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Abstract Background Complications such as forearm hematoma after coronary intervention through the radial artery are a common complication. Material and methods By observing, describing, and analyzing the pictures taken during clinical diagnosis and consultation, we summarize the prevention, treatment, and nursing of forearm hematoma after percutaneous coronary intervention, to provide reference for the nursing of patients with forearm hematoma. Results We have innovatively summarized the risk classification of forearm hematoma and the three key time points for preventing hematoma. Conclusion Complications such as forearm hematoma after coronary intervention through the radial artery are a common complication. We have innovatively summarized the risk classification of forearm hematoma and the three key time points for preventing hematoma, providing reference for the prevention and management of forearm hematoma in clinical practice. For patients undergoing transradial coronary intervention, the three key time points for preventing hematoma and symptomatic management based the risk classification of forearm hematoma are crucial.

There is an effective way to enhance the spatial resolution of hyperspectral remote sensing images by fusing them with multispectral remote sensing images. However, most of the existing deep fusion techniques adopt discretized explicit models to approximate the complex continuous nonlinear mapping in the fusion process, leading to limitations in enhancing the fidelity of spatial details. Additionally, existing algorithms commonly utilize discrete methods such as bilinear or bicubic interpolation during the hyperspectral upsampling process, leading to the loss of crucial spatial-spectral features. To this end, this study proposes a novel Implicit Transformer Fusion Generative Adversarial Network (ITF-GAN), which incorporates the continuity perception mechanism of implicit neural representation with the powerful self-attention mechanism of the Transformer architecture, which uses point-to-point implicit functions aiming to efficiently process information in both spatial and spectral dimensions. Besides, a guided implicit neural sampling module is introduced in the hyperspectral image up-sampling process to enhance the coordinated expression of features in the spatial and spectral domains, which improves the spatial resolution and spectral fidelity of the fused image during the upsampling process. A series of fusion experiments including 4x, 8x, and 16x scale factors have shown that ITF-GAN has significant advantages over current popular fusion algorithms in both objective evaluation indicators and subjective visual evaluation.

Ice surface temperature (IST) plays a fundamental role in the Antarctic ice sheet/shelf study. However, the production of spatially and temporally continuous Antarctic IST products remains a challenge. We proposed an instantaneous IST retrieval framework that can generate the spatially and temporally continuous Antarctic IST using Advanced Microwave Scanning Radiometer 2 data. To generate a temporally continuous IST product, we developed an innovative scheme, which was based on the acquisition time difference between input and output data. We considered the impact of terrain and sensor observation state. The corresponding parameters were used as the auxiliary variables to improve the model accuracy. We trained and validated nine machine learning models using the generated sample set. The Light Gradient Boosting Machine (LightGBM) model presents the best performance, and the root-mean-square error (RMSE) of the LightGBM model is only half of that of the typical linear models. The RMSE of the LightGBM model decreased with the training sample set size and stabilized at 1.67 K. Further validation using multisource data showed that the IST retrieved using the LightGBM model has RMSEs of 1.39–2.32 K (relative to IST from Landsat-8) and 3.7–5.9 K (relative to IST from Baseline Surface Radiation Network data). Compared to the commonly used ERA5 IST data, the retrieved IST in this study has higher accuracy. We retrieved Antarctic IST from 2013 to 2020. Antarctic IST decreased continuously from 2013 to 2015. After 2015, Antarctic IST increased with large fluctuations.

Abstract Perovskite materials and their applications in optoelectronics have attracted intensive attentions in recent years. However, in-depth understanding about their anisotropic behavior in ultrafast carrier dynamics is still lacking. Here we explore the ultrafast dynamical evolution of photo-excited carriers and photoluminescence based on differently-oriented MAPbBr3 wafers. The distinct in-plane polarization of carrier relaxation dynamics of the (100), (110) and (111) wafers and their out-of-plane anisotropy in a picosecond time scale were found by femtosecond time- and polarization-resolved transient transmission measurements, indicating the relaxation process dominated by optical/acoustic phonon interaction is related to photoinduced transient structure rearrangements. Femtosecond laser two-photon fabricated patterns exhibit three orders of magnitude enhancement of emission due to the formation of tentacle-like microstructures. Such a ultrafast dynamic study carried on differently-oriented crystal wafers is believed to provide a deep insight about the photophysical process of perovskites and to be helpful for developing polarization-sensitive and ultrafast-response optoelectronic devices.

The three-dimensional (3-D) acceleration, azimuth dependence, and real-time processing are the main issues to be solved in highly squinted frequency-modulation continuous-wave (FMCW) synthetic aperture radar (SAR) with a curved trajectory. To overcome these issues, a modified wavenumber-domain algorithm is developed in this article. The proposed modified wavenumber-domain algorithm mainly includes the following six aspects. First, a modified range model considering 3-D acceleration for a curved trajectory is established. Then, the spectrum compression and rotation operations are performed to guarantee further processing. Afterward, residual phase terms introduced by acceleration are bulk compensated for. Moreover, the azimuth dependence is eliminated by the azimuth resampling to achieve uniform focusing. Subsequently, the range–azimuth coupling is removed by the modified Stolt interpolation. Finally, to avoid image aliasing, the azimuth wavenumber domain is selected to focus the final image. The experimental results of both numerical and raw-measured FMCW-SAR data demonstrate the superiority of the proposed method.

Forward-looking imaging is crucial in many civil and military fields, such as precision guidance, autonomous landing, and autonomous driving. The forward-looking imaging performance of airborne radar may deteriorate significantly due to the constraint of the Doppler history. The deconvolution method can be used to improve the quality of forward-looking imaging; however, it will not work well for complex imaging scenes. To solve the problem of scene sparsity measurement and characterization in complex forward-looking imaging configurations, an efficient probability model-driven airborne Bayesian forward-looking super-resolution imaging algorithm is proposed for multitarget scenarios to improve the azimuth resolution. First, the data dimension of the forward-looking imaging scene was expanded from single-frame to multiframe spaces to enhance the sparsity of the imaging scene. Then, the sparse characteristics of the imaging scene were statistically modeled using the generalized Gaussian probability model. Finally, the super-resolution imaging problem was solved using the Bayesian framework. Because the sparsity characterization parameters are embedded in the entire process of imaging, the forward-looking imaging parameters will be updated during each iteration. The effectiveness of the proposed algorithm was verified using simulation and real data.

