Fingerprint Ridge Research Articles

AIE Active Imidazole-Stilbene Conjugated Fluorescent Probes: Illuminating Latent Fingerprints and Advancing Anticounterfeiting Technologies.

Aggregation-induced emission luminogens (AIEgens) are widely used in the realm of latent fingerprint visualization owing to their luminosity and resistance to photobleaching. However, challenges such as significant background interference and limited resolution hinder their rapid advancement. Consequently, there is a pressing need to improve the detailed visualization of latent fingerprint (LFP) imaging, particularly for analyzing level 3 details. To address this, we have designed donor-acceptor (D-A) type AIEgens named MMIMV, DMIMV, and TMIMV. These compounds exhibit robust emissions ranging from 481 to 552 nm and signify positive fluorosolvatochromism. When applied as powder dusting, these derivatives enable the fluorescence imaging of LFPs on various material substrates. The analysis of these imaged LFPs yields intricate details regarding fingerprint ridge patterns. Our results underscore the potential of highly emissive AIEgens MMIMV, DMIMV, and TMIMV as promising candidates for fingerprint visualization, thus offering significant implications for forensic investigations. Furthermore, these derivatives serve as effective fluorescent security inks for writing and drawing, presenting a novel avenue for robust anticounterfeiting applications.

The Study Of Dermatoglyphics Pattern In Females With Primary Infertility

Background: Dermatoglyphics, the study of fingerprint ridge patterns, has been recognized for its potential in reflecting genetic and developmental variations. Primary infertility, defined as the inability to conceive after a year of regular, unprotected intercourse, is influenced by genetic, hormonal, and environmental factors. This study aims to investigate dermatoglyphic patterns in females with primary infertility to explore possible correlations between these patterns and infertility, providing insights for early diagnosis and management. Objective: The primary objective of this protocol is to systematically analyze dermatoglyphic patterns in females with primary infertility and compare them with those of fertile females. The study seeks to identify specific fingerprint characteristics that may serve as non-invasive markers for primary infertility. Methodology: This cross-sectional study will include two groups: females diagnosed with primary infertility and age-matched fertile controls. Dermatoglyphic data will be collected using the ink method, and the following parameters will be analyzed: total ridge count (TRC), patterns of arches, loops, and whorls, and other key qualitative features. Statistical analysis will be performed to evaluate significant differences between the two groups. Expected outcome: The study is expected to reveal distinct dermatoglyphic patterns in females with primary infertility compared to fertile females. Identifying such patterns may provide valuable markers for assessing genetic predispositions and could potentially assist in early diagnosis and personalized treatment strategies for infertility. Conclusion: This protocol outlines a method for studying the potential role of dermatoglyphic patterns in primary infertility, proposing a non-invasive, cost-effective diagnostic approach. Further research may help in establishing dermatoglyphics as a supplementary tool in infertility assessment and managemen.

Sol-gel synthesis of LaFeO3 perovskite oxide for distinct ridges detection of level II and III latent fingerprints

Latent fingerprints are considered a primary source of best reference for personal identification in criminal investigations. However, poor resolution, less background hindrance, and sensitivity over fingerprint ridges are often problems in fingerprint development. To address these issues, special care is required by developing new fluorescence materials. As a result, this effort was made to synthesize lanthanum ferrite (LaFeO3) fluorescent nano perovskite oxide by the sol–gel method using glycine as fuel, to detect three (I, II, and III) levels of fingerprints. In addition, the absorption spectrum was recorded in a dispersed medium, and dual peaks at 329 and 406 nm in visible regions were obtained, followed by the photoluminescence spectra that showed a broad peak at 527 nm with chromaticity coordinates. Powder X-ray diffraction confirms the synthesized LaFeO3 orthorhombic phase with a crystallite size of 54 nm, and the morphology of LaFeO3 was found to be highly monodisperse. X-ray photoelectron spectroscopy confirmed that La has + 3 with Fe + 3 oxidation states, and Infrared spectroscopic techniques revealed all functional groups were present uniformly. The powder dusting method was applied on various porous and non-porous surfaces, revealing distinct ridges of fingerprints without background hindrance and with precise sensitivity; this proves LaFeO3 is suitable for forensic science.

