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Three spacecraft of LISA/TAIJI mission follow their respective geodesic trajectories, and their interferometric arms are unequal and time-varying due to orbital dynamics. Time-delay interferometry (TDI) is proposed to suppress the laser frequency noise caused by the unequal-arm. By employing the numerical orbit, we investigate the sensitivity of the first-generation TDI configurations and their corresponding optimal A, E, and T channels. The sensitivities of T channels from Michelson and Monitor/Beacon configurations diverge from the equal-arm case in frequencies lower than 10 mHz, and their performances vary with the inequality of the arm lengths. The mismatches of the laser beam paths are evaluated in a dynamic case, and the residual laser noise in the first-generation TDI could not satisfy the mission requirement., 25 pages, 12 figures

In this paper, a novel Model Predictive Control (MPC) scheme based on discrete-time Linear Extended State Observer (LESO) is proposed for the Aerodynamic Heat Simulation Heating System (AHSHV). First of all, the mathematical model and the predictive model of AHSHV are established, while the unknown terms of the predictive model can be observed by discrete-time LESO. Next, the cost function is constructed for rolling optimization control, and the rolling optimization replaces global optimization with local optimization. Each local optimal control is a feedback correction, and the combination of rolling optimization and feedback correction ensures the performance of the control system. Finally, the simulations and comparison results verify that the MPC scheme proposed in this paper performs better than the traditional PID control scheme in terms of static characteristics, dynamic characteristics, and robustness.

The high-temperature performance of 4H-SiC ultraviolet avalanche photodiodes (APDs) in both linear and Geiger modes is extensively investigated. During the temperature-dependent measurements, a fixed bias voltage is adopted for the device samples, which is much more practical and important for high-temperature applications. The results show that the fabricated 4H-SiC APDs are very stable and reliable at high temperatures. As the temperature increases from room temperature to 425 K, the dark current at 95% of the breakdown voltage increases slightly and remains lower than 40 pA. In Geiger mode, our 4H-SiC APDs can be self-quenched in a passive-quenching circuit, which is expected for high-speed detection systems. Moreover, an interesting phenomenon is observed for the first time: the single-photon detection efficiency shows a non-monotonic variation as a function of temperature. The physical mechanism of the variation in high-temperature performance is further analyzed. The results in this work can provide a fundamental reference for researchers in the field of 4H-SiC APD ultraviolet detectors.

Micro-double gear is an important component that transmits power or motion as one of the key components of micro-device. In order to realize the mass and industrial production of micro-double gear, an injection mold of micro-double gear was designed. The single factor experiment and orthogonal experiment were used to optimize the process parameters of wire cut electrical discharge machining (WEDM) for machining micro-double gear mold cavity insert at the maximum cutting speed. The results show that the influence of process parameters on cutting speed is successively N, Toff and Ton , and N has the most significant influence on cutting speed, which is the key factor. When Ton =8µs, Toff =3Ton and N=5, the maximum cutting speed is 99.24mm2/min. The combination parameters of the maximum cutting speed were used to process the cavity insert of micro-double gear mold, and the cavity of micro-double gear mold was better fabricated.

Currently, the discussion on the modeling method characterized by the small electrodynamic shakers, especially the mathematic analytical method, is relatively sparse. In this paper, taking BK4809 as an example, a modeling method for small shakers based on analytical formulations is discussed. The detailed mathematical analysis and derivation process for the small shakers are performed, and the corresponding modeling formulations are concluded; then, the simulation tests are carried out in MATLAB. Through comparison with the reference data, the validation tests show that based on analytic formulations combined with the MATLAB built-in system identification functions, the results of modeling methods match well with the experiment data, and the concluded method is effective.

Facing the problem of having trouble building an exact mathematical model for aerodynamic heat simulation heating system (AHSHS), the conventional PID is considered to have the characteristics of simple operation, easy parameter adjustment, and high accuracy, but it is sensitive to external disturbances and has a poor anti-interference ability. In this paper, the fuzzy PID scheme for AHSHS is introduced to conquer the above problems. Firstly, the affiliation functions are constructed according to the system output errors and deviation variations. Next, the fuzzy rule table is designed, and the parameter autotune of PID is implemented utilizing both fuzzy inference and inverse fuzzification. Finally, comparative analysis through simulation verifies that the fuzzy PID scheme is more advantageous.

