Data simulation monitoring system and method based on human hair PFRs compounds

Abstract

The present invention relates to the technical field of non-invasive monitoring of human biology, and discloses a data simulation monitoring system based on human hair PFRs compounds and a method thereof, wherein the detection system is composed of a reverse tracing module, a data area division module, a regional environmental data acquisition module, a PFRs value comprehensive calculation module and a monitoring module. The present invention divides the region into industrial areas, urban areas and rural areas according to the result of the reverse tracing module, which is helpful for analyzing the different environmental influences on the PFRs content in the hair sample, collecting environmental data such as climate data and population density in each region, and using the collected regional environmental data and the PFRs value in the hair sample, the system calculates the PFRs content value of the region to which each hair sample belongs, and the monitoring module identifies the region with too high PFRs value according to the calculation result, makes a judgment through a set threshold, and takes necessary environmental protection and public health management measures, so as to achieve the beneficial effect of being able to obtain accurate data of the PFRs value of the source of human hair.

Description

Technical Field

[0001] The present invention relates to the technical field of human biological monitoring, in particular to a data simulation monitoring system and method based on human hair PFRs compounds. Background Art

[0002] In recent years, the production and consumption of organophosphate flame retardants (PFRs) as substitutes for PBDEs and HBCDs have shown a significant increase. At present, PFRs are widely detected in indoor air and dust, water, sediment, organisms, human milk and blood. At the same time, studies have shown that PFRs have potential negative effects on organisms and humans, and their ecological and human health effects have also attracted widespread attention. Human hair, as a non-invasive biological monitoring material for human biological monitoring, has been widely used in recent years to assess the exposure level of human organic pollutants.

[0003] After searching, it was found that the prior art publication number is CN 111474259 B, which is a method for synchronously extracting and analyzing multiple flame retardants in hair. It belongs to the field of human biological monitoring technology. The present invention can synchronously extract polybrominated diphenyl ethers (PBDEs), hexabromocyclododecanes (HBCDs), traditional and emerging organophosphorus flame retardants (PFRs / ePF Rs) in hair at one time, and the final recovery rate of the target compound is 90-110%. It solves the problem of how to use hair as an exposure marker to evaluate the health effects of flame retardants on the human body, and at the same time promotes the application of hair as a non-invasive biological monitoring material for human exposure to organic pollutants in medicine and epidemiology.

[0004] The aforementioned technical solution proposes a technical solution for the simultaneous extraction and analysis of multiple flame retardants in hair, which solves the problem of PFRs detection. However, it does not solve the problem of simulating the actual PFRs pollution level in the area based on the proportion of PFRs detected in the hair. It can only obtain approximate data through simple conversion based on the proportion of sample data. However, in the actual environment, there are differences in population density and the proportion between residential and industrial areas. It is impossible to calculate in detail the difference in the proportion of small-scale data in the area where the sample data is located. Summary of the invention

[0005] Technical issues solved:

[0006] In view of the deficiencies in the prior art, the present invention provides a data simulation monitoring system and method based on human hair PFRs compounds, which has the advantages of being able to obtain accurate data on the PFRs value of the origin of human hair and calculate the proportion of small-range data in the area where the sample data is located, thereby solving the problems of the above-mentioned technologies.

[0007] Technical solution:

[0008] To achieve the above-mentioned object, the present invention provides the following technical solutions: a data simulation monitoring system based on human hair PFRs compounds, the detection system is composed of a reverse tracing module, a data area division module, a regional environmental data acquisition module, a PFRs numerical comprehensive calculation module and a monitoring module;

[0009] The reverse tracing module is used to reversely trace each individual sample in a batch of hair samples to lock the original collection area of ​​the hair;

[0010] The data area division module is used to mark the hair area traced by the reverse tracing module, and divide it using industrial areas, urban areas and rural areas as standards, wherein the standard for urban areas is ≥100 people per 100 square kilometers, the standard for industrial areas is ≥5 industrial and mining enterprises per 100 square kilometers, and the standard for rural areas is ≤100 people per 100 square kilometers. The division priority is industrial areas>urban areas>rural areas, that is, when multiple conditions are met, the priority shall prevail;

[0011] The regional environmental data acquisition module is used to collect climate data and population density of the area to which each individual sample belongs divided by the data area division module;

[0012] The PFRs value comprehensive calculation module is used to use the data collected by the regional environmental data collection module as variables and introduce the PFRs value of each individual sample in the hair sample and the region to which it belongs, and perform comprehensive calculation to obtain the PFRs content value of the region to which the hair sample belongs;

[0013] The monitoring module is used to monitor the area where the PFRs value is too high according to the calculation results of the PFRs value comprehensive calculation module.

