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Purpose: To intelligently diagnose whether there is bladder outlet obstruction (BOO) in female with decent detrusor contraction ability by focusing on urodynamic study (UDS) data. Materials and Methods: We retrospectively reviewed the UDS data of female patients during urination. Eleven easily accessible urinary flow indicators were calculated according to the UDS data of each patient during voiding period. Eight diagnosis models based on back propagation neural network with different input feature combination were constructed by analyzing the correlations between indicators and lower urinary tract dysfunction labels. Subsequently, the stability of diagnostic models was evaluated by five-fold cross-validation based on training data, while the performance was compared on test dataset. Results: UDS data from 134 female patients with a median age of 51 years (range, 27–78 years) were selected for our study. Among them, 66 patients suffered BOO and the remaining were normal. Applying the 5-fold cross-validation method, the model with the best performance achieved an area under the receiver operating characteristic curve (AUC) value of 0.949±0.060 using 9 UDS input features. The accuracy, sensitivity, and specificity for BOO diagnosis model in the testing process are 94.4%, 100%, and 89.3%, respectively. Conclusions: The 9 significant indicators in UDS were employed to construct a diagnostic model of female BOO based on machine learning algorithm, which performs preferable classification accuracy and stability.

In this study, plasma nitriding and multi-arc ion plating techniques were employed to enhance the load-bearing capacity of the TC4 alloy. The tribological properties were characterized, and the mechanisms were discussed in detail. Subsequently, the tribological properties of the coating enhanced with MoS2 were then evaluated, and the results indicated that the plasma nitriding treatment, which exhibited optimal friction performance, resulted in the formation of a nitrided layer with a thickness of 98 μm on the surface of the TC4 alloy, thereby significantly improving its mechanical properties. Furthermore, the TiN coating samples treated with plasma nitriding demonstrated superior mechanical properties, achieving the highest hardness value (20 GPa), high load-carrying capacity (58 N) and the lowest wear rate (9.16 × 10−6 mm3·N−1·m−1). Moreover, the tribological properties of MoS2 deposited on the surface of the PN-2/TiN sample were significantly enhanced, which can be attributed to the synergistic effect of the excellent load-bearing characteristics of the plasma nitriding treatment and the wear resistance of the TiN layer. This study investigates the factors contributing to the superior tribological performance of the PN-2/TiN sample and the extended friction lifetime of the PN-2/TiN/MoS2 sample. The composite coating provides a new method to improve the anti-friction of soft metals, especially titanium alloys, and is expected to be applied in the aerospace field.

In order to address the issues of image quality degradation and distortion that arise in the context of video transmission coding and decoding, a method based on an enhanced version of CycleGAN is put forth. The lightweight attention module is integrated into the residual block of the generator module structure, thereby facilitating the extraction of image details and motion compensation. Furthermore, the perceptual function LPIPS loss is increased to align the image restoration effect more closely with human perception. Additionally, the network training method is modified, and the original image is divided into 128 × 128 small blocks for training, thus enhancing the network’s accuracy in restoring details. The experimental results demonstrate that the algorithm attains an average PSNR value of 30.1147 on the publicly accessible YUV sequence dataset, YUV Trace Dataset, which is a 9.02% enhancement compared to the original network. Additionally, the LPIPS value reaches 0.2639, representing a 10.42% reduction, and effectively addresses the issue of image quality deterioration during transmission.

In a Magnetically Coupled Resonant Wireless Power Transfer (MCR-WPT) system, the magnetic coupling coil is one of the key factors that determines the system’s output power, transmission efficiency, anti-offset capability, and so on. This article proposes a coil parameter optimization method for a wireless power transfer system based on crowding distance division and adaptive genetic operators. Through optimizing the design of decision variables, such as the numbers of transmitting and receiving coil turns, the spacings between transmitting and receiving coil turns, the inner radii of the transmitting and receiving coils, and the vertical distance of the coil, the best transmission performance can be achieved. This study improves the NSGA-II algorithm through proposing a genetic operator algorithm for average crowding and high crowding populations based on adaptive operators, as well as a genetic operator algorithm for low crowding populations based on information entropy. These improved algorithms avoid problems inherent to traditional genetic operators such as fixed genetic proportions, do not easily cause the algorithm to fall into a local optimal solution, and show better convergence in the ZDT1–ZDT3 test functions. The optimization design method in this article is not only independent of commercial software such as ANSYS Maxwell 2021 R1, but can also significantly improve the calculation speed compared with traditional simulation software.

