scholarly journals Effects of Social Experience on the Habituation Rate of Zebrafish Startle Escape Response: Empirical and Computational Analyses

2018 ◽  
Vol 12 ◽  
Author(s):  
Choongseok Park ◽  
Katie N. Clements ◽  
Fadi A. Issa ◽  
Sungwoo Ahn
2016 ◽  
Vol 47 (3) ◽  
pp. 125-135 ◽  
Author(s):  
Sarah E. Gaither ◽  
Jessica D. Remedios ◽  
Jennifer R. Schultz ◽  
Keith B. Maddox ◽  
Samuel R. Sommers

Abstract. Research shows that I-sharing, or sharing subjective experiences with an outgroup member, positively shapes attitudes toward that outgroup member. We investigated whether this type of social experience would also promote a positive interracial interaction with a novel outgroup member. Results showed that White and Black participants who I-shared with a racial outgroup member (vs. I-sharing with a racial ingroup member) expressed more liking toward that outgroup member. However, I-sharing with an outgroup member did not reduce anxious behavior in a future social interaction with a novel racial outgroup member. Therefore, although sharing subjective experiences may increase liking toward one individual from a racial outgroup, it remains to be seen whether this positive experience can influence behaviors in future interactions with other racial outgroup members. Future directions are discussed.


Localities ◽  
2014 ◽  
Vol 4 ◽  
pp. 125
Author(s):  
Patrick Tacussel
Keyword(s):  

2000 ◽  
Vol 28 (1-2) ◽  
pp. 141-147 ◽  
Author(s):  
P. W. Longest ◽  
Clement Kleinstreuer ◽  
P. J. Andreotti

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 525 ◽  
Author(s):  
Mehdi Keshavarz-Ghorabaee ◽  
Maghsoud Amiri ◽  
Edmundas Kazimieras Zavadskas ◽  
Zenonas Turskis ◽  
Jurgita Antucheviciene

The weights of criteria in multi-criteria decision-making (MCDM) problems are essential elements that can significantly affect the results. Accordingly, researchers developed and presented several methods to determine criteria weights. Weighting methods could be objective, subjective, and integrated. This study introduces a new method, called MEREC (MEthod based on the Removal Effects of Criteria), to determine criteria’ objective weights. This method uses a novel idea for weighting criteria. After systematically introducing the method, we present some computational analyses to confirm the efficiency of the MEREC. Firstly, an illustrative example demonstrates the procedure of the MEREC for calculation of the weights of criteria. Secondly, a comparative analysis is presented through an example for validation of the introduced method’s results. Additionally, we perform a simulation-based analysis to verify the reliability of MEREC and the stability of its results. The data of the MCDM problems generated for making this analysis follow a prevalent symmetric distribution (normal distribution). We compare the results of the MEREC with some other objective weighting methods in this analysis, and the analysis of means (ANOM) for variances shows the stability of its results. The conducted analyses demonstrate that the MEREC is efficient to determine objective weights of criteria.


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