171 research outputs found

    Strongly Nonlinear Topological Phases of Cascaded Topoelectrical Circuits

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    Circuits provide ideal platforms of topological phases and matter, yet the study of topological circuits in the strongly nonlinear regime, has been lacking. We propose and experimentally demonstrate strongly nonlinear topological phases and transitions in one-dimensional electrical circuits composed of nonlinear capacitors. Nonlinear topological interface modes arise on domain walls of the circuit lattices, whose topological phases are controlled by the amplitudes of nonlinear voltage waves. Experimentally measured topological transition amplitudes are in good agreement with those derived from nonlinear topological band theory. Our prototype paves the way towards flexible metamaterials with amplitude-controlled rich topological phases and is readily extendable to two and three-dimensional systems that allow novel applications.Comment: accepted by Frontiers of Physics, 18+9 pages, 4+3 figure

    Locally-Enriched Cross-Reconstruction for Few-Shot Fine-Grained Image Classification

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    Few-shot fine-grained image classification has attracted considerable attention in recent years for its realistic setting to imitate how humans conduct recognition tasks. Metric-based few-shot classifiers have achieved high accuracies. However, their metric function usually requires two arguments of vectors, while transforming or reshaping three-dimensional feature maps to vectors can result in loss of spatial information. Image reconstruction is thus involved to retain more appearance details: the test images are reconstructed by different classes and then classified to the one with the smallest reconstruction error. However, discriminative local information, vital to distinguish sub-categories in fine-grained images with high similarities, is not well elaborated when only the base features from a usual embedding module are adopted for reconstruction. Hence, we propose the novel local content-enriched cross-reconstruction network (LCCRN) for few-shot fine-grained classification. In LCCRN, we design two new modules: the local content-enriched module (LCEM) to learn the discriminative local features, and the cross-reconstruction module (CRM) to fully engage the local features with the appearance details obtained from a separate embedding module. The classification score is calculated based on the weighted sum of reconstruction errors of the cross-reconstruction tasks, with weights learnt from the training process. Extensive experiments on four fine-grained datasets showcase the superior classification performance of LCCRN compared with the state-of-the-art few-shot classification methods. Codes are available at: https://github.com/lutsong/LCCRN

    Inherent-opening-controlled pattern formation in carbon nanotube arrays

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    We have introduced inherent openings into densely packed carbon nanotube arrays to study self-organized pattern formation when the arrays undergo a wetting–dewetting treatment from nanotube tips. These inherent openings, made of circular or elongated hollows in nanotube mats, serve as dewetting centres, from where liquid recedes from. As the dewetting centres initiate dry zones and the dry zones expand, surrounding nanotubes are pulled away from the dewetting centres by liquid surface tension. Among short nanotubes, the self-organized patterns are consistent with the shape of the inherent openings, i.e. slender openings lead to elongated trench-like structures, and circular holes result in relatively round nest-like arrangements. Nanotubes in a relatively high mat are more connected, like in an elastic body, than those in a short mat. Small cracks often initialize themselves in a relatively high mat, along two or more adjacent round openings; each of the cracks evolves into a trench as liquid dries up. Self-organized pattern control with inherent openings needs to initiate the dewetting process above the nanotube tips. If there is no liquid on top, inherent openings barely enlarge themselves after the wetting–dewetting treatment

    Structural Mechanism of Smad4 Recognition by the Nuclear Oncoprotein Ski Insights on Ski-Mediated Repression of TGF-β Signaling

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    AbstractThe Ski family of nuclear oncoproteins represses TGF-β signaling through interactions with the Smad proteins. The crystal structure of the Smad4 binding domain of human c-Ski in complex with the MH2 domain of Smad4 reveals specific recognition of the Smad4 L3 loop region by a highly conserved interaction loop (I loop) from Ski. The Ski binding surface on Smad4 significantly overlaps with that required for binding of the R-Smads. Indeed, Ski disrupts the formation of a functional complex between the Co- and R-Smads, explaining how it could lead to repression of TGF-β, activin, and BMP responses. Intriguingly, the structure of the Ski fragment, stabilized by a bound zinc atom, resembles the SAND domain, in which the corresponding I loop is responsible for DNA binding

    QTL mapping and BSA-seq map a major QTL for the node of the first fruiting branch in cotton

