Simulation Study on Residual Stress Distribution of Machined Surface Layer in Two-Step Cutting of Titanium Alloy.

Ti-6Al-4V titanium alloy is known as one of the most difficult metallic materials to machine, and the machined surface residual stress distribution significantly affects properties such as static strength, fatigue strength, corrosion resistance, etc. This study utilized finite element software Abaqus 2020 to simulate the two-step cutting process of titanium alloy, incorporating stages of cooling, unloading, and de-constraining of the workpiece. The chip morphology and cutting force obtained from orthogonal cutting tests were used to validate the finite element model. Results from the orthogonal cutting simulations revealed that with increasing cutting speed and the tool rake angle, the residual stress undergoes a transition from compressive to tensile stress. To achieve greater residual compressive stress during machining, it is advisable to opt for a negative rake angle coupled with a lower cutting speed. Additionally, in two-step machining of titanium alloy, the initial cutting step exerts a profound influence on the subsequent cutting step, thereby shortening the evolution time of the Mises stress, equivalent plastic strain, and stiffness damage equivalent in the subsequent cutting step. These results contribute to optimizing titanium alloy machining processes by providing insights into controlling residual stress, ultimately enhancing product quality and performance of structural part of titanium alloy.

Laser Processing and Multi-Energy Field Manufacturing of High-Performance Materials.

The laser is one of the major inventions of the 20th century, along with atomic energy, the computer and semiconductors [...].

Preparation of In Situ Growth Multiscale ß-Sialon Grain-Reinforced Al2O3-Based Composite Ceramic Tool Materials.

A kind of multiscale ß-sialon grain-reinforced Al2O3 matrix composite ceramic tool material, named ASN, was prepared and studied. For the ASN, ß-sialon (molecular formula: Si4Al2O2N6) was synthesized in situ by a hot-pressing and solid-solution reaction process. A total of six samples were prepared at varying sintering temperatures and holding times under vacuum conditions. The solid solution reaction mechanism of ß-sialon, the phase composition, mechanical properties, microstructure, and strengthening and toughening mechanisms of the composite ASN were investigated. As a result, within the experimental parameters, an optimal ASN tool material was obtained under a pressure of 32 MPa and at a temperature of 1550 °C for 20 min. The tested mechanical properties of the optimal sample were as follows: flexural strength 997 ± 59 MPa, fracture toughness 6.4 ± 0.3 MPa·m1/2, Vickers hardness 18.2 ± 0.4 GPa, and relative density 98.1 ± 0.2%. According to crystal defect theory, the solid solution reaction mechanism of in-situ-synthesized ß-sialon in an Al2O3 matrix involves a double mechanism of unequivalence (or hetero-valence) and interstitial filling. The multiscale ß-sialon grains mainly consisted of four grains, which were elongated ß-sialon grains with a diameter of 0.3-0.4 µm and an aspect ratio of 6-9, elongated ß-sialon grains with a diameter of 70 nm and an aspect ratio of 10, ß-sialon whiskers with a diameter of 0.2 µm and an aspect ratio of 12-15, and intragranular ß-sialon whiskers with a diameter of 70 nm. The mechanical properties were improved due to strengthening and toughening mechanisms, such as mixed structure mode (intergranular and transgranular), elongated grain pullout, interface bonding, crack reflection, pinning, and bridging.

Microstructure and Properties of WC/Ni-Based Laser-Clad Coatings with Different WC Content Values.

The purpose of this work is to investigate the effect of the WC content on the surface characteristics and nanoindentation behaviors of WC/Ni-based composite laser-clad coatings. Four NiCrSiBC coatings with WC wt% of 30%, 40%, 50%, and 60%, respectively, were clad on carbon steel substrates using a laser. The morphologies and phase compositions of four clad coatings were comparatively observed. In addition, the hardness and elastic modulus values of the four coatings were measured and quantitatively calculated. As a result, with the increase in WC, the coating grains were more refined. Meanwhile, cracks and WC particle breakage occurred in the 50-60% WC coatings, whereas this was not found in the 30-40% WC coatings. When the WC content increased from 40% up to 50%, the coating hardness and elastic modulus significantly increased. However, a further increase in WC from 50% to 60% did not result in considerable improvement in coating quality but considerably worsened the coating's cracking behavior instead. Therefore, for WC/Ni-based composite coatings, a threshold exists for the WC content, and this value was 50% within the experimental scope of this study.