The spaceborne-missile bistatic forward-looking Synthetic Aperture Radar (SAR) is a promising imaging guidance technology that can obtain high-resolution images of the area in front of the missile all day and in all weather types. However, the coupling and spatial variations in range and azimuth parameters hinder the development of high-resolution spaceborne-missile bistatic forward-looking SAR imaging. In this study, the accurate-range Doppler domain analytical formula for echo signals was derived based on the low-orbit spaceborne illuminator and high-speed forward-looking missile-borne receiving platform configuration. Subsequently, in range processing, a range Nonlinear Chirp Scaling (NCS) was proposed to equalize the range cell migration and range Frequency Modulation (FM) rate, and both can be uniformly compensated in the two-dimensional frequency domain. In azimuth processing, the proposed method decomposed the azimuth FM rates of the transmitter and receiver. Then, the azimuth NCS was used to eliminate the high-order spatial variation of the azimuth FM rate. Finally, a two-dimensional matched filtering was performed to obtain a SAR image with a good global focus. The point and scene simulation verify the effectiveness of the proposed algorithm.

When the near-field and far-field information of a target is uncertain, it is necessary to choose a suitable localization method. The modified polar representation (MPR) method integrates the two scenarios and achieves a unified localization with direction of arrival (DOA) estimation in the far field and position estimation in the near field. Previous studies have only proposed solutions for stationary environments and have not considered the motion factor. Therefore, this paper proposes a new unified positioning algorithm using multi-sensor time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements without prior target source information. The method represents the position of the target source using MPR and describes the localization problem as a weighted least squares (WLS) problem with two constraints. We first obtain the initial estimates by WLS without considering the constraints and then investigate a two-step error correction method based on the constraints. The first step corrects the initial estimate using the Taylor series expansion technique, and the second step corrects the DOA estimate in the previous step using the direct error compensation technique based on the properties of the second constraint. Simulation experiments show that the method is effective for the unified positioning of moving targets and can achieve the Cramer–Rao lower bound (CRLB).

Abstract Glioblastoma (GBM) is a lethal cancer characterized by hypervascularity and necrosis associated with hypoxia. Here, it is found that hypoxia preferentially induces the actin‐binding protein, Transgelin (TAGLN), in GBM stem cells (GSCs). Mechanistically, TAGLN regulates HIF1α transcription and stabilizes HDAC2 to deacetylate p53 and maintain GSC self‐renewal. To translate these findings into preclinical therapeutic paradigm, it is found that sodium valproate (VPA) is a specific inhibitor of TAGLN/HDAC2 function, with augmented efficacy when combined with natural borneol (NB) in vivo. Thus, TAGLN promotes cancer stem cell survival in hypoxia and informs a novel therapeutic paradigm.

Abstract Aim To investigate the effectiveness of de-escalation of ticagrelor (from ticagrelor 90 mg to clopidogrel 75 mg or ticagrelor 60 mg) on the prognosis of patients with ST segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI) after 3 months of oral dual antiplatelet therapy (DAPT). Methods From March 2017 to August 2021, 1056 patients with STEMI in a single centre, through retrospective investigation and analysis, were divided into intensive (ticagrelor 90 mg), standard (clopidogrel 75 mg after PCI) and de-escalation groups (clopidogrel 75 mg or ticagrelor 60 mg after 3 months of treatment with 90 mg ticagrelor) based on the type and dose of P2Y12 inhibitor 3 months after PCI, and the patients had a ≥ 12-month history of oral DAPT. The primary end point was major adverse cardiovascular and cerebrovascular events (MACCEs) during the 12-month follow-up period, including composite end points of cardiac death, myocardial infarction, ischaemia-driven revascularization and stroke. The major safety endpoint was bleeding events. Results The results showed that during the follow-up period, there was no statistically significant difference in the incidence of MACCEs between the intensive and de-escalation groups (P > 0.05). The incidence of MACCEs in the standard treatment group was higher than that in the intensive treatment group (P = 0.014), but the incidence of bleeding events in the de-escalation group was significantly lower than that in the standard group (9.3% vs. 18.4%, χ²=7.191, P = 0.027). The Cox regression analysis showed that increases in haemoglobin (HGB) (HR = 0.986) and estimated glomerular filtration rate (eGFR) (HR = 0.983) could reduce the incidence of MACCEs, while old myocardial infarction (OMI) (P = 0.023) and hypertension (P = 0.013) were independent predictors of MACCEs. Conclusion For STEMI patients undergoing PCI, the de-escalation scheme of ticagrelor to clopidogrel 75 mg or ticagrelor 60 mg at 3 months after PCI was related to the reduction of bleeding events, especially minor bleeding events, without an increase in ischaemic events.

Facing the increasingly complex electromagnetic interference environment, Synthetic Aperture Radar (SAR) interference suppression has become an urgent problem to be solved. The existing mainstream synthetic aperture radar nonparametric/parametric interference suppression methods, which heavily rely on interference priori and strong energy difference, have serious problems such as high computational complexity and signal loss, and have difficulty in meeting the needs of countering increasingly complex interference. To solve the aforementioned problems, we propose an anti-interference method using self-supervised learning based on deep learning, which uses the time-frequency domain texture difference between normal radar echo and interference to overcome the constraint of using interference prior. First, we construct an interference location network model Location-Net, which compresses and reconstructs the time-frequency spectrum of the radar echo and locates the interference according to the network’s reconstruction error. Second, aiming at the signal loss caused by interference suppression, a signal recovery neural network model Recovery-Net is constructed to recover the echo signal after interference suppression. Compared with traditional methods, our method overcomes the need for interference prior, can effectively resist various complex interference types and has strong generalization ability. The anti-interference processing results based on simulation and measured data verify the effectiveness of the proposed method for various active main lobe suppression interference and show the superiority of the algorithm proposed here by comparing it with three existing anti-interference methods. Finally, comparing the complexity difference between the proposed and mainstream lightweight neural networks shows that the neural networks designed here have low computational complexity and real-time application prospects.

