Shape Estimation Research Articles

Mathematical and Numerical Modeling of Repeated Floods from the Siret Basin, Romania, a Risk for Population, Environment, and Agriculture

In recent decades in Romania, no flood management plan has been implemented in natural riverbeds, although there are known areas that face repeated floods such as the Siret River basin. Practically every year, floods produce uncontrolled erosions and landslides in certain areas, followed by the deposition of sediments, usually on agricultural land, compromising crops indefinitely. This paper analyzes the natural transport capacity of the Siret River based on direct measurements and data recorded during the floods of 2005 and 2020. The mathematical model of the sediment transport is presented, starting with the upstream zone, from the confluence with its main tributaries: Bistrita, Trotus, and Cracau. The recorded flood hydrographs are used in this analysis to model the sediment transport for variable flow rates. The upstream flood hydrograph, the steady downstream level, and the initial riverbed cross-sections represent the boundary conditions. The mathematical model is numerically tested for the risk zones by determining the modifications of the riverbed cross-sections. The variation in time of the liquid and solid phases allows the estimation of the longitudinal riverbed shape with the floodable surfaces. To mitigate the effects of floods—and to protect the population, agricultural lands, and environment—some solutions are finally proposed.

Making military conscription count? Converting competencies between the civilian and military spheres in a neoliberal Estonia

While past decades Western societies have been shifting from mandatory military service toward all-volunteer forces, a number of them have retained conscription. A growing emphasis on individualization and neoliberalist ideas results in a tension for youths between fulfilling a duty and the need for constant self-development. We argue that a central mechanism for addressing this challenge is convertibility, the ability to use competencies gained in one sphere in another, and thus increasing the individual value of conscription for recruits. By linking convertibility to societal expectations, we demonstrate how societies shape ideas of what is convertible and why, and by relating convertibility to agency and motivation, we extend the concept to the individual level. We argue that as material rewards are limited and conscripts cannot rely on occupational motivations, convertibility has a potential to increase the value of conscription for recruits and enable them to combine institutional motivators with utilitarian motives.

QUANTIFYING SULFUR DISPERSION USING POPULATION SURVIVAL ANALYSIS OF TENSILE STRENGTH

ABSTRACT High-performance rubber compounds require good dispersion of polymers, fillers, and other additives. However, fine powdery additives such as zinc oxide and insoluble sulfur (IS) are characteristically difficult to disperse, and poor dispersion may lead to large crosslink and modulus gradients in the final vulcanizate. IS dispersion can be assessed directly or indirectly, yet many techniques suffer from a lack of sensitivity and accuracy or are cost prohibitive. Herein, we describe the application of a two-parameter Weibull distribution and population survival analysis of cured rubber tensile strength as a simple technique to evaluate IS dispersion. We use statistical tools to determine the optimum number of sample replicates required to differentiate the quality of dispersion in rubber articles through the Weibull scale and shape estimates (α and β, respectively). We then demonstrate how mixing cycle time and intensity affect the dispersion of two IS grades and show that judicious choice of IS can lead to reduced cycle mix times, productivity improvements, and energy cost savings.

Practical theology in Arab evangelical perspective: considering a particular practice of theological reflection

ABSTRACT In this article, I describe and analyse the nature of the practice of theological reflection (TR) from a small-scale qualitative case study among Arabic-speaking evangelical theology students from Muslim-majority, Arab socio-religious contexts studying at the Arab Baptist Theological Seminary. As a central meaning-making process for practical theology, practices of TR can offer a window into how cultural orientations and socio-religious values shape practical theology within particular contexts. To broaden our understanding, then, of how people in Majority world contexts construct practical theology requires giving attention to key emphases in particular, local expressions of tying theological thought to practice. Using reflexive thematic analysis on data from semi-structured interviews, I generated the notion of the practice of TR engendering ‘divinely ordered connectivity’. Three additional themes constituted this notion: (1) seeing and doing with God, (2) finding the unity of all things in God, and (3) building respectful community, which together lead to ‘regulating society’ towards a divinely authorised order. The particularities of this Arab evangelical practice of TR contribute to the limited scholarship on the nature of theological discourse among Arab evangelicals’, and to understanding how socio-religious and cultural orientations shape ideas about what practical theology is in the first place.

Sampling Information for Generalized Rayleigh Distribution with Application to Parameter Estimation

In the current paper, we considered the Fisher information matrix from generalized Rayleigh distribution (GR) distribution in moving extremes ranked set sampling (MERSS). The numerical results show that the ranked set sample carry more information about $$\lambda$$ and $$\alpha$$ than a simple random sample of equivalent size. In order to give more insight into the performance of MERSS with respect to (w.r.t.) simple random sampling (SRS), a modified unbiased estimator and a modified best linear unbiased estimator (BLUE) of scale and shape $$\lambda$$ and $$\alpha$$ from GR distribution in SRS and MERSS are studied. The numerical results show that the modified unbiased estimator and the modified BLUE of $$\lambda$$ and $$\alpha$$ in MERSS are significantly more efficient than the ones in SRS.

