Accurate age estimates of immature necrophagous insects associated with a human or animal body can provide evidence of how long the body has been dead.These estimates are based on species-specific details of the inse...Accurate age estimates of immature necrophagous insects associated with a human or animal body can provide evidence of how long the body has been dead.These estimates are based on species-specific details of the insects’aging processes,and therefore require accurate species identification and developmental stage estimation.Many professionals who produce or use identified organisms as forensic evidence have little training in taxonomy or metrology,and appreciate the availability of formalized principles and standards for biological identification.Taxonomic identifications are usually most readily and economically made using categorical and qualitative morphological characters,but it may be necessary to use less convenient and potentially more ambiguous characters that are continuous and quantitative if two candidate species are closely related,or if identifying developmental stages within a species.Characters should be selected by criteria such as taxonomic specificity and metrological repeatability and relative error.We propose such a hierarchical framework,critique various measurements of immature insects,and suggest some standard approaches to determine the reliability of organismal identifications and measurements in estimating postmortem intervals.Relevant criteria for good characters include high repeatability(including low scope for ambiguity or parallax effects),pronounced discreteness,and small relative error in measurements.These same principles apply to individuation of unique objects in general.展开更多
The generation of a DNA profile from skeletal remains is an important part of the identifica-tion process in both mass disaster and unidentified person cases. Since bones and teeth are often the only biological materi...The generation of a DNA profile from skeletal remains is an important part of the identifica-tion process in both mass disaster and unidentified person cases. Since bones and teeth are often the only biological materials remaining after exposure to environmental conditions, intense heat, certain traumatic events and in cases where a significant amount of time has passed since the death of the individual, the ability to purify large quantities of informative DNA from these hard tissues would be beneficial. Since sampling the hard tissues for gen-etic analysis is a destructive process, it is important to understand those environmental and intrinsic factors that contribute to DNA preservation. This will serve as a brief introduction to these topics, since skeletal sampling strategies and molecular taphonomy have been dis-cussed in depth elsewhere. Additionally advances in skeletal DNA extraction and analysis will be discussed. Currently there is great variation in the DNA isolation methods used by laboratories to purify DNA from the hard tissues;however, a standardized set of short tan-dem repeat (STR) loci is analyzed by many US laboratories to allow for comparisons across samples and jurisdictions. Recent advances have allowed for the generation of DNA profiles from smaller quantities of template DNA and have expanded the number of loci analyzed for greater discriminatory power and predictions regarding the geographic ancestry and phenotype of the individual. Finally, utilizing databases and expanding the number of com-parison samples will be discussed in light of their role in the identification process.展开更多
The probative value of animal forensic genetic evidence relies on laboratory accuracy and reliability.Inter-laboratory comparisons allow laboratories to evaluate their performance on specific tests and analyses and to...The probative value of animal forensic genetic evidence relies on laboratory accuracy and reliability.Inter-laboratory comparisons allow laboratories to evaluate their performance on specific tests and analyses and to continue to monitor their output.The International Society for Animal Genetics(ISAG)administered animal forensic comparison tests(AFCTs)in 2016 and 2018 to assess the limitations and capabilities of laboratories offering forensic identification,parentage and species determination services.The AFCTs revealed that analyses of low DNA template concentrations(≤300 pg/μL)constitute a significant challenge that has prevented many laboratories from reporting correct identification and parentage results.Moreover,a lack of familiarity with species testing protocols,interpretation guidelines and representative databases prevented over a quarter of the participating laboratories from submitting correct species determination results.Several laboratories showed improvement in their genotyping accuracy over time.However,the use of forensically validated standards,such as a standard forensic short tandem repeat(STR)kit,preferably with an allelic ladder,and stricter guidelines for STR typing,may have prevented some common issues from occurring,such as genotyping inaccuracies,missing data,elevated stutter products and loading errors.The AFCTs underscore the importance of conducting routine forensic comparison tests to allow laboratories to compare results from each other.Laboratories should keep improving their scientific and technical capabilities and continuously evaluate their personnel’s proficiency in critical techniques such as low copy number(LCN)analysis and species testing.Although this is the first time that the ISAG has conducted comparison tests for forensic testing,findings from these AFCTs may serve as the foundation for continuous improvements of the overall quality of animal forensic genetic testing.展开更多
