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The flow field-flow fractionation (FIFFF) technique is a promising method for separating and analysing particles and large size macromolecules from a few nanometers to approximately 50 μm. A new fractionation channel is described featuring well defined flow conditions even for low channel heights with convenient assembling and operations features. The application of the new flow field-flow fractionation channel is proved by the analysis of pigments and other small particles of technical interest in the submicrometer range. The experimental results including multimodal size distributions are presented and discussed.
A wide range catalyst screening with noble metal and oxide catalysts for a metal–air battery with an aqueous alkaline electrolyte was carried out. Suitable catalysts reduce overpotentials during the charge and discharge process, and therefore improve the round-trip efficiency of the battery. In this case, the electrodes will be used as optimized cathodes for a future lithium–air battery with an aqueous alkaline electrolyte. Oxide catalysts were synthesized via atmospheric plasma spraying. The screening showed that IrO2, RuO2, La0.6Ca0.4Co3, Mn3O4, and Co3O4 are promising bi-functional catalysts. Considering the high price for the noble metal catalysts further investigations of the oxide catalysts were carried out to analyze their electrochemical behavior at varied temperatures, molarities, and in case of La1−x Ca x CoO3 a varying calcium content. Additionally all catalysts were tested in a longterm test to proof cyclability at varied molarities. Further investigations showed that Co3O4 seems to be the most promising bi-functional catalyst of the tested oxide catalysts. Furthermore, it was shown that a calcium content of x = 0.4 in LCCO has the best performance.
We present a two-dimensional (2D) planar chromatographic separation of estrogenic active compounds on RP-18 W (Merck, 1.14296) phase. A mixture of 8 substances was separated using a solvent mix consisting of hexane, ethyl acetate, acetone (55:15:10, v/v) in the first direction and of acetone and water (15:10, v/v) in the second direction. Separation was performed on an RP-18 W plate over a distance of 70 mm. This 2D-separation method can be used to quantify 17α-ethinylestradiol (EE2) in an effect-directed analysis, using the yeast strain Saccharomyces cerevisiae BJ3505. The test strain (according to McDonnell) contains the estrogen receptor. Its activation by estrogen active compounds is measured by inducing the reporter gene lacZ which encodes the enzyme β-galactosidase. This enzyme activity is determined on plate by using the fluorescent substrate MUG (4-methylumbelliferyl-β-d-galactopyranoside).
Serendipities in der Medizin
(2016)
Zufälle begleiten unser Leben. Auch bei wichtigen Entdeckungen und Entwicklungen in der Medizin spielt der „Zufall“ (engl. „serendipity“) eine Rolle. Hierzu gehören u. a. die Mendelschen Gesetze, die Ermittlung der menschlichen Chromosomenzahl, die Entdeckung der DNS durch Watson und Crick, der PAP-Test oder die Entdeckung der Röntgenstrahlung und der Radioaktivität. Aber auch und gerade in der Pharmakologie gibt es viele Beispiele für Serendipitäten. Einige gehen eng mit Zufällen bei der Entdeckung der Bakteriologie einher.
The authors claim that location information of stationary ICT components can never be unclassified. They describe how swarm-mapping crowd sourcing is used by Apple and Google to worldwide harvest geo-location information on wireless access points and mobile telecommunication systems' base stations to build up gigantic databases with very exclusive access rights. After having highlighted the known technical facts, in the speculative part of this article, the authors argue how this may impact cyber deterrence strategies of states and alliances understanding the cyberspace as another domain of geostrategic relevance. The states and alliances spectrum of activities due to the potential existence of such databases may range from geopolitical negotiations by institutions understanding international affairs as their core business, mitigation approaches at a technical level, over means of cyber deterrence-by-retaliation.