Rotor proliferation promotes high-brightness AIE of iridium emitter accomplishing high-contrast luminous imaging of latent fingerprints to level 3 details

Luminous imaging of latent fingerprints (LFPs) necessitates the possession of high-brightness aggregation-state luminescence by developers to ensure sufficient imaging contrast and resolution. A novel strategy involving incremental rotor modification is presented for AIE activation of the iridium developer. The rotor proliferation prominently improves the rotational activity of groups and facilitates high-efficiency RIM, thereby prompting the AIE activation of iridium developer with high luminous efficiency. Subsequently, a prompt, high-contrast, and robust LFP imaging protocol is developed utilizing the high-brightness AIE-active iridium developer. This innovative protocol realizes the luminous imaging and quantification of microscopic features in fingerprint ridges and furrows, including ridge widths, edge morphology of ridges, included angles, pores, and pore pitches with exceptional imaging contrast and refined detail resolution. Moreover, it allows for accurate identification of individual traits across diverse substrates without any pre-/post-processing to LFPs. The high-brightness AIE-active iridium developer provides outstanding aging resistance to developed fingerprints, thereby strongly supporting the acquisition, transfer, and preservation of fingerprint evidence. The luminous imaging protocol of LFPs based on high-brightness AIE exhibits robust adaptability to actual scenes and offers a premium scheme for facilitating forensic investigation.

Biometric-Tuned E-Skin Sensor with Real Fingerprints Provides Insights on Tactile Perception: Rosa Parks Had Better Surface Vibrational Sensation than Richard Nixon.

The dense mechanoreceptors in human fingertips enable texture discrimination. Recent advances in flexible electronics have created tactile sensors that effectively replicate slowly adapting (SA) and rapidly adapting (RA) mechanoreceptors. However, the influence of dermatoglyphic structures on tactile signal transmission, such as the effect of fingerprint ridge filtering on friction-induced vibration frequencies, remains unexplored. A novel multi-layer flexible sensor with an artificially synthesized skin surface capable of replicating arbitrary fingerprints is developed. This sensor simultaneously detects pressure (SA response) and vibration (RA response), enabling texture recognition. Fingerprint ridge patterns from notable historical figures - Rosa Parks, Richard Nixon, Martin Luther King Jr., and Ronald Reagan - are fabricated on the sensor surface. Vibration frequency responses to assorted fabric textures are measured and compared between fingerprint replicas. Results demonstrate that fingerprint topography substantially impacts skin-surface vibrational transmission. Specifically, Parks' fingerprint structure conveyed higher frequencies more clearly than those of Nixon, King, or Reagan. This work suggests individual fingerprint ridge morphological variation influences tactile perception and can confer adaptive advantages for fine texture discrimination. The flexible bioinspired sensor provides new insights into human vibrotactile processing by modeling fingerprint-filtered mechanical signals at the finger-object interface.

Skin Surface Sebum Analysis by ESI-MS.

The skin surface is an important sample source that the metabolomics community has only just begun to explore. Alterations in sebum, the lipid-rich mixture coating the skin surface, correlate with age, sex, ethnicity, diet, exercise, and disease state, making the skin surface an ideal sample source for future noninvasive biomarker exploration, disease diagnosis, and forensic investigation. The potential of sebum sampling has been realized primarily via electrospray ionization mass spectrometry (ESI-MS), an ideal approach to assess the skin surface lipidome. However, a better understanding of sebum collection and subsequent ESI-MS analysis is required before skin surface sampling can be implemented in routine analyses. Challenges include ambiguity in definitive lipid identification, inherent biological variability in sebum production, and methodological, technical variability in analyses. To overcome these obstacles, avoid common pitfalls, and achieve reproducible, robust outcomes, every portion of the workflow-from sample collection to data analysis-should be carefully considered with the specific application in mind. This review details current practices in sebum sampling, sample preparation, ESI-MS data acquisition, and data analysis, and it provides important considerations in acquiring meaningful lipidomic datasets from the skin surface. Forensic researchers investigating sebum as a means for suspect elimination in lieu of adequate fingerprint ridge detail or database matches, as well as clinical researchers interested in noninvasive biomarker exploration, disease diagnosis, and treatment monitoring, can use this review as a guide for developing methods of best-practice.

