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PURPOSE: To assess the accuracy of intraoperative wavefront aberrometry (IWA) versus modern intraocular lens formulas in post-myopic laser vision correction (LVC) patients undergoing cataract surgery with capsular tension ring placement. METHODS: This is a retrospective chart review conducted at an academic outpatient center. All post-myopic LVC eyes undergoing cataract surgery with IWA from a single surgeon from 05/2017 to 12/2019 were included. All patients received a capsular tension ring (CTR). Mean numerical error (MNE), median numerical error (MedNE), and percentages of prediction error within 0.50D, 0.75D, and 1.00D were calculated for the above formulas. RESULTS: Twenty-seven post-myopic LVC eyes from 18 patients were included. In post-myopic LVC, MNE with Optiwave Refractive Analysis (ORA), Barrett True K (BTK), Haigis, Haigis-L, Shammas, SRK/T, Hill-RBF v3.0, and W-K AL-adjusted Holladay 1 were + 0.224, - 0.094, + 0.193, - 0.231, - 0.372, + 1.013, + 0.860, and + 0.630 (F = 8.49, p

The goal of information security is to prevent unauthorized access to data. There are several conventional ways to confirm user identity, such as using a password, user name, and keys. These conventional methods are rather limited; they can be stolen, lost, copied, or cracked. Because multimodal biometric identification systems are more secure and have higher recognition efficiency than unimodal biometric systems, they get attention. Single-modal biometric recognition systems perform poorly in real-world public security operations because of poor biometric data quality. Some of the drawbacks of current multimodal fusion methods include low generalization and single-level fusion. This study presents a novel multimodal biometric fusion model that significantly enhances accuracy and generalization through the power of artificial intelligence. Various fusion methods, encompassing pixel-level, feature-level, and score-level fusion, are seamlessly integrated through deep neural networks. At the pixel level, we employ spatial, channel, and intensity fusion strategies to optimize the fusion process. On the feature level, modality-specific branches and jointly optimized representation layers establish robust dependencies between modalities through backpropagation. Finally, intelligent fusion techniques, such as Rank-1 and modality evaluation, are harnessed to blend matching scores on the score level. To validate the model's effectiveness, we construct a virtual homogeneous multimodal dataset using simulated operational data. Experimental results showcase significant improvements compared to single-modal algorithms, with a remarkable 2.2 percentage point increase in accuracy achieved through multimodal feature fusion. The score fusion method surpasses single-modal algorithms by 3.5 percentage points, reaching an impressive retrieval accuracy of 99.6%. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions The purpose of this study was to simulate the impact of biometric measure uncertainties, lens equivalent and toric power labelling tolerances and axis alignment errors on the refractive outcome after cataract surgery with toric lens implantation.In this retrospective non‐randomised cross sectional Monte‐Carlo simulation study we evaluated a dataset containing 7458 LenStar 900 preoperative biometric measurements. The biometric uncertainties from literature, lens power labelling according to ISO 11979, and axis alignment tolerances of a modern toric lens (Hoya Vivinex) were taken to be normally distributed and used in a Monte‐Carlo simulation with 100 000 samples per eye. The target variable was the defocus equivalent (DEQ) derived using the Castrop (DEQC) and the Haigis (DEQH) formulae.Mean/median / 90% quantile DEQC was 0.22/0.21/0.36 D and DEQH was 0.20/0.19/0.32 D. Ignoring the variation in lens power labelling and toric axis alignment the respective DEQC was 0.20/0.19/0.32 D and DEQH was 0.18/0.17/0.29 D. DEQC and DEQH increased with shorter eyes, steeper corneas, equivalent lens power and highly with toric lens power.According to our simulation results, uncertainties in biometric measures, lens power labelling tolerances, and axis alignment errors are responsible for a significant part of the refraction prediction error after cataract surgery with toric lens implantation. Additional labelling of the exact equivalent and toric power on the lens package could be a step to improve postoperative results. [ABSTRACT FROM AUTHOR]

The broad usage of mobile devices nowadays, the sensitiveness of the information contained in them, and the shortcomings of current mobile user authentication methods are calling for novel, secure, and unobtrusive solutions to verify the users' identity. In this article, we propose TypeFormer, a novel transformer architecture to model free-text keystroke dynamics performed on mobile devices for the purpose of user authentication. The proposed model consists in temporal and channel modules enclosing two long short-term memory recurrent layers, Gaussian range encoding, a multi-head self-attention mechanism, and a block-recurrent transformer layer. Experimenting on one of the largest public databases to date, the Aalto mobile keystroke database, TypeFormer outperforms current state-of-the-art systems achieving equal error rate values of 3.25% using only five enrolment sessions of 50 keystrokes each. In such way, we contribute to reducing the traditional performance gap of the challenging mobile free-text scenario with respect to its desktop and fixed-text counterparts. To highlight the design rationale, an analysis of the experimental results of the different modules implemented in the development of TypeFormer is carried out. Additionally, we analyse the behaviour of the model with different experimental configurations such as the length of the keystroke sequences and the amount of enrolment sessions, showing margin for improvement. [ABSTRACT FROM AUTHOR]

Cancelable template protection techniques are indispensable to provide essential security and privacy privileges in biometric systems. This paper introduces an efficient cancelable palmprint recognition technique based on multi-level transformations. Gabor filtering with feature remapping is introduced for extracting highly discriminative features. Histogram remapping is applied to nonlinearly transform the downsampled Gabor features to be normally distributed. This feature-remapping step is proposed to enhance the discriminatory power and alleviate the effect of feature variability and image artifacts. Comb filtering is applied to the mapped features as a first protection layer. To provide security guarantees against linkability attacks, index-based locality-sensitive hashing (LSH) is introduced as a second protection layer to transform the comb-filtered mapped real-valued features into maximum-ranked indices. Recognition is performed in the secured domain to accelerate matching and to preserve the user's privacy. Results show that the proposed scheme provides a large re-issuance ability, protects templates from being inverted, and demonstrates strong unlinkability across different databases. In addition, favorable verification/identification accuracy is obtained and the system satisfies the needs for real-time applications. A global measure D ↔ sys value of 0.01 is obtained, and thus, correlation attacks are mitigated. The recognition results for the legitimate scenario are 100% identification accuracy and 0% EER. For the worst case (same token scenario), the corresponding results are 99.752% and 0.31%, respectively. Highlights: • Multi-level transformations are proposed for efficient cancelable palmprints. • Histogram-remapped downsampled Gabor features are subjected to comb filtering. • Locality-sensitive hashing follows comb filtering to obtain maximum-ranked indices. • The algorithm provides significant capability for re-issuance. • The system protects templates from inversion and ensures unlinkability across databases. [ABSTRACT FROM AUTHOR]

Generating human images from open-vocabulary text descriptions is an exciting but challenging task. Previous methods (i.e., Text2Human) face two challenging problems: (1) they cannot well handle the open-vocabulary setting by arbitrary text inputs (i.e., unseen clothing appearances) and heavily rely on limited preset words (i.e., pattern styles of clothing appearances); (2) the generated human image is inaccuracy in open-vocabulary settings. To alleviate these drawbacks, we propose a flexible diffusion-based framework, namely HumanDiffusion, for open-vocabulary text-driven human image generation (HIG). The proposed framework mainly consists of two novel modules: the Stylized Memory Retrieval (SMR) module and the Multi-scale Feature Mapping (MFM) module. Encoded by the vision-language pretrained CLIP model, we obtain coarse features of the local human appearance. Then, the SMR module utilizes an external database that contains clothing texture details to refine the initial coarse features. Through SMR refreshing, we can achieve the HIG task with arbitrary text inputs, and the range of expression styles is greatly expanded. Later, the MFM module embedding in the diffusion backbone can learn fine-grained appearance features, which effectively achieves precise semantic-coherence alignment of different body parts with appearance features and realizes the accurate expression of desired human appearance. The seamless combination of the proposed novel modules in HumanDiffusion realizes the freestyle and high accuracy of text-guided HIG and editing tasks. Extensive experiments demonstrate that the proposed method can achieve state-of-the-art (SOTA) performance, especially in the open-vocabulary setting. [ABSTRACT FROM AUTHOR]

