Hardening of Dental Gold-Copper Alloys
X-ray diffraction studies of several proprietary dental gold alloys demonstrated that hardening probably is a dual mechanism of precipitation and order-hardening. Lattice parameter measurements showed that the ordered structure was AuCu. In addition, it was shown that maximum hardness occurs at about 75% full order.
Ageing behaviour in a dental low-gold alloy with high copper content
Phase transformation behaviour in a dental low-gold alloy with high copper content during continuous heating was investigated by hardness tests, electrical resistivity measurements, X-ray diffraction, scanning and transmission electron microscopies. Two kinds of solution treatment conditions (at 873 K and 1073 K) followed by iced-brine quench, represented different ageing behaviours. Although subsequent anisothermal annealing produced same phase separation of face-centred cubic disordered and ordered (Cu3Au) phases in both specimens, the specimen quenched from 1073 K had already been hardened by a spinodal decomposition. © 1998 Chapman & Hall
Research on Fracture Recognition in Well Logging Images: Adversarial Learning with Attention
Semantic recognition of fractures in well logging images is vital for engineers to implement oil and gas exploration. An essential approach to accomplishing the object is to adopt deep learning based on convolutional neural networks. However, due to the lack of annotated labels in well logging images, it is scarcely available to directly train the semantic segmentation network. In this paper, we explore a domain shift model attempting to achieve domain adaptation from one annotated dataset to our target well logging images. This model's core is to utilize adversarial learning, including generator and discriminator, which can prompt the model to generate fracture segmentation similar to the source domain in the target domain. For enhancing the domain adaptive model further, an attention module is introduced, which can suppress redundant noise in semantic segmentation results. We demonstrate that our proposed model performs well by extensive tests and ablation experiments in the ultrasonic well logging images.