Aiming at the problem of high water content and low degree of recovery of low permeability heavy oil reservoir in Guan128 block of Dagang Oilfield, the microscopic seepage law and residual oil characteristics of viscosity reducers flooding were studied through indoor experiments, and the planar wave and characteristics and residual oil distribution law were quantitatively analysed with the help of AI intelligent recognition. The experimental results show that after the viscosity reducer emulsification of crude oil, the emulsion aggregates and can block the water-driven flux channels, the advantageous transport channels of oil droplets increase, improve the wave and reach coefficient, and reduce the oil saturation. AI image identified pore throat droplets of oil, the wall membrane oil, the residual oil in the dead corner and the residual oil without wave and flake oil and other types of residual oil distribution, and the formation mechanism was analyzed, and measures of surfactants injection and encryption of the network of wells were put forward, and the blocking of high seepage channels was adjusted. Adding viscosity-reducing agent system can reduce the starting pressure gradient and improve the fluidity of heavy oil. After the conversion of water drive to chemical drive, the oil washing effect of residual oil in the pores and throat and residual oil in the dead space is improved, and the recovery rate is increased by 15.28%. The research results provide important theoretical reference for the research on the mechanism of efficient oil enhancement and field application of viscosity-reducing agent injection in the late stage of water-drive development of low-permeability heavy oil reservoirs.

The changes in clouds are complex and diverse, playing a significant role in weather forecast and disaster warning, and affecting our daily lives. The observation of clouds is mainly carried out through radar, remote sensing satellites, and all-sky imagers. The recorded cloud images are divided into radar cloud images, satellite cloud images, and ground-based cloud images, all of which are indispensable parts of cloud observation. With the development of machine learning in multiple fields, it has gradually been applied to cloud segmentation and has made great progress. Through extensive research on literature and achievements in related fields, machine learning cloud segmentation was divided into three types: cloud segmentation methods based on neural networks, cloud segmentation methods based on transfer learning, and cloud segmentation methods based on lightweight models. The methods proposed in recent years for each type were compared, and improvement methods for different problems in cloud segmentation were further summarized. Several improvement schemes were provided for reference.

There are various evaluation methods for the effectiveness of asphalt pavement grouting repair, most of which rely on on-site testing of a single indicator. Up to now, there are few related reports in the comprehensive evaluation of multiple indicators. In order to comprehensively understand the detection methods of asphalt pavement grouting repair effect and promote the development and application from single index evaluation to multi index evaluation methods, the research status of relative methods were summarized including drilling core method, grouting plug gauge method, deflection detection method, modulus inverse algorithm, ground penetrating radar method, and transient Rayleigh surface wave method in the detection of grouting filling quality, pavement strength, pavement modulus, compaction degree, void ratio, and grouting repair degree and other indicators. Furthermore, drawing on the current research status in the fields of tunnel grouting and goaf grouting, the application prospects of fuzzy analytic hierarchy process, grey correlation degree method were analyzed, as well as subjective and objective weighting cloud model in the evaluation of grouting repair effect of internal diseases in asphalt pavement, and looks forward to the development trend of precision, objectivity, and informatization in the evaluation of grouting repair effect of asphalt pavement were forecasted. Diversified method guidance is provided for evaluating the grouting repair effect of internal diseases in asphalt pavement.

In order to study the failure mode and energy dissipation law of granite with double elliptical defects, dynamic splitting tensile experiments were conducted on granite with double elliptical defect angles of 0°, 45°, 90°, and 135° using a SHPB(split Hopkinson bar) device. The relationship between the angle and spacing of double elliptical defects, as well as the failure morphology and energy of granite, was explored. The results show that when the distance between double elliptical defects remains constant, the larger the included angle, the easier the specimen is to fracture. When the angle remains constant, the spacing increases and the rock sample is more prone to fracture. The dissipated energy density of the specimen decreases with the increase of the included angle, and the downward trend gradually tends to be gentle. The failure mode of the specimen is highly sensitive to the angle, that is, as the angle increases, the degree of fragmentation of the rock sample gradually intensifies, the symmetry of the fragments disappears, the wedge effect gradually becomes obvious, and the plasticity increases. When the included angle exceeds 90°, the degree of fragmentation begins to decrease again, and the rock sample exhibits symmetrical fracture.

