latent interaction effects, mixture distribution, ML estimation, structural equation modeling (SEM), EM algorithm,

The development of statistically efficient and computationally practicable estimation methods for the analysis of structural equation models with multiple nonlinear effects has been called for by substantive researchers in psychology, marketing research, and sociology. But the development of efficient methods is complicated by the fact that a nonlinear model structure implies specifically nonnormal multivariate distributions for the indicator variables. In this paper, nonlinear structural equation models with quadratic forms are introduced and a new Quasi-Maximum Likelihood method for simultaneous estimation of model parameters is developed with the focus on statistical efficiency and computational practicability. The Quasi-ML method is based on an approximation of the nonnormal density function of the joint indicator vector by a product of a normal and a conditionally normal density. The results of Monte-Carlo studies for the new Quasi-ML method indicate that the parameter estimation is almost as efficient as ML estimation, whereas ML estimation is only computationally practical for elementary models. Also, the Quasi-ML method outperforms other currently available methods with respect to efficiency. It is demonstrated in a Monte-Carlo study that the Quasi-ML method permits computationally feasible and very efficient analysis of models with multiple latent nonlinear effects. Finally, the applicability of the Quasi-ML method is illustrated by an empirical example of an aging study in psychology.

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The generalizability of K. M. Cramer's (1999) help-seeking model was examined for Asian and Asian American college students. The construct of acculturation was then added to Cramer's model to determine if it would improve the model fit. Asian and Asian American (n ϭ 202) students completed help-seeking measures and behavioral and value-based measures of acculturation. White (n ϭ 336) students completed only help-seeking measures. Although path analyses showed that Cramer's model fit both samples, structural invariance analysis indicated differential model functioning between groups that can be primarily attributed to self-concealment, a concept central to understanding Asians' and Asian Americans' attitudes toward help seeking. The addition of acculturation, especially adherence to Asian value, to Cramer's model improved model fit.

Evaluating model fit in nonlinear multilevel structural equation models (MSEM) presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are non-normally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of non-normality, they have not yet been investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.

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In this article we present some weaknesses in the RC4 cipher and their cryptographic applications. Especially we improve the attack described in [2] in such a way, that it will work, if the weak keys described in that paper are avoided. A further attack will work even if the first 256 Byte of the output remain unused. Finally we show that variants of the RC4 algorithm like NGG and RC4A are also vulnerable by these techniques.

Li-ion cells are used in a variety of mobile and stationary applications. Their use must be safe under all conditions, even for aged cells in second-life applications. In the present study, different aging mechanisms are taken into account for accelerating rate calorimetry (ARC) tests. 18650-type cells are cycled at 0 • C (Li plating expected) and at 45 • C (SEI growth expected). After extensive evaluation of the electrochemical results (voltage curve analysis, capacity fade, energy fade, Coulombic efficiency), the cells are tested by PostMortem analysis (CT, GD-OES, SEM) to reveal the main aging mechanisms and by ARC to test the safety behavior. Besides typical ARC results such as onset-of-self-heating, onset-of-thermal runaway and maximum temperatures, as well as acoustic responses of thermal runaway are evaluated and a method is developed to compare fresh cells and cells aged until different SOHs. It turns out that the safety of aged cells is not simply a function of the SOH. However, safety is strongly affected by the main aging mechanism and to the history of operating parameters during the life-time of the cell. Driven by the demand for higher capacity, lower volume, and lower weight, Li-ion technology was developed in the 1980s.1,2 Nowadays, Li-ion technology is used for energy storage in a large variety of applications, e.g. smartphones, tablets, or drones. In particular, electric vehicles in combination with renewable energy sources are promising for reducing climate change and the corresponding glacier melting and sea level rise which is influenced by burning fossil fuels.3-6 For all applications, the safety behavior under all specified operating conditions is most important.7-9 The same is true for aged Li-ion cells used in second-life applications, for example cells which are utilized in stationary energy storage applications after their usage in electric cars.In the past, failure of Li-ion cells led to product recalls which are very expensive for the manufacturers and unsettle customers, even if such incidents happen only in very few cases (ppm range).10 At the moment, safety tests have to be performed with Li-ion prototypes cells before market release. In these tests, fresh cells are always used, however, aged cells are usually neglected. Even if fresh cells show an acceptable safety behavior, this can change for aged cells. 7,[11][12][13][14][15] While some authors observed decreases for certain safety properties, 7,11,12 others found improvements. 12,13,15 It is well known that aging mechanisms change the properties of the materials inside Li-ion cells. [16][17][18][19] Operating conditions and materials have a strong influence on these aging mechanisms. 12,[20][21][22][23] We recently reported on a change of the aging mechanism with temperature for cycling aging of commercial 18650-type cells with graphite anodes and NMC/LMO cathodes. 20 This mechanism change is expressed by a V-shape in Arrhenius plots of the capacity fade rates obtained from cycling at different ambient temperatures. 20 This c...