[0014] Preferably, the reverse tracing module is used to output the original collection area information of each hair sample, so that the monitoring system can track and analyze the source location of the PFRs compounds in the hair sample.

[0015] Preferably, the reverse tracing module expression is:

[0016] The PFRs content of the hair sample is expressed as follows: The PFRs content of the i-th hair sample is PFRs i ;

[0017] Geographic location data representation: Assume that the geographic location data of the i-th hair sample is (lat i ,lon i ), where lat i is the latitude, lon i is the longitude;

[0018] Geographic information matching function: Define the matching function M to evaluate the geographic location (lat i ,lon i ) and the collection area R j the relationship between;

[0019] Reverse tracing model: Combining the PFRs content in hair samples with geographic location data, the reverse tracing model is used to infer the original collection area R i , expressed as:

[0020]

[0021] in, Indicates that in all acquisition areas R j Find the region R that maximizes the matching function M i .

[0022] Preferably, the matching function (M) is expressed as:

[0023] M=(PFRs i ,(lat i ,lon i ),R j ) PFRs ·f PFRs (PFRs i )+w dist ·f dist ((lat i ,lon i ),R j )+w features ·f features (R j )

[0024] in:

[0025] f PFRs (PFRs i ) is a function of the PFRs content, which is a simple linear weighting or a more complex nonlinear function, used to evaluate the content of PFRs compounds in hair samples;

[0026] f dist ((lat i ,lon i ),R j ) is a function of geographic distance, evaluating the geographic location of the hair sample (lat i ,lon i ) and region R j The distance between

[0027] f features (R j) is a function of regional characteristics, considering region R j Various characteristics: population density, industrial distribution;

[0028] w PFRs ,w dist ,w features is the corresponding weight, which is used to adjust the importance of each factor in the matching process, where w PFRs Indicates the importance of the PFRs compound content in the hair sample in the matching process, w dist represents the importance of the distance between the geographical location of the hair sample and the collection area in the matching process, w features Indicates the importance of regional characteristics: population density, industrial distribution, in the matching process.

[0029] Preferably, the standard expression for urban areas in the data area division module is:

[0030]

[0031] in, Indicates region R j PFRs content value; f is the comprehensive calculation function; Data(R j ) represents region R j Environmental data in PFR hair Indicates the PFRs content in the hair sample.

[0032] Preferably, the expression of the industrial area standard in the data area division module is:

[0033]

[0034] Among them, R industrial (R j ) is a Boolean function representing the region R j Whether it meets the standards of industrial zones, is an indicator function, which means that if Rindustrial (R j )=1, otherwise R industrial (R j )=0,Area(R j ) represents region R j The total area of ​​​​IndustrialCount(R j ) represents region R j The number of industrial and mining enterprises within a region is the total number of all industrial and mining enterprises in the region.

[0035] The expression of the rural area standard in the data area division module is:

[0036]

[0037] Where: R uninhabited (R j ) is a Boolean function used to determine the region R j Whether it meets the standards for rural areas, 1 means it meets the standards, 0 means it does not meet the standards, Indicates region R j Population density; otherwise means if the condition If the population density is greater than 100, then R uninhabited (R j ) value is 0, the area does not meet the criteria for a rural area.

[0038] Preferably, the PFRs numerical comprehensive calculation module expression is:

[0039] PFRs hair Indicates the PFRs content in the hair sample, Data(R j ) represents region R j The environmental data in the figure are as follows:

[0040] PFRsregion(R j )=f(Data(R j ),PFRs hair )

[0041] Among them, PFRsregion(R j ) represents the calculation result, which is calculated by the f function. f is a comprehensive calculation function that combines the regional environmental data and the PFRs content value in the hair sample to calculate the PFRs content value of the area to which the hair sample belongs.