Application of Deep Learning on the Prognosis of Cutaneous Melanoma Based on Full Scan Pathology Images.

Introduction: The purpose of this study is to use deep learning and machine learning to learn and classify patients with cutaneous melanoma with different prognoses and to explore the application value of deep learning in the prognosis of cutaneous melanoma patients. Methods: In deep learning, VGG-19 is selected as the network architecture and learning model for learning and classification. In machine learning, deep features are extracted through the VGG-19 network architecture, and the support vector machine (SVM) model is selected for learning and classification. Compare and explore the application value of deep learning and machine learning in predicting the prognosis of patients with cutaneous melanoma. Result: According to receiver operating characteristic (ROC) curves and area under the curve (AUC), the average accuracy of deep learning is higher than that of machine learning, and even the lowest accuracy is better than that of machine learning. Conclusion: As the number of learning increases, the accuracy of machine learning and deep learning will increase, but in the same number of cutaneous melanoma patient pathology maps, the accuracy of deep learning will be higher. This study provides new ideas and theories for computational pathology in predicting the prognosis of patients with cutaneous melanoma.

Prediction and verification of the effect of psoriasis on coronary heart disease based on artificial neural network.

Background and objectives: Psoriasis is an independent risk factor for coronary heart disease. It is important for predicting the complications of coronary heart disease in patients with psoriasis. Methods: In this study, related cases were collected from the case system of Qingdao University, and commonly used laboratory indicators were extracted. Artificial neural network (ANN) and logistics regression analysis were used to learn to distinguish psoriasis patients, coronary heart disease patients, and psoriasis patients with coronary heart disease. We identified independent risk factors for coronary heart disease in psoriasis patients that exacerbate coronary heart disease symptoms in patients with psoriasis. Findings: Analysis shows that the accuracy of the ANN model was higher than 79%. It was determined that age, chlorinated, phosphorus, magnesium, low-density lipoprotein, triglycerides, high density lipoprotein and total cholesterol are independent risk factors for coronary heart disease in patients with psoriasis. Similarly, gender, age, chlorinated, magnesium, triglycerides, and high density lipoprotein are risk factors that exacerbate coronary heart disease symptoms in patients with psoriasis. Interpretation: The presented approach is a valuable tool for identifying psoriasis patients, coronary heart disease patients, and psoriasis patients with coronary heart disease. It can also serve as a support tool clinicians in the diagnostic process, by providing an outstanding support in the diagnostics prevention of coronary heart disease in psoriasis.

Surface Properties of Medium-Entropy Alloy Coatings Prepared through a Combined Process of Laser Cladding and Ultrasonic Burnishing.

The preparation of functional coatings on metal substrates is an effective method to enhance the surface of steel structures with good serviceability in applications for engineering parts. The objective of this research is to analyze the surface properties of two sorts of medium-entropy alloy (MEA) coatings prepared by laser cladding. After cladding, the two prepared coatings were strengthened by ultrasonic burnishing (UB) treatment. Cladding coating samples before and after being UB-treated were comparatively tested in order to investigate the process effects of UB. When compared with corresponding untreated coating samples, the roughness values of the two sorts of UB-treated samples were decreased by 88.7% and 87.6%, the porosities were decreased by 63.8% and 73.4%, and the micro-hardness values were increased by 41.7% and 32.7%, respectively. Furthermore, the two sorts of UB-treated coating samples exhibited better mechanical properties and wear resistance than corresponding untreated samples.

CCNB1 and CCNB2 involvement in the pathogenesis of psoriasis: a bioinformatics study.

