Efficient Prediction of Stability Boundaries in Milling Considering the Variation of Tool Features and Workpiece Materials.

Theoretical stability analysis is a significant approach to predicting chatter-free machining parameters. Accurate milling stability predictions highly depend on the dynamic properties of the process system. Therefore, variations in tool and workpiece attributes will require repeated and time-consuming experiments or simulations to update the tool tip dynamics and cutting force coefficients. Considering this problem, this paper proposes a transfer learning framework to efficiently predict the milling stabilities for different tool-workpiece assemblies through reducing the experiments or simulations. First, a source tool is selected to obtain the tool tip frequency response functions (FRFs) under different overhang lengths through impact tests and milling experiments on different workpiece materials conducted to identify the related cutting force coefficients. Then, theoretical milling stability analyses are developed to obtain sufficient source data to pre-train a multi-layer perceptron (MLP) for predicting the limiting axial cutting depth (aplim). For a new tool, the number of overhang lengths and workpiece materials are reduced to design and perform fewer experiments. Then, insufficient stability limits are predicted and further utilized to fine-tune the pre-trained MLP. Finally, a new regression model to predict the aplim values is obtained for target tool-workpiece assemblies. A detailed case study is developed on different tool-workpiece assemblies, and the experimental results validate that the proposed approach requires fewer training samples for obtaining an acceptable prediction accuracy compared with other previously proposed methods.

Fault Diagnosis Method for Imbalanced Data Based on Multi-Signal Fusion and Improved Deep Convolution Generative Adversarial Network.

The realization of accurate fault diagnosis is crucial to ensure the normal operation of machines. At present, an intelligent fault diagnosis method based on deep learning has been widely applied in mechanical areas due to its strong ability of feature extraction and accurate identification. However, it often depends on enough training samples. Generally, the model performance depends on sufficient training samples. However, the fault data are always insufficient in practical engineering as the mechanical equipment often works under normal conditions, resulting in imbalanced data. Deep learning-based models trained directly with the imbalanced data will greatly reduce the diagnosis accuracy. In this paper, a diagnosis method is proposed to address the imbalanced data problem and enhance the diagnosis accuracy. Firstly, signals from multiple sensors are processed by the wavelet transform to enhance data features, which are then squeezed and fused through pooling and splicing operations. Subsequently, improved adversarial networks are constructed to generate new samples for data augmentation. Finally, an improved residual network is constructed by introducing the convolutional block attention module for enhancing the diagnosis performance. The experiments containing two different types of bearing datasets are adopted to validate the effectiveness and superiority of the proposed method in single-class and multi-class data imbalance cases. The results show that the proposed method can generate high-quality synthetic samples and improve the diagnosis accuracy presenting great potential in imbalanced fault diagnosis.

Analysis of Correlation Between Coronary Heart Disease and Genetic Polymorphism Detected by Gold Magnetic Nanoparticles Chromatography.

It aimed to explore the correlation of Glu504Lys locus mutation of aldehyde dehydrogenase-2 (ALDH2) with coronary heart disease (CHD) based on gold magnetic nanoparticles (GMNPs) chromatography and amplification refractory mutation system-PCR (ARMS-PCR). 120 CHD patients admitted to the cardiovascular Department of Wenling First People's Hospital affiliated to Wenzhou Medical University from December 2020 to December 2021 were selected as Case group and 80 non-CHD patients admitted during the same period were selected as Ctrl group. The venous blood and indexes of Total Cholesterol (TC), Triglyceride (TG), Low Density Lipoprotein Cholesterol (LDL-C), High Density Lipoprotein Cholesterol (HDL-C), and Fasting Blood Glucose (FBS) were collected. The ARMS-PCR GMNPs chromatography based on ARMS-PCR and immunochromatography assay was adopted to detect gene polymorphism of ALDH2. Correlation between ALDH2 gene polymorphism and risk factors of CHD was analyzed via logistic regression. In contrast to Ctrl group, the genotypes of GG, GA, and AA in Case group were evidently different (P < 0.05), and the frequency of A allelic gene was obviously increased (P < 0.05). Under the dominant model, frequency of GA + AA genotype in Case group was remarkably higher in contrast to Ctrl group (P < 0.05). Under the recessive model, there was no obvious difference in genotype frequency between two groups. In contrast to Ctrl group, TC, LDL-C, and FBS in Case group were notably increased (P < 0.05), while HDL-C was notably decreased (P < 0.05). The distribution frequency of abnormal LDL-C, HDL-C, and FBS in Case group was notably higher in contrast to Ctrl group (P < 0.05). LDL-C and FBS had no obvious effect on the genotypes and frequency distribution of alleles in CHD patients. However, the frequency distribution of genotypes of GA and AA and A allelic gene in patients with abnormal HDL-C was notably lower in contrast to those with normal HDL-C (P < 0.05). Logistic regression analysis showed that abnormal HDC-C with A allelic gene were independent risk factors for CHD (P = 0.001, OR = 1.934). The gene polymorphism of Glu504Lys locus of ALDH2 was closely related to the pathogenesis of CHD, A allelic gene may be a susceptibility gene for CHD, and patients with abnormal HDC-C and carried A allelic gene had relatively higher incidence of CHD.

