Forensic Research Articles

I-vector and variability compensation techniques for mobile phone recognition

Mobile phone recognition consists of trying to identify the mobile phone brand or model, which is very important in forensic analysis. In this paper, we exploit the audio recordings to realize this task. Audio data conveys many information, one of them is related to the source of records, i.e., is a specific audio was captured by a given mobile phone. In order to separate between this particular information and the rest of audio content, we introduce the I-vector technique. Additionally, Linear Discriminant Analysis (LDA) and Within-Class Covariance Normalization (WCCN) methods were used in different ways to compensate the speaker and channel variability. We evaluate the performance of our proposed system by correct rate recognition based on Gaussian Probabilistic Linear Discriminant Analysis (GPLDA) and Cosine Similarity Score (CSS) methods. To train the mobile phone models and do tests, two datasets were prepared: the public MOBIPHONE database and a novel local database. Experiments done with different configurations demonstrate the effectiveness of I-vectors models with the combination of LDA – WCCN compensation techniques and CSS as a similarity measurement method. A correct recognition rates of 97.23 %, 98.91 %, and 99.45 % were obtained for MOBIPHONE, the local Same Environment (SE) and Different Environment (DE) databases, respectively.

Forensic Analysis of Adult Acute Poisoning in Makkah Region: A retrospective study

Forensic Analysis of Adult Acute Poisoning in Makkah Region: A retrospective study

Postmortem interval estimation of human skeletonized remains through luminol chemiluminescence.

Postmortem interval (PMI) estimation represents a significant challenge in the forensic sciences, particularly when dealing with human skeletal remains. A screening protocol for distinguishing possible remains of forensic interest is a crucial tool for judicial purposes. In this context, luminol chemiluminescence emerges as a promising method, with low overall costs and required time. This method is primarily used as a presumptive test, based on the understanding that the intensity of the chemiluminescence reactions decreases with an increase in the postmortem interval, thus underlining its practical implications.This research aims to expand previous research on the potential of luminol chemiluminescence, evaluating its usefulness in estimating PMI. Our sample comprised 239 human clavicles, with known PMI. The luminol solution was sprayed on each powder bone sample in a dark room, observed by the naked eye and photographed. The intensity of the chemiluminescence reaction was measured using a binary and a 5-level scale.The present results reveal that this method is a suitable tool for PMI estimation as a presumptive test, reducing time and costs in criminal investigations. The findings underscore the high sensitivity of luminol chemiluminescence for detecting recent PMI but also highlight a notable incidence of false positives. Thus, our results confirm luminol chemiluminescence as a powerful tool for dating time of death, particularly for identifying forensic relevant remains. Still, the relatively low specificity indicates that it should be complemented with additional tests for further confirmation and scientific validation of the remains' forensic relevance.

Organic fluorophores in developing latent fingerprints: an up-to-date review

AbstractFingerprints have been established as legitimate and critical forensic science evidence for identifying criminals beginning as early as the twentieth century. This article details the different types of fingerprints, the broad range of surfaces, and various development techniques available for on-site latent fingerprint collection, with fingerprint fidelity being of prime significance. Fluorescent imaging of latent finger-marks benefits from enhanced sensitivity, selectivity, and reduced reliance on instruments. The review focuses on the topical developments reported on small-molecule organic fluorophores which could be used to develop latent prints through powder, solution, and fuming approaches. These inexpensive luminophores extend wide emission profiles that span the visible spectrum to visualize the latent prints with exceptional resolution, free from any interference originating from the background surface. Further, the critical challenges and prospective scope for future research developments to improve the detection of latent fingerprints using small-molecule fluorophores are also discussed. Graphical abstract

