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Engineered magnetic nanoparticles have been extensively explored for magnetic resonance imaging (MRI) diagnosis of a tumor to improve the visibility. However, most of these nanoparticles display "always-on" signals without tumor specificity, causing insufficient contrast and false positives. Here, we provide a new paradigm of MRI diagnosis using MnCO3 nanorhombohedras (MnNRs) as an ultrasensitive T1-weighted MRI contrast agent, which smartly enhances the MR signal in response to the tumor microenvironment. MnNRs would quickly decompose and release Mn2+ at mild acidity, one of the pathophysiological parameters associated with cancer malignancy, and then Mn2+ binds to surrounding proteins to achieve a remarkable amplification of T1 relaxivity. In vivo MRI experiments demonstrate that MnNRs can selectively brighten subcutaneous tumors from the edge to the interior may be because of the upregulated vascular permeation at the tumor edge, where cancer cell proliferation and angiogenesis are more active. Specially, benefiting from the T2 shortening effect in normal liver tissues, MnNRs can detect millimeter-sized liver metastases with an ultrahigh contrast of 294%. The results also indicate an effective hepatic excretion of MnNRs through the gallbladder. As such, this pH-activatable MRI strategy with facility, biocompatibility, and excellent efficiency may open new avenues for tumor malignancy and metastasis diagnosis and holds great promise for precision medicine.

Poly(methyl methacrylate) (PMMA) latices for organic coating systems were prepared via emulsion polymerization using various emulsifying techniques. The dispersion modes have an important effect on the particle size and particle size distribution (PSD) of polymeric latices during the emulsion polymerization process. The different dispersion modes, such as magnetic stirring, ultrasound, and the combination of magnetic stirring and ultrasound, were examined to prepare particle size small and narrow PSD polymer latex. PMMA latex of size less than 20 nm in diameter and narrow PSD was successfully produced using the probe ultrasound method. By modifying the amplitude, temperature, and duration of the ultrasound probe and surfactant/water ratio, the optimal ultrasound conditions for the microemulsion polymerization were determined. This research provides new insights into the relationship between the dispersion modes and the colloidal properties of latex, which may offer more effective and simpler routes to prepare latices with fast polymerization rate and high conversion.

Natural intervertebral disks (IVDs) exhibit distinctive anisotropic mechanical support and dissipation performances due to their well-developed special microstructures. As the intact IVD structure degrades, the absence of function will lead to severe backache. However, the complete simulation for the characteristic structure and function of native IVD is unattainable using current methods. In this work, by overall construction of the two-phase structure of native IVD (extraction of the naturally aligned cellulose framework and in situ polymerization of the nanocomposite hydrogel), a complete wood framework IVD (WF-IVD) is manufactured containing elastic nanocomposite hydrogel-based nucleus pulposus (NP) and anisotropic wood cellulose hydrogel-based annulus fibrosus (AF). In addition to the imitation and construction of the natural structure, WF-IVD also achieves favorable mechanical matching and good biocompatibility and possesses unique mechanical buckling buffer characteristics owing to the aligned fiber bundles. This study offers a promising strategy for the mimicking and construction of complex native tissues.

Bug localization is the automated process of finding the possible faulty files in a software project. Bug localization allows developers to concentrate on vital files. Information retrieval (IR)-based approaches have been proposed to assist automatically identify software defects by using bug report information. However, some bug reports that are not semantically related to the relevant code are not helpful to IR-based systems. Running an IR-based reporting system can lead to false-positive results. In this paper, we propose a classification model for classifying a bug report as either uninformative or informative. Our approach helps to lower false positives and increase ranking performances by filtering uninformative information before running an IR-based bug location system. The model is based on implicit features learned from bug reports that use neural networks and explicit features defined manually. We test our proposed model on three open-source software projects that contain over 9000 bug reports. The results of the evaluation show that our model enhances the efficiency of a developed IR-based system in the trade-off between precision and recall. For implicit features, our tests with comparisons show that the LSTM network performs better than the CNN and multilayer perceptron with respect to the F-measurements. Combining both implicit and explicit features outperforms using only implicit features. Our classification model helps improve precision in bug localization tasks when precision is considered more important than recall.

Recently, two-dimensional layered perovskites have emerged as effective additives for stabilizing conventional three-dimensional metal halide perovskites. With the addition of layered perovskites, the perovskite-based devices also exhibited enhanced optoelectronic properties, such as reduced nonradiative recombination and ionic migration, strengthened crystallinity, and anisotropic charge transport. However, the influence of the large organic cations on the performance metrics of the photodiodes is not fully understood. In this work, we systematically investigate the device performance and related optoelectronic features of the layered perovskite-enhanced perovskite photodiodes. In particular, with the addition of large organic cations to the FA

A model predictive control (MPC) strategy for grid-connected power converters is proposed in this article to reduce the current ripples without using ac voltage sensors. First, a sliding-mode observer is designed to estimate the grid voltage with an adaptive compensation algorithm. Thus, grid-voltage sensors are removed. The novelty of the proposed grid-voltage observation method is that it is inherent frequency adaptive without using the accurate grid angular frequency. By implementing the MPC strategy using the estimated grid voltage, the current ripples are reduced, especially under distorted grid-voltage conditions because of the low-pass filter used in the observer. Next, to further reduce the current ripples, a double-voltage vector-based MPC strategy is proposed based on the principle of the modulated MPC. Detailed theoretical analyses are also carried out to show its effectiveness for the first time. Finally, experimental studies are carried out to verify the validity of the proposed ac voltage sensorless MPC strategy.

