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The increased use of computational human models in evaluation of safety systems demands greater attention to selected methods in coupling the model to its seated environment. This study assessed the THUMS v4.0.1 in an upright driver posture and a reclined occupant posture. Each posture was gravity settled into an NCAC vehicle model to assess model quality and HBM to seat coupling. HBM to seat contact friction and seat stiffness were varied across a range of potential inputs to evaluate over a range of potential inputs. Gravity settling was also performed with and without constraints on the pelvis to move towards the target H-Point. These combinations resulted in 18 simulations per posture, run for 800 ms. In addition, 5 crash pulse simulations (51.5 km/h delta V) were run to assess the effect of settling time on driver kinematics. HBM mesh quality and HBM to seat coupling metrics were compared at kinetically identical time points during the simulation to an end state where kinetic energy was near zero. A gravity settling time of 350 ms was found to be optimal for the upright driver posture and 290 ms for the reclined occupant posture. This suggests that reclined passengers can be settled for less time than upright passengers, potentially due to the increased contact area. The pelvis constrained approach was recommended for the upright driver posture and was not recommended for the reclined occupant posture. The recommended times were sufficient to gravity settle both postures to match the quality metrics of the 800 ms gravity settled time. Driver kinematics were found to be vary with gravity settling time. Future work will include verifying that these recommendations hold for different HBMs and test modes.

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Background Our study focused on meningitis, an infection that can spread through the bloodstream as a primary or secondary infection from other body parts, such as sinuses, ears, and lungs. It can affect patients who have experienced trauma or surgery, as well as those with congenital defects like spina bifida. Specifically, we examined bacterial, viral, and tuberculous meningitis (TBM) cases. The primary method for confirming the diagnosis of these types of meningitis is to analyze the cerebrospinal fluid (CSF). Early diagnosis can utilize cytological and biochemical parameters. Our objective is to determine CSF's cytological and biochemical profile in patients with these specific types of meningitis. Methods A study was carried out at the central pathology lab from October 24, 2017, to April 24, 2018. CSF samples from suspected meningitis patients were examined for various parameters, including hematological, biochemical, microbiological, and cytomorphological aspects and specific tests for bacterial, fungal, and TBM. The study focused on patients aged 16 and above, excluding those under 16, non-compliant patients, and individuals with specific health conditions. Data were analyzed using IBM SPSS Statistics for Windows, Version 20 (Released 2011; IBM Corp., Armonk, New York, United States), and the results were presented through the use of mean, standard deviation, and percentages. Statistical tests were utilized to compare categorical variables and mean, with a significance level of p<0.05. Results We included a total of 156 cases, with the mean age of presentation being 56.628 years. The male-to-female ratio was 1.0526:1. Of the patients, 81 (52.1%) had been diagnosed with TBM, had elevated adenosine deaminase (ADA) levels of 48.8733±37.43740 IU/L, and CSF lymphocytosis (99%). Additionally, cases of bacterial meningitis showed markedly raised mean total leukocyte count (TLC) of 2085.50±445.47727 cells/mm3 and mean CSF protein levels of 349.45±113.73105 mg/dL. The study found a significant increase in protein levels and a decrease in glucose levels in the CSF of TBM and bacterial meningitis patients compared to those with other causes of meningitis (p<0.001). Guillain-Barre syndrome (GBS) and multiple sclerosis (MS) patients had TLC and ADA within normal limits. CSF ADA level greater than 6 IU/L showed a sensitivity of 97.53% and a specificity of 96.0%, making it the most specific test. A protein level in the CSF greater than 45 mg/dL demonstrated a sensitivity of 98.78% and a specificity of 24.32%, indicating it is sensitive but less specific in diagnosing TBM. Lymphocytic predominance, defined as TLC of more than 5 cells/mm3 with at least 50% of the cells being lymphocytes in the CSF of TBM patients, showed a sensitivity of 97.53% and a specificity of 6.67%. CSF glucose had a sensitivity of 38.27%, making it the least reliable indicator for diagnosing meningitis. Conclusion The CSF analysis is the primary diagnostic method for detecting meningitis. Its cost-effectiveness is a key factor, especially for patients from lower socioeconomic backgrounds in government medical colleges in India, where access to expensive diagnostic tests is limited. The efficiency of CSF analysis for early diagnosing different types of meningitis aids in management, helping to prevent complications and fatal outcomes.

