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Multifunctional nanoparticles were simply synthesized by mixing a TICT+AIE featured molecule (TPAPP-CHO) with PBS solution. The fluorescent (FL) dots entered the cells via energy-related endocytosis and were located in lysosome emitting green FL. This indicated that the nanoparticles were dissociated in the lysosome. Moreover, the synthesized nanoparticles (NPs) demonstrate potent cytotoxicity against human U87 glioblastoma cells by inducing cell apoptosis via triggering intracellular ROS overproduction.

In this paper, we propose a general purpose, simple and fast fusion algorithm based on guided image filter. The proposed method can well combine useful source image information into the fused image supported by multi-scale image decomposition, structure transferring property, visual saliency detection, and weight map construction. Multi-scale image decomposition is appropriate to represent and manipulate image features at various scales. Structure transferring property enabled by our algorithm can induce structures of one source image into the other. A new visual saliency detection based on guided image filter introduced in this paper is able to extract significant regions from visually different images of the same scene. The choice of weight maps helped to integrate the complementary information pixel by pixel at each scale. Experimental outcomes of the proposed method are compared and analyzed with traditional and recent guided image filter-based fusion algorithms in terms of visual quality, fusion metrics and run time. In addition, to enhance fusion results further we made an effort to find a suitable image and video enhancement algorithm. The fusion performance analysis clearly indicates that the proposed method is very promising along with less run time.

In this paper, an extensive survey on PLD methods for low-altitude aircraft safety based on image processing is presented. First, primary features of power lines are introduced. Then, main studies on PLD are summarized, including PLD approaches based on tradition image processing methods and machine learning. Besides, a few latest research works, such as PLD based on deep learning and infrared images, are discussed. By discussing and comparing current methods, we have proposed future development directions of PLD, with the aim of providing a starting point for researchers in PLD. Specifically, image fusion and multimodal sensor fusion should be able to provide better detection performance and lower false alarm rate by exploiting complementary information from different sensors. In addition, AI will be an important technique in PLD, with the help of transfer learning to utilize limited training data and of multimodal learning to deal with different kinds of information.

This paper describes a facile one-pot protocol to synthesize 2-aminophenol derivatives via a palladium-catalyzed C–H acetoxylation strategy with 5-nitropyrimidine as a directing group (DG), which can be easily preinstalled and readily removed under mild condition after the coupling. In addition, the transformation is operationally simple, has high functional group tolerance, and is amenable to gram-scale. Moreover, several examples were shown that introduction/removal of 5-nitropyrimidine and the C–H oxylation sequence could be integrated in one pot.

Traditional vibration sensor of ship machinery using cable for power supply cannot meet the requirements of a large number of distributed sensors of the intelligent ship. A bouncing-ball based triboelectric nanogenerator (BB-TENG) to be used as a self-powered vibration frequency monitoring sensor is proposed. In the sensing test, the vibration frequency of 15 ∼ 50 Hz under different amplitudes can be measured accurately. The frequency calculation of the voltage signal can accurately reflect external vibration frequency, while the change of short-circuit current has linear relationship with the frequency, and the correlation coefficient is about 0.99. In addition, electrical signal test results and photos taken by high-speed cameras show that the limit of the available detection frequency of BB-TENG increases with the increase of amplitude and support height. The electrical output of BB-TENG under different working conditions are tested, which provides the basis for selecting suitable BB-TENG according to different vibration characteristics.

With the development of intelligent ship, types of advanced sensors are in great demand for monitoring the work conditions of ship machinery. In the present work, a self-powered and highly accurate vibration sensor based on bouncing-ball triboelectric nanogenerator (BB-TENG) is proposed and investigated. The BB-TENG sensor consists of two copper electrode layers and one 3D-printed frame filled with polytetrafluoroethylene (PTFE) balls. When the sensor is installed on a vibration exciter, the PTFE balls will continuously bounce between the two electrodes, generating a periodically fluctuating electrical signals whose frequency can be easily measured through fast Fourier transform. Experiments have demonstrated that the BB-TENG sensor has a high signal-to-noise ratio of 34.5 dB with mean error less than 0.05% at the vibration frequency of 10 Hz to 50 Hz which covers the most vibration range of the machinery on ship. In addition, the BB-TENG can power 30 LEDs and a temperature sensor by converting vibration energy into electricity. Therefore, the BB-TENG sensor can be utilized as a self-powered and highly accurate vibration sensor for condition monitoring of intelligent ship machinery.