Healing Function for Abraded Fingerprint Ridges in Tactile Texture Sensors.

Tactile texture sensors are designed to evaluate the sensations felt when a human touches an object. Prior studies have demonstrated the necessity for these sensors to have compliant ridges on their surfaces that mimic human fingerprints. These features enable the simulation of contact phenomena, especially friction and vibration, between human fingertips and objects, enhancing the tactile sensation evaluation. However, the ridges on tactile sensors are susceptible to abrasion damage from repeated use. To date, the healing function of abraded ridges has not been proposed, and its effectiveness needs to be demonstrated. In this study, we investigated whether the signal detection capabilities of a sensor with abraded epidermal ridges could be restored by healing the ridges using polyvinyl chloride plastisol as the sensor material. We developed a prototype tactile sensor with an embedded strain gauge, which was used to repeatedly scan roughness specimens. After more than 1000 measurements, we observed significant deterioration in the sensor's output signal level. The ridges were then reshaped using a mold with a heating function, allowing the sensor to partially regain its original signal levels. This method shows potential for extending the operational lifespan of tactile texture sensors with compliant ridges.

Forensic Fingerprint Analysis

Fingerprint evidence found at crime scenes provides vital impressions left when these skin secretions touch surfaces clues in serial criminal investigations. A fingerprint identification system employing deep machine learning and Convolutional Neural Networks (CNNs) could automate the analysis process. Images obtained from various physical and chemical crime scene investiga2tion techniques are entered into the database. However, partial latent prints lifted from scenes are often difficult to classify. The system operates in three phases: preprocessing fingerprint images, feature extraction, and matching. Preprocessing enhances image quality before feature extraction identifies distinctive minutiae points - ridge endings and bifurcations. False minutiae removal further refines the data. The preprocessed fingerprint data serves as input to train and test the CNN model. As the system persist due to the immutable individuality of fingerprint ridge arrangements [5]. While criminals attempt concealment, fingerprint traces stubbornly remain where other evidence would dissipate [6]. Without these durable biometric markers, crime scenes would often lack the critical traces needed to connect acts to perpetrators [7]. Latent prints lifted from crime scenes first undergo photographic documentation and chemical enhancement techniques in order to visualize trace details [8]. Computer analysis then further improves clarity, isolating minute identifying features known as minutiae [9]. Algorithmic extraction of differentiating traits classifies new latent prints, it continuously incorporates the prints enables training of automated comparison systems using along with confirmed suspect identity matches to improve accuracy. Automated classification and matching facilitate identification. The approach scales as the database grows in size without proportionate growth in human effort. Rapid fingerprint evidence analysis accelerates investigations, potentially solving more crimes by linking serial cases through a central digital repository. I aimed to restate the key technical ideas and flow using alternative vocabulary and phrasing while preserving semantic meaning. Please let me know if you need any clarification or have additional requirements for rephrasing the passage.

Sexual dimorphism and topological variability in fingerprint ridge density in a north-west Indian population.

The science of fingerprints is very crucial in criminal investigation as it helps identify perpetrators or victims of a crime. Fingerprint ridge density (FPRD), which refers to the number of ridges within a specific area on the epidermal skin layer of the distal phalanges in humans, has been found to differ between males and females. This study attempts to estimate the sex from FPRD and evaluates the diversity in FPRD across several topological areas. The study involves 208 participants (120 males, 88 females) between the ages 18 to 25years from a North-west Indian population. Fingerprints were collected, and FPRD was accessed in radial, ulnar, and proximal areas as recommended by Gutierrez-Redomero et al. (Forensic Sci Int 180(1):17-22, 2008). FPRD has been quantified using the techniques described by Acree (Forensic Sci Int 102(1):35-44, 1999). When evaluating FPRD in the lateral pocket loops and twin loops, the proximal-side core was considered. The study reveals that males have a mean fingerprint ridge density of 12.82 ridges/25 mm2 while females have 13.01 ridges/25 mm2. Females have higher fingerprint ridge density solely in the proximal area; males have higher fingerprint ridge density in both radial and ulnar areas. In conclusion, this research underscores the potential of fingerprint ridge density as a parameter for investigating population variations and individual identification. Future studies on fingerprint ridge density in India's diverse population will help establish reference ranges, allowing for sex and likely population group estimation, making it a valuable tool for preliminary examinations and exclusion criteria for sex estimation in crime scene investigations.

A direct analysis method using sheath flow probe electrospray ionisation-mass spectrometry (sfPESI-MS) to detect drug residues from fingerprint forensic gel lifts.

Latent fingerprints at crime scenes are frequently recovered using forensic gel-lifters, which can help to preserve the crime scene and to enhance visualisation of traces such as blood or paint. In addition to providing fingerprint ridge detail, additional chemical information can also be recovered from gel lifts that may prove pertinent to an investigation. However, while DNA and metal ions have been shown to be able to be detected in gel-lifted fingerprints, the determination of other types of chemical information such as the presence of drugs in gel-lifted prints has not been previously shown. This study demonstrates the application of an ambient ionisation method, sheath flow probe electrospray ionisation-mass spectrometry (sfPESI-MS), to the direct analysis of gel-lifted fingerprints. A model drug compound (zolpidem) is successfully detected from gel-lifted prints from three different surface types: glass, metal, and paper. The surface activity-based separation associated with probe electrospray approaches is shown to resolve zolpidem ions from background phthalate species, significantly enhancing the response obtained from the gel-lifter. A depletion series experiment shows that the drug residue can be detected with up to 100% efficiency after eight consecutive contacts; however, detection efficiency drops to 20% after 30 contacts. The developed approach has potential application to analysis of historical gel-lifters to obtain additional chemical information.

Potential of Y2Sn2O7:Eu3+, Dy3+ Inorganic Nanophosphors in Latent Fingermark Detection

In this work, we investigated the potential of Eu3+/Dy3+-codoped Y2Sn2O7 fluorescent nanophosphors to visualize latent fingermarks. We prepared these nanophosphors with various doping concentrations by the conventional coprecipitation reaction. The crystal structure, morphology, luminescence properties, and energy transfer mechanisms were studied. The crystalline phase was characterized by X-ray diffraction and crystal structure refinement using the Rietveld method. XRD measurements showed that the samples crystallized in the pure single pyrochlore phase with few more peaks originated from secondary phases and impurities generated during phosphor production, and that Eu3+ ions occupied D3d symmetry sites. The average crystallite size after mechanical grinding was less than 100 nm for all compositions. The optical characterization showed that, when excited under 532 nm, the Eu3+/Dy3+-codoped Y2Sn2O7 samples’ main intense emission peaks were located at 580–707 nm, corresponding to the 5D0→7Fj (j = l, 2, 3, and 4) transitions of europium. In fact, the 5D0→7F2 hypersensitive transition is strongly dependent on the local environment and was quite weak in Eu3+:Y2Sn2O7 at low Eu3+ doping levels. We found that the presence of Dy3+ as a codopant permitted enhancing the emission from this transition. The calculated PL CIE coordinates for the synthesized nanophosphors were very close to those of the reddish-orange region and only slightly dependent on the doping level. Various surfaces, including difficult ones (wood and ceramic), were successfully tested for latent fingerprint development with the prepared Eu3+/Dy3+-codoped Y2Sn2O7 fluorescent nanophosphor powder. Thanks to the high contrast obtained, fingerprint ridge patterns at all three levels were highlighted: core (level 1) islands, bifurcation, and enclosure (level 2), and even sweat pores (level 3).

Enhanced photocatalytic, photoluminescence and fingerprint properties of Dy3+ ions doped BaZrO3 nanopowders for multifunctional applications

