Data Augmentation Vision Transformer for Fine-grained Image Classification

Recently, the vision transformer (ViT) has made breakthroughs in image recognition. Its self-attention mechanism (MSA) can extract discriminative labeling information of different pixel blocks to improve image classification accuracy. However, the classification marks in their deep layers tend to ignore local features between layers. In addition, the embedding layer will be fixed-size pixel blocks. Input network Inevitably introduces additional image noise. To this end, we study a data augmentation vision transformer (DAVT) based on data augmentation and proposes a data augmentation method for attention cropping, which uses attention weights as the guide to crop images and improve the ability of the network to learn critical features. Secondly, we also propose a hierarchical attention selection (HAS) method, which improves the ability of discriminative markers between levels of learning by filtering and fusing labels between levels. Experimental results show that the accuracy of this method on the two general datasets, CUB-200-2011, and Stanford Dogs, is better than the existing mainstream methods, and its accuracy is 1.4\% and 1.6\% higher than the original ViT, respectivelyComment: IEEE Signal Processing Letter

A Lightweight Reconstruction Network for Surface Defect Inspection

Currently, most deep learning methods cannot solve the problem of scarcity of industrial product defect samples and significant differences in characteristics. This paper proposes an unsupervised defect detection algorithm based on a reconstruction network, which is realized using only a large number of easily obtained defect-free sample data. The network includes two parts: image reconstruction and surface defect area detection. The reconstruction network is designed through a fully convolutional autoencoder with a lightweight structure. Only a small number of normal samples are used for training so that the reconstruction network can be A defect-free reconstructed image is generated. A function combining structural loss and $\mathit{L}1$ loss is proposed as the loss function of the reconstruction network to solve the problem of poor detection of irregular texture surface defects. Further, the residual of the reconstructed image and the image to be tested is used as the possible region of the defect, and conventional image operations can realize the location of the fault. The unsupervised defect detection algorithm of the proposed reconstruction network is used on multiple defect image sample sets. Compared with other similar algorithms, the results show that the unsupervised defect detection algorithm of the reconstructed network has strong robustness and accuracy.Comment: Journal of Mathematical Imaging and Vision(JMIV

Highly efficient vortex four-wave mixing in asymmetric semiconductor quantum wells

© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement Orbital angular momentum (OAM) is an important property of vortex light, which provides a valuable tool to manipulate the light-matter interaction in the study of classical and quantum optics. Here we propose a scheme to generate vortex light fields via four-wave mixing (FWM) in asymmetric semiconductor quantum wells. By tailoring the probe-field and control-field detunings, we can effectively manipulate the helical phase and intensity of the FWM field. Particularly, when probe field and control field have identical detuning, we find that both the absorption and phase twist of the generated FWM field are significantly suppressed. Consequently, the highly efficient vortex FWM is realized, where the maximum conversion efficiency reaches around 50%. Our study provides a tool to transfer vortex wavefronts from input to output fields in an efficient way, which may find potential applications in solid-state quantum optics and quantum information processing

Morphological and phylogenetic analyzes reveal two new species of Melanconiella from Fujian Province, China

IntroductionSpecies of Melanconiella include a diverse array of plant pathogens as well as endophytic fungi. Members of this genus have been frequently collected from the family Betulaceae (birches) in Europe and North America. Little, however, if known concerning the distribution of Melanconiella and/or their potential as pathogens of other plant hosts.MethodsFungi were noted and isolated from diseased leaves of Loropetalum chinense (Chinese fringe flower) and Camellia sinensis (tea) in Fujian Province, China. Genomic DNA was extracted from fungal isolates and the nucleotide sequences of four loci were determined and sued to construct phylogenetic trees. Morphological characteristics of fungal structures were determined via microscopic analyses.ResultsFour strains and two new species of Melanconiella were isolated from infected leaves of L. chinense and C. sinensis in Fujian Province, China. Based on morphology and a multi-gene phylogeny of the internal transcribed spacer regions with the intervening 5.8S nrRNA gene (ITS), the 28S large subunit of nuclear ribosomal RNA (LSU), the second largest subunit of RNA polymerase II (RPB2), and the translation elongation factor 1-α gene (TEF1-α), Melanconiellaloropetali sp. nov. and Melanconiellacamelliae sp. nov. were identified and described herein. Detailed descriptions, illustrations, and a key to the known species of Melanconiella are provided.DiscussionThese data identify new species of Melanconiella, expanding the potential range and distribution of these dark septate fungi. The developed keys provide a reference source for further characterization of these fungi

Assessing the structure and diversity of fungal community in plant soil under different climatic and vegetation conditions

