This paper reports the first documentation of ultramafic rocks exposed in the northern segment of Wuchuan-Sihui fault in Guangdong. These ultramafic rocks, classified as olivine pyroxenite, occur as a dike within early Late Jurassic (≈160 Ma) granites of the Dadongshan pluton. Zircon U-Pb LA-ICPMS analysis of the olivine pyroxenite yields an age of 160±2 Ma, suggesting that zircons were captured from the surrounding granite during dike intrusion. Additionally, the ⁴⁰Ar/³⁹Ar plateau age of biotite from the olivine pyroxenite is 135±1 Ma, indicating that the dike emplacement occurred at the Early Cretaceous, corresponding to a significant extensional event in South China. Whole-rock major element geochemical analysis reveals enrichment in K and Al, relatively high Ti and P contents, and moderate Mg. SiO₂ content (43.78%–44.80%) of the sample is less than 45%. These features classify the rock as an ultramafic rock, predominantly exhibiting characteristics of alkaline basalt. Whole-rock trace and rare earth element (REE) analyses show enrichment of Nb, Ta, Th, U, LILE (large ion lithophile elements), and LREE (light REE), along with pronounced fractionation between light and heavy REE. The rock displays signatures of high-Nb OIB-type mafic rocks (Ocean Island Basalts), suggesting a metasomatized asthenospheric mantle source modified by subduction components, primarily forming in an intraplate extensional tectonic setting. Combining fault activity, geochronological and geochemical characteristics, we propose that during the Early Cretaceous, the tearing and delamination of the subducted Paleo-Pacific Plate beneath South China created metasomatized asthenospheric mantle sources enriched for OIB-type mafic rocks. Subsequently, intracontinental extension caused crustal thinning, while the lithosphere-penetrating Wuchuan-Sihui Fault facilitated rapid ascent of OIB-type mafic magmas along the fracture system. These magmas ultimately crystallized to form the Jiangwan olivine pyroxenite, with intraplate geochemical affinities. 

To develop the Scale of Paranoid Personality Organization Type (SPPOT) and test its reliability and validity, the initial scale was developed based on the diagnostic standard in the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) of PPD, personality organization theory and the clinical behavior samples. Sample 1 of 683 effective participants filled out SPPOT and Millon Clinical Multiaxial Inventory-III (MCMI-III). Sample 2 of 484 subjects filled out SPPOT and Inventory of Personality Organization (IPO). 60 effective participants were involved in checking of test-retest correlation at 5-week intervals. The final version of SPPOT had 18 items (including 4 lie detection items) and 3 dimensions: Hostile (Ht), Distrust (Dt) and Paranoid Thinking (PT), which cumulatively explained 42.28% variance. The scale had good structural validity (χ²/df=1.1, RMSEA=0.01, GFI=0.98, NFI=0.95, CFI=0.99). Cronbach’s α of SPPOT, Ht, Dt and PT was 0.77, 0.64, 0.35 and 0.64 respectively. The intraclass correlation coefficient (ICC) of Ht, Dt, PT and SPPOT were 0.79, 0.72, 0.63 and 0.75 (P<0.001). The criterion-related validity with MCMI-III and IPO sounded acceptable (r=0.13–0.31, P<0.001). SPPOT generally meets the measurement requirements for paranoid personality types and levels of personality organization.

Based on the characteristics of space particle radiation in the sun-synchronous orbit (SSO), a space particle radiation effect comprehensive measuring instrument (SPRECMI) was installed on the orbital platform of upper stage of Chinese CZ-4C carrier rocket for obtaining the high-energy proton energy spectra, linear energy transfer (LET) spectra of particles, and radiation dose rate. The detection results can be used for in-orbit fault analysis and operational control management of spacecraft and serve as reference data for component validation tests. After SPRECMI’s development, accelerator calibration and simulations were conducted, and the results demonstrated that the measured indicators such as high-energy protons, total radiation dose, and LET spectrum all met the requirements of detection range, accuracy, and sensitivity. Furthermore, the in-orbit flight test revealed that the detection results of the load components were consistent with the physical characteristics of the particle radiation environment of the spacecraft orbit.

