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A transparent digital twin (DT) is designed for output control using the belief rule base (BRB), namely, DT-BRB. The goal of the transparent DT-BRB is not only to model the complex relationships between the system inputs and output but also to conduct output control by identifying and optimizing the key parameters in the model inputs. The proposed DT-BRB approach is composed of three major steps. First, BRB is adopted to model the relationships between the inputs and output of the physical system. Second, an analytical procedure is proposed to identify only the key parameters in the system inputs with the highest contribution to the output. Being consistent with the inferencing, integration, and unification procedures of BRB, there are also three parts in the contribution calculation in this step. Finally, the data-driven optimization is performed to control the system output. A practical case study on the Wuhan Metro System is conducted for reducing the building tilt rate (BTR) in tunnel construction. By comparing the results following different standards, the 80% contribution standard is proved to have the highest marginal contribution that identifies only 43.5% parameters as the key parameters but can reduce the BTR by 73.73%. Moreover, it is also observed that the proposed DT-BRB approach is so effective that iterative optimizations are not necessarily needed.

In wireless sensor networks (WSNs), due to the limited energy of sensor nodes, how to design efficient hierarchical routing algorithms to balance network resources and extend network life is an important problem to be solved. Aiming at the problems such as random selection of cluster head, redundancy of working node, and construction of cluster head transmission path, which affect network energy consumption, this paper proposes a multihop routing algorithm based on path tree (MHRA-PT) to optimize the network energy. Firstly, some nodes are those close to the base station and have large remaining energy which are selected to construct a cluster head set. Then, after clustering, each cluster is divided into different regions, and in each region, nodes with residual energy greater than the average residual energy of the cluster are selected as a working node. Finally, the cluster heads are sorted according to their distance from base station, and the next hop node is selected for each cluster head in turn until a path tree rooted at base station is formed completely, leading to data transmission from working node to base station. Simulation results show that the proposed algorithm can effectively reduce network energy consumption, balance network resources, and prolong network life cycle.

Nanopesticides were selected as one of the top 10 emerging technologies in chemistry that will change our world in 2019. Facile, smart, and degradable metal-organic framework MIL-101(FeIII) nanopesticides gated with FeIII-tannic acid (TA) networks are created using a universal strategy. The capping of the FeIII-TA network gatekeepers is instinctively oriented by the coordinatively unsaturated FeIII sites on the surfaces of the MIL-101(FeIII) nanocarriers; thus, their combination is perfectly matched. This is the first example that one smart gated nanoparticle is integrated with seven stimuli-responsive performances to meet the diverse controlled release of encapsulated cargos by the disassembly of the gatekeepers and/or the degradation of the nanocarriers. More importantly, each of the seven stimuli (acidic/alkaline pH, H2O2, glutathione, phosphates, ethylenediaminetetraacetate, and near-infrared light of sunlight) is closely related to the biological and natural environments of crops, and the biocompatible nanocarriers are eventually degraded against bioaccumulation even if the nanopesticides enter crops. These mechanisms of the stimuli-responsive controlled release are identified and clearly elaborated. It is found that the natural polyphenol can improve the wettability of aqueous droplets of nanopesticides on model hydrophobic foliage for pesticide adhesion and retention. The nanopesticides encapsulated with the fungicide tebuconazole show high fungicidal activities against pathogenic fungi Rhizoctonia solani (rice sheath blight) and Fusarium graminearum (wheat head blight); good safety on seed germination, seedling emergence, and plant height of wheat by seed dressing; and satisfactory control efficacy in wheat powdery mildew caused by Blumeria graminis in the greenhouse. The nanopesticides have potential applications in the field for high quality and yield of agricultural production.

Nanoemulsion provides an effective way for the efficient, safe, and environmentally friendly use for pesticides. In this study, the influence of the type, dosage of emulsifier, and emulsifying proc...

Microcapsulses can effectively encapsulate, protect, and control the release of insecticides. In this study, emulsion–solvent evaporation method was used to fabricate microcapsules (MCs) by using beta-cyhalothrin as the entrapped insecticide, dichloromethane as the solvent, polylactic acid (PLA) as the carrier materials, and polyvinyl alcohol as the emulsifier. Response surface methodology was used to determine the optimal process of beta-cyhalothrin MCs, the specific parameters are as follows: 0.52 g beta-cyhalothrin, 0.46 g PLA, 6.67 g dichloromethane and 0.37 g PVA. The fabricated beta-cyhalothrin MCs were characterized through microscopic morphology observation, particle size and distribution analysis, and Fourier transform infrared spectroscopy. The release kinetics in the acetonitrile and the bioassay of beta-cyhalothrin MCs were investigated. The results showed that the beta-cyhalothrin was successfully encapsulated in the PLA. The beta-cyhalothrin MCs showed a regular spherical structure, relatively uniform particle size, and the D50 was 2.44 μm. Compared to the technical beta-cyhalothrin, the beta-cyhalothrin MCs showed good sustained release performance and prolonged the control effect against Blattella germanica.

Permeable pavement (PP) can be used to decrease urban surface runoff. However, few studies have been conducted to explore the runoff reduction effect of various structures of PP in the carriageway. In this study, several structures of PP used in the carriageway of sponge cities in China were investigated and divided into three types: surface drainage, base course storage and drainage, and fully permeable. Then, the runoff models were developed by Storm Water Management Model to simulate the effect of the three types under various rainfall recurrence periods. Results show that rainfall recurrence period, structure and thickness of the permeable layer were identified as the most influential factors in PP runoff reduction. The surface drainage can reduce total runoff depth and coefficient by more than 14%, and also delay runoff start time and duration by more than 40 minutes. Surface runoff in the base course storage and drainage can only be generated when recurrence period is 50 years. The fully permeable does not generate any runoff under all recurrence periods. Based on simulation results, a series of runoff coefficient values for PP were recommended to help the design and implementation of PP in mitigating urban waterlogging problems.

