A Dual Domain Robust Reversible Watermarking Algorithm for Frame Grouping Videos Using Scene Smoothness

The proposed robust reversible watermarking algorithm addresses the compatibility challenges between robustness and reversibility in existing video watermarking techniques by leveraging scene smoothness for frame grouping videos.Grounded in the H.264 video coding standard,the algorithm first employs traditional robust watermark stitching technology to embed watermark information in the low-frequency coefficient domain of the U channel.Subsequently,it utilizes histogram migration techniques in the high-frequency coefficient domain of the U channel to embed auxiliary information,enabling successful watermark extraction and lossless recovery of the original video content.Experimental results demonstrate the algorithm’s strong imperceptibility,with each embedded frame in the experimental videos achieving a mean peak signal-to-noise ratio of 49.3830 dB and a mean structural similarity of 0.9996.Compared with the three comparison algorithms,the performance of the two experimental indexes is improved by 7.59%and 0.4%on average.At the same time,the proposed algorithm has strong robustness to both offline and online attacks:In the face of offline attacks,the average normalized correlation coefficient between the extracted watermark and the original watermark is 0.9989,and the average bit error rate is 0.0089.In the face of online attacks,the normalized correlation coefficient between the extracted watermark and the original watermark is 0.8840,and the mean bit error rate is 0.2269.Compared with the three comparison algorithms,the performance of the two experimental indexes is improved by 1.27%and 18.16%on average,highlighting the algorithm’s robustness.Furthermore,the algorithm exhibits low computational complexity,with the mean encoding and the mean decoding time differentials during experimental video processing being 3.934 and 2.273 s,respectively,underscoring its practical utility.

An Innovative Coupled Common-Node Discrete Element Method-Smoothed Particle Hydrodynamics Model Developed with LS-DYNA and Its Applications

In this study,a common-node DEM-SPH coupling model based on the shared node method is proposed,and a fluid–structure coupling method using the common-node discrete element method-smoothed particle hydrodynamics(DS-SPH)method is developed using LS-DYNA software.The DEM and SPH are established on the same node to create common-node DEM-SPH particles,allowing for fluid–structure interactions.Numerical simulations of various scenarios,including water entry of a rigid sphere,dam-break propagation over wet beds,impact on an ice plate floating on water and ice accumulation on offshore structures,are conducted.The interaction between DS particles and SPH fluid and the crack generation mechanism and expansion characteristics of the ice plate under the interaction of structure and fluid are also studied.The results are compared with available data to verify the proposed coupling method.Notably,the simulation results demonstrated that controlling the cutoff pressure of internal SPH particles could effectively control particle splashing during ice crushing failure.

A modified smoothed particle hydrodynamics method considering residual stress for simulating failure and its application in layered rock mass

Residual strength is an indispensable factor in evaluating rock fracture,yet the current Smoothed Particle Hydrodynamics(SPH)framework rarely considers its influence when simulating fracture.An improved cracking strategy considering residual stress in the base bond SPH method was proposed to simulate failures in layered rocks and slopes and verified by experimental results and other simulation methods(i.e.,the discrete element method).Modified Mohr–Coulomb failure criterion was applied to distinguish the mixed failure of tensile and shear.Bond fracture markψwas introduced to improve the kernel function after tensile damage,and the calculation of residual stress after the damage was derived after shear damage.Numerical simulations were carried out to evaluate its performance under different stress and scale conditions and to verify its effectiveness in realistically reproducing crack initiation and propagation and coalescence,even fracture and separation.The results indicate that the improved cracking strategy precisely captures the fracture and failure pattern in layered rocks and rock slopes.The residual stress of brittle tock is correctly captured by the improved SPH method.The improved SPH method that considers residual strength shows an approximately 13%improvement in accuracy for the safety factor of anti-dip layered slopes compared to the method that does not consider residual strength,as validated against analytical solutions.We infer that the improved SPH method is effective and shows promise for applications to continuous and discontinuous rock masses.

