There is a clear positive assortativity mixing with regards to the mobility trails of Gowalla users.

Even when controlling for the home-distance distribution the average pairwise similarity in the real network is significantly higher compared to that of a randomized network.</p

Decision boundaries for positive, negative or random mixing in the network.

<p>If the average similarity of connected nodes in the network falls in the top 2.5% quantile of (e.g., green line) we can conclude—at the significance level of <i>α</i> = 0.05—that the network is positively mixed. Similarly, if falls in the bottom 2.5% quantile of (e.g., red line) the network is negatively mixed. Otherwise (e.g., orange line) we cannot reject the hypothesis that the network is randomly mixed with respect to <b>x</b>.</p

Comparison of the VA-index with the baseline extension of assortativity coefficient.

The VA-index outperforms the baseline metric in all cases, irrespective of x’s elements variance, correlation and the density δ of Σ. Nevertheless, for low variance the baseline performs almost equally as good with respect to the RMSE.</p

Sensitivity of our metric with respect to <i>ξ</i> and <i>ϵ</i>.

<p>The proposed VA-index outperforms the baseline extension of assortativity coefficient. Furthermore, it does not appear sensitive to the choice of <i>ϵ</i> (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146188#pone.0146188.e049" target="_blank">Eq (5)</a>) and/or similarity metric.</p

The computation of VA-index in a nutshell.

<p>VA-index involves network randomization and empirical hypothesis testing for quantifying the assortativity of a network with respect to a mutli-dimensional nodal attribute.</p

The bias and the variance of the VA-index.

<p>Both the bias and the variance of the VA-index have small absolute values. However, values around <i>ϵ</i> = 1 appear to provide the best performance with regards to minimizing the mean square error of the estimator.</p

Mean difference Δ<i>e</i>_<i>ν</i> between the absolute error of our method and the baseline.

<p>The significance codes correspond to the two-sample t-test: 0 ‘***’ 0.01 ‘**’ 0.05 ‘*’ 0.1 ‘.’ 1 ‘’. Low, medium and high density correspond to <i>δ</i> ∈ [0, 0.2], <i>δ</i> ∈ [0.4, 0.6] and <i>δ</i> ∈ [0.8, 1] respectively.</p

DataSheet1_Oleaginous Microalga Coccomyxa subellipsoidea as a Highly Effective Cell Factory for CO2 Fixation and High-Protein Biomass Production by Optimal Supply of Inorganic Carbon and Nitrogen.docx

Microalgae used for CO2 biofixation can effectively relieve CO2 emissions and produce high-value biomass to achieve “waste-to-treasure” bioconversion. However, the low CO2 fixation efficiency and the restricted application of biomass are currently bottlenecks, limiting the economic viability of CO2 biofixation by microalgae. To achieve high-efficient CO2 fixation and high-protein biomass production, the oleaginous microalga Coccomyxa subellipsoidea (C. subellipsoidea) was cultivated autotrophically through optimizing inorganic carbon and nitrogen supply. 0.42 g L−1 NaHCO3 supplemented with 2% CO2 as a hybrid carbon source resulted in high biomass concentration (3.89 g L−1) and productivity (318.33) with CO2 fixation rate 544.21 mg L−1 d−1 in shake flasks. Then, used in a 5-L photo-fermenter, the maximal protein content (60.93% DW) in batch 1, and the highest CO2 fixation rate (1043.95 mg L−1 d−1) with protein content (58.48% DW) in batch 2 of repeated fed-batch cultures were achieved under 2.5 g L−1 nitrate. The relative expression of key genes involved in photosynthesis, glycolysis, and protein synthesis showed significant upregulation. This study developed a promising approach for enhancing carbon allocation to protein synthesis in oleaginous microalga, facilitating the bioconversion of the fixed carbon into algal protein instead of oil in green manufacturing.</p

Supporting_Information – Supplemental material for An effective strategy for preparation of a polyclonal antibody with an addition of carbon chain of ciprofloxacin

Supplemental material, Supporting_Information for An effective strategy for preparation of a polyclonal antibody with an addition of carbon chain of ciprofloxacin by Dong Wei, Guozhen Fang and Shuo Wang in European Journal of Inflammation</p

Additional file 1: of Comprehensive anticancer drug response prediction based on a simple cell line-drug complex network model

Table S1. The distance matrix of drugs in CCLE dataset. (XLSX 37 kb