Compliant Hall-Effect Sensor Array for Passive Magnetic Instrument Tracking

Minimally invasive surgical procedures can strongly benefit from nonvisual magnetic instrument tracking. Most state-of-the-art sensor systems for magnetic tracking, however, are rigid and bulky or depend on multimodal sensor technologies. In this work, we investigate a compliant, wearable 2-D Hall-effect sensor array with self-sensing ability and a minimal spatial footprint. Our tracking algorithm is based on a permanent magnet model and a least squares optimization. For evaluation of self-sensing, we tested the sensor array attached to 3D-printed circular frames with known geometries. Tracking was experimentally evaluated moving the target magnet on a preset path utilizing a robotic actuator. Results show that stronger bending radii lead to larger errors of the shape estimation with an overall absolute error of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$8.33^{\circ }$</tex-math></inline-formula> . However, larger radii eventually lead to a decreased Euclidean distance error in the actual tracking procedure between 1.31 mm and 3.38 mm. Thus, the additional efforts due to shape estimation appear fair, since the overall performance of the tracking improves and the spatial footprint can be minimized with our approach. Future work will address performance improvement and implementation of a machine learning approach, aiming for real-time capability.

Video2mesh: 3D human pose and shape recovery by a temporal convolutional transformer network

AbstractFrom a 2D video of a person in action, human mesh recovery aims to infer the 3D human pose and shape frame by frame. Despite progress on video‐based human pose and shape estimation, it is still challenging to guarantee high accuracy and smoothness simultaneously. To tackle this problem, we propose a Video2mesh, a temporal convolutional transformer (TConvTransformer) based temporal network which is able to recover accurate and smooth human mesh from 2D video. The temporal convolution block achieves the sequence‐level smoothness by aggregating image features from adjacent frames. The subsequent multi‐attention transformer improves the accuracy due to its multi‐subspace for better middle‐frame feature representation. Meanwhile, we add a TConvTransformer discriminator which is trained together with our 3D human mesh temporal encoder. This TConvTransformer discriminator further improves the accuracy and smoothness by restricting the pose and shape in a more reliable space based on the AMASS dataset. We conduct extensive experiments on three standard benchmark datasets and show that our proposed Video2mesh outperforms other state‐of‐the‐art methods in both accuracy and smoothness.

Recognizing the Shape and Size of Tundra Lakes in Synthetic Aperture Radar (SAR) Images Using Deep Learning Segmentation

Permafrost tundra contains more than twice as much carbon as is currently in the atmosphere, and it is warming six times as fast as the global mean. Tundra lakes dynamics is a robust indicator of global climate processes, and is still not well understood. Satellite data, particularly, from synthetic aperture radar (SAR) is a suitable tool for tundra lakes recognition and monitoring of their changes. However, manual analysis of lake boundaries can be slow and inefficient; therefore, reliable automated algorithms are required. To address this issue, we propose a two-stage approach, comprising instance deep-learning-based segmentation by U-Net, followed by semantic segmentation based on a watershed algorithm for separating touching and overlapping lakes. Implementation of this concept is essential for accurate sizes and shapes estimation of an individual lake. Here, we evaluated the performance of the proposed approach on lakes, manually extracted from tens of C-band SAR images from Sentinel-1, which were collected in the Yamal Peninsula and Alaska areas in the summer months of 2015–2022. An accuracy of 0.73, in terms of the Jaccard similarity index, was achieved. The lake’s perimeter, area and fractal sizes were estimated, based on the algorithm framework output from hundreds of SAR images. It was recognized as lognormal distributed. The evaluation of the results indicated the efficiency of the proposed approach for accurate automatic estimation of tundra lake shapes and sizes, and its potential to be used for further studies on tundra lake dynamics, in the context of global climate change, aimed at revealing new factors that could cause the planet to warm or cool.

