Back-scattering from rough sea surface with foams

By using iterative method to solve the vector radiative transfer equation of discrete scatterers with randomly rough under-boundary, the back-scattering coefficient is derived, and is applied to the two-scale model of sea surface with foam scatterers driven by strong wind. By employing the modified probability density function of Cox and Munk's, and Pierson's sea spectrum, numerical results of polarized back-scatter ing are calculated. The functional dependence on wind speed and direction, observation angle, polarization and other parameters are discussed, and theoretical results are favorably matched with experimental data.

Numerical Simulation on the Extraction of Modal Back-Scattering Matrix from Reverberation Data for High Frequency Cases

The modal back-scattering matrix can be extracted from reverberation data. For high frequency cases the ’window smoothed’ processing has been proposed by E. C. Shang, T. F. Gao and D. J. Tang (2002) to extract the ’window averaged’ back-scattering matrix. It is pointed out in this paper that in order to inverse the ’window averaged’ back-scattering matrix by changing the source depth data we have to assume that the matrix is not related to the source depth, and the numerical simulation on the question has been conducted.

Smart prediction of liquefaction-induced lateral spreading

The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challenging task for civil/geotechnical engineers.In this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping ground.Along with a comparison with conventional approaches for predicting the Dh,four additional regression-based soft computing models,i.e.Gaussian process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and compared with the GEP model.The results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,respectively.The overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,respectively.For the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,respectively.Finally,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.

Individual dynamics and local heterogeneity provide a microscopic view of the epidemic spreading

The COVID-19 pandemic has caused severe global disasters,highlighting the importance of understanding the details and trends of epidemic transmission in order to introduce efficient intervention measures.While the widely used deterministic compartmental models have qualitatively presented continuous “analytical” insight and captured some transmission features,their treatment usually lacks spatiotemporal variation.Here,we propose a stochastic individual dynamical(SID)model to mimic the random and heterogeneous nature of epidemic propagation.The SID model provides a unifying framework for representing the spatiotemporal variations of epidemic development by tracking the movements of each individual.Using this model,we reproduce the infection curves for COVID-19 cases in different areas globally and find the local dynamics and heterogeneity at the individual level that affect the disease outbreak.The macroscopic trend of virus spreading is clearly illustrated from the microscopic perspective,enabling a quantitative assessment of different interventions.Seemingly,this model is also applicable to studying stochastic processes at the “meter scale”,e.g.,human society’s collective dynamics.

Influence of network structure on spreading dynamics via tie range

There are various phenomena of malicious information spreading in the real society, which cause many negative impacts on the society. In order to better control the spreading, it is crucial to reveal the influence of network structure on network spreading. Motifs, as fundamental structures within a network, play a significant role in spreading. Therefore, it is of interest to investigate the influence of the structural characteristics of basic network motifs on spreading dynamics.Considering the edges of the basic network motifs in an undirected network correspond to different tie ranges, two edge removal strategies are proposed, short ties priority removal strategy and long ties priority removal strategy. The tie range represents the second shortest path length between two connected nodes. The study focuses on analyzing how the proposed strategies impact network spreading and network structure, as well as examining the influence of network structure on network spreading. Our findings indicate that the long ties priority removal strategy is most effective in controlling network spreading, especially in terms of spread range and spread velocity. In terms of network structure, the clustering coefficient and the diameter of network also have an effect on the network spreading, and the triangular structure as an important motif structure effectively inhibits the spreading.

Possible Cortical Spreading Depression Recorded Intraoperatively Following a Generalized Seizure: Illustrative Case

Background: We present a compelling case fitting the phenomenon of cortical spreading depression detected by intraoperative neurophysiological monitoring (IONM) following an intraoperative seizure during a craniotomy for revascularization. Cortical spreading depression (CSD, also called cortical spreading depolarization) is a pathophysiological phenomenon whereby a wave of depolarization is thought to propagate across the cerebral cortex, creating a brief period of relative neuronal inactivity. The relationship between CSD and seizures is unclear, although some literature has made a correlation between seizures and a cortical environment conducive to CSD. Methods: Intraoperative somatosensory evoked potentials (SSEPs) and electroencephalography (EEG) were monitored continuously during the craniotomy procedure utilizing standard montages. Electrophysiological data from pre-ictal, ictal, and post-ictal periods were recorded. Results: During the procedure, intraoperative EEG captured a generalized seizure followed by a stepwise decrease in somatosensory evoked potential cortical amplitudes, compelling for the phenomenon of CSD. The subsequent partial recovery of neuronal function was also captured electrophysiologically. Discussion: While CSD is considered controversial in some aspects, intraoperative neurophysiological monitoring allowed for the unique analysis of a case demonstrating a CSD-like phenomenon. To our knowledge, this is the first published example of this phenomenon in which intraoperative neurophysiological monitoring captured a seizure, along with a stepwise subsequent reduction in SSEP cortical amplitudes not explained by other variables.