Palmprint as biometrics has gained increasing attention recently due to its discriminative ability and robustness. However, existing methods mainly improve palmprint verification within one spectrum, which is challenging to verify across different spectrums. Additionally, in distributed server-client-based deployment, palmprint verification systems predominantly necessitate clients to transmit private data for model training on the centralized server, thereby engendering privacy apprehensions. To alleviate the above issues, in this paper, we propose a physics-driven spectrum-consistent federated learning method for palmprint verification, dubbed as PSFed-Palm. PSFed-Palm draws upon the inherent physical properties of distinct wavelength spectrums, wherein images acquired under similar wavelengths display heightened resemblances. Our approach first partitions clients into short- and long-spectrum groups according to the wavelength range of their local spectrum images. Subsequently, we introduce anchor models for short- and long-spectrum, which constrain the optimization directions of local models associated with long- and short-spectrum images. Specifically, a spectrum-consistent loss that enforces the model parameters and feature representation to align with their corresponding anchor models is designed. Finally, we impose constraints on the local models to ensure their consistency with the global model, effectively preventing model drift. This measure guarantees spectrum consistency while protecting data privacy, as there is no need to share local data. Extensive experiments are conducted to validate the efficacy of our proposed PSFed-Palm approach. The proposed PSFed-Palm demonstrates compelling performance despite only a limited number of training data. The codes have been released at https://github.com/Zi-YuanYang/PSFed-Palm. [ABSTRACT FROM AUTHOR]

Palmprint is a promising biometric modality and has several advantages. However, many serious challenges severely restrict the development of palmprint recognition in mobile environments. Double-line-single-point (DLSP), as a state-of-the-art assisting graph, can be free from pre-processing, and effectively reduce the errors of pre-processing; however, its accuracy heavily depends on users' cooperation and operation proficiency. This paper proposes boundary line calibration (BLC) and finger valley calibration (FVC) to suppress the translational dislocations in DLSP. Firstly, the samples acquired according to DLSP are rotated around the center so that the assisting lines are horizontal. Secondly, a rectangular area is cropped as the region of line detection (RLD) with the assisting line as the reference; while a rectangular area is cropped as the region of point detection (RPD) with the assisting point as the reference. The cropped rectangular regions are convolved with Gabor filters along an optimized direction to enhance edges. The accurate palm boundary is localized in RLD to reduce the vertical dislocation; and the accurate inter-finger valley point (IFVP) is localized in RPD to reduce the horizontal dislocation. The sufficient experiments show that the proposed algorithm can calibrate the translational dislocations caused by users' imperfect cooperation, and accordingly remarkably improve the accuracy and users' comfort. [ABSTRACT FROM AUTHOR]

Hand vein identification stands out to be an increasingly popular approach for biometric identification due to its distinctiveness and convenience. While state-of-the-art techniques are able to achieve good performance, they share two common drawbacks: (1) complex preprocessing procedures, e.g., vein enhancement and Region of Interest (ROI) extraction, and (2) vein information loss due to hand ROI partition. To address these issues, we propose VeinTr, an end-to-end full-hand vein identification approach. In particular, our VeinTr consists of three components: a local feature extractor, a lightweight transformer, and a global feature decoder. We first obtain local features via convolution-based ResNet-like blocks. Then the attention mechanism is employed to aggregate global features from local features, which can be then decoded as global hand vein features. Finally, a global feature decoder is applied to generate robust hand features. By doing so, VeinTr is capable of directly extracting robust hand vein features from raw hand vein images. We evaluate our method on CASIA, TPV, and PLUSVein hand vein datasets. Experimental results show that our approach outperforms the state-of-the-art methods and has strong inter-dataset generalization abilities. [ABSTRACT FROM AUTHOR]

Likelihood ratios compare two values (i.e., case rates) in order to illustrate the magnitude of the difference between the two. This ratio increases the confidence one can have in a diagnostic test from a different vantage point than that of sensitivity and specificity. The calculations of likelihood ratios are presented along with a simplified approach. Likelihood ratios are another tool the toxicologist should employ in their understanding of statistics and probability. [ABSTRACT FROM AUTHOR]

Predicting video virality is the holy grail of marketing today. Previous video virality prediction research has relied upon two processes that may lead to incomplete data or incomplete analyses: non-subconscious data collection and self-reporting. This exploratory study evaluates the potential of using a physiological manifestation of emotions captured through facial expressions and skin conductance to predict video viewer engagement across the viewing experience. In the context of video virality and user-focused emotional response, an experiment with 64 subjects viewing 13 videos collected facial expression and galvanic skin response data during the entire viewing experience. XGBoost classifier was deployed using 42 collected features (physiological data and socio-behavioural responses). The selected classifier could predict user engagement with over 80% accuracy. In addition to socio-demographic data and behavioural features, the predictive model identified several facial expression-based features, including action units (mouth open, cheek raise, eye closure, lip raise, and smile), emotions (joy), engagement and positive valence along with head movement (attention) and arousal (GSR peaks) as the most impactful. This study confirms the predictive capability of physiological data and elevates the value and need to understand further the role of viewers' physiological and subconscious responses to video content across the viewing experience. [ABSTRACT FROM AUTHOR]

Existing data reveals prevalent performance and image-enhancing drug (PIED) use in specific global regions and higher rates among athletes, however, research on performance-enhancement experiences among elite untested athletes is lacking. Drawing on conceptual frameworks that emphasize the intersection of context and practice, this research aims to gain insights into the subjective perspectives, motivations, and challenges faced by athletes in managing and optimizing their performance while using PIEDs. In-depth interviews were conducted with seventeen strength sports athletes, including powerlifters and bodybuilders, who had competed at national and/or international levels within untested federations. Thematic analysis was employed to examine the interview data within a social constructivist ontology. Findings revealed that PIEDs have dual roles as tools for enhanced recovery and heightened training stress, a delicate balance that aligns with Foucault's notion of self-transformation through technological advancements. These substances exerted power beyond consumption events with long-term psychological effects such as anxiety and irrational behavior emerging as key concerns. Peers with lived experience were key actors in the relationship between responsible drug management, however, the need for informed guidance was acknowledged. Non-human actors, notably biometric data tracking, played a pivotal role in guiding substance consumption. The study underscores the need for further research and tailored frameworks to support the health and well-being of athletes in this domain while addressing the broader implications of PIED use in public health discourse. Specifically, this study highlights the significance of integrating lived experiences and social contexts, emphasizing the need for nuanced harm-reduction strategies in this space. [ABSTRACT FROM AUTHOR]

A signature is a biometric attribute commonly used for identity verification. It can be represented by a shape created with a classic pen, but it can also contain dynamic information. This information is acquired using a digital input device, such as a graphic tablet or a digital screen and stylus. Information about the dynamics of the signing process is stored in the form of signals that change over time, including pen velocity, pressure, and more. These dynamics are characteristic of an individual and are difficult for a human to forge. However, it is an interesting research issue whether the values of signals describing a dynamic signature can be predicted using artificial intelligence methods. Predicting the dynamics of the signals describing a signature would benefit various scientific problems, including improving the quality of reference signals by detecting anomalies, creating signature templates better suited to individuals, and more effectively detecting potential forgeries by identity verification systems. In this paper, we propose a method for predicting dynamic signature signals using an artificial neural network. The method was evaluated using samples collected in the DeepSignDB database, distributed by BiDA Lab. [ABSTRACT FROM AUTHOR]

