Integrated Use of Alternative Methods for Evaluating the Skin Sensitization Potencies of Five Frequently Used Preservatives in Cosmetics

In vitro skin sensitization testing methods based on the adverse outcome pathway(AOP)were used to evaluate the skin sensitization potencies of 5 commonly used preservatives.According to the“2 out of 3”principle of the integrated approaches to testing and assessment(IATA)the direct peptide reactivity assay(DPRA)and the human cell line activation test(h-CLAT)were used to detect the preservatives commonly used in cosmetics,including phenoxyethanol.methyl paraben,propyl paraben,imidazolidinyl urea and DMDM hydantoin.The DPRA and the h-CLA were carried out according to the OEC442C and 442E guidelines,respectively.The results show that.phenoxyethanol and methyl paraben are both negative in DPRA and h-CLAT while imidazolidinyl urea and DMDM hydantoin are both positive in these two tests.Propyl paraben has negative result in DPRA but positive result in h-CLAT.Therefore,imidazolidiny urea and DMDM hydantoin are sensitizers,while phenoxyethanol and methylparaben are non-sensitizers.Taken animal and human data into consideration,it is predicted that propyl paraben should be a non-sensitizer.The combination of DPRA and h-CLAT can make up for the limitations of using a single method,and it is suitable for the preliminary screening of cosmetic raw materials according to skin sensitization.

Using an Alternative Method to Estimate the Status of Iodine Nutrition in Pregnant Women

Iodine is an element that is essential for the synthesis of thyroid hormones.Adequate intake of dietary iodine has been recognized as a critical factor for maintaining health.It is a well-known fact that iodine deficiency can impede the production of thyroid hormones in both the mother and fetus,which increases the risk of brain damage in the fetal stage.

Impact Force Localization and Reconstruction via ADMM-based Sparse Regularization Method

In practice,simultaneous impact localization and time history reconstruction can hardly be achieved,due to the illposed and under-determined problems induced by the constrained and harsh measuring conditions.Although l_(1) regularization can be used to obtain sparse solutions,it tends to underestimate solution amplitudes as a biased estimator.To address this issue,a novel impact force identification method with l_(p) regularization is proposed in this paper,using the alternating direction method of multipliers(ADMM).By decomposing the complex primal problem into sub-problems solvable in parallel via proximal operators,ADMM can address the challenge effectively.To mitigate the sensitivity to regularization parameters,an adaptive regularization parameter is derived based on the K-sparsity strategy.Then,an ADMM-based sparse regularization method is developed,which is capable of handling l_(p) regularization with arbitrary p values using adaptively-updated parameters.The effectiveness and performance of the proposed method are validated on an aircraft skin-like composite structure.Additionally,an investigation into the optimal p value for achieving high-accuracy solutions via l_(p) regularization is conducted.It turns out that l_(0.6)regularization consistently yields sparser and more accurate solutions for impact force identification compared to the classic l_(1) regularization method.The impact force identification method proposed in this paper can simultaneously reconstruct impact time history with high accuracy and accurately localize the impact using an under-determined sensor configuration.

Application of in Vitro Alternative Tests Based on AOP in Skin Sensitization Evaluation of Cosmetics

To evaluate and discuss two novels in vitro alternative tests which based on the 2nd and 4th event of the AOP in skin sensitization and their application in skin sensitization evaluation of cosmetics in vitro.The DSens(DSens method)and Jurkat(TCPA method)were used as the test models and 9 of reference chemicals and 12 kinds of cosmetic products were used to confirm and assess the application capability in skin sensitization.The results showed that the DSens method was more sensitive to the reference chemicals compare to the TCPA method.All the results of cosmetic products showed a high consistency between these two assays and h-CLAT or in vivo assay.As the new screening method for skin sensitization evaluation of cosmetics,the in vitro alternative tests based on AOP have certain effectiveness.The reasonable combination strategy can bring a bright future for the development and application of animal alternative test in China.

