Multivariate Discriminant Function Research Articles

Sex estimation from skull measurements of a contemporary Japanese population using three-dimensional computed tomography images.

In this study, we assessed the sexual dimorphism of the contemporary Japanese skull and established sex discriminant function equations based on cranial measurements using three-dimensional (3D) computed tomography (CT) images. The CT images of 263 corpses (142 males, 121 females) that underwent postmortem CT scanning and subsequent forensic autopsy were evaluated. Twenty-one cranial measurements were obtained from 3D CT reconstructed images, which extracted only bone data. We performed descriptive statistics and discriminant function analyses for the measurements. Nineteen measurements were significantly larger in males, suggesting sexual dimorphism of the Japanese skulls. Univariate discriminant function analyses using these measurements showed a sex classification accuracy of 57.8-88.2%, and bizygomatic breadth provided the highest correct prediction rate. Multivariate discriminant function analyses offered the most accurate model using seven variables with an estimation rate of 93.9%. Our results suggest that cranial measurements based on 3D CT images may help in the sex estimation of unidentified bodies in a contemporary Japanese population.

Evaluation of circulating plasma miR-9, miR-29a, miR-192, and miR-375 as potential biomarkers for predicting prediabetes and type 2 diabetes in Nepali adult population

Circulating plasma miRNAs have emerged as potential early predictors of glucometabolic disorders. However, their biomarker potential remains unvalidated in populations with diverse genetic backgrounds, races, and ethnicities. This study aims to validate the biomarker potential of plasma miR-9, miR-29a, miR-192, and miR-375 for early detection of prediabetes and type 2 diabetes mellitus (T2DM) in Nepali populations that represent distinct genetic backgrounds, races, and ethnicities. A total of 46 adults, categorized into healthy controls (n = 25), prediabetes (n = 9), and T2DM (n = 12) groups, were enrolled. Baseline sociodemographic, anthropometric, and clinical characteristics were collected. Fold change in plasma expression of all four miRNAs was quantified using RT-qPCR against the RNU6B reference gene. Their biomarker potential was determined by receiver operating characteristic (ROC) curve analysis. Multivariate discriminant function and hierarchical cluster analyses were used to evaluate the effectiveness of the miRNA panel in reclassifying study participants who were initially categorized according to their glucose tolerance status. Plasma expression of all four miRNAs was significantly upregulated in T2DM patients compared to normoglycemic controls. Furthermore, the expression of only miR-29a and miR-375 was upregulated in T2DM patients than in prediabetic individuals. Notably, only miR-192 expression was significantly upregulated in prediabetic individuals than in the normoglycemic controls. The miRNA expression profiles had the potential of reclassifying the participants into three original groups with an accuracy of 69.6 %. ROC curve analysis identified miR-192 as the predictor for both prediabetes and T2DM, while miR-9, miR-29a, miR-192, and miR-375 were predictive only for T2DM. The specific set of miRNA combinations significantly improved their predictive accuracy. This study validates the early predictive biomarker potential of plasma miR-9, miR-29a, miR-192, and miR-375 also in the Nepali population and paves the way for future translational studies to validate their utility in clinical laboratories.

The latest steps of human evolution: What the hard evidence has to say about it?

The latest periods of human evolution are a heated topic of debate and have been at the center of paleoanthropological discussions since the beginning of the field. In the last twenty years, new excavations increased the geographic range of paleoanthropological data, new fossil hominins of the last third of the Pleistocene were found, and old key fossils were redated by modern and more accurate methods. The new picture emerging from this research changed the discussion about the neandertal-sapiens interaction, the finding of their common ancestor, and the understanding of how our lineage evolved. To integrate these new discoveries and to better contextualize how they fit in the hominin framework of the Chibanian, we compared the cranial morphology of 86 well-preserved fossils from Europe, Africa, and Asia of the last 500 thousand years. 25 linear measurements were used to describe the cranial morphology of the fossils, and their biological affinities were explored though multivariate discriminant function analyses. These analyses allow us to assess affinities and possible phylogenetic relationships of Archaic Homo species, including the expressive morphological variability of the specimens included under the umbrella-term “Homo heidelbergensis” from Africa, Asia, and Europe. Our results support that cannot be accommodated in one same species. Additionally, we contribute to the disputable discussion about the origin of H. sapiens, adding support to an African origin for our species.