An edge computing system was designed by the spiking neural network chip PAICORE2.0 of Peking University, in conjunction with Xilinx ZYNQ. However, the software encoding and frame generation processes on the processing system (PS) side is slow and limits the performance of the system. Therefore, a hardware acceleration method is proposed. The software encoding and frame generation processes, which is serially executed on the PS side, is moved to the data path on the programmable logic (PL) side for pipelined parallel execution. The hardware acceleration unit mainly consists of highly parallel convolution units, parameterizable spiking neurons, width-balanced data buffers and other modules. The results show that the method removes the time overhead of software encoding and frame generation without increasing the data path transmission delay. In the example of CIFAR-10 image classification, compared with software encoding and frame generation, the hardware encoding and frame generation module results in only a marginal increase in resource utilization — 9.3% more Look-Up Tables (LUTs), 3.7% more Block RAMs (BRAMs), 2.6% more flip-flops (FFs), 0.9% more LUTRAMs, and 14.9% more digital signal processors (DSPs), as well as a 14.6% increase in power consumption. However, it achieves approximately an 8.72-fold improvement in inference speed.

In order to improve the accuracy of trajectory tracking control of wheeled mobile robot (WMR), a backstepping optimized double sliding mode control strategy was proposed. Initially, based on the kinematics and dynamics model of WMR, the kinematic backstepping sliding mode controller and dynamic backstepping integral sliding mode controller are designed. The stability of the designed controllers is proved by Lyapunov theory. Then particle swarm optimization (PSO) algorithm is used to optimize the controller parameters. Finally, considering the external disturbance and system input saturation, Matlab/Simulink is used to verify the control strategy. The results show that the proposed control strategy not only ensures the robustness and real-time performance of the system, but also improves the control accuracy of the system.

To monitor the space environment and its effects in the low-Earth sun-synchronous orbit of China’s FY-3 satellite, a comprehensive detection technology based on the type Ⅱ loads of the space environment monitor is proposed. In the process of ground development, various technical indicators of the space environment comprehensive detection payload have been calibrated and experimentally verified by different methods such as standard radiation source, equivalent signal source, particle accelerator and standard magnetic field. The results show that the multi-direction full-spectrum particle detection achieves an energy range of 30 keV–300 MeV, with the accuracy of ≤10%. The magnetic field detection realizes the measurement range of −65023–+65023 nT, with the accuracy of ≤0.73 nT. The potential detection realizes the measurement range of −32.4–+23.7 kV, with the sensitivity of ≤10V. The detection of radiation dose realizes the measurement range of 0–3×104 rad (Si), with the sensitivity of ≤8.3 rad (Si). Through comprehensive observation of particle radiation environment, change of in-situ magnetic field vector, radiation dose accumulation and change of satellite surface potential in satellite operation orbit, the space environment monitor provides necessary data support for space activities, satellite design, space science research and space weather early warning and prediction. 

In order to understand the research hotspots and frontier directions of Rauvolfia in the field of traditional Chinese medicine, the literature about chemical composition, pharmacological activity and clinical application were searched in CNKI and Web of Science databases. CiteSpace 6.1.R6 was used for authors and research institutions co-occurrence, keyword co-occurrence, keyword clustering and keyword timeline mapping and analysis. A total of 173 effective Chinese articles and 356 effective English articles were included, and the annual number of articles showed a fluctuating upward trend overall. The authors with the most publications in Chinese and English were CAO Fuxiang and Stockigt J, respectively. The institutions with the most publications were Central South University of Forestry and Technology and Johannes Gutenberg-Universität Mainz, respectively. The analysis of keywords showed that the research direction of Rauvolfia mainly focused on cultivation, chemical composition extraction, identification and pharmacological activity analysis. Chinese literature focused on the cultivation of various Rauvolfia. English literature focused on the extraction and identification of strictosidine synthase and other chemical components, as well as the antibacterial and antioxidant effects of pharmacological activities of various chemical components. How to rationally use the chemical components of Rauvolfia and study their pharmacological activities and clinical applications are the main trends in the future.