Two-level Bregmanized method for image interpolation with graph regularized sparse coding

A two-level Bregmanized method with graph regularized sparse coding （TBGSC） is presented for image interpolation. The outer-level Bregman iterative procedure enforces the observation data constraints, while the inner-level Bregmanized method devotes to dictionary updating and sparse represention of small overlapping image patches. The introduced constraint of graph regularized sparse coding can capture local image features effectively, and consequently enables accurate reconstruction from highly undersampled partial data. Furthermore, modified sparse coding and simple dictionary updating applied in the inner minimization make the proposed algorithm converge within a relatively small number of iterations. Experimental results demonstrate that the proposed algorithm can effectively reconstruct images and it outperforms the current state-of-the-art approaches in terms of visual comparisons and quantitative measures.

Fast alternating direction method of multipliers for total-variation-based image restoration

A novel algorithm, i.e. the fast alternating direction method of multipliers （ADMM）, is applied to solve the classical total-variation （ TV ）-based model for image reconstruction. First, the TV-based model is reformulated as a linear equality constrained problem where the objective function is separable. Then, by introducing the augmented Lagrangian function, the two variables are alternatively minimized by the Gauss-Seidel idea. Finally, the dual variable is updated. Because the approach makes full use of the special structure of the problem and decomposes the original problem into several low-dimensional sub-problems, the per iteration computational complexity of the approach is dominated by two fast Fourier transforms. Elementary experimental results indicate that the proposed approach is more stable and efficient compared with some state-of-the-art algorithms.

An Efficient Smoothing and Thresholding Image Segmentation Framework with Weighted Anisotropic-Isotropic Total Variation

In this paper,we design an efficient,multi-stage image segmentation framework that incorporates a weighted difference of anisotropic and isotropic total variation(AITV).The segmentation framework generally consists of two stages:smoothing and thresholding,thus referred to as smoothing-and-thresholding(SaT).In the first stage,a smoothed image is obtained by an AITV-regularized Mumford-Shah(MS)model,which can be solved efficiently by the alternating direction method of multipliers(ADMMs)with a closed-form solution of a proximal operator of the l_(1)-αl_(2) regularizer.The convergence of the ADMM algorithm is analyzed.In the second stage,we threshold the smoothed image by K-means clustering to obtain the final segmentation result.Numerical experiments demonstrate that the proposed segmentation framework is versatile for both grayscale and color images,effcient in producing high-quality segmentation results within a few seconds,and robust to input images that are corrupted with noise,blur,or both.We compare the AITV method with its original convex TV and nonconvex TVP(O<p<1)counterparts,showcasing the qualitative and quantitative advantages of our proposed method.

Fully Distributed Learning for Deep Random Vector Functional-Link Networks

In the contemporary era, the proliferation of information technology has led to an unprecedented surge in data generation, with this data being dispersed across a multitude of mobile devices. Facing these situations and the training of deep learning model that needs great computing power support, the distributed algorithm that can carry out multi-party joint modeling has attracted everyone’s attention. The distributed training mode relieves the huge pressure of centralized model on computer computing power and communication. However, most distributed algorithms currently work in a master-slave mode, often including a central server for coordination, which to some extent will cause communication pressure, data leakage, privacy violations and other issues. To solve these problems, a decentralized fully distributed algorithm based on deep random weight neural network is proposed. The algorithm decomposes the original objective function into several sub-problems under consistency constraints, combines the decentralized average consensus (DAC) and alternating direction method of multipliers (ADMM), and achieves the goal of joint modeling and training through local calculation and communication of each node. Finally, we compare the proposed decentralized algorithm with several centralized deep neural networks with random weights, and experimental results demonstrate the effectiveness of the proposed algorithm.

Progressive Collapse Resistance of a New Staggered Story Isolated System

A new staggered isolated system developed from the mid-story isolated system is the new staggered story isolated system. There are not many studies on this structure currently. In this study, an 18-story new staggered story isolated system model is established using SAP2000. The dynamic nonlinear dynamic alternate method is used to analyze the structure against progressive collapse. Results show that the structure has good resistance to progressive collapse, and there is no progressive collapse under each working condition. The progressive collapse does not occur for the case of removing only one vertical structural member of the new staggered of isolated system. The side column has big influence on this isolated structures’ progressive collapse;the removal of vertical structural member of the isolation layer has less impact on the structure than the removal of the bottom vertical structural member. After the removing of the member, the internal force of the structure will be redistributed, and the axial force of the adjacent columns will change obviously, showing a trend of “near large and far small”.

