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Mimicry, where an organism (the mimic) convergently evolves traits resembling another (the model), is one of the most compelling phenomena in evolutionary biology. Despite ants frequently serving as models for Batesian mimics in other arthropod taxa, mimicry among ants is still underexplored. Rapid mimetic adaptations may superficially suggest a pathway to speciation; therefore, a thorough exploration of the phenomenon requires multivariate analyses. Consequently, we collected morphometric data from Colobopsis samples across the Mediterranean Basin and the Caucasus, documented color patterns of mimics and local models, and performed unsupervised multivariate analyses to examine evolutionary dynamics in the Mediterranean Colobopsis mimicry system. Our central questions were whether adaptive color changes in regional mimic populations reflect distinct evolutionary lineages leading to speciation or represent intraspecific responses to local environmental pressures, that is, adjustment to locally available models. We sought morphometric discontinuities in morphospace that might indicate the existence of distinct lineages among mimic populations with different color schemes. Biogeographic analyses show that Colobopsis imitans Schifani et al., 2022 replaces Colobopsis truncata (Spinola, 1808) throughout southern Europe and displays remarkably versatile region‐specific mimetic visual adaptations to local model species—hence the title analogy; this species is a true chameleon, in a biogeographical sense. Our research presents a scenario where mimicry‐driven microevolutionary adaptations can produce significant phenotypic diversity without leading to speciation. We collected morphometric data from Colobopsis samples across the Mediterranean Basin and the Caucasus, documented color patterns of these mimics and their local models, and performed unsupervised multivariate analyses. Morphometric data suggest a scenario where mimicry‐driven microevolutionary adaptations can produce significant phenotypic diversity without leading to speciation. Biogeographic analyses show that Colobopsis imitans displays remarkably versatile region‐specific mimetic visual adaptations to local model species.

Background Undernutrition is a serious health problem and highly prevalent in developing countries. There is no as such confirmatory test to measure undernutrition. The objective of the present study is to determine a new Composite Score using anthropometric measurements. Composite Score was then compared with other methods like body mass index (BMI) and mid-upper arm circumference (MUAC) classification, to test the significance of the method. Methods Anthropometric data were collected from 780 adult Oraon (Male = 387, Female = 393) labourers of Alipurduar district of West Bengal, India, following standard instruments, and protocols. Nutritional status of the study participants were assessed by conventional methods, BMI and MUAC. Confirmatory factor analysis was carried out to reduce 12 anthropometric variables into a single Composite Score (C) and classification of nutritional status was done on the basis of the score. Furthermore, all the methods (BMI, MUAC and C) were compared and discriminant function analysis was adopted to find out the percentage of correctly classified individuals by each of the three methods. Result The frequency of undernutrition was 45.9% according to BMI category, 56.7% according to MUAC category and 51.8% according to newly computed Composite Score. Further analysis showed that Composite Score has a higher strength of correct classification (98.7%), compared to BMI (95.9%) and MUAC (96.2%). Conclusion Therefore, anthropometric measurements can be used to identify nutritional status in the population more correctly by calculating Composite Score of the measurements and it is a non-invasive and relatively correct way of identification.

Dimensions of the pelvic and skull bones are known to be sexually dimorphic in various population groups. The recovery of these bones is potentially beneficial in estimating the sex in forensic cases. Since both bones are not always available for forensic analysis, standards for sex estimation must be established for other bones of the postcranial skeleton. Previous studies have reported that postcranial skeletal elements (e.g. femur) perform like the pelvis and better than the cranium in sex estimation. Thus, this study explored the potential of CT-derived femoral measurements in sex estimation in a South African population. The sample consisted of 280 contemporary Black South Africans (50% sex ratio) whose scan reports are stored in the Radiology Department of Charlotte Maxeke Johannesburg Academic Hospital, Johannesburg, South Africa. The Xiris and IntelliSpace software was used to reconstruct the images into 3D formats from which measurements were taken. Previously derived sex estimation equations of the femur were tested using data from the current study and these equations presented low average classification accuracies. Using discriminant function and logistic regression analyses, new sex estimation equations were formulated, and these new equations yielded average sex estimation classification accuracies of between 82.5 and 91.4% (by multivariable logistic regression) and 79.3–84.3% (by multivariable discriminant function). The results indicate that population-specific femoral measurements obtained by CT are more reliable than those obtained by direct osteometry and that the femur has a high sexual dimorphism with relevant forensic applications.

Sex estimation is an essential step in the process of the identification of the skeletal remains in forensic anthropology since it reduces the number of possible matches by half. In this study, sex estimation with 21 sacral and coccygeal metric parameters obtained from Computerized Tomography images of a Turkish population which consists of 480 patients that are equalized according to their sexes and ages, is performed. Univariate discriminant analysis, linear discriminant function analysis, stepwise discriminant function analysis, and multilayer perceptron neural networks are used in this study. A maximum of 67.1% accuracy for univariate discriminant analysis, 82.5% for linear discriminant function analysis, 78.8% for stepwise discriminant function analysis, and 86.3% for multilayer perceptron neural networks, were achieved. Although it does not reach an acceptable accuracy rate of 95% or more for sacrum and coccyx, sex estimation with neural networks is a promising field of research in corpses where identification is otherwise not possible, and further studies with other bones and with new techniques might give useful information.