In today's digital era, ensuring robust and secure authentication mechanisms is crucial. Multi-fusion biometric authentication systems have emerged as a powerful solution to enhance security and reliability by integrating multiple biometric traits. This paper presents a novel Multi-Fusion Biometric Authentication approach using Minutiae-Driven Fixed-Size Template Matching (MFTM). The proposed method leverages the unique features of minutiae points in fingerprints and combines them with other biometric modalities, such as iris and facial recognition, to create a fixed-size template for matching. The fusion process involves extracting and normalizing minutiae points from the fingerprint, followed by their integration with iris and facial features using a robust feature fusion algorithm. The fixed-size template ensures consistency and efficiency in the matching process, addressing challenges related to template size variability and computational overhead. Extensive experiments conducted on standard biometric datasets demonstrate that the proposed MFTM approach significantly enhances authentication accuracy, reduces false acceptance and rejection rates, and provides a highly secure and scalable authentication solution suitable for various applications, including access control and identity verification. The results show an authentication accuracy of 98.7%, a false acceptance rate (FAR) of 0.2%, and a false rejection rate (FRR) of 0.5%. Additionally, the computational time for matching is reduced by 25% compared to traditional methods, highlighting the efficiency and practicality of the proposed approach. [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing interest in biometric recognition based on finger dorsal patterns, making it a significant area of research. This paper introduces a biometric classification system that utilizes dorsal finger middle creases. The viability of this trait is assessed through the implementation of a new method known as multi block circular shift combination local binary pattern (MBCSC-LBP). The MBCSC-LBP approach involves dividing the image into multiple blocks to enhance robustness and capture both local and global information, thereby extracting discriminative features. These features from each block are then concatenated to form a comprehensive feature vector. To evaluate the accuracy of the proposed MBCSC-LBP feature extractor, a support vector machine (SVM) with a linear kernel is utilized. The classification accuracy achieved by this method is 96.22% indicating a promising performance. [ABSTRACT FROM AUTHOR]

Purpose. To compare biometric and optical coherence tomography parameters as well as refractive status in preterm children aged 4–8 years with or without retinopathy of prematurity (ROP), and evaluate their correlations with age and gender‐matched full‐term children. Methods. Retrospective comparative cohort study of four groups of children. Children with a history of preterm birth, including ROP who received intravitreal bevacizumab (IVB) treatment, children with a history of ROP that regressed without treatment and those with no history of ROP were compared to age and gender‐matched full‐term children as a control group. Best corrected visual acuity (BCVA), spherical equivalent of refraction (SE), macular and choroidal thickness, as well as biometric parameters was measured. Results. A total of 120 eyes of 120 children (30 children in each group) were included. There was no significant difference in BCVA, SE, and subjective cylinder between groups (p = 0.05, p = 0.3, p = 0.6, respectively). Axial length was significantly shorter, and the cornea was steeper in both ROP groups than in other groups (p = 0.001, p < 0.001, respectively). The central macular thickness was significantly thicker in the treated, regressed ROP and preterm groups than in full‐term children (p < 0.001). The gestational age was negatively correlated with macular thickness in both treated and regressed ROP groups (r = −0.517; p = 0.003, r = − 0.490; p = 0.006, respectively). Conclusions. Children with a history of ROP had a shorter axial length, steeper cornea, and thicker macula that correlated with lower gestational age. [ABSTRACT FROM AUTHOR]

Purpose: To compare the biometric measurements obtained from the Pentacam AXL Wave, IOLMaster 700, and ANTERION and calculate the recommended intraocular lens power using the Barrett Formulae. Methods: This was a retrospective cross-sectional study of patients who underwent biometry using the Pentacam AXL Wave, IOLMaster 700, and ANTERION. Flat keratometry (K1), steep keratometry (K2), anterior chamber depth (ACD), and axial length (AL) from each device were measured and compared. These parameters were used to calculate the recommended IOL powers using the Barrett formula. Results: The study included 252 eyes of 153 patients. The IOLMaster had the highest acquisition rate among the two biometers. The Pentacam obtained the shortest mean AL, the IOLMaster measured the highest mean keratometry values, and the ANTERION measured the highest mean ACD. In terms of pairwise comparisons, keratometry and axial length were not significantly different between the Pentacam-IOLMaster and ANTERION-IOLMaster groups, while the rest of the pairwise comparisons were statistically significant. In nontoric and toric eyes, 35–45% of patients recommended the same sphere of IOL power. In another 30–40%, the Pentacam and ANTERION recommended an IOL power one step greater than that of the IOLMaster-derived data. 50% of the study population recommended the same toric-cylinder IOL power. Conclusions: The Pentacam AXL Wave, IOLMaster 700, and ANTERION can reliably provide data for IOL power calculations; however, these data are not interchangeable. In nontoric and toric eyes, 35–45% of cases recommended the same sphere IOL power, and in another 30–40%, the Pentacam and ANTERION recommended one-step higher IOL power than the IOLMaster-derived data. In targeting emmetropia, selecting the first plus IOL power is advisable when using the Pentacam and ANTERION to approximate the IOL power calculations recommended by the IOLMaster 700. [ABSTRACT FROM AUTHOR]

Count regression models, particularly negative binomial regression (NBR), are widely used in various fields, including biometrics, ecology, and insurance. Over-dispersion is likely when dealing with count data, and NBR has gained attention as an effective tool to address this challenge. However, multicollinearity among covariates and the presence of outliers can lead to inflated confidence intervals and inaccurate predictions in the model. This study proposes a comprehensive approach integrating robust and regularization techniques to handle the simultaneous impact of multicollinearity and outliers in the negative binomial regression model (NBRM). We investigate the estimators' performance through extensive simulation studies and provide analytical comparisons. The simulation results and the theoretical comparisons demonstrate the superiority of the proposed robust hybrid KL estimator (M-NBKLE) with predictive accuracy and stability when multicollinearity and outliers exist. We illustrate the application of our methodology by analyzing a forestry dataset. Our findings complement and reinforce the simulation and theoretical results. [ABSTRACT FROM AUTHOR]

Over the last decades, magnetic resonance imaging (MRI) has emerged as a valuable adjunct to prenatal ultrasound for evaluating fetal malformations. Several radiological societies advocate for standardised and structured reporting practices to enhance the uniformity of imaging language. Compared to narrative formats, standardised and structured reports offer enhanced content quality, minimise reader variability, have the potential to save reporting time, and streamline the communication between specialists by employing a shared lexicon. Structured reporting holds promise for mitigating medico-legal liability, while also facilitating rigorous scientific data analyses and the development of standardised databases. While structured reporting templates for fetal MRI are already in use in some centres, specific recommendations and/or guidelines from international societies are scarce in the literature. The purpose of this paper is to propose a standardised and structured reporting template for fetal MRI to assist radiologists, particularly those with less experience, in delivering systematic reports. Additionally, the paper aims to offer an overview of the anatomical structures that necessitate reporting and the prevalent normative values for fetal biometrics found in current literature. [ABSTRACT FROM AUTHOR]

The Later Iron Age in Britain was a transformative period: material culture, settlement patterns, technology, trade networks, and the structures of power changed, ultimately leading to the Roman invasion. This paper examines the significance of investigating animal economies in this period within the broader context of socio‐economic developments. It reviews the available evidence regarding animal economies in this period, integrates new osteometric analyses, and discusses diachronic changes using the Roman evidence on a comparative basis. The investigation shows a broad pattern of continuity of practice, with relatively uniform livestock types and management strategies until the very end of the Iron Age. This suggests that the trajectory of local farming practices was largely independent from Mediterranean developments. This study contributes to a deeper understanding of Iron Age societies and their response to external influences, while also informing future research directions in archaeology. [ABSTRACT FROM AUTHOR]

