Miniature mass spectrometer signal processing based on ensemble empirical mode decomposition feature enhancement.

RATIONALE: The high sensitivity of the miniature mass spectrometer plays an irreplaceable role in rapid on-site detection. However, its analysis accuracy and stability should be improved due to the influence of sample pretreatment and use environment. The present study investigates the processing effects of ensemble empirical mode decomposition (EEMD) feature enhancement methods on the determination coefficient (R2 ) and relative standard deviation (RSD) of caffeine mass spectrometry (MS) signals. METHODS: This paper employs the EEMD method combined with polynomial curve fitting to enhance the characteristics of seven caffeine mass spectrum signals with different concentrations and 15 groups of caffeine mass spectrum signals with the same concentration, and the wavelet analysis method was used for comparative verification. The determination coefficient and RSD of the two methods were compared. RESULTS: We found the EEMD method's capability in adaptively decomposing caffeine mass spectrum signals is better than wavelet analysis method. The determination coefficient of the EEMD enhanced feature is better than 0.999, and the RSD is better than 2%, and both are better than wavelet analysis methods. CONCLUSIONS: The feature enhancement processing using the EEMD method has significantly improved the determination coefficient and RSD of the sample curve, improving the accuracy and stability of the data and providing a new way for miniature mass spectrometer signal processing.

Novel hollow-electrode glow discharge mass spectrometry for the quantitative analysis of protein content in food.

Protein content in food is an important indicator of nutritional value and food safety. Therefore, it is of great significance to accurately detect protein content in food. In this work, a combustion furnace and novel hollow-electrode glow discharge ion source-quadrupole mass spectrometry (HGD-MS) were designed, which were used to construct a "combustion furnace + mass spectrometry" experimental platform to detect the protein content in food. Five food standard samples were selected for the analysis. The food samples were combusted in the combustion furnace at a high temperature (1300 °C) in an oxygen-rich environment. The gas products were passed into the novel hollow electrode glow discharge ion source-quadrupole mass spectrometer. A standard curve of y = 635.06x + 11 082, R2 = 0.9994 was plotted by detecting the NO+ ion intensity at a relative standard deviation (RSD) of 1.8% to 5.7%. Using the same method, food samples no. 6 and 7 were combusted and NO+ ion intensity was measured to verify the accuracy of the quantitation curve. Subsequently, the protein content was determined using a nitrogen-to-protein conversion factor of 6.25. This method provides a rapid, accurate, and environmentally friendly approach for determining protein content in food.

Temporal Reference, Attentional Modulation, and Crossmodal Assimilation.

Crossmodal assimilation effect refers to the prominent phenomenon by which ensemble mean extracted from a sequence of task-irrelevant distractor events, such as auditory intervals, assimilates/biases the perception (such as visual interval) of the subsequent task-relevant target events in another sensory modality. In current experiments, using visual Ternus display, we examined the roles of temporal reference, materialized as the time information accumulated before the onset of target event, as well as the attentional modulation in crossmodal temporal interaction. Specifically, we examined how the global time interval, the mean auditory inter-intervals and the last interval in the auditory sequence assimilate and bias the subsequent percept of visual Ternus motion (element motion vs. group motion). We demonstrated that both the ensemble (geometric) mean and the last interval in the auditory sequence contribute to bias the percept of visual motion. Longer mean (or last) interval elicited more reports of group motion, whereas the shorter mean (or last) auditory intervals gave rise to more dominant percept of element motion. Importantly, observers have shown dynamic adaptation to the temporal reference of crossmodal assimilation: when the target visual Ternus stimuli were separated by a long gap interval after the preceding sound sequence, the assimilation effect by ensemble mean was reduced. Our findings suggested that crossmodal assimilation relies on a suitable temporal reference on adaptation level, and revealed a general temporal perceptual grouping principle underlying complex audio-visual interactions in everyday dynamic situations.