Diagnosis of ball bearing with various degree rolling element defects based on local mean decomposition

This paper aims to explore fault characteristics extraction method to deal with the light and severe rolling element faults based on local mean decomposition (LMD) and Fourier transform (FT). The characteristics of LMD are studied by processing multi-component frequency modulation and amplitude modulation (FM-AM) signal, which are usually used to describe the bearing fault signals. Based on the simulation analysis, the envelope spectrum method called LMD-FT is used to deal with the vibration signals of rolling balling bearing with various element faults. Moreover, the fault features extracted by LMD are compared with those obtained from conventional Hilbert transform (HT). The results demonstrate that LMD method is an effective way to identify the characteristics of rolling element defect generated at the initial stage

散料在锥仓中的静压接触状态与影响因素

Finite element models, which employ the Drucker-Prager yield criterion, have been developed to simulate the static contact statuses between conical silos and granular materials in 3 forms: the near contact, the sliding contact and the sticking contact. Contact conditions are established when 2 separated surfaces touch at normal direction while maintaining tangential relative movement. In general physical meaning, the surfaces in contact status have the following characteristics: 1) No penetration between each other; 2) The normal pressure and the tangent friction force may be transferred during contact; 3) Generally the normal pulling force cannot be transferred when surface separation occurs. Due to the symmetric property of conical structures, simplified two-dimensional contacting simulations are carried out in this paper, nonlinear finite element software ANSYS is used and the contacting surfaces between granular materials and conical silos are defined with rigid-to-flexible surface-to-surface contact pair. The target surfaces of conical silos are modeled with TARGE169 element and the contact surfaces of granular materials are modeled with CONTA171 element. During finite element analysis, conical silos and granular materials are meshed with two-dimensional solid element, PLANE42. The static contact statuses are investigated with conical silos containing different granular materials. The silo geometries vary at a dip angle of 20°, 33.7° and 45°. Sunflower seeds, corn, coal, rounded gravel and wheat are selected as the granular materials. Results show that the mechanical properties of granular materials (including bulk density, elastic modulus, Poisson's ratio, dilation angle, internal friction angle, cohesion) and silo designs (especially dip angle) have significant effects on the contact statuses at the interface between conical silos and granular materials: 1) For various granular material, 3 contact statuses, i.e. the form of near contact, sliding contact and sticking contact, can be found between granular materials and conical silo walls; 2) The contact statuses between conical silos and granular materials do not depend on (or not mainly depend on) any mechanical property of granular materials. The contact statuses are a combined effect of all mechanical properties of granular materials. Those granular materials with very small dilation angle may have the near contact statuses. Those granular materials with higher cohesive force usually present a smaller sticking contact area, and those granular materials with higher elastic modulus and bulk density usually present a larger sticking contact area than those with opposite material properties; 3) With the decreasing of conical silo depth, the near contact area disappears, the sliding contact area decreases and the sticking contact area increases. 4) Under the sliding contact status, the friction energy dissipation is mainly due to the relative motion between contact surfaces. Under the sticking contact status, the friction energy dissipation is mainly due to the elastic deformation because of the contact. The greater the sticking contact area, the more difficultly the silo discharges. The greater the sliding contact area, the more seriously the silo internal surfaces could be damaged. Since larger sticking/sliding contact area inevitably causes unloading difficulties or friction damage, contact statuses between granular materials and conical silos should be optimized in the silos design in order to boost storage efficiency

HMGA1 variant IVS5-13insC is associated with insulin resistance and type 2 diabetes: an updated meta-analysis

