A review study on forensic optometry: new insights in forensic science to solve crime scenes, domestic violence and sexual assaults.

Forensic science has made a lot of progress in the medical field, but still ocular signs are not so well known to forensic scientists, whereas ocular signs play a very important role in forensic science. The major goal of this study to describe the importance of eye related clues in forensic science to solve the crime scenes and know the actual cause of death for the conviction of the criminals and save an innocent persons. Narrative review was done to review the articles available on the PubMed, Google Scholar, Research Gate, Web of Science and Medline related to the forensic optometry about the various methods of identification and strategies to deal with the forensic cases. The review covered studies that focused on interventions for forensic optometry and eye-related clues to the current study target. Twenty-seven of the 54 studies that met the inclusion criteria yielded good results, and all examined the significance of eye-related clues in forensic optometry. Peer reviewed articles/studies were referred to ascertain the eye related clues in the forensic science. Some authors suggest that eye related clues are very important aspects towards the forensic science and done the clinical research on that aspects. Criminal cases, domestic abuse and sexual assault affect people of all socioeconomic backgrounds. As a result, these traits would be highly valuable in determining the way of death and the chronological history of events leading up to a crime.

Raman Spectroscopy for the Time since Deposition Estimation of a Menstrual Bloodstain.

Forensic chemistry plays a crucial role in aiding law enforcement investigations by applying analytical techniques for the analysis of evidence. While bloodstains are frequently encountered at crime scenes, distinguishing between peripheral and menstrual bloodstains presents a challenge. This is due to their similar appearance post-drying. Raman spectroscopy has emerged as a promising technique capable of discriminating between the two types of bloodstains, offering invaluable probative information. Moreover, estimating the time since deposition (TSD) of bloodstains aids in crime scene reconstruction and prioritizing what evidence to collect. Despite extensive research focusing on TSD estimations, primarily in peripheral bloodstains, a crucial gap exists in determining the TSD of menstrual bloodstains. This study demonstrates how Raman spectroscopy effectively analyzes biological samples like menstrual blood, showing similar aging patterns to those of peripheral blood and provides proof-of-concept models for determining the TSD of menstrual blood. While this work shows promising results for creating a universal model for bloodstain age determination, further testing with more donors needs to be conducted before the implementation of this method into forensic practice.

A robust self-supervised image hashing method for content identification with forensic detection of content-preserving manipulations.

Image content identification systems have many applications in industry and academia. In particular, a hash-based content identification system uses a robust image hashing function that computes a short binary identifier summarizing the perceptual content in a picture and is invariant against a set of expected manipulations while being capable of differentiating between different pictures. A common approach to designing these algorithms is crafting a processing pipeline by hand. Unfortunately, once the context changes, the researcher may need to define a new function to adapt. A deep hashing approach exploits the feature learning capabilities in deep networks to generate a feature vector that summarizes the perceptual content in the image, achieving outstanding performance for the image retrieval task, which requires measuring semantic and perceptual similarity between items. However, its application to robust content identification systems is an open area of opportunity. Also, image hashing functions are valuable tools for image authentication. However, to our knowledge, its application to content-preserving manipulation detection for image forensics tasks is still an open research area. In this work, we propose a deep hashing method exploiting the metric learning capabilities in contrastive self-supervised learning with a new modular loss function for robust image hashing. Moreover, we propose a novel approach for content-preserving manipulation detection for image forensics through a sensitivity component in our loss function. We validate our method through extensive experimentation in different data sets and configurations, validating the generalization properties in our work.

Signs of how the Sydney Declaration article is received in the forensic science literature.

The Sydney Declaration is an initiative led by an informal group of forensic scientists with diverse backgrounds. It offers a vision of forensic science based on the trace, as a vestige of a past event related to security or a possible law violation. An article published in Forensic Science International (FSI) introduces to this view [1]. Our investigation delves into how the forensic science literature has received this article (the SD article), nearly two years after its publication. One of the main challenges of this exploratory study was to define the appropriate scope of forensic scientific literature, within which the SD article must be located. In general, the publishing domain is quickly evolving, with many competing players, while still being structured around standard academic disciplines. The forensic literature, meanwhile, is scattered and poorly connected. This reflects the fragmentation of practice and research in forensic science, and the difficulty of situating a scientific activity in such a way as to bring out its forensic substance. Nonetheless, the SD article fills a gap. By deciphering the critical concept of trace, it highlights how pivotal forensic science is in addressing societal challenges. Scholarly literature expresses clear quantitative interest in the SD article. It has received significant qualitative citations on multiple levels and dimensions, in a highly relevant manner and in accordance with its aim of providing a forensic foundation for various debates that have been conducted separately, notably over the last fifteen years.

