Modified Radiological Union Score of Tibia (RUST) Scores in Diaphyseal Fractures Treated by the Ilizarov Frame: A Retrospective Analysis Evaluating Reliability.

Introduction The number of cases of tibia diaphyseal fractures treated by Ilizarov fixation is increasing. Fractures with infective etiology and altered bone biology due to the requirement of revision surgery or open wounds, which are often treated by the Ilizarov method, have challenges in ascertaining radiological signs of union. In this study, we aim to demonstrate the application of the modified Radiological Union Score of Tibia (m-RUST) scores in the assessment of fracture union in patients operated by the Ilizarov method. The secondary aim is to assess the interobserver and intraobserver variability of the m-RUST score validated by orthopaedicians and radiologists. Methodology A total of 119 patients who were treated with an Ilizarov fixator from February 2017 to December 2023 were included in the study. Four observers (two orthopaedicians and two radiologists) independently applied the m-RUST score for the included patients. Clinical data were not disclosed to the observers who worked independently of each other. Intraclass correlation coefficients (ICC) with 95% confidence intervals (CI) were used to measure the reliability of the m-RUST score. Interobserver reliability was measured by examining the scores of four observers from the second assessment, and intra-observer variability was assessed by a repeat evaluation after two weeks following the first assessment. Results The m-RUST score of the 119 X-rays analysed ranged from 8 to 16. The mean score in the first assessment was 11.36±3.51, and in the second assessment was 11.42±3.39. The reliability between all the observers was "substantial agreement" (ICC: 0.74, 95% CI). The ICC among the orthopaedicians was 0.77 and that among the radiologists was 0.72. Conclusion The m-RUST score has potential in other long bone fractures such as femur or humerus. Assessment of the m-RUST score in the healing of infective sequel and bone grafting conditions has been found effective. The m-RUST score is a dependable score in evaluating union in tibia fractures treated by the Ilizarov frame.

An observer tool to enhance learning of medical students during simulation training of cardiopulmonary resuscitation: a randomised controlled trial.

BACKGROUND: Simulation training in cardiopulmonary resuscitation (CPR) is effective but active practice time is limited given the large number of students and the learning effect size remains small. To improve learning during observation, the use of an observer tool (OT) has been advocated. The aim was to assess the value of OT to improve medical students' learning outcomes during CPR simulation training. METHODS: This prospective, randomized study took place during CPR training of medical students. The workshop targeted recognition of unconsciousness, absence of breathing, call for help, cardiac massage and defibrillation. Students practicing in dyads were randomized to use an OT (i.e., a checklist summarizing CPR skills and step-by-step actions) (OT +) or not (OT-) when observing others. At the end of the training, the global performance of the dyad was assessed by an evaluator using the OT checklist (primary outcome). The non-technical skills (NTS), chest compression quality, perceived improvement in knowledge and skills and knowledge score (MCQ) were also recorded. RESULTS: The student dyads were included (OT + : n = 40 and OT-: n = 41). Immediately after training, the global performance was similar between the two groups: OT + : 24 [23-25] and OT-: 23 [21-24] (out of 25), p = 0.052. However, better learning of breathing assessment and cardiac massage performance, as well as a better knowledge score, were found in the OT + group. No significant difference was observed for NTS or perceived improvement in knowledge and skills. Satisfaction was higher in the OT- group. CONCLUSIONS: The use of an OT during CPR simulation did not show any pedagogical benefit on the global performance of medical students. However, a potential benefit was found for several important secondary outcomes. Further studies are needed to confirm these positive results.

Integral sliding mode control for an anthropomorphic finger based on nonlinear extended state observer.

Due to the disturbance of couplings, the anthropomorphic finger lacks sufficient stability and accuracy in joint motion control, which further affects the performance of complex grasping and operating for anthropomorphic hands. In order to obtain stable and accurate joint motion control effect, an anthropomorphic finger control strategy is proposed for an anthropomorphic finger driven by pneumatic artificial muscles (PAMs) in this paper. A nonlinear extended state observer (NESO) is presented to observe the disturbance of couplings for the anthropomorphic finger. An integral sliding mode controller (ISMC) is proposed to realize joint motion control and improve steady state performance. The convergences of the NESO and the ISMC are demonstrated by Lyapunov methods. Furthermore, experimental results illustrate the validity of the proposed control strategy.

Belief in a just world and fair behavior among clinical nurses: a moderated mediation model of empathy and observer justice sensitivity.