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    Understanding the genetic basis of the node of the first fruiting branch (NFFB) improves early-maturity cotton breeding. Here we report QTL mapping on 200 F2 plants and derivative F2:3 and F2:4 populations by genotyping by sequencing (GBS). BC1F2 population was constructed by backcrossing one F2:4 line with the maternal parent JF914 and used for BSA-seq for further QTL mapping. A total of 1,305,642 SNPs were developed between the parents by GBS, and 2,907,790 SNPs were detected by BSA-seq. A high-density genetic map was constructed containing 11,488 SNPs and spanning 4,202.12 cM in length. A total of 13 QTL were mapped in the 3 tested populations. JF914 conferred favorable alleles for 11 QTL, and JF173 conferred favorable alleles for the other 2 QTL. Two stable QTL were repeatedly mapped in F2:3 and F2:4, including qNFFB-D3-1 and qNFFB-D6-1. Only qNFFB-D3-1 contributed more than 10% of the phenotypic variation. This QTL covered about 24.7 Mb (17,130,008–41,839,226 bp) on chromosome D3. Two regions on D3 (41,779,195–41,836,120 bp, 41,836,768–41,872,287 bp) were found by BSA-seq and covered about 92.4 Kb. This 92.4 Kb region overlapped with the stable QTL qNFFB-D3-1 and contained 8 annotated genes. By qRT-PCR, Ghir_D03G012430 showed a lower expression level from the 1- to 2-leaf stage and a higher expression level from the 3- to 6-leaf stage in the buds of JF173 than that of JF914. Ghir_D03G012390 reached the highest level at the 3- and 5-leaf stages in the buds of JF173 and JF914, respectively. As JF173 has lower NFFB and more early maturity than JF914, these two genes might be important in cell division and differentiation during NFFB formation in the seedling stage. The results of this study will facilitate a better understanding of the genetic basis of NFFB and benefit cotton molecular breeding for improving earliness traits

    Proton pitch angle distributions in the Martian induced magnetosphere: A survey of Tianwen-1 Mars Ion and Neutral Particle Analyzer observations

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    The pitch angle distributions of ions and electrons can be affected by various processes; thus, they can serve as an important indicator of the physical mechanisms driving the dynamics of space plasmas. From observations from the Mars Ion and Neutral Particle Analyzer onboard the Tianwen-1 orbiter, we calculated the pitch angle distributions of protons in the Martian induced magnetosphere by using information from the magnetohydrodynamically simulated magnetic field, and we statistically analyzed the spatial occurrence pattern of different types of pitch angle distributions. Even though no symmetrical features were seen in the dataset, we found the dominance of the field-aligned distribution type over the energy range from 188 to 6232 eV. Maps of the occurrence rate showed the preferential presence of a trapped-like distribution at the lower altitudes of the surveyed nightside region. Although our results are more or less restricted by the adopted magnetic field, they indicate the complexity of the near-Mars proton pitch angle distributions and infer the possibility of wave–particle interactions in the Martian induced magnetosphere

    A Companion Cell–Dominant and Developmentally Regulated H3K4 Demethylase Controls Flowering Time in Arabidopsis via the Repression of FLC Expression

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    Flowering time relies on the integration of intrinsic developmental cues and environmental signals. FLC and its downstream target FT are key players in the floral transition in Arabidopsis. Here, we characterized the expression pattern and function of JMJ18, a novel JmjC domain-containing histone H3K4 demethylase gene in Arabidopsis. JMJ18 was dominantly expressed in companion cells; its temporal expression pattern was negatively and positively correlated with that of FLC and FT, respectively, during vegetative development. Mutations in JMJ18 resulted in a weak late-flowering phenotype, while JMJ18 overexpressors exhibited an obvious early-flowering phenotype. JMJ18 displayed demethylase activity toward H3K4me3 and H3K4me2, and bound FLC chromatin directly. The levels of H3K4me3 and H3K4me2 in chromatins of FLC clade genes and the expression of FLC clade genes were reduced, whereas FT expression was induced and the protein expression of FT increased in JMJ18 overexpressor lines. The early-flowering phenotype caused by the overexpression of JMJ18 was mainly dependent on the functional FT. Our findings suggest that the companion cell–dominant and developmentally regulated JMJ18 binds directly to the FLC locus, reducing the level of H3K4 methylation in FLC chromatin and repressing the expression of FLC, thereby promoting the expression of FT in companion cells to stimulate flowering

    Coal Mine Rock Burst and Coal and Gas Outburst Perception Alarm Method Based on Visible Light Imagery

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    To solve the current reliance of coal mine rock burst and coal and gas outburst detection on mainly manual methods and the problem wherein it is still difficult to ensure disaster warning required to meet the needs of coal mine safety production, a coal mine rock burst and coal and gas outburst perception alarm method based on visible light imagery is proposed. Real-time video images were collected by color cameras in key areas of underground coal mines; the occurrence of disasters was determined by noting when the black area of a video image increases greatly, when the average brightness is less than the set brightness threshold, and when the moving speed of an object resulting in a large increase in the black area is greater than the set speed threshold (V > 13 m/s); methane concentration characteristics were used to distinguish rock burst and coal and gas outburst accidents, and an alarm was created. A set of disaster-characteristic simulation devices was designed. A Φ315 mm white PVC pipe was used to simulate the roadway and background equipment; Φ10 mm rubber balls were used to replace crushed coal rocks; a color camera with a 2.8 mm focal length, 30 FPS, and 110° field angle was used for image acquisition. The results of our study show that the recognition effect is good, which verifies the feasibility and effectiveness of the method
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