Multiscale Hierarchical Structure and Laminated Strengthening and Toughening Mechanisms

Metal matrix composites with multiscale hierarchical structure and laminated structure have been developed to provide a novel route to achieve high strength, toughness and ductility. In this chapter, a lot of scientific research has been carried out in the preparation, processing, properties and application of metal matrix composite. Many toughening mechanisms and fracture behavior of composites with multiscale hierarchical structure and laminated structure are overviewed. It is revealed that elastic property and yield strength of laminated composites follow the “rule of average.” However, the estimation of fracture elongation and fracture toughness is complex, which is inconsistent with the “rule of average.” The fracture elongation of laminated composites is related to the layer thickness size, interface, gradient structure, strain hardening exponent, strain rate parameter and tunnel crack, which are accompanied with crack deflection, crack blunting, crack bridging, stress redistribution, local stress deformation, interfacial delamination crack and so on. The concept of laminated composites can be extended by applying different combination of individual layer, and provides theoretical as well as experimental fundamentals on strengthening and toughening of metal matrix composites

NORM: Knowledge Distillation via N-to-One Representation Matching

Existing feature distillation methods commonly adopt the One-to-one Representation Matching between any pre-selected teacher-student layer pair. In this paper, we present N-to-One Representation (NORM), a new two-stage knowledge distillation method, which relies on a simple Feature Transform (FT) module consisting of two linear layers. In view of preserving the intact information learnt by the teacher network, during training, our FT module is merely inserted after the last convolutional layer of the student network. The first linear layer projects the student representation to a feature space having N times feature channels than the teacher representation from the last convolutional layer, and the second linear layer contracts the expanded output back to the original feature space. By sequentially splitting the expanded student representation into N non-overlapping feature segments having the same number of feature channels as the teacher's, they can be readily forced to approximate the intact teacher representation simultaneously, formulating a novel many-to-one representation matching mechanism conditioned on a single teacher-student layer pair. After training, such an FT module will be naturally merged into the subsequent fully connected layer thanks to its linear property, introducing no extra parameters or architectural modifications to the student network at inference. Extensive experiments on different visual recognition benchmarks demonstrate the leading performance of our method. For instance, the ResNet18|MobileNet|ResNet50-1/4 model trained by NORM reaches 72.14%|74.26%|68.03% top-1 accuracy on the ImageNet dataset when using a pre-trained ResNet34|ResNet50|ResNet50 model as the teacher, achieving an absolute improvement of 2.01%|4.63%|3.03% against the individually trained counterpart. Code is available at https://github.com/OSVAI/NORMComment: The paper of NORM is published at ICLR 2023. Code and models are available at https://github.com/OSVAI/NOR

Giant coercivity, resistivity upturn, and anomalous Hall effect in ferrimagnetic FeTb

Despite the blooming interest, the transition-metal rare-earth ferrimagnets have not been comprehensively understood in terms of their coercivity and transport properties. Here, we report a systematic study of the magnetic and transport properties of ferrimagnetic FeTb alloy by varying the layer thickness and temperature. The FeTb is tuned from the Tb-dominated regime to the Fe-dominated regime via the layer thickness, without varying the composition. The coercivity closely follows the $1/\cos\theta_H$ scaling (where $\theta_H$ is the polar angle of the external magnetic field) and increases quasi-exponentially upon cooling (exceeding 90 kOe at low temperatures), revealing that the nature of the coercivity is the thermally-assisted domain wall depinning field. The resistivity exhibits a quasi-linear upturn upon cooling possibly due to thermal vibrations of the structure factor of the amorphous alloy. The existing scaling laws of the anomalous Hall effect in the literature break down for the amorphous FeTb that are either Fe- or Tb-dominated. These findings should advance the understanding of the transition-metal-rare-earth ferrimagnets and the associated ferrimagnetic phenomena in spintronics.Comment: In press at Phys. Rev.

