基于 ResU-Net 的三维断层识别方法及应用

断层刻画了地层的边界位置,地震成像数据中反射层的不连续性可作为断层解释的主要依据。深度神经网络的强非线性性质可作为地震数据中断层不连续特征表达的有力工具,断层识别问题可视作一个像素级别的二分类问题,并使用深度学习方法对此问题进行建模求解。据此可给出一种端到端的基于深度学习网络的三维断层自动识别方法。首先利用地震子波与反射系数卷积合成多组三维地震数据,建立用于深度网络学习断层特征的样本数据,随后搭建网络进行训练,网络训练完成后应用于实际地震数据。鉴于残差模块可很好地提升网络泛化性能,所提出的将残差网络中的残差块结构引入U-Net中的方法,可用于提升通过合成数据样本训练得到的网络模型在训练数据之外,即实际地震数据上的断层识别性能。所建立网络用于断层解释时,输入为叠后三维地震数据,输出为相同维度的三维数据体,其中每一输出值代表输入三维地震数据相同位置处断层的概率。实际算例对比测试表明,此方法可对三维地震数据中的断层进行有效识别,在合成数据集上训练精度相差不大的前提下,引入残差模块的ResU-Net在实际地震数据上的断层识别泛化性能得到提升。     

外卖配送路径多目标实时优化研究

随着外卖行业的不断发展,外卖配送的路径优化问题已引起学者们的广泛关注。但现有研究未将骑手的目标考虑在内,且未考虑动态场景下多目标如何设定权重的问题。因此,本文对外卖配送路径的多目标实时优化进行深入研究。建立多目标外卖配送路径优化模型。该模型不仅考虑订单履行时间、平台利润和骑手服务质量3个常用的目标,另外增加骑手等待时间和骑手空驶距离这两个目标,充分将外卖平台、顾客和骑手的目标综合考虑。设计动态调整权重的多目标外卖配送路径启发式算法,解决动态场景下多目标权重如何设定的问题。通过外卖配送的实时数据进行算例分析。结果表明,本文提出的算法可以有效对多目标的外卖配送问题进行实时路径优化,且订单的密集程度对骑手等待时间和订单履行时间有直接的影响。     

Peptidyl Virus-Like Nanovesicles as Reconfigurable “Trojan Horse” for Targeted siRNA Delivery and Synergistic Inhibition of Cancer Cells

The self-assembly of peptidyl virus-like nanovesicles (pVLNs) composed of highly ordered peptide bilayer membranes that encapsulate the small interfering RNA (siRNA) is reported. The targeting and enzyme-responsive sequences on the bilayer's surface allow the pVLNs to enter cancer cells with high efficiency and control the release of genetic drugs in response to the subcellular environment. By transforming its structure in response to the highly expressed enzyme matrix metalloproteinase 7 (MMP-7) in cancer cells, it helps the siRNA escape from the lysosomes, resulting in a final silencing efficiency of 92%. Moreover, the pVLNs can serve as reconfigurable “Trojan horse” by transforming into membranes triggered by the MMP-7 and disrupting the cytoplasmic structure, thereby achieving synergistic anticancer effects and 96% cancer cell mortality with little damage to normal cells. The pVLNs benefit from their biocompatibility, targeting, and enzyme responsiveness, making them a promising platform for gene therapy and anticancer therapy.     

车辆四轮转向系统的控制方法

系统地评述了车辆四轮转向系统的原理及其控制方法的发展,在此基础上指出四轮转向系统的研究必须以闭环综合评价为出发点,并与其它主动安全技术相结合才能真正达到实用阶段。     

平面有限元单元网格自动生成

本文通过对平面三角形单元、四边形单元节点信息及单元定义的分析,用C语言编制了能自动生成平面三节点三角形单元,四节点、八节点四边形单元的有限元问题的前处理程序FEMPRE2D．C．通过使用FEMPRE2D．C程序可大大节省数据录入人员的工作量,减少准备数据的时间,并能消除录入数据时可能发生的错误,从而为正确解决工程问题提供可靠的保证．     

国外污泥处置技术

污泥处置是一个引入注目的问题,本文就区盟及其成员国的污泥产量,质量,污泥处置方式的现状及可能的发展趋势进行了综述与讨论。     

一次风反切系统的数值模拟和多相流动特性分析

四角切圆燃烧锅炉,存在着稳燃和结渣的矛盾,一次风微反切技术已在多台锅炉上得到应用,较好地解决了这对矛盾并能在一定程度上降低ＮＯｘ的排放量。本文把湍流理论和多相流动理论应用于炉内空气动力场的计算机数值模拟,用投影法编制的计算软件对６００ＭＷ锅炉炉内流动进行了计算,得出了一次风反切系统中炉内速度场、实际切圆、颗粒运动轨迹等结果,与冷炉和冷模试验基本吻合,对一次风反切系统的设计和调试具有参考价值。     

High-performance aromatic polyimide fibres

A new polyimide has been synthesized from 3,3,4,4-biphenyltetracarboxylic dianhydride (BPDA) and 2,2-dimethyl-4,4-diaminobiphenyl (DMB). A high-strength, high-modulus, high-temperature fibre has been developed from this polyimide via a dry-jet wet spinning method. The tensile strength of BPDA-DMB fibres is 3.3 GPa and the tensile modulus is around 130 GPa. The compressive strength of the fibres has been investigated through a tensile recoil test (TRT), while the fibre morphology after compression has been studied via polarized light microscopy (PLM) and scanning electron microscopy (SEM). From the TRT measurements, we have observed that the compressive strength of this fibre is 665 (±5) MPa, which is higher than those of other aromatic polymer fibres. The effect of fibre diameter on the compressive strength of BPDA-DMB fibres is not substantial. The critical compressive strain for this fibre at which the kink bands start appearing under the observation of PLM is at 0.51–0.54%. Subglass relaxation processes have been observed and the measure of an apparent relaxation strength may serve as one of the factors which significantly affect the compressive strength of the fibres. Tensile tests of pre-compressed fibres reveal a continuous loss in tensile strength (up to 30%) with increasing the compressive strain (up to 2.6%). PLM and SEM observations show that during the compression BPDA-DMB fibres form regularly-spaced kink bands at ±60 ° (±2 °) with respect to the fibre axis. The kink band density initially increases with the compressive strain, and reaches a maximum at around 1.1%. Further increase of the compressive strain decreases this density due to the merge of the neighbouring bands. The size of kink bands also correspondingly increases within this compressive strain region. The morphological observation via SEM implies the existence of a skin-core structure and microfibrillar texture which are common features in polymer fibres.     

Fast structural optimization with frequency constraints by genetic algorithm using adaptive eigenvalue reanalysis methods

Structural optimization with frequency constraints is highly nonlinear dynamic optimization problems. Genetic algorithm (GA) has greater advantage in global optimization for nonlinear problem than optimality criteria and mathematical programming methods, but it needs more computational time and numerous eigenvalue reanalysis. To speed up the design process, an adaptive eigenvalue reanalysis method for GA-based structural optimization is presented. This reanalysis technique is derived primarily on the Kirsch’s combined approximations method, which is also highly accurate for case of repeated eigenvalues problem. The required number of basis vectors at every generation is adaptively determined and the rules for selecting initial number of basis vectors are given. Numerical examples of truss design are presented to validate the reanalysis-based frequency optimization. The results demonstrate that the adaptive eigenvalue reanalysis affects very slightly the accuracy of the optimal solutions and significantly reduces the computational time involved in the design process of large-scale structures.