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A New Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier
(2016)
A new in vitro tool to investigate cardiac contractility under physiological mechanical conditions
(2019)
Advances in polymer science have significantly increased polymer applications in life sciences. We report the use of free-standing, ultra-thin polydimethylsiloxane (PDMS) membranes, called CellDrum, as cell culture substrates for an in vitro wound model. Dermal fibroblast monolayers from 28- and 88-year-old donors were cultured on CellDrums. By using stainless steel balls, circular cell-free areas were created in the cell layer (wounding). Sinusoidal strain of 1 Hz, 5% strain, was applied to membranes for 30 min in 4 sessions. The gap circumference and closure rate of un-stretched samples (controls) and stretched samples were monitored over 4 days to investigate the effects of donor age and mechanical strain on wound closure. A significant decrease in gap circumference and an increase in gap closure rate were observed in trained samples from younger donors and control samples from older donors. In contrast, a significant decrease in gap closure rate and an increase in wound circumference were observed in the trained samples from older donors. Through these results, we propose the model of a cell monolayer on stretchable CellDrums as a practical tool for wound healing research. The combination of biomechanical cell loading in conjunction with analyses such as gene/protein expression seems promising beyond the scope published here.
A novel scheme for precise diagnostics and effective stabilization of currents in a fuel cell stack
(2010)
A novel scheme for detecting inhomogeneous internal currents in a fuel cell stack is presented. In this paper the scheme is investigated for the case that the flow field plates consist of graphite. Then plates of high conductivity, e.g. aluminium between the flow field plates together with small slits in these plates have three effects: (a) Whenever a local inhomogeneity of the electric current occurs at a particular cell in the stack, this will induce a surface current close to that cell perpendicular to the averaged current. This current can be detected. (b) The plates of high conductivity completely prevent the inhomogeneities from spreading to neighbouring cells. (c) Even at the particular cell the inhomogeneity is suppressed as far as possible. Thus this scheme leads to much better diagnostic possibilities and at the same time reduces electric instabilities to an extent, where they probably become harmless. This scheme will first be explained for a simple model to clarify the idea. However, very precise three dimensional computations using realistic parameters are presented, corroborating the results of the simple model.
Within the developments for the Crystal Clear small animal PET project (CLEARPET) a dual head PET system has been established. The basic principle is the early digitization of the detector pulses by free running ADCs. The determination of the γ-energy and also the coincidence detection is performed by data processing of the sampled pulses on the host computer. Therefore a time mark is attached to each pulse identifying the current cycle of the 40 MHz sampling clock. In order to refine the time resolution the pulse starting time is interpolated from the samples of the pulse rise. The detector heads consist of multichannel PMTs with a single LSO scintillator crystal coupled to each channel. For each PMT only one ADC is required. The position of an event is obtained separately from trigger signals generated for each single channel. An FPGA is utilized for pulse buffering, generation of the time mark and for the data transfer to the host via a fast I/O-interface.
A small PET system has been built up with two multichannel photomultipliers, which are attached to a matrix of 64 single LSO crystals each. The signal from each multiplier is being sampled continuously by a 12 bit ADC at a sampling frequency of 40 MHz. In case of a scintillation pulse a subsequent FPGA sends the corresponding set of samples together with the channel information and a time mark to the host computer. The data transfer is performed with a rate of 20 MB/s. On the host all necessary information is extracted from the data. The pulse energy is determined, coincident events are detected and multiple hits within one matrix can be identified. In order to achieve a narrow time window the pulse starting time is refined further than the resolution of the time mark (=25 ns) would allow. This is possible by interpolating between the pulse samples. First data obtained from this system will be presented. The system is part of developments for a much larger system and has been created to study the feasibility and performance of the technique and the hardware architecture.
A second-order L-stable exponential time-differencing (ETD) method is developed by combining an ETD scheme with approximating the matrix exponentials by rational functions having real distinct poles (RDP), together with a dimensional splitting integrating factor technique. A variety of non-linear reaction-diffusion equations in two and three dimensions with either Dirichlet, Neumann, or periodic boundary conditions are solved with this scheme and shown to outperform a variety of other second-order implicit-explicit schemes. An additional performance boost is gained through further use of basic parallelization techniques.
