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Real drilling near the upper Ordovician pinch-out line in the Tahe Oilfield shows that the drilling encountered karst reservoir. However, due to the transitional position between the denudation area and the overlying area and the special karst geological background, the existing drilling and completion data show that the reservoir space types in this area are complex and diverse. In this article, the classification of reservoir space near the Upper Ordovician pinch-out line and the extraction of logging response characteristics have been carried out based on drilling, logging, core, and crude oil quality data. Through this study, the classification scheme of karst reservoir space in the study area is proposed. The reservoir space types of karst reservoirs include fracture–cave, fracture–pore (light and low resistivity), fracture–pore (heavy and high resistivity), dissolved pore–pore (light and low resistivity), dissolved pore–pore (heavy and high resistivity), isolated pore (relatively isolated distribution of pores and fractures, weakly connected), and cave-type reservoir (sand and gravel filled or semi-unfilled). Furthermore, conventional logging parameters and five parameters sensitive to reservoir properties are extracted. The intersection maps based on the combination forms, fluid properties, and reservoir space effectiveness of different types of reservoir spaces are effective in distinguishing seven types of reservoir spaces and two types of stratified karst reservoirs. In this study, the reservoir space types and logging response characteristics of reservoirs near the Upper Ordovician pinch-out line are defined, which can provide a reliable geological basis for the quantitative identification and distribution evaluation of karst reservoirs.

Road roughness significantly impacts vehicle safety and dynamic responses. For nonlinear suspension systems, the nonlinear characteristics often make it challenging for estimators to identify the actual road roughness accurately. This paper proposes a hybrid road roughness identification algorithm based on nonlinear auto-regressive with exogenous inputs (NARX) and a process noise adaptive square root cubature Kalman filter (PASCKF) to address this issue. Driven by vehicle acceleration data, an NARX-based road roughness identification system is constructed to mitigate the model uncertainties. Furthermore, a hybrid strategy is proposed. On the one hand, the accurate road roughness estimated by the NARX is converted into process noise covariance, enhancing the estimator's accuracy and convergence rate. Another switching strategy is proposed to optimize the non-convergence issues of the PASCKF. Finally, simulation and actual vehicle experiment data demonstrate that this approach offers superior identification accuracy and adaptability compared to the standalone SCKF algorithm. [ABSTRACT FROM AUTHOR]

Rosa roxburghii Tratt fruit is a highly valued fruit that contains abundant functional and nutritional constituents. In this study, a novel polysaccharide, named RTFP-1, was isolated and purified from R. roxburghii Tratt fruit. Structural characterization indicated that RTFP-1 was a homogeneous heteropolysaccharide with the molecular weight (Mw) of 128.7 kDa and consisted of arabinose, galactose, glucose, mannose, xylose, and fucose with molar ratio percentages of 34.84, 40.59, 12.11, 5.06, 3.39, and 4.01%, respectively. A CCK-8 assay indicated that RTFP-1 inhibited the cell growth of HepG2 cells in a dose-dependent manner. Morphological analysis and flow cytometry experiment showed that RTFP-1 promoted the apoptosis of HepG2 cells and increased reactive oxygen species (ROS) level. The underlying molecular mechanisms indicated that RTFP-1 activated the apoptosis of HepG2 cells through ROS-mediated MAPK, STAT, and p53 apoptotic pathways. These results suggest that RTFP-1 might be a potential chemopreventive and antitumor agent., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)