS) based on ECMS is developed for a parallel HEV-HD truck which uses predictive discharge of the battery and adaptive operating strategy regarding the height profile and the vehicle mass. The presented EMS can reproduce the global optimal operating strategy over long phases and lead to a fuel saving potential of up to 2% compared with a heuristic strategy. Furthermore, the fuel saving potential is correlated with the investigated boundary conditions to deepen the understanding of the impact of intelligent EMS for HEV-HD trucks.
Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling.
It has been shown that muscle fascicle curvature increases with increasing contraction level and decreasing muscle–tendon complex length. The analyses were done with limited examination windows concerning contraction level, muscle–tendon complex length, and/or intramuscular position of ultrasound imaging. With this study we aimed to investigate the correlation between fascicle arching and contraction, muscle–tendon complex length and their associated architectural parameters in gastrocnemius muscles to develop hypotheses concerning the fundamental mechanism of fascicle curving. Twelve participants were tested in five different positions (90°/105°*, 90°/90°*, 135°/90°*, 170°/90°*, and 170°/75°*; *knee/ankle angle). They performed isometric contractions at four different contraction levels (5%, 25%, 50%, and 75% of maximum voluntary contraction) in each position. Panoramic ultrasound images of gastrocnemius muscles were collected at rest and during constant contraction. Aponeuroses and fascicles were tracked in all ultrasound images and the parameters fascicle curvature, muscle–tendon complex strain, contraction level, pennation angle, fascicle length, fascicle strain, intramuscular position, sex and age group were analyzed by linear mixed effect models. Mean fascicle curvature of the medial gastrocnemius increased with contraction level (+5 m−1 from 0% to 100%; p = 0.006). Muscle–tendon complex length had no significant impact on mean fascicle curvature. Mean pennation angle (2.2 m−1 per 10°; p < 0.001), inverse mean fascicle length (20 m−1 per cm−1; p = 0.003), and mean fascicle strain (−0.07 m−1 per +10%; p = 0.004) correlated with mean fascicle curvature. Evidence has also been found for intermuscular, intramuscular, and sex-specific intramuscular differences of fascicle curving. Pennation angle and the inverse fascicle length show the highest predictive capacities for fascicle curving. Due to the strong correlations between pennation angle and fascicle curvature and the intramuscular pattern of curving we suggest for future studies to examine correlations between fascicle curvature and intramuscular fluid pressure.
Herein, fibroin, polylactide (PLA), and carbon are investigated for their suitability as biocompatible and biodegradable materials for amperometric biosensors. For this purpose, screen-printed carbon electrodes on the biodegradable substrates fibroin and PLA are modified with a glucose oxidase membrane and then encapsulated with the biocompatible material Ecoflex. The influence of different curing parameters of the carbon electrodes on the resulting biosensor characteristics is studied. The morphology of the electrodes is investigated by scanning electron microscopy, and the biosensor performance is examined by amperometric measurements of glucose (0.5–10 mM) in phosphate buffer solution, pH 7.4, at an applied potential of 1.2 V versus a Ag/AgCl reference electrode. Instead of Ecoflex, fibroin, PLA, and wound adhesive are tested as alternative encapsulation compounds: a series of swelling tests with different fibroin compositions, PLA, and Ecoflex has been performed before characterizing the most promising candidates by chronoamperometry. Therefore, the carbon electrodes are completely covered with the particular encapsulation material. Chronoamperometric measurements with H2O2 concentrations between 0.5 and 10 mM enable studying the leakage current behavior.