Study on Grinding-Affected Layer of Outer-Ring Inner Raceway of Tapered Roller Bearing.

In the grinding of bearing raceways, the coupling effect between grinding force and heat in the contact area between the grinding wheel and the workpiece causes changes in the material structure and mechanical properties of the raceway surface layer, which can lead to the formation of a grinding-affected layer. The grinding-affected layer has a significant impact on the service performance and fatigue life of bearings. In order to improve the ground surface quality of the outer-ring inner raceway of tapered roller bearings and optimize the processing parameters, this paper presents a study on the grinding-affected layer. A finite element simulation model for grinding the outer-ring inner raceway of the tapered roller bearing was established. The grinding temperature field was simulated to predict the affected-layer thickness during raceway grinding. The correctness of the model was verified through grinding experiments using the current industrial process parameters of bearing raceway grinding. The research results indicate that the highest grinding temperature of the outer-ring inner raceway of the tapered roller bearing is located near the center of the grinding arc area on the thin end edge. As the workpiece speed and grinding depth decrease, the highest grinding temperature decreases, and the dark layer thickness of the grinding-affected layer decreases or even does not occur. The research results can provide theoretical guidance and experimental reference for grinding the raceway of tapered roller bearings.

Automatic Extrinsic Calibration of 3D LIDAR and Multi-Cameras Based on Graph Optimization.

In recent years, multi-sensor fusion technology has made enormous progress in 3D reconstruction, surveying and mapping, autonomous driving, and other related fields, and extrinsic calibration is a necessary condition for multi-sensor fusion applications. This paper proposes a 3D LIDAR-to-camera automatic calibration framework based on graph optimization. The system can automatically identify the position of the pattern and build a set of virtual feature point clouds, and can simultaneously complete the calibration of the LIDAR and multiple cameras. To test this framework, a multi-sensor system is formed using a mobile robot equipped with LIDAR, monocular and binocular cameras, and the pairwise calibration of LIDAR with two cameras is evaluated quantitatively and qualitatively. The results show that this method can produce more accurate calibration results than the state-of-the-art method. The average error on the camera normalization plane is 0.161 mm, which outperforms existing calibration methods. Due to the introduction of graph optimization, the original point cloud is also optimized while optimizing the external parameters between the sensors, which can effectively correct the errors caused during data collection, so it is also robust to bad data.

Detection of Lower Body for AGV Based on SSD Algorithm with ResNet.

Detection of human lower body provides an implementation idea for the automatic tracking and accurate relocation of automatic vehicles. Based on traditional SSD and ResNet, this paper proposes an improved detection algorithm R-SSD for human lower body detection, which utilizes ResNet50 instead of VGG16 to improve the feature extraction level of the model. According to the application of acquisition equipment, the model input resolution is increased to 448 × 448 and the model detection range is expanded. Six feature maps of the updated resolution network are selected for detection and the lower body image dataset is clustered into five categories for aspect ratio, which are evenly distributed to each feature detection map. The experimental results show that the model R-SSD detection accuracy after training reaches 85.1% mAP. Compared with the original SSD, the detection accuracy is improved by 7% mAP. The detection confidence in practical application reaches more than 99%, which lays the foundation for subsequent tracking and relocation for automatic vehicles.

[Ginsenoside Rg_1 protects PC12 cells against Aß-induced injury through promotion of mitophagy by PINK1/parkin activation].

Amyloid ß-protein(Aß) deposition in the brain is directly responsible for neuronal mitochondrial damage of Alzheimer's disease(AD) patients. Mitophagy, which removes damaged mitochondria, is a vital mode of neuron protection. Ginsenoside Rg_1(Rg_1), with neuroprotective effect, has displayed promising potential for AD treatment. However, the mechanism underlying the neuroprotective effect of Rg_1 has not been fully elucidated. The present study investigated the effects of ginsenoside Rg_(1 )on the autophagy of PC12 cells injured by Aß_(25-35) to gain insight into the neuroprotective mechanism of Rg_1. The autophagy inducer rapamycin and the autophagy inhi-bitor chloroquine were used to verify the correlation between the neuroprotective effect of Rg_1 and autophagy. The results showed that Rg_1 enhanced the viability and increased the mitochondrial membrane potential of Aß-injured PC12 cells, while these changes were blocked by chloroquine. Furthermore, Rg_(1 )treatment increased the LC3Ⅱ/Ⅰ protein ratio, promoted the depletion of p62 protein, up-regulated the protein levels of PINK1 and parkin, and reduced the amount of autophagy adaptor OPTN, which indicated the enhancement of autophagy. After the silencing of PINK1, a key regulatory site of mitophagy, Rg_1 could not increase the expression of PINK1 and parkin or the amount of NDP52, whereas it can still increase the LC3Ⅱ/Ⅰ protein ratio and promote the depletion of OPTN protein which indicated the enhancement of autophagy. Collectively, the results of this study imply that Rg_1 can promote autophagy of PC12 cells injured by Aß, and may reduce Aß-induced mitochondrial damage by promoting PINK1-dependent mitophagy, which may be one of the key mechanisms of its neuroprotective effect.

