Health Status Recognition Method for Rotating Machinery Based on Multi-Scale Hybrid Features and Improved Convolutional Neural Networks.

Rotating machinery is susceptible to harsh environmental interference, and fault signal features are challenging to extract, leading to difficulties in health status recognition. This paper proposes multi-scale hybrid features and improved convolutional neural networks (MSCCNN) health status identification methods for rotating machinery. Firstly, the rotating machinery vibration signal is decomposed into intrinsic modal components (IMF) using empirical wavelet decomposition, and multi-scale hybrid feature sets are constructed by simultaneously extracting time-domain, frequency-domain and time-frequency-domain features based on the original vibration signal and the intrinsic modal components it decomposes. Secondly, using correlation coefficients to select features sensitive to degradation, construct rotating machinery health indicators based on kernel principal component analysis and complete health state classification. Finally, a convolutional neural network model (MSCCNN) incorporating multi-scale convolution and hybrid attention mechanism modules is developed for health state identification of rotating machinery, and an improved custom loss function is applied to improve the superiority and generalization ability of the model. The bearing degradation data set of Xi'an Jiaotong University is used to verify the effectiveness of the model. The recognition accuracy of the model is 98.22%, which is 5.83%, 3.30%, 2.29%, 1.52%, and 4.31% higher than that of SVM, CNN, CNN + CBAM, MSCNN, and MSCCNN + conventional features, respectively. The PHM2012 challenge dataset is used to increase the number of samples to validate the model effectiveness, and the model recognition accuracy is 97.67%, which is 5.63%, 1.88%, 1.36%, 1.49%, and 3.69% higher compared to SVM, CNN, CNN + CBAM, MSCNN, and MSCCNN + conventional features methods, respectively. The MSCCNN model recognition accuracy is 98.67% when validated on the degraded dataset of the reducer platform.

Trajectory Planning for Coal Gangue Sorting Robot Tracking Fast-Mass Target under Multiple Constraints.

Aiming at the problems of grab failure and manipulator damage, this paper proposes a dynamic gangue trajectory planning method for the manipulator synchronous tracking under multi-constraint conditions. The main reason for the impact load is that there is a speed difference between the end of the manipulator and the target when the manipulator grabs the target. In this method, the mathematical model of seven-segment manipulator trajectory planning is constructed first. The mathematical model of synchronous tracking of dynamic targets based on a time-minimum manipulator is constructed by taking the robot's acceleration, speed, and synchronization as constraints. The model transforms the multi-constraint-solving problem into a single-objective-solving problem. Finally, the particle swarm optimization algorithm is used to solve the model. The calculation results are put into the trajectory planning model of the manipulator to obtain the synchronous tracking trajectory of the manipulator. Simulation and experiments show that each joint of the robot's arm can synchronously track dynamic targets within the constraint range. This method can ensure the synchronization of the position, speed, and acceleration of the moving target and the target after tracking. The average position error is 2.1 mm, and the average speed error is 7.4 mm/s. The robot has a high tracking accuracy, which further improves the robot's grasping stability and success rate.

High Quality Coal Foreign Object Image Generation Method Based on StyleGAN-DSAD.

Research on coal foreign object detection based on deep learning is of great significance to safe, efficient, and green production of coal mines. However, the foreign object image dataset is scarce due to collection conditions, which brings an enormous challenge to coal foreign object detection. To achieve augmentation of foreign object datasets, a high-quality coal foreign object image generation method based on improved StyleGAN is proposed. Firstly, the dual self-attention module is introduced into the generator to strengthen the long-distance dependence of features between spatial and channel, refine the details of the generated images, accurately distinguish the front background information, and improve the quality of the generated images. Secondly, the depthwise separable convolution is introduced into the discriminator to solve the problem of low efficiency caused by the large number of parameters of multi-stage convolutional networks, to realize the lightweight model, and to accelerate the training speed. Experimental results show that the improved model has significant advantages over several classical GANS and original StyleGAN in terms of quality and diversity of the generated images, with an average improvement of 2.52 in IS and a decrease of 5.80 in FID for each category. As for the model complexity, the parameters and training time of the improved model are reduced to 44.6% and 58.8% of the original model without affecting the generated images quality. Finally, the results of applying different data augmentation methods to the foreign object detection task show that our image generation method is more effective than the traditional methods, and that, under the optimal conditions, it improves APbox by 5.8% and APmask by 4.5%.

Multi-Arm Global Cooperative Coal Gangue Sorting Method Based on Improved Hungarian Algorithm.

