The great ethnolinguistic diversity found today in mainland Southeast Asia (MSEA) reflects multiple migration waves of people in the past. Maritime trading between MSEA and India was established at the latest 300 BCE, and the formation of early states in Southeast Asia during the first millennium CE was strongly influenced by Indian culture, a cultural influence that is still prominent today. Several ancient Indian-influenced states were located in present-day Thailand, and various populations in the country are likely to be descendants of people from those states. To systematically explore Indian genetic heritage in MSEA populations, we generated genome-wide SNP data (using the Affymetrix Human Origins array) for 119 present-day individuals belonging to 10 ethnic groups from Thailand and co-analyzed them with published data using PCA, ADMIXTURE, and methods relying on f-statistics and on autosomal haplotypes. We found low levels of South Asian admixture in various MSEA populations for whom there is evidence of historical connections with the ancient Indian-influenced states but failed to find this genetic component in present-day hunter-gatherer groups and relatively isolated groups from the highlands of Northern Thailand. The results suggest that migration of Indian populations to MSEA may have been responsible for the spread of Indian culture in the region. Our results also support close genetic affinity between Kra-Dai-speaking (also known as Tai-Kadai) and Austronesian-speaking populations, which fits a linguistic hypothesis suggesting cladality of the two language families.

Background/Objectives: Determination of the biological profile, particularly sex and stature, constitutes an essential component for individual identification in forensic and archaeological anthropology; however, validation of anthropometric equations remains inadequately implemented in contemporary research. This study addresses two limitations: the isolated development of sex and stature estimation methods and the lack of rigorous validation using independent samples. Methods: In this research, we analyzed 400 well-preserved scapulae from a Northeastern Thai population divided into training (n = 300: 150 male scapulae, 150 female scapulae) and validation (n = 100: 50 male scapulae, 50 female scapulae) groups. Eight standardized measurements were used for both sex and stature estimation. Results: All measurements demonstrated significant sexual dimorphism, with males exhibiting larger dimensions. For sex estimation, a multivariate model incorporating the maximum scapular height, maximum length of the spine, and scapula weight achieved 96.3% accuracy in the training samples and maintained 95.0% accuracy in independent validation. For stature estimation, a three-variable equation combining scapula weight, longitudinal scapular length, and maximum scapular breadth was strongly correlated (R = 0.769, SEE = 5.32 cm) with consistent performance across validation samples. Conclusions: Validation testing confirmed the high accuracy, reliability, and stability of both equations when applied to independent samples, with no significant differences in performance metrics between training and validation groups. These validated equations provide reliable standards for forensic practitioners analyzing scapular remains in practical applications within the northeastern Thai population.

Background: Sex estimation from skeletal remains is important for forensic identification, but many methodologies focus on complete elements despite high fragmentation rates in operational contexts. The aim of this study was to develop and validate discriminant function equations for sex estimation between complete and fragmented Thai femora. Materials and Methods: A total of 560 adult femora (280 males and 280 females) were used for measurements of eight osteometric variables. Then, discriminant function analysis was applied to complete femora and anatomically isolated segments, including proximal, diaphyseal, and distal, with leave-one-out cross-validation. Results: All measurements showed significant sexual dimorphism, with percentage differences ranging from 6.56% to 42.27%. Complete femur stepwise analysis achieved 90.47% accuracy by using four optimally selected variables, performing comparably to eight-variable models. Isolated segment accuracies varied substantially: proximal segments achieved 89.64% accuracy, differing by only 0.83 percentage points from complete performance; distal segments demonstrated 86.25% accuracy from bicondylar width alone; and diaphyseal segments achieved 80.88%. Combined segment approaches demonstrated synergistic effects approaching complete femur performance. Conclusions: These population-specific equations provided validated methodologies for sex estimation from complete and fragmentary Thai femora. Anatomical region selection still maintained high classification accuracy despite skeletal incompleteness, in line with the fragmentary conditions commonly encountered in forensic and archeological contexts.

Background/Objective: Sex estimation from cranial remains is essential in forensic biological profile reconstruction, yet systematic comparisons of statistical classifiers under formally verified assumption conditions remain limited in Thai populations. This study aimed to develop and validate sex estimation models from craniofacial measurements in a Northeastern Thai skeletal sample using DFA, BLR, and SVM, and to examine whether distributional assumption violations influence classifier performance and generalizability under holdout validation. Methods: Eight linear craniometric parameters connecting five osteometric landmarks were measured in 300 adult skeletal specimens (150 males, 150 females) from the Unit of Human Bone Warehouse for Research, Khon Kaen University. Specimens were allocated into a training dataset (n = 200) and a holdout dataset (n = 100). Five multivariate model configurations were developed under direct-entry and stepwise parameter-entry strategies. Formal assumption diagnostics included Shapiro–Wilk normality testing, Levene’s test, Box’s M test, and variance inflation factor analysis. Results: All parameters demonstrated excellent interobserver reliability and significant sex-based differences (p < 0.01), with males recording larger mean values throughout. Apparent multivariate accuracy ranged from 78.0% to 85.5%. Holdout validation revealed consistent performance decline across all five configurations, with accuracy reductions of 3.0 to 9.5 percentage points and AUC reductions of 0.042 to 0.079. The stepwise DFA model showed the smallest overall accuracy decline, although this apparent stability reflected an uneven sex-specific trade-off, with a specificity decline offset by a sensitivity gain, while SVM and DFA direct-entry models showed the largest decline. Conclusions: Craniofacial measurements provide moderate discriminatory capacity for sex estimation in Northeastern Thai skeletal remains. Although univariate assumption violations were observed, DFA’s performance remained comparable to BLR and SVM under the present large, balanced sample; multivariate analysis or distributional assumption-free methods offer practical alternatives where violations are present. Apparent performance alone is insufficient to establish forensic reliability, and holdout validation should be regarded as a necessary component of sex estimation model development.