Visible Edge Research Articles

Fabrication of gold nanodots decorated on 2D tungsten sulfide (Au-WS2) photoanode for simultaneous oxidation of phenol and arsenic (III) from industrial wastewater

Two dimensional (2D) photoelectrocatalysts with a tunable band gap and a large surface area have emerged in recent years for advanced oxidation processes that remove toxic compounds from wastewater. In this study, ultra-thin 2D tungsten sulfide (2D WS2) photoelectrocatalysts have been fabricated using organosulfur sources, and the resulting 2D WS2 has high chemical stability and visible light band edges. Additionally, citrate stabilized Au nanodots were successfully incorporated into the 2D WS2 nanosheets in order to reduces the charge carrier recombination. The morphology, composition, chemical state, and optical properties of the Au-WS2 photoanodes have been systematically investigated. An Au-WS2 photoanode is successfully assembled in a photoelectrochemical cell (PEC) for removing phenol and oxidizing toxic As(III) into non-toxic As(V) under visible light. The studies show that the Au-WS2 photoanode had an oxidation efficiency of 99% for phenol and 95% for As(III) under visible light illumination. Furthermore, X-ray photoelectron spectroscopy (XPS) and theoretical analyses were used to investigate the oxidation pathways of phenol and As(III). A reachability study was carried out to demonstrate that mixed synthetic wastewater containing phenol and arsenite could be used for extended periods in a practical manner. In this study, Au-WS2 photoanodes were demonstrated to be highly effective in enhancing environmental remediation using advanced oxidation methods.

High efficient and stable Z-scheme g-C3N4/Zn0.5Cd0.5S photocatalyst driven by visible light for hydrogen evolution

It is extremely desirable to develop efficient and cheap water splitting photocatalysts. An ultrahigh performance and stable photocatalyst g-C3N4/Zn0.5Cd0.5S was prepared by simple sintering method. g-C3N4nanosheets are evenly distributed around 20–30 nm ZnCdS nanoparticles, which can accelerate carriers separation and transfer, and increase the carriers life-time from 4.1 ns to 5.5 ns. UV–vis absorption spectra demonstrate that their absorption range can reach to visible light edge of 539 nm. The photocatalyst has a high photocatalytic hydrogen evolution rate of 16.66 mmol•h−1•g−1 under visible light illumination (λ = 400–780 nm). Furthermore, after six recycles of photocatalyst, the hydrogen evolution stability still remains 94%. The excellent photocatalytic performance is attributed to the Z-scheme energy band structure formed between g-C3N4 and Zn0.5Cd0.5S by simple sintering method. This work provides significant progress toward the synthesis of cheap Z-scheme photocatalysts for practical applications.

ER-Pose: Learning edge representation for 6D pose estimation of texture-less objects

6D pose estimation from a single RGB image is a fundamental task in computer vision. We introduce a two-stage 6D pose estimation method for texture-less objects. Instead of utilizing the object mask in almost current monocular methods, we propose an edge representation for texture-less objects. An object is represented by the combination of visible edges corresponding to the object’s 6D pose, allowing the neural network to focus more on the object’s invariant global shape and structure, rather than indistinguishable local patches with image noise and similar texture. Given an RGB image, the proposed method predicts the direction and distance to a certain object keypoint from all object pixels within the range of object edge representation, establishes voting-based sparse 2D-3D correspondences, and solves the object pose with PnP algorithm. In the experiments, we found that directly replacing the object mask with the edge representation can bring a performance improvement in two current two-stage pipelines without any modification. Further evaluations on three different benchmark datasets containing symmetric and occluded objects show our method outperforms the state-of-the-art methods using RGB images only.

