Refine
Year of publication
- 2019 (198) (remove)
Institute
- Fachbereich Medizintechnik und Technomathematik (65)
- IfB - Institut für Bioengineering (41)
- Fachbereich Luft- und Raumfahrttechnik (38)
- Fachbereich Elektrotechnik und Informationstechnik (30)
- INB - Institut für Nano- und Biotechnologien (20)
- Fachbereich Energietechnik (19)
- Fachbereich Maschinenbau und Mechatronik (17)
- Fachbereich Chemie und Biotechnologie (11)
- Fachbereich Bauingenieurwesen (8)
- MASKOR Institut für Mobile Autonome Systeme und Kognitive Robotik (8)
Language
- English (198) (remove)
Document Type
- Article (97)
- Conference Proceeding (76)
- Part of a Book (15)
- Book (4)
- Doctoral Thesis (3)
- Conference: Meeting Abstract (2)
- Talk (1)
Keywords
- Enterprise Architecture (2)
- Seismic design (2)
- Achilles tendon (1)
- Advanced driver assistance systems (ADAS/AD) (1)
- Aircraft design (1)
- Analytics (1)
- Architectural gear ratio (1)
- Assistive technology (1)
- Automatic control (1)
- BEV (1)
- Case Study (1)
- Change Management (1)
- Combustion (1)
- Components (1)
- Corporate Culture (1)
- Correlations (1)
- Decentral (1)
- Design examples (1)
- Design rules (1)
- Digital Age (1)
- Diversity Management (1)
- Drag (1)
- Earthquake (1)
- Emilia-Romagna earthquake (1)
- Empirical consequence curves (1)
- Empirical fragility functions (1)
- Engineering (1)
- Engineering optimization (1)
- Eurocode 8 (1)
- Force (1)
- Gearbox (1)
- Geometry (1)
- Goodness-of-fit test (1)
- Graph Theory (1)
- Green aircraft (1)
- Gust wind response (1)
- Human-Computer interaction (1)
- Hybrid-electric aircraft (1)
- Hydrogen (1)
- ISO 26262 (1)
- In-plane (1)
- Industrial units (1)
- Innovation Management (1)
- Isolation (1)
- Iterative learning control (1)
- Knee (1)
- Load modeling (1)
- Low NOx (1)
- Low emission (1)
- Machine learning (1)
- Mechanical (1)
- Mixed-integer nonlinear black-box optimization (1)
- Multi-sample problem (1)
- On-site (1)
- Optimization (1)
- Out-of-plane (1)
- PBEE (1)
- Parametric bootstrap (1)
- Powertrain (1)
- Pre-treatment (1)
- Precast buildings (1)
- Preface (1)
- Product family optimization (1)
- Pushover analysis (1)
- Rehabilitation engineering (1)
- Resilience Assessment (1)
- Response spectrum (1)
- Robotic Process Automation (1)
- Running (1)
- Safety of the intended functionality (SOTIF) (1)
- Safety-critical systems validation (1)
- Seismic (1)
- Silos (1)
- Software Robots (1)
- Spectral analysis (1)
- Statistics (1)
- Stiffness (1)
- Tanks (1)
- Tendon properties (1)
- Training (1)
- Unmanned Air Vehicle (1)
- Volume of confidence regions (1)
- WLTP (1)
- Water Supply System (1)
- Wind turbulence (1)
- asymptotic relative efficiency (1)
- batch reproducibility (1)
- concentrating collector (1)
- environmental correlation (1)
- fluorescent protein carrier (1)
- frequency mixing magnetic detection (1)
- greenhouse cultivation (1)
- likelihood ratio test (1)
- magnetic actuation (1)
- magnetic sandwich immunoassay (1)
- magnetic separation (1)
- magnetic tweezers (1)
- magnetophoretic velocity (1)
- multinomial distribution (1)
- multiparametric immunoassays (1)
- multivariate normal distribution (1)
- plant molecular farming (1)
- point-focussing system (1)
- raytracing (1)
- responsive space (1)
- small solar system body characterisation (1)
- small spacecraft asteroid lander (1)
- small spacecraft solar sail (1)
- solar process heat (1)
- superparamagnetic bead (1)
