Human Identification Research Articles

Robust Biometric Verification Using Phonocardiogram Fingerprinting and a Multilayer-Perceptron-Based Classifier

Recently, a new set of biometric traits, called medical biometrics, have been explored for human identity verification. This study introduces a novel framework for recognizing human identity through heart sound signals, commonly referred to as phonocardiograms (PCGs). The framework is built on extracting and suitably processing Mel-Frequency Cepstral Coefficients (MFCCs) from PCGs and on a classifier based on a Multilayer Perceptron (MLP) network. A large dataset containing heart sounds acquired from 206 people has been used to perform the experiments. The classifier was tuned to obtain the same false positive and false negative misclassification rates (equal error rate: EER = FPR = FNR) on chunks of audio lasting 2 s. This target has been reached, splitting the dataset into 70% and 30% training and testing non-overlapped subsets, respectively. A recurrence filter has been applied to also improve the performance of the system in the presence of noisy recordings. After the application of the filter on chunks of audio signal lasting from 2 to 22 s, the performance of the system has been evaluated in terms of recall, specificity, precision, negative predictive value, accuracy, and F1-score. All the performance metrics are higher than 97.86% with the recurrence filter applied on a window lasting 22 s and in different noise conditions.

Enhanced BMP Signaling Alters Human β-Cell Identity and Function.

Inflammation contributes to the pathophysiology of diabetes. Identifying signaling pathways involved in pancreatic β-cell failure and identity loss can give insight into novel potential treatment strategies to prevent the loss of functional β-cell mass in diabetes. It is reported earlier that the immunosuppressive drug tacrolimus has a detrimental effect on human β-cell identity and function by activating bone morphogenetic protein (BMP) signaling. Here it is hypothesized that enhanced BMP signaling plays a role in inflammation-induced β-cell failure. Single-cell transcriptomics analyses of primary human islets reveal that IL-1β+IFNγ and IFNα treatment activated BMP signaling in β-cells. These findings are validated by qPCR. Furthermore, enhanced BMP signaling with recombinant BMP2 or 4 triggers a reduced expression of key β-cell maturity genes, associated with increased ER stress, and impaired β-cell function. Altogether, these results indicate that inflammation-activated BMP signaling is detrimental to pancreatic β-cells and that BMP-signaling can be a target to preserve β-cell identity and function in a pro-inflammatory environment.

Pedagogical Perspectives of Utu: Reclaiming Primacy of African Values for Moral-ethical for Youth Development in Tanzania

Abstract The decline of moral and ethics in Tanzania especially to the youth is associated by different factors among which is the decrease in abiding by traditional values centered in utu concept. This study examined the way in which, pedagogical perspectives of utu contribute greatly in reclaiming primacy of African values for moral-ethical development of the youth in Tanzania. This study has used a desktop research study method whereby literature has been surveyed. The study argues that pedagogical perspectives of utu should be embraced for reclaiming the primacy of African values for moral-ethical development of youth in Tanzania. This study reaffirms the fact that the utu concept can stand out as a paradigm for the holistic concept of the human person and worldview that sees the reality of life as an interrelated. The moral/ethical values practiced in the light of utu on the basis of unity and brotherhood within a human family can help the Tanzanian society to recuperate a sense of national identity. Therefore, Tanzanian society today needs to cultivate, transmit, and practice utu in daily life for holistic development. The study recommends that, the utu concept which advocates the value of human dignity and identity, reminds us of the necessity of clarifying and living what we mean by “values” in education today since not all aspects of life and practice attributed to culture contain educational values worth of human dignity.

Steady-State Visual Evoked Potential-Based Brain–Computer Interface System for Enhanced Human Activity Monitoring and Assessment

Advances in brain–computer interfaces (BCIs) have enabled direct and functional connections between human brains and computing systems. Recent developments in artificial intelligence have also significantly improved the ability to detect brain activity patterns. In particular, using steady-state visual evoked potentials (SSVEPs) in BCIs has enabled noticeable advances in human activity monitoring and identification. However, the lack of publicly available electroencephalogram (EEG) datasets has limited the development of SSVEP-based BCI systems (SSVEP-BCIs) for human activity monitoring and assisted living. This study aims to provide an open-access multicategory EEG dataset created under the SSVEP-BCI paradigm, with participants performing forward, backward, left, and right movements to simulate directional control commands in a virtual environment developed in Unity. The purpose of these actions is to explore how the brain responds to visual stimuli of control commands. An SSVEP-BCI system is proposed to enable hands-free control of a virtual target in the virtual environment allowing participants to maneuver the virtual target using only their brain activity. This work demonstrates the feasibility of using SSVEP-BCIs in human activity monitoring and assessment. The preliminary experiment results indicate the effectiveness of the developed system with high accuracy, successfully classifying 89.88% of brainwave activity.

