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The carrier transport capacity of the unintentionally doped InGaN upper waveguide (UWG) layer affects the hole injection efficiency of GaN-based blue laser diode. In this article, we studied the carrier transport property of UWG layer grown under various conditions by Metal Organic Chemical Vapor Deposition (MOCVD). Hole diffusion length in these samples were obtained by photoluminescence. It is found that higher diffusion length can be obtained with growth temperature around 840℃~870℃ and V/III ratio about 16,000. It is also found that reducing the threading dislocation density can enhance the carrier transport capacity of the UWG layer.

In recent years, spiking neural network(SNNs) has increasingly received the attention of research in the field of artificial intelligence due to high biological plausibility, low energy consumption and abundant spatio-temporal information. However, the non-differential spike activity makes SNNs more difficult to train in supervised training. Most existing methods focusing on introducing an approximated derivative to replace it, while they are often based on static surrogate functions. In this paper, we proposed a progressive surrogate gradient learning for backpropagation of SNNs, which is able to approximate the step function gradually and reduce information loss. Furthermore, memristor cross arrays are used for speeding up calculation and reducing system energy consumption for their hardware advantage. The proposed algorithm is evaluated on both static and neuromorphic datasets using fully-connected and convolutional network architecture, and the results of experiment indicated that our approach has a high performance compared with previous research.

The non-intrusive load decomposition method is an essential approach of appreciating the water requirements of consumers. Traditional techniques of load breakdown have a number of drawbacks, including a poor level of water identification precision. In order to do this, a model for load decomposition based on generative adversarial networks has been developed. By applying a convolutional autoencoder to the total power noise, the generative network constructs the power breakdown sequence of the given home appliance. The discriminant network is then utilized to determine whether or not the created sequence is legitimate. In order to achieve a more natural and authentic sequence, the participants compete against one another. In light of the shortcomings of the centralized model training method, the network model implementation scheme based on asynchronous federated learning is utilized to replace the traditional convolution in order to realize the model’s lightweight nature. This allows the model to be applied to terminal devices such as smart water meters, and it is carried out in a cloud-edge collaborative manner. In addition, the model is carried out in a manner that is collaborative between the cloud and the edge. Training not only eases the strain of communication transmission but also protects the privacy of users and the integrity of their data.

Objective. Motor Imagery Brain-Computer Interface (MI-BCI) is an active Brain-Computer Interface (BCI) paradigm focusing on the identification of motor intention, which is one of the most important non-invasive BCI paradigms. In MI-BCI studies, deep learning-based methods (especially lightweight networks) have attracted more attention in recent years, but the decoding performance still needs further improving. Approach. To solve this problem, we designed a filter bank structure with sinc-convolutional layers for spatio-temporal feature extraction of MI-electroencephalography in four motor rhythms. The Channel Self-Attention method was introduced for feature selection based on both global and local information, so as to build a model called Filter Bank Sinc-convolutional Network with Channel Self-Attention for high performance MI-decoding. Also, we proposed a data augmentation method based on multivariate empirical mode decomposition to improve the generalization capability of the model. Main results. We performed an intra-subject evaluation experiment on unseen data of three open MI datasets. The proposed method achieved mean accuracy of 78.20% (4-class scenario) on BCI Competition IV IIa, 87.34% (2-class scenario) on BCI Competition IV IIb, and 72.03% (2-class scenario) on Open Brain Machine Interface (OpenBMI) dataset, which are significantly higher than those of compared deep learning-based methods by at least 3.05% ( p = 0.0469), 3.18% ( p = 0.0371), and 2.27% ( p = 0.0024) respectively. Significance. This work provides a new option for deep learning-based MI decoding, which can be employed for building BCI systems for motor rehabilitation.

In this paper, one of the state-of-the-art deep reinforcement learning (DRL) algorithms, the proximal policy optimization (PPO) algorithm is used to achieve the learning of the attitude controller of hypersonic vehicles (HSVs). The HSV attitude-tracking control problem belongs to continuous control problems, which means the state space and the action space of the HSV are both continuous. The goal of DRL is to maximize accumulated rewards rather than the instant reward, so a fixed time length training episode and a normalized instantaneous reward function are presented to facilitate a comparison of each episodic return. Numerical simulation results show the proposed training manner can effectively make the learning controller track the attitudes for the longitudinal motion of HSVs with uncertainties. This training manner also can generalize to other continuous control problems.