Crystal clear connections - database matching unknown glass fragments to reference glass from ATM explosions.

This paper introduces the concept of an operational reference glass database, specifically designed for broken glass fragments from ATM attacks, jewelry store robberies, and ramraids on high-end clothing stores. The database, initiated in 2014, is used to compare glass traces from organized crews involved said criminal activities. Utilizing LA-ICPMS, this study establishes a methodology for collecting reference glass samples from the scenes of the aforementioned crimes, thus creating a comprehensive database containing over 3500 reference glass samples from crime scenes. The operational database is employed to match trace elemental profiles of glass fragments from suspected items to known reference samples, offering specificity and accuracy. Analysis of results, while ongoing due to the nature of active cases, find matches of trace materials in over 50 % of case requests since 2019. Challenges such as database scalability and continuous updating are acknowledged, and future directions include technological advancements to enhance precision and the application into other areas of forensic material analysis. The paper emphasizes the efficacy of this specialized approach in chemical profiling, providing a potent tool for linking glass traces to specific criminal contexts and providing intelligence and investigative leads into individuals involved in ATM-related crimes.

Speaker identification in courtroom contexts - Part III: Groups of collaborating listeners compared to forensic voice comparison based on automatic-speaker-recognition technology.

Expert testimony is only admissible in common-law systems if it will potentially assist the trier of fact. In order for a forensic-voice-comparison expert's testimony to assist a trier of fact, the expert's forensic voice comparison should be more accurate than the trier of fact's speaker identification. "Speaker identification in courtroom contexts - Part I" addressed the question of whether speaker identification by an individual lay listener (such as a judge) would be more or less accurate than the output of a forensic-voice-comparison system that is based on state-of-the-art automatic-speaker-recognition technology. The present paper addresses the question of whether speaker identification by a group of collaborating lay listeners (such as a jury) would be more or less accurate than the output of such a forensic-voice-comparison system. As members of collaborating groups, participants listen to pairs of recordings reflecting the conditions of the questioned- and known-speaker recordings in an actual case, confer, and make a probabilistic consensus judgement on each pair of recordings. The present paper also compares group-consensus responses with "wisdom of the crowd" which uses the average of the responses from multiple independent individual listeners.

A call for open science in forensics.

The modern canon of open science consists of five "schools of thought" that justify unfettered access to the fruits of scientific research: i) public engagement, ii) democratic right of access, iii) efficiency of knowledge gain, iv) shared technology, and v) better assessment of impact. Here, we introduce a sixth school: due process. Due process under the law includes a right to "discovery" by a defendant of potentially exculpatory evidence held by the prosecution. When such evidence is scientific, due process becomes a Constitutional mandate for open science. To illustrate the significance of this new school, we present a case study from forensics, which centers on a federally funded investigation that reports summary statistics indicating that identification decisions made by forensic firearms examiners are highly accurate. Because of growing concern about validity of forensic methods, the larger scientific community called for public release of the complete analyzable dataset for independent audit and verification. Those in possession of the data opposed release for three years while summary statistics were used by prosecutors to gain admissibility of evidence in criminal trials. Those statistics paint an incomplete picture and hint at flaws in experimental design and analysis. Under the circumstances, withholding the underlying data in a criminal proceeding violates due process. Following the successful open-science model of drug validity testing through "clinical trials," which place strict requirements on experimental design and timing of data release, we argue for registered and open "forensic trials" to ensure transparency and accountability.

Forensic measurement comparison of foot insole impressions.

In forensic podiatry, footprints have been shown to provide a valuable source of discriminatory information. Footprints may be found in various forms, such as bare footprints, sock-clad footprints, or as impressions on insoles within footwear. This study utilized quantitative measures of foot impressions on pairs of insoles from shoes worn by the same person from a population of 31 adults. The measurements were determined by using the Reel method and comprised measurements from the heel to the tips of the toes and width of the ball. The purpose of the study was to assess the margin of error for these measurements to determine whether they were sufficiently accurate for forensic use. A secondary purpose of this study was to determine whether the analyst's experience or lack thereof in forensic podiatry had an impact on the precision of measurement data. The insole foot impressions were assessed by two podiatrists with forensic podiatry experience in footprint analysis, footprint research, and in using the Reel method of footprint measurement, as well as by three students of podiatric medicine without any such experience. A statistical analysis of the data from the study was performed using SPSS v28 (IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp). The most reliable measurements were of forefoot width, heel to first toe, heel to second toe, and heel to fourth toe. The greatest variation occurred in the measurements of the heel to the third and fifth toes. The measurements of the forensic podiatrist analysts showed less variability than those of the podiatry students, suggesting that measurement precision is related to the experience of the analyst.

