Dispersive Estimates Research Articles

Marine and atmospheric transport modeling supporting nuclear preparedness in Norway: Recent achievements and remaining challenges.

Numerical transport models are important tools for nuclear emergency decision makers in that they rapidly provide early predictions of dispersion of released radionuclides, which is key information to determine adequate emergency protective measures. They can also help us understand and describe environmental processes and can give a comprehensive assessment of transport and transfer of radionuclides in the environment. Transport of radionuclides in air and ocean is affected by a number of different physico-chemical processes. Along with uncertainty arising from the input data, the model estimates will therefore involve a combination of numerous uncertain factors, caused by knowledge gaps and assumptions in the model system. As discussed in this paper, the major sources to uncertainty affecting the model results are release descriptions, driving data, process descriptions and parameters. Here, we give a synthesis of the most important improvements in atmospheric and marine models achieved through the CERAD programme. In the atmospheric transport model, an important improvement has been inclusion of uncertainties in the dispersion estimates. Recent developments also include adaption to high resolution forcing data and ensemble forecasts, inversion methods and long term analyses. Case studies clearly show improved predictions from ensemble mean values compared to single deterministic runs, and promises for future upgrades of preparedness decision support systems. A major improvement in the marine model system was implementation of dynamic speciation including transformation of species, identifying particle size and parameterizations to be key factors affecting radionuclide distribution. The model system was further developed in a case study involving the impact of changing environmental factors on the transport of aluminium river run-off to an estuary in southeastern Norway. Suggestions for future improvements include implementation of an operational preparedness model for marine transport, better quantification of uncertainties using ensemble methods and improved source identification with further development of inverse transport.

Tetrascatt Model: Born Approximation for the Estimation of Acoustic Dispersion of Fluid-Like Objects of Arbitrary Geometries

Abstract Modeling the acoustic scattering response due to penetrable objects of arbitrary shapes, such as those of many marine organisms, can be computationally intensive, often requiring high-performance computing equipment when considering a completely general situation. However, when the physical properties (sound speed and density) of the scatterer are similar to those of the surrounding medium, the Born approximation provides a computationally efficient way to calculate it. For simple geometrical shapes like spheres and spheroids, the acoustic scattering in the far field evaluated through the Born approximation recipe results in a formula that has been historically employed to predict the response of weakly scattering organisms, such as zooplankton. Further, the Born approximation has been extended to bodies whose geometry can be described as a collection of noncircular rings centered on a smooth curve. In this work, we have developed a numerical approach to calculate the far-field backscattering by arbitrary 3D objects under the Born approximation. The object's geometry is represented by a volumetric mesh composed of tetrahedrons, and the computation is efficiently performed through analytical 3D integration, yielding a solution expressed in terms of elementary functions. On a current desktop PC the model can compute the scattering from meshes with millions of elements in a matter of minutes. This model is able to compute the scattering from a complex shape 200× faster than other methods like the Boundary Element Method, without compromising the numeric quality of the solution. The method's correctness has been successfully validated against benchmark solutions. Additionally, we present acoustic scattering results for species with complex geometries. To enable other researchers to use and validate the method, a computational package named tetrascatt was developed in the R programming language and published in the CRAN (Comprehensive R Archive Network).

Larval dispersal predictions are highly sensitive to hydrodynamic modelling choices

AbstractLarval dispersal is a critical ecological process in marine ecosystems, responsible for connecting and replenishing populations in patchy habitat. Because empirical measurements of larval dispersal are very challenging, coupled biological and oceanographic simulations (“biophysical models”) of larval dispersal are commonly used to answer ecological questions and support conservation management decisions. In the process of creating biophysical models, a series of choices must be made that do not have a single correct answer—sometimes because the oceanographic or ecological processes are uncertain; sometimes because trade-offs are required between different goals (e.g. computational time versus spatial resolution). In this paper, we demonstrate that larval dispersal estimates at management scales are strongly affected by these choices. Using three different hydrodynamic models of the Great Barrier Reef, we estimated the dispersal of crown-of-thorns starfish larvae in the spawning seasons between 2018 and 2021. Despite sharing similar physical forcings and using similar models of larval behaviour, we find that the different hydrodynamic models produce divergent predictions of larval dispersal between the reefs. If used to support crown-of-thorns starfish control decisions, these different predictions would recommend different priority reefs. Our results caution against the use of single models of larval dispersal, and suggest that multi-model ensembles may offer a valuable new perspective on dispersal patterns in marine environments.

