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This study aimed to assess the effect of intraocular pressure (IOP) changes on biometry and intraocular lens (IOL) power calculation in patients diagnosed with primary open-angle glaucoma (POAG) and ocular hypertension (OHT). This prospective non-randomized cohort study enrolled patients with diagnosed POAG and OHT, presenting with IOP levels exceeding 25 mmHg. Thai Clinical Trials Registry number was TCTR20180912007. Optical biometry, encompassing measurements such as corneal thickness (CCT), keratometry, anterior chamber depth (ACD), and axial length, was conducted before and after IOP reduction. The IOL power was also determined using the SRK/T formula. The main outcomes measured were alterations in biometry and IOL power. Correlations between IOP, biometric parameters, and IOL power were analyzed. In total, 28 eyes were included in the study, with a mean patient age of 65.71±10.2 years. After IOP reduction, all biometric parameters, except CCT and ACD, exhibited a decrease without reaching statistical significance (all p>0.05). Meanwhile, IOL power showed a slight increase of 0.214±0.42 diopters (P = 0.035). The correlation between IOP and biometric parameters was found to be weak. However, there was a moderate correlation between IOP and IOL power (r2 = 0.267). Notably, IOL power tended to increase by more than 0.5 diopters when IOP decreased by more than 10 mmHg (p < 0.001). In conclusion, changes in IOP among patients with POAG and OHT do not significantly impact biometry and IOL power calculations. Nonetheless, it may be prudent to consider a slight adjustment in IOL power when IOP is lowered by more than 10 mmHg. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the accuracy of two portable ultrasound machines (PUM) in assessing fetal biometry and estimated gestational age (EGA). Methods: This was a secondary analysis of data from the Fetal Age Machine Learning Initiative, an observational study of pregnant women in the USA and Zambia. Each participant underwent ultrasound assessment by an experienced sonographer using both a high‐specification ultrasound machine (HSUM) and a PUM (Butterfly iQ or Clarius C3) to measure fetal biometry and calculate EGA at each visit. By comparing paired PUM and HSUM scans, we estimated agreement between individual biometry measurements and aggregate gestational age estimates by reporting mean difference, intraclass correlation coefficient (ICC) and Bland–Altman plots, adjusting for trend. Results: Between April and December 2021, 818 participants contributed 1386 paired PUM–HSUM ultrasound investigations, of which 991 PUM scans were obtained using the Butterfly iQ device and 395 using the Clarius C3 device. Gestational age at scan ranged from 7 to 38 weeks. Compared with HSUM, the Butterfly iQ PUM had a mean difference of −0.20 (95% CI, −0.60 to 0.20) days in the first trimester and −0.68 (95% CI, −0.93 to −0.44) days in the second/third trimesters. Compared with HSUM, the Clarius C3 PUM had a mean difference of −0.47 (95% CI, −1.11 to 0.18) days in the first trimester and −1.67 (95% CI, −2.10 to −1.25) days in the second/third trimesters. ICCs were 0.989 or greater throughout. Increasing gestational age was associated with increasing error and absolute error in EGA and fetal biometry. Both PUM devices demonstrated a modest trend toward underestimation of EGA with advancing gestational age in second/third‐trimester scans, compared with HSUM. Conclusion: The Butterfly iQ and Clarius C3 PUM devices were highly accurate in performing fetal biometry in a diverse population from the USA and Zambia. © 2023 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

The rapidly evolving field of biometric recognition and verification technologies has seen substantial progress recently. However, the storage of biometric data in cloud environments presents significant security challenges, including data theft and unauthorized modifications. Cancelable biometrics emerge as a strategic solution to these issues. This study examines the efficacy of diverse cancelable biometric methods, classified into transformation, encryption, and hybrid approaches. We introduce a novel cancelable biometric system that combines a hybrid optical asymmetric phase truncated Fourier transform (PTFT) with a symmetric cipher scheme, enhanced by a two-level block-based shuffling technique. This innovation improves security through a streamlined shuffling process that divides the PTFT output into four sections for shuffling and an exclusive OR operations with a unique key, enhancing security and computational efficiency. Our empirical evaluation on three distinct datasets (Faces, Iris, and Fingerprints) from FERET, UPOL and CASIA, and FVC2002 DB1 and DB2, respectively, demonstrates superior performance of our system compared to traditional PTFT-based systems. Notable performance metrics include an Area under the receiver operating characteristic curve of 0.9998. Significant improvements were also observed in false acceptance and false rejection ratios, along with more uniform histogram distributions, thereby enhancing randomness in the resultant deformed patterns. From a security standpoint, our system exhibits a high entropy of 7.95 and achieves near-optimal results in the number of pixels change rate and unified average changing intensity, with values of 98.9115 and 23.9755%, indicating robust resilience against potential differential attacks. The research findings, supported by detailed tables and graphical illustrations, underscore the additional security benefits offered by the two-level encryption mechanism. [ABSTRACT FROM AUTHOR]

Understanding the ontogenetic age and sex composition of zooarchaeological assemblages can reveal details about past human hunting and herding strategies as well as past animal morphology and behavior. As such, the accuracy of our estimates underlies our ability to ascertain details about site formation and gain insights into how people interacted with different animals in the past. Unfortunately, our estimates typically rely on only a small number of bones, limiting our ability to fruitfully use these estimates to make meaningful comparisons to theoretical expectations or even between multiple assemblages. This paper describes a method to use zooarchaeological remains with standard biometric measurements to estimate the ontogenetic age and sex composition of the assemblage, focused on immature, adult-sized female, and adult-sized male specimens. The model uses a Bayesian framework to ensure that the parameter estimates are biologically meaningful. Simulated assemblages show that the model can accurately estimate the biometry and composition of zooarchaeological assemblages. Two archaeological case studies also show how the model can be applied to produce tangible insights. The first, focused on sheep from Neolithic Pinarbaşı B, highlights the model's ability to elucidate site formation and function. The second, focused on cattle remains from four assemblages from 7th-6th millennium BCE northwestern Anatolia, showcases how to use the mixture modeling results to compare assemblages to one another and to specific hypotheses. This modeling framework provides a new avenue for investigating long-term trajectories in animal biometry alongside contextual analyses of past human choices in butchery and consumption. [ABSTRACT FROM AUTHOR]