Spatiotemporal Distribution of Human Rabies and Identification of Predominant Risk Factors in China from 2004 to 2020.

Human rabies is a prevalent issue in China, posing a significant public health concern in the country. This study fitted the Bayesian model of separable in spatial and temporal variation and inseparable spatiotemporal variation in disease risk respectively based on Integrated Nested Laplace Approximation (INLA) to investigate the spatiotemporal characteristics of human rabies across 31 provinces in China from 2004 to 2020. It also investigated the influence of natural and socio-environmental factors on the incidence of the disease. Within the study period, a total of 26,807 cases of human rabies were reported, with the highest risk of incidence occurring in 2007, followed by a steady annual decline to the lowest risk in 2020. Guangxi Province exhibited the highest risk, while Jilin Province had the lowest, with the southern, central, and eastern regions reporting higher risks than the northern and western areas. By 2020, most provinces such as Guangxi and Guizhou had significantly reduced their relative risk (RR) of human rabies from historical highs. However, some provinces like Hunan, Henan, and Jiangsu experienced an increase in RR compared to previous years. As the annual average temperature increases, the risk of human rabies incidence in China correspondingly rises. Conversely, with increases in the annual average daily sunshine duration, per capita disposable income of urban residents, and local government healthcare expenditures, the risk of human rabies incidence declines. We conclude that the risk of human rabies in China initially increased and then decreased annually from 2004 to 2020. Future efforts should continuously increase financial investments in rabies prevention and control, focusing particularly on Hunan, Henan, Jiangsu, and provinces characterized by higher temperatures, shorter sunshine durations, and lower economic levels.

John Locke: entre a animalidade e a humanidade

The aim of this text is to analyse the arguments that Locke mobilises to demonstrate the difference between animals and humans, from the perspective of personal identity. It is divided into two parts: in the first, the presence of the parrot in Brazil will be evoked, from which Locke draws his example to discuss human identity, a task that will be developed in the second part. We hope to contribute to the debate on the relationship between humans and non-humans, particularly in the English seventeenth century.

Anthropocenic Futures and Precarious Bodies. A Reading of "Mugre rosa" (2020) by Fernanda Trías

Mugre rosa (2020), by Uruguayan author Fernanda Trías, depicts a near-future Montevideo, where the population is confronted with climatic disaster and the propagation of a devastating disease. In this article, I explore the representation of bodily precarity in the context of environmental catastrophe, arguing that this vulnerability constitutes a point of resistance from which to rethink human identity. On the one hand, exposure to an anthropogenic environment is interpreted as instrumental to late capitalist biopolitics. This is revealed through the cartographies of precarity emerging from the novel, which reflect not only the chasm between Global North and Global South but also local inequalities. On the other hand, this corporeal exposure constitutes a challenge to traditional representations of the human. Through the analysis of the depiction of the illness, I discuss how this deconstruction of the body favours the emergence of a new, interconnected identity. Ultimately, I suggest that a destabilising age such as the Anthropocene constitutes not only a profound moment of crisis but also a privileged space to rethink human subjectivity and its modes of representation.

Retraction Note: Human identification with their VOC distribution through CMS– SEN Model

Retraction Note: Human identification with their VOC distribution through CMS– SEN Model

Collagen Isolated from Human Adipose Tissue and Its Cellular Affinity.

The use of collagen in cell cultures promotes cell proliferation and differentiation, and it has been commercialized. In this study, we separated and purified collagen from adipose tissue discarded during liposuction and prepared collagen-coated dishes. After collagen was identified from human adipose tissue, type identification and quantification were performed using SDS-PAGE and FPLC. Collagen type I was used to coat culture dishes. Human skin fibroblasts and human adipose tissue-derived stem cells were seeded at a density of 2.5×105 cells/mL on prepared dishes at a collagen concentration of 3 mg/mL and cultured for 7 days. Cell viability was then measured and analyzed. The WST-1 assay was used to evaluate the results. The amount of collagen in 300 g of adipose tissue was 25.5 mg for type I, 41.4 mg for type III, 10.6 mg for type IV, 6.5 mg for type V, and 15 mg for type VI. The highest rates were observed for adipose stem cells cultured on human adipose tissue-derived collagen-coated dishes. In cell cultures, cell affinity was higher when cells and the substrate used were of the same origin, and affinity was stronger when the tissue of origin was the same.

