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Purpose Social loafing in knowledge contribution (namely, knowledge contribution loafing [KCL]) usually happens in group context, especially in the mobile collaboration tasks. KCL shows dynamic features over time. However, most previous studies are based on static assumption, that is, KCL will not change over time. This paper aims to reveal the dynamics of KCL in mobile collaboration and analyze how network centrality influences KCL states considering the current loafing state. Design/methodology/approach This study is based on empirical study design. Real mobile collaboration behavioral data related to knowledge contribution were collected to investigate the dynamic relationship between network centrality and KCL. In total, 4,127 chat contents were collected through Slack (a mobile collaboration APP). The text data were first analyzed using the text analysis method and then analyzed by a machine learning method called hidden Markov model. Findings First, the results reveal the inner structure of KCL, showing that it has three states (low, medium and high). Second, it is found that network centrality positively influences individuals involved in medium and high loafing state, while it has a negative influence on individuals with low loafing state. Research limitations/implications The limitations are related to the single machine learning method and no subdivision of social network. First, this paper only uses one kind of text classification model (TF-IDF) to divide chat contents, which may not be superior to other classification models. This paper considers the eigenvector centrality, and not further divides the social network into advice network and expressive network. Practical implications This study helps companies infer tendency of different KCL and dynamically re-organize a mobile collaborative team for better knowledge contribution. Originality/value First, previous studies based on static assumptions regarding KCL as static and the relationship between loafing reducing mechanisms and team members KCL does not change over time. This study relaxes static assumptions and allows KCL to change during the process of collaboration. Second, this study allows the impact of network centrality to be different when members are in different KCL states.

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Lanthanide-containing persistent luminescence materials are promising candidates for a wide range of applications by virtue of splendid superiorities in afterglow performance. However, it is a crucial challenge to achieve high-quality afterglow materials at the attractive nanoscale, with uniform size, controllable morphology, and satisfying brightness. Herein, a bottom-up approach was developed to construct the high-quality afterglow nanoparticles, incorporating luminescent lanthanide complex and organic molecular ingredients under mild conditions. These nanoparticles exhibited intrinsic lanthanide luminescence with superbright red afterglow (>10 cd m −2 ) in a homogeneous solution. The afterglow solution with excellent processability can serve as ideal building blocks for the on-demand fabrication of functional nanomaterials. Water-dispersible afterglow nanoparticles with stateof-the-art high brightness were uniformly constructed to perform whole-blood lateral flow assay of procalcitonin with a nakedeye detection limit of 0.5 ng mL −1 , promoting the point-of-care testing development.