空间关联白噪声影响下小世界神经元网络系统的同步动力学

以电耦合的Terman-Wang小世界神经元网络系统为研究对象, 研究了空间关联白噪声影响下神经元网络系统的同步动力学. 首先将动力学平均场近似理论扩展到受空间关联白噪声影响下的小世界网络系统中, 将描述网络系统动力学演化的2N维随机微分方程简化为11个确定性的矩微分方程. 其次, 基于动力学平均场近似理论所推导的矩方程, 讨论了空间关联噪声、网络结构参数对神经元网络系统同步动力学的关键影响, 发现较大的噪声空间关联系数、耦合强度及节点平均度均对神经元网络系统同步放电具有积极作用. 进一步地, 利用计算机仿真数值模拟原神经元网络系统的同步动力学, 并与基于动力学平均场近似理论所得到的结果进行比较, 发现二者具有较好的一致性.     

Variational Solution of Stochastic Schrödinger Equations With Power-Type Nonlinearity

We investigate a Schrödinger problem with multiplicative Gaussian noise term and power-type nonlinearity on a bounded one-dimensional domain. In order to prove the existence and uniqueness of the variational solution, a further process will be introduced which allows to transform the stochastic nonlinear Schrödinger problem into a pathwise one. Galerkin approximations and compact embedding results are used.     

光学频率梳非线性传输及其在相位噪声探测中的应用

光纤传递链路中相位噪声探测是基于光纤的精确射频标准传递系统中重要组成部分。为解决光纤链路相位噪声探测中节点反射干扰的问题, 本文基于广义非线性薛定谔方程, 理论上研究了窄带光学频率梳在色散位移光纤中的非线性光学传播特性。在理论分析的基础上, 结合密集波分复用架构, 提出了一种基于锁模光学频率梳进行光纤传递射频信号的相位噪声探测新技术, 克服了节点反射干扰, 给出了初步实验验证。     

Toward automatic evaluation of defect detectability in infrared images of composites and honeycomb structures

Non-destructive testing (NDT) refers to inspection methods employed to assess a material specimen without impairing its future usefulness. An important type of these methods is infrared (IR) for NDT (IRNDT), which employs the heat emitted by bodies/objects to rapidly and noninvasively inspect wide surfaces and to find specific defects such as delaminations, cracks, voids, and discontinuities in materials. Current advancements in sensor technology for IRNDT generate great amounts of image sequences. These data require further processing to determine the integrity of objects. Processing techniques for IRNDT data implicitly looks for defect visibility enhancement. Commonly, IRNDT community employs signal to noise ratio (SNR) to measure defect visibility. Nonetheless, current applications of SNR are local, thereby overseeing spatial information, and depend on a-priori knowledge of defect’s location. In this paper, we present a general framework to assess defect detectability based on SNR maps derived from processed IR images. The joint use of image segmentation procedures along with algorithms for filling regions of interest (ROI) estimates a reference background to compute SNR maps. Our main contributions are: (i) a method to compute SNR maps that takes into account spatial variation and are independent of a-priori knowledge of defect location in the sample, (ii) spatial background analysis in processed images, and (iii) semi-automatic calculation of segmentation algorithm parameters. We test our approach in carbon fiber and honeycomb samples with complex geometries and defects with different sizes and depths.     

How Many Molecules are Required to Obtain a Steady Faradaic Current from Mediated Electron Transfer at a Single Nanoparticle on a Supporting Surface?

We investigate the chronoamperometric noise characteristics of electron‐transfer reactions occurring on single nanoparticles (NPs) and assemblies of well‐separated NPs on a supporting surface. To this end, we combine a formerly described expression for the steady‐state current of a single particle with the shot‐noise model and derive an expression for the signal‐to‐noise ratio as a function of bulk concentration and particle radius. Our findings are supported by random‐walk simulations, which closely match the analytical results.     

