Using Maxwell’s Theory to model and quantify the fracture evolution of cyclothymic deposition phosphate rock

The evolution and stability of fracturing in the cyclothymic deposition of phosphate rocks are strongly affected by the viscoelasticity and structural form of the rock-forming minerals. Presently, there is no standardized method that has been widely accepted to accurately quantify the elastic-plastic deformation and fracturing of such striped structural rock nor reflect the role of the different lithogenous minerals in phosphate rocks when subjected to viscoelastic strain loading. In this study, integrated mathematical equations were formulated for modelling the mechanical and fracture behaviour of cyclothymic deposition in structured phosphate rocks. These constitutive equations were developed based on Maxwell’s Theory after the elastic modulus and damping coefficient of the rock-forming mineral from the mechanical testing were substituted into the derived-equations. In these new models, the apatite stripes and dolomite stripes were incorporated into the transverse isotropic model through the analysis of structural characteristics of the phosphate rock. Through experimental validation, the response curves of the creep and stress relaxation tests were found to be consistent with the deformation curves generated by modelling using the mathematical equations. Overall, the formulated model along with the corresponding equations was found to exhibit good applicability properties to describe phosphate’s mechanical and fracture behaviour under low horizontal compressive stresses. In the study, the creep mechanism in phosphate rocks were satisfactorily analysed from the angles of microscopic morphology, cracks evolution, and inter-crystalline strength. The hard brittle apatite was found to be surrounded and separated by high creep variant dolomite. Furthermore, the analysis showed that dolomite crystals possessing high creep properties dominated the distribution and evolution of secondary structures in the phosphate rock, under the condition of long-term low-stress loading

Polypyrimidine tract binding protein knockdown reverses depression-like behaviors and cognition impairment in mice with lesioned cholinergic neurons

Background and objectivesDepression is a common comorbidity of dementia and may be a risk factor for dementia. Accumulating evidence has suggested that the cholinergic system plays a central role in dementia and depression, and the loss of cholinergic neurons is associated with memory decline in aging and Alzheimer’s patients. A specific loss of cholinergic neurons in the horizontal limb of the diagonal band of Broca (HDB) is correlated with depression and dysfunction of cognition in mice. In this study, we examined the potential regenerative mechanisms of knockdown the RNA-binding protein polypyrimidine tract binding protein (PTB) in reversing depression-like behaviors and cognition impairment in mice with lesioned cholinergic neurons.MethodsWe lesioned cholinergic neurons in mice induced by injection of 192 IgG-saporin into HDB; then, we injected either antisense oligonucleotides or adeno-associated virus-shRNA (GFAP promoter) into the injured area of HDB to deplete PTB followed by a broad range of methodologies including behavioral examinations, Western blot, RT-qPCR and immunofluorescence.ResultsWe found that the conversion of astrocytes to newborn neurons by using antisense oligonucleotides on PTB in vitro, and depletion of PTB using either antisense oligonucleotides or adeno-associated virus-shRNA into the injured area of HDB could specifically transform astrocytes into cholinergic neurons. Meanwhile, knockdown of PTB by both approaches could relieve the depression-like behaviors shown by sucrose preference, forced swimming or tail-suspension tests, and alleviate cognitive impairment such as fear conditioning and novel object recognition in mice with lesioned cholinergic neurons.ConclusionThese findings suggest that supplementing cholinergic neurons after PTB knockdown may be a promising therapeutic strategy to revert depression-like behaviors and cognitive impairment

Generalized Nonlinear Chirp Scaling Algorithm for High-Resolution Highly Squint SAR Imaging

This paper presents a modified approach for high-resolution, highly squint synthetic aperture radar (SAR) data processing. Several nonlinear chirp scaling (NLCS) algorithms have been proposed to solve the azimuth variance of the frequency modulation rates that are caused by the linear range walk correction (LRWC). However, the azimuth depth of focusing (ADOF) is not handled well by these algorithms. The generalized nonlinear chirp scaling (GNLCS) algorithm that is proposed in this paper uses the method of series reverse (MSR) to improve the ADOF and focusing precision. It also introduces a high order processing kernel to avoid the range block processing. Simulation results show that the GNLCS algorithm can enlarge the ADOF and focusing precision for high-resolution highly squint SAR data

Sidelobe Suppression with Resolution Maintenance for SAR Images via Sparse Representation

Severe sidelobe interference is one of the major problems with traditional Synthetic Aperture Radar (SAR) imaging. In the observation scene of sea areas, the number of targets in the observation scene is so small that targets can be regarded as sparse. Taking this into account, a method of sidelobe suppression, on the basis of sparsity constraint regularization, is proposed to reduce sidelobes of Gaofen-3 (GF-3) images in sea areas of the image domain. This proposed method has a prominent sidelobe suppression effect with resolution maintenance and without destruction of amplitude and phase information. This method can also be applied to SAR images of other satellites. In addition to the employment of peak sidelobe ratio (PSLR) and integrated sidelobe ratio (ISLR) in evaluating sidelobe suppression level, AE (amplitude error) and PE (phase error) are firstly defined for the evaluation of amplitude and phase-preserving quality, respectively. Through the proposed method, AE and PE values are nearly unchanged and the PSLR and ISLR are significantly reduced. The method, as an important part of the quality-improvement project of GF-3, has been successfully applied to the sidelobe suppression of GF-3 data