Panax notoginseng saponins protect PC12 cells against Aß induced injury via promoting parkin-mediated mitophagy.

ETHNOPHARMACOLOGICAL RELEVANCE: Panax notoginseng (Burk) F. H. Chen is a well-known traditional Chinese medicine with a long history and is widely used in the treatment of cerebrovascular disease. Panax notoginseng saponins (PNS) are the main active ingredients in Panax notoginseng (Burk) F. H. Chen, and its injection is used to treat nerve damage caused by cerebral ischemia and other conditions. PNS is thought to alleviate cognitive impairment in patients with Alzheimer's disease; however, its mechanism of action is unclear. AIM OF THE STUDY: We elucidated the role of PNS in attenuating cellular mitochondrial damage caused by amyloid ß (Aß) protein and in protecting cell viability from the perspective of regulating autophagy. By investigating the effects of PNS on the targets regulating mitophagy, we wanted to reveal the autophagy related mechanism by which PNS attenuated Aß damage in neuronal cells. MATERIALS AND METHODS: The effect of PNS on the mitochondrial membrane potential of Aß-injured PC12 cells was detected using flow cytometry, which reflected the alleviating effect of PNS on mitochondrial damage. Using mRFP-GFP-LC3-transfected PC12 cells, the effect of PNS on cellular autophagy flux was observed using laser confocal microscopy. Formation of the intracellular autophagosome was observed using transmission electron microscopy, which reflected the activation of autophagy by PNS. The siPINK1 lentivirus was used to silence the PINK1 gene in PC12 cells to obtain siPINK1-PC12 cells. The effects of PNS on the expression of the PINK1 gene and on the autophagy-related proteins LC3II/Ⅰ, p62, PINK1, parkin, NDP52, and OPTN were observed to reveal the possible targets of PNS in regulating autophagy. RESULTS: After PNS treatment, the viability of Aß-injured PC12 cells improved and the mitochondrial membrane potential was restored. PNS treatment significantly enhanced the autophagy flux of damaged cells and increased the levels of LC3II/Ⅰ protein and decreased p62 protein, while significantly improving the structure and mitochondrial morphology of PC12 cells injured by Aß. These changes led to more autophagosomes wrapping around the damaged mitochondria and promoting the depletion of OPTN, a mitophagy receptor. After silencing the PINK1 gene, PNS could not alter the PINK1 gene and protein levels, but could still increase LC3II/Ⅰ, decrease p62 and OPTN, and significantly increase the amount of parkin. CONCLUSIONS: PNS could enhance the autophagic activity of cells, alleviate mitochondrial damage caused by Aß injury, and protect the activity of PC12 cells. It is possible that enhanced autophagy was achieved by promoting the recruitment of parkin protein to the mitochondrial receptors in a non-PINK1-dependent manner.

Antifriction Mechanism of Longitudinal Vibration-Assisted Insertion in DBS.

Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease. The insertion of brain tissue is an important procedure that affects the whole operation and the sequela. During the insertion process, the friction between the tissue and the needle shaft is the main factor affecting the degree of tissue damage and the accuracy of target location. Vibration-assisted needle insertion has been shown to reduce friction during needle insertion into biological tissue. LuGre model is a friction model that includes coulomb friction and viscous friction between two contact surfaces and accurately describes the Stribeck effect. This paper studies the influence of longitudinal vibration on the friction force during needle insertion. Based on LuGre model, the influence of longitudinal vibration parameters on friction force is discussed. Through experiments on porcine brain tissue and gel phantom, the friction force during insertion and the positive pressure of tissue against the needle under different vibration parameters were investigated. The experiment showed that the vibration can change the friction force by affecting the equivalent friction coefficient and the positive pressure of tissue against the needle. The equivalent friction coefficient showed a specific trend with the change of vibration parameters, while the positive pressure does not change with the vibration parameters.

Exploring the Mechanism of Panax notoginseng Saponins against Alzheimer's Disease by Network Pharmacology and Experimental Validation.

