Safe and efficient protection against chemical warfare agents is of strategic importance in human society due to their lethal damage to living organisms. Current protective materials are confronted with defects of incomplete elimination, slow degradation, and potential secondary toxicity during exposure to chemical warfare agents in real environments. Herein, asymmetric nanofiber membranes (ANMs) in side‐by‐side heterostructure are constructed by a scalable dual‐channel electrospinning strategy with a polyvinyl alcohol skeleton, hygroscopic LiCl, amine‐rich polyethyleneimine as a non‐volatile base, and defective UiO‐66‐NH 2 nanoparticles as the catalyst for simultaneous moisture adsorption and catalytic hydrolysis of a nerve agent simulant of dimethyl 4‐nitrophenyl phosphate (DMNP) in a wide range of relative humidity. The ANMs exhibit fast hydration, effective transport, and high‐density storage of water molecules with a high moisture adsorption capacity of 1.74 g g −1 at 90% relative humidity. The side‐by‐side heterostructure of ANM shortens the mass transport path and accelerates the catalytic hydrolysis of DMNP with an initial half‐life of ≈0.56 h and conversion efficiency of more than 95%. The synergistic hygroscopic and catalytic effect of the asymmetric nanofiber membrane promotes the detoxification of DMNP in the atmospheric environment, providing a smart strategy for materials design against chemical warfare agents.

High-performance all-solid-state fiber supercapacitors assembled with MXene/RGO/PEDOT:PSS hybrid fiber electrodes with radially oriented channels and an anti-freezing electrolyte exhibit excellent capacitance retention at ultralow temperatures.

Although atmospheric water harvesting is a promising approach for extracting clean water in water deficient areas, most atmospheric water collectors require additional energy for releasing the water absorbed. It is still challenging to improve both moisture absorption capacity and desorption efficiency of moisture water collectors. Inspired by clean solar energy and the large humidity difference between day and night, super-hygroscopic calcium chloride (CaCl2)/graphene oxide (GO)/poly(N-isopropylacrylamide) (PNIPAM) gels are designed for spontaneous collection of atmospheric water in a wide range of relative humidity (RH) followed by solar-driven release of the water absorbed. An optimal CaCl2/GO/PNIPAM hygroscopic gel possesses a hierarchical porous structure with directional water transport channels, facilitating water capture and release, thus exhibiting a high moisture absorption capacity of up to 3.6 g g-1 at an RH of 90%. Driven by simulated sunlight, the solar-thermal energy conversion effect of the GO component triggers a unique hydrophilic-hydrophobic conformational transition and shrinkage of the PNIPAM for efficient release of the water absorbed. The integration of the spontaneous harvesting of atmospheric water and the solar-driven water release makes the super-hygroscopic gels promising for efficiently utilizing atmospheric water for special applications where water is desperately necessary but unavailable.

An improved maritime object detection algorithm, SRC-YOLO, based on the YOLOv4-tiny, is proposed in the foggy environment to address the issues of false detection, missed detection, and low detection accuracy in complicated situations. To confirm the model’s validity, an ocean dataset containing various concentrations of haze, target angles, and sizes was produced for the research. Firstly, the Single Scale Retinex (SSR) algorithm was applied to preprocess the dataset to reduce the interference of the complex scenes on the ocean. Secondly, in order to increase the model’s receptive field, we employed a modified Receptive Field Block (RFB) module in place of the standard convolution in the Neck part of the model. Finally, the Convolutional Block Attention Module (CBAM), which integrates channel and spatial information, was introduced to raise detection performance by expanding the network model’s attention to the context information in the feature map and the object location points. The experimental results demonstrate that the improved SRC-YOLO model effectively detects marine targets in foggy scenes by increasing the mean Average Precision (mAP) of detection results from 79.56% to 86.15%.

Transparent superhydrophobic films are attractive for applications in a wide range of fields, such as electronics, windshields and displays. However, it is especially challenging to manufacture a superhydrophobic film with high transparency and mechanical robustness because the high transparency and superhydrophobicity are generally competitive surface properties while the robustness and water repellency are also mutually exclusive. In this paper, transparent superhydrophobic boehmite (γ-AlOOH) films modified by perfluorodecyltrisethoxysilane (C16H19F17O3Si) with different morphology were prepared via a simple hydrothermal method in a solution of Al(NO3)3·9H2O and CH3COONa. The results showed that morphology impacted the wettability, transparency and mechanical durability of the film. The superhydrophobic boehmite film synthesized at the proportion of 40: 1 (Al(NO3)3·9H2O: CH3COONa) consisted of nano scale flaky boehmite clusters perpendicular to the glass surface and micro-nano scale pores between the crystals and achieved a high wear resistance, good chemical stability and appropriate transparency. The formation mechanism of this film and the reason for its mechanical robustness was explored in this paper. It was proposed that the excellent wear resistance benefited from the frame microstructure formed by interconnected flaky crystal clusters as well as the chemical bonding between the boehmite grain and the glass substrate. The nanostructure boehmite film prepared by the simple hydrothermal method in this paper not only could reach a proper balance between superhydrophobicity and transparency, but also exhibited an excellent mechanical durability, which demonstrated a potential application prospect in the field of transparent superhydrophobicity.