Inhomogeneous Superconductivity Onset in FeSe Studied by Transport Properties

Heterogeneous superconductivity onset is a common phenomenon in high-Tc superconductors of both the cuprate and iron-based families. It is manifested by a fairly wide transition from the metallic to zero-resistance states. Usually, in these strongly anisotropic materials, superconductivity (SC) first appears as isolated domains. This leads to anisotropic excess conductivity above Tc, and the transport measurements provide valuable information about the SC domain structure deep within the sample. In bulk samples, this anisotropic SC onset gives an approximate average shape of SC grains, while in thin samples, it also indicates the average size of SC grains. In this work, both interlayer and intralayer resistivity were measured as a function of temperature in FeSe samples of various thicknesses. To measure the interlayer resistivity, FeSe mesa structures oriented across the layers were fabricated using FIB. As the sample thickness decreases, a significant increase in superconducting transition temperature Tc is observed: Tc raises from 8 K in bulk material to 12 K in microbridges of thickness ∼40 nm. We applied analytical and numerical calculations to analyze these and earlier data and find the aspect ratio and size of the SC domains in FeSe consistent with our resistivity and diamagnetic response measurements. We propose a simple and fairly accurate method for estimating the aspect ratio of SC domains from Tc anisotropy in samples of various small thicknesses. The relationship between nematic and superconducting domains in FeSe is discussed. We also generalize the analytical formulas for conductivity in heterogeneous anisotropic superconductors to the case of elongated SC domains of two perpendicular orientations with equal volume fractions, corresponding to the nematic domain structure in various Fe-based superconductors.

Long Life Power Factor Corrected LED Driver with Capacitive Energy Mechanism for Street Light Applications

Conventional switch-mode LED drivers have problems such as poor performance in harmonic distortion, flickering, power factor correction, stresses on the switches, high switching losses, large size, and high cost. To resolve these problems, we propose a long-life LED driver with the ability of power factor correction. The proposed system is based on the integration of a half-bridge LLC resonant converter and two boundary-conducted boost converters. Both boost converters share a common inductor designed in such a way that both boost converters work in boundary conduction mode to attain the natural power factor correction. Half-bridge LLC resonant converter has soft switching characteristics, which assure the zero-voltage switching (ZVS) of primary-side switches and zero-current switching (ZCS) of diodes on the secondary side. This significantly reduces switching losses and improves the overall efficiency of the system. Voltage divider capacitors are used on the input side, which minimizes the bus voltages. The proposed system has two identical secondary windings with a coupled inductor to eliminate the mismatch between them, which powers two independent LED strings. The simulation of a 100-watt 240 V AC converter yields the approximate sinusoidal shape of the input current. It shows that the switches on the primary side are operated in ZVS and the diodes in ZCS. At 240-volt AC input, the efficiency is 87.4%, the total harmonics distortion (THD) is 10.98%, and the power factor (PF) is 0.98.

Voices of Silence: Experiences in Disseminating Scholarship as a Global South Researcher

Issue: There is an unspoken requirement that medical education researchers living in the Global South must disseminate their work using dominant frames constructed by individuals living in the Global North. As such, the published literature in our field is dominated by researchers whose work primarily benefits the Western world, casting the rest of what is published as localized and unhelpful knowledge. In this article, we use Audre Lorde’s conception of the Master’s house as a metaphor to narrate the experiences of two South African medical education researchers trying to disseminate their work into North American venues. In addition to narrating these stories, we describe the personal and professional consequences they experienced as a result of their efforts. Evidence: For researchers working outside of the Global North, entering the Master’s formidable house is daunting, and there is no clear pathway in. These narratives illustrate how reviewers and editorial staff act as gatekeepers, continuously shaping ideas about what it means to do acceptable research, and who is allowed to disseminate it within the field. These narratives also show that those who have been rejected by these gatekeepers are often conflicted about their position within the larger field of medical education. Implications: To begin to address this issue, we have made several suggestions for the research community to consider. First, medical education research journals need to create spaces for researchers publishing from the Global South. One suggestion is for journals to create a submission type that is dedicated to researchers working outside of North America. Second, journals should also include more Global South editors and reviewers to help with knowledge translation when articles are submitted from outside North America. If our collective goal is to improve the training of physicians and the health outcomes of humanity, then we need to renovate the Master’s house and begin to break down the barriers that separate us from truly building together.

Research Progress of Elastomer Materials and Application of Elastomers in Drilling Fluid.

An elastomer is a material that undergoes large deformation under force and quickly recovers its approximate initial shape and size after withdrawing the external force. Furthermore, an elastomer can heal itself and increase volume when in contact with certain liquids. They have been widely used as sealing elements and packers in different oil drilling and development operations. With the development of drilling fluids, elastomer materials have also been gradually used as drilling fluid additives in drilling engineering practices. According to the material type classification, elastomer materials can be divided into polyurethane elastomer, epoxy elastomer, nanocomposite elastomer, rubber elastomer, etc. According to the function classification, elastomers can be divided into self-healing elastomers, expansion elastomers, etc. This paper systematically introduces the research progress of elastomer materