Journal of forensic sciences最新文献

{"title":"Using ATR-FTIR spectroscopy and machine learning for forensic hair identification","authors":"Zehua Fan PhD,&nbsp;Chenyu Li PhD,&nbsp;Qiran Sun PhD,&nbsp;Yiwen Luo PhD,&nbsp;Hancheng Lin PhD,&nbsp;Bin Cong PhD,&nbsp;Ping Huang PhD","doi":"10.1111/1556-4029.70062","DOIUrl":"10.1111/1556-4029.70062","url":null,"abstract":"<p>The purpose of this experiment is to utilize attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy for the discrimination of different types of hair, as numerous studies have substantiated its efficacy in substance classification. In this study, ATR-FTIR spectroscopy was employed to analyze scalp hair, pubic hair, and armpit hair from human subjects. Additionally, a machine learning model was integrated to differentiate between hairs originating from distinct body regions. Because of the limited sampling conditions, we only chose samples from Chinese people who have been living in Shanghai and the surrounding areas for a long time to conduct the experiment. We developed partial least squares discriminant analysis (PLS-DA), random forest (RF), and support vector machine (SVM) classification models and compared their performance in identification. The results show that the SVM model has the best identification results with 90.37% accuracy, 90.37% recall, and 90.38% precision. This preliminary study suggests that ATR-FTIR spectroscopy combined with SVM may be an effective and promising aid in assisting the identification of hair in different parts of the human body. This method is non-destructive, fast, and accurate, and does not require a sample preparation process, which makes it promising in the field of forensic science. Also, we found that the main substance differences that contributed to the good distinction between hairs were expressed in amide I, followed by amide III and C-H deformation.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1537-1543"},"PeriodicalIF":1.5,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144251611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Marabunta ants on post-mortem interval estimation in pigs: Insights from Okuku, Nigeria","authors":"Cletus Obun BSc, MSc, PhD,&nbsp;Darlington Nnamdi Onyejike BSc, MSc, MBA, PhD,&nbsp;Ugochukwu Godfrey Esomonu BSc, MSc, PhD,&nbsp;Ogugua Augustine Egwu BSc, MSc, PhD,&nbsp;Chiwendu Modesta Dimkpa BSc","doi":"10.1111/1556-4029.70067","DOIUrl":"10.1111/1556-4029.70067","url":null,"abstract":"<p>The rising homicide rates in Nigeria underscore the necessity for comprehensive post-mortem interval (PMI) estimations to enhance the reliability of forensic investigations. This study investigates the impact of Marabunta ants (Hymenoptera: Formicidae) on the decomposition process and PMI estimation in pig carcasses during the wet season in Okuku, Nigeria. Using two juvenile domestic pigs, we employed a controlled experimental approach at the Department of Anatomy and Forensic Anthropology Research Facility. The study spanned 30 days, with systematic observations of postmortem changes, insect activity and environmental conditions recorded at specified intervals. Results indicated pronounced effects of Marabunta ants on decomposition dynamics. Notably, the presence of these ants altered the expected insect succession patterns, delaying the colonisation by blowflies, which typically dominate the initial decay stages. By the second day, marked ant activity was observed, leading to distinct bite marks on the carcasses, while the other carcasses exhibited standard decomposition without any interference. Accumulated degree days (ADD) and total body scores (TBS) demonstrated a parabolic relationship, revealing rapid initial decay followed by a stabilisation phase as skeletonisation progressed. This research confirms that environmental conditions and insect activities significantly influence decomposition rates and PMI estimations. The findings suggest a need for forensic practitioners to recognise the role of Marabunta ants in decay processes and the potential misinterpretations of ant-induced marks as perimortem injuries. Future studies should explore seasonal variations in decomposition and insect succession to refine forensic entomological methodologies.