Researchers face difficulties in studying the effects of driveline efficiency on car fuel economy via bench and road tests because of long working periods, high costs, and heavy workloads. To simplify the study process and shorten test cycles, a car fuel economy simulation forecast method for combining computer simulation forecasting with bench tests is proposed. Taking a continuously variable transmission (CVT) as the research object, a transmission efficiency model based on a bench test is constructed. An optimal economic variogram based on the original CVT variogram, the boundary conditions of vehicle performance, the road conditions and the driving behavior of the driver is generated in the Gear Shift Program (GSP)-Generation module in AVL Cruise. And on this basis a driveline simulation model that can calculate the fuel consumption based on the driveline data of a test car is built. The model is used to forecast fuel consumption and calculate real-time CVT efficiency under different conditions. Contrastive analyses on simulation results and real car drum test results are made. The largest error between simulation results and drum test results in driving cycles is 4.099%, which is 5.449% under constant velocity condition in driver control mode and 4.2% under constant velocity condition in automatic cruise mode. The results confirm the feasibility of the method and the good performance of the driveline simulation model in accurately forecasting fuel consumption. The method can efficiently investigate the effects of driveline efficiency on car fuel economy. Moreover, this research provides instruction for accurately forecasting fuel economy as well as references for studies on the effects of drivelines on car fuel economy. which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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The process of colorectal cancer (CRC) formation is considered a typical model of multistage carcinogenesis in which aberrant DNA methylation plays an important role. In this study, 752 methylation-driven genes (MDGs) were identified by the MethylMix package based on methylation and gene expression data of CRC in The Cancer Genome Atlas (TCGA). Iterative recursive feature elimination (iRFE) based on linear discriminant analysis (LDA) was used to determine the minimum MDGs (iRFE MDGs), which could distinguish between cancer and cancer-adjacent tissues. Further analysis indicated that the changes in methylation levels of the four iRFE MDGs, ADHFE1-Cluster1, CNRIP1-Cluster1, MAFB, and TNS4, occurred in adenoma tissues, while changes did not occur until stage IV in cell-free DNA. Furthermore, the methylation levels of iRFE MDGs were correlated with the genes involved in the reprogramming process of somatic cells to pluripotent stem cells, which is considered the common signature of cancer cells and embryonic stem cells. The above results indicated that the four iRFE MDGs may play roles in the early stage of colorectal carcinogenesis and highlighted the complicated relationship between tissue DNA and cell-free DNA (cfDNA).

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