The interaural time difference (ITD) is an important cue for the localization of sounds. ITD changes as little as 10 μs can be detected by the human auditory system. By provision of one ear with a cochlear implant (CI) ITD are altered due to the partial replacement of the peripheral auditory system. A hearing aid (HA), in contrast, does not replace but adds a processing delay component to the peripheral auditory system extending ITD. The aim of the present study was to quantify interaural stimulation timing between these different modalities to estimate the need for central auditory temporal compensation in single sided deaf CI users or bimodal CI/HA users. For this purpose, wave V latencies of auditory brainstem responses evoked either acoustically (ABR) or electrically via the CI (EABR) have been measured. The sum of delays consisting of CI signal processing measured in the MED-EL OPUS2 audio processor and EABR wave V latencies evoked on different intracochlear sites allowed an estimation of the entire CI channel-specific delay for MED-EL MAESTRO CI systems. We compared these values with ABR wave V latencies measured in the contralateral normal hearing or HA provided ear in different frequency bands. The results showed that EABR wave V latencies were consistently shorter than those evoked acoustically in the unaided normal hearing ear. Thus, artificial delays within the audio processor can be implemented to adjust interaural stimulation timing. The currently implemented group delays in the MED-EL CI system turned out to be reasonably similar to those of the unaided ear. For adjustment of CI and contralateral HA, in contrast, an adjustable additional across-frequency delay in the range of 1–11 ms implemented in the CI would be required. Especially for bimodal CI/HA users the adjustment of interaural stimulation timing may induce improved binaural hearing, reduced need for central auditory temporal compensation and increased acceptance of the CI/HA provision.
Time-of-Flight Cameras Enabling Collaborative Robots for Improved Safety in Medical Applications
(2017)
Human-robot collaboration is being used more and more in industry applications and is finding its way into medical applications. Industrial robots that are used for human-robot collaboration, cannot detect obstacles from a distance. This paper introduced the idea of using wireless technology to connect a Time-of-Flight camera to off-the-shelf industrial robots. This way, the robot can detect obstacles up to a distance of five meters. Connecting Time-of-Flight cameras to robots increases the safety in human-robot collaboration by detecting obstacles before a collision. After looking at the state of the art, the authors elaborated the different requirements for such a system. The Time-of-Flight camera from Heptagon is able to work in a range of up to five meters and can connect to the control unit of the robot via a wireless connection.
In many application domains, in particular automotives, guaranteeing a very low failure rate is crucial to meet functional and safety standards. Especially, reliable operation of memory components such as SRAM cells is of essential importance. Due to aggressive technology downscaling, process and runtime variations significantly impact manufacturing yield as well as functionality. For this reason, a thorough memory failure rate assessment is imperative for correct circuit operation and yield improvement. In this regard, Monte Carlo simulations have been used as the conventional method to estimate the variability induced failure rate of memory components. However, Monte Carlo methods become infeasible when estimating rare events such as high-sigma failure rates. To this end, Importance Sampling methods have been proposed which reduce the number of required simulations substantially. However, existing methods still suffer from inaccuracies and high computational efforts, in particular for high-sigma problems. In this paper, we fill this gap by presenting an efficient mixture Importance Sampling approach based on Bayesian optimization, which deploys a surface model of the objective function to find the most probable failure points. Its advantages include constant complexity independent of the dimensions of design space, the potential to find the global extrema, and higher trustworthiness of the estimated failure rate by accurately exploring the design space. The approach is evaluated on a 6T-SRAM cell as well as a master-slave latch based on a 28nm FDSOI process. The results show an improvement in accuracy, resulting in up to 63× better accuracy in estimating failure rates compared to the best state-of-the-art solutions on a 28nm technology node.
Battery degradation is a complex physicochemical process that strongly depends on operating conditions. We present a model-based analysis of lithium-ion battery degradation in a stationary photovoltaic battery system. We use a multi-scale multi-physics model of a graphite/lithium iron phosphate (LiFePO4, LFP) cell including solid electrolyte interphase (SEI) formation. The cell-level model is dynamically coupled to a system-level model consisting of photovoltaics (PV), inverter, load, grid interaction, and energy management system, fed with historic weather data. Simulations are carried out for two load scenarios, a single-family house and an office tract, over annual operation cycles with one-minute time resolution. As key result, we show that the charging process causes a peak in degradation rate due to electrochemical charge overpotentials. The main drivers for cell ageing are therefore not only a high state of charge (SOC), but the charging process leading towards high SOC. We also show that the load situation not only influences system parameters like self-sufficiency and self-consumption, but also has a significant impact on battery ageing. We assess reduced charge cut-off voltage as ageing mitigation strategy.