Using the System for Observation of Play and Recreation in Communities (SOPARC), 36 observations were conducted in three parks in Shenzhen, China, to count the physical activity levels of 12297 visitors in 78 target sports grounds. The gender and age differences in the physically active populations were analyzed in formal and informal sports grounds. The results indicate that the physical activity levels of children and adolescents were significantly higher than those of middle-aged and elderly individuals, and males exhibited significantly higher physical activity levels than females. Among formal sports grounds, the physical activity levels on soccer fields, basketball courts, tennis courts, and ping-pong tables were significantly higher than those on other sports grounds. In informal sports grounds, the physical activity levels of children’s non-apparatus activity spaces were the lowest. Some informal sports areas supported a greater variety of physical activities, such as dancing, badminton, soccer, and kite-flying, on park squares and open grassy areas. The research findings can provide environmental strategies for constructing urban parks that are conducive to enhancing physical activity levels.

This study summarizes and reviews Chinese medicinal mangroves’ chemical constituent and medicinal effect researches in the past 50 years. Since 2000, the research on medicinal mangroves has increased exponentially, and the most attention is paid to Pongamia pinnata. 27 kinds of medicinal mangroves have been confirmed, and the main medicinal components include terpenoids, flavonoids, steroids, quinones, carbohydrates, phenylpropanoids and alkaloids. Most medicinal mangroves have anti-tumour, antioxidant and anti-inflammatory effects, and some mangrove plants have unique medicinal effects, including anti-depression and anti-Alzheimer's disease. Existing research mainly focuses on the medicinal effects of mangrove plants, but the pharmacological mechanism needs further study. In view of the problems in medical components and the pharmacological effect of mangroves, some suggestions are put forward for their further development and utilization.

A low-resource anisotropic magnetoresistance-based vector magnetometer for space science applications is presented. The proposed vector magnetometer can detect magnetic fields in a range of ±65000 nT, has a –3 dB bandwidth of DC to 10 Hz, and a noise power spectral density of ≤0.2 nT/Hz^1/2@1 Hz. Furthermore, the device has a non-linearity error of ≤3.6%oo over the entire range and non-orthogonality error of ≤1.2%oo. The vector magnetometer was equip on a Chinese Feng-Yun meteorological satellite (FY-3E) whose orbit was a sun synchronous orbit. The first in-flight science results show that the sensor can detect transient physical signals with amplitudes of 20–60 nT.

In order to improve performance with stable power consumption, based on ECore embedded processor platform, which had a single-issue in-order pipeline structure originally, two lightweight superscalar structures were introduced: selective register renaming and dual issue of compact instructions. The experimental data showed that the average utilization of dual-issue structure reached 28% by adding dual issue logic. Using selective register renaming, the average stalling rate caused by name hazard reduced from 7.2% to 0.6%. Compared with the original design, the IPC increased 4.8% and the power consumption only increased 2.5%.

Object detection algorithms based on deep learning use big models are difficult to be deployed at the edge. Taking YOLO (you only look once) object detection algorithm as an example, an acceleration module based on an ARM+FPGA heterogeneous platform is proposed. The FPGA chip accelerates the forward process of the compressed model while ARM is responsible for process scheduling. Experiment results show that the peak performance of the system reaches 425.8 GOP/s under 200 MHz working frequency. The system on a Xilinx ZCU102 board achieves a frame rate at 30.3 fps, while the power consumption is 3.56 W. It is also configurable.

A hardware accelerator of object detection algorithm based on FPGA is designed to accelerate the computation of SSD object detection algorithm. Loop tiling and loop unrolling are used to optimize the loops of convolution and pooling, and can be re-configurated in any parallelism. In order to reduce data transmission time, feature maps are reorganized based on AXI, without any hardware resource overhead. After implementing the hardware accelerator to Xilinx ZCU development board, it can accelerate SSD at a performance of 534.72 GOPS, and the inference time is 113.81 ms.

