A 3D point cloud dataset of Jining Qing Goats for segmentation analysis and body size measurement.

ABSTRACT In this paper, we develop a mathematical theory for the statement and validation of the hypersonic similarity law within the framework of Radon measure solutions to the steady compressible Euler equations. We investigate two scenarios: (1) two‐dimensional steady nonisentropic compressible Euler flows past infinitely long slender curved wedges, and (2) three‐dimensional steady nonisentropic compressible Euler flows past infinitely long axisymmetric cones. We find that for hypersonic flow over a slender body with a small slenderness parameter , if the parameter is fixed, then as (which corresponds to the Mach number of the incoming flow ), the flow field structures, after scaling, become independent of the body's shape and the Mach number . Instead, they depend solely on and the adiabatic exponent of the polytropic gas. Mathematically, we revisit the classical hypersonic small‐disturbance equations within the framework of Radon measure solutions, enabling explicit construction of solutions with concentration boundary layers. We demonstrate that as , under suitable nondimensional scalings, the Radon measure solutions of the original hypersonic flow problems converge to those of the corresponding hypersonic small‐disturbance problems. The explicit forms of the Radon measure solutions obtained for the two scenarios facilitate the convergence analysis.

Dieting is a common occurrence during adolescence. Dieting behaviours and cognitions can have a profound impact during this critical period of development, when youth have a heightened sensitivity to appearance and are actively forming their body image. Adolescents are particularly susceptible to internalizing the myriad and conflicting "health" messages disseminated through mainstream and social media, peer interactions, family dynamics, school systems and health care encounters. These messages can influence their perception of what constitutes a "normal" or "healthy" body, motivating dieting behaviours that are undertaken in an attempt to change their body weight or shape (or both).

Sex, body size and environmental conditions are key determinants of home range size in large mammals, yet their relative importance within populations remains unclear for many wide-ranging carnivores such as brown bears. This study combined GPS-collar data and detailed morphometrics from 69 free-ranging brown bears (46 males, 23 females) in Türkiye to test how home range size relates to sex, body mass, and body dimensions. Individual home ranges were estimated using 95% minimum convex polygon (MCP95) and kernel utilisation distribution methods, and the MCP95 area was log-transformed and analysed with linear models that included sex, log body mass, representative linear size measures, sampling effort covariates, and principal component scores derived from a multivariate analysis of eight morphometric traits. Home range size varied markedly among individuals (5.1-203.9 km2), with males consistently having nearly twice the MCP95 area of females, with sex accounting for most of the variance in log home range size. In contrast, neither body mass nor linear body dimensions showed significant within-sex relationships with home range size, and sex × mass interactions were not supported. Principal component analysis revealed a dominant body size axis, but this multivariate size component, as well as a secondary shape axis, did not explain additional variation once sex was included. Models that accounted for the number of GPS fixes, tracking duration, and influential points confirmed the robustness of the sex effect and indicated only modest contributions of sampling effort. Overall, the results showed that sex, rather than fine-scale variation in body size or shape, is the primary intrinsic driver of home range size in this southern brown bear population, highlighting the need for sex-specific but not size-specific spatial planning and conservation strategies in the future.

BackgroundAccumulating evidence suggests that sleep disorders are strongly associated with obesity, particularly visceral adiposity. A Body Shape Index has been recognized as a more accurate anthropometric indicator for assessing overall obesity and visceral fat levels. This study aimed to explore the potential relationship between obesity and sleep disorders in a representative sample of the U.S. adult population.MethodsThis retrospective study involved data from 25,057 adults aged 20 years and older who participated in the National Health and Nutrition Examination Survey between 2005 and 2016. Multivariate logistic regression models, restricted cubic spline analysis, and subgroup stratification were used to analyze the association between A Body Shape Index and sleep disorders.ResultsAmong the 25,057 participants, 6310 reported experiencing sleep disorders. After adjusting for potential confounders, the results revealed that a unit increase in A Body Shape Index was associated with a 10% higher likelihood of sleep disorders (odds ratio = 1.1, 95% confidence interval: 1.02-1.18, p < 0.05). When A Body Shape Index was categorized into tertiles, individuals in the highest tertile exhibited a significantly higher prevalence of sleep disorders compared with those in the lowest tertile (odds ratio = 1.13, 95% confidence interval: 1.04-1.23, p < 0.05). Restricted cubic spline analysis revealed a nonlinear relationship between A Body Shape Index and sleep disorders (p = 0.004). Additionally, subgroup analysis demonstrated a statistically significant interaction between age and A Body Shape Index categories (p < 0.05).ConclusionThese findings demonstrate a positive association between A Body Shape Index and the prevalence of sleep disorders. A Body Shape Index may serve as a practical and simple anthropometric marker for identifying individuals at increased risk of sleep disorders.

