International Trade Modelling Using Open Flow Networks: A Flow-Distance Based Analysis

<div><p>This paper models and analyzes international trade flows using open flow networks (OFNs) with the approaches of flow distances, which provide a novel perspective and effective tools for the study of international trade. We discuss the establishment of OFNs of international trade from two coupled viewpoints: the viewpoint of trading commodity flow and that of money flow. Based on the novel model with flow distance approaches, meaningful insights are gained. First, by introducing the concepts of trade trophic levels and niches, countries’ roles and positions in the global supply chains (or value-added chains) can be evaluated quantitatively. We find that the distributions of trading “trophic levels” have the similar clustering pattern for different types of commodities, and summarize some regularities between money flow and commodity flow viewpoints. Second, we find that active and competitive countries trade a wide spectrum of products, while inactive and underdeveloped countries trade a limited variety of products. Besides, some abnormal countries import many types of goods, which the vast majority of countries do not need to import. Third, harmonic node centrality is proposed and we find the phenomenon of centrality stratification. All the results illustrate the usefulness of the model of OFNs with its network approaches for investigating international trade flows.</p></div

Illustration of a balanced country node from the viewpoint of commodity flow.

<p>Illustration of a balanced country node from the viewpoint of commodity flow.</p

Illustration of an open flow network.

<p>Illustration of an open flow network.</p

A fragment of the NBER-United Nations trade dataset.

<p>A fragment of the NBER-United Nations trade dataset.</p

Illustration of a balanced country node from the viewpoint of money flow.

<p>Illustration of a balanced country node from the viewpoint of money flow.</p

Countries-products matrix reporting countries’ trophic levels in different OFNs with different products.

<p>Rows (countries) and columns (products) are arranged in descending order of <i>n</i>, and then <math><msubsup><mi>l</mi><mrow><mi>S</mi><mi>o</mi><mi>u</mi><mi>r</mi><mi>c</mi><mi>e</mi><mo>,</mo><mi>i</mi></mrow><mi>α</mi></msubsup><mo>¯</mo></math>, where <i>n</i> and <math><msubsup><mi>l</mi><mrow><mi>S</mi><mi>o</mi><mi>u</mi><mi>r</mi><mi>c</mi><mi>e</mi><mo>,</mo><mi>i</mi></mrow><mi>α</mi></msubsup><mo>¯</mo></math> are the number of colored points and the mean of trading trophic levels respectively.</p

List of countries sorted by <i>f</i>_<i>i</i> for the money flow network of trading live bovine animals.

<p>List of countries sorted by <i>f</i>_<i>i</i> for the money flow network of trading live bovine animals.</p

Countries-products matrix reporting countries’ harmonic centrality rankings in columns.

<p>Countries are sorted in ascending order by the average ranking, and products are arranged in descending order of the number of trading countries.</p

Trading niches of countries for the commodity of live bovine animals from the viewpoint of money flow.

<p>The red diagonal line separates importers and exporters. <i>θ</i> is the angle between vertical axis and the line connecting the origin and country node.</p

Table_5_Characterization of a mobilizable megaplasmid carrying multiple resistance genes from a clinical isolate of Pseudomonas aeruginosa.XLSX

IntroductionThe horizontal transfer of antibiotic resistance genes mediated by plasmids seriously hinders the effectiveness of modern medical treatment, and thus has attracted widespread attention. Additionally, the co-selection mechanism of antibiotic resistance genes (ARGs) and heavy metal resistance genes (MRGs) on mobile elements may further exacerbate the horizontal transfer of resistance genes.MethodsIn this study, a multidrug-resistant Pseudomonas aeruginosa strain, termed BJ86 (CHPC/NPRC1.4142), was isolated from a patient's sputum specimen. In vitro tests for antimicrobial susceptibility, conjugation, whole-genome sequencing, and bioinformatics analysis were used to explore the potential mechanisms of resistance and its spread.Results and discussionSequencing analysis indicates that P. aeruginosa BJ86 carries an amazing 522.5 kb-length megaplasmid, pBJ86, which contained a 93.5 kb-length multiple resistance region (MRR); 18 kinds of genes were identified as ARGs in this region, including tmexCD-oprJ, blaDIM−1, qnrVC6 that mediate resistance to multiple antibiotics and the operons mer that mediates heavy metal mercury resistance. In addition, there is also an 80 kb variable region (VR) on the plasmid pBJ86, and the genes encoding relaxase and type IV coupling protein (T4CP) were determined in this region, both of which are related to the conjugation and transfer ability of the plasmid. Bioinformatics analysis shows that many functional genes have insertion sequences and transposases on their flanks, which may have accumulated in the plasmid pBJ86 after multiple acquisition events. Conjugated transfer and in vitro tests for antimicrobial susceptibility verified the mobility and plasmid pBJ86-mediated resistance. To our knowledge, we are the first to report a mobilizable megaplasmid that simultaneously carried tmexCD-oprJ, blaDIM−1, qnrVC6, and the operons mer and can be transferred with frequencies of 6.24 × 10−7 transconjugants per donor cell.</p