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1603-1608"},"PeriodicalIF":1.5,"publicationDate":"2025-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144145263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimized detection and localization of copy-rotate-move forgeries using biogeography-based optimization algorithm","authors":"Deepak Joshi MTech,&nbsp;Abhishek Kashyap PhD,&nbsp;Parul Arora PhD","doi":"10.1111/1556-4029.70068","DOIUrl":"10.1111/1556-4029.70068","url":null,"abstract":"<p>In today's digital era, the proliferation of image processing tools has made image forgery detection a critical challenge. Malicious actors exploit these tools to manipulate images, spreading misinformation and misleading society. Existing tampering detection methods struggle with detecting complex transformations such as copy-rotate-move forgeries, often facing limitations in computational efficiency, robustness, and accuracy. Many approaches rely on traditional feature extraction techniques that fail under severe transformations or require extensive processing time. To address these shortcomings, we propose a novel and computationally efficient algorithm that integrates Radon Transform with Biogeography-Based Optimization (BBO) for enhanced copy-rotate-move forgery detection. Unlike conventional optimization techniques, BBO effectively enhances feature selection and matching, improving detection robustness against rotation and scale variations. The proposed algorithm has been rigorously evaluated on multiple benchmark datasets, demonstrating superior performance in terms of F1-score, recall, and accuracy compared to existing state-of-the-art methods. The results affirm that our approach significantly improves forgery localization while maintaining computational efficiency, making it a promising solution for real-world digital forensics applications.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1392-1413"},"PeriodicalIF":1.5,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144129836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crossbow impact effect on clothing and potential associated injuries","authors":"Richard Critchley PhD,&nbsp;Niall Patrick Hennessy MSc,&nbsp;James Read MSc,&nbsp;Rachael Hazael PhD","doi":"10.1111/1556-4029.70079","DOIUrl":"10.1111/1556-4029.70079","url":null,"abstract":"<p>There has been an increase in crossbow use for hunting practices, sport target shooting, and criminal activity. In the UK, there is minimal legislation surrounding the crossbow. UK law states individuals must be over 18 to buy or possess a crossbow. To date, little experimental research has been conducted, with most of the research focusing on injuries resulting from crossbow incidents. The aim of this study was to ascertain what effect crossbow bolts would have against ordinary clothing worn by the public and how or if different combinations of clothing would fare differently against the bolts and if that could be of use to the forensic examiner. An 80 lb. Armex tomcat II crossbow was used with three types of clothing used in four combinations, along with a non-clothed gelatine block. The results showed that all 10 bolts penetrated the non-clothed gelatine block, T-shirt, and polo shirt series, while nine bolts penetrated the hoodie/T-shirt combination and only three penetrated the hoodie/polo shirt combination. Significant differences were highlighted between the mean penetration depths of the non-clothed gelatine block and each clothing series, with the highest observed value being the thickest layer combination. Inspections of bolts and wound tracts revealed the presence of clothing fibers. The conclusions of this study demonstrated that this information can be utilized by forensic investigators and medical professionals as a source of trace evidence. Further research into crossbow effects on clothing would prove beneficial to increase the understanding of how the crossbow reacts with the environment.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1544-1557"},"PeriodicalIF":1.5,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1556-4029.70079","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An analysis of firearm legality and lethality in 625 U.S.-based mass murders involving firearms","authors":"Russell T. Rogers MA,&nbsp;Hannah Hesson BA,&nbsp;Sloan E. Bergstresser BS,&nbsp;Paul S. Appelbaum MD,&nbsp;Gary Brucato PhD,&nbsp;Ragy R. Girgis MD","doi":"10.1111/1556-4029.70078","DOIUrl":"10.1111/1556-4029.70078","url":null,"abstract":"<p>Understanding the relationship between firearm regulations and the lethality of mass murder involving firearms has implications for prevention efforts. We examined 625 incidents of mass murder involving firearms that occurred in the United States between 1900 and 2023. The stringency of regulatory practices was based on the 2010 rankings provided by the Giffords Law Center to Prevent Gun Violence. We identified a significant difference in fatalities when examining events in which firearms with only semi-/fully automatic, only non-automatic, or both firing methods were used (<i>p</i> = 0.019), primarily driven by high-fatality rates associated with events in which both types of weapons were used. In high-regulation states, there were significantly fewer events per capita (<i>M</i> = 0.070, SD = 0.044) relative to low-regulation states (<i>M</i> = 0.118, SD = 0.059, <i>p</i> = 0.002). Most events involved firearms that were exclusively acquired legally (64%). The legal status of firearms used in mass murders was significantly associated with fatalities. This was found to be driven primarily by fatalities associated with events in which all firearms were legally acquired being higher than those associated with events in which at least one firearm was illegally acquired. Per capita event and fatality rates of mass murder involving firearms were significantly higher after the Federal Assault Weapons Ban expired. These data support a relationship between firearm regulation and the incidence of mass murder involving firearms, perhaps implying that effective prevention can at least partially be a top-down process.