CN116128277A - Dynamic early warning method and system for classification and grading of fixed pollution sources - Google Patents
Dynamic early warning method and system for classification and grading of fixed pollution sources Download PDFInfo
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Abstract
The application discloses a dynamic early warning method and a system for classification and classification of a fixed pollution source, wherein the dynamic early warning method for classification and classification of the fixed pollution source specifically comprises the following steps: acquiring a risk index variable value; dynamically acquiring a fixed pollution source evaluation score according to the acquired risk index variable value; judging whether the level adjustment is required according to the fixed pollution source evaluation score; if the level is required to be adjusted, sending out an audit prompt; establishing an enterprise credit risk early warning model according to the risk index variable value to acquire an enterprise environment credit risk value; judging whether the credit risk value of the enterprise environment exceeds a specified threshold value; and if the credit risk value of the enterprise environment exceeds the specified threshold, sending a prompt for increasing the inspection frequency. According to the method, qualitative indexes are quantized through technical means, latest acquired and recorded information is automatically and regularly acquired, dynamic classification and risk early warning of scoring standards are completed according to the acquired information, time cost is reduced, and management refinement level and working efficiency are improved.
Description
Technical Field
The application relates to the field of environmental pollution source management, in particular to a dynamic early warning method and a system for classifying and grading fixed pollution sources.
Background
The ecological civilization idea is a systematic and scientific treatment idea, the improvement of ecological environment, the need of accurate analysis to influence the outstanding problem and weak links of ecological environment quality, the symptomatic medication of different pollution sources in different areas, industries and industries, and the implementation of differentiation and fine management. In recent years, the concept of environmental credit of other provinces nationwide is adopted in Beijing city, classification and grading system test points are carried out on the fixed pollution sources (fixed pollution discharge units (except for radiation sources) which are produced and managed in administrative regions and generate pollutant discharge) of Beijing city, local enterprises are motivated to cooperate to develop classification and grading evaluation of the fixed pollution sources, the enterprises are motivated to fulfill environmental legal obligations and social responsibilities, environmental belief behaviors of the enterprises are restrained and punished, and the problems that the periodic law enforcement and inspection workload of environmental protection law enforcement departments is large, the emphasis is not outstanding and the environment belief behavior of the enterprises cannot be prevented are solved. However, in the specific implementation process, it is found that the fixed pollution source classification and grading evaluation indexes are mostly qualitative indexes, so that the fixed pollution source classification and grading evaluation indexes can be completed only by on-site inspection and reference of related data and professional knowledge, which not only consumes a long time, but also consumes a large amount of manpower and material resources.
Therefore, how to provide a method for classifying and grading fixed pollution sources so as to timely perform environmental risk early warning on enterprises is a problem which needs to be solved by those skilled in the art.
Disclosure of Invention
The method and the system have the advantages that qualitative indexes can be quantized through technical means, daily information can be automatically searched and identified, relevant index scores are calculated, environmental default risk values of enterprises are obtained through a credit risk early warning model, the effects of real-time monitoring, pre-warning, advanced prevention by an environmental protection department and enhanced management and control are achieved, and the problems that the existing manual evaluation means are poor in real time, difficult to quantize and incapable of being prevented and controlled in advance by a supervision department are solved.
In order to achieve the above purpose, the application provides a dynamic early warning method for classifying and grading fixed pollution sources, which specifically comprises the following steps: acquiring a risk index variable value; dynamically acquiring a fixed pollution source evaluation score according to the acquired risk index variable value; judging whether the level adjustment is required according to the fixed pollution source evaluation score; if the level is required to be adjusted, sending out an audit prompt; establishing an enterprise credit risk early warning model according to the risk index variable value to acquire an enterprise environment credit risk value; judging whether the credit risk value of the enterprise environment exceeds a specified threshold value; and if the credit risk value of the enterprise environment exceeds the specified threshold, sending a prompt for increasing the inspection frequency.
As described above, before the initial value of the risk indicator variable is obtained, the method further includes obtaining data in each platform, and setting the fixed pollution source classification evaluation indicator and the quantization method table according to the data obtained from each platform.
