Based on the computer simulation technology of zero memory nonlinearity (ZMNL), this paper combines with the backscattering features of sea clutter and conducts simulation for four typical backscattering coefficient empirical models of sea clutter, namely, Technology Service Corporation, Georgia Institutes of Technology, Hybrid Sea Clutter Model, and Naval Research Laboratory. According to the results, the signals of sea clutter simulated by zero memory nonlinearity are able to well satisfy the requirements of spectrum characteristics and amplitude distribution according to experiments on the fitting characteristics of simulated signals. After that, the above-mentioned sea clutter scattering coefficient fitting characteristics are applied to the finite difference time domain (FDTD) electromagnetic scattering equation of the numerical method, and the optimal recursive solution to the backward scattering area fitted by the above four semi-empirical models is proposed for the first time. Then, the method of discretizing the power spectrum equation of the differential form is combined with the FDTD discrete form. The numerical results of discrete simulation take the form of the random phase ω between 0 and 2π and then are converted into a basic iteration of one-dimensional rough length, thus realizing time domain power spectrum inversion. Finally, combined with the above conclusions, this paper proposes a new statistical model based on sea surface backscatter coefficient to invert the two-dimensional sea surface, that is, the three-parameter statistical model. At the same time, this paper further deduces the backscattering function of sea clutter based on random distribution and points out that the incident frequency and the rubbing angle are the main factors affecting the sea clutter scattering model. Based on this conclusion, this paper combines the sea clutter estimation model and the directional function model to simulate a two-dimensional random rough sea surface satisfying the physical laws of the ocean.INDEX TERMS Zero memory nonlinearity, empirical models, finite difference time domain, twodimensional sea surface.

Neuroimaging evidence implies that cognitive impairment in patients with end-stage renal disease (ESRD) is related to the disruption of the default-mode network (DMN). The DMN can be divided into three functionally independent subsystems, which include the cortical hub subsystem [consisting of the posterior cingulate cortex (PCC) and the anterior medial prefrontal cortex (aMPFC)], the dorsal medial prefrontal cortex (dMPFC) subsystem, and the medial temporal lobe (MTL) subsystem. However, it is unknown how the functional connectivity (FC) in DMN subsystems is differentially impaired in ESRD. This prospective study was carried out at the Affiliated Hospital of Qingdao University, China, between August 2018 and July 2020. Thirty-two ESRD patients and forty-five healthy controls (HCs) were recruited for this study and received resting-state functional magnetic resonance imaging (rs-fMRI) scanning, and FCs on predefined regions of interest (ROIs) were individually calculated in three DMN subsystems using both ROI-and seed-based FC analyses to examine FC alterations within and between DMN subsystems. The two-sample t-test was used for the comparisons between groups. We also tested the associations between FC changes and clinical information using Pearson's correlation analysis. The results demonstrated that ESRD patients, compared with HCs, exhibit reduced FC specifically within the cortical hubs and between the DMN hubs and two subsystems (the dMPFC and MTL subsystems). Moreover, the FC values between the aMPFC and PCC were positively correlated with creatinine and urea levels in the ESRD patients. Our results suggest that the cortical hubs (PCC and aMPFC) are preferentially disrupted and that other subsystems may be progressively damaged to a certain degree as the disease develops.

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Combining the contrast characteristics of Wen's directional spectrum and Donelan's distribution function, this paper proposed a simulation model of 2-D random rough sea surface based on improved Wen's spectrum and Monte Carlo method, and analyzes distribution characteristics of the 2-D random rough sea surface under the condition of 320 • wind direction, different wind speeds, and fetch. On the basis of the classical two-scale method for calculating the electromagnetic scattering of the sea surface, this paper attempts to compare the electromagnetic scattering results of the above simulated 2-D random rough sea surface with the backscattering simulation data of four typical semi-empirical sea clutter models, such as Technology Service Corporation, the Georgia Institutes of Technology, the Hybrid Sea Clutter Model, and the Naval Research Laboratory for the first time. Then, the electromagnetic scattering characteristics of 2-D random rough sea surface with improved Wen's spectrum in HH and VV polarization modes under different sea conditions, grazing angle, and incident frequency are studied. Finally, this paper analyzes the fitting characteristics between the above model and improved Wen's spectrum from the perspective of inversion of the wave spectrum by combining the spectral characteristics of the simulated wave spectrum and summarizes the respective adaptive ranges of different models.INDEX TERMS Donelan's distribution function, improved Wen's spectrum, Monte Carlo method, two-scale method, semi-empirical sea clutter models.

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