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Ecdysteroids represent a large class of polyhydroxylated steroids which, due to their anabolic properties, are marketed as dietary supplements. Some ecdysteroids also act as important hormones in arthropods, where they regulate molting, development, and reproduction and many of these insects are miniature organisms that contain submicroliter levels of circulating biofluids Analysis of ecdysteroids is further complicated by their very low abundance, large fluctuations during development, and difficult access to a pooled sample, which is important for quantitative measurements. In this work, we propose a new method that overcomes the described difficulties and allows validated quantification of four ecdysteroids in minimal amounts of biological material. After methanolic extraction, detectability of the ecdysteroids is increased 16- to 20-fold by conversion to their 14,15-anhydrooximes. These are further purified by pipette tip solid phase extraction (PT-SPE) on a three-layer sorbent and subjected to HPLC-MS/MS analysis. Full validation was achieved using hemolymph from larvae of the firebug Pyrrhocoris apterus as a blank matrix and by the determination of ecdysteroids in a single Drosophila larva. The LLOQs for the four target ecdysteroids (20-hydroxyecdysone, ecdysone, makisterone A, and 2-deoxyecdysone) were 0.01; 0.1; 0.05; 0.025 pg·mL-1 (20; 200; 100; 50 fmol·mL-1) respectively, with very good accuracy, precision (RSD < 15%) and recoveries (96% - 119.9%).The general suitability of the new method was demonstrated by quantification of ecdysteroids in various biological materials including human serum.

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PURPOSE: To judge the injury mode and injury severity of the real human body through the measured values of anthropomorphic test devices (ATD) injury indices, the mapping relationship of lumbar injury between ATD and human body model (HBM) was explored. METHODS: Through the ATD model and HBM simulation, the mapping relationship of lumbar injury between the 2 subjects was explored. The sled environment consisted of a semi-rigid seat with an adjustable seatback angle and a 3-point seat belt system with a seatback-mounted D-ring. Three seatback recline states of 25°, 45°, and 65° were designed, and the seat pan angle was maintained at 15°. A 23 g, 47 km/h pulse was used. The validity of the finite element model of the sled was verified by the comparison of ATD simulation and test results. ATD model was the test device for human occupant restraint for autonomous vehicles (THOR-AV) dummy model and HBM was the total human model for safety (THUMS) v6.1. The posture of the 2 models was adjusted to adapt to the 3 seat states. The lumbar response of THOR-AV and the mechanical and biomechanical data on L1-L5 vertebrae of THUMS were output, and the response relationship between THOR-AV and THUMS was descriptive statistically analyzed. RESULTS: Both THOR-AV and THUMS were submarined in the 65° seatback angle case. With the change of seatback angle, the lumbar spine axial compression force (Fz) of THOR-AV and THUMS changed in the similar trend. The maximum Fz ratio of THOR-AV to THUMS at 25° and 45° seatback angle cases were 1.6 and 1.7. The flexion moment (My) and the time when the maximum My occurred in the 2 subjects were very different. In particular, the form of moment experienced by the L1 - L5 vertebrae of THUMS also changed. The changing trend of My measured by THOR-AV over time can reflect the changing trend of maximum stress of L1 and L2 of THUMS. CONCLUSION: The Fz of ATD and HBM presents a certain proportional relationship, and there is a mapping relationship between the 2 subjects on Fz. The mapping function can be further clarified by applying more pulses and adopting more seatback angles. It is difficult to map My directly because they are very different in ATD and HBM. The My of ATD and stress of HBM lumbar showed a similar change trend over time, and there may be a hidden mapping relationship.

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Automatic pose estimation has become a valuable tool for the study of human behavior, including dyadic interactions. It allows researchers to analyze the nuanced dynamics of interactions more effectively, and facilitates the integration of behavioral data with other modalities (EEG, etc.). However, many technical difficulties remain. Particularly, for parent-infant interactions, automatic pose estimation for infants is unpredictable; the immature proportions and smaller bodies of children may cause misdetections. OpenPose is one tool that has shown high performance in pose tracking from video, even in infants. However, OpenPose is limited to 2D (i.e., coordinates relative to the image space). This may be undesirable in a multitude of paradigms (e.g., naturalistic settings). We developed a method for expanding the functionality of OpenPose to 3D, tailored to parent-infant interaction paradigms. This method merges the estimations from OpenPose with the depth information from a depth camera to obtain a 3D pose that works even for young infants.•Video recordings of interactions of parents and infants are taken using a dual color-depth camera.•2D-positions of parents and their infants are estimated from the color video.•Using the depth camera, we transform the 2D estimations into real-world 3D positions, allowing movement analysis in full-3D space.

