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The generation of runaway electrons (REs) is observed during the low-density helium ohmic plasma discharge in the Experimental Advanced Superconducting Tokamak (EAST). The growth rate of hard x-ray (HXR) is inversely proportional to the line-average density. Besides, the RE generation in helium plasma is higher than deuterium plasma at the same density, which is obtained by comparing the growth rate of HXR with the same discharge conditions. The potential reason is the higher electron temperature of helium plasma in the same current and electron density plateau. Furthermore, two Alfvén eigenmodes driven by REs have been observed. The frequency evolution of the mode is not fully satisfied with the Alfvén scaling and when extension of the Alfvén frequency is towards 0, the high frequency branch is ~50 kHz. The different spatial position of the two modes and the evolution of the helium concentration could be used to understand deviation between theoretical and experimental observation.

The plasma-beta effect on the n = 1 resonant magnetic perturbation (RMP) field penetration in purely radio-frequency (RF) wave heated discharges has been investigated in EAST. The experimental results show that the dependence of the threshold RMP coil current for field penetration, I RMP,th , on the total absorbed power P tot scales as approximately I RMP,th ∝ P tot 0.30 , indicating that the error-field tolerance is improved with increasing RF power. This is benefited by the increased electron perpendicular flow dominated by a counter-current electron diamagnetic flow with increasing RF power. However, theoretical scaling in cylindrical geometry overestimates the power index. Assuming an additional term β N α β N for the normalized beta in the scaling, it is shown that the fitted α β N from the experimental observation is around −1, indicating a degradation effect of plasma beta. To clarify the underlying physics of the plasma-beta effect that was not included in the theoretical scaling in cylindrical geometry, the MARS-Q code with full toroidal geometry is employed for simulation of nonlinear field penetration (Liu et al 2013 Phys. Plasmas 20 042503). The MARS-Q simulation results reproduce the β N dependence well, and hence the P tot scaling of the threshold current in experimental observations. The main reason for this is that the net total torque, which is mainly contributed by the neoclassical toroidal viscosity (NTV), increases with increasing plasma β N . The results demonstrate that the nonlinear toroidal coupling effect via NTV torque plays an important role in determining field penetration, even in cases with relatively low β N ∈ [ 0.3 , 0.6 ] , which is far less than the no-wall beta limit.

The accurate prediction of remaining useful life is a significant issue for ensuring the reliable operation of the system. Considering the dynamic transfer of degenerate state can improve the prediction accuracy and reduce the number of late prediction. Firstly, a time series density peak clustering algorithm suitable for real-time manifold data clustering is proposed. By choosing larger truncation distance at points with high sample density, the cluster centers can be found more accurately. Then, different degradation state patterns according to clustering results can be divided. Moreover, the smoothing parameters can be adaptively updated according to the sample density under different degradation modes and an adaptive kernel density remaining useful life estimation model is established. The test of the gearbox verifies the necessity and accuracy of the proposed model by comparison with the remaining useful life predictions of kernel density estimation without considering degraded state transitions.

MXene based materials have a high performance in electromagnetic interference shielding. However, designing a MXene-based electromagnetic interference shielding material with broad-band, lightweight, thin thickness properties is still a challenge. In this work, we successfully fabricated patterned MXene films and MXene/silver nanowires films using laser ablation technique, which could effectively boost the shielding efficiency of materials in X-band without adding the thickness and with less weight. As shown in the results, the shielding efficiency of the patterned MXene films increased with the pattern depth, up to 37.7 dB, which is 10% larger than that of un-patterned MXene film. The silver nanowires doped patterned films had the same trend, with a maximum shielding efficiency of 38.4 dB. We attribute this effect to the small interfaces brought by engraving pattern, which can make a growing number of reflections of electromagnetic waves in the material, reduce surface reflection, and enhance the shielding efficiency of MXene. Meanwhile, we verified the enhancement mechanism by simulation. This work provides a feasible strategy to boost electromagnetic shielding efficiency without increasing the thickness and weight of material, which may have a potential application prospect.

In this study, a terahertz (THz) composite slab (TCS) based on metal grating and dielectric films is experimentally and numerically investigated in the THz region. By combining a dielectric film, the TCS exhibits different sharp resonances for varied polarization waves. A sharp Fano resonance is excited for transverse magnetic (TM) waves, which originates from the introduced asymmetric factor by dielectric films. The film thickness and refractive index can be used for the Fano resonance tuning. The resonant Q-factor can be improved using thinner and lower refractive index films. For transverse electric (TE) modes, a resonance termed guided modes can also be induced when the dielectric film is thick enough. The effects of film thickness and refractive index on these resonances are analyzed in detail. These results demonstrated that this TCS with high Q-factors or narrow resonances for both TM and TE waves is a promising component for THz filter and sensor applications.