Smoothed-Particle Hydrodynamics Simulation of Ship Motion and Tank Sloshing under the Effect of Regular Waves

Predicting the response of liquefied natural gas(LNG)contained in vessels subjected to external waves is extremely important to ensure the safety of the transportation process.In this study,the coupled behavior due to ship motion and liquid tank sloshing has been simulated by the Smoothed-Particle Hydrodynamics(SPH)method.Firstly,the sloshing flow in a rectangular tank was simulated and the related loads were analyzed to verify and validate the accuracy of the present SPH solver.Then,a three-dimensional simplified LNG carrier model,including two prismatic liquid tanks and a wave tank,was introduced.Different conditions were examined corresponding to different wave lengths,wave heights,wave heading angles,and tank loading rates.Finally,the effects of liquid tank loading rate on LNG ship motions and sloshing loading were analyzed,thereby showing that the SPH method can effectively provide useful indications for the design of liquid cargo ships.

Influence of Angiotensin II on α1-Adrenergic Receptors Function in Rat Aorta and Expression in Vascular Smooth Muscle Cells

Angiotensin II (Ang II) is the main mediator of the Renin-Angiotensin-System acting on AT1 and other AT receptors. It is regarded as a pleiotropic agent that induces many actions, including functioning as a growth factor, and as a contractile hormone, among others. The aim of this work was to examine the impact of Ang II on the expression and function of α1-adrenergic receptors (α1-ARs) in cultured rat aorta, and aorta-derived smooth muscle cells. Isolated Wistar rat aorta was incubated for 24 h in DMEM at 37˚C, then subjected to isometric tension and to the action of added norepinephrine, in concentration-response curves. Ang II was added (1 × 10−5 M), and in some experiments, 5-Methylurapidil (α1A-AR antagonist), AH11110A (α1B-AR antagonist), or BMY-7378 (α1D-AR antagonist), were used to identify the α1-AR involved in the response. Desensitization of the contractile response to norepinephrine was observed due to incubation time, and by the Ang II action. α1D-AR was protected from desensitization by BMY-7378;while RS-100329 and prazosin partially mitigated desensitization. In another set of experiments, isolated aorta-derived smooth muscle cells were exposed to Ang II and α1-ARs proteins were evaluated. α1D-AR increased at 30 and 60 min post Ang II exposure, the α1A-AR diminished from 1 to 4 h, while α1B-AR remained unchanged over 24 h of Ang II exposure. Ang II induced an increase of α1D-AR at short times, and BMY-7378 protected α1D-AR from desensitization.

A flexible multiscale algorithm based on an improved smoothed particle hydrodynamics method for complex viscoelastic flows

Viscoelastic flows play an important role in numerous engineering fields,and the multiscale algorithms for simulating viscoelastic flows have received significant attention in order to deepen our understanding of the nonlinear dynamic behaviors of viscoelastic fluids.However,traditional grid-based multiscale methods are confined to simple viscoelastic flows with short relaxation time,and there is a lack of uniform multiscale scheme available for coupling different solvers in the simulations of viscoelastic fluids.In this paper,a universal multiscale method coupling an improved smoothed particle hydrodynamics(SPH)and multiscale universal interface(MUI)library is presented for viscoelastic flows.The proposed multiscale method builds on an improved SPH method and leverages the MUI library to facilitate the exchange of information among different solvers in the overlapping domain.We test the capability and flexibility of the presented multiscale method to deal with complex viscoelastic flows by solving different multiscale problems of viscoelastic flows.In the first example,the simulation of a viscoelastic Poiseuille flow is carried out by two coupled improved SPH methods with different spatial resolutions.The effects of exchanging different physical quantities on the numerical results in both the upper and lower domains are also investigated as well as the absolute errors in the overlapping domain.In the second example,the complex Wannier flow with different Weissenberg numbers is further simulated by two improved SPH methods and coupling the improved SPH method and the dissipative particle dynamics(DPD)method.The numerical results show that the physical quantities for viscoelastic flows obtained by the presented multiscale method are in consistence with those obtained by a single solver in the overlapping domain.Moreover,transferring different physical quantities has an important effect on the numerical results.

