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Multi-set membership queries are fundamental operations in data science. In this paper, we propose a new data structure for multi-set membership queries, named coloring embedder, which is fast, accurate, and memory efficient. The idea of coloring embedder is to first map elements to a high-dimensional space, which nearly eliminates hashing collisions, and then use a dimensional reduction representation, similar to coloring a graph, to save memory. Theoretical proofs and experimental results show that the coloring embedder is effective in solving the problem of multi-set membership queries. We also find that web cache sharing is one of the typical application scenarios of the multi-set membership queries and current methods based on Bloom filters always send redundant queries. We apply coloring embedder to web cache sharing by arranging our data structure on the on-chip and off-chip memory and designing query, insertion and deletion operations for this scenario. The experimental results show that compared with the present method, our method can reduce the queries sent by proxies while reaching equal hit rate with the same size of on-chip memory. The source code of coloring embedder has been released on Github.

To design an automatic harvesting machine for hydroponic lettuce (Lactuca sativa L.), physical and mechanical properties of hydroponic lettuce were investigated and analyzed. Moisture content of stem, root and leaf, geometric characteristics, pulling force, and root cutting force were studied for harvesting hydroponic lettuce. The pulling force was examined by a tensile experiment, while the root cutting force was investigated by a shear experiment on the electronic universal testing machine. The moisture content of hydroponic lettuce was obtained by direct drying. Experiment data were processed using regression analysis and mathematical statistics method. A regression equation and the law of numerical distribution were obtained. The results showed that the geometric size of different hydroponic lettuce had little difference, and the distribution of physical parameters was concentrated. Moisture content was found statistically similar in stem and root (around 91%), while the highest moisture content was found in the leaf of 95.73%. The root cutting force decrease with the increase of cutting speed and decrease with the cutting position move downward. The minimum average root cutting force in the experiment was 1.41 N. The average pulling force was 13 N. This study provides adequate theoretical support for the design of the automatic harvesting machine of hydroponic lettuce.

Dion-Jacobson (DJ) quasi-2D perovskite solar cells (PSCs) have received increasing attention due to their greater potentials in realizing efficient and stable quasi-2D PSCs relative to their Ruddlesden-Popper counterpart. The substitution of methylammonium (MA+) with formamidinium is expected to be able to further increase the stability and power conversion efficiency (PCE) of DJ quasi-2D PSCs. Herein, we report a multifunctional additive strategy for preparing high-quality MA-free DJ quasi-2D perovskite films, where 1,1'-carbonyldi(1,2,4-triazole) (CDTA) molecules are incorporated into the perovskite precursor solution. CDTA modification can control phase distribution, enlarge grain size, modulate crystallinity and crystal orientation, and passivate defects. After CDTA modification, more favorable gradient phase distribution and accordingly gradient band alignment are formed, which is conducive to carrier transport and extraction. The improved crystal orientation can facilitate carrier transport and collection. The enlarged grain size and effective defect passivation contribute to reduced defect density. As a result, the CDTA-modified device delivers a PCE of 16.07%, which is one of the highest PCEs ever reported for MA-free DJ quasi-2D PSCs. The unencapsulated device with CDTA maintains 92% of its initial PCE after aging under one sun illumination for 360 h and 86% after aging at 60 °C for 360 h.

In recent years, ionic conductive hydrogels have shown great potential for application in flexible sensors, energy storage devices, and actuators. However, developing facile and effective methods for fabricating such hydrogels remains a great challenge, especially for hydrogels that retain their properties in extreme environmental conditions, such as at subzero temperatures or storage in open-air conditions. Herein, a water-miscible ionic liquid (IL), such as 1-ethyl-3-methylimidazolium acetate (EMImAc), was introduced to form an IL/water binary solvent system for poly(vinyl alcohol) (PVA) to create ionic conductive PVA hydrogels. The physically crosslinked PVA/EMImAc/H2O hydrogels showed better mechanical properties and transparency than the traditional PVA hydrogel prepared by the freeze-thaw method due to the formation of homogeneous and small PVA microcrystals in the EMImAc/H2O binary solvent system. More importantly, the PVA/EMImAc/H2O hydrogel exhibited significant anti-freezing and water-retaining properties because of the presence of the IL. The hydrogels remained flexible and conductive at temperatures as low as -50 °C and retained more than 90% of their weight after storage in open-air conditions for 2 weeks. In addition, the thermal stability of the hydrogel could be increased to 95 °C through the addition of Mg(II) ions. A multimodal sensor based on the PVA/EMImAc/H2O/Mg(II) hydrogel showed high sensitivity and a quick response to changes in pressure, strain, and temperature, with both long-term stability and a wide working temperature range. This study may open a new route for the fabrication of functional PVA-based hydrogel electrolytes and provide a practical pathway for their use in multifunctional electronic and sensory device applications.

Polymer composites with high dielectric constant and thermal stability have shown great potential applications in the fields relating to the energy storage. Herein, core-shell structured polyimide@BaTiO3 (PI@BT) nanoparticles were fabricated via in-situ polymerization of poly(amic acid) (PAA) and the following thermal imidization, then utilized as fillers to prepare PI composites. Increased dielectric constant with suppressed dielectric loss, and enhanced energy density as well as heat resistance were simultaneously realized due to the presence of PI shell between BT nanoparticles and PI matrix. The dielectric constant of PI@BT/PI composites with 55 wt% fillers increased to 15.0 at 100 Hz, while the dielectric loss kept at low value of 0.0034, companied by a high energy density of 1.32 J·cm−3, which was 2.09 times higher than the pristine PI. Moreover, the temperature at 10 wt% weight loss reached 619°C, demonstrating the excellent thermostability of PI@BT/PI composites. In addition, PI@BT/PI composites exhibited improved breakdown strength and toughness as compared with the BT/PI composites due to the well dispersion of PI@BT nanofillers and the improved interfacial interactions between nanofillers and polymer matrix. These results provide useful information for the structural design of high-temperature dielectric materials.