BACKGROUND: Exploration of the relationship between nursing staffs' justice in belief world and fair behavior is important to promote equity and access to health services in health organizations, as well as to enhance the quality of care. In order to further dissect the influencing factors of fair behavior among clinical nurses, the current study aims to investigate how belief in a just world influences the fair behavior among nurses. Based on the belief in a just world theory, the empathy-altruism theory and the protective-protective model, the current study aimed to provide a deeper understanding of the effect of belief in a just world on fair behavior by investigating the mediating role of empathy and the moderating role of observer justice sensitivity. METHOD: This was a cross-sectional study. 571 registered clinical nurses were included from five hospitals in Fuzhou through a convenience sampling method. Measurements included Chinese translations of belief in a just world scale, empathy scale, observer justice sensitivity scale, fair behavior scale. SPSS 22.0 was used to describe descriptive statistics and the variables' Pearson correlation coefficient. SPSS PROCESS macro Model 4 and model 14 were used to examine the mediation and the moderation between the relationship of belief in a just world and fairness behavior. RESULT: The results shower that fairness behavior was positively correlated with one's belief in a just world (r = 0.26, p < 0.01); (2)empathy mediated the relationship between belief in a just world and fair behavior. The mediation model explains 20.83%; (3) Observer justice sensitivity moderated the relationship between empathy and fair behavior. CONCLUSIONS: Belief in a just world, empathy, and observer justice sensitivity were motivations for nurses' fair behavior. Nursing administrators should focus on cultivating nurses' belief in a just world, their empathy abilities, and positive qualities of justice sensitivity to enhance fair behavior in a healthcare setting.

A comparison of target volumes drawn on arterial and venous phase scans during radiation therapy planning for patients with pancreatic cancer: the PANCRINJ study.

BACKGROUND: The planification of radiation therapy (RT) for pancreatic cancer (PC) requires a dosimetric computed tomography (CT) scan to define the gross tumor volume (GTV). The main objective of this study was to compare the inter-observer variability in RT planning between the arterial and the venous phases following intravenous contrast. METHODS: PANCRINJ was a prospective monocentric study that included twenty patients with non-metastatic PC. Patients underwent a pre-therapeutic CT scan at the arterial and venous phases. The delineation of the GTV was performed by one radiologist (gold standard) and two senior radiation oncologists (operators). The primary objective was to compare the Jaccard conformity index (JCI) for the GTVs computed between the GS (gold standard) and the operators between the arterial and the venous phases with a Wilcoxon signed rank test for paired samples. The secondary endpoints were the geographical miss index (GMI), the kappa index, the intra-operator variability, and the dose-volume histograms between the arterial and venous phases. RESULTS: The median JCI for the arterial and venous phases were 0.50 (range, 0.17-0.64) and 0.41 (range, 0.23-0.61) (p = 0.10) respectively. The median GS-GTV was statistically significantly smaller compared to the operators at the arterial (p < 0.0001) and venous phases (p < 0.001), respectively. The GMI were low with few tumors missed for all patients with a median GMI of 0.07 (range, 0-0.79) and 0.05 (range, 0-0.39) at the arterial and venous phases, respectively (p = 0.15). There was a moderate agreement between the radiation oncologists with a median kappa index of 0.52 (range 0.38-0.57) on the arterial phase, and 0.52 (range 0.36-0.57) on the venous phase (p = 0.08). The intra-observer variability for GTV delineation was lower at the venous phase than at the arterial phase for the two operators. There was no significant difference between the arterial and the venous phases regarding the dose-volume histogram for the operators. CONCLUSIONS: Our results showed inter- and intra-observer variability in delineating GTV for PC without significant differences between the arterial and the venous phases. The use of both phases should be encouraged. Our findings suggest the need to provide training for radiation oncologists in pancreatic imaging and to collaborate within a multidisciplinary team.

Angle attitude control for a networked pneumatic muscle actuators system with input quantization: A prescribed-time nonlinear ESO approach.

In this paper, angle attitude control is investigated for a networked pneumatic muscle actuators system (NPMAS) with input quantization and disturbance. A hysteretic quantizer is presented to effectively avoid the problem of high frequency oscillation in the process of quantization. A novel prescribed-time nonlinear extended state observer (PTNESO) is designed to continuously observe states and lumped disturbances of NPMAS, which ensures that the observation error converges in prescribed time. An active disturbance rejection control (ADRC) method based on PTNESO is designed to compensate for the lumped disturbances and achieve accurate angle tracking. A sufficient condition of bounded stability for NPMAS is given by the Lyapunov method. Finally, comparative experiments are provided to verify the effectiveness of the proposed control method.

