Zobrazeno 1 - 10
of 409
pro vyhledávání: '"John H. Booske"'
Publikováno v:
IEEE Access, Vol 7, Pp 36568-36578 (2019)
We describe the results of a wideband, reconfigurable reflectarray concept based on polarization-rotating unit cells (PRUCs) with a minimum-switch topology design. To enhance the simplicity and decrease the cost, the approach focuses exclusively on a
Externí odkaz:
https://doaj.org/article/da8c19abb3354d4a8c486de7123486ec
Autor:
Mirhamed Mirmozafari, Zongtang Zhang, Meng Gao, Jiahao Zhao, Mohammad Mahdi Honari, John H. Booske, Nader Behdad
Publikováno v:
Applied Sciences, Vol 11, Iss 15, p 6890 (2021)
We review mechanically reconfigurable reflectarray (RA) and transmitarray (TA) antennas. We categorize the proposed approaches into three major groups followed by a hybrid category that is made up of a combination of the three major approaches. We di
Externí odkaz:
https://doaj.org/article/d5cf59ceb3374b2f80e83d3ea050e662
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0298866 (2024)
We demonstrate that applying electric field pulses to hepatocytes, in vitro, in the presence of enhanced green fluorescent protein (EGFP)-expressing adeno-associated virus (AAV8) vectors reduces the viral dosage required for a given transduction leve
Externí odkaz:
https://doaj.org/article/a5a88326ebc44b2987bc306ab8ea8330
Publikováno v:
IEEE Transactions on Plasma Science. :1-13
A Dual-Band Transmitarray Antenna Employing Ultra-Thin, Polarization-Rotating Spatial Phase Shifters
Publikováno v:
IEEE Transactions on Antennas and Propagation. 70:11132-11137
Publikováno v:
IEEE Transactions on Antennas and Propagation. 70:6646-6658
Publikováno v:
IEEE Transactions on Antennas and Propagation. 70:4414-4425
Publikováno v:
2023 17th European Conference on Antennas and Propagation (EuCAP).
Publikováno v:
IEEE Transactions on Antennas and Propagation. 70:1600-1611
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing. 60:1-11
We present the results of an experimental and computational pilot study of cranberry crop yield prediction using low-power microwave sensing and machine learning. We simulated backscattered radiation from cranberry canopies using plane-wave illuminat