Multi-sensor monitoring data provide abundant information resources for complex machine systems, which facilitates monitoring the degradation process of machinery and ensuring the reliability of the industrial process. However, previous prognostic methods focus more on the sequential data obtained from multi-sensors, while ignoring the underlying prior structural information of the equipment. To fully leverage the structural information into the modeling process, and thus improve the remaining useful life (RUL) prediction performance, a hierarchical graph neural network with adaptive cross-graph fusion (HGNN-ACGF) method for RUL prediction is proposed in this study. In the HGNN-ACGF method, a hierarchical graph consisting of a sensor graph and a module graph is constructed by introducing the structural information to fully model the degradation trend information of the complex machine system. Besides, the graph neural network (GNN) is adopted to learn the representation at both the module graph and sensor graph, and an adaptive cross-graph fusion (ACGF) block is proposed. Owing to the cross-graph fusion block, the representation from different graphs can be fused adaptively by considering the relative importance between different modules and sensors. To verify the proposed method, the experiments were conducted on a set of degradation data sets of aircraft engines provided by the Commercial Modular Aero-Propulsion System Simulation. The experimental results show that the proposed method has superior performance in RUL prediction over the state-of-the-art methods.

The high-reliability requirement of 5 G electronic products poses a higher challenge to its protective films, the high transmission quality of high-frequency signals, excellent heat dissipation and anticorrosive capability, which promotes the ultra-thin protective films with good adhesion and anticorrosion. In this work, a nanometer-scale p-HMDSO film was obtained on the Cu alloy with hexamethyldisiloxane (HMDSO) as the precursor by the low-temperature RF-PECVD method. Compared with Parylene and p-PFDA (1H, 1H, 2H, 2H-Perfluorodecyl acrylate) films, the p-HMDSO film possesses better hydrophobicity, mechanical stability and anticorrosive property. The corrosion inhibition efficiency of the p-HMDSO film reaches 99.95%. Meanwhile, it provides 3 orders of magnitude increment of charge-transfer impedance, a salt spray corrosion resistance for 24 h, and the protection of 10 days in the 3.5 wt% NaCl solution, which develops a better application prospect in the protection of integrated electronics.

Elliptical airy vortex beams (EAVBs) can spontaneously form easily identifiable topological charge focal spots. They are used for topological charge detection of vortex beams because they have the abruptly autofocusing properties of circular airy vortex beams and exhibit unique propagation characteristics. We study the use of the dynamic phase and Pancharatnam–Berry phase principles for generation and modulation of EAVBs by designing complex-amplitude metasurface and phase-only metasurface, at an operating wavelength of 1500 nm. It is found that the focusing pattern of EAVBs in the autofocusing plane splits into |m|+1 tilted bright spots from the original ring, and the tilted direction is related to the sign of the topological charge number m. Due to the advantages of ultra-thin, ultra-light, and small size of the metasurface, our designed metasurface device has potential applications in improving the channel capacity based on orbital angular momentum communication, information coding, and particle capture compared to spatial light modulation systems that generate EAVBs.

CaBi2 has been experimentally found to be a superconductor with a transition temperature of 2 K and identified as a topological insulator via spin- and angle-resolved photoemission spectroscopy, which makes it a possible platform to study the interplay between superconductivity and topology. But the detailed transport properties for CaBi2 single crystal remain unexplored in experiments. Here, we systematically studied the magneto-transport properties of CaBi2 single crystal grown by a flux method. CaBi2 shows a magnetic-field-induced upturn behavior with a plateau in resistivity at low temperature. An extremely large and non-saturating magnetoresistance up to ∼15000% at 3 K and 12 T was achieved. The possible reason for the magnetic field and temperature dependence of resistivity and extremely large magnetoresistance at low temperature was discussed by adopting the Kohler’s scaling law, which can be understood by the compensation effect confirmed by the Hall Effect measurement.