As described above, the fixed pollution source classification rating index and quantization method table includes a plurality of indexes and one or more risk index variables corresponding to each index, where each risk index variable corresponds to a quantized original deduction value.
As described above, the obtained data in each platform is used to quantify the original deduction value, so as to obtain a specific value of the original deduction value.
As above, the fixed pollution source evaluation score C is specifically expressed as:
wherein the method comprises the steps of
Representing the originalThe score, i=1, 2,3.
As described above, the fixed pollution source evaluation scores of different time periods are dynamically obtained, and if the difference between the fixed pollution source evaluation scores obtained in the next time period and the fixed pollution source evaluation scores obtained in the previous time period exceeds a specified threshold, the level of the pollution source is adjusted.
As above, wherein the time period is one hour, one day, half month or one month.
As above, wherein the enterprise environment credit risk value Y k The concrete steps are as follows:
λ 0 ∈R，λ i ∈R n r represents a real number set,
x ik standardized value of the ith evaluation index affecting credit status for the kth enterprise, x jk The j index representing the credit status of enterprise influence, n is the number of evaluation indexes, wherein n=17, G is coefficient matrix in FM model, G i Is the ith row of the coefficient matrix G, G j Represents the j-th row of the coefficient matrix G.
As above, wherein
A dynamic early warning system for classifying and grading fixed pollution sources specifically comprises: the system comprises a risk index variable acquisition unit, a fixed pollution source evaluation score acquisition unit, a grading judgment unit, a first prompt unit, an enterprise environment credit risk value acquisition unit, a risk value judgment unit and a second prompt unit; the risk index variable acquisition unit is used for acquiring a risk index variable value; the fixed pollution source evaluation score acquisition unit is used for dynamically acquiring the fixed pollution source evaluation score according to the acquired risk index variable value; the level adjustment judging unit is used for judging whether level adjustment is needed according to the fixed pollution source evaluation score; the first prompting unit is used for sending out an audit prompt if the level adjustment is required; the enterprise environment credit risk value acquisition unit is used for establishing an enterprise credit risk early warning model according to the risk index variable value to acquire an enterprise environment credit risk value; the risk value judging unit is used for judging whether the credit risk value of the enterprise environment exceeds a specified threshold value; and the second prompting unit is used for sending out a prompt for increasing the inspection frequency if the credit risk value of the enterprise environment exceeds a specified threshold value.
The application has the following beneficial effects:
(1) According to the method, the qualitative indexes are quantized by a technical means, the latest acquired and recorded information is automatically and regularly acquired, and a large number of qualitative indexes are converted into data which can be recognized and calculated by a system, so that dynamic scoring and grading of credit evaluation indexes and scoring standards are completed, and the problems of large manual auditing workload and high time cost are solved.
(2) By establishing the enterprise environment credit risk early warning model, the method is suitable for all enterprises in the same area to incorporate the cross verification matrix, and solves the problems that the enterprise has the same environmental behavior (such as acquiring pollution discharge license or discharging pollutant with the same concentration as required) and administrative punishment standard inconsistency and environmental risk value judgment are controversial due to different policies in each area in China and possibly different deduction standards in different places.
(3) According to the enterprise environment credit risk value dynamic calculation method and system, the enterprise environment credit risk value is calculated dynamically by utilizing the enterprise environment credit risk early warning model, so that the prompt for strengthening the enterprise inspection and management with higher risk is sent out in a targeted manner, and the risk of environmental accidents is effectively reduced.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following description will briefly introduce the drawings that are required to be used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments described in the present application, and other drawings may also be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a flow chart of a dynamic early warning method for classification and classification of stationary pollution sources provided according to an embodiment of the present application;
fig. 2 is an internal structural diagram of a dynamic early warning system for classification and classification of fixed pollution sources according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application, taken in conjunction with the accompanying drawings, clearly and completely describes the technical solutions of the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
According to the method, the fixed pollution source is dynamically evaluated according to the classification grading standard and method of the fixed pollution source after the acquired information is quantitatively judged by periodically searching the relevant index information of the credit evaluation of the enterprise, and the credit risk value of the enterprise environment is predicted by means of a factoring machine model (Factorization machine, FM) so as to realize dynamic early warning.