The quality score of a biometric sample is intended to predict the sample's degree of utility for biometric recognition. Different authors proposed different definitions for utility. A harmonized definition of utility would be useful to facilitate the comparison of biometric sample quality assessment algorithms. In this article, we compare different definitions of utility and apply them to both face image and fingerprint image data sets containing multiple samples per biometric instance and covering a wide range of potential quality issues. The results differ only slightly. We show that discarding samples with low utility scores results in rapidly declining false non-match rates. The obtained utility scores can be used as target labels for training biometric sample quality assessment algorithms and as baseline when summarizing utility-prediction performance in a single plot or even in a single figure of merit. [ABSTRACT FROM AUTHOR]

A large number of images are available on the Internet with the growth of social networking services, and many of them are face photos or contain faces. It is necessary to protect the privacy of face images to prevent their malicious use by face image de-identification techniques that make face recognition difficult, which prevent the collection of specific face images using face recognition. In this paper, we propose a face image de-identification method that generates a de-identified image from an input face image by embedding facial features extracted from that of another person into the input face image. We develop the novel framework for embedding facial features into a face image and loss functions based on images and features to de-identify a face image preserving its appearance. Through a set of experiments using public face image datasets, we demonstrate that the proposed method exhibits higher de-identification performance against unknown face recognition models than conventional methods while preserving the appearance of the input face images. [ABSTRACT FROM AUTHOR]

Introduction Modern warfare operations are volatile, highly complex environments, placing immense physiological, psychological, and cognitive demands on the warfighter. To maximize cognitive performance and warfighter resilience and readiness, training must address psychological stress to enhance performance. Resilience in the face of adversity is fundamentally rooted in an individual's psychophysiological stress response and optimized through decreased susceptibility to the negative impact of trauma exposure. The current project aims to optimize warfighter expertise, resilience, adaptability, and performance by utilizing a validated Full Dive Virtual Reality (FDVR) training platform to provide high-fidelity, safe, and scalable, controlled stress exposure in highly realistic simulated training scenarios with the most advanced, immersive technology available. Materials and Methods Following Institutional Review Board approval and consent, 2 operators were fitted with high-fidelity virtual reality headsets with hand and eye tracking, full-body haptic feedback suits, a 360° omnidirectional treadmill, and Food and Drug Administration (FDA) cleared biometric monitors. Following acclimation, operators were placed in an industrial fire scenario and instructed to respond as a firefighter and paramedic, to search for and resuscitate any casualties, extinguish the fire, and exfiltrate safely. Following initial acclimation and after each demonstration (n  = 2), 3 semistructured interviews asked operators their perceptions and experiences related to FDVR, focusing on usability, feasibility, and safety. Biometric data were continuously recorded using the Caretaker Medical VitalStream. Results Proof-of-concept (POC) testing proved that the FDVR training platform is usable, safe, and feasible. It creates an immersive environment with physiological responses to mimic realistic Mass Casualty Events (MCEs). Using a case study approach, transcript data were analyzed using thematic analysis. Three major themes emerged: Sensory deficits reduced realism, but sensory feedback improved fidelity, vestibular discord affected the virtual reality experience but only when the system did not respond naturally to operator movement after acclimation, and movement accommodations were made by operators to enhance usability, especially for fine motor movements. Biometric data analysis correlated timestamps from the VitalStream unit with operator responses to stress-inducing events (i.e. explosions, fires, and a deceased victim). Both operators exhibited significant physiological responses, including elevated heart rate, systolic blood pressure, and mean arterial pressure, particularly following explosions, encountering fire, and encountering the deceased victim within the training environment. Conclusions The FDVR training platform overcomes the obstacles of in-person simulation training and provides the closest to real-life experience available. It will allow warfighters to train with their teams in immersive environments that replicate the conditions in which they are expected to perform their duties. The POC demonstrated that physiological responses can be mapped to scenario events to allow tracking of stress responses, cognitive load, as well as performance, and decision-making of the warfighter. The POC only involved 2 operators, but served to prove that the platform was safe and effective. Future testing plans to include 200 warfighters in operational teams of 10 to 12 to further validate the training effectiveness of the FDVR platform. [ABSTRACT FROM AUTHOR]

Morphometric characteristics of fishes were observable characteristics that are set of largely statistical methods used for examining variations in body size and shape. The objectives taken for the current study were to examine the complete morpho-biology of Schizothorax richardsonii from three major snow-fed rivers of the Kumaun Himalaya in Uttarakhand, India, and to establish the statistical relationship among various morphological characteristics related to body size and fin shape. In this study 120 fish specimen including 66 male and 54 female were studied for one year. Twelve distinct morphometric and five meristic counts had been examined in percentage of their body length and head length respectively. For biostatistics, the data was analysed by using various statistical methods including summary statistics, correlation, PCA analysis, Barlett’s test of sphericity, and multiple linear regression. Fish samples studied were found within the range of 17.7 – 42.2 cm in TL and BW from 60 - 780 gm. Morphological characteristics had high coefficient of correlation (r ≥ 0.90), indicating the characters' strong relationship, with the highest correlation (r = 0.99). Additionally, the coefficient of determination (R² ) value was found within the range of 0.62 to 0.99, which shows a significant relationship between the morphometric characteristics. PCA analysis revealed the major significance found among parameters, together with regression analysis. This study will provide a baseline data and a valuable insight into the population dynamics, and may contribute to the development of more effective strategies for the management. [ABSTRACT FROM AUTHOR]

The delivery of academic statistical collaboration resources can vary among types of institutions and across time. In particular, this variation might occur in the management of infrastructure and the business model, the staffing model and opportunities for staff development. In this manuscript, we present examples of these three themes in modern academic statistical collaboration units and describe key advantages and challenges. [ABSTRACT FROM AUTHOR]

Members of the ASA's Section on Statistical Consulting established the Pathways to Promotion Committee in 2021 to provide guidance and support for navigating a career as a collaborative statistician. In three years of existence, the Committee has produced seven webinars on relevant topics, each attended by more than one hundred participants. Committee members have given four oral presentations, organized three roundtables, led multiple discussions at ASA meetings and published four articles. These efforts have inspired, created and facilitated new connections for collaborative statisticians who feel isolated in their career path. This paper describes the formation and development of the Committee, reports its impact on the community of collaborative statisticians and discusses potential future directions. [ABSTRACT FROM AUTHOR]

Background/Objectives: To evaluate the advanced lens measurement approach (ALMA) formula accuracy using different lens constants available on the user group for laser interference biometry (ULIB) and IOL Con platforms. Methods: In this retrospective, comparative, case-series study, 150 eyes of 160 patients with previous myopic Photorefractive Keratectomy (PRK) or laser-assisted in situ keratomileusis (LASIK), who underwent uneventful cataract surgery and IOL implantation, were examined. The ALMA formula was evaluated to calculate the refractive prediction error (PE), analysing four different categories of lens constants: both nominal and optimized A-Constant for SRKT, which are available on the ULIB and IOL Con platforms. An additional analysis was carried out in this study, evaluating if a decreased ULIB optimized constant (DUOC) with different fixed factors (−1.2 −1.3 −1.4 −1.5) could improve refractive outcomes. Median absolute error (MedAE) and percentage of eyes within ±0.50 and ±1.00 diopters (D) of prediction error were measured as the main outcomes. Results: Comparing the lens factors available on ULIB and IOL Con platforms, the ALMA formula reported a lower MedAE and higher percentages of eyes with a refractive PE within 1.0 D using ULIB nominal constants (all p < 0.05). Using DUOC (−1.3), and there was a statistically significant improvement of both MedAE and of the percentages of eyes with PE within ±0.50 D with the ALMA method compared to nominal ULIB constants (all p < 0.05). Conclusions: The impact of different lens factors in the IOL power calculation after myopic LRS should be carefully evaluated. The ALMA formula, in the absence of optimized constants by zeroing the mean error, should be used by subtracting 1.3 from the optimized ULIB constants available on the IOL Con website. This finding suggests further studies to test which of these constants could work better with the other post-refractive surgery formulas. [ABSTRACT FROM AUTHOR]