Introduction to Nuclear Forensics Analysis Techniques

Abstract Nuclear forensics is the interdisciplinary branch of forensic science that deals with the analysis and examination of nuclear or other radioactive materials, or of evidence that is contaminated with radionuclides in the context of legal proceedings under international or national law related to nuclear security. To control and avoid the threat of terrorism posed by illicit trafficking and mismanagement, nuclear and other radioactive materials must be strictly regulated. Thus, the goal of nuclear forensic analysis is to discover what radioactive materials were confiscated, how, when, and where they were manufactured, and what their intended applications were. Nuclear forensic scientist has a wide array of analytical tools to use for detecting signatures in radioactive materials. These individual techniques can be sorted into three broad categories: bulk analysis tools, imaging tools, and microanalysis tools. Particular interest in nuclear forensics is particle morphology, isotopic composition of a material, presence of impurities, and microstructure. These properties can vary between materials of different origins due to varying processing or geological conditions, thus, allowing for discrimination of material history and prediction of provenance. This review article presents many key analytical techniques and discusses the main application and challenges of the most common techniques currently used in nuclear forensics analysis.

Forensic Diatom Analysis: Where Do We Stand and What Are the Latest Diagnostic Advances?

Background: diatoms are unicellular algae that have been used for more than a century for forensic purposes to diagnose drowning, with more or less success depending on the historical era. Although many years have passed, scientific research on diatoms has never ceased, which testifies to their enduring allure in forensics. Of course, diatom research has evolved and expanded over time, changing with the availability of new techniques and technologies. The volume of articles and their production over a period of many years has resulted in old, current, and new knowledge on diatoms being scattered over a large number of books and articles. Objectives: the purpose of this narrative literature review is, therefore, to summarize all this information and bring it together in a single work that can be useful for those who are studying diatoms and their usefulness for forensics for the first time, for those who are looking for proven methods of analysis, and finally for those who are interested in exploring new frontiers of research. Methods: a comprehensive literature search that included all studies dealing with the applications of diatoms in forensic science was performed in the most popular electronic databases. Results: traditional methods have been complemented by molecular and imaging methods and, more recently, by artificial intelligence. In addition, new biological substrates have been found for the analysis of diatoms. Conclusions: all this has led, on the one hand, to the consolidation of a whole body of knowledge on diatoms, on which this forensic analysis is still based, and, on the other hand, has opened up numerous new research directions.

Artificial intelligence powered OCR models for digitizing ayurveda manuscripts

This article presents a novel approach to transcribe Ayurveda manuscripts using Optical Character Recognition (OCR) technology enhanced with machine learning and forensic handwriting analysis techniques. Traditional transcription methods for these manuscripts are time-consuming and challenging due to diverse scripts and handwriting styles. The proposed methodology involves collecting manuscript samples from various sources and training OCR models to recognize the nuances of these scripts. By incorporating forensic handwriting principles, such as consistency and natural variation, the OCR models achieve greater accuracy. Additionally, the development of user-friendly interfaces allows scholars to train these models without needing technical expertise, streamlining the digitization process. Preliminary results show that this approach significantly improves transcription accuracy compared to conventional OCR software. This method offers a scalable solution for digitizing Ayurveda texts, preserving cultural heritage, and accelerating research in Ayurveda medicine. Future research will focus on refining OCR models and expanding their application to other scripts and languages.

Is it time for a unified forensic science taxonomy?

Prompted by disparate data highlighted in responses to a Sydney Declaration survey, this paper examines how forensic science ‘disciplines’ are defined and described by various professional organizations. A considerable degree of disagreement in taxonomic organization of forensic science ‘disciplines’ was uncovered. This paper suggests that the global forensic science community come together to develop and implement a standard taxonomic system for defining, describing and classifying the disciplines/subdisciplines within forensic science. Such uniform taxonomic structure could serve to align education and awareness while at the same time contributing to the goal of professionalization. This taxonomy should be built on a foundation based on underlying forensic science philosophies and principles, such as those delineated in the Sydney Declaration.