Properly wearing a face mask has become an effective way to limit the COVID-19 transmission. In this work, we target at detecting the fine-grained wearing state of face mask: face without mask, face with wrong mask, face with correct mask. This task has two main challenging points: 1) absence of practical datasets, and 2) small intra-class distance and large inter-class distance. For the first challenging point, we introduce a new practical dataset covering various conditions, which contains 8635 faces with different wearing status. For the second challenging point, we propose a novel detection framework about conditions of wearing face mask, named Context-Attention R-CNN, which enlarge the intra-class distance and shorten inter-class distance by extracting distinguishing features. Specifically, we first extract the multiple context feature for region proposals, and use attention module to weight these context feature from channel and spatial levels. And then, we decoupling the classification and localization branches to extract more appropriate feature for these two tasks respectively. Experiments show that the Context-Attention R-CNN achieves 84.1% mAP on our proposed dataset, outperforming Faster R-CNN by 6.8 points. Moreover, Context-Attention R-CNN still exceed some state-of-the-art single-stage detectors.

In order to improve the waterproof and mildew resistance of electronic equipment, a superhydrophobic coating was prepared on a circuit board. First, hexadecyl trimethoxysilane was used to modify the nano silica and nano zinc oxide particles, and then the modified nanoparticles were mixed with the silica sol. Then the superhydrophobic coating was prepared on the surface of the printed circuit board by a spraying process. The preparation technology and physical and chemical properties of the coating were studied. The contact angle of the final sample can reach 169.47°, the sliding angle can reach 1.2°, it has good acid and alkali corrosion resistance, resistance to NaCl, self-cleaning performance and antimildew performance.

In order to quantitatively understand the residual strain distributions and benefits of engineering components following special technique treatment, such as Autofrettaging, Hot Isostatic Pressing (HIP) and Dissimilar Material Welding (DMW), the Neutron Diffraction Technique (NDT) has been employed recently to measure residual strain and stress distributions on following three cases of (a) Autofrettaged Aluminum 7075 high pressure vessels; (b) Hot Isostatic Pressed (HIPPED) heavy metals of tungsten clad in tantalum plate and (c) Dissimilar Material Welding (DMW) of 316L austenitic stainless steel and ferritic steel AS508 with Alloy 52 weld filler. This paper reports the recent research findings, including (a) NDT can identify optimal Autofrettage pressure level, by which load bearing capacity of the Autofrettaged pressure vessel increased by 215MPa; (b) NDT is able to reveal residual strains within heavy metals of Tungsten clad in Tantalum plate HIPPED and (c) NDT revealed a maximum residual tensile hoop stress value of about 494MPa in the interface between parent material SA508 and the weld seam. This is vital information for the post weld process and subsequent safe use of the dissimilar materials weld. Other researchers’ successful examples of working with NDT are also briefly reviewed. Future prospective of Engineering Materials Diffractometer (EMD) at CSNS is described too with a view to demonstrating the application and importance of NDT in revealing residual strain-stresses that are inevitable within engineering materials and engineering components following any manufacturing process.

As a result of the opening Arctic waters, Arctic Northeast Passage (NEP) can be used as a shortcut between Asian and European ports, which may bring considerable economic benefits. Due to the harsh...

In this paper, an energy level analysis model of oil transfer station system is established, which is divided into oil transfer station subsystem and pipeline network subsystem. From the perspective of the level of energy, the system is evaluated and optimized by virtue of using energy level analysis method and combining with the ”three box” analysis model. Moreover, the energy level evaluation indexes of import and export, energy level difference and energy level balance coefficient, are calculated in terms of the calculation results. Then the energy utilization diagrams (EUD) are drawn, it can be seen that more than 95% of the supply energy in the oil transfer station subsystem is provided by gas. The energy level difference of the heating furnace is the largest, which can be seen intuitively that the heating furnace is the weak link of energy utilization in the whole system. Based on the influencing factors, the corresponding energy saving and consumption reduction measures are preliminarily proposed.

The preference values in group decision-making (GDM) process can differ significantly between different experts, which may yield a low level of group consensus. Therefore, different consensus models have been developed for the modification of preference values to assist experts in improving their consensus degrees. However, most consensus models do not consider collective intelligence (CI) that may decrease as the consensus degree increases under certain circumstances. From the perspective of CI, the distrust relationship allows the group to better explore the decision space, rather than prematurely converge on an agreed suboptimal solution. Inspired by this idea, a theoretical framework of solving intuitionistic fuzzy GDM problems with low group consensus is proposed in this paper, which mainly includes two steps: (1) building the trust/distrust relationships and (2) establishing a consensus model. For two experts with a direct relationship, the trust/distrust relationships between them are constructed by fusing their knowledge levels and representativeness levels. For two experts with an indirect relationship, a new operator is designed to construct the trust/distrust relationships between them, which can describe the information attenuation of the decreasing trust along with the increasing distrust. Additionally, a consensus model based on the social network relationships density and trust/distrust relationships is proposed, which improves consensus degree and CI level conducively. Finally, a ranking of alternatives is constructed to select the optimal alternative. An illustrative example is used to demonstrate the effectiveness and applicability of the proposed method.

The inherent low activity at room temperature has greatly limited the utilization of Co3O4 in indoor air purification. In this work, an extremely facile and mild method utilizing the strong oxidati...

