Orientation Parameters Research Articles

First and Second-Order Polynomial Transformation for satellite image correction

The absence of ground control points (GCPs) in historical declassified intelligence satellite photography (DISP) images, as well as satellite orbit parameters, and camera interior and exterior orientation parameters, necessitated the creation of a first-order 1st polynomial equation model and a second-order 2nd polynomial equation model for orthorectification purposes. The Mosul region of northwest Iraq was used as a case study, with data from Satellite 7 released on April 15, 1999. The study achieved an RMS of approximately 2.1 x 10−8 and the error ratio was considered acceptable due to the 30-meter resolution of the satellite image.

Camera-Aided Orientation of Mobile Lidar Point Clouds Acquired from an Uncrewed Water Vehicle.

This article presents a system for recording 3D point clouds of riverbanks with a mobile lidar mounted on an uncrewed water vehicle. The focus is on the orientation of the platform and the lidar sensor. Rivers are areas where the conditions for highly accurate GNSS can be sub-optimal due to multipath effects from the water and shadowing effects by bridges, steep valleys, trees, or other objects at the riverbanks. Furthermore, a small measurement platform may have an effect on the accuracy of orientations measured by an IMU; for instance, caused by electromagnetic fields emitted by the boat rotors, the lidar, and other hardware decreasing IMU accuracy. As an alternative, we use exterior orientation parameters obtained by photogrammetric methods from the images of a camera on the boat capturing the riverbanks in time-lapse mode. Using control points and tie points on the riverbanks enables georeferenced position and orientation determination from the image data, which can then be used to transform the lidar data into a global coordinate system. The main influences on the accuracy of the camera orientations are the distance to the riverbanks, the size of the banks, and the amount of vegetation on them. Moreover, the quality of the camera orientation-based lidar point cloud also depends on the time synchronization of camera and lidar. The paper describes the data processing steps for the geometric lidar-camera integration and delivers a validation of the accuracy potential. For quality assessment of a point cloud acquired with the described method, a comparison with terrestrial laser scanning has been carried out.

Acute modification of hemodynamic forces in patients with severe aortic stenosis after transcatheter aortic valve replacement

Abstract Funding Acknowledgements Type of funding sources: None. Background Transcatheter-Aortic-Valve-Implantation (TAVI) is the established first-line treatment for patient with severe aortic stenosis not suitable for surgery. Echocardiographic evaluation of hemodynamic forces (HDFs) is a growing field, holding the potential to early predict improvement in LV function. Methods A prospective observational study was conducted. Transthoracic echocardiography was performed before and after TAVI. HDFs were analyzed along with traditional left ventricular (LV) function parameters. Results 25 consecutive patients undergoing TAVI were enrolled: mean age 83±5 years, 74.5% male, mean LV Ejection Fraction (LVEF) at baseline 57±8%. Post-TAVI echocardiographic evaluation was performed 2.4±1.06 days after the procedure. HDFs amplitude parameters improved significantly after the procedure: LV Longitudinal Forces (LF) apex-base [mean difference (MD) 1.79%; 95%CI 1.07–2.5; P-value <0.001]; LV systolic LF apex-base (MD 2.6%; 95%CI 1.57–3.7; P-value <0.001); LV impulse (LVim) apex-base (MD 2.9%; 95%CI 1.48–4.3; P-value <0.001). Similarly, HDFs orientation parameters improved: LVLF angle (MD 1.5°; 95%CI 0.07–2.9; P-value 0.041); LVim angle (MD 2.16°; 95%CI 0.76–3.56; P-value 0.004). Conversely, Global Longitudinal Strain and LVEF did not show any significant difference before and after the procedure. Conclusion: Echocardiographic analysis of HDFs could help differentiate patients with LV function recovery after TAVI from patients with persistent hemodynamic dysfunction.