DiriNet:An Estimation Network for Spectral Response Function and Point Spread Function

Hyper-and multi-spectral image fusion is an important technology to produce hyper-spectral and hyper-resolution images,which always depends on the spectral response function andthe point spread function.However,few works have been payed on the estimation of the two degra-dation functions.To learn the two functions from image pairs to be fused,we propose a Dirichletnetwork,where both functions are properly constrained.Specifically,the spatial response function isconstrained with positivity,while the Dirichlet distribution along with a total variation is imposedon the point spread function.To the best of our knowledge,the neural network and the Dirichlet regularization are exclusively investigated,for the first time,to estimate the degradation functions.Both image degradation and fusion experiments demonstrate the effectiveness and superiority of theproposed Dirichlet network.

Bearing Capacity Analysis of Spread Footing on Massif in the “Corniche Ouest” of the Dakar Peninsula (Senegal, West Africa)

This study presents various approaches to calculating the bearing capacity of spread footings applied to the rock mass of the western corniche at the tip of the Dakar peninsula. The bearing capacity was estimated using empirical, analytical and numerical approaches based on the parameters of the rock mass and the foundation. Laboratory tests were carried out on basanite, as well as on the other facies detected. The results of these studies give a range of allowable bearing capacity values varying between 1.92 and 11.39 MPa for the empirical methods and from 7.13 to 25.50 MPa for the analytical methods. A wide dispersion of results was observed according to the different approaches. This dispersion of results is explained by the use of different rock parameters depending on the method used. The allowable bearing capacity results obtained with varying approaches of calculation remain admissible to support the loads. On the other hand, the foundation calculations show acceptable settlement of the order of a millimeter for all the layers, especially in the thin clay layers resting on the bedrock at shallow depths, where the rigidity of the rock reduces settlement.

Physics-constrained deep-inverse point spread function model:toward non-line-of-sight imaging reconstruction

Non-line-of-sight(NLOS)imaging has emerged as a prominent technique for reconstructing obscured objects from images that undergo multiple diffuse reflections.This imaging method has garnered significant attention in diverse domains,including remote sensing,rescue operations,and intelligent driving,due to its wide-ranging potential applications.Nevertheless,accurately modeling the incident light direction,which carries energy and is captured by the detector amidst random diffuse reflection directions,poses a considerable challenge.This challenge hinders the acquisition of precise forward and inverse physical models for NLOS imaging,which are crucial for achieving high-quality reconstructions.In this study,we propose a point spread function(PSF)model for the NLOS imaging system utilizing ray tracing with random angles.Furthermore,we introduce a reconstruction method,termed the physics-constrained inverse network(PCIN),which establishes an accurate PSF model and inverse physical model by leveraging the interplay between PSF constraints and the optimization of a convolutional neural network.The PCIN approach initializes the parameters randomly,guided by the constraints of the forward PSF model,thereby obviating the need for extensive training data sets,as required by traditional deep-learning methods.Through alternating iteration and gradient descent algorithms,we iteratively optimize the diffuse reflection angles in the PSF model and the neural network parameters.The results demonstrate that PCIN achieves efficient data utilization by not necessitating a large number of actual ground data groups.Moreover,the experimental findings confirm that the proposed method effectively restores the hidden object features with high accuracy.

水下舰艇扩频通信体制研究

水下舰艇通信采用的水声通信方式在长距离传输中信号衰减严重,且因为隐蔽性需求信号功率受限,叠加受到多径干扰和海洋背景噪声干扰,通信误码率较高。为此,提出水下舰艇扩频通信体制研究。设计扩频通信体制,利用扩频通信体制拓宽传输带宽,提升远距离衰减下的通信信噪比;采用类白噪声的伪随机码m序列和OPS序列作为扩频码组建编码序列集,解决白噪声干扰、多径干扰和码分多址的问题。测试结果表明:同等条件下,采用m序列的扩频通信结果更优,可以实现-25 dB下误码率低于1%的可靠通信。经过该方法调制后,剔除了噪声干扰和多径干扰,增强了衰减的高频信号,解决了水下通信远距离衰减、多径干扰、背景噪声干扰等问题。

双圈图的Laplace spread

图的Laplace spread定义为图的最大Laplace特征值与次小Laplace特征值之差.利用多项式函数的性质,得到了具有最大Laplace spread的双圈图.