Automated medical image analysis solutions should closely mimic complete human actions to be useful in clinical practice. However, more often an automated image analysis solution represents only part of a human task, which restricts its practical utility. In the case of ultrasound-based fetal biometry, an automated solution should ideally recognize key fetal structures in freehand video guidance, select a standard plane from a video stream and perform biometry. A complete automated solution should automate all three subactions. In this article, we consider how to automate the complete human action of first-trimester biometry measurement from real-world freehand ultrasound. In the proposed hybrid convolutional neural network (CNN) architecture design, a classification regression-based guidance model detects and tracks fetal anatomical structures (using visual cues) in the ultrasound video. Several high-quality standard planes that contain the mid-sagittal view of the fetus are sampled at multiple time stamps (using a custom-designed confident-frame detector) based on the estimated probability values associated with predicted anatomical structures that define the biometry plane. Automated semantic segmentation is performed on the selected frames to extract fetal anatomical landmarks. A crown–rump length (CRL) estimate is calculated as the mean CRL from these multiple frames. Our fully automated method has a high correlation with clinical expert CRL measurement (Pearson's p = 0.92, R -squared [ R 2] = 0.84) and a low mean absolute error of 0.834 (weeks) for fetal age estimation on a test data set of 42 videos. A novel algorithm for standard plane detection employs a quality detection mechanism defined by clinical standards, ensuring precise biometric measurements. [ABSTRACT FROM AUTHOR]

Objective: Low‐cost devices have made obstetric sonography possible in settings where it was previously unfeasible, but ensuring quality and consistency at scale remains a challenge. In the present study, we sought to create a tool to reduce substandard fetal biometry measurement while minimizing care disruption. Methods: We developed a deep learning artificial intelligence (AI) model to estimate gestational age (GA) in the second and third trimester from fly‐to cineloops—brief videos acquired during routine ultrasound biometry—and evaluated its performance in comparison to expert sonographer measurement. We then introduced random error into fetal biometry measurements and analyzed the ability of the AI model to flag grossly inaccurate measurements such as those that might be obtained by a novice. Results: The mean absolute error (MAE) of our model (±standard error) was 3.87 ± 0.07 days, compared to 4.80 ± 0.10 days for expert biometry (difference −0.92 days; 95% CI: −1.10 to −0.76). Based on simulated novice biometry with average absolute error of 7.5%, our model reliably detected cases where novice biometry differed from expert biometry by 10 days or more, with an area under the receiver operating characteristics curve of 0.93 (95% CI: 0.92, 0.95), sensitivity of 81.0% (95% CI: 77.9, 83.8), and specificity of 89.9% (95% CI: 88.1, 91.5). These results held across a range of sensitivity analyses, including where the model was provided suboptimal truncated fly‐to cineloops. Conclusions: Our AI model estimated GA more accurately than expert biometry. Because fly‐to cineloop videos can be obtained without any change to sonographer workflow, the model represents a no‐cost guardrail that could be incorporated into both low‐cost and commercial ultrasound devices to prevent reporting of most gross GA estimation errors. Synopsis: Our model predicts gestational age (GA) more accurately from routinely available fly‐to cineloops than expert sonographer acquired biometry and can act as a guardrail to prevent gross GA estimation errors. [ABSTRACT FROM AUTHOR]

Objective: To construct a simple term small‐for‐gestational‐age (SGA) neonate prediction model that is clinically practical. Methods: This analysis was based on the Born in Guangzhou Cohort Study (BIGCS). Mothers who had a singleton pregnancy, delivered a term neonate, and had an ultrasonography within 30 + 0 to 32 + 6 weeks of gestation were included. Term SGA was defined with customized population percentiles. Prediction models were constructed with backward selection logistic regression in a four‐step approach, where model 1 contained fetal biometrics only, models 2 and 3 included maternal features and a time factor (weeks between ultrasonography and delivery), respectively; and model 4 contained all features mentioned. The prediction performance of individual models was evaluated based on area under the curve (AUC) and a calibration test was performed. Results: The prevalence of SGA in the study population of 21 346 women was 11.5%. With a complete‐case analysis approach, data of 19 954 women were used for model construction and validation. The AUC of the four models were 0.781, 0.793, 0.823, and 0.834, respectively, and all were well‐calibrated. Model 3 consisted of fetal biometrics and corrected for time to delivery was chosen as the final model to build risk prediction graphs for clinical use. Conclusion: A prediction model derived from fetal biometrics in early third trimester is satisfactory to predict SGA. Synopsis: A simple SGA prediction model based on fetal biometrics that requires no additional tests and no prior knowledge of the patient is clinically useful. [ABSTRACT FROM AUTHOR]

In recent years, face biometrics recognition systems are a wide space of a computer usage which is mostly employed for security purpose. The main purpose of the face biometrics recognition system is to authenticate a user from a given database. Due to the widespread expansion of the surveillance cameras and facial recognition technology, a robust face recognition system required. The recognition system needs to store a large number of training samples in any storage unit, that time hackers can access and control that data. So, Protecting and managing sensitive data is essential object. This requires a technique that preserve the privacy of individuals, maintain data integrity, and prevent information leakage. The storage of biometric templates on centralized servers has been associated with potential privacy risks. To address this issue, we have developed and implemented a proof-of-concept facial biometric identification system that uses a private Blockchain platform and smart contract technology. So, the proposed approach is presented a secure and tamper-proof from data breaches as well as hacks with data availability, by using the Blockchain platform to store face images. This paper aims to utilize Blockchain technology to identify individuals based on their biometric traits, specifically facial recognition system makes it tamper-proof (immutable) ensuring security. The system consists of enrolment and authentication phases. Blockchain technology uses peer-to-peer communication, cryptography, consensus processes, and smart contracts to ensure the security. The proposed approach was tested on two popular datasets: CelebFaces Attributes (CelebA) and large-scale face UTKFace datasets. The experimental results indicate that the system yields highly performance outcomes, as evidenced by the Equal Error Rate (EER) values of 0.05% and 0.07% obtained for the CelebA and UTKFace datasets, respectively. The system was compared to three baseline methods and scored the lowest Equal Error Rate. [ABSTRACT FROM AUTHOR]