In the present investigation photoluminescent, photocatalytic and advanced forensic applications of hydrothermally prepared BaZrO3:Dy3+ (1–9 mol%) nanopowders were studied in detail. Fresh green Aloe Vera (AV) gel was used as capping agent for the preparation of NPs. The pure cubic phase was observed by powder X-ray diffraction (PXRD) profiles. Fourier transform infrared (FTIR) was utilized to investigate the functional groups present in the prepared NPs. The modification in surface morphology was investigated by using Field emission scanning electron microscope (FESEM) images. The grain size was evaluated by utilizing transmission electron microscope (TEM) images and found to be around 48 nm. Further, with the help of high-resolution TEM (HR-TEM) images the interplanar distance was calculated and found to be 0.32 nm. Photoluminescence (PL) studies were carried out in detail using excitation and emission spectra. The maximum intensity was detected for peak 388 nm ascribed to 6H15/2 → 4I13/2 + 4F7/2 of Dy3+ transition under 574 nm emanation wavelength. The obtained emanation spectra consist of 3 characteristics peaks of Dy3+ ions at 480, 574 and 666 nm attributed to 4F9/2→ 6H15/2, 4F9/2→ 6H13/2 and 4F9/2→ 6H11/2 respectively. The PL intensity increases up to 7 mol% dopant ion weight and afterwards it decreases due to concentration quenching phenomena. The dipole–dipole interaction was responsible for this quenching. The color coordinates results in white emission witnessed from the Commission International de I'Eclairage (CIE) and correlated color temperature (CCT) diagrams. The average CCT value was observed around 4836 K. Further, the color purity (CP) and external quantum efficiency (QE) was estimated and found to be 86 % and 64 % respectively. The photocatalytic degradation activity was also studied for the prepared powders and found that, the optimum degradation was observed till 180 min. The kinetics studies revealed that, the present powders were in agreement with the 0th order with estimated ko = 0.015 with R2 value of 0.98 respectively. The powders were also explored for their latent fingerprint (LFP) visualization on various porous and non-porous surfaces and found that, the powders exhibited all types of fingerprint ridge details including the 3rd type such as sweat pores and scar. The observed all outcomes specify that, the prepared powders can be used as a potential candidate for the fabrication of white LEDs (wLEDs), excellent photocatalyst and fingerprint visualization.

Hierarchical Perceptual Noise Injection for Social Media Fingerprint Privacy Protection.

Billions of people share images from their daily lives on social media every day. However, their biometric information (e.g., fingerprints) could be easily stolen from these images. The threat of fingerprint leakage from social media has created a strong desire to anonymize shared images while maintaining image quality, since fingerprints act as a lifelong individual biometric password. To guard the fingerprint leakage, adversarial attack that involves adding imperceptible perturbations to fingerprint images have emerged as a feasible solution. However, existing works of this kind are either weak in black-box transferability or cause the images to have an unnatural appearance. Motivated by the visual perception hierarchy (i.e., high-level perception exploits model-shared semantics that transfer well across models while low-level perception extracts primitive stimuli that result in high visual sensitivity when a suspicious stimulus is provided), we propose FingerSafe, a hierarchical perceptual protective noise injection framework to address the above mentioned problems. For black-box transferability, we inject protective noises into the fingerprint orientation field to perturb the model-shared high-level semantics (i.e., fingerprint ridges). Considering visual naturalness, we suppress the low-level local contrast stimulus by regularizing the response of the Lateral Geniculate Nucleus. Our proposed FingerSafe is the first to provide feasible fingerprint protection in both digital (up to 94.12%) and realistic scenarios (Twitter and Facebook, up to 68.75%). Our code can be found at https://github.com/nlsde-safety-team/FingerSafe.

Gender Determination Using Fingerprint Ridge Density in Perambalur District of Tamil Nadu

Gender Determination Using Fingerprint Ridge Density in Perambalur District of Tamil Nadu

An Interpretable Siamese Attention Res‐CNN for Fingerprint Spoofing Detection

In recent years, fingerprint authentication has gained widespread adoption in diverse identification systems, including smartphones, wearable devices, and attendance machines, etc. Nonetheless, these systems are vulnerable to spoofing attacks from suspicious fingerprints, posing significant risks to privacy. Consequently, a fingerprint presentation attack detection (PAD) strategy is proposed to ensure the security of these systems. Most of the previous work concentrated on how to build a deep learning framework to improve the PAD performance by augmenting fingerprint samples, and little attention has been paid to the fundamental difference between live and fake fingerprints to optimize feature extractors. This paper proposes a new fingerprint liveness detection method based on Siamese attention residual convolutional neural network (Res‐CNN) that offers an interpretative perspective to this challenge. To leverage the variance in ridge continuity features (RCFs) between live and fake fingerprints, a Gabor filter is utilized to enhance the texture details of the fingerprint ridges, followed by the construction of an attention Res‐CNN model to extract RCF between the live and fake fingerprints. The model mitigates the performance deterioration caused by gradient disappearance. Furthermore, to highlight the difference in RCF, a Siamese attention residual network is devised, and the ridge continuity amplification loss function is designed to optimize the training process. Ultimately, the RCF parameters are transferred to the model, and transfer learning is utilized to aid its acquisition, thereby assuring the model’s interpretability. The experimental outcomes conducted on three publicly accessible fingerprint datasets demonstrate the superiority of the proposed method, exhibiting remarkable performance in both true detection rate and average classification error rate. Moreover, our method exhibits remarkable capabilities in PAD tasks, including cross‐material experiments and cross‐sensor experiments. Additionally, we leverage Gradient‐weighted Class Activation Mapping to generate a heatmap that visualizes the interpretability of our model, offering a compelling visual validation.

