Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
The dataset analyzed in this article contains spatial and temporal values of the hydro-geometric parameters of River Atuwara. The hydro-geometrical data analyses of various sampling point on River Atuwara was examined and their geometric properties were taken with the use of a paddled boat, depth meter and global positioning system (GPS). The co-ordinates, width, depth, slopes, area, velocity, flow were gotten in-situ while the area and wetted perimeter were computed ex-situ. The statistical relationships between separate variables were considered using scatter plots and regression line equations. Inferences drawn from various variable comparisons can be used to validate predictive models for various time seasons.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5998175 | PMC |
http://dx.doi.org/10.1016/j.dib.2018.04.071 | DOI Listing |
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