Objective After bone prosthesis replacement, M1-type macrophage polarization can be induced by titanium (Ti) particles and produce inflammatory, leading to osteolysis. Adipocyte-derived exosomes (ADEs) exert immune-modulatory impact on the macrophage, while whether it can inhibit the macrophage polarization induced by Ti is unclear. This study focuses on the M1-type macrophage and aims to determine the effect of ADEs on Ti-induced M1-type macrophage polarization in osteolytic mice and the involved mechanism. Methods Ti particle-induced osteolysis mouse model was established and macrophages were isolated from the osteolysis site. The levels of NLRP3 and specific markers for M1-type macrophage were determined. ADEs isolated from adipocyte cell line 3T3-L1, or conditioned ADEs with low-expressed miR-34a isolated from 3T3-L1 transfected with miR-34a inhibitor were co-cultured with RAW 264.7 to determine their impact on the polarization of macrophage. Results ADEs reduced the M1-type macrophage polarization and caused the upregulation of miR-34a in macrophage of the osteolysis site of the osteolysis mouse model. Also, the level of miR-34a in ADEs was higher than that in the adipocyte. The conditioned ADEs expressed a low level of miR-34a and boosted the Ti-induced M1-type polarization. MiR-34a could target NLRP3 and negatively regulated its expression. Moreover, NLRP3 knockdown in macrophage restricted the conditioned ADEs to promote macrophage towards to Ti-induced M1-type polarization. The inhibitory function of ADEs on M1-type macrophage polarization was abolished by miR-34a silencing in the mouse osteolysis model. Conclusion The miR-34a carried by ADEs reduced the polarization of M1-type macrophages by targeting macrophage NLRP3 during Ti particle-induced osteolysis.

This paper presents a capacitor calibration technique called median selection for improving the static and dynamic performance of the successive approximation register (SAR) analog-to-digital converter (ADC). Monte Carlo simulations in MATLAB are presented to demonstrate the effect of the proposed method. Simulation results show that for an 18-bit RC-hybrid SAR ADC with the mismatch of the unit capacitor ( $${\sigma _u} = {{{\sigma _0}}\big / {{C_u}}}$$ ) of 0.05%, the root mean square (rms) of differential nonlinearity is improved by 94.7%–0.23 LSB and the rms of integral nonlinearity is promoted by 96.7%–0.20 LSB by the proposed median selection. On the other hand, the median selection improves the mean value of the spurious free dynamic range from 94.09 to 128.85 dB, while the mean value of the signal-to-noise-and-distortion ratio is improved from 88.70 to 109.82 dB.

In view of the disadvantage that coal waste powder(CWP) can reduce the crack resistance of asphalt mortar at low temperature, silane coupling agent KH-550 was used to modify coal waste powder. The surface characteristics and modification mechanism of silane coupling agent modified coal waste powder were characterized by using Scanning Electronic Microscopy (SEM). Five kinds of silane coupling agent modified coal waste powder asphalt mortar with content 0%, 0.5%, 1.0%, 1.5%, 2.0% and limestone(LS) powder asphalt mortar were prepared under different filler-asphalt ratios, respectively. The effects and mechanism of silane coupling agent modified coal waste powder on the pavement performance of asphalt mortar and asphalt mixture was studied by the dynamic shear rheological test(DSR), low temperature bending beam rheological test (BBR), Brookfield viscosity test, adhesion test, Fourier Transform Infrared Spectroscopy (FTIR), rutting test, bending test at low temperature, immersion Marshall test and freeze-thaw split test. The results showed that the optimal proportion of KH-550 is 1.5% of CWP mass and CWP modified by silane coupling agent can greatly enhance high temperature performance, low temperature performance and adhesion of the asphalt mortar. Furthermore, CWP modified by silane coupling agent can significantly improve rutting resistance, low temperature crack resistance and water damage resistance of asphalt mixture.

Ti(C, N)-based cermet materials represent the best choice of materials for the manufacturing industry and military products. In this study, we use cubic β-cobalt(β-Co) as the binder phase to strengthen constructed cermets. At the same time, to optimize the microstructure, (Ti, W, Mo, Ta) (C, N) powders are added to form two kinds of core-rim morphologies. Here, β-cobalt powders with face-centered cubic structures are obtained by the solid-phase reaction of high-energy ball milling. A solid-phase chemical reaction and a carbothermic reduction-nitridation method are used to prepare the (Ti, W, Mo, Ta) (C, N) powders. In our process, first we mix the cobalt and (Ti, W, Mo, Ta) (C, N) powders; then we press the powder mixtures into rectangular samples and sinter them in a pressure sintering furnace to obtain Ti(C, N)-based cermets with two kinds of core-rim structure, that is, black core/white rim and white core/gray rim. The results show that the new cermets demonstrate excellent toughness and performance.

Summary The cost of offshore drilling operations can be significantly reduced by discharging drilling cuttings into the seabed. However, this leads to accumulation of cuttings piles on the seabed near the drilling site. A certain thickness of cuttings piles changes the original trend of the seabed terrain undulation condition, thus bringing potential safety hazards to the underwater installation of production manifolds. Moreover, the interaction between cuttings and ocean currents near the cuttings piles causes the geometric shape of cuttings piles to evolve over time, which makes it more difficult to accurately predict their characteristics. On the basis of the force analysis of cuttings, considering the effects of cuttings properties (cutting size, density) and ocean-current velocity on the geometric characteristic evolution of the formed cuttings piles, a continuous model for describing the evolution of the returned cuttings piles is established in this study. This model can quantitatively characterize the functional relationship between characteristics of cuttings piles and relevant parameters (current velocity, cutting size, evolution time), and predict the location and geometry characteristics of the cuttings piles evolving into a stable state in ocean currents. Comparing the measured data in laboratory experiments and at an offshore drilling field, the relative error of the model amounts to less than 10%, which demonstrates its rationality. Simulation results show that there will be significant changes in the geometry of cuttings piles before and after the evolution, in which the intensity is correlated with current velocity and cuttings size, and cuttings piles might even split into several parts under certain conditions. The simulation and analysis of the transport and deposition of cuttings returned from the wellhead on the seabed is highly significant for the guide and optimal design of underwater production manifolds.

