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Composite sustainable manufacturing practice and performance framework: Chinese auto-parts suppliers׳ perspective

Overview of attention for article published in International Journal of Production Economics, December 2015
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1 X user

Citations

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Title
Composite sustainable manufacturing practice and performance framework: Chinese auto-parts suppliers׳ perspective
Published in
International Journal of Production Economics, December 2015
DOI 10.1016/j.ijpe.2015.09.035
Pubmed ID
Authors

Zhen Wang, Nachiappan Subramanian, Angappa Gunasekaran, Muhammad D. Abdulrahman, Chang Liu

Abstract

High-throughput DNA sequencing techniques have greatly accelerated the pace of research into the repertoires of antibody and T cell receptor gene rearrangements that confer antigen specificity to adaptive immune responses. Studies of aging-related changes in human B cell repertoires have benefited from the ability to detect and quantify thousands to millions of B cell clones in human samples, and study the mutational lineages and isotype switching relationships within each clonal lineage. Correlation of repertoire analysis with antibody gene data from antigen-specific B cells is poised to give much greater insight into clinically relevant B cell responses and memory storage. Here, we describe strategies for preparing and analyzing human antibody gene libraries for studying B cell repertoires.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 269 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 <1%
United Kingdom 1 <1%
South Africa 1 <1%
Colombia 1 <1%
Unknown 264 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 48 18%
Student > Ph. D. Student 44 16%
Student > Bachelor 25 9%
Student > Doctoral Student 21 8%
Researcher 16 6%
Other 47 17%
Unknown 68 25%
Readers by discipline Count As %
Engineering 89 33%
Business, Management and Accounting 47 17%
Social Sciences 10 4%
Agricultural and Biological Sciences 6 2%
Economics, Econometrics and Finance 6 2%
Other 27 10%
Unknown 84 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 December 2015.
All research outputs
#20,674,485
of 25,394,764 outputs
Outputs from International Journal of Production Economics
#746
of 923 outputs
Outputs of similar age
#291,703
of 395,593 outputs
Outputs of similar age from International Journal of Production Economics
#16
of 23 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 923 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 395,593 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.