Guangxi is located in the South China block, its structure is relatively stable, the seismic activity observed by the instrument is relatively weak. The little observation data leads to weak research on the crustal stress field in the area. In 2019, the Beiliu earthquake sequence occurrence in this area leads to the accumulation of considerable focal mechanism data. The focal mechanism data were collected in Guangxi and its adjacent areas. Using the grid search algorithm, the stress field in overall region and subregions were inverted. The results show as follows. The statistics of the focal mechanism in this area is mainly strike-slip type, and from the distribution of NW to ES, the focal mechanism of the reverse type gradually increases, and the focal mechanism of the normal fault type gradually decreases. The principal compressive stress axis of the overall stress field is NW-SE direction, the principal extensional stress axis is NE-SW direction, both of them are close to horizontal, which representing strike-slip type. The direction of the principal compressive stress axis in the western region is close to the N-E direction, and that in the east gradually changes to the direction of NW-SE, which makes the pattern of the compressive stress direction present a fan-shaped in the overall area. Based on the stress field analysis of subregions: NE-SW and NW-SE faults are easily generated in region-a by primarily of strike-slip type. NNE-SSW and NWW-SEE faults are easily generated in region-b, with NNE-SSW faults more towards reverse strike-slip type and NWW-SEE faults tending towards strike-slip type. Pure azimuth N-S and E-W faults are easily generated in region-c, but its main fault properties are not reflected due to the influence of surrounding fault extensions, with faults mainly of reverse strike-slip and reverse fault types. NW-SE and NE-SW faults are easily generated in region-d, with NW-SE faults more towards reverse fault and NE-SW faults tending towards strike-slip.

The tectonic activities at the bottom and surrounding the sedimentary basin will inevitably lead to changes in the sedimentary filling characteristics and evolution of the basin. These changes serve as records of the sedimentary strata’s response to tectonic activities. Based on logging interpretation and outcrop data, the sedimentary evolution of the Middle and Late Jurassic to Early Cretaceous in the Ordos Basin was analyzed through paleogeography and sedimentary facies restoration. The results indicate that the southern part of the basin developed multi-phase depositional systems, including alluvial fan, river-delta-lake, and desert phases. There was a sedimentary divergence from east to west, with the sedimentary center migrating from east to west. During this period, the basin was primarily influenced by the Yanshan Movement, with strong tectonic activities occurring around it. Consequently, a tectonic pattern emerged within the basin, characterized by uplifting and tilting in the east and sinking and depression in the west. The intense tectonic activities at the western edge of the basin also led to the development of an intralittoral foreland basin at the southwestern edge during the Late Jurassic Fenfanghe Stage. Additionally, multiple sets of molasse formations and unconformity contacts were present during the Late Jurassic and Early Cretaceous periods. Based on these insights, a model map of the Middle and Late Jurassic to Early Cretaceous tectono-sedimentary evolution has been established. The occurrence of these sedimentary events serves as a record of the basin’s response to the early and middle stages of the Yanshan Movement, proving a close relationship between sedimentary evolution and the uplift of the Qinling-Qilian Mountain orogenic belt and the Lvliang Mountains. These insights not only complement and improve the theory of tectonic-sedimentary response in the southern basin during the Yanshan Movement but also have practical significance for the exploration and development of mineral resources such as oil, gas, and uranium in the southern basin.

The Sichuan Basin, situated in the heart of China, is renowned for its abundant oil and gas reserves within a geologically intricate sedimentary basin. A multitude of strike-slip faults, characterized by their extensive reach, substantial scale, and modest displacement, are particularly prominent in the basin’s central region. In order to elucidate the influence of these faults on the formation of oil and gas reservoirs, high-precision seismic data analysis and numerical simulation techniques were used to investigate the strike-slip fault system in the central Sichuan area. The results show that the primary strike-slip faults in the central Sichuan region bifurcate into two distinct orientations: nearly EW(east-west) and NE(northeast-southwest). These first-order faults are inclined to emerge along the peripheries of secondary tectonic units. The near EW-oriented faults were predominantly active prior to the Permian era, coinciding with the Hercynian phase, whereas the NE-oriented faults were shaped later, during the transition from the Late Hercynian to the Indosinian period. The evolution of these strike-slip faults is intricately tied to a series of overlapping tectonic events. The culmination of the ancient uplift in central Sichuan predating the Permian era precipitated the genesis of the near EW-oriented faults. Subsequently, a pivotal tectonic regime shift during the Late Hercynian epoch, coupled with the subsequent Indosinian period’s fore-arc structural modifications near the Longmen Mountains, catalyzed the emergence of the NE-oriented faults. Moreover, the Deyang Anyue fault trough is identified as a pivotal factor in dictating the regional stress distribution, effectively hindering the east-west faults from traversing beyond the fault trough boundary, thereby stifling their further development.