Calculation of the Approximate Energy of Ground and Excited Stationary States in Quantum Mechanics Using Delta Method

In this paper, pursuing a new advised method called Delta method which is basically similar to variational method, we find the ground and excited states, according to a typical quantum Hamiltonian. Moreover, applying this method, the upper bound values for the eigenenergies of the so-called ground and excited states are estimated. We will show that this new method, is as beneficial as the traditional variational method which is common in deriving eigenenergies of some of the quantum Hamiltonians. This method helps physics students to broaden their knowledge about the possible mathematical ways;they can use to obtain eigenenergies of some quantum Hamiltonians. The advantage of Delta method to variational method is in its simplicity and reduction of the calculation procedures.

Development of Alternative to Animal Testing on Cosmetics by Middle-out Strategy

The discussion on cosmetic animal testing ban started since 1990s, with the fnally implementation of full animal testing ban in both research and marketing in EU and Israel in 2013. Now it has been fully or partially banned by law in 33 countries or regions, with more and more countries lining up to do the same. Beyond animal welfare consideration, the need of mutual acceptance of data （MAD） and harmonization of global market have made non-animal testing an irresistible general trend for worldwide countries to made regulation and policy. Recently, China is in critical crossroad to shift the toxicity paradigm and explore a proper strategy to promote the development of cosmetic non-animal testing. 3R theory has been frstly introduced in Chinese legislation in 2006 that is an important step forward to seriously thinking of animal test. In the following 10 years, the alternative technology in China has been developed dramatically with the implementation of relevant legislations, holding various theoretical and hands-on training, exploration work on methods validation, adoption of internationally recognized methods, propagation of alternative standards and in-depth investigation in in vitro bioscience. The ultimate goal of alternative technology is the regulatory application, thus demands infrastructure constructing, technology capability building and national standard forming. However, concrete works should be carefully planned to facilitate the technology transformation and standardization. This paper will give a retrospective review on the progress in recent years and put forward a middle-out strategy to promote the development of cosmetics alternative in China.

Method Optimization and Application Extension of Bovine Corneal Opacity and Permeability Assay

This paper systematically summarizes the improvements in bovine corneal opacity and permeability assay(BCOP),an alternative method of eye irritation test,further explores the usage mode of combinatorial methods with BCOP at the core module,introduces the application of each single method and their combination in the assessment of pesticides,plant extracts,medical devices and medicines.By optimizing traditional methods,the alternative method is more scientific and individually applicable.

Image reconstruction based on total-variation minimization and alternating direction method in linear scan computed tomography

Linear scan computed tomography （LCT） is of great benefit to online industrial scanning and security inspection due to its characteristics of straight-line source trajectory and high scanning speed. However, in practical applications of LCT, there are challenges to image reconstruction due to limited-angle and insufficient data. In this paper, a new reconstruction algorithm based on total-variation （TV） minimization is developed to reconstruct images from limited-angle and insufficient data in LCT. The main idea of our approach is to reformulate a TV problem as a linear equality constrained problem where the objective function is separable, and then minimize its augmented Lagrangian function by using alternating direction method （ADM） to solve subproblems. The proposed method is robust and efficient in the task of reconstruction by showing the convergence of ADM. The numerical simulations and real data reconstructions show that the proposed reconstruction method brings reasonable performance and outperforms some previous ones when applied to an LCT imaging problem.