While body mass index (BMI) is the most used measure of adiposity, it does not account for fat distribution. Novel indices, such as A Body Shape Index (ABSI) and Body Roundness Index (BRI), may better reflect cardiometabolic risk. However, their association with subclinical cardiac damage, particularly left ventricular hypertrophy (LVH), remains unclear. The aim of this study was to evaluate the association between novel adiposity indices (ABSI and BRI) and left ventricular mass (LVM) assessed by echocardiography in a large cohort of patients with hypertensive. We conducted a cross-sectional study including 724 hypertensive adults who underwent standardized anthropometric and echocardiographic assessments. Adiposity indices (BMI, waist circumference, ABSI, and BRI) were calculated, and left ventricular mass was indexed to body surface area and height2.7. Correlations and multivariate analyses were performed, and receiver operating characteristic (ROC) curves were used to assess diagnostic performance. All adiposity indices were significantly higher in individuals with LVH. BRI showed the strongest correlation with LVMH2.7 (r=0.423), particularly in women. In multivariate analysis, BRI remained significantly associated with LVMH2.7 in both sexes, while ABSI was not independently associated in men. ROC curve analysis demonstrated that BRI had the highest diagnostic accuracy for identifying LVH, outperforming BMI and ABSI, especially when LVH was defined using LVMH2.7. BRI outperformed traditional and novel adiposity indices in identifying LVH in hypertensive patients, particularly when LVM was indexed to height2.7. Given its superior diagnostic performance, BRI may represent a valuable tool in cardiovascular risk stratification, though further studies are warranted.

Prognostic value of abdominal obesity indicators for all-cause mortality in familial hypercholesterolemia.

This study combines experimental and numerical approaches to investigate flow behavior downstream of bluff bodies placed at the mid-span of a rectangular sudden expansion configurations common in combustion chambers, burners, flame stabilizers, and chemical mixers. The three-dimensional, steady, incompressible, and turbulent flow was analyzed for varying Reynolds numbers, bluff body shapes (square, diamond, circular, triangular-arrow-left and arrow-right), sizes, and streamwise positions. Introducing a bluff body significantly modified flow field, intensifying adverse pressure gradients and delaying reattachment compared with configuration without a bluff body. The pressure recovery coefficient strongly depended on geometry; at Re = 74,200, the diamond body achieved a value 179% higher than that of the triangle–arrow-left configuration. Increasing bluff body size consistently reduced pressure recovery and increased losses, for instance, enlarging a cylindrical body by 2.2 times at Re = 93,734 increased the upper-wall pressure drop by 240%. Numerical simulations, validated against experiments with less than 2% deviation, revealed multiple recirculation zones and complex wake vortices that expanded with Reynolds number. Flow asymmetry occasionally appeared due to combined effects of geometry, size, and position. Drag increased with Reynolds number, with the triangle–arrow-right body producing the highest drag. Overall, the results demonstrate a strong dependence of sudden-expansion flow characteristics on bluff body parameters, providing valuable insights for optimizing engineering systems involving flow control and pressure recovery.

