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Glaucoma is a chronic degenerative disease that is the second leading cause of irreversible blindness worldwide. For a precise and automatic screening of glaucoma, detecting the optic disc and cup precisely is significant. In this paper, combining the elliptical-like morphological features of the disc and cup, we reformulate the segmentation task from a perspective of ellipse detection to explicitly segment and directly get the glaucoma screening indicator. We detect the minimum bounding boxes of ellipses firstly, and then learn the ellipse parameters of these regions to achieve optic disc and cup segmentation. Considering the spatial geometry prior knowledge that the cup should be within the disc region, Paired-Box RPN is introduced to simultaneously detect the disc and cup coupled. In addition, boundary attention module is introduced to use edges of the disc and cup as an important guide for context aggregation to improve the accuracy. Comprehensive experiments clearly show that our method outperforms the state-of-the-art methods for optic disc and cup segmentation. Simultaneously, the proposed method also obtains the good glaucoma screening performance with calculated vCDR value. Joint optic disc and cup segmentation, which utilizes the elliptical-like morphological features and spatial geometry constraint, could improve the performance of optic disc and cup segmentation.
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Glaucoma , Disco Óptico , Humanos , Disco Óptico/diagnóstico por imagem , Glaucoma/diagnóstico por imagem , Técnicas de Diagnóstico Oftalmológico , Programas de Rastreamento , Fundo de OlhoRESUMO
Self-assembly of identical organometallic supramolecules into ordered superstructures is of great interest in both chemical science and nanotechnology due to its potential to generate neoteric properties through collective effects. In this work, we demonstrate that large-scale self-organization of atomically precise organometallic supramolecules can be achieved through cascaded on-surface chemical reactions, by the combination of intra- and inter-supramolecular interactions. Supramolecules with defined size and shape are first built through intramolecular reaction and intermolecular metal coordination, followed by the formation of well-ordered two-dimensional arrays with the assistance of Br atoms by -C-H···Br interactions. The mechanism of this process has been investigated from the perspectives of thermodynamics and kinetics.
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Ultrathin van der Waals (vdW) magnets are heavily pursued for potential applications in developing high-density miniaturized electronic/spintronic devices as well as for topological physics in low-dimensional structures. Despite the rapid advances in ultrathin ferromagnetic vdW magnets, the antiferromagnetic counterparts, as well as the antiferromagnetic junctions, are much less studied owing to the difficulties in both material fabrication and magnetism characterization. Ultrathin CrTe3 layers have been theoretically proposed to be a vdW antiferromagnetic semiconductor with intrinsic intralayer antiferromagnetism. Herein, the epitaxial growth of monolayer (ML) and bilayer CrTe3 on graphite surface is demonstrated. The structure, electronic and magnetic properties of the ML CrTe3 are characterized by combining scanning tunneling microscopy/spectroscopy and non-contact atomic force microscopy and confirmed by density functional theory calculations. The CrTe3 MLs can be further utilized for the fabrication of a lateral heterojunction consisting of ML CrTe2 and ML CrTe3 with an atomically sharp and seamless interface. Since ML CrTe2 is a metallic vdW magnet, such a heterostructure presents the first in-plane magnetic metal-semiconductor heterojunction made of two vdW materials. The successful fabrication of ultrathin antiferromagnetic CrTe3 , as well as the magnetic heterojunction, will stimulate the development of miniaturized antiferromagnetic spintronic devices based on vdW materials.
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We report an example that demonstrates the clear interdependence between surface-supported reactions and molecular-adsorption configurations. Two biphenyl-based molecules with two and four bromine substituents, i.e., 2,2'-dibromobiphenyl (DBBP) and 2,2',6,6'-tetrabromo-1,1'-biphenyl (TBBP), show completely different reaction pathways on a Ag(111) surface, leading to the selective formation of dibenzo[e,l]pyrene and biphenylene dimer, respectively. By combining low-temperature scanning tunneling microscopy, synchrotron radiation photoemission spectroscopy, and density functional theory calculations, we unravel the underlying reaction mechanism. After debromination, a biradical biphenyl can be stabilized by surface Ag adatoms, while a four-radical biphenyl undergoes spontaneous intramolecular annulation due to its extreme instability on Ag(111). Such different chemisorption-induced precursor states between DBBP and TBBP consequently lead to different reaction pathways after further annealing. In addition, using bond-resolving scanning tunneling microscopy and scanning tunneling spectroscopy, we determine with atomic precision the bond-length alternation of the biphenylene dimer product, which contains 4-, 6-, and 8-membered rings. The 4-membered ring units turn out to be radialene structures.
