Fabric defect detection plays an important role in the textile production process, but there are still some challenges in detecting defects rapidly and accurately. In this paper, we propose a ...powerful detection method for automatic fabric defect detection using a deep convolutional neural network (CNN). It consists of three main steps. First, the fabric image is decomposed into local patches and each local patch is labelled. Then the labelled patches are transmitted to the pretrained deep CNN for transfer learning. Finally, defects are detected during the inspection phase by sliding over the whole image using the trained model, and the category and position of each defect is obtained. The proposed method is validated on two public and one self‐made fabric database. The experimental results demonstrate that our method significantly outperforms selected state‐of‐the art methods in terms of both quality and robustness.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
In order to solve the current energy crisis, it is necessary to develop an economical and environmentally friendly alternative energy storage system in order to provide potential solutions for ...intermittent renewable energy sources such as solar and wind energy. Redox flow battery (RFB) is reviving due to its ability to store large amounts of electrical energy in a relatively efficient and inexpensive manner. RFBs also have unique characteristics, which make them more attractive than conventional batteries. For example, they can separate the rated maximum power from the rated energy, and have greater design flexibility. The iron-based aqueous RFB (IBA-RFB) is gradually becoming a favored energy storage system for large-scale application because of the low cost and eco-friendliness of iron-based materials. This review introduces the recent research and development of IBA-RFB systems, highlighting some of the remarkable findings that have led to improving battery performance over the years. The role of components such as the electrode, membrane, and electrolyte in the overall function and the relevant work in this field are comprehensively reviewed and discussed. Finally, the challenges and future research directions are proposed briefly.
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•The current development status of IBA-RFBs in energy storage has been reviewed.•Comprehensive coverage of components of IBA-RFBs is given.•The working principle, battery performance, and cost of IBA-RFBs are highlighted.•The advantages, disadvantages, and challenges of IBA-RFBs are discussed.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
Circulating exosomal microRNAs (exomiR) have been demonstrated to be novel diagnostic biomarkers for various cancers. In this study, we found that circulating exomiR-1229 levels were significantly ...increased in the serum exosomes of patients with colorectal cancer (CRC) and significantly associated with tumor size, lymphatic metastasis, TNM stage and poor survival. Treatment with siRNA-Drosha, siRNA-ALIX and GW4869 repressed the expression of exomiR-1229 secreted from CRC cells. Both CRC-derived exosomes and exomiR-1229 mimic promoted the tubulogenesis of HUVECs, but transfection with exomiR-1229 inhibitor anta-miR-1229 significantly suppressed tube formation. Subsequently, HIPK2 was identified as a target of exomiR-1229 and responsible for the effect of exomiR-1229 on angiogenesis of HUVECs. ExomiR-1229 inhibited the protein expression of HIPK2, thereby activating VEGF pathway. Finally, anta-miR-1229 effectively inhibited tumor growth and angiogenesis in the nude mouse xenograft model. These results highlighted a novel mechanism of CRC angiogenesis and the biological roles of exomiR-1229.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
The vigorous development of modern information and communication technology (ICT) has driven the digital trade featured by the ICT technique and industry as the carrier. This study empirically tests ...the impact of ICT-based digital trade openness on green total factor productivity (GTFP) by selecting ICT as the representative digital trade data of 30 provinces in China over the timespan 2002–2018. We employ the slack-based model and global Malmquist–Luenberger (SBM-GML) estimation method to calculate the provincial GTFP and explore the heterogeneous impact of digital trade openness on GTFP through the scale effect, technology effect, and structure effect. In terms of empirical results, the panel fixed model and panel quantile estimation model both suggest the same findings. With the continuous expansion of the scale of digital trade, its scale effect has a significant inhibitory effect on GTFP, whereas the structure effect combined with human capital and the technology effect correlated with technological research and development (R&D) have a significant promoting effect on GTFP. The panel quantile regression model reveals that the interaction intensity increases gradually from a low quantile to high quantile. Further robustness tests also verify the consistency and stability of the results. Finally, the study puts forward corresponding practical suggestions for the construction of a high-quality open pattern of digital trade and the coordinated development of GTFP. The specific policy implications include the following: (1) Emphasize on the penetration and connection effect of the new generation of ICT, and strengthen the construction of enterprise informatization. (2) Expand digital trade openness and broaden the field of industrial cooperation. (3) Optimize the industrial structure of digital trade, and accelerate the development of core industries of digital trade. (4) Gradually promote the transformation of digital trade from relying on quantity and scale to product quality.