BACKGROUND: Panax notoginseng saponins (PNS) have been used for neurodegenerative disorders such as cerebral ischemia and Alzheimer's disease (AD). Although increasing evidences show the neuron protective effects of PNS, the vital compounds and their functional targets remain elusive. To explore the potential functional ingredients of PNS for the AD treatment and their molecular mechanisms, an in vitro neuron injured model induced by Aß was investigated, and the potential mechanism was predicted by network pharmacology approach and validated by molecular biology methods. METHODS: Network pharmacology approach was used to reveal the relationship between ingredient-target disease and function-pathway of PNS on the treatment of AD. The active ingredients of PNS were collected from TCMSP, PubChem database, and literature mining in PubMed database. DrugBank and GeneCards database were used to predict potential targets for AD. The STRING database was performed to reveal enrichment of these target proteins, protein-protein interactions, and related pathways. Networks were visualized by utilizing Cytoscape software. The enrichment analysis was performed by the DAVID database. Finally, neuroprotective effect and predictive mechanism of PNS were investigated in an in vitro AD model established by Aß 25-35-treated PC12 cells. RESULTS: An ingredient-target disease and function-pathway network demonstrated that 38 active ingredients were derived from PNS modulated 364 common targets shared by PNS and AD. GO and KEGG analysis, further clustering analysis, showed that mTOR signaling targets were associated with the neuroprotective effects of PNS. In Aß-treated PC12 cells, PNS treatment improved neuroprotective effect, including mTOR inhibition and autophagy activation. CONCLUSIONS: Collectively, the protective effects of PNS on AD-neuron injury are related to the inhibition of mTOR and autophagy activation.

Effect of vibration frequency on frictional resistance of brain tissue during vibration-assisted needle insertion.

Deep brain stimulation (DBS) is an effective treatment for Parkinson's disease. The cannula insertion process plays an important role in DBS. The friction force during needle insertion influences the precision of the insertion and the degree of damage to the brain tissue. This paper proposes a method of longitudinal vibration assisted insertion to reduce the friction during insertion and improve the effects of the insertion. Cannulas were inserted into twenty eight pig brains at multiple frequencies and fixed amplitudes, and the resulting friction force was measured. On this basis, the LuGre model was used to analyze the friction force trend under vibration-assisted conditions. The frictional forces of vibration-assisted insertion with frequencies ranging from 200-1200 Hz and an amplitude of 1 µm were measured. The results show that the friction between the needle shaft and the tissue is smaller with vibration than without vibration. In this experiment, the friction is reduced by up to 24.43%. The friction force trend of vibration-assisted insertion conforms to the simulation results of the LuGre model.

Fault Diagnosis of Loader Gearbox Based on an ICA and SVM Algorithm.

When a part of the loader's gearbox fails, this can lead to equipment failure due to the complex internal structure and the interrelationship between the parts. Therefore, it is imperative to research an efficient strategy for transmission fault diagnosis. In this study, the non-contact characteristics of noise diagnosis using sound intensity probes were used to collect noise signals generated under gear breaking conditions. The independent component analysis (ICA) technique was applied for feature extraction from the original data and to reduce the correlation between the signals. The correlation coefficient between the independent components and the source data was used as the input parameters of the support vector machine (SVM) classifier. The separation of the independent components was achieved by MATLAB simulation. The misdiagnosis rate was 5% for 40 sets of test data. A 13-point test platform for noise testing of the loader gearbox was built according to Chinese national standards. Source signals under the normal and fault conditions were analyzed separately by ICA and SVM algorithms. In this case, the misdiagnosis rate was 7.5% for the 40 sets of experimental test data. This proved that the proposed method could effectively realize fault classification and recognition.

A Study on Noise Reduction of Gear Pumps of Wheel Loaders Based on the ICA Model.

In order to reduce the noise level of wheel loaders caused by gear pumps and realize environmentally sustainable development, the noise generation mechanism of a gear pump was studied, and the influence of flow pulsation and gear impact on noise was analyzed. In order to reduce the interference of other noise sources on the noise level of the gear pump, a noise test rig was established. The mixed noise signals obtained from the rig test were separated using the ICA model. The ICA model includes the following algorithms: The fast Fourier transform (FFT), independent component analysis (ICA) and inverse fast Fourier transform (IFFT). Some theories about the influence of the teeth number and teeth profile on noise were analyzed by theory and simulation. A noise reduction strategy was proposed by increasing the teeth numbers and modifying the teeth profile of the gear pump. The tests results showed that the noise values of the external and the driver's ear of the wheel loader were reduced to 1 and 2.2 dB (A), respectively. This proves the effectiveness of the optimization scheme of gear pump noise reduction.

Avoiding the Health Hazard of People from Construction Vehicles: A Strategy for Controlling the Vibration of a Wheel Loader.

The vibration control of a construction vehicle must be carried out in order to meet the aims of sustainable environmental development and to avoid the potential human health hazards. In this paper, based on market feedback, the driver seat vibration of a type of wheel loader in the left and right direction, is found to be significant over a certain speed range. In order to find abnormal vibration components, the order tracking technique (OTT) and transmission path analysis (TPA) were used to analyze the vibration sources of the wheel loader. Through this analysis, it can be seen that the abnormal vibration comes from the interaction between the tire tread and the road, and this is because the vibration was amplified by the cab mount, which was eventually transmitted to the cab seat. Finally, the seat vibration amplitudes were decreased by up to 50.8%, after implementing the vibration reduction strategy.