[0042] Preferably, the monitoring module expression is:

[0043]

[0044] Where: PFRsregion(R j ) represents region R j PFRs content value; PFRs threshold (R j ) represents R j PFRs threshold; otherwise is the preset PFRs standard value.

[0045] A data simulation monitoring method based on human hair PFRs compounds, the monitoring method is generated by a monitoring system, and the steps of the monitoring method are:

[0046] Step 1: trace back each individual sample in a batch of hair samples to determine its original collection area;

[0047] Step 2: According to the original collection area of ​​the hair samples determined by the reverse tracing module, the area is divided into industrial areas, urban areas and rural areas;

[0048] Step 3: Collect environmental data such as climate data and population density of the area where each hair sample belongs;

[0049] Step 4: Calculate the PFRs content value of the area to which each hair sample belongs by using the regional environmental data and the PFRs value in the hair sample;

[0050] Step 5: Based on the results obtained by the PFRs value comprehensive calculation module, monitor and identify areas where the PFRs values ​​are too high.

[0051] Compared with the prior art, the present invention provides a data simulation monitoring system and method based on human hair PFRs compounds, which has the following beneficial effects:

[0052] 1. The present invention divides the region into industrial areas, urban areas and rural areas according to the results of the reverse tracing module, which is helpful to analyze the different environmental influences on the PFRs content in the hair samples, collects environmental data such as climate data and population density in each region, and ensures the scientificity and accuracy of the calculation. The system calculates the PFRs content value of the region to which each hair sample belongs by using the collected regional environmental data and the PFRs value in the hair sample, and combines the geographical environment and chemical data to provide numerical support for accurate evaluation. The monitoring module identifies the area with too high PFRs value according to the calculation results, makes judgments based on the set threshold, and takes necessary environmental protection and public health management measures, thereby achieving the beneficial effect of obtaining accurate data on the PFRs value of the origin of human hair.

[0053] 2. The present invention collects climate data, population density and other environmental data of the region to which each hair sample belongs through the regional environmental data collection module, which is not only used for the comprehensive calculation of PFRs values, but also can be used to calculate the specific proportions of various environmental factors in a small range. The PFRs value comprehensive calculation module combines the regional environmental data and the PFRs content in the hair sample to obtain the PFRs content value of the region to which each hair sample belongs. These values ​​reflect the specific distribution of PFRs in a small range, provide a basis for the subsequent calculation of the proportion value, and achieve the beneficial effect of calculating the proportion of small-range data in the region where the sample data is located. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a schematic diagram of the steps of the method of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] See also Figure 1 , a data simulation monitoring system based on human hair PFRs compounds, the detection system consists of a reverse tracing module, a data area division module, a regional environmental data acquisition module, a PFRs numerical comprehensive calculation module and a monitoring module;

[0057] The reverse tracing module is used to reversely trace each individual sample in a batch of hair samples to lock the original collection area of ​​the hair;

[0058] The data area division module is used to mark the hair area traced by the reverse tracing module, and divide it into industrial areas, urban areas and rural areas, where the standard for urban areas is ≥100 people per 100 square kilometers, the standard for industrial areas is ≥5 industrial and mining enterprises per 100 square kilometers, and the standard for rural areas is ≤100 people per 100 square kilometers;

[0059] The regional environmental data acquisition module is used to collect climate data and population density of the area to which each individual sample belongs divided by the data area division module;

[0060] The PFRs value comprehensive calculation module is used to use the data collected by the regional environmental data collection module as variables and introduce the PFRs value of each individual sample in the hair sample and the region to which it belongs, and perform comprehensive calculation to obtain the PFRs content value of the region to which the hair sample belongs;

[0061] The monitoring module is used to monitor the area where the PFRs value is too high according to the calculation results of the PFRs value comprehensive calculation module.

[0062] Preferably, the reverse tracing module is used to output the original collection area information of each hair sample, so that the monitoring system can track and analyze the source location of the PFRs compounds in the hair sample.