Objective To explore the influence of scarring moxibustion on the changes of serum melatonin (MT) and neuropeptide Y (NPY) expressions in the insomnia model rats. Methods A total of 40 SD rats were randomly divided into a blank group, a model group, a scarring moxibustion group, an embedding needling group and a mild moxibustion group, 8 rats in each group. The intraperitoneal injection of p-chlorophenylalanine (PCPA) was adopted to establish the insomnia model rats and the corresponding interventions were given, consecutively for 6 days. Separately, before modeling and the first intervention as well as before sample collection, the body weight was measured and the serum was collected in the insomnia model rats. The enzyme linked immunosorbent assay (ELISA) was used to detect the levels of serum MT and NPY. Results Compared with the blank group, the body weight of rat in the model group was lower (P 0.05). Conclusion The regulation mechanism of sleep-wake circadian rhythm may be related to the levels of serum MT and NPY in the insomnia model rats. Scarring moxibustion increases the levels of MT and NPY more effectively and displays the effect in the intervention as compared with embedding needling and mild moxibustion in the insomnia model rats.

Defect modulation usually has a great influence on the electronic structures and activities of photocatalysts. Here, atomically layered g-C3N4 modified via defect engineering with nitrogen vacancy ...

Ferries are usually used for transporting passengers and vehicles among docks, and any deviation of the course can lead to serious consequences. Therefore, transportation ferries must be watched closely by local maritime administrators, which involves much manpower. With the use of historical data, this article proposes an intelligent method of integrating artificial potential field with Bayesian Network to trigger deviation warnings for a ferry based on its trajectory, speed and course. More specifically, a repulsive potential field-based model is first established to capture a customary waterway of ferries. Subsequently, a method based on non-linear optimisation is introduced to train the coefficients of the proposed repulsive potential field. The deviation of a ferry from the customary route can then be quantified by the potential field. Bayesian Network is further introduced to trigger deviation warnings in accordance with the distribution of deviation values, speeds and courses. Finally, the proposed approach is validated by the historical data of a chosen ferry on a specific route. The testing results show that the approach is capable of providing deviation warnings for ferries accurately and can offer a practical solution for maritime supervision. &nbsp

Accurate and reliable measurements of the 3D flame temperature profile are highly desirable to achieve in-depth understanding of the combustion and pollutant formation processes. In this paper, a measurement method for reconstruction of a 3D flame temperature profile was proposed by using a light field camera. It combines the convolution imaging model and radiative transfer equation and takes into account the characteristics of emission, absorption, and scattering of a semitransparent flame. According to the point spread function characteristics of the imaging system, the number and positions of the refocus planes were set by comprehensive consideration of the reconstruction accuracy and efficiency. The feasibility of the present method was proved by numerical simulation and an experiment of a candle flame. This method achieves the reconstruction of a 3D asymmetric flame profile through a single exposure of a single camera, which overcomes the problem of complexity of a multicamera system and the time delay of a conventional scanning camera system.

Distributed acoustic sensing (DAS) technology plays an increasingly important role in the field of underwater acoustic detection because of its own advantages. To measure acoustic pressure sensitivity of seven kinds of optical cables in the same condition synchronously, the experimental setup based on DAS is proposed. Seven kinds of optical cables are connected in series to the DAS system, and the acoustic pressure sensitivity at different locations (different optical cables) is detected simultaneously via the DAS system. The highest acoustic pressure sensitivity of the sensitized optical cable is 69.9 mrad/Pa. The experimental results provide experimental data support for the selection of optical cables.

The relational measurement based on Markov-switching GRG copula constructed by this paper is harnessed to analyze the dependence structure between WTI (BRENT) crude oil futures price and 12 kinds of Chinese agricultural commodity futures prices. The empirical results show that there exist two structural states of Markov switching between the futures prices of different agricultural commodities and crude oil futures price. The two states have different duration periods, and the degree of correlation with crude oil futures prices varies under different agricultural commodity futures prices. Among all the 12 kinds of agricultural commodity futures, 11 kinds of agricultural commodity futures prices mainly present positive correlations with crude oil futures prices, although the positive correlation differs between non-extreme and extreme conditions. The remaining agricultural commodity futures price is not related to crude oil futures prices.

In this paper, we present a precision non-contact displacement sensor based on the near-field property of specklegrams, achieving a precision of 10 nm and a detection range of 3–4 μm. The compact device envelope enables the application of the new fiber-optic sensor in many space-limited applications, e.g., probe-based nanofabrication and micro-/mesoscale positioning systems. In the sensor system, the laser is first coupled into a 50/50 fiber coupler; the flexible fiber transmits the laser beam to the remote sensor head that is a few micrometers away from the sample surface; the reflected light is collected by the sensor head. The interference among the different eigenmodes propagating in the multimode fiber form unique specklegram images for different sample positions in space. By recording the varying specklegrams along the scanning path, highly precise and repeatable non-contact displacement detection can be realized by comparing the recorded specklegrams with the calibrated specklegram database through imaging processing techniques. In the experiments, we demonstrate the fiber-optic sensor can perform one-axis displacement sensing with a precision of 10 nm over a range of 3–4 μm at 100 Hz, where the specklegram acquisition rate is limited only by the speed of the camera. The new fiber-optic sensor is flexible, precise, and low-cost, which may find important applications in optical metrology and nanomanufacturing.