This paper presents the development of an environmentally friendly, small molecular depressant citrus pectin for improving the recovery of cassiterite resources. Citrus pectin extracted from citrus peel was utilized as the depressant, and it demonstrated significant potential in separating calcite from cassiterite in micro-flotation tests. The molecular weight of the citrus pectin extracted in this paper decreased from 11,485,412 Da to 32,959 Da compared to commercial pectin, resulting in the depressant efficiency of the reagent. The results of a zeta potential and adsorption test indicated that citrus pectin had less and weaker adsorption on the cassiterite surface and could be replaced with NaOL. The chemical adsorption process of citrus pectin on the surface of calcite was determined through FTIR spectroscopy analysis. XPS analysis results indicated that the interaction between the carboxyl groups of citrus pectin and calcium atoms enables adsorption to occur. The AFM revealed that citrus pectin displayed a uniform and dense pattern of point-like adsorption on the surface of calcite. Micro-flotation experiments showed that cassiterite recovery of 80% can be obtained at a citrus pectin dosage of 10 mg/L. Citrus pectin has the advantages of being low-cost, highly selective, and environmentally suitable, making it a promising alternative to conventional reagents.

During the spaceborne inverse synthetic aperture ladar (ISAL) imaging, the radial velocity between the piggyback satellite of ladar and the observed satellite is usually relatively large, which will introduce the inner-pulse Doppler that cannot be ignored in the echo. In this case, the traditional “stop-and-go” assumption will no longer hold, and the compressed result along the range direction would be seriously broaden. Therefore, to obtain a well-focused ISAL image, this article proposed a spaceborne ISAL imaging algorithm for high-speed moving targets based on the inner-pulse Doppler compensation and residue video phase (RVP) correction. In the article, the estimate method of the radial velocity, the inner-pulse Doppler compensation method, and the RVP correction method are given. After inner-pulse Doppler compensation, RVP correction and translational motion compensation, the range-compressed result under the “stop-and-go” assumption can be obtained, and the target can then be imaged by the traditional ISAL imaging algorithm. The simulation results demonstrate the effectiveness of the proposed algorithm.

The missile-borne SAR may create high-resolution two-dimensional images of the observation area to gather detailed geomorphological information and information on the size and shape of the target, thereby helping to choose the attack place and enhancing assault precision and effectiveness. Compared with conventional airborne and satellite-based SAR imaging systems, missile-borne SAR brings new problems to radar imaging technology due to its characteristics of long-range detection, large maneuver curve raid, and multiplatform cooperative operations. The missile attack stage is in two- or three-dimensional accelerated high-forward squint imaging mode. The flight trajectory differs from the general SAR imaging mode, resulting in the severe coupling of distance orientation and deteriorating imaging quality. The ballistic SAR will operate in a forward-looking mode during the attack flight stage, which will blur the images and reduce their clarity. The missile beam antenna will also be pointing directly toward the target area. With these issues in mind, this paper introduces the key technologies and development status of ballistic SAR imaging in terms of curved-track large oblique imaging, forward-looking imaging, and cooperative imaging based on military requirements and anticipates the future development trend of this technology.

This study proposes a multi-rank range-spread target detection method for multi-channel array radar under a non-Gaussian clutter background. The method aims to detect the target from real clutter using the multi-channel array radar. First, a multi-rank range-spread target model was formulated using a subspace matrix with a rank greater than one and the coordinate vectors of corresponding range bins. Then, by exploiting the persymmetric structure information of the clutter covariance matrix under the detection scenario, wherein the radar receiver units were central symmetric in space or time, a small sample estimation strategy for the parameters to be solved through the unitary transformation was constructed. Further, a non-Gaussian clutter background multi-rank range-spread target detection method was designed based on the generalized likelihood ratio, Rao, and Wald tests. Finally, a theoretical derivation proved that the proposed detection method has the constant false alarm rate property. The experimental results based on both the simulated and measured data showed that the proposed detection method can ensure the constant false alarm rate property of the clutter covariance matrix. Additionally, compared with the existing detection methods, the proposed detection method improves the target detection performance under small sample support. Besides, the proposed detection method effectively improves the robustness of target detection under the condition of steering vector mismatch.

BackgroundThis study aimed to systematically evaluate the effects of different types and doses of pretreatment with P2Y12 inhibitors in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) undergoing percutaneous coronary intervention (PCI).MethodsElectronic databases were searched for studies comparing pretreatment with different types and doses of P2Y12 inhibitors or comparison between P2Y12 inhibitor pretreatment and nonpretreatment. Electronic databases included the Cochrane Library, PubMed, EMBASE, and Web of Science. Literature was obtained from the establishment of each database until June 2022. The patients included in the study had pretreatment with P2Y12 inhibitors with long-term oral or loading doses, or conventional aspirin treatment (non-pretreatment). The primary endpoint was major adverse cardiac and cerebrovascular events (MACCEs) during follow-up within 30 days after PCI, which included determining the composite endpoints of cardiac death, myocardial infarction, ischemia-driven revascularization, and stroke. The safety endpoint was a major bleeding event.ResultsA total of 119,014 patients from 21 studies were enrolled, including 13 RCTs and eight observational studies. A total of six types of interventions were included—nonpretreatment (placebo), clopidogrel pretreatment, ticagrelor pretreatment, prasugrel pretreatment, double loading pretreatment (double loading dose of clopidogrel, ticagrelor, prasugrel) and P2Y12 inhibitors pretreatment (the included studies did not distinguish the types of P2Y12 inhibitors, including clopidogrel, ticagrelor, and prasugrel). The network meta-analysis results showed that compared to patients without pretreatment, patients receiving clopidogrel pretreatment (RR = 0.78, 95% CI:0.66, 0.91, P 0.05).ConclusionsIn patients with NSTE-ACS, pretreatment with P2Y12 inhibitors before percutaneous intervention reduced the incidence of recurrent ischemic events without increasing the risk of major bleeding after PCI compared with nonpretreatment. Clopidogrel or double loading dose P2Y12 inhibitors can be considered for the selection of pretreatment drugs.