Influence of On-Site Camera Calibration with Sub-Block of Images on the Accuracy of Spatial Data Obtained by PPK-Based UAS Photogrammetry

Unmanned Aerial Systems (UAS) Photogrammetry has become widely used for spatial data acquisition. Nowadays, RTK (Real Time Kinematic) and PPK (Post Processed Kinematic) are the main correction methods for accurate positioning used for direct measurements of camera station coordinates in UAS imagery. Thus, 3D camera coordinates are commonly used as additional observations in Bundle Block Adjustment to perform Global Navigation Satellite System-Assisted Aerial Triangulation (GNSS-AAT). This process requires accurate Interior Orientation Parameters to ensure the quality of photogrammetric intersection. Therefore, this study investigates the influence of on-site camera calibration with a sub-block of images on the accuracy of spatial data obtained by PPK-based UAS Photogrammetry. For this purpose, experiments of on-the-job camera self-calibration in the Metashape software with the SfM approach were performed. Afterward, experiments of GNSS-Assisted Aerial Triangulation with on-site calibration in the Erdas Imagine software were performed. The outcomes show that only the experiment of GNSS-AAT with three Ground Control Points yielded horizontal and vertical accuracies close to nominal precisions of the camera station positions by GNSS-PPK measurements adopted in this study, showing horizontal RMSE (Root-Mean Square Error) of 0.222 m and vertical RMSE of 0.154 m. Furthermore, the on-site camera calibration with a sub-block of images significantly improved the vertical accuracy of the spatial information extraction.

Effect of Freeze–Thaw Cycling on the Screw Direct Withdrawal Resistance of Beech, Ozigo, and Okoume Plywoods

Wood has been used in the construction, furniture, and automotive industries since ancient times. In areas where wood material is used, it is combined with various fasteners. The durability of the products produced using wooden materials depends on the performance of the fasteners. Since wood is a hygroscopic and biodegradable material, various changes occur in its structure when exposed to external weather conditions. Wood materials used especially in the field of construction and urban furniture are exposed to effects such as extreme temperatures, freezing, moisture, or drying depending on the seasons. In this study, the effect of the freeze–thaw cycling (FTC) process on screw direct withdrawal resistance (SDWR) of plywood produced from beech, ozigo, and okoume species was investigated. In this context, the effects of screwing time (before or after), screw orientation (face or edge), the number of cycles (0 to 7) in the FTC process, and plywood type parameters on SDWR were investigated. As a result of the tests, when the mean SDWR values were examined according to the plywood type, the highest values were obtained in beech, ozigo, and okoume plywood, respectively. Considering the screwing time parameter, it was determined that there was no statistically significant difference between the mean SDWR values in other plywood types except beech plywood (p < 0.05). When the screw orientation parameter was examined, screwing in the face direction gave better results than screwing in the edge direction in all plywood types. There was a decrease in the mean SDWR values that was inversely proportional to the increase in the number of cycles in FTC-treated plywood.

Визначення сили впливу іонного променя на об’єкт космічного сміття за контурами його зображень з використанням глибокого навчання

The goal of this article is to develop an effective image preprocessing algorithm and a neural network model for determining the force to be transmitted to a space debris object (SDO) for its non-contact deorbit. In the development and study of the algorithm, use was made of methods of theoretical mechanics, machine learning, computer vision, and computer simulation. The force is determined using a photo taken by an onboard camera. To increase the efficiency of the neural network, an algorithm was developed for feature recognition by the SDO edge in the photo. The algorithm, on the one hand, selects a sufficient number of features to describe the properties of the figure and, on the other hand, significantly reduces the amount of data at the neural network input. A dataset with the features and corresponding reference force values was created for model training. A neural network model was developed to determine the force to be exerted on a SDO from the SDO features. The model was tested using a set of eighteen calculated cases to determine the effectiveness, accuracy, and speed of the algorithm. The proposed algorithm was compared with two existing ones: the method of central projections onto an auxiliary plane and the multilayered neural network model that calculates the force using the SDO orientation parameters. The comparison was performed using the root mean square error, the maximum absolute error, and the maximum relative error. The test results are presented as tables and graphs. The proposed approach makes it possible to develop a system of SDO non-contact removal that does not need to determine the exact relative position and orientation with respect to the active spacecraft. Instead, the algorithm uses camera-taken photos, from which the features necessary for calculation are extracted. This makes it possible to reduce the requirements for its computing elements, to abandon sensors for determining the relative position and orientation, and to reduce the cost of the system.

