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
Exposure to asbestos fibres is related to a number of severe lung diseases, and therefore, rapid, accurate and reliable in situ or on-site asbestos detection in real-life samples is of considerable importance. This work presents a comprehensive investigation of all six types of asbestos by mid-infrared ATR-FTIR, NIR spectroscopy and Raman microspectroscopy. Our studies demonstrate that for practical applications, NIR spectroscopy is potentially the most powerful method for asbestos identification in materials utilised by the construction industry. By focusing on the narrow spectral region, 7300-7000 cm (~1370-1430 nm, overtones of O‒H vibrations), which is highly specific to these materials, and optimising the sensitivity and resolution of the instrumentation, we have been able to discriminate and identify each of the six types of asbestos with the level of detection significantly better than 1 wt%. Furthermore, straightforward computational analysis has allowed for automated objective evaluation of the spectroscopic data.
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Source |
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http://dx.doi.org/10.1016/j.jhazmat.2020.123951 | DOI Listing |
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