Biomedical and Health Sciences
This Free CAD files are for the manuscript "A temperature-controlled patch-clamp platform demonstrated on Jurkat T lymphocytes and human stem cell derived neurons". The files allow for easily 3D-printing a housing box for the electronics.
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The Voltammetry-Based Sensing (VBS) methods are extremely interesting due to high specificity in several biochemical applications. Several considerations can be applied to use this method to measure different analytes, and implement efficient and optimized electronic measurement platform for point-of-care diagnostic, in wearable, portable, or IoT systems. The dataset contains the data presented in [1], which proves on real experimental data a method to define the optimized setup to develop efficient and electronic bio-sensing platforms.
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A human-user study with ten healthy subjects provides this experimental setup. The experimental protocol consists in capturing kinematic data while subjects walk, with the donned H2 lower-limb exoskeleton, across seven experimental conditions: Subjects completed 7 trials each. There were 7 different trials, 3 with marks every 30, 45 and 60 cm on 3 separate 10 meter lanes.
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These videos show bottom and side views of the treatment by a He/O2 plasma jet of a solution containing ultra-pure water, potassium iodide and starch. As the plasma reaches the liquid, a purple filament characteristic of the triiodide ion/starch complex appears. This complex is formed by the reaction between iodide ion and a reactive oxygen and nitrogen species (RONS) such as ozone, hydrogen peroxide, hydroxide ion, nitric oxyde or nitrate. Therefore, the formation of these RONS in the liquid phase is temporally and spatially quantified.
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Evidence-based guidelines have been proved to exhibit a positive impact on the quality of the treatment process. However, their influence on patient care remains limited. For the success and effectiveness of clinical guidelines, a fast and clear provision of knowledge at the point of care for all treating physicians is essential. A uniform formal representation is developed so that the knowledge extracted from the patient data is consistently presented at the human-machine interface.
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This dataset include lncRNA-disease association and disease semantic similarity matrix
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