INTELLIGENT MONITORING FOR DETECTIONS AND ESTIMATING RADIOLOGICAL PLUME DISPERSION IN AQUATIC ENVIRONMENTS: RIVERS AND SEAS

This work continues the presentation INTELLIGENT MONITORING FOR RADIOLOGICAL PLUME DISPERSION ESTIMATION - INTELLIGENT MONITORING FOR RADIOLOGICAL PLUM DISPERSION ESTIMATION, developed as part of the event hosted by ABDAN at the third edition of the Nuclear Trade & Technology Exchange – NT2E, Brazilian Nuclear Olympics (ONB), Hackapower. The primary objective was to develop a system for monitoring radiological plumes in aquatic environments, using a model based on Gaussian Process Regression (GPR) and Particle Swarm Optimization (PSO). The proposed system aims to estimate radiation dispersion in scenarios where plant systems are unavailable, similar to the Fukushima accident. Given this context, it was necessary to create mobile devices with radiation detection capabilities to provide accurate data on dose rate distribution. The model was developed to predict dose distribution using simulated data from a hypothetical accident and involved the use of LoRaWAN networks for drone communication and a firefly algorithm for signaling areas with different radiation levels. The implementation of GPR utilized the ScikitLearn library, while PSO was applied through the pyswarm library, focusing on optimization based on information entropy. Results indicated that the model successfully reconstructed the dose rate profile with an estimate close to the actual values, although data non-uniformity may have impacted accuracy. The use of drones for data collection proved innovative and effective, enabling real-time analysis and offering a robust solution for radiological monitoring in emergency scenarios. Analysis of radiation permeability variation in different aquatic environments highlighted the importance of adjusting measurements according to water density and composition. In conclusion, the work achieved its goal by developing an intelligent system for radiation dispersion estimation, and future work should explore new scenarios and dynamics to enhance model accuracy in real radiological emergency situations.

Percutaneous revascularization in late-presenting STEMI with absence of viability: effects on left ventricular remodeling and scar

Abstract Introduction In patients with ST-elevation myocardial infarction (STEMI), percutaneous coronary intervention (PCI) should be conducted within 12 hours of symptom onset. The potential benefits attributable to late reperfusion in STEMI fall under the "open artery hypothesis" where the stunned peri-infarction zone after revascularization would restore blood supply and contractility. Purpose To estimate the differences on the LV ejection fraction (LVEF), indexed LV end-systolic volume (iLVESV) and scar in patients with STEMI without viabilitity randomized to optimal medical therapy (OMT) alone or OMT and a late percutaneous coronary intervention (PCI) performed between 24 hours and 30 days after the event. Methods Patients with non-reperfused STEMI were evaluated from September 2021 to June 2022 at a tertiary cardiology hospital. The patients underwent Cardiac Magnetic Resonance (CMR) to assess myocardial viability and were classified as non-viable if they had only 1 wall segment with less than fifty percent thickness of the affected wall with late gadolinium enhancement. The patients were randomized to PCI or OMT alone. CMR was repeated at 6 months to evaluate LVEF, iLVESV and fibrosis. This summary presents a planned partial analysis of the 6-month results (N=51). Descriptive statistics analysis included central and dispersion estimators, or absolute and relative frequencies. To explore the differences between groups and time, Mann-Whitney and Wilcoxon tests were run, and results were given as point-estimates and confidence intervals at 95% (95% CI). A significance level of 5% was adopted for inferential analysis. Results 51 patients (60±11 years, 71% male) were included in the analysis. Of this total, 24 were randomized to PCI + OMT, and 27 to isolated OMT. The groups showed balanced distribution regarding clinical characteristics and initial CMR parameters (LVEF, iLVESV, and fibrosis). The difference in LVEF at the end of 6 months between the OMT and PCI groups was 2.07%, favoring the OMT group; however, this difference was not significant (p= 0.677, 95% CI: -5 to 10). Between the groups, the difference at the end of 6 months in iLVESV was -6.82 ml/m², also without statistical significance (p= 0.858, 95% CI: -19 to 11). There was a significant reduction in the amount of fibrosis in both PCI group with -14.68g (p= 0.011) and in the OMT group with -12.57g (p= 0.009). Detailed results are presented in Table 1. Conclusion Despite a significant reduction in fibrosis in both groups, there was no superiority observed in late PCI compared to isolated OMT in reducing reverse remodeling and fibrosis in patients with non-viable STEMI when compared to isolated OMT.Remodeling changes.

Dispersive and Strichartz Estimates for Schrödinger Equation with One Aharonov–Bohm Solenoid in a Uniform Magnetic Field

Dispersive and Strichartz Estimates for Schrödinger Equation with One Aharonov–Bohm Solenoid in a Uniform Magnetic Field

Estimation of dispersion and attenuation of Rayleigh waves in viscoelastic inhomogeneous layered half-space based on spectral method

Estimation of dispersion and attenuation of Rayleigh waves in viscoelastic inhomogeneous layered half-space based on spectral method

Dispersive estimates for Maxwell's equations in the exterior of a sphere

The goal of this article is to establish general principles for high frequency dispersive estimates for Maxwell's equation in the exterior of a perfectly conducting ball. We construct entirely new generalized eigenfunctions for the corresponding Maxwell propagator. We show that the propagator corresponding to the electric field has a global rate of decay in L1−L∞ operator norm in terms of time t and powers of h. In particular we show that some, but not all, polarizations of electromagnetic waves scatter at the same rate as the usual wave operator. The Dirichlet Laplacian wave operator L1−L∞ norm estimate should not be expected to hold in general for Maxwell's equations in the exterior of a ball because of the Helmholtz decomposition theorem.

A predictive model for the estimation of industrial [formula omitted] emissions for IoT-based devices

The paper is devoted to solving the problem, associated with increasing the forecasting accuracy of pollutant concentration level based on PM2.5 dust. The LANN model (LANN – Lagrange powered Artificial Neuron Network), proposed in the paper, allows you to take into account the mutual influence of pollution sources on the concentration level at monitoring points, which, on the one hand, allows to manage the volume of emissions from industrial enterprises in such a way as to avoid penalties and, on the other hand, allows the regulatory agencies to determine points for environmental control, at which permissible standards will be most likely exceeded. The suggested solution makes it possible to use low-cost IoT-based air quality monitoring devices, which were primarily considered not applicable due to their low accuracy and exposure to the influence of short-term stochastic factors; besides, no models were available, which would be capable to provide the necessary accuracy and forecast horizon on the base of IoT data. At the same time, the obtained model has low requirements for computing resources compared to dispersion models and is dependent on the accuracy of weather information; besides, the model allows you to take into account trends and obtain better forecast values in terms of accuracy than the models, that use regression methods, neural network models and ML models, stochastic models and their ensembles. The application of the model improves well-known pollutant dispersion estimation calculation techniques through the use of measurement data flow and dynamic adaptation to changing conditions. The model was trained on the dataset over the period 2022–2023 collected from 5 monitoring devices, which were installed in the catchment area of the group, incl. 13 industrial points of PM2.5 pollutant sources.

Wind Tunnel Experiment on the Footprint of a Block-Arrayed Urban Model in a Neutrally Stratified Boundary Layer

This study addresses the need to investigate footprint function features in urban areas and establish a validation database for numerical methods. Concentration and its flux footprints of a block-arrayed urban model were measured in a wind tunnel with a neutrally stratified boundary layer. The velocity and concentration were simultaneously measured by an X-probe hot wire anemometer and a fast-response flame ionization detector to evaluate the vertical flux. Experimental results highlighted the influence of the measurement heights on footprint distributions. Because the sensors were immersed in the roughness sublayer, their footprints showed strong heterogeneity across horizontal positions caused by building configurations. It was found that turbulent flux contributes up to 70% of total flux footprints, emphasizing the importance of accurate turbulent dispersion estimation in numerical methods. Furthermore, measured footprints were compared to those modeled by a widely used analytical method (Kormann and Meixner in Boundary-Layer Meteorol 99:207–224, 2001, https://doi.org/10.1023/ A:1018991015119). The measured footprints extended further along the streamwise direction and their spanwise dispersions were constrained by the rows of blocks, which failed to be reproduced in the analytical method. This indicates the significant effects of building configurations on footprint functions in urban areas.