Background: This study aims to compare the refractive outcomes of cataract surgery using two different biometry devices, the IOL Master 500 and IOL Master 700, and to investigate the influence of patient-related factors on these outcomes. Methods: In this retrospective study, we analyzed data from 2994 eyes that underwent cataract surgery. Multiple linear regression analyses were performed to examine the impact of the biometry device (IOL Master 500 or IOL Master 700), patient age, time elapsed between biometry and surgery, gender, and insurance status, as well as biometric parameters (anterior chamber depth, axial length, and corneal curvature), on postoperative refractive outcomes, specifically the deviation from target refraction. Results: The choice of the IOL Master device did not result in a statistically significant difference between the two devices (p = 0.205). Age (p = 0.006) and gender (p = 0.001) were identified as significant predictors of refractive outcomes, with older patients and males experiencing slightly more hyperopic outcomes compared to younger patients and females, respectively. The time elapsed between biometry and surgery and insurance status did not significantly influence the refractive outcomes. Conclusions: Our study, supported by a large cohort and a diverse group of patients representing typical anatomical variants seen in cataract surgery, supports the thesis that the IOL Master 500 and IOL Master 700 can be regarded as equivalent and effective for biometry in cataract surgery. The differences between the devices were negligible. Therefore, switching between the devices is safe for bilateral patients. [ABSTRACT FROM AUTHOR]

Reliance on null hypothesis significance testing often leads to misinterpretation of research results. Common misinterpretations include that a statistically nonsignificant difference (p ≥ 0.05) implies no difference between groups, and that a statistically significant finding (p < 0.05) is unbiased and clinically important. We aimed to develop a tool — the Conclusion Generator — to mitigate these misconceptions. We reviewed the content of the Conclusion Generator and validated its output using published and simulated data. The Conclusion Generator is a free online application designed to generate conclusions for scientific papers based on the values and clinical interpretation of the point estimate and confidence interval. Both relative and absolute measures of effect are supported. It offers two modes for interpretation: (1) Statistical mode provides an accurate statistical interpretation of results, with an optional specification of superiority and noninferiority bounds; (2) Clinical mode evaluates the clinical importance of the point estimate and confidence limits as specified by the user. Both modes assume no uncontrolled biases. Users must specify the number of decimals, the direction of a beneficial effect (e.g. , relative risk <1 vs. >1), and the level of detail (concise vs. elaborated) for the output. The validation confirmed the Conclusion Generator's capability to interpret research results, considering random error and clinical relevance, while avoiding common misinterpretations associated with null hypothesis significance testing. The Conclusion Generator facilitates an appropriate interpretation of research results by emphasizing estimation and clinical relevance over hypothesis testing. [ABSTRACT FROM AUTHOR]

In contexts requiring user authentication, such as financial, legal, and administrative systems, signature verification emerges as a pivotal biometric method. Specifically, handwritten signature verification stands out prominently for document authentication. Despite the effectiveness of triplet loss similarity networks in extracting and comparing signatures with forged samples, conventional deep learning models often inadequately capture individual writing styles, resulting in suboptimal performance. Addressing this limitation, our study employs a triplet loss Siamese similarity network for offline signature verification, irrespective of the author. Through experimentation on five publicly available signature datasets—4NSigComp2012, SigComp2011, 4NSigComp2010, and BHsig260—various distance measure techniques alongside the triplet Siamese Similarity Network (tSSN) were evaluated. Our findings underscore the superiority of the tSSN approach, particularly when coupled with the Manhattan distance measure, in achieving enhanced verification accuracy, thereby demonstrating its efficacy in scenarios characterized by close signature similarity. [ABSTRACT FROM AUTHOR]

The gait variable minimum toe clearance (MTC) has been investigated concerning trip-related fall research in older adults. However, comparing studies is difficult due to the different methods used to measure MTC and shoe conditions, which may affect agreement. Measurement methods can include using a single virtual point (SVP), multiple virtual points (MVPS), or metatarsal head markers (marker-based). The shoe types used in MTC studies include standard shoes (SS), personal shoes (PS), and barefoot (BF) conditions. What is the agreement, inter and intra-rater reliability, and repeatability for the 3 commonly used methods of measuring MTC (SVP, MVPS, marker-based) under the 3 shoe conditions for optical motion capture systems (SS, PS, BF)? Twelve healthy young adults (mean [SD] 23.8 [1.9] years,7 males) participated in this observational study. In a randomized order, participants completed 25 walking trials at self-selected normal and slow speeds in SS, PS, and BF conditions while infrared cameras recorded the maker trajectories. Each participant performed a familiarization trial for at least 1 minute before collecting data on each shoe condition. Statistical analyses included Bland-Altman 95 % limits of agreement (LOA) analyses, interclass correlation coefficient (ICC) analyses for inter- and intra-rater reliability, and the repeatability coefficient (RC). The SVP and MVPS had a tighter 95 % LOA than the marker-based method, particularly under SS and BF conditions. The inter-rater reliability was good to excellent under these shoe conditions. Intra-reliability for all methods under all shoe conditions was excellent (ICC >.90). The RC was very similar for each method, with none exceeding 1.02 cm. The study provides estimates of the agreement between MTC methods and suggests that only SVP or MVPS produced similar results in SS/BF conditions. Additionally, a "true" change in MTC requires a difference greater than 1.02 cm. • Single and multiple virtual point methods to assess MTC agreed in shoe and barefoot conditions. • The intra-rater reliability was excellent for marker and virtual point methods of assessing MTC. • "True" change in MTC requires a difference greater than 1.02 cm. [ABSTRACT FROM AUTHOR]

Score-driven models have recently been introduced as a general framework to specify time-varying parameters of conditional densities. The score enjoys stochastic properties that make these models easy to implement and convenient to apply in several contexts, ranging from biostatistics to finance. Score-driven parameter updates have been shown to be optimal in terms of locally reducing a local version of the Kullback–Leibler divergence between the true conditional density and the postulated density of the model. A key limitation of such an optimality property is that it holds only locally both in the parameter space and sample space, yielding to a definition of local Kullback–Leibler divergence that is in fact not a divergence measure. The current paper shows that score-driven updates satisfy stronger optimality properties that are based on a global definition of Kullback–Leibler divergence. In particular, it is shown that score-driven updates reduce the distance between the expected updated parameter and the pseudo-true parameter. Furthermore, depending on the conditional density and the scaling of the score, the optimality result can hold globally over the parameter space, which can be viewed as a generalization of the monotonicity property of the stochastic gradient descent scheme. Several examples illustrate how the results derived in the paper apply to specific models under different easy-to-check assumptions, and provide a formal method to select the link function and the scaling of the score. [ABSTRACT FROM AUTHOR]