Alumina ceramics used in microwave systems are susceptible to the multiplication of secondary electron emission on the surface due to the influence of resonance between electrons and the radiofrequency electric field, and a detrimental multipactor effect may therefore be triggered. For the alumina-loaded microwave components, it is essential to achieve low secondary electron yield (SEY) on the inserted alumina surfaces to mitigate multipactor. In this work, to achieve an ultralow SEY surface of alumina, two recognized low-SEY treatments were combined. For the primary SEY suppression, a series of microstructures were fabricated on the alumina surfaces with varied porosity and aspect ratio at the hundred-micrometer scale by infrared laser etching. The microstructure with 52.14% porosity and 1.78 aspect ratio showed an excellent low-SEY property, which could suppress the SEY peak value ( δ m ) of alumina from 2.46 to 1.00. For the secondary SEY suppression, the SEY dependence of TiN coating on sputtering parameters was studied, and the lowest δ m of 1.19 was achieved when the gas flow ratio of Ar:N2 was 15:7.5. Thereafter, by depositing TiN ceramic coating onto the laser-etched porous samples, an ultralow SEY, with δ m of 0.69, was achieved on the alumina surfaces. The simulation work revealed the impact of dielectric surface charge on electron multiplication and revealed a mechanism of using low-SEY surfaces to inhibit multipactor. Some coaxial filters filled with alumina were fabricated for verification; the results revealed that the multipactor threshold increased from 125 W to 425 W after applying the TiN-coated porous alumina, and to 650 W after treating another multipactor-sensitive area with the same low-SEY process. This work developed an advisable method to sharply reduce SEY, which is of great significance for the multipactor mitigation of alumina-loaded microwave components.

This article studies characteristics of 3LPE external coating material and cathodic protection technology for offshore pipeline firstly, analysis the mechanism of cathodic disbondment and specified properties, carries out cathodic disbonding tests base on different cathodic protection current density applied on coated samples at given temperature, and then analyses the relationship between coating failure life and index of cathodic protection using Arrhenius model and inverse power law model, puts forward a recommended maximal cathodic protection current density for offshore pipeline at a certain design life of coating.

Memristive neural network has attracted tremendous attention since the memristor array can perform parallel multiply-accumulate calculation (MAC) operations and memory-computation operations as compared with digital CMOS hardware systems. However, owing to the variability of the memristor, the implementation of high-precision neural network in memristive computation units is still difficult. Existing learning algorithms for memristive artificial neural network (ANN) is unable to achieve the performance comparable to high-precision by using CMOS-based system. Here, we propose an algorithm based on off-chip learning for memristive ANN in low precision. Training the ANN in the high-precision in digital CPUs and then quantifying the weight of the network to low precision, the quantified weights are mapped to the memristor arrays based on VTEAM model through using the pulse coding weight-mapping rule. In this work, we execute the inference of trained 5-layers convolution neural network on the memristor arrays and achieve an accuracy close to the inference in the case of high precision (64-bit). Compared with other algorithms-based off-chip learning, the algorithm proposed in the present study can easily implement the mapping process and less influence of the device variability. Our result provides an effective approach to implementing the ANN on the memristive hardware platform.

Two-dimensional (2D) bismuth triiodide (BiI3) has been emerging as a potential layered material for optoelectronic applications due to its air stability and high atomic density. Although much effort has been devoted to improvements of carrier mobility, conductivity and photoelectric response, performance is still very limited. Here, we report a simple and scalable strategy for greatly improving the electrical and optical properties of 2D BiI3 through high-κ dielectric engineering. Upon covering with a high-κ dielectric oxide (Al2O3), air isolation and dielectric screening effects can lead to the reduction of the contact barrier, passivation of trap states, and suppression of Coulomb scattering. As a result, BiI3-based phototransistors can increase carrier mobility by three orders of magnitude and improve photoresponsivity by three orders of magnitude up to 8.05 × 103 A W−1. This work develops a new 2D BiI3 material and efficient dielectric engineering for improving mobility and photoelectrical performance, expanding the family of 2D materials and offering a promising strategy for potential nano-device applications.