Evaluating the patella bone for sex estimation in Northwest Indian subjects: A radiological study

ObjectivesIn forensic identification, pelvis, post cranial bones especially long bones and skull are considered best for sex estimation. But there are circumstances where these bones cannot be recovered for establishing the correct biological profile of unknown human skeletal remains. In those cases, other skeletal bones should be investigated for sex estimation. The goal of the present study was to validate whether the patellar bone measurements through CT scan can be used for the sex estimation in Northwest Indian subjects. Materials and methodsThis study comprises of 344 subjects (179 males and 165 females) between the age group of 18- 80 years. Eight variables of patella were selected in the study for sex estimation using CT scan images of patella. ResultsAll the variables were statistically significant with p-value< 0.05 for indicating the sex. Univariate and multivariate discriminant function analysis (direct and stepwise method) were applied for sex estimation. The overall accuracy rate of classifying sex was 88.4% for multivariate stepwise discriminant function analysis and 87.8% for multivariate direct discriminant function analysis. Total perimeter of patella (TPP) was found to be the best variable for sex estimation with overall accuracy rate of 84.9%. ConclusionThe present study emphasized on the most dimorphic variables of patella in Northwest Indian subjects. New variables of patella namely Patellar Femoral Distance (PFD), Patellar Apex Angle (PAA), Frontal Surface Area of patella (FSA) and Total Perimeter of Patella (TPP) were added in the study of Indian subjects. This brought an overall accuracy rate of classification above 85%. The study confirmed that patellar bone's linear and angular measurements can be used for forensic identification casework.

Cranio-facial bones evaluation based on clinical CT data for sex determination in Northwest Indian population

The skull and pelvis have been the first choice of bones for determination of unknown human remains. The goal of the present study was to derive discriminant function equations by using clinical CT scan data of cranio-facial bones for sex determination in Northwest Indian population. This study was conducted at Department of Radiology, by collecting the retrospective data of CT scan of 217 samples. In the data, 106 were males and 111 were females in the age group between 20 and 80 years. The total number of parameters under investigation were 10. All the selected variables were sexually dimorphic and showed significant values. 91.7% of original grouped cases were correctly classified to their sex category. The TEM, rTEM and R were under the acceptable limits. The univariate, multivariate and stepwise discriminant function analysis recorded an accuracy of 88.9%, 91.7% and 93.6% respectively. Multivariate direct discriminant function analysis stepwise method yielded the highest level of accuracy in differentiating males and females. All the variables reflected statistically significant difference between males and females (p less than 0.001). The best single parameter with highest level of sexual dimorphic trait was length of cranial base. This study aims to provide sex assessment using clinical data of CT scan in Northwest Indian population by incorporating the BIOFB cranio-facial parameter. The morphometric measurements taken on CT scan images can be utilized by forensic experts in identification process.

Machine learning and discriminant function analysis in the formulation of generic models for sex prediction using patella measurements

Sex prediction from bone measurements that display sexual dimorphism is one of the most important aspects of forensic anthropology. Some bones like the skull and pelvis display distinct morphological traits that are based on shape. These morphological traits which are sexually dimorphic across different population groups have been shown to provide an acceptably high degree of accuracy in the prediction of sex. A sample of 100 patella of Mixed Ancestry South Africans (MASA) was collected from the Dart collection. Six parameters: maximum height (maxh), maximum breadth (maxw), maximum thickness (maxt), the height of articular facet (haf), lateral articular facet breadth (lafb), and medial articular facet breath (mafb) were used in this study. Stepwise and direct discriminant function analyses were performed for measurements that exhibited significant differences between male and female mean measurements, and the “leave-one-out” approach was used for validation. Moreover, we have used eight classical machine learning techniques along with feature ranking techniques to identify the best feature combinations for sex prediction. A stacking machine learning technique was trained and validated to classify the sex of the subject. Here, we have used the top performing three ML classifiers as base learners and the predictions of these models were used as inputs to different machine learning classifiers as meta learners to make the final decision. The measurements of the patella of South Africans are sexually dimorphic and this observation is consistent with previous studies on the patella of different countries. The range of average accuracies obtained for pooled multivariate discriminant function equations is 81.9–84.2%, while the stacking ML technique provides 90.8% accuracy which compares well with those presented for previous studies in other parts of the world. In conclusion, the models proposed in this study from measurements of the patella of different population groups in South Africa are useful resent with reasonably high average accuracies.