The aim of the study was to assess the external and internal compatibility of the Biometrics E-LINK EP9 evaluation system device in the area of hand grip and pinch strength in the Polish population. The testing of hand grip and pinch strength was carried out among 122 healthy students. Two examiners performed hand grip and pinch strength measurements with a Biometrics E-LINK EP9 evaluation system device. Measurements were made for the right and left hands. The same people were tested again two weeks later, under the same conditions. The scores of one rater on the first and second tests were compared for reproducibility, and the scores of the two raters were compared to assess the reliability of the instrument. The measurements were found to be highly consistent both between the investigators and between the tests in the hand grip dynamometer test. The findings show high values of the Pearson's correlation coefficient equal or close to 1, as well as the interclass correlation coefficient (ICC) >0.9. Analysis of pinch strength measurements performed using the pinchmeter also found high values of the Pearson's correlation coefficient close to 1, as well as the interclass correlation coefficient >0.9; this reflects high agreement between the measurements performed by two investigators as well as assessments performed by one investigator at time intervals. These findings were confirmed by analyses performed using Bland-Altman plots. The measurements made with the Biometrics E-link EP9 evaluation system show high internal and external consistency in hand grip and pinch strength assessment. Biometrics E-link EP9 can be recommended for daily clinical practice. [ABSTRACT FROM AUTHOR]

Background: The aim of the present study was to provide ocular biometry percentile values for Indian children between the ages of 6 and 12 and to validate the usefulness of centiles in predicting myopia development. Methods: The study was part of a longitudinal study—the Sankara Nethralaya Tamil Nadu Essilor Myopia Study (STEM), where objective refraction and ocular biometry were measured for children studying in grades 1, 4, and 6 at baseline (2019–2020). These data were used to generate ocular biometry percentile curves (both for axial length (AL) and AL/corneal curvature (AL/CR) ratios). The usefulness of percentile values in predicting myopia development was estimated from follow-up data (2022). Results: The total number of children in the three grades at baseline was 4514 (age range 6 to 12). Boys represented 54% (n = 2442) of the overall sample. The prevalence of myopia at baseline was 11.7% (95% CI from 10.8 to 12.7%) in these three grades. Both the AL and AL/CR ratio centiles showed a linear trend with an increase in AL and AL/CR with increasing grades (p < 0.001) for all percentiles (2, 5, 10, 25, 50, 75, 90, 95, 98, and 99) when stratified by sex. In the follow-up data (n = 377), the 75th and 50th percentiles of the AL/CR ratio had an area under the curve (AUC) of 0.79 and 0.72 to predict myopia onset for grade 4 and 6 children at baseline. Combining baseline AL with the centile shift in follow-up as a predictor increased the AUC to 0.83. Conclusions: The present study has provided centile values specific for Indian children between the ages of 6 and 12 to monitor and intervene where children are at a higher risk of myopia development. [ABSTRACT FROM AUTHOR]

Humanitarian organisations are increasingly calling for the decolonisation of the sector, but this often overlooks colonialities reproduced by technology. By scrutinising the deployment and ubiquity of biometric technologies in the sector, this article seeks to reinvigorate sincere efforts towards decolonisation. [ABSTRACT FROM AUTHOR]

Zooarchaeological research all over Europe has suggested a generalised pattern of livestock size decrease during the transition between the Roman times and the Early Middle Ages. Different reasons have been proposed to explain this pattern, including a change in management and feeding practices, in the context of a shift of animal husbandry from large to small scale production. This paper is based on faunal material from Roman and early medieval Augusta Raurica, north-western Switzerland, and provides a first attempt to test this hypothesis, by combining zooarchaeological information (taxonomic frequencies and biometrical analysis) and stable carbon and nitrogen isotope data from bone collagen of cattle and pig. The results suggest important changes in livestock management, such as a shift towards pig husbandry, and evidence for increased use of pannage and forest pastures has been found. [ABSTRACT FROM AUTHOR]

Biometric authentication plays a vital role in various everyday applications with increasing demands for reliability and security. However, the use of real biometric data for research raises privacy concerns and data scarcity issues. A promising approach using synthetic biometric data to address the resulting unbalanced representation and bias, as well as the limited availability of diverse datasets for the development and evaluation of biometric systems, has emerged. Methods for a parameterized generation of highly realistic synthetic data are emerging and the necessary quality metrics to prove that synthetic data can compare to real data are open research tasks. The generation of 3D synthetic face data using game engines' capabilities of generating varied realistic virtual characters is explored as a possible alternative for generating synthetic face data while maintaining reproducibility and ground truth, as opposed to other creation methods. While synthetic data offer several benefits, including improved resilience against data privacy concerns, the limitations and challenges associated with their usage are addressed. Our work shows concurrent behavior in comparing semi-synthetic data as a digital representation of a real identity with their real datasets. Despite slight asymmetrical performance in comparison with a larger database of real samples, a promising performance in face data authentication is shown, which lays the foundation for further investigations with digital avatars and the creation and analysis of fully synthetic data. Future directions for improving synthetic biometric data generation and their impact on advancing biometrics research are discussed. [ABSTRACT FROM AUTHOR]

Biometric technology has various applications in smart healthcare systems, including patient authentication, health monitoring, telemedicine, clinical decision support, and personalized care. In addition, medical records contain sensitive and personal information, making them vulnerable to unauthorized access and theft. Because biometric data is distinct and unchangeable, unlike passwords or PINs, using biometric technologies in smart healthcare systems creates privacy problems. This creates privacy concerns as this information is highly sensitive and can be used to identify an individual, making it a valuable target for malicious actors. Subsequently, the storage and use of biometric data in smart healthcare systems must be handled with care to ensure that individuals' privacy rights are protected. Privacy by design is a concept that emphasizes the importance of incorporating privacy considerations into the design and development of products, services, and systems. In this paper, we presented different forms of biometric factors and technologies and their applications in the smart healthcare system to enhance security and privacy in relation to principles of privacy by design. In addition, the study analyzed a variety of attacks and techniques that can be utilized to compromise biometric technology in a smart healthcare system and presented some open research questions. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to investigate the uncertainty in the formula predicted refractive outcome REFU after cataract surgery resulting from measurement uncertainties in modern optical biometers using literature data for within‐subject standard deviation Sw. Methods: This Monte–Carlo simulation study used a large dataset containing 16 667 preoperative IOLMaster 700 biometric measurements. Based on literature Sw values, REFU was derived for both the Haigis and Castrop formulae using error propagation strategies. Using the Hoya Vivinex lens (IOL) as an example, REFU was calculated both with (WLT) and without (WoLT) consideration of IOL power labelling tolerances. Results: WoLT the median REFU was 0.10/0.12 dpt for the Haigis/Castrop formula, and WLT it was 0.13/0.15 dpt. WoLT REFU increased systematically for short eyes (or high power IOLs), and WLT this effect was even more pronounced because of increased labelling tolerances. WoLT the uncertainty in the measurement of the corneal front surface radius showed the largest contribution to REFU, especially in long eyes (and low power IOLs). WLT the IOL power uncertainty dominated in short eyes (or high power IOLs) and the uncertainty of the corneal front surface in long eyes (or low power IOLs). Conclusions: Compared with published data on the formula prediction error of refractive outcome after cataract surgery, the uncertainty of biometric measures seems to contribute with ⅓ to ½ to the entire standard deviation. REFU systematically increases with IOL power and decreases with axial length. [ABSTRACT FROM AUTHOR]