Gestalt psychology indicates that simplicity is central to image vectorization, i.e., observers tend to perceive jagged raster edges as piecewise smooth curves and color changes as being either gradual (along edges) or abrupt (across edges). In this paper, we give a pair of simplicity-driven formulations to respectively cope with the two challenges. In detail, we formulate the underlying as-rigid-as-possible edges as the axes of symmetry of the edge saliency map, while reconstructing the color field by enforcing the fidelity and the smoothness at the same time (except on the detected boundaries). We finally convert a rasterized image into gradient-aware vector graphics whose base domain is a high-quality triangle mesh. On the one hand, the rigidity of the boundary curves is naturally achieved based on the assumption of simplicity, instead of by an empirically-grounded curve fitting operation; on the other hand, the color of near-boundary regions is inferred by Hessian energy (an extrapolation-like technique). Our vectorization method is able to yield more visually realistic results than existing approaches and is useful in flexible recoloring, shape editing, and hierarchical level-of-detail (HLOD) image representation.

Hadoop Distributed File System (short for HDFS) is a high availability file system designed to run on commodity hardware. It uses multiple replicas to ensure high reliability, and many data are transmitted between storage nodes. The performance of data transmission has a great impact on the latency of writing operations. Remote Direct Memory Access (short for RDMA) is a protocol with low latency and high through which is running on the Infiniband network. When HDFS runs on the Infiniband network, the default protocol IPoIB can not take advantage of the high-speed network. The latency of the writing process is similar to a TCP/IP network. In this paper, we present a new RDMA-based HDFS writing mechanism. It enables DataNodes to read data parallelly from the Client through RDMA. And by using RDMA primitive, the transmission latency is slower than the original TCP/IP protocol. The experiments show that our approach reduces the latency of the writing process by 10.11%–40.81% compared with the original HDFS.

Recently, computer vision and deep learning technology has been applied in various gait rehabilitation researches. Considering the long short-term memory (LSTM) network has been proved an excellent performance in learn sequence feature representations, we proposed a lower limb joint trajectory prediction method based on LSTM for conducting active rehabilitation on a rehabilitation robotic system. Our approach based on synergy theory exploits that the follow-up lower limb joint trajectory, i.e. limb intention, could be generated by joint angles of the previous swing process of upper limb which were acquired from Kinect platform, an advanced computer vision platform for motion tracking. A customize Kinect-Treadmill data acquisition platform was built for this study. With this platform, data acquisition on ten healthy subjects is processed in four different walking speeds to acquire the joint angles calculated by Kinect visual signals of upper and lower limb swing. Then, the angles of hip and knee in one side which were presented as lower limb intentions are predicted by the fore angles of the elbow and shoulder on the opposite side via a trained LSTM model. The results indicate that the trained LSTM model has a better estimation of predicting the lower limb intentions, and the feasibility of Kinect visual signals has been validated as well.

Silicon nanocomposites with surface coating have been promising candidates for high-performance anodes in Li-ion batteries. Here we report a simple yet effective way to synthesize Si@SiO2 nanocomposites with amorphous SiO2 coating through a fluoride ion-mediated continuous etching–redeposition process. The Si@SiO2 nanocomposite anode exhibits significantly improved lithium storage properties, with a reversible capacity of 1356 mA h g−1 at 2.1 A g−1 for 300 cycles.

Foot-and-mouth disease (FMD) is an infectious and sometimes fatal viral disease that affects cloven-hoofed animals, and Chinese government adopts compulsory immunization measures for FMD. The adverse effects of FMD vaccine to pigs, cattle and goats have been reported increasingly frequent during the spring and autumn seasons when large numbers of farm livestock are vaccinated. The financial losses caused by vaccine adverse effects have been a serious concern for both farmers and primary prevention personnel. There are various causative factors reported to involve into adverse effect of FMD vaccine, including the inappropriate vaccine production, transportation and storage, livestock poor tolerance, and unqualified vaccinating manipulations. Symptomatic treatment and early drug prevention have a certain effect on the adverse effects. To analyze causes and propose countermeasures, in the current study possible reasons during the production and processing procedures of inactivated FMD vaccine were reviewed and corresponding countermeasures were recommended. The review may provide references for better use of vaccine to prevent FMD.