The PompeQoL questionnaire: Development and validation of a new measure for children and adolescents with Pompe disease.

Genetic disorders pose great challenges for affected individuals and their families, as they must cope with the irreversible nature of the disease and a life-long dependence on medical assistance and treatment. Children and adolescents dealing with Pompe disease (PD) often struggle to keep up with their peers in physical activities. To gain valuable insights into their subjective experiences and better understand their perception and coping related to daily challenges linked to their condition and treatment, the use of standardized questionnaires is crucial. This study introduces the novel PompeQoL 1.0 questionnaire for children and adolescents with PD, designed for comprehensive assessment of both disease-specific FDH and HRQoL through self- and proxy reports. Content validity was ensured through patients' and parents' involvement at the initial stages of development and in subsequent cognitive debriefing process. Participants found the questionnaire easy to understand, answerable, relevant, and comprehensive. Adjustments based on feedback from patients and their parents improved its utility as a patient- and observer-reported outcome measure. After careful item examination, 52 items were selected, demonstrating moderate to excellent test-retest reliability for most scales and initial evidence for satisfactory construct validity. The PompeQoL questionnaire stands as a valuable screening instrument for both clinical and research purposes. Future research should prioritize additional revisions and larger validation studies, focusing on testing the questionnaire in clinical practice and trials. Nevertheless, the PompeQoL 1.0 stands out as the first standardized measure providing insights into disease-specific FDH and HRQoL among children and adolescents with various forms of PD.

A deep learning anthropomorphic model observer for a detection task in PET.

BACKGROUND: Lesion detection is one of the most important clinical tasks in positron emission tomography (PET) for oncology. An anthropomorphic model observer (MO) designed to replicate human observers (HOs) in a detection task is an important tool for assessing task-based image quality. The channelized Hotelling observer (CHO) has been the most popular anthropomorphic MO. Recently, deep learning MOs (DLMOs), mostly based on convolutional neural networks (CNNs), have been investigated for various imaging modalities. However, there have been few studies on DLMOs for PET. PURPOSE: The goal of the study is to investigate whether DLMOs can predict HOs better than conventional MOs such as CHO in a two-alternative forced-choice (2AFC) detection task using PET images with real anatomical variability. METHODS: Two types of DLMOs were implemented: (1) CNN DLMO, and (2) CNN-SwinT DLMO that combines CNN and Swin Transformer (SwinT) encoders. Lesion-absent PET images were reconstructed from clinical data, and lesion-present images were reconstructed with adding simulated lesion sinogram data. Lesion-present and lesion-absent PET image pairs were labeled by eight HOs consisting of four radiologists and four image scientists in a 2AFC detection task. In total, 2268 pairs of lesion-present and lesion-absent images were used for training, 324 pairs for validation, and 324 pairs for test. CNN DLMO, CNN-SwinT DLMO, CHO with internal noise, and non-prewhitening matched filter (NPWMF) were compared in the same train-test paradigm. For comparison, six quantitative metrics including prediction accuracy, mean squared errors (MSEs) and correlation coefficients, which measure how well a MO predicts HOs, were calculated in a 9-fold cross-validation experiment. RESULTS: In terms of the accuracy and MSE metrics, CNN DLMO and CNN-SwinT DLMO showed better performance than CHO and NPWMF, and CNN-SwinT DLMO showed the best performance among the MOs evaluated. CONCLUSIONS: DLMO can predict HOs more accurately than conventional MOs such as CHO in PET lesion detection. Combining SwinT and CNN encoders can improve the DLMO prediction performance compared to using CNN only.

Multi-Agent System Based Cooperative Control for Speed Convergence of Virtually Coupled Train Formation.

This paper investigates the problem of spacing control between adjacent trains in train formation and proposes a distributed train-formation speed-convergence cooperative-control algorithm based on barrier Lyapunov function. Considering practical limitations such as communication distance and bandwidth constraints during operation, not all trains can directly communicate with the leader and obtain the expected trajectory it sends, making it difficult to maintain formation consistency as per the predetermined ideal state. Furthermore, to address the challenge of unknown external disturbances encountered by trains during operation, this paper designs a distributed observer deployed on each train in the formation. This observer can estimate and dynamically compensate for unknown reference trajectories and disturbances solely based on the states of adjacent trains. Additionally, to ensure that the spacing between adjacent trains remains within a predefined range, a safety hard constraint, this paper encodes the spacing hard constraint using barrier Lyapunov function. By integrating nonlinear adaptive control theory to handle model parameter uncertainties, a barrier Lyapunov function-based adaptive control method is proposed, which enables all trains to track the reference trajectory while ensuring that the spacing between them remains within the preset interval, therefore guaranteeing the asymptotic stability of the closed-loop system. Finally, a practical example using data from the Guangzhou Metro Line 22, specifically the route from Shiguang Road Station to Chentougang Station over three stations and two sections, is utilized to validate the effectiveness and robustness of the proposed algorithm.