Objective This study aimed to evaluate fetal biometrics as predictors of shoulder dystocia (SD) in a low-risk obstetrical population. Study Design Participants were enrolled as part of a U.S.-based prospective cohort study of fetal growth in low-risk singleton gestations (n = 2,802). Eligible women had liveborn singletons ≥2,500 g delivered vaginally. Sociodemographic, anthropometric, and pregnancy outcome data were abstracted by research staff. The diagnosis of SD was based on the recorded clinical impression of the delivering physician. Simple logistic regression models were used to examine associations between fetal biometrics and SD. Fetal biometric cut points, selected by Youden's J and clinical determination, were identified to optimize predictive capability. A final model for SD prediction was constructed using backward selection. Our dataset was randomly divided into training (60%) and test (40%) datasets for model building and internal validation. Results A total of 1,691 women (98.7%) had an uncomplicated vaginal delivery, while 23 (1.3%) experienced SD. There were no differences in sociodemographic or maternal anthropometrics between groups. Epidural anesthesia use was significantly more common (100 vs. 82.4%; p = 0.03) among women who experienced SD compared with those who did not. Amniotic fluid maximal vertical pocket was also significantly greater among SD cases (5.8 ± 1.7 vs. 5.1 ± 1.5 cm; odds ratio = 1.32 [95% confidence interval: 1.03,1.69]). Several fetal biometric measures were significantly associated with SD when dichotomized based on clinically selected cut-off points. A final prediction model was internally valid with an area under the curve of 0.90 (95% confidence interval: 0.81, 0.99). At a model probability of 1%, sensitivity (71.4%), specificity (77.5%), positive (3.5%), and negative predictive values (99.6%) did not indicate the ability of the model to predict SD in a clinically meaningful way. Conclusion Other than epidural anesthesia use, neither sociodemographic nor maternal anthropometrics were significantly associated with SD in this low-risk population. Both individually and in combination, fetal biometrics had limited ability to predict SD and lack clinical usefulness. Key Points SD unpredictable in low-risk women. Fetal biometry does not reliably predict SD. Epidural use associated with increased SD risk. SD prediction models clinically inefficient. [ABSTRACT FROM AUTHOR]

Introduction: Accurate assessment of ocular biometry and corneal aberrations for diagnosis and therapy is crucial in many clinical settings. Devices to improve the measurements of these parameters are constantly being developed. Aim: To evaluate the repeatability of ocular biometry and corneal aberrations obtained by the Pentacam® AXL in normal eyes. Materials and Methods: This cross-sectional study was conducted in the Optometry Department of King Saud Universiy, Riyadh, Saudi Arabia from September 2021 to February 2022. The study included a total of 120 eyes from 60 normally sighted adult participants whose of ocular biometry and corneal aberrations were measured three times in a single session using the Pentacam® AXL. Biometric parameters include Axial Length (AL), mean K-reading (Km), Anterior Chamber Depth (ACD), Central Corneal Thickness (CCT), and Horizontal White-to-White Distance (HWTW). The aberrometry parameters include the most significant corneal higher-order aberrations (coma, trefoil, spherical aberration), and the Root Mean Square (RMS) of the higher-order aberrations. Repeatability was assessed using within-subject Standard Deviation (SDw), the repeatability limit (r), and the Intraclass Correlation Coefficient (ICC). Results: The current study included 120 eyes of 60 subjects with a mean age of 21±2.08 years (range: 18 to 28 years). The repeatability was good for all recorded biometric measurements, with the most repeatable being AL (r=0.028, SD=0.01). All values of ICC for biometric measurements revealed excellent repeatability, being over 0.994. In addition, coma and spherical aberrations had excellent repeatability with ICC =0.935, and RMS, trefoil, secondary astigmatism, and quadrafoil aberrations had good repeatability with ICC 0.938, 0.823, 0.898, and 0.827, respectively. Conclusion: The Pentacam® AXL demonstrated good repeatability for ocular biometry and corneal aberrations in healthy eyes. [ABSTRACT FROM AUTHOR]

To efficiently allocate medical resources at disaster sites, medical workers perform triage to prioritize medical treatments based on the severity of the wounded or sick. In such instances, evaluators often assess the severity status of the wounded or sick quickly, but their measurements are qualitative and rely on experience. Therefore, we developed a wearable device called Medic Hand in this study to extend the functionality of a medical worker's hand so as to measure multiple biometric indicators simultaneously without increasing the number of medical devices to be carried. Medic Hand was developed to quantitatively and efficiently evaluate "perfusion" during triage. Speed is essential during triage at disaster sites, where time and effort are often spared to attach medical devices to patients, so the use of Medic Hand as a biometric measurement device is more efficient for collecting biometric information. For Medic Hand to be handy during disasters, it is essential to understand and improve upon factors that facilitate its public acceptance. To this end, this paper reports on the usability evaluation of Medic Hand through a questionnaire survey of nonmedical workers. [ABSTRACT FROM AUTHOR]