Background: High-mobility group A1 (HMGA1) polymorphism has been suspected as a gene variant associated with type 2 diabetes (T2D). However, conflicting outcomes have been reported. Objective: This meta-analysis aimed to predict the association between the HMGA1 variant IVS5-13insC and T2D. Methods: Statistical analyses were performed using Stata/SE 12.0 software. Results: A total of 11 case-control studies in 6 articles were included. Results suggested that the HMGA1 variant IVS5-13insC was associated with an increased risk of insulin resistance (OR = 0.61, 95% CI 0.56 to 0.66, P < 0.0001), T2D (OR = 0.67, 95% CI 0.61 to 0.73, P < 0.0001), particularly for Caucasians with increased risks of T2D (OR = 0.56, 95% CI 0.49 to 0.65, P < 0.0001) compared with wild-type subjects. Conclusion: This meta-analysis indicated that the HMGA1 variant IVS5-13insC can be a risk factor of T2D development, particularly among Caucasians. Significant risks were also found (Asian: OR = 0.74, 95% CI: 0.63 to 0.86, P < 0.0001, Hispanic-American: OR = 0.81, 95% CI: 0.65 to 1.01, P < 0.0001) in non-Caucasian population. However, ethnical studies should be conducted to reveal whether the HMGA1 variant IVS5-13insC is associated with an increased risk of T2D.Keywords: HMGA1, type 2 diabetes, insulin resistance, variant, meta-analysis

EFFECT OF ILLUMINATION ON THE OBSTACLE-CROSSING BEHAVIORS OF ELDERLY WOMEN

The purpose of this study was to determine how illumination affect elderly women when stepping over obstacles. A motion capture system was used to collect the kinematics data of 15 elderly women. The results revealed that the obstacle-crossing behavior of elderly women were affected by the illumination. Compare to the high illumination condition, the elderly women decreased their toe distance and heel distance (

HMGA1 variant IVS5-13insC is associated with insulin resistance and type 2 diabetes: an updated meta-analysis

Background: High-mobility group A1 (HMGA1) polymorphism has been suspected as a gene variant associated with type 2 diabetes (T2D). However, conflicting outcomes have been reported. Objective: This meta-analysis aimed to predict the association between the HMGA1 variant IVS5-13insC and T2D. Methods: Statistical analyses were performed using Stata/SE 12.0 software. Results: A total of 11 case-control studies in 6 articles were included. Results suggested that the HMGA1 variant IVS5-13insC was associated with an increased risk of insulin resistance (OR = 0.61, 95% CI 0.56 to 0.66, P < 0.0001), T2D (OR = 0.67, 95% CI 0.61 to 0.73, P < 0.0001), particularly for Caucasians with increased risks of T2D (OR = 0.56, 95% CI 0.49 to 0.65, P < 0.0001) compared with wild-type subjects. Conclusion: This meta-analysis indicated that the HMGA1 variant IVS5-13insC can be a risk factor of T2D development, particularly among Caucasians. Significant risks were also found (Asian: OR = 0.74, 95% CI: 0.63 to 0.86, P < 0.0001, Hispanic-American: OR = 0.81, 95% CI: 0.65 to 1.01, P < 0.0001) in non-Caucasian population. However, ethnical studies should be conducted to reveal whether the HMGA1 variant IVS5-13insC is associated with an increased risk of T2D

A tree species classification model based on improved YOLOv7 for shelterbelts

Tree species classification within shelterbelts is crucial for shelterbelt management. The large-scale satellite-based and low-altitude drone-based approaches serve as powerful tools for forest monitoring, especially in tree species classification. However, these methods face challenges in distinguishing individual tree species within complex backgrounds. Additionally, the mixed growth of trees within protective forest suffers from similar crown size among different tree species. The complex background of the shelterbelts negatively impacts the accuracy of tree species classification. The You Only Look Once (YOLO) algorithm is widely used in the field of agriculture and forestry, ie., plant and fruit identification, pest and disease detection, and tree species classification in forestry. We proposed a YOLOv7-Kmeans++_CoordConv_CBAM (YOLOv7-KCC) model for tree species classification based on drone RGB remote sensing images. Firstly, we constructed a dataset for tree species in shelterbelts and adopted data augmentation methods to mitigate overfitting due to limited training data. Secondly, the K-means++ algorithm was employed to cluster anchor boxes in the dataset. Furthermore, to enhance the YOLOv7 backbone network’s Efficient Layer Aggregation Network (ELAN) module, we used Coordinate Convolution (CoordConv) replaced the ordinary 1×1 convolution. The Convolutional Block Attention Module (CBAM) was integrated into the Path Aggregation Network (PANet) structure to facilitate multiscale feature extraction and fusion, allowing the network to better capture and utilize crucial feature information. Experimental results showed that the YOLOv7-KCC model achieves a mean average [email protected] of 98.91%, outperforming the Faster RCNN-VGG16, Faster RCNN-Resnet50, SSD, YOLOv4, and YOLOv7 models by 5.71%, 11.75%, 5.97%, 7.86%, and 3.69%, respectively. The GFlops and Parameter values of the YOLOv7-KCC model stand at 105.07G and 143.7MB, representing an almost 5.6% increase in F1 metrics compared to YOLOv7. Therefore, the proposed YOLOv7-KCC model can effectively classify shelterbelt tree species, providing a scientific theoretical basis for shelterbelt management in Northwest China focusing on Xinjiang