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BACKGROUND: This study aimed to conduct a detailed and comparative analysis of body composition and dietary habits in elite swimming and water polo athletes. Through the examination of these key parameters, this study seeks to compare the dietary intake of these two distinct aquatic sports disciplines. METHODS: A total of 10 top-level swimmers and 13 water polo athletes participated in anthropometric and body composition assessments, as well as a detailed analysis of nutritional intake. To compare the two groups, an independent samples t-test was used, and variance homogeneity was checked using Levene's test. The effect size of the group differences was evaluated using Hedges' g. RESULTS: Water polo athletes showed significantly greater height (189.4 ± 2.9 vs. 186.5 ± 2.0 cm, p = 0.013), body mass index (24.3 ± 1.4 vs. 22.1 ± 0.5 kg/m2, p < 0.001), fat-free mass (62.9 ± 1.4 vs. 61.1 ± 1.38 kg, p < 0.001), skeletal muscle mass (47.1 ± 1.3 vs. 43.9 ± 1.6 kg, p < 0.001), and overall weight (86.9 ± 6.9 vs. 76.7 ± 2.2 kg, p < 0.001) in comparison to swimmers. Swimmers consumed greater amounts of mean daily energy (60.0 ± 1.0 vs. 39.0 ± 1.0 kcal/kg, p < 0.001), carbohydrate (7.8 ± 0.3 vs. 4.4 ± 0.5 g/kg, p < 0.001), protein (1.7 ± 0.5 vs. 1.4 ± 0.5 g/kg, p < 0.001), and fat (2.4 ± 0.5 vs. 1.7 ± 0.5 g/kg, p < 0.001) compared to water polo athletes. CONCLUSION: Our findings highlight the need for differentiated targeted nutritional interventions to enhance athletic performance in different types of water sports. Compared to water polo athletes, swimmers consumed significantly higher amounts of calories, matching their increased calorie demand from their specific training regime. However, this is an observational study and the differential needs of energy and macronutrients in water sports should be confirmed by studies with energy expenditure measurements.

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Few studies investigate the impact of anterior-posterior excitation frequency on the time-domain vibrational response and injury risk of the lumbar spine in seated individuals. Firstly, this study utilised a previously developed finite element model of an upright seated human body on a rigid chair without a backrest to investigate the modes that affect the anterior-posterior vibrations of the seated body. Subsequently, transient dynamic analysis was employed to calculate the lumbar spine's time-domain responses (displacement, stress, and pressure) and risk factors under anteroposterior sinusoidal excitation at varying frequencies (1-8 Hz). Modal analysis suggested the frequencies significantly affecting the lumbar spine's vibration were notably at 4.7 Hz and 5.5 Hz. The transient analysis results and risk factor assessment indicated that the lumbar responses were most pronounced at 5 Hz. In addition, risk factor assessment showed that long-term exposure to 8 Hz vibration was associated with a greater risk of lumbar injury.

Although the anterior-posterior resonance frequency of the sitting body is around 1 Hz, the anterior-posterior vibrations approaching 5 Hz and at 8 Hz inflict more significant harm upon the lumbar spine than other frequencies, thereby elevating the risk of lumbar injury and back disorders.

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Background: The COVID-19 pandemic highlighted the need for accurate virtual sizing in e-commerce to reduce returns and waste. Existing methods for extracting anthropometric data from images have limitations. This study aims to develop a semantic segmentation model trained on synthetic data that can accurately determine body shape from real images, accounting for clothing. Methods: A synthetic dataset of over 22,000 images was created using NVIDIA Omniverse Replicator, featuring human models in various poses, clothing, and environments. Popular CNN architectures (U-Net, SegNet, DeepLabV3, PSPNet) with different backbones were trained on this dataset for semantic segmentation. Models were evaluated on accuracy, precision, recall, and IoU metrics. The best performing model was tested on real human subjects and compared to actual measurements. Results: U-Net with EfficientNet backbone showed the best performance, with 99.83% training accuracy and 0.977 IoU score. When tested on real images, it accurately segmented body shape while accounting for clothing. Comparison with actual measurements on 9 subjects showed average deviations of -0.24 cm for neck, -0.1 cm for shoulder, 1.15 cm for chest, -0.22 cm for thallium, and 0.17 cm for hip measurements. Discussion: The synthetic dataset and trained models enable accurate extraction of anthropometric data from real images while accounting for clothing. This approach has significant potential for improving virtual fitting and reducing returns in e-commerce. Future work will focus on refining the algorithm, particularly for thallium and hip measurements which showed higher variability.