中性风在中低纬Spread-F中的作用

讨论了中低纬度电离层F区中有碰撞的Rayleigh-Taylor不稳定性的线性增长率,着重考察背景中性风对增长率的影响,首先建立了适合于描述中低纬地区R-T不稳定性的基本方程,其中包括背景中性风和电场。在此基础上导出了色散关系和不稳定性增长率γ。结果表明,γ随纬度增加而逐渐减小,虽然东西方向和垂直向下的中性风分量有利于不稳定性增长,但在比30度更高的纬度,正常的背景中性风很难使γ为正值,除非存在合适的东西方向电场,亦即电场在中纬度Spread F的形成方面起着重要的作用。文中还根据比较合乎实际的电离层电子密度分布模式估算了线性增长率γ的季节变化。

基于Spread业务支撑系统的拓扑构造

基于Spread具有的高度灵活性和自动发现功能,构造一个基于Spread的业务支撑系统,并研究了该系统的拓扑构造,给出了系统拓扑常见的4种情况:服务节点加入、服务节点离开、动态拓扑增加和动态拓扑减少的算法.仿真实验表明,该系统具有良好的稳定性、扩展性和容灾抗毁能力.

一种类Spreadsheet结构的信息汇聚方法

SpreadSheet样式的数据操作具有很好的可用性,但在SpreadSheet结构中如何表示并操纵XML数据以及如何使用复制、粘贴、移动等简单操作表示复杂的XQuery查询是两个难点问题。提出一种基于XML模式的操作表示方法,将复杂的XQuery查询语句分解为XML模式上的粘贴节点、移动节点等操作,从而可以表示XQuery语言的核心语句FLOWR。在Spreadsheet结构中将XML模式显示为嵌套表格,用户在嵌套表格上的操作转换为XML模式上的操作。使用该方法可以构造多数据源的XQuery查询,并实现了概念验证的原型系统。与当前流行的XQuery查询构造工具相比较,原型系统更适合于无编程经验的最终用户构造XQuery查询。

声重波激发的赤道Spread—F的拓扑特性研究

本文对声重波激发的Spread-F扰动的非线性制约方程的拓扑特性进行了定性讨论和数值计算．研究了Spread-F的混沌特征及参数范围．结果表明声重波在不同条件时对Spread-F的激发作用有本质的不同．

声重波激发的赤道 Spread—F 不稳定性

本文导出了声重波扰动与赤道电离层扩展Ｆ层相互作用的基本方程，并对数值模拟结果进行了讨论．结果表明当声重波扰动与Ｋａｖｌｅｉｇｈ－Ｔａｙｌｏｒ不稳定性共同作用于赤道Ｆ层时，将导致大尺度波状结构的Ｓｐｒｅａｄ－Ｆ．其特征为以一定速度漂移的准周期不规则性，发展到后期伴有羽柱形状的ｂｕｂｂｌｅ（电子密度低区）产生．这种现状的ｂｕｂｂｌｅ可上升至Ｆ层顶部并发生倾斜．声重波波矢量的方向决定着羽柱的倾斜方向．这些结果与实验观测特征相符，说明声重波扰动不仅是大尺度Ｓａｒｅａｄ－Ｆ的触发源，而且对其整个形态发展过程起着重要的作用．

Spread-F的经度效应

从三维地理坐标系出发建立模型 ,考虑了地磁倾角和偏角的影响 ,研究Spread F现象的全球分布特点 ,是对以前的研究从赤道地区向中、低纬度地区的推广。从该三维模型中可以看到地磁场的大小和位型的影响 (包括磁倾角和磁偏角的效应 )。由于地磁位型的不同 ,发生率的分布并不具有经度对称性 ,即使在磁赤道附近也如此。在某些特殊的经度和纬度地区 ,会达到发生率的峰值。

确定美式Spread期权自由边界的一种算法

Spread期权是一种新型两维美式差价期权 ,即客户有权以价格E ,一份标的资产s2 交换一份标的资产s1.这种期权涉及到两标的资产且可提前执行 ,其数学模型是抛物型方程的自由边界问题 .确定期权价格的关键在于自由边界位置的确定 .通过坐标变换、高精度分裂算法及奇性消除方法等手段 ,计算出可靠的数值结果 .

The burden of upper motor neuron involvement is correlated with the bilateral limb involvement interval in patients with amyotrophic lateral sclerosis:a retrospective observational study

Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.

中低纬Spread-F的数值模拟

本文导出了中低纬地区电离层F区中的Rayleigh-Taylor不稳定性的线性增长率,并对一些典型情况进行了数值模拟研究.结果表明,Ravleigh-Taylor不稳定性的线性增长率随纬度的增加而降低,在中纬度地区,如果没有合适的东西向水平外电场,纯Rayleiyh-Taylor模难于增长,初始扰动将被稳定化.在这些区域,线性增长率的表达式还表明,外电场导致的E×B模的增长率虽然随纬度的增加而减小,但其减小的速率慢于R-T模增长率的减小.非线性的数值模拟则显示,中纬非线性E×B漂移不能象在赤道地区那样使电子密度减小的区域抬升到F区顶部以上,亦即在中纬地区,F顶部以上通常不出现电离层泡,但在F区较低部分可以演化出较大范围的电子密度增强区,这与中低纬地区Spread-F的某些观测特征一致.这说明Rayleigh-Taylor不稳定性与东向水平外电场一起可以成为导致中纬Spread-F发展的一种机制.