Martian microbes research and lessons learnt for forensic science.

A new method for looking for life outside the Earth is used as an example to demonstrate how ways of presenting complex scientific concepts to the general public, used in planetary science, could be used in forensic science. The work led to a pared down, practical definition of detectable Life for planetary exploration, An organised system capable of processing energy sources to its advantage. For nearly three quarters of Earth's history the only lifeforms were microbes, which are the target for looking for extraterrestrial life. Microbes are microscopic and may be sparsely distributed, but their metabolic products can form large, durable rocks, much easier to find and which may contain the organisms or their remains. There are similar challenges in presenting astrobiological and forensic science. Both may have to deal with very large or very small numbers which are not immediately comprehensible but can be understood by analogy. To increase the impact on the listener or reader, dramatic analogues are valuable, for example, referring to the mineralised microbial metabolic products as, "fossilised breath of bacteria" demands the audience's attention and engages them before more detailed explanations are given. The power of practical experiments or demonstrations is most important to reinforce what might otherwise be a fairly abstract concept. Surprisingly, most of these approaches can be made to work equally well in both spoken and written forms as well as in both sciences.

Enhancing the student learning experience through memes.

Meme-making is an effective method for engaging students and enhancing the learning environment. Memes are a social media cultural phenomenon that the majority of those in Higher Education are exposed to on an almost daily occurrence. This research examined the use of meme-making within the forensic sciences to allow students to reflect on their knowledge. Students studying modules in forensic science across six universities in the UK and USA participated in the study. At the end of a teaching session, students produced a meme (using Meme Generator) to reflect on what they had learned; memes were then shared with the class anonymously via Padlet. This allowed all class members to see and engage with the memes created. At the end of the activity students were anonymously surveyed on their experience using Microsoft Forms and analysis of the results were undertaken using SPSS software. Meme-making was found to be an inclusive learning activity with no limitations, including age (part-time, distance learning and visually impaired students were not part of the study parameters). Results showed that not only did students find the practice fun, but it also helped with the retention of the class content suggesting that the meme-making process is an effective way to enhance the learning environment while engaging students. Student feedback suggests that to maximise participation the educator should stress reflection and learning as the key purpose of generating a meme, rather than being witty or entertaining. The forensic science educator should be mindful of selecting appropriate subject matter for this often-humorous activity.

Application of augmented reality for crime scene investigation training and education.

The role of the crime scene investigator is complex, and investigators need to be able to conduct multiple frequently performed tasks. Appropriate training and education are critical to impart the crime scene investigator with the necessary capabilities. For a range of reasons, including the COVID-19 pandemic and the need for multi-disciplinary capabilities, training and education requirements have evolved in recent times to be more flexible and accessible. The skills of a crime scene investigator can be broadly categorised into two types of fundamental skills: decision-making and psychomotor skills. Both these skills need to be taught and assessed within training and education programs. The most common approach to impart these skills is by incorporating a crime scene simulation facility; however, not everyone has access to these facilities. Furthermore, crime scene staff often undertake refresher courses and are required to complete proficiency assessments. Conducting these activities in a dedicated crime scene simulation facility is time consuming and costly. Virtual tools have been developed in recent years to address this, but these tools only assess decision-making skills and not psychomotor skills. This paper argues that the implementation of augmented reality (AR) technology should be considered in crime scene investigator training and university education, because it can provide significant advantages when paired with conventional methods of training and education. When appropriately managed, AR can provide an avenue of training where both decision-making and psychomotor skills can be addressed simultaneously, while providing a more flexible and accessible approach. The implementation of AR has the potential to significantly improve the standards of teaching, resulting in better equipped crime scene investigators. The paper will explore how AR has the potential to improve accessibility of training, increase safety, enhance the student experience, enhance collaboration and feedback through connectivity and potentially reduce cost. This paper will also provide an insight into what would need to be considered before implementing AR technology into crime scene investigation training and education alongside current approaches. It is argued that the inclusion of AR into the current training and education arsenal provides significant benefits that are worthy of exploration.

