Effects of Cooling Rate and Component on the Microstructure and Mechanical Properties of Mg–Zn–Y Alloys

The microstructure and mechanical properties of Mg–6Zn–1Y and Mg–6Zn–3Y(wt%) alloys under different cooling rates were investigated. The results show that the second dendrite arm spacing(SDAS) of Mg–6Zn–1Y and Mg–6Zn–3Y is reduced by 32 and 30% with increasing cooling rates(Rc) from 10.2 to 23 K/s, which can be predicted using a empirical model of SDAS=68 R 0:45:45cand SDAS=73 R 0c, respectively. The compressive strength of both alloys increases with increasing the cooling rate, which is attributed to the increase of volume fraction(Vf) of secondary phases under high cooling rate. The interaction of the cooling rate and component with SDAS has been theoretically analyzed using interdependence theory.     

Process and joint quality of ultrasonic vibration enhanced friction stir lap welding

In order to improve the process effectiveness and joint quality, ultrasonic vibrations were integrated with friction stir lap welding. Effect of ultrasonic exertion on the process and joint quality of AA 6061-T6 were investigated. Upon ultrasonic exertion, joints owned larger effective lap width, shorter hooks and improved strength. Weld fracture mode changed from a ductile–brittle mixed mode to a more ductile mode while the fracture path shifted from lap interface to beyond the stir zone. Material flow and interface defects were characterised using lap welded dissimilar aluminium alloy joints. Ultrasonic vibration improved the material flow and reduced the interfacial defects. Variations in failure load of joints were found in accordance with the variations in material flow and interfacial defects.     

Theoretical Prediction of Chiral 3D Hybrid Organic–Inorganic Perovskites

Hybrid organic–inorganic perovskites (HOIPs), in particular 3D HOIPs, have demonstrated remarkable properties, including ultralong charge‐carrier diffusion lengths, high dielectric constants, low trap densities, tunable absorption and emission wavelengths, strong spin–orbit coupling, and large Rashba splitting. These superior properties have generated intensive research interest in HOIPs for high‐performance optoelectronics and spintronics. Here, 3D hybrid organic–inorganic perovskites that implant chirality through introducing the chiral methylammonium cation are demonstrated. Based on structural optimization, phonon spectra, formation energy, and ab initio molecular dynamics simulations, it is found that the chirality of the chiral cations can be successfully transferred to the framework of 3D HOIPs, and the resulting 3D chiral HOIPs are both kinetically and thermodynamically stable. Combining chirality with the impressive optical, electrical, and spintronic properties of 3D perovskites, 3D chiral perovskites is of great interest in the fields of piezoelectricity, pyroelectricity, ferroelectricity, topological quantum engineering, circularly polarized optoelectronics, and spintronics.     

Role of Co in formation of Ni-Ti clusters in maraging stainless steel

The effect of Co addition on the formation of Ni-Ti clusters in maraging stainless steel was studied by three dimensional atom probe (3DAP) and first-principles calculation. The cluster analysis based on the maximum separation approach showed an increase in size but a decrease in density of Ni-Ti clusters with increasing the Co content. The first-principles calculation indicated weaker Co-Ni (Co-Ti) interactions than Co-Ti (Fe-Ti) interactions, which should be the essential reason for the change of distribution characteristics of Ni-Ti clusters in bcc Fe caused by Co addition.     

基于图像增强的去雾快速算法的FPGA实现

基于图像增强方法，本文提出了一种使用亮度映射的图像去雾快速算法。此算法通过调整室外多雾场景图像的对比度，提高了雾中物体的辨识度。算法的复杂度低、处理延迟小，实时性高，利于FPGA的实现。实现时不需外存储器，延时为ns级，并提供了强度调节接口，以适应较广的应用环境。     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.

     

Design and fabrication of an on-chip micro flow cytometer with integrated micro-lens

Microsystem Technologies - In this paper, the design and fabrication of an on-chip micro flow cytometer chip with integrated micro-lens with a size of...     

A dynamic SVR–ARMA model with improved fruit fly algorithm for the nonlinear fiber stretching process

Natural Computing - The fiber stretching process plays the key role in the process of fiber production and its effects is measured by the stretching ratio. The stretching ratio is determined by the...