Distributed State Observer for Systems with Multiple Sensors under Time-Delay Information Exchange.

The issues of state estimations based on distributed observers for linear time-invariant (LTI) systems with multiple sensors are discussed in this paper. We deal with the scenario when the information exchange has known time delays, and aim at designing a distributed observer for each subsystem such that each distributed observer can estimate the system state asymptotically by rejecting the time delay. To begin with, by rewriting the target system in a connecting form, a subsystem which is affected by the time-delay states of other nodes is established. And then, for this subsystem, a distributed observer with time delay is constructed. Moreover, an equivalent state transformation is made for the observer error dynamic system based on the observable canonic decomposition theorem. Further, in order to ensure that the distributed observer error dynamic system is asymptotically stable even if there exists a time delay, a linear matrix inequality (LMI) which is relative to the Laplace matrix is elaborately set up, and a special Lyapunov function candidate based on the LMI is considered. Next, based on the Lyapunov function and Lyapunov stability theory, we prove that the error dynamic system of the distributed observer is asymptotically stable, and the observer gain is determined by a feasible solution of the LMI. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.

Craniocervical Morphometry in Pomeranians-Part I: Intra-Observer, Interobserver, and Intermodality (CT vs. MRI) Agreement.

BACKGROUND: Currently, there are no diagnostic imaging-based studies that have focused specifically on the craniocervical morphology of Pomeranian dogs in relation to Chiari-like malformation and syringomyelia (CM/SM). The aims of Part I of this two-part study are to assess the intra-observer, interobserver, and intermodality reliability and agreement for various aspects of the craniocervical morphology of Pomeranians with and without CM/SM. METHODS: Prospectively, Pomeranians were included that underwent both CT and MRI studies of the head and cervicothoracic vertebral column. Two observers (experienced and novice) independently performed CM and SM classifications, qualitative assessments, and quantitative measurements. The experienced observer performed these assessments twice. A third observer (experienced) performed CM and SM normal or abnormal classifications. RESULTS: Ninety-nine (99) dogs were included. Interobserver reliability was influenced by observer experience level. For the experienced versus novice observers, substantial interobserver agreement was found for classification of SM as normal or abnormal (Cohen's kappa = 0.63), while interobserver agreement was fair for classification of SM as normal or abnormal (Cohen's kappa = 0.31). Interobserver, intra-observer, and intermodality reliability were variable for different measurements and assessments, and best overall for the CT-based measurements. CONCLUSIONS: Interobserver reliability and agreement results should be taken into account in the evaluation of results of future studies as well as the evaluation of imaging studies of Pomeranians presented clinically.

Neural network-based adaptive fault-tolerant control for nonlinear systems with uncertainties.

This paper proposes a novel fault-tolerant control (FTC) scheme for real-time uncertainty estimation in nonlinear systems. It addresses the challenges arising from nonlinear dynamics in system inputs, states, and outputs, along with measurement uncertainties, within an output feedback framework. Our approach leverages two key components: 1) A neural network NN descriptor-based observer: this novel observer concurrently estimates both system states and sensor uncertainties. It is particularly capable of handling unbounded sensor uncertainties in specific situations. It utilizes NNs as universal approximators to capture the system's complex nonlinearities. 2) A robust model reference tracking controller: this controller employs the estimated states from the NN descriptor-based observer to achieve the desired system performance despite the existence of uncertainties. It exhibits robustness, guaranteeing system stability and asymptotic state tracking to a given reference model. The efficacy of the proposed FTC scheme is validated through theoretical analysis and its application to two real-world case studies.

Task-based image quality assessment of an intraoperative CBCT for spine surgery compared with conventional CT.