In order to improve the performance of post training quantization model, a quantization preprocessing method based on outlier removal is proposed. This method is simple and easy to use. The outliers of weight and activation value are removed only through simple operations such as sorting and comparison, so that the quantization model loses only a small amount of information and improves the accuracy. The experimental results show that the performance can be significantly improved by preprocessing with this method before using different quantization methods.

Aiming at the problems of long inference time and poor effect of the compression model obtained by the current mainstream pruning methods, an easy-to-use and excellent layer pruning method is proposed. The original convolution layers in the model are transformed into fusible residual convolutional blocks, and then layer pruning is realized by sparse training, therefore a layer pruning method with engineering ease is obtained, which has the advantages of short inference time and good pruning effect. The experimental results show that the proposed layer pruning method can achieve a very high compression rate with less accuracy loss in image classification tasks and object detection tasks, and the compression performance is better than the advanced convolutional kernel pruning methods.

Using the seismic data of three underground nuclear tests and three nearby natural earthquakes, the focal seismic moment tensor is obtained by inversion, and the underground nuclear explosion is identified by matrix decomposition method. The results show that there are obvious explosion sources (EXP), compensated linear vector dipole (CLVD) source and double couple (DC) source in the source of underground nuclear explosion earthquake. The physical mechanism of CLVD is medium rupture caused by explosion, which accounts for a large proportion of underground nuclear explosion sources. Compared with underground nuclear explosion, natural earthquake is generally shear dislocation mode, and DC accounts for a large proportion of its source.

Wafer-to-wafer bond technology has breakthrough semiconductor manufacturing from 2D to 3D, but the bonded wafer brings more locating and patterning rules, it is too complex to layout the frame cells by traditional floor plan arrangement. This article provides a new floor plan arrangement method in face-to-face bonding product. It could setup all floor plans at same time only by flipping the motherboard. The new method is introduced. Final result with new method’s benefit is shown based on actually bonding product taping out procedure.

A three-dimensional hydrodynamic-water quality model of Lake Dianchi was used to simulate the dynamic process of lake hydrodynamics and water quality, identify the characteristics of dissolved oxygen (Do) in the lake water. Combined with the setting of the external load reduction scenario, the effects of dissolved oxygen on the endogenous release of sediment and the cycle of nitrogen and phosphorus were explored. The results are conckyded. 1) The severe hypoxia in Lake Dianchi from June to September is caused by a combination of algae outbreaks and obstructed oxygen transport in the water. 2) Dissolved oxygen regulates the release of nitrogen and phosphorus nutrients in the sediment, and then significantly affects the concentration of nitrogen and phosphorus in the bottom water. 3) The improvement of the hypoxia condition at the bottom of the lake has high requirements on the reduction of external load. 4) The dissolved oxygen concentration at the phosphorus absorption-release equilibrium point of the sediment is about 3.3 mg/L, and the change in nitrogen concentration in Lake Dianchi is more susceptible to external load.

The development of 3D land seismic data acquisition in the direction of wide azimuth and high density will lead to huge dataset. The classical first arrival time tomography algorithms are not suit for processing huge seismic dataset due to very high memory request and computing time cost. In order to solve this problem, the authors develop an optimal mathematical formula from the classical first break travel time tomography method to avoid the memory occupation that required by Frechet derivative matrix and Hessian matrix, and reduce the time cost of computing Hessian matrix inversion. This method can efficiently solve the tomography inversion problem for huge datasets. It is suitable for huge and high-density land seismic exploration, and not affect the dataset and model accuracy. It is easy for parallel processing. Both the model and real data examples confirm the effectiveness of this method. It can provide reliable tomographic results for static correction when the first breaks reaches a certain amount.