Lithium solid-state batteries (SSBs) with tantalum doped Li7La3Zr2O12 (LLZT) inorganic ceramic electrolytes have been attracting much interest for its extraordinary lithium ionic conductivity, non-flammability, and wide electrochemical window. However, poor solid–solid contact between the electrodes and electrolyte results in large interfacial resistance, which hinders its normal operation and practical application. Herein, triethylene glycol diacetate-2-propenoic acid butyl ester (TEGDA-BA) based gel polymer electrolytes (GPE) were fabricated and coated on both sides of spark plasma sintering (SPS)–derived LLZT pellet. GPE introduction not only provides intimate contact between solid electrolyte and electrodes but also avoids side reactions such as reduction of LLZT by lithium anode. Moreover, symmetric Li cell markedly reduced interfacial resistance and exhibited a critical current density up to 1.0 mA cm−2 at room temperature (25 °C), and it can also stably cycle at 0.5 mA cm−2 for over 277 h without Li dendrite formation. The assembled solid-state LiNi0.5Co0.2Mn0.3O2 (NCM523)/GPE–LLZT–GPE/Li battery exhibits high initial capacity (163.5 mAh g−1) at 0.2 C. This work provides a facile method to reduce the interfacial resistance and demonstrates durable high-energy solid-state lithium metal batteries suitable for practical application.

Bulk and interfacial nonradiative recombination hinder the further enhancement of the power conversion efficiency (PCE) and stability of SnO2-based planar perovskite solar cells (PSCs). To date, it is still a huge challenge to minimize the bulk and interfacial nonradiative recombination losses, and thus maximize the potentials of PCE and stability. Herein, a novel and effective multifunctional modification strategy through incorporating Girard's Reagent T (GRT) molecules with multiple functional groups to modify SnO2 nanoparticles (NPs), which significantly reduces the bulk and interfacial nonradiative recombination losses through the simultaneous achievement of suppressing nanoparticle agglomeration, improving the electronic property of SnO2 films, facilitating the vertical growth and enlarging the grain size of perovskite crystals, and passivating interfacial defects is reported. As a result, the device based on GRT modification delivers a much higher PCE of 21.63%, along with significantly suppressed hysteresis, as compared to the control device (19.77%). The device stability is ameliorated after GRT modification. The unencapsulated device with GRT maintains 99.5% of its initial PCE after aging at 60 °C for 720 h and 58.5% after illumination for 672 h under one sun, respectively. The present work provides guidance for the design of multifunctional modification molecules toward efficient and stable PSCs.

Due to their outstanding properties, bioadhesive hydrogels have been extensively studied by researchers in recent years. By designing the properties of bioadhesive hydrogels, they can be reasonably applied to biomedicine. Therefore, this practicality has prompted the birth of many bioadhesive hydrogels with excellent properties. In this review, by studying the progress in the field of bioadhesive hydrogels, we summarized the properties of hydrogels in bioadhesion, including adhesion, biocompatibility, degradability and antibacterial properties. In addition, we also summarized the applications of bioadhesive hydrogels in wound dressings, tissue repair, cell adhesion and wearable sensors. Finally, we summarized and outlooked the research on bioadhesive hydrogels, hoping to provide a valuable reference for the progress in the field of bioadhesive hydrogels.

Sentiment classification has been broadly applied in real life, such as product recommendation and opinion-oriented analysis. Unfortunately, the widely employed sentiment classification systems based on deep neural networks (DNNs) are susceptible to adversarial attacks with imperceptible perturbations into the legitimate texts (also called adversarial texts ). Adversarial texts could cause erroneous outputs even without access to the target model, bringing security concerns to systems deployed in safety-critical applications. However, studies on defending against adversarial texts are still in the early stage and not ready for tackling the emerging threats, especially in dealing with unknown attacks. Investigating the minor differences between adversarial texts and legitimate texts and enhancing the robustness of target models are two mainstream ideas for defending against adversarial texts. However, both of them suffer the generalization issue in dealing with unknown adversarial attacks. In this paper, we proposed a general method, called TextFirewall , for defending against adversarial texts crafted by various adversarial attacks, which shows the potential in identifying new developed adversarial attacks in the future. Given a piece of text, our TextFirewall identifies the adversarial text by investigating the inconsistency between the target model’s output and the impact value calculated by important words in the text. TextFirewall could be deployed as a third-party tool without modifying the target model and agnostic to the specific type of adversarial texts. Experimental results demonstrate that our proposed TextFirewall effectively identifies adversarial texts generated by the three state-of-the-art (SOTA) attacks and outperforms previous defense techniques. Specifically, TextFirewall achieves an average accuracy of 90.7% on IMDB and 96.9% on Yelp in defending the three SOTA attacks.

While the design and implementation of cascade reactions in organic chemistry and enzymatic biosynthesis flourished in the past decades, cascade reactions in polymerization remain an emerging conce...

Flexible ionic conductive hydrogel is attracting significant interest as it could be one of the crucial components for multifunctional ionotronic devices. However, their features of inevitably drying out without package and freezing at subzero temperatures may greatly limit the applications of conventional hydrogels in specific situations. Here, we present an ionic conductive hydrogel with water retention and freezing tolerance that consists of silk fibroin, ionic liquid, water, and inorganic salt. It is discovered that the ionic liquid serves multiple purposes to prevent water evaporation, decrease the freezing point, provide the essential conductivity of the hydrogel, etc. As a binary mixed solvent, the ionic liquid/water mixture enhances both water retention and freezing tolerance of the hydrogel electrolyte. Based on the silk fibroin (SF)/1-ethyl-3-methylimidazolium acetate (EMImAc)/H2O/KCl hydrogel electrolyte, the flexible fiberlike supercapacitor could still function well at a temperature as low as -50 °C and after being stored in the open air for a long time. It is anticipated that this hydrogel will prove useful in developing new applications operating under harsh environments.