Global health resource distribution during COVID-19 and in future pandemics: Here’s what people say

Abstract During the COVID-19 pandemic, countless individuals across the world needed novel and sophisticated health care resources simultaneously, leading to dramatic global shortages. How to distribute resources in such situations? This dilemma is neither new nor understudied: Its complexity is well known to medical ethicists, public health scientists and philosophers. Building on this knowledge, powerful global distribution frameworks were proposed already early into the pandemic. Despite this knowledge, no globally consensual regulations existed (and exist) on the political sphere. Worse still, numerous countries hoarded resources for themselves, increasing global inequalities and prolonging the pandemic for everyone. For future emergencies, it is thus necessary to develop immediately applicable strategies. Because public acceptance is key for such interventions, evidence on the public opinion towards allocation principles is strongly needed. In 2021, we asked representative samples of N = 2694 adults in England and Germany to rate seven COVID-19-specific global allocation principles. In line with literature on justice attitudes in general, extensions of bifactor(S-1) models showed that participants would have preferred a more equity- or equality-based global resource distribution during the pandemic, presenting themselves as more cosmopolitan than global leaders. Trying to understand these attitudes better, we tested preregistered hypotheses on relations with other constructs and found positive associations between equity- and equality-directed preferences and global human identification, among others. To ensure generalisability on future pandemics, we collected data from a second cohort in spring 2024. All results will be presented in detail. With their responses, European citizens call upon the development of fairer and more efficient global distribution mechanisms. This global public health perspective could inform preparations for future global emergencies. Key messages • European citizens would have preferred a more equity- or equality-based global distribution of scarce health care resources during the COVID-19 pandemic than global leaders organised. • Citizens’ global perspective on public health and their strong emphasis on global fairness should inform preparations for future pandemics and other global emergencies.

Characterisation of identity-informative genetic markers in the Australian population with European ancestry

Identity-informative single nucleotide polymorphisms (iiSNPs) are valuable genetic markers for human identification and kinship testing in forensic casework, especially when the quality and quantity of DNA evidence is not suitable for routine short tandem repeat (STR) profiling. This study analysed 105 buccal samples representing the Australian population with European ancestry in order to assign allele frequencies and conduct population genetic analyses for 94 iiSNPs and 20 STRs. The markers were assessed by calculating relevant forensic statistics and testing for deviations from Hardy-Weinberg and linkage equilibrium. No linkage of statistical significance was observed between any of the pair-wise combinations of the combined 114 identity-informative markers and only one STR exhibited deviation from Hardy-Weinberg equilibrium (D8S1179). The probability of matching genotypes being observed within this population was of the order of 10−23 for STRs, 10−38 for iiSNPs and 10−60 for the combined identity-informative marker panel, improving the ability to discriminate between individuals when calculating likelihood ratios in direct or indirect matching scenarios. Further, the addition of iiSNPs will facilitate identifications when suboptimal STR profiles are recovered from compromised or challenging samples and aid comparisons to genetic relatives for familial or kinship testing.

LGBTQ Visibility Measured Consistently and Persistently in US Twitter Bios from 2012 through 2023

LGBTQ visibility is an often discussed but rarely quantified concept. Here we operationalize visibility as the prevalence of active social media accounts with an LGBTQ signifier in the profile bio and measure the prevalence of such accounts consistently and persistently at daily resolution over twelve years in the United States. We found that prevalence for the signifiers lesbian, gay, bisexual, trans and queer increased. The term ‘gay’ grew most rapidly. Accounts with LGBTQ signifiers were especially visible on days corresponding to political or violent events. The rainbow flag emoji also increased in prevalence, including a notable ratchet each June (Pride Month). This work is a case study in ipseology – i.e. the study of human identity using large datasets and computational methods. Social scientists should embrace ipseology as a new opportunity to observe how people describe their selves to a public audience.

Survivor detection approach for post earthquake search and rescue missions based on deep learning inspired algorithms

Rapid and reliable detection of human survivors trapped under debris is crucial for effective post-earthquake search and rescue (SAR) operations. This paper presents a novel approach to survivor detection using a snake robot equipped with deep learning (DL) based object identification algorithms. We evaluated the performance of three main algorithms: Faster R-CNN, Single Shot MultiBox Detector (SSD), and You Only Look Once (YOLO). While these algorithms are initially trained on the PASCAL VOC 2012 dataset for human identification, we address the lack of a dedicated dataset for trapped individuals by compiling a new dataset of 200 images that specifically depicts this scenario, featuring cluttered environment and occlusion. Our evaluation takes into account detection accuracy, confidence interval, and running time. The results demonstrate that the YOLOv10 algorithm achieves the 98.4 mAP@0.5, accuracy of 98.5% for inference time of 15 ms. We validate the performance of these algorithms using images of human survivors trapped under debris and subjected to various occlusions.