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A cleanroom free optimized fabrication of a low-cost facile tungsten diselenide (WSe2) combined with chitosan-based hydrogel device is reported for multifunctional applications including tactile sensing, pulse rate monitoring, respiratory rate monitoring, human body movements detection, and human electrophysiological signal detection. Chitosan being a natural biodegradable, non-toxic compound serves as a substrate to the semiconducting WSe2 electrode which is synthesized using a single step hydrothermal technique. Elaborate characterization studies are performed to confirm the morphological, structural, and electrical properties of the fabricated chitosan/WSe2 device. Chitosan/WSe2 sensor with copper contacts on each side is put directly on skin to capture human body motions. The resistivity of the sample was calculated as 26 kΩ m-1. The device behaves as an ultrasensitive pressure sensor for tactile and arterial pulse sensing with response time of 0.9 s and sensitivity of around 0.02 kPa-1. It is also capable for strain sensing with a gauge factor of 54 which is significantly higher than similar other reported electrodes. The human body movements sensing can be attributed to the piezoresistive character of WSe2 that originates from its non-centrosymmetric structure. Further, the sensor is employed for monitoring respiratory rate which measures to 13 counts/min for healthy individual and electrophysiological signals like ECG and EOG which can be used later for detecting numerous pathological conditions in humans. Electrophysiological signal sensing is carried out using a bio-signal amplifier (Bio-Amp EXG Pill) connected to Arduino. The skin-friendly, low toxic WSe2/chitosan dry electrodes pave the way for replacing wet electrodes and find numerous applications in personalized healthcare.

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Human motion detection technology holds significant potential in medicine, health care, and physical exercise. This study introduces a novel approach to human activity recognition (HAR) using convolutional neural networks (CNNs) designed for individual sensor types to enhance the accuracy and address the challenge of diverse data shapes from accelerometers, gyroscopes, and barometers. Specific CNN models are constructed for each sensor type, enabling them to capture the characteristics of their respective sensors. These adapted CNNs are designed to effectively process varying data shapes and sensor-specific characteristics to accurately classify a wide range of human activities. The late-fusion technique is employed to combine predictions from various models to obtain comprehensive estimates of human activity. The proposed CNN-based approach is compared to a standard support vector machine (SVM) classifier using the one-vs-rest methodology. The late-fusion CNN model showed significantly improved performance, with validation and final test accuracies of 99.35 and 94.83% compared to the conventional SVM classifier at 87.07 and 83.10%, respectively. These findings provide strong evidence that combining multiple sensors and a barometer and utilizing an additional filter algorithm greatly improves the accuracy of identifying different human movement patterns.

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The human louse (Pediculus humanus) is an obligatory blood feeding ectoparasite with two ecotypes: the human body louse (Pediculus humanus humanus), a competent vector of several bacterial pathogens, and the human head louse (Pediculus humanus capitis), responsible for pediculosis and affecting millions of people around the globe. GABA (γ-aminobutyric acid) receptors, members of the cys-loop ligand gated ion channel superfamily, are among the main pharmacological targets for insecticides. In insects, there are four subunits of GABA receptors: resistant-to-dieldrin (RDL), glycin-like receptor of drosophila (GRD), ligand-gated chloride channel homologue3 (LCCH3), and 8916 are well described and form distinct phylogenetic clades revealing orthologous relationships. Our previous studies in the human body louse confirmed that subunits Phh-RDL, Phh-GRD, and Phh-LCCH3 are well clustered in their corresponding clades. In the present work, we cloned and characterized a putative new GABA receptor subunit in the human body louse that we named HoCas, for Homologous to Cys-loop α like subunit. Extending our analysis to arthropods, HoCas was found to be conserved and clustered in a new (fifth) phylogenetic clade. Interestingly, the gene encoding this subunit is ancestral and has been lost in some insect orders. Compared to the other studied GABA receptor subunits, HoCas exhibited a relatively higher expression level in all development stages and in different tissues of human body louse. These findings improved our understanding of the complex nature of GABA receptors in Pediculus humanus and more generally in arthropods.

