The hydrothermal method was used to prepare flexible BiOCl-BiOI films on one stainless steel wire mesh. Nano-flower like BiOCl-BiOI crystals consisted of nanoplates were formed, and BiOCl was uniformly distributed. The XPS (X-ray photoelectron spectroscopy) spectra confirm the formation of BiOCl-BiOI heterojunction, which enhanced the visible light absorption of the BiOI film. The photocatalytic activity of the BiOCl-BiOI film in degrading RhB and MB was elevated by at most 8.7 and 2.4 times, respectively, comparing with the individual BiOI film. We designed and constructed a piezo/photocatalytic platform in which the prepared BiOCl-BiOI films were fixed on a rotating shaft. Compared with the static state, the photocatalytic activity of the BiOCl-BiOI film was increased by 1.4 times when the shaft was rotating. We believe that the enhancement of the photocatalytic activity should be ascribed to the piezoelectric field by introducing bending deformation, which accelerated the separation of photogenerated electrons and holes. The improvement mechanism of the photocatalytic and piezo/photocatalytic performance was proposed and discussed. The flexible BiOCl-BiOI heterojunction films show significant application potential in the pollution control of fluid fields such as rivers, oceans, waterfalls, and air.

Precise single-point positioning using carrier-phase measurements can be provided by the synchronized pseudolite system. The primary task of carrier phase positioning is ambiguity resolution (AR) with rapidity and reliability. As the pseudolite system is usually operated in the dense multipath environment, cycle slips may lead the conventional least-squares ambiguity decorrelation adjustment (LAMBDA) method to incorrect AR. A new AR method based on the idea of the modified ambiguity function approach (MAFA), which is insensitive to the cycle slips, is studied in this paper. To improve the model strength of the MAFA and to eliminate the influence of constant multipath biases on the time-average model in static mode, the kinematic multi-epoch MAFA (kinematic ME-MAFA) algorithm is proposed. A heuristic method for predicting the 'float position' corresponding to every Voronoi cell of the next epoch, making use of Doppler-based velocity information, is implemented to improve the computational efficiency. If the success rate is very close to 1, it is possible to guarantee reliable centimeter-level accuracy positioning without further ambiguity validation. Therefore, a computing method of the success rate for the kinematic ME-MAFA is proposed. Both the numerical simulations and the kinematic experiment demonstrate the feasibility of the new AR algorithm according to its accuracy and reliability. The accuracy of the horizontal positioning solution is better than 1.7 centimeters in our pseudolite system.

The pseudo-satellite local positioning system can solve the problem of blind spots in satellite navigation systems, such as tunnels, underground parking lots, and indoor positioning. The method of direction-finding positioning can be combined with distance-finding positioning to improve positioning accuracy, and it can also independently realize positioning functions. The basis of direction-finding positioning is to accurately estimate the direction of the signal source. The sum-difference patterns of amplitude monopulse angle measurement algorithm has mature applications in the field of tracking radar, and can achieve accurate angle estimation. The sum-difference patterns of amplitude monopulse angle measurement algorithm is applied to a pseudo-satellite local positioning system. Through simulation experiments, the angle measurement performance of the algorithm under different conditions is analyzed.

A synthetic aperture radar (SAR) target recognition method is proposed via linear representation over the global and local dictionaries. The collaborative representation is performed on the local dictionary, which comprises of training samples from a single class. Then, the reconstruction errors as for representing the test sample reflect the absolute representation capabilities of different training classes. Accordingly, the target label can be directly decided when one class achieves a notably lower reconstruction error than the others. Otherwise, several candidate classes with relatively low reconstruction errors are selected as the candidate classes to form the global dictionary, based on which the sparse representation-based classification (SRC) is performed. SRC also produces the reconstruction errors of the candidate classes, which reflect their relative representation capabilities for the test sample. As a comprehensive consideration, the reconstruction errors from the collaborative representation and SRC are fused for decision-making. Therefore, the proposed method could inherit the high efficiency of the collaborative representation. In addition, the selection of the candidate training classes also relieves the computational burden during SRC. By combining the absolute and relative representation capabilities, the final classification accuracy can also be improved. During the experimental evaluation, the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset is employed to test the proposed method under several different operating conditions. The proposed method is compared with some other SAR target recognition methods simultaneously. The results show the superior performance of the proposed method.