Modelling and Estimation of Interior Orientation of Non-Metric Cameras using Artificial Intelligence

With the advancement of low-cost digital cameras and their widespread, especially in smartphones, these cameras are not designed for photogrammetry applications. The main aim of this study is to model and estimate the interior orientation parameters (IOPs) for images captured by volunteer-run cameras using artificial intelligence. These cameras were unavailable to perform traditional calibration processes or use images from unknown sources for image measuring. Estimating IOPs using random values within the range determined by testing the selected sample's consistency. Optimization was performed by Utilizing the Simulated Annealing algorithm based on stereo calibration to obtain the best possible values of these parameters that produce the minimum RMS-reprojection error attained. By The variance between the parameters from the pre-calibration process and estimated by an artificial intelligence system, The coefficient of determination in the IOPs (focal length R2 = 0.717 to 0.812, principal point (X, Y) R2 = (0.674 to 0.869, 0.504 to 0.613), Both radial and tangential coefficients, R2 was close to zero). Therefore, the estimations of radial distortions k1, k2, and tangential distortions p1 and p2 are invalid. A reasonably strong relationship between principal distance and principal point with low lens distortion parameters due to the significant relative differences between the distortion parameters, sufficient strength of the relationship between calculating parameters, and estimating according to accuracy tolerance in photogrammetry applications.

Understanding microtopography changes in agricultural landscapes through precision assessments of digital surface models by the UAV-RTK-PPK method without ground control points

Soil erosion on agricultural land causes severe environmental problems and damages crop plants. Structure-from-motion with multiview stereo (SfM-MVS) together with data obtained via unmanned aerial vehicles (UAVs) helps understand spatiotemporal changes in the ground surface if there is enough precise data. However, installing ground control points in the field is labor intensive and disturbs field conditions. Here, images georeferenced using the Real-Time Kinematic (RTK) method were further improved using Post-Processing Kinematic (PPK) analysis. This study aims to verify whether the UAV-RTK-PPK method can create precise digital surface models to evaluate topographic changes owing to erosion without ground control points. The effects of the camera's interior orientation parameters settings and the addition of oblique images to nadiral images on the precision were also examined to reduce the positional error by the doming and bowling phenomena. Field observations were conducted in a 150 m × 25 m potato field with 156 poles to consider the three-dimensional object shapes in the verification. The doming or bowling phenomena occurred using only the nadiral images. The precision of the digital surface model was approximately 0.40 and 0.20 m (in the Z-direction) using the estimated and fixed camera's interior orientation parameters, respectively. In contrast, the digital surface models produced by adding oblique images to the nadiral images had a precision of approximately 0.04 m, regardless of the camera's interior orientation parameters. Thus, a high-precision digital surface model was obtained from images acquired using the UAV-RTK-PPK and SfM-MVS methods without ground control points. The digital surface model positional precision was improved by adding oblique images to the nadiral images without having to consider the camera's interior orientation parameters. Topographic changes >0.05 m after erosion by heavy rainfall were evaluated without ground control points using the UAV-RTK-PPK method with oblique and nadiral images. Therefore, our method can monitor the erosion of agricultural fields that may cause crop damage, such as the greening of potatoes.

Percolation Threshold of Clustered, Oriented and Polydisperse Sticks in a Plane

AbstractMonte‐Carlo methods are used to study the influence of stick polydispersity, orientation and clustering on the percolation of sticks in the plane. The results show that for polydisperse stick lengths, the percolation threshold exhibits a linear dependence on the reciprocal of the length‐weighted mean stick length. Reinterpretation of data from the literature confirms this dependence and shows it to persist for oriented networks. Also, the number of intersections per stick at percolation, is independent of orientation for percolation perpendicular to the direction of preferential orientation; in the direction of preferential orientation, it is a linear function of an orientation parameter. For networks of sticks clustered according to a compound Poisson process, a cluster intensity, Ψ is introduced; when this is less than the percolation threshold of a random network of sticks, the percolation threshold increases linearly with cluster intensity and is independent of cluster size. Above this, non‐linear size‐dependent relationships are observed.