To integrate a terahertz pump into an ultrafast electron diffraction (UED) experiment has attracted much attention due to its potential to initiate and detect the structural dynamics both directly. However, the deflection of the electron probe by the electromagnetic field of the terahertz pump alters the incident angle of the electron probe on the sample, impeding it from recording structural information afterwards. In this article, we studied this issue by a theoretical simulation of the terahertz-induced deflection effect on the electron probe, and came up with several possible schemes to reduce such effect. As a result, a terahertz-pump-electron-probe UED experiment with a temporal resolution comparable to the terahertz period is realized. We also found that MeV UED was more suitable for such terahertz pump experiment.

By considering a 3-mode optomechanical system formed by two cavities interacting with a common mechanical mode, we demonstrate that phonon-counting measurements lead to a significant enhancement of entanglement in the output of the two cavities. This conclusion still holds for an inefficient detector, but the dependence on system parameters changes qualitatively from the ideal limit of perfect projective measurements. We find non-trivial optimal points for the entanglement as functions of detector efficiency, measurement outcome, and optical drive strengths. We characterize both the highest achievable entanglement as well as a ‘typical’ value, obtained at the most likely measurement outcome. Numerical results are well understood within an approximate analytical approach based on perturbation theory around the ideal detector limit.

We demonstrate the coherent transfer of an ultrastable optical frequency reference over a 490 km noisy field fiber link. The fiber-induced phase noise power spectrum density per-unit-length at 1 Hz offset frequency can reach up to 510 rad2⋅Hz−1⋅km−1, which is much higher than the fiber noise observed in previous reports. This extreme level of phase noise is mainly due to the fiber link laying underground along the highway. Appropriate phase-locked loop parameters are chosen to complete the active compensation of fiber noise by measuring the intensity fluctuation of additional phase noise and designing a homemade digital frequency division phase discriminator with a large phase detection range of 212 π rad. Finally, a noise suppression intensity of approximately 40 dB at 1 Hz is obtained, with fractional frequency instability of 1.1 × 10−14 at 1 s averaging time, and 3.7 × 10−19 at 10000 s. The transfer system will be used for remote atomic clock comparisons and optical frequency distribution over a long-distance communication network established in China.

Aiming at the unreasonable test-times selection method in the precision evaluation of inertial navigation system, this paper puts forward the test-times selection method. The test conclusion confidence, test condition confidence, and the sample confidence limit are included in this test-times selection method for quantitative test-times. In addition, the selection process is illustrated through an example.

Complaint prediction is a hot topic in current research. Due to complaint prediction is random, the accuracy of complaint prediction is not high. To solve this problem, this paper proposes a complaint prediction method based on feature weighted Naive Bayes. According to rough set theory, we first calculate the importance of each conditional attribute, combine the importance of attribute as the weight with the naive Bayes classifier to form a weighted naive Bayes classifier. We use multiple classifiers to make predictions, the latter classifier performs iterative learning on the basis of the previous classifier, and finally all classifiers are given different weights to make decisions. The experimental results show that the proposed method effectively combines the weighting method and the Naive Bayes method to achieve reliable prediction of complaints.

With the continuous development of computer technology and industrial design technology, the traditional manual drawing design method has seriously affected the effect of industrial design. The research on computer-aided industrial design system has gradually attracted the attention of experts and scholars. This paper expounds the application characteristics of computer-aided industrial design technology from CAD industrial design technology in detail, and finally designs the computer-aided industrial design system according to the more mature hierarchy method and structure method, and conducts detailed analysis and comparison of specific components.

Due to environmental friendliness, electric vehicles have become more and more popular nowadays in the transportation system. For many express companies, it is more and more important to meet the predetermined time window of customers. The uncertainty in travel times often causes uncertain energy consumption and uncertain recharging time, thus electric vehicles may miss the time windows of customers. Therefore, this paper addresses the electric vehicle routing problem with time windows under travel time uncertainty, which aims to determine the optimal delivery strategy under travel time uncertainty. To solve this problem, a robust optimization model is built based on the route-dependent uncertainty sets. However, considering the complexity of the problem, the robust model can only solve few instances including the small number of customers. Thus, a hybrid metaheuristic consisting of the adaptive large neighborhood search algorithm and the local search algorithm is proposed. The results show that the algorithm can obtain the optimal solution for the small-sized instances and the large-sized instances.