Part-Whole Relational Few-Shot 3D Point Cloud Semantic Segmentation

The author wishes to extend sincere appreciation to Professor Lin Shi for the generous provision of equipment support, which significantly aided in the successful completion of this research. Furthermore, the author expresses gratitude to Associate Professor Ning Li and Teacher Wei Guan for their invaluable academic guidance and unwavering support. Their expertise and advice played a crucial role in shaping the direction and quality of this research.Peer reviewe

GP-NAS-ensemble: a model for NAS Performance Prediction

It is of great significance to estimate the performance of a given model architecture without training in the application of Neural Architecture Search (NAS) as it may take a lot of time to evaluate the performance of an architecture. In this paper, a novel NAS framework called GP-NAS-ensemble is proposed to predict the performance of a neural network architecture with a small training dataset. We make several improvements on the GP-NAS model to make it share the advantage of ensemble learning methods. Our method ranks second in the CVPR2022 second lightweight NAS challenge performance prediction track

Phylogenetic analysis, structural evolution and functional divergence of the 12-oxo-phytodienoate acid reductase gene family in plants

BACKGROUND: The 12-oxo-phytodienoic acid reductases (OPRs) are enzymes that catalyze the reduction of double-bonds in α, β-unsaturated aldehydes or ketones and are part of the octadecanoid pathway that converts linolenic acid to jasmonic acid. In plants, OPRs belong to the old yellow enzyme family and form multigene families. Although discoveries about this family in Arabidopsis and other species have been reported in some studies, the evolution and function of multiple OPRs in plants are not clearly understood. RESULTS: A comparative genomic analysis was performed to investigate the phylogenetic relationship, structural evolution and functional divergence among OPR paralogues in plants. In total, 74 OPR genes were identified from 11 species representing the 6 major green plant lineages: green algae, mosses, lycophytes, gymnosperms, monocots and dicots. Phylogenetic analysis showed that seven well-conserved subfamilies exist in plants. All OPR genes from green algae were clustered into a single subfamily, while those from land plants fell into six other subfamilies, suggesting that the events leading to the expansion of the OPR family occurred in land plants. Further analysis revealed that lineage-specific expansion, especially by tandem duplication, contributed to the current OPR subfamilies in land plants after divergence from aquatic plants. Interestingly, exon/intron structure analysis showed that the gene structures of OPR paralogues exhibits diversity in intron number and length, while the intron positions and phase were highly conserved across different lineage species. These observations together with the phylogenetic tree revealed that successive single intron loss, as well as indels within introns, occurred during the process of structural evolution of OPR paralogues. Functional divergence analysis revealed that altered functional constraints have occurred at specific amino acid positions after diversification of the paralogues. Most notably, significant functional divergence was also found in all pairs, except for the II/IV, II/V and V/VI pairs. Strikingly, analysis of the site-specific profiles established by posterior probability revealed that the positive-selection sites and/or critical amino acid residues for functional divergence are mainly distributed in α-helices and substrate binding loop (SBL), indicating the functional importance of these regions for this protein family. CONCLUSION: This study highlights the molecular evolution of the OPR gene family in all plant lineages and indicates critical amino acid residues likely relevant for the distinct functional properties of the paralogues. Further experimental verification of these findings may provide valuable information on the OPRs' biochemical and physiological functions

Imaging the scattering field of a single GaN nanowire

In this work, a single gallium nitride (GaN) nanowire has been examined by our previously reported technique parametric indirect microscopic imaging (PIMI). Mapping of the nanoscale scattering signals from GaN nanowire has been achieved with PIMI system. A comparison with classical far field microscopy and FDTD simulations is included to show the relevant differences and the strength of this technique. In PIMI, highly defined modulated illumination, far field variation quantification, and filtering process resolve the nanoscale scattering field distribution in the form of polarization parameters. We believe that our system provides us a platform to understand the physics of these nanoscale scattering fields from optical nanoantennas.The authors wish to acknowledge the financial support National Key Research and Development Program of China (2017YFF0107100), National Natural Science Foundation of China (NSFC) (61501239), NSFC-2017 (International Young Scientist Research Fund No. 61750110520) and the 'Zijin Professor Project' of Nanjing University of Science and Technology. B G C wants to thank the financial support from Agencia Estatal de Investigación and FEDER for the Project TEC2016-77242-C3-1-R AEI/FEDER, UE and Comunidad de Madrid for the SINFOTON-CM Research Program (S2013/MIT-2790).Publicad