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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.
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 novel solar sterilization and water destillation system : experiment and thermodynamic analysis
(1991)
A novel scheme for precise diagnostics and effective stabilization of currents in a fuel cell stack
(2010)
BACKGROUND
Currently, several techniques exist for the downstream processing of protein, phytic acid and sinapic acid from rapeseed and rapeseed meal, but no technique has been developed to separate all of the components in one process. In this work, two new downstream processing strategies focusing on recovering sinapic acid, phytic acid and protein from rapeseed meal were established.
RESULTS
The sinapic acid content was enhanced by a factor of 4.5 with one method and 5.1 with the other. The isolation of sinapic acid was accomplished using a zeolite-based adsorbent with high adsorptive and optimal desorption characteristics. Phytic acid was isolated using the anion-exchange resin Purolite A200®. In addition, the processes resulted in two separated protein fractions. The ratios of globulin and albumin ratio to the total protein were 59.2% and 40.1%, respectively. The steps were then combined in two different ways: (a) a ‘sequential process’ using the zeolite and A200 in batch processes; and (b) a ‘parallel process’ using only A200 in a chromatographic system to separate all of the compounds.
CONCLUSIONS
It can be concluded that isolation of all three components was possible in both processes. These could enhance the added value of current processes using rapeseed meal as a protein source. © 2015 Society of Chemical Industry
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.
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.
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.
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.
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.
A new solar desalination system with heat recovery for decentralised drinking water production
(2009)
The determination of spacing, edge and end distance requirements for self-tapping screws requires numerous and comprehensive insertion tests. Yet the results of such tests cannot be transferred to other types of screws or even to screws of different diameter because of differences in shape or geometry. To reduce the effort of insertion tests a new method was developed which allows the estimation of required spacings, distances and timber thickness.
A new in vitro tool to investigate cardiac contractility under physiological mechanical conditions
(2019)
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 Class of Biosensors Based on Tobacco Mosaic Virus and Coat Proteins as Enzyme Nanocarrier
(2016)
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.