Evaluation of Four Forensic Investigative Genetic Genealogy Analysis Approaches with Decreased Numbers of SNPs and Increased Genotyping Errors

Background: Forensic investigative genetic genealogy (FIGG) has developed rapidly in recent years and is considered a novel tool for crime investigation. However, crime scene samples are often of low quality and quantity and are challenging to analyze. Deciding which approach should be used for kinship inference in forensic practice remains a troubling problem for investigators. Methods: In this study, we selected four popular approaches—KING, IBS, TRUFFLE, and GERMLINE—comprising one method of moment (MoM) estimator and three identical by descent (IBD) segment-based tools and compared their performance at varying numbers of SNPs and levels of genotyping errors using both simulated and real family data. We also explored the possibility of making robust kinship inferences for samples with ultra-high genotyping errors by integrating MoM and the IBD segment-based methods. Results: The results showed that decreasing the number of SNPs had little effect on kinship inference when no fewer than 164 K SNPs were used for all four approaches. However, as the number decreased further, decreased efficiency was observed for the three IBD segment-based methods. Genotyping errors also had a significant effect on kinship inference, especially when they exceeded 1%. In contrast, MoM was much more robust to genotyping errors. Furthermore, the combination of the MoM and the IBD segment-based methods showed a higher overall accuracy, indicating its potential to improve the tolerance to genotyping errors. Conclusions: In conclusion, this study shows that different approaches have unique characteristics and should be selected for different scenarios. More importantly, the integration of the MoM and the IBD segment-based methods can improve the robustness of kinship inference and has great potential for applications in forensic practice.

Role of Artificial Intelligence in Forensics

Artificial Intelligence (AI) is a critical domain within software engineering, focusing on computer processes capable of emulating human behaviors and cognitive processes such as learning, reasoning, adaptation and self –correction. Concurrently forensic science applies scientific methodologies to criminal investigations, specifically concentrating on analyzing evidence within criminal cases. The conventional methods of conducting autopsies and forming opinions exhibit numerous limitations, many of which can be effectively addressed through AI integration. Digital forensics stands out as one of the most rapidly advancing technologies, profoundly influencing the techniques and tools employed for analyzing, monitoring and visualizing crime scenes to mitigate emerging threats and cyber-attacks. Moreover, the realm encompasses forensic medicine, which applies medical expertise to administer justice in Legal proceedings, thereby resolving associate legal complexities. Leveraging the capabilities of AI enables the swift and through sorting of files without manual intervention, significantly expediting investigative processes. Furthermore,AI plays a pivotal role in the identification of mutilated bodies, facilitating the development of tools to reconstruct full facial features. AI generated images can provide remarkable resemblances, aiding in accurately depicting facial features to aid identification efforts. Integrating AI into forensic practices enhances efficiency, accuracy and overall effectiveness in resolving criminal cases

Profile of Homicidal Death Cases: One-Year Retrospective Study

Background: Homicide is regarded as a notorious crime against the society that causes intentional killing, aggravated assaults resulting in death. Nowadays, the incidence of homicide is increasing worldwide and it is a matter of great concern all over the world and it has significant consequence for both social and economic security of the people as well as national development. Objective: This study was aimed to describe the pattern homicidal behavior and the relationships among socio-demographic characteristics. Materials and Methods: A record-based retrospective cross-sectional study includes 180 cases of homicide out of the total of 1296 medico-legal autopsies conducted at Forensic Medicine Department of Dhaka Medical College during the year from July 2021 to June 2022. Results: A total number of 1296 medico-legal autopsies were conducted, of them 180(13.89%) cases were homicide and others (RTA, suicide, fall from height, poisoning, hanging, burn) were 1116(86.11%). Out of 180 homicidal death, most of them were 30-40 age group 66(36.67%), 144 cases were male (80 %) and 36 were female (20 %) whereas considering religion, the majority were Muslim 156 in number (86.67%) and the rest were of other religion. Among the homicidal death married were 150 (83.33%), in case of occupation most of them were Jobholder 39 (21.67%). According to the method of homicide, stab wound was the favorite homicide method used over victims 60(33.33%), 36(20%) cases were chop, 30(16.67%) cases were gunshot & strangulation and 24(13.33%) cases were others causes. Regarding place of residence of most of them were from Shahbag thana 108(60%). Conclusion: Stab wound was the favorite homicide method in Bangladesh and the most common age of the victims were 30-40 age group. The usefulness of the data in the scientific community is the database of homicide that should be advantageous for pathologists and forensic scientists work and particularly to be a guideline for homicide investigations in Bangladesh. KYAMC Journal Volume: 15, No: 01, April 2024: 25-28.

