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A novel allergy biosensor is designed and fabricated by using thin film bulk acoustic resonator (TFBAR) devices with shear mode ZnO piezoelectric thin films. To fabricate TFBAR devices, the off-axis RF magnetron sputtering method for the growth of piezoelectric ZnO piezoelectric thin films is adopted. The influences of the relative distance and sputtering parameters are investigated. In this report, the piezoelectric ZnO thin films with tilting angle are set by controlling the deposition parameters. The properties of the shear mode ZnO thin films are investigated by X-ray diffraction and scanning electron microscopy. The frequency response is measured using an HP8720 network analyzer with a CASCADE probe station. The resonance frequency of the shear mode is 796.75 MHz. The sensitivity of the shear mode is calculated to be 462.5 kHz·cm2/ng.
Unawareness of deficits is common and is associated with poor outcomes in Alzheimer's disease (AD); however, little is known about correlated neurobiochemical changes.
Proton magnetic resonance spectroscopy was used to examine neurobiochemical correlates of unawareness of deficits as assessed by the Dementia Deficit Scale in 36 patients with AD. Magnetic resonance spectroscopy spectra were acquired from the anterior cingulate area and right orbitofrontal area. Concentrations of N-acetyl-aspartate (NAA), total creatine, and other neurometabolites were calculated.
Nineteen (52.8%) participants had relative unawareness of deficits. This condition was negatively correlated with NAA/creatine in the anterior cingulate area (β = −0.36, p = 0.025) and positively correlated with NAA/creatine in the right orbitofrontal area (β = 0.41, p = 0.009) after controlling for dementia severity.
These findings suggest unawareness of deficits in AD was associated with the altered neurochemical metabolites in the anterior cingulate area and right orbitofrontal area. However, the two areas might have opposite neuronal functions in unawareness of deficits.
Currently Vessel Traffic Service (VTS) does not have enough technical capability to monitor a crowded surveillance area to maintain safety. Without an efficient alerting system, many marine accidents have occurred due to operator oversight. In this article, a new fuzzy logic method is proposed to add vessel collision avoidance capability to VTS/AIS systems for all potential collision ships in the surveillance area. Starting from the VTS standpoint and integrating AIS data into the Marine Geographic Information System (MGIS) as a platform, the calculations of ship domain and ship inertial force are utilized to generate models of a guarding ring and danger index. By this means, a precise prediction of collision time and position can be achieved using a marine GIS spatial analyst module. The proposed method is able to enhance the VTS operator's decision-making abilities by providing a collision avoidance alerting system.
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