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Evaluation of fragility curves for a three-storey-reinforced-concrete mock-up of SMART 2013 project
(2016)
Based on an identifying Volterra type integral equation for randomly right censored observations from a lifetime distribution function F, we solve the corresponding estimating equation by an explicit and implicit Euler scheme. While the first approach results in some known estimators, the second one produces new semi-parametric and pre-smoothed Kaplan–Meier estimators which are real distribution functions rather than sub-distribution functions as the former ones are. This property of the new estimators is particular useful if one wants to estimate the expected lifetime restricted to the support of the observation time.
Specifically, we focus on estimation under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring indicator given the observation belongs to a parametric family. We show that some estimated linear functionals which are based on the new semi-parametric estimator are strong consistent, asymptotically normal, and efficient under SRCM. In a small simulation study, the performance of the new estimator is illustrated under moderate sample sizes. Finally, we apply the new estimator to a well-known real dataset.
We present an electromechanically coupled computational model for the investigation of a thin cardiac tissue construct consisting of human-induced pluripotent stem cell-derived atrial, ventricular and sinoatrial cardiomyocytes. The mechanical and electrophysiological parts of the finite element model, as well as their coupling are explained in detail. The model is implemented in the open source finite element code Code_Aster and is employed for the simulation of a thin circular membrane deflected by a monolayer of autonomously beating, circular, thin cardiac tissue. Two cardio-active drugs, S-Bay K8644 and veratridine, are applied in experiments and simulations and are investigated with respect to their chronotropic effects on the tissue. These results demonstrate the potential of coupled micro- and macroscopic electromechanical models of cardiac tissue to be adapted to experimental results at the cellular level. Further model improvements are discussed taking into account experimentally measurable quantities that can easily be extracted from the obtained experimental results. The goal is to estimate the potential to adapt the presented model to sample specific cell cultures.
Background/Aims: Common systems for the quantification of cellular contraction rely on animal-based models, complex experimental setups or indirect approaches. The herein presented CellDrum technology for testing mechanical tension of cellular monolayers and thin tissue constructs has the potential to scale-up mechanical testing towards medium-throughput analyses. Using hiPS-Cardiac Myocytes (hiPS-CMs) it represents a new perspective of drug testing and brings us closer to personalized drug medication. Methods: In the present study, monolayers of self-beating hiPS-CMs were grown on ultra-thin circular silicone membranes and deflect under the weight of the culture medium. Rhythmic contractions of the hiPS-CMs induced variations of the membrane deflection. The recorded contraction-relaxation-cycles were analyzed with respect to their amplitudes, durations, time integrals and frequencies. Besides unstimulated force and tensile stress, we investigated the effects of agonists and antagonists acting on Ca²⁺ channels (S-Bay K8644/verapamil) and Na⁺ channels (veratridine/lidocaine). Results: The measured data and simulations for pharmacologically unstimulated contraction resembled findings in native human heart tissue, while the pharmacological dose-response curves were highly accurate and consistent with reference data. Conclusion: We conclude that the combination of the CellDrum with hiPS-CMs offers a fast, facile and precise system for pharmacological, toxicological studies and offers new preclinical basic research potential.
Operational Modal Analysis (OMA) is a promising candidate for flutter testing and Structural Health Monitoring (SHM) of aircraft wings that are passively excited by wind loads. However, no studies have been published where OMA is tested in transonic flows, which is the dominant condition for large civil aircraft and is characterized by complex and unique aerodynamic phenomena. We use data from the HIRENASD large-scale wind tunnel experiment to automatically extract modal parameters from an ambiently excited wing operated in the transonic regime using two OMA methods: Stochastic Subspace Identification (SSI) and Frequency Domain Decomposition (FDD). The system response is evaluated based on accelerometer measurements. The excitation is investigated from surface pressure measurements. The forcing function is shown to be non-white, non-stationary and contaminated by narrow-banded transonic disturbances. All these properties violate fundamental OMA assumptions about the forcing function. Despite this, all physical modes in the investigated frequency range were successfully identified, and in addition transonic pressure waves were identified as physical modes as well. The SSI method showed superior identification capabilities for the investigated case. The investigation shows that complex transonic flows can interfere with OMA. This can make existing approaches for modal tracking unsuitable for their application to aircraft wings operated in the transonic flight regime. Approaches to separate the true physical modes from the transonic disturbances are discussed.
Bonding of polymer-based microfluidics to polymer substrates still poses a challenge for Lab-On-a-Chip applications. Especially, when sensing elements are incorporated, patterned deposition of adhesives with curing at ambient conditions is required. Here, we demonstrate a fabrication method for fully printed microfluidic systems with sensing elements using inkjet and stereolithographic 3D-printing.
In this study, we show that synthetic sapphire (Al₂O₃), an established implant material, can also serve as a platform material for biosensors comparable to nanocrystalline diamond. Sapphire chips, beads, and powder were first modified with (3-aminopropyl) triethoxysilane (APTES), followed by succinic anhydride (SA), and finally single-stranded probe DNA was EDC coupled to the functionalized layer. The presence of the APTES-SA layer on sapphire powders was confirmed by thermogravimetric analyis and Fourier-transform infrared spectroscopy. Using planar sapphire chips as substrates and X-ray photoelectron spectroscopy (XPS) as surface-sensitive tool, the sequence of individual layers was analyzed with respect to their chemical state, enabling the quantification of areal densities of the involved molecular units. Fluorescence microscopy was used to demonstrate the hybridization of fluorescently tagged target DNA to the probe DNA, including denaturation- and re-hybridization experiments. Due to its high thermal conductivity, synthetic sapphire is especially suitable as a chip material for the heat-transfer method, which was employed to distinguish complementary- and non-complementary DNA duplexes containing single-nucleotide polymorphisms. These results indicate that it is possible to detect mutations electronically with a chemically resilient and electrically insulating chip material.