Hot atoms can exhibit non-magnetic optical non-reciprocal transmission due to their chiral properties, which are characteristic of most alkali metal atoms. In fact, the nonreciprocity in hot atoms depends on the propagation direction of the coupling field due to the Doppler effect. Herein, the reciprocal to non-reciprocal conversion based on the single- and double-dark states is realized by controlling the bidirectional coupling fields in a three-level electromagnetically induced transparent medium coupled with a ring cavity. Tuning the frequency difference between the two coupling fields causes the multi-frequency-channel reciprocity and nonreciprocity manipulation to occur. The experimental proof can be applied to quantum communications and quantum networks, such as optical transistors, all-optical switching or routing and logic gate operation.

The nonlinear Schrödinger equation (NLS) is widely used in different branches of physics. The GP equation is a kind of NLS equation with potential function term. In this paper, the soliton solutions of a generalized GP equation are explored. Firstly, we construct the Lax pair and Darboux transform(DT) of the equation. Then, we solve the single and double soliton solutions of the equation. Lastly, we draw the images of the single and double soliton solutions, and investigate the properties of the solitons. It is found that the amplitude of a single solitary wave does not change, and the shape and amplitude of the double solitary wave remain unchanged after the collision.

This paper first analyzes and determines the scope and contents of highway engineering environmental supervision from the aspects of highway engineering composition, construction stage division, impact environmental factors and their characteristics, environmental protection requirements, etc., combines with the characteristics of high-resolution remote sensing images, proposes the construction process and supervision precision requirements for the highway engineering in which environment protection control can be carried out by using satellite remote-sensing images and UAV (unmanned aerial vehicle) remote-sensing images. Through the environmental investigation experiment of high-resolution satellite remote sensing images commonly used in typical road sections, the satellite remote-sensing images meeting the highway engineering environmental supervision requirements are selected through comparative analysis from the perspectives of spatial resolution, revisit cycle, spectral waveband characteristics, environmental supervision precision requirements and image purchase cost rationality.

In recent years, malicious code emerges in endlessly. New types of malicious code evade the traditional malicious code detection technology through polymorphism, shelling, confusion and other ways. In order to solve the challenges brought by various technologies to the research of malicious code detection, in this paper, we propose a malicious code detection method based on static features and ensemble learning. This method extracts the information in the PE header file of malicious code samples as static features, and on this basis, builds a malicious code detection model by using stacking ensemble learning. In order to verify the effectiveness of the model, experiments are carried out on a dataset containing 5000 malicious codes and 4943 benign codes. Experiments show that the classification model based on stacking ensemble learning is the best, with 97.22% precision rate and 96.45% stable F1 score.

Brake-by-wire (BBW) system is the key system to ensure the safety and stability control of intelligent vehicle chassis. How to evaluate the BBW systems to meet the safety design requirements is one of the important links of system design. This article takes the BBW system as an example to illustrate the basic process of the safety assessment of intelligent vehicle. The fault tree analysis (FTA) method is used to quantitatively evaluate the failure status of the complete loss of the main brake function, and the fault tree analysis process is detailed. The results show that FTA plays an important role in guiding the design of system architecture. With the help of the importance index, we can quickly find out the weaknesses in the system architecture, when the probability of the failure state of the automobile brake-by-wire system cannot meet the ASIL requirements. Furthermore, effective countermeasures can be taken to optimize the design of the system architecture. Finally, the failure probability corresponding to the failure state of the car’s brake-by-wire system is reduced to 7×10-14.

At present, the network virus defense is facing a more severe form, especially the emergence of various network viruses, which leads to the emergence of network security incidents in an endless stream, causing more serious damage and loss to related industries and fields. The traditional network virus defense measures have some defects, such as information lag, data update slow and backward technology, which have been difficult to deal with the real virus threat. Based on this, this paper first analyses the utilization status and advantages of data mining tech, then studies the utilization of network virus defense based on data mining, and finally gives the specific development strategy of data mining tech of computer network virus defense.

With the continuous development of information technology, computers have been widely used in various fields of society, filled with rich information in the network, network security has been widely concerned. In view of the problem of insufficient network security, we must strengthen the application of security measures, among which information encryption technology is one of the important means to ensure network information security at the present stage. This paper mainly summarizes the information encryption technology, analyzes the factors affecting network security, and puts forward effective protective measures to ensure the security of computer network.