Example 1
As shown in fig. 1, the method for dynamic early warning of classification and classification of fixed pollution sources provided in the embodiment of the present application specifically includes the following steps:
step S110: and acquiring a risk index variable value.
The method comprises the steps of acquiring the initial values of risk index variables, automatically and periodically acquiring data in each platform, and setting a 'fixed pollution source grading evaluation index and a quantization method table' according to the data acquired from each platform. Wherein the table is set with reference to emission standards for pollutants in the prior art.
Specifically, each platform is a public platform in the network. Such as an enterprise online monitoring platform, an environmental protection agency administrative punishment platform, a pollution discharge license management platform and an information disclosure platform.
The fixed pollution source grading evaluation index and the quantitative method are shown in table 1, and each risk index variable can be obtained from table 1.
TABLE 1
Specifically, the quantification of the original deduction value is performed according to the data obtained from each platform, for example, the online monitoring data or the administrative punishment data are obtained and compared with the corresponding standard value to obtain the original deduction value
Is a quantization of (2).
The standard value is a standard value corresponding to on-line monitoring data or administrative punishment data, for example, a standard value of the discharged atmospheric pollutants, a standard value of the discharged water pollutants, and the like, and the standard value can be obtained by the prior art, and specific numerical values are not repeated herein.
By acquiring on-line monitoring data or administrative penalty data and comparing with standard values, implementation of the on-line data can be directly compared, and if the enterprise is detected to have penalty records, the number of penalty records is used
The enterprise environmental credit score for each enterprise is dynamically validated as per table 1. Specifically, after the quantization mode is determined, table 1 specifically includes a class one penalty index, a class two penalty index, an encouragement index, a credit accumulation index, and a "one ticket overrule" index. Each index corresponds to one or more risk index variables, each risk index variable corresponds to a quantized original deduction value, each original deduction value corresponds to one or more specific deduction values, for example, when the discharged atmospheric pollutants exceed the standard by a factor less than or equal to 3, 35 points are deducted each time on the basis of the credit score of the enterprise environment, the discharged atmospheric pollutants exceed the standard by a factor less than or equal to 3< exceeding the standard by a factor less than or equal to 5, and 45 points are deducted each time on the basis of the credit score of the enterprise environment.
Further, the maximum credit of the enterprise environment is divided into 100 points, the minimum credit is divided into 0 points, the standard credit is divided into 80 points, and a subtraction item and an addition item are set; the direct count of the occurrence of the "one ticket overrule" situation is 0 points and the add term must not be used.
Still further, the pollution source units of the enterprises are divided into four grades in advance, which are respectively: the sum of the enterprise environment credit scores is more than 90 points (inclusive), the enterprise environment credit score is between 60 points (inclusive) and 90 points is "good", the enterprise environment credit score is between 30 points (inclusive) and 60 points is "warning", and the enterprise environment credit score is below 30 points is "bad";
preferably, the different levels may be represented in different colors, with the enterprise environmental credits being "honest" identified by green cards; the credit of the enterprise environment is good, and is marked by blue cards; the enterprise environmental credit is 'warning', and is marked by yellow cards; the enterprise environment credit is bad, and is marked by black cards.
Step S120: and dynamically acquiring the fixed pollution source evaluation score according to the acquired risk index variable value.
Wherein dynamic acquisition of a fixed pollution source evaluation score is enabled based on the risk indicator variable values in table 1, wherein the fixed pollution source evaluation score is substantially increased or decreased based on the original enterprise environment credit score.
Specifically, the fixed pollution source evaluation score C of the enterprise is specifically expressed as:
wherein the method comprises the steps of
The original deduction values are represented, i=1, 2,3. When->
When there is no ticket overrule, the evaluation criterion and method are calculated as +.>
When a ticket overrule exists, the credit score of the enterprise environment is directly 0.