Soybean rust detection and disease severity classification by remote sensing

AbstractThe detection and monitoring of soybean rust (SBR) through remote sensing is promising because of the importance of the crop and the aspects of the disease. We evaluated the effects of different levels of SBR severity on soybean [Glycine max (L.) Merr.] leaflets reflectance aiming for the construction of a disease classification model. Leaflet reflectance was evaluated on two cultivars (susceptible and partially resistant) at four disease severity levels: healthy, low, moderate, and high. Leaflets were collected in the field and taken to the laboratory for spectral evaluation through the spectrophotometer UV 2700 coupled with Integrating Sphere Attachment ISR‐603, in the range of 270–1000 nm. The feasibility of using a collection of vegetation indices (VIs) and data dimensionality reduction through multiple factor analysis (MFA) was evaluated, and a classification model was constructed. Ten algorithms were assessed based on precision, sensibility, and accuracy parameters, using 80% of the dataset as training data and 20% as testing dataset. The visible range and red edge region contributed more significantly to the disease prediction and classification model. The MFA performed satisfactorily in the dimensionality reduction and unveiled the effect of specific wavelengths on the classification of each class. Most of the VIs studied had high correlation performance across the severity classes. Classification accuracy and precision were >70% for all models. Linear support vector machine with the collection of VIs achieved the best results. This study provides a practical path for developing a detection model to be integrated into SBR management programs.

Reply : Effect of time since primary laser-assisted in situ keratomileusis on flap relift success and epithelial ingrowth risk.

We thank Moshirfar and Basharat for their interest in our study. They were concerned about the clinical characteristics of some eyes, definition and ascertainment of the epithelial ingrowth (EI) outcome, and surgical technique. In our study, 2 cases had unsuccessful flap relift. One case had a flap created with the femtosecond laser 20 years before the enhancement surgery. The flap edge was not visible under slitlamp during preoperative examination, and therefore, the surgeon decided to perform a flap recut instead of relift. No EI developed after 3 months postoperatively. The other case had a flap created with microkeratome 12 years before the enhancement surgery. The flap could not be relifted despite a visible flap edge, and therefore, the surgeon switched to perform a flap recut. No EI developed after 1 year postoperatively. Because of the retrospective nature of our study, where no patient consent was obtained, we did not publish the clinical characteristics of each case. Instead, we presented the summary statistics and the associations of risk factors with outcomes for illustration. This also avoids potential deidentification of patients because the outcomes are rare. Clinically significant EI is commonly defined as EI that requires removal, which corresponds to EI of grade 2 or more using Probst/Machat classification.1 We defined clinically significant EI using reported criteria from other studies additionally, which we referred to as “stringent.” In other words, an EI would have been more likely to be classified as being clinically significant. This should have only overestimated the incidence and does not explain our low EI incidence. We agree that a sufficiently long postoperative follow-up period is more desirable to ensure the outcome to occur. Our study included eyes that had a postoperative follow-up of ≥75 days, given most EI would have been evident at around 3 months.2 Besides, as a retrospective study, we were unable to provide additional examinations to patients who did not come back for further checkup. Nevertheless, we believe that the EI occurrence was adequately captured. We were aware of different flap relift techniques that aim to reduce EI, such as the one by Chan et al., which we have mentioned in our study.3 However, we have hypothesized that the difference in EI incidence in our study could be due to the use of a sharp needle and aspiration at the end of the procedure, which was not the case in the study by Chan et al.3 It may be worth conducting a study to specifically compare different apparatus and techniques in the future.

Visible and near-infrared dual band switchable metasurface edge imaging

Optical edge detection at the visible and near infrared (VNIR) wavelengths is deployed widely in many areas. Here we demonstrate numerically transmissive VNIR dual band edge imaging with a switchable metasurface. Tunability is enabled by using a low-loss and reversible phase-change material Sb2S3. The metasurface acts simultaneously as a high-pass spatial filter and a tunable spectral filter, giving the system the freedom to switch between two functions. In Function 1 with amorphous Sb2S3, this metasurface operates in the edge detection mode near 575 nm and blocks near infrared (NIR) transmission. In Function 2 with crystalline Sb2S3, the device images edges near 825 nm and blocks visible light images. The switchable Sb2S3 metasurfaces allow low cross talk edge imaging of a target without complicated optomechanics.

