A GC-MS method is reported for separation and characterization of widely different amounts of benzoic and phenolic acids as their trimethylsilyl derivatives simultaneously in cranberry. Fifteen benzoic and phenolic acids (benzoic, o-hydroxybenzoic, cinnamic, m-hydroxybenzoic, p-hydroxybenzoic, p-hydroxyphenyl acetic, phthalic, 2,3-dihydroxybenzoic, vanillic, o-hydroxycinnamic, 2,4-dihydroxybenzoic, p-coumaric, ferulic, caffeic, and sinapic acid) were identified in cranberry fruit in their free and bound forms on the basis of GC retention times and simultaneously recorded mass spectra. Except for benzoic, p-coumaric, caffeic, ferulic, and sinapic acids, 10 other phenolic acids identified have not been reported in cranberry before. The quantitation of the identified components was based on total ion current (TIC). The experimental results indicated cranberry fruit contains a high content of benzoic and phenolic acids (5.7 g/kg fresh weight) with benzoic acid being the most abundant (4.7 g/kg fresh weight). The next most abundant are p-coumaric (0.25 g/kg fresh weight) and sinapic (0.21 g/kg fresh weight) acid. Benzoic and phenolic acids occur mainly in bound forms and only about 10% occurs as free acid.

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The autonomous driving is rapid developing recently and model predictive controls (MPCs) have been widely used in unmanned vehicle trajectory tracking. MPCs are advantageous because of their predictive modeling, rolling optimization, and feedback correction. In recent years, most studies on unmanned vehicle trajectory tracking have used only linear model predictive controls to solve MPC algorithm shortcomings in real time. Previous studies have not investigated problems under conditions where speeds are too fast or trajectory curvatures change rapidly, because of the poor accuracy of approximate linearization. A nonlinear model predictive control optimization algorithm based on the collocation method is proposed, which can reduce calculation load. The algorithm aims to reduce trajectory tracking errors while ensuring real-time performance. Monte Carlo simulations of the uncertain systems are carried out to analyze the robustness of the algorithm. Hardware-in-the-loop simulation and actual vehicle experiments were also conducted. Experiment results show that under i7-8700, the calculation time is less than 100 ms, and the mean square error of the lateral deviation is maintained at 10−3 m2, which proves the proposed algorithm can meet the requirement of real time and accuracy in some particular situations. The unmanned vehicle trajectory tracking method provided in this article can meet the needs of real-time control.

OBJECTIVE The application of robots in the field of pedicle screw placement has achieved great success. However, decompressive laminectomy, a step that is just as critical as pedicle screw placement, does not have a mature robot-assisted system. To address this lack, the authors designed a collaborative spine robot system to assist with laminectomy. In this study, they aimed to investigate the reliability of this novel collaborative spinal robot system and compare it with manual laminectomy (ML). METHODS Thirty in vitro porcine lumbar vertebral specimens were obtained as experimental bone specimens. Robot-assisted laminectomy (RAL) was performed on the left side of the lamina (n = 30) and ML was performed on the right side (n = 30). The time required for laminectomy on one side, whether the lamina was penetrated, and the remaining thickness of the lamina were compared between the two groups. RESULTS The time required for laminectomy on one side was longer in the RAL group than in the ML group (median 326 seconds [IQR 133 seconds] vs 108.5 seconds [IQR 43 seconds], p < 0.001). In the RAL group, complete lamina penetration occurred twice (6.7%), while in the ML group, it occurred 9 times (30%); the difference was statistically significant (p = 0.045). There was no statistically significant difference in the remaining lamina thickness between the two groups (median 1.035 mm [IQR 0.419 mm] vs 1.084 mm [IQR 0.383 mm], p = 0.842). CONCLUSIONS The results of this study confirm the safety of this novel spinal robot system for laminectomy. However, its efficiency requires further improvement.