Characterization of Echolocation Calls from Insectivorous Bats in Puting Bato Cave 5, Burdeos, Polillo Island, Philippines

Acoustic recording is rarely applied in studying Philippine bats, which is reflected by the scarcity of related publications in the country. As a result, the echolocation calls of many local bat species are still unknown, and a reliable bat call library does not exist. Here, we described the echolocation call of some insectivorous bats in Polillo Island and used the call characteristics to define each species. We captured and recorded the echolocation calls of cave-dwelling bats in Puting Bato Cave 5 in October and November 2019. Using BatSound, we measured the spectral and temporal call characteristics and determined the call structure and duty cycle of all recorded individuals. Then, we applied multivariate discriminant function analysis (DFA) to classify the calls into species and identify the call parameter with the highest discriminating power. In total, we recorded 104 individual bats from five species belonging to four families. All species from families Miniopteridae and Vespertilionidae produced steep frequency-modulated (FM) sweeps, while the species belonging to families Hipposideridae and Rhinolophidae emitted calls with constant frequency and FM components. Among the recorded species, Hipposideros coronatus had the highest peak frequency record (&gt; 150 kHz), while Myotis macrotarsus had the lowest (&lt; 40 kHz). Meanwhile, the longest call duration was recorded from Rhinolophus arcuatus (&gt; 40 ms), while Miniopterus paululus produced the shortest call (&lt; 3 ms). The DFA perfectly classified the calls into the correct species and peak frequency was the most important predictor among the call parameters measured. Our results provide strong evidence that insectivorous bats in Puting Bato Cave 5 produce species-specific echolocation calls, and acoustic recording can be a reliable method to enhance research on these cave-dwelling bats

Virtual Morphometry of the First Lumbar Vertebrae for Estimation of Sex Using Computed Tomography Data in the Turkish Population

IntroductionIt may be necessary to make sex estimation by examining other bones that have been obtained intact. Vertebrae, especially the thoracic and lumbar vertebrae, are among the best-preserved skeletal elements from the forensic and archaeological point of view. Therefore, lumbar vertebrae can become an important skeletal element for sex estimation. In our study, measurements were made on the CT images of the first lumbar vertebra, and the accuracy of sex estimation from the L1 vertebra was investigated in the Turkish population.Materials and methodsThree dimensional (3D) models of the L1 vertebra were created from CT images of 241 (121 females and 120 males) individuals. Twenty-two linear measurements were taken in lateral, anterior, and superior views of 3D models of the L1 vertebra. Univariate and multivariate discriminant function analyzes were applied to the measured parameters to determine predictive rates of sex. Intra- and interobserver errors were calculated.Results All linear measurements were higher in males than females. All parameters excluding SCD (Spinal canal depth), PLu (Upper pedicle length), PLI (Lower pedicle length), AHi (Inferior articular process height), and SPH (Spinous process height) showed statistically significant differences between sex. The highest rate of 70.5% was obtained for the EPWu (Upper end-plate width) and EPWl (Lower end-plate width) parameters. When all variables of L1 vertebra were included in the stepwise discriminant analysis, correct prediction rates were determined as 72.6%.ConclusionOur study is the first study in which L1 vertebrae are examined with the purpose of sex estimation in the Turkish population and we think that our data will be an important reference for sex estimation from the L1 vertebra in the Turkish population.