The morphological variation in Schizothorax oconnori, Schizothorax waltoni, and their natural hybrids was examined using conventional and image‐based analysis approaches. In total, 38 specimens of S. oconnori, 35 of S. waltoni, and 37 natural hybrids were collected from the Shigatse to the Lhasa section of the Yarlung Zangbo River during June and July 2021. A total of 21 morphometric, 4 meristic, and 27 truss variables were employed for the classification of S. oconnori, S. waltoni, and natural hybrids. Principal component analysis (PCA) and factor analysis (FA), as well as discriminant function analysis (DFA) and cluster analysis (CA), were conducted to identify differences based on traditional and truss measurements. Four principal components explained 75.92% of the variation among the morphometric characters, while five principal components accounted for 79.69% of the variation among the truss distances. FA results showed that factor 1 was associated with head shape, and factor 2 was associated with fins based on morphometric characters. Among the truss characters, factor 1 was related to head shape, and factor 2 was related to chest shape. In DFA, morphometric measurements achieved higher accuracy (100%) compared to truss distances (94.55%). The head morphology of hybrids exhibited intermediate traits between S. oconnori and S. waltoni. Both morphometry‐based and truss‐based clustering indicated that the morphology of natural hybrids leaned toward S. oconnori. In conclusion, the combination of morphometric and truss analysis is beneficial for classifying S. oconnori, S. waltoni, and their natural hybrids. The presence of natural hybrids could be considered an evolutionary response to the differentiation of nutritional and spatial niches in the middle Yarlung Zangbo River. The combination of morphometric and truss analysis is beneficial for classifying Schizothorax oconnori, Schizothorax waltoni, and their natural hybrids. The presence of natural hybrids could be considered an evolutionary response to the differentiation of nutritional and spatial niches in the middle Yarlung Zangbo River.

The accurate identification of locomotion states from wearable sensor data using machine learning relies heavily on carefully selecting algorithm parameters, which remains a challenging task. This study systematically optimised key parameters—including window length, sampling frequency, temporal resolution, overlapping value, and normalisation effects—to enhance the accuracy of machine learning models for distinguishing different locomotor tasks. Our study was conducted on participants ( N  = 35, 19 ♂10 ♀, 27.4 ± 26.5 years, 1.74 ± 0.8 m, 71.5 ± 11.3 kg) who wore accelerometers on the sacrum, thighs and shanks. Principal component and discriminant function analyses were applied to acceleration data from three locomotor tasks: self-selected slow, normal and fast walking. The parameters explored for the optimisation of the algorithm were accelerometer window length, sampling frequency, spectral temporal resolution, overlapping value, and accelerometer amplitude normalisation effects. Unnormalised data, with longer feature window lengths and decreasing temporal resolutions, yielded the highest quality discrimination. Setting the sampling rate to 40 Hz and overlapping value to 66% provided optimal discrimination. Baseline results highlight that the sacrum is the best-performing location, yet optimal (longer) window lengths, and optimal (shorter) temporal resolutions change the best-performing sensor attachment location to the shanks. Specific values of parameters were found to be optimal for our study, and these results can guide manufacturers, engineers, and researchers in designing wearable devices and machine learning algorithms that more effectively identify locomotor tasks. Practitioners and clinicians may also use these findings to select appropriate tools or methodologies tailored to their specific research or clinical objectives.

Identify which NIH Toolbox Cognition Battery (NIHTB-CB) subtest(s) best differentiate healthy controls (HC) from those with amnestic mild cognitive impairment (aMCI) and compare the discriminant accuracy between a model using a priori \"Norm Adjusted\" scores versus \"Unadjusted\" standard scores with age, sex, race/ethnicity, and education controlled for within the model. Racial differences were also examined. Participants were Black/African American (B/AA) and White consensus-confirmed (HC = 96; aMCI = 62) adults 60-85 years old that completed the NIHTB-CB for tablet. Discriminant function analysis (DFA) was used in the Total Sample and separately for B/AA ( = 80) and White participants ( = 78). Picture Sequence Memory (an episodic memory task) was the highest loading coefficient across all DFA models. When stratified by race, differences were noted in the pattern of the highest loading coefficients within the DFAs. However, the overall discriminant accuracy of the DFA models in identifying HCs and those with aMCI did not differ significantly by race (B/AA, White) or model/score type (Norm Adjusted versus Unadjusted). Racial differences were noted despite the use of normalized scores or demographic covariates-highlighting the importance of including underrepresented groups in research. While the models were fairly accurate at identifying consensus-confirmed HCs, the models proved less accurate at identifying White participants with an aMCI diagnosis. In clinical settings, further work is needed to optimize computerized batteries and the use of NIHTB-CB norm adjusted scores is recommended. In research settings, demographically corrected scores or within model correction is suggested.

