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  • The present study The evidence reported above supports the notion that social support both directly affects the relapse tendency of women experiencing heroin addiction, but also may have an indirect impact through the active coping strategies. In addition, the role of social support may also be moderated by openness to experience. Further, previous studies of heroin addiction found that the age of addict and their parents' level of education level were significantly correlated with their rates of heroin abuse (Aggarwal et al., 2015; Kolodny et al., 2015). Therefore, it is necessary to control for these factors in the present study. Based on the above analysis, this study proposes the hypotheses listed here and summarized in the model in Fig. 1. (1) Active coping strategies would mediate the relationship between social support and the relapse tendency. (2) Openness to experience would moderate the relationships between social support and active coping strategies, and between social support and the relapse tendency. (3) Openness to experience would moderate the mediating effect of active coping strategies in the relationship between social support and the relapse tendency. Statistical analyses Descriptive analyses and Pearson’s correlations were used by SPSS 22.0 for all variables. To test the moderated mediation model, we have adopted Stride's advice, and constructs are measured by latent variables as opposed to observed variables (Stride, Gardner, Catley, & Thomas, 2015). The analysis process of the entire model corresponds to the SPSS macro PROCESS (http://www.afhayes.com) suggested by Hayes (2018) but applying Mplus 7.4. The mediating (indirect) effect with 5000 bootstrap samples. In order to better reveal the relationship between latent variables, we used the item parceling strategy (Hall, Snell, & Foust, 1999; Little, Cunningham, Shahar, & Widaman, 2002). The critical value of the statistical test includes p value under the standard 0.05 level, and 95% bias-correction bootstrap confidence interval.
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  • Habenula QSM data upload test
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    • Image
    • Dataset
  • Sharp ended α-Fe core microwire covered with PrDyFeCoB amorphous shell with enhanced stray magnetic field is proposed for magnetic tweezers, stepwise switchable in external homogeneous magnetic field. Four stable magnetic states of the microwire, controlled by external magnetic field, were determined by magneto-optical Kerr effect (MOKE) microscopy. Distribution of the stray field near the microwire tip was plotted by magneto-optical indicator film (MOIF) technique. Large gradient of the stray magnetic field in the vicinity of the microwire tip is quite enough to provide magnetic force ~ 2000 pN, well enough for capturing of the PrDyFeCoB microparticle. Significance of the obtained results is in switching of the focused stray field of the microwire under external homogeneous magnetic field. This provides simple way of stepwise attaching-detaching of microparticles without electromagnetic micro coils.
    Data Types:
    • Software/Code
    • Image
    • Dataset
  • This is data collected on the nutritional status of non-academic staff of the Tamale Campus of University for Development Studies, Tamale - Ghana Interviews were conducted on staff nutrition and their dietary practices using questionnaires. Weight and height measurements were taken for anthropometric data of respondents to assess their nutritional status. Participants were also asked through the questionnaire, to indicate all foods and drinks that were consumed over the previous 24 hours whether at home or outside the home. As part of data collection, a table was created with various food groups and participants indicated which foods they consumed. The data should be interpreted taken into cognisance that these staff are at a higher institution of learning. The hypothesis was that poor nutrition knowledge result in poor dietary practices and nutritional status.
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    • Software/Code
    • Dataset
  • This paper investigates the claim that the election of Donald Trump in 2016 prompted a decline in trust among Democrats and an increase in trust among Republicans. I test these hypotheses with four-wave panel data from Pew Research's American Trends Panel project, collected before and after the election. The evidence points to a relationship between Trump’s victory and a collapse of social trust among electoral losers with strong partisan attachments. From 2014 to 2018, the sharpest declines in trust occurred among Democrats in the pre- to post-electoral period (2016-2017). Pre-election Democrats were also the least likely to become and remain trusting of others following the election. No other partisan group experienced changes of trust in response to the election, including those who only weakly identify as Democrats. However, there is also evidence that the effect was temporary. By 2018, generalized trust among Democrats rebounded. The implication of these findings is that the 2016 election had a negative effect on America’s already depleted supply of social trust.
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  • A reliable and unobtrusive quantification of changes in cortical activity during short-term memory (STM) task can be used to evaluate the efficacy of interfaces and to provide real-time user-state information. In this dataset, we record electroencephalogram (EEG) signals in STM and baseline activity.
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    • Software/Code
    • Tabular Data
    • Dataset
    • File Set
  • The dataset consists of 3D scans of the upper and lower dentitions of 24 patients, all in their growth age, taken at different time intervals. All patients had normal occlusions with no history of orthodontic treatment. There are 3 scans avaialble for 8 out of 24 patients, and 2 scans available for the remaining 16 patients. The interval between each two consecutive scans is at least 2 years and at most 10 years. The dataset was created by 3D scanning of plaster models using a benchtop structured-light 3D scanner (Maestro 3D Desktop Scanner, Pontedera, Italy) with a point accuracy of <10 μm and resolution of <70 μm in all directions.
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  • these data will be published in the "A phenomenological model for the spontaneous exchange bias effect" article
    Data Types:
    • Software/Code
    • Dataset
  • In a scenario of expanding competition between tourist destinations, DMOs face the challenge of positioning them attractively. To this end, these organizations can make use of various communication marketing strategies, including social media, platforms whose effectiveness is measured through engagement. From these channels originate the digital influencers, which in recent years have gained greater academic and marketing prominence. Given this theoretical foundation, this research aimed to measure the degree of engagement in publications with digital influencers on Instagram of Brazilian DMOs, with time frame between December / 17 and December / 18. To achieve the necessary results for the proposed problem, the data mining technique was used in a sample of 11 Instagram profiles from Brazilian state DMOs, selected after a filtering process. The collected data were treated from a quantitative descriptive approach, having as parameter three main indicators, as follows: (1) total publications, (2) likes and (3) comments. All these indices were defined after consulting the engagement literature. In addition, a T Test was done between paired samples to verify if there was a significative difference on the means. In general, the results indicated that posts with digital influencers have better results, given the proposed time frame, especially when compared with the indexes of general posts. However, inferential statistics indicated that the differences between means were not relevant. In such a way, the strategy of endorsement by influencers does not seem to produce relevant effects on user interaction in the profiles of Brazilian DMOs.The innovative character of this research stems from the use of the data mining technique to deliver accurate results as to the effectiveness of a rising social media strategy, providing managers with a solid framework for analysis and fostering the field of discussion.
    Data Types:
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    • Tabular Data
    • Dataset
    • Document
  • This data contains four variables, childhood psychological maltreatment, immorality, empathy and cyberbullying perpetration attitudes
    Data Types:
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    • Dataset
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