The massless Dirac equation in three dimensions: Dispersive estimates and zero energy obstructions

We investigate dispersive estimates for the massless three dimensional Dirac equation with a potential. In particular, we show that the Dirac evolution satisfies a 〈t〉−1 decay rate as an operator from L1 to L∞ regardless of the existence of zero energy eigenfunctions. We also show this decay rate may be improved to 〈t〉−1−γ for any 0≤γ<1/2 at the cost of spatial weights. This estimate, along with the L2 conservation law allows one to deduce a family of Strichartz estimates in the case of a threshold eigenvalue. We classify the structure of threshold obstructions as being composed of zero energy eigenfunctions. Finally, we show the Dirac evolution is bounded for all time with minimal requirements on the decay of the potential and smoothness of initial data.

Symmetry, Asymmetry and Studentized Statistics

Inferences on the location parameter λ in location-scale families can be carried out using Studentized statistics, i.e., considering estimators λ˜ of λ and δ˜ of the nuisance scale parameter δ, in a statistic T=g(λ˜,δ˜) with a sampling distribution that does not depend on (λ,δ). If both estimators are independent, then T is an externally Studentized statistic; otherwise, it is an internally Studentized statistic. For the Gaussian and for the exponential location-scale families, there are externally Studentized statistics with sampling distributions that are easy to obtain: in the Gaussian case, Student’s classic t statistic, since the sample mean λ˜=X¯ and the sample standard deviation δ˜=S are independent; in the exponential case, the sample minimum λ˜=X1:n and the sample range δ˜=Xn:n−X1:n, where the latter is a dispersion estimator, which are independent due to the independence of spacings. However, obtaining the exact distribution of Student’s statistic in non-Gaussian populations is hard, but the consequences of assuming symmetry for the parent distribution to obtain approximations allow us to determine if Student’s statistic is conservative or liberal. Moreover, examples of external and internal Studentizations in the asymmetric exponential population are given, and an ANalysis Of Spacings (ANOSp) similar to an ANOVA in Gaussian populations is also presented.

A Closer Look at the Extended Edge-on Low-surface Brightness Galaxies

To understand the origin of extended disks of low-surface brightness (LSB) galaxies, we studied in detail four such systems with large disks seen edge on. Two of them are edge-on giant LSB galaxies (gLSBGs) recently identified by our team. The edge-on orientation of these systems boosts their surface brightnesses that provided an opportunity to characterize stellar populations spectroscopically and yielded the first such measurements for edge-on gLSBGs. We collected deep images of one galaxy using the 1.4 m Milanković Telescope, which we combined with the archival Subaru Hyper Suprime-Cam and DESI Legacy Surveys data available for the three other systems, and measured the structural parameters of the disks. We acquired deep long-slit spectra with the Russian 6 m telescope and the 10 m Keck II telescope and estimated stellar population properties in the high-surface brightness and LSB regions as well as the gas-phase metallicity distribution. The gas metallicity gradients are shallow to flat in the range between 0 and −0.03 dex per exponential disk scale length, which is consistent with the extrapolation of the gradient–scale length relation for smaller disk galaxies. Our estimates of stellar velocity dispersion in the LSB disks as well as the relative thickness of the disks indicate the dynamical overheating. Our observations favor mergers as the essential stage in the formation scenario for massive LSB galaxies.

120 Cross-validation of breeding values and future phenotypes for heifer pregnancy in Red Angus cattle using the LR method

Abstract Heifer pregnancy (HP) in beef cattle is a heritable and economically relevant trait but is challenging to predict using best linear unbiased prediction (BLUP) methodology due to the binary nature of the phenotypes. The observed categorical responses (e.g., 1 = pregnant; 0 = non-pregnant) are due to an animal either exceeding a particular threshold for pregnancy or not on an underlying genetic distribution which is why this binary trait is commonly evaluated using a threshold model (TM). However, TM are susceptible to scenarios where only 1 category of observation is predominant. In this study we compare genetic evaluations including “partial” and “whole” data to cross-validate methodologies for the prediction of HP. The objectives of this study were then to evaluate estimators of prediction accuracy, bias, and dispersion. Heifer fertility data were obtained from the Red Angus Association of America. Evaluations for HP were performed using ASREML3.0 and a univariate, BLUP, traditional TM; and a linear continuous BLUP animal model (LM) on both reference (whole) and validation (partial) datasets. Reference data included all animals with HP phenotypes, and validation data had censored the most recent 5 yr of HP phenotypes (~16% of HP phenotypes). Reference and validation estimated breeding values (EBV) were then compared using linear regression (LR) methods. Heritability estimates were 0.05 (± 0.007) and 0.15 (± 0.009) for LM and TM respectively. The average BIF accuracy of censored validation animals (n = 10,175) using a LM on whole and partial datasets were 0.07 and 0.03 respectively, and using a TM on whole and partial datasets were 0.09 and 0.04 respectively. Comparing the mean EBV from the partial and whole datasets can be a good estimator of bias in the model as the difference is expected to be 0. The difference between the mean EBV from partial and mean EBV from whole datasets were –0.003 and –0.016 for LM and TM respectively, suggesting that the TM is a slightly more biased evaluation. The regression of EBV obtained with whole data on EBV estimated with partial data has an expected value of 1 if there is no over/under dispersion which can be a useful tool in determining model correctness and gauge bias in an evaluation. The closer a regression coefficient is to 1, the less biased the evaluation is. The slope of the regression of EBV estimated from whole data on partial data for validation animals were 0.98 (P &amp;lt; 0.0001) and 0.91 (P &amp;lt; 0.0001) for LM and TM respectively. Although both regression coefficients were above 0.90 suggesting both evaluations are performing well, these results suggest that TM models may be a more biased predictor of HP than LM despite a small benefit in prediction accuracy for the trait.