A two-dimensional nanocarbon, graphene, has attracted substantial interest due to its excellent properties. The reduction of graphene oxide (GO) has been investigated for the mass production of gra...

In this paper, we aim at applying improvement sets and image space analysis to investigate scalarizations and optimality conditions of the constrained set-valued optimization problem. Firstly, we use the improvement set to introduce a new class of generalized convex set-valued maps. Secondly, under suitable assumptions, some scalarization results of the constrained set-valued optimization problem are obtained in the sense of (weak) optimal solution characterized by the improvement set. Finally, by considering two classes of nonlinear separation functions, we present the separation between two suitable sets in image space and derive some optimality conditions for the constrained set-valued optimization problem. It shows that the existence of a nonlinear separation is equivalent to a saddle point condition of the generalized Lagrangian set-valued functions.

Waterborne fluorinated polyurethane–acrylate hybrid emulsion modified by long aliphatic chains (WFPUA) is prepared by two steps, which include that the stearyl alcohol (SA)-blocked (end-capped) polyurethanes (SPU) are carried out in the mixtures of vinyl monomers, and then, the WFPUA is prepared via the free radical polymerization after the pre-emulsification of the said system. The characteristic of the reaction is the phase-inversion polymerization. The results show that the emulsifiability of SPU is firstly improved then decreased with the continuous increase in SA content. When the molar ratio of SA to 2-hydroxyethyl methacrylate (HEA) in the SPU is 1:1, the stability, zeta potential, viscosity and particle sizes of the WFPUA emulsion have the best results. The mechanical properties of WFPUA hybrid films deteriorate with the increase in SA content at 20 °C, but the mechanical properties of WFPUA films with more SA content achieve better results at 80 °C. The fluorinated groups migrated to the surfaces more easily with more SA content. In order to form the liquid crystalline-like structure on the WFPUA’s surface, the gradient heating treatment to an elevated temperature (i.e., 120 °C) to properly orient the fluorinated chains is necessary.

It is of great importance to remove lead ions from wastewater as lead pollution is a serious problem. Hence, a new magnetic adsorbent (Tannic-Ni0.6Fe2.4O4) was synthesized by modifying nickel-iron oxide nanoparticles with tannic to selectively adsorb Pb(II) from wastewater. The adsorption capacity of Tannic-Ni0.6Fe2.4O4 for Pb(II) was investigated by batch experiment. The effects of pH, time, initial concentration and temperature on the sorption capacity were studied. The regenerated experiments and adsorption mechanisms have been also discussed. pH4 is the best condition for the adsorption experiment. The adsorption reaches equilibrium in 200 min and the maximum adsorption capacity is 139.8 mg/g. After five repetitive experiments, the adsorption capacity was reduced only from 70% to 61.5%. In addition, the entire adsorption process is based on monolayer chemisorptions because it conforms to the pseudo-second-order and Langmuir models. The thermodynamic data revealed that the adsorption is a spontaneous endothermic process. After 5 cycles, Tannic-Ni0.6Fe2.4O4 still maintained a good adsorption capacity. Tannic-Ni0.6Fe2.4O4 was successfully applied for selective adsorption of Pb(II) from wastewater with various metal ions. The uptake of Pb(II) by Tannic-Ni0.6Fe2.4O4 mainly followed ion exchange and chelation mechanism. Therefore, Tannic-Ni0.6Fe2.4O4 is a perfectly valid and useful adsorbent for the elimination of Pb(II) pollution.

The development of two-dimensional (2D) materials has opened up possibilities for their application in electronics, optoelectronics and photovoltaics, because they can provide devices with smaller size, higher speed and additional functionalities compared with conventional silicon-based devices1. The ability to grow large, high-quality single crystals for 2D components—that is, conductors, semiconductors and insulators—is essential for the industrial application of 2D devices2–4. Atom-layered hexagonal boron nitride (hBN), with its excellent stability, flat surface and large bandgap, has been reported to be the best 2D insulator5–12. However, the size of 2D hBN single crystals is typically limited to less than one millimetre13–18, mainly because of difficulties in the growth of such crystals; these include excessive nucleation, which precludes growth from a single nucleus to large single crystals, and the threefold symmetry of the hBN lattice, which leads to antiparallel domains and twin boundaries on most substrates19. Here we report the epitaxial growth of a 100-square-centimetre single-crystal hBN monolayer on a low-symmetry Cu (110) vicinal surface, obtained by annealing an industrial copper foil. Structural characterizations and theoretical calculations indicate that epitaxial growth was achieved by the coupling of Cu step edges with hBN zigzag edges, which breaks the equivalence of antiparallel hBN domains, enabling unidirectional domain alignment better than 99 per cent. The growth kinetics, unidirectional alignment and seamless stitching of the hBN domains are unambiguously demonstrated using centimetre- to atomic-scale characterization techniques. Our findings are expected to facilitate the wide application of 2D devices and lead to the epitaxial growth of broad non-centrosymmetric 2D materials, such as various transition-metal dichalcogenides20–23, to produce large single crystals. The epitaxial growth of large single-crystal hexagonal boron nitride monolayers on low-symmetry copper foils is demonstrated.