[0063] By utilizing the precise geographic location data of each hair sample, geographical errors are minimized and the accuracy of subsequent analysis is ensured. Machine learning algorithms are used to automatically learn and adapt to complex data patterns, reduce the subjectivity of human judgment, and improve the accuracy and efficiency of inferring the original collection location. The accuracy of regional locking: the results output by the algorithm accurately lock each hair sample to the original collection area, providing accurate geographical reference for subsequent regional environmental data collection and PFRs numerical comprehensive calculation. The reverse traceability module can fully output the original collection area information of each hair sample, so that the monitoring system can effectively track and analyze the source location of PFRs compounds, providing accurate data input for other modules.

[0064] Preferably, the reverse tracing module expression is:

[0065] The PFRs content of the hair sample is expressed as follows: The PFRs content of the i-th hair sample is PFRs i ;

[0066] Geographic location data representation: Assume that the geographic location data of the i-th hair sample is (lat i ,lon i ), where lat i is the latitude, lon i is the longitude;

[0067] Geographic information matching function: Define the matching function M to evaluate the geographic location (lat i ,lon j ) and the collection area R j the relationship between;

[0068] Reverse tracing model: Combining the PFRs content in hair samples with geographic location data, the reverse tracing model is used to infer the original collection area R i , expressed as:

[0069]

[0070] in, Indicates that in all acquisition areas R j Find the region R that maximizes the matching function M i .

[0071] The above model combines the chemical data (PFRs content) and geographic data (geographic location) of hair samples, and uses mathematical models (matching function (M) and maximization selection) to accurately infer the original collection location of the hair samples. Through this precise geographic positioning and calculation method, the reverse traceability module can provide a highly accurate basis for subsequent environmental data analysis and PFRs content assessment, thereby enhancing the scientific nature and application value of the monitoring system.

[0072] The matching function (M) is expressed as:

[0073] M=(PFRs i ,(lat i ,lon i ),R j ) PFRs ·f PFRs (PFRs i )+w dist ·f dist ((lat i ,lon i ),R j )

[0074] +w features ·f features (R j )

[0075] in:

[0076] f PFRs (PFRs i ) is a function of the PFRs content, which is a simple linear weighting or a more complex nonlinear function, used to evaluate the content of PFRs compounds in hair samples;

[0077] f dist ((lat i ,lon i ),R j ) is a function of geographic distance, evaluating the geographic location of the hair sample (lat i ,lon i ) and region R j The distance between

[0078] f features (R j ) is a function of regional characteristics, considering region R j Various characteristics: population density, industrial distribution;

[0079] w PFRs ,w dist ,w features is the corresponding weight, which is used to adjust the importance of each factor in the matching process, where w PFRs Indicates the importance of the PFRs compound content in the hair sample in the matching process, w dist represents the importance of the distance between the geographical location of the hair sample and the collection area in the matching process, w features Indicates the importance of regional characteristics: population density, industrial distribution, in the matching process.

[0080] Preferably, the standard expression for urban areas in the data area division module is:

[0081]

[0082] in, Indicates region R j PFRs content value; f is the comprehensive calculation function; Data(R j ) represents region R j Environmental data in PFRs hair Indicates the PFRs content in the hair sample.

[0083] This expression is based on the region R j The population density and geographical area are used to determine whether it is an urban area. When the population density in an area reaches or exceeds 100 people per square unit area, the area is defined as an urban area, which helps the system to accurately distinguish different types of geographical areas and provides an important reference framework for subsequent environmental data collection and PFRs numerical evaluation.

[0084] Preferably, the expression of the industrial area standard in the data area division module is:

[0085]

[0086] Among them, R industrial (R j ) is a Boolean function representing the region R j Whether it meets the standards of industrial zones, is an indicator function, which means that if Rindustrial (R j )=1, otherwise R industrial (R j )=0,Area(R j ) represents region R j The total area of ​​​​IndustrialCount(R j ) represents region R j The number of industrial and mining enterprises within a region is the total number of all industrial and mining enterprises in the region.