Design and performance analysis of 3D-printed stiffness gradient femoral scaffold.

Studies on 3D-printed porous bone scaffolds mostly focus on materials or structural parameters, while the repair of large femoral defects needs to select appropriate structural parameters according to the needs of different parts. In this paper, a kind of stiffness gradient scaffold design idea is proposed. Different structures are selected according to the different functions of different parts of the scaffold. At the same time, an integrated fixation device is designed to fix the scaffold. Finite element method was used to analyze the stress and strain of homogeneous scaffolds and the stiffness gradient scaffolds, and the relative displacement and stress between stiffness gradient scaffolds and bone in the case of integrated fixation and steel plate fixation. The results showed that the stress distribution of the stiffness gradient scaffolds was more uniform, and the strain of host bone tissue was changed greatly, which was beneficial to the growth of bone tissue. The integrated fixation method is more stable, less stress and evenly distributed. Therefore, the integrated fixation device combined with the design of stiffness gradient can repair the large femoral bone defect well.

Mechanical and biological properties of the micro-/nano-grain functionally graded hydroxyapatite bioceramics for bone tissue engineering.

Functionally graded materials (FGM) open the promising approach for bone tissue repair. In this study, a novel functionally graded hydroxyapatite (HA) bioceramic with micrograin and nanograin structure was fabricated. Its mechanical properties were tailored by composition of micrograin and nanograin. The dynamic mechanical analysis (DMA) indicated that the graded HA ceramics had similar mechanical property compared to natural bones. Their cytocompatibility was evaluated via fluorescent microscopy and MTT colorimetric assay. The viability and proliferation of rabbit bone marrow mesenchymal stem cells (BMSCs) on ceramics indicated that this functionally graded HA ceramic had better cytocompatibility than conventional HA ceramic. This study demonstrated that functionally graded HA ceramics create suitable structures to satisfy both the mechanical and biological requirements of bone tissues.

[Effects of demineralized bone matrix modified with type II cadherin ectodomain on adhesion and osteogenic differentiation of BMSCs].

UNLABELLED: OBJECTIVE; To evaluate the adhesion, proliferation and osteogenic differentiation of rabbit BMSCs after cultured on freeze-dried demineralized bone matrix (FDBM) modified with type II cadherin ectodomain (Cad-II). METHODS: BMSCs isolated from 10 Japanese white rabbits (male and female, 4-week-old, 0.61-0.88 kg) were cultured. The second generation of BMSCs (cell density 1 x 10(6)/mL) were seeded onto the Cad-II modified allogenic FDBM (experimental group) and only FDBM (control group) respectively, and then cocultured in vitro. The densities of seeded cells, the adhesion rate and their ALP activity were measured. The complex was observed through inverted phase contrast microscope and scanning electron microscope to evaluate the interaction between cells and FDBM. Another group of second generation of BMSCs (cell density 5 x 10(5)/mL) were seeded onto the Cad-II modified FDBM (experimental group) and only FDBM (control group) respectively, and then cocultured in vitro too. The ALP activity and osteocalcin immunohistochemical was measured. RESULTS: There was no significant difference in cell proliferation between experimental group and control group. The adhesion rate of cells in the experimental group was 87.41% +/- 5.19%, higher than that in the the control group 35.56% +/- 1.75% (P < 0.01); the densities of seeded cells reached 5.0 x 10(5), showing significant difference compared with the control group (2.6 x 10(4), P < 0.05). Inverted phase contrast microscope showed that in the experimental group, more cultured BMSCs pasted in the hole and edge of the scaffold than that in the control group. HE staining showed the densities of seeded cells in the experimental group was higher than that in the control group. Scanning electron microscope showed that in the experimental group, a lot of cultured BMSCs adhered, spreaded in the scaffold, in the control group only a few BMSCs unevenly distributed in the scaffold. After 7 days of culture, the cultured BMSCs on modified FDBM expressed higher ALP activity; after 14 days of culture, the ALP activity (29.33 +/- 1.53) was higher than that cultured on unmodified FDBM (18.31 +/- 1.32), the positive rates of osteocalcin were 83% +/- 7% in the experimental group and 56% +/- 7% in the control group, showing significant difference (P < 0.01). CONCLUSION: Cad-II enhanced cell adhesion to FDBM and promoted BMSCs differentiate to osteoblast, but no obvious effects were observed in cell proliferation.