The existing multi-manipulator sorting method for gangue that utilizes a multi-task allocation strategy is not satisfactory. The single manipulator working space is fixed, lowering the cooperation degree between the manipulators and leading to a low sorting rate. Therefore, this paper proposes a multi-manipulator cooperative sorting method that can work globally. First, a benefit function based on the sorting time and quality of the gangue is constructed by combining the gangue flow information and the manipulator state. The time parameter is obtained via the manipulator's dynamic target tracking trajectory planning algorithm based on PID control. Secondly, the benefits matrix is standardized and updated many times to improve the Hungarian algorithm to achieve task allocation, and the initial solution with priority is obtained. Finally, the solutions are analyzed and processed cooperatively in order of priority. The conflicts between multiple robotic arms are eliminated through task cooperation and trajectory cooperation until the sorting task that the robot arm can execute is obtained from the allocation results. Experiments involving different sorting methods were completed on a multi-arm coal and gangue sorting experimental robot platform. The experimental results show that the sorting efficiency of the proposed method is about 10% and 20% higher than that of the fixed space dynamic and designated space fixed points methods, respectively, under different belt speeds. This method can guarantee system benefits, effectively implements cooperative control of multi-manipulator operations in the whole area, and improves the efficiency of coal gangue sorting.

Effects of catalpol on the activity of human liver cytochrome P450 enzymes.

1. Catalpol possesses numerous pharmacological activities, and however, little data available for the effects of catalpol on the activity of human liver cytochrome P450 (CYP) enzymes. 2. This study investigates the inhibitory effects of catalpol on the main human liver CYP isoforms. In this study, the inhibitory effects of catalpol on the eight human liver CYP isoforms 1A2, 2A6, 2E1, 2D6, 2C9, 2C19, 2C8 and 3A4 were investigated in human liver microsomes. 3. The results indicated that catalpol could inhibit the activity of CYP3A4, CYP2E1 and CYP2C9, with IC50 values of 14.27, 22.4 and 14.69 µM, respectively, but those other CYP isoforms were not affected. Enzyme kinetic studies showed that catalpol was not only a noncompetitive inhibitor of CYP3A4, but also a competitive inhibitor of CYP2E1 and CYP2C9, with Ki values of 7.40, 10.75 and 7.37 µM, respectively. In addition, catalpol is a time-dependent inhibitor for CYP3A4, with maximum inactivation (kinact) and 50% maximum inactivation (KI) values of 0.02 min-1 and 1.86 µM, respectively. 4. The in vitro studies of catalpol with CYP isoforms suggest that catalpol has the potential to cause pharmacokinetic drug interactions with other co-administered drugs metabolized by CYP3A4, CYP2E1 and CYP2C9. Further in vivo studies are needed in order to evaluate the significance of this interaction.

Effect of Mir-122 on Human Cholangiocarcinoma Proliferation, Invasion, and Apoptosis Through P53 Expression.

BACKGROUND Bile duct carcinoma is a common digestive tract tumor with high morbidity and mortality. As a kind of important non-coding RNA, microRNA (miR) plays an important role in post-transcriptional regulation. MiR-122 is the most abundant miR in the liver. Multiple studies have shown that miR-122 level is reduced in a variety of liver tumors and can be used as a specific marker for liver injury. P53 is a classic tumor suppressor gene that can induce tumor cell apoptosis through various pathways. Whether miR-122 affects p53 in bile duct carcinoma still needs investigation. MATERIAL AND METHODS miR inhibitor or mimics was transfected to bile duct carcinoma cells to evaluate its function on proliferation, invasion, apoptosis, and p53 expression. RESULTS MiR-122 overexpression reduced cell invasion and migration ability, and inhibited cell apoptosis and p53 expression. Inhibiting miR-122 caused the opposite results. CONCLUSIONS Upregulating miR-122 can suppress bile duct carcinoma cell proliferation and induce apoptosis. MiR-122 could be used as a target for bile duct carcinoma treatment, which provides a new strategy for cholangiocarcinoma patients.

Ground-based airglow imaging interferometer. Part 2: forward model and inverse method.