Herein, we developed a novel effervescence-assisted dual microextraction method, abbreviated as EM-LPSH, using lighter-than-water phosphonium-based ionic liquids (LPILs) and switchable hydrophilic/hydrophobic fatty acids (SHFAs). The EM-LPSH method was utilized for quick enrichment/extraction of polycyclic aromatic hydrocarbons (PAHs) in edible oils. Owing to lower density than water, LPILs used as the first extractant were floated on the upper layer of the aqueous phase, leading to a convenient separation/collection compared with traditional heavier-than-water imidazolium-based ionic liquids. Interestingly, SHFAs play triple functions: a dispersive solvent in the microextraction process, an acidic source in effervescent reaction, and the second extractant in dual microextraction, due to switchability from hydrophilicity to hydrophobicity. Consequently, the integration of LPILs with SHFAs greatly enhanced the extraction efficiency for PAHs owing to the quick dual microextraction process. Some important variables were rigorously optimized using a one-factor-at-a-time approach. Under optimized conditions, the EM-LPSH/HPLC-FLD method provided a wide linear range (0.07~0.63–200 μg kg−1), satisfactory recovery (80.12–103.27%), and low limit of detection (0.02–0.19 μg kg−1), as well as high intra-day and inter-day precision (0.03–6.55) for six PAHs in edible oils. By using certified reference material in olive oil samples (GBW10162), the recoveries ranged from 97.40 to 98.39%, demonstrating high accuracy and precision. According to the detected levels of PAHs in six unheated and heated oils, their edible safety was evaluated in detail. In short, the newly developed method is simple, convenient, and highly efficient, thereby showing great prospects for application in conventional monitoring of trace-level PAHs in edible oils.

In recent years, virtual synchronous generator (VSG) control algorithm has been widely studied in distributed grid-connected power inverters to deal with active and reactive power adjustment by simulating the operation principle of the actual synchronous generator. Nevertheless, once the current sensor fails, the grid-connected power inverter will lose its stability. To enhance the fault-tolerant operation ability of the grid-connected power inverter, a new inverter side current sensor-less model predictive control method based on sliding mode observer (SMO) is proposed. The stability of the SMO is analyzed by using the Lyapunov stability criterion. The gains of the SMO are then designed by analyzing their influences on the current and voltage observation based on the closed-loop transfer functions. Besides, to show the influences of the capacitance changes on the current observation, a detailed parameter sensitivity analysis is also carried out. Then, by using the estimated inductance current from the SMO, a current sensor-less model predictive control method is finally proposed. The main novelty of the proposed method is that both the output voltage of the inverter and the inverter side inductance are not required in the proposed SMO. So, the accuracy of current sensor-less control is improved. To verify the effectiveness of the proposed method, detailed experimental studies are carried out based on a Typhoon and PE-Expert 4 based experimental platform.

Two-dimensional (2D) semiconductor nanostructures have exhibited great prospect as an efficient photocatalyst for solar-to-fuel application. In this work, a unique 2D tandem heterojunction consisting of ultrathin CdxZn1−xIn2S4 nanosheets coupled with rectangular CdS flakes and defect-rich MoS2 few-layered nanosheets was constructed for the first time. Remarkably, the efficient electron transfer channels present in the CdS/CdxZn1−xIn2S4 and CdxZn1−xIn2S4/MoS2 2D tandem heterojunctions facilitate the spatial separation and directional migration of photo-induced charge carriers effectively. Moreover, such 2D tandem heterojunction CdxZn1−xIn2S4–CdS–MoS2 is provided with excellent light harvesting capacity and abundant HER active sites from the defective MoS2 co-catalyst. These distinct advantages endow the optimized C0.15ZIS–5C–3M hybrid (5 wt% CdS, 3 wt% MoS2) with an exceptional photocatalytic H2 evolution reaction (HER) activity of 27.14 mmol h−1 g−1, approximately 47 times that of pure ZnIn2S4 and it is much superior to that of Pt-decorated C0.15ZIS–5C and most ZnIn2S4-based composites reported previously. A high HER apparent quantum yield (AQY) of 19.97% is achieved at λ = 400 nm. In addition, both the cycling and long-term HER measurements evidence the prominent stability of C0.15ZIS–5C–3M for H2 production. The results indicated here could pave the way for the exploitation of new 2D heterostructures toward highly-efficient solar conversion and utilization.

The development of high quantum efficiency and stable red emitting phosphors with high color purity is an urgent need for multifunctional optical applications. In this work, we propose a nonlinear optical material (NLOM)-inspired methodology to synthesize a novel red emission pyrophosphate phosphor Rb2Ba3(P2O7)2:Eu3+. XRD Rietveld refinement and energy dispersive X-ray spectroscopy were then exploited to obtain information on the phase purity, crystal structure and chemical composition. Moreover, the optical bandgap of different Eu3+ doped Rb2Ba3(P2O7)2 phosphors was analyzed by diffuse reflectance spectroscopy and further confirmed by first principles calculation. Furthermore, the Eu3+ site occupation preference, the characteristic luminescence properties and luminescence kinetics as a function of Eu3+ doping concentration were investigated by employing the cryogenic spectra at 4 K, room temperature emission spectra and decay curves. The luminescence analysis indicated that Rb2Ba3(P2O7)2:Eu3+ could emit red emission light with high quantum efficiency (IQE ∼ 77.04%), high color purity (96.4%) and excellent thermal stability (87%@ 140 °C) under ultraviolet light excitation. In addition, the excellent stability of Rb2Ba3(P2O7)2:Eu3+ against external pressure, cathode-ray irradiation, water and acid–base was further proved by pressure-driven (from 0 to 20 GPa) luminescence analysis, cathodoluminescence analysis and emission photography after infiltrating in water, acid, and alkali. The current work indicates that Rb2Ba3(P2O7)2:Eu3+ exhibits unprecedented excellent luminescence properties compared to other recently discovered phosphate red phosphors, and can serve as a potential red phosphor candidate in multifunctional optical applications, like LEDs, FEDs, artistic appreciation or some applications under extreme conditions (high temperature, strong pressure, and infiltrating in water, acid, and alkali).