PURPOSE: To analyze the image quality of a novel, state-of-the art platform for CBCT image-guided spine surgery, focusing particularly on the dose-effectiveness compared with conventional CT (the gold standard for postoperative assessment). METHODS: The ClarifEye platform (Philips Healthcare) with integrated augmented-reality surgical navigation, has been compared with a GE Revolution CT (GE Healthcare). The 3D spatial resolution (TTF) and noise (NPS) were evaluated considering relevant feature contrasts (200-900 HU) and background noise for differently sized patients (200-300 mm water-equivalent diameter). These measures were used to determine the noise equivalent quanta (NEQ) and observer model detectability. RESULTS: The CBCT system exhibited a linear response with 50% TTF at 5.7 cycles/cm (10% TTF at 9.2 cycles/cm), and the axial noise power peaking at about 3.6 cycles/cm (average frequency of 4.1 cycles/cm). The noise magnitude and texture differed markedly compared to iteratively reconstructed CT images (GE ASiR-V). The CBCT system had 26% lower detectability for a high-frequency task (related to edge detection) compared with CT images reconstructed using the Bone kernel combined with ASiR-V 50%. Likewise, it had 18% lower detectability for low- and mid-frequency tasks compared with CT images reconstructed using the Standard kernel. This difference translates to 50%-80% higher CBCT imaging doses required to match the CT image quality. CONCLUSIONS: The ClarifEye platform demonstrates intraoperative CBCT-imaging capabilities that under certain circumstances are comparable with conventional CT. However, due to limited dose-effectiveness, a trade-off between timeliness and radiation exposure must be considered if end-of-procedure CBCT is to replace postoperative CT.

Robust internal model control based on a novel generalized extended state observer and its application on a two-inertia system.

Disturbance observer (DOB) and extended state observer (ESO) are extensively utilized to handle external disturbances and model uncertainties in the control system. Nevertheless, the integration of these two methods to improve disturbance suppression remains an open question. In this research, the disturbance compensation mechanism of DOB is employed to compensate the disturbance estimation error of ESO, thereby achieving an effective integration of DOB and ESO. Additionally, a generalized ESO (GESO) is proposed to replace ESO. A robust internal mode control (RIMC) scheme is then developed by incorporating GESO into a two-degree-of-freedom internal mode control (TDF-IMC) framework. Moreover, the equivalence of RIMC and classical TDF-IMC is given by a rigorous derivation under the frequency domain description. Finally, the RIMC is applied to the control of a two-inertia system to verify its superiority in terms of robustness, disturbance rejection, and resonance suppression.

Adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems with unmeasurable states.

This paper addresses the adaptive fixed-time fuzzy containment control for uncertain nonlinear multiagent systems, where the states and nonlinear functions are not feasible for the controller design. To address the issue of unmeasurable states, a state observer is developed, and fuzzy logic systems are utilized to approximate unknown nonlinear functions. Under the framework of fixed-time Lyapunov function theory and cooperative control, an adaptive fixed-time fuzzy containment control protocol is derived via the adaptive backstepping and adding one power integrator method. The derived fixed-time containment controller can confirm that the closed-loop systems are practical fixed-time stable, which implies that all signals in the systems are bounded and all follower agents can converge to the convex hull formed by the leader agents within fixed-time in the presence of unmeasurable states and unknown nonlinear functions . Simulation examples are conducted to test the validity of the present control algorithm.

Evaluating the impact of delayed-phase imaging in Contrast-Enhanced Mammography on breast cancer staging: A comparative study of abbreviated versus complete protocol.

PURPOSE: Contrast-enhanced mammography (CEM) is an innovative imaging tool for breast cancer detection, involving intravenous injection of a contrast medium and the assessment of lesion enhancement in two phases: early and delayed. The aim of the study was to analyze the topographic concordance of lesions detected in the early- versus delayed phase acquisitions. MATERIALS AND METHODS: Approved by the Ethics Committee (No. 118/20), this prospective study included 100 women with histopathological confirmed breast neoplasia (B6) at the Radiodiagnostics Department of the Maggiore della Carità Hospital of Novara, Italy from May 1, 2021, to October 17, 2022. Participants underwent CEM examinations using a complete protocol, encompassing both early- and delayed image acquisitions. Three experienced radiologists blindly analyzed the CEM images for contrast enhancement to determine the topographic concordance of the identified lesions. Two readers assessed the complete study (protocol A), while one reader assessed the protocol without the delayed phase (protocol B). The average glandular dose (AGD) of the entire procedure was also evaluated. RESULTS: The analysis demonstrated high concordance among the three readers in the topographical identification of lesions within individual quadrants of both breasts, with a Cohen's κ > 0.75, except for the lower inner quadrant of the right breast and the retro-areolar region of the left breast. The mean whole AGD was 29.2 mGy. The mean AGD due to CEM amounted to 73% of the whole AGD (21.2 mGy). The AGD attributable to the delayed phase of CEM contributed to 36% of the whole AGD (10.5 mGy). CONCLUSIONS: As we found no significant discrepancy between the readings of the two protocols, we conclude that delayed-phase image acquisition in CEM does not provide essential diagnostic benefits for effective disease management. Instead, it contributes to unnecessary radiation exposure.