Using data from 690 meteorological observatories and GIMMS NDVI 3g data from 1982 to 2014, trend analysis, wavelet partial cross-correlation analysis, partial correlation analysis and lag analysis were used to explore the change rule of NDVI during the growing season (May to October) and its relationship with climate in North China and the adjacent areas in the past 33 years. The results showed that the average growing season NDVI increased from 0.44 in the 1980s to 0.49 in the 2010s. NDVI in the growing season increased rapidly in the central part of the research area, but decreased in the northwest desert area. The increase of NDVI in the growing season of the research area was benefited from the increase of temperature and precipitation, and the influence of precipitation was greater. NDVI of the research area was positively correlated with the temperature in most areas. Except for the southeastern part of the study area, NDVI and precipitation had strong positive correlation. At 15-day resolution, the response of NDVI to temperature in the growing season in most areas did not have obvious lag or was lagged in one period (15 days), and the response to precipitation was lagged about 1–2 periods (15–30 days). Therefore, in general, vegetation growth in North China and the adjacent areas responded more rapidly to temperature than precipitation.

Through the software of optical character recognition (OCR), this study sorts out seismic phase report of seismic stations worldwide from 1918 to 1970, earthquake location and focal mechanisms (fault plane solution) of part of the earthquakes are measured in Asia and nearby areas at that time. Specific work is carried out in two aspects. 1) Using arrival time and arrival-time difference in 1918?1970 from International Seismological Summery (ISS) and EHB Bulletin, the relocation of 338 earthquakes are calculated, and 316 among them are reliable. 2) Utilizing P wave initial motion in 1933?1970 from ISS and EHB Bulletin, the focal mechanisms of 244 earthquakes are calculated, and 209 among them are reliable. Based on global seismic network observation, the focal mechanisms of modern strong earthquakes in Asia from 1918 to 1970 have been enriched. Another important significance of this study is to provide a set of feasible methods for the study of modern earthquakes, which can be instructive in other regions or in other magnitudes.

In order to improve the efficiency and accuracy of the inversion of Rayleigh wave dispersion curves near the surface, fast scalar transfer algorithm which has the characteristics of high computational efficiency is introduced to calculate the forward theoretical value of Rayleigh wave dispersion curve. The performances of genetic algorithm (GA), simulated annealing algorithm (SA) in the inversion of Rayleigh wave dispersion curves before and after adding linear constraints are compared. On this basis, linear constraints are added to GA and SA to improve the speed of convergence, and Monte Carlo method (MC) with fast computing speed is used to identify the types of formation as a supplementary means. Then the inversion results obtained by GA are taken as the initial state of SA as well as narrowing search scope appropriately, and this kind of joint inversion is carried out to overcome the premature problem of GA. Using the above method to calculate the three-layer model, noisecontaining data and actual model of the work area. The results show that the method above is efficient, accurate and stable, and it has strong ability of global optimization and anti-noise ability to a certain extent.

A nonparametric regression — random forest model for the estimation of fractional vegetation coverage (FVC) in a complex topographic area is presented based on low-altitude unmanned aerial vehicle (UAV) hyperspectral imagery. In order to collect a large number of sufficient training samples required for random forest algorithm, the UAV equipped with an optical camera was used to vertically capture the images of land covers in several inaccessible areas such as high mountains, water body and densely forested areas, to increase the density of the ground sampling. The RGBVI (red-green-blue vegetation index) was calculated first and then the Otsu method was adopted to extract the FVC values of the samples from the UAV optical images and ground photos. After that, the hyperspectral images captured by the UAV GaiaSky-mini2 hyperspectral imaging system in the Youlougou Mining area, Chayouzhong County, Inner Mongolia on August 16?18, 2018 were used to extract feature variables, and this feature set was filtered by recursive feature elimination algorithm based on the importance of the variables. On the basis of the optimized feature set and extended training samples using the proposed UAV-ground cosampling approach, the random forest estimation model was constructed to estimate the FVC in the study area. Results indicated that the model achieved a determinant coefficient (R²) of 0.923 and a RMSE of 0.087 on the testing sample set and outperformed the commonly used Pixel Dichotomy method. It can be used in the fast and accurate monitoring of vegetation dynamics in mining areas.