Disaster victim identification issues are especially critical and urgent after a large-scale disaster.The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on...Disaster victim identification issues are especially critical and urgent after a large-scale disaster.The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on dental panoramic radiographs(DPRs)using deep learning to promote its applicability as human identifiers.A total of 1638 DPRs,of which the chronological age ranged from 20 to 49 years old,were collected from January 2000 to November 2020.This dataset consisted of natural teeth,prostheses,teeth with root canal treatment,and implants.The detection of natural teeth and dental treatment patterns including the identification of teeth number was done with a pre-trained object detection network which was a convolutional neural network modified by EfficientDet-D3.The objective metrics for the average precision were 99.1%for natural teeth,80.6%for prostheses,81.2%for treated root canals,and 96.8%for implants,respectively.The values for the average recall were 99.6%,84.3%,89.2%,and 98.1%,in the same order,respectively.This study showed outstanding performance of convolutional neural network using dental panoramic radiographs in automatically identifying teeth number and detecting natural teeth,prostheses,treated root canals,and implants.展开更多
We investigated the forensic efficacy of the 30 insertion/deletion(Indel)markers included in the Qiagen Investigator■DIPplex kit in 529 Pakistani individuals from five major subpopulations in Pakistan(Punjabi,Pashtun...We investigated the forensic efficacy of the 30 insertion/deletion(Indel)markers included in the Qiagen Investigator■DIPplex kit in 529 Pakistani individuals from five major subpopulations in Pakistan(Punjabi,Pashtun,Sindhi,Saraiki,and Baloch).In the Sindhi population,the distribution of HLD81 and HLD97 alleles deviated from Hardy-Weinberg equilibrium after Bonferroni correction.The combined match probability ranged from 2.0E-12(Pashtun and Baloch)to 1.0E-12(Sindhi),and the mean paternity exclusion power varied from 0.995(Punjabi,Sindhi,and Saraiki)to 0.996(Pashtun and Baloch).The high combined power of discrimination(0.99999999999997)and low combined match probability(1.7E-12)for all subpopulations studied support the utility of the 30 Indel markers for forensic identification in the studied subpopulations.The allele frequencies of the Indel markers in the Pakistani subpopulations were compared with those from 18 other populations.The results show that the populations clustered according to geography.The subpopulations investigated in this work showed a close genetic relationship with others from Pakistan,as well as with South Central Asian and Middle Eastern populations.The results suggest that the Investigator■DIPplex kit can be useful as a supplementary tool for human identification in the five Pakistani subpopulations investigated in this study.展开更多
In this paper,camera recognition with the use of deep learning technique is introduced.To identify the various cameras,their characteristic photo-response non-uniformity(PRNU)noise pattern was extracted.In forensic sc...In this paper,camera recognition with the use of deep learning technique is introduced.To identify the various cameras,their characteristic photo-response non-uniformity(PRNU)noise pattern was extracted.In forensic science,it is important,especially for child pornography cases,to link a photo or a set of photos to a specific camera.Deep learning is a sub-field of machine learning which trains the computer as a human brain to recognize similarities and differences by scanning it,in order to identify an object.The innovation of this research is the use of PRNU noise patterns and a deep learning technique in order to achieve camera identification.In this paper,AlexNet was modified producing an improved training procedure with high maximum accuracy of 80%–90%.DIGITS showed to have identified correctly six cameras out of 10 with a success rate higher than 75%in the database.However,many of the cameras were falsely identified indicating a fault occurring during the procedure.A possible explanation for this is that the PRNU signal is based on the quality of the sensor and the artefacts introduced during the production process of the camera.Some manufacturers may use the same or similar imaging sensors,which could result in similar PRNU noise patterns.In an attempt to form a database which contained different cameras of the same model as different categories,the accuracy rate was low.This provided further proof of the limitations of this technique,since PRNU is stochastic in nature and should be able to distinguish between different cameras from the same brand.Therefore,this study showed that current convolutional neural networks(CNNs)cannot achieve individualization with PRNU patterns.Nevertheless,the paper provided material for further research.展开更多