The core premise of cancelable biometrics lies in the creation of a distinct biometric template for every individual, which can be either canceled or regenerated as needed. This process requires the use of a uniquely-defined key during the generation of such template. The generated templates are tailored to be key-specific. This ensures that each distinct key will generate a unique template, while preserving the integrity and security of the original biometric data, ensuring that it remains uncompromised. In this paper, a cancelable biometric system based on electrocardiography (ECG) and photoplethysmography (PPG) signals is introduced. A signal fusion process is implemented for the two traits to generate a single template per user. In order to enhance the security of generated templates, a well-designed permutation stage is implemented according to a user-specific key. The permutation key is obtained through a well-designed look-up table created by the authors. The user verification is conducted on the cancelable template, without the need for any inversion processes. The user verification scheme depends on a two-pronged approach: robust feature extraction followed by the application of a machine learning (ML) classifier. The mel-frequency cepstral coefficients (MFCCs) extraction algorithm is employed for feature extraction due to the low frequency range of the adopted biometric signals and the nonlinearity of the filter bank used for MFCC extraction. Several ML classifiers are adopted to validate the system with cancelable templates without any inversion process. Simulation results with multilayer perceptron (MLP) and logistic regression (LR) classifiers demonstrated superior effectiveness of the proposed authentication framework, with accuracy rates up to 100% and 99.7% on the pulse transit time PPG and BIDMC datasets, respectively. Hence, the proposed system proves effective access control and user verification in the Internet-of-Things (IoT) applications. [ABSTRACT FROM AUTHOR]

Background: Despite being integral to women's well-being, achieving good menstrual health (MH) remains a challenge. This study examined MH services uptake (including information, analgesics, and a choice of MH products - the menstrual cup and reusable pads) and sustained use of MH products within an integrated sexual and reproductive health intervention for young people in Zimbabwe. Methods: This mixed-methods study was nested within a cluster randomised trial of integrated sexual and reproductive health services (CHIEDZA) for youth in three provinces (Harare, Mashonaland East, and Bulawayo). The study collected qualitative and quantitative data from 27,725 female clients aged 16–24 years, who accessed CHIEDZA from April 2019 – March 2022. Using a biometric (fingerprint recognition) identification system, known as SIMPRINTS, uptake of MH information, products, and analgesics and other services was tracked for each client. Descriptive statistics and logistic regression were used to investigate MH service uptake and product choice and use over time, and the factors associated with these outcomes. Thematic analysis of focus group discussions and interviews were used to further explore providers' and participants' experiences of the MH service and CHIEDZA intervention. Results: Overall, 36,991 clients accessed CHIEDZA of whom 27,725 (75%) were female. Almost all (n = 26,448; 95.4%) took up the MH service at least once: 25433 took up an MH product with the majority (23,346; 92.8%) choosing reusable pads. The uptake of cups varied across province with Bulawayo province having the highest uptake (13.4%). Clients aged 20–24 years old were more likely to choose cups than reusable pads compared with those aged 16–19 years (9.4% vs 6.0%; p < 0.001). Over the implementation period, 300/1819 (16.5%) of clients swapped from the menstrual cup to reusable pads and 83/23346 (0.4%) swapped from reusable pads to the menstrual cup. Provision of the MH service encouraged uptake of other important SRH services. Qualitative findings highlighted the provision of free integrated SRH and MH services that included a choice of MH products and analgesics in a youth-friendly environment were key to high uptake and overall female engagement with SRH services. Conclusions: High uptake demonstrates how the MH service provided much needed access to MH products and information. Integration of MH within an SRH intervention proved central to young women accessing other SRH services. [ABSTRACT FROM AUTHOR]

Due to their user-friendliness and reliability, biometric systems have taken a central role in everyday digital identity management for all kinds of private, financial and governmental applications with increasing security requirements. A central security aspect of unsupervised biometric authentication systems is the presentation attack detection (PAD) mechanism, which defines the robustness to fake or altered biometric features. Artifacts like photos, artificial fingers, face masks and fake iris contact lenses are a general security threat for all biometric modalities. The Biometric Evaluation Center of the Institute of Safety and Security Research (ISF) at the University of Applied Sciences Bonn-Rhein-Sieg has specialized in the development of a near-infrared (NIR)-based contact-less detection technology that can distinguish between human skin and most artifact materials. This technology is highly adaptable and has already been successfully integrated into fingerprint scanners, face recognition devices and hand vein scanners. In this work, we introduce a cutting-edge, miniaturized near-infrared presentation attack detection (NIR-PAD) device. It includes an innovative signal processing chain and an integrated distance measurement feature to boost both reliability and resilience. We detail the device's modular configuration and conceptual decisions, highlighting its suitability as a versatile platform for sensor fusion and seamless integration into future biometric systems. This paper elucidates the technological foundations and conceptual framework of the NIR-PAD reference platform, alongside an exploration of its potential applications and prospective enhancements. [ABSTRACT FROM AUTHOR]

Background Methods Results Discussion Clinical Relevance Compared to other providers, nurses spend more time with patients, but the exact quantity and nature of those interactions remain largely unknown. The purpose of this study was to characterize the interactions of nurses at the bedside using continuous surveillance over a year long period.Nurses' time and activity at the bedside were characterized using a device that integrates the use of obfuscated computer vision in combination with a Bluetooth beacon on the nurses' identification badge to track nurses' activities at the bedside. The surveillance device (AUGi) was installed over 37 patient beds in two medical/surgical units in a major urban hospital. Forty‐nine nurse users were tracked using the beacon. Data were collected 4/15/19–3/15/20. Statistics were performed to describe nurses' time and activity at the bedside.A total of n = 408,588 interactions were analyzed over 670 shifts, with >1.5 times more interactions during day shifts (n = 247,273) compared to night shifts (n = 161,315); the mean interaction time was 3.34 s longer during nights than days (p < 0.0001). Each nurse had an average of 7.86 (standard deviation [SD] = 10.13) interactions per bed each shift and a mean total interaction time per bed of 9.39 min (SD = 14.16). On average, nurses covered 7.43 beds (SD = 4.03) per shift (day: mean = 7.80 beds/nurse/shift, SD = 3.87; night: mean = 7.07/nurse/shift, SD = 4.17). The mean time per hourly rounding (HR) was 69.5 s (SD = 98.07) and 50.1 s (SD = 56.58) for bedside shift report.As far as we are aware, this is the first study to provide continuous surveillance of nurse activities at the bedside over a year long period, 24 h/day, 7 days/week. We detected that nurses spend less than 1 min giving report at the bedside, and this is only completed 20.7% of the time. Additionally, hourly rounding was completed only 52.9% of the time and nurses spent only 9 min total with each patient per shift. Further study is needed to detect whether there is an optimal timing or duration of interactions to improve patient outcomes.Nursing time with the patient has been shown to improve patient outcomes but precise information about how much time nurses spend with patients has been heretofore unknown. By understanding minute‐by‐minute activities at the bedside over a full year, we provide a full picture of nursing activity; this can be used in the future to determine how these activities affect patient outcomes. [ABSTRACT FROM AUTHOR]

