Few-shot Semantic Segmentation with Support-induced Graph Convolutional Network

Few-shot semantic segmentation (FSS) aims to achieve novel objects segmentation with only a few annotated samples and has made great progress recently. Most of the existing FSS models focus on the feature matching between support and query to tackle FSS. However, the appearance variations between objects from the same category could be extremely large, leading to unreliable feature matching and query mask prediction. To this end, we propose a Support-induced Graph Convolutional Network (SiGCN) to explicitly excavate latent context structure in query images. Specifically, we propose a Support-induced Graph Reasoning (SiGR) module to capture salient query object parts at different semantic levels with a Support-induced GCN. Furthermore, an instance association (IA) module is designed to capture high-order instance context from both support and query instances. By integrating the proposed two modules, SiGCN can learn rich query context representation, and thus being more robust to appearance variations. Extensive experiments on PASCAL-5i and COCO-20i demonstrate that our SiGCN achieves state-of-the-art performance.Comment: Accepted in BMVC2022 as oral presentatio

Influences of Strain on the Microstructure and Mechanical Properties of High-Carbon Steel

The effects of strain on the microstructure and mechanical properties of 0.81C-0.22Si-0.31Mn (wt%) high-carbon steel were investigated by thermal simulation, scanning electron microscopy, high-resolution transmission electron microscopy (HRTEM), and an electron backscatter diffractometer (EBSD). It was found that when the steel was deformed at 670 °C (a temperature between A1 and Ar1), a deformation-induced pearlite transformation and cementite spheroidization occurred. The volume fraction of pearlite and the spheroidization ratio of cementite increased with a strain increase from 20% to 75%. The microstructure mainly consisted of pearlite when the deformation strain exceeded 40%. The aspect ratio was at its maximum (5.3) at 40% strain and decreased to 1.4 at 75% strain. In addition, the strength of the steel decreased and the elongation increased rapidly with the increase in strain from 20% to 60% due to the spheroidization of cementite. However, as the strain further increased to 75%, the strength increased slightly due to the refinement of the ferrite matrix. The comprehensive performance of the investigated steel can be improved by applying a strain between A1 and Ar1

Dynamic Mechanical Behaviors and Failure Mechanism of Lignite under SHPB Compression Test

There is an obvious impact effect of on-site blasting on the slope coal mass of open-pit mines, so it is of great significance to study the dynamic mechanical response characteristics of coal rock for slope stability control. In this paper, first, the mineral composition and microstructure of lignite from open-pit mine are analyzed, and it is found that the content of non-organic minerals in lignite such as clay accounts for more than 24.40%; meanwhile, the rock sample has obvious horizontal bedding characteristics and mainly micro pores and transition pores inside; further, there are obvious banded areas with high water content in the rock, which has the same extending direction as the beddings. Based on the SHPB test system, the dynamic compression tests of lignite with different impact velocities are carried out. The results show that there is a significant hardening effect caused by the increase of strain rate on the dynamic mechanical parameters of rock samples, and the stress–strain curve has obvious “double peak” characteristics; meanwhile, the macroscopic crack of the rock appears at the first stress peak and disappears after further compression until the interlayer fracture occurs; further, the fracture fractal dimension of lignite increases linearly with the impact velocity, revealing that the fragmentation of rock samples increases gradually. In addition, with the increase of impact velocity, the input energy and dissipated energy of rock samples increase linearly, while the elastic property increases slowly and at a low level. The bedding characteristics of lignite and the wave impedance difference between the layers cause the high-reflection phenomenon in the process of stress-wave propagation, and then produce the obvious tensile stress wave in the rock sample, which finally results in the interlayer fracture failure of the rock

Dynamic Mechanical Behaviors and Failure Mechanism of Lignite under SHPB Compression Test

There is an obvious impact effect of on-site blasting on the slope coal mass of open-pit mines, so it is of great significance to study the dynamic mechanical response characteristics of coal rock for slope stability control. In this paper, first, the mineral composition and microstructure of lignite from open-pit mine are analyzed, and it is found that the content of non-organic minerals in lignite such as clay accounts for more than 24.40%; meanwhile, the rock sample has obvious horizontal bedding characteristics and mainly micro pores and transition pores inside; further, there are obvious banded areas with high water content in the rock, which has the same extending direction as the beddings. Based on the SHPB test system, the dynamic compression tests of lignite with different impact velocities are carried out. The results show that there is a significant hardening effect caused by the increase of strain rate on the dynamic mechanical parameters of rock samples, and the stress–strain curve has obvious “double peak” characteristics; meanwhile, the macroscopic crack of the rock appears at the first stress peak and disappears after further compression until the interlayer fracture occurs; further, the fracture fractal dimension of lignite increases linearly with the impact velocity, revealing that the fragmentation of rock samples increases gradually. In addition, with the increase of impact velocity, the input energy and dissipated energy of rock samples increase linearly, while the elastic property increases slowly and at a low level. The bedding characteristics of lignite and the wave impedance difference between the layers cause the high-reflection phenomenon in the process of stress-wave propagation, and then produce the obvious tensile stress wave in the rock sample, which finally results in the interlayer fracture failure of the rock

Smart nanoparticles for cancer therapy

Abstract Smart nanoparticles, which can respond to biological cues or be guided by them, are emerging as a promising drug delivery platform for precise cancer treatment. The field of oncology, nanotechnology, and biomedicine has witnessed rapid progress, leading to innovative developments in smart nanoparticles for safer and more effective cancer therapy. In this review, we will highlight recent advancements in smart nanoparticles, including polymeric nanoparticles, dendrimers, micelles, liposomes, protein nanoparticles, cell membrane nanoparticles, mesoporous silica nanoparticles, gold nanoparticles, iron oxide nanoparticles, quantum dots, carbon nanotubes, black phosphorus, MOF nanoparticles, and others. We will focus on their classification, structures, synthesis, and intelligent features. These smart nanoparticles possess the ability to respond to various external and internal stimuli, such as enzymes, pH, temperature, optics, and magnetism, making them intelligent systems. Additionally, this review will explore the latest studies on tumor targeting by functionalizing the surfaces of smart nanoparticles with tumor-specific ligands like antibodies, peptides, transferrin, and folic acid. We will also summarize different types of drug delivery options, including small molecules, peptides, proteins, nucleic acids, and even living cells, for their potential use in cancer therapy. While the potential of smart nanoparticles is promising, we will also acknowledge the challenges and clinical prospects associated with their use. Finally, we will propose a blueprint that involves the use of artificial intelligence-powered nanoparticles in cancer treatment applications. By harnessing the potential of smart nanoparticles, this review aims to usher in a new era of precise and personalized cancer therapy, providing patients with individualized treatment options