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Evaluating the anisotropy of rock and its size effect in spatial variation is of great significance for improving engineering efficiency and stability. For this purpose, an anisotropy index is used to quantify the magnitude of anisotropy in rock. Digital drilling tests are carried out in three directions on six types of rock to investigate the anisotropy of drilling parameters. The rock is subdivided into multiple small units along the depth of drilling, and the effect of size on rock anisotropy based on drilling work was studied. The research findings indicate that the drilling work on six rock types exhibits anisotropy, and the anisotropy sequence for the total drilling work of each rock is as follows: red sandstone > granite > slate > gneiss > sandstone > argillaceous sandstone. As the length of rock units increases, the anisotropy index of drilling work initially exhibits a fluctuating trend, subsequently reaching a state of stability, thereby manifesting a size effect. Furthermore, the representative elementary volume (REV) for each type of rock exhibits distinct variations. The anisotropy indices for drilling work along the depth of the borehole exhibit an initial phase of rapid increase, followed by a convergence towards a value close to 1.0. The anisotropy of rocks demonstrates size dependence, and size effects also exhibit anisotropy. Anisotropy and its size effects are interconnected and inseparable. The reliability of the cited anisotropy index is checked by comparison with two other anisotropy indices. This comparison shows that our method can reliably determine rock anisotropy. In summary, the research outlined in this paper presents a highly efficient and straightforward approach to evaluate the effect of size on rock anisotropy. [ABSTRACT FROM AUTHOR]

Magnetic resonance cholangiopancreatography (MRCP) plays a significant role in diagnosing common bile duct stones (CBDS). Currently, there are no studies to detect CBDS by using the deep learning (DL) model in MRCP. This study aimed to use the DL model You Only Look Once version 5 (YOLOv5) to diagnose CBDS in MRCP images and verify its validity compared to the accuracy of radiologists. By collecting the thick-slab MRCP images of patients diagnosed with CBDS, 4 submodels of YOLOv5 were used to train and validate the performance. Precision, recall rate, and mean average precision (mAP) were used to evaluate model performance. Analyze possible reasons that may affect detection accuracy by validating MRCP images in 63 CBDS patients and comparing them with radiologist detection accuracy. Calculate the correctness of YOLOv5 for detecting one CBDS and multiple CBDS separately. The precision of YOLOv5l (0.970) was higher than that of YOLOv5x (0.909), YOLOv5m (0.874), and YOLOv5s (0.939). The mAP did not differ significantly between the 4 submodels, with the following results: YOLOv5l (0.942), YOLOv5x (0.947), YOLO5s (0.927), and YOLOv5m (0.946). However, in terms of training time, YOLOv5s was the fastest (4.8 h), detecting CBDS in only 7.2 milliseconds per image. In 63 patients the YOLOv5l model detected CBDS with an accuracy of 90.5% compared to 92.1% for radiologists, analyzing the difference between the positive group successfully identified and the unidentified negative group not. The incorporated variables include common bile duct diameter > 1 cm (p =.560), combined gallbladder stones (p =.706), maximum stone diameter (p =.057), combined cholangitis (p =.846), and combined pancreatitis (p =.656), and the number of CBDS (p =.415). When only one CBDS was present, the accuracy rate reached 94%. When multiple CBDSs were present, the recognition rate dropped to 70%. YOLOv5l is the model with the best results and is almost as accurate as the radiologist's detection of CBDS and is also capable of detecting the number of CBDS. Although the accuracy of the test gradually decreases as the number of stones increases, it can still be useful for the clinician's initial diagnosis. [ABSTRACT FROM AUTHOR]

Summary: This paper proposes a multi‐loads capacitive power transfer (CPT) system based on a single relay plate for railway monitoring systems. The proposed system can supply power wirelessly to the monitoring system on the trackside and train carriages simultaneously to eliminate traditional power cables connection and prevent frequent battery replacement. Unlike the traditional multiple loads CPT systems, the proposed system uses only one relay plate, which is more stable and uncomplicated considering the coupler installation space and moving dynamically in the railway system. The proposed system adopts a CL‐LCLC‐CL compensation network to achieve a load‐independent output. The limitation of the charging load quantity is given in detail considering the coupler voltage stress distribution. An experimental prototype with three loads is also built to verify the effectiveness of the proposed system. Experimental results show that the proposed system achieves wireless power transfer to multiple loads simultaneously with two loads on the receiver and one on the repeater side. The load‐independent property is also achieved when two loads are removed. The maximum experimental efficiency is about 87.13%. [ABSTRACT FROM AUTHOR]