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This study aims to solve the overfitting problem caused by insufficient labeled images in the automatic image annotation field. We propose a transfer learning model called CNN-2L that incorporates the label localization strategy described in this study. The model consists of an InceptionV3 network pretrained on the ImageNet dataset and a label localization algorithm. First, the pretrained InceptionV3 network extracts features from the target dataset that are used to train a specific classifier and fine-tune the entire network to obtain an optimal model. Then, the obtained model is used to derive the probabilities of the predicted labels. For this purpose, we introduce a squeeze and excitation (SE) module into the network architecture that augments the useful feature information, inhibits useless feature information, and conducts feature reweighting. Next, we perform label localization to obtain the label probabilities and determine the final label set for each image. During this process, the number of labels must be determined. The optimal K value is obtained experimentally and used to determine the number of predicted labels, thereby solving the empty label set problem that occurs when the predicted label values of images are below a fixed threshold. Experiments on the Corel5k multilabel image dataset verify that CNN-2L improves the labeling precision by 18% and 15% compared with the traditional multiple-Bernoulli relevance model (MBRM) and joint equal contribution (JEC) algorithms, respectively, and it improves the recall by 6% compared with JEC. Additionally, it improves the precision by 20% and 11% compared with the deep learning methods Weight-KNN and adaptive hypergraph learning (AHL), respectively. Although CNN-2L fails to improve the recall compared with the semantic extension model (SEM), it improves the comprehensive index of the F1 value by 1%. The experimental results reveal that the proposed transfer learning model based on a label localization strategy is effective for automatic image annotation and substantially boosts the multilabel image annotation performance.
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Algoritmos , Curadoria de Dados/métodos , Aprendizado Profundo , Processamento de Imagem Assistida por Computador/métodos , Redes Neurais de Computação , Tomografia Computadorizada por Raios X/métodos , HumanosRESUMO
On-surface fabrication of two-dimensional (2D) metal organic frameworks (MOFs) has been continuously attracting attentions for years. However, the synthesis of 2D MOFs with large-amplitude flexibility was rarely carried out since the bonding configurations in the coordination nodes are typically highly directional. Here we demonstrate that single alkali ions, which are fully isotropic in ionic bonding, can act as pivot joints for constructing tunable 2D MOFs by bonding to dihalogen groups in organic molecules. We take 2,3,6,7,10,11-hexabromotriphenylene, a 3-fold polycyclic molecule with three ortho-dibromo groups, and sodium (Na) atoms as a model system and successfully construct Na-based MOFs on Au(111) surface. The deflection angle of the Na coordination nodes is variable in an unprecedentedly large range between ±36° that allows the construction of multiple 2D MOF architectures. Such a flexible alkali-halogen bonding may provide a unique toolbox for designing and constructing more tunable MOFs by choosing various alkali atoms and halogen moieties.
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Heterostructure devices based on two-dimensional materials have been under intensive study due to their intriguing electrical and optical properties. One key factor in understanding these devices is their nanometer-scale band profiles, which is challenging to obtain in devices. Here, we use a technique named contact-mode scanning tunneling spectroscopy to directly visualize the band profiles of MoS2/WSe2 heterostructure devices at different gate voltages with nanometer resolution. The long-held view of a conventional p-n junction in the MoS2/WSe2 heterostructure is reexamined. Due to strong inter- and intralayer charge transfer, the MoS2 layer in contact with WSe2 is found to convert from n-type to p-type, and a series of gate-tunable p-n and p-p+ junctions are developed in the devices. Highly conductive edges are also discovered which could strongly affect the device properties.