Smoothness加强的全局和局部显著目标检测

显著目标检测是计算机视觉的重要组成部分。针对基于对比度的方法存在的前景和背景容易被误检的问题,提出Smoothness加强的全局和局部显著目标检测的方法。在全局对比度检测过程中引入中心先验知识,在局部对比度检测过程中引入Compactness特征,再使用Smoothness特征加强全局的显著性及局部的显著性,最后将全局显著图和局部显著图进行线性融合。在MSRA-1000、ECSSD数据集上的评估中,该算法有更高的准确率,在CSSD数据集上能和最先进算法相媲美。实验表明,从全局和局部两个角度出发的显著性检测的方法能够有效的互补,Smoothness能够有效加强前景和背景的差异性,并且有效纠正一些误检现象,从而取得更好的结果。

On the k-smoothness and k-strong Smoothness

In this paper, by normwe give a sufficient and necessary condition of k-smooth points and k-strong smooth points.

Machine learning based online fault prognostics for nonstationary industrial process via degradation feature extraction and temporal smoothness analysis

Fault degradation prognostic, which estimates the time before a failure occurs and process breakdowns, has been recognized as a key component in maintenance strategies nowadays. Fault degradation processes are, in general,slowly varying and can be modeled by autoregressive models. However, industrial processes always show typical nonstationary nature, which may bring two challenges: how to capture fault degradation information and how to model nonstationary processes. To address the critical issues, a novel fault degradation modeling and online fault prognostic strategy is developed in this paper. First, a fault degradation-oriented slow feature analysis(FDSFA) algorithm is proposed to extract fault degradation directions along which candidate fault degradation features are extracted. The trend ability assessment is then applied to select major fault degradation features. Second, a key fault degradation factor(KFDF) is calculated to characterize the fault degradation tendency by combining major fault degradation features and their stability weighting factors. After that, a time-varying regression model with temporal smoothness regularization is established considering nonstationary characteristics. On the basis of updating strategy, an online fault prognostic model is further developed by analyzing and modeling the prediction errors. The performance of the proposed method is illustrated with a real industrial process.

Smoothness Prior Approach for Spectral Smoothing and Baseline Correction

Smoothness prior approach for spectral smoothing is investigated using Fourier frequency filter analysis.We show that the regularization parameter in penalized least squares could continuously control the bandwidth of low-pass filter.Besides,due to its property of interpolating the missing values automatically and smoothly,a spectral baseline correction algorithm based on the approach is proposed.This algorithm generally comprises spectral peak detection and baseline estimation.First,the spectral peak regions are detected and identified according to the second derivatives.Then,generalized smoothness prior approach combining identification information could estimate the baseline in peak regions.Results with both the simulated and real spectra show accurate baseline-corrected signals with this method.

A NOTE ON SINGULAR INTEGRALS WITH DOMINATING MIXED SMOOTHNESS IN TRIEBEL-LIZORKIN SPACES

Let h, be a measurable function defined on R^＋ ×R^＋. Let Ω ∈ L（log L^＋）^υq （S^n1-1 × S^n2-1） （1≤ υq ≤ 2） be homogeneous of degree zero and satisfy certain cancellation conditions. We show that the singular integral Tf（x1,x2）=p.v.∫∫R^n1＋n2 Ω（y′1,y′2）h（｜y1｜,｜y2｜）/｜y1｜^n1｜y2｜^n2 f（x1-y1,x2-y2）dy1dy2maps from Sp,q^α1,α2F（R^n1×R^n2）boundedly to itself for 1 〈 p, q 〈 ∞, α1, α2 ∈R.