Step S130: judging whether the level adjustment is needed according to the fixed pollution source evaluation score.
Specifically, dynamically acquiring the fixed pollution source evaluation scores of enterprises in different time periods, dynamically acquiring the fixed pollution source evaluation scores in different time periods, and if the difference value between the fixed pollution source evaluation scores acquired in the next time period and the fixed pollution source evaluation scores acquired in the previous time period exceeds a specified threshold, performing grade adjustment of the pollution source.
For example, if the fixed pollution source evaluation score calculated in the first time period is 90 minutes, the pollution source grade of the enterprise is "honest", and if the fixed pollution source evaluation score calculated in the next time period is 80 minutes, the pollution source grade of the enterprise needs to be graded, and specifically, the pollution source grade is adjusted from "honest" to "good".
If the level adjustment is required, step S140 is performed. If the level adjustment is not needed, the process exits.
Where each time period may be one hour, one day or half month, the specific deadline settings for the time period are set by the staff.
Step S140: and sending out an audit prompt.
Specifically, if the pollution source grade needs to be regulated, reminding the personnel to check again.
Step S150: and establishing an enterprise credit risk early warning model according to the variable value of the risk index to obtain the enterprise environment credit risk value.
Specifically, the enterprise credit risk early-warning model is an FM (Factorization Machine, factoring machine) model in the prior art, and the enterprise environment credit risk value obtained by the enterprise credit risk early-warning model is specifically expressed as:
wherein Y is k Representing enterprise environmental credit risk value, Y k =0 indicates that the enterprise existsIs at a pollution risk of 0, Y k =1 means that the risk of pollution of the enterprise is 100% and the enterprise environmental credit is 0.
λ 0 ∈R，λ i ∈R n R represents a real number set,
x ik standardized value of ith evaluation index (i is more than or equal to 1 and less than or equal to n) affecting credit state of kth enterprise, and x jk The jth index (1. Ltoreq.j.ltoreq.n) representing the kth enterprise's impact credit status, n being the number of rating indices, where n=17, i.e. the ith rating index and the jth rating index are x in table 1 1 ,x 2 ,...x 17 G is a coefficient matrix in the FM model, G i Is the ith row of the coefficient matrix G, G j Represents the j-th row of the coefficient matrix G, i.e. G i ＝(g i1 ,g i2 ,...g is )，G j ＝(g j1 ,g j2 ,...g js ) And->
Wherein->
Wherein the coefficient lambda 0 And each parameter in the matrix in G is a random number, and is obtained by least square fitting under the condition that certain deduction conditions and risk values are acquired in the model.
Wherein x is ik The concrete steps are as follows:
wherein the method comprises the steps of
The original value of the ith evaluation index of the kth enterprise, namely +.>
Values, e.g. of a businessThe industry is a one-dimensional array of 17 columns in the coefficient matrix G, if there are 20 enterprises, the coefficient matrix G becomes a two-bit array of 20×17, and m is the number of enterprises.
Step S160: and judging whether the credit risk value of the enterprise environment exceeds a specified threshold.
If the enterprise environmental credit risk value exceeds the specified threshold, step S170 is performed. Otherwise, the flow exits.
The specific value is not limited herein, and the specified threshold is a value set in advance by a worker.
Step S170: and sending out a prompt for increasing the inspection frequency.
The prompt is an early warning prompt, and specifically reminds a worker to increase the inspection times of the enterprise.
The steps S120-140 and the steps S150-170 can be performed simultaneously or sequentially.
Example two
As shown in FIG. 2, the dynamic early warning system for classifying and grading the fixed pollution sources provided by the embodiment of the application specifically comprises: the risk indicator variable obtaining unit 210, the fixed pollution source evaluation score obtaining unit 220, the grading judging unit 230, the first prompting unit 240, the enterprise environment credit risk value obtaining unit 250, the risk value judging unit 260 and the second prompting unit 270.
Wherein the risk indicator variable obtaining unit 210 is configured to obtain a risk indicator variable value.