- system engineering (1)
Suppose we have k samples X₁,₁,…,X₁,ₙ₁,…,Xₖ,₁,…,Xₖ,ₙₖ with different sample sizes ₙ₁,…,ₙₖ and unknown underlying distribution functions F₁,…,Fₖ as observations plus k families of distribution functions {G₁(⋅,ϑ);ϑ∈Θ},…,{Gₖ(⋅,ϑ);ϑ∈Θ}, each indexed by elements ϑ from the same parameter set Θ, we consider the new goodness-of-fit problem whether or not (F₁,…,Fₖ) belongs to the parametric family {(G₁(⋅,ϑ),…,Gₖ(⋅,ϑ));ϑ∈Θ}. New test statistics are presented and a parametric bootstrap procedure for the approximation of the unknown null distributions is discussed. Under regularity assumptions, it is proved that the approximation works asymptotically, and the limiting distributions of the test statistics in the null hypothesis case are determined. Simulation studies investigate the quality of the new approach for small and moderate sample sizes. Applications to real-data sets illustrate how the idea can be used for verifying model assumptions.
Enzyme-catalyzed reactions have been designed to mimic various Boolean logic gates in the general framework of unconventional biomolecular computing. While some of the logic gates, particularly OR, AND, are easy to realize with biocatalytic reactions and have been reported in numerous publications, some other, like NXOR, are very challenging and have not been realized yet with enzyme reactions. The paper reports on a novel approach to mimicking the NXOR logic gate using the bell-shaped enzyme activity dependent on pH values. Shifting pH from the optimum value to the acidic or basic values by using acid or base inputs (meaning 1,0 and 0,1 inputs) inhibits the enzyme reaction, while keeping the optimum pH (assuming 0,0 and 1,1 input combinations) preserves a high enzyme activity. The challenging part of the present approach is the selection of an enzyme with a well-demonstrated bell-shape activity dependence on the pH value. While many enzymes can satisfy this condition, we selected pyrroloquinoline quinone (PQQ)-dependent glucose dehydrogenase as this enzyme has the optimum pH center-located on the pH scale allowing the enzyme activity change by the acidic and basic pH shift from the optimum value corresponding to the highest activity. The present NXOR gate is added to the biomolecular “toolbox” as a new example of Boolean logic gates based on enzyme reactions.
The MYOTONES experiment is the first to monitor changes in the basic biomechanical properties (tone, elasticity and stiffness) of the resting human myofascial system due to microgravity with a oninvasive, portable device on board the ISS. The MyotonPRO device applies several brief mechanical stimuli to the surface of the skin, and the natural oscillation signals of the tissue beneath are detected and computed by the MyotonPRO. Thus, an objective, quick and easy determination of the state of the underlying tissue is possible.
Two preflight, four inflight and four post flight measurements were performed on a male astronaut using the same 10 measurement points (MP) for each session. MPs were located on the plantar fascia, Achilles tendon, M. soleus, M. gastrocnemius, M. multifidus, M. splenius capitis, M. deltoideus anterior, M. rectus femoris, infrapatellar tendon, M. tibialis anterior. Subcutaneous tissues thickness above the MPs was measured using ultrasound imaging. Magnetic resonance images (MRI) of lower limb muscles and functional tests were also performed pre- and postflight.