A stable super-slip material with the electrical conductive property has been synthesized by chemical grafting. The multi-walled carbon nanotubes (MWCNTs) were chosen as the electrical conductive matrix. After the acidification of the mixed acid, the original MWCNTs were oxidized to form carboxyl groups on the surface. The octadecylamine (ODA) was bonded on the acidified MWCNTs with the amidation reaction. In order to obtain higher grafting rate, dicyclohexylcarbodiimide (DCC) was added into the reaction system. The MWCNTs with the ODA grifted had properties of superhydrophobic and super-slip. The modified MWCNTs properties of anti-icing, resistance of ultraviolet and acid-alkali were verified during the testing. The modified MWCNTs can be used as electrical conductors for special service, such as devices requiring hydrophobicity and super-slip.

Abstract. Multifeature decision fusion is an effective way to promote the performance of target recognition of synthetic aperture radar (SAR) images. This paper proposes a joint multifeature decision fusion strategy for target recognition in SAR images based on multitask compressive sensing (MtCS). The proposed method can exploit the intercorrelations among different features by enforcing the constraint on the sparsity pattern. Furthermore, the time consumption for MtCS is almost the same with that of single feature-based compressive classification, such as sparse representation-based classification. Experiments on the moving and stationary target acquisition and recognition dataset and comparison with several state-of-the-art methods demonstrate the validity of the proposed method.

The soft error caused by single event effects is one of the main factors that affect the reliability of aerospace electronic system. This paper introduces the theoretical basis of soft error propagation based on cellular automata theory, and then establishes the propagation model of soft errors in the system. The mathematical function is used to express the state parameters of each module and the coupling relationship between the modules, quantify the propagation process of the soft errors in the system, and obtain the sensitivity of each module to the soft errors to judge the sensitive modules of the system.

The spatial information processing of satellite-borne synthetic aperture radar (SAR) images has very important meanings. This paper proposes an SAR automatic target recognition (ATR) method based on the fusion of complementary features. PCA features, elliptical Fourier descriptors (EFDs) and local binary pattern (LBP) are used to describe SAR images from different aspects thus they can jointly give the SAR targets more detailed representations. The three features are classified by sparse representation-based classification (SRC), respectively. And their decisions are fused based on Bayesian decision fusion for target recognition. Experiments are conducted on the moving and stationary target acquisition recognition (MSTAR) dataset to evaluate the effectiveness of the proposed method.

With the rapid growth of economy, the situation of oil/water pollution has been intensified to be solved urgently. A membrane for separating emulsions with opposite wettability is prepared by modified with FeOOH and ZnO nanoparticles. The membrane preforms properties of superoleophobicity under water and superhydrophobicity under oil. The oil contact angle of hydrophilic side is 151.7° and water contact angle of hydrophobic is 153.6°. Due to the opposite wettability at the two sides, oil-in-water and water-in-oil emulsions can be separated by the membrane. This membrane shows a universal strategy to solve complex emulsion separation problem by using multifunctional materials.

Introduction: Large granular lymphocyte (LGL) leukemia is a spectrum of rare clonal lymphoproliferative disorders, all of which involve expansion of large granular lymphocytes. Immunosuppressive regimens using methotrexate or cyclophosphamide are utilized as front-line treatments in LGL leukemia but are not curative nor are they effective in all patients. The aggressive LGL variants have no effective treatment and are refractory to conventional chemotherapy. The lack of effective and targeted therapies results from an incomplete picture of survival mechanisms that contribute to the pathogenesis of leukemic LGLs.

Improving the autonomous operation ability has become a main goal of satellite navigation system in the new century. The technology to apply inter-satellite link (ISL) to perform high precision measuring between satellites is a technology to implementing autonomous operation of navigation satellite constellation, and Dual-One-Way Ranging (DOWR) of Ka band is an effective way to carry out high precision measurement between satellites. Ka DOWR data of satellite-ground could be achieved by setting up the measuring link between orbiting satellite and pseudolite on the ground, analyzing precision it combined with precision analysis of troposphere and ionosphere correcting models, we can further infer the ranging precision of satellite–satellite. In order to evaluate the precision of satellite–ground Ka DOWR data, a method of using SLR data as exterior checking for comparison is proposed. The raw data of Ka and SLR contain environment effect, and their measuring time and spatial reference do not coincide. To achieve high precision evaluation of Ka DOWR data by SLR, it is needed to go through the environment error correction, time, and spatial reference formalization and some other steps. The errors in the steps will have impact on the final precision evaluation result. In order to verify the feasibility of this evaluation method, this paper starts from the principal of Ka DOWR and SLR, then analyzes the error sources that impact the evaluation result and expounds the principle and process of this evaluation method. By setting up the ground test simulation platform of ISL, the Ka satellite-ground DOWR and SLR data are obtained and analyzed. The simulation results show that the evaluation precision of this proposed method is in the magnitude of centimeters, which can provide reference for the analysis of the satellite–ground test data of ISL.