Developmental and validation of a novel small and high-efficient panel of microhaplotypes for forensic genetics by the next generation sequencing

BackgroundIn the domain of forensic science, the application of kinship identification and mixture deconvolution techniques are of critical importance, providing robust scientific evidence for the resolution of complex cases. Microhaplotypes, as the emerging class of genetic markers, have been widely studied in forensics due to their high polymorphisms and excellent stability.Results and discussionIn this research, a novel and high-efficient panel integrating 33 microhaplotype loci along with a sex-determining locus was developed by the next generation sequencing technology. In addition, we also assessed its forensic utility and delved into its capacity for kinship analysis and mixture deconvolution. The average effective number of alleles (Ae) of the 33 microhaplotype loci in the Guizhou Han population was 6.06, and the Ae values of 30 loci were greater than 5. The cumulative power of discrimination and cumulative power of exclusion values of the novel panel in the Guizhou Han population were 1-5.6 × 10− 43 and 1-1.6 × 10− 15, respectively. In the simulated kinship analysis, the panel could effectively distinguish between parent-child, full-sibling, half-sibling, grandfather-grandson, aunt-nephew and unrelated individuals, but uncertainty rates clearly increased when distinguishing between first cousins and unrelated individuals. For the mixtures, the novel panel had demonstrated excellent performance in estimating the number of contributors of mixtures with 1 to 5 contributors in combination with the machine learning methods.ConclusionsIn summary, we have developed a small and high-efficient panel for forensic genetics, which could provide novel insights into forensic complex kinships testing and mixture deconvolution.

Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) analysis of human nails: Implications for age determination in forensics.

A person's age estimation from biological evidence is a crucial aspect of forensic investigations, aiding in victim identification and criminal profiling. In this study, we present a novel approach of utilizing Attenuated Total Reflection Fourier Transform Infrared (ATR FT-IR) spectroscopy to predict the age of donors based on nail samples. A diverse dataset comprising nails from donors spanning different age groups was analyzed using ATR FT-IR, with subsequent multivariate analysis techniques used for age prediction. The developed partial least squares regression (PLS-R) model demonstrated promising accuracy in age estimation, with a root mean square error of prediction (RMSEP) equal to 11.1 during external validation. Additionally, a partial least squares discriminant analysis (PLS-DA) classification model achieved high accuracy of 88% in classifying donors into younger and older age groups during external validation. This proof-of-concept study highlights the potential of ATR FT-IR spectroscopy as a non-destructive and efficient tool for age estimation in forensic investigations, offering a new approach to forensic analysis with practical implications.

A Deep Feature Driven Expert System to Estimate the Postmortem Interval From Corneal Opacity Development

ABSTRACTPostmortem interval (PMI) estimation remains an unresolved challenge in forensic science, necessitating practical, reliable and more accurate tools. This study aimed to develop a quantitative PMI estimation tool that effectively meets these needs. Focusing on the postmortem opacity development of the eye as a key marker for determining time since death, we propose an artificial intelligence‐based clinical PMI prediction system utilising computer vision, deep learning and machine learning methods. The AlexNet algorithm was utilised to extract deep features from the postmortem eye images. Extracted features were then processed by machine learning algorithms. For feature selection, Lasso and Relief techniques were employed, while SVM and KNN were applied for classifications. The results were validated using the leave‐one‐subject‐out method. The system was tested across different postmortem ranges, providing multi‐label predictions. The performance was evaluated using various metrics. The deep features exhibited effective performance in grading postmortem opacity development, achieving state‐of‐the‐art results. The accuracy scores were 0.96 and 0.97 for 3‐h intervals (i.e., 5‐class) and 5‐h intervals (i.e., 3‐class) experiments, respectively. The experimental results indicate that the proposed system represents a promising tool for PMI estimation.