Crosstalk between the CBM complex/NF-κB and MAPK/P27 signaling pathways of regulatory T cells contributes to the tumor microenvironment

Regulatory T cells (Tregs), which execute their immunosuppressive functions by multiple mechanisms, have been verified to contribute to the tumor microenvironment (TME). Numerous studies have shown that the activation of the CBM complex/NF-κB signaling pathway results in the expression of hypoxia-inducible factor-1 (HIF-1α) and interleukin-6 (IL-6), which initiate the TME formation. HIF-1α and IL-6 promote regulatory T cells (Tregs) proliferation and migration through the MAPK/CDK4/6/Rb and STAT3/SIAH2/P27 signaling pathways, respectively. IL-6 also promotes the production of HIF-1α and enhances the self-regulation of Tregs in the process of tumor microenvironment (TME) formation. In this review, we discuss how the crosstalk between the CARMA1–BCL10–MALT1 signalosome complex (CBM complex)/NF-κB and MAPK/P27 signaling pathways contributes to the formation of the TME, which may provide evidence for potential therapeutic targets in the treatment of solid tumors

A Novel 5-Enolpyruvylshikimate-3-Phosphate Synthase Shows High Glyphosate Tolerance in Escherichia coli and Tobacco Plants

A key enzyme in the shikimate pathway, 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) is the primary target of the broad-spectrum herbicide glyphosate. Identification of new aroA genes coding for EPSPS with a high level of glyphosate tolerance is essential for the development of glyphosate-tolerant crops. In the present study, the glyphosate tolerance of five bacterial aroA genes was evaluated in the E. coli aroA-defective strain ER2799 and in transgenic tobacco plants. All five aroA genes could complement the aroA-defective strain ER2799, and AM79 aroA showed the highest glyphosate tolerance. Although glyphosate treatment inhibited the growth of both WT and transgenic tobacco plants, transgenic plants expressing AM79 aroA tolerated higher concentration of glyphosate and had a higher fresh weight and survival rate than plants expressing other aroA genes. When treated with high concentration of glyphosate, lower shikimate content was detected in the leaves of transgenic plants expressing AM79 aroA than transgenic plants expressing other aroA genes. These results suggest that AM79 aroA could be a good candidate for the development of transgenic glyphosate-tolerant crops

The Molecular Signature Underlying the Thymic Migration and Maturation of TCRαβ+CD4+CD8- Thymocytes

BACKGROUND: After positive selection, the newly generated single positive (SP) thymocytes migrate to the thymic medulla, where they undergo negative selection to eliminate autoreactive T cells and functional maturation to acquire immune competence and egress capability. METHODOLOGY/PRINCIPAL FINDINGS: To elucidate the genetic program underlying this process, we analyzed changes in gene expression in four subsets of mouse TCRαβ(+)CD4(+)CD8(-) thymocytes (SP1 to SP4) representative of sequential stages in a previously defined differentiation program. A genetic signature of the migration of thymocytes was thus revealed. CCR7 and PlexinD1 are believed to be important for the medullary positioning of SP thymocytes. Intriguingly, their expression remains at low levels in the newly generated thymocytes, suggesting that the cortex-medulla migration may not occur until the SP2 stage. SP2 and SP3 cells gradually up-regulate transcripts involved in T cell functions and the Foxo1-KLF2-S1P(1) axis, but a number of immune function-associated genes are not highly expressed until cells reach the SP4 stage. Consistent with their critical role in thymic emigration, the expression of S1P(1) and CD62L are much enhanced in SP4 cells. CONCLUSIONS: These results support at the molecular level that single positive thymocytes undergo a differentiation program and further demonstrate that SP4 is the stage at which thymocytes acquire the immunocompetence and the capability of emigration from the thymus