The permanent magnetic suspension dust-free conveying system is introduced. According to the suspension force model and the prototype structure, a nonlinear model of the control decoupling system is established. Using the coordinate transformation decoupling strategy, four-point independent control is changed to a three-degree-of-freedom control suspension vehicle. Finally, PID control and fuzzy PID control are used to simulate the displacement step of the permanent magnet levitation vehicle with three degrees of freedom. The simulation results show that the PID controller has a faster response speed and can return to a stable position after several oscillations. The adjustment time is 0.3 seconds, but the overshoot is relatively large, about 8%. For the fuzzy PID platform, the rise time is about 0.2s, the steady-state error is about 1%, there is no overshoot, and the system has good rigidity, damping characteristics, and robustness.

Flexible and lightweight supercapacitors with satisfactory energy density and long-term stability are urgently required to provide power for flexible, foldable, and wearable electronic devices. Herein, reedlike carbon nanofibers (RCNFs) with hierarchical macropores in the core and micropores and honeycomb mesopores in the shell are designed by electrospinning, carbonization, and etching, leading to high electronic conductivity and satisfactory mechanical flexibility and foldability. Subsequently, flowerlike Ni-Co-S nanoarrays are grown in situ on RCNFs by electrodeposition, and fern leaf-like Fe2O3-C core-shell nanoneedles, in which porous Fe2O3 are coated with ultrathin carbon layers, are decorated on RCNFs via hydrothermal synthesis, polydopamine modification, and thermal annealing. Because of unique core-shell structures and synergistic effects of these active components, the RCNF@ Ni-Co-S cathode and the RCNF@Fe2O3-C anode exhibit high specific capacitances of 1728 and 221.5 F g(-1) at 1 A g(-1), respectively. With a poly(vinyl alcohol) (PVA)/potassium hydroxide (KOH) solid gel as both an electrolyte and a separator, the assembled flexible quasi-solid-state asymmetric supercapacitor achieves a high energy density of 44.9 W h kg(-1) at 1549.7 W kg(-1), and the capacitance remains at 94% after bending the asymmetric supercapacitor to 180 degrees. The flexible electrodes with excellent electrochemical performances are highly promising for high-performance wearable energy storage devices.

Polyacrylamide (PAM)-based microspheres are commonly used as water plugging and profile control agents, but the poor mechanical strength and few studies on the dispersion stability, both of which are closely related to the profile control performance, limit the application of microspheres. Herein, we synthesize nanoscale PAM-based copolymer hydrogel microspheres with an inverse microemulsion copolymerization of acrylamide (AM) and 2-methyl-2-acrylic amide propyl sulfonic acid (AMPS) in the presence of vinyl-functionalized silica nanoparticles (VSNPs). The results show that a small amount of VSNPs (1.0 wt %) increases the compressive strength of the hydrogel by 0.6 times. The swollen nanoscale PAM/silica hydrogel microspheres show good dispersion stability. VSNPs significantly improve the elasticity of the hydrogel microspheres, and their dispersion stability under high temperature and high-salinity conditions. The simulation evaluation of core plugging suggests that the plugging rate of PAM-based polymer/silica hybrid microspheres with addition of 0.7 wt % VSNPs increases from 80% to 92% compared to neat polymer microspheres. This work provides a novel design of nanoscale cross-linked microspheres for deep profile control in different geological environments.