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1424-1432"},"PeriodicalIF":1.5,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144096108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward a unified methodology for preliminary digital evidence assessment: Standardizing forensic investigations","authors":"Arwa Juma AlBusaidi PhD,&nbsp;Laiha Binti Mat Kiah PhD,&nbsp;Ainuddin Wahid Bin Abdul Waha PhD","doi":"10.1111/1556-4029.70070","DOIUrl":"10.1111/1556-4029.70070","url":null,"abstract":"<p>The increasing reliance on forensic investigations on digital evidence raises concerns about reliability, standardization, and misinterpretation. Inconsistent forensic evaluations necessitate a structured approach for examining digital evidence's strength impacting judicial outcomes. This study aimed to propose a systematic preliminary digital evidence assessment methodology by integrating Bayesian reasoning to enhance evaluative interpretations. A phase-phase structured framework is introduced to guide forensic practitioners in assessing digital evidence through observation, hypothesis generation, and inference. The methodology utilizes the Certainty Scale (C-Scale) to improve consistency among forensic assessments, standardizing evaluative opinions. Additionally, developing a proof-of-concept database for digital evidence cases of manipulation is essential to support evidence strength determination in investigations. The results showed that this approach advances transparency and limits cognitive bias in forensic evaluations. Aligned with international forensic regulatory frameworks and standards like ISI-21043, the methodology proposed enhances forensic decision-making, particularly for investigators who lack digital forensic expertise. The current study contributed to forensic sciences by presenting a standardized method for examining digital evidence strength, catering to the gap between theoretical evaluation models and practical applications in forensics. To enhance transparency and provide a balanced perspective on the evidential value of observed digital evidence, it is crucial to standardize the approach that digital forensic practitioners take in formulating and articulating their preliminary evaluative opinions.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1571-1583"},"PeriodicalIF":1.5,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Traumatic brain injury graphing: A case study of Charles Whitman","authors":"K. A. Strube BSAST","doi":"10.1111/1556-4029.70071","DOIUrl":"10.1111/1556-4029.70071","url":null,"abstract":"<p>Research has identified violent behavior (i.e., assault, murder, and suicide) as a possible sequela of moderate to severe traumatic brain injury (TBI) and repeated mild TBI (rmTBI). However, misconceptions about consciousness and its ability to control an injured brain, the diverse spectrum of potential outcomes, and the role genetics/environmental factors can play make proving TBI's influence on inciting violent behavior by a perpetrator extremely difficult. Though the cause and execution may be complex, multifaceted, and vary in each individual, violent behavior is often preceded and accompanied by other emotional, behavioral, cognitive, and/or physical consequences. This research examines the benefits of graphing, using data interpreted from in-depth, color-coded reverse chronology, as a visualization tool for analyzing/displaying the potential impacts of TBI injuries and aggravators on violent outcomes, especially in complex situations. The case of Charles J. Whitman (herein referred to as CW) was used to demonstrate this method. Results revealed that sequelae clusters appeared shortly after suspected TBI injuries, sequelae changed and progressed over time, and numerous TBI aggravators were present at the time of the tragedy, including: an extended period of excessively high ambient temperatures, sleep deprivation (SD), drug use, blood loss, and emotional stressors. TBI graphing (utilizing reverse chronology) served as a valuable tool for observing the potential TBI sequelae progression prior to the violent event.