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Loop Interactions and Dynamics Tune the Enzymatic Activity of the Human Histone Deacetylase 8
(2013)
Determination of regional lung function in cystic fibrosis using electrical impedance tomography
(2016)
Effects of physiotherapeutic breathing therapy on ventilation distribution in cystic fibrosis
(2018)
Impact of lung volume changes on perfusion estimates derived by Electrical Impedance Tomography
(2019)
Optimization of platinum adhesion in electrochemical etching process for multi-sensor systems
(2007)
Differences in respiratory mechanics estimation with respect to manoeuvres and mathematical models
(2017)
Transport mechanisms in nanostructured porous silicon layers for sensor and filter applications
(2012)
Mechanical investigation of perforated and porous membranes for micro- and nanofilter applications
(2007)
Cameras play a prominent role in the context of 3D data, as they can be designed to be very cheap and small and can therefore be used in many 3D reconstruction systems. Typical cameras capture video at 20 to 60 frames per second, resulting in a high number of frames to select from for 3D reconstruction. Many frames are unsuited for reconstruction as they suffer from motion blur or show too little variation compared to other frames. The camera used within this work has built-in inertial sensors. What if one could use the built-in inertial sensors to select a set of key frames well-suited for 3D reconstruction, free from motion blur and redundancy, in real time? A random forest classifier (RF) is trained by inertial data to determine frames without motion blur and to reduce redundancy. Frames are analyzed by the fast Fourier transformation and Lucas–Kanade method to detect motion blur and moving features in frames to label those correctly to train the RF. We achieve a classifier that omits successfully redundant frames and preserves frames with the required quality but exhibits an unsatisfied performance with respect to ideal frames. A 3D reconstruction by Meshroom shows a better result with selected key frames by the classifier. By extracting frames from video, one can comfortably scan objects and scenes without taking single pictures. Our proposed method automatically extracts the best frames in real time without using complex image-processing algorithms.
Feasibility of Parylene C for encapsulating piezoelectric actuators in active medical implants
(2023)
Parylene C is well-known as an encapsulation material for medical implants. Within the approach of miniaturization and automatization of a bone distractor, piezoelectric actuators were encapsulated with Parylene C. The stretchability of the polymer was investigated with respect to the encapsulation functionality of piezoelectric chips. We determined a linear yield strain of 1% of approximately 12-μm-thick Parylene C foil. Parylene C encapsulation withstands the mechanical stress of a minimum of 5×105 duty cycles by continuous actuation. The experiments demonstrate that elongation of the encapsulation on piezoelectric actuators and thus the elongation of Parylene C up to 0.8 mm are feasible.
Analysis of Microarray Data
(2012)