A Body Shape Index (BSI), previously developed and evaluated as an improvement over traditional adiposity measures for predicting health risks, has not been comprehensively characterized with respect to its temporal trends, population disparities, and prognostic value in the United States. This analysis examined data from 47,762 adults across 10 NHANES cycles (1999-2018). BSI trends were assessed across demographic and health-related subgroups. All-cause mortality risk was evaluated using Cox regression, with adjustment for multiple confounders. Interaction and restricted cubic spline analyses explored effect modification and nonlinearity. Mean BSI increased significantly over the two decades. Disparities persisted or widened over time. Elevated BSI was independently associated with higher mortality risk, particularly above the median, with a nonlinear escalation in risk at higher BSI levels. The impact of high BSI on all-cause mortality was stronger in males and varied by race/ethnicity, while lower BSI showed no protective effect. BSI demonstrates a rising trend and persistent disparities among U.S. adults, with high BSI independently predicting adverse all-cause mortality in a nonlinear manner. These findings from the analyzed data supported the utility of BSI in risk stratification and highlighted the need for targeted interventions. Future research should explore BSI's role in public health strategies.

BackgroundCognitive impairment is a primary contributor to disability among older adults, with growing evidence identifying central adiposity as an adjustable risk factor for neurodegeneration, but comprehensive predictive models integrating central adiposity indices for mild cognitive impairment (MCI) in aging individuals remain underexplored.ObjectiveThis study aimed to establish and verify a model for predicting the risk of MCI in elderly population by incorporating anthropometric indices.MethodsWe calculated five central adiposity indices using anthropometric measurements from 2464 United States adults aged 60 years or older (National Health and Nutrition Examination Survey, 2011-2014). Cognitive performance was assessed using three standardized neuropsychological tests. A random assignment placed participants into either a training (n = 1725) or a validation (n = 739) set. Furthermore, the data from participants in the 2011 wave of the China Health and Retirement Longitudinal Study served as an external validation cohort (n = 536). LASSO-selected predictors were employed to inform multivariable logistic regression modeling.ResultsPositive linear relationships were found between three anthropometric indices-A Body Shape Index (ABSI), Conicity Index (CoI) and Weight-Adjusted-Waist Index (WWI)-with MCI risk (p < 0.05, p for nonlinearity > 0.05). The nomogram incorporating ABSI demonstrated strong discriminative capacity (training AUC = 0.861; internal validation AUC = 0.826; external validation AUC = 0.798), precise calibration, and good clinical utility.ConclusionsThe risk of MCI was independently linked to central adiposity indices (ABSI, WWI, and CoI). The nomogram incorporating ABSI provided a validated, clinically applicable prediction model for initial screening of MCI in older populations.

Mature body size and weight of sheep are important traits that significantly influence mutton yield and economic benefits of sheep farming. The exploration for key genes underlying these traits will facilitate the advancement of molecular breeding in meat sheep. In this study, key candidate genes for five body size traits and the body weight were identified in mature Huameng meat sheep through GWAS and ROH analysis. After quality control, 451 individuals and 16 751 761 variants were analyzed using EMMAX software in a linear mixed model (LMM). A total of 3 genome-wide and 35 chromosome-wide significant SNPs were identified, respectively. Several key candidate genes have been uncovered, including ZFAT, ACSL3, and GRID2 for cannon bone circumference; UNC5C and BMPR1B for body weight and chest girth; PCDH15 and NUP93 for hip width; and PTPRD for body height. ROH analysis revealed a high-frequency ROH hotspot region on chrX. In addition, ROH analysis suggested that inbreeding may lead to a significant depression in body height of sheep. This study provides important clues for revealing the molecular mechanisms underlying sheep body morphological traits and identifies key candidate genes for molecular breeding in meat sheep.