The self-absorption effect in laser-induced breakdown spectroscopy (LIBS) reduces the accuracy of quantitative measurement results. The self-absorption-free LIBS (SAF-LIBS) has been proved to directly capture the optically thin plasma spectra by setting an appropriate exposure time. In this work, a novel SAF-LIBS technique with high repetition rate acousto-optic gating is developed, in which an acousto-optic modulator is used as the shutter to diffract the optically thin fluorescence, and a high repetition rate laser is used to produce quasi-continuous plasmas to enhance the integral spectral intensity, so that the CCD spectrometer can replace an intensified CCD (ICCD) and echelle spectrometer in SAF-LIBS. Experimental results show that the average absolute prediction error of aluminum is reduced to 0.18%, which is equivalent to that of traditional SAF-LIBS. This technique not only effectively shields continuous background radiation and broadened spectral lines in optically thick plasma, but also has advantages of miniaturization, low cost, convenience and reliability.

As one of the important power transmission and transformation equipment, the reliability of transformer is directly related to the safe operation of power system. At present, the on-line monitoring technology based on dissolved gas analysis in oil is widely valued by researchers all over the world because it can continuously monitor the operation status of transformers and timely and effectively find the early faults of transformers. In this paper, the on-site oil chromatography data are differentiated and classified according to the voltage level of the transformer. The curve fitting method is used for statistical analysis and to build a distribution model. The cumulative probability is associated with the defect rate and failure rate of the equipment, and the corresponding threshold value is obtained by using the inverse cumulative distribution function as the attention value and warning value. By using this method, the attention values of the volume fraction of dissolved gas in oil and the gas production rate of dissolved gas in the existing national standards are improved, and the corresponding warning values are calculated to make the warning mechanism more flexible and reliable.

In this work, the effects of O2 or N2 microwave plasma treatment on β-Ga2O3 surface prior to Schottky metal deposition are reported. The device uniformity of Schottky barrier diodes is improved significantly by the microwave plasma treatments without any degradation such as ideality factor (near 1.0), and on-state resistance (R on ∼3 mΩ cm2). The standard deviation of Schottky barrier height (SBH, φB) is as small as less than 10 m eV. Kelvin probe force microscope analysis shows that the surface electrostatic potential after O2 microwave plasma treatment is lower than that of the N2 microwave plasma treatment, which is consistent with the change of SBH obtained by capacitance–voltage (C–V) and current–voltage (I–V) measurements. The relatively low SBH with O2 microwave-plasma treatment corresponds to the high reverse leakage current. The oxygen related adsorption at metal/Ga2O3 interface by O2 microwave plasma treatment confirmed by x-ray photoelectron spectroscopy can be attributed to the SBH and surface potential lowing.

In this study, we explore the hadronic coupling constants , , and of the exotic states within the pictures of both the tetraquark and molecular states with the tentative assignments based on rigorous quark-hadron duality. Subsequently, we obtain the total widths and , which are consistent with experimental values from the BESIII collaboration, , and LHCb collaboration, , respectively, and support assigning and as the hidden-charm tetraquark and molecular states with , respectively.

The permittivity of lunar regolith is crucial for further processing and interpretation of radar data. The conventional hyperbolic fitting method ignores the antenna height and spacing and has a significant error at a shallow depth. For the new method that considers the layout of the antenna, the influencing factors have not been studied. In this paper, we studied the influence of the position of the hyperbola peak and time zero on the new method for permittivity derivation. The simulation results show that when the input errors of time zero, abscissa and ordinate of the hyperbolic peak are ±2 ns, ±0.02 m and ±0.2 ns respectively, the average errors of the calculated results by points within 1 m from the hyperbolic peak are 10.0%, 16.7% and 38.2%, respectively. To improve the accuracy, we used the average results by points that are horizontally more than 1 m away from the hyperbola peak. Hence, we calculated the permittivity of the lunar regolith by the new method based on Lunar Penetrating Radar data. The average permittivity of the lunar regolith is estimated to be 3.3 ± 1.2.

The two types of nonlinear optical cryptosystems (NOCs) that are respectively based on amplitude-phase retrieval algorithm (APRA) and phase retrieval algorithm (PRA) have attracted a lot of attention due to their unique mechanism of encryption process and remarkable ability to resist common attacks. In this paper, the securities of the two types of NOCs are evaluated by using a deep-learning (DL) method, where an end-to-end densely connected convolutional network (DenseNet) model for cryptanalysis is developed. The proposed DL-based method is able to retrieve unknown plaintexts from the given ciphertexts by using the trained DenseNet model without prior knowledge of any public or private key. The results of numerical experiments with the DenseNet model clearly demonstrate the validity and good performance of the proposed the DL-based attack on NOCs.