To investigate the associations between corneal curvature (CC) and other anterior segment biometrics in young myopic adults. In this retrospective multi-center study, 7893 young myopic adults were included. CC and other anterior segment biometrics were measured by Scheimpflug imaging (Pentacam). CC was defined as SimK at central 3 mm area, and other anterior segment biometrics included white-to-white corneal diameter (WTW), central corneal thickness (CCT), corneal volume (CV) at 3 mm, 5 mm, and 7 mm area, anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA), anterior corneal eccentricity (ACE) and asphericity (ACAP), posterior corneal eccentricity (PCE) and asphericity (PCAP), anterior chamber depth (ACD), and anterior chamber volume (ACV). Univariate regression analyses were used to assess the associations between CC and other anterior segment biometrics, and multivariate regression analyses were further performed to adjusted for age, gender and spherical equivalent. CC was higher in patients of female gender and higher myopia (all P < 0.05). Eyes in higher CC quartiles had lower WTW, thinner CCT, lower CV at 3 mm and 5 mm, lower ACD, and lower ACV (all P < 0.001), but had larger ACA, larger PCA, less PCE and less PCAP (all P < 0.001), compared to eyes in lower CC quartiles. The trends of CV at 7 mm, ACE and ACAP were inconsistent in different CC quartiles. After adjusting for age, gender and spherical equivalent with multivariate linear regression, CC was positively correlated to CV at 7 mm (βs = 0.069), ACA (βs = 0.194), PCA (βs = 0.187), ACE (βs = 0.072), PCAP (βs = 0.087), and ACD (βs = 0.027) (all P < 0.05), but was negatively correlated to WTW (βs = − 0.432), CCT (βs = − 0.087), CV-3 mm (βs = − 0.066), ACAP (βs = − 0.043), PCE (βs = − 0.062), and ACV (βs = − 0.188) (all P < 0.05). CC was associated with most of the other anterior segment biometrics in young myopic adults. These associations are important for better understanding of the interactions between different anterior segment structures in young myopic patients, and are also useful for the exploration of the pathogenesis of myopia. [ABSTRACT FROM AUTHOR]

Humanitarian organisations are increasingly utilising biometric data. However, we know little about the extent and scope of this practice, as its benefits and risks have attracted all the attention so far. This paper explores the biometric practices of the United Nations Refugee Agency, the United Nations World Food Programme, the International Committee of the Red Cross, Médecins Sans Frontières, and World Vision International. The study analysed relevant documents published over the past two decades and 17 semi‐structured interviews with humanitarian workers conducted between June 2021 and June 2022. The findings reveal that humanitarian organisations use diverse types and functions of biometric data for different services, collaborate with many actors, and employ various data protection measures. Ultimately, challenging the straightforward generalisations about the use of such data, the paper argues that variational applications of biometrics in the humanitarian context require case‐by‐case analysis, as each instance will likely produce a different outcome. [ABSTRACT FROM AUTHOR]

In this study, an internal fingerprint-guided epidermal thickness of fingertip skin is proposed for optical image encryption based on optical coherence tomography (OCT) combined with U-Net architecture of a convolutional neural network (CNN). The epidermal thickness of fingertip skin is calculated by the distance between the upper and lower boundaries of the epidermal layer in cross-sectional optical coherence tomography (OCT) images, which is segmented using CNN, and the internal fingerprint at the epidermis–dermis junction (DEJ) is extracted based on the maximum intensity projection (MIP) algorithm. The experimental results indicate that the internal fingerprint-guided epidermal thickness is insensitive to pressure due to normal correlation coefficients and the encryption process between epidermal thickness maps of fingertip skin under different pressures. In addition, the result of the numerical simulation demonstrates the feasibility and security of the encryption scheme by structural similarity index matrix (SSIM) analysis between the original image and the recovered image with the correct and error keys decryption, respectively. The robustness is analyzed based on the SSIM value in three aspects: different pressures, noise attacks, and data loss. Key randomness is valid by the gray histograms, and the average correlation coefficients of adjacent pixelated values in three directions and the average entropy were calculated. This study suggests that the epidermal thickness of fingertip skin could be seen as important biometric information for information encryption. [ABSTRACT FROM AUTHOR]

Biometric technology encompasses a proliferating array of data forms, applications, and stakeholders but has raised numerous social and ethical concerns. This article examines contending perceptions of biometrics by developing a three-way framework of science–society orderings, drawn from social studies of biometrics and wider science studies literature. By analysing documentary sources and participant observation data through this framework, the article identifies a series of distinct normative interpretations or imaginaries of biometrics. It is argued that these imaginaries, described, respectively, as 'public good', 'collective control', and 'societal risks', project contending normative framings of science–society relations. These imaginaries were also however found to reflexively encompass perceived challenges, giving rise to practices that I term imaginative politics. These findings raise the need for science policy studies to consider the distinction between imagining and realizing in greater depth and to consider more profoundly the politics of science–society co-production. [ABSTRACT FROM AUTHOR]

