Refine
Year of publication
Institute
- Fachbereich Medizintechnik und Technomathematik (1935)
- Fachbereich Elektrotechnik und Informationstechnik (1150)
- Fachbereich Wirtschaftswissenschaften (1121)
- Fachbereich Energietechnik (1067)
- Fachbereich Chemie und Biotechnologie (898)
- Fachbereich Maschinenbau und Mechatronik (809)
- Fachbereich Luft- und Raumfahrttechnik (769)
- Fachbereich Bauingenieurwesen (664)
- IfB - Institut für Bioengineering (627)
- INB - Institut für Nano- und Biotechnologien (587)
Has Fulltext
- no (9329) (remove)
Language
Document Type
- Article (5532)
- Conference Proceeding (1421)
- Book (1062)
- Part of a Book (567)
- Patent (177)
- Bachelor Thesis (169)
- Report (83)
- Doctoral Thesis (81)
- Conference: Meeting Abstract (75)
- Other (67)
Keywords
- Illustration (10)
- Nachhaltigkeit (10)
- Corporate Design (9)
- Erscheinungsbild (8)
- Gamification (8)
- Redesign (7)
- Animation (6)
- Datenschutz (6)
- Deutschland (6)
- Digitalisierung (6)
The msprop program presented in this work is capable of solving the Maxwell–Schrödinger equations for one or several laser fields propagating through a medium of quantum optical few-level systems in one spatial dimension and in time. In particular, it allows to numerically treat systems in which a laser field interacts with the medium with both its electric and magnetic component at the same time. The internal dynamics of the few-level system is modeled by a quantum optical master equation which includes coherent processes due to optical transitions driven by the laser fields as well as incoherent processes due to decay and dephasing. The propagation dynamics of the laser fields is treated in slowly varying envelope approximation resulting in a first order wave equation for each laser field envelope function. The program employs an Adams predictor formula second order in time to integrate the quantum optical master equation and a Lax–Wendroff scheme second order in space and time to evolve the wave equations for the fields. The source function in the Lax–Wendroff scheme is specifically adapted to allow taking into account the simultaneous coupling of a laser field to the polarization and the magnetization of the medium. To reduce execution time, a customized data structure is implemented and explained. In three examples the features of the program are demonstrated and the treatment of a system with a phase-dependent cross coupling of the electric and magnetic field component of a laser field is shown.
Results are presented on the ratios of the nucleon structure function in copper to deuterium from two separate experiments. The data confirm that the nucleon structure function,F 2, is different for bound nucleons than for the quasi-free ones in the deuteron. The redistribution in the fraction of the nucleon's momentum carried by quarks is investigated and it is found that the data are compatible with no integral loss of quark momenta due to nuclear effects.
The spin asymmetry in deep inelastic scattering of longitudinally polarised muons by longitudinally polarised protons has been measured over a large x range (0.01<x<0.7). The spin-dependent structure function g1(x) for the proton has been determined and its integral over x found to be 0.114±0.012±0.026, in disagreement with the Ellis-Jaffe sum rule. Assuming the validity of the Bjorken sum rule, this result implies a significant negative value for the integral of g1 for the neutron. These values for the integrals of g1 lead to the conclusion that the total quark spin constitutes a rather small fraction of the spin of the nucleon.
Purpose
To calculate local specific absorption rate (SAR) correctly, both the amplitude and phase of the signal in each transmit channel have to be known. In this work, we propose a method to derive a conservative upper bound for the local SAR, with a reasonable safety margin without knowledge of the transmit phases of the channels.
Methods
The proposed method uses virtual observation points (VOPs). Correction factors are calculated for each set of VOPs that prevent underestimation of local SAR when the VOPs are applied with the correct amplitudes but fixed phases.
Results
The proposed method proved to be superior to the worst-case calculation based on the maximum eigenvalue of the VOPs. The mean overestimation for six coil setups could be reduced, whereas no underestimation of the maximum local SAR occurred. In the best investigated case, the overestimation could be reduced from a factor of 3.3 to a factor of 1.7.
Conclusion
The upper bound for the local SAR calculated with the proposed method allows a fast estimation of the local SAR based on power measurements in the transmit channels and facilitates SAR monitoring in systems that do not have the capability to monitor transmit phases
A microscopic photometric method for measuring erythrocyte deformability. Artmann, Gerhard Michael
(1986)
Gearboxes are mechanical transmission systems that provide speed and torque conversions from a rotating power source. Being a central element of the drive train, they are relevant for the efficiency and durability of motor vehicles. In this work, we present a new approach for gearbox design: Modeling the design problem as a mixed-integer nonlinear program (MINLP) allows us to create gearbox designs from scratch for arbitrary requirements and—given enough time—to compute provably globally optimal designs for a given objective. We show how different degrees of freedom influence the runtime and present an exemplary solution.