Background: The precise determination of gestational age is essential for effectively managing and prognosis of all pregnancies. Through careful biometry, timely interventions can be implemented, leading to positive outcomes for both the mother and fetus. In routine fetal biometry, parameters such as biparietal diameter (BPD), femur length (FL), head circumference (HC), and abdominal circumference (AC) have been traditionally used. This study aims to evaluate the usefulness of fetal kidney length (FKL) as a marker for fetal biometry. Methodology: This prospective, observational, and cross-sectional study was conducted in the Radiodiagnosis and Obstetrics and Gynaecology departments, including a diverse group of pregnant women from various socio-economic backgrounds, with adherence to ethical standards. Women with singleton pregnancies between 22 and 40 weeks of gestation who met the inclusion and exclusion criteria were examined through ultrasound. The data collected were subsequently analyzed. Result: In the current study, 280 participants with an average age of 26.71 ± 3.6 years were included. The agreement between the mean fetal kidney length and standard biometry parameters was almost perfect, with a strength of agreement exceeding 0.99. A strong and statistically significant positive correlation existed between fetal kidney length and the estimated gestational period calculated using DLMP/standard biometric measurements. Conclusion: Fetal kidney length is a reliable indicator of gestational age and can supplement standard biometric measurements to provide a more precise estimation of gestational age, especially in the later stages when obtaining such standard measurements may be challenging. [ABSTRACT FROM AUTHOR]

Clinical relevance: Measuring axial length is key in the field of myopia development and control. Hence, the precision and agreement of commercially available biometers is of vital interest to understand their variability and interchangeability in the paediatric population. Background: Different biometers are available to measure axial length and monitor myopia progression in clinical practice. The purpose of this study was to assess the precision (repeatability and reproducibility) and agreement of the MYAH and AL-Scan biometers in a paediatric population. Methods: Three consecutive measurements were performed using MYAH and AL-Scan biometers in each subject by the same operator to test for repeatability. To test for reproducibility, two measurements were performed for each subject by two different observers with a 5-min interval between measurements. To test the agreement, each subject was measured once with each instrument. Results: A total of 187 subjects, with a mean age of 8.5 ± 0.3 years and mean spherical equivalent refractive error of +0.22 ± 0.77 D participated in the study. For the repeatability study, the within-subject standard deviation was 0.01 mm, and the repeatability limit was 0.04 mm for both instruments, with no statistically significant differences among repeated measures (p = 0.162 for MYAH and p = 0.774 for AL-Scan). For the reproducibility study, the within-subject standard deviation was 0.01 mm and the repeatability limit was 0.04 mm. There were statistically significant differences for the repeated measures for the AL-Scan (p = 0.002) but not for the MYAH (p = 0.643). Regarding the agreement between both instruments, the 95% limit of agreement ranged from −0.04 to 0.05 mm, and the differences were statistically significant (p = 0.021). Conclusions: The repeatability, reproducibility, and agreement of the MYAH and AL-Scan biometers seem optimal for following children with myopia. [ABSTRACT FROM AUTHOR]

Feature extractors significantly impact the performance of biometric systems. In the field of hand gesture authentication, existing studies focus on improving the model architectures and behavioral characteristic representation methods to enhance their feature extractors. However, loss functions, which can guide extractors to produce more discriminative identity features, are neglected. In this paper, we improve the margin-based Softmax loss functions, which are mainly designed for face authentication, in two aspects to form a new loss function for hand gesture authentication. First, we propose to replace the commonly used cosine function in the margin-based Softmax losses with a linear function to measure the similarity between identity features and proxies (the weight matrix of Softmax, which can be viewed as class centers). With the linear function, the main gradient magnitude decreases monotonically as the quality of the model improves during training, thus allowing the model to be quickly optimized in the early stage and precisely fine-tuned in the late stage. Second, we design an adaptive margin scheme to assign margin penalties to different samples according to their separability and the model quality in each iteration. Our adaptive margin scheme constrains the gradient magnitude. It can reduce radical (excessively large) gradient magnitudes and provide moderate (not too small) gradient magnitudes for model optimization, contributing to more stable training. The linear function and the adaptive margin scheme are complementary. Combining them, we obtain the proposed linear adaptive additive angular margin (L3AM) loss. To demonstrate the effectiveness of L3AM loss, we conduct extensive experiments on seven hand-related authentication datasets, compare it with 25 state-of-the-art (SOTA) loss functions, and apply it to eight SOTA hand gesture authentication models. The experimental results show that L3AM loss further improves the performance of the eight authentication models and outperforms the 25 losses. The code is available at https://github.com/SCUT-BIP-Lab/L3AM. [ABSTRACT FROM AUTHOR]

This study employs Principal Component Analysis to examine cranial measurements from both extant and fossil specimens spanning 38 species and comprising over 300 individuals within the subfamily Cervinae. Our findings elucidate craniometric distinctions among cervids characterized by varying body sizes and certain evolutionary adaptations. While our results generally corroborate previous assertions regarding the limited craniometric variability among plesiometacarpal deer, they also unveil specific cranial adaptations within certain genera and species. The Principal Component Analysis of craniometric data revealed that giant and large-sized deer display significantly broader ecomorphological diversity in cranial shape compared to small-sized deer. Secondly, small-sized deer exhibit greater uniformity in their cranial shape, appearing densely clustered on the factorial map. Thus, we conclude that body size imposes ecological constraints, limiting the available niches due to eco-physiological factors. This study demonstrates that endemic insular deer do not evolve consistent craniometric features attributable to insular isolation, while the cranial proportions of medium-to-small-sized deer delineate a ubiquitous morphological archetype characteristic of numerous cervid taxa spanning diverse phylogenetic lineages and sharing comparable body sizes. This group of "Dama-like" deer, characterized by similar body size, metabolic rates, ecological needs, and cranial morphometry, is referred to here as the fundamental eco-physiological type, typical of warm regions within the Palearctic and Oriental biogeographic realms. [ABSTRACT FROM AUTHOR]

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Background/Objectives: Very preterm infants are at increased risk of brain injury and impaired brain development. The Total Abnormality Score and biometric parameters, such as biparietal width, interhemispheric distance and transcerebellar diameter, are simple measures to evaluate brain injury, development and growth using cerebral magnetic resonance imaging data at term-equivalent age. The aim of this study was to evaluate the association between the Total Abnormality Score and biometric parameters with general movements in very preterm infants with brain injury. Methods: This single-center retrospective cohort study included 70 very preterm infants (≤32 weeks' gestation and/or <1500 g birth weight) born between January 2017 and June 2021 in a level-three neonatal intensive care unit with brain injury—identified using cerebral magnetic resonance imaging data at term-equivalent age. General movements analysis was carried out at corrected age of 8–16 weeks. Binary logistic regression and Spearman correlation were used to examine the associations between the Total Abnormality Score and biometric parameters with general movements. Results: There was a significant association between the Total Abnormality Score and the absence of fidgety movements [OR: 1.19, 95% CI = 1.38–1.03] as well as a significant association between the transcerebellar diameter and fidgety movements (Spearman ρ = −0.269, p < 0.05). Conclusions: Among very preterm infants with brain injury, the Total Abnormality Score can be used to predict the absence of fidgety movements and may be an easily accessible tool for identifying high-risk very preterm infants and planning early interventions accordingly. [ABSTRACT FROM AUTHOR]