Objective.Radiotherapy (RT) requires accurate and consistent patient positioning to ensure precise radiation delivery and minimize unnecessary exposure to healthy tissues. Conventional workflows rely heavily on clinicians' experience and repeated CT-based registration, leading to inefficiency, patient discomfort, and potential alignment inconsistencies. This work aims to develop an automatic, robust, and low-cost posture offset detection method that overcomes these limitations.Approach.We propose a prompt-guided incremental fine-tuning model built upon a large-scale image segmentation backbone. The system captures real-time two-dimensional images from a single RGB camera and automatically generates adaptive prompt points based on individual body shapes and postures, improving segmentation robustness and reducing environmental interference. An incremental fine-tuning strategy enables continuous adaptation to newly collected patient images throughout the treatment cycle. Furthermore, a multi-level offset analysis framework is introduced, integrating contour-level, keypoint-level, and pixel-level estimations to identify, localize, and quantify posture deviations across multiple granularities. The system is deployed clinically to collect real RT data and construct a dedicated validation dataset.Main Results.Extensive experiments on real clinical data show that the proposed method achieves accurate, fast, and stable posture offset detection. It substantially improves positioning consistency and efficiency compared with conventional workflows. Ablation studies further demonstrate the effectiveness and necessity of each module within the framework.Significance.This study provides a practical and low-cost solution for RT positioning, reducing clinician workload and patient burden while improving treatment accuracy. It demonstrates the potential of prompt-guided incremental adaptation and multi-level offset analysis in real RT environments, offering a promising direction for intelligent, automated RT positioning systems.

A parametric framework for population-specific 3D human body shape reconstruction using SMPL

Body image dissatisfaction (BID) among adolescents is a growing public health concern globally, linked to unhealthy eating behaviors, low self-esteem, and psychological distress. In Nepal, research on BID remains limited, particularly in exploring both genders and the influence of behavioral, perceptual, and familial factors. This study aimed to assess the prevalence of BID and its associated factors among adolescents in Kathmandu Metropolitan City. A community-based cross-sectional study was conducted among 313 adolescents aged 10-19 years. Data were collected between 8th -30th June 2024 using a semi-structured, interviewer-administered questionnaire and anthropometric measurements. The questionnaire covered four domains: socio-demographic, behavioral, perceptual, and anthropometric characteristics. Validated instruments, including Body Shape Questionnaire (BSQ-16B), Figure Rating Scale, and Perceived Beauty Standards Scale (PBSS-8), were utilized. Eight wards were randomly selected, and households were approached through systematic sampling at fixed intervals. Descriptive and inferential statistical analyses were performed, and multivariable binary logistic regression was used to identify factors associated with body image dissatisfaction. Statistical significance was set at p < 0.05. The prevalence of BID was 24.3% (95% CI: 19.8-28.8). Female adolescents were nearly twice as likely as males to report dissatisfaction (AOR = 1.99; 95% CI: 1.02-3.88). Overweight/obese adolescents had significantly higher odds of BID (AOR = 2.41; 95% CI: 1.16-5.02). Adolescents who skipped meals (AOR = 4.14; 95% CI: 2.01-8.52) and those who experienced body shaming (AOR = 2.70; 95% CI: 1.37-5.36) were at increased risk. Perceiving one's body as "a bit too large" (AOR = 3.51; 95% CI: 1.33-9.31) or "much too large" (AOR = 8.68; 95% CI: 2.99-20.14) also showed strong associations with dissatisfaction. Nearly one in four adolescents experienced BID, with greater vulnerability among females, those with overweight/obesity, and those exposed to body shaming. These findings suggest the importance of incorporating body image literacy and psychosocial wellbeing components into existing adolescent health and school-based education programs in Nepal.