Reconstruction of electrical capacitance tomography images based on fast linearized alternating direction method of multipliers for two-phase flow system

Electrical capacitance tomography(ECT)has been applied to two-phase flow measurement in recent years.Image reconstruction algorithms play an important role in the successful applications of ECT.To solve the ill-posed and nonlinear inverse problem of ECT image reconstruction,a new ECT image reconstruction method based on fast linearized alternating direction method of multipliers(FLADMM)is proposed in this paper.On the basis of theoretical analysis of compressed sensing(CS),the data acquisition of ECT is regarded as a linear measurement process of permittivity distribution signal of pipe section.A new measurement matrix is designed and L1 regularization method is used to convert ECT inverse problem to a convex relaxation problem which contains prior knowledge.A new fast alternating direction method of multipliers which contained linearized idea is employed to minimize the objective function.Simulation data and experimental results indicate that compared with other methods,the quality and speed of reconstructed images are markedly improved.Also,the dynamic experimental results indicate that the proposed algorithm can ful fill the real-time requirement of ECT systems in the application.

Nested Alternating Direction Method of Multipliers to Low-Rank and Sparse-Column Matrices Recovery

The task of dividing corrupted-data into their respective subspaces can be well illustrated,both theoretically and numerically,by recovering low-rank and sparse-column components of a given matrix.Generally,it can be characterized as a matrix and a 2,1-norm involved convex minimization problem.However,solving the resulting problem is full of challenges due to the non-smoothness of the objective function.One of the earliest solvers is an 3-block alternating direction method of multipliers(ADMM)which updates each variable in a Gauss-Seidel manner.In this paper,we present three variants of ADMM for the 3-block separable minimization problem.More preciously,whenever one variable is derived,the resulting problems can be regarded as a convex minimization with 2 blocks,and can be solved immediately using the standard ADMM.If the inner iteration loops only once,the iterative scheme reduces to the ADMM with updates in a Gauss-Seidel manner.If the solution from the inner iteration is assumed to be exact,the convergence can be deduced easily in the literature.The performance comparisons with a couple of recently designed solvers illustrate that the proposed methods are effective and competitive.

Two-stage ADMM-based distributed optimal reactive power control method for wind farms considering wake effects

Since the connection of small-scale wind farms to distribution networks,power grid voltage stability has been reduced with increasing wind penetration in recent years,owing to the variable reactive power consumption of wind generators.In this study,a two-stage reactive power optimization method based on the alternating direction method of multipliers(ADMM)algorithm is proposed for achieving optimal reactive power dispatch in wind farm-integrated distribution systems.Unlike existing optimal reactive power control methods,the proposed method enables distributed reactive power flow optimization with a two-stage optimization structure.Furthermore,under the partition concept,the consensus protocol is not needed to solve the optimization problems.In this method,the influence of the wake effect of each wind turbine is also considered in the control design.Simulation results for a mid-voltage distribution system based on MATLAB verified the effectiveness of the proposed method.

ALTERNATING METHOD STUDY ON STRESS ANALYSIS OF SURROUNDING ROCK FOR TWO RANDOM GEOMETRY TUNNELS

The stress analysis of surrounding rock for two random geometry tunnels is studied in this paper by using Schwarz’s alternating method. The simple and effective alternating algorithm is found, in which the surplus surface force is approximated by Fourier series, thus the iteration derivation can be conducted according to the precision required, finally, the stress results with high precision are obtained.

Alternating Direction Finite Volume Element Methods for Three-Dimensional Parabolic Equations

This paper presents alternating direction finite volume element methods for three-dimensional parabolic partial differential equations and gives four computational schemes, one is analogous to Douglas finite difference scheme with second-order splitting error, the other two schemes have third-order splitting error, and the last one is an extended LOD scheme. The L2 norm and H1 semi-norm error estimates are obtained for the first scheme and second one, respectively. Finally, two numerical examples are provided to illustrate the efficiency and accuracy of the methods.

Crank-Nicolson ADI Galerkin Finite Element Methods for Two Classes of Riesz Space Fractional Partial Differential Equations

In this paper,two classes of Riesz space fractional partial differential equations including space-fractional and space-time-fractional ones are considered.These two models can be regarded as the generalization of the classical wave equation in two space dimensions.Combining with the Crank-Nicolson method in temporal direction,efficient alternating direction implicit Galerkin finite element methods for solving these two fractional models are developed,respectively.The corresponding stability and convergence analysis of the numerical methods are discussed.Numerical results are provided to verify the theoretical analysis.