Medium- and Long-Term Prediction of Polar Motion Using Weighted Least Squares Extrapolation and Vector Autoregressive Modeling

ABSTRACT This article presents the application of weighted least squares (WLS) extrapolation and vector autoregressive (VAR) modeling in polar motion prediction. A piecewise weighting function is developed for the least squares (LS) adjustment in consideration of the effect of intervals between observation and prediction epochs on WLS extrapolation. Furthermore, the VAR technique is used to simultaneously model and predict the residuals of x p, y p pole coordinates for WLS misfit. The simultaneous predictions of x p, y p pole coordinates are subsequently computed by the combination of WLS extrapolation of harmonic models for the linear trend, Chandler and annual wobbles, and VAR stochastic prediction of the residuals (WLS+VAR). The 365-day-ahead x p, y p predictions are compared with those generated by LS extrapolation+univariate AR prediction and LS extrapolation+VAR modeling. It is shown that the x p, y p predictions based on WLS+VAR taking into consideration both the interval effect and correlation between x p and y p outperform those generated by two others. The accuracies of the x p predictions are 13.97 mas, 18.47 mas, and 20.52 mas, respectively for the 150-, 270-, and 365-day horizon in terms of the mean absolute error statistics, 36%, 24.8%, and 33.5% higher than LS+AR, respectively. For the y p predictions, the 150-, 270-, and 365-day accuracies are 15.41 mas, 21.17 mas, and 21.82 mas respectively, 27.4%, 11.9%, and 21.8% higher than LS+AR respectively. Moreover, the absolute differences of the WLS+VAR predictions and observations are smaller than the differences from LS+VAR and LS+AR, which is practically important to practical and scientific users, although the improvement in accuracies is no more than 10% relative to LS+VAR. The further comparison with the predictions submitted to the 1st Earth Orientation Parameters Prediction Comparison Campaign (1st EOP PCC) shows that while the accuracy of the predictions within 30 days is comparable with that by the most accurate prediction techniques including neural networks and LS+AR participating in the campaign for x p, y p pole coordinates, the accuracy of the predictions up to 365 days into the future are better than accuracies by the other techniques except best LS+AR used in the EOP PCC. It is therefore concluded that the medium- and long-term prediction accuracy of polar motion can be improved by modeling x p, y p pole coordinates together.

73‐4: The Value and Benefit of Multiscale Material Simulation for OLED R&D: Prediction and Validation of Triplet Emitter Orientation Yielding > 90% In‐plane Transition Dipole Orientation for Ir(ppy)3 Derivatives

In order to fulfill the demand for ever‐improving OLED panel properties, material design has to adapt quickly. We propose multiscale material simulations as a tool to elucidate structure‐property relations guiding us towards materials with desired properties. As an example, we present benchmarking and application of a simulation workflow for triplet emitter optical orientation validated by experiment. Using this we were able to improve the isotropic optical orientation of the phosphorescent triplet emitter Ir(ppy)3 to unprecedented orientation parameters o<0.1. This means that >90% of the emitter transition dipoles can be in the substrate plane, allowing for better outcoupling and thus higher external quantum efficiency. Such a high degree of orientation realized by help of material simulation is a remarkable result for octahedral (non‐planar) complexes based on Ir(ppy)3.

DESIGN AND IMPLEMENTATION OF STEREO VISUAL ODOMETRY SYSTEM BASED ON ROP ADJUSTMENT

Abstract. Stereo Visual Odometry (SVO) is a technique used to estimate the continuous position and orientation of a moving platform using a dual-camera system that captures stereo image pairs. To obtain accurate results, A SVO system must be calibrated before use. System calibration is necessary to determine the intrinsic camera parameters (ICPs) and the relative orientation parameters (ROPs) between the cameras at real scale. Compared to monocular visual odometry, a calibrated SVO system can recover the real scale of the translation vector without additional sensors.The proposed method in this study utilizes ROP adjustment for SVO. Instead of conventional bundle adjustment, this method adopts all sets of ROPs as measurements in the designed network adjustment model. Specifically, there are six sets of ROPs among time-adjacent stereo image pairs.A SVO system was designed to implement the proposed SVO method. Two experiments were conducted in outdoor and indoor test fields to evaluate the performance. Several ground check points were set up for distance and position verification. The drift ratio was also evaluated. The results demonstrate that the designed SVO system has great feasibility and accuracy for navigation applications.