Cardiometabolic multimorbidity (CMM) is prevalent among individuals with hypertension. Although insulin resistance (IR)-related indices have been linked to CMM, their associations with incident CMM in hypertensive populations remain unclear. This study examined the associations in this high-risk group, focusing on the roles of genetic factors and biomarkers. This observational prospective cohort analysis used data from the UK Biobank, comprising 129,853 hypertensive patients free of pre-existing coronary heart disease, stroke, or type 2 diabetes. Eight IR-related indices were computed: triglyceride-glucose (TyG) index, TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), TyG-a body shape index (TyG-ABSI), TyG-weight-adjusted waist index (TyG-WWI), TyG-body roundness index (TyG-BRI), and triglyceride to high-density lipoprotein cholesterol ratio (TG-HDL-C). Associations were examined using Cox proportional hazards models. Incremental predictive value was quantified using the net reclassification improvement, integrated discrimination improvement, and the C index. We also analyzed their joint and interaction effects with genetic risk and conducted exploratory biomarker analyses. Over a median follow-up of 13years, 28,455 incident CMM events were recorded. Multivariable-adjusted hazard ratios (95% CIs) the highest versus lowest tertiles were: 1.78 (1.73-1.83) for TyG index, 2.10 (2.04-2.17) for TyG-BMI, 2.29 (2.21-2.37) for TyG-WC, 2.23 (2.16-2.30) for TyG-WHtR, 2.08 (2.02-2.15) for TyG-WWI, 2.17 (2.10-2.24) for TyG-BRI, 1.90 (1.84-1.97) for TyG-ABSI, and 1.73 (1.68-1.79) for TG-HDL-C. Per standard deviation increment was associated with 18%-48% higher risks. All indices improved incremental predictive value, with TyG-WHtR showing the strongest performance. Individuals with high IR-related indices and high genetic risk exhibited the highest CMM risk, with additive interactions. High genetic risk appeared to strengthen the adverse associations between IR-related indices and CMM, with evidence of multiplicative interactions. Biomarker analyses suggested that systemic inflammation and biomarkers of liver and renal function might statistically account for part of the observed associations. Higher levels of IR-related indices, especially TyG-WHtR, were associated with an elevated risk of incident CMM in individuals with hypertension, particularly among those with high genetic risk. Inflammatory, hepatic, and renal biomarker abnormalities were related to the associations. IR-related indices, particularly TyG-WHtR, may provide useful information for risk stratification of CMM among individuals with hypertension.

We aim to understand how landslides affect the shape and rotational motion of small rubble planetary bodies. We limit ourselves to axisymmetric global landslides and take the primordial shape of the body to be axisymmetric as well. The landslides are modelled as shallow granular surface flows using depth averaging, while incorporating the effects of the body’s rotation, topographical changes from previous landslides, its non-uniform gravity field and possible surface mass shedding. The body’s rotational dynamics is coupled to its shape change due to the transport of regolith – surface grains – and also accounts for the influence of radiation torque. We utilise our framework to investigate regolith motion on idealised rubble bodies and actual asteroids. We then study the evolution of the shape and spin state of an initially spherical rubble asteroid undergoing multiple global landsliding events over millions of years – a time scale comparable to typical asteroidal lifetimes. We find that shape changes due to landsliding resist spin-up due to radiation torque and, in some instances, may even cause the body to spin down. Furthermore, rotational fission is delayed, and may even be suppressed, by regolith redistribution toward the body’s equator. Finally, top-shaped configurations may emerge rapidly, which may explain the prevalence of top-shaped asteroids in near-Earth orbits.

Today, an increasing number of applications in domains such as cultural heritage, healthcare, education, entertainment, and fashion require high-fidelity 3D avatars. However, generating avatars that faithfully reproduce users' bodies through modeling or acquisition techniques remains challenging and time-consuming, particularly in applications where the accurate quantitative reproduction of body shape and precise anthropometric measurements is required. Thus, attention is shifting towards machine learning-based approaches, in particular those able to fit a parametric model representing the avatar to the intended body shape. Among these models, the Sparse Unified Part-Based Human Representation (SUPR) has been proven to offer superior performance compared to other representations. However, its adoption is primarily hindered by the lack of datasets built upon it. This paper addresses this gap by proposing BOdy shape parameter and 3D meshes of Individuals basEd on SUPR (BODIES), a dataset containing 84,000 synthetic-generated subjects described using the SUPR model with different numbers of parameters. The paper also presents the results of three experimental studies aimed at assessing the improvements brought by the SUPR model over the state-of-the-art when used to feed an existing framework for generating 3D avatar meshes.

