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A variable frequency hopping (VFH) signal is a kind of frequency hopping (FH) signal that varies both in frequency and dwell time. However, in radio surveillance, the existing methods for unidentified signals using VFH cannot be effectively handled. In this paper, we proposed an improved joint analysis method based on time–frequency domain features, which adopts multi-level processing to solve the time–frequency domain feature analysis problem of the VFH signal. First, the received signal is pre-processed by Short-Time Fourier Transform (STFT) and binarization, and a highly discriminative time–frequency image is obtained; then, the fixed frequency signal is removed based on the feature of connected domains, and the conventional frequency hopping (CFH) signal is removed by density-based spatial clustering of applications with noise (DBSCAN); finally, the overlapping region is cropped by the joint energy peak time–domain continuity properties. After the above multi-level joint processing method, the problem of VFH signal processing is effectively solved. The simulation result shows that the Mean Square Error (MSE) between the output results and the time–frequency image of the original VFH signal tends to be close to 0 when the Signal-to-Noise ratio (SNR) is 5 dB.

Magnetic field gradients interfere with the coherence of the atomic ensemble and degrade the performance of the spin-exchange relaxation-free (SERF) atomic magnetometer. In this paper, the influence of magnetic field gradients is incorporated into the response model of single-beam atomic magnetometer, and the theoretical models of transverse relaxation rate, spin polarization and scale factor are established. Based on this model, we find that magnetic field gradients in different directions can cause varying degrees of degradation in the performance parameters of the magnetometer. The magnetic linewidths under different light power and magnetic field gradients are measured using the designed dedicated magnetic field gradients coils, and the spin polarization and magnetic field gradients relaxation rate are obtained through fitting. An unevenness and deviation of the curve are also observed in the experiments, indicating the presence of the magnetic field gradient of approximately 2 nT/cm in the magnetic shields. Furthermore, in a magnetic field gradient environment of 20 nT/cm, the mean of the long-term sensitivity decreased by 3.5 times and the standard deviation increased by 11 times. It shows that the magnetic field gradients will not only affect the signal-to-noise ratio, but also make the magnetometer more vulnerable to external interference when working. The sensitivity and stability of magnetometer will be greatly reduced. The research in this article provides a theoretical and experimental basis for eliminating the influence of magnetic field gradients and improving the accuracy of magnetic field measurements.

The efficient and accurate prediction of urban travel demand, which is a hot topic in intelligent transportation research, is challenging due to its complicated spatial-temporal dependencies, dynamic nature, and uneven distribution. Most existing forecasting methods merely considered the static spatial dependencies while ignoring the influence of the diversity of dynamic demand patterns and/or uneven distribution. In this paper, we propose a traffic demand forecasting framework of a hybrid dynamic graph convolutional network (HDGCN) model to deeply capture the characteristics of urban travel demand and improve prediction accuracy. In HDGCN, traffic flow similarity graphs are designed according to the dynamic nature of travel demand, and a dynamic graph sequence is generated according to time sequence. Then, the dynamic graph convolution module and the standard graph convolution module are introduced to extract the spatial features from dynamic graphs and static graphs, respectively. Finally, the spatial features of the two components are fused and combined with the gated recurrent unit (GRU) to learn the temporal features. The efficiency and accuracy of the HDGCN model in predicting urban taxi travel demand are verified by using the taxi data from Manhattan, New York City. The modeling and comparison results demonstrate that the HDGCN model can achieve stable and effective prediction for taxi travel demand compared with the state-of-the-art baseline models. The proposed model could be used for the real-time, accurate, and efficient travel demand prediction of urban taxi and other urban transportation systems.

Chinese indigenous pig breeds in the Taihu Lake (TL) region of Eastern China are well documented by their exceptional prolificacy. There are seven breeds in this region including Meishan (MS), Erhualian (EHL), Jiaxing Black (JXB), Fengjing (FJ), Shawutou (SWT), Mi (MI), and Hongdenglong (HDL). At present, these breeds are facing a great threat of population decline, inbreeding depression and lineage admixture since Western commercial pigs have dominated in Chinese pig industry. To provide better conservation strategies and identify candidate genes under selection for these breeds, we explored genome-wide single nucleotide polymorphism (SNP) markers to uncover genetic variability and relatedness, population structure, historical admixture and genomic signature of selection of 440 pigs representing the most comprehensive lineages of these breeds in TL region in a context of 1228 pigs from 45 Eurasian breeds. We showed that these breeds were more closely related to each other as compared to other Eurasian breeds, defining one of the main ancestral lineages of Chinese indigenous pigs. These breeds can be divided into two subgroups, one including JXB and FJ, and the other comprising of EHL, MI, HDL, MS, and SWT. In addition, HDL was highly inbred whereas EHL and MS had more abundant genetic diversity owing to their multiple conservation populations. Moreover, we identified a list of candidate genes under selection for body size and prolificacy. Our results would benefit the conservation of these valuable breeds and improve our understanding of the genetic mechanisms of body size and fecundity in pigs.

In this paper, we present a novel event-triggered control mechanism for nonlinear systems with hysteresis quantization. To describe the tendency of the dynamic quantizer parameter, an auxiliary parameter is created and the relationship between the quantizer parameter and the auxiliary parameter has been discussed. Via thoroughly analyzing the structure of the hysteresis quantizer, the hysteresis quantizer based event-triggered control mechanism is designed to appropriately decide the accurate signal transmission instants with simple calculation process. Moreover, under the proposed method, the nonlinear system could be stabilized and Zeno behavior could be intrinsically avoided. Furthermore, a numerical example is given to demonstrate the efficiency of the proposed mechanism.

Based on structural interpretation of the recent seismic data in central Sichuan Basin, combined with data of drilling and outcrops around the basin, this paper discusses the evolutional characteristics of unconformities at various stages in the Leshan-Longnüsi paleo-uplift, and studies the evolution of the paleo-uplift and its control on Sinian gas reservoir accumulation. Sinian, Paleozoic, Mesozoic and other major regional unconformities were developed in the Leshan-Longnüsi paleo-uplift. According to characteristics and denudation thickness of the unconformities, the paleo-uplift tectonic evolution is divided into four stages, namely, embryonic, developmental, stable burial, and finalization. The analysis of the effects of the tectonic evolution on the Sinian gas accumulation show that: (1) the unconformities controlled the development of ancient karst reservoirs relevant to paleo-weathering crust; (2) the tectonic evolution of the paleo-uplift controlled evolution of organic matter and hydrocarbon migration and accumulation; (3) morphological changes of the paleo-uplift controlled the formation and the mergence of structural traps. Key words: Sichuan Basin, paleo-uplift, Sinian strata, tectonic evolution, gas accumulation, unconformities, ancient karst