The width of convolutional neural networks (CNNs) is crucial for improving performance. Many wide CNNs use a convolutional layer to fuse multiscale features or fuse the preceding features to subsequent features. However, these CNNs rarely use blocks, which consist of a series of successive convolutional layers, to fuse multiscale features. In this paper, we propose an approach for improving performance by fusing the low-level features extracted from different blocks. We utilize five different convolutions, including $3\times 3, 5\times 5, 7\times 7,5\times 3\,\cup \, 3\times 5$ and $7\times 3\,\cup \, 3\times 7$ , to generate five low-level features, and we design two fusion strategies: low-level feature fusion (L-Fusion) and high-level feature fusion (H-Fusion). Experimental results show that the L-Fusion is more helpful for improving the performance of CNNs, and the $5\times 5$ convolution is more suitable for multiscale feature fusion. We summarize the conclusion as a strategy that fuses multiscale features in the preceding stage of CNNs. Furthermore, we propose a new architecture to perceive the input of CNNs by using two self-governed blocks based on the strategy. Finally, we modify five off-the-shelf networks, DenseNet-BC (depth = 40), ALL-CNN-C (depth = 9), Darknet 19 (depth = 19), Resnet 18 (depth = 18) and Resnet 50 (depth = 50), by utilizing the proposed architecture to verify the conclusion, and these updated networks provide more competitive results.

There is an urgent need to develop phosphors with high quantum efficiencies (QEs) since white light-emitting diodes (WLEDs) have emerged as a new generation of illumination materials. Utilizing energy transfer to improve the absorption of activators and adjust the emission colors of samples is one effective strategy. Here, color-tunable phosphors of the form CaAl4O7:Ce,Tb were synthesized aiming at efficient energy transfer from Ce3+ to Tb3+. Since Tb3+ can be suitably sensitized by Ce3+, the co-doped phosphors can be effectively excited by near-ultraviolet (NUV) light. The internal QE of CaAl4O7:0.04Ce,0.04Tb under 350 nm excitation is as high as 92.55%, and the external QE is 71.02%. A WLED fabricated from BAM:Eu2+, CaAl4O7:0.04Ce,0.04Tb, and CaAlSiN3:Eu2+ with a 365 nm LED chip exhibited a correlated color temperature (CCT) of 4706 K and a color rendering index (CRI, Ra) of 81.44. The energy transfer mechanism and thermal stability of the phosphor were also investigated. The results provide an effective approach for developing highly efficient green-emitting phosphors for NUV WLEDs.

Recently, deep convolutional neural networks (CNNs) have been widely explored in single image super-resolution(SISR) and obtained remarkable performance. However, most of the existing CNN-based SISR methods tend to produce over-smoothed outputs and miss some textural details. To address these issues, we propose a wavelet-based asymmetric convolution network (WACN). Different from conventional CNN methods that directly infer HR images, our approach firstly learns to predict the LR’s corresponding series of HR’s wavelet coefficients before reconstructing HR images from them. This helps to capture more structural information in images to preserve texture information and avoid artifacts. To enhance the ability of feature extraction, we propose an asymmetric convolution block (ACB) structure to form a very deep network. In the training phase, ACB can provide different receptive fields to enrich feature information. In the inference phase, ACB’s asymmetric convolution kernel can be equivalently fused into the standard square-kernel layers, such that no extra computational burdens are introduced in the inference phase. Furthermore, we propose a variance-based channel attention (VCA) mechanism to adaptively rescale channel-wise features by considering interdependencies among channels. Extensive experimental results demonstrate the superiority of the proposed WACN in comparison with the state-of-the-art methods.

Understanding self-crystallization characteristics of calcium-magnesium-alumina- silicate (CMAS) glass is of great significance for seeking for solution to its corrosion to thermal barrier coatings (TBCs). Here, we design a series of experiments to investigate the relationship between CMAS self-crystallization behavior and cooling/heating rates and dwell temperature, and emphasize the potential influence of self-crystallization on CMAS corrosion behavior to TBCs. With the cooling rate decreasing, crystalline phases formed in a sequence of diopside, wollastonite and anorthite, and the thickness of the crystalline layer increased. During the heating process, diopside and melilite phases formed when the temperature was lower than 1050 °C; while at higher temperatures, melilite transformed to anorthite and wollastonite, independent on the heating rate. Although self-crystallization can slow molten CMAS penetration, the function on protecting TBCs from damage is limited, and other strategies alleviating CMAS corrosion are necessitated to be developed.

Populations of multipopulation genetic algorithms (MPGAs) parallely evolve with some interaction mechanisms. Previous studies have shown that the interaction structures can impact on the performance of MPGAs to some extent. This paper introduces the concept of complex networks such as ring-shaped networks and small-world networks to study how interaction structures and their parameters influence the MPGAs, where subpopulations are regarded as nodes and their interaction or migration of elites between subpopulations as edges. After solving the flexible job-shop scheduling problem (FJSP) by MPGAs with different parameters of interaction structures, simulation results were measured by criteria, such as success rate and average optimal value. The analysis reveals that (1) the smaller the average path length (APL) of the network is, the higher the propagation rate will be; (2) the performance of MPGAs increased first and then decreased along with the decrease of APL, indicating that, for better performance, the networks should have a proper APL, which can be adjusted by changing the structural parameters of networks; and (3) because the edge number of small-world networks remains unchanged with different rewiring possibilities of edges, the change in performance indicates that the MPGA can be improved by a more proper interaction structure of subpopulations as other conditions remain unchanged.

Two image enhancement contrast methods are proposed in this paper for low-intensity images. The first method (LEAM) is a new greyscale mapping function, and it can be significantly enhanced in the low grey range and compressed slowly in the high grey range, which is beneficial for retaining more image details; the second method (LEAAM) is based on the data characteristics of a histogram combined with the first mapping function, which adaptively sets the gamma value to correct the image. The experimental results show that compared with a traditional mapping function, LEAM is more effective at enriching image details and enhancing visual effects, and LEAAM, compared with a recent low-illumination image enhancement algorithm, achieves good performance for average gradient, information entropy and contrast index; additionally, the overall visual effect is the best compared with other methods.

This work proposes a novel SLAM framework for stereo and visual inertial odometry estimation. It builds an efficient and robust parametrization of co-planar points and lines which leverages specific geometric constraints to improve camera pose optimization in terms of both efficiency and accuracy. %reduce the size of the Hessian matrix in the optimization. The pipeline consists of extracting 2D points and lines, predicting planar regions and filtering the outliers via RANSAC. Our parametrization scheme then represents co-planar points and lines as their 2D image coordinates and parameters of planes. We demonstrate the effectiveness of the proposed method by comparing it to traditional parametrizations in a novel Monte-Carlo simulation set. Further, the whole stereo SLAM and VIO system is compared with state-of-the-art methods on the public real-world dataset EuRoC. Our method shows better results in terms of accuracy and efficiency than the state-of-the-art. The code is released at https://github.com/LiXin97/Co-Planar-Parametrization.

