An organically modified montmorillonite was compounded with ethylene vinyl acetate copolymer (EVA), low density polyethylene (LDPE), and high density polyethylene (HDPE) in a twin‐screw extruder. The resulting organoclay‐polyethylene nanocomposites were then blown into films. Tensile properties and oxygen permeability of these nanocomposite films were investigated to understand the effects of organoclay on different types of polyethylene. It was found that the clay enhancing effects are function of the matrix. The mechanical and oxygen barrier properties of clay/EVA systems increased with clay loading. Both the tensile modulus and oxygen barrier of EVA doubled at 5 wt% clay. Maleic anhydride grafted polyethylene (MAPE) usually is used as a compatibilizer for LDPE and HDPE‐based nanocomposites. However, the MAPEs were found to weaken the oxygen barrier of the PEs, especially for HDPE. This is believed to be a result of less compactness caused by the large side groups and the increase in polarity of the MAPEs. Incorporating 5 wt% clay improves the oxygen barrier by 30% and the tensile modulus by 37% for the LDPE/MAPE system. Incorporation of clay does not enhance the properties of the HDPE‐based systems, likely due to large domain structure and poor bonding. Halpin–Tsai equation and the tortuous path equation were used to model the tensile modulus and oxygen permeability of the clay/EVA nanocomposite films. POLYM. ENG. SCI., 47:1101–1107, 2007. © 2007 Society of Plastics Engineers

Despite many advantages of wood–polyethylene composites, the shortcomings of this kind of composite include relatively low modulus, low notched impact resistance, relatively large thermal expansion, as well as substantial creep. In this article, in addition to using maleic anhydride grafted polyethylene as compatibilizer, organoclay was introduced into the polyethylene matrix so as to further enhance the thermal and mechanical performance. First, the influence of maleic anhydride grafted polyethylene type and loading on the morphology and properties of wood/HDPE composites was studied. Then, the effects of organoclay loading and of the compounding procedure on the wood/HDPE composites were investigated. The compatibilization was found to result in better polymer impregnation on the wood, reduced linear thermal expansion coefficients, and significantly improved mechanical properties. Incorporation of organoclay further reduced the thermal expansion and elevated the heat deflection temperature. More compatibilizer is needed to maintain the mechanical properties with the presence of clay. POLYM. ENG. SCI., 47:797–803, 2007. © 2007 Society of Plastics Engineers

Previous findings have shown that impulsivity and Behavioral Inhibition/Approach System (BIS/BAS) have substantial effects on adolescents’ Internet addiction, but the mechanisms underlying these associations and gender differences in these effects have received little attention. We examined the mediating effects of coping styles from impulsivity, and BIS/BAS to Internet addiction as well as gender differences in these associations. A total of 416 Chinese adolescents were examined using a cross-sectional survey involving Young’s Diagnostic Questionnaire for Internet Addiction, Barratt Impulsiveness Scale, BIS/BAS scales, and Coping Style Scale for Middle School Students. The data were analyzed using the independent sample t-test, chi-square test, Pearson correlation, and structure equation modeling. The results from the multiple-group (by adolescent gender) structural model analysis revealed that both impulsivity (p < 0.001) and BIS (p = 0.001) directly predicted positive Internet addiction in girls, while both impulsivity (p = 0.011) and BAS (p = 0.048) directly predicted positive Internet addiction in boys. Furthermore, emotion-focused coping mediated the relationship between impulsivity and Internet addiction (β = 0.080, 95% CI: 0.023–0.168) and the relationship between BIS and Internet addiction (β = 0.064, 95% CI: 0.013–0.153) in girls, while in boys, problem-focused coping and emotion-focused coping mediated the association between impulsivity and Internet addiction (β = 0.118, 95% CI: 0.031–0.251; β = 0.065, 95% CI: 0.010–0.160, respectively) and problem-focused coping mediated the association between BAS and Internet addiction [β = −0.058, 95% CI: (−0.142)–(−0.003)]. These findings extend our insight into the mechanisms underlying the associations among impulsivity, BIS/BAS, and Internet addiction in adolescents and suggest that gender-sensitive training approaches to decrease adolescents’ Internet addiction are indispensable. These interventions should focus on the different gender predictors of adolescent Internet addiction and on the development of specific coping styles for boys and girls respectively.

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Predicting facial attributes from faces in the wild is very challenging due to pose and lighting variations in the real world. The key to this problem is to build proper feature representations to cope with these unfavourable conditions. Given the success of Convolutional Neural Network (CNN) in image classification, the high-level CNN feature, as an intuitive and reasonable choice, has been widely utilized for this problem. In this paper, however, we consider the mid-level CNN features as an alternative to the high-level ones for attribute prediction. This is based on the observation that face attributes are different: some of them are locally oriented while others are globally defined. Our investigations reveal that the mid-level deep representations outperform the prediction accuracy achieved by the (fine-tuned) high-level abstractions. We empirically demonstrate that the midlevel representations achieve state-of-the-art prediction performance on CelebA and LFWA datasets. Our investigations also show that by utilizing the mid-level representations one can employ a single deep network to achieve both face recognition and attribute prediction.

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Insulator faults detection is an important task for high-voltage transmission line inspection. However, current methods often suffer from the lack of accuracy and robustness. Moreover, these methods can only detect one fault in the insulator string, but cannot detect a multi-fault. In this paper, a novel method is proposed for insulator one fault and multi-fault detection in UAV-based aerial images, the backgrounds of which usually contain much complex interference. The shapes of the insulators also vary obviously due to the changes in filming angle and distance. To reduce the impact of complex interference on insulator faults detection, we make full use of the deep neural network to distinguish between insulators and background interference. First of all, plenty of insulator aerial images with manually labelled ground-truth are collected to construct a standard insulator detection dataset ‘InST_detection’. Secondly, a new convolutional network is proposed to obtain accurate insulator string positions in the aerial image. Finally, a novel fault detection method is proposed that can detect both insulator one fault and multi-fault in aerial images. Experimental results on a large number of aerial images show that our proposed method is more effective and efficient than the state-of-the-art insulator fault detection methods.

Internet gaming disorder (IGD), which involves unhealthy and excessive Internet use, has been a global problem since the recent development of the Internet. IGD may lead to serious impairments in psychological and social functioning, such as anxiety, reductions in academic and occupational performance, and even suicidal behaviors (Petry, Rehbein, Ko, & O'Brien, 2015). Because of its clinically significant harmfulness, IGD has been included in the appendix of the Diagnostic and Statistical Manual of Mental Disorders (5th ed., DSM-5). Thus, there is a need for the further exploration of IGD's clinical relevance and underlying neural mechanisms. Various neurobiological hypotheses have been postulated to explain why adolescence is the peak period of IGD and