Friction ridges are important and unique biometric features that have been studied in fingerprint science since antiquity and used for human identification. This study aimed to analyze palmprints and soleprints of Callithrix penicillata, including the description of flexion creases, regions, minutiae classification, and delta counting, in order to evaluate the uniqueness of these data and feasibility of using this information as an identification method. Palmprints and footprints were collected using commercial fingerprint ink on A4 size paper. Following image digitalization using the GIMP (2.10.14) image editing program, regions and flexion creases were identified. A total of 600 minutiae were classified in females (288 palms and 312 soles) and 732 in males (360 palms and 372 soles), and all deltas were counted. It was possible to identify three main inconstant flexion creases, in both palmprints and soleprints, with different distribution and orientation when compared to those in humans. Less variety in the types of minutiae and differences in the distribution of deltas were found when compared to human studies. In addition, the hypothesis of non-coincident characteristics in each sample was confirmed. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the effect of botulinum toxin-A (BTX-A) treatment on corneal topography, ocular biometry and keratometry in patients with benign essential blepharospasm (BEB) and hemifacial spasm (HFS). Methods: This study comprised 66 eyes of 33 patients with BEB and 5 eyes of 5 patients with HFS who underwent BTX-A injections consecutively. Refractive error values, tear break-up time (TBUT), corneal topography [corneal power of flat axis (K1) and steep axis (K2), mean corneal power (Km), corneal astigmatism (K2–K1)] and ocular optical biometry [axial length (AL), anterior chamber depth (ACD)] were recorded before BTX-A treatment and 1 month after BTX-A treatment. The researchers calculated the expected emmetropic intraocular lens power (emm-IOL) using the SRK-T, Holladay, Hoffer-Q and Haigis formulas at each examination. Results: K1 (43.48 ± 2.02 vs. 43.57 ± 2.08, p = 0.036), Km (43.91 ± 1.99 vs. 43.99 ± 2.06, p = 0.024) and ACD (3.22 (2.77–3.76) vs. 3.41 (2.99–4.02), p < 0.001) values were found to be significantly higher. The expected emm-IOL according to the SRK-T (21.04 ± 1.6 vs. 20.93 ± 1.6, p = 0.048), Holladay (21.05 ± 1.6 vs. 20.91 ± 1.62, p = 0.037) and Hoffer-Q (21.08 ± 1.65 vs. 20.94 ± 1.68, p = 0.038) decreased significantly. The expected emm-IOL according to the Haigis formula slightly decreased, but it was not significant (p = 0.386). Additionally, TBUT was found to be significantly lower (p < 0.001) after BTX-A injection. Other parameters were not statistically significant (p > 0.05). Conclusions: Our study is the first in the literature to compare optic biometry data and intraocular lens power calculation formulas before and after BTX-A injection in eyes with BEB and HFS. BTX-A injection could play an important role in changing the keratometric and ACD values. It should be considered that IOL power calculations that might be unpredictable due to blepharospasm, so repeated measurements and especially measurements after releasing the spasm with BTX-A injections, are necessary in BEB and HFS. [ABSTRACT FROM AUTHOR]

Objectives: This study aims to verify the accuracy of a new calculation formula, Barrett true axial length formula (T-AL), and the optimized lens factor (LF) for predicting postoperative refraction after cataract surgery. Methods: We included 156 Japanese patients who underwent cataract surgery using Clareon monofocal intraocular lenses at our clinic between January 2022 and June 2023. Postoperative spherical equivalent was calculated using subjective refraction values obtained 1 month post-surgery. The LFs were optimized so that the mean prediction error (PE) of each calculation formula was zero (zero optimization). We calculated the mean absolute PE (MAE) to assess accuracy and used a Friedman test for statistical comparisons. The accuracy of T-AL and the optimized LFs was compared with that of the conventional Barrett Universal II formula for ARGOS (AR-B) and OA-2000 (OA-B) with equivalent refractive index. Results: For T-AL, AR-B, and OA-B, the MAEs ± standard deviations were 0.225 ± 0.179, 0.219 ± 0.168, and 0.242 ± 0.206 D, respectively. The Friedman test showed no statistically significant differences among the three groups. The device-optimized LFs were 2.248–2.289 (T-AL), 2.236–2.246 (AR-B), and 2.07–2.08 (OA-B); the corresponding zero-optimized LFs were 2.262–2.287 (T-AL), 2.287–2.303 (AR-B), and 2.160–2.170 (OA-B). Conclusion: There were no significant differences in prediction accuracy among the formulas. However, the accuracy of LF optimization varied by device, with T-AL being closest to the value under zero optimization. This suggests that T-AL is clinically useful for predicting an accurate postoperative refraction without zero optimization. [ABSTRACT FROM AUTHOR]

The use of burned plant biomass ashes could help not only with respect to utilizing combustion residues, but also with respect to optimizing the nutrition of cultivated agricultural plants without harming the environment. With this aim, a pot experiment of the effects of multi-crop biomass ash on faba bean seedlings was carried out in the Academy of Agriculture of the Vytautas Magnus University (VMU). Four ash fertilization rates were tested: 1. unfertilized (N0, comparative-control treatment); 2. fertilized at a low rate (N1, 200 kg ha−1); 3. fertilized at an average rate (N2, 1000 kg ha−1); 4. fertilized at a high rate (N3, 2000 kg ha−1). Final observations showed that ash fertilization significantly increases the height of faba bean sprouts by 21–38%, the length of the roots by 10–20% and the chlorophyll concentration in the leaves by 17%. The average green biomass of faba bean sprouts consistently increased with increasing fertilization rate, from 56% to 209%. Dried biomass increased by 160–220%. With increasing ash fertilization rate, the percentage of dry matter in the roots decreased by 10–50%. We recommend fertilizing faba bean with medium (1000 kg ha−1) and high (2000 kg ha−1) ash rates, as these rates led to the largest plants with the highest productivity potential. [ABSTRACT FROM AUTHOR]

Facial biometrics are widely used to reliably and conveniently recognize people in photos, in videos, or from real-time webcam streams. It is therefore of fundamental importance to detect synthetic faces in images in order to reduce the vulnerability of biometrics-based security systems. Furthermore, manipulated images of faces can be intentionally shared on social media to spread fake news related to the targeted individual. This paper shows how fake face recognition models may mainly rely on the information contained in the background when dealing with generated faces, thus reducing their effectiveness. Specifically, a classifier is trained to separate fake images from real ones, using their representation in a latent space. Subsequently, the faces are segmented and the background removed, and the detection procedure is performed again, observing a significant drop in classification accuracy. Finally, an explainability tool (SHAP) is used to highlight the salient areas of the image, showing that the background and face contours crucially influence the classifier decision. [ABSTRACT FROM AUTHOR]

In the United States, normal-risk pregnancies are monitored with the recommended average of 14 prenatal visits. Check-ins every few weeks are the standard of care. This low time resolution and reliance on subjective feedback instead of direct physiological measurement, could be augmented by remote monitoring. To date, continuous physiological measurements have not been characterized across all of pregnancy, so there is little basis of comparison to support the development of the specific monitoring capabilities. Wearables have been shown to enable the detection and prediction of acute illness, often faster than subjective symptom reporting. Wearables have also been used for years to monitor chronic conditions, such as continuous glucose monitors. Here we perform a retrospective analysis on multimodal wearable device data (Oura Ring) generated across pregnancy within 120 individuals. These data reveal clear trajectories of pregnancy from cycling to conception through postpartum recovery. We assessed individuals in whom pregnancy did not progress past the first trimester, and found associated deviations, corroborating that continuous monitoring adds new information that could support decision-making even in the early stages of pregnancy. By contrast, we did not find significant deviations between full-term pregnancies of people younger than 35 and of people with "advanced maternal age", suggesting that analysis of continuous data within individuals can augment risk assessment beyond standard population comparisons. Our findings demonstrate that low-cost, high-resolution monitoring at all stages of pregnancy in real-world settings is feasible and that many studies into specific demographics, risks, etc., could be carried out using this newer technology. [ABSTRACT FROM AUTHOR]