General Signal Model for Multiple-Input Multiple-Output GMTI Radar

Multiple-input multiple-output (MIMO) ground moving target indication (GMTI) radar has been studied recently because of its excellent performance. In this paper, a general signal model is established for the MIMO GMTI radar with both fast-time and slow-time waveforms. The general signal model can be used to evaluate the performance of the MIMO GMTI radar with arbitrary waveforms such as the ideal orthogonal, code division multiple access (CDMA), frequency-division multiple access (FDMA), time division multiple access (TDMA), and Doppler division multiple access (DDMA) waveforms. We proposed a range-compensation method to eliminate the range-dependence of the FDMA waveforms. The simulation results indicate that the improved performance of FDMA waveforms is achieved utilizing the range-compensation method

Generalized Chirp Scaling Combined with Baseband Azimuth Scaling Algorithm for Large Bandwidth Sliding Spotlight SAR Imaging

This paper presents an efficient and precise imaging algorithm for the large bandwidth sliding spotlight synthetic aperture radar (SAR). The existing sub-aperture processing method based on the baseband azimuth scaling (BAS) algorithm cannot cope with the high order phase coupling along the range and azimuth dimensions. This coupling problem causes defocusing along the range and azimuth dimensions. This paper proposes a generalized chirp scaling (GCS)-BAS processing algorithm, which is based on the GCS algorithm. It successfully mitigates the deep focus along the range dimension of a sub-aperture of the large bandwidth sliding spotlight SAR, as well as high order phase coupling along the range and azimuth dimensions. Additionally, the azimuth focusing can be achieved by this azimuth scaling method. Simulation results demonstrate the ability of the GCS-BAS algorithm to process the large bandwidth sliding spotlight SAR data. It is proven that great improvements of the focus depth and imaging accuracy are obtained via the GCS-BAS algorithm

Frequency Diversity Gain of a Wideband Radar Signal

Wideband radar has high-range directional resolution, which can effectively reduce the fluctuation of echo and improve the detection probability of a target under the same detection probability requirement. In this paper, a unified wideband radar χ2 distribution target model with more practical significance is innovatively established, on which the probability density function and detection probability function of Swerling 0, Swerling II and Swerling IV targets are analyzed, respectively. A generalized “frequency diversity gain” of wideband radar is proposed and defined based on the contradiction between suppression of fluctuation and accumulation loss, which represents the ratio of Signal-to-Noise Ratio (SNR) gain between broadband signal and reference bandwidth signal under the same condition (when the reference bandwidth is used, the radar target has only one range unit), and the mathematical relation equation of the target detection performance and signal bandwidth (equivalent to the number of distinguishable range elements of the target) is given. A Monte Carlo simulation experiment is designed. Based on the target model established in this paper, the optimal number of target range units corresponding to different detection probability requirements is obtained, which verifies the correctness of the concept proposed in this paper

Reverse Backprojection Algorithm for the Accurate Generation of SAR Raw Data of Natural Scenes

Future synthetic aperture radar (SAR) mission concepts often rely on locally nonlinear (e.g., high orbits and bistatic) surveys or acquisition schemes. The simulation of the raw data of natural scenes as acquired by future systems appears as one powerful tool in order to understand the particularities of these systems and assess the impact of system and propagation errors on their performance. We put forward, in this letter, a new formulation of the reverse backprojection algorithm for the accurate simulation of raw data of natural surfaces. In particular, the algorithm is perfectly suited to accommodate any kind (1-D/2-D) of temporal and spatial variation, e.g., in observation geometry, acquisition strategy, or atmospheric propagation. The algorithm is analyzed with respect to its SAR image formation sibling, and tested under different simulation scenarios. We expect the reverse backprojection algorithm to play a relevant role in the simulation of future geosynchronous and multistatic SAR missions

A Compensation Method for Airborne SAR with Varying Accelerated Motion Error

Motion error is one of the most serious problems in airborne synthetic aperture radar (SAR) data processing. For a smoothly distributing backscatter scene or a seriously speed-varying velocity platform, the autofocusing performances of conventional algorithms, e.g., map-drift (MD) or phase gradient autofocus (PGA) are limited by their estimators. In this paper, combining the trajectories measured by global position system (GPS) and inertial navigation system (INS), we propose a novel error compensation method for varying accelerated airborne SAR based on the best linear unbiased estimation (BLUE). The proposed compensating method is particularly intended for varying acceleration SAR or homogeneous backscatter scenes, the processing procedures and computational cost of which are much simpler and lower than those of MD and PGA algorithms