In this study, three different fermentation methods, such as photo-fermentation (PF), dark-fermentation (DF) and dark-photo co-fermentation (DPCF) for bio-hydrogen production from corn stover were ...compared in terms of hydrogen production, substrate consumption, by-products formation and energy conversion efficiency. A modified Gompertz model was applied to perform the kinetic analysis of hydrogen production. The maximum cumulative hydrogen yield of 141.42 mL·(g TS)−1 was achieved by PF, DF with the minimum cumulative hydrogen yield of 36.08 mL· (g TS)−1 had the shortest lag time of 4.33 h, and DPCF had the maximum initial hydrogen production rate of 1.88 mL· (g TS)−1·h−1 and maximum initial hydrogen content of 44.40%. The results also indicated PF was an acid-consuming process with a low total VFAs concentration level of 2.90–4.19 g·L−1, DF was a process of VFAs accumulation with a maximum total VFAs concentration of 12.66 g·L−1, and DPCF was a synergistic process in which the total VFAs concentration was significantly reduced and the hydrogen production efficiency was effectively improved compared with DF. The energy conversion efficiency of PF, DF and DPCF were 10.12%, 2.58% and 6.45%, respectively.
•PF, DF and DPCF for bio-hydrogen production from corn stover were compared.•PF was a more promising method for bio-hydrogen production from corn stover.•DPCF effectively improved the hydrogen production efficiency when compared to DF.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP
The electromagnetic-inverse-scattering (EMIS) problem is solved by a novel two-step deep-learning (DL) approach in this article. The newly proposed two-step DL approach not only predicts the ...multifrequency EM scattered field, but also overcomes the limitation of the conventional methods for solving EMIS problems, such as expensive computational cost, strong ill-conditions, and invalidity on high contrast. In the first step, the complex-valued deep residual convolutional neural network (DRCNN) is utilized to predict multifrequency EM scattered fields only using single-frequency EM scattered field information. Based on a new complex-valued deep convolutional encoder-decoder (DCED) structure, the second step utilizes the obtained multifrequency EM scattered field "images" to realize the reconstruction of the target scatterers. In such a manner, the proposed approach can solve the EMIS problem accurately and efficiently even for inhomogeneous and high-contrast scatterers. The training of the proposed two DL models is based on the simple synthetic dataset. Numerical examples based on various dielectric objects are given to demonstrate the accuracy and performance of the newly proposed approach. The proposed DL-based method opens a new path for handling real-time quantitative microwave imaging.
Li anodes have been rapidly developed in recent years owing to the rising demand for higher‐energy‐density batteries. However, the safety issues induced by dendrites hinder the practical applications ...of Li anodes. Here, Li metal anodes stabilized by regulating lithium plating/stripping in vertically aligned microchannels are reported. The current density distribution and morphology evolution of the Li deposits on porous Cu current collectors are systematically analyzed. Based on simulations in COMSOL Multiphysics, the tip effect leads to preferential deposition on the microchannel walls, thus taking full advantage of the lightening rod theory of classical electromagnetism for restraining growth of Li dendrites. The Li anode with a porous Cu current collector achieves an enhanced cycle stability and a higher average Coulombic efficiency of 98.5% within 200 cycles. In addition, the resultant LiFePO4/Li full battery demonstrates excellent rate capability and stable cycling performance, thus demonstrating promise as a current collector for high‐energy‐density, safe rechargeable Li batteries.