Narrow-area Bragg-edge transmission of iron samples using superconducting neutron sensor

This study investigates a current-biased kinetic inductance detector (CB-KID) performance by investigating Bragg-edge spectra from the restricted-area neuron transmission of materials. Iron samples with a size of 5 × 5 ×2 mm3 were used as typical test materials. The ergodic theorem was used to obtain a visible transmission spectrum so that a long-time averaging of a transmission spectrum can alternatively be evaluated using a space average of independently selected area spectra with the same ensemble size. The most visible edges were observed with a limited area sample of 0.43 mm2 using a minimum time bin of 25 μs in a time-of-flight (ToF) spectrum or a wavelength resolution of 0.0007 nm of each neutron pulse at beamline BL10 of the Japan Proton Accelerator Research Complex (J-PARC) center. The main Bragg edge of iron as a sum of random 100 ensembles (with an ensemble size of 3.1 × 2.3 μm2) thus obtained has a distinctive signal-to-noise ratio and can be fitted well with the Rietveld Imaging of Transmission Spectra (RITS) program with Miller indices. We consider that our CB-KID system is, in principle, able to analyze the Bragg edge of samples as small as 3.1 × 2.3 μm2.

Dynamic strain and switchable polarization: A pathway to enhance the oxygen evolution reaction on InSnO2N

InSnO2N is a novel promising material for photoelectrochemical water splitting because of its band gap in the visible range and band edges position, which straddle the redox levels of water. Moreover, this material shows a spontaneous polarization, which could give rise to a photoferroic effect, thus enhancing the power-to-hydrogen conversion efficiency. In this work, we investigate, using Density Functional Theory (DFT) calculations, the photo-electrochemical response of this material to strain. Strain can reduce the reaction overpotentials for the Oxygen Evolution Reaction (OER) to 0.45 V for a −2.5 % compressive strain on the positively polarized material and to 0.40 V for a 2.3 % tensile strain on the negatively polarized structure. When a polarization switching is combined with a dynamic change of the strain during the reaction, the OER overpotential reaches the lowest value of 0.05 V (far below the ideal case for oxides, which is 0.37 V, and what can be reached by considering only the polarization switching at a fixed strain value). This study demonstrates the potential of InSnO2N as a catalyst for OER and highlights how surface engineering and dynamic catalysis can enhance the electro-catalytic properties of a material.

Image dehazing based on polarization information and deep prior learning

(objective)Generally, images taken under hazy weather have lower visibility and contrast. Therefore, how to improve their visibility and contrast and recover the image information is critical. Various dehazing algorithms have been proposed based on light intensity information. However, these methods mostly lack sufficient scattering information about atmospheric particles. Polarization supplies extra information independent of intensity, which can be used to effectively remove scattered light from haze particles, making it possible to help image dehazing. (methods)Therefore, this paper proposes a new image dehazing algorithm based on polarization information and deep prior learning (polarization-based unsupervised dehazing network, PUDN). Polarization information can provide more information about the image, while prior knowledge can constrain and optimize the network. This algorithm can remove haze without pretraining or corresponding ground-truth image. (result)Experimental results show that introducing polarization information and prior knowledge can improve the visibility and contrast of haze images, significantly improve haze image quality. Among them, the visible edge of heavy-haze image is improved by 71% on average, and the contrast is improved by 31 %. The dehazing performance is superior to that of traditional and supervised learning methods. Our method provides a new direction for image dehazing processing.

