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The dynamic characteristics prediction and frequency-modulation of pipeline was an important work for the design of aircraft hydraulic structure.

A complex pipeline was deemed as a combination of several segments of straight-pipe-element (SPE). The 3D vibration equations of each SPE were established in their local coordinate system based on Timoshenko-beam model and Euler-beam model, respectively. The dynamic-stiffness-matrixes were deduced from the dispersion relation of these equations. According to the complex pipeline layout in the global coordinate system, a multi dynamic stiffness matrixes assembling (MDSMA) algorithm was carried out to establish the characteristic equations of the whole complex pipeline. The MDSMA solutions were verified to be consistent with experimental results.

The MDSMA method based on Timoshenko-Beam model was more suitable for the short span aviation pipeline and the vibration at high frequency stage (>350 Hz). The layout affected the pipeline's in-plane stiffness and out-plane stiffness, for the Z-shaped pipe, each order natural mode took place on the ZP and NP alternately. Reasonable designs of bending position and bending radius were effective means for complex pipeline frequency-modulation.

A new dynamic modeling method of aircraft complex pipeline was proposed to obtain the influence of pipeline layout parameters on dynamic characteristics.

Improvement and optimization design of a two-stage vibration isolation system proposed in this paper are conducted to ensure the device of electronic work effective.

The proposed two-stage vibration isolation system of airborne equipment is optimized and parameterized based on multi-objective genetic algorithm.

The results show that compared with initial two-stage vibration isolation system, the angular vibration of the two-stage vibration isolation system becomes 3.55 × 10^-4 rad, which decreases by 89%. The linear isolation effect is improved by at least 67.7%.

The optimized two-stage vibration isolation system effectively improves the vibration reduction effect, the resonance peak is obviously improved and the reliability of the mounting bracket and the shock absorber is highly improved, which provides an analysis method for two-stage airborne equipment isolation design under complex dynamic environment.

This paper aims to propose a two-stage vibration isolation system for large airborne equipment to isolate aircraft vibration load.

First, the vibration isolation law of the discrete model of large airborne equipment under different damping ratios, stiffness ratios and mass ratios is analyzed, which guides the establishment of a three-dimensional solid model of large airborne equipment. Subsequently, the vibration isolation transfer efficiency is analyzed based on the three-dimensional model of the airborne equipment, and the angular and linear vibration responses of the two-stage vibration isolation system under different frequencies are studied.

Finally, studies have shown that the steady-state angular vibration at the non-resonant frequency changes little. In contrast, the maximum angular vibration at the resonance peak reaches 0.0033 rad, at least 20 times the response at the non-resonant frequency. The linear vibration at the resonant frequency is at least 2.14 times the response at the non-resonant frequency. Obviously, the amplification factor of linear vibration is less than that of angular vibration, and angular vibration has the most significant effect on the internal vibration of airborne equipment.

The two-stage vibration isolation equipment designed in this paper has a positive guiding significance for the vibration isolation design of large airborne equipment.

This article has been withdrawn as it was published elsewhere and accidentally duplicated. The original article can be seen here: 10.1108/00022660710780641. When citing the article, please cite: Chen Li, Chongzhao Han, Huimin Chen, Hongyan Zhu, (2007), “Data association for target tracking by IR sensors”, Aircraft Engineering and Aerospace Technology, Vol. 79 Iss: 5, pp. 511 - 517.

This paper seeks to examine the dynamic problem of associating measurements at a given period from several IR sensors in the presence of clutter, missed detections.

On the basis of a dynamic S‐D assignment algorithm, a new association algorithm for associating and tracking multiple targets is presented. By considering the special feature of the IR sensor, the dynamic assignment cost coefficient incorporates the radiation intensity information into the association process using a joint probabilistic model for the two separate sources of information (intensity and trajectory).

The simulation results show that the new algorithm can attain almost the same accuracy of tracking estimation with less computational load by utilizing special feature information of the IR sensor into dynamic S‐D assignment.

There are still some parameters to be set in advance, which influence the estimate result to some extent. And the tracking stage follows the image processor, so the tracking performance is also related with the quality of images. Those problems will be considered deeply in the future research based on different maneuvering level of targets and the real tracking environment.

This new algorithm may be adopted by tracking systems based on passive sensors in the future.

This new algorithm utilizes more information and fairly small and stable errors in position and velocity can be obtained. At the same time, it decreases computational load.

The purpose of this paper is to propose an iterative Legendre technique to deal with a continuous optimal control problem (OCP).

For the system in the considered problem, the control variable is a function of the state variables and their derivatives. State variables in the problem are approximated by Legendre expansions as functions of time t. A constant matrix is given to express the derivatives of state variables. Therefore, control variables can be described as functions of time t. After that, the OCP is converted to an unconstrained optimization problem whose decision variables are the unknown coefficients in the Legendre expansions.