REAL-TIME PARAMETRIC DIAGNOSTICS OF MARINE DIESEL ENGINES

Using modern high-performance microcontrollers with wireless interfaces, built-in ADC and low overall consumption, it is possible to develop a portable real-time parametric diagnostic system for marine engines. The system is based on the use of modern Android/iOS gadgets that receive information from sensors via Bluetooth and then make the necessary calculations and display charts and data in real time. The system being developed uses a combination of a gas pressure sensor in the working cylinder and a vibroacoustic sensor, which expands the diagnostic capabilities of marine diesel engines under operating conditions. This solution makes it possible to diagnose the fuel injection system, the valves control mechanism, as well as some other engine systems. In order to develop a portable diagnostic system for marine diesel engines, it is first necessary to solve the problem of analytically determining TDC, since such a system does not involve the use of special sensors for this. Parameters of irregular engine operation are considered, which can be calculated in real time using time diagrams of pressure and vibration. Methods for expressly assessing the stability of the functioning of the main engine systems by monitoring and analyzing a number of successive operating cycles are considered. To assess the unevenness of engine operation, a dispersion estimate of deviations of the main parameters is used. For a comprehensive assessment of engine stability in real time, the CII (cycle’s irregularity index) criterion is proposed. The assessment of fuel injection irregularity in the engine cylinder can be carried out by analyzing the phase fronts of the vibration signal of the injector. Coefficients for assessing the irregularity of fuel injection and gas distribution valves timing are also proposed, using dispersion analysis of vibrograms fronts. The data processing methods proposed in the article will make it possible to analyze the stability of operating cycles, as well as to perform optimal tuning of engine systems and monitor the results during operation.

Dispersion and Attenuation Estimation of Ultrasonic Guided Waves using Multi-Subarrays Matrix Pencil Method

Abstract Dispersion and attenuation estimation of ultrasonic guided waves is important for waveguide characterization. Matrix pencil (MP) method has been proposed for multimode complex wavenumber estimation, but its performance highly depends on the signal to noise ratio (SNR), which still brings challenges for high attenuation waveguide evaluation. In addition, the model order, i.e., matrix size in MP method, significantly impacts the dispersion curve extraction. In this study, to avoid the model order interference and compensate the SNR sensitivity of the classical MP algorithm, a multi-subarrays MP method is proposed for accurate dispersion and attenuation estimation. Considering with different Hankel matrix sizes, the multi-subarrays MP method estimates the complex wavenumbers from each pair of submatrices to filter uncertain results. A soft threshold strategy is applied to compensate the noise sensitivity of the estimation. Simulated results prove the proposed method can improve the dispersion and attenuation curve estimation.

