Background and Objectives:PA is a multi-factorial behavior that is affected by interpersonal, intra personal, environmental and social factors. In this study we applied explanatory model to determine the total, indirect and direct impact of physical environment, personal factors and social support on PA among employed women.Methods:This study was a correlational cross-sectional study which was conducted to model total, indirect and direct impact of environmental, psychological and social factors on PA. A total of 200 women were chosen from Tabriz University by using convenience sampling method. Data about demographic characteristics, psychological variables, social and physical environment were gathered by using self-reported questionnaire and also the PA was measured by using the International PA Questionnaire and pedometer.Results:personal factors, physical and social environment, showed direct effects on PA. Social factors could be seen to have indirect effects on PA through their influence on personal factors such as pros, cons and self-efficacy; also physical environment had indirect effects on PA through social environment. The total effects of physical and social environment on PA type were respectively 0.17, 0.16 on walking, 0.05, 0.07 on moderate activity and 0.15, 0.18 on vigorous activity.Conclusions:Findings from this study indicated that social factors had indirect effects on walking, moderate and vigorous activity, especially through the effects on these factors of self-efficacy, physical environment, pros and cons, and the interactive role of individual, environmental and social impacts on PA. The current study identifies that psychological, physical and social factors could be shown to have direct and indirect influences on all forms of activity. The barriers of PA were the most predictor of this behavior, and based on results, it can be concluded that decreasing the barriers along with improving social and physical environment can lead to increasing PA and health promotion.

In the present study reported, fully electrochemical methodology was used to prepare a new nanocomposite on a glassy carbon electrode. Cysteic acid was formed by electrochemical oxidation of L-cysteine on the surface of a glassy carbon electrode (GCE) and used as a proper polymeric framework for deposition of Au nanoparticles (AuNPs). Field emission scanning electron microscopy (FESEM) was used for the surface characterization. It was shown that this composite electrode not only separates the voltammetric signals of hydroquinone (HQ) and catechol (CC), but also shows higher oxidation current for these molecules. Under the optimized condition, a linear dynamic range of 0.09 μmol dm−3 to 39.2 μmol dm−3 range for hydroquinone with the detection limit of 20 nM and from 0.09 μmol dm−3 to 39.2 μmol dm−3 for catechol with the detection limit of 60 nM were obtained. The proposed method was evaluated by determination of HQ and CC in rain and tap water samples with satisfactory results (recovery > 96%).

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Hardware impairments are the inevitable limiting factors in radio frequency communication systems, and in particular in mm-wave, the impairments can severely affect system performance. In this paper, we propose an additive noise modeling technique for modeling and analyzing the residual hardware impairments, more accurately than previously done in the literature. We analyze the effects of joint residual phase noise and IQI in both transmitter and receiver by using additive noise modeling as a representation method and indicate how other impairments can be described in the same framework. We derive the signal to distortion plus noise ratio (SDNR) for both the joint and the individual effects of impairments and validate the formulations with simulations which also acknowledge the usefulness of the additive noise modeling as a mean for accurate hardware impairments study. Index Terms-Hardware impairments, residual phase noise, IQI, additive noise modeling, variance of error.

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