The 40Bi2O3-30B2O3-(30−x)ZnO-xSrO (x=0–15mol%, BBZSr) glass system was prepared by the conventional melt quenching method. The effect of SrO addition on structure, thermal properties, chemical stability and sealing performance of BBZSr glass were investigated thoroughly. The experimental results show that the total proportions of [BO3] group and [BO4] group decrease and the vibrations of [BiO3] group and [BiO6] group become weaker with the increase of SrO addition content, suggesting the glass network structure is strengthened owing to the SrO addition. Hence, both the thermal and chemical stability were significantly improved as the SrO content was increased. When the SrO content increased from 0 to 15mol%, the glass transition temperature and softening temperature slightly increased from 380 to 388 °C and from 392.7 to 402.2 °C, respectively, meanwhile the coefficient of thermal expansion also increased from 10.49×10−6 to 11.16× 10−6/°C (30–300 °C). The BBZSr glass with 15mol% SrO exhibited excellent comprehensive properties with low glass transition temperature(384.9 °C), low softening temperature(400.3 °C), high coefficient of thermal expansion (11.14×10−6 C, 30–300 °C), good thermal and chemical stability. Besides, the glass had the good wetting behavior and sealing performance for Al-50%Si alloy.

As ultralight and superelastic aerogels are quite desirable for pressure sensing and energy storage applications, superelastic and ultralight carbon nanofiber (CNF)/transition metal carbides and carbonitrides (MXenes) hybrid aerogels with anisotropic microchannels are thus fabricated by liquid nitrogen-assisted unidirectional-freezing followed by freeze-drying. The CNFs with high aspect ratios entangle and assemble into the interconnected scaffolds, while the MXene sheets enhance structural stability of the framework of CNFs and endow the aerogels with satisfactory electronic conductivities. Benefiting from the stable architecture with orientated microchannels, the CNF/MXene aerogel (CNF/MX) with an ultralow density of 4.87 mg cm(-3) exhibits superb compressible resilience at the strain of 50% for at least 5000 cycles and a high strain of 95% for 500 cycles. Importantly, the outstanding strain- or pressure-responses endow the CNF/MX aerogel sensor with high sensitivity (65 kPa(-1)), ultralow detection limit (<5 Pa), rapid response (26 ms), large workable strain range (0-95%), and superb response stability. Furthermore, the presence of MXene with excellent electrochemical activity makes the binder-free CNF/MX electrode exhibit a high rate performance with 80% capacitance retention when the current density increases by 100 times and a high cycling stability with capacitance retention of 90% after 20,000 cycles at 5 A g(-1). (C) 2020 Elsevier Inc. All rights reserved.

The development of switchable wettability membranes with high permeation fluxes is crucial for oily sewage treatment. A hierarchical beadlike porous PS fibrous membrane with pH-switchable wettability was precisely fabricated by nonsolvent-induced phase separation during electrospinning, followed by UV photografting copolymers of 2-(dimethylamino) ethyl acrylate (DMAEA) and 3,3,4,4,5,5,6,6,7,7,8,8,8-tridecafluorooctyl acrylate (TFOA). The designed unique structure notably increases the roughness of surface and enhances superwettability. Protonation of the amine groups on the fibers triggered by an acid solution (pH < 2) induces underwater super-oleophobicity, which in turn causes superoleophilicity in a neutral or basic solution. The as-prepared fibrous membrane can effectively separate the hexane/water mixture with an oil flux of 10 186.8 L m(-2) h(-1) and a separation efficiency of 99.2% only driven by gravity. Especially, excellent separation performances (water fluxes) were also realized for other oil/water mixtures with higher viscosity by switching the wettability from superoleophilicity to hydrophilicity. Moreover, the as-prepared fibrous membrane can also be applied to a continuous T-shaped tube device delivering a high handling capacity of 6631.5 L m(-2) h(-1), which provides the oily sewage treatment with a facile strategy in practical application.

Novel bimetallic nickel cobalt telluride nanotubes are grown on nickel foam by solvothermal synthesis and ion-exchange reaction for constructing self-standing hybrid supercapacitor electrodes with high specific capacity and electrical conductivity.

Speckle is a kind of noise commonly found in ultrasound images (UIs). Although traditional local operation-based methods, such as bilateral filtering, perform well in de-noising normal natural images with suitable parameters, these methods may break local correlations and, hence, their performance will be highly degraded when applied to UIs with high levels of speckle noise. In this work, we propose a new method, based on superpixel segmentation and detail compensation, to reduce UI speckle noise. In particular, considering that superpixel segmentation has the advantage of adhering accurately to the boundaries of objects or local structures, we propose a superpixel version of bilateral filtering to better protect the local structure during de-noising. Additionally, a human visual system (HVS)-inspired strategy for spatial compensation is introduced, in order to recover sophisticated edges as much as possible while weakening the high-frequency noise. Experiments on synthetic images and real UIs of different organs show that, compared to other methods, the proposed strategy can reduce ultrasound speckle noise more effectively.