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We develop computational mechanical modeling and methods for the analysis and simulation of the motions of a human body. This type of work is crucial in many aspects of human life, ranging from comfort in riding, the motion of aged persons, sports performance and injuries, and many ergonomic issues. A prevailing approach for human motion studies is through lumped parameter models containing discrete masses for the parts of the human body with empirically determined spring, mass, damping coefficients. Such models have been effective to some extent; however, a much more faithful modeling method is to model the human body as it is, namely, as a continuum. We present this approach, and for comparison, we choose two digital CAD models of mannequins for a standing human body, one from the versatile software package LS-DYNA and another from open resources with some of our own adaptations. Our basic view in this paper is to regard human motion as a perturbation and vibration from an equilibrium position which is upright standing. A linear elastodynamic model is chosen for modal analysis, but a full nonlinear viscoelastoplastic extension is possible for full-body simulation. The motion and vibration of these two mannequin models is analyzed by modal analysis, where the normal vibration modes are determined. LS-DYNA is used as the supercomputing and simulation platform. Four sets of low-frequency modes are tabulated, discussed, visualized, and compared. Higher frequency modes are also selectively displayed. We have found that these modes of motion and vibration form intrinsic basic modes of biomechanical motion of the human body. This view is supported by our finding of the upright walking motion as a low-frequency mode in modal analysis. Such a "walking mode" shows the in-phase and out-of-phase movements between the legs and arms on the left and right sides of a human body, implying that this walking motion is spontaneous, likely not requiring any directives from the brain. Dynamic motions of CAD mannequins are also simulated by drop tests for comparisons and the validity of the models is discussed through Fourier frequency analysis. All computed modes of motion are collected in several sets of video animations for ease of visualization. Samples of LS-DYNA computer codes are also included for possible use by other researchers.

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The objective of the study is to investigate the vibration behavior of the entire spine inside the human body and the influence of muscle soft tissue and lower limbs on spinal response under vertical whole-body vibration. This study conducted modal and random response analyses to simulate the modal displacements and stress of all intervertebral discs in the vertical principal mode in the skeleton, upper, and whole body. Additionally, the acceleration response of intervertebral discs under vertical random excitation was investigated. The results revealed that removing muscle soft tissue and lower limbs significantly changed the resonant frequency, modal displacement, and stress. Particularly, there was a rapid increase in vertical displacement of the lumbar spine in the skeleton model. The reason for that was due to the lack of soft tissue to provide stability, leading to significant lumbar spine bending. Under random excitation, the fore-aft acceleration of intervertebral discs in the skeleton model was considerably larger than that in the whole body, especially in the lumbar spine where it can reach up to four times higher. Conversely, the vertical response of the intervertebral discs inside the human body model was 1.4-2.4 times larger than that of the skeleton model. Muscle soft tissue contributes to the strength of the spine, reducing fore-aft response. The muscle soft tissue in the gluteal region, connected below the spine, can lower the vertical natural frequency and attenuate spinal impact. Although the lower limbs enhance spinal stability, stimulation from the feet can superimpose vibrational responses in the spine.

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Continuous monitoring of physiological signals from the human body is critical in health monitoring, disease diagnosis, and therapeutics. Despite the needs, the existing wearable medical devices rely on either bulky wired systems or battery-powered devices needing frequent recharging. Here, we introduce a wearable, self-powered, thermoelectric flexible system architecture for wireless portable monitoring of physiological signals without recharging batteries. This system harvests an exceptionally high open circuit voltage of 175-180 mV from the human body, powering the wireless wearable bioelectronics to detect electrophysiological signals on the skin continuously. The thermoelectric system shows long-term stability in performance for 7 days with stable power management. Integrating screen printing, laser micromachining, and soft packaging technologies enables a multilayered, soft, wearable device to be mounted on any body part. The demonstration of the self-sustainable wearable system for detecting electromyograms and electrocardiograms captures the potential of the platform technology to offer various opportunities for continuous monitoring of biosignals, remote health monitoring, and automated disease diagnosis.

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Human anatomy is a fundamental aspect of a physician's knowledge. While novel technologies offer innovative ways to teach anatomy, cadavers remain an essential component of anatomical education. The quality of specimens begins with well-preserved cadavers, and the chosen vascular access for injection plays a crucial role. Unfortunately, there is a lack of literature regarding embalming procedures, as discourse on such practices could enhance the quality, safety, and effectiveness of anatomical instruction. In this study, a femoral artery approach is described for embalming, which entails a meticulous process of cutting through the skin, navigating through fascias and adipose tissue by means of blunt dissection, ultimately reaching the artery for embalming injection. Tips and techniques pertaining to this technique are provided, including vital details for convenient accessibility and minimal impairment of tissue. The objective of this study is to facilitate anatomists and technicians in the adoption of the femoral artery approach, and to encourage further exploration of alternative embalming methods, thus contributing to the continuous advancement of anatomical sciences.