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The recent proposal of antidoping scheme breaks new ground in conceiving conversely functional materials and devices; yet, the few available examples belong to the correlated electron systems. Here, we demonstrate both theoretically and experimentally that the main group oxide BaBiO3 is a model system for antidoping using oxygen vacancies. The first-principles calculations show that the band gap systematically increases due to the strongly enhanced Bi-O breathing distortions away from the vacancies and the annihilation of Bi 6s/O 2p hybridized conduction bands near the vacancies. Our further spectroscopic experiments confirm that the band gap increases systematically with electron doping, with a maximal gap enhancement of â¼75% when the film's stoichiometry is reduced to BaBiO2.75. These results unambiguously demonstrate the remarkable antidoping effect in a material without strong electron correlations and underscores the importance of bond disproportionation in realizing such an effect.
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The structure determination of surface species has long been a challenge because of their rich chemical heterogeneities. Modern tip-based microscopic techniques can resolve heterogeneities from their distinct electronic, geometric, and vibrational properties at the single-molecule level but with limited interpretation from each. Here, we combined scanning tunneling microscopy (STM), noncontact atomic force microscopy (AFM), and tip-enhanced Raman scattering (TERS) to characterize an assumed inactive system, pentacene on the Ag(110) surface. This enabled us to unambiguously correlate the structural and chemical heterogeneities of three pentacene-derivative species through specific carbon-hydrogen bond breaking. The joint STM-AFM-TERS strategy provides a comprehensive solution for determining chemical structures that are widely present in surface catalysis, on-surface synthesis, and two-dimensional materials.
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Interfacial polarons have been demonstrated to play important roles in heterostructures containing polar substrates. However, most of polarons found so far are diffusive large polarons; the discovery and investigation of small polarons at interfaces are scarce. Herein, we report the emergence of interfacial polarons in monolayer SnSe2 epitaxially grown on Nb-doped SrTiO3 (STO) surface using angle-resolved photoemission spectroscopy (ARPES) and scanning tunneling microscopy (STM). ARPES spectra taken on this heterointerface reveal a nearly flat in-gap band correlated with a significant charge modulation in real space as observed with STM. An interfacial polaronic model is proposed to ascribe this in-gap band to the formation of self-trapped small polarons induced by charge accumulation and electron-phonon coupling at the van der Waals interface of SnSe2 and STO. Such a mechanism to form interfacial polaron is expected to generally exist in similar van der Waals heterojunctions consisting of layered 2D materials and polar substrates.
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In this study, a convolutional neural network with threshold optimization (CNN-THOP) is proposed to solve the issue of overlabeling or downlabeling arising during the multilabel image annotation process in the use of a ranking function for label annotation along with prediction probability. This model fuses the threshold optimization algorithm to the CNN structure. First, an optimal model trained by the CNN is used to predict the test set images, and batch normalization (BN) is added to the CNN structure to effectively accelerate the convergence speed and obtain a group of prediction probabilities. Second, threshold optimization is performed on the obtained prediction probability to derive an optimal threshold for each class of labels to form a group of optimal thresholds. When the prediction probability for this class of labels is greater than or equal to the corresponding optimal threshold, this class of labels is used as the annotation result for the image. During the annotation process, the multilabel annotation for the image to be annotated is realized by loading the optimal model and the optimal threshold. Verification experiments are performed on the MIML, COREL5K, and MSRC datasets. Compared with the MBRM, the CNN-THOP increases the average precision on MIML, COREL5K, and MSRC by 27%, 28% and 33%, respectively. Compared with the E2E-DCNN, the CNN-THOP increases the average recall rate by 3% on both COREL5K and MSRC. The most precise annotation effect for CNN-THOP is observed on the MIML dataset, with a complete matching degree reaching 64.8%.
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Curadoria de Dados/métodos , Processamento de Imagem Assistida por Computador/métodos , Algoritmos , Redes Neurais de Computação , Tomografia Computadorizada por Raios X/métodosRESUMO
Adsorption of magnetic transition metal atoms on a metal surface leads to the formation of Kondo states at the atom/metal interfaces. However, the significant influence of surrounding environment presents challenges for potential applications. In this work, we realize a novel strategy to regularize the Kondo states by moving a CoPc molecular mold on an Au(111) surface to capture the dispersed Co adatoms. The symmetric and ordered structures of the atom-mold complexes, as well as the strong dπ-π bonding between the Co adatoms and conjugated isoindole units, result in highly robust and uniform Kondo states at the Co/Au(111) interfaces. Even more remarkably, the CoPc further enables a fine tuning of Kondo states through the molecular-mold-mediated superexchange interactions between Co adatoms separated by more than 12 Å. Being highly precise, efficient and reproducible, the proposed molecular mold strategy may open a new horizon for the construction and control of nano-sized quantum devices.