IntroductionUnderstanding microbial communities in diverse ecosystems is crucial for unraveling the intricate relationships among microorganisms, their environment, and ecosystem processes. In this study, we investigated differences in the fungal community structure and diversity in soils from two contrasting climatic and vegetation conditions: the Xinjiang western China plateau and the Fujian southeastern coastal province.MethodsA total of 36 soil samples collected from two climatic regions were subjected to high-throughput ITS gene sequencing for fungal community analysis. In conjunction soil physicochemical properties were assessed and compared. Analyses included an examination of the relationship of fungal community structure to environmental factors and functional profiling of the community structure was using the FUNGuild pipeline.ResultsOur data revealed rich fungal diversity, with a total of 11 fungal phyla, 31 classes, 86 orders, 200 families, 388 genera, and 515 species identified in the soil samples. Distinct variations in the physicochemical properties of the soil and fungal community structure were seen in relation to climate and surface vegetation. Notably, despite a colder climate, the rhizosphere soil of Xinjiang exhibited higher fungal (α-)diversity compared to the rhizosphere soil of Fujian. β-diversity analyses indicated that soil heterogeneity and differences in fungal community structure were primarily influenced by spatial distance limitations and vegetation type. Furthermore, we identified dominant fungal phyla with significant roles in energy cycling and organic matter degradation, including members of the Sordariomycetes, Leotiomycetes, Archaeosporomycetes, and Agaricomycetes. Functional analyses of soil fungal communities highlighted distinct microbial ecological functions in Xinjiang and Fujian soils. Xinjiang soil was characterized by a focus on wood and plant saprotrophy, and endophytes, whereas in Fujian soil the fungal community was mainly associated with ectomycorrhizal interactions, fungal parasitism, and wood saprotrophy.DiscussionOur findings suggest fungal communities in different climatic conditions adapt along distinct patterns with, plants to cope with environmental stress and contribute significantly to energy metabolism and material cycling within soil-plant systems. This study provides valuable insights into the ecological diversity of fungal communities driven by geological and environmental factors

Preparation of carboxymethyl sago pulp hydrogel from sago waste by electron beam irradiation and swelling behavior in water and various pH media.

Solutions of carboxymethyl sago pulp (CMSP) of various degree of substitution were irradiated with electron beam of various radiation doses. The gelation dose (Dg) and po/qo ratio (po is degradation density, qo is crosslinking density) is dependent on CMSP concentration and degree of substitution. In the range of concentrations of 10% to 80% (w/v) CMSP with degree of substitutions of 0.4, 0.6, and 0.8, the po/qo ratio decreases with increasing %CMSP showing that crosslinking processes are dominating and increasing the gel network of the CMSP hydrogel. The fourier transform infrared spectra of CMSP hydrogels of degree of substitutions of 0.4, 0.6, and 0.8 with percentage of gel fractions 25, 35, and ≥ 40 show differences in the intensity of the absorption bands at 1020–1100, 1326, and 1422 cm−1 with different degree of substitutions and percentage of gel fraction (%GF) that correspond to different extents of chain scission and crosslinking. The swelling behavior in water shows that CMSP hydrogels could absorb 3500–5300% of water by 1 g of CMSP hydrogel. The ability to absorb water increases with the decrease of degree of substitution and %GF of the CMSP hydrogels. It is also observed that the optimum pH for swelling CMSP hydrogel is at pH 7

Design of Tensile Strained InGaAsP/InGaAsP MQW for 1.55μmpolarization Indepent Semiconductor Optical Amplifier

The theoretical optimization of tensile strained InGaAsP/InGaAsP MQW for 1.5μm window polarization-independent semiconductor optical amplifier is reported. The valence-band structure of the MQw is calculated by using K·P method, in which 6×6 Luttinger effective-mass Hamiltonian is taken into account. LThe polarization dependent optical gain is calculated with various well width, strain, and carrier density

Propagation Characteristics of High-Power Vortex Laguerre-Gaussian Laser Beams in Plasma

The propagation characteristics of high-power laser beams in plasma is an important research topic and has many potential applications in fields such as laser machining, laser-driven accelerators and laser-driven inertial confined fusion. The dynamic evolution of high-power Laguerre-Gaussian (LG) beams in plasma is numerically investigated by using the finite-difference time-domain (FDTD) method based on the nonlinear Drude model, with both plasma frequency and collision frequency modulated by the light intensity of laser beam. The numerical algorithms and implementation techniques of FDTD method are presented for numerically simulating the nonlinear permittivity model of plasma and generating the LG beams with predefined parameters. The simulation results show that the plasma has different field modulation effects on the two exemplified LG beams with different cross-sectional patterns. The self-focusing and stochastic absorption phenomena of high-power laser beam in plasma are also demonstrated. This research also provides a new means for the field modulation of laser beams by plasma

1.5μm Self-Aligned Spotsize Converter Integrated DFB Fabricated by Selective Area Grown MOVPE

High performance 1.57μm spotsize converter monolithically integrated DFB is fabricated by the technique of self-aligned selective area growth. The upper optical confinement layer and the butt-coupled tapered thickness waveguide are regrown simultaneously, which not only offeres the separated optimization of the active region and the integrated spotsize converter, but also reduces the difficulty of the butt-joint selective regrowth. The threshold current is as low as 4.4mA. The output power at 49mA is 10.1mW. The side mode suppression ratio (SMSR) is 33.2dB. The vertical and horizontal far field divergence angles are as small as 9° and 15° respectively, the 1dB misalignment tolerance are 3.6μm and 3.4μm

Selective Area Growth InGaAsP by MOVPE

The wide stripe (ISjum) selective area growth (SAG) of InGaAsP by low pressure MOVPE is systematically investigated. The characteristics of the growth ratios,thickness enhancement factors .bandgap modulation,and composition modulation vary with the growth conditions such as mask width,growth pressure. Flux of III-group precursors are outlined and the rational mechanism behind SAG MOVPE is explained. In addition,the surface spike of the SAG InGaAsP is shown and the course of it is given by the variation of V /III