Assessing the Validity of Mojave Desert Lake Mohave and Silver Lake Projectile-Point Types

ABSTRACT This study uses univariate and multivariate statistical analyses to assess whether Lake Mohave and Silver Lake projectile points from the Mojave Desert of western North America are statistically discrete, recognizable, and valid types. Univariate analyses run on 400 Lake Mohave and Silver Lake points reveal significant differences in six linear and three angle measures, though overlapping measurements pose difficulties for differentiating the types. To address the problem of overlapping measurements, multivariate principal components and discriminant function analyses were employed to statistically define groups of related attributes. Size- and shape-based attributes of the stem distinguish approximately 80% of the sample to type and reveal region-wide consistency among archaeologists who have classified these points to type. Though this study did not entirely overcome the challenge of using metrics to differentiate Lake Mohave from Silver Lake points, key discriminating variables are now better defined and the types deemed valid.

Sex estimation in a Turkish population using Purkait’s triangle: a virtual approach by 3-dimensional computed tomography (3D-CT)

Sex estimation is considered one of the first steps in the forensic identification process. Morphological and morphometrical differences between males and females have been used as means for morphoscopic and metric methods on both cranial and postcranial skeletal elements. When dry skeletal elements are not available, virtual data can be used as a substitute. The present research explores 3-dimensional (3D) scans from a Turkish population to test a sex estimation method developed by Purkait (2005). Overall, 296 individuals were used in this study (158 males and 138 females). Purkait’s triangle parameters were measured on computed tomography (CT) scans obtained from both right and left femora of each patient at the Bakirkoy Dr. Sadi Konuk Training Research Hospital (Istanbul, Turkey). Intra- and inter-observer errors were assessed for all variables through technical error of measurements analysis. Bilateral asymmetry and sex differences were evaluated using parametric and non-parametric statistical approaches. Univariate and multivariate discriminant function analyses were then conducted. Observer errors demonstrated an overall agreement within and between experts, as indicated by technical error of measurement (TEM) results. No bilateral asymmetries were reported, and all parameters demonstrated a statistically significant difference between males and females. Fourteen discriminant models were generated by applying single and combined parameters, producing a total correct sex classification ranging from 78.4% to 92.6%. In addition, over 67% of the total sample was accurately classified, with 95% or greater posterior probabilities. Our study demonstrates the feasibility of 3D sex estimation using Purkait’s triangle on a Turkish population, with accuracy rates comparable to those reported in other populations. This is the first attempt to apply this method on virtual data and although further validation and standardisation are recommended for its application on dry bone, this research constitutes a significant contribution to the development of population-specific standards when only virtual data are available. Key points CT analysis using Purkait’s triangle is a suitable tool for assessment of sex in unidentified individuals. The best overall estimation rate was achieved with the F11 model, with around 92% of accuracy. The results suggested 78.4% to 92.6% correct sex identification rates. More research is needed to expand the sample set and verify the results.

Identification of sex using discriminant function analysis of fingerprint ridge density at three topological areas among North Indian population

The present study attempted to identify sex of an individual using a fingerprint ridge density at three topological areas in the North Indian population. The study population consisted of 134 males and 136 females aged 17 to 25 years (mean age 19.34±2.12). Ridge density (RD) at radial, ulnar and proximal topological areas of the distal phalanges were determined on the surface area of 25mm2. Fingerprint ridge density in a defined area was significantly higher among females as compared to their male counterparts at radial, ulnar and proximal topological areas for both hands. Sexual dimorphic ratio also supported this trend for all three counting areas in right and left hands. Univariate discriminant function analysis explained that the left 2 radial (L2R) (88.1%) had the highest percentage of accuracy for sex identification, followed by the left 3 ulnar (L3U) (82.1%) and the right 2 ulnar (R2U) (81.6%). Multivariate discriminant function analysis showed that the radial topological area of the left hand was the best predictor of sex with the overall accuracy of 84.4%with following discriminant function equation −8.263 − 0.236(L1R) + + 0.321(L2R) + 0.269(L3R) + 0.268(L4R) − 0.067(L5R).&#x0D; It can be inferred that ridge density in the radial topological area of left hand is the most reliable tool for identifying the sex of an individual.