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1635-1644"},"PeriodicalIF":1.5,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/1556-4029.70071","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144082997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frame duplication forgery detection and localization based on QR decomposition and Minkowski distance","authors":"Khaled Loukhaoukha PhD","doi":"10.1111/1556-4029.70043","DOIUrl":"10.1111/1556-4029.70043","url":null,"abstract":"<p>The widespread use of multimedia editing tools has facilitated the creation of realistic video forgeries, jeopardizing the trust in video content. To address frame duplication forgery, a prevalent technique, this paper introduces a novel algorithm leveraging QR decomposition (orthogonal-triangular decomposition) and Minkowski distance. The algorithm extracts frame features using QR decomposition and compares them with a reference frame using Minkowski distance. Candidate duplicates are identified through random block matching. We evaluate the proposed method on standard datasets (TDTVD, LASIESTA, and IVY LAB) and a self-generated dataset. Our method achieves exceptional performance, attaining a perfect <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>F</mi>\u0000 <mn>1</mn>\u0000 </msub>\u0000 </mrow>\u0000 </semantics></math>-score for video-level detection on both the TDTVD and our self-generated datasets. Notably, for frame-level detection, it achieves an average accuracy of 0.9943, precision of 0.9752, recall of 0.9858, and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mi>F</mi>\u0000 <mn>1</mn>\u0000 </msub>\u0000 </mrow>\u0000 </semantics></math>-score of 0.9803 across all datasets. Our analysis demonstrates the proposed method demonstrates promising performance in detecting multiply-duplicated frames and shows robustness against post-processing, potentially outperforming existing approaches.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1359-1374"},"PeriodicalIF":1.5,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144061335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Letter to the Editor – Black-box studies do not reflect decisions and errors in casework","authors":"Itiel Dror PhD","doi":"10.1111/1556-4029.70077","DOIUrl":"10.1111/1556-4029.70077","url":null,"abstract":"","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":""},"PeriodicalIF":1.5,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144052579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring machine learning approaches for efficient image forgery detection","authors":"Abilash Radhakrishnan MEng,&nbsp;Tukaram Namdev Sawant ME,&nbsp;Cheepurupalli Raghuram MTech,&nbsp;Dani Jermisha Railis MEng,&nbsp;Harjasdeep Singh MTech","doi":"10.1111/1556-4029.70069","DOIUrl":"10.1111/1556-4029.70069","url":null,"abstract":"<p>In the digital age, accessible image manipulation raises concerns about authenticity, with forgery techniques threatening personal, journalistic, and security contexts. Detecting alterations is crucial for maintaining trust in visual content. A robust system capable of detecting various types of image forgeries, such as copy-move, splicing, and object removal, while minimizing false positives and negatives. Develop and implement robust feature extraction methods to identify key characteristics that differentiate forged images from authentic ones, focusing on both low-level and high-level features. The Two-dimensional maximum Shannon Entropy Median Filter (TSETMF) enhances image quality by reducing noise while preserving and enhancing details, which aids machine learning models in recognizing and identifying image forgeries. Multidimensional Spectral Hashing (MSH) enables efficient feature extraction by creating compact representations, thereby enhancing pattern recognition and boosting both speed and accuracy in detecting image forgeries within machine learning frameworks. Faster Region-Based Convolutional Neural Networks (FR-CNN) improve image forgery detection by swiftly identifying and localizing manipulated areas, enhancing feature extraction and accuracy for real-time forensic analysis. Machine learning approaches significantly enhance image forgery detection, with techniques like CNNs and MSH improving accuracy, processing speed, and robustness against diverse forgery methods, ensuring effective real-time analysis. The result shows that the proposed method significantly excelled, reaching an accuracy of 98.5%, alongside high precision (97.0%), recall (98.2%), and F1 score (98.1%), implemented using Python Colab. Future research can focus on developing more robust models, integrating unsupervised learning techniques, enhancing real-time detection capabilities, and exploring cross-domain applications to combat evolving image forgery methods effectively.</p>","PeriodicalId":15743,"journal":{"name":"Journal of forensic sciences","volume":"70 4","pages":"1375-1391"},"PeriodicalIF":1.5,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144035145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}