Ultrathin ferroelectrics are of great technological interest for high-density electronics, particularly non-volatile memories and field-effect transistors. With the rapid development of micro-electronics technology, there is an urgent requirement for higher density electronic devices, which need ultra-thin ferroelectric materials films. However, as ferroelectric films have becomes thinner and thinner, electrical spontaneous polarization signals have been found in a few atomic layers or even monolayer structures. The mechanisms of detection and formation of these signals are not well understood and various controversial interpretations have emerged. In this review, we summarized the recent research progress in the ultra-thin film ferroelectric material, such as HfO2, CuInP2S6, In2Se3, MoTe2and BaTiO3. Various key aspects of ferroelectric materials are discussed, including crystal structure, ferroelectric mechanism, characterization, fabrication methods, applications, and future outlooks. We hope this review will offer ideas for further improvement of ferroelectric properties of ultra-thin films and promotes practical applications.

Objective. Achieving high precision rapid serial visual presentation (RSVP) task often requires many electrode channels to obtain more information. However, the more channels may contain more redundant information and also lead to its limited practical applications. Therefore, it is necessary to reduce the number of channels to enhance the classification performance and users experience. Furthermore, cross-subject generalization has always been one of major challenges in electroencephalography channel reduction, especially in the RSVP paradigm. Most search-based channel selection method presented in the literature are single-objective methods, the classification accuracy (ACC) is usually chosen as the only criterion. Approach. In this article, the idea of multi-objective optimization was introduced into the RSVP channel selection to minimize two objectives: classification error and the number of channels. By combining a multi-objective evolutionary algorithm for solving large-scale sparse problems and hierarchical discriminant component analysis (HDCA), a novel channel selection method for RSVP was proposed. After that, the cross-subject generalization validation through the proposed channel selection method. Main results. The proposed method achieved an average ACC of 95.41% in a public dataset, which is 3.49% higher than HDCA. The ACC was increased by 2.73% and 2.52%, respectively. Besides, the cross-subject generalization models in channel selection, namely special-16 and special-32, on untrained subjects show that the classification performance is better than the Hoffmann empirical channels. Significance. The proposed channel selection method could reduce the calibration time in the experimental preparation phase and obtain a better accuracy, which is promising application in the RSVP scenario that requires low-density electrodes.

In order to enable the microgrid to meet the system load demand while performing economically optimal operation scheduling, this paper establishes an island-type microgrid model, which is optimized by using an improved immune particle swarm algorithm, and the inertia weight and learning the two parameters of the factor are improved. On the basis of the immune particle swarm algorithm, a power exponential function operator is added to the inertia weight to improve the search ability of the algorithm, in order to reduce the computing time, the dynamically adjusted learning factor is introduced to optimize the immune particle swarm algorithm the local search ability is stronger. Two examples are selected to verify the algorithm, the results prove that the method has better global convergence and local search capabilities and the convergence speed has been improved.

We study theoretically the generation of strong entanglement of two mechanical oscillators in an unresolved-sideband optomechanical cavity, using a reservoir engineering approach. In our proposal, the effect of unwanted counter-rotating terms is suppressed via destructive quantum interference by the optical field of two auxiliary cavities. For arbitrary values of the optomechanical interaction, the entanglement is obtained numerically. In the weak-coupling regime, we derive an analytical expression for the entanglement of the two mechanical oscillators based on an effective master equation, and obtain the optimal parameters to achieve strong entanglement. Our analytical results are in accord with numerical simulations.

The paper focuses on the sea surface wind speed retrieval and validation using the future SWOT data. Ka band backscatter coefficient and wind speed were simulated by using theoretical model of Quasi-specular scatter and the simulated position of observation point. The Ka band model function of incident angles from 1° to 4° was proposed based the form of KuLMOD2. Wind speed was retrieved by using Ka band model function, and the results of validation show that the RMSE (Root Mean Squared Error) is 0.35. Therefore, the wind speed retrieval was validated with the ECMWF, which showed good coincidence. Ka band model function was proposed for applicable to the future SWOT data.

Band renormalization effects play a significant role for two-dimensional (2D) materials in designing a device structure and customizing their optoelectronic performance. However, the intrinsic physical mechanism about the influence of these effects cannot be revealed by general steady-state studies. Here, band renormalization effects in organic superacid treated monolayer MoS2, untreated monolayer MoS2 and few-layer MoS2 are quantitatively analyzed by using broadband femtosecond transient absorption spectroscopy. In comparison with the untreated monolayer, organic superacid treated monolayer MoS2 maintains a direct bandgap structure with two thirds of carriers populated at K valley, even when the initial exciton density is as high as 2.05 × 1014 cm−2 (under 400 nm excitations). While for untreated monolayer and few-layer MoS2, many-particle induced band renormalizations lead to a stronger imbalance for the carrier population between K and Q valleys in k space, and the former experiences a direct-to-indirect bandgap transition when the initial exciton density exceeds 5.0 × 1013 cm−2 (under 400 nm excitations). Those many-particle induced band renormalization processes further suggest a band-structure-controlling method in practical 2D devices.