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The formation of the Dirac nodal line (DNL) requires intrinsic symmetry that can protect the degeneracy of continuous Dirac points in momentum space. Here, as an alternative approach, we propose an extrinsic symmetry protected DNL. On the basis of symmetry analysis and numerical calculations, we establish a general principle to design the nonsymmorphic symmetry protected 4-fold degenerate DNL against spin-orbit coupling in the nanopatterned 2D electron gas. Furthermore, on the basis of experimental measurements, we demonstrate the approximate realization of our proposal in the Bi/Cu(111) system, in which a highly dispersive DNL is observed at the boundary of the Brillouin zone. We envision that the extrinsic symmetry engineering will greatly enhance the ability for artificially constructing the exotic topological bands in the future.
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Considering the problems of low resolution and rough details in existing mural images, this paper proposes a superresolution reconstruction algorithm for enhancing artistic mural images, thereby optimizing mural images. The algorithm takes a generative adversarial network (GAN) as the framework. First, a convolutional neural network (CNN) is used to extract image feature information, and then, the features are mapped to the high-resolution image space of the same size as the original image. Finally, the reconstructed high-resolution image is output to complete the design of the generative network. Then, a CNN with deep and residual modules is used for image feature extraction to determine whether the output of the generative network is an authentic, high-resolution mural image. In detail, the depth of the network increases, the residual module is introduced, the batch standardization of the network convolution layer is deleted, and the subpixel convolution is used to realize upsampling. Additionally, a combination of multiple loss functions and staged construction of the network model is adopted to further optimize the mural image. A mural dataset is set up by the current team. Compared with several existing image superresolution algorithms, the peak signal-to-noise ratio (PSNR) of the proposed algorithm increases by an average of 1.2-3.3 dB and the structural similarity (SSIM) increases by 0.04 = 0.13; it is also superior to other algorithms in terms of subjective scoring. The proposed method in this study is effective in the superresolution reconstruction of mural images, which contributes to the further optimization of ancient mural images.
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Processamento de Imagem Assistida por Computador , Tomografia Computadorizada por Raios X , Algoritmos , Redes Neurais de Computação , Razão Sinal-RuídoRESUMO
Two-dimensional layered transition-metal telluride can build stable metallic, metastable metallic, or semimetallic polymorphic crystal structures with enormous technological and scientific applications. Herein the hexagonal structures of zirconium ditelluride (ZrTe2) and ZrTe2(1-x)Se2x (0 ≤ x ≤ 1) single crystals were selectively synthesized through the chemical vapor transport method. The electronic band structures were systematically studied through angle-resolved photoemission spectroscopy (ARPES) combined with first-principles density functional theory (DFT) calculations. The ARPES results suggested a clear electronic phase transition from a semimetal to a semiconductor in ZrTe2(1-x)Se2x with the x value changing. Compared with pristine ZrTe2, the valence band splitting in ZrTe2(1-x)Se2x decreased at the Γ point due to the reduction of the spin-orbit interaction, whereas an indirect band gap opened in the vicinity of the Fermi level with the increase in Se concentration. Our DFT calculations further confirmed that the substituted Se atoms on Te sites could affect the band structure of ZrTe2 to induce a distinct transition from semimetal to semiconductor, suggesting their high potential for valleytronics applications.
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Controlling selectivity between homochiral and heterochiral reaction pathways on surfaces remains a great challenge. Here, competing reactions of a prochiral alkyne on Ag(111): two-dimensional (2D) homochiral Glaser coupling and heterochiral cross-coupling with a Bergman cyclization step have been examined. We demonstrate control strategies in steering the reactions between the homochiral and heterochiral pathways by tuning the precursor substituents and the kinetic parameters, as confirmed by high-resolution scanning probe microscopy (SPM). Control experiments and density functional theory (DFT) calculations reveal that the template effect of organometallic chains obtained under specific kinetic conditions enhances Glaser coupling between homochiral molecules. In contrast, for the reaction of free monomers, the kinetically favorable reaction pathway is the cross-coupling between two heterochiral molecules (one of them involving cyclization). This work demonstrates the application of kinetic control to steer chiral organic coupling pathways at surfaces.