A reduction in the use of aluminum (Al)-based flocculants in the treatment of drinking water is considered essential for human health reasons. In this study, a novel composite flocculant, made of carboxymethylpullulan-AlCl3 , is evaluated in a lab-scale, jar test system for the flocculation of kaolin. The results showed that the coagulation efficiency of carboxymethylpullulan-AlCl3 was more effective in reducing turbidity than the solo use of carboxymethylpullulan or AlCl3 . The optimum treatment conditions assessed by a response surface methodology were obtained at pH 6.50, 13.03 mg/L carboxymethylpullulan, and 94.87 mg/L AlCl3 . Zeta potential measurements and photometric dispersion analysis demonstrated that AlCl3 had a more significant influence on charge neutralization than carboxymethylpullulan, whilst carboxymethylpullulan facilitated absorption and the development of particle bridges. Thus, the composite flocculant possessed both advantages that enhanced flocculation, and decreased the dosage of AlCl3 , thereby reducing the potential for secondary environment pollution. When 90 mg/L carboxymethylpullulan-AlCl3 was added to the model kaolin suspension characterized by a turbidity of 50 nephelometric turbidity units, the zeta potential and the maximum flocculating activity were determined as -2.28 mV and 98.0%, respectively. The results provide insight into the development of an environment-friendly composite flocculant prepared from water-dissolved polysaccharide and inorganic flocculants. PRACTITIONER POINTS: A novel composite flocculant CMP-AlCl3 was achieved by combining CMP and AlCl3 for water treatment. The coagulation efficiency of CMP-AlCl3 was more effective in reducing turbidity than the solo use of CMP or AlCl3 . The flocculation efficiency and mechanism were investigated by Zeta potential analysis, surface morphology, electron microscopy, and coagulation.

Tensor train is a hierarchical tensor network structure that helps alleviate the curse of dimensionality by parameterizing large-scale multidimensional data via a set of network of low-rank tensors. Associated with such a construction is a notion of Tensor Train subspace and in this paper we propose a TT-PCA algorithm for estimating this structured subspace from the given data. By maintaining low rank tensor structure, TT-PCA is empirically more robust to noise as compared to PCA or Tucker-PCA. This is borne out numerically by testing the proposed approach on the Extended YaleFace Dataset B, MINIST Dataset, CIFAR-10 dataset. This paper shows that the TT-PCA methods achieve less storage requirements, and have computationally faster online implementation with improved classification performance.

Single-molecule cytoplasmic dynein function is well understood, but there are major gaps in mechanistic understanding of cellular dynein regulation. We reported a mode of dynein regulation, force adaptation, where lipid droplets adapt to opposition to motion by increasing the duration and magnitude of force production, and found LIS1 and NudEL to be essential. Adaptation reflects increasing NudEL-LIS1 utilization; here, we hypothesize that such increasing utilization reflects CDK5-mediated NudEL phosphorylation, which increases the dynein-NudEL interaction, and makes force adaptation possible. We report that CDK5, 14-3-3ε, and CDK5 cofactor KIAA0528 together promote NudEL phosphorylation and are essential for force adaptation. By studying the process in COS-1 cells lacking Tau, we avoid confounding neuronal effects of CDK5 on microtubules. Finally, we extend this in vivo regulatory pathway to lysosomes and mitochondria. Ultimately, we show that dynein force adaptation can control the severity of lysosomal tug-of-wars among other intracellular transport functions involving high force.

The Environmental Impact Assessment (EIA) is one of the important means of environmental management worldwide, and the EIA follow-up is one of the crucial measures to ensure the concrete implementation of the EIA. In this research, systematic reviews of EIA follow-up for projects in China were conducted to comprehensively appraise the implementation of the EIA follow-up and to identify the potential to improve the practice of an EIA follow-up. First, the EIA follow-up reports were collected through various sources. In total, there were 74 EIA follow-up reports that were identified and acquired. Second, a reviewing framework, containing 16 different indicators, was developed to systematically document and classify these EIA follow-up reports. Third, these EIA follow-up reports were grouped into several categories according to various indicators and then were analyzed to recognize their key features, including sources of data, analytic tools adopted, spatial-temporal distribution, industrial distribution, triggering causes, content, structure and effectiveness. The results showed that there were considerable disparities in the quality and the rigor of EIA follow-ups conducted. These features, along with some existing deficiencies of EIA follow-up, such as the lack of corresponding monitoring and management, can greatly limit the overall application and effectiveness of EIA follow-up in China. However, a number of good practices were identified. For example, a list of projects subject to mandatory EIA follow-up was promulgated, and the conditions for projects subject to EIA follow-up were explicitly stipulated in regulations. These good practices would be very helpful for the international EIA community to advance the practice of EIA follow-up, to reduce the disparities in the quality and the rigor of EIA follow-up, to improve the overall effectiveness of EIA follow-up and to promote the future implementation and development of EIA follow-up

In developed countries, the automation and intelligent development of vehicles has reached a relatively high level and has gradually developed in China. In recent years, algorithms for lane detection have emerged in an endless stream, but the advantages and disadvantages of comprehensive comparison of various algorithms have resulted in the following problems: First, the robustness of lane line detection is poor, mainly due to the surrounding environment of the road. The impact is greater, in traffic-intensive city streets, affected by natural factors such as trees or building shadows around the driveway; second, the real-time nature of the lane line detection is poor, affected by other marking lines on the driveway, or damaged in the lane. When the pollution is serious, the image of the lane line collected by the system is incomplete and of poor quality, which increases the difficulty of analyzing and processing data of the detection system. This article aims at the problems existing in the current lane line detection and determines the research focus of the article: (1) Improve the accuracy and real-time performance of the detection algorithm. Most of the factors affecting the detection of the lane line are generated before the image is acquired. This requires the strict pre-processing of the collected lane line image to remove a large amount of interference. After the information, not only can the detection result be more accurate but also the complexity of the algorithm be simplified, making the detection result accurate and effective. (2) Use the FPGA for verification. This paper simulates the detection algorithm from two aspects of MATLAB and FPGA, learns the working mode of the related chip and different interface protocols, optimizes the logic design through the hardware design language, and facilitates the hardware implementation of the algorithm. This method can effectively improve the image processing speed, save the logic resources, and better realize the lane recognition function. (3) Improve the existing lane line detection algorithm. There are many algorithms for lane detection, but each algorithm has its own advantages and disadvantages. Part of this article summarizes the advantages and disadvantages of these detection algorithms, analyzes their feasibility in actual detection, and improves the algorithm based on this.