[0087] Preferably, the expression of the rural area standard in the data area division module is:

[0088]

[0089] Where: R uninhabited (R j ) is a Boolean function used to determine the region R j Whether it meets the standards for rural areas, 1 means it meets the standards, 0 means it does not meet the standards, Indicates region R j Population density; otherwise means if the condition If the population density is greater than 100, then R uninhabited (R j ) value is 0, the area does not meet the criteria for a rural area.

[0090] Preferably, the PFRs numerical comprehensive calculation module expression is:

[0091] PFRs hair Indicates the PFRs content in the hair sample, Data(R j ) represents region R j The environmental data in the figure are as follows:

[0092] PFRsregion(R j )=f(Data(R j ),PFRs hair )

[0093] Among them, PFRsregion(R j ) represents the calculation result, which is calculated by the f function. f is a comprehensive calculation function that combines the regional environmental data and the PFRs content value in the hair sample to calculate the PFRs content value of the area to which the hair sample belongs.

[0094] Preferably, the monitoring module expression is:

[0095]

[0096] Where: PFRsregion(R j ) represents region R j PFRs content value; PFRs threshold (R j ) represents R j PFRs threshold; otherwise is the preset PFRs standard value.

[0097] A data simulation monitoring method based on human hair PFRs compounds, the monitoring method is generated by a monitoring system, and the steps of the monitoring method are:

[0098] Step 1: trace back each individual sample in a batch of hair samples to determine its original collection area;

[0099] Step 2: According to the original collection area of ​​the hair samples determined by the reverse tracing module, the area is divided into industrial areas, urban areas and rural areas;

[0100] Step 3: Collect environmental data such as climate data and population density of the area where each hair sample belongs;

[0101] Step 4: Calculate the PFRs content value of the area to which each hair sample belongs by using the regional environmental data and the PFRs value in the hair sample;

[0102] Step 5: Based on the results obtained by the PFRs value comprehensive calculation module, monitor and identify areas where the PFRs values ​​are too high.

[0103] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations may be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A data simulation monitoring system based on human hair PFRs compounds, characterized in that: The monitoring system consists of a reverse tracing module, a data area division module, a regional environmental data acquisition module, a PFRs numerical comprehensive calculation module and a monitoring module; The reverse tracing module is used to reversely trace each individual sample in a batch of hair samples to lock the original collection area of ​​the hair; The data area division module is used to mark the hair area traced by the reverse tracing module, and divide it into industrial areas, urban areas and rural areas, where the standard for urban areas is ≥100 people per 100 square kilometers, the standard for industrial areas is ≥5 industrial and mining enterprises per 100 square kilometers, and the standard for rural areas is ≤100 people per 100 square kilometers; The regional environmental data acquisition module is used to collect climate data and population density of the area to which each individual sample belongs divided by the data area division module; The PFRs value comprehensive calculation module is used to use the data collected by the regional environmental data collection module as variables and introduce the PFRs value of each individual sample in the hair sample and the region to which it belongs, and perform comprehensive calculation to obtain the PFRs content value of the region to which the hair sample belongs; The monitoring module is used to monitor the area where the PFRs value is too high according to the calculation results of the PFRs value comprehensive calculation module.

2. The data simulation monitoring system based on human hair PFRs compounds according to claim 1, characterized in that: The reverse tracing module is used to output the original collection area information of each hair sample, so that the monitoring system can track and analyze the source location of the PFRs compounds in the hair sample.

3. The data simulation monitoring system based on human hair PFRs compounds according to claim 1, characterized in that: The reverse tracing module expression is: The PFRs content of the hair sample is expressed as follows: The PFRs content of the i-th hair sample is PFRs i ; Geographic location data representation: Assume that the geographic location data of the i-th hair sample is (lat i ,lon i ), where lat i is the latitude, lon i is the longitude; Geographic information matching function: Define the matching function M to evaluate the geographic location (lat i ,lon i ) and the collection area R j the relationship between; Reverse tracing model: Combining the PFRs content in hair samples with geographic location data, the reverse tracing model is used to infer the original collection area R i , expressed as: in, Indicates that in all acquisition areas R j Find the region R that maximizes the matching function M i .