Recently, scientists have achieved significant progress in experiments searching for excited and baryons such as , , , , , , and . Motivated by these achievements, we systematically analyze the and states of and baryons using the method of quantum chromodynamics sum rules. By constructing three types of interpolating currents, we calculate the masses and pole residues of these heavy baryons with different excitation modes: , , and . Subsequently, we decode the inner structures of , , , and and favor assigning these states as the baryons with the quantum numbers and , , , and , respectively. In addition, the predictions for the masses and pole residues of the other and and baryons in this paper will be useful for studying D-wave bottom baryons in the future.

Unsupervised and supervised deep learning extract effective and abstract features from different perspectives, which have been successfully applied in soft sensors. However, few studies have fused them and explored the complementary effect between the two kinds of features, which limits the utilization of comprehensive prediction information. To address the problem, a novel random subspace method with stacked auto-encoder (SAE) and bidirectional long short-term memory (Bi-LSTM), named RS-SBL, is proposed for soft sensors. Firstly, unsupervised and supervised deep representation features are extracted by SAE and Bi-LSTM, respectively. Secondly, to leverage the complementarity of the fusion features, an improved random subspcae (RS) method with a structure sparsity learning model is designed to discriminate the relative importance of different features and generate ensemble prediction results. Finally, the experiments on two real-world industrial nonlinear processes demonstrate that the proposed RS-SBL with the feature fusion strategy improves the prediction performance, and outperforms the other comparison soft sensor models.

Deep learning plays an important role in soft sensors of industrial processes for the timely measurement of key quality variables. However, since sensors are often operated under noisy and nonstationary industrial conditions, the collected industrial process data exhibit extreme complexity, which severely restricts the learning capacity and measurement accuracy of deep learning methods. In this paper, a novel denoising and multiscale residual deep network (DMRDN) is proposed for soft sensor modeling. Firstly, a stacked denoising autoencoder with level-aware attention is developed to denoise the process data, in which denoised features on different levels are learned and fused. Secondly, the denoised features are fed into multiscale residual convolutional neural network with scale-aware attention, which is designed to capture and fuse deep dynamic features from different scales. Finally, experiments were conducted on an industrial debutanizer column. The experimental results demonstrate that the proposed DMRDN greatly strengthens the learning ability and achieves better prediction performance compared with other methods.

Although laser-induced breakdown spectroscopy (LIBS), as a fast on-line analysis technology, has great potential and competitiveness in the analysis of chemical composition and proximate analysis results of coal in thermal power plants, the measurement repeatability of LIBS needs to be further improved due to the difficulty in controlling the stability of the generated plasmas at present. In this paper, we propose a novel x-ray fluorescence (XRF) assisted LIBS method for high repeatability analysis of coal quality, which not only inherits the ability of LIBS to directly analyze organic elements such as C and H in coal, but also uses XRF to make up for the lack of stability of LIBS in determining other inorganic ash-forming elements. With the combination of elemental lines in LIBS and XRF spectra, the principal component analysis and the partial least squares are used to establish the prediction model and perform multi-elemental and proximate analysis of coal. Quantitative analysis results show that the relative standard deviation (RSD) of C is 0.15%, the RSDs of other elements are less than 4%, and the standard deviations of calorific value, ash content, sulfur content and volatile matter are 0.11 MJ kg−1, 0.17%, 0.79% and 0.41% respectively, indicating that the method has good repeatability in determination of coal quality. This work is helpful to accelerate the development of LIBS in the field of rapid measurement of coal entering the power plant and on-line monitoring of coal entering the furnace.

In order to improve the operating efficiency of the integrated energy system and reduce emissions, this paper proposes a multi-objective optimization method for the integrated energy system that considers energy saving. Set energy-saving goals, electric power balance, thermal power balance, operating cost constraints and other calculation equations. On the basis again, an optimization model of the integrated energy system is constructed. According to the characteristics of the constraint conditions, a penalty function is constructed, and the fuzzy satisfaction scheme is standardized to complete the operation optimization of the system. The analysis of calculation examples proves that the method in this paper can alleviate the environmental pollution problem, and can improve the operating efficiency and reduce the operating cost of the system.