Association between forensic DNA and odontology in human identification during mass disaster: a systematic review

BACKGROUND: According to the literature, forensic odontology is one of the most effective and affordable scientific techniques for identifying victims of mass disasters. This research methodically reviews the role and function of forensic odontologists in several global mass disasters. Forensic DNA in odontology is associated with the importance of its application in the identification of humans of mass disasters. As the crime rate continues to rise, the field of forensic medicine has evolved significantly. Forensic dentists play a pivotal role in various areas of crime scene investigations, thereby helping solve innumerable mysteries. AIM: The study aimed to increase the body of knowledge for future research on forensic odontology by conducting a systematic review search to investigate possible forensic DNA in odontology associated with the importance of its application in the identification of humans of mass disasters. MATERIALS AND METHODS: Six databases, including Google Scholar, PubMed, Scopus, Embase, Web of Science, and ScienceDirect, were analyzed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) quality scale. The literature search, conducted until February 2024, informed important research choices. RESULTS: A total of 16 (100%) studies related to forensic DNA of mass disasters were identified. Of these, only seven (43.75%) articles related to dental DNA were included in this review. Of the 4,808 articles obtained, 138 duplicates or irrelevant articles were eliminated. Following a full-text review, seven studies were selected based on eligibility criteria. The highest percentage of victims was identified using dental DNA. In a few studies, some samples were insufficient for complete DNA profiling due to factors such as the method of DNA extraction. CONCLUSION: Forensic odontology has played a significant role in the identification of victims of several mass disasters around the world. Although teeth are an excellent source of DNA for humans, future studies with larger sample sizes, appropriate control groups, and standardized techniques of DNA extraction need to be conducted.

Human Health Risk Assessment and Source Identification of Toxic Heavy Metals by Multivariate Tools in Groundwater

Human Health Risk Assessment and Source Identification of Toxic Heavy Metals by Multivariate Tools in Groundwater

Validation of morphological ear classification devised by principal component analysis using three-dimensional images for human identification.

This study attempts to classify ear morphology for human identification in forensic investigations by distinguishing between the upper auricle and lobule areas. A three-dimensional homologous model of the ear was created using 414 ear images of males aged 17-93 years reconstructed from computed tomography scans of forensic autopsy cases. Morphological changes were visualized using principal component analysis and areas of significant individual differences within the entire ear were identified. The classification criterion images for the upper auricle (ten images) and lobule (12 images) were developed by combining multiple principal component values: components 1-5 for the upper auricle and 1-6 for the lobule. Three-dimensional ear images of the upper auricle and lobule areas from 414 subjects were categorized using a measurement method based on the minimum distance between 5,507 corresponding points. The results indicate the applicability of the criterion images for the morphological classification of ears in this study.

A new metric method for sex estimation using three-dimensional imaging of the nuchal crest.

In Walker's nonmetric method, the nuchal crest serves as the representative region for indicating sexual dimorphism in cranial bones. However, the accuracy of sex estimation using the nuchal crest is lower than that using other anatomical regions. Furthermore, because of the protruding processes and structurally challenging features characterized by uneven and rough surfaces, there is a lack of metric methods for sex estimation, making quantification challenging. In this study, we aimed to validate a derived metric method for sex estimation by reconstructing the nuchal crest region in three-dimensional (3D) images obtained from computed tomography scans of cranial bones and compare its accuracy with that of the nonmetric method. A total of 648 images were collected, with 100 randomly selected for use in the nonmetric method. We applied our metric method to the remaining 548 images. Our findings showed that the surface area of the nuchal crests was greater in male individuals than in female individuals. The nuchal crest surface area quantified by the metric method increased the accuracy of sex estimation by 48% compared with that by the nonmetric method. Our metric method for sex estimation, which quantifies the nuchal crest surface area using 3D images of the skull, led to a high sex estimation accuracy of 93%. Future studies should focus on proposing and quantifying new measurement methods for areas showing sexual characteristics in the skull that are difficult to measure, thereby enhancing the accuracy and reliability of sex estimation in human skeletal identification across various fields.

