Lateral single incision laparoscopic totally extraperitoneal hernioplasty (L-SILTEP) after laparoscopic radical prostatectomy: A rare case report with literature review.

INTRODUCTION: Single-incision laparoscopic totally extraperitoneal hernioplasty is a commonly used surgical procedure for the treatment of inguinal hernia. However, it is difficult to use traditional single incision laparoscopic totally extraperitoneal hernioplasty to treat inguinal hernia after laparoscopic radical prostatectomy. We successfully and smoothly cured a patient with left inguinal hernia after laparoscopic radical prostatectomy using lateral single incision laparoscopic totally extraperitoneal hernioplasty. CASE PRESENTATION: We report the case of a 70-year-old man who underwent laparoscopic radical prostatectomy 2 years earlier and had an evanescent mass in the left inguinal region for 1 month. DIAGNOSIS: On the basis of preoperative abdominal computed tomography and intraoperative findings, the patient was diagnosed with a left indirect inguinal hernia, and post-laparoscopic radical prostatectomy. INTERVENTIONS: The patient underwent lateral single incision laparoscopic totally extraperitoneal hernioplasty. OUTCOMES: The patient recovered well after the operation, and there were no postoperative complications or recurrence of inguinal hernia 3 months after the operation. CONCLUSION: For patients who have undergone laparoscopic radical prostatectomy, lateral single-incision laparoscopic totally extraperitoneal hernioplastycan be performed.

Influence of Martensite/Bainite Dual Phase-Content on the Mechanical Properties of EA4T High-Speed Axle Steel.

In this work, we have investigated the effect of martensite/bainite dual phase content on the mechanical properties of EA4T high-speed axle steel. For evaluation and control of the strength, ductility, and toughness of steel, the microstructure of lath martensite (LM) and granular bainite (GB) was clarified through an optical microscope (OM), electron backscatter diffraction (EBSD), and transmission electron microscopy (TEM). Besides, the tensile fracture morphology was studied by scanning electron microscopy (SEM). For this purpose, this study conducted a quantitative analysis of the LM and GB fractions using the Pro Imaging software-2018 of OM. The remarkable effect of the LM/GB structure on mechanical properties is discussed. The results have shown that by increasing the volume fraction of the GB structure, the LM structure is refined and its microhardness and strength are improved. Meanwhile, the micro strength of LM follows the Hall-Petch relationship with the lath martensite packet size. Subsequently, the mechanical property prediction model of EA4T steel based on the LM/GB content was established by regression analysis of all experiment dates. When the LM fraction in the steel is about 40-70%, a superior combination of strength, ductility, and toughness can be obtained in EA4T steel.

Spatial-Frequency Attention Network for Crowd Counting.

Counting the number of people in crowded scenarios is a crucial task in video surveillance and urban security system. Widely deployed surveillance cameras provide big data for training, a compelling deep learning-based counting network. However, large-scale variations in dense crowds are still not entirely solved. To address this problem, we propose a spatial-frequency attention network (SFANet) for crowd counting in this article. A bottleneck spatial attention module is built to emphasize features in various spatial locations and select a region containing individuals adaptively in the spatial domain. As a complementary, in the frequency domain, a multispectral channel attention module is adopted to obtain a more complete set of frequency components for representing each channel. The two attention modules are combined to focus on the discriminative region and suppress the misleading information by their mutual promotion. Experimental results on five benchmark crowd data sets demonstrate that the SFANet can achieve the state-of-the-art performance in terms of accuracy and robustness.

Multi-Focus Image Fusion Method for Vision Sensor Systems via Dictionary Learning with Guided Filter.

Vision sensor systems (VSS) are widely deployed in surveillance, traffic and industrial contexts. A large number of images can be obtained via VSS. Because of the limitations of vision sensors, it is difficult to obtain an all-focused image. This causes difficulties in analyzing and understanding the image. In this paper, a novel multi-focus image fusion method (SRGF) is proposed. The proposed method uses sparse coding to classify the focused regions and defocused regions to obtain the focus feature maps. Then, a guided filter (GF) is used to calculate the score maps. An initial decision map can be obtained by comparing the score maps. After that, consistency verification is performed, and the initial decision map is further refined by the guided filter to obtain the final decision map. By performing experiments, our method can obtain satisfying fusion results. This demonstrates that the proposed method is competitive with the existing state-of-the-art fusion methods.

[Working Temperature Predication of Artificial Heart Based on Neural Network].

The purpose of this paper is to achieve a measurement of temperature prediction for artificial heart without sensor, for which the research briefly describes the application of back propagation neural network as well as the optimized, by genetic algorithm, BP network. Owing to the limit of environment after the artificial heart implanted, detectable parameters out of body are taken advantage of to predict the working temperature of the pump. Lastly, contrast is made to demonstrate the prediction result between BP neural network and genetically optimized BP network, by which indicates that the probability is 1.84% with the margin of error more than 1%.

[Hemodynamic analysis of a centrifugal blood pump].

This paper built the mathematical model of a centrifugal blood pump, which was designed by ourselves, combined it with that of the human cardiovascular system and simulated the coupling system using Matlab. Then we set up the experiment platform, linked the blood pump to mock human cardiovascular system in case of three-stage heart failure, and measured aortic pressure and flow under different speed. The comparison between experiment results and simulation results not only indicates the coupling model is correct and the blood pump works well, but also shows that with the increase of blood pump speed, the pulsation of aortic pressure and flow will be reduced, this situation will affect the structure and function of blood vessels.