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Two-dimensional (2D) topological materials, including quantum spin/anomalous Hall insulators, have attracted intense research efforts owing to their promise for applications ranging from low-power electronics and high-performance thermoelectrics to fault-tolerant quantum computation. One key challenge is to fabricate topological materials with a large energy gap for room-temperature use. Stanene-the tin counterpart of graphene-is a promising material candidate distinguished by its tunable topological states and sizeable bandgap. Recent experiments have successfully fabricated stanene, but none of them have yet observed topological states. Here we demonstrate the growth of high-quality stanene on Cu(111) by low-temperature molecular beam epitaxy. Importantly, we discovered an unusually ultraflat stanene showing an in-plane s-p band inversion together with a spin-orbit-coupling-induced topological gap (~0.3 eV) at the Γ point, which represents a foremost group-IV ultraflat graphene-like material displaying topological features in experiment. The finding of ultraflat stanene opens opportunities for exploring two-dimensional topological physics and device applications.
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Folding can be an effective way to tailor the electronic properties of graphene and has attracted wide study interest in finding its novel properties. Here we present the experimental characterizations of the structural and electronic properties of a narrow graphene wrinkle on a SiO2/Si substrate using scanning tunneling microscopy/spectroscopy. Pronounced and nearly equally separated conductance peaks are observed in the d I/d V spectra of the wrinkle. We attribute these peaks to pseudo-Landau levels (PLLs) that are caused by a gradient-strain-induced pseudomagnetic field up to about 42 T in the narrow wrinkle. The introduction of the gradient strain and thus the pseudomagnetic field can be ascribed to the lattice deformation. A doubly-folded structure of the wrinkle is suggested. Our density functional theory calculations show that the band structure of the doubly folded graphene wrinkle has a parabolic dispersion, which can well explain the equally separated PLLs. The effective mass of carriers is obtained to be about 0.02 me ( me: the rest mass of electron), and interestingly, it is revealed that there exists valley polarization in the wrinkle. Such properties of the strained doubly folded wrinkle may provide a platform to explore some exciting phenomena in graphene, like zero-field quantum valley Hall effect.
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Topological properties of matters have attracted tremendous interest in the past years due to the scientific and technological importance. It is of great interest to discover the analogs of topological phases in molecular architectures, if the key constituents of the phases are properly mimicked. Using scanning tunneling microscopy, we demonstrate that quasi-1D molecular chains assembled from conformation-switchable dibenzo[ g, p]chrysene molecules show hidden antiparallel order analogous to the hidden antiferromagnetic order in the Haldane phase, a known topological phase of quantum spin-1 chains. This is realized by mimicking the spin degree of freedom with the intramolecular helicene chiral switches and by emulating the interspin antiferromagnetic coupling with intermolecular homochiral coupling. The discovery of the molecular analog of topological matters may inspire the search of molecular architectures with nontrivial topological properties.
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The doping types of graphene sheets are generally tuned by different dopants with either three or five valence electrons. As a five-valence-electrons element, however, nitrogen dopants in graphene sheets have several substitutional geometries. So far, their distinct effects on electronic properties predicted by theoretical calculations have not been well identified. Here, we demonstrate that the doping types of graphene can be tuned by N monoelement under proper growth conditions using chemical vapor deposition (CVD), characterized by combining scanning tunneling microscopy/spectroscopy, X-ray/ultraviolet photoelectron spectroscopy, Hall effect measurement, Raman spectroscopy, and density functional theory calculations. We find that a relatively low partial pressure of CH4 (mixing with NH3) can lead to the growth of dominant pyridinic N substitutions in graphene, in contrast with the growth of dominant graphitic N substitutions under a higher partial pressure of CH4. Our results unambiguously confirm that the pyridinic N leads to the p-type doping, and the graphitic N leads to the n-type doping. Interestingly, we also find that the pyridinic N and the graphitic N are preferentially separated in different domains. Our findings shed light on continuously tuning the doping level of graphene monolayers by using N monoelement, which can be very convenient for growth of functional structures in graphene sheets.