According to Kottelat (2001), the genus Barbonymus is distributed throughout southeast Asian countries, such as Indonesia, Malaysia, Thailand, Vietnam, Laos, and Cambodia. [...]morphometric data is valuable for discriminating among fish species, as was done in the current study. The scatter plot (Figure 3) shows that Function 1 successfully discriminated the individuals into two separate groups, where the lampam-A group overlapped with the lampam-B group, and there was a negative relationship between the characters of the groups. [...]Function 2 also successfully discriminated the individuals into two different groups, where lampam-A and lampam-B overlapped between these characters (group I) and naleh was grouped separately (group II), and there was a positive relationship between the characters of group I and group II (Fig. 3). [...]the DFA scatter plot showed that the individual samples were overlapping between these two species, and this is an initial indication that the two taxa can be presumed to be the same species of B. schwanenfeldii. [...]study on genetic data analysis is crucial to validate the precise taxonomic status of Barbonymus in Aceh waters.

The objective of this study was to analyze the diverse morphological attributes of Kotdhar goat native to Shivalik hill region of Himachal Pradesh. A total number of 180 goats, comprising 150 females and 30 males aged between 1 and 3 years, were randomly selected to estimate15 distinct morphological traits and ten body indices. Mean values of 17.66 cm, 11.68 cm, 8.73 cm, 71.94 cm, 69.83 cm, 74.48 cm, 38.10 cm, 73.38 cm, 20.55 cm, 16.48 cm, 14.89 cm, 13.57 cm, 19.20 cm, 7.71 cm and 26.12 kg were estimated for head length, head width, face length, body length, wither height, heart girth, chest depth, rump height, rump length, rump width, haunch width, bicoastal width, shoulder width, cannon bone and body weight respectively. In addition, morphological indices viz. body index, length index, body ratio, thoracic development, pelvic index, longitudinal pelvic index, transverse pelvic index, proportionality index, dactyl thorax index and relative depth of thorax were estimated from morphological traits. Results of morphological indices indicated that Kotdhar goat are medium bodied, longilinear, tall animals and well-suited for meat production. Phenotypic correlation among most of traits was positive and significant. Among all correlations, correlation between head length and head width was found lowest (− 0.270), while the correlation between heart girth and chest depth was observed highest (0.861). Canonical discriminant function analysis showed that there was no considerable level of intermixing for morphological traits in Kotdhar goat. Employing principal component analysis with varimax rotation, three principal components were observed, accounting for 68.47% of the total variation. First principal component (PC1) encapsulated the highest proportion of variance (44.39), revealing the high loadings on head length (0.777), body length (0.747), wither height (0.782), heart girth (0.785), chest depth (0.706), rump height (0.762), haunch width (0.734) and bicoastal width (0.793). Hence, it is possible to utilize these eight variables out of the 15 morphological traits for the characterization of the Kotdhar goat.

The geographic isolation of conspecific populations can produce a diversification of signals through genetic drift, which may be reinforced by selection if populations (or sibling species) come into secondary contact. As conspicuous visual signals, bobbing displays of lizards have been described for numerous genera, and differences in display structure have been documented between some isolated conspecific populations. Although bobbing display structure has been detailed for several Galápagos Lava Lizard species (Microlophus sp.), intraspecific populations on different islands also exhibit various degrees of display structure divergence. In the present study, our goal was to determine if Microlophus bivittatus on San Cristóbal Island and a population on its adjacent islet of Isla Lobos possess differences in bobbing display structure. Interestingly, adult males on Isla Lobos exhibit gigantism compared to those on San Cristóbal, and the two populations have been isolated by the sea for several thousand years. We predicted that bobbing display speed would scale inversely with body size, such that displays would be detectably slower and longer in the supersized Isla Lobos males than those in the smaller San Cristóbal males. To test this prediction, we elicited displays from subjects by using a conspecific-mimicking robot. We measured two displays from 16 subjects in each population by using conventional unit-based variables as well as Fourier transform-based variables. After determining correlations among display variables, we tested for differences in uncorrelated display unit durations between Isla Lobos and San Cristóbal males. We then quantified within-subject, among-subject, and between-population variance for all variables by using nested ANOVAs and tested if variance differed between study populations at any level. Next, we used principal component analysis to create a small number of normally distributed variables (i.e., the principal components) from our original variables. These principal components then were used as inputs for discriminant function analysis to classify displays to populations. Comparisons of display unit durations supported our prediction only for the initial bob in displays, which was longer in Isla Lobos males than in San Cristóbal males. Nevertheless, when we considered multiple variables collectively, discriminant function analyses classified displays to the correct population at a level significantly greater than chance in all four unit-based analyses and three of four discrete Fourier transform-based analyses. Finally, supported by data on sexual size dimorphism and genetic differences between pairs of M. bivittatus populations (FST), our results indicate that divergence in bobbing display structure can occur relatively quickly if populations are sufficiently isolated.