4. The data simulation monitoring system based on human hair PFRs compounds according to claim 3, characterized in that: The matching function M is expressed as: M(PFRs i ,(lat i ,lon i ),R j ) =w PFRs ·f PFRs (PFRs i )+w dist ·f dist ((lat i ,lon i ),R j )+w features ·f features (R j ) in: f PFRs (PFRs i ) is a function of the PFRs content, which is a simple linear weighting or a more complex nonlinear function, used to evaluate the content of PFRs compounds in hair samples; f dist ((lat i ,lon i ),R j ) is a function of geographic distance, evaluating the geographic location of the hair sample (lat i ,lon i ) and region R j The distance between f features (R j ) is a function of regional characteristics, considering region R j Various characteristics: population density, industrial distribution; w PFRs ,w dist ,w features is the corresponding weight, which is used to adjust the importance of each factor in the matching process, where w PFRs Indicates the importance of the PFRs compound content in the hair sample in the matching process, w dist represents the importance of the distance between the geographical location of the hair sample and the collection area in the matching process, w features Indicates the importance of regional characteristics: population density, industrial distribution, in the matching process.

5. The data simulation monitoring system based on human hair PFRs compounds according to claim 1, characterized in that: The standard expression for urban areas in the data area division module is: in, Indicates urban area R j PFRs content value; f is the comprehensive calculation function; Data(R j ) represents region R j Environmental data in PFRs hair Indicates the PFRs content in the hair sample.

6. The data simulation monitoring system based on human hair PFRs compounds according to claim 5, characterized in that: The expression of the industrial area standard in the data area division module is: Among them, R industrial (R j ) is a Boolean function representing the region R j Whether it meets the standards of industrial zones, is an indicator function, which means that if Rindustrial (R j )=1, otherwise R industrial (R j )=0,Area(R j ) represents region R j The total area of ​​​​IndustrialCount(R j ) represents region R j The number of industrial and mining enterprises within a region is the total number of all industrial and mining enterprises in the region.

7. The data simulation monitoring system based on human hair PFRs compounds according to claim 5, characterized in that: The expression of the rural area standard in the data area division module is: Where: R uninhabited (R j ) is a Boolean function used to determine the region R j Whether it meets the standards for rural areas, 1 means it meets the standards, 0 means it does not meet the standards, Indicates region R j Population density; otherwise means if the condition If the population density is greater than 100, then R uninhabited (R j ) value is 0, the area does not meet the criteria for a rural area.

8. The data simulation monitoring system based on human hair PFRs compounds according to claim 1, characterized in that: The PFRs numerical comprehensive calculation module expression is: PFRs hair Indicates the PFRs content in the hair sample, Data(R j ) represents region R j The environmental data in the figure are as follows: PFRsregion(R j )=f(Data(R j ),PFRs hair ) Among them, PFRsregion(R j ) represents the calculation result, which is calculated by the f function. f is a comprehensive calculation function that combines the regional environmental data and the PFRs content value in the hair sample to calculate the PFRs content value of the area to which the hair sample belongs.

9. The data simulation monitoring system based on human hair PFRs compounds according to claim 1, characterized in that: The monitoring module expression is: Where: PFRsregion(R j ) represents region R j PFRs content value; PFRs threshold (R j ) represents R j PFRs threshold; otherwise is the preset PFRs standard value.

10. A data simulation monitoring method based on human hair PFRs compounds, characterized in that: The monitoring method is used in the monitoring system according to claim 1, and the steps of the monitoring method are: Step 1: trace back each individual sample in a batch of hair samples to determine its original collection area; Step 2: According to the original collection area of ​​the hair samples determined by the reverse tracing module, the area is divided into industrial areas, urban areas and rural areas; Step 3, collecting climate data and population density environment data of the area where each hair sample belongs; Step 4: Calculate the PFRs content value of the area to which each hair sample belongs by using the regional environmental data and the PFRs value in the hair sample; Step 5: Based on the results obtained by the PFRs value comprehensive calculation module, monitor and identify areas where the PFRs values ​​are too high.

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