Development of noble-metal-free photocatalysts for efficient solar-powered water-splitting is of great interest yet still challenging to date. In this work, unique ternary Cd0.85Zn0.15S@WO3/WS2 (CZ0.15S@WO3/WS2) core-shell nanorods consisting of amorphous WO3 and few-layered WS2 nanosheets were synthesized through a two-step solvothermal method for the first time. The composition of WO3/WS2 shell is found to vary with the change of W content, which has a significant impact on the photocatalytic property of CZ0.15S@WO3/WS2 toward H2 evolution reaction (HER). Under visible-light irradiation (λ > 420 nm), the optimized CZ0.15S@WO3/WS2 composite (n (WO3): n (WS2) = 3:1) demonstrates a superior HER activity of 76.33 mmol h−1 g−1 (corresponding to an AQY of 23.9% at 420 nm), which can be further remarkably increased to 157.29 mmol h−1 g−1 when the reaction is driven by full Xe-lamp spectrum. The HER capability of CZ0.15S@WO3/WS2 is much better than that of Pt-decorated CZ0.15S and most CdS-based photocatalysts ever reported, due to the notably enhanced charge transfer and separation via the synergistic cooperation of Z-scheme and type-I charge transfer processes. The findings displayed here could inspire new strategies to optimize the charge separation of multi-component photocatalysts for highly-effective solar conversion and utilization.

The cationic group distribution along the polymeric backbones of anion exchange membranes (AEMs) has significant influence on their microscopic morphology and anion conductivity. To develop high-performance AEMs for vanadium redox flow batteries (VRFBs), a series of poly (fluorenyl ether) samples bearing di- and tri-quaternary ammonium side chains with similar ion exchange capacities (IECs) were synthesized by grafting cationic alkyl chains with tertiary amine-containing poly(fluorenyl ether) precursors. The experimental results indicate that the introduction of the multi-cationic side chains facilitates the formation of micro-phase-separated morphologies and enhances anion conductivity. Moreover, the number of spacer atoms between the quaternary ammonium groups on the side chains affects the water uptake of the membranes, thus complicating the relationship between the density of cationic group distribution and anion conductivity. The poly(fluorenyl ether)s with dicationic side chains and six spacing atoms (DQA-PFE-C6) showed the highest anion conductivity. A VRFB assembled with DQA-PFE-C6 exhibited a maximum power density of 239.80 mW cm−2 at 250 mA cm−2, which is significantly higher than a VRFB assembled with Nafion 212. Therefore, side chain engineering is an effective chemical approach to enhance the properties of AEMs for VRFB applications.

Searching for coexistence of wide energy gap (Eg > 3.5 eV) and large second-harmonic generation efficiency (dij > 0.6  AgGaS2) for the non-centrosymmetric (NCS) materials in the IR nonlinear optic...

Recently, model predictive control has been widely used to control grid-connected inverters due to its advantages. However, the conventional model predictive control methods usually require two AC voltage and current sensors to sample the grid voltages and currents. Particularly, the DC voltage sensor is also required to calculate the values of the voltage vectors. The inverter will lose its stability once these sensors fail. Thus, in this study, to improve the operational reliability of the grid-connected inverters, a sliding mode observer-based AC voltage sensorless model predictive control is proposed. First, a sliding mode observer is designed to estimate the grid voltage. Next, a new adaptive compensation strategy is proposed to remove the phase and amplitude errors caused by the low-pass filter. The main novelty of this compensation strategy is that it is immune to the actual grid frequency. Therefore, the grid voltage can be identified accurately, even under frequency deviation conditions. Besides, the stability and parameter designing method of the sliding mode observer is also analysed to provide a theoretical basis for its implementation. Finally, based on the observed grid voltage, the AC voltage sensorless model predictive control is achieved. Detailed comparative experimental results show the validity of the proposed method.

Lead halide perovskite nanocrystals (NCs) have shown remarkable properties for emission applications, but their toxicity and instability are a hindrance to many commercial uses. Herein, we report t...

In this paper the observability of bearing-only tracking is analyzed and the trajectory optimization algorithms to enhance the observability during the rendezvous are presented. Firstly, the relative dynamic model and measurement model are established, and the necessary and sufficient condition for observability when maneuvering is determined using the pseudo linear method. Then, the observability indices, such as the filter covariance matrix trace and the Fisher information matrix (FIM) determinant, are combined with the fuel consumption index to optimize the approaching trajectory. In order to keep the line-of-sight (LOS) aligned with the target and to ensure continuous observation, the attitude of the observer is adjusted synchronously during the rendezvous. Finally, the coordinated control of attitude and orbit for the observer is achieved by optimizing the thrust distribution of the onboard propulsion system. Numerical results demonstrate that the combined optimization of the observability and fuel consumption can generate an optimal control trajectory with high tracking accuracy. The simulation also presents how to choose the optimal relative weight of the two optimization terms, optimal rendezvous time and optimal docking point according to the practical requirements to get the best comprehensive performance of observability and fuel consumption.

A green and straightforward emulsification liquid–liquid micro-extraction combined with the HPLC approach was established for the determination of malachite green (MG) and crystal violet (CV) in shrimp water samples using deep eutectic solvent (DES). The DES was made up of thymol and camphor at a molar ratio of 1:1, which was used as extraction agent, and nonionic surfactant TMN-10 (branched secondary alcohol ethoxylate) was used as an emulsifying agent. A series of parameters were optimized including pH, volume of DES and emulsifying agent, salt concentration as well as centrifugal time. Under optimal conditions, the calibration graphs were linear in the concentration range from 0.2 to 200 μg L−1 for MG and CV. MG and CV of the relative standard deviations (% RSDs) were 1.4 and 2.3, and the limits of detections were 0.09 and 0.13 μg L−1, respectively. Also, the proposed method was applied to analyze the MG and CV in shrimp water samples, and the observed recoveries were between 82.0–99.3% and 78.0–91.4%, respectively.