In this study, a simple and convenient method of demulsification-induced fast solidification was demonstrated to in situ prepare Zn/RE-906 polyurethane acrylate (906) polymer film layer structure composites. The mechanical connection strength between 906 polymer films and Zn, that is, adhesive strength, was characterized via lap shear testing. The adhesive strength between the 906 polymer films and Zn is adjustable by adjusting the adhesive time and adhesive temperature. The 906 polymer films exhibited an outstanding adhesive performance within the temperature range from room temperature to 175?. The 906 polymer films exhibited excellent adhesion capacity with Zn, making them attractive for applications in the automotive and aeronautic.

With application of high-speed power line carrier communication (HPLC), some problems are emerging such as network outliers, low success rate of power outage reporting and short single hop communication distance. Wireless communication (RF) can effectively solve these problems and thus become an effective complement to HPLC. For OFDM based wireless communication in HPLC&RF dual mode system, a channel estimation method is proposed. Compared with LTF-based and pilot-based channel estimation methods applicable to cases with few and multiple physical layer load symbols respectively, the proposed method can be applied in all cases. When the number of symbols is small, it outperforms pilot-based method by 2~3 dB and is still better than LTF-based method. When the number of symbols is large, it outperforms LTF-based method by 2~5 dB and still better than pilot-based method.

In order to meet the practical requirements of the balun structure while improving the output balance and isolation, an improved planar broadband balun model was designed based on Marchand balun. Aiming at the situation that the phase transition speed of the two output terminals is not synchronized due to the input transient transmission of the microstrip line, the method of compensating the microstrip line by loading the ground short-circuit ends of the two couplers is used to adjust the phase speed to synchronization and thereby improve the output balance. At the same time, a single-layer planar structure is used to reduce the vol-ume of the balun structure, and isolation circuits are introduced at the input and output ends to optimize the isolation. Simulation verification based on the model showed that the minimum isolation at the working frequency of 2.969GHz-3.702GHz was reduced to -24.53dB, and the phase imbalance at the output fluctuated between+0.32 °and -0.99 °, and the amplitude unbal-ance degree does not exceed 0.08db. The balance does not exceed -0.08dB. Both output bal-ance and isolation have been significantly improved.

Global warming, caused by rising concentration of carbon dioxide and other greenhouse gases, has made great damage to the earth ecological environment. Low carbonization has become an inevitable trend of social development. Developing low-car bon economy, promoting low-carbon life and reducing carbon emissions have become the target and responsibility of all countries in the world. Tourism is a comprehensive human activity, a comprehensive experience of material civilization and spiritual civilization. Low-carbon tourism, as a new type, is a practical need to protect ecological environment and realize sustainable development. Starting from connotation of low-carbon as well as low-carbon tourism, the paper fully analyzes and expounds the necessity of developing low-carbon tourism. On this basis, it puts forward some concrete implementation paths for developing low-carbon tourism.

In the current paper, the ageing and de-ageing phenomena in ferroelectric ceramics are modelled by a Landau-type model based on the internal bias field theory. A new phenomenological term for the internal bias electrical field is added into the free energy function to simulate the phenomenon of lattice symmetry during the ageing phenomenon. The simulations for both ageing and de-ageing phenomena are successfully presented in the current paper. The hysteretic behaviours of the ageing and de-ageing phenomena are captured very well by the proposed model.

Many structural health monitoring (SHM) systems of actual tunnels are underused, with abstract data, chaotic information and the diagnostic results beyond comprehension. It is necessary to establish the visual connection between the visualization of monitoring network and massive structural information of tunnels. To address this issue, this study proposed a structural visualization method based on the panoramic virtual reality technology, combining the panoramic spherical image and the real-time monitoring data of tunnel obtained from SHM system. First, a software system for structural safety monitoring of an actual shield tunnel was developed on the basis of the combination of the panoramic visual technology and B/S (Browser/Server) architecture system. Second, the panoramic modelling method for specific tunnel structure environment was discussed in detail, and then the mechanism of data transmission and information access in panoramic virtual reality environment was investigated deeply. Finally, in view of the demands of practical application, the function modules of the abovementioned software system were described. Some key issues of how to develop each software module using the panoramic virtual reality technique were analysed e.g., online geographic information and cloud platform management. The results show that the panoramic virtual reality technology completely meets the needs of real-time processing, information management, virtual roaming and maintenance management in tunnel structural safety monitoring.