A new strategy to restrain lithium dendrite growth is proposed and demonstrated using vertically aligned microchannel Cu current collectors for Li metal anodes. Most of the lithium is preferentially deposited into the microchannels. The current‐density distribution, deposition behavior, and electrochemical performance are simulated and investigated experimentally to understand the effectiveness of the microchannel structure.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Alzheimer's disease (AD) continues to be a major global health challenge, and the recent approval of Aduhelm and Leqembi has opened new avenues for its treatment. Small‐molecule inhibitors targeting ...Aβ aggregation hold promise as an alternative to monoclonal antibodies. In this study, we evaluated the ability of berbamine hydrochloride (BBMH), a member of the bisbenzylisoquinoline alkaloids, to reduce Aβ aggregation and cytotoxicity. Thioflavin T kinetics, circular dichroism spectroscopy, and atomic force microscopy results indicated that BBMH effectively inhibited Aβ aggregation. Surface plasmon resonance and molecular docking results further revealed that BBMH could bind to Aβ fibrils, thereby hindering the aggregation process. This physical picture has been confirmed in a quantitative way by chemical kinetics analysis, which showed BBMH tends to bind with the fibril ends and thus prevents the transition from protofibrils to mature fibrils as well as the elongation process. Additionally, our MTT results showed that BBMH was able to reduce the cytotoxicity of Aβ40 on N2a cells. Our results demonstrate, for the first time, the potential of BBMH to inhibit Aβ aggregation and cytotoxicity, offering a promising direction for further research and drug development efforts in the fight against Alzheimer's disease.
The inhibitory effects of berbamine hydrochloride (BBMH) on Aβ aggregation were comprehensively evaluated using several widely‐used biophysical assays. Furthermore, the inhibitory mechanisms of BBMH were elucidated through SPR analysis and chemical kinetics analysis. These findings suggest that bisbenzylisoquinoline alkaloids hold great promise in the battle against Alzheimer's disease.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
This paper proposes a novel deep learning (DL) approach to solve electromagnetic inverse scattering (EMIS) problems in inhomogeneous media. The conventional approaches for solving inhomogeneous EMIS ...problems generally have to consider inhomogeneous Green's functions or conduct approximation operations to media, which inevitably introduces various challenges, including complex mathematical derivation, high computation cost, unavoidable nonlinearity and even strong ill-posedness. To avoid these challenges, we propose a DL approach based on the complex-valued deep convolutional neural networks (DConvNets), which comprise of the deep convolutional encoder-decoder (DCED) structure. Its training data are collected based on the simple synthetic dataset. While the scattered fields received in measurement domain is utilized as the input for the encoder to extract feature fragments, the final output for the counterpart decoder is the contrasts (permittivities) of dielectric scatterers in target domain. In this way, unlike the conventional methods, the unknown domain between target domain and measurement domain never has to be considered to compute inhomogeneous Green's functions. Consequently, the inhomogeneous EMIS problems could be solved with higher accuracy even for extremely high-contrast targets. Numerical examples illustrate the feasibility of the proposed DL approach. It acts as a new candidate for solving EMIS problems in inhomogeneous media.
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•Lemon seed residue was utilized as a raw material for CNCs extraction.•CNCs were isolated using acid hydrolysis, APS oxidation and TEMPO oxidation.•Extraction method can influence ...the structure and properties of CNCs.•CNCs by acid hydrolysis and APS oxidation can stabilize Pickering emulsions better.
In this study, the lemon (Citrus limon) seeds as typical agricultural processing wastes were utilized to extract cellulose nanocrystals (CNCs) by sulfuric acid hydrolysis (S-LSCNC), ammonium persulfate oxidation (A-LSCNC) and TEMPO oxidation (T-LSCNC). The properties of CNCs were comparatively investigated by Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), thermogravimetric analysis (TG), and atomic force microscope (AFM), and the application in Pickering emulsions was also preliminarily studied. The results showed that all CNCs maintained cellulose Iβ structure and had a good dispersion regardless of extraction methods. Differently, T-LSCNC had a higher yield, larger size and lower CrI than A-LSCNC and S-LSCNC. Comparatively, A-LSCNC showed the highest CrI and S-LSCNC showed the lowest size. For the application of Pickering emulsions, S-LSCNC and A-LSCNC showed a better ability as Pickering stabilizers than T-LSCNC. This study is beneficial for developing the potential utilization of CNCs from lemon by-products.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPUK, ZAGLJ, ZRSKP