The fitting training of neural machine translation is easy to fall into a local optimal solution on a lowresource corpus such as Uyghur to Chinese, resulting in the translation result of a single model may not be a global optimal solution. In order to solve this problem, the probability distribution predicted by multiple models is effectively integrated through the ensemble strategy, and multiple translation models are taken as a whole. At the same time, the translation models with opposite decoding directions are integrated by the reordering method based on cross entropy, and the candidate translation with the highest comprehensive score is selected as the output. The experiment on CWMT2015 Uighur-Chinese parallel corpus shows that proposed method has 4.82 BLEU values improvement compared with a single transformer model.

To solve the topic missing problem of text generated by computers, this paper proposed a new discourse-level text generation method based on topical constraint. Providing a short topic description, the approach extracted several topic words from the text, then extended and clustered the keywords to form topical planning which were used to restrain the generation of each paragraphs. The model improved the attention based recurrent neural network form three aspects including topic distribution, attention scoring function and topic coverage generation. In experiments, the proposed method was compared with benchmark models such as Char-RNN, SC-LSTM and MTA-LSTM on three real datasets, three improvement strategies were verified and analysed independently. Experimental results show that proposed model is more efficient than benchmark models on human and BLEU metrics, and the generated text can catch the topic more effectively.

As the impedance of the conventional plasma etching system at the edge of the wafer is not consistent with that at the center of the wafer, the movement trajectory of ions at the edge of the wafer is deviated and it is difficult to meet the more stringent requirements on etching process uniformity and high aspect ratio. A method to optimize the movement direction of edge ions by adjusting the impedance of the wafer edge is proposed which can continuously and real-time adjust the movement trajectory of edge ions and control the direction of edge ions. The results show that the direction of ion movement can be optimized to be perpendicular to the surface of the wafer, the uniformity of the edge etch rate is optimized, and the vertical etching morphology is obtained.

Based on the data from the array deployed by Peking University around high-speed rail in Baoding City, Hebei Province, China, in order to obtain spectra with higher signal to noise ratio at farther stations, the paper considers the variation of train type and stacks the spectra of three components of high-speed rail seismic signal produced by the same type trains on the same station. Using the clustering algorithm, the regular pattern of how the three component spectra vary with the train type and station position is obtained. Based on the characteristics of high-speed rail seismic spectra and their variation, we propose the concept of 4D ground-frequency map, and discuss its practicability in monitoring the status of high-speed rail and its surrounding media.

The seismic signal propagating along the viaduct of a high-speed rail when the train is approaching or departing is extracted by cross-correlation method. Stable average cross-correlation function can be obtained by stacking the cross-correlation functions of different trains. The average cross-correlation function can be used as the characteristic quantity of the wavefield produced by high-speed rail. This quantity has potential to monitor the structural changes of the high-speed rail viaduct.

Employing a total of 10461 seismic records induced by 951 high-speed trains recorded by 11 shortperiod stations of a temporary array deployed by Peking University under the high-speed railway viaduct, we observe how the spectral characteristics vary with the speed and model of the train as well as the rail and groundsill by using a clustering algorithm K-Means. For a high-speed train in uniform motion, the spectrum of the produced seismic wave is mainly composed of nearly equally spaced peaks and its fundamental frequency is equal to the ratio of the train speed to the carriage length. By aligning the fundamental frequency, the influence of the train speed is reduced to make the spectrum pattern time-independent and easy for comparison. Clustering results show that the spectra of the high-speed rail seismic events have stable patterns when the train model, rail and groundsill conditions keep the same; the stable spectrum patterns change significantly with the change of the train model, rail and groundsill conditions. The monitoring of the stable spectral characteristics might possibly be used in safety control of high-speed rail.

In order to invert shallow or deep underground structure by using high-speed train source, the far-field wave field excited by high-speed train is simulated by wave front superposition, solving acoustic wave field and elastic wave field in semi-infinite space. During the calculation, a pier of high-speed rail is regarded as a point source. The results of wave field calculated by convolution of different types of source time function and Green’s function show that the wave field corresponding to the low frequency source time function of pier static response considering the influence of high-speed train deadweight is similar to the actual record.