Remaining useful life (RUL) prediction plays an important role in improving the availability and productivity of systems. To improve the accuracy of real-time RUL prediction during system operation, we propose a modeling method for real-time RUL prediction based on adaptive kernel window width density. First, a non-parametric kernel density estimation (KDE) real-time RUL prediction model is proposed, and a window width model with adaptive kernel window width density is established by introducing a local density factor in the window width selection. The local density of sample points is calculated by the k-nearest neighbor distance, and the KDE is performed by adaptively selecting the window width value according to the local density of sample points in the region of non-uniform distribution of sample points. As the monitoring data changes in real time, the kernel density estimates of known samples are used to recursively update the kernel density estimates of new samples. Moreover, the logarithmic transformation of random variables and space mapping are used in the establishment of the RUL prediction model. A model of logarithmic kernel diffeomorphism transformation is established to solve the boundary shift problem of kernel estimation in the prediction to improve the prediction accuracy. Finally, the validity of the method is verified through case studies, and the accuracy of the model is judged using evaluation quasi-measures.

The use of multi-sensor information fusion techniques is essential for condition monitoring and prediction in large complex systems. In this paper, a new distributed model fusion method is proposed to predict the remaining useful life (RUL) of a nonlinear Wiener process. First, the state–space model of the nonlinear Wiener process is established, based on multi-sensor monitoring, and the distributed Kalman filtering algorithm is used to filter and fuse the measurement data received from multiple sensors. Next, the parameters and degradation states of the state–space model are estimated and updated online in real time using the expectation maximum and smoothing filter algorithms. Moreover, the distribution of the system’s RUL is obtained according to the estimated state–space model considering the random failure threshold factor. Finally, numerical experiments are conducted to elucidate the accuracy of the adopted distributed fusion method, and the adaptability and effectiveness of the proposed method are verified using the FD001 data of the C-MPASS dataset as an example.

Enterprises to carry out effective cost management, can increase revenue, reduce expenditure for enterprises and improve the competitiveness of enterprises in the market. This paper first explains the problems existing in enterprise cost management and supervision mechanism and the overview of enterprise cost control and big data system. At the same time, it discusses how Chinese enterprises should do a good job in cost management in the era of big data for readers’ reference.

Self-positioning system is the key link of humanoid soccer robot, in which the robot needs to estimate its position and direction in the football field based on non-probing sensors. However, the modeling error of the robot system and the deviation of information acquisition bring the uncertain noise to the self-positioning system, which makes it difficult to carry out effective real-time positioning by using the traditional methods such as geometric measurement and track prediction. Existing filtering methods such as Kalman Filter and Monte Carlo Filter estimate the position and direction of the robot through observations, reducing the influence of uncertain factors. Although the accuracy of positioning is improved, the state estimation method relies on the accuracy of observations. The deviation in blurred image processing and camera ranging during the motion of the robot results in the deviation of the observations, which is more obvious in the case of multi-target observations. In this paper, a self-positioning method based on robust EKF using confidence is proposed to improve the accuracy of the robot’s self-positioning by integrating observations.

Utilizing renewable resources and accelerating thermal stabilization have been two main effective technical means to reduce the cost of poly(acrylonitrile) (PAN) based carbon fibre (CF). In this work, cross-linked poplar lignin (CPPL) with higher carbon content and 15 times the weight-average molecular weight of poplar lignin (PPL) was formed by doping boron phosphate (BP) in situ composites, which was blended with poly(acrylonitrile-co-vinyl acetate) (PANVA) to prepare a low-cost partially bio-based composite PANVA/CPPL-BP. During thermal stabilization, the C1s curve-fitting of x-ray photoelectron spectroscopy (XPS) spectra showed that the conjugated ladder structure of PANVA/CPPL-BP started to form at 230 °C, which was 20 °C lower than PANVA. And the acceleration in forming conjugated ladder structures was further confirmed by Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), thermogravimetric (TG), and TG-FTIR. During simulated low-temperature carbonization for composites stabilized at 230 °C in advance, the addition of CPPL-BP greatly improved the order of graphitic structure for PANVA. The mechanical property of CF mats has also been obviously improved by CPPL-BP. The possible mechanism that CPPL-BP accelerating the formation of conjugated ladder structures for PANVA/CPPL-BP during thermal stabilization was proposed. With such improvement on accelerating thermal stabilization and utilizing cheap bio-material at the same time, this PANVA/CPPL-BP composite has a great potential in developing low-cost CF.

