Funded OA publications

Distributed in-memory processing frameworks accelerate iterative workloads by caching suitable datasets in memory rather than recomputing them in each iteration. Selecting appropriate datasets to cache as well as allocating a suitable cluster configuration for caching these datasets play a crucial role in achieving optimal performance. In practice, both are tedious, time-consuming tasks and are often neglected by end users, who are typically not aware of workload semantics, sizes of intermediate data, and cluster specification. To address these problems, we present Juggler, an end-to-end framework, which autonomously selects appropriate datasets for caching and recommends a correspondingly suitable cluster configuration to end users, with the aim of achieving optimal execution time and cost. We evaluate Juggler on various iterative, real-world, machine learning applications. Compared with our baseline, Juggler reduces execution time to 25.1% and cost to 58.1%, on average, as a result of selecting suitable datasets for caching. It recommends optimal cluster configuration in 50% of cases and near-to-optimal configuration in the remaining cases. Moreover, Juggler achieves an average performance prediction accuracy of 90%.

Recent trends in 3D cell culturing has placed organotypic tissue models at another level. Now, not only is the microenvironment at the cynosure of this research, but rather, microscopic geometrical parameters are also decisive for mimicking a tissue model. Over the years, technologies such as micromachining, 3D printing, and hydrogels are making the foundation of this field. However, mimicking the topography of a particular tissue-relevant substrate can be achieved relatively simply with so-called template or morphology transfer techniques. Over the last 15 years, in one such research venture, we have been investigating a micro thermoforming technique as a facile tool for generating bioinspired topographies. We call them MatriGrid®s. In this research account, we summarize our learning outcome from this technique in terms of the influence of 3D micro morphologies on different cell cultures that we have tested in our laboratory. An integral part of this research is the evolution of unavoidable aspects such as possible label-free sensing and fluidic automatization. The development in the research field is also documented in this account.

Our long-term goal is the development of a wearable warning system that uses electrocutaneous stimulation. To find appropriate stimulation parameters and electrode configurations, we investigate perception amplitude thresholds and qualitative perceptions of electrocutaneous stimulation for varying pulse widths, electrode sizes, and electrode positions. The upper right arm was stimulated in 81 healthy volunteers with biphasic rectangular current pulses varying between 20 and 2000 μs. We determined perception, attention, and intolerance thresholds and the corresponding qualitative perceptions for 8 electrode pairs distributed around the upper arm. For a pulse width of 150 μs, we find median values of 3.5, 6.9, and 13.8 mA for perception, attention, and intolerance thresholds, respectively. All thresholds decrease with increasing pulse width. Lateral electrode positions have higher intolerance thresholds than medial electrode positions, but perception and attention threshold are not significantly different across electrode positions. Electrode size between 15 × 15 mm2 and 40 × 40 mm2 has no significant influence on the thresholds. Knocking is the prevailing perception for perception and attention thresholds while mostly muscle twitching, pinching, and stinging are reported at the intolerance threshold. Biphasic stimulation pulse widths between 150 μs and 250 μs are suitable for electric warning wearables. Within the given practical limits at the upper arm, electrode size, inter-electrode distance, and electrode position are flexible parameters of electric warning wearables. Our investigations provide the basis for electric warning wearables.

Binder- and conducting additive-free Si-O-C composite layers are deposited electrochemically under potentiostatic conditions from sulfolane-based organic electrolyte. Quartz crystal microbalance with damping monitoring is used for evaluation of the layer growth and its physical properties. The sodiation-desodiation performance of the material is afterward explored in Na-ion electrolyte. In terms of specific capacity, rate capability, and long-term electrochemical stability, the experiments confirm the advantages of applying the electrochemically formed Si-O-C structure as anode for Na-ion batteries. The material displays high (722 mAh g^-1) initial reversible capacity at j = 70 mA g^-1 and preserves stable long-term capacity of 540 mAh g^-1 for at least 400 galvanostatic cycles, measured at j = 150 mA g^-1. The observed high performance can be attributed to its improved mechanical stability and accelerated Na-ion transport in the porous anode structure. The origin of the material electroactivity is revealed based on X-Ray photoelectron spectroscopic analysis of pristine (as deposited), sodiated, and desodiated Si-O-C layers. The evaluation of the spectroscopic data indicates reversible activity of the material due to the complex contribution of carbon and silicon redox centers.

Real-time monitoring of bioanalytes in organotypic cell cultivation devices is a major research challenge in establishing stand-alone diagnostic systems. Presently, no general technical facility is available that offers a plug-in system for bioanalytics in diversely available organotypic culture models. Therefore, each analytical device has to be tuned according to the microfluidic and interface environment of the 3D in vitro system. Herein, we report the design and function of a 3D automated culture and analysis device (3D-ACAD) which actively perfuses a custom-made 3D microbioreactor, samples the culture medium and simultaneously performs capillary-based flow ELISA. A microstructured MatriGrid® has been explored as a 3D scaffold for culturing HepaRG cells, with albumin investigated as a bioanalytical marker using flow ELISA. We investigated the effect of acetaminophen (APAP) on the albumin secretion of HepaRG cells over 96 h and compared this with the albumin secretion of 2D monolayer HepaRG cultures. Automated on-line monitoring of albumin secretion in the 3D in vitro mode revealed that the application of hepatotoxic drug-like APAP results in decreased albumin secretion. Furthermore, a higher sensitivity of the HepaRG cell culture in the automated 3D-ACAD system to APAP was observed compared to HepaRG cells cultivated as a monolayer. The results support the use of the 3D-ACAD model as a stand-alone device, working in real time and capable of analyzing the condition of the cell culture by measuring a functional analyte. Information obtained from our system is compared with conventional cell culture and plate ELISA, the results of which are presented herein.