Substantiation of Drilling Parameters for Undermined Drainage Boreholes for Increasing Methane Production from Unconventional Coal-Gas Collectors

Decarbonization of the mining industry on the basis of closing the energy generation, on the basis of cogeneration of coal mine methane, and on the internal consumption of the mine is a promising direction in ensuring sustainable development. Known problems of deep underground mining do not allow for realizing the potential of man-made gas reservoirs due to the deterioration of the conditions of development of reserves of georesources. The aim of the work was to improve recommendations for the substantiation of drilling parameters for undermined drainage boreholes for increasing methane production from unconventional coal-gas collectors. The authors’ approach innovation lies in the possibility of using the established patterns of better natural stability of undermined boreholes to optimize them as spatial orientation parameters in an existing drilling passport for the improvement of methane extraction productivity. For this purpose, smoothing (LOESS) of the experimental data of two similar types of wells was used; then deterministic interpolation methods in combination with a three-dimensional representation of the response function in “gnuplot” were used. As a result, it was found that the increase in the inclination angle from 40° to 60° leads to a significant transformation of the model of the studied process, accompanied by a decline in the dynamics of methane emission and a decrease in the distance of the productive work zone of this type of well from 13 to 5 m before the roof landing, which then is replaced by a sharp increase in the productive work zone up to 35 m ahead of the longwall face. This allows under specific conditions for recommending increasing the productivity of methane capex from technogenic disturbed coal-gas reservoir replacement of wells with a smaller angle of rise to the transition to a more frequent grid of clusters from wells #4.

ITRF2020: an augmented reference frame refining the modeling of nonlinear station motions

To better describe the shape of the constantly deforming Earth’s surface, the ITRF2020 is provided as an augmented terrestrial reference frame that precisely models nonlinear station motions for both seasonal (annual and semi-annual) signals present in the station position time series and Post-Seismic Deformation (PSD) for sites impacted by major earthquakes. Reprocessed solutions in the form of station position time series and Earth Orientation Parameters using the full observation history provided by the four space geodetic techniques (DORIS, GNSS, SLR and VLBI) were used as input data, spanning 28, 27, 38 and 41 years of observations, respectively. The ITRF2020 long-term origin follows linearly with time the Earth’s Center of Mass (CM) as sensed by SLR, based on observations collected over the time span 1993.0–2021.0. We evaluate the accuracy of the ITRF2020 long-term origin position and time evolution by comparison to previous solutions, namely ITRF2014, ITRF2008 and ITRF2005, to be at the level of or better than 5 mm and 0.5 mm/yr, respectively. The ITRF2020 long-term scale is defined by a rigorous weighted average of selected VLBI sessions up to 2013.75 and SLR weekly solutions covering the 1997.75–2021.0 time span. For the first time of the ITRF history, the scale agreement between SLR and VLBI long-term solutions is at the level of 0.15 ppb (1 mm at the equator) at epoch 2015.0, with no drift. To accommodate most of ITRF2020 users, the seasonal station coordinate variations are provided in the CM as well as in the Center of Figure frames, together with a seasonal geocenter motion model. While the PSD parametric models were determined by fitting GNSS data only, they also fit the station position time series of the three other techniques that are colocated with GNSS, demonstrating their high performance in describing site post-seismic trajectories.

Ultra-short-term prediction of LOD using LSTM neural networks

Earth orientation parameters (EOPs) are essential in geodesy, linking the terrestrial and celestial reference frames. Due to the time needed for data processing and combining different space geodetic techniques, EOPs of the highest quality suffer latencies from several days to several weeks. However, real-time EOPs are needed for multiple geodetic and geophysical applications. Predictions of EOPs in the ultra-short term can overcome the latency of EOP products to a certain extent. Traditionally, predictions are performed using statistical methods. With the rapid expansion of computing capacity and data volume, the application of deep learning in geodesy has become increasingly promising in recent years. In particular, the Long Short-Term Memory (LSTM) neural networks, one of the most popular Recurrent Neural Network varieties, are promising for geodetic time series prediction. In this study, we investigate the potential of using LSTM to predict daily length of day (LOD) variations up to ten days in advance, accounting for the contribution of effective angular momentum (EAM). The data are first preprocessed to obtain residuals by combining physical and statistical models. Then, we employ LSTM networks to predict the LOD residuals using both LOD and EAM residuals as input features. Our methods outperform all other state-of-the-art methods in the first eight days with an improvement of up to 43% under the first EOP Prediction Comparison Campaign conditions. In addition, we assess the performance of LOD predictions using more extended time series to consider the improvements of EOP products over the last decade. The results show that extending data volume significantly increases the performance of the methods.