We consider the numerical approximation of second-order semi-linear parabolic stochastic partial differential equations interpreted in the mild sense which we solve on general two-dimensional domains with a C² boundary with homogeneous Dirichlet boundary conditions. The equations are driven by Gaussian additive noise, and several Lipschitz-like conditions are imposed on the nonlinear function. We discretize in space with a spectral Galerkin method and in time using an explicit Euler-like scheme. For irregular shapes, the necessary Dirichlet eigenvalues and eigenfunctions are obtained from a boundary integral equation method. This yields a nonlinear eigenvalue problem, which is discretized using a boundary element collocation method and is solved with the Beyn contour integral algorithm. We present an error analysis as well as numerical results on an exemplary asymmetric shape, and point out limitations of the approach.
An increasing number of applications target their executions on specific hardware like general purpose Graphics Processing Units. Some Cloud Computing providers offer this specific hardware so that organizations can rent such resources. However, outsourcing the whole application to the Cloud causes avoidable costs if only some parts of the application benefit from the specific expensive hardware. A partial execution of applications in the Cloud is a tradeoff between costs and efficiency. This paper addresses the demand for a consistent framework that allows for a mixture of on- and off-premise calculations by migrating only specific parts to a Cloud. It uses the concept of workflows to present how individual workflow tasks can be migrated to the Cloud whereas the remaining tasks are executed on-premise.
To prevent the reduction of muscle mass and loss of strength coming along with the human aging process, regular training with e.g. a leg press is suitable. However, the risk of training-induced injuries requires the continuous monitoring and controlling of the forces applied to the musculoskeletal system as well as the velocity along the motion trajectory and the range of motion. In this paper, an adaptive norm-optimal iterative learning control algorithm to minimize the knee joint loadings during the leg extension training with an industrial robot is proposed. The response of the algorithm is tested in simulation for patients with varus, normal and valgus alignment of the knee and compared to the results of a higher-order iterative learning control algorithm, a robust iterative learning control and a recently proposed conventional norm-optimal iterative learning control algorithm. Although significant improvements in performance are made compared to the conventional norm-optimal iterative learning control algorithm with a small learning factor, for the developed approach as well as the robust iterative learning control algorithm small steady state errors occur.
The esophageal Doppler monitor (EDM) is a minimally-invasive hemodynamic device which evaluates both cardiac output (CO), and fluid status, by estimating stroke volume (SV) and calculating heart rate (HR). The measurement of these parameters is based upon a continuous and accurate approximation of distal thoracic aortic blood flow. Furthermore, the peak velocity (PV) and mean acceleration (MA), of aortic blood flow at this anatomic location, are also determined by the EDM. The purpose of this preliminary report is to examine additional clinical hemodynamic calculations of: compliance (C), kinetic energy (KE), force (F), and afterload (TSVRi). These data were derived using both velocity-based measurements, provided by the EDM, as well as other contemporaneous physiologic parameters. Data were obtained from anesthetized patients undergoing surgery or who were in a critical care unit. A graphical inspection of these measurements is presented and discussed with respect to each patient’s clinical situation. When normalized to each of their initial values, F and KE both consistently demonstrated more discriminative power than either PV or MA. The EDM offers additional applications for hemodynamic monitoring. Further research regarding the accuracy, utility, and limitations of these parameters is therefore indicated.
Neuromuscular strength training of the leg extensor muscles plays an important role in the rehabilitation and prevention of age and wealth related diseases. In this paper, we focus on the design and implementation of a Cartesian admittance control scheme for isotonic training, i.e. leg extension and flexion against a predefined weight. For preliminary testing and validation of the designed algorithm an experimental research and development platform consisting of an
industrial robot and a force plate mounted at its end-effector has been used. Linear, diagonal and arbitrary two-dimensional motion trajectories with different weights for the leg extension and flexion part are applied. The proposed algorithm is easily adaptable to trajectories consisting of arbitrary six-dimensional poses and allows the implementation of individualized trajectories.
The scope of this study is the measurement of endotoxin adsorption rate for carbonized rice husk. It showed good adsorption properties for LPS. During the batch experiments, several techniques were used and optimized for improving the material’s adsorption behavior. Also, with the results obtained it was possible to differentiate the materials according to their adsorption capacity and kinetic characteristics.