This paper deals with adaptive moving target detection for a forward scatter radar in complex Gaussian noise. The echoes received by the forward scatter radar include not only the noise and the possible target signals but also the direct signals. To suppress the direct signals and detect the target signals, Rao and Wald tests are derived in two cases: the secondary data which contain no target signal are available or not available. Different from monostatic radar, it is proved that the derived Rao and Wald detectors for the forward scatter radar have the same test statistics as the generalized likelihood ratio test-based detector in the complex Gaussian noise both when the secondary data are available or not available. The numerical evaluation further demonstrates the equivalence and the effectiveness of the proposed detectors.

Acute coronary syndrome (ACS), diagnosed by optical coherence tomography (OCT), is caused primarily by plaque rupture, plaque erosion, and calcified nodules. Plaque erosion is more common in patients with non-ST-segment elevation myocardial infarction than ST-segment elevation myocardial infarction. This study reports the details of a case of ACS caused by massive thrombus formation due to plaque erosion. The factors associated with plaque erosion and thrombosis could not be confirmed on the basis of clinical examination findings and the physicians’ experience; therefore, the initial diagnosis of an ischemic event was replaced by a diagnosis of rapid plaque progression, as microscopically confirmed by OCT. Therefore, OCT examination must be performed for blurred or “rapidly progressing” lesions identified through angiography.

In synthetic aperture radar (SAR), increasing the pulsewidth of signal is an effective way to achieve high signal-to-noise ratio (HSNR) imaging. However, when the pulse repetition frequency (PRF) is fixed, increasing the pulsewidth will reduce the maximum unambiguous swath width of SAR. In order to solve this contradiction, a method based on continuous pulse coding (CPC) which increases the average transmit power by multiple pulses with varying high PRF is proposed in this article. Due to the small interval between pulses, the echo will have range ambiguity and occlusion problems. To obtain the complete echo, we first use the form of CPC signal and the swath width of radar to construct a linear equation set to model the ambiguous echo of each receiving window. Next, the established linear equations are split according to the distribution law of receiving window. Finally, the echo energy accumulation of multiple pulses is accomplished by solving the split sublinear equations. Therefore, the echo with both swath width corresponding to narrow pulse and HSNR corresponding to wide pulse is obtained to realize HSNR and wide swath SAR imaging. The experimental results have confirmed the effectiveness of the method proposed in this article.

This article presents an imaging solution for high maneuvering bistatic forward-looking SAR with stationary transmitter (STHM-BFSAR). In STHM-BFSAR configuration that the transmitter is mounted on a stationary platform in side-looking mode while the receiver does high-speed maneuvering in forward-looking mode, high speed and acceleration induced by high dynamic characteristics of receiver in both along-track and height direction cause larger range cell migration (RCM) and more severe 2-D spatial variation of Doppler characteristics, which makes it more difficult to obtain well-focused bistatic SAR image. Furthermore, different from the general airborne bistatic SAR, STHM-BFSAR has a larger azimuth cubic phase term that exceeds $\pi /4$ rad, which seriously affects the image quality. To deal with these problems, an imaging algorithm based on extended keystone transform (EKT) and modified frequency nonlinear chirp scaling (FNCS) is proposed in this article. EKT can correct spatial variant range curvature and bulk linear RCM, and the residual RCM is smaller than traditional keystone transform. The proposed modified FNCS is used to equalize the azimuth-range-dependent Doppler parameters in the frequency domain, which produces lower side-lobes and higher accuracy by compensating for the second-order spatial variation of the azimuth cubic coefficients. The final simulation results in this article verify the effectiveness of the proposed algorithm.

Summary: Glioma stem cells (GSCs) in the hypoxic niches contribute to tumor initiation, progression, and recurrence in glioblastoma (GBM). Hypoxia induces release of high-mobility group box 1 (HMGB1) from tumor cells, promoting the development of tumor. Here, we report that HMGB1 is overexpressed in human GBM specimens. Hypoxia promotes the expression and secretion of HMGB1 in GSCs. Furthermore, silencing HMGB1 results in the loss of stem cell markers and a reduction in self-renewal ability of GSCs. Additionally, HMGB1 knockdown inhibits the activation of RAGE-dependent ERK1/2 signaling pathway and arrests the cell cycle in GSCs. Consistently, FPS-ZM1, an inhibitor of RAGE, downregulates HMGB1 expression and the phosphorylation of ERK1/2, leading to a reduction in the proliferation of GSCs. In xenograft mice of GBM, HMGB1 knockdown inhibits tumor growth and promotes mouse survival. Collectively, these findings uncover a vital function for HMGB1 in regulating GSC self-renewal potential and tumorigenicity.

BackgroundUser modifications can alter the toxicity and addictiveness of electronic nicotine delivery systems (ENDSs). YouTube has been a major platform where ENDS users obtain and share information about ENDS modifications. Past research has examined the content and characteristics of ENDS modification videos. ObjectiveThis study aims to analyze the video comments to understand the viewers’ reactions to these videos. MethodsWe identified 168 YouTube videos depicting ENDS modifications. Each video’s top 20 most liked comments were retrieved. The final sample included 2859 comments. A content analysis identified major themes of the comment content. ResultsMost comments were directed to creators and interacted with others: 952/2859 (33.30%) expressed appreciation, 135/2859 (4.72%) requested more videos, 462/2859 (16.16%) asked for clarification, and 67/2859 (2.34%) inquired about product purchases. In addition, comments mentioned viewers’ experiences of ENDS modifications (430/2859, 15.04%) and tobacco use (167/2859, 5.84%); about 198/2859 (6.93%) also indicated intentions to modify ENDSs and 34/2859 (1.19%) mentioned that they were “newbies.” Moreover, comments included modification knowledge: 346/2859 (12.10%) provided additional information, 227/2859 (7.94%) mentioned newly learned knowledge, and 162/2859 (5.67%) criticized the videos. Furthermore, few comments mentioned the dangers of ENDS modifications (136/2859, 4.76%) and tobacco use (7/2859, 0.24%). Lastly, among the 15 comments explicitly mentioning regulations, 13/2859 (0.45%) were against and 2/2859 (0.07%) were supportive of regulations. ConclusionsThe results indicated acceptance and popularity of ENDS modifications and suggested that the videos might motivate current and new users to alter their devices. Few comments mentioned the risks and regulations. Regulatory research and agencies should be aware of online ENDS modification information and understand its impacts on users.

