Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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In this work, a conductive composite film composed of multi-walled carbon nanotubes (MWCNTs) and multi-layer TiCTx MXene nanosheets is used to construct a strain sensor on sandpaper Ecoflex substrate. The composite material forms a sophisticated conductive network with exceptional electrical conductivity, resulting in sensors with broad detection ranges and high sensitivities. The findings indicate that the strain sensing range of the Ecoflex/TiCTx/MWCNT strain sensor, when the mass ratio is set to 5:2, extends to 240%, with a gauge factor (GF) of 933 within the strain interval from 180% to 240%. The strain sensor has demonstrated its robustness by enduring more than 33,000 prolonged stretch-and-release cycles at 20% cyclic tensile strain. Moreover, a fast response time of 200 ms and detection limit of 0.05% are achieved. During application, the sensor effectively enables the detection of diverse physiological signals in the human body. More importantly, its application in a data glove that is coupled with machine learning and uses the Support Vector Machine (SVM) model trained on the collected gesture data results in an impressive recognition accuracy of 93.6%.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11857537 | PMC |
http://dx.doi.org/10.3390/mi16020123 | DOI Listing |