The application of liquid scintillators as energy conversion materials in nuclear batteries was proposed. By introducing liquid scintillators, the output properties of radioluminescence (RL) nuclear batteries based on different liquid scintillators were investigated via low-energy X-ray. Results indicated that the values of short circuit current Isc and maximum output power Pmax increased as the X-ray intensity increased, and the output power of nuclear battery with Ultima Gold liquid scintillator was greater than those of batteries with Emulsifier-Safe or Bioscint liquid scintillator under excitation condition of 25 kV tube voltage. To analyze the RL effects of the liquid scintillators under X-ray excitation, we measured the RL spectra of the different liquid scintillators. Considering luminescence utilization in batteries, the surface of the quartz cuvette was covered with Al film. Al is a high-performance reflective material that can increase the scintillation light released by Ultima Gold, reaching the GaInP/GaAs/Ge device. After covering a thin Al film, the output power of the battery was significantly improved under X-ray excitation.

We successfully synthesized the Bi2WO6 (BWO) with gradient concentration of oxygen vacancies and exhibited the excellent photocatalytic NO oxidation activity. And the oxygen vacancy introduced in photocatalyst is a popular method to enhance the photocatalytic performance. The formation of oxygen vacancy defects in BWO is responsible for the tuning band structure and modifying surface chemical state to improve carriers separation efficiency, enlarge visible light absorption range and facilitate reactant activation, which is unambiguously verified by the UV–vis DRS, XPS, EPR and DFT calculations. Moreover, the role of surface oxygen vacancy defects and reaction mechanism of photocatalytic NO oxidation were discussed in detail by combing the in situ DRIFT and theoretical calculations. This work could be broadly used to the design and synthesize high efficient photocatalysts and pave a way to understand the reaction mechanism of NO oxidization.

Highly luminescent CsPbBr3 perovskite quantum dots (QDs) are very attractive for applications in power-generating devices. The CsPbBr3 QD solution and its corresponding solid films were satisfactor...

This paper provides some new characterizations of the solution sets for non-differentiable generalized convex fuzzy optimization problem. Firstly, we introduce some new generalized convex fuzzy functions and discuss the relationships among them. Secondly, some properties of these new generalized convex fuzzy functions are given. Finally, as applications, some characterizations of the solution sets for non-differentiable generalized convex fuzzy optimization problem are obtained.

Herein, a facile method for the preparation of an acrylic resin-based superhydrophobic coating is provided. Firstly, ZnO nanoparticles were modified with silane to obtain hydrophobic ZnO, which was then homogeneously blended with acrylic resin. Subsequently, the mixture was sprayed on an aluminum sheet to form a cured coating. The surface composition and morphology of the coating were characterized using X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). The hydrophobicity, wear resistance, and antibacterial properties of the prepared samples were tested. The optimized hydrophobicity was achieved with 10 wt% modification agent and resin-to-ZnO mass ratio of 1:4, exhibiting contact and sliding angles of 168.11° and 7.2°, respectively. Wear resistance was insufficient with a low resin content, while it grew with the increase in the resin content. However, when the resin content was excessively high, the hydrophobicity was reduced because the resin could wrap the modified ZnO nanoparticles and decrease the number of hydrophobic groups on the surface. Compared with the pure acrylic resin coating, the ZnO nanoparticle/acrylic resin superhydrophobic coating demonstrated a significant enhancement in the antibacterial properties.

As a common preventive maintenance technique for asphalt pavement, micro-surface (MS) has the advantages of waterproofing and crack sealing. However, issues such as the fact that the conventional MS generates large noise and the evaluation of the indexes of tire-road noise are relatively less studied. The traditional surface texture index cannot reveal the range and distribution of pavement surface texture, thus hindering research of low-noise MS. To study the mechanism of tire-road noise generated by MS, and propose the tire-road noise and surface texture indicators for MS. In this study, the mechanism of five low-noise MS was systematically analyzed and compared through surface texture and noise tests. Then, a three-dimensional digital texture model (3D-DTM) of MS surface texture was constructed using a series of digital image processing techniques, including grayscale identification, binary conversion, and noise reduction. The results show that optimizing the gradation, adding sound-absorbing materials, and improving the workability of construction can improve the noise reduction performance of MS, it is worth mentioning that the MS prepared with sound-absorbing materials and low-noise gradation has the greatest noise reduction effect, with a maximum reduction of 6.3 dB(A). In addition, it was also found that the 3D-DTM can well reflect the surface texture characteristics of MS. The probability of convex peak distribution (PCD) and the proportion of convex peak area (PCA) with peak heights greater than 0.25 mm (Kh ≥ 0.25), which are extracted from the 3D-DTM, can well reflect the surface texture, tire-road noise, respectively. The results show that the 3D-DTM is a promising tool to optimize the design of low-noise MS.