文摘Accurate age estimates of immature necrophagous insects associated with a human or animal body can provide evidence of how long the body has been dead.These estimates are based on species-specific details of the insects’aging processes,and therefore require accurate species identification and developmental stage estimation.Many professionals who produce or use identified organisms as forensic evidence have little training in taxonomy or metrology,and appreciate the availability of formalized principles and standards for biological identification.Taxonomic identifications are usually most readily and economically made using categorical and qualitative morphological characters,but it may be necessary to use less convenient and potentially more ambiguous characters that are continuous and quantitative if two candidate species are closely related,or if identifying developmental stages within a species.Characters should be selected by criteria such as taxonomic specificity and metrological repeatability and relative error.We propose such a hierarchical framework,critique various measurements of immature insects,and suggest some standard approaches to determine the reliability of organismal identifications and measurements in estimating postmortem intervals.Relevant criteria for good characters include high repeatability(including low scope for ambiguity or parallax effects),pronounced discreteness,and small relative error in measurements.These same principles apply to individuation of unique objects in general.
文摘The generation of a DNA profile from skeletal remains is an important part of the identifica-tion process in both mass disaster and unidentified person cases. Since bones and teeth are often the only biological materials remaining after exposure to environmental conditions, intense heat, certain traumatic events and in cases where a significant amount of time has passed since the death of the individual, the ability to purify large quantities of informative DNA from these hard tissues would be beneficial. Since sampling the hard tissues for gen-etic analysis is a destructive process, it is important to understand those environmental and intrinsic factors that contribute to DNA preservation. This will serve as a brief introduction to these topics, since skeletal sampling strategies and molecular taphonomy have been dis-cussed in depth elsewhere. Additionally advances in skeletal DNA extraction and analysis will be discussed. Currently there is great variation in the DNA isolation methods used by laboratories to purify DNA from the hard tissues;however, a standardized set of short tan-dem repeat (STR) loci is analyzed by many US laboratories to allow for comparisons across samples and jurisdictions. Recent advances have allowed for the generation of DNA profiles from smaller quantities of template DNA and have expanded the number of loci analyzed for greater discriminatory power and predictions regarding the geographic ancestry and phenotype of the individual. Finally, utilizing databases and expanding the number of com-parison samples will be discussed in light of their role in the identification process.
文摘The probative value of animal forensic genetic evidence relies on laboratory accuracy and reliability.Inter-laboratory comparisons allow laboratories to evaluate their performance on specific tests and analyses and to continue to monitor their output.The International Society for Animal Genetics(ISAG)administered animal forensic comparison tests(AFCTs)in 2016 and 2018 to assess the limitations and capabilities of laboratories offering forensic identification,parentage and species determination services.The AFCTs revealed that analyses of low DNA template concentrations(≤300 pg/μL)constitute a significant challenge that has prevented many laboratories from reporting correct identification and parentage results.Moreover,a lack of familiarity with species testing protocols,interpretation guidelines and representative databases prevented over a quarter of the participating laboratories from submitting correct species determination results.Several laboratories showed improvement in their genotyping accuracy over time.However,the use of forensically validated standards,such as a standard forensic short tandem repeat(STR)kit,preferably with an allelic ladder,and stricter guidelines for STR typing,may have prevented some common issues from occurring,such as genotyping inaccuracies,missing data,elevated stutter products and loading errors.The AFCTs underscore the importance of conducting routine forensic comparison tests to allow laboratories to compare results from each other.Laboratories should keep improving their scientific and technical capabilities and continuously evaluate their personnel’s proficiency in critical techniques such as low copy number(LCN)analysis and species testing.Although this is the first time that the ISAG has conducted comparison tests for forensic testing,findings from these AFCTs may serve as the foundation for continuous improvements of the overall quality of animal forensic genetic testing.