The ground-based airglow imaging interferometer (GBAII) observes the nighttime airglow of the O2(0-1) 867.7 nm line, peaked at 94 km altitude, to measure the upper atmospheric wind and temperature field. Its forward model, a code package in interactive data language (IDL), is developed to simulate the expected imaging interference fringes. It includes eight modules to simulate the light source, the atmospheric radiation transmission, the wide-angle Michelson interferometer, the interference filter, the optical system decay function, the responsivity, the imaging CCD, and the noises. The inverse method is also developed for obtaining the rest phase calibration, temperature, and wind. By means of both theoretical tools, we carry out a comparison of theoretical results with a field observation case. The apparent quantities J(1-p) from the forward model has the deviation of 1.5%-2.5% compared with that from the observation image. The temperature falls mainly in the range of 167-196 K with the precision of 2 K. The zonal and meridional winds are mainly in the region of 5.1 to 46.5 m/s and 12.5 to 48.3 m/s respectively, with errors of 13.2 to 21.5 m/s. The consistent trends between the observation results and standard models (MSISE90 and HWM93) suggest that the forward model and inverse method are suitable for GBAII.

Ground-based airglow imaging interferometer. Part 1: instrument and observation.

A ground-based airglow imaging interferometer (GBAII) is proposed to measure simultaneously the temperature and wind in the mesopause region by using airglow emissions of the O2(0-1) band. Since it employs a wide angle Michelson interferometer with a large air gap, combined with the rotational temperature measurement, both the phase and spectral information can be obtained from the imaging results. Based on the optimization and calibrations for the optical system in the laboratory, we developed and assembled a prototype of a GBAII, and carried out one observation at the observatory of Xi'an University of Technology on 12 June 2012. The observed temperatures fall mainly on the range of 167-196 K, while both the zonal and meridional winds faintly show the feature of half-day oscillation. The consistent trends between the observation results and the standard atmospheric models suggest that the GBAII has achieved our basic design goals.

Partially light-controlled imager based on liquid crystal plate and image intensifier for aurora and airglow measurement.

In order to obtain information both of aurora and airglow in one image by the same detector, a PLCI based on liquid crystal plate LCP and super second-generation image intensifier SSGII is proposed in this research. The detection thresholds of the CCD for aurora and airglow are calculated. For the detectable illumination range of 10(4)-10(-2) lx, the corresponding electron count is 1.57×10(5) - 0.2 for every pixel of CCD. The structure and work principle of the PLCI are described. An LC is introduced in the front of CCD to decrease the intensities of aurora in overexposure areas by means of controlling transmittances pixel by pixel, while an image intensifier is set between the LC and CCD to increase the intensity of the weak airglow. The modulation transfer function MTF of this system is calculated as 0.391 at a Nyquist frequency of 15 lp/mm. The curve of transmittance with regard to gray level for the LC is obtained by calibration experiment. Based on the design principle, the prototype is made and used to take photos of objects under strong light greater than 2×10(5) lx. The clear details of [symbols: see text] presented in the image indicate that the PLCI can greatly improve the imaging quality. The theoretical calculations and experiment results prove that this device can extend the dynamic range and it provides a more effective method for upper atmospheric wind measurement.

Increased Expression of miR-487b Is Associated With Poor Prognosis and Tumor Progression of HBV-Related Hepatocellular Carcinoma.

BACKGROUND: Increasing evidence has demonstrated the involvement of microRNAs in the pathogenesis of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). The aims of this study were to analyze whether miR-487b can be used as a diagnostic and prognostic biomarker for HBV-related HCC and to explore its effect on the biological function of HCC. METHODS: The expression levels of miR-487b in the serum of all subjects were measured by real-time quantitative fluorescence polymerase chain reaction. The diagnostic value of miR-487b in serum was assessed using the receiver operating characteristic (ROC) curve. The relationship between miR-487b and the clinical data of patients was analyzed using the chi-square test. The prognostic value of miR-487b in HCC was assessed by Cox regression analysis and Kaplan-Meier survival. Moreover, CCK-8 and Transwell assays were performed to investigate the effect of miR-487b on HBV-related HCC function. RESULTS: Our data indicated that miR-487b in HCC patients was significantly higher than in chronic hepatitis B (CHB) patients and healthy controls. Meanwhile, the ROC curve showed that miR-487b had high specificity and sensitivity in the diagnosis of HBV-related HCC. MiR-487b can significantly distinguish between HCC patients and healthy controls and can differentiate HCC patients from CHB patients. Cox regression analysis showed that miR-487b was an independent risk factor. Overexpression of miR-487b was associated with Tumor Node Metastasis stage stage and Barcelona Clinic Liver Cancer stage in HCC patients. Cell function experiments demonstrated that upregulated miR-487b promoted cell proliferation, migration, and invasion. CONCLUSIONS: Combined the results of the current study demonstrate that the upregulation of serum miR-487b may serve as a promising noninvasive diagnostic biomarker for HBV-related HCC.