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Dielectrophoretic functionalization of nanoelectrode arrays for the detection of influenza viruses
(2017)
Structural health monitoring activities are of primal importance for managing transport infrastructure, however most SHM methodologies are based on point-based sensors that have limitations in terms of their spatial positioning requirements, cost of development and measurement range. This paper describes the progress on the SENSKIN EC project whose objective is to develop a dielectric-elastomer and micro-electronics-based sensor, formed from a large highly extensible capacitance sensing membrane supported by advanced microelectronic circuitry, for monitoring transport infrastructure bridges. Such a sensor could provide spatial measurements of strain in excess of 10%. The actual sensor along with the data acquisition module, the communication module and power electronics are all integrated into a compact unit, the SENSKIN device, which is energy-efficient, requires simple signal processing and it is easy to install over various surface types. In terms of communication, SENSKIN devices interact with each other to form the SENSKIN system; a fully distributed and autonomous wireless sensor network that is able to self-monitor. SENSKIN system utilizes Delay-/Disruption-Tolerant Networking technologies to ensure that the strain measurements will be received by the base station even under extreme conditions where normal communications are disrupted. This paper describes the architecture of the SENSKIN system and the development and testing of the first SENSKIN prototype sensor, the data acquisition system, and the communication system.
Preclinical assessment of penetration not only in intact, but also in barrier‐disrupted skin is important to explore the surplus value of novel drug delivery systems, which can be specifically designed for diseased skin. Here, we characterized physical and chemical barrier disruption protocols for short‐term ex vivo skin cultures with regard to structural integrity, physiological and biological parameters. Further, we compared the penetration of dexamethasone (Dex) in different nanoparticle‐based formulations in stratum corneum, epidermis and dermis extracts of intact vs. barrier‐disrupted skin as well as by dermal microdialysis at 6, 12 and 24 hours after topical application. Dex was quantified by liquid‐chromatography ‐ tandem‐mass spectrometry (LC‐MS/MS). Simultaneously, we investigated the Dex efficacy by interleukin (IL) analysis. Tape‐stripping (TS) and 4 hours sodium lauryl sulfate 5 % (SLS) exposure were identified as highly effective barrier disruption methods assessed by reproducible transepidermal water loss (TEWL) changes and IL‐6/8 increase which was more pronounced in SLS‐treated skin. The barrier state has also a significant impact on the Dex penetration kinetics: for all formulations, TS highly increased dermal Dex concentration despite the fact that nanocrystals quickly and effectively penetrated both, intact and barrier‐disrupted skin reaching significantly higher dermal Dex concentration after 6 hours compared to Dex cream. The surplus value of encapsulation in ethyl cellulose nanocarriers could mostly be observed when applied on intact skin, in general showing a delayed Dex penetration. Estimation of cytokines was limited due to the trauma caused by probe insertion. In summary, ex vivo human skin is a highly interesting short‐term preclinical model for the analysis of penetration and efficacy of novel drug delivery systems.
Embedded smart home
(2017)
The popularity of MOOCs has increased considerably in the last years. A typical MOOC course consists of video content, self tests after a video and homework, which is normally in multiple choice format. After solving this homeworks for every week of a MOOC, the final exam certificate can be issued when the student has reached a sufficient score. There are also some attempts to include practical tasks, such as programming, in MOOCs for grading. Nevertheless, until now there is no known possibility to teach embedded system programming in a MOOC course where the programming can be done in a remote lab and where grading of the tasks is additionally possible. This embedded programming includes communication over GPIO pins to control LEDs and measure sensor values. We started a MOOC course called "Embedded Smart Home" as a pilot to prove the concept to teach real hardware programming in a MOOC environment under real life MOOC conditions with over 6000 students. Furthermore, also students with real hardware have the possibility to program on their own real hardware and grade their results in the MOOC course. Finally, we evaluate our approach and analyze the student acceptance of this approach to offer a course on embedded programming. We also analyze the hardware usage and working time of students solving tasks to find out if real hardware programming is an advantage and motivating achievement to support students learning success.