SMOOTHNESS INDICATOR OF WENO SCHEME FOR RESOLVING SHORT WAVE

Based on the traditional fifth-order weighted essentially non-oscillatory(WENO)scheme,a smoothness indicator is introduced to improve the capability of WENO schemes for resolving short waves.In the construction of the new smoothness indicator,the proportion of the first-order term in the original smoothness indicator is reduced by replacing the square of the first-order term with the product of the first-order and the third-order terms.To preserve the fifth-order of convergence rate,the smoothness indicator is combined with the method of Borges,et al.The numerical results show that the proposed schemes are more suitable for simulating turbulent flows or aeroacoustics problems than the previous fifth-order WENO schemes,thanks to its improved resolution on short waves.

Equivalence between Modulus of Smoothness and K-Functional on Rotation Group SO(3)

In this paper we obtain the equivalence between modulus of smoothness and K-functional on rotation group SO(3).

GLOBAL SMOOTHNESS PRESERVATION BY BIVARIATE INTERPOLATION OPERATORS

Extending the results of [4] in the univariate case, in this paper we prove that the bivariate interpolation polynomials of Hermite-Fejér based on the Chebyshev nodes of the first kind, those of Lagrange based on the Chebyshev nodes of second kind and ±1, and those of bivariate Shepard operators, have the property of partial preservation of global smoothness, with respect to various bivariate moduli of continuity.

MicroRNA-146a Promotes Embryonic Stem Cell Differentiation towards Vascular Smooth Muscle Cells through Regulation of Kruppel-like Factor 4

Objective Vascular smooth muscle cell(VSMC)differentiation from stem cells is one source of the increasing number of VSMCs that are involved in vascular remodeling-related diseases such as hypertension,atherosclerosis,and restenosis.MicroRNA-146a(miR-146a)has been proven to be involved in cell proliferation,migration,and tumor metabolism.However,little is known about the functional role of miR-146a in VSMC differentiation from embryonic stem cells(ESCs).This study aimed to determine the role of miR-146a in VSMC differentiation from ESCs.Methods Mouse ESCs were differentiated into VSMCs,and the cell extracts were analyzed by Western blotting and RT-qPCR.In addition,luciferase reporter assays using ESCs transfected with miR-146a/mimic and plasmids were performed.Finally,C57BL/6J female mice were injected with mimic or miR-146a-overexpressing ESCs,and immunohistochemistry,Western blotting,and RT-qPCR assays were carried out on tissue samples from these mice.Results miR-146a was significantly upregulated during VSMC differentiation,accompanied with the VSMC-specific marker genes smooth muscle-alpha-actin(SMαA),smooth muscle 22(SM22),smooth muscle myosin heavy chain(SMMHC),and h1-calponin.Furthermore,overexpression of miR-146a enhanced the differentiation process in vitro and in vivo.Concurrently,the expression of Kruppel-like factor 4(KLF4),predicted as one of the top targets of miR-146a,was sharply decreased in miR-146a-overexpressing ESCs.Importantly,inhibiting KLF4 expression enhanced the VSMC-specific gene expression induced by miR-146a overexpression in differentiating ESCs.In addition,miR-146a upregulated the mRNA expression levels and transcriptional activity of VSMC differentiation-related transcription factors,including serum response factor(SRF)and myocyte enhancer factor 2c(MEF-2c).Conclusion Our data support that miR-146a promotes ESC-VSMC differentiation through regulating KLF4 and modulating the transcription factor activity of VSMCs.

Equivalence of <i>K</i>-Functionals and Modulus of Smoothness Generated by a Generalized Dunkl Operator on the Real Line

This paper is intended to establish the equivalence between K-functionals and modulus of smoothness tied to a Dunkl type operator on the real line.