In recent years, video data have increased in size, which results in enormous transmission pressure. Rate control plays an important role in stabilizing video stream transmissions by balancing the rate and distortion of video compression. To achieve high-quality videos through low-bandwidth transmission, video multi-scale-based end-to-end rate control is proposed. First, to reduce video data, the original video is processed using multi-scale bicubic downsampling as the input. Then, the end-to-end rate control model is implemented. By fully using the temporal coding correlation, a two-branch residual-based network and a two-branch regression-based network are designed to obtain the optimal bit rate ratio and Lagrange multiplier λ for rate control. For restoring high-resolution videos, a hybrid efficient distillation SISR network (HEDS-Net) is designed to build low-resolution and high-resolution feature dependencies, in which a multi-branch distillation network, a lightweight attention LCA block, and an upsampling network are used to transmit deep extracted frame features, enhance feature expression, and improve image detail restoration abilities, respectively. The experimental results show that the PSNR and SSIM BD rates of the proposed multi-scale-based end-to-end rate control are −1.24% and −0.50%, respectively, with 1.82% rate control accuracy.

Heterostructured materials show great potential to enhance the specific capacity, rate performance and cycling lifespan of lithium-ion batteries owing to their unique interfaces, robust architectures, and synergistic effects. Herein, a polypyrrole (PPy)-coated nanotube-like Mo3S4/CoMo2S4 heterostructure is prepared by the hydrothermal and subsequent in situ polymerization methods. The well-designed nanotube-like structure is beneficial to relieve the serious volume changes and facilitate the infiltration of electrolytes during the charge/discharge process. The Mo3S4/CoMo2S4 heterostructure could effectively enhance the electrical conductivity and Li+ transport kinetics owing to the refined energy band structure and the internal electric field at the heterostructure interface. Moreover, the conductive PPy-coated layer could inhibit the obvious volume expansion like a firm armor and further avoid the pulverization of the active material and aggregation of generated products. Benefiting from the synergistic effects of the well-designed heterostructure and PPy-coated nanotube-like architecture, the prepared Mo3S4/CoMo2S4 heterostructure delivers high reversible capacity (1251.3 mAh g−1 at 300 mA g−1), superior rate performance (340.3 mAh g−1 at 5.0 A g−1) and excellent cycling lifespan (744.1 mAh g−1 after 600 cycles at a current density of 2.0 A g−1). Such a design concept provides a promising strategy towards heterostructure materials to enhance their lithium storage performances and boost their practical applications.

According to the intelligent development needs of railway operation and maintenance, turnout maintenance also needs an efficient and intelligent means of detection. It is the main method used to measure the access depth of static contact manually. In order to change the disadvantages of the low efficiency and strong subjectivity of traditional schemes, a low-complexity accurate ranging algorithm of the Mask RCNN is proposed to measure the on–off working parts. Firstly, the Mask RCNN and an interactive iterative method are used to segment the region of interest accurately twice. Secondly, the graph distortion is corrected according to the vertex mapping principle. Finally, the accurate actual distance is calculated through fitting the linear distance transformation equation. Through the secondary segmentation and correction algorithm, the accurate calculation of a small target is completed. The experimental results show that the algorithm can accurately measure the distance of different working parts; the average processing time is 0.8 s/amplitude and the measurement error is ±1 mm.

Listeria monocytogenes (LM) is a pathogenic bacterium which can release 3-hydroxy-2-butanone (3H-2B) as a biological indicator. We report a high-performance 3H-2B gas sensing strategy for the selective detection of LM. This strategy is realized by n-CdO/n-SnO _2 hetero-nanofibers with controllable compositions, synthesized via a facile one-step electrospinning method. The tailored morphologies and microstructures of CdO/SnO _2 nanofibers were systematically characterized by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). With the introduction of CdO into SnO _2 nanofibers, x-ray diffraction (XRD) and x-ray photoelectron spectroscopy (XPS) were performed to investigate the effects of crystal phases and elemental states on the 3H-2B sensing properties. According to the gas sensing results, the variation of Cd/Sn molar ratios has a great influence on the 3H-2B sensing properties of CdO/SnO _2 nanofibers. The maximum response (45) to 5 ppm 3H-2B is found for 5 mol% CdO/SnO _2 nanofibers at 260 °C. Meanwhile, 5 mol% CdO/SnO _2 nanofibers exhibit a short response/recovery time (9 s/5 s), outstanding stability, and discriminative selectivity to 3H-2B. The enhanced sensing performance is mainly attributed to the synergy between the resistance modulation of n-CdO/n-SnO _2 heterojunctions and the doping effect of Cd ^2+ ions.