Recent applications of high-performance thin-layer chromatography (HPTLC) in forensic drug analysis

Recent applications of high-performance thin-layer chromatography (HPTLC) in forensic drug analysis

Forensic Science Research on the Web of Science Database Over 22 Years: A Bibliometric Analysis

Background: We reviewed the literature on forensic genetics from 1991 to 2022, emphasizing short tandem repeats. The objectives were to assess the caliber of research and draw attention to issues facing scientists and practitioners.Methods: Except for China, a metrological study was performed on forensic literature from 1991 to 2022 using the Web of Science (WoS).Results: The “journal of forensic sciences” had 380 papers that were the most read out of 2139 publications in the study. Also, “forensic science international: Genetics” had the most citations. Analysis with R software showed that 2001 was the peak publication year. “Journal of forensic sciences” and Budowle B were the most prolific. “Forensic science international: genetics” and Heller MJ received the most citations, and “forensic science”, “STRs”, and “DNA typing” were among the frequently used keywords.Conclusion: The study could help scientists understand the trends of short tandem repeats based on forensic science research by highlighting the top ten research institutions, funding prospects, authors, and high-citation journals to anticipate future research directions.

Exploring nanopore direct sequencing performance of forensic STRs, SNPs, InDels, and DNA methylation markers in a single assay

IntroductionThe field of forensic DNA analysis has undergone rapid advancements in recent decades. The integration of massively parallel sequencing (MPS) has notably expanded the forensic toolkit, moving beyond identity matching to predicting phenotypic traits and biogeographical ancestry. This shift is of particular significance in cases where conventional DNA profiling fails to identify a single suspect. Supplementing forensic analyses with estimated biological age may be valuable but involves a complex and time-consuming DNA methylation analysis. This study explores and validates the performance of a comprehensive forensic third-generation sequencing assay utilizing Oxford Nanopore Technologies (ONT) in an adaptive and direct sequencing approach. We incorporated the most widely used forensic markers, i.e., STRs, SNPs, InDels, mitochondrial DNA (mtDNA), and two methylation-based clock classifiers, thereby combining forensic genetic and epigenetic analysis in one single workflow. Methods and resultsIn our investigation, DNA from six anonymous individuals was sequenced using the ONT standard adaptive direct sequencing approach, reaching a mean percentage of on-target reads ranging from 6.6 % to 7.7 % per sample. ONT data was compared to standard MPS data and Illumina EPIC DNA methylation profiles. Basecalling employed recommended ONT software packages. TREAT was used for ONT-based analysis of autosomal and Y-chromosome STRs, achieving 90–92 % correct calls depending on allelic read depth thresholds. InDel analyses for two lower-quality samples proved challenging due to inadequate read depth, while the remaining four samples significantly contributed to the observed percentage markers (60.9 %) and correct calls (97.8 %). SNP analysis achieved a 98 % call rate, with only two mismatches and two missed alleles. ONT-generated DNA methylation data demonstrated Pearson’s correlation coefficients with EPIC data ranging from 0.67 to 0.97 for Horvath’s clock. Additional age-associated markers exhibited Pearson’s correlation coefficients with chronological age between 0.14 (ELOVL2) and 0.96 (FHL2) at read depths of <30 and <20, respectively. Despite excluding mtDNA from our targeted sequencing approach, adaptive proof-reading fragments covered the complete mtDNA with an average read depth of 21–72, showing 100 % concordance with reference data. DiscussionOur exploratory study using ONT adaptive sequencing for conventional forensic and age associated DNA methylation markers showed high sequencing accuracy for a significant number of markers, showcasing ONT as a promising (epi)genetic forensic method. Future studies must address three critical aspects: determining clear quantity and quality measures and detection thresholds for accuracy, optimizing input DNA quantity for forensic casework expectations, and addressing ethical considerations associated with phenotype and ancestry analysis to prevent ethnic biases.

What Should Be Typical about the Way We Calculate Typicality?