One-step sputtering with elevated substrate temperature was used to fabricate Cu(In,Ga)Se2 (CIGSe) and Cu(In,Ga)S2 (CIGS) films. We investigated the influence of this approach on the structure and electrical properties of CIGSe and CIGS films. Compact films with large grain size were achieved at relatively low substrate temperatures below 400 °C without post-treatments. The films obtained from CIGSe targets showed larger grain and higher crystallinity compared to that prepared from CIGS targets. It was found that the substrate temperature over 400 °C brought some undesirable effects on the film quality, such as voids and secondary phases. The loss of Ga and In during the fabrication process was detected, resulting in the formation of Cu-rich films with low carrier density. HBr solution etching reduced the Cu/(In + Ga) ratio of the sputtered films, leading to the improvement of the performance of the CIGSe solar cells along with the enhancement of carrier density.

Small-scale evolution antennas have the advantages of high gain, wide bandwidth and small size, and have broad application prospects in the aerospace field. Aiming at the complex high-dimensional and dynamic problems of aerial antenna modeling, a dynamic hill-climbing algorithm based on orthogonal design is designed and implemented to simulate and optimize the single-span antenna in high-frequency operation mode. In the optimization problem, this paper defines a new individual comparison mechanism, which can reflect the number of violations of constraints and the degree of violation of each constraint, making the comparison of individuals more reasonable. The antenna simulation results demonstrate the effectiveness and feasibility of using dynamic evolutionary algorithms for antenna design.

The traditional face recognition technology is more complicated for the extraction of facial image features and the selection of classifiers, and the recognition rate is not high. With the continuous maturity of the convolutional neural network from handwritten digit recognition to face recognition, A face recognition algorithm that tests CNN using the Python+Keras framework. The method mainly involves two aspects. One is to observe the influence on the network by changing the number of neurons in the hidden layer; the other is to observe the influence on the network by changing the number of feature maps of the convolutional layer 1 and the convolutional layer 2. The best CNN model is 36-76-1024 through multiple sets of experimental tests. The model can automatically extract facial image features and classify them. Using adam optimizer and softmax classifier for face recognition can make training faster convergence and more. Effectively improve accuracy and use the Dropout method to avoid overfitting. The experimental results show that the recognition rate of the CNN model on the olivettifaces face database is 97.5%. When the optimal CNN model is used, the average recognition rate is close to 100%, which verifies the validity and accuracy of the algorithm and model.

Based on the basis of the constructed Lie super algebra, the super-isospectral problem of KN hierarchy is considered. Under the frame of the zero curvature equation, the super-KN hierarchy is obtained. Furthermore, its super-Hamiltonian structure is presented by using super-trace identity and it has super-bi-Hamiltonian structure.

Linear birefringence is one of the most important parameters of optical (fibre-optic) current-sensing heads, which can obviously affect the performance of optical current sensors. Therefore, it is of great importance to measure the linear birefringence inside the optical current-sensing head to enhance the properties of sensors. A novel method to measure the linear birefringence inside bulk glass current-sensing heads is reported in this paper, which gives a theoretical analysis of the principle, the measurement uncertainty analysis—using the Jones matrix as a mathematical tool—and an applied example. This method overcomes the shortcomings of the two methods reported before which cannot uniquely determine the value of the linear birefringence or introduce large measurement uncertainty. The experimental result shows that this method can certainly enhance the measurement precision.

To achieve robust posture measurement and identification (ID) of a group of fast-moving mobile robots in a robot soccer system in real time, a novel image-processing algorithm is proposed. The algorithm consists of an illumination-adaptive filter, a fast look-up table, a run-length-encoding- based image reconstruction and a robot ID design. Camera calibration and elimination of parallax errors are also considered. Experimental results verify the speed, reliability and accuracy of the proposed algorithm under different illumination conditions and rapid movement of mobile robots.

Considering a new type of environment influences, we use a two-energy-level (nu (1)-nu (2)) quantum system to investigate neutrino oscillations in medium. Besides the matter effects derived by Wolfenstein, there may exist extra terms due to a unitary evolution of the system between pure and mixed states, so the evolution equation is modified obviously. We show that the extra terms may play some role and induce observable effects in solar neutrino problem, especially, in the long baseline neutrino oscillation experiments which are under serious consideration recently if the parameters fall into a suitable region.

A small high-speed liquid jet apparatus has been set up at the Nagoya Institute of Technology. High-speed liquid jets with the maximum velocity of ~1 km/s can be obtained using the apparatus. This facility has the characteristics of highly reproducibility and convenience in operation. Any jet can be generated in about one minute. It can be used in liquid atomization study or liquid impact erosion study.