The coupling and spatial variation of range and azimuth parameters is the biggest challenge for bistatic forward-looking SAR (BFSAR) imaging. In contrast with the monostatic SAR and translational invariant bistatic SAR (TI-BSAR), the range cell migration (RCM), and Doppler parameters of high-speed bistatic forward-looking SAR (HS-BFSAR) have two-dimensional spatial variation characteristics, which makes it difficult to obtain SAR images with satisfactory global focusing. Firstly, based on the configuration of the spaceborne illuminator and high-speed forward-looking receiving platform, the accurate range-Doppler domain expression of the echo signal is derived in this paper. Secondly, using this analytical expression, a range nonlinear chirp scaling (NLCS) is proposed to equalize the RCM and equivalent range frequency modulation (FM) rate so that they can be uniformly processed in the two-dimensional frequency domain. Next, in the azimuth processing, the proposed method decomposes the Doppler contribution of the transmitter and receiver, respectively. Then, an azimuth NLCS is used to eliminate the spatial variation of the azimuth FM rate. Finally, a range-dependent azimuth filter is constructed to achieve azimuth compression. Simulation results validate the efficiency and effectiveness of the proposed algorithm.

Memoryless nonlinear transform (MNLT) method was widely used in the statistical model for sea clutter simulations. When the radar scattering data sets were obtained, we can simulate large scene and long-time varying 3-D sea surface scattering using expended power spectral quickly and accurately. Compared with the personal computer platform, field-programmable gate array (FPGA) has the unique merit of energy efficiency, high performance and adaptability. In this article, we proposed a novel architecture for implementing the 3-D MNLT algorithm on FPGA using high-level synthesis. As the simulation size increases, the demand for storage resources will also increase rapidly, and the on-chip memory resource will be limited on FPGA. Aiming at these problems, we divided the 3-D space-time simulation into a 2-D spatial simulation and a 3-D temporal simulation, so that we can make full use of the off-chip memory. Our design employs multiple on-chip buffer structures to decrease the transfer time of internal and external data on the FPGA. We also design a dataflow inverse fast Fourier transform processing engine (PE). The dataflow implementation overlapped butterfly operation, increasing concurrency and the overall throughput of this PE. Experimental results show that we can obtain the same accuracy and higher efficiency on a Xilinx Zynq XC7Z100 SoC platform.

The rotation matching between synthetic aperture radar (SAR) and optical images is essential for their registration. In this article, we introduce a novel fast rotation matching method for SAR and optical images. In the method, the absolute directional derivative histograms (ADDHs) of SAR and optical images can be used to reflect the rotation difference between them, and then the rotation difference is removed by the cross correlation of the two images’ ADDHs. Subsequently, we generate the ADDHs by oriented Gaussian-Gamma-shaped operator. Then, the cross correlation based on fast Fourier transform is used to deal with the ADDHs of SAR and optical images in order to determine the rotation difference of the two images. The experiment results demonstrate that the proposed method can detect the rotation difference in various conditions and achieves rotation matching with high speed.

The image fusion of multi-band and multi-polarization synthetic aperture radar (SAR) images can improve the efficiency of band and polarization information processing. In this paper, we introduce a fusion method that simultaneously fuses multi-band and polarization SAR images. In the method, we first use non-subsampled shearlet transform (NSST) to fuse multi-band and polarization SAR images. The sub-band images decomposed from the NSST are fused by the coefficient of variation (CV) and phase consistency (PC) weighted fusion rules. Subsequently, we extract the band and polarization difference information from the multi-band and polarization SAR images. The fusion image is finally colorized according to the band and polarization differences. In the experiments, we used Ka and S-band multi-polarization SAR images to test the fusion performance. The experiment results prove that the proposed fused images not only preserve much valuable information but also can be interpreted easily.

In order to study the effect of surface roughness on the Elastohydrodynamic Lubrication (EHL) performance of cylindrical roller bearing, an EHL model of cylindrical roller bearing with three dimensional surface cosine roughness based on finite length line contact theory is established. The EHL performance of cylindrical roller bearing is calculated by the Finite Difference Method (FDM) program, with which the effects of surface cosine roughness amplitude, wavelength and texture angle on EHL performance of cylindrical roller bearing are analyzed. The numerical results show that the roughness amplitude, wavelength and texture angle have great influence on the EHL performance in the contact area. The increase of roughness amplitude and wavelength in a reasonable range is beneficial to the enhancement of EHL performance of the cylindrical roller bearing, and the transverse roughness is more favorable to enhance the bearing capacity and reduce the friction coefficient.

A phase error correction method is proposed to compensate for the phase error in super-resolution correlated imaging based on metamaterial antennas. The varying carrier frequencies of a metamaterial antenna can generate the random radiation field for super-resolution correlation imaging, but the variation of the signal carrier frequency leads to large phase errors in the imaging results. In this proposed method, the sampling matrix in the super-resolution correlated imaging algorithm is used to compensate for the phase errors. Each element of the matrix is multiplied by a compensation phase corresponding to the phase error, and the error is subtly removed from the algorithm. In the experiment, the antenna pattern at each frequency of the metamaterial antenna is measured and recorded. In addition, an external field experiment is also carried out, and the collected data are imaged with the improved algorithm. Experimental results show that this technology can effectively solve the effect of phase errors on imaging results caused by signal carrier frequency changes.