Sibling Discrimination Using Linear Fusion on Deep Learning Face Recognition Models

Facial recognition technology has revolutionised human identification, providing a non-invasive alternative to traditional biometric methods like signatures and voice recognition. The integration of deep learning has significantly enhanced the accuracy and adaptability of these systems, now widely used in criminal identification, access control, and security. Initial research focused on recognising full-frontal facial features, but recent advancements have tackled the challenge of identifying partially visible faces, a scenario that often reduces recognition accuracy. This study aims to identify siblings based on facial features, particularly in cases where only partial features like eyes, nose, or mouth are visible. Utilising advanced deep learning models such as VGG19, VGG16, VGGFace, and FaceNet, the research introduces a framework to differentiate between sibling images effectively. To boost discrimination accuracy, the framework employs a linear fusion technique that merges insights from all the models used. The methodology involves preprocessing image pairs, extracting embeddings with pre-trained models, and integrating information through linear fusion. Evaluation metrics, including confusion matrix analysis, assess the framework's robustness and precision. Custom datasets of cropped sibling facial areas form the experimental basis, testing the models under various conditions like different facial poses and cropped regions. Model selection emphasises accuracy and extensive training on large datasets to ensure reliable performance in distinguishing subtle facial differences. Experimental results show that combining multiple models' outputs using linear fusion improves the accuracy and realism of sibling discrimination based on facial features. Findings indicate a minimum accuracy of 96% across different facial regions. Although this is slightly lower than the accuracy achieved by a single model like VGG16 with full-frontal poses, the fusion approach provides a more realistic outcome by incorporating insights from all four models. This underscores the potential of advanced deep learning techniques in enhancing facial recognition systems for practical applications.

Comparison of commercial targeted amplicon sequencing assays for human remains identification casework.

Targeted amplicon sequencing (TAS) facilitates the genotyping of forensically informative single nucleotide polymorphisms (SNPs) using massively parallel sequencing (MPS). For human remains identification, where any extracted DNA is likely to be degraded, TAS may succeed when short tandem repeat (STR) profiling using capillary electrophoresis fails. Further, as well as yielding identity information, SNPs can provide information about ancestry, phenotype, kinship and paternal lineage (Y chromosome haplotypes). Two TAS platforms were compared in this study: Ion AmpliSeq™ panels coupled with Ion Torrent sequencing on an Ion GeneStudio™ S5 Plus System, manufactured by Thermo Fisher Scientific, and the ForenSeq® Kintelligence Kit coupled with Illumina sequencing on the MiSeq FGx® Sequencing System, manufactured by QIAGEN. Four Ion AmpliSeq™ panels (Precision ID Identity, Precision ID Ancestry, DNA Phenotyping and HID Y-SNP) share 177 SNPs with the ForenSeq® Kintelligence Kit and all five were used to profile the DNA extracted from the petrous part of the temporal bone from six skeletonised cadavers. Of the 6 × 177 = 1,062 SNP genotype comparisons, 1,055 (99%) were concordant between the Ion AmpliSeq™ panels and Kintelligence Kit. Of the seven (< 1%) non-concordant SNPs, only three of them (0.3%) would have resulted in erroneous genotypes being reported as a result of allele dropout by either assay, using our optimised relative variant frequency windows for allele calling. We conclude that both the Ion AmpliSeq™ panels and the ForenSeq® Kintelligence Kit were suitable for TAS applied to the human remains in this study.

Bioinformatics analysis of immune infiltration in human diabetic retinopathy and identification of immune-related hub genes and their ceRNA networks

Diabetic retinopathy (DR) is the most common microvascular complication in diabetic patients, and recent studies have shown that immune regulatory mechanisms are closely associated with retinal damage in DR. Therefore, this study focused on exploring immune cells and immune-related genes (IRGs) in DR and gaining insight into the ceRNA mechanisms by which IRGs regulate DR progression. Four datasets from human DR model retinal tissues were obtained from the Gene Expression Omnibus (GEO) database. R software was first used to identify differentially expressed mRNAs (DE-mRNAs) in the dataset GSE160306-mRNAs, then the distribution of immune cells in the gene matrix was analyzed by xCell and ImmuCellAI, ImmPort and InnateDB database were used to obtain immune-related hub genes (IRHGs) in the DR, and finally the STRING online tool and Cytoscape to construct the immune-related ceRNA network. The datasets GSE102485, GSE160308 and GSE160306-lncRNAs were used to validate the results of the ceRNA network further. The results of immune cell infiltration analysis showed that macrophages are important immune cells in DR; immune-related gene screening showed that FCGR2B is an IRHG in DR, and 2 immune-related ceRNA networks of IRHG were obtained: DDN-AS1/miR-10a-5p/FCGR2B and LINC01515/miR-10a-5p/FCGR2B. Our study suggests that infiltration of immune cells, especially the immune role of macrophages, is an important component of DR progression; the immune-related hub gene FCGR2B and its ceRNA network may be a key regulatory network for DR progression. The discovery of key immune cells, IRHG and ceRNA networks in this study may provide new prospects for early intervention and targeted treatment of DR.