Our first measurements on board the ISS confirmed increased tone and stiffness of the lumbar multifidus muscle, an important trunk stabilizer, dysfunction of which is known to be associated with back pain. Furthermore, reduced tone and stiffness of Achilles tendon and plantar fascia were observed inflight vs. preflight, confirming previous findings from terrestrial analog studies and parabolic
flights. Unexpectedly, the deltoid showed negative inflight changes in tone and stiffness, and increased elasticity, suggesting a potential risk of muscle atrophy in longer spaceflight that should be addressed by adequate inflight countermeasure protocols. Most values from limb and back MPS showed deflected patterns (in either directions) from inflight shortly after the re-entry phase on the landing day and one week later. Most parameter values then normalized to baseline after 3 weeks likely due to 1G re-adaptation and possible outcome of the reconditioning protocol. No major changes in subcutaneous tissues thickness above the MPs were found inflight vs preflight, suggesting no bias (i.e., fluid shift, extreme tissue thickening or loss). Pre- and postflight MRI and functional tests showed negligible changes in calf muscle size, power and force, which is likely due to training effects from current inflight exercise protocols.
The MYOTONES experiment is currently ongoing to collect data from further crew members. The potential impact of this research is to better understand the effects of microgravity and countermeasures over the time course of an ISS mission cycle. This will enable exercise countermeasures to be tailored
In modern bioanalytical methods, it is often desired to detect several targets in one sample within one measurement. Immunological methods including those that use superparamagnetic beads are an important group of techniques for these applications. The goal of this work is to investigate the feasibility of simultaneously detecting different superparamagnetic beads acting as markers using the magnetic frequency mixing technique. The frequency of the magnetic excitation field is scanned while the lower driving frequency is kept constant. Due to the particles’ nonlinear magnetization, mixing frequencies are generated. To record their amplitude and phase information, a direct digitization of the pickup-coil’s signal with subsequent Fast Fourier Transformation is performed. By synchronizing both magnetic beads using frequency scanning in magnetic frequency mixing technique magnetic fields, a stable phase information is gained. In this research, it is shown that the amplitude of the dominant mixing component is proportional to the amount of superparamagnetic beads inside a sample. Additionally, it is shown that the phase does not show this behaviour. Excitation frequency scans of different bead types were performed, showing different phases, without correlation to their diverse amplitudes. Two commercially available beads were selected and a determination of their amount in a mixture is performed as a demonstration for multiplex measurements.
The optical performance of a 2-axis solar concentrator was simulated with the COMSOL Multiphysics® software. The concentrator consists of a mirror array, which was created using the application builder. The mirror facets are preconfigured to form a focal point. During tracking all mirrors are moved simultaneously in a coupled mode by 2 motors in two axes, in order to keep the system in focus with the moving sun. Optical errors on each reflecting surface were implemented in combination with the solar angular cone of ± 4.65 mrad. As a result, the intercept factor of solar radiation that is available to the receiver was calculated as a function of the transversal and longitudinal angles of incidence. In addition, the intensity distribution on the receiver plane was calculated as a function of the incidence angles.
The paper industry is the industry with the third highest energy consumption in the European Union. Using recycled paper instead of fresh fibers for papermaking is less energy consuming and saves resources. However, adhesive contaminants in recycled paper are particularly problematic since they reduce the quality of the resulting paper-product. To remove as many contaminants and at the same time obtain as many valuable fibres as possible, fine screening systems, consisting of multiple interconnected pressure screens, are used. Choosing the best configuration is a non-trivial task: The screens can be interconnected in several ways, and suitable screen designs as well as operational parameters have to be selected. Additionally, one has to face conflicting objectives. In this paper, we present an approach for the multi-criteria optimization of pressure screen systems based on Mixed-Integer Nonlinear Programming. We specifically focus on a clear representation of the trade-off between different objectives.
Human induced pluripotent stem cells (hiPSCs) have shown to be promising in disease studies and drug screenings [1]. Cardiomyocytes derived from hiPSCs have been extensively investigated using patch-clamping and optical methods to compare their electromechanical behaviour relative to fully matured adult cells. Mathematical models can be used for translating findings on hiPSCCMs to adult cells [2] or to better understand the mechanisms of various ion channels when a drug is applied [3,4]. Paci et al. (2013) [3] developed the first model of hiPSC-CMs, which they later refined based on new data [3]. The model is based on iCells® (Fujifilm Cellular Dynamics, Inc. (FCDI), Madison WI, USA) but major differences among several cell lines and even within a single cell line have been found and motivate an approach for creating sample-specific models. We have developed an optimisation algorithm that parameterises the conductances (in S/F=Siemens/Farad) of the latest Paci et al. model (2018) [5] using current-voltage data obtained in individual patch-clamp experiments derived from an automated patch clamp system (Patchliner, Nanion Technologies GmbH, Munich).