When a target is moving at high-speed, its high-resolution range profile (HRRP) will be stretched by the high-order phase error caused by the high velocity. In this case, the inverse synthetic aperture radar (ISAR) image would be seriously blurred. To obtain a well-focused ISAR image, the phase error induced by target velocity should be compensated. This article exploits the variation continuity of a high-speed moving target’s velocity and proposes a noise-robust high-speed motion compensation algorithm for ISAR imaging. The target’s velocity within a coherent processing interval (CPI) is modeled as a high-order polynomial based on which a parametric high-speed motion compensation signal model is developed. The entropy of the ISAR image after high-speed motion compensation is treated as an evaluation metric, and a parametric minimum entropy optimization model is established to estimate the velocity and compensate it simultaneously. A gradient-based solver of this optimization is then adopted to iteratively find the optimal solution. Finally, the high-order phase error caused by the target’s high-speed motion can be iteratively compensated, and a well-focused ISAR image can be obtained. Extensive simulation experiments have verified the noise robustness and effectiveness of the proposed algorithm.

This paper discusses the problem of detecting subspace signals in structured interference plus compound Gaussian sea clutter with persymmetric structure. The sea clutter is represented by a compound Gaussian process wherein the texture obeys the inverse Gaussian distribution. The structured interference lies in a known subspace, which is independent with the target signal subspace. By resorting to the two-step generalized likelihood ratio test, two-step Rao, and two-step Wald design criteria, three adaptive subspace signal detectors are proposed. Moreover, the constant false-alarm rate property of the proposed detectors is proved. The experimental results based on IPIX real sea clutter data and simulated data illustrate that the proposed detectors outperform their counterparts.

Large Unmanned Aerial Vehicle (UAV) clusters, containing hundreds of UAVs, have widely been used in the modern world. Therein, mission planning is the core of large UAV cluster collaborative systems. In this paper, we propose a mission planning method by introducing the Simple Attention Model (SAM) into Dynamic Information Reinforcement Learning (DIRL), named DIRL-SAM. To reduce the computational complexity of the original attention model, we derive the SAM with a lightweight interactive model to rapidly extract high-dimensional features of the cluster information. In DIRL, dynamic training conditions are considered to simulate different mission environments. Meanwhile, the data expansion in DIRL guarantees the convergence of the model in these dynamic environments, which improves the robustness of the algorithm. Finally, the simulation experiment results show that the proposed method can adaptively provide feasible mission planning schemes with second-level solution speed and that it exhibits excellent generalization performance in large-scale cluster planning problems.

Platform vibration introduces sinusoidal modulation in inverse synthetic aperture lidar (ISAL) imaging, which causes paired echoes in ISAL imaging. In this paper, a varying amplitude vibration phase suppression algorithm is proposed. Working without prior knowledge, the proposed algorithm can suppress paired echoes under the condition of varying vibration amplitude and will not introduce new phase errors. Furthermore, the method is suitable for the imaging scene without isolated points. Both the simulated and real experiment results of ISAL turntable data demonstrate the effectiveness of the proposed algorithm.

For air-missile borne bistatic forward-looking beam-steering synthetic aperture radar (BFLBS-SAR), the receiver platform moves along a curve track due to the existence of accelerations. Besides, transmitting and receiving antenna beams rotate around a certain rotary center during the process of data collection to extend or shorten synthetic aperture time. These characteristics imply that the echo signal suffers serious range–azimuth coupling and aliasing problems of azimuth spectrum. Worse still, the echo process has problems of double-radical sign and high-order terms, which makes the rotary beam center unable to be obtained directly, and thus, the traditional polar formation algorithm (PFA) cannot be applied directly to BFLBS-SAR. To solve these problems, this paper proposes a generalized PFA (GPFA) for air-missile borne BFLBS-SAR. The algorithm uses the equivalent bistatic linear range model first to separate platform acceleration errors. By equating the bistatic mode to the monostatic one, an equivalent rotary center is obtained, and a new azimuth Deramp function is introduced to eliminate aliasing. Then, spectrum utilization and azimuth sampling rate are improved by spectral rotation and interpolation, and the image format is changed. In the azimuth focusing phase, azimuth aliasing is avoided by means of azimuth scaling, which makes azimuth focusing possible eventually. Numerous simulation experiments verify the effectiveness of the proposed GPFA.

Traditional forward-looking super-resolution methods mainly concentrate on enhancing the resolution with ground clutter or no clutter scenes. However, sea clutter exists in the sea-surface target imaging, as well as ground clutter when the imaging scene is a seacoast.Meanwhile, restoring the contour information of the target has an important effect, for example, in the autonomous landing on a ship. This paper aims to realize the forward-looking imaging of a sea-surface target. In this paper, a multi-prior Bayesian method, which considers the environment and fuses the contour information and the sparsity of the sea-surface target, is proposed. Firstly, due to the imaging environment in which more than one kind of clutter exists, we introduce the Gaussian mixture model (GMM) as the prior information to describe the interference of the clutter and noise. Secondly, we fuse the total variation (TV) prior and Laplace prior, and propose a multi-prior to model the contour information and sparsity of the target. Third, we introduce the latent variable to simplify the logarithm likelihood function. Finally, to solve the optimal parameters, the maximum posterior-expectation maximization (MAP-EM) method is utilized. Experimental results illustrate that the multi-prior Bayesian method can enhance the azimuth resolution, and preserve the contour information of the sea-surface target.

This paper addresses the problem of ground moving target relocation (GMTR) for airborne dual-channel wide-area radar systems. The monopulse technique can be utilized to perform GMTR. However, in real conditions, the GMTR performance degrades greatly due to the effect of channel mismatch. To tackle this problem, prior knowledge of the antenna pattern information is fully utilized to improve the GMTR performance, and a knowledge-aided GMTR algorithm (KA-GMTR) for airborne dual-channel wide-area radar is proposed in this paper. First, the GMTR model for the two receiving channels is analyzed. The channel mismatch model is constructed, and its expression is derived. Then, the channel mismatch phase error is well estimated by exploiting the prior antenna pattern information based on the least squares (LS) method. Meanwhile, the knowledge-aided monopulse curve (KA-MPC) is derived to perform the direction of arrival (DOA) estimation for potential targets. Finally, KA-GMTR, based on the KA-MPC, is performed to estimate the azimuth offsets and relocate the geometry positions of the potential targets when channel mismatch occurs. Moreover, the target relocation performance is analyzed, and the intrinsic reason that degrades the target relocation accuracy is figured out. The performance assessment based on airborne real-data, also in comparison to the conventional GMTR method, has demonstrated that our proposed KA-GMTR algorithm offers preferable target relocation results under channel mismatch scenarios.