The probability of correct classification, and ultimately identification, lies at the heart of forensic anthropological analyses. To this end, practitioners rely on a variety of ways to assess the error or uncertainty of their estimates, including the use of statistically based analytical packages such as FORDISC. This article addresses typicality probabilities and specifically examines issues and assumptions with calculating F-statistic typicalities both statistically and within FORDISC. It uses multiple methods to calculate F-test typicality from publicly accessible craniometric data drawn from the Howells data set, a data set also included as reference groups within FORDISC. While the results of these calculations agree across various F-tests proposed by different authors, the results do not match the “TypF” values generated by FORDISC when using the “resubstitution” option. Through additional calculations and various reproducibility exercises, the authors demonstrate how and why “TypF” in FORDISC produces erroneous typicality values with the “resubstitution” option. They also identify the correct equation to incorporate into the software to rectify this problem. This work represents the logical conclusion of a long-running debate the authors had with Stephen D. Ousley and a desire to improve the accuracy and interpretability of analyses generated in FORDISC.

Genital findings in adult females: a forensic analysis of photographic records

BackgroundIn the investigation of sexual assault cases, a standard practice involves examining female genitalia to identify injuries. The majority of research was done to examine findings in the child age group, but very little research was done on the adult age group. There is a need for guidelines to follow for the interpretation of adult female findings as they hold the same significance as in children. The Dammam Forensic Medicine Center conducted a retrospective chart review study in the period from 2014 to 2021 to examine adult female genital findings utilizing photographic documentation.ResultsOne hundred sixty-three cases involving adults between the ages of 18 and 52 were examined. Cases were divided into two groups to focus on hymenal findings that fell in the class of no expert consensus. The first group included self-defined virgins, who denied having ever experienced vaginal penetration in their entire lives, including the reported incidence, which represented 38 cases. The rest of the cases had at least a single incident of vaginal penetration. The normal genitourinary findings were found comparable to those in the child age group. All of the participants who showed notches or clefts, below the 3 o’clock or 9 o’clock location, which extends nearly to the base of the hymen, but is not a complete transection belonged to the group with a history of vaginal penetration. The three participants who showed a notch or a cleft in the hymen rim at 3 o’clock or 9 o’clock which extends nearly to the base of the hymen, but is not a complete transection belonged to the same group.ConclusionsFindings that lack expert consensus in the child age group are likely the result of injury in the study participants. This result gives valuable information on genital findings in self-identified virgin adult females, which can be utilized in conjunction with other studies to establish standards for the assessment of cases of alleged sexual assault in adult females.

Environmentally friendly screen-printed electrodes for the selective detection of 4-bromo-2,5-dimethoxyphenethylamine (2C-B) in forensic analysis.

In response to the growing need for sustainable analytical methods, this study explores the repurposing of screen-printed electrodes (SPEs) that would otherwise be discarded. This involves recoating the working electrode surface with a graphite (Gr) and chitosan (CTS) dispersion, creating a reusable SPE (SPE-Gr/CTS). Demonstrating its utility, SPE-Gr/CTS was employed for the detection of 4-bromo-2,5-dimethoxyphenethylamine (2C-B), a phenylethylamine commonly used for recreational proposes. Identifying 2C-B in fluid oral and seized samples is of great interest for forensic and toxicological applications. The 2C-B detection using SPE-Gr/CTS was optimized in Britton-Robinson buffer solution (0.1 mol L-1) at pH 2.0, employing square-wave adsorptive stripping voltammetry. The electrochemical behavior of 2C-B on SPE-Gr/CTS exhibited one irreversible oxidation and a reversible redox process. The proposed method presented a dynamic linear range for 2C-B determination (0.05 to 7.5 μmol L-1) with a low LOD (0.015 μmol L-1). Moreover, the stability of 2C-B electrochemical responses on SPE-Gr/CTS was confirmed using the same or different electrodes (N = 3), with a relative standard deviation of less than 5.0%. Interference studies with seventeen other illicit drugs and adulterants demonstrated that the proposed method is selective for 2C-B detection even in the presence of these substances. Real seized and oral fluid samples containing 2C-B were analyzed using this method, and the results were confirmed by LC-MS. The proposed device demonstrates to be an environmentally friendly and selective sensor for 2C-B detection in forensic analysis, offering a rapid and straightforward screening method for seized and biological samples. In addition, a portable and sensitive determination of 2C-B in forensic samples is presented with minimal sample consumption (50 μL).