The convergence of the proposed algorithm is proved. Experimental results, which contain the controlled Duffing oscillator problem demonstrate that the proposed technique is faster than existing methods.

Experimental results, which contained the controlled Duffing oscillator problem demonstrate that the proposed technique can be faster while securing exactness.

This paper aims to examine how emotions affect consumers' food choices and food preparation activities during stressful periods, using the context of the coronavirus disease 2019 (COVID-19) outbreak in China.

This study used an online survey, with a sample of 1,050 individuals from 32 regions in China. Multi-regression and mediation models were used to test the relationships among perceived knowledge, emotions and food behaviors.

The results show that positive emotions positively affect healthy food consumption and engagement in food preparations. In contrast, negative emotions contribute to an increase in indulgent food consumption and quick-and-easy meal preparations. Increased knowledge of the current situation can enhance positive emotions and thus promote healthy food behaviors. Lacking knowledge may result in unhealthy food behaviors through negative emotions.

This study contributes to the understanding of emotions and food behaviors by examining the effects of both negative and positive emotions in the general population, exploring a wider constellation of food behaviors and identifying perceived knowledge as an important antecedent to emotions' effects on food behaviors. Implications for consumers and public policy are offered.

The purpose of this study is to explore the association between eating patterns, social identity and the well-being of adolescents via a mixed methods study of Chinese teenagers. The specific research questions presented in this study are as follows: What is the relationship between social eating and well-being? How is the relationship between social eating and well-being mediated by social identity?

This study is based on a sequential mixed methods study, including interviews with 16 teenage–parent dyads, and a large-scale survey of over 1,000 teenagers on their eating patterns, conducted with the support of public schools. A model that tests relationships among social eating, social identity and subjective well-being is developed and tested.

The results show that dining with family members leads to improved subjective well-being for teenagers, through a partial mediator of stronger family identity. However, dining with peers is not found to influence subjective well-being.

The privileged position of family meals demonstrated through this study may be an artifact of the location of this study in one Chinese city. Further research is needed related to the connections among social identity, objective well-being and the social patterns of teenagers’ food consumption behavior.

To improve the subjective well-being of teenagers, families, public policy-makers and food marketers should support food consumption patterns that promote family meals.

While many food-related consumer studies focus on the individual, social and environmental influences of food choices of adolescents, few studies address how eating patterns affect overall well-being. These results reinforce the importance of understanding the effect of the social context of teenagers’ eating patterns on health and well-being.

The purpose of this paper is to predict the effect of bra pad specifications on breast deformation during jumping using a finite element (FE) method. Breast deformation is a key concern for women during exercise and can be effectively controlled with sports bras. In most studies, the deformation of breasts when wearing a sports bra is measured using motion capture devices to judge their effectiveness. However, the operation of such devices is highly complex and time-consuming. Computer-aided technology is an efficient way to simulate these experiments.

In this study, the breast model was obtained using three-dimensional (3D) scanning. Assembling models were obtained for FE analysis using reverse engineering and computer-aided design (CAD) software. The breast deformation results were obtained by completing pre-processing, solving and post-processing in the FE simulation software. To extend the application of these models, pads of different sizes and thicknesses within the bra were constructed to simulate the effect of pads on breast deformation.

The calculated root mean square errors were <1%, which indicated good agreement between the FE and experimental data in all the models. Nipple deformation was always the largest in most models. The smallest deformation occurred at the superior position of breasts in all models. In addition, larger pads were not effective in reducing breast deformation; however, thicker pads were.

The method developed in this study provides an effective way to predict breast deformation in multiple positions and is convenient for designing compression bras.

Based on resource dependence theory and transaction cost economics this study explores how green customer integration (GCI) affects financial performance via information sharing and opportunistic behavior, and the moderating effects of dependence and trust.

This study develops a theoretical model and tests it using data from two-waved survey data of 206 Chinese manufacturers. The hypotheses were tested using hierarchical linear regression analysis.

The results show that GCI has a significant and positive impact on information sharing, but its impact on opportunistic behavior is insignificant. Notably, information sharing has a significant and positive impact on financial performance, while opportunistic behavior has an insignificant impact on financial performance. In addition, dependence negatively moderates the impact of GCI on information sharing and positively moderates the impact of GCI on opportunistic behavior. Trust negatively moderates the impact of GCI on opportunistic behavior.

Although GCI has received widespread attention, how it affects a firm's performance remains unclear. Most previous studies have focused only on its bright side and ignored its dark side. This study highlights how GCI affects financial performance through information sharing and opportunistic behavior, and the moderating effects of dependence and trust. This enriches the understanding of how and under what conditions GCI affects a firm's performance.