Dispersive estimates for 1D matrix Schrödinger operators with threshold resonance

Dispersive estimates for 1D matrix Schrödinger operators with threshold resonance

Methods of Real-Time Parametric Diagnostics for Marine Diesel Engines

Abstract Using modern high-performance microcontrollers with wireless interfaces, built-in ADCs and low overall consumption, we develop a portable, real-time parametric diagnostic system for marine engines. The system is based on the use of modern Android/iOS gadgets that receive information from sensors via Bluetooth and then carry out the necessary calculations and display charts and data in real time. The system developed here uses a combination of a gas pressure sensor in the working cylinder and a vibroacoustic sensor, which expands the diagnostic capabilities of marine diesel engines under operating conditions. This solution allows for diagnosis of the fuel injection system, the valve train mechanism, and several other engine systems. In order to develop a portable diagnostic system for marine diesel engines, it is first necessary to solve the problem of analytically determining top dead centre (TDC), since such a system does not use special sensors for this. An algorithm for determining TDC is proposed here, based on an analysis of the measured pressure diagram rather than its derivative, which minimises the influence of digital and analogue noise. Our algorithm for determining TDC and subsequent data synchronisation is applicable in the absence of information about the actual compression ratio in the cylinder, which is a typical scenario for modern engines with variable valve timing. The algorithm also works under conditions of only approximate data on the charge air pressure, which are refined during the iteration process. A formula is proposed for determining the initial TDC position. Parameters for irregular operation of the engine are considered, and can be calculated in real time using time diagrams of pressure and vibration. Methods for expressly assessing the stability of the functioning of the main engine systems by monitoring and analysing a number of successive operating cycles are considered. To assess the unevenness of operation of the engine, a dispersion estimate of the deviations in the main parameters is used. To enable a comprehensive assessment of the engine stability in real time, the CII (cycle irregularity index) criterion is developed. The data processing methods described in this article provide an accurate estimate of the indicated power, due to the precise determination of TDC, thereby enabling an analysis of the stability of the operating cycles, optimal tuning of the engine systems, and monitoring of the results during operation.

Effects of probability model misspecification on the number of ground motions required for seismic performance assessment

The number of ground motions used in nonlinear response history analysis (NRHA) determines the precision of the parameter estimates obtained in seismic performance assessments. While this issue has been extensively studied in the earthquake engineering literature, the relationship of probability model misspecification to parameter estimation uncertainty, and the implication to the required number of ground motions needed for NRHA, has not been examined. Probability model misspecification has the potential to increase estimation uncertainty and hence requires a greater number of ground motions to achieve the same precision compared to when misspecification is disregarded. This study develops a procedure to determine the required number of ground motions in seismic code-prescriptive and risk-based assessments with possible probability model misspecification. Specifically, we employ the quasi-maximum likelihood estimation (QMLE), which is robust to probability model misspecification, to evaluate estimation uncertainty. The QMLE approach is applied to an archetype California bridge under the two seismic assessment scenarios. In the code-prescriptive assessment, misspecification errors are identified for dispersion estimates of the bridge column ductility demand. In the most extreme case of the risk-based evaluation, misspecification increases the estimation uncertainty of the mean annual frequency of exceeding a limit state by as much as three times, which substantially increases the required number of ground motions. Based on the findings from this study, we advocate for the use of QMLE to detect and rectify the implications of model misspecification to estimation uncertainty and the number of ground motions used in probabilistic seismic performance assessments.

Visual system structural and functional connections during face viewing in body dysmorphic disorder.

Individuals with body dysmorphic disorder (BDD) perceive distortions in their appearance, which could be due to imbalances in global and local visual processing. The vertical occipital fasciculus connects dorsal and ventral visual stream regions, integrating global and local information, yet the role of this structural connection in BDD has not been explored. Here, we investigated the vertical occipital fasciculus's white matter microstructure in those with BDD and healthy controls and tested associations with psychometric measures and effective connectivity while viewing their face during fMRI. We analyzed diffusion MRI and fMRI data in 17 unmedicated adults with BDD and 21 healthy controls. For diffusion MRI, bundle-specific analysis was performed, enabling quantitative estimation of neurite density and orientation dispersion of the vertical occipital fasciculus. For task fMRI, participants naturalistically viewed photos of their own face, from which we computed effective connectivity from dorsal to ventral visual regions. In BDD, neurite density was negatively correlated with appearance dissatisfaction and negatively correlated with effective connectivity. Further, those with weaker effective connectivity while viewing their face had worse BDD symptoms and worse insight. In controls, no significant relationships were found between any of the measures. There were no significant group differences in neurite density or orientation dispersion. Those with BDD with worse appearance dissatisfaction have a lower fraction of tissue having axons or dendrites along the vertical occipital fasciculus bundle, possibly reflecting impacting the degree of integration of global and local visual information between the dorsal and ventral visual streams. These results provide early insights into how the vertical occipital fasciculus's microstructure relates to the subjective experience of one's appearance, as well as the possibility of distinct functional-structural relationships in BDD.