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
In China, there are currently different degrees of arbitrariness in setting environmental administrative fines, and in many areas the faults are not equal to the penalties. To construct a more reasonable and feasible environmental punishment strategy where violators are fined in accordance with the severity of their actions, we use mathematical models to determine the specific range of environmental administrative fines based on the idea of realizing the appropriate balance between the interest of the violators and those of the public, meanwhile, law enforcement officers are allowed to use their discretion within a certain range. We use an example to prove that the punishment scheme provided by our models can be used to more effectively supervise violators' illegal behaviors than the penalty clause prescribed by law, and through sensitivity analysis and comparison, we prove that the described models are stable and feasible, and provide advantages over the existing methods. We hope our approach provides intellectual support for maintaining legal order, regulating the environmental administrative fine process, guiding business behaviors, and, most importantly, achieving the goal of protecting the environment.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8126002 | PMC |
http://dx.doi.org/10.3390/ijerph18095011 | DOI Listing |
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