Anthropometric characteristics of patella for sex estimation using magnetic resonance images

• The sexual diagnostic accuracy of patella for transverse, craniocaudal and antro-posterior lenght were 84.5%, 75.2% and 65.8% respectively. • The maximum transvers and craniocaudal lenghts were selected in the stepwise with an average accuracy of 85.7% in correct sex clasification. • Measuring the patella dimensions by the MRI method can be effective for sex estimation with good accuracy in the Iranian population. Sex estimation of skeletal remains is an essential step in forensic anthropology since. In this study, sex estimation with patella metric parameters obtained from Magnetic resonance imaging ( MRI ) of an Iranian population, which consists of 161 living subjects (79 males, 82 female) aged between 30 – 50 years, is performed. Univariate discriminant analysis and multivariate discriminant function analysis are used for three measurements on the patella (transverse length, craniocaudal length, and anterioposterior length) in this study. The diagnostic accuracy of patella sex estimation for transverse, craniocaudal and Anterior-posterior lengths were %84.5, %75.2 and %65.8, respectively. In the discriminant analysis, the maximum transverse length and maximum craniocaudal length were selected in the stepwise analysis with an average accuracy of 85.7% in correct sex classification. In conclusion, measuring the patella dimensions by the MRI method can be effective for Sex estimation with good accuracy in the Iranian population.

Sex estimation in a modern Turkish population using the clavicle: a computed tomography study

ABSTRACT Morphometric analysis of the clavicle is a potential source of useful data for the estimation of sex. Clavicle is often retrieved intact from decomposed and scavenged remains when pelvis and skull, essential sex indicators, are often found damaged or missing. The objective of this study is to analyse clavicle morphometric data for sex estimation in a Turkish population. Computed tomography (CT) scans of the thorax of two hundred Turkish adult patients (71 male and 81 female patients with an age range of 22–80 years) were included. Furthermore, morphometric data for the left clavicle using two-dimensional (2D) and three-dimensional (3D) clavicle CT images were obtained, and six variables were measured in the clavicle images. Univariate and multivariate discriminant function analysis (DFA) was used to create population-specific functions for sex estimation. The classification accuracy for the cross-validated data ranged from 75% to 89% in the uni- and multivariate DFA. Stepwise discrimination analysis yielded an 89% accuracy rate for the maximum length and midshaft circumference variables. The study showed that the clavicle can provide useful data for estimating sex in a modern Turkish population and that when there is difficulty accessing bone collections, CT scans can provide useful data for sex estimation.

SEX DETERMINATION FROM DISCRIMINANT FUNCTION ANALYSIS OF CEPHALOMETRIC MEASUREMENTS OF BROKPAS AND PURIGPAS OF LADAKH (UT): A FORENSIC ANTHROPOLOGICAL STUDY

Forensic anthropology involves diverse applications of anthropological knowledge to medico-legal problems like human identification based on sex determination, age estimation, stature reconstruction and deciphering ancestry of unknown living individuals or skeletal remains. Sex can be determined by using different body parts such as extremities (legs and arms) parameters, head, face, clavicle, and others parameters. In present cross-sectional study, cephalometric dimensions of 800 Ladakhi subjects (431 males and 369 females) of Purigpas and Brokpas ancestry were taken. Descriptive statistics of cumulative cephalometrics in two sexes revealed that all the measurements were significantly larger in males than the females (p<0.001). Statistically significant sex differences were found in the various anthropometric, cephalometric and morphological features of Brokpas and Purigpas of Kargil (Ladakh, UT). Univariate discriminant function analysis found head length as the best cephalofacial variable to estimate sex of 73.4% individuals; followed by physiognomic facial length to estimate sex of 71% subjects. From multivariate discriminant function analysis, the physiological facial length, head length, nasal breadth, head circumference, nasal height, bizygomatic breadth, length of right ear and left ear breadth were selected as the best variables to correctly classify sex of 83.8% individuals to their category (81.9% males and 85.9% females). The present study results are the only cephalometric standards which have been suggested for Purigpas and Brokpas of Ladakh (Jammu and Kashmir) which can be used for medico-legal sex determination of unknown individuals of studied population.

Sex estimation from upper limb bones in a Thai population.

