ForensicNet: Modern convolutional neural network-based image forgery detection network

The advancements in Image editing techniques produce realistic-looking artificial images with ease. These images can easily circumvent the forensic systems making the authentication process more tedious and difficult. To overcome this problem, we introduce a modern convolutional neural network (CNN) named ForensicNet, inspired by the recent developments in computer vision. The three major contributions of our CNNs are inverted bottleneck, separate downsampling layers, and using depth-wise convolutions for mixing information in the spatial dimension. The inverted bottlenecks help improve accuracy and reduce network parameters/FLOPs. The separate downsampling layers help converge the network. The normalization layers also help stabilize training whenever the spatial resolution is changed. The depth-wise convolution is a grouped convolution where the number of groups and channels are the same. The experiments show that ForensicNet outperforms the state-of-the-art methods by a large margin.     

An analysis of data curated from 5 years of identifying human remains

An archive of 5 years of cases involving the identification of human remains was curated, collecting information on: The sample type submitted, the number of STR loci yielding interpretable results, the kinship challenge posed, and the outcome for the case. A total of 129 cases of remains ID were investigated using manual DNA extraction and recovery methods with amplification of STR markers using the Power Plex 21 multiplex STR kit from Promega Corp. In 52 cases, blood spots collected by the ME were provided as sample and in 100% of those cases, probabilities of relatedness to the reference samples was ≥99%. In 77 cases, tissue other than blood was provided as a source of DNA. These other samples were grouped categorically into long bones (femur and tibia; 40 cases), skull bones/teeth (11 cases), other bones (16 cases), and tissue (normally adherent to bone) (10 cases). Reference samples provided for cases included alleged parents or child(ren) of the victim (86 cases), alleged full siblings of the victim (38 cases), or alleged second-order relatives (five cases). The overall success rate in confirming the identity of the source of the remains in these cases was 89.2%. Our results demonstrate that a laboratory can be often successful identifying human remains using methods easily implemented in any DNA typing laboratory.     

Environmental assessment of gunshot residue particles in the public domain of the United Kingdom

Only limited data currently exists on the inadvertent transfer of gunshot residue (GSR), or GSR-like particles through contact with public places. In this study, an assessment occurrence of GSR in public environments in England, UK was undertaken. Utilizing a stubbing sampling technique over 260 samples were collected from areas accessible to the public, including buses, trains, taxis, and train stations. Stub analysis was performed by Scanning Electron Microscopy with Energy Dispersive X-ray Analysis (SEM-EDX). The results showed no characteristic GSR particles were detected on any of the 262 samples taken. From these samples, a total of four indicative/consistent particles were identified on one train seat (2× BaAl, 2× PbSb). Although geographical location and firearm association is likely to influence GSR occurrence, the data suggests that the potential for inadvertent GSR transfer through contact with public transport and associated communal areas is insignificant. Further research assessing environmental background levels of GSR in additional geographical locations is critical in an evaluation of the potential for GSR transfer from the environment.     

Copycatting the smell of death: Deciphering the role of cadaveric scent components used by detection dogs to locate human remains

Human remains detection dogs (HRDD) are commonly used by law enforcement agencies to search for cadavers. Biological material is typically used as a training stimulus, also called aids, to train dogs to recognize the smell of cadavers. While HRDD training approaches have received extensive attention, information remains limited on the olfactory cues used to train them. Here, we aimed to decipher the chemical basis of detection dog olfaction. Five specific objectives were explored to precise whether the composition or the concentration of the training aids drives the HRDDs responses. We recorded the behavioral responses of four HRDDs exposed to different cadaveric-like smells. We found that HRDDs recognized a simplified synthetic aid composed of cadaveric compounds. The lowest concentration at which HRDDs continued to perceive the cadaveric smell was determined. HRDDs were not impacted by slight modifications to the chemical composition of a blend of odors that they have been trained with. HRDDs associated sulfur and nitrogen compounds as human cadaver. Our findings highlight a lack of specificity of HRDDs to cadaveric compounds, which could lead to error of detection. Moreover, all dogs did not positively respond to the same blends, despite being trained with the same aids and procedure. However, we confirmed that dogs could be trained with a simplified blend of molecules. The chemical composition of a training aid has, therefore, high consequences on the performance of the trained animal, and this conclusion opens additional questions regarding olfaction-based detection animals.     

