Nonsimilar solution of a boundary layer flow of a Reiner–Philippoff fluid with nonlinear thermal convection

The thermodynamics modeling of a Reiner–Philippoff-type fluid is essential because it is a complex fluid with three distinct probable modifications. This fluid model can be modified to describe a shear-thinning, Newtonian, or shear-thickening fluid under varied viscoelastic conditions. This study constructs a mathematical model that describes a boundary layer flow of a Reiner–Philippoff fluid with nonlinear radiative heat flux and temperature- and concentration-induced buoyancy force. The dynamical model follows the usual conservation laws and is reduced through a nonsimilar group of transformations. The resulting equations are solved using a spectral-based local linearization method, and the accuracy of the numerical results is validated through the grid dependence and convergence tests. Detailed analyses of the effects of specific thermophysical parameters are presented through tables and graphs. The study reveals, among other results, that the buoyancy force, solute and thermal expansion coefficients, and thermal radiation increase the overall wall drag, heat, and mass fluxes. Furthermore, the study shows that amplifying the space and temperature-dependent heat source parameters allows fluid particles to lose their cohesive force and, consequently, maximize flow and heat transfer.     

基于改进残差特征蒸馏的轻量级超分辨率网络

基于深度学习的图像超分辨率算法通常采用递归的方式或参数共享的策略来减少网络参数，这将增加网络的深度，使得运行网络花费大量的时间，从而很难将模型部署到现实生活中。为了解决上述问题，本文设计一种轻量级超分辨率网络，对中间特征的关联性及重要性进行学习，且在重建部分结合高分辨率图像的特征信息。首先，引入层间注意力模块，通过考虑层与层之间的相关性，自适应地分配重要层次特征的权重。其次，使用增强重建模块提取高分辨率图像中更精细的特征信息，以此得到更加清晰的重建图片。通过大量的对比实验表明，本文设计的网络与其他轻量级模型相比，有更小的网络参数量，并且在重建精度和视觉效果上都有一定的提升。     

Numerical simulation of the influence of confined multi-point ignited H2–O2 mixture on the propagation of shock waves towards a deformable plate

The study of shock wave propagation in a detonation chamber is of great importance as a part of the plate forming process. Investigations related to the effects of premixed gas detonation on the deflection of a plate require in-depth examination. An Eulerian-Lagrangian numerical simulation is conducted using the space-time conservation element and solution element method of LS-DYNA software to study the effect of confined multi-point ignited gaseous mixture on the dynamic response of thin plates clamped at the end of a combustion chamber. The FSI couples a Lagrangian finite element solver with a Eulerian fluid solver in a 2D space with detailed chemistry of H₂–O₂ mixture. The solution contains the detonation wave propagation through the combustion chamber and its interaction with the plate. The influence of variation in the multi-point ignition locations and combustion chamber dimensions on the pressure history and plate deflection is studied. To verify the model, a comparison with the experimental study is carried out using an adjustable model representative of the real experiment. The verified model is used to link the evolution of plate shape with the arrival time and intensity of shock waves within the chamber. It is found that a longer distance between the ignition point and the plate intensifies the ultimate deflection of the plate. In addition, a fairly large combustion area employed in a direction rather than transverse to the plate surface is unable to influence the ultimate deformation of the plate.     

No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion

This paper presents a novel No-Reference Video Quality Assessment (NR-VQA) model that utilizes proposed 3D steerable wavelet transform-based Natural Video Statistics (NVS) features as well as human perceptual features. Additionally, we proposed a novel two-stage regression scheme that significantly improves the overall performance of quality estimation. In the first stage, transform-based NVS and human perceptual features are separately passed through the proposed hybrid regression scheme: Support Vector Regression (SVR) followed by Polynomial curve fitting. The two visual quality scores predicted from the first stage are then used as features for the similar second stage. This predicts the final quality scores of distorted videos by achieving score level fusion. Extensive experiments were conducted using five authentic and four synthetic distortion databases. Experimental results demonstrate that the proposed method outperforms other published state-of-the-art benchmark methods on synthetic distortion databases and is among the top performers on authentic distortion databases. The source code is available at https://github.com/anishVNIT/two-stage-vqa.     