The reliability and stability of a grid-connected converter is vital to the power conversion system. The faults of switching device and current sensor lead to operation failure for a grid-connected converter. An improved model predictive power control (MPPC) based on reconstructed currents is proposed for fault-tolerant operation of a grid-connected converter. Firstly, the three-phase currents are reconstructed using the sampled dc current and normal sensor information according to the relationship between the voltage vector and output currents. Secondly, the predictive power model is built based on fault-tolerant three-phase four-switch topology. Then the reconstructed current is used for the MPPC method. To keep the balance of dc capacitor voltages, the cost function is optimised and the switching vector, which minimises the cost function, is applied to the fault-tolerant converter. Finally, the experiment platform and simulation models are built to verify the proposed method. The results show that the proposed MPPC using reconstructed currents can keep the fault-tolerant operation of the grid-connected converter with sinusoidal currents and stable output power. The proposed method achieves the fault-tolerant operation under switching device and ac current sensor fault, which improve the reliability of the system.

External diaphragm joint has been widely used in concrete-filled steel tubular (CFST) structure because of its large stiffness, good plasticity, and high bearing capacity. This paper studied new external diaphragm joints designed to connect concrete-filled double steel tubular (CFDST) columns and steel beams. Experiments were conducted to investigate the cyclic performance of nine joint specimens subject to cyclic horizontal load and fixed axial load at the top of the column. The variable parameters considered in the test were axial load of the CFDST column, width of external diaphragm, configuration of anchorage web and beam to column bending stiffness ratio. The load–displacement hysteresis behaviors were discussed. Failure mode of the joints was mainly dependent on beam to column bending stiffness ratio (k) and axial compression ratio (n), so the limit of these two factors should be considered to avoid the column failure in engineering design applications. The shear strain level in panel zone was high especially for weak-column joints. Results also showed that initial stiffness of external diaphragm joint significantly increased with the improvement of axial compression ratio, but the stiffness suffered a sharp degradation; the ductility and energy absorption ability improved with the width improvement of the external diaphragm; ribbed anchorage webs effectively improved initial stiffness and bearing capacity of external diaphragm joints.

Metronidazole(MTZ) is an important antibiotic, which has been widely applied to cure protozoal and bacterial diseases for human beings or animals. Herein, three novel drug supramolecular crystals constructed by MTZ with 2,5-dihydroxy-benzoic acid(2,5-DHBA)(1), 2,6-dihydroxy-benzoic acid(2,6-DHBA)(2) and 3,5-dihydroxy-benzoic acid(3,5-DHBA)(3), respectively, have been discovered. The hydrogen bonds of N—H⋯O(O—H⋯N), C—H⋯O and O—H⋯O play important roles in the 3D supramolecular framework formation for crystals 1–3. Interestingly, due to the vary locations of the substituent groups, the two-dimensional layers in crystals 1 or 2 are constructed via intermolecular hydrogen bonds between MTZ and 2,5-DHBA or 2,6-DHBA, while in crystal 3 water molecules play a significant role except the intermolecular hydrogen bonds between MTZ and 3,5 -DHBA. In addition, five synthons of I R22(8), II R33(9) in crystal 1, III R21(4), IV R22(8) in crystal 2 and V R22(7) in crystal 3 formed through various hydrogen bonds are founded in this work. Systematic studies of syntheses, crystal structures and thermal analysis are reported.

Fantastic structures in nature have inspired much incredible research. Wood, a typical model of anisotropy and hierarchy, has been widely investigated for its mechanical properties and water extraction abilities, although applications in biological areas remain challenging. Delignified wood composite with in situ deposited hydroxyapatite (HAp) and infiltrated polycaprolactone (PCL) is hereby fabricated in an attempt to mimic natural bone. The inherent structure and properties of wood are carefully preserved during the fabrication, showing anisotropic mechanical properties in the radial direction (420 MPa) and longitudinal direction (20 MPa). In addition, it also performs directional liquid transport, effectively inducing the migration and alignment of cells to simulate the uniform seeding behavior of various cells in natural bone. Moreover, the synergistic effect of blended HAp and PCL largely promotes cell proliferation and osteogenic differentiation, providing a promising candidate for bone regeneration materials.

Genetic algorithm is a frequently used evolutionary algorithm that cannot avoid premature convergence. Multi-population is usually used to overcome this disadvantage, obtaining multi-population genetic algorithm (MGA). If sub-populations and communications among them are considered as nodes and edges, respectively, an MGA can be represented as a complex network. After reviewing previous researches, we find that the network structures used to design MGAs are limited and some parameters (SPS, sub-population size, and SPN, sub-population number) under a certain total individual number (TIN) are always ignored. Using seven network structures (BAnet, BDnet, CTnet, ERnet, HAnet, LCnet, and SWnet) to design MGAs that are used to solve some flexible job shop scheduling problems, how the network structures and parameters affect the performances of MGAs is addressed. The simulation results indicate that: (i) the MGA with ERnet rather than the famous BAnet often performs well although their performances are problem-dependent; (ii) the Hamming distance index proposed here can properly capture the phenomenon that the smaller the average path length, the higher the propagation rate; and (iii) under a certain TIN, their performances first increase and then decrease gradually as SPN increases, and their performances first increase rapidly and then remain almost unchanged as SPS increases.

Over the past decades, plenty of filtering algorithms have been presented to distinguish ground and non-ground points from airborne LiDAR point clouds. However, with the existing methods, it is difficult to derive satisfactory filtering results on rugged terrains with dense vegetation due to the low-level penetration ability of laser pulses. Therefore, a multi-level interpolation-based filter is developed in this paper. The novelty of the algorithm lies within its usage of multi-scale morphological operations and robust z-score to correctly select ground seeds as more as possible, and a terrain-adaptive residual threshold to adapt to various terrain characteristics. Rural samples provided by International Society for Photogrammetry and Remote Sensing (ISPRS) were employed to assess the performance of the proposed method and its results were compared with 15 filtering algorithms developed in recent 5 years (2015-2019). Results show that the proposed method with the optimized parameters produces the best accuracy with the average total error and kappa coefficient of 1.89% and 87.88%, respectively. We further filtered high-density point clouds in six forested areas with different vegetation covers and terrain slopes. Results demonstrate that the proposed algorithm is more accurate than the well-known filtering methods including morphological-based filter, progressive TIN densification filter (PTD), improved PTD and cloth simulation filter, with the average total error decreased by 26.2%, 19.9%, 3.8% and 40.4%, respectively. Moreover, the DEMs of the proposed method have lower average root mean square errors than the four classical filters. Therefore, the proposed method can be considered as an effective ground filtering algorithm for airborne LiDAR point clouds in forested areas.