With the rapid industrialization and urbanization, more attention is turning to heavy metal contamination in the soil environment. To assess the potential environmental risk on soil, a comprehensive geochemistry study on heavy metal was performed in Laizhou, eastern China, using 3834 surface soil samples (0–20 cm, regular grid of 1 × 1 km2) and 60 layered soil samples (0–200 cm) were analyzed. The average concentrations of As, Cd, Cr, Cu, Hg, Ni, Zn and Pb were 7.60 mg·kg−1, 0.15 mg·kg−1, 45.50 mg·kg−1, 19.10 mg·kg−1, 44.00μg·kg−1, 18.70 mg·kg−1, 51.40 mg·kg−1 and 29.00 mg·kg−1, which were lower than the threshold levels of the Grade II criteria of China national environment quality standard for soil, but the contents of As, Cd, Hg, and Pb were higher than background values of eastern Shandong Province surface soil. Fractionation analysis showed that the potential bioavailability in surface soils decreases in the order of Cd > As > Cu > Ni > Zn > Cr > Pb > Hg. Soil assessments with enrichment factor, contamination factor, Nemerow composite index, geo-accumulation index and potential ecological risk index, indicate the soil in Laizhou is contaminated strongly with As, Cd and Hg and a moderately Cr, Ni, Cu and Zn. The level of Pb pollution is between moderate to high. Multivariate analyses suggest that Cr and Ni were derived mainly from natural sources, and As, Cd, Pb, while Hg mostly came from anthropogenic sources. Cu and Zn were from a mixture of anthropogenic and natural sources. Our results demonstrate that more attention should be paid to monitoring soil quality in the heavily polluted site.

In a short observation time, after the range alignment and phase adjustment, the motion of a target can be approximated as a uniform rotation. The radar observing process can be simply described as multiplying an observation matrix on the ISAR image, which can be thought of as a linear system. It is known that the longer observation time is, the higher cross-range resolution is. In order to deal with the conflict between short observation time and high cross-range resolution, we introduce Kalman filtering (KF) into the ISAR imaging and propose a novel method to reconstruct a high-resolution image with short time observed data. As KF has excellent reconstruction performance, it leads to a good application in ISAR image reconstruction. At each observation aperture, the reconstructed image denotes the state vector in KF at the aperture time. It is corrected by a two-step KF process: prediction and update. As iteration continues, the state vector is gradually corrected to a well-focused high-resolution image. Thus, the proposed method can obtain a high-resolution image in a short observation time. Both simulated and real data are applied to demonstrate the performance of the proposed method.

The target detection of the passive multiple-input multiple-output (MIMO) radar that is comprised of multiple illuminators of opportunity and multiple receivers is investigated in this paper. In the passive MIMO radar, the transmitted signals of illuminators of opportunity are totally unknown, and the received signals are contaminated by the colored Gaussian noise with an unknown covariance matrix. The generalized likelihood ratio test (GLRT) is explored for the passive MIMO radar when the channel coefficients are also unknown, and the closed-form GLRT is derived. Compared with the GLRT with unknown transmitted signals and channel coefficients but a known covariance matrix, the proposed method is applicable for a more practical case whenthe covariance matrix of colored noise is unknown, although it has higher computational complexity. Moreover, the proposed GLRT can achieve similar performance as the GLRT with the known covariance matrix when the number of training samples is large enough. Finally, the effectiveness of the proposed GLRT is verified by several numerical examples.

Low phosphorus increases acid phosphatase activity and transfers soluble phosphorus from the underground to the above-ground, but also inhibits the growth and development of the Moso bamboo root system. Purple acid phosphatase (PAP), a kind of acid phosphatase, plays an important role in phosphorus (P) uptake and metabolism. In our study of the Moso bamboo PAP gene family, we identified 17 Moso bamboo PAP genes (PePAP) in the entire genome and further analyzed their physical and chemical properties and functions PePAP. According to the analysis of the phylogenetic tree, special domains and conserved motifs, these 17 genes can be divided into four categories. The gene structure and conserved motifs are relatively conservative, but the 17 sequences of the PePAP domain are diverse. The prediction of the subcellular location indicated that PePAPs are mainly located in the secretory pathway. We have studied the expression levels of these PePAP in different organs, such as the roots, stems and leaves of Moso bamboo, and the results show that the expression of most PePAP genes in roots and stems seems to be higher than that in leaves. In addition to tissue-specific expression analysis, we also studied the expression of PePAPs under low phosphorus stress. Under such conditions, the PePAP genes show an increase in expression in the roots, stem and leaves, and the extent of this change varies between genes. In summary, our results reveal the evolution of the PePAP gene in the Moso bamboo genome and provide a basis for understanding the molecular mechanism of the PePAP-mediated response of Moso bamboo to low phosphorus.

Background: Pseudoaneurysm with median nerve injury is a serious complication of radial artery puncture. It is very important to summarize the prevention and treatment experience of this complication through case discussion. Case report: A 66-year-old woman was admitted to the hospital because of “paroxysmal chest tightness and suffocation for 5 days.” Coronary angiography was performed. During insertion of the arterial sheath, the patient experienced severe pain in the right forearm, which radiated to the palm. The puncture sheath did not return blood after the sheath core was withdrawn. The sheath was removed and local compression was used to stop bleeding. There was no obvious bleeding at the puncture point, and the compression was removed 6 hours after the procedure. Local swelling and increased tension were seen in the right forearm. At the 1-week follow-up she exhibited swelling, high local tension, small blisters, and bluish-purple skin of the right forearm, with an acceptable right radial artery pulsation. She had severe pain in the affected limb, which radiated to the thumb, index finger, and middle finger. Case discussion: We discuss the causes of and treatment measures for pseudoaneurysm with median nerve injury caused by radial artery puncture.