Internal friction combined with SEM, DSC and XRD measurements was first applied so far to investigate phase transformation behaviors of Fe-Al elemental powders. Special attentions are concentrated on the influence of mechanical ball-milling on microstructure transition during sintering process. A tailored solid solution degree of the Fe-Al powder mixture can be obtained by mechanical ball-milling for different time. Four typical internal friction peaks are observed as termed P1, P2, P3 and P4 peak respectively for Fe-Al ball-milled powder compact. While for no ball-milled one, only P2 and P4 peaks appear. It was rationalized that the four internal friction peaks are probably associated with the formation of FeAl3, Fe2Al5, FeAl2 and FeAl respectively because of solid diffusion reaction during sintering process. In addition, increasing ball-milling time results in enhancement of solid solution degree owing to refined powder particle and substructure as well as increased solid defect density and interfacial area, and thus phase transformation and corresponding internal friction peaks shift to a lower temperature. The absence of two internal friction peaks in no ball-milled one is ascribed to lower solid solution degree.

The temperature field and flow field during the selective laser melting (SLM) process of Mg-3.4Y-3.6Sm-2.6Zn-0.8Zr alloy were simulated by using a re-developed Fluent 17.0 commercial finite volume method (FVM). The surface tension, Marangoni convection, and the laser heat source with Gaussian distribution are taken into account. The effects of laser power and scanning speed on the temperature and the size of the molten pool are studied, and the influence of line energy density (LED) on the flow and densification behavior of the molten pool is also discussed. It shows that the temperature and the size of the molten pool are positively correlated with the laser power, and negatively correlated with the scanning speed. The LED affects the flow of the molten pool and the movement of the bubbles, thereby affecting the densification behavior. For an optimized laser power of 50 W and scanning speed of 0.4 m s−1, the bubbles can escape smoothly, the existence time of the molten liquid is 355.58 μs and a molded part with the optimal density (95.98 ± 1.4)% is obtained. The experimental and numerical simulation results are in good agreement. It is concluded that a laser power of 50 W, and a scanning speed of 0.4 m s−1 are the optimal process parameters.

To understand the biogeochemical processes associated with soil organic matter (SOM) decomposition, we analyzed the SOM contents, the δ13C and δ15N values of the dominant species foliage, litter and SOM from soil samples for five soil profiles with different vegetation conditions in the Loess Plateau, Northwestern China. Results showed that the amounts of soil organic carbon (SOC) and total nitrogen (TN) mainly concentrated on the surface soil and differentiated according to the vegetation conditions in the following order: broad-leaved forest > coniferous woodland > shrub forest > grassland > wasteland. SOC and TN contents decreased with depth and varied in the ranges of 1.1–31.2 g/kg and 0.3–3.7 g/kg, respectively. Compared with the other regions, the 13C and 15N were enriched and the δ13C and δ15N values of topsoil SOM respectively increased in the ranges of 0.5%o–3.2%o and 0.7%o–4.6%o during litter degradation to SOM on the surface soil, which was controlled by SOM turnover rates. This result indicates that the effect of isotopic fractionation was obvious during the transformation of SOM from plant debris to SOM in topsoil, which resulted in great increments of SOM δ13C and δ15N. Litter inputs lowered the surface soil δ13C and δ15N values while decomposition increased δ13C and δ15N values in deeper soil. Foliage and litter inputs averaged 1.0% and 1.3% δ15N and -28.3% and -27.0% δ13C, respectively. The five soil profiles with different vegetation conditions had similar characteristics in variations of SOM δ13C and δ15N and increased with depth, respectively. However, the patterns of δ13C in our sites were less pronounced than the patterns of δ15N primarily because the discrimination against 13C during organic matter decomposition is weaker than the discrimination against 15N. Except for the shrub profiles, significant correlations were found between the two stable isotopes, 15N and 13C. Combined with information on SOM contents, the variations of the isotopic values of SOM showed a mixing process of litter inputs between different soil profiles. Two controls of soil isotopic compositions were established: new litter inputs and overall isotopic fractionation during decomposition. In conclusion, the overall isotopic fractionation during decomposition left residual soil N and C enriched in 15N and 13C, explaining the high δ15N and δ13C values observed in deeper soil.