We propose an underwater image enhancement model inspired by the morphology and function of the teleost fish retina. We aim to solve the problems of underwater image degradation raised by the blurring and nonuniform color biasing. In particular, the feedback from color-sensitive horizontal cells to cones and a red channel compensation are used to correct the nonuniform color bias. The center-surround opponent mechanism of the bipolar cells and the feedback from amacrine cells to interplexiform cells then to horizontal cells serve to enhance the edges and contrasts of the output image. The ganglion cells with color-opponent mechanism are used for color enhancement and color correction. Finally, we adopt a luminance-based fusion strategy to reconstruct the enhanced image from the outputs of ON and OFF pathways of fish retina. Our model utilizes the global statistics (i.e., image contrast) to automatically guide the design of each low-level filter, which realizes the self-adaption of the main parameters. Extensive qualitative and quantitative evaluations on various underwater scenes validate the competitive performance of our technique. Our model also significantly improves the accuracy of transmission map estimation and local feature point matching using the underwater image. Our method is a single image approach that does not require the specialized prior about the underwater condition or scene structure.

[目的]本研究旨在有效解决果皮有缺陷的水果图像在去除背景时部分缺陷被误分割为背景,以及水果表面缺陷难以有效分割提取的问题.[方法]以I分量图来构建掩模模板,根据其灰度直方图信息,通过双峰法选择单一阈值(T=75)分以纽荷尔脐橙为研究对象,提出基于HSI颜色空间模型法去除背景割背景并填充孔洞得到掩模模板Imask,然后掩模模板Imask与I分量图通过点乘运算得到去除背景的I分量图;提出基于多尺度高斯函数图像亮度校正算法对去除背景后的I分量图像进行亮度校正,通过构建多尺度高斯函数滤波器,将去除背景后的I分量图与构建的多尺度高斯函数进行卷积运算即得到去除背景后的I分量图像表面光照分量图,最后将去除背景后的I分量图与得到的光照分量图进行点除运算即得到去除背景后的I分量图像亮度校正图;然后采用单一全局阈值法对脐橙表面缺陷进行提取.[结果]基于HSI颜色空间模型法去除背景,可在有效去除背景的同时完好保留脐橙的表面信息,有利于后续操作;基于多尺度高斯函数的图像亮度校正算法分别对6种常见脐橙缺陷进行图像亮度校正后采用单阈值法提取缺陷,使不同灰度等级的脐橙表面缺陷一次性分割成功,其中分割率最高为100％,最低为88.5％,整体达92.7％.通过试验分析后发现造成部分误分割或漏分割的原因主要在于部分缺陷果缺陷处颜色较轻,与正常区域灰度差较小,从而造成漏分割;还有部分缺陷果由于缺陷面积小,在图像形态学处理过程被误认为是噪声而被去除;同时发现正常果的误判率也达到了10.8％,经分析发现误判的正常果表皮组织区域的褶皱位于图像的边缘区域,从而被误认为是边缘区域的缺陷,导致误判.[结论]基于HSI颜色空间模型法去除背景及基于多尺度高斯函数的图像亮度不均校正算法对纽荷尔脐橙图像背景分割和去除背景后的I分量图像表面亮度校正均取得了较好的效果,能有效识别脐橙缺陷区域,为脐橙精确分级提供了技术支持,也为其他果品表面缺陷快速检测提供了一种新思路.

With very simple implementation, regression-based color constancy (CC) methods have recently obtained very competitive performance by applying a correction matrix to the results of some low level-based CC algorithms. However, most regression-based methods, e.g., Corrected Moment (CM), apply a same correction matrix to all the test images. Considering that the captured image color is usually determined by various factors (e.g., illuminant and surface reflectance), it is obviously not reasonable enough to apply a same correction to different test images without considering the intrinsic difference among images. In this work, we first mathematically analyze the key factors that may influence the performance of regression-based CC, and then we design principled rules to automatically select the suitable training images to learn an optimal correction matrix for each test image. With this strategy, the original regression-based CC (e.g., CM) is clearly improved to obtain more competitive performance on four widely used benchmark datasets. We also show that although this work focuses on improving the regression-based CM method, a noteworthy aspect of the proposed automatic training data selection strategy is its applicability to several representative regression-based approaches for the color constancy problem.