The social network has become the primary medium of rumor propagation. Moreover, manual identification of rumors is extremely time-consuming and laborious. It is crucial to identify rumors automatically. Machine learning technology is widely implemented in the identification and detection of misinformation on social networks. However, the traditional machine learning methods profoundly rely on feature engineering and domain knowledge, and the learning ability of temporal features is insufficient. Furthermore, the features used by the deep learning method based on natural language processing are heavily limited. Therefore, it is of great significance and practical value to study the rumor detection method independent of feature engineering and effectively aggregate heterogeneous features to adapt to the complex and variable social network. In this paper, a deep neural network- (DNN-) based feature aggregation modeling method is proposed, which makes full use of the knowledge of propagation pattern feature and text content feature of social network event without feature engineering and domain knowledge. The experimental results show that the feature aggregation model has achieved 94.4% of accuracy as the best performance in recent works.

This paper aims at examining the key factors for a movie to be influential. Instead of employing the widely tested variables such as box office, the paper quantifies the level of influence by the number of times a movie being referred by other movies. This model was initially proposed by Bioglio and Pensa (2018), and refined in the paper to offset the time impact. Meanwhile, a few factors are selected to verify their relationship with the influence of movies, including movie metadata, sentiments of movie reviews and sentiment fluctuation of movie descriptions. Especially, a Long Short-Term Memory (LSTM) network is built to perform sentiment analysis on movie reviews, and an ensemble model combining rule-based method and LSTM model is also raised. Both results of two models are compared in regression analysis and it is found that the combination method performs better in tree models and LSTM model works better for other regression models. In addition, a novel method of quantifying the level of sentiment fluctuation is as well proposed in the paper. Finally, it is indicated that a movie should probably aim at achieving a higher popularity in the market than a higher reputation among the audience to be influential.

Thermal analysis is exceptionally important for operation safety of axial permanent magnet couplings (APMCs). Combining a finite element method (FEM) with a lumped-parameter thermal network (LPTN) is an effective yet simple thermal analysis strategy for an APMC that is developed in this paper. Also, some assumptions and key considerations are firstly given before analysis. The loss, as well as the magnetic field distribution of the conductor sheet (CS) can be accurately calculated through FEM. Then, the loss treated as source node loss is introduced into the LPTN model to obtain the temperature results of APMCs, where adjusting conductivity of the CS is a necessary and significant link to complete an iterative calculation process. Compared with experiment results, this thermal analysis strategy has good consistency. In addition, a limiting and safe slip speed can be determined based on the demagnetization temperature permanent magnet (PM).

Large field-of-view (FOV) calibration is indispensable to ensure the accuracy of vision measurement systems for large aviation components. We propose an improved separated-parameter calibration method for large-FOV binocular vision measurements with a high flexibility and accuracy. Firstly, the camera parameters are separately calibrated according to the sub-area features of image. Subsequently, based on the spatial-calibration accuracy, a stereoscopic calibration object is devised. The mean error of the proposed method is experimentally obtained as 0.13 mm for a FOV of 2.0 m × 1.5 m. Its feasibility and effectiveness for the measurement in the field is validated by workshop calibration.

The photoelectric conversion efficiency of dye-sensitized solar cells is affected by the catalytic ability of counter electrode materials. Therefore, it is crucial to develop inexpensive and highly efficient counter electrode materials. In this article, we successfully prepared the Co3S4 with different morphologies (nanosheet and nanoflower). Scanning electron microscopy images display that the Co3S4 nanoflowers have a special spatial structure, which has more reactive sites than the Co3S4 nanosheets. The Co3S4 samples were used as counter electrodes (CEs) for dye-sensitized solar cells (DSSCs), and the photoelectric conversion efficiency of the DSSCs was tested. The DSSC assembled with the Co3S4 nanoflowers CE shows superior power conversion efficiency (PCE) of 7.09% than the Co3S4 nanosheets and Pt CEs under AM 1.5 G irradiation, which indicate that the Co3S4 nanoflowers performed outstanding catalytic actives.

We propose an optimal transport (OT) framework for generalized zero-shot learning (GZSL), seeking to distinguish samples for both seen and unseen classes, with the assist of auxiliary attributes. The discrepancy between features and attributes is minimized by solving an optimal transport problem. {Specifically, we build a conditional generative model to generate features from seen-class attributes, and establish an optimal transport between the distribution of the generated features and that of the real features.} The generative model and the optimal transport are optimized iteratively with an attribute-based regularizer, that further enhances the discriminative power of the generated features. A classifier is learned based on the features generated for both the seen and unseen classes. In addition to generalized zero-shot learning, our framework is also applicable to standard and transductive ZSL problems. Experiments show that our optimal transport-based method outperforms state-of-the-art methods on several benchmark datasets., To appear in WACV 2021

This paper aims to compare the damage characteristics of the waste engine oil bottom (WEOB) rejuvenated asphalt binder with aromatic extract oil rejuvenated asphalt binder in the non-linear range. To fulfil this objective, the aged asphalt binder was prepared by aging SBS modified asphalt binder in the laboratory. High temperature, fatigue and low-temperature damage characteristics in the non-linear range were evaluated by conducting multiple stress creep and recovery (MSCR) test, linear amplitude sweep (LAS) test and double edge notched tension (DENT) test, respectively. The microstructure of rejuvenated asphalt binders was characterized by environmental scanning electron microscope (ESEM). The results showed that although the performance of aged asphalt binder can be restored to some extent with two recycling agents, however after conditioning in the bath for 120 h, the two rejuvenated asphalt binders exhibited different ductile states. The microstructure of rejuvenated asphalt binders revealed that WEOB rejuvenated asphalt binder presented a more gelation transition than aromatic extract oil rejuvenated asphalt binder which could be considered as the main reason for the reduction in the ductile performance of WEOB rejuvenated asphalt binder.