The oxygen content of boiler flue gas is a valid indicator of boiler efficiency and emissions. Measuring the oxygen content of boiler flue gas is time consuming and costly. To overcome the latter shortcomings, a novel deep belief network algorithm based hybrid prediction model for the oxygen content of boiler flue gas is proposed. First, the algorithm is used to build a model based on the historical data collected from the distribution control system. The variables are divided into control variables and state variables to meet the needs of advanced control requirement. Then, a lasso algorithm is used to select variables highly related to the oxygen content as the inputs of the prediction model. Two basic models based on the deep-belief network are established, one using control variables, and the other, state variables. Finally, the two basic models are combined with a least square support vector machine to improve prediction accuracy of the oxygen content of boiler flue gas. To test the accuracy of the proposed algorithm, experiments based on three industrial datasets are performed. Performance of the comparison of the proposed deep belief algorithm is compared with five machine learning algorithms. Computational experience has shown that the model derived with the deep-belief algorithm produced better accuracy than the models generated by the other algorithms.

To explore different photoluminescence phenomenon of Ti4+ ions, a rare-earth-free self-activated phosphor Li2TiSiO5 was synthesized and studied in detail. The crystal structure, photoluminescence properties and thermal quenching of Li2TiSiO5 were discussed. The crystal structure has been investigated by Rietveld refinement, and this indicates that there is a special kind of TiO5 square pyramids in this structure. Under 245 nm excitation, Li2TiSiO5 emits white light ranging from 400 to 780 nm with CIE coordinates of (0.388, 0.441), which is due to the existence of isolated TiO5 square pyramids and TiO6 octahedra in the disordered non-crystalline powder, which is also proved by the time-resolved photoluminescence. The abnormal serious thermal quenching is ascribed to thermal ionization. The study of Li2TiSiO5 broadens the research of rare-earth-free Ti-doped oxides due to its self-activated luminescence and the realization of white light emission in a single host.

This paper proposes an integrated time-frequency rate distribution (TFRD) technique, i.e., coherently integrated trilinear autocorrelation function (CITAF), for the detection and parameter estimation of quadratic frequency modulated (QFM) signal embedded in white Gaussian noise. The basic idea is to design a trilinear autocorrelation function (TAF) enabling a coherent integration of the signal energy in both of the time and lag-time domains. Theoretical analysis and numerical simulations show that this new method has a lower signal to noise ratio (SNR) threshold and higher estimation accuracy in comparison with several state-of-the-art algorithms. Furthermore, the coherently integrated nonuniform TAF (CINTAF) is briefly introduced.

This paper focuses on the inverse synthetic aperture radar (ISAR) imaging of nonuniformly rotating targets under low signal-to-noise ratio (SNR) environment, and an effective ISAR imaging algorithm based on a novel parameter estimation method is proposed. For nonuniformly rotating targets, the received signals in a range cell can be modeled as multicomponent cubic phase signals (CPSs) after the migration compensation and translation-induced phase error correction. For the CPS model, the chirp rate (CR) and quadratic chirp rate (QCR) will induce image defocus. To estimate the CR and QCR of CPS, a novel parameter method is presented. The basic idea of this method is to design a third order autocorrelation function (TOAF) which enable coherent accumulation of the signal energy in both of the time and lag-time domain. Compared with several state-of-the-art algorithms, the proposed method has a significant anti-noise performance improvement, while offering a proper computational complexity. The effectiveness and the superiority of the proposed ISAR imaging algorithm have been demonstrated through several simulation results.

To attenuate positional errors of LiDAR-derived datasets for constructing digital elevation models (DEMs), a feature-preserving point denoising algorithm (F-PDA) is developed in this paper. F-PDA i...

This paper presents a double-vector-based model predictive control method for three-phase grid-connected AC/DC converters. The conventional model predictive control (MPC) presents high steady-state ripples due to the application of only one voltage vector during one control period. To reduce the current ripples, a new MPC method is proposed. Double-voltage vectors are selected and applied it each control period in the proposed method. To reduce the calculation burden, the duration time of each voltage vector is calculated based on the principle of modulated MPC. Furthermore, the effectiveness of the proposed double-voltage vector-based MPC strategy is analyzed in theory for the first time. Then, it is further verified by comparative experiment studies.

Supply networks (SN) must maintain operations and connectedness under disruptions to remain competitive; this is referred to as SN resilience. Building a resilient SN is an underlying challenge in ...

Hole-conductor-free carbon-based perovskite solar cells (C-PSCs) are known for their low-cost and superstability. In this work, different mesoporous structures, namely, mesoporous TiO2 + Al2O3 (mp-TiO2 + Al2O3), mp-TiO2 + ZrO2, mp-Al2O3, mp-TiO2, and blocking compact layer of TiO2 (bl-TiO2), were investigated and systematically compared. Results revealed that the performance of PSCs with double-layer mesoporous structure was better than that of the other mesoporous structures, especially PSC with the structure of mp-TiO2 + Al2O3 obtained the open-circuit voltage (Voc) of 0.97 V and the current density (Jsc) of 23.77 mA cm−2, respectively, the photoelectric conversion efficiency (PCE) reached 11.3% because of the function of the mesoporous layer in separating TiO2 and carbon, thereby avoiding direct contact and reducing the leakage of the current. Al2O3 and ZrO2 are insulating materials that could effectively prevent electrons from transmitting back to C. The mesoporous structure of the device based on mp-TiO2 + Al2O3 was evenly distributed, the perovskite crystal particles based on mp-TiO2 + Al2O3 were enlarged, uniform, and relatively tight, and the grain boundaries between the perovskite crystal particles were remarkably reduced. Among the films, the perovskite film of mp-TiO2 + Al2O3 structure had the highest absorption intensity. This study provided a new basis for commercializing low-cost PSCs.