An extended hysteresis observer-based adaptive robust control method for nonlinear macro-micro motion system.

In this paper, for macro-micro composite motion platform with piezoelectric hysteresis, an finite-time adaptive robust control method based on extended hysteresis observer is proposed. The dynamic model of macro-micro system is constructed at first. An extended hysteresis observer was designed to estimate the actual displacement and speed of motion system. Then, an adaptive robust control law is designed to eliminate the uncertain hysteresis model parameters. After this, exponential convergence result of the proposed control method is given and proved. By setting the expected bandwidth of macro-micro system, the gain adjustment process of the control method can be reduced in computation. The effectiveness of the proposed control method is demonstrated by comparison with other control methods in simulation, and the proposed control method has more stable tracking effect and smaller tracking error.

Understanding interobserver variability of pathologists to improve oral epithelial dysplasia grading.

OBJECTIVE: This study aimed to understand reasons for interobserver variability in the grading of oral epithelial dysplasia (OED) through a survey of pathologists to provide insight for improvements in the reliability and reproducibility of OED diagnoses. METHODS: The study design included quantitative and qualitative methodology. A pre-validated 31-item questionnaire was distributed to general, head and neck, and oral and maxillofacial histopathology specialists worldwide. RESULTS: A total of 132 pathologists participated and completed the questionnaire. Over two-thirds used the three-tier grading system for OED, while about a third used both binary and three-tier systems. Regular reporters of OED preferred the three-tier system and grading architectural features. Continuing education significantly aided recognition of architectural and cytological changes. Irregular epithelial stratification and drop-shaped rete ridges had the lowest prognostic value and recognition scores, while loss of epithelial cell cohesion had the highest. Most participants used clinical information and often sought a second opinion when grading OED. CONCLUSION: Our study has found that frequency of OED reporting and attendance of CME/CPD can play an important role in grading OED. Variations in the prognostic value of individual histological features and the use of clinical information may further contribute to interobserver variability.

Reliability of a forensic odontology method for age-at-death estimation in adults: A Mexican case study.

This study aimed to evaluate the reliability of an age estimation method based on the pulp/tooth area ratio by assessing intra- and inter-examiner agreement across five observers at different intervals. Using the same X-ray device and technical parameters, 96 digital periapical X-ray images of upper and lower canines were obtained from 28 deceased people in Central America, whose age at death ranged from 19 to 49 years. Excellent and good agreement of results were achieved, and there were no statistically significant differences. The R2 value for upper teeth (54.0%) was higher than the R2 value for lower teeth (45.7%). The highest intraclass correlation coefficient value was 0.995 (0.993-0.997) and the lowest 0.798 (0.545-0.895). Inter-examiner agreement was high with values of 0.975 (0.965-0.983) and 0.927 (0.879-0.955). This method is adequate for assessing age in missing and unidentified people, including victims of mass disasters.

The fundamental role of character coding in Bayesian morphological phylogenetics.

Phylogenetic trees establish a historical context for the study of organismal form and function. Most phylogenetic trees are estimated using a model of evolution. For molecular data, modeling evolution is often based on biochemical observations about changes between character states. For example, there are four nucleotides, and we can make assumptions about the probability of transitions between them. By contrast, for morphological characters, we may not know a priori how many characters states there are per character, as both extant sampling and the fossil record may be highly incomplete, which leads to an observer bias. For a given character, the state space may be larger than what has been observed in the sample of taxa collected by the researcher. In this case, how many evolutionary rates are needed to even describe transitions between morphological character states may not be clear, potentially leading to model misspecification. To explore the impact of this model misspecification, we simulated character data with varying numbers of character states per character. We then used the data to estimate phylogenetic trees using models of evolution with the correct number of character states and an incorrect number of character states. The results of this study indicate that this observer bias may lead to phylogenetic error, particularly in the branch lengths of trees. If the state space is wrongly assumed to be too large, then we underestimate the branch lengths, and the opposite occurs when the state space is wrongly assumed to be too small.