MedicVR : Acceleration and Enhancement Techniques for Direct Volume Rendering in Virtual Reality
(2019)
The movement of magnetic beads due to a magnetic field gradient is of great interest in different application fields. In this report we present a technique based on a magnetic tweezers setup to measure the velocity factor of magnetically actuated individual superparamagnetic beads in a fluidic environment. Several beads can be tracked simultaneously in order to gain and improve statistics. Furthermore we show our results for different beads with hydrodynamic diameters between 200 and 1000 nm from diverse manufacturers. These measurement data can, for example, be used to determine design parameters for a magnetic separation system, like maximum flow rate and minimum separation time, or to select suitable beads for fixed experimental requirements.
Manufacturing Process Simulation for the Prediction of Tool-Part-Interaction and Ply Wrinkling
(2019)
In product development, numerous design decisions have to be made. Multi-domain virtual prototyping provides a variety of tools to assess technical feasibility of design options, however often requires substantial computational effort for just a single evaluation. A special challenge is therefore the optimal design of product families, which consist of a group of products derived from a common platform. Finding an optimal platform configuration (stating what is shared and what is individually designed for each product) and an optimal design of all products simultaneously leads to a mixed-integer nonlinear black-box optimization model. We present an optimization approach based on metamodels and a metaheuristic. To increase computational efficiency and solution quality, we compare different types of Gaussian process regression metamodels adapted from the domain of machine learning, and combine them with a genetic algorithm. We illustrate our approach on the example of a product family of electrical drives, and investigate the trade-off between solution quality and computational overhead.
In comparison to crude oil, biorefinery raw materials are challenging in concerns of transport and storage. The plant raw materials are more voluminous, so that shredding and compacting usually are necessary before transport. These mechanical processes can have a negative influence on the subsequent biotechnological processing and shelf life of the raw materials. Various approaches and their effects on renewable raw materials are shown. In addition, aspects of decentralized pretreatment steps are discussed. Another important aspect of pretreatment is the varying composition of the raw materials depending on the growth conditions. This problem can be solved with advanced on-site spectrometric analysis of the material.
Kyphoplasty of Osteoporotic Fractured Vertebrae: A Finite Element Analysis about Two Types of Cement
(2019)
Effective training requires high muscle forces potentially leading to training-induced injuries. Thus, continuous monitoring and controlling of the loadings applied to the musculoskeletal system along the motion trajectory is required. In this paper, a norm-optimal iterative learning control algorithm for the robot-assisted training is developed. The algorithm aims at minimizing the external knee joint moment, which is commonly used to quantify the loading of the medial compartment. To estimate the external knee joint moment, a musculoskeletal lower extremity model is implemented in OpenSim and coupled with a model of an industrial robot and a force plate mounted at its end-effector. The algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee. The results show that the algorithm is able to minimize the external knee joint moment in all three cases and converges after less than seven iterations.
Improved efficiency prediction of a molten salt receiver based on dynamic cloud passage simulation
(2019)
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through the presentation layer of existing application systems. For this simple emulation of user input and output by software robots, no changes of the systems and architecture is required. However, considering strategic aspects of aligning business and technology on an enterprise level as well as the growing capabilities of RPA driven by artificial intelligence, interrelations between RPA and Enterprise Architecture (EA) become visible and pose new questions. In this paper we discuss the relationship between RPA and EA in terms of perspectives and implications. As workin- progress we focus on identifying new questions and research opportunities related to RPA and EA.