Although labile soil organic carbons (LSOC) represent only a small part of soil organic carbon (SOC), they are an important source of energy for the belowground portion of the ecosystem and play a crucial role regarding changes in the quality of soil organic matter (SOM). This study measured and compared the content of LSOC and SOC in limestone soil (developed from limestone) and sandstone soil (developed from sandstone) in the karstic area of southwest China to better understand the impacts of different soil types on LSOC (water-extractable and readily oxidizable organic carbon) and evaluate the existence of a possible relationship between LSOC and SOC in the soil. The results demonstrated that the amounts of SOC, soil readily oxidizable carbon (SROC), and soil water-extractable organic carbon (WEOC) (hot-water extractable organic carbon (hot-WEOC) and cold-water extractable organic carbon (cold-WEOC)) were the highest in the surface soil and decreased with increasing depth in both types of soil profiles. In addition, the content of SOC and LSOC were significantly higher in the limestone soil profiles than those in the sandstone soil profiles. This may be as a result of the occurrence of higher pH values and higher content of calcium, magnesium, and clay minerals in the limestone soil than in the sandstone soil. The proportions of WEOC in total SOC extracted at 25°C and 70°C in the sandstone soil profiles displayed higher average values of 0.040% and 0.527%, respectively, whereas the limestone soil profiles displayed lower average values of 0.015% and 0.255% for the WEOC extracted at 25°C and 70°C, respectively. Regarding the SROC content, both soil profiles showed higher values than WEOC content, ranging from 39.4%–55.2%. The results also showed that for the two types of soils significant correlations were found between samples of SROC, WEOC, and SOC (P < 0.01). Among the LSOC, the hot-WEOC showed clear differences between different soil types, and significant relationships were observed for not only SOC but also SROC. The correlation coefficients between hot-WEOC and SOC or SROC were higher than those between cold-WEOC and SOC or SROC. This study, therefore, suggests that hot-WEOC could be a useful indicator of changes in the quality of SOM in different soil types.

We demonstrate a novel polarization control system based on a gradient descent algorithm, applied to a 450-km optical frequency transfer link. The power of the out-loop beat note is retrieved by controlling the polarization state of the transferred signal, with a recovery time of 24 ms, thereby ensuring the long-term evaluation of the fiber link. As a result, data utilization is enhanced from 70% to 99% over a continuous measurement period of ∼12 h. A fractional transfer instability of 7.2 × 10−20 is achieved at an integration time of 10000 s. This work lays the foundation for the comparison of a remote optical clock system via a long-haul optical fiber link.

The NO3 radical is one of the important indicators of atmospheric oxidation capability at night, and its accurate detection has been extensively investigated. High reflectivity cavity instruments, such as cavity ring-down spectroscopy (CRDS) and cavity-enhanced absorption spectroscopy (CEAS), are generally employed for NO3 radical detection. However, sampling detection easily adsorbs radicals on surfaces, which causes complications and even additional loss. According to the chemical conversion relationship between NO3 radical and NO2, a method of absolute calibration different from the previous relative calibration method is applied by combining the CRDS and CEAS instruments for the NO3 radical and NO2, respectively. Experimental results show that the overall transmission efficiency of the NO3 radical for the CRDS instrument is approximately 75% ± 9% at a flow rate of 6.5 SLPM. Comparative experiments between the two methods are conducted to estimate the accuracy of this method. The achieved results indicate that absolute calibration is a reliable and feasible method for radical calibration in the laboratory. Furthermore, the absolute calibration method has the potential to realize accurate real-time calibration in field measurements.

We demonstrate a 300-km+200-km cascaded coherent phase transfer via fiber link. The transfer is divided into a 300-km span and a 200-km span with independent phase locking loops, aiming to extend the phase control bandwidth of the whole link. The phase noise and transfer instability of the cascaded transmission are investigated and compared with those in the case of a single-span 500-km transfer. We achieve the transfer instabilities of 1.8 × 10−14 at 1 s, 8.9 × 10−20 at 104 s for the 300-km + 200-km cascaded transmission, and 2.7 × 10−14 at 1 s for the 500-km single-span transfer.