VLBI Astrometry of radio stars to link radio and optical celestial reference frames. I. HD 199178 & AR Lacertae

ABSTRACT To accurately link the radio and optical Celestial Reference Frames (CRFs) at optical bright end, i.e. with GaiaG-band magnitude $\lesssim$13, increasing number and improving sky distribution of radio stars with accurate astrometric parameters from both Very Long Baseline Interferometry (VLBI) and Gaia measurements are mandatory. We selected two radio stars HD 199178 and AR Lacertae as the target for a pilot program for the frame link, using the Very Long Baseline Array at 15 GHz at six epochs spanning about 1 yr, to measure their astrometric parameters. The measured parallax of HD 199178 is 8.949 ± 0.059 mas and the proper motion is μαcos δ = 26.393 ± 0.093 and μδ = −0.950 ± 0.083 mas yr−1, while the parallax of AR Lac is 23.459 ± 0.094 mas and the proper motion is μαcos δ = −51.906 ± 0.138 and μδ = 46.732 ± 0.131 mas yr−1. Our VLBI measured astrometric parameters have accuracies about 4–5 times better than the corresponding historic VLBI measurements and comparable accuracies with those from Gaia, validating the feasibility of frame link using radio stars. With the updated astrometric parameters for these two stars, there is a ∼25 per cent reduction of the uncertainties on the Y-axis for both orientation and spin parameters.

The concept of aerial photography using a two-element active optoelectronic complex

The article proposes the concept of obtaining images on the basis of which it is possible to create three-dimensional models of objects. In particular, images contain the data necessary to recreate the three-dimensional form of an object. Such data include: the length, width of the modeled object as well as the lengthening of the shadow cast on the base surface. In accordance with the proposed concept, an important condition for obtaining images suitable for interpretation is the use of spatially separated equipment generating and recording optical radiation. The orientation parameters of the illumination source and the camera are selected, taking into account the requirements for the photogrammetric quality of images. A characteristic of geometric distortions that occur when changing the shooting mode from plan to perspective is presented, which demonstrates the change in the aspect ratio of the image depending on the angle of the camera. A characteristic of the shadow elongation depending on the spatial position of the optical radiation source is presented, which shows the influence of the orientation parameters of the optical illumination means on the length of the shadow cast on the base surface. On the basis of these characteristics, the choice of parameters of relative orientation in space of the source of optical illumination and the equipment that detects optical radiation is substantiated. Predicting the value of geometric distortions of images at the stage of choosing the parameters of relative orientation of the equipment of a two-element active optoelectronic complex allows you to save the photogrammetric quality of images and, as a result, measure the length and width of an object. Predicting the magnitude of the shadow elongation under conditions of artificial optical illumination provides the possibility of transferring features in the image for calculating the applicate and, as a result, recreating the three-dimensional shape of the object. The proposed concept of image registration finds application in topographic and geodetic and engineering work in conditions of insufficient natural light. For example, the use of a two-element active optical-electronic complex makes it possible to obtain three-dimensional photo plans of the terrain of geographic regions with a short daylight hours.

Changes in the microstructure of the human aortic adventitia under biaxial loading investigated by multi-photon microscopy.