Species discrimination from hair using ATR-FTIR spectroscopy: Application in wildlife forensics.

Hair is a commonly encountered trace evidence in wildlife crimes involving mammals and can be used for species identification which is essential for subsequent judicial proceedings. This proof of concept study aims, to distinguish the black guard hair of three wild cat species belonging to the genus Panthera i.e. Royal Bengal Tiger (Panthera tigris tigris), Indian Leopard (Panthera pardus fusca), and Snow Leopard (Panthera uncia) using a rapid and non-destructive ATR-FTIR spectroscopic technique in combination with chemometrics. A training dataset including 72 black guard hair samples of three species (24 samples from each species) was used to construct chemometric models. A PLS2-DA model successfully classified these three species into distinct classes with R-Square values of 0.9985 (calibration) and 0.8989 (validation). VIP score was also computed, and a new PLS2DA-V model was constructed using variables with a VIP score ≥ 1. External validation was performed using a validation dataset including 18 black guard hair samples (6 samples per species) to validate the constructed PLS2-DA model. It was observed that PLS2-DA model provides greater accuracy and precision compared to the PLS2DA-V model during cross-validation and external validation. The developed PLS2-DA model was also successful in differentiating human and non-human hair with R-Square values of 0.99 and 0.91 for calibration and validation, respectively. Apart from this, a blind test was also carried out using 10 unknown hair samples which were correctly classified into their respective classes providing 100 % accuracy. This study highlights the advantages of ATR-FTIR spectroscopy associated with PLS-DA for differentiation and identification of the Royal Bengal Tiger, Indian Leopard, and Snow Leopard hairs in a rapid, accurate, eco-friendly, and non-destructive way.

The importance of assessing the ghosting phenomenon in dynamic footprints when estimating stature - Forensic implications.

In cases where multiple footprints are found at a crime scene, it is unusual that all are static, and some are likely dynamic. Depending on how the footprint was made, we distinguish between dynamic and static footprints. A distinguishing feature that has only recently been associated with dynamic footprints is the fact that dynamic footprints differ from static footprints by the presence of additional markings around the back of the heel and the tops of the toe prints, the so-called ghosting phenomenon. The present study aims to analyse the ghosting phenomenon on dynamic footprints - its occurrence in relation to sex, laterality, and different areas of footprints as well as length features. Additionally, it aims to investigate the assessment of the ghosting phenomenon on dynamic footprints when estimating stature for biological profiling in the forensic field. The study sample comprised of 170 young adults aged 18 - 30 years of both biological sexes. Stature was measured and dynamic footprints were obtained where the ghosting phenomenon was analysed together with length measurements of the same footprint with and without ghosting. In the first and second toes of footprints, the ghosting phenomenon occurred most frequently in both sexes and in the sex-mixed group. Sex differences were not significant in ghosting occurrence on right and left footprints (p > 0.05), except for the area of the left fifth toe (p = 0.045). All the footprints' lengths with ghosting were significantly higher (p < 0.001) than those without ghosting. Statures calculated from footprint length measurements with ghosting predicted stature more accurately than statures calculated from the same footprint length measurements without ghosting. In the case of finding dynamic footprints at crime scenes, it is necessary to correctly identify and evaluate ghosting of the footprint. This comparison can be helpful in interpreting how ghosting should be taken into account when estimating a person's stature.

3D scanning a crime scene to enhance juror understanding of Bloodstain Pattern Analysis evidence.

There are numerous crime scene investigation applications of 3D scanning that have been previously documented. This paper documents the application of a 3D point cloud in the presentation of Bloodstain Pattern Analysis evidence to mock jurors. 150 mock jurors viewed a presentation of Bloodstain Pattern Analysis evidence from a murder trial in the UK. After viewing the evidence, the participants were tested on their knowledge of the evidence and repeated the test again 2 weeks later; to simulate criminal trial conditions; whereby there is a time lapse between the initial viewing of evidential material and deliberation. This paper found that the mock jurors who additionally viewed a 3D flythrough of a point cloud of the crime scene, better retained knowledge of the evidence over time, reported a greater ability to visualise the crime scene and had higher levels of interest in the evidence. Crucially, the 3D flythrough group did not report different levels of confidence in the accuracy of their memories of the evidence, nor different levels of emotional arousal to the group that viewed the evidence without the 3D presentation. Together, these findings suggest that 3D scanning of crime scenes, and the resultant point cloud's presentation to jurors, could add further value to the justice system when spatial information, such as Bloodstain Pattern Analysis evidence, is presented.

