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Purpose
To design and evaluate a four-channel cardiac transceiver coil array for functional cardiac imaging at 7T.
Materials and Methods
A four-element cardiac transceiver surface coil array was developed with two rectangular loops mounted on an anterior former and two rectangular loops on a posterior former. specific absorption rate (SAR) simulations were performed and a Burn:x-wiley:10531807:media:JMRI22451:tex2gif-stack-1 calibration method was applied prior to obtain 2D FLASH CINE (mSENSE, R = 2) images from nine healthy volunteers with a spatial resolution of up to 1 × 1 × 2.5 mm3.
Results
Tuning and matching was found to be better than 10 dB for all subjects. The decoupling (S21) was measured to be >18 dB between neighboring loops, >20 dB for opposite loops, and >30 dB for other loop combinations. SAR values were well within the limits provided by the IEC. Imaging provided clinically acceptable signal homogeneity with an excellent blood-myocardium contrast applying the Burn:x-wiley:10531807:media:JMRI22451:tex2gif-stack-2 calibration approach.
Conclusion
A four-channel cardiac transceiver coil array for 7T was built, allowing for cardiac imaging with clinically acceptable signal homogeneity and an excellent blood-myocardium contrast. Minor anatomic structures, such as pericardium, mitral, and tricuspid valves and their apparatus, as well as trabeculae, were accurately delineated.
Digital elevation models (DEMs), represent the three-dimensional terrain and are the basic input for numerical snow avalanche dynamics simulations. DEMs can be acquired using topographic maps or remote-sensing technologies, such as photogrammetry or lidar. Depending on the acquisition technique, different spatial resolutions and qualities are achieved. However, there is a lack of studies that investigate the sensitivity of snow avalanche simulation algorithms to the quality and resolution of DEMs. Here, we perform calculations using the numerical avalance dynamics model RAMMS, varying the quality and spatial resolution of the underlying DEMs, while holding the simulation parameters constant. We study both channelized and open-terrain avalanche tracks with variable roughness. To quantify the variance of these simulations, we use well-documented large-scale avalanche events from Davos, Switzerland (winter 2007/08), and from our large-scale avalanche test site, Valĺee de la Sionne (winter 2005/06). We find that the DEM resolution and quality is critical for modeled flow paths, run-out distances, deposits, velocities and impact pressures. Although a spatial resolution of ~25 m is sufficient for large-scale avalanche modeling, the DEM datasets must be checked carefully for anomalies and artifacts before using them for dynamics calculations.
We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures – known for their complex spatial and temporal dynamics – we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.
The importance of the availability of stored blood or blood cells, respectively, for urgent transfusion cannot be overestimated. Nowadays, blood storage becomes even more important since blood products are used for epidemiological studies, bio-technical research or banked for transfusion purposes. Thus blood samples must not only be processed, stored, and shipped to preserve their efficacy and safety, but also all parameters of storage must be recorded and reported for Quality Assurance. Therefore, blood banks and clinical research facilities are seeking more accurate, automated means for blood storage and blood processing.