Objectives Design Setting Participants Main Outcome Measures Results Conclusions Trial Registration Accurate assessment of gestational age (GA) is important at both individual and population levels. The most accurate way to estimate GA in women who book late in pregnancy is unknown. The aim of this study was to externally validate the accuracy of equations for GA estimation in late pregnancy and to identify the best equation for estimating GA in women who do not receive an ultrasound scan until the second or third trimester.This was a prospective, observational cross‐sectional study.57 prenatal care centres, France.Women with a singleton pregnancy and a previous 11–14‐week dating scan that gave the observed GA were recruited over an 8‐week period. They underwent a standardised ultrasound examination at one time point during the pregnancy (15–43 weeks), measuring 12 foetal biometric parameters that have previously been identified as useful for GA estimation.A total of 189 equations that estimate GA based on foetal biometry were examined and compared with GA estimation based on foetal CRL. Comparisons between the observed GA and the estimated GA were made using R2, calibration slope and intercept. RMSE, mean difference and 95% range of error were also calculated.A total of 2741 pregnant women were examined. After exclusions, 2339 participants were included. In the 20 best performing equations, the intercept ranged from −0.22 to 0.30, the calibration slope from 0.96 to 1.03 and the RSME from 0.67 to 0.87. Overall, multiparameter models outperformed single‐parameter models. Both the 95% range of error and mean difference increased with gestation. Commonly used models based on measurement of the head circumference alone were not amongst the best performing models and were associated with higher 95% error and mean difference.We provide strong evidence that GA‐specific equations based on multiparameter models should be used to estimate GA in late pregnancy. However, as all methods of GA assessment in late pregnancy are associated with large prediction intervals, efforts to improve access to early antenatal ultrasound must remain a priority.The proposal for this study and the corresponding methodological review was registered on PROSPERO international register of systematic reviews (registration number: CRD4201913776). [ABSTRACT FROM AUTHOR]

Introduction: The almond tree is a major global nut crop, and its production has surged dramatically in recent years. Super high-density (SHD) planting systems, designed to optimize resource efficiency and enhance precocity, have gained prominence in almond cultivation. A shift in cropping systems toward sustainable intensification (SI) pathways is imperative, and so maximizing branching density within the canopies of SHD trees is crucial to establish and maintain productive potential, especially for hedge-pruned trees. This study investigates the influence of different almond cultivars grafted onto a novel growth-controlling rootstock on tree architectural and growth parameters in a SHD orchard. This open field research provided valuable insights for the development and application of new tools and methods to increase productivity and sustainability in almond growing. Methods: Three cultivars (Lauranne® Avijour, Guara Tuono, and Filippo Cea) were evaluated in Gravina in Puglia (BA) over a two-year period. Canopy growth parameters, such as canopy volume and trunk cross-sectional area, and architectural traits, like branching density, branching angle, number and length of subterminal shoots, and number of brachyblasts, were measured through qualitative and quantitative measurements. Results and discussion: Results revealed significant differences in tree height, canopy thickness, width, volume, and vigor among the cultivars. Architectural traits, including branch parameters, brachyblast parameters, and subterminal shoots, varied among the cultivars. Lauranne displayed a more compact welldistributed canopy and exhibited the lowest vigor. Filippo Cea showed the highest vigor and the greatest canopy volume. Tuono had a higher number of buds and bud density. The best ideotype for SHD orchards is a smaller tree, with high branching density and smaller trunk diameters, i.e. the vigor. Cv. Lauranne seemed to be the best cultivar, mostly with the lowest tree vigor of all the cultivars involved. These findings provide valuable insights for almond growers and breeders seeking to optimize orchard design and management for enhanced SHD orchards productivity and sustainability. Future research will explore the relationship between canopy architecture and yield parameters, considering different scion/rootstock combinations in different environmental conditions. [ABSTRACT FROM AUTHOR]

Facial recognition systems have emerged as indispensable components in identity verification. These systems heavily rely on facial data, which is stored in a biometric database. However, storing such data in a database raises concerns about privacy breaches. To address this issue, several technologies have been proposed for protecting facial biometrics. Unfortunately, many of these methods can cause irreversible damage to the data, rendering it unusable for other purposes. In this paper, we propose a novel reversible anonymization scheme for face images via cyclic learning. In our scheme, face images can be de-identified for privacy protection and reidentified when necessary. To achieve this, we employ generative adversarial networks with a cycle consistency loss function to learn the bidirectional transformation between the de-identified and re-identified domains. Experimental results demonstrate that our scheme performs well in terms of both de-identification and reidentification. Furthermore, a security analysis validates the effectiveness of our system in mitigating potential attacks. [ABSTRACT FROM AUTHOR]

Species diff erentiation within the genus Mesorbitolina Schroeder 1962 is primarily based on the general structure of the megalospheric embryo and its biometrics. The taxonomy of three taxa, namely Mesorbitolina texana (Roemer 1849), Mesorbitolina subconcava (Leymerie 1878) and Mesorbitolina pervia (Douglass 1960) is complicated due to diff ering species concepts between authors, and, in the case of the fi rst two named, by missing type designations in the original descriptions as well as disagreements with respect to their type-localities. Herein, it is demonstrated that M. pervia is the junior synonym of Mesorbitolina birmanica (Sahni 1937) due to priority reasons, both taxa characterized by a similar-sized plano-convex protoconch. Some concepts of M. texana and M. subconcava can also be placed in M. birmanica, but not those as defi ned by lectotypes. Published data for M. birmanica suggest a late Aptian (late Gargasian) to early (? late) Albian age and a cosmopolitan distribution. Mesorbitolina texana appears slightly earlier in the late Aptian persisting into the middle Albian, and a distribution ranging from the southern USA to the Middle East. [ABSTRACT FROM AUTHOR]

Similar to most Psittaciformes, the blue-fronted parrot (Amazona aestiva) lacks sexual dimorphism. In this way, sexing methods have been investigated to assist in the reproductive management and medical care of these birds. This study aimed to assess head and radiographic biometry for sex identification of blue-fronted parrots. Six head measurements and 23 radiographic measurements of 52 carcasses (24 males and 28 females) were taken. Males exhibited higher mean values than females for most of the measurements. For head biometry, the proposed discriminant equation containing rhinotheca length and head plus rhinotheca length allowed for correct sexing of 60% of males and 88% of females, while for radiographic biometry the discriminant equation containing head heigh and right alula length allowed the discrimination of 84.6% of males and 66.7% of females. This is the first study evaluating the use of radiographic biometry for sexing psittaciforms. Both biometric methods are suitable for sexing blue-fronted parrots when DNA sampling is not possible, since they are low-cost, provide immediate results, and are non-invasive techniques. [ABSTRACT FROM AUTHOR]

Jerome Wakefield criticizes my biostatistical analysis of the pathological—as statistically subnormal biological part-functional ability relative to species, sex, and age—for its lack of a harm clause. He first charges me with ignoring two general distinctions: biological versus medical pathology, and disease of a part versus disease of a whole organism. He then offers 10 counterexamples that, he says, are harmless dysfunctions but not medical disorders. Wakefield ends by arguing that we need a harm clause to explain American psychiatry's 1973 decision to declassify homosexuality. I reply, first, that his two distinctions are philosophic fantasies alien to medical usage, invented only to save his own harmful-dysfunction analysis (HDA) from a host of obvious counterexamples. In any case, they do not coincide with the harmless/harmful distinction. In reality, medicine admits countless chronic diseases that are, contrary to Wakefield, subclinical for most of their course, as well as many kinds of typically harmless skin pathology. As for his 10 counterexamples, no medical source he cites describes them as he does. I argue that none of his examples contradicts the biostatistical analysis: all either are not part-dysfunctions (situs inversus, incompetent sperm, normal-flora infection) or are indeed classified as medical disorders (donated kidney, Typhoid Mary's carrier status, latent tuberculosis or HIV, cherry angiomas). And if Wakefield's HDA fits psychiatry, the fact that it does not fit medicine casts doubt on psychiatry's status as a medical specialty. [ABSTRACT FROM AUTHOR]