The addition of Sc and Zr into an Al–Mg–Mn alloy produced by selective laser melting exhibited exceptional properties. Multiple factors eventually lead to the improvement of properties, such as densification behaviors, grain characteristics, texture and the precipitated phases. We firstly investigate evolution of the melt pool characteristics which are varied under different processing parameters and lead to different solidified microstructures, densification behaviors and corresponding mechanical properties. Meanwhile, the characteristics of melt pool can be predicted through the normalized enthalpy of input energy, which presents more credible relationship with the melt pool dimensions. To this end, the relative density is up to 99.88% when the volume energy density and normalized enthalpy are combined used. Recrystallisation inhabitations induced by the added Sc and Zr is supposed after comparing the grain sizes under different conditions. Regrettably, the relationship between melt pool characteristics and the equiaxed/columnar ratio can not be described accurately, which due to the pseudo-equiaxed regions in XZ/YZ sections through regulating the melt track orientations via 67° scanning rotation. There are dispersed Al6Mn and Al3(Sc, Zr) particles exist in as-fabricated samples result in better mechanical properties and the subsequent aging treatment can further improve the comprehensive mechanical properties. Finally, the ultimate tensile strength and ductility is separately about 494.32 ± 4.16 MPa and 15 ± 1.27% after aging for 4 h at 325 °C. In contrast, the processing parameters have little impact on mechanical properties, especially for the yield strength, mainly owing to the homologous precipitate phase and grain sizes when the relative density is similar. The connection involving the whole periods from solidification to the final mechanical properties is discussed that may offer feasible ideas for alloy design and corresponding parameter optimization.

The addition of Sc and Zr endows selective laser melted Al–Mg-based alloys with exceptional properties, which are predominately related to the Al3(ScxZr1-x) precipitates. The Al3(ScxZr1-x) precipitates formed in different stage of processing are identified as primary- Al3(ScxZr1-x) and aged- Al3(ScxZr1-x) according to different crystallographic characteristics. The experimental results show most of primary Al3(ScxZr1-x) particles located in the grain boundaries with incoherent interface and irregular shape, which is seldom reported in conventional casting. In contrast, the subsequent aging brings out more spherical Al3(ScxZr1-x) with coherent interface emerged in the grains. Combined the first-principle calculations with pseudo binary-diagram, we search the possible structures of Al3(ScxZr1-x) based on their formation enthalpy and binding energy, whose space group should be altered as Sc enters the Al3Zr (DO23) dispersoids. The most possible structure of primary Al3(ScxZr1-x) phase is evaluated as Al12Sc3Zr, and the calculated crystallo-graphic parameters are consistent with the experimental results. As the primary Al3(ScxZr1-x) is hard to act as nucleation particle, it can be inferred that the grain refinement resulting from the modification and hindrance of these particles during grain growth. A corresponding ultimate tensile strength and ductility is separately about 521.26 ± 12.30 MPa and 15.83 ± 0.94% after aging at 325 °C for 4 h. The results demonstrate the difference between the primary Al3(ScxZr1-x) and the aged Al3(ScxZr1-x) as well as the formation of primary Al3(ScxZr1-x), which offer a new idea to design new alloy for additive manufacturing.

Maraging steel is a promising material for additive manufacturing due to its ultrahigh yield strength, reasonable ductility and good weldability. However, the ductility of the fabricated part will be degraded after aging treatment. In this regard, we firstly designed a new composition of maraging steel Fe-18.3Ni-9Co-4.84Mo-0.92Ti-0.27Al-0.13Cr-0.01C (wt.%), whose strength and ductility can be simultaneously improved by selective laser melting. The relationship between laser process parameters and forming defects has been studied. Using single-track and single-layer experiments, fully dense parts were fabricated with a certain range of process parameters, corresponding to the 30–50% lap rate in the X–Y plane and 70% remelted rate along Z-axis. Besides, we found film-like reverted austenite along the martensite lath boundaries in the as-fabricated part. The effects of heat treatment processes on the reverted austenite and mechanical properties of the fabricated parts were also studied; the strength-ductility trade-off of maraging steel after heat treatment can be alleviated. The tensile strength and elongation of printed samples after direct aging treatment can respectively reach 2037 MPa and 6.4%, and 2182 MPa, 4.8% after solution and aging treatment.