CQTDs/SiO2NPs nanocomposite for Pb2+ and Cd2+ remediation and reuse applications in LFP detection and photocatalysis

Due to their propensity to bioaccumulate, lead and cadmium, two hazardous heavy metals, can seriously disrupt the ecosystem. These metals have the potential to cause major environmental and human health problems. Herein, carbon quantum dots were used to coat silica nanoparticles to create a brand-new nanocomposite called CQTDs/SiO2NPs. Cd2+ and Pb2+ ions were effectively removed from water and preconcentrated using the produced nanocomposite. The novel nanocomposite was characterized using SEM, TEM, FT-IR, XRD, and XRF. The bending vibration of Si–O–Si/Si–O–C and Si–OH are responsible for the FT-IR bands that were detected in the nanocomposite at 1041 and 954 cm−1, respectively. XRD demonstrated that the silica nanoparticles were amorphous. Additionally, SEM and TEM analysis revealed the nanocomposite's shape, which was determined to be spherical with minimal agglomeration.While XPS demonstrated the binding energy of the functional group present in the composite and further confirmed the metal loaded onto the adsorbent. On CQTDs/SiO2NPs nanocomposite, the optimum pH and dosage were 8 and 0.2 g respectively. The highest Cd2+ and Pb2+ ion adsorption capabilities are 14.87 and 38.49 mg g −1, respectively. The use of the nanocomposite resulted in an exothermic, physical and non-spontaneous adsorption that closely resembled the Langmuir equilibrium isotherm and the second-order kinetics. The metal loaded adsorbent used as a fingerprint labelling agent displayed clear fingerprint ridges and degraded the sulfamethoxazole (SMX) for up to 90 %. The prepared composite has proven to be coherent in heavy metal removal and can thus be reused in Latent fingerprint and photocatalysis applications. The reuse of the nanocomposite in the above-mentioned applications is an alternative solution to avoid secondary pollution.

An individual's skin stiffness predicts their tactile discrimination of compliance.

Individual differences in tactile acuity have been correlated with age, gender and finger size, whereas the role of the skin's stiffness has been underexplored. Using an approach to image the 3-D deformation of the skin surface during contact with transparent elastic objects, we evaluate a cohort of 40 young participants, who present a diverse range of finger size, skin stiffness and fingerprint ridge breadth. The results indicate that skin stiffness generally correlates with finger size, although individuals with relatively softer skin can better discriminate compliant objects. Analysis of contact at the skin surface reveals that softer skin generates more prominent patterns of deformation, in particular greater rates of change in contact area, which correlate with higher rates of perceptual discrimination of compliance, regardless of finger size. Moreover, upon applying hyaluronic acid to soften individuals' skin, we observe immediate, marked and systematic changes in skin deformation and consequent improvements in perceptual acuity in differentiating compliance. Together, the combination of 3-D imaging of the skin surface, biomechanics measurements, multivariate regression and clustering, and psychophysical experiments show that subtle distinctions in skin stiffness modulate the mechanical signalling of touch and shape individual differences in perceptual acuity. KEY POINTS: Although declines in tactile acuity with ageing are a function of multiple factors, for younger people, the current working hypothesis has been that smaller fingers are better at informing perceptual discrimination because of a higher density of neural afferents. To decouple relative impacts on tactile acuity of skin properties of finger size, skin stiffness, and fingerprint ridge breadth, we combined 3-D imaging of skin surface deformation, biomechanical measurements, multivariate regression and clustering, and psychophysics. The results indicate that skin stiffness generally correlates with finger size, although it more robustly correlates with and predicts an individual's perceptual acuity. In particular, more elastic skin generates higher rates of deformation, which correlate with perceptual discrimination, shown most dramatically by softening each participant's skin with hyaluronic acid. In refining the current working hypothesis, we show the skin's stiffness strongly shapes the signalling of touch and modulates individual differences in perceptual acuity.

