Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1038/s41598-017-03512-3 http://scihub22266oqcxt.onion/10.1038/s41598-017-03512-3 C5478654!5478654!28634332     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2017 ; 7 (ä): ä Nephropedia Template TP {{tp|p=28634332|t=2017. Predicting the potential risk area of illegal vaccine trade in China |pdf=|usr=}}{{28634332}} gab.com Text Predicting the potential risk area of illegal vaccine trade in China JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=28634332 #FOAvip Since the disclosure of the ?Illegal vaccine operation series case in Jinan, Shandong? in March, 2016, this issue has attracted a great deal of attention and has led to public concerns about the safety and efficacy of the vaccines involved in this case. The main purpose of this paper is to scientifically and scrupulously predict the possible geographic distribution of illegal vaccines in China, and provide a foundation to guide future governmental policies and actions. A species distribution model was used because of the advantages of using presence/pseudo-absence or presence-only data, and it performs well with incomplete species distribution data. A series of socioeconomic variables were used to simulate habitat suitability distribution. Maxent (Maximum Entropy Model) and GARP (Genetic Algorithm for Rule set Production) were used to predict the risks of illegal vaccines in China, and define the spatial distribution and significant factors of the area at risk from illegal vaccines. Jackknife tests were used to evaluate the relative importance of socioeconomic variables. It was found that: (1) Shandong, Hebei, Henan, Jiangsu and Anhui are the main high-risk areas impacted by the vaccines involved in Jinan case. (2) Population density and industrial structure are the main socioeconomic factors affecting areas which may be at risk from illegal vaccines. Twit Text FOAVip Predicting the potential risk area of illegal vaccine trade in China ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=28634332 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28634332 #FOAvip English Wikipedia <ref>{{Cite pmid|28634332}}</ref> Predicting the potential risk area of illegal vaccine trade in China #MMPMID28634332 Liao Y; Lei Y; Ren Z; Chen H; Li D Sci Rep 2017[]; 7 (ä): ä PMID28634332show ga Since the disclosure of the ?Illegal vaccine operation series case in Jinan, Shandong? in March, 2016, this issue has attracted a great deal of attention and has led to public concerns about the safety and efficacy of the vaccines involved in this case. The main purpose of this paper is to scientifically and scrupulously predict the possible geographic distribution of illegal vaccines in China, and provide a foundation to guide future governmental policies and actions. A species distribution model was used because of the advantages of using presence/pseudo-absence or presence-only data, and it performs well with incomplete species distribution data. A series of socioeconomic variables were used to simulate habitat suitability distribution. Maxent (Maximum Entropy Model) and GARP (Genetic Algorithm for Rule set Production) were used to predict the risks of illegal vaccines in China, and define the spatial distribution and significant factors of the area at risk from illegal vaccines. Jackknife tests were used to evaluate the relative importance of socioeconomic variables. It was found that: (1) Shandong, Hebei, Henan, Jiangsu and Anhui are the main high-risk areas impacted by the vaccines involved in Jinan case. (2) Population density and industrial structure are the main socioeconomic factors affecting areas which may be at risk from illegal vaccines. äPredicting the potential risk area of illegal vaccine trade in China (epmc).pdf DeepDyve Pubget Overpricing