The solution of atmospheric chemical kinetics is considered as the dominant computationally intensive task in chemical transport models. Reported strategies for improving computational efficiency have not changed the essence of solving ordinary differential equations. In this study, we emulate a typical gas-phase chemistry solver implemented in chemical transport models in Chinese Mainland using a 28-layer residual regression neural network. Validation results have a total R2 of 0.985 with the original numerical solution for 194 species during a single timestep. Multiple-timestep test for one month verified the accuracy and stability of our model while no exponential accumulated bias was observed, though a slow accumulation of biases existed. There were 102 species with R2 values higher than 0.90 and 137 species with daily NMB values below 30% among the 194 species throughout the month. Meanwhile, the computational efficiency of gas-phase chemistry using the deep learning emulator was promoted by 10.6 times on one CPU and 85.2 times on one GPU. Our study confirms the feasibility of emulating an atmospheric chemical kinetic solver with data-driven models through deep learning and represents a step towards a deep learning solver being used in a chemical transport model. The deep learning emulator is expected to not only accelerate atmospheric chemical kinetic solutions by orders of magnitude but also provide a promising pathway for implementing near-explicit rather than lumped chemical mechanisms in chemical transport models.

Lithium-rich layered compound cathode materials recently attract ever-growing attention in lithium ion batteries for electric vehicles and energy storage devices due to their high discharge capacities of over 250 mAh g −1 and low cost. However, they still suffer from capacity fade, voltage decay and poor rate capability and thermal stability. In this paper, the Al&F co-doped Li 1.2 Ni 0.13 Co 0.13- x Mn 0.54 Al x O 2(1- y ) F 2 y cathode material has been successfully prepared via a co-precipitation reaction and a subsequent solid phase calcination. The resulting material combines the advantages of both Al-doping and F-doping, which can effectively mitigate the intrinsic layered-to-spinel phase transformation, and as a consequence, inhibits the capacity fade and voltage decay: delivering a discharge capacity of 217 mAh g −1 with retention of 88.21% and an average discharge voltage decay of 0.4019 V upon 150 cycling at 0.5 C. On the other side, with an increased electronic and ionic conductivity, this co-doping practice enhances the rate capability by a considerable extent that it delivers a discharge capacity of 157 mAh g −1 at 10 C, thus facilitating its application for quick charging devices. In addition, the thermal stability related with battery safety is significantly meliorated. Specifically, the co-doped cathode material exhibits an initial exothermal peak at a higher temperature of 273 °C and a much less overall heat generation of 221 J g −1 compared to the 210 °C and 755 J g −1 for the pristine one. In conclusion, the anion/cation co-substitution strategy has been demonstrated to be of great promise for the improvement of lithium-rich layered cathode materials.

Nowadays the Unmanned Aerial Vehicle (UAV) has been widely used due to its low-cost and unique flexibility. Specifically, the high-altitude operational capability makes it the ideal tool in military and civilian surveillance system, in which object tracking based on computer vision is the core ingredient. In this paper, we presented a survey on object tracking methods in aerial surveillance. After briefly reviewing the development history and current research institutions, we summarized frequently used sensors in aerial platform. Then we focused on UAV-based tracking methods by providing detailed descriptions of its common framework (ego motion compensation, object detection, object tracking) and representative tracking algorithms. Through discussing the requirement of a good tracking system and deficiency of current technologies, future directions for aerial surveillance were proposed.

Ensemble models have been extensively applied to credit scoring. However, advanced tree-based classifiers have been seldom utilized as components of ensemble models. Moreover, few studies have considered dynamic ensemble selection. To fill the research gap, this paper aims to develop a novel tree-based overfitting-cautious heterogeneous ensemble model (i.e., OCHE) for credit scoring which departs from existing literature on base models and ensemble selection strategy. Regarding base models, tree-based techniques are employed to acquire a balance between predictive accuracy and computational cost. In terms of ensemble selection, the proposed method can assign weights to base models dynamically according to the overfitting measure. Validated on five public datasets, the proposed approach is compared with several popular benchmark models and selection strategies on predictive accuracy and computational cost measures. For predictive accuracy, the proposed approach outperforms the benchmark models significantly in most cases based on the non-parametric significance test. It also performs marginally better than several state-of-the-art studies. Our proposal remains robust in several scenarios. In terms of computational cost, the proposed method provides acceptable performance and benefits from GPU acceleration considerably.

Computing geodesic distances on polyhedral surfaces is an important task in digital geometry processing. Speed and accuracy are two commonly-used measurements of evaluating a discrete geodesic algorithm. In applications, such as parametrization and shape analysis, a smooth distance field is often preferred over the exact, non-smooth geodesic distance field. We use the term Quasi-geodesic Distance Field (QGDF) to denote a smooth scalar field that is as close as possible to an exact geodesic distance field. In this paper, we formulate the problem of computing QGDF into a standard quadratic programming (QP) problem which maintains a trade-off between accuracy and smoothness. The proposed QP formulation is also flexible in that it can be naturally extended to point clouds and tetrahedral meshes, and support various user-specified constraints. We demonstrate the effectiveness of QGDF in defect-tolerant distances and symmetry-constrained distances. The authors would like to thank the anonymous reviewers for their valuable comments and suggestions. This work is supported by National Natural Science Foundation of China (61772016, 61772312), the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (U1909210), the Dalian University of Technology 2019 Discipline Platform Fund (1000-82212201), the National Young Talents Program of China, and the Strategic Priority Research Program of Chinese Academy of Science (XDA21010205).