Emergence of fentanyl-related deaths in Travis County,Texas and surrounding areas: A retrospective review of postmortem fentanyl-related drug toxicities from 2020 to 2022

The opioid epidemic has affected the United States (US) for decades with fentanyl and its analogs accounting for a recent surge in morbidity and mortality. Currently, there is a relative lack of information characterizing fentanyl-related fatalities specifically in the Southern US. A retrospective study was conducted to examine all postmortem fentanyl-related drug toxicities in Travis County, Texas, encompassing Austin (one of the fastest-growing cities in the US), from 2020 to 2022. Fentanyl contributed to 2.6% and 12.2% of deaths submitted for toxicology between 2020 and 2022, respectively, representing a 375% increase in fentanyl-related deaths over this 3-year period (n = 517). Fentanyl-related fatalities primarily occurred in males in their mid-30s. Fentanyl and norfentanyl concentrations ranged from 0.58 to 320 ng/mL and 0.53 to 140 ng/mL with mean (median) concentrations of 17.2 ± 25.0 (11.0) and 5.6 ± 10.9 (2.9) ng/mL, respectively. Polydrug use was present in 88% of cases, with methamphetamine (or other amphetamines) (25%), benzodiazepines (21%), and cocaine (17%) representing the most frequently identified concurrent substances. Co-positivity rates of various drugs and drug classes widely varied over time. Scene investigations reported illicit powder(s) (n = 141) and/or illicit pill(s) (n = 154) in 48% (n = 247) of fentanyl-related deaths. Illicit oxycodone (44%, n = 67) and illicit “Xanax” (38%, n = 59) pills were frequently reported on scene; however, toxicology only identified oxycodone and alprazolam in 2 and 24 of these cases, respectively. The results of this study provide a better understanding of the fentanyl epidemic in this region creating an opportunity to promote increased awareness, shift focus to harm reduction, and aid in minimizing public health risks.     

Identification of document paper using hybrid feature extraction

Document forgery is a significant issue in Korea, with around ten thousand cases reported every year. Analyzing paper plays a crucial role in examining questionable documents such as marketable securities and contracts, which can aid in solving criminal cases of document forgery. Paper analysis can also provide essential insights in other types of criminal cases, serving as an important clue for solving cases such as the source of a blackmail letter. The papermaking process generates distinct forming fabric marks and formations, which are critical features for paper classification. These characteristics are observable under transmitted light and are created by the forming fabric pattern and the distribution of pulp fibers, respectively. In this study, we propose a novel approach for paper identification based on hybrid features. This method combines texture features extracted from images converted using the gray-level co-occurrence matrix (GLCM) approach and a convolutional neural network (CNN), with another set of features extracted by the CNN using the same images as input. We applied the proposed method to classification tasks for seven major paper brands available in the Korean market, achieving an accuracy of 97.66%. The results confirm the applicability of this method for visually inspecting paper products and demonstrate its potential for assisting in solving criminal cases involving document forgery.     

Paired stable carbon and oxygen isotope analyses of human enamel for forensic human geolocation: An exploratory study

Stable carbon isotope analysis has proven utility for reconstructing dietary information in humans in past populations. The usefulness of stable carbon for forensic geolocation has been little investigated, largely because of the globalization of the human diet seemingly rendering it inconsequential. This study queried this assumption at a country-wide level on a known sample group. Stable carbon isotope values were obtained from human enamel with known biographical and geographical information to determine whether stable carbon, when paired with stable oxygen isotope values, could differentiate Canadians from non-Canadians. Samples originating outside of Canada were separated into three regions, and a linear discriminant analysis was used to generate discriminant functions that best separate the regions according to the stable carbon and oxygen isotope values. The results revealed two functions, where the first function explained 92.1% and the second 7.9% of the variance. Although some overlap in stable carbon and oxygen values was observed for individuals from both the United States and Canada, differences were observed between those from Canada and other geographical regions. This study demonstrated that pairing the dietary isotope carbon with the geolocator stable oxygen isotope, produced an interesting separation geographically, one that might well be helpful when attempting a geolocation query on unknown human remains.     