Objective: To compare the performance of two‐dimensional ultrasound (2D‐US), three‐dimensional ultrasound (3D‐US) and magnetic resonance imaging (MRI) at 36 weeks' gestation in predicting the delivery of a large‐for‐gestational‐age (LGA) neonate, defined as birth weight ≥ 95th percentile, in patients at high and low risk for macrosomia. Methods: This was a secondary analysis of a prospective observational study conducted between January 2017 and February 2019. Women with a singleton pregnancy at 36 weeks' gestation underwent 2D‐US, 3D‐US and MRI within 15 min for estimation of fetal weight. Weight estimations and birth weight were plotted on a growth curve to obtain percentiles for comparison. Participants were considered high risk if they had at least one of the following risk factors: diabetes mellitus, estimated fetal weight ≥ 90th percentile at the routine third‐trimester ultrasound examination, obesity (prepregnancy body mass index ≥ 30 kg/m2) or excessive weight gain during pregnancy. The outcome was the diagnostic performance of each modality in the prediction of birth weight ≥ 95th percentile, expressed as the area under the receiver‐operating‐characteristics curve (AUC), sensitivity, specificity and positive and negative predictive values. Results: A total of 965 women were included, of whom 533 (55.23%) were high risk and 432 (44.77%) were low risk. In the low‐risk group, the AUCs for birth weight ≥ 95th percentile were 0.982 for MRI, 0.964 for 2D‐US and 0.962 for 3D‐US; pairwise comparisons were non‐significant. In the high‐risk group, the AUCs were 0.959 for MRI, 0.909 for 2D‐US and 0.894 for 3D‐US. A statistically significant difference was noted between MRI and both 2D‐US (P = 0.002) and 3D‐US (P = 0.002), but not between 2D‐US and 3D‐US (P = 0.503). In the high‐risk group, MRI had the highest sensitivity (65.79%) compared with 2D‐US (36.84%, P = 0.002) and 3D‐US (21.05%, P < 0.001), whereas 3D‐US had the highest specificity (98.99%) compared with 2D‐US (96.77%, P = 0.005) and MRI (96.97%, P = 0.004). Conclusions: At 36 weeks' gestation, MRI has better performance compared with 2D‐US and 3D‐US in predicting birth weight ≥ 95th percentile in patients at high risk for macrosomia, whereas the performance of 2D‐US and 3D‐US is comparable. For low‐risk patients, the three modalities perform similarly. © 2023 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

Identifying individual animals, especially in large mammals, is an important goal for wildlife biologists and managers. Bears, occupying diverse habitats, face and experience significant conflict. Among Asian bears, the sloth bear Melursus ursinus (Shaw, 1791; Vulnerable IUCN Red List) is reported vulnerable due to negative interactions with humans, requiring solutions like identifying bear individuals using morphological features. To do so, we used an image-comparison algorithm to evaluate the uniqueness of chest markings using structural similarity index (SSIM) and trained a deep learning model based on the EfficientNet architecture for predicting an individual bear classification. We collected 1567 images (of 144 bears) to examine individual-level differences in chestmark patterns. The comparison yielded 98% accuracy in differentiating chestmarks as a unique pattern for an individual. Subsequently, we trained a circular classification model based on EfficientNet framework using augmented 5628 images for training (80%; of 115 bears), which was validated over 95% for top one and 99% for five individual predictions on 1407 testing images (20%; of 115 bears). The final step involved passing 58 non-augmented images (of 29 out-of-train bears), and the top five predictions of closely similar patterns suggested by the model were then manually compared for similarities in shapes, which suggested whether the image belonged to a new individual. The high accuracy of comparison and classification models suggests the potential applicability of this technique for helping maintain the ex-situ bear database, identifying the conflict individual and estimating bear populations. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms and the factors influencing the phenology, reproduction and biometrics of long-distance migrants are extremely important as global climate warming has induced changes in the locations of geographic ranges and dates of migration and reproduction. In this article, we compare phenology, reproductive parameters and adult biometrics of core and peripheral populations of a rare and endangered bird—the barred warbler Curruca nisoria—that inhabits the farming landscapes and makes long-distance trans-continental migrations. We predicted that: (i) individuals nesting in the core population would be larger than in the peripheral population; (ii) the reproductive parameters of the Barred Warblers in the core population would be higher than in the peripheral population. The Barred Warblers nesting in the centre of the range laid larger clutches and were clearly larger than individuals from the small, peripheral population. However, no differences in egg size and productivity were observed between the analysed populations. The Barred Warblers synchronised their breeding dates over a large geographical area as they had only a short time window for reproduction and had to lay their eggs as soon as possible. Individuals arriving earlier on the breeding grounds had larger clutches, longer wings and produced more nestlings. The pressure of the passage of time during the breeding season was a more important factor than the geographical location affecting the breeding characteristics in these populations. [ABSTRACT FROM AUTHOR]

Roots play a key role in withstanding wheat abiotic stress. In this work, we phenotyped seedling root morphology of two semi-dwarf bread wheat cultivars, the Chinese cv Lankaodali and the Italian cv Rebelde, under the hypothesis that these two genotypes have contrasting root traits and could be used as donors in breeding programs. Root development was compared in a semi-hydroponic screening, where full-strength (FS) vs. half-strength (HS) complete Hoagland's solution represented high and moderate nutrient availability, and a screening comparing HS solution with tap water corresponding to a condition of nutrient starvation. Genotypes were further compared in soil under full watering (100% of field capacity) vs. drought stress (50% of field capacity). Lankaodali outperformed Rebelde by producing 50% more leaf mass and 70% more root mass in FS solution, 125% more leaf mass and 106% more root mass in HS solution, and 65% more leaf mass and 36% more root mass under nutrient starvation. This cv also showed a positive correlation between leaf mass and root length and mass (between r = 0.82–0.9 and r = 0.83–0.87, respectively, p < 0.05). In the soil screening experiment, Lankaodali produced more biomass than Rebelde regardless of water availability, 48% more leaf mass, 32% more root mass, and 31% more absolute rhizosheath mass (average across water availability treatments). Lankaodali proved to be more responsive than Rebelde to both water and nutrient availability. High values of broad-sense heritability—ranging between 0.80 for root mass and 0.90 for length in a hydroponic screen and 0.85 for rhizosheath size in soil—indicate that these traits could be useful for breeding. [ABSTRACT FROM AUTHOR]

This paper presents a novel multitask learning framework for palmprint biometrics, which optimizes classification and hashing branches jointly. The classification branch within our framework facilitates the concurrent execution of three distinct tasks: identity recognition and classification of soft biometrics, encompassing gender and chirality. On the other hand, the hashing branch enables the generation of palmprint hash codes, optimizing for minimal storage as templates and efficient matching. The hashing branch derives the complementary information from these tasks by amalgamating knowledge acquired from the classification branch. This approach leads to superior overall performance compared to individual tasks in isolation. To enhance the effectiveness of multitask learning, two additional modules, an attention mechanism module and a customized gate control module, are introduced. These modules are vital in allocating higher weights to crucial channels and facilitating task-specific expert knowledge integration. Furthermore, an automatic weight adjustment module is incorporated to optimize the learning process further. This module fine-tunes the weights assigned to different tasks, improving performance. Integrating the three modules above has shown promising accuracies across various classification tasks and has notably improved authentication accuracy. The extensive experimental results validate the efficacy of our proposed framework. [ABSTRACT FROM AUTHOR]

