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. 2020 Mar 17;10:4900. doi: 10.1038/s41598-020-61829-y

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Relationship of the MCHS-P and the MCS-P with classical performance measures. Subfigure (a) is for a homogeneous scenario such as 6000-urban-16, and shows that both the MCHS-P and the MCS-P have a positive relationship with the classic performance measure. Subfigure (b) is for a heterogeneous scenario such as 6000-three-16RR3.0-2.0-1.2, and it shows that the MCHS-P has a positive relationship with the classic performance measures, whereas the MCS-P has a nearly negative relationship with these performance measures.