Particle swarm optimization (PSO) has many advantages such as fewer parameters, faster convergence and easy implementation; however, it is also prone to fall into local optimum. Because inertia weight parameters can increase the diversity of particles and effectively overcome this problem, a large number of studies have done on inertia weight strategy since it was put forward, and many different improvement strategies have been put forward, but these improvement strategies still do not make full use of the multi-dimensional information of particles, resulting in limited improvement of PSO performance. In this study, on the one hand, based on the summary of current inertial weight strategies, aiming at the problems existing in the classification of inertial weight strategies, the inertial weight strategies are reclassified. According to the new classification methods, the inertial weight strategies are divided into four categories, including “no variable with iteration”, “single variable with iteration”, “double variables with iteration” and “triple variables with iteration” inertia weight. On the other hand, in view of the shortcomings of the existing inertial weight improvement strategies, this study proposes a multi-information fusion “triple variables with iteration” inertia weight PSO algorithm (MFTIWPSO), which combines the multi-dimensional information of particle’s time (or iteration), particle and dimension (or space). In order to test the optimization performance of our proposed MFTIWPSO, the benchmark functions are used to test the optimization performance, and then the algorithm is used to optimize the parameters of machine learning classifier and classify the biological datasets. The results of two tests show that the proposed MFTIWPSO algorithm has better optimization performance than other optimization algorithms.

A superhydrophobic and superoleophilic gamma-AlOOH membrane on stainless steel mesh was fabricated by an inexpensive, template-free hydrothermal method using Al(NO3)(3)center dot 9H(2)O and Na2C2O4 as starting materials. A novel gamma-AlOOH film with a grass-like structure was synthesized and grass-like grains were tightly connected to form a hierarchical microstructure, which created a rougher stainless steel mesh surface. The influences of the additive amount of Na2C2O4 and Al(NO3)(3)center dot 9H(2)O on morphology and water contact angle of products were discussed. The prepared film is superhydrophobic not only for pure water but also for corrosive water under acidic or alkaline conditions. The obtained superhydrophobic and superlipophilic coated mesh exhibited high efficient oil/water separation. Besides the maximum diesel-water separation efficiency reach 99.6%, a high water intrusion pressure value of 2.2 kPa is also calculated, which make it promising application in large-scale, high-efficient and reusable oil/water separation filed.

Multi-illuminant-based color constancy (MCC) is quite a challenging task. In this paper, we proposed a novel model motivated by the bottom-up and top-down mechanisms of human visual system (HVS) to estimate the spatially varying illumination in a scene. The motivation for bottom-up based estimation is from our finding that the bright and dark parts in a scene play different roles in encoding illuminants. However, handling the color shift of large colorful objects is difficult using pure bottom-up processing. Thus, we further introduce a top-down constraint inspired by the findings in visual psychophysics, in which high-level information (e.g., the prior of light source colors) plays a key role in visual color constancy. In order to implement the top-down hypothesis, we simply learn a color mapping between the illuminant distribution estimated by bottom-up processing and the ground truth maps provided by the dataset. We evaluated our model on four datasets and the results show that our method obtains very competitive performance compared with the state-of-the-art MCC algorithms. Moreover, the robustness of our model is more tangible considering that our results were obtained using the same parameters for all the datasets or the parameters of our model were learned from the inputs, that is, mimicking how HVS operates. We also show the color correction results on some real-world images taken from the web.

In this work, nitrogen-doped carbon modified MgO-MgFe2O4 (CN-MgFeO) magnetic composites were synthesized by a facile thermal decomposition of Mg-Fe layered double hydroxide (MgFe-LDH) and cyanamide mixture precursors. A series of comprehensive characterization studies including powder X-ray diffraction, transmission electron microscopy, Fourier transform infrared of CO2 adsorption, CO2-temperature programmed desorption, and X-ray photoelectron spectroscopy indicated that the introduction of cyanamide could finely tune the surface basicity of the resulting CN-MgFeO composites, especially surface strong Lewis basicity. Compared with CN-free MgFeO, the as-fabricated CN-MgFeO catalysts showed higher activity in the liquid-phase transesterification of tributyrin with methanol. Particularly, the CN-MgFeO composite prepared at a cyanamide/Mg molar ratio of 1.5 in the synthesis mixture gave a highest methylbutyrate yield of 80% after a reaction for 20 min. The high catalytic performance was attributable to the presence of a large amount of strong Lewis basic sites originating from highly dispersed basic MgO-MgFe2O4 mixed metal oxides and CN component in the composite. What is more, such a cost-effective CN-MgFeO catalyst had the advantages of intrinsic magnetic properties and an excellent structural stability. We expect that they may have potential practical applications in the field of industrial production of biodiesels.