Aim: Insular environments theoretically promote within‐species phenotypic variance, in part but not only because insular species enjoy a lower number of trophic interactions than their mainland counterparts. However, environmental factors apparently confound empirical comparisons between insular and mainland systems. To address this issue, we studied sympatric, congeneric species from the same small island, but that stemmed from separate colonization events. We predicted that the time since the species had colonized the island would correlate positively with the within‐species variance in morphometrics. Location: Lifu island, New Caledonia, South Pacific. Taxa: Zosterops inornatus, Z. minutus, Z. lateralis (Passeriformes). Methods: We measured seven morphological traits and used principal component analysis to compute axes of variation. Results: The within‐species variance in bill size and in feet/tail ratio corrected for body size increased with the estimated time since the species had been on the island. A similar but non‐significant trend existed for body size and bill width. Main Conclusions: The morphometrics of the three species of Zosterops birds from Lifu supported the hypothesis that insular environments promote within‐species phenotypic variance, and cast a new light on the role of competition in the erosion of phenotypic variance. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate postoperative outcomes after implantation of toric intraocular lenses (IOLs) made of high-water-content hydrophobic acrylic material in Japanese patients using a swept-source optical coherence tomography (SS-OCT) biometer integrated with a surgical guiding system. Patients and Methods: In this prospective observational study, toric IOL models CNW0T3 to CNW0T9 (Alcon) were implanted in 33 eyes of 33 patients and followed-up for one month. Powers and toric models were determined using an SS-OCT biometer ARGOS® Ver 1.5 (Alcon), and the IOLs were aligned using surgical guidance. Differences between planned and actual axis positions at the end of the surgery (misalignment) and rotations from the end of surgery to one month postoperatively were measured. Additionally, postoperative uncorrected visual acuity, refraction, and residual astigmatism were evaluated. Results: Mean and median misalignments were 2.3° (standard deviation [SD]: 1.6, 95% confidence interval [CI]: 1.7– 2.9) and 2°, and those of postoperative rotation were 2.4° (SD: 2.6, 95% CI: 1.5– 3.4) and 2°, respectively. Mean postoperative refraction was 0.06 D (SD: 0.62). Prediction errors within ± 0.5 and ± 1.0 D were 69.7% and 93.9%, respectively. Mean residual astigmatisms were 0.19 D (SD: 0.41), and mean uncorrected visual acuity was 0.00 logMAR (SD: 0.11), and 64% of the eyes scored 20/20 or better. Conclusion: Implantation of high-water-content hydrophobic acrylic toric IOLs using SS-OCT biometry integrated with a surgical guiding system effectively corrected corneal astigmatism with accurate IOL alignment in Japanese patients. [ABSTRACT FROM AUTHOR]

In order to ensure reliable inferences in scientific experiments, sampling criteria should be determined and defined during the experimental design phase. Determining plot and sample sizes without scientific criteria could result in resource and labor inefficiencies with no gain in experimental precision. In this work we estimate plot and sample sizes for biometric variable analyses in lettuce seedlings. The seedlings were sown in four expanded polystyrene foam transplant trays with 128 and 200 cells. Foliar area, stem diameter, shoot height, root length, root volume, root area, fresh and dry shoot and root masses. The methods described by Paranaiba (PARANAIBA et al., 2009) and Cochran (COCHRAN, 1977) were used for plot size and sample size estimations, respectively. Sample size varied according to the variables analysed and transplant tray cell number. Root variables required the highest number of samples. For a 10% margin of error, 12 seedlings were necessary for evaluations in a 128 cell tray, while 11 seedlings were required for analysis in 200 cell trays. [ABSTRACT FROM AUTHOR]

Tongue diagnosis is one of the important diagnostic methods in Kampo (traditional Japanese) medicine, in which the color and shape of the tongue are used to determine the patient's constitution and systemic symptoms. Tongue diagnosis is performed with the patient in the sitting or supine positions; however, the differences in tongue color in these two different positions have not been analyzed. We developed tongue image analyzing system (TIAS), which can quantify tongue color by capturing tongue images in the sitting and supine positions. We analyzed the effects on tongue color in two different body positions. Tongue color was quantified as L ∗ a ∗ b ∗ from tongue images of 18 patients in two different body positions by taking images with TIAS. The CIEDE 2000 color difference equation (ΔE00) was used to assess the difference in tongue color in two different body positions. Correlations were also determined between ΔE00, physical characteristics, and laboratory test values. The mean and median ΔE00 for 18 patients were 2.85 and 2.34, respectively. Of these patients, 77.8% had a ΔE00 < 4.1. A weak positive correlation was obtained between ΔE00 and systolic blood pressure and fasting plasma glucose. Approximately 80% of patients' tongue color did not change between the sitting and supine positions. This indicates that the diagnostic results of tongue color are trustworthy even if medical professionals perform tongue diagnosis in two different body positions. [ABSTRACT FROM AUTHOR]

Background: To assess the anterior scleral thickness (AST), Schlemm's canal diameter (SCD), trabecular meshwork diameter (TMD) and conjunctiva tenon capsule thickness (CTT) in high myopic (HM) subjects and HM subjects with glaucoma (HMG) compared to control eyes. Methods: One hundred and twenty eyes were included, and AST at 0, 1, 2 and 3 mm from the scleral spur, SCD, TMD and CTT were measured. Results: Mean age was 64.2 ± 11.0 years, and the temporal SCD and temporal TMD were significantly longer in the HMG subjects compared to the controls (380.0 ± 62 μm vs. 316.7 ± 72 μm, p = 0.001) and (637.6 ± 113 μm vs. 512.1 ± 97 μm, p = 0.000), respectively. There were no significant differences between the HM and HMG subjects in SCD and TMD (all p > 0.025). Compared to the HM subjects, the temporal AST0 (432.5 ± 79 μm vs. 532.8 ± 99 μm, p = 0.000), temporal AST1 (383.9 ± 64 μm vs. 460.5 ± 80 μm, p = 0.000), temporal AST2 (404.0 ± 68 μm vs. 464.0 ± 88 μm, p = 0.006) and temporal AST3 (403.0 ± 80 μm vs. 458.1 ± 91 μm, p = 0.014) were significantly thinner in the HMG group. No differences were found between the CTT in the three groups (all p > 0.025). Conclusions: Our data indicate a thinner AST in HMG subjects and no differences in SCD and TMD between HM and HMG subjects. [ABSTRACT FROM AUTHOR]