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BACKGROUND The molecular profiling of patients with advanced non-small-cell lung cancer (NSCLC) for known oncogenic drivers is recommended during routine care. Nationally, however, the feasibility and effects on outcomes of this policy are unknown. We aimed to assess the characteristics, molecular profiles, and clinical outcomes of patients who were(More)
Probe-based memory devices using ferroelectric media have the potential to achieve ultrahigh data-storage densities under high write-read speeds. However, the high-speed scanning operations over a device lifetime of 5-10 years, which corresponds to a probe tip sliding distance of 5-10 km, can cause the probe tip to mechanically wear, critically affecting(More)
BACKGROUND Malignant pleural mesothelioma is an aggressive cancer with poor prognosis, linked to occupational asbestos exposure. Vascular endothelial growth factor is a key mitogen for malignant pleural mesothelioma cells, therefore targeting of vascular endothelial growth factor might prove effective. We aimed to assess the effect on survival of(More)
Maneuver recognition and trajectory prediction of moving vehicles are two important and challenging tasks of advanced driver assistance systems (ADAS) at urban intersections. This paper presents a continuing work to handle these two problems in a consistent framework using non-parametric regression models. We provide a feature normalization scheme and(More)
It is well-recognized that MEMS switches, compared to their more traditional solid state counterparts, have several important advantages for wireless communications. These include superior linearity, low insertion loss and high isolation. Indeed, many potential applications have been investigated such as Tx/Rx antenna switching, frequency band selection,(More)
Driving intention recognition and trajectory prediction of moving vehicles are two important requirements of future advanced driver assistance systems (ADAS) for urban intersections. In this paper, we present a consistent framework for solving these two problems. The key idea is to model the spatio-temporal dependencies of traffic situations with a(More)
Understanding of traffic situations is an essential part of future advanced driver assistance systems (ADAS). This has to handle spatio-temporal dependencies of multiple traffic participants and uncertainties from different sources. Most existing approaches use probabilistic generative joint structures like Hidden Markov Models (HMM), which have long been(More)
To achieve an appropriate level of reliance on an automated system, the operator must have an accurate system representation such that he/she is aware of the capabilities and limitations of the system. The appropriate use of an automated system can lead to optimal performance by the human-machine dyad. This study investigates the relationship between an(More)