Voltammetric analysis of luminescent markers in gunshot residues

Currently, SEM-EDS is used to detect gunshot residue (GSR) from the presence of Ba, Pb, and Sb in the sample. However, the development of new nontoxic ammunition (NTA) has prevented conventional metals from being found. In this work, we aim to determine the presence of an inorganic luminescent chemical marker based on rare earth in gunshot residues using the technique of squarewave voltammetry (SWV). After firing, the luminescent complex [(Eu₂Zr)(btc)₃(Hbtc)_0.5.6H₂O], which is used as a chemical marker, can be detected under a UV lamp. An aqueous solution with 0.1 mol L⁻¹ KCl as supporting electrolyte can be easily collected on carbon paste electrode surfaces for SWV analysis A = 100 mV, f = 10 Hz, and step potential of 5 mV are required. The luminescent marker incorporated into the carbon paste electrode showed two anodic peak currents in the region of 0.4 V (vs Ag/AgCl) and at 0.75 V (vs Ag/AgCl) and also a cathodic one in 0.4 V (vs Ag/AgCl). SEM-EDS was able to analyze the same voltammetric results for conventional and nontoxic ammunition containing the luminescent marker. Therefore, voltammetry and SEM-EDS are valid for detecting the new residue marker in GSR. Despite this, the electrochemical method is still more advantageous because of its low cost and lack of expensive equipment and supplies in forensic laboratories.     

Rapid and non-destructive approach for characterization and differentiation of sealing wax using ATR-FTIR spectroscopy

Sealing wax is used for maintaining the integrity and authenticity of a document or physical evidence. Any tampering with the seal calls into question the overall integrity and authenticity of the tangible evidence or document. In these circumstances, determining the authenticity of the sealing material (physical and chemical) becomes imperative. In this study, ATR-FTIR spectroscopy supported by chemometrics has been used to differentiate sealing wax samples belonging to 12 different brands available across India. All the samples were first melted, cooled, and then analyzed using ATR-FTIR spectroscopy in the mid-infrared region (4000–600 cm⁻¹). The obtained spectra were first examined visually for the presence of different functional groups. Principal component analysis (PCA) and principal component analysis-linear discriminant analysis (PCA-LDA) were employed to analyze the sample clustering patterns and to categorize them into their respective groups, respectively. For classification, a PCA-LDA training model was applied, and it demonstrated 95.83% accuracy. The validation test resulted in an accuracy of 83.33%. PCA-LDA model offered 100% accurate prediction for samples on various substrates, including cloth, cardboard, and paper. A blind study was also performed using five unknown samples, which were accurately classified into their respective groups. PCA-LDA model will be helpful in providing investigative leads by linking a questioned sealing wax sample with its respective group.     

The rise and rise of fentanyl in postmortem casework

Forensic toxicology laboratories are navigating a period of time with increasing drug overdose deaths, an opioid epidemic, the impact of the COVID-19 pandemic, and the illicit drug market flooded with novel psychoactive substances. In New York City, the Department of Forensic Toxicology has experienced a 56% increase in postmortem casework in the past decade with fentanyl detected in 80% of all overdose deaths. Over a period of 2.5 years, 15,638 postmortem cases were tested for the presence of fentanyl and fentanyl analogs using liquid-chromatography tandem mass spectrometry (LCMSMS). Fentanyl was detected in approximately one third of cases and of these 4447 cases with femoral blood. A twofold increase in cases with high concentrations of fentanyl (>100 ng/mL) was observed between 2021 and 2022. The minor metabolite and precursor chemical, 4-ANPP (4-anilino-N-phenethylpiperidine) may help differentiate between illicit and licit fentanyl. 4-ANPP blood concentrations were <10 ng/mL in 98% of the cases and the 4-ANPP:fentanyl ratio was <0.67 for 99.1% of blood specimens. Only six cases had 4-ANPP concentrations higher than the corresponding fentanyl blood concentration. This study also highlights, the changing fentanyl analogs found in postmortem cases since 2016 in NYC with the emergence of fluorofentanyl initially identified in 2020 and continuing to dominate in comparison with the prevalence of other analogs, many of which are no longer detected in casework. The detection of one of the latest drugs to be mixed with fentanyl, namely xylazine, has also increased in prevalence by 36.7% in 2022 compared with 2021.