Y2O3:Eu3+ phosphors co-doped with different metal cations (Li+, Na+, K+, Mg2+, Ca2+) are prepared by the gel-combustion method with Y2O3, Eu2O3, and R(NO3) x (R = Li, Na, K, Mg, Ca) serving as raw materials and glycine as fuel, calcined at 1000 °C for 2 h. The synthesized Y2O3:Eu3+ phosphors doped with different metal cations and doping ratios are characterized by x-ray diffractometry (XRD), fluorescence and phosphorescent spectrophotometer. The co-doping metal cations are advantageous to the development of Y2O3:Eu3+ lattice. All the samples can emit red light peaked at 611 nm under 254-nm excited. The luminescence intensities of co-doping samples are increased because the cations increase the electron transition probability of Eu3+ from 5D0 level to 7F level. The fluorescence lifetime of Eu3+ (5D0 → 7F2) is increased by doping metal cations.

The fluid dynamic phenomena of a high speed liquid jet impact on a deep water surface have been studied using Imacon high-speed photography. Both framing and streak techniques are applied to investigate the initial impact stage and penetration velocity. The cavitation caused by air entrapment between two colliding liquid surfaces has been found. The bubble collapse experiences different stages in relation to the contact area, liquid shock wave, release wave and fluid convection.

Many previous studies about teleportation are based on pure state. Study of quantum channel as mixed state is more realistic but complicated as pure states degenerate into mixed states by interaction with environment, and the Werner state plays an important role in the study of the mixed state. In this paper, the quantum wireless multihop network is proposed and the information is transmitted hop by hop through teleportation. We deduce a specific expression of the recovered state not only after one-hop teleportation but also across multiple intermediate nodes based on Werner state in a quantum wireless multihop network. We also obtain the fidelity of multihop teleportation.

Shape memory polymers (SMPs) are a class of intelligent materials with the ability to recover their initial shape from a temporarily fixable state when subjected to external stimuli. In this work, the thermo-mechanical behavior of a deployable SMP-based hinged structure is modeled by the finite element method using a 3D constitutive model with shape memory effect. The influences of hinge structure parameters on the nonlinear loading process are investigated. The total shape memory of the processes the hinged structure goes through, including loading at high temperature, decreasing temperature with load carrying, unloading at low temperature and recovering the initial shape with increasing temperature, are illustrated. Numerical results show that the present constitutive theory and the finite element method can effectively predict the complicated thermo-mechanical deformation behavior and shape memory effect of SMP-based hinged shell structures.

Cu2O–TiO2–ZnO ternary nano-heteroarchitectures were designed and successfully fabricated using titanium (IV) oxideacetylacetonate (TiO(acac)2) as a precursor and polyethyleneimine (PEI) as a binding agent. Field emission and photocatalytic activities of pure Cu2O nanopines, Cu2O–TiO2 core–shell nanopines and Cu2O–TiO2–ZnO ternary composites were investigated and compared. The results revealed that the as-prepared nano-heterojunctions and nanoparticles at the surface remarkably enhanced the field emission and photocatalytic activities of pure Cu2O nanopines. The as-prepared nano-heterojunctions induced interfacial states and energy band differentials, which caused electron transition and the inhibition of photo-induced electron–hole pair recombination. The nanoparticles at the surface formed thousands of surface nano-protrusions and active sites for photocatalytic chemical reactions.

Self-assembled InAs quantum wires (QWRs) are fabricated on an InP substrate by solid-source molecular beam epitaxy (SSMBE). Photoluminescence (PL) spectra are investigated in these nanostructures as a function of temperature. An anomalous enhancement of PL intensity and a temperature insensitive PL emission are observed from InAs nanostructures grown on InP substrates using InAlGaAs as the matrix layer and the origin of this phenomenon is discussed. We attribute the anomalous temperature dependence of photoluminescence to the formation of Al-rich and In-rich region in the InAlGaAs buffer layer and the cap layer.

Rayleigh–Taylor instability at a gas-water interface has been investigated experimentally. Such instability was produced by accelerating a water column down a vertical circular tube employing shock wave impact. Accelerations from 50 to 100 times gravitational acceleration with fluid depths from 125 to 250 mm were studied. The resulting instability from small amplitude random perturbations was recorded and later analyzed using high-speed video images. Cavity formation was observed in the middle of the gas–water interface soon after the shock wave impact; bubbles and spikes then developed across the rest of the interfacial plane. Measurements of the growth coefficient of the bubbles and spikes show that they are nearly constant over different runs.