The purpose of this study was to characterize the endogenous cellulase gene MaCel1 of Monochamus alternatus, which is an important vector of Bursaphelenchus xylophilus, a pine wood nematode, which causes pine wilt disease (PWD). In this study, MaCel1 was cloned by rapid amplification of cDNA end (RACE), and its expression analyzed by RT-qPCR (real-time quantitative PCR detecting). A total of 1778 bp of cDNA was obtained. The encoding region of this gene was 1509 bp in length, encoding a protein containing 502 amino acids with a molecular weight of 58.66 kDa, and the isoelectric point of 5.46. Sequence similarity analysis showed that the amino acids sequence of MaCel1 had high similarity with the β-Glucosinolate of Anoplophoraglabripennis and slightly lower similarity with other insect cellulase genes (GH1). The β-D-Glucosidase activity of MaCel1 was 256.02 ± 43.14 U/L with no β-Glucosinolate activity. MaCel1 gene was widely expressed in the intestine of M. alternatus. The expression level of MaCel1 gene in male (3.46) and female (3.51) adults was significantly higher than that in other developmental stages, and the lowest was in pupal stage (0.15). The results will help reveal the digestive mechanism of M. alternatus and lay the foundation for controlling PWD by controlling M. alternatus.

The reconstruction of sea clutter plays an important role in target detection and recognition in a maritime environment. Reproducing the temporal and spatial correlations of real data simultaneously is always a problem in the reconstruction of sea clutter due to the complex coupling between them. In this paper, the spatial–temporal correlated proportional method (STCPM), based on a compound model, is proposed to reconstruct K-distributed sea clutter with correlation characteristics obtained from the real data. The texture component with spatial–temporal correlation is generated by the proportional method and the speckle component with temporal correlation is generated by matrix transformation. Compared with previous methods, the biggest innovation of the STCPM is that it can more accurately generate K-distributed sea clutter with both temporal and spatial correlations. The comparison of the reconstructed and real data demonstrates that the method can reproduce the characteristics of real sea clutter well.

This paper presents a novel real-time compressive sensing (CS) reconstruction which employs high density field-programmable gate array (FPGA) for hardware acceleration. Traditionally, CS can be implemented using a high-level computer language in a personal computer (PC) or multicore platforms, such as graphics processing units (GPUs) and Digital Signal Processors (DSPs). However, reconstruction algorithms are computing demanding and software implementation of these algorithms is extremely slow and power consuming. In this paper, the orthogonal matching pursuit (OMP) algorithm is refined to solve the sparse decomposition optimization for partial Fourier dictionary, which is always adopted in radar imaging and detection application. OMP reconstruction can be divided into two main stages: optimization which finds the closely correlated vectors and least square problem. For large scale dictionary, the implementation of correlation is time consuming since it often requires a large number of matrix multiplications. Also solving the least square problem always needs a scalable matrix decomposition operation. To solve these problems efficiently, the correlation optimization is implemented by fast Fourier transform (FFT) and the large scale least square problem is implemented by Conjugate Gradient (CG) technique, respectively. The proposed method is verified by FPGA (Xilinx Virtex-7 XC7VX690T) realization, revealing its effectiveness in real-time applications.

With the rapid development of distributed renewable energy (DRE), demand response (DR) programs, and the proposal of the energy internet, the current centralized trading of the electricity market model is unable to meet the trading needs of distributed energy. As a decentralized and distributed accounting mode, blockchain technology fits the requirements of distributed energy to participate in the energy market. Corresponding to the transaction principle, a blockchain-based integrated energy transaction mechanism is proposed, which divides the trading process into two stages: the call auction stage and the continues auction stage. The transactions among the electricity and heat market participants were used as examples to explain the details of the trading process. Finally, the smart contracts of the transactions were designed and deployed on the Ethereum private blockchain site to demonstrate the validity of the proposed transaction scheme.

Multiple-input multiple-output (MIMO) radar imaging can provide higher resolution and better sensitivity and thus can be applied to targets detection, recognition, and tracking. Missile-borne forward-looking SAR (MFL-SAR) is a new and special MIMO radar mode. It has advantage of two-dimensional (2D) imaging capability in forward direction over monostatic missile-borne SAR and airborne SAR. However, it is difficult to obtain accurate 2D frequency spectrum of the target echo signal due to the high velocity and descending height of this platform, which brings a lot of obstacles to imaging algorithm design. Therefore, a new imaging algorithm for MFL-SAR configuration based on the method of series reversion is proposed in this paper. This imaging method can implement range compression, secondary range compression (SRC), and range cell migration correction (RCMC) effectively. Finally, some simulations of point targets and comparison results confirm the efficiency of our proposed algorithm.

As a special multiple-input multiple-output (MIMO) radar networking mode, missile-borne forward-looking synthetic aperture radar (MFL-SAR) has many potential applications. This paper describes and analyzes properties of this new configuration. Range history and Doppler history are analyzed and derived using the designed geometric configuration. Then the expressions of range and Doppler resolution are determined based on the validity of two-dimensional (2D) resolution imaging capability. To help to design the proper system and motion parameters of this configuration, key parameters affecting the imaging ability are found out. Due to high velocities and accelerations of both transmitter and receiver, high-order terms in the slant range equation should be kept to reduce the approximation error. The range resolution and Doppler resolution of MFL-SAR are both space-variant and time-variant owing to the complexity of this configuration. The tiny changes of 2D resolution during the synthetic aperture time should be considered when designing the imaging algorithm of MFL-SAR.

High-frequency (HF) over-the-horizon radar (OTHR) works in a very complicated electromagnetic environment. It usually suffers performance degradation caused by transient interference. In this paper, we study the transient interference excision and full spectrum reconstruction of maneuvering targets. The segmental subspace projection (SP) approach is applied to suppress the clutter and locate the transient interference. After interference excision, the spectrum is reconstructed from incomplete measurements via compressive sensing (CS) by using a redundant Fourier-chirp dictionary. An improved orthogonal matching pursuit (IOMP) algorithm is developed to solve the sparse decomposition optimization. Experimental results demonstrate the effectiveness of the proposed methods.