Search

Double-threshold method is a typical and simple time-of-flight (TOF) measurement method for time-difference-based ultrasonic flowmeter. Some improvements have been proposed to suppress the cycle-skip phenomenon in double-threshold method. However, there are still some application limitations when the waveform is distorted caused by the environment change, especially the temperature change. This paper proposes a similarity judgment-based double-threshold method to deal with the cycle-skip problem. In this method, time values of three consecutive positive zero-crossing points after the feature point are acquired and five consecutive cycles after the first obtained time are saved. The TOF is automatically selected from three acquired time values according to an adaptive determination function which bases on the similarity between signals from two adjacent measurements. These operations guarantee that the obtained TOF locates on the same positive zero-crossing point in each measurement. The proposed method was validated by both numerical and experimental tests. Comparison between the proposed method and other double-threshold methods shows that the proposed method successfully eliminates cycle-skip phenomenon under different working conditions. [ABSTRACT FROM PUBLISHER]

The tumorgenesis process of lung cancer involves the regulatory dysfunctions of multiple pathways. Although many signaling pathways have been identified to be associated with lung cancer, there are little quantitative models of how inactions between genes change during the process from normal to cancer. These changes belong to different dynamic co-expressions patterns. We quantitatively analyzed differential co-expression of gene pairs in four datasets. Each dataset included a large number of lung cancer and normal samples. By overlapping their results, we got 14 highly confident gene pairs with consistent co-expression change patterns. Some of they, such as ARHGAP30 and GIMAP4, had been recorded in STRING network database while some of them were novel discoveries, such as C9orf135 and MORN5, TEKT1 and TSPAN1 were positively correlated in both normal and cancer but more correlated in normal than cancer. These gene pairs revealed the underlying mechanisms of lung cancer occurrence. • We analyzed differential co-expression of gene pairs in four datasets. • We got 14 highly confident gene pairs with consistent co-expression change patterns. • We uesd an R package DiffCorr. [ABSTRACT FROM AUTHOR]