Sex estimation from skeletal remains is an important practice for forensic human identification. The aims of this study were to assess sexual dimorphism and to develop discriminant function equations for sex estimation using 12 measurements of upper limb bones (humerus, ulna, and radius) in a Thai population. The sample consisted of 228 Thai skeletons (114 males and 114 females) from the Forensic Osteology Research Center, Chiang Mai University, Chiang Mai, Thailand. All skeletal length variables were measured according to the Standards for Data Collection from Human Skeletal Remains. The values of measurements were used to develop the sex estimation equations using univariate and multivariate discriminant function analyses. The results of sexual dimorphism showed that upper limb bone lengths of males were statistically significantly longer than those of females in all dimensions (P<0.05). For univariate discriminant function analysis, the results showed that the epicondylar breadth of the humerus, the physiological length of the ulna, and the antero-posterior diameter at the midshaft of the radius were the best indicators for sex estimation in the humerus, ulna, and radius, respectively. Moreover, the multivariate discriminant function equation using all variables of the ulna and radius was the best indicator for sex estimation. In conclusion, the discriminant function equations derived from upper limb bone measurements provided highly accurate sex estimation in Thai samples. Therefore, these equations using humerus, radius, and ulna measurements can be applied for sex estimation with good accuracy in Thais.

Assessing zygomatic shape and size for estimating sex and ancestry in a South African sample

Unidentified, decomposed and skeletonised human remains are frequently found in South Africa, therefore, standardised, reliable and relevant sex and ancestry estimation methods are required for forensic identification. This study assessed sex and ancestral variation in zygomatic size and shape in a South African population using geometric morphometric analyses. The zygoma of 158 South African individuals were sampled. Eight zygomatic landmarks were captured in 3-dimensions using a Microscribe G2 digitiser and assessed using procrustean geometric morphometrics. Shape and size differences were analysed using multivariate linear regression, discriminant function and canonical variate analyses. Males had significantly larger zygomas than females. Significant shape variation was found between ancestral groups. Bantu-speaking and Mixed ancestry individuals had narrower, shorter and more anteriorly projecting orbital margins, whilst Europeans had vertically elongated and receded orbital margins. European ancestral groups were most discernible from Bantu-speakers and Mixed ancestral groups. Ancestry estimation accuracies improved when ancestry was aggregated with sex. Pairwise ancestry-linked comparisons in females were as follows; Bantu-speakers (76%) from Europeans (72%), Bantu-speakers (71%) from Mixed ancestry (59%) and European (72%) from Mixed ancestry (63%). Similarly, ancestry-linked comparisons in males were as follows; Bantu-speakers (77%) from Europeans (81%), Bantu-speakers (53%) from Mixed ancestry (59%) and European (72%) from Mixed ancestry (82%). Size differences are putatively linked to variations in hormone-regulated growth and muscular robusticity between males and females. Shape variations between ancestral groups are likely attributable to the heterogenous genetic and ancestral origins of the South African population. It is challenging to distinguish between South Africa Bantu speakers and Mixed ancestry people due to Mixed ancestry individuals having variable genetic contributions from Khoesan, Bantu-speakers, Europeans and Asians. Bantu-speaking and Mixed ancestry people had zygomatic morphologies consistent with historical thermoregulatory adaptations to sub-Saharan climates, reported in African-descendants. Zygomatic morphology in European descendants suggests ancestral origins from colder climatic regions. This study demonstrated the utility of the zygoma in distinguishing between ancestral groups in South Africa, but further research is required to develop population-specific standards to distinguish between South African populations with shared African ancestry. The zygoma shows a promising ability to estimate sex and ancestry in South Africans, suggesting population specific standards for this bone may be of forensic interest.

Sex estimation from handprints in a Croatian population sample

Aim: To test if handprint measurements show sexual dimorphism in the Croatian population, and to develop population-specific sex estimation standards. Methods: A cross-sectional study was conducted on 100 adult volunteers from a Croatian population (50 males and 50 females) aged between 20 and 45 years. Using a fingerprint ink, we collected handprints of both hands on a paper sheet. We scanned handprints and took 13 measurements. Bilateral asymmetry and sexual dimorphism of the measurements was analyzed and sex estimation models were developed using linear discriminant analysis. Results: All measurements exhibited statistically significant sexual dimorphism (P&amp;lt;0.001). Univariate discriminant functions provided sexing accuracy from 75% to 92%. The highest accuracy rate (92%) and the lowest sexing bias (0%) was obtained using the handprint breadth. A multivariate discriminant function could estimate sex with 93% accuracy, but with more pronounced sexing bias (10%). Conclusion: We showed that handprint measurements could be used for sex estimation in the Croatian population with a high accuracy level. Therefore, they could serve as a valuable tool for biological profiling of perpetrators in criminal investigations when other evidence is not conclusive.