Kinesin is a molecular motor that can step processively on microtubules via the hydrolysis of ATP molecules. An important factor characterizing the processivity of the kinesin motor is its dissociation from the microtubule. Here, using all-atom molecular dynamics simulations, we studied the dissociation process of the kinesin head in weak-microtubule-binding or ADP state from tubulin on the basis of the available high-resolution structural data for the head and tubulin. By analyzing the simulated snapshots of the structure of the head-tubulin complex we provided detailed structural and dynamic information for the dissociation process. We found that the dissociation of the head along different directions relative to the tubulin exhibits very different dynamic behaviors. Moreover, the potential forms or energy landscapes of the interaction between the head and tubulin along different directions were determined. The studies have important implications for the detailed molecular mechanism of the dissociation of the kinesin motor and thus are critical to the mechanism of its processivity.

A versatile scheme for design of planar ultra-wideband impedance transformer is proposed by using fragment-type structures (FTS) for modeling and MOEA/D-GO for optimization. To improve the optimization efficiency, non-uniform FTS cells are applied. To find the optimal planar FTS transformer, two objective functions characterizing the return loss and the insertion loss of the impedance transformer, respectively, are defined on a ultra-wide bandwidth. For demonstration, a 25-ohm to 50-ohm FTS impedance transformer is designed, which acquires reflection coefficient lower than -20 dB and extra insertion loss less than 0.27 dB in ultra-wide frequency band of 0.89-5.00 GHz.

Position and attitude change during sit to stand transfer is the most important change in daily life. On the basis of fully studying the existing equipment, position and attitude during sit to stand transfer is analysed, and the mathematical model of this process is established, the motion trajectory of hip joint during sit to stand transfer is normalized, then the feature points are extracted from motion trajectory. Based on the feature points, and using the linkage mechanism, the dimension synthesis of linkage mechanism is completed by graphic method, the method of realizing anthropomorphic motion trajectory during sit to stand transfer is given systematically based on linkage mechanism. The simulation results show that the designed mechanism can realize the anthropomorphic motion trajectory accurately during sit to stand transfer, and it lays a good foundation for the subsequent design of sit to stand assistance equipment.

The chiral magnetic effect (CME) is a novel transport phenomenon, arising from the interplay between quantum anomalies and strong magnetic fields in chiral systems. In high-energy nuclear collisions, the CME may survive the expansion of the quark-gluon plasma fireball and be detected in experiments. Over the past decade, the experimental searches for the CME have aroused extensive interest at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). The main goal of this article is to investigate three pertinent experimental approaches: the $\gamma$ correlator, the $R$ correlator and the signed balance functions. We will exploit both simple Monte Carlo simulations and a realistic event generator (EBE-AVFD) to verify the equivalence in the kernel-component observables among these methods and to ascertain their sensitivities to the CME signal for the isobaric collisions at RHIC., Comment: 18 pages, 8 figures, 2 tables. Extended the discussion on R observable with the consideration of multiplicity fluctuation as used in practice

Cooling holes (number 100 ∼ 200, diameter 0.3 ∼ 1.2 mm) are important heat dissipation structures of a turbine blade in aero-engine. Due to the small sizes and similar contours of cooling holes, it is difficult to extract and match their features by traditional stereo reconstruction methods. This paper proposes a novel cooling hole inspection method for turbine blades utilizing 3D reconstruction technique of stereo vision, which combines the stereo vision principle with the invariance of cross-ratio. The feature points of contours are extracted and matched by calculating two intersection points of circular contours and a line through the center points of adjacent cooling holes. Additionally, the 3D points corresponding to the feature points are reconstructed, by which, the diameters of cooling holes can be calculated successfully. Moreover, measurement experiments verify the effectiveness and accuracy of the proposed method. The experimental results show that the average errors of the standard circle ruler and tiny hole sample are within 0.05 mm, which satisfies the inspection requirement of cooling holes.

