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.

Adaptive Video Dual Domain Watermarking Scheme Based on PHT Moment and Optimized Spread Transform Dither Modulation

To address the challenges of video copyright protection and ensure the perfect recovery of original video,we propose a dual-domain watermarking scheme for digital video,inspired by Robust Reversible Watermarking(RRW)technology used in digital images.Our approach introduces a parameter optimization strategy that incre-mentally adjusts scheme parameters through attack simulation fitting,allowing for adaptive tuning of experimental parameters.In this scheme,the low-frequency Polar Harmonic Transform(PHT)moment is utilized as the embedding domain for robust watermarking,enhancing stability against simulation attacks while implementing the parameter optimization strategy.Through extensive attack simulations across various digital videos,we identify the optimal low-frequency PHT moment using adaptive normalization.Subsequently,the embedding parameters for robust watermarking are adaptively adjusted to maximize robustness.To address computational efficiency and practical requirements,the unnormalized high-frequency PHT moment is selected as the embedding domain for reversible watermarking.We optimize the traditional single-stage extended transform dithering modulation(STDM)to facilitate multi-stage embedding in the dual-domain watermarking process.In practice,the video embedded with a robust watermark serves as the candidate video.This candidate video undergoes simulation according to the parameter optimization strategy to balance robustness and embedding capacity,with adaptive determination of embedding strength.The reversible watermarking is formed by combining errors and other information,utilizing recursive coding technology to ensure reversibility without attacks.Comprehensive analyses of multiple performance indicators demonstrate that our scheme exhibits strong robustness against Common Signal Processing(CSP)and Geometric Deformation(GD)attacks,outperforming other advanced video watermarking algorithms under similar conditions of invisibility,reversibility,and embedding capacity.This underscores the effectiveness and feasibility of our attack simulation fitting strategy.

倾斜射流撞壁形成液膜的铺展形态及波动特征

为了深入理解倾斜射流撞壁液膜表面波的形成演变机理和液膜不同的铺展形态,开展了倾斜射流撞壁的实验观测和数值模拟.使用高速相机记录了不同射流速度和倾角的液膜铺展形态,并通过数值模拟结合实验观测揭示了液膜表面波的形成和演变过程.结果表明随着射流速度的增加,液膜的铺展形态将经历平滑液膜-闭合边缘、波动液膜-闭合边缘和波动液膜-开放边缘3种状态.液膜的铺展高度和宽度与射流速度近似正比关系,但随着液膜边缘的破碎,将会体现非线性变化.随着射流倾角的增加,液膜铺展将从窄变宽,并且液膜边缘形态可由闭合变为开放.射流速度和射流倾角的增加,都会使撞击点上方的区域趋向失稳破碎,导致液膜边缘出现指状结构.射流内的湍流扰动会在撞击壁面后激励起液膜的二维表面波,撞击点附近初始的表面波在下游发展过程中会发生展向演变,出现三维特征.射流速度越快,射流表面扰动越强,液膜表面形成的表面波也越复杂,三维表面波与撞击点越接近.表面波的形成会影响液膜的流动和厚度分布,在波峰处,液膜的流动速度较快,随着下游的发展,波峰的速度将会逐渐减小,在液膜表面还会出现两个波之间追赶的现象.

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.

喷雾助剂对乙基多杀菌素药液在杧果叶片润湿铺展行为的影响

乙基多杀菌素是防治杧果蓟马的常用药剂之一,农药喷雾助剂的添加可以提高农药的药效。合理选择和使用助剂产品,对提高农药利用率、减少农药使用量至关重要。本研究通过测定添加5种不同类型、不同浓度的农药助剂产品后乙基多杀菌素药液的静态、动态表面张力,以及药液在杧果叶片正面、背面的接触角、铺展面积和蒸发时间,探究不同类型农药助剂产品在杧果叶片表面的润湿铺展行为。结果表明:添加不同助剂产品均能有效降低乙基多杀菌素药液的静态、动态表面张力,同时降低药液在叶片表面的接触角,提高药液在杧果叶片表面的铺展面积。除高分子类助剂(诺普信天盾)在叶片背面表现出抗蒸发性外,其他助剂产品均缩短了蒸发时间。不同类型的助剂产品在杧果叶片上的润湿性表现并不一致,有机硅类助剂(极润)润湿性最好,其余依次为硅酸金属复合盐类助剂(迈道)、改性植物油(迈飞)、橙皮精油(丹罗丰)、高分子类助剂(诺普信天盾)。通过比较不同处理组药液在杧果叶片正面、背面的润湿铺展行为,得出叶片背面比正面更难以被农药药液润湿。药液的理化性质和叶片的表面结构是影响喷雾液滴在叶片上润湿行为的重要因素。杧果蓟马常常在叶片背面活动取食,因此在防治杧果蓟马时,应根据助剂的类型、蓟马的为害特点选择合适的浓度,才能取得较好的防治效果。研究结果揭示了不同类型助剂在杧果叶片上的润湿铺展行为,为合理选择使用农药喷雾助剂产品提供数据支撑。

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。

文化大国、文化贸易与中华文化传播

在全球化背景下,文化大国可以依托巨大的国内市场规模和独特的文化偏好,提升其文化在全球范围内的经济价值,进而影响全球化文化产品中的文化元素投入偏向。本土文化产业的发展也可以发挥“本地市场效应”,通过文化贸易出口来促进其文化国际传播。中国作为一个文化大国,一方面通过渐进式开放和文化贸易进口,吸引全球文化产品加入中华文化元素并进行全球销售;另一方面通过发挥“本地市场效应”,中国的文化贸易出口也正在以中国文化产品为载体,将中华文化传播至世界各地。今后需要高度重视文化贸易的文化传播功能,在开放中更好平衡文化传播、产业发展和产业国际竞争力的关系,重视文化贸易理论与实践的相互促进作用,充分理解文化产品和服务的经济属性,在文化贸易促进文化传播的实践中,实现经济效益与社会效益相统一。

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。

中国天然气市场发展形势

介绍了中国和世界天然气市场的发展状况,指出了中国天然气市场发展的前景和存在的主要问题,提出了发展我国天然气市场的几点政策建议。

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．

通风管道作用下烟气跨舱室蔓延规律研究

船舶舱室通风依赖通风系统,但通风管道极有可能成为火灾中烟气蔓延的隐蔽路径,从而造成火灾烟气的大面积扩散.本文针对船舶双舱室火灾中烟气跨舱室蔓延问题,考虑通风管道和走廊两种烟气蔓延路径,结合1/2尺度实验和数值模拟,通过分析火源舱室和毗邻舱室内温度和烟气流动的基本特征,重点探究了通风管道在烟气跨舱室蔓延过程中的作用.结果表明,在热浮力作用下,烟气将经通风管道更早进入毗邻舱室,流入的高温烟气主导毗邻舱室环境的同时限制走廊内烟气的流入.同时,通风管道内的烟气质量流率随两舱室间压力差增加而显著增加,且呈负指数关系.经计算,经通风管道蔓延的烟气质量流率约占实验平台流出烟气总流率的30%.

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．