The mesoporous pebble-like NiCo2O4 nanostructures were smoothly obtained via a simple hydrothermal route and the succeeding annealing treatment. Various techniques, including XRD, SEM, TEM, Raman spectra, FTIR, and MH curves have been used to study the obtained products. The obtained results exhibited that the morphology of spinel NiCo2O4 could be controlled by adjusting the content of cetyltrimethylammonium bromide (CTAB). The morphology of NiCo2O4 nanostructures transformed from a 300-nm popcorn-like to 30–40-nm pebble-like nanostructure by changing the content of CTAB. Compared with the popcorn-like NiCo2O4 nanostructures, the pebble-like samples showed effective blue shifting of Raman spectroscopy, which might be due to the nano-sized effect of NiCo2O4 particles. Finally, vibration sample magnetometer (VSM) measurements indicated the samples transformed from weak ferromagnetic (popcorn-like) to paramagnetic (pebble-like) due to small particle size.

Rainfall networks are the most direct sources of precipitation data and their optimization and evaluation are essential and important. Information entropy can not only represent the uncertainty of rainfall distribution but can also reflect the correlation and information transmission between rainfall stations. Using entropy this study performs optimization of rainfall networks that are of similar size located in two big cities in China, Shanghai (in Yangtze River basin) and Xi'an (in Yellow River basin), with respect to temporal variability analysis. Through an easy-to-implement greedy ranking algorithm based on the criterion called, Maximum Information Minimum Redundancy (MIMR), stations of the networks in the two areas (each area is further divided into two subareas) are ranked during sliding inter-annual series and under different meteorological conditions. It is found that observation series with different starting days affect the ranking, alluding to the temporal variability during network evaluation. We propose a dynamic network evaluation framework for considering temporal variability, which ranks stations under different starting days with a fixed time window (1-year, 2-year, and 5-year). Therefore, we can identify rainfall stations which are temporarily of importance or redundancy and provide some useful suggestions for decision makers. The proposed framework can serve as a supplement for the primary MIMR optimization approach. In addition, during different periods (wet season or dry season) the optimal network from MIMR exhibits differences in entropy values and the optimal network from wet season tended to produce higher entropy values. Differences in spatial distribution of the optimal networks suggest that optimizing the rainfall network for changing meteorological conditions may be more recommended.

Vehicle positioning has played an important role in intelligent transportation systems. Previous research has had difficulties in increasing the sensor aperture and reducing the computational complexity of the vehicle positioning algorithm. This paper proposes a new sensor model to extend the sensor aperture, which is similar to the nested sensor model combined with fourth-order cumulants. The proposed algorithm estimates the number of vehicles, which is much higher than the actual number of sensors. An ideal characteristic equation-based method is used to avoid the use of eigenvalue decomposition and spectrum peak search, thereby greatly reducing the computation complexity. In addition, the weighted coefficient matrix is introduced for optimization. Theoretical analysis and simulation results show that the proposed algorithm has lower computational complexity, avoids 2-D parameter matching, and has a high utilization of arrays while still ensuring accurate parameter estimation.

Optical and photonics techniques such as computer-generated holograms (CGHs) are suggested to be used in security applications. In this paper, we present an approach to generate an authenticable phase-only hologram (APOH) for steganographic optical image encryption with phase optimization. The phase hologram can be calculated by the proposed integrated two-stage optimization method where Fresnel domain optimized random phase (OARP) method and modified two-step iterative Fourier transform algorithm under phase constraints are involved. The computer-generated APOH can be respectively verified and decrypted with an authentication key (A-key) and a decryption key(D-key). Numerical and experiment results prove the validity and security of the proposed approach, which offers a new method of holographic encryption for optical images.

The development of antifouling biosensors capable of detecting biomarkers at low concentrations in complex bio-fluids with many interference components is of great importance in the diagnosis and treatment of diseases. Certain zwitterionic peptides composed of natural L-amino acids have been used for the construction of low fouling biosensors and demonstrated excellent antifouling performances, but they are prone to enzymatic degradation in biological media, such as serum that contains a variety of enzymes. In this work, a novel antifouling peptide with the sequence of cppPPEKEKEkek was designed, and three unnatural D-amino acids were set at both ends of the peptide to enhance its tolerance to enzymatic degradation. An electrochemical biosensor was constructed by coupling the antifouling peptide with a conducting polymer polyaniline (PANI) to achieve accurate detection of alpha-fetoprotein (AFP) in clinical samples. Owing to the presence of the designed peptide with partial D-amino acids (pD-peptide), the biosensing interface showed significantly high antifouling performance and enhanced stability in human serum. Meanwhile, the pD-peptide based biosensor exhibited high sensitivity toward the target AFP, with the linear range from 0.1 fg mL−1 to 1.0 ng mL−1 and the limit of detection of 0.03 fg mL−1 (S/N = 3). This strategy of enhancing the stability (tolerance to enzymolysis) of antifouling peptides in biological samples provided an effective way to develop antifouling biosensors for practical applications.

Nylon-6-b-polydimethylsiloxane copolymer was synthesized with macroinitiator through in situ polymerization. The macroinitiator with two chain-growing centers per molecule is based on hydroxyl term...