Meticulously tailoring phase boundary in KNN-based ceramics to enhance piezoelectricity and temperature stability

Although KNN-based ceramics with high electrical properties are obtained through a variety of strategies, the temperature sensitivity is still one of the key technical bottlenecks hindering practical applications. Here, we use a new strategy, meticulously tailoring phase boundary, to refine the ferroelectric boundary of KNN-based ceramics, leading to high piezoelectricity companied with improving temperature stability. The highest d₃₃ value in this system reaches 501 pC/N with a T_C ∼ 240°C, whereas a large strain of ∼0.134% can be kept with 10% lower deterioration until 100°C. The origin of high piezoelectricity is mainly attributed to the well-preserved multiphase coexistence and the appearance of nanodomains, which greatly facilitate the polarization rotation. Instead of the changed intrinsic thermal insensitivity, the precision phase boundary engineering plays an important role in strengthening the temperature stability of electric-induced strain. This work provides a simple and effective method to obtain both high electrical properties and excellent thermal stability in KNN-based ceramics, which is expected to promote the practical applications in the future.     

The use of seed texture features for discriminating different cultivars of stored apples

The aim of this study was to identify the textural features of apple seeds with the highest discriminatory power for distinguishing the seeds of different apple cultivars with the use of discriminative classifiers. The seeds of apple cvs. Gala, Jonagold and Idared were scanned with the use of a flatbed scanner, and the acquired images were processed to calculate textural features from color channels: L, a, b, R, G, B, Y, U, V, H, S, I, X, Y and Z. The selected textures were used to develop discriminative models and distinguish the seeds of the examined apple cultivars. The analyses were performed for color spaces and color channels. The seeds of apple cvs. Gala and Idared were discriminated with 100% accuracy in models based on the textures from Lab and YUV color spaces and color channel L for the Naive Bayes, Multilayer Perceptron and Multi Class classifiers. The discriminatory accuracies of the seeds of all analyzed apple cultivars (Gala, Idared and Jonagold) ranged from 72% to 85%. The discriminatory accuracy of the textures selected from Lab color space for the Naive Bayes classifier reached 85%. The seeds of apple cvs. Gala and Jonagold were discriminated with 78–90% accuracy, and the discriminatory accuracy of the textures from Lab color space and color channel b for the Naive Bayes classifier reached 90%. The seeds of apple cvs. Idared and Jonagold were distinguished with 80–94% accuracy. The models based on textures from Lab color space and color channel b for the Naive Bayes classifier were characterized by 94% discriminatory accuracy. The study demonstrated that textural features are useful for discriminating the seeds of different apple cultivars.     

非分裂完全匹配层边界存储时间域全波形反演

正演波场的储存或重建是制约时间域全波形反演的关键问题，以计算代替存储的常规分裂完全匹配层（PML）边界存储策略可有效减少存储量。但常规分裂PML边界条件所需变量个数多、计算存储量大以及编程复杂。为此，采用非分裂复频移完全匹配层（CFS-NPML）有效边界存储策略重建正演波场实现时间域全波形反演。研究表明：CFS-NPML所需变量个数少，在边界吸收层网格点较少时吸收效果优于常规PML边界条件，波场重建过程中所需存储量少于常规PML边界条件。数值试验表明，该存储策略得到的重建波场与正向传播波场几乎无差别，其全波形反演结果与常规保存波场反演法一致；正演过程中引入并行计算技术未显著增加波场重建导致的额外正演时间。     

傣族织锦的艺术特征与传承

文章阐述了傣族织锦的艺术特征及传承发展现状,对其纹样、内涵及应用进行了分析,提出了傣锦传承和发展的措施与方法,为傣锦的保护和传承提供参考。     

显色图像分析技术在水稻叶耳花青甙显色目测分级中的应用

目的基于颜色特征的叶耳花青甙显色分级研究。方法以水稻倒二叶叶耳花青甙显色测试为切入点,在Emgu Cv3.0图像分析软件基础上,对完成图像分割的目标区域提取红绿蓝(red green blue, RGB)、色调饱和度亮度(hue saturation value, HSV)颜色特征,利用SPSS软件对颜色特征和测试分级数据进行相关性、回归等统计分析,建立颜色特征多元回归模型。结果叶耳花青甙显色强度与R(红色)、G(绿色)、B(蓝色)、H(色调)、V(亮度)极显著负相关;所有颜色特征值中,G值与叶耳花青甙显色强度相关性最显著,是一元和多元回归主要自变量; G值建立的一元回归模型中, R~2为0.980;多元回归模型R~2值为0.994。结论回归模型的拟合效果好,用这两个模型均可完成叶耳花青甙显色强度分级。