Greedy Algorithm in m-Term Approximation for Periodic Besov Class with Mixed Smoothness

Nonlinear m-term approximation plays an important role in machine learning, signal processing and statistical estimating. In this paper by means of a nondecreasing dominated function, a greedy adaptive compression numerical algorithm in the best m -term approximation with regard to tensor product wavelet-type basis is pro-posed. The algorithm provides the asymptotically optimal approximation for the class of periodic functions with mixed Besov smoothness in the L q norm. Moreover, it depends only on the expansion of function f by tensor pro-duct wavelet-type basis, but neither on q nor on any special features of f.

Automatic Assessment of Fabric Smoothness Grade Using Double CCD Grating Projection

Automatically assessing fabric smoothness grade is very important in the evaluation of fabric appearance.A system for objectively evaluating the fabric smoothness grade based on a grating projection unit and double colored CCD(short form of charge coupled device) was constructed in this paper.Two images captured by different CCD compensated each other which reduced the influence of noises.The application of the four-step phase-shifting method enabled the calculation of the exact phase in a point easy and quick.A large amount of 3D points with three coordinates X,Y and Z were obtained precisely making the definition and calculation of fabric smoothness characters easy.Then four parameters which intuitively denoted the fabric smoothness degree were obtained.Finally,a proper neural network was built,which successfully performed the fabric smoothness classification.The experimental results show that the system is applicable for all the fabric whatever pattern or color.The experimental grades provided by this grating projection system are also highly consistent with the subjective results.

Inhibitory Effect of PPARδAgonist GW501516 on Proliferation of Hypoxia-induced Pulmonary Arterial Smooth Muscle Cells by Regulating the mTOR Pathway

Objective This study aimed to investigate the effects of the peroxisome proliferator-activated receptorδ(PPARδ)agonist GW501516 on the proliferation of pulmonary artery smooth muscle cells(PASMCs)induced by hypoxia,in order to search for new drugs for the treatment and prevention of pulmonary vascular remodeling.Methods PASMCs were incubated with different concentrations of GW501516(10,30,100 nmol/L)under the hypoxic condition.The proliferation was determined by a CCK-8 assay.The cell cycle progression was analyzed by flow cytometry.The expression of PPARδ,S phase kinase-associated protein 2(Skp2),and cell cycle-dependent kinase inhibitor p27 was detected by Western blotting.Then PASMCs were treated with 100 nmol/L GW501516,100 nmol/L mammalian target of rapamycin(mTOR)inhibitor rapamycin and/or 2µmol/L mTOR activator MHY1485 to explore the molecular mechanisms by which GW501516 reduces the proliferation of PASMCs.Results The presented data demonstrated that hypoxia reduced the expression of PPARδin an oxygen concentration-and time-dependent manner,and GW501516 decreased the proliferation of PASMCs induced by hypoxia by blocking the progression through the G0/G1 to S phase of the cell cycle.In accordance with these findings,GW501516 downregulated Skp2 and upregulated p27 in hypoxia-exposed PASMCs.Further experiments showed that rapamycin had similar effects as GW501516 in inhibiting cell proliferation,arresting the cell cycle,regulating the expression of Skp2 and p27,and inactivating mTOR in hypoxia-exposed PASMCs.Moreover,MHY1485 reversed all the beneficial effects of GW501516 on hypoxia-stimulated PASMCs.Conclusion GW501516 inhibited the proliferation of PASMCs induced by hypoxia through blocking the mTOR/Skp2/p27 signaling pathway.

Application of Rough Sets to Evaluate Fabric Smoothness Grade

For garment or fabric appearance, the cloth smoothness grade is one of the most important performance factors in textile and garment community. In this paper, on the base of Rough Set Theory,a new objective method for fabric smoothness grade evaluation was constructed. The objective smoothness grading model took the parameters of 120 AATCC replicas' point-sampled models as the conditional attributes and formed the smoothness grading decision table. Then, NS discretization method and genetic algorithm reduction method were used in the attributes discretization and feature reduction. Finally, the grading model was expressed as simple and intuitional classification rules. The simulation results show the validity of the fabric smoothness grading system which is built on the use of rough sets.