With recent industrial upgrades, it is essential to transform the current forward supply networks (FSNs) into closed-loop supply networks (CLSNs), which are formed by the integration of forward and reverse logistics. The method chosen in this paper for building reverse logistics is to add additional functions to the existing forward logistics. This process can be regarded as adding reverse edges to the original directed edges in an FSN. Due to the limitation of funds and the demand for reverse flow, we suppose that a limited number of reverse edges can be built in a CLSN. To determine the transformation schemes with excellent robustness against malicious attacks, this paper proposes a multi-population evolutionary algorithm with novel operators to optimize the robustness of the CLSN, and this algorithm is abbreviated as MPEA-RSN. Then, both the generated and realistic SNs are taken as examples to validate the effectiveness of MPEA-RSN. The simulation results show that the index R, introduced to evaluate the robustness of CLSNs, can be improved by more than 95%, and this indicates that (1) the different schemes for adding reverse routes to an FSN can lead to different robustness values, and (2) the robustness of the transformed CLSN to malicious attacks can be significantly improved after optimization by MPEA-RSN. When an FSN is to be transformed into a CLSN, this paper can provide a frame of reference for building a CLSN that is robust to malicious attacks from a network structural perspective.

Relative permeability curve is a key factor in describing the characteristics of multiphase flow in porous media. The steady-state method is an effective method to measure the relative permeability curve of oil and water. The capillary discontinuity at the end of the samples will cause the capillary end effect. The capillary end effect (CEE) affects the flow and retention of the fluid. If the experimental design and data interpretation fail to eliminate the impact of capillary end effects, the relative permeability curve may be wrong. This paper proposes a new stability factor method, which can quickly and accurately correct the relative permeability measured by the steady-state method. This method requires two steady-state experiments at the same proportion of injected liquid (wetting phase and non-wetting phase), and two groups of flow rates and pressure drop data are obtained. The pressure drop is corrected according to the new relationship between the pressure drop and the core length. This new relationship is summarized as a stability factor. Then the true relative permeability curve that is not affected by the capillary end effect can be obtained. The validity of the proposed method is verified against a wide range of experimental results. The results emphasize that the proposed method is effective, reliable, and accurate. The operation steps of the proposed method are simple and easy to apply.

Airborne light detection and ranging (LiDAR) technology has become the mainstream data source in geosciences and environmental sciences. Point cloud filtering is a prerequisite for almost all LiDAR-based applications. However, it is challenging to select a suitable filtering algorithm for handling high-density point clouds over complex landscapes. Therefore, to determine an appropriate filter on a specific environment, this paper comparatively assessed the performance of five representative filtering algorithms on six study sites with different terrain characteristics, where three plots are located in urban areas and three in forest areas. The representative filtering methods include simple morphological filter (SMRF), multiresolution hierarchical filter (MHF), slope-based filter (SBF), progressive TIN densification (PTD) and segmentation-based filter (SegBF). Results demonstrate that SMRF performs the best in urban areas, and compared to MHF, SBF, PTD and SegBF, the total error of SMRF is reduced by 1.38%, 48.21%, 48.25% and 31.03%, respectively. MHF outperforms the others in forest areas, and compared to SMRF, SBF, PTD and SegBF, the total error of MHF is reduced by 1.98%, 35.87%, 45.11% and 9.42%, respectively. Moreover, both SMRF and MHF keep a good balance between type I and II errors, which makes the produced DEMs much similar to the references. Overall, SMRF and MHF are recommended for urban and forest areas, respectively, and MHF averagely performs slightly better than SMRF on all areas with respect to kappa coefficient.

Large-scale landsliding is an extremely important geological process in shaping landscapes in the Tibetan Plateau. In this research, an ancient river-damming landslide with an estimated debris volume of 4.9 × 107 m3, located in the upper Jinsha River, SE Tibetan Plateau, was studied. The landslide once formed a dam over 60 m high and blocked the river. Lacustrine sediments, composed of silty clay with particle sizes of 0.002–0.25 mm, are intermittently distributed along both banks, extending about 6.5 km upstream. The OSL dating indicates that the lacustrine sediments have an age of 2.6 ± 0.2 ka. Detailed field investigation and theoretical analysis was performed to investigate the characteristics, potential cause and mechanism of the landslide. The results suggest that the landslide was most likely triggered by buckling of planar rock slabs under gravity. It may start as a translational sliding along the weak interlayer composed of mica schist at the upper part of the slope and then formed buckles by curving amphibolite rock beds near the slope toe. The hillslope has still been affected by gravitational deformations, with geomorphology characterized by tension cracks, buckle folds, and small landslide scars distributed on the slope surface, suggesting that the evolution of the river valley caused by buckling deformation has not achieved equilibrium.

We proposed the Retinex-based fast algorithm (RBFA) to achieve low-light image enhancement in this paper, which can restore information that is covered by low illuminance. The proposed algorithm consists of the following parts. Firstly, we convert the low-light image from the RGB (red, green, blue) color space to the HSV (hue, saturation, value) color space and use the linear function to stretch the original gray level dynamic range of the V component. Then, we estimate the illumination image via adaptive gamma correction and use the Retinex model to achieve the brightness enhancement. After that, we further stretch the gray level dynamic range to avoid low image contrast. Finally, we design another mapping function to achieve color saturation correction and convert the enhanced image from the HSV color space to the RGB color space after which we can obtain the clear image. The experimental results show that the enhanced images with the proposed method have better qualitative and quantitative evaluations and lower computational complexity than other state-of-the-art methods.

