Hongling Wang

It has been reported that vanillin has been intentionally added to enhance the taste and flavor of low-quality vegetable oils. Therefore, it is crucial to investigate the accurate concentrations of vanillin in three types of fragrant vegetable oils commonly consumed in China. In this study, a method has been developed for the quantification of vanillin in commercial fragrant vegetable oils using the stable isotope dilution assay (SIDA) and headspace–solid-phase microextraction (HS–SPME) coupled with gas chromatography/mass spectrometry (GC/MS). The limit of detection (LOD) and limit of quantification (LOQ) of the analyte were determined to be 20 µg kg⁻¹ and 50 µg kg⁻¹, respectively. The validation study demonstrated that the recoveries ranged from 89% to 101%, with intra-day and inter-day precision being less than 7.46%. A survey of 80 commercially available fragrant vegetable oils was performed using the present method. Vanillin was found to be widely present in fragrant vegetable oils, with sesame oils showing the highest average content (842.6 µg kg⁻¹), followed by rapeseed oils (262.1 µg kg⁻¹) and peanut oils (115.0 µg kg⁻¹). The results indicate that the proposed method is a simple, accurate, and eco-friendly approach for determining the presences of vanillin in fragrant vegetable oils.

Perception-driven hierarchical simultaneous localization and mapping approach is proposed based on a distributed particle of percolator model adapted to search and rescue post-disaster environment. The proposed hierarchical analysis reduced the complexity; it can only highlight the interesting three-dimensional objects marked on the two-dimensional map, which adapted to urgent search and rescue post-disaster scenarios. Object identification, area coverage, and loop closure are the key issues that simultaneous localization and mapping faces when mobile robots detect and reach survivors in search and rescue collapsed environments. We developed hierarchical analysis using iterative extended Kalman filter method to improve the localization accuracy in simultaneous localization and mapping of mobile robots with an iteration process. An analytic hierarchical map-building mechanism efficiently constructs a globally consistent topological map using graph-based nodes and data association. An improved iterative extended Kalman filter procedure is used to estimate positions and the covariance matrix. The proposed algorithm incorporates a prediction step and a measurement update step, which performs the state vector time update in constant time interval and the correction of the state vector based on the new sensor measurement. The hierarchical mapping process is divided into three levels. The bottom level perceives the surroundings and collects input. The middle level receives and processes data from the bottom level. The upper level organizes the feature information from the previous levels to form a global, topologically consistent map. Simulations and experiments using the mobileRobot platform, Pioneer LX robot, and a crawler mobile robot validate the efficiency of this hierarchical simultaneous localization and mapping approach adapting to search and rescue post-disaster scenarios.

We propose a simultaneous localization and mapping (SLAM)method that adds robot arm exploration to the SLAM process anduses a graphical user interface and Cyton Commands program tocontrol a robot arm to implement perceptive exploration duringthe SLAM.

In this study, volatile compounds of five varieties of mandarin juices [Tankan, Miyagawa, Mashui (MS), Skiranui, and Ponkan (PG)] were investigated by gas chromatography–olfactometry (GC–O) and gas chromatography–mass spectrometry (GC–MS). A total of 47 volatile compounds were identified by GC–MS. Partial least-squares regression was used to process the mean scores from sensory evaluation by panelists of volatile compounds and samples. The sample PG was associated with “fruity”, “floral”, and “sweet” notes, while MS was correlated with “green” and “peely” notes. In addition, 36 aroma-active compounds, including esters, alcohols, aldehydes, ketones, and monoterpenes, were detected by GC–O. According to the quantitative results, 29 aroma compounds were important, which indicated that their odor activity values (OAVs) were ≥1. On the basis of the GC–O results and OAVs of these volatile compounds, 22 odor-active compounds were mixed to simulate successfully the overall aroma of PG mandarin juice. Furthermore, omission experiments confirmed that nonanal, hexanal, linalool, and (R)-(+)-limonene were the key odorants for the overall aroma of PG juice sample and that β-ionone, decanal, γ-terpinene, and methyl butyrate were also important odor-active compounds.