The fixed pollution source evaluation score obtaining unit 220 is connected to the risk indicator variable obtaining unit 210, and is configured to dynamically obtain a fixed pollution source evaluation score according to the obtained risk indicator variable value.
The level adjustment judging unit 230 is connected to the fixed pollution source evaluation score obtaining unit 220, and is configured to judge whether level adjustment is required according to the fixed pollution source evaluation score.
The first prompting unit 240 is connected to the level adjustment judging unit 230, and is configured to issue an audit prompt if level adjustment is required.
The enterprise environmental credit risk value obtaining unit 250 is connected to the risk indicator variable obtaining unit 210, and is configured to establish an enterprise credit risk early warning model according to the risk indicator variable value, and obtain an enterprise environmental credit risk value.
The risk value determining unit 260 is connected to the enterprise environmental credit risk value obtaining unit 250, and is configured to determine whether the enterprise environmental credit risk value exceeds a specified threshold.
The second prompting unit 270 is connected to the risk value determining unit 260, and is configured to issue a prompt for increasing the inspection frequency if the credit risk value of the enterprise environment exceeds a specified threshold.
The application has the following beneficial effects:
(1) According to the method, the qualitative indexes are quantized by a technical means, the latest acquired and recorded information is automatically and periodically acquired, and a large number of qualitative indexes are converted into data which can be recognized and calculated by a system, so that dynamic scoring and grading of credit evaluation indexes and scoring standards are completed, the time cost is reduced, and the working efficiency is improved.
(2) By establishing the enterprise credit risk early warning model and the dynamic enterprise environment credit risk value, the enterprise inspection and management prompt with higher risk is conveniently and pertinently sent, the environment supervision frequency is optimized, the fixed pollution source supervision efficiency is improved, and the risk of environmental accidents is effectively reduced.
Although the examples referred to in the present application are described for illustrative purposes only and not as limitations on the present application, variations, additions and/or deletions to the embodiments may be made without departing from the scope of the application.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A dynamic early warning method for classifying and grading a fixed pollution source is characterized by comprising the following steps:
acquiring a risk index variable value;
dynamically acquiring a fixed pollution source evaluation score according to the acquired risk index variable value;
judging whether the level adjustment is required according to the fixed pollution source evaluation score;
if the level is required to be adjusted, sending out an audit prompt;
establishing an enterprise credit risk early warning model according to the risk index variable value to acquire an enterprise environment credit risk value;
judging whether the credit risk value of the enterprise environment exceeds a specified threshold value;
and if the credit risk value of the enterprise environment exceeds the specified threshold, sending a prompt for increasing the inspection frequency.
2. The method of claim 1, further comprising, prior to obtaining the initial values of the risk indicator variables, obtaining data from each platform, and setting a table of a fixed pollution source classification evaluation index and a quantization method based on the data obtained from each platform.
3. The method of claim 2, wherein the table of the classification and rating index and the quantization method of the fixed pollution source comprises a plurality of indexes and one or more risk index variables corresponding to each index, each risk index variable corresponding to a quantized original deduction value.
4. The method for dynamic early warning of classification and classification of stationary pollution sources according to claim 3, wherein the obtained data in each platform is used for quantifying the original deduction value to obtain a specific value of the original deduction value.
5. The method for dynamic early warning of classification and classification of stationary sources of pollution as set forth in claim 4, wherein the stationary source evaluation score C is specifically expressed as:
wherein the method comprises the steps of
The original deduction values are represented, i=1, 2,3.
6. The method for dynamically pre-warning classification of stationary pollution sources according to claim 5, wherein stationary pollution source evaluation scores of different time periods are dynamically obtained, and the classification of the pollution sources is adjusted if the difference between the stationary pollution source evaluation scores obtained in the next time period and the stationary pollution source evaluation scores obtained in the previous time period exceeds a specified threshold.