A novel retinal image generation model with the preservation of structural similarity and high resolution

Due to data scarcity and class imbalance in medical images, the training dataset seriously affects the classification accuracy of the model. We propose a retinal image generation model based on GAN (RetiGAN). A dual-scale discriminator is operated to train the network at two scales to improve the quality of generated images. RetiGAN can better retain the semantic information of the original images under the guidance of the content loss due to the embedding of the VGG network into RetiGAN to extract the high-level semantic information of the original and the generated images. Besides, in order to enhance the details of the generated image, RetiGAN is guided to generate the retinal images with clearer edges by feeding smoothed images to the discriminator and forcing it to distinguish the smoothed from the original ones. The qualitative and quantitative analysis verifies that the generated retinal images are similar to the original ones in structure rather than simple copies. In addition, ablation experiments exhibit that the model can improve the resolution of generated images with better visibility and clearer edges. In summary, RetiGAN is superior to other retinal image generation models in the aspects of the preservation of structural similarity and high resolution.

CuBi2O4 Based Hybrid Photocathodes for Enhancement of the Photoelectrochemical Reduction of CO2

Photoelectrochemical (PEC) CO2 reduction reaction (CO2RR) is a promising strategy to mitigate energy shortage and global warming by conversion of CO2 into chemical fuels. CuBi2O4 (CBO) is an attractive p-type photoelectrode, because it has a suitable band gap (1.5 to 1.8 eV) for visible light absorption and band edge position for PEC CO2RR. Furthermore, Cu-based catalysts can convert CO2 into multi-carbon products. However, the photoconversion efficiency of CBO is limited by short carrier diffusion length and poor photostability. In this work, we fabricated hydrothermal CBO based hybrid photocathode. The hydrothermal CBO/cellulose nano fibers (CNFs) composites with a large surface area and a porous network structure were prepared to achieve higher photocurrent density, in which CNFs are an abundant, non-toxic, and eco-friendly polymer, offering a porous and flexible network structure as a template during hydrothermal treatment. To enhance the PEC CO2RR, we introduce the ultrathin TiO2 a passivation layer deposited by atomic layer deposition (ALD) and NiO as a hole transport layer (HTL) to increase charge transport efficiency. Therefore, we will discuss enhanced performance and stability by introducing these improvement methods.

The tale of torn Descemet's membrane

To report three cases of late presentations of forceps birth trauma leading to DM tear and their management. Forceps delivery has become a rare method of child delivery in the modern clinical era. However, in the clinics, we still see patients with Descemet's membrane (DM) tear who have had ocular birth trauma with forceps. Most of the time, it is an incidental finding. Forceps injuries are usually unilateral and affect the left eye as the most common fetal head position is left occiput anterior. In the immediate postpartum period, the rupture in the DM leads to corneal edema, which eventually disappears, leaving the visible edges of the break. In the late presentations, patients can have high myopic astigmatism (steep cornea) and secondary amblyopia, which can mimic unilateral keratoconus and, later in life, can lead to corneal endothelial decompensation leading to bullous keratopathy. Here we report three cases of DM tear due to forceps injury with three late presentations. Patient 1 came with bullous keratopathy; patient 2 presented with high myopic astigmatism, amblyopia, and beaten metal appearance in between the torn edges; and patient 3 presented as keratoconus. To conclude, this case series highlights the various clinical features and signs of forceps induced birth injury to the cornea. In this report, the clinical history, ocular examination, and optical coherence tomography scan confirmed the diagnosis. Early rehabilitation with glasses or contact lenses can prevent the development of deep amblyopia. Corneal decompensation can be a presentation later in life; thus, these patients should have a close follow up. Endothelial keratoplasty helps in visual rehabilitation in cases where bullous keratopathy has developed, which can be up to the preoperative amblyopia state.