Purpose
Two semi-empirical models were recently published, both making use of existing literature data, but each taking into account different physical phenomena that trigger hemolysis. In the first model, hemoglobin (Hb) release is described as a permeation procedure across the membrane, assuming a shear stress-dependent process (sublethal model). The second model only accounts for hemoglobin release that is caused by cell membrane breakdown, which occurs when red blood cells (RBC) undergo mechanically induced shearing for a period longer than the threshold time (nonuniform threshold model). In this paper, we introduce a model that considers the hemolysis generated by both these possible phenomena.
Methods
Since hemolysis can possibly be caused by permeation of hemoglobin through the RBC functional membrane as well as by release of hemoglobin from RBC membrane breakdown, our proposed model combines both these models. An experimental setup consisting of a Couette device was utilized for validation of our proposed model.
Results
A comparison is presented between the damage index (DI) predicted by the proposed model vs. the sublethal model vs. the nonthreshold model and experimental datasets. This comparison covers a wide range of shear stress for both human and porcine blood. An appropriate agreement between the measured DI and the DI predicted by the present model was obtained.
Conclusions
The semiempirical hemolysis model introduced in this paper aims for significantly enhanced conformity with experimental data. Two phenomenological outcomes become possible with the proposed approach: an estimation of the average time after which cell membrane breakdown occurs under the applied conditions, and a prediction of the ratio between the phenomena involved in hemolysis.
A New Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier
(2016)
There are different types of games that try to make use of the motivation of a gaming situation in learning contexts. This paper introduces the new terminology ‘Competence Developing Game’ (CDG) as an umbrella term for all games with this intention. Based on this new terminology, an assessment framework has been developed and validated in scope of an empirical study. Now, all different types of CDGs can be evaluated according to a defined and uniform set of assessment criteria and, thus, are comparable according to their characteristics and effectiveness.
A new in vitro tool to investigate cardiac contractility under physiological mechanical conditions
(2019)
A new solar desalination system with heat recovery for decentralised drinking water production
(2009)
The integration of sensors is one of the major tasks in embedded, control and “internet of things” (IoT) applications. For the integration mainly digital interfaces are used, starting from rather simple pulse-width modulation (PWM) interface to more complex interfaces like CAN (Controller Area Network). Even though these interfaces are tethered by definition, a wireless realization is highly welcome in many applications to reduce cable and connector cost, increase the flexibility and realize new emerging applications like wireless control systems. Currently used wireless solutions like Bluetooth, WirelessHART or IO-Link Wireless use dedicated communication standards and corresponding higher protocol layers to realize the wireless communication. Due to the complexity of the communication and the protocol handling, additional latency and jitter are introduced to the data communication that can meet the requirements for many applications. Even though tunnelling of other bus data like CAN data is generally also possible the latency and jitter prevent the tunnelling from being transparent for the bus system. Therefore a new basic technology based on dual-mode radio is used to realize a wireless communication on the physical layer only, enabling a reliable and real-time data transfer. As this system operates on the physical layer it is independent of any higher layers of the OSI (open systems interconnection) model. Hence it can be used for several different communication systems to replace the tethered physical layer. A prototype is developed and tested for real-time wireless PWM, SENT (single-edge nibble transmission) and CAN data transfer with very low latency and jitter.
In order for traditional masonry to stay a competitive building material in seismically active regions there is an urgent demand for modern, deformation-based verification procedures which exploit the nonlinear load bearing reserves. The Capacity Spectrum Method (CSM) is a widely accepted design approach in the field of reinforced concrete and steel construction. It compares the seismic action with the load-bearing capacity of the building considering nonlinear material behavior with its post-peak capacity. The bearing capacity of the building is calculated iteratively using single wall capacity curves. This paper presents a new approach for the bilinear approximation of single wall capacity curves in the style of EC6/EC8 respectively FEMA 306/FEMA 356 based on recent shear wall test results of the European Collective-Research Project “ESECMaSE”. The application of the CSM to masonry structures by using bilinear approximations of capacity curves as input is demonstrated on the example of a typical German residential home.
We present a new Min-Max theorem for an optimization problem closely connected to matchings and vertex covers in balanced hypergraphs. The result generalizes Kőnig’s Theorem (Berge and Las Vergnas in Ann N Y Acad Sci 175:32–40, 1970; Fulkerson et al. in Math Progr Study 1:120–132, 1974) and Hall’s Theorem (Conforti et al. in Combinatorica 16:325–329, 1996) for balanced hypergraphs.
To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.
To meet the challenges of manufacturing smart products, the manufacturing plants have been radically changed to become smart factories underpinned by industry 4.0 technologies. The transformation is assisted by employment of machine learning techniques that can deal with modeling both big or limited data. This manuscript reviews these concepts and present a case study that demonstrates the use of a novel intelligent hybrid algorithms for Industry 4.0 applications with limited data. In particular, an intelligent algorithm is proposed for robust data modeling of nonlinear systems based on input-output data. In our approach, a novel hybrid data-driven combining the Group-Method of Data-Handling and Singular-Value Decomposition is adapted to find an offline deterministic model combined with Pareto multi-objective optimization to overcome the overfitting issue. An Unscented-Kalman-Filter is also incorporated to update the coefficient of the deterministic model and increase its robustness against data uncertainties. The effectiveness of the proposed method is examined on a set of real industrial measurements.