基金This study was approved by the Institutional Review Board(IRB)of Seoul National University Dental Hospital with a waiver for informed consent(ERI20032).
文摘Disaster victim identification issues are especially critical and urgent after a large-scale disaster.The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on dental panoramic radiographs(DPRs)using deep learning to promote its applicability as human identifiers.A total of 1638 DPRs,of which the chronological age ranged from 20 to 49 years old,were collected from January 2000 to November 2020.This dataset consisted of natural teeth,prostheses,teeth with root canal treatment,and implants.The detection of natural teeth and dental treatment patterns including the identification of teeth number was done with a pre-trained object detection network which was a convolutional neural network modified by EfficientDet-D3.The objective metrics for the average precision were 99.1%for natural teeth,80.6%for prostheses,81.2%for treated root canals,and 96.8%for implants,respectively.The values for the average recall were 99.6%,84.3%,89.2%,and 98.1%,in the same order,respectively.This study showed outstanding performance of convolutional neural network using dental panoramic radiographs in automatically identifying teeth number and detecting natural teeth,prostheses,treated root canals,and implants.
基金The study was supported by an overseas research grant to Muhammad Adnan Shan from the University of the Punjab,Pakistan[grant number D-1829-Est-I/2017].
文摘We investigated the forensic efficacy of the 30 insertion/deletion(Indel)markers included in the Qiagen Investigator■DIPplex kit in 529 Pakistani individuals from five major subpopulations in Pakistan(Punjabi,Pashtun,Sindhi,Saraiki,and Baloch).In the Sindhi population,the distribution of HLD81 and HLD97 alleles deviated from Hardy-Weinberg equilibrium after Bonferroni correction.The combined match probability ranged from 2.0E-12(Pashtun and Baloch)to 1.0E-12(Sindhi),and the mean paternity exclusion power varied from 0.995(Punjabi,Sindhi,and Saraiki)to 0.996(Pashtun and Baloch).The high combined power of discrimination(0.99999999999997)and low combined match probability(1.7E-12)for all subpopulations studied support the utility of the 30 Indel markers for forensic identification in the studied subpopulations.The allele frequencies of the Indel markers in the Pakistani subpopulations were compared with those from 18 other populations.The results show that the populations clustered according to geography.The subpopulations investigated in this work showed a close genetic relationship with others from Pakistan,as well as with South Central Asian and Middle Eastern populations.The results suggest that the Investigator■DIPplex kit can be useful as a supplementary tool for human identification in the five Pakistani subpopulations investigated in this study.
基金funded by the Netherlands Forensic Institute Den Haag,Netherlands.
文摘In this paper,camera recognition with the use of deep learning technique is introduced.To identify the various cameras,their characteristic photo-response non-uniformity(PRNU)noise pattern was extracted.In forensic science,it is important,especially for child pornography cases,to link a photo or a set of photos to a specific camera.Deep learning is a sub-field of machine learning which trains the computer as a human brain to recognize similarities and differences by scanning it,in order to identify an object.The innovation of this research is the use of PRNU noise patterns and a deep learning technique in order to achieve camera identification.In this paper,AlexNet was modified producing an improved training procedure with high maximum accuracy of 80%–90%.DIGITS showed to have identified correctly six cameras out of 10 with a success rate higher than 75%in the database.However,many of the cameras were falsely identified indicating a fault occurring during the procedure.A possible explanation for this is that the PRNU signal is based on the quality of the sensor and the artefacts introduced during the production process of the camera.Some manufacturers may use the same or similar imaging sensors,which could result in similar PRNU noise patterns.In an attempt to form a database which contained different cameras of the same model as different categories,the accuracy rate was low.This provided further proof of the limitations of this technique,since PRNU is stochastic in nature and should be able to distinguish between different cameras from the same brand.Therefore,this study showed that current convolutional neural networks(CNNs)cannot achieve individualization with PRNU patterns.Nevertheless,the paper provided material for further research.
