GPT-Prompt Controlled Diffusion for Weakly-Supervised Semantic Segmentation

Weakly supervised semantic segmentation (WSSS), aiming to train segmentation models solely using image-level labels, has received significant attention. Existing approaches mainly concentrate on creating high-quality pseudo labels by utilizing existing images and their corresponding image-level labels. However, the quality of pseudo labels degrades significantly when the size of available dataset is limited. Thus, in this paper, we tackle this problem from a different view by introducing a novel approach called GPT-Prompt Controlled Diffusion (GPCD) for data augmentation. This approach enhances the current labeled datasets by augmenting with a variety of images, achieved through controlled diffusion guided by GPT prompts. In this process, the existing images and image-level labels provide the necessary control information, where GPT is employed to enrich the prompts, leading to the generation of diverse backgrounds. Moreover, we integrate data source information as tokens into the Vision Transformer (ViT) framework. These tokens are specifically designed to improve the ability of downstream WSSS framework to recognize the origins of augmented images. Our proposed GPCD approach clearly surpasses existing state-of-the-art methods. This effect is more obvious when the amount of available data is small, demonstrating the effectiveness of our method

Symmetry-breaking-induced giant Stark effect in 2D Janus materials

Symmetry breaking generally induce exotic physical properties, particularly for low-dimensional materials. Herein we demonstrate that symmetry breaking induces a giant Stark effect in 2D Janus materials using group IV-V monolayers with a four-atom-layer structure as a model system, which are constructed by Ge and As element substitution of symmetrical SnSb monolayer. A linear giant Stark effect is found in Janus semiconductor monolayers, as verified by the band gap variation up to 134 meV of Sn2SbAs monolayer, which is 30 times larger than that of SnSb monolayer (4 meV) when the applied electric field is increased from -0.30 to 0.30 V/{\AA}. By considering the induced electronic field, we propose a generalized and effective formula that efficiently determines the band gap variation owing to Stark effect. The calculated results from proposed formula are well agreement with those from DFT-HSE06 functional. The giant Stark effect is originated from the large spatial separation of centers of the conduction band minimum and valence band maximum states of Janus structure due to its intrinsic potential gradient. The wide-range tuning of band gap under electronic field shows potential applications of 2D Janus materials in optoelectronic devices.Comment: 10 pages, 5 figure

Comparison of the Solid Solution Properties of Mg-RE (Gd, Dy, Y) Alloys with Atomistic Simulation

Molecular dynamic simulations have been performed to study the solid solution mechanism of Mg100-xREx (RE=Gd,Dy,Y, x=0.5,1,2,3,4  at.%). The obtained results reveal that the additions of Gd, Dy and Y increase the lattice constants of Mg-RE alloys. Also the axis ratio c/a remains unchanged with increase in temperature, restraining the occurrence of nonbasal slip and twinning. Furthermore, it is confirmed that bulk modulus of Mg alloys can be increased remarkably by adding the Gd, Dy, Y, especially Gd, because the solid solubility of Gd in Mg decrease sharply with temperature in comparison with Dy and Y. Consequently, the addition of the RE can enhance the strength of Mg-based alloys, which is in agreement with the experimental results

Investigation on Cutting Power of Wood–Plastic Composite Using Response Surface Methodology

For the sake of improving the benefit of enterprise by reducing energy waste. RSM (response surface methodology) was used to investigated the cutting power of wood–plastic composite at different cutting conditions (rake angle, cutting speed, depth of cut, and flank wear). Based on the experimental results, a cutting power model with a high degree of fitting was developed, which can be used to predict cutting power and optimal cutting conditions. Meanwhile, the effects of rake angle, cutting speed, depth of cut, and flank wear and their interaction on the cutting power were probed by analysis of variance, and the significant terms were determined. Finally, the optimal cutting condition was obtained as follows: rake angle of 10°, cutting speed of 300 m/min, depth of cut of 1.5 mm, and flank wear of 0.1 mm. This parameter combination is suggested to be used for industrial manufacturing of wood–plastic composite in terms of the incredible machining efficiency and the lowest energy consumption

Segregation of alloying elements at the TiC/V interface: A first-principles study

For precipitation/matrix coherent interface, the interfacial segregation behavior of solute atom plays a vital role in controlling the effectiveness of precipitation strengthening of the alloy. In this study, first-principles calculations based on density functional theory are used to figure out the interfacial structure of precipitates/vanadium and explain how solute atoms segregate at the interface and affect the interfacial strengthening. Firstly, according to the Baker-Nutting orientation relationship, the equilibrium interface structures are obtained. Meanwhiles, the segregation behavior of solute atoms at the different interfaces in vanadium alloys was studied. It is found that elements Sc, Ti, Y, Zr, Hf, and Ta, in the TiC/V(100) interface, tend to segregate at the interface, while other ones are not easy to segregate. The alloy elements show the same segregation trend as the TiC/V(100) interface, except for Nb, which also tends to segregate at the TiC/V(110) interface. According to the calculation, it is found that the alloying element with the larger atomic size and Voronoi volume is more likely to segregate into the interface, indicating that the atomic size effect dominates alloying element segregation at the two interfaces. The findings of this work can be used to develop theoretical approaches for future alloy designs by controlling alloying element doping

Effects of Point Defects on the Stable Occupation, Diffusion and Nucleation of Xe and Kr in UO₂

Xe and Kr gases produced during the use of uranium dioxide (UO2)-fuelled reactors can easily form bubbles, resulting in fuel swelling or performance degradation. Therefore, it is important to understand the influence of point defects on the behaviour of Xe and Kr gases in UO2. In this work, the effects of point defects on the behavioural characteristics of Xe/Kr clusters in UO2 have been systematically studied using molecular dynamics. The results show that Xe and Kr clusters occupy vacancies as nucleation points by squeezing U atoms out of the lattice, and the existence of vacancies makes the clusters more stable. The diffusion of interstitial Xe/Kr atoms and clusters in UO2 is also investigated. It is found that the activation energy is ~2 eV and that the diffusion of the interstitial atoms is very difficult. Xe and Kr bubbles form at high temperatures. The more interstitial Xe/Kr atoms or vacancies in the system, the easier the clusters form