羟甲基化木质素磺酸盐添加剂对钻井液性能的影响

为了进一步优化木质素磺酸盐作为钻井液处理剂的效能,利用其与甲醛的羟甲基化反应制备了羟甲基化木质素磺酸盐;采用红外光谱仪、X射线粉末衍射仪、扫描电镜等分析了其结构;测定了改性前后的木质素磺酸盐对钻井液流变性、降滤失性、黏土水化膨胀抑制性等性能的影响.结果显示,改性后的羟甲基化木质素磺酸盐的整体结构变化不大,但羟基数量增加,与水的相溶性增强.与木质素磺酸盐相比,羟甲基化木质素磺酸盐在室温下对基浆有较强的提黏作用,经180℃高温老化后降黏、降滤失作用有所增强,形成的泥饼厚度降低,对黏土水化膨胀的抑制作用增强.     

Pandemic-Driven Development of a Medical-Grade,Economic and Decentralized Applicable Polyolefin Filament for Additive Fused Filament Fabrication

A polyolefin with certified biocompatibility according to USP class VI was used by our group as feedstock for filament-based 3D printing to meet the highest medical standards in order to print personal protective equipment for our university hospital during the ongoing pandemic. Besides the chemical resistance and durability, as well as the ability to withstand steam sterilization, this polypropylene (PP) copolymer is characterized by its high purity, as achieved by highly efficient and selective catalytic polymerization. As the PP copolymer is suited to be printed with all common printers in fused filament fabrication (FFF), it offers an eco-friendly cost–benefit ratio, even for large-scale production. In addition, a digital workflow was established focusing on common desktop FFF printers in the medical sector. It comprises the simulation-based optimization of personalized print objects, considering the inherent material properties such as warping tendency, through to validation of the process chain by 3D scanning, sterilization, and biocompatibility analysis of the printed part. This combination of digital data processing and 3D printing with a sustainable and medically certified material showed great promise in establishing decentralized additive manufacturing in everyday hospital life to meet peaks in demand, supply bottlenecks, and enhanced personalized patient treatment.     

Wavelet transforms in separation science for denoising and peak overlap detection

Wavelet transform is a versatile time‐frequency analysis technique, which allows localization of useful signals in time or space and separates them from noise. The detector output from any analytical instrument is mathematically equivalent to a digital image. Signals obtained in chemical separations that vary in time (e.g., high‐performance liquid chromatography) or space (e.g., planar chromatography) are amenable to wavelet analysis. This article gives an overview of wavelet analysis, and graphically explains all the relevant concepts. Continuous wavelet transform and discrete wavelet transform concepts are pictorially explained along with their chromatographic applications. An example is shown for qualitative peak overlap detection in a noisy chromatogram using continuous wavelet transform. The concept of signal decomposition, denoising, and then signal reconstruction is graphically discussed for discrete wavelet transform. All the digital filters in chromatographic instruments used today potentially broaden and distort narrow peaks. Finally, a low signal‐to‐noise ratio chromatogram is denoised using the procedure. Significant gains (>tenfold) in signal‐to‐noise ratio are shown with wavelet analysis. Peaks that were not initially visible were recovered with good accuracy. Since discrete wavelet transform denoising analysis applies to any detector used in separation science, researchers should strongly consider using wavelets for their research.     

开式轴流风扇气动噪声预测

本文采用LES/FW-H的匹配方法,研究了开式轴流风扇内部旋涡流动特征及其与叶片表面干涉引起的气动噪声之间的联系,同时进行了远场噪声预测,探讨了叶轮不同表面辐射噪声时的频谱分布特征.研究结果表明,开式轴流风扇吸力面附近形成的叶尖涡和前缘分离涡在吸力面叶片表面相应位置形成大压力波动,形成主要噪声源;叶片吸力面的辐射噪声可以通过改善吸力面附近的旋涡流动来降低;低速轴流叶轮由叶轮壁面辐射的噪声以宽频成分为主.