The Diagnostic ultrasound is a rapidly developing imaging technology that is widely used in the clinic. A typical ultrasound imaging pipeline including the following algorithms: beamforming, Envelope detection, log-compression, and scan-conversion [1]. In tradition, ultrasound imaging is implemented using Application-specific integrated circuits (ASICs) and FPGAs due to its high throughput and massive data processing requirements. With the development of the GPGPU and its programming environments (e.g. CUDA), researchers use software to implement ultrasound imaging algorithms [2], [3]. For now, the two limiting factors of developing ultrasound imaging are: First, using a hardware development approach to implement ultrasound imaging algorithms is complex, time-consuming and lacks flexibility. Second, the existing CUDA-based ultrasound imaging implementations are limited to Nvidia hardware, which is also a restriction applying more architectures. oneAPI is a cross-platform and unified programming environment developed by intel. It enables heterogeneous computing across multiple hardware architectures using Data Parallel C++ (DPC++). This new programming suite can be used to address the problems mentioned above. To be clear, using a high-level language like DPC++ to program FPGA can accelerate ultrasound imaging application development. SYCL-based ultrasound imaging applications can be easily migrated to other vendor's hardware. To implement an ultrasound imaging application across multiple architectures (e.g., GPU, FPGA, and CPU) in a unified programming environment. We migrated a CUDA-based open-source ultrasound imaging project SUPRA [4]. The migration process was performed using oneAPI compatibility tool (e.g. dpct). After migration, the code was tuned to run on GPU, FPGA, and CPU. In this talk, we will discuss our experiences with the complete process of migrating a CUDA code to oneAPI code. First, the whole process of migrating CUDA code base using the dpct will be presented, including usage, code modification, API comparison and build instruction. Second, the ultrasound imaging algorithms’ computation characteristics will be analyzed, and we will show how to optimize the application on Intel GPUs, Including ESIDM usage. Third, the early experiences of tuning the migrated code to target FPGA will be highlighted, this will include device code rewrite for FPGA and programming skills to improve performance on FPGA. The device code comparison of GPU and FPGA will also be discussed. Last, we will compare ultrasound imaging algorithms performance and computation results on different hardware, including Intel GPU (integrated GPU and discrete GPU), Intel Arria 10 FPGA, Intel CPU, Nvidia GTX 1080 GPU, and GTX 960M GPU.

The elevator brake wheel may have friction with the brake shoe during operation, which is easy to reduce the braking force and cause safety hazards. The temperature analysis software designed in this paper takes the thermal image of the brake wheel by the infrared thermal imager as the research object. So that we can use the non-contact method to measure the surface temperature and judge the friction of the brake wheel. The temperature analysis software can provide reference for the safe operation of the elevator.

To investigate the effect of chlorhexidine (CHX)-loaded carboxyl-terminated poly (amido amine) dendrimer (CHX-PAMAM-COOH) on matrix metalloproteinase (MMP) activities and remineralization in human dentin, CHX-PAMAM-COOH was prepared and characterized by Fourier-transform infrared spectroscopy. The inhibitory effects of CHX, PAMAM-COOH, and CHX-PAMAM-COOH on soluble recombinant human matrix metalloproteinase (rhMMP-2) and dentin-bound endogenous MMP activity were measured using an MMP Activity Assay Kit. In situ zymography was performed to evaluate the gelatinase activity in dentin pretreated with CHX, PAMAM-COOH, and CHX-PAMAM-COOH. The remineralization of etched dentin pretreated with CHX, PAMAM-COOH, and CHX-PAMAM-COOH was evaluated by field emission-scanning electron microscopy (SEM) and energy disperse spectroscopy (EDS) after incubation in artificial saliva for 14 days. The results of the rhMMP-2 activity assay showed that the MMP-2 activity in the CHX-PAMAM-COOH group and the CHX group decreased significantly to 5.58 ± 0.85% (P 0.05) and 4.86 ± 1.12% (P 0.05), respectively, but that in the PAMAM-COOH group increased significantly to 213.38 ± 0.11% (P 0.05). The results of total MMP activity and in situ zymography showed a significant reduction in endogenous gelatinase activity in dentin in the CHX-PAMAM-COOH group and the CHX group. The SEM and EDS results showed that rod-like crystals were formed on the etched dentin surface in the PAMAM-COOH group and the CHX-PAMAM-COOH group, and their Ca/P ratios were 1.73 and 1.71, respectively. In conclusion, CHX-PAMAM-COOH can inhibit dentin-bound endogenous MMPs and induce remineralization in etched dentin simultaneously. However, it is important to note that the catalytic role of PAMAM dendrimers may have an undesired excitatory effect on MMP activity, which cannot be ignored if PAMAM dendrimers were used alone in the oral environment.

Nucleic acid-based gene therapy has recently made important progress toward clinical implementation, and holds tremendous promise for the treatment of some life-threatening diseases, such as cancer and inflammation. However, the on-demand delivery of nucleic acid therapeutics in target cells remains highly challenging. The development of delivery systems responsive to specific pathological cues of diseases is expected to offer promising alternatives for overcoming this problem. Among them, the reactive oxygen species (ROS)-responsive delivery systems, which in response to elevated ROS in cancer cells or activated inflammatory cells, can deliver nucleic acid therapeutics on-demand via ROS-induced structural and assembly behavior changes, constitute a promising approach for cancer and anti-inflammation therapies. In this short review, we briefly introduce the ROS-responsive chemical structures, ROS-induced release mechanisms and some representative examples to highlight the current progress in constructing ROS-responsive delivery systems. We aim to provide new insights into the rational design of on-demand gene delivery vectors.

Belief Rule-Based (BRB) model has been widely used for complex system classification and prediction. However, excessive antecedent attributes will cause the combinatorial explosion problem, which restricts the applicability of the BRB model to high-dimensional problems. In this paper, we propose an Ensemble-BRB model with the use of the bagging framework to downsize the belief rule base and avoid the combinatorial explosion problem. The kernel of the Ensemble-BRB model is to generate several weak BRBs orderly, each of which only consists of a subset of antecedent attributes. Different combination methods can be used to integrate these weak BRBs coherently for classification and prediction respectively. Four benchmark problems are tested to validate the efficiency of the proposed Ensemble-BRB model in classification, and a real case on the health index prediction of engines proves the feasibility of the Ensemble-BRB model in prediction. The results on both classification and prediction show that the Ensemble-BRB model can effectively downsize the BRB as well as reach a high modeling accuracy.