Among the three layers of the aortic wall, the media is primarily responsible for its mechanical properties, but the adventitia prevents the aorta from overstretching and rupturing. The role of the adventitia is therefore crucial with regard to aortic wall failure, and understanding the load-induced changes in tissue microstructure is of high importance. Specifically, the focus of this study is on the changes in collagen and elastin microstructure in response to macroscopic equibiaxial loading applied to the aortic adventitia. To observe these changes, multi-photon microscopy imaging and biaxial extension tests were performed simultaneously. In particular, microscopy images were recorded at 0.02 stretch intervals. The microstructural changes of collagen fiber bundles and elastin fibers were quantified with the parameters of orientation, dispersion, diameter, and waviness. The results showed that the adventitial collagen was divided from one into two fiber families under equibiaxial loading conditions. The almost diagonal orientation of the adventitial collagen fiber bundles remained unchanged, but the dispersion was substantially reduced. No clear orientation of the adventitial elastin fibers was observed at any stretch level. The waviness of the adventitial collagen fiber bundles decreased under stretch, but the adventitial elastin fibers showed no change. These original findings highlight differences between the medial and adventitial layers and provide insight into the stretching process of the aortic wall. STATEMENT OF SIGNIFICANCE: To provide accurate and reliable material models, it is essential to understand the mechanical behavior of the material and its microstructure. Such understanding can be enhanced with tracking of the microstructural changes caused by mechanical loading of the tissue. This study provides therefore a unique dataset of structural parameters of the human aortic adventitia obtained under equibiaxial loading. The structural parameters describe orientation, dispersion, diameter, and waviness of collagen fiber bundles and elastin fibers. Eventually, the microstructural changes in the human aortic adventitia are compared with the microstructural changes in the human aortic media from a previous study. This comparison reveals the cutting-edge findings on the differences in the response to the loading between these two human aortic layers.

Dynamical evolution of basaltic asteroids outside the Vesta family in the inner main belt

Context. Basaltic V-type asteroids are leftovers from the formation and evolution of differentiated planetesimals. They are thought to originate from mantles and crusts of multiple different parent bodies. Identifying the links between individual V-type asteroids and multiple planetesimals is challenging, especially in the inner part of the main asteroid belt, where the majority of V-type asteroids are expected to have originated from a single planetesimal, namely, (4) Vesta. Aims. In this work, we aim to trace the origin of a number of individual V-type asteroids from the inner part of the main asteroid belt. The main goal is to identify asteroids that may not be traced back to (4) Vesta and may therefore originate from other differentiated planetesimals. Methods. We performed a 2 Gyr backward numerical integration of the orbits of the selected V-type asteroids. For each asteroid, we used 1001 clones to map the effect of orbital uncertainties. In the integration, we use information on physical properties of the considered V-type asteroids such as pole orientation, rotational period, and thermal parameters. Results. The majority of the studied objects can be traced back to the Vesta family within 2 Gyr of integration. The number of objects of the low-inclination V-types did not reach the boundary of the Vesta family during the integration time. Two asteroids, namely, (3307) Athabasca and (17028) 1999 FJ5, do not show a dynamic link to (4) Vesta. Increasing the integration time for these objects leads to further separation from (4) Vesta. Conclusions. The majority of V-types in the inner main belt outside the Vesta family are clearly Vesta fugitives. Two objects, namely, (3307) Athabasca and (17028) 1999 FJ5, show no clear dynamical link to (4) Vesta. Together with (809) Lundia (from our previous work), these objects could represent the parent bodies of anomalous HED meteorites such as the Banbura Rockhole. Furthermore, some objects of the low-inclination population cannot be traced back to (4) Vesta within the 2 Gyr integration.

Giving Historical Photographs a New Perspective: Introducing Camera Orientation Parameters as New Metadata in a Large-Scale 4D Application

The ongoing digitization of historical photographs in archives allows investigating the quality, quantity, and distribution of these images. However, the exact interior and exterior camera orientations of these photographs are usually lost during the digitization process. The proposed method uses content-based image retrieval (CBIR) to filter exterior images of single buildings in combination with metadata information. The retrieved photographs are automatically processed in an adapted structure-from-motion (SfM) pipeline to determine the camera parameters. In an interactive georeferencing process, the calculated camera positions are transferred into a global coordinate system. As all image and camera data are efficiently stored in the proposed 4D database, they can be conveniently accessed afterward to georeference newly digitized images by using photogrammetric triangulation and spatial resection. The results show that the CBIR and the subsequent SfM are robust methods for various kinds of buildings and different quantity of data. The absolute accuracy of the camera positions after georeferencing lies in the range of a few meters likely introduced by the inaccurate LOD2 models used for transformation. The proposed photogrammetric method, the database structure, and the 4D visualization interface enable adding historical urban photographs and 3D models from other locations.