On the basis of analyzing and summarizing the current situation of the construction and use of distribution automation systems at home and abroad, according to the requirements of the use of distribution automation systems, a data two-way interactive distribution automation system architecture design is proposed. In response to the requirements for multi-source data collection in the distribution network, a distribution automation system architecture with partitioned collection and bidirectional data flow is proposed to improve the perception of distribution network equipment. Propose the self-recognition technology of power distribution system and terminal based on IEC61968 and IEC61850 model mapping to realize the fast access of power distribution terminal. Propose a grid integration modeling and global decision analysis method based on model splicing technology to realize multi-dimensional data fusion and analysis applications.

Based on the optical system characteristics of coded aperture snapshot spectral imager (CASSI), an optimized optical system of shortwave infrared dual camera CASSI was designed based on improved Offner-Wynne imaging spectrometer. The operating wavelength of the optical system ranges from 900nm to 1700nm, and the focal length is 1200mm. It consists of two parts: the two dimensional imaging system and the multispectral CASSI imaging system. The key technical parameters of the two parts are the same and there is no visual axis difference. Therefore, the optimized optical system can effectively improve real-time performance, optical transmittance and compactness of the dual camera shortwave infrared CASSI, which is conducive to the application in optical measurement scenes in the shooting range.

Ag/SiO2 and Au/SiO2 samples were prepared by separately implanting 30 keV Ag and Au ions into 0.5-mm-thick SiO2 slabs at a fluence of 6 × 1016 ion·cm−2, and their optical and structural properties were studied in detail by using a fiber spectrometer and a transmission electron microscope, respectively. Our results showed that the two samples featured by their respective nanocomposite surface layers were asymmetrical in structure, and hence, their characteristic signals in the reflectance spectra excited by the lights incident from the rear surfaces were able to exhibit corresponding blueshifts when the overlays on the implanted surfaces were increased in refractive index with respect to air. Our results also showed that each of characteristic signals was strongly dependent on the localized surface plasmon resonance (LSPR) behavior of the involved Ag or Au nanoparticles (NPs), and it could not appear at a wavelength position smaller than or equal to that of the LSPR absorption peak since the involved Ag or Au NPs were quite small in size. These results meant that the two samples could be regarded as the LSPR sensors with a negative refractive index sensitivity (RIS), although their sensing abilities would lose when the overlays were very large in refractive index. Especially, the two samples were demonstrated to be relatively high in stability because the involved Ag and Au NPs were closely hugged and chemically protected by the matrices of SiO2, and consequently, they could have a chance to become prospective sensing devices in some special fields as long as their RISs and linearities could be improved in the future. The above findings substantially confirmed that the metal ion implantation into transparent dielectric slab was an effective route to the high-stability LSPR sensors.

Non-Common Path Error (NCPE) is one of the factors that limit an Adaptive Optics (AO) system from delivering ultra-high performance. To correct the NCPE associated static aberration, we propose a simple but robust and high-performance pupil-plane based wavefront measurement and correction technique, which can copy a single-mode fiber generated perfect wavefront to the AO system via an iteration optimization process, and the NCPE can be effectively corrected by directly commanding the Deformable Mirror (DM) of the AO system. Compared with the previous focal-plane based approach that uses focal plane based Point Spread Function (PSF) for correction evaluation, the pupil-plane based approach can be reliably and rapidly converged to a global optimization result and provides better performance, in particular for an AO system with a large initial static wavefront error. This technique we proposed can be implemented in astronomical AO systems where extremely high performance is required.

In this paper, we choose the scalar and axialvector diquark operators in the color antitriplet as the fundamental building blocks to construct the four-quark currents and investigate the diquark-antidiquark type axialvector tetraquark states $c\bar{c}u\bar{s}$ in the framework of the QCD sum rules. The predicted tetraquark mass $M_Z=3.99\pm0.09\,\rm{GeV}$ is in excellent agreement with the experimental value $3985.2^{+2.1}_{-2.0}\pm1.7\,\rm{MeV}$ from the BESIII collaboration, which supports identifying the $Z_{cs}(3985)$ as the cousin of the $Z_c(3900)$ with the quantum numbers $J^{PC}=1^{+-}$. We take into account the light flavor $SU(3)$ mass-breaking effect to estimate the mass spectrum of the diquark-antidiquark type hidden-charm tetraquark states having the strangeness according to the previous works., 13 pages, 4 figures