Suitability of different multivariate analysis methods for monitoring leaf N accumulation in winter wheat using in situ hyperspectral data

Leaf nitrogen accumulation (LNA) is an important indicator of crop growth, and the real-time and nondestructive estimation of LNA by hyperspectral remote sensing is crucial for crop N management. In this study, five field experiments were conducted over four successive years at three ecological sites (Xinyang, Zhengzhou and Zhoukou) in Henan, China, incorporating different N amounts and wheat varieties. The canopy spectral data were obtained by a ground-based spectrometer, and the original spectral reflectance (R) was transformed using continuum removal (CR), first-derivative reflectance (FDR) and inverse-log reflectance (log (1/R)) methods. The effective bands of the above four transformed reflectance data were selected by the variable importance in projection (VIP) scores of the partial least square regression method (PLSR). Then, four multivariate regression methods (PLSR, stepwise multiple linear regression (SMLR), extreme learning machine (ELM) and support vector machine (SVM)) were used to develop an optimal forecasting model for LNA in winter wheat. The results show that FDR spectral data had the best comprehensive performance and were a better method for spectral data preprocessing. In the comparison of different nonparametric algorithms, the SVM model performed the best using the full wavelengths, in which R2cal/val and RMSEcal/val were 0.927–0.963/0.899–0.925 and 0.725–1.066/1.161–1.331 g m−2, respectively. The characteristic bands of FDR were mainly distributed in the visible light and red edge regions (445, 501, 546, 683, 747 and 771 nm, respectively), and these effective bands were consistent under different field conditions. The SVM regression method using the effective wavelengths of FDR exhibited excellent performance for LNA prediction with R2val = 0.875 and RMSEval = 1.294. In addition, the FDR-PLSR-SVM model produced satisfactory inversion results under different field conditions. The accuracy of the filling period was better than that of the reviving-anthesis growth period, which might be due to diminished N dilution and stable canopy structure during the reproductive stage. R2val and RMSEval of the FDR-PLSR-SVM model during the filling period were 0.914 and 1.156 g m−2 in Xinyang, 0.825 and 1.542 g m−2 in Zhengzhou and 0.796 and 1.902 g m−2 in Zhoukou, respectively. Considering the advantages of simple and efficient computer calculations, the FDR-PLSR-SVM algorithm is strongly recommended to predict the LNA in winter wheat. This study provides a reference basis for the selection of effective wavelengths for N nutrition diagnosis by unmanned aerial vehicles and satellite remote sensing in the future.

Research on controllable deep learning of multi-channel image coding technology in Ferrographic Image fault classification

Utilizing computer technology to realize ferrographic analysis and intelligent fault diagnosis technology is fundamental research to ensure the normal operation of precision, complex and severe marine mechanical equipment. This work is focused on the issues that affect the feature extraction and accuracy of the computer model, such as fuzzy edge and complex surface texture of wear particle image in ferrographic image. This research creatively establishes a new multi-channel image encoder, which artificially encodes the information of the original ferrographic image. The new encoding image includes the original channel information, artificial edge enhancement information, and artificial surface enhancement information, to improve the edge and surface features of the image. The encoder can not only improve the visible edge and surface characteristics of the picture but also form the MCECNN model after connecting to the convolutional neural network. The model can successfully improve the accuracy, convergence speed, generalization, and controllability of the model, to solve the problem of online intelligent recognition in the field of ferrography to the greatest extent.

Lead-free vacancy ordered double perovskites In2Pd (Br/I)6 for solar cells, and thermoelectric applications

The renewable energy sources are explored vastly in the world to fulfil the demands of energy. In the present article the optical, electronic, and thermoelectric properties of vacancy ordered double perovskites In2Pd(Br/I)6 are explored comprehensively. The tolerance factor is computed by atomic radii to confirm structural stability and formation energy is computed for thermodynamic stability. The computed band gaps 1.2 eV and 0.9 eV for In2PdBr6 and In2PdI6, respectively. The absorption coefficient, and dielectric constant confirm the absorption in visible region for In2PdBr6, and infrared to visible edge for In2PdI6. The less reflection and optical loss of light in visible range raises their importance for solar cells. Furthermore, transport characteristics are addressed by the BoltzTraP code. The ultralow lattice thermal conductivity, and substantial standards of figure of merit also get them appropriate for thermoelectric devices.