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3D scanning and printing technologies are quickly evolving and offer great potential for use in gross anatomical education. The use of human body donors to create digital scans and 3D printed models raises ethical concerns about donor informed consent, potential commodification, and access to and storage of potentially identifiable anatomical reproductions. This paper reviews available literature describing ethical implications for the application of these emerging technologies, existing published best practices for managing and sharing 2D imaging, and current adherence to these best practices by academic body donation programs. We conclude that informed consent is paramount for all uses of human donor and human donor-derived materials and that currently there is considerable diversity in adherence to established best practices for the management and sharing of 3D digital content derived from human donors. We propose a new and simplified framework for categorizing donor-derived teaching materials and the corresponding level of consent required for digital sharing. This framework proposes an equivalent minimum level of specific consent for human donor and human donor-derived materials relative to generalized, nonidentical teaching materials (i.e., artificial plastic models). Likewise, we propose that the collective path forward should involve the creation of a centralized, secure repository for digital human donor 3D content as a mechanism for accumulating, regulating, and controlling the distribution of properly consented human donor-derived 3D digital content that will also increase the availability of ethically created human-derived teaching materials while discouraging commodification.

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INTRODUCTION: Informed consent is critical for maintaining the ethical standards associated with the utilization of human donor bodies by tertiary education institutions. Body donation programs undertake the responsibility for procuring human donor bodies for didactic and research purposes. However, its processes require scrutiny regarding best practice guidelines and the South African National Health Act (SA-NHA) (2013). Moreover, acknowledging and addressing the current perceptions of human body donation are indispensable in bridging the gap between academia and society. This study aimed to compare informed consent documentation and procedures across South African tertiary education institutions and their affiliated human body donation programs (HBDP) in accordance with international guidelines. The findings were used to create a human body donation form template aligned to current international best practices for consideration by the South African HBDP. METHODOLOGY: A review of information and consent forms collected from South Africa's eight HBDP was conducted. The analyses consisted of a broad evaluation of information provided, ranging from the terms-of-use for human donor bodies to the commitments made by HBDP to body-donors. The results were considered in conjunction with the International Federation of Associations of Anatomists and other recent publications on informed consent in HBDP. RESULTS: Only two of the eight HBDP provided information and consent forms in more than one language. Most allowed donors to select how their bodies will be utilized - education, training and/or research. Some (6/8) made provisions for the next-of-kin to receive the cremains. Only one tertiary educational institution mentioned the occurrence of a memorial service in its documentation. An HBDF template was created aligned to current international best practices for presentation and possible adaption by SA HBDP. DISCUSSION & CONCLUSIONS: Human body donation forms (HBDF) requires thorough examination for the promotion and sustainability of HBDP. Effective communication by employing standardized non-technical terminology conveyed in language that is understandable and native to potential donors facilitates the deliverance of informed consent. Inconsistencies regarding the use and management of bodies catalyze the weakening perception of human body donation. Thus, this process of securing informed consent for body donation should be conducted in conjunction with public awareness campaigns and underpinned by the necessary policy and legislative reform.

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Forensic reconstruction and scenario evaluation are crucial in investigations of suspicious deaths related to falls from a height. In such cases, distinguishing between accidental falls, being pushed or jumping is an important but difficult task, since objective methods to do so are currently lacking. This paper explores the possibility of repurposing a passive rigid body model of a human from commercially available crash simulation software for forensic reconstruction and scenario evaluation of humans dropping from heights. To use this approach, a prerequisite is that the human body model can produce realistic movements compared to those of a real human, given similar environmental conditions. Therefore, this study assessed the validity of the commercially available Simcenter Madymo Pedestrian Model (MPM) for simulating human fall movements. Experimental kinematic and kinetic data was collected from nine participants, who dropped from a height in three different ways: passively tilting over, getting pushed, and jumping. Next, the performance of the MPM in reproducing the kinematics of the experimental falls was assessed by comparing the orientation of the body 0.3 s after platform release. The results show that the MPM currently does not consistently reproduce the experimentally recorded falling movements across multiple falling conditions and outcome measures. The MPM must therefore be adapted if to be used for forensic reconstruction and scenario evaluation, for example by implementing active movement.

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The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

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