Surface-enhanced Raman spectroscopy (SERS) has attracted lots of interest in academic and industrial fields in recent years. The improvement in long-time sensitivity and repeatability is highly demanded by the on-site applications. Herein, we present an expedient SERS strip tactic with these desired advantages. Specifically, the tactic utilized the outstanding stability of colloidal particles to maintain the SERS materials during the storage. Upon usage, the strip is rapidly prepared on-site, and then the targets were sampled with a dip-coating and heating method, which is designed to standardize the whole detection process with the sensitivity kept. Thanks to the tactic, only one-third of SERS sensitivity decay was observed for rhodamine 6G after half a year. Besides rhodamine 6G, the SERS spectra of different animal blood samples were also investigated with the SERS strip tactic, and a species-based discrimination capability was preliminarily demonstrated.

Understanding the socially influenced decision-making process that determines voluntary vaccination is essential for developing strategies and interventions of vaccine-preventable diseases. Both theoretical and experimental studies have suggested that a variety of factors, such as safety of vaccines, severity of diseases, information and advice from healthcare professionals, influence an individual's intention to vaccinate. However, limited research has been conducted on analysing systematically how individuals’ vaccine acceptance decisions are made from their beliefs and judgements on the influential factors. In particular, there is lack of quantitative analysis on how individuals’ beliefs and judgements may evolve from the spreading of vaccination-related information in a social network, which further affects their decision making. In this paper, an integrated model is first proposed to characterise the socially influenced vaccination decision-making process, in which each individual's beliefs and subjective judgements on the decision criteria are formulated as belief distributions in the framework of multiple criteria decision analysis (MCDA). The spreading of social influence in the network environment is further incorporated into the information aggregation process for supporting informed vaccination decision analysis. A series of simulation-based analyses on a real-world social network is conducted to demonstrate that the overall vaccination coverage is determined primarily by individuals’ beliefs and judgements on the decision criteria, and is also affected sensitively by the characteristics of influence spreading (including the content and amount of vaccination-related information) in the social network.

Betweenness is a crucial measure to evaluate the significance of the nodes and link in the networks, which is widely used in centrality ordering, failure cascading modeling and path planning. However, we have very little knowledge about the betweenness, which prevents the deep analysis. In this paper, we discovered two betweenness identities, which represent that the node and link betweenness is closely relative to the average length of the shortest paths in the network. Betweenness distribution is a globally parameter and uniquely determines the small-world property of the network.

With the advancement of science and technology, the interaction between the occupants and the user interface system is becoming more and more complicated. It is of great value to study the layout of the user interface. Given the interface layout of the user interfaces, this paper uses a firefly algorithm (FA) to optimize the interface layout. First, this paper analyzes the layout characteristics of the user interface and then abstracts this problem into a multi-constrained two-dimensional packing problem. Afterward, we summarized the solution of the two-dimensional packing problem, and we established the mathematical model, where the object is to maximize the space occupancy rate of the interface. Finally, this paper uses the firefly algorithm to solve it. The simulation results show that our method has a good effect and improves the utilization of interface space.

This paper presents a new framework with a siamese feature aggregation network (SFANet) for visual localization based on remote sensing scene matching. Specifically, the presented framework predicts the location of a query image by finding the matching remote sensing images with geographical information. We employ the fully convolutional networks (FCNs) and a siamese network of NetVLAD to aggregate local features and learn the global representations for images from different sources. A new soft margin loss function is established for the network. Geographic coordinates of the query images are obtained by calculating the similarity with satellite images. We also collect a multi-scale dataset that contains 136959 images from 45653 locations. Various experiments are carried out on it. Experimental results show the effectivity of the proposed method.

This paper studies the dissipative problem of neural networks with time-varying delay and external disturbance. A suitable augmented Lyapunov-Krasovskii functional (LKF) is constructed by taking full advantage of the delay information of the system and the conditions of the excitation function. Then by employing auxiliary function inequalities, the reciprocally convex combination and a vector zero-value method to deal with the derivative of the LKF, a less conservative delay-dependent dissipative criterion is obtained. Finally, a numerical example is given to show the effectiveness of this criterion.

Sliding-base (SB) systems are efficient for protecting low-rise buildings in high-seismicity rural areas. The normalized peak pseudoacceleration (NPPA) of one-story SB structures under thre...

Shale gas reserves is enormously abundant in the world and has considerable prospects for exploration. Therefore, how to accurately calculate the dynamic reserves of shale gas reservoirs is very important. In recent years, scholars have proposed a variety of material balance equations for shale gas reservoirs to calculate dynamic reserves. However, only parts of factors were considered. Based on previous research, a new dual-porosity media material balance equation is established to more accurately calculate the dynamic reserves of gas reservoirs. In the new material balance equation, the critical desorption pressure, the adsorbed phase porosity, the change in the volume of the adsorbed phase, the dissolved gas in kerogen and water are all taken into consideration. The rock compressibility is revised as well. The cases analysis show that different factors exert a certain influence on the calculation results of reserves. Therefore, to effectively predict the dynamic reserves and guide the exploitation of shale gas reservoirs, all factors should be comprehensively considered to establish the correct material equilibrium equation.

Traditional stochastic inventory models assume to have complete knowledge about the demand probability distribution. However, in reality it is often difficult to characterize demand precisely, especially with limited historical data or through subjective forecasting. In this paper, we aim to develop a consistent framework of formulating demand uncertainties in single-period (newsvendor) problems, where a set of discrete assessment grades and/or grade intervals are used to represent complex uncertainties in both quantitative and qualitative evaluations. In this uncertainty formulation framework, we use random set theory to study optimal ordering policies for the newsvendor problem under optimistic, pessimistic, minimum regret and maximum entropy criteria respectively. Numerical studies are conducted to illustrate the effectiveness of the proposed approach.