Expanding the Efficacy of Fingermark Enhancement Using ToF-SIMS.

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) has been shown to enhance fingermark recovery compared to standard processes used by police forces, but there is no data to show how generally applicable the improvement is. Additionally, ToF-SIMS can be run in either positive or negative ion mode (or both), and there is no data on which mode of operation is most effective at revealing fingerprints. This study aims to fill these gaps by using ToF-SIMS to image fingerprints deposited on two common exhibit-type surfaces (polyethylene and stainless steel) using 10 donors and ageing fingerprints in either ambient, rainwater, or underground for 1 and 5 months. In all, 120 fingerprints were imaged using ToF-SIMS, and each was run in positive and negative modes. A fingerprint expert compared the fingerprint ridge detail produced by the standard process to the ToF-SIMS images. In over 50% of the samples, ToF-SIMS was shown to improve fingerprint ridge detail visualised by the respective standard process for all surfaces tested. In over 90% of the samples, the ridge detail produced by ToF-SIMS was equivalent to standard development across all different ageing and exposure conditions. The data shows that there is a benefit to running the ToF-SIMS in both positive and negative modes, even if no ridge detail was seen in one mode.

Inferring the age and sex of ancient potters from fingerprint ridge densities: A data-driven, Bayesian mixture modelling approach

The density of epidermal ridges in a fingerprint varies predictably by age and sex. Archaeologists are therefore interested in using recovered fingerprints to learn about the ancient people who produced them. Recent studies focus on estimating the age and sex of individuals by measuring their fingerprints with one of two similar metrics: mean ridge breadth (MRB) or ridge density (RD). Yet these attempts face several critical problems: expected values for adult females and adolescent males are inherently indistinguishable, and inter-assemblage variation caused by biological and technological differences cannot be easily estimated. Each of these factors greatly decreases the accuracy of predictions based on individual prints, and together they condemn this strategy to relative uselessness. However, information in fingerprints from across an assemblage can be pooled to generate a more accurate depiction of potter demographics. We present a new approach to epidermal ridge density analysis using Bayesian mixture models with the following key benefits:•Age and sex are estimated more accurately than existing methods by incorporating a data-driven understanding of how demographics and ridge density covary.•Uncertainty in demographic estimates is automatically quantified and included in output.•The Bayesian framework can be easily adapted to fit the unique needs of different researchers.

Sex Differentiation from Fingerprint Ridge Density

Background: Determination of sex is an important parameter other than age, race and stature during forensic identification and crime scene investigation. Females tend to have finer and denser ridges on their fingertips than males. Present study aims at differentiating gender from fingerprint ridge density. Material and Methods: This is a cross sectional study conducted from March 2022 to March 2023 in Nobel Medical College Teaching Hospital, Nepal. Seven hundred fingerprints samples (350 males and 350 females), from 70 Nepalese medical students were collected and analyzed for gender differences. Comparative analysis was done using Student’s t-test (p<0.05). Likelihood ratio and posterior probability using Baye’s theorem were calculated to interpret the possibility of gender differentiation from various fingerprint ridge densities. Results: Students t-test revealed significant difference (p < 0.001) between the fingerprint ridge density of male and female (t= -16.733). The results showed ridge density <14/25mm2and >15/25mm2 are “more likely than not” from males and females respectively. Posterior probability using Baye’s theorem further revealed ridge density <13/25mm2 (C/C1=5.75,P=0.86) and >16/25mm2 (C1/C=4.29, P1=0.84) have higher probability of originating from males and females respectively. No any male and female had ridge density >16/25mm2 and <13/25mm2 respectively. Conclusion: The study revealsstatistically significantlygreater fingerprint ridge densities in female than in male Nepalese medical students.