Silicon nanocomposites with surface coating have been promising candidates for high-performance anodes in Li-ion batteries. Here we report a simple yet effective way to synthesize Si@SiO2 nanocomposites with amorphous SiO2 coating through a fluoride ion-mediated continuous etching-redeposition process. The Si@SiO2 nanocomposite anode exhibits significantly improved lithium storage properties, with a reversible capacity of 1356 mA h g-1 at 2.1 A g-1 for 300 cycles.

A method for smoke detection in video is proposed. The camera monitoring the scene is assumed to be stationary. With the atmospheric scattering model, dissipation function is reflected the transmissivity between the background objects in the scene and the camera. Dark channel prior and fast bilateral filter are used for estimating dissipation function which is only the function of the depth of field. Based on dissipation function, visual background extractor (ViBe) can be used for detecting smoke as a result of smoke’s motion characteristics as well as detecting other moving targets. Later on, various characteristics of smoke are extracted. Color feature and high-frequency energy based on wavelet transformation is selected to constitute the final recognition vectors, and Support vector machine (SVM) is used as a classification model. The final experimental results show that the accuracy rate of this method for smoke detection can reach 90.1%.

Precise monitoring of human respiration is crucial to the diagnosis of a wide range of respiratory and cardiovascular disorders and (thus) is of great interest to both clinicians and researchers. Existing measurements may include electrocardiography (ECG), nasal cannula and respiratory plethysmography. However, low comfort levels and signal shifts which are often observed in these techniques pose limitations for long-term, accurate monitoring of human respiration. In this paper, we develop a convenient respiratory signal acquisition method based on angular velocity derived from suprasternal notch. Research has found that waveforms collected from the suprasternal notch display higher robustness, as well as less gender variability. We use the median filter method and intersection detection technique to extract the respiratory waveform, respiratory frequency and respiratory phase parameters. And validated the respiratory signals derived from suprasternal angular velocity in both males and females. The extracted parameters are validated against a carbon dioxide concentration acquisition device, which serves as our golden reference platform. The results demonstrate the potential of suprasternal-derived angular velocity as a simple, low-cost and unobtrusive method for monitoring human respiration.

By improving the long-term correlation tracking (LCT) algorithm, an effective object tracking method, improved LCT (ILCT), is proposed to address the issue of occlusion. If the object is judged being occluded by the designed criterion, which is based on the characteristic of response value curve, an added re-detector will perform re-detection, and the tracker is ordered to stop. Besides, a filtering and adoption strategy of re-detection results is given to choose the most reliable one for the re-initialization of the tracker. Extensive experiments are carried out under the conditions of occlusion, and the results demonstrate that ILCT outperforms some state-of-the-art methods in terms of accuracy and robustness.

This study discussed the harmony of Chinese Basketball Association (CBA). We found that inharmonious factors include the audiences violence, athletes violence, referees’ qualification and black whistle. Based on these studies we proposed several strategies for creating harmonious competition: the Basketball Management Center has to establish necessary management and legal systems; the clubs have to improve the stadium security and the course condition; the audience and fans must set up correct attitude and improve their ball ethics; the athletes, coaches and referees need to strengthen their own occupation morality. Keywords—CBA, harmony, stadium violence

This study used literature survey and questionnaire methods to investigate the age structure, research ability, professional standards, education levels and other aspects of physical education teachers in Hubei Vocational Colleges. The results indicated that the age structure of the faculty in higher vocational colleges in Hubei province is reasonable, but there are still some problems, such as a serious imbalance in the ratio of teachers and students, lower degree of full-time teachers, and lack of scientific research ability. In order to solove these problems, this study came up with several suggestions and strategies to improve the qualification of physical education teachers in vocational colleges. Keywords—Hubei, Higher vocational colleges and universities, physical education teachers, strategy

In basetball teaching and training, many teachers/coaches often overlook the vision practice of students or players. The limited vision affects the technical and stratigical level of the whole team. In this study, I conducted systematical and scientific analyses on the character of basketball players’ vision, the effecting factors of vision, and raised some suggestions for training. Keywords—vision, characters of vision, effecting factors, training suggestions