SARS-CoV-2 caused the COVID-19 pandemic that lasted for more than a year. Globally, there is an urgent need to use safe and effective vaccines for immunization to achieve comprehensive protection against SARS-CoV-2 infection. Focusing on developing a rapid vaccine platform with significant immunogenicity as well as broad and high protection efficiency, we designed a SARS-CoV-2 spike protein receptor-binding domain (RBD) displayed on self-assembled ferritin nanoparticles. In a 293i cells eukaryotic expression system, this candidate vaccine was prepared and purified. After rhesus monkeys are immunized with 20 μg of RBD–ferritin nanoparticles three times, the vaccine can elicit specific humoral immunity and T cell immune response, and the neutralizing antibodies can cross-neutralize four SARS-CoV-2 strains from different sources. In the challenge protection test, after nasal infection with 2 × 105 CCID50 SARS-CoV-2 virus, compared with unimmunized control animals, virus replication in the vaccine-immunized rhesus monkeys was significantly inhibited, and respiratory pathology observations also showed only slight pathological damage. These analyses will benefit the immunization program of the RBD–ferritin nanoparticle vaccine in the clinical trial design and the platform construction to present a specific antigen domain in the self-assembling nanoparticle in a short time to harvest stable, safe, and effective vaccine candidates for new SARS-CoV-2 isolates.

Graphene has been wildly used as a host to suppress dendrite growth to stabilize the lithium metal anode. However, the high overpotential of lithium deposition on pure graphene has to be lowered by doping or employing precious metals. Additionally, the soft nature of graphene rendered itself to aggregate, consequently squeezing room for lithium accommodation. Herein, a tough graphene framework composed of 3D periodic hollow spheres was reported as a free-standing host to stabilize lithium metal anodes. The prepared 3D periodic hollow structure not merely reinforces the framework to maintain hollow structure under pressure caused by assembling battery, but also lowers the overpotential without the help of dopant or precious metals. It is worthy to note that high efficiency of ion diffusion, thanks to the channels interconnecting hollow spheres by holes on the walls, benefits both suppression of lithium dendrite and rate capability. The properties of low density and high mechanical strength make graphene frameworks electrode a promising lightweight Li host material, which reveals a new avenue for designing high-energy density electrode materials.

Carbon materials with a high specific surface area are usually preferred to construct the air cathode of lithium-air batteries due to their abundant sites for oxygen reduction and discharge product growth. However, the high surface area also amplifies electrolyte degradation during charging, which would become the threshold of cyclability after addressing the issue of electrode passivation and pore clogging, but is usually overlooked in relevant research. Herein, it is proven that the critical influence of cathode surface area on electrolyte consumption by adopting carbon-ceramic composites to reduce the surface area of the air cathode. After screening several potential ceramic materials, an optimal composite of Ketjenblack (KB) and La0.7 Sr0.3 MnO3 (LSM) delivered a discharge capacity that was even higher than that of pure KB. This composite effectively mitigated the parasitic reaction current by 45 % if polarized at 4.4 V versus Li+ /Li. Correspondingly, this composite prolonged the cycle life of the cell by 156 %. The results demonstrate that electrolyte consumption during charging is one of the critical boundary conditions to restrain the cyclic stability of lithium-air batteries.

This paper focuses on geostationary satellites with an electric propulsion system and develops two efficient station-keeping strategies in full and failure modes. High-precision mean orbital elements are calculated by an estimator and used as the inputs of two control strategies. In the full mode, an optimization-based maneuver planner, which requires the computations of future orbits, is proposed to achieve long-term minimum-fuel station-keeping. In the failure mode, a fault detection algorithm is designed to diagnose the thruster failure and compute the orbital deviation caused by faulted thruster. Subsequently, a real-time control law as well as a threshold function is formulated to produce the on-off commands of electric thrusters, which correct the orbital deviation. Finally, numerical simulations are made to validate the accuracy and efficiency of two strategies.

Artificial Z-scheme photocatalytic systems have received considerable attention in recent years because they can achieve wide light-absorption, high charge-separation efficiency, and strong redox ability simultaneously. Nevertheless, it is still challenging to exploit low-cost and stable Z-scheme photocatalysts with highly-efficient H2 evolution from solar water-splitting so far. Herein, we report a novel all-solid-state Z-scheme photocatalyst Cd1− x Zn x S@WO3− x consisting of Cd1− x Zn x S nanorods coated with oxygen-deficient WO3− x amorphous layers. The Cd1− x Zn x S@WO3− x exhibits an outstanding H2 evolution reaction (HER) activity as compared with Pt-loaded Cd1− x Zn x S and most WO3- and CdS-based photocatalysts, due to the generation of stronger reducing electrons through the appropriate Zn-doping in Cd1− x Zn x S and the enhanced charge transfer by introducing oxygen vacancies (W5+/OVs) into the ultrathin WO3− x amorphous coatings. The optimal HER rate of Cd1− x Zn x S@WO3− x is determined to be 21.68 mmol h−1 g−1, which is further raised up to 28.25 mmol h−1 g−1 (about 12 times more than that of Pt/Cd1− x Zn x S) when Cd1− x Zn x S@WO3− x is hybridized by CoO x and NiO x dual cocatalysts (Cd1− x Zn x S@WO3− x /CoO x /NiO x ) through in - situ photo-deposition. Moreover, the corresponding apparent quantum yield (AQY) at 420 nm is significantly increased from 34.6% for Cd1− x Zn x S@WO3− x to 60.8% for Cd1− x Zn x S@WO3− x /CoO x /NiO x . In addition, both Cd1− x Zn x - S@WO3− x and Cd1− x Zn x S@WO3− x /CoO x /NiO x demonstrate good stability towards HER. The results displayed in this work will inspire the rational design and synthesis of high-performance nanostructures for photocatalytic applications.

Nanostructured ZnO semiconductors as gas sensing materials have attracted great attention due to their high sensitivities, especially to reducing gases. However, ZnO based gas sensors lack controll...

Exosomes are bilayer vesicles with particle sizes between 50 and 150 nm. Owing to their bilayer membrane structure, cell-to-cell communication, and good absorbability, exosomes are increasingly used as carriers for drug delivery through phospholipid membrane structures to lesion sites with enhanced targeting. Exosome sources and drug-loading methods are important factors affecting their use as drug carriers. There are various ways to pack species in exosomes, and researchers are constantly seeking new and improved approaches. In both in vivo and in vitro evaluations, exosomal vectors have achieved good antitumor efficacies. Despite the importance of exosomes as drug delivery systems with accurate targeting ability and biocompatibility, improvements are needed to facilitate their widespread clinical use. This review focuses on the preparation of exosomes as carriers and their utilization in antitumor research.