The Journey of the Asian Forensic Sciences Network (AFSN) through Fifteen Years.

The Asian Forensic Sciences Network was formed in 2008 by a small group of six forensic institutes from six countries in Asia, with the vision to create a common platform for scientists in the region to come together to advance forensic science, raise quality standards, and foster collaboration. Since its inception, the network has experienced remarkable growth, now comprising 70 member institutes from 18 countries across Asia. An Annual Meeting & Symposium, hosted by a member institute each year, serves as a cornerstone event for the network. In addition, the network runs nine technical workgroups covering areas in Crime Scene Investigation, Digital Forensics, DNA, Fingerprint, Forensic Medicine, Illicit Drugs, Questioned Document, Toxicology, and Trace Evidence, alongside a dedicated Quality Assurance and Standards Committee. These workgroups and committee work in tandem with the AFSN Board to formulate strategies aligned with the network's core objectives. This paper chronicles AFSN's journey over the past fifteen years, highlighting the pivotal role of the Board and the Workgroups, as well as the dedicated passion and unwavering commitment of the members in shaping the network through numerous activities.

The effect of following best practice reporting recommendations on legal and community evaluations of forensic examiners reports.

Commentators have recommended that forensic scientists' reports contain various disclosures to facilitate comprehension. However, little research has explored whether following best practice recommendations for disclosure impacts on receivers' impressions of the evidence. We examined whether forensic science reports that are more compliant with these best practice recommendations reduced overvaluing of the evidence and sensitized legal and community decision-makers to evidence quality. Across three experiments, 240 legal practitioners/trainees and 566 community decision-makers were presented with a fingerprint or footwear report that was either compliant or non-compliant with best practice recommendations. Participants were then asked to make evaluations and decisions based on the report. We found mixed effects of report compliance. Report compliance affected community participant's evaluations of the persuasiveness of the evidence but had limited impact on the judgments of legal practitioners/trainees. When presented with compliant reports, we found that community participants regarded unknown reliability evidence as less reliable and less persuasive than high reliability evidence, suggesting disclosures helped reduce overvaluing of the evidence and create sensitivity to differences in evidence quality. These results suggest compliance with reporting recommendations does affect community impressions, while only minimally influencing legal impressions of forensic science evidence. The costs and/or benefits of this outcome require further examination.

Uncovering Forensic Evidence: A Path to Age Estimation through DNA Methylation.

Age estimation is a critical aspect of reconstructing a biological profile in forensic sciences. Diverse biochemical processes have been studied in their correlation with age, and the results have driven DNA methylation to the forefront as a promising biomarker. DNA methylation, an epigenetic modification, has been extensively studied in recent years for developing age estimation models in criminalistics and forensic anthropology. Epigenetic clocks, which analyze DNA sites undergoing hypermethylation or hypomethylation as individuals age, have paved the way for improved prediction models. A wide range of biomarkers and methods for DNA methylation analysis have been proposed, achieving different accuracies across samples and cell types. This review extensively explores literature from the past 5 years, showing scientific efforts toward the ultimate goal: applying age prediction models to assist in human identification.

On the advantages of using AI-generated images of filler faces for creating fair lineups.

Recent advances in artificial intelligence (AI) enable the generation of realistic facial images that can be used in police lineups. The use of AI image generation offers pragmatic advantages in that it allows practitioners to generate filler images directly from the description of the culprit using text-to-image generation, avoids the violation of identity rights of natural persons who are not suspects and eliminates the constraints of being bound to a database with a limited set of photographs. However, the risk exists that using AI-generated filler images provokes more biased selection of the suspect if eyewitnesses are able to distinguish AI-generated filler images from the photograph of the suspect's face. Using a model-based analysis, we compared biased suspect selection directly between lineups with AI-generated filler images and lineups with database-derived filler photographs. The results show that the lineups with AI-generated filler images were perfectly fair and, in fact, led to less biased suspect selection than the lineups with database-derived filler photographs used in previous experiments. These results are encouraging with regard to the potential of AI image generation for constructing fair lineups which should inspire more systematic research on the feasibility of adopting AI technology in forensic settings.