Forensic odontological sex determination of Ajnala skeletal remains based on the statistical equations generated from the odontometrics of known teeth

Anthropological techniques are evolving and expanding continuously to decode and interpret the hidden information embedded within human skeletal and dental remains as biological language. Various studies have been reported for sex estimation from odontometric features of the teeth found in forensic or bio-archaeological contexts. Though the accuracy levels of such methods is just close to forensic thresholds, they serve as significant adjuncts to identity assessments from other methods. Thousands of bones and teeth were excavated from a disused well found situated underneath a religious structure at Ajnala (Amritsar, India) in April 2014. In the present study, the sex of unknown molar teeth retrieved from Ajnala skeletal assemblage was estimated using the customized discriminant and logistic regression formulas generated from the odontometrics of known teeth collected from Northwest Indian subjects. Five hundred and eleven mandibular molars (254 modern and 257 Ajnala human teeth) were measured for eight buccolingual and mesiodistal diameters at different levels. The multivariate discriminant and logistic regression equations were developed from odontometrics of known teeth to classify 75.4% and 76.1% teeth to their sex category, respectively. These equations were applied to odontometrics of Ajnala teeth and their D-estimates were calculated. It was found that 83% and 96% Ajnala teeth were identified to be of males from the multivariate logistic regression and discriminant function analysis, respectively. It corroborated the written versions about the Ajnala skeletal remains belonged to male soldiers killed in 1857 by the colonial rulers.

Sex estimation by Mastoid Triangle using 3D models.

Mastoid Triangle (MT) is a triangle constructed between the landmarks porion, mastoidale and asterion. The aim of the study is to evaluate the sex differences in the MT size in Bulgarian adults and to develop discriminant functions for sex estimation based on the MT sides and area. The study was carried out on 148 head CT scans. A sample of 53 males and 53 females was used for development of discriminant functions, and a test sample of 21 males and 21 females was applied for their validation. Using the software InVesalius©, 3D models of the skulls were segmented and exported in STL format. The 3D coordinates of the landmarks porion, asterion and mastoidale were collected using the software MeshLab©. The MT sides, area and angles were calculated. The sex differences were assessed by the independent t-test. Bilateral differences were evaluated using the paired t-test. Univariate and multivariate discriminant function analyses were applied. The results showed that the MT sides and area differed significantly between both sexes. Sex differences were also established for the angle at mastoidale. Bilateral differences were found in males for the distance porion-mastoidale, which was significantly greater on the right side. The MT dimensions showed sufficient discriminating power for sex estimation among Bulgarians (up to 89%), and the total MT area proved to be the best single sex discriminating trait. The test sample corroborated the usefulness of the MT in sex estimation demonstrating similar or higher overall accuracy rates.

An Intelligent Automatic Fault Detection Technique Incorporating Image Processing and Fuzzy Logic

Fault detection is considered an important and challenging task to be incorporated in many industrial applications. It has gained interest in recent years, and many techniques have been proposed for developing an effective fault detection approach due to its significant importance in everyday life. This study presents an automated intelligent fault detection technique incorporating image processing and fuzzy logic. Image processing is the first step where features such as entropy estimation, color-based segmentation and depth estimation from gradients are obtained. The extracted features (number of {blobs, minima, maxima}, and estimated entropy) act as input to the fuzzy logic. The subsequent step incorporates fuzzy logic; the four inputs are fed to fuzzy which extract the fault and acts as knowledge rule-based tool and final step, i.e. the output generation, classifies it accordingly into four categories of faults (rust, bumps, hole, wrinkles/roller marks). The proposed method is compared with Linear Vector Quantization, and Multivariate Discriminant Function approaches. The method is tested on a database of 150 images. The proposed method demonstrated its significance and effectiveness with performance accuracy of 99%, 98%, 96.8% and 97.6% for rust, bumps, holes and wrinkles/roller marks respectively.