Glass formation and optical properties of Sn modified GeS2-Ga2S3-CsCl chalcogenide glasses

Chalcogenide glass is emerging as important IR materials for advanced athermal infrared (IR) optical systems because of its low thermal coefficient of refractive index. New chalcogenide glasses based on 75GeS2-15Ga2S3-10CsCl were developed through the substitution of GeS2 by SnS2. The introduction of heavier tin (Sn) results in the red shift of transmission window, both of visible and long-wavelength IR cut-off edges, the elevation of refractive index dispersion curves, and the decreasing of glass transition temperature. The formation of [SnS4-xClx] structural units, instead of [GeS4-xClx], should be responsible for the variation of these structural properties. In addition, homogeneous Sn modified GeS2-Ga2S3-CsCl chalcogenide glass of Φ30 mm was also prepared successfully, showing it of high potential for commercial applications.

Unidirectional transmission of visible region topological edge states in hexagonal boron nitride valley photonic crystals.

Here we theoretically design valley photonic crystals (VPCs) based on two-dimensional (2D) hexagonal boron nitride (hBN) materials, which are able to support topological edge states in the visible region. The edge states can achieve spin-dependent unidirectional transmission with a high forward transmittance up to 0.96 and a transmission contrast of 0.99. We further study the effect of refractive index on transmittance and bandwidth, and it is found that with the increase of refractive index, both transmittance and bandwidth increased accordingly. This study opens new possibilities in designing unidirectional transmission devices in the visible region and will find broad applications.

Time series classification based on complex network

Time series classification is an important topic in data mining. Time series classification methods have been studied by many researchers. A feature-weighted classification method is proposed based on complex network. There are four stages in the proposed classification algorithm. First, we obtain visible points and edge weights by applying an improved weighted visibility graph algorithm to transform the original time series into weighted complex networks. Next, weighted features are calculated based on visible points and weights, and unable-weighted features are obtained by utilizing NetworkX. After that, we combine two types of features to obtain a total features matrix. We then reconsider the weight of each independent feature by utilizing the importance function of random forest to measure the relative importance of features and construct a importance weighted features matrix. Finally, we utilize a traditional classifier called random forest to cluster the weighted features matrix and generate classification results. Simultaneously, a novel feature weight calculation method is applied during the classification process. We compare the proposed method to other classification methods and the results indicate that the proposed method can improve classification accuracy for time series datasets.

Measuring margin and skew errors in scanned printed customer content

Print margin and skew describe an image placed crookedly on the printed page. It is one of the most common defects in electrophotographic printers and dramatically affects print quality. It primarily might occur when using a two-sided printing module on the printer. To solve or correct the print margin and skew error, we should first accurately detect the print margin and skew on the printed page. This paper proposes a method to accurately detect the print margin and skew based on the Hough Lines Detection algorithm. There are three steps of this print margin and skew detection method. We first project the digital master images into the scanned test image with master image edges. The second step is the most challenging part of designing this method because all of our scanned test pages had only two or three and barely visible edges of the printed paper to the naked eye. We use an image processing method and Hough Lines Detection algorithm to extract the paper edges. The third step uses the projected master images edge and the extracted paper edges to calculate the print margin and skew result. Our algorithm is an efficient and accurate method to detect print margin and skew errors based on factual scanned image verification.

Pyrochlore-structural Nd2Ta2O5N2 photocatalyst with an absorption edge of over 600 nm for Z-scheme overall water splitting.

A pyrochlore-structural oxynitride Nd2Ta2O5N2 with a visible light absorption edge of ca. 620 nm was explored for photocatalytic water splitting. Dual functions of Nd2Ta2O5N2 were confirmed by proton reduction and water oxidation half-reactions through separately loading Pt or CoOx as a cocatalyst in the presence of the corresponding sacrificial reagent. Finally, the platinum modified sample (Pt/Nd2Ta2O5N2) was prepared and employed as the H2-evolving photocatalyst to fabricate an effective photocatalytic Z-scheme overall water splitting together with PtOx/WO3 as the O2-evolving photocatalyst and IO3-/I- as shuttle ions under visible light irradiation.