7. The method of claim 6, wherein the time period is one hour, one day, half month or one month.
8. The method for dynamic early warning of classification and grading of stationary pollution sources according to claim 1, wherein the enterprise environmental credit risk value Y k The concrete steps are as follows:
λ 0 ∈R，λ i ∈R n r represents a real number set,
x ik standardized value of the ith evaluation index affecting credit status for the kth enterprise, x jk The j index representing the credit status of enterprise influence, n is the number of evaluation indexes, wherein n=17, G is coefficient matrix in FM model, G i Is the ith row of the coefficient matrix G, G j Represents the j-th row of the coefficient matrix G. />
9. The method of dynamic early warning of stationary source classification in accordance with claim 8, wherein G i ＝(g i1 ,g i2 ,...g is ),s＝2,
10. The utility model provides a dynamic early warning system of classification of fixed pollution source which characterized in that specifically includes: the system comprises a risk index variable acquisition unit, a fixed pollution source evaluation score acquisition unit, a grading judgment unit, a first prompt unit, an enterprise environment credit risk value acquisition unit, a risk value judgment unit and a second prompt unit;
the risk index variable acquisition unit is used for acquiring a risk index variable value;
the fixed pollution source evaluation score acquisition unit is used for dynamically acquiring the fixed pollution source evaluation score according to the acquired risk index variable value;
the level adjustment judging unit is used for judging whether level adjustment is needed according to the fixed pollution source evaluation score;
the first prompting unit is used for sending out an audit prompt if the level adjustment is required;
the enterprise environment credit risk value acquisition unit is used for establishing an enterprise credit risk early warning model according to the risk index variable value to acquire an enterprise environment credit risk value;
the risk value judging unit is used for judging whether the credit risk value of the enterprise environment exceeds a specified threshold value;
and the second prompting unit is used for sending out a prompt for increasing the inspection frequency if the credit risk value of the enterprise environment exceeds a specified threshold value.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116822970A (en) * | 2023-08-30 | 2023-09-29 | 湖北省生态环境科学研究院(省生态环境工程评估中心) | Automatic judging method and system for monitoring priority of high-environmental-health-risk pollutants |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110705855A (en) * | 2019-09-23 | 2020-01-17 | 清华苏州环境创新研究院 | Enterprise environment portrait evaluation method and system |
| CN111507603A (en) * | 2020-04-13 | 2020-08-07 | 苏州杜班环境安全技术有限公司 | Method and system for evaluating current environmental risk situation of in-production enterprise |
| CN114172272A (en) * | 2021-12-13 | 2022-03-11 | 铜陵有色金属集团铜冠建筑安装股份有限公司 | Energy-saving multi-load power distribution cabinet debugging method |
-
2022
- 2022-09-28 CN CN202211190902.7A patent/CN116128277A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110705855A (en) * | 2019-09-23 | 2020-01-17 | 清华苏州环境创新研究院 | Enterprise environment portrait evaluation method and system |
| CN111507603A (en) * | 2020-04-13 | 2020-08-07 | 苏州杜班环境安全技术有限公司 | Method and system for evaluating current environmental risk situation of in-production enterprise |
| CN114172272A (en) * | 2021-12-13 | 2022-03-11 | 铜陵有色金属集团铜冠建筑安装股份有限公司 | Energy-saving multi-load power distribution cabinet debugging method |
Non-Patent Citations (2)
| Title |
|---|
| 佟孟华等: "基于FM模型的工业企业碳减排信用风险预警研究", 《数量经济技术经济研究》, pages 147 - 162 * |
| 崇佳文: "企业环保信用体系研究——以苏州市S公司为例", 《中国优秀硕士学位论文全文数据库经济与管理科学辑》, pages 152 - 595 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116822970A (en) * | 2023-08-30 | 2023-09-29 | 湖北省生态环境科学研究院(省生态环境工程评估中心) | Automatic judging method and system for monitoring priority of high-environmental-health-risk pollutants |
| CN116822970B (en) * | 2023-08-30 | 2023-11-21 | 湖北省生态环境科学研究院(省生态环境工程评估中心) | Automatic judging method and system for monitoring priority of high-environmental-health-risk pollutants |
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