OBJECTIVE: The cell cycle-related proteins cyclin B1 (CCNB1) and cyclin B2 (CCNB2) are potentially involved in the underlying mechanisms of psoriasis. The present study aimed to explore this possibility using bioinformatics approaches. METHODS: CCNB1 and CCNB2 protein levels were evaluated in 14 psoriasis patients and five healthy controls by enzyme-linked immunosorbent assays, and their mRNA levels were evaluated using data from four publicly available datasets (GSE53552, GSE41664, GSE14905, and GSE13355). Comparison of high- and low-expressing groups were performed to reveal CCNB1- and CCNB2-related differentially expressed genes, which were then assessed based on gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Correlation analyses between CCNB1 and CCNB2 levels and immune infiltration, as well as typical targets of psoriasis, were also performed. RESULTS: Overall, 12 CCNB1 and CCNB2 common immune-related targets potentially involved in psoriasis were identified. These could regulate the cell cycle of through multiple pathways. In addition, CCNB1 and CCNB2 were found to potentially support the release of key molecular targets of psoriasis through the regulation of mast cell activation and macrophage polarization. CONCLUSIONS: These findings suggest that CCNB1 and CCNB2 may represent valuable molecular biomarkers of psoriasis, contributing to its onset and progression.

Bioinformatic Analysis and Translational Validation of Psoriasis Candidate Genes for Precision Medicine.

Background: Psoriasis is a recurrent, chronic, inflammation- and immune-mediated skin disease with multiple causative factors. However, the genetic markers associated with recurrence have not yet been fully elucidated. Accordingly, in this study, we aimed to identify markers associated with the recurrence of psoriasis. Methods: We analyzed differentially expressed genes to determine which targets were associated with the recurrence of psoriasis and used these data to construct a protein-protein interaction network using Cytoscape software. The results were then validated by analysis of core targets using Gene Expression Omnibus (GEO) datasets and clinical samples. Functional enrichment analysis was used to explore the potential mechanisms mediating the recurrence of psoriasis. Results: We screened out six core targets that played important roles in recurrence of psoriasis, and validation of GEO datasets and clinical samples showed that the expression levels of five core targets were higher in patients with psoriasis than in healthy individuals. Functional enrichment analysis revealed that the cell cycle and oocyte meiosis signaling pathways were involved in the recurrence of psoriasis. Conclusion: Our findings provided insights into the mechanisms mediating the onset and recurrence of psoriasis.

Mining database for the clinical significance and prognostic value of CBX family in skin cutaneous melanoma.

BACKGROUND: Skin cutaneous melanoma (SKCM) is one of the most aggressive malignancies with high invasiveness. Chromobox (CBX) family are involved in the regulation of the tumorigenesis, progression, invasion, and apoptosis of many malignancies. METHODS: The clinical significance and prognostic value of CBX family in SKCM were analyzed via a series of databases, including ONCOMINE, GEPIA, UALCAN, TIMER, GSCALite, DAVID 6.8, GeneMANIA, and LinkedOmics. RESULTS: We found that the level of CBX2, CBX3, CBX5, and CBX6 was upregulated while the level of CBX7 and CBX8 was downregulated in tumor tissues in SKCM. Moreover, the mRNA expression of CBX1 and CBX2 was significantly associated with the pathological stage in SKCM. Prognosis analysis revealed that SKCM patients with high CBX5 level and low CBX7 level had a poor prognosis. Immune infiltrations analysis revealed that the expression of CBX family was associated with the abundance of certain immune cells in SKCM. We also found that CBX family were associated with the activation of cell cycle pathway and DNA damage response, and the inhibition of apoptosis pathway. Moreover, enrichment analysis revealed that CBX family and correlated genes were enriched in chromatin modification, PcG protein complex, transcription coactivator activity, protein binding, and RNA splicing. Several Kinase targets (ATM, CDK1, and PLK1) and miRNA targets (MIR-331, MIR-296, and MIR-496) of CBX family were also identified. CONCLUSION: Our study may uncover CBX family-associated molecular mechanisms involved in the tumorigenesis and progression of SKCM and provide additional choice for the prognosis and therapy biomarker for SKCM.