To observe the effects of LPS(lipopolysaccharide)-HDAC3(induced histone deacetylase 3) on the expression of HMGB1(high mobility histone B1) and nuclear translocation in RAW264.7 cells, and the intervention effect of SFI(Shenfu injection). RAW264.7 cells were induced by LPS to establish a cellular inflammatory injury model, and the cells were intervened with SFI at doses of 3, 6, and 12 μL/mL for 24 h. RT-qPCR(real-time fluorescence PCR) was used to detect the transcriptional levels of HDAC3, HMGB1, IL-1β, and TNF-α in the cells, and Western-blot was used to detect the protein expression of HMGB1 and HDAC3, and immune immunoassay to detect the protein expression of HMGB1 and HDAC3.HDAC3 protein expression, immunofluorescence to observe the effect of SFI on the subcellular localization of HMGB1. ELISA to detect the secretion levels of HMGB1, IL-1β, and TNF-α in the cell supernatant. And small interfering RNA(siRNA) after targeting to silence the HDAC3 in RAW264.7 cells. to observe the effect of SFI on HMGB1 subcellular localization. Compared with the control group, the transcription and expression of HDAC3 in RAW264.7 cells in the model group were significantly reduced (P<0.01), and the expression of HMGB1 was significantly elevated (P<0.01) and simultaneously migrated from the nucleus to the cytoplasm. The inflammatory factors in the supernatant of the cells, such as HMGB1, IL-1β and TNF-α, were significantly elevated (P<0.01). And compared with the model group, SFI (6, 12 μL/mL dose group) up-regulated the transcription and expression levels of HDAC3, down-regulated the transcription, expression, and nuclear translocation of the inflammatory factor HMGB1, and inhibited the secretion of HMGB1, IL-1β, and TNF-α in RAW264.7 cells. After targeted silencing of HDAC3, a large amount of HMGB1 was localized in the cytoplasm, and there was no significant change in protein localization after LPS stimulation, and SFI could not reverse the abnormal localization of HMGB1. SFI may inhibit LPS-induced extra-nuclear migration of HMGB1 in RAW264.7 cells by up-regulating HDAC3 expression, which in turn inhibited its downstream inflammatory response.

Addressing the issues of large model parameters and high computational complexity in apple target detection algorithms for complex orchard environments, which hinder application on devices with limited computational resources, an improved and lightweight apple target detection algorithm named YOLOv8n-Apple based on YOLOv8 was proposed. The backbone network, yaniaNet, was introduced to reduce model parameters and complexity. The original C2f module in the model was replaced with the C2fGhost module, which further decreased model parameters by obtaining similar feature maps through fewer convolutional operations. The lightweight upsampling operator CARAFE was utilized to address the issues of semantic loss and excessively small receptive fields associated with traditional upsampling operators. Given that traditional loss functions cannot fully capture the relative position and size differences between targets, the WIoU bounding box was adopted as the regression loss function. A dataset comprising 3 120 images of mature apples in various scenarios, including distant and close views under front-light and backlight conditions, was collected from diverse angles and backgrounds, to mitigate potential dataset uncertainties. The improved apple detection model for orchard environments demonstrated an average detection accuracy of 90%, which was 7.5, 4.8, 2.2, 3.8, and 3.4 percentage points higher than SSD, Faster R-CNN, YOLOv5, YOLOv7, and YOLOv8, respectively. The detection speed reached 286 frames per second, and the model size was reduced to 1.8 MB, representing an improvement of 41 frames per second compared to the original model, while occupying only 60.0% of size.

There are certain requirements for the mechanical properties of paper or paper-based materials during their service. However, existing experimental and theoretical studies of size effects indicate that the mechanical properties of specimens with different sizes are not identical. Therefore, it is necessary to clarify the size effect of their mechanical properties to ensure their safety. The kraft paper, which is easy to obtain and has high strength, was selected to carry out uniaxial tensile tests on with different sizes. And then the size effects of mechanical properties and their dispersions were determined. By analyzing the deformation characteristics and macro-microscopic damage features of different sizes specimens, the intrinsic mechanism of the size effect on the mechanical properties of kraft paper was revealed. Finally, a size effect model of mechanical properties for kraft paper was established. The study finds that the nominal tensile strength and nominal peak strain of kraft paper first increase and then decrease as the sizes increases. This is because the cut edge fibers cause the edges of the kraft paper specimens to have weaker stress and strain capabilities, and the proportion of weakened edges in small-sized specimens is relatively large, leading to an increasing size effect on the nominal tensile strength and nominal peak strain. In large-sized specimens, the proportion of weakened edges can be ignored, and the internal fracture process zone plays a dominant role, leading to a decreasing size effect on the nominal tensile strength and nominal peak strain. The established edge-internal fracture process zone size effect model can well describe the size effect on the nominal tensile strength and nominal peak strain of kraft paper. However, this model cannot capture the nonlinear characteristics of the increasing size effect stage for the nominal tensile strength and nominal peak strain.