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.

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 β-Sialon Grain-Reinforced AlO-Based Composite Ceramic Tool Materials.

A kind of multiscale β-sialon grain-reinforced AlO matrix composite ceramic tool material, named ASN, was prepared and studied. For the ASN, β-sialon (molecular formula: SiAlON) 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.

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.

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.

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.

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.

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).

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.

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.