Background To further assess the relationship between obesity and infertility, we employed a novel anthropometric index, specifically designed to assess the relationship between a body shape index (ABSI) and infertility in women of childbearing age. Furthermore, we examined the correlation between ABSI and visceral obesity index (VAI) in relation to infertility. Methods A total of 1989 female participants of childbearing age were included, based on National Health and Nutrition Examination Survey (NHANES) data from 2013 to 2016. The ABSI is calculated by dividing waist circumference by body mass index (BMI) 2/3* height1/2. VAI was calculated using the following formula: waist circumference/(36.58 + (1.89*BMI)) x (triglycerides/0.81) × (1.52/HDL cholesterol). Infertility or fertility status was defined by interviewing female participants of childbearing age through a reproductive health questionnaire. Weighted multifactorial logistic regression analysis was used to explore the independent relationship between ABSI and infertility. Smoothed curve fitting, subgroup analyses and interaction tests were also performed. Results Among the 1989 participants, 183 (9.2%) women were categorized as infertile. Logistic regression modeling showed that ABSI was positively associated with infertility and remained significant even after adjusting for all confounders(OR = 1.31, 95% CI: 1.07–1.60, p = 0.0098). This association was consistent across all subgroups (age, race, smoking, alcohol consumption, hypertension, diabetes mellitus, and the regularity of menstruation over the previous 12 months), (p > 0.05 for all interactions). The results of the smooth curve fitting demonstrated a linear, positive association between ABSI and infertility. Conclusion There is a statistically significant positive correlation between body mass index and infertility. As a body shape index rises, women of childbearing age are at greater risk of infertility.

Life expectancy (LE) at birth has increased in many countries throughout the twentieth and twenty-first centuries. Future LE values are estimated by extrapolating existing data. However, it remains difficult to determine the LE limit using mathematical models such as the Kannisto model and the Gompertz function due to significant random fluctuations in centenarian mortality rates. There are 12 biological hallmarks of ageing, including epigenetic changes and senescent cells. These microscopic dysfunctions and cellular energy are deeply intertwined, based on the inevitable cellular energy deficiency experienced by the elderly. We recently derived an age-dependence of standard cellular energy for people of healthy body shape. The logistic function taking into account standard cellular energy and also a lifespan Tc strictly reproduced the robust age-specific mortality data for ages under 100years in many countries, by adjusting two parameters Tc and C. We applied the logistic function to the recent Japanese data with the world's longest LE of 87.5years and the highest natural death rates in centenarians. Consequently, the logistic function explicitly detected the maximum Tc value of 105, even though the C value continuously increased. By setting Tc to 105 and only increasing the C value, we obtained an achievable upper limit of LE = 98. Then, the survival rate trajectory became rectangular due to the biological effect of cellular energy depletion. The LE values of many countries are expected to reach the Japanese LE of 87.5. Standard cellular energy and Tc in the logistic function were essential to detect the LE limit in the Japanese data.

Abstract Most vision-based robotic tracking methods focus on general objects instead of human beings. This limitation stems from the inherent morphological variations in humans, characterized by non-rigid deformations and diverse kinematic configurations, which constrains the reliable limb tracking through conventional methods. The 3D representation of the human body provides rich spatial information and the inherent semantics of the limbs offer stable target signatures, while these properties remain under-exploited in dynamic motion tracking tasks. To address these challenges, we propose a dual-view fusion of perception-to-action framework for limb tracking, incorporating cross-view feature aggregation. This dual-view visual fusion attention mechanism captures both body shape and posture variations, as well as maintaining egocentric-perception of the target limb. The reasoning and planning capabilities across perspectives also be enhanced through this approach. Additionally, we present a feature extractor based on human semantic parsing to improve the limb perception. To further reduce the complexity of human image features and increase sim-to-real transfer efficiency, we develop an image matching mechanism based on 3D human reconstruction. Through the examination of various simulated and real-robot examples, our methods exhibit superior properties compared with current vision-based methods in terms of the success rate.