Graphene-loaded porous ZnCo 2 O 4 nanosheets composite (ZnCo 2 O 4 /RGO) had been synthesized by annealing the precursors, which were obtained after a simple hydrothermal method. Scanning electron microscope (SEM) and transmission electron microscopy (TEM) images revealed the microstructure of as-synthesized products. Raman spectroscopy confirmed the existence of RGO in the composite. ZnCo 2 O 4 /RGO composite exhibited great electrocatalytic property for reduction of I 3− , which showed enormous enhancements than that of pure ZnCo 2 O 4 and RGO. It can be ascribed to the synergetic effect between porous ZnCo 2 O 4 nanosheets and RGO films. As counter electrode (CE) for dye-sensitized solar cells (DSSCs), ZnCo 2 O 4 /RGO composite gained power conversion efficiency (PCE) of 6.73%, which was up to 88% of that for Pt CE (7.69%).

High-voltage pulse discharge (HVPD) technology has a broad prospect in concrete crushing. The model of concrete beam sections is established by ANSYS/LS-DYNA finite element software. The shock wave, caused by the electrohydraulic effect of HVPD with 50 kJ energy, is equivalent to an explosive blast shock load . The analysis of concrete beam sections throughout loading was carried out. The section size of each beam segment is width × height = 400 mm × 800 mm, and the lengths of beams are: 600 mm, 700 mm, 800 mm, 900 mm, 1000 mm and 1100 mm respectively. The influence of aperture and spacing of holes on the crushing effect of the concrete beam segment was investigated. Two holes were drilled vertically on the wide and length surface of the concrete beam section, and the corresponding drilling spacing for each length of beam section is 200 mm, 300 mm, 400 mm, 500 mm, 600 mm and 700 mm respectively. The depth of holes in each beam is 450 mm, and the diameters of holes are 30 mm, 50 mm and 70 mm respectively. The analysis results show that with the increase of the hole diameter and the decrease of the hole spacing, the crushing effect of the concrete beam section is gradually enhanced. Depending on the crushing effect of the beam section, the optimal layout scheme is determined that the hole diameter is 50 mm, the hole spacing is 400 mm and the hole end (edge) spacing is 250 mm. A scheme is proposed to set multiple rows of holes in the width direction for the beams which have a large size. And the maximum row spacing of holes is the same as the maximum spacing of holes. The models of beam segments with width of 900 mm, 1300 mm and 1700 mm are established to verify the rationality of the arrangement scheme. Of the beam, the section size is 800 mm × 900 mm, the hole diameter is 50 mm, the hole spacing is 400 mm, and the hole row spacing is 400 mm. The analysis results show that the concrete beam segment is effectively crushed under the multi-row hole layout scheme.

Interfacial defect and residual stress hinder the further enhancement of power conversion efficiency (PCE) and stability of perovskite solar cells (PSCs). Here, we report a multifunctional interface modification strategy where KPF6 molecule is employed to modify SnO2/perovskite interface. It is revealed that PF6− is still located at interface whereas most of K+ ions diffuse into perovskite layer. PF6− can chemically link SnO2 layer and perovskite layer via the hydrogen bond with perovskites and coordination bond with SnO2, resulting in improved interfacial contact. KPF6 interface modification leads to improved perovskite film quality, interfacial defect passivation, and interfacial stress release. As a result, the KPF6-modified device achieves an efficiency enhancement from 19.66% to 21.39% as compared to the control device. Meanwhile, moisture, thermal and light stability are ameliorated after interface modification. The unencapsulated KPF6-modified device maintains 80.1% of its initial PCE after aging for 960 h at 60 °C and 57.2% after aging for 960 h under one sun illumination, respectively. This work provides an idea for developing multifunctional interface molecules toward simultaneously enhancing efficiency and stability of PSCs.

A 1-μm thick N-polar gallium nitride (GaN) thin film has been grown on 2-inch vicinal sapphire substrate (c off 2° toward m plane) by metal organic chemical vapor deposition (MOCVD). The smooth surface without any inversion domains is demonstrated by the optical microscopy, atomic force microscopy, and scanning electron microscopy. The N-polar property is confirmed by potassium hydroxide etching and the atomic layout through high-resolution transmission electron microscopy (HRTEM). The good crystalline quality is verified by X-ray rocking curves and photoluminescence.

The new 3-D spongy NiCo2S4 nanospheres have been successfully fabricated by a temperate hydrothermal method assisted sulfuration procedure and were used as counter electrode (CE) for dye-sensitized solar cells (DSSCs). The electrochemical tests such as cyclic voltammetry, electrochemical impedance spectra analysis, and Tafel curve measurements, indicated that the NiCo2S4 nano-spheres electrode possesses high conductivity, low charge transfer resistance at the electrolyte–electrode interface, excellent electrocatalytic activity, and fast reaction kinetics for the I−/I3− redox reaction for DSSCs. Furthermore, the DSSC fabricated using the NiCo2S4 nanostructure CE exhibits an efficiency of 6.47% comparing the convention Pt with 6.33% as reference. The results indicated that the NiCo2S4 nanostructure CE can display an excellent efficiency comparable to the Pt CE. Consequently, it is promising to substitute Pt CE for the NiCo2S4 nanostructure in the future.

Binary metal oxides have been considered as promising anode materials, which exhibit much better performances than single metal oxides in view of their variable oxidation state and fairly high electrical conductivity. In this research, NiCo2O4 nanocrystals are prepared from a facile procedure including microemulsion-solvothermal reaction and subsequent calcination at 400 °C for 4 hours. The as-prepared NiCo2O4 nanocrystals are characterized by X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS). When applied as an anode for a lithium ion battery, it demonstrates excellent cycling and rate stability. The initial charge/discharge efficiency is as high as 75.41% at a current density of 100 mA g−1. After 45 cycles, the discharge capacity still retains up to 1175.9 mA h g−1, which is even much higher than that of the initial discharge capacity. Meanwhile, the reversible capacity remains over 644.9 mA h g−1 at a large current density of 1600 mA g−1, ascribed to the dispersed nanoparticles, which will help to improve the conductivity of the electrode material during the lithium-ion insertion/deintercalation process, shorten the ion diffusion path and reduce the charge transfer resistance (Rct).

In this work, novel MoS2/nitrogen-doped carbon shell–core microspheres (MNCS) have been designed and prepared through the microwave-assisted method, and used as counter electrodes for platinum-free dye-sensitized solar cells (DSSCs). The results show that as-prepared shell–core composite microspheres possess low charge transfer resistance and high electrocatalytic activity. When used as a counter electrode for DSSCs, the powder conversion efficiency of an as-prepared cell with optimized MNCS reaches 6.2% under standard light illumination, which is comparable to cells with a conventional Pt counter electrode.

Speckle noise can reduce the image quality of synthetic aperture radar (SAR) and complicate image interpretation. This study proposes a novel three-step approach based on the conventional probabilistic patch-based (PPB) algorithm to minimize the impact of bright structures on speckle suppression. The first step improves the calculation accuracy of the weight by pre-processing speckle noise with a linear minimum mean-square error filter and reassessing similarity between pixels. In the second step, an iterative method is developed to avoid interfering with bright structures and acquires a more accurate homogeneous factor by adaptively changing the size of the search window. In the final step, the spreading and blurring of bright structures is corrected using a modified bias-reduction technique. Experimental results demonstrate the proposed algorithm has improved performance for both speckle suppression and preservation of edges and textures, evaluated by indicators including the equivalent number of looks, the edge preservation index, the mean, and standard deviation of ratio images.

Owing to their promising applications in flexible electronics, researchers have extensively explored flexible and conductive gels. However, these gels have unsatisfactory strength and flexibility as well as easily dry in air. Herein, a rationally designed robust regenerated silk fibroin (RSF)-based gel with significant flexibility and strength, favorable conductivity, and excellent air stability is fabricated by inducing the conformation transition of RSF from random coil to β-sheet in ionic liquid (IL)/water mixtures. We found that such RSF-based gels have a unique homogeneous network structure of RSF nanofibers, which is likely formed because of evenly distributed cross-links dominated by small-sized β-sheet domains created during the conformation transition of RSF. Although the unique homogeneous nanostructure/network contributes toward improving the mechanical properties of these gels, it also provides pathways for ionic transport to help the gels preserve high conductivity of ILs. The prepared RSF-based gels display a remarkable air stability and reversible loss/absorption water capability in a wide humidity range environment primarily because of the distinguished combination of the IL and water. Therefore, the novel RSF-based gels hold a great potential in various applications as multifunctional, flexible, conductive materials, which are dispensed with encapsulation.

Dielectric elastomer (DE) is a type of electric field type electroactive polymer material that can produce greater deformation under the action of an electric field and has a faster recovery speed. It has the advantages of high energy density, large strain, low quality, and commercialization, and has become the most widely concerned and researched electroactive polymer material. In this study, copper calcium titanate (CCTO) particles with a large dielectric constant were selected as the filling phase, and a silicone rubber (PDMS) with better biocompatibility and lower elastic modulus was used as the matrix to prepare CCTO/PDMS, which is a new type of dielectric elastomer material. The structure of the dielectric elastomer is analyzed, and its mechanical properties, dielectric properties, and driving deformation are tested. Then, KH550, KH560, and KH570 modified CCTO is used in order to improve the dispersibility of CCTO in PDMS, and modified particles with the best dispersion effect are selected to prepare dielectric elastomer materials. In addition, mechanical properties, dielectric properties, and driving deformation are tested and compared with the dielectric elastomer material before modification. The results show that as the content of CCTO increases, the dielectric constant and elastic modulus of the dielectric elastomer also increase, and the dielectric loss remains basically unchanged at a frequency of 100 Hz. When the filling amount reaches 20 wt%, the dielectric constant of the CCTO/PDMS dielectric elastomer reaches 5.8 (100 Hz), an increase of 120%, while the dielectric loss at this time is only 0.0038 and the elastic modulus is only 0.54 MPa. When the filling amount is 5 wt%, the dielectric elastomer has the largest driving deformation amount, reaching 33.8%. Three silane coupling agents have been successfully grafted onto the surface of CCTO particles, and the KH560 modified CCTO has the best dispersibility in the PDMS matrix. Based on this, a modified CCTO/PDMS dielectric elastomer was prepared. The results show that the improvement of dispersibility improves the dielectric constant. Compared with the unmodified PDMS, when the filling content is 20 wt%, the dielectric constant reaches 6.5 (100 Hz). Compared with PDMS, it has increased by 150%. However, the improvement of dispersion has a greater increase in the elastic modulus, resulting in a decrease in its strain parameters compared with CCTO/PDMS dielectric elastomers, and the electromechanical conversion efficiency has not been significantly improved. When the filling amount of modified CCTO particles is 5 wt%, the dielectric elastomer has the largest driving deformation, reaching 27.4%.

A detailed geometric model for calculating the edge dislocation density through X-ray diffraction rocking curves is proposed in this study. Based on this model, we deduce a new formula to evaluate the edge dislocation density from the full-width at half-maximum values of skew symmetric rocking curves. The widely used formula proposed by Srikant et al. is an approximate result of this formula. The fitting results obtained by the two formulae coincide well from the measurement data of gallium nitride films grown on silicon substrate.

In this work, graphene/carbon nanotubes (CNTs)/activated carbon (AC) (GTAC) hybrids were designed and fabricated by combing graphene, CNTs with AC into one new type of hybrid and applied as capacitive deionization (CDI) electrodes. The morphology, structure and electrochemical performance of the GTAC were characterized by scanning electron microscopy, nitrogen adsorption–desorption, cyclic voltammetry and electrochemical impedance spectroscopy. The results show that the GTAC with 72 wt% CNTs, 8 wt% graphene and 20 wt% AC exhibits the best electrochemical performance among all the samples. When used as a CDI electrode, GTAC exhibits a higher electrosorption capacity of 2.30 mg g−1 than those of optimized graphene/AC (1.10 mg g−1), graphene/CNTs (1.06 mg g−1) and CNTs/AC (0.96 mg g−1) in this work. The higher electrosorption capacity of GTAC can be ascribed to the superiority of the “plane-to-line-to-point” (graphene-to-CNTs-to-AC) conducting network. This result demonstrates that GTAC should be a promising candidate as a CDI electrode.

The interface, optical and electrical properties of InGaN light emitting diodes (LEDs) with different H2 flow treatment during the barrier growth are investigated in this study. With H2 treatment, the interface between the quantum well and barrier becomes rougher and the photoluminescence intensity decreases. The external quantum efficiency of the LEDs with 600 sccm (2.7%) H2 treatment has the best performance among the samples. Both the forward and reverse leakage currents of the samples are reduced significantly when treated with H2. Among the samples, a H2 flow with 600 sccm (2.7%) gives the best performance.

Rainfall data are needed for water resource management and decision making and are obtained from rainfall networks. These data are especially important for streamflow simulations and forecasting the occurrence of intense rainfall during the flood season. Therefore, rainfall networks should be carefully designed and evaluated. Several methods are used for rainfall network design, and information theory-based methods have recently received significant attention. This study focuses on the design of a rainfall network, especially for streamflow simulation. A multi-objective design method is proposed and applied to the Wei River basin in China. We use the total correlation as an indicator of information redundancy and multivariate transinformation as an indicator of information transfer. Information redundancy refers to the overlap of information between rainfall stations, and information transfer refers to the rainfall-runoff relationship. The outlet streamflow station (Huaxian station in the Wei River basin) is used as the target station for the streamflow simulation. A non-dominated sorting genetic algorithm (NSGA‐II) was used for the multi-objective optimization of the rainfall network design. We compared the proposed multi-objective design with two other methods using an artificial neural network (ANN) model. The optimized rainfall network from the proposed method led to reasonable outlet streamflow forecasts with a balance between network efficiency and streamflow simulation. Our results indicate that the multi-objective strategy provides an effective design by which the rainfall network can consider the rainfall-runoff process and benefit streamflow prediction on a catchment scale.

The primary objective of this paper is to understand reversible aging properties of modified asphalt binders containing different percentages of coal liquefaction residue (CLR), which is a by-product of the coal liquefaction process. To fulfill this objective, regular performance grading test, extended bending beam rheometer test, and dynamic shear rheometer test were conducted to comprehensively evaluate the effect of CLR on base asphalt while reversible aging was also considered. The results showed that adding a certain percentage of CLR significantly increased the high-temperature performance grade of modified asphalt while the regular low-temperature performance grade kept constant. However, when the conditioning time prolonged, all the CLR modified asphalts in this study experienced severe hardening trend and the grade loss higher than 6 °C after 72 h conditioning time. From statistical analysis, it could be concluded that the grade loss had a significant change even just by adding 3% CLR in base asphalt binder. For all the CLR modified asphalt systems containing different percentages of CLR, significant differences in the grade loss between 24 and 72 h conditioning time occurred. However, no significant differences were observed when the conditioning time extended from 72 to 168 h.

Deep neural networks have demonstrated state-of-the-art performance in a variety of real-world applications. In order to obtain performance gains, these networks have grown larger and deeper, containing millions or even billions of parameters and over a thousand layers. The trade-off is that these large architectures require an enormous amount of memory, storage, and computation, thus limiting their usability. Inspired by the recent tensor ring factorization, we introduce Tensor Ring Networks (TR-Nets), which significantly compress both the fully connected layers and the convolutional layers of deep neural networks. Our results show that our TR-Nets approach {is able to compress LeNet-5 by $11\times$ without losing accuracy}, and can compress the state-of-the-art Wide ResNet by $243\times$ with only 2.3\% degradation in {Cifar10 image classification}. Overall, this compression scheme shows promise in scientific computing and deep learning, especially for emerging resource-constrained devices such as smartphones, wearables, and IoT devices., Comment: Accepted to CVPR 2018

In this paper, we propose a Tensor Train Neighborhood Preserving Embedding (TTNPE) to embed multi-dimensional tensor data into low dimensional tensor subspace. Novel approaches to solve the optimization problem in TTNPE are proposed. For this embedding, we evaluate novel trade-off gain among classification, computation, and dimensionality reduction (storage) for supervised learning. It is shown that compared to the state-of-the-arts tensor embedding methods, TTNPE achieves superior trade-off in classification, computation, and dimensionality reduction in MNIST handwritten digits and Weizmann face datasets., Accepted to IEEE Transactions on Signal Processing, Mar 2018

Polysaccharide films used as intelligent food packaging possess the advantages of renewability, safety and biodegradability. Printing on the polysaccharidic food packaging is challenging due to the high demand for edible-ink and the need for a suitable printing technique. In this work, we propose an electrochemical method for writing on polysaccharide film. Unlike conventional printing, this electrochemical writing process relies on the pH responsive color change of anthocyanin embedded in the chitosan/agarose hydrogel. By biasing a negative potential to a stainless wire (used as a pen) contacting the surface of the chitosan/agarose/ATH hydrogel, the locally generated pH change induced the color change of ATH and wrote programmed information on the hydrogel. We demonstrate the writing can be temporary in the hydrogel but stable when the hydrogel is dried. We further demonstrate that the written film is applicable for the detection of the spoilage of crucian fish. The reported electrochemical writing process provides a novel method for printing information on polysaccharide film and great potential for intelligent food packaging.