TY - JOUR A1 - Terekhov, Maxim A1 - Elabyad, Ibrahim A. A1 - Schreiber, Laura M. T1 - Global optimization of default phases for parallel transmit coils for ultra-high-field cardiac MRI JF - PLoS One N2 - The development of novel multiple-element transmit-receive arrays is an essential factor for improving B\(_1\)\(^+\) field homogeneity in cardiac MRI at ultra-high magnetic field strength (B\(_0\) > = 7.0T). One of the key steps in the design and fine-tuning of such arrays during the development process is finding the default driving phases for individual coil elements providing the best possible homogeneity of the combined B\(_1\)\(^+\)-field that is achievable without (or before) subject-specific B\(_1\)\(^+\)-adjustment in the scanner. This task is often solved by time-consuming (brute-force) or by limited efficiency optimization methods. In this work, we propose a robust technique to find phase vectors providing optimization of the B-1-homogeneity in the default setup of multiple-element transceiver arrays. The key point of the described method is the pre-selection of starting vectors for the iterative solver-based search to maximize the probability of finding a global extremum for a cost function optimizing the homogeneity of a shaped B\(_1\)\(^+\)-field. This strategy allows for (i) drastic reduction of the computation time in comparison to a brute-force method and (ii) finding phase vectors providing a combined B\(_1\)\(^+\)-field with homogeneity characteristics superior to the one provided by the random-multi-start optimization approach. The method was efficiently used for optimizing the default phase settings in the in-house-built 8Tx/16Rx arrays designed for cMRI in pigs at 7T. KW - optimization KW - magnetic resonance imaging KW - power grids KW - swine KW - electromagnetics KW - linear regression analysis KW - thorax KW - wave interference Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-265737 VL - 16 IS - 8 ER - TY - JOUR A1 - Wallmann-Sperlich, Birgit A1 - Froboese, Ingo T1 - Physical Activity during Work, Transport and Leisure in Germany - Prevalence and Socio-Demographic Correlates N2 - Background This study aimed 1) to provide data estimates concerning overall moderate- and vigorous-intensity physical activity (MVPA) as well as MVPA during work, transport and leisure in Germany and 2) to investigate MVPA and possible associations with socio-demographic correlates. Methods A cross-sectional telephone survey interviewed 2248 representative participants in the age of 18–65 years (1077 men; 42.4±13.4 years; body mass index: 25.3±4.5kg•m−2) regarding their self-reported physical activity across Germany. The Global Physical Activity Questionnaire was applied to investigate MVPA during work, transport and leisure and questions were answered concerning their demographics. MVPA was stratified by gender, age, body mass index, residential setting, educational and income level. To identify socio-demographic correlates of overall MVPA as well as in the domains, we used a series of linear regressions. Results 52.8% of the sample achieved physical activity recommendations (53.7% men/52.1% women). Overall MVPA was highest in the age group 18–29 years (p<.05), in participants with 10 years of education (p<.05) and in participants with lowest income levels <1.500€ (p<.05). Regression analyses revealed that age, education and income were negatively associated with overall and work MVPA. Residential setting and education was positively correlated with transport MVPA, whereas income level was negatively associated with transport MVPA. Education was the only correlate for leisure MVPA with a positive association. Conclusions The present data underlines the importance of a comprehensive view on physical activity engagement according to the different physical activity domains and discloses a need for future physical activity interventions that consider socio-demographic variables, residential setting as well as the physical activity domain in Germany. KW - educational attainment KW - age groups KW - body mass index KW - Germany KW - global health KW - education KW - adults KW - linear regression analysis Y1 - 2014 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-113648 ER -