Rationale During each beat, cardiac myocytes generate the mechanical output necessary for heart function through contractile mechanisms that involve shortening of sarcomeres along myofibrils. Human induced pluripotent stem cells can be differentiated into cardiac myocytes that model cardiac contractile mechanical output more robustly when micropatterned into physiological shapes. Quantifying the mechanical output of these cells enables us to assay cardiac activity in a dish. Objective We sought to develop a computational platform that integrates analytical approaches to quantify the mechanical output of single micropatterned cardiac myocytes from microscopy videos. Methods and Results We micropatterned single cardiac myocytes differentiated from human induced pluripotent stem cells on deformable polyacrylamide substrates containing fluorescent microbeads. We acquired videos of single beating cells, of microbead displacement during contractions, and of fluorescently labeled myofibrils. These videos were independently analyzed to obtain parameters that capture the mechanical output of the imaged single cells. We also developed novel methods to quantify sarcomere length from videos of moving myofibrils and to analyze loss of synchronicity of beating in cells with contractile defects. We tested this computational platform by detecting variations in mechanical output induced by drugs and in cells expressing low levels of myosin binding protein C. Conclusions Our method can measure cardiac function in cardiac myocytes differentiated from induced pluripotent stem cells and determine contractile parameters that can be used to elucidate the mechanisms that underlie variations in cardiac myocyte function. This platform will be amenable to future studies of the effects of mutations and drugs on cardiac function.

We investigate how the combination of numerical simulation tools and optimization routines can be used to design micro-devices. Experimental devices that are designed in this way can only provide optimal performance if the simulation model, used in the optimization procedure, reflects the real device characteristics accurately. Owing to this fact, the modeling of acoustofluidic devices is summarized. The mathematical formulation of the optimization problem, the parameterization of the device design and the implementation of the optimization loop is addressed alongside with practical recommendations for the chosen genetic algorithm optimization. In order to validate the implementation, an optimized planar resonator is compared with the optimal geometry given in the literature. The optimization of a typical 3D micro-device shows that devices can be designed to generate any desired acoustic mode shape at maximum pressure amplitude. The presented automatic design approach is of great practical relevance for the development of highly optimized micro-devices and it can speed up and facilitate the design-process in the growing field of acoustofluidics.

In the absence of position data such as radar data, aircraft noise calculations usually rely on the definition of flight geometries in terms of flight track and flight profile data. Typically, the ground track is constructed as a backbone track with a number of subtracks accounting for the lateral flight dispersion. Depending on the nature of the tracks, for instance when considering diverging tracks compared to very narrow tracks, the number of subtracks needs to be such that smooth noise contours and footprints are computed, putting a requirement on the minimum number of subtracks needed. In practice however, as the tracks need to be digitized by expert hand, the number of available subtracks is often limited. Furthermore, the location of the subtracks is often unknown, requiring corridor boundaries to be estimated and to be translated into subtrack locations.<br/> This paper presents a method for the construction of the required number of subtracks based on an estimate of lateral flight dispersion. Two cases are envisioned: the first being an estimate of the lateral flight dispersion using a set of three pre-existing subtracks (one backbone track and left/right subtracks), the second being an estimate using a backbone track and corridor boundaries. The method uses geometric matching of the original tracks, followed by an estimation of the local lateral track dispersion. The lateral distribution function is then used for the construction of new subtracks. A series of aircraft noise calculations using diff erent numbers of subtracks are shown, showcasing the influence of the number of subtracks on the noise contours, depending on the nature of the tracks (e.g.situations with tight turns).

Recent aircraft noise calculation methods separate engine and airframe noise components to provide accurate single-flight noise predictions. General noise mapping, such as legal compliance calculations, usually relies on position data as the only available input. Therefore, more advanced input variables of engine and airframe noise models require estimation based on position data. We present a methodology to estimate aircraft's configuration and engine rotational speed for jet airliners from position data. The problem is split into a statistical evaluation of the aircraft's configuration, and a flight phase specific modelling of engine rotational speed. The modelling is validated using flight data recorder data, both as relative deviations of the estimation with respect to the reference and in terms of its acoustic impact on noise contours. The latter gave receiver level deviations of less than 0.2 dB for 85% and of less than 0.6 dB for 95% of the areas affected by departures, as well as of less than 1 dB for 95% of the areas affected by approaches. Major differences (above 0.6 dB) mostly occur in areas with low relevance for noise contours for scenarios. With a few modifications based on local procedures, the models are applicable to other airports.

For aircraft noise calculations, lateral flight dispersion is commonly represented by means of subtracks – a backbone track and side-tracks to each side of the backbone track – where each subtrack is assigned a movement percentage. Aircraft noise calculations impose quality demands on these subtracks, while the latter are often created based on limited information.This paper presents a method to increase flexibility when designing subtracks. The method allows to redistribute subtracks geometrically, allowing for the design of simplified track representations, for instance through a lower number of subtracks and very basic indications of movement allocations. The method is based on the geometric matching of the initial subtracks and on the estimation of the lateral movement distributions for both input and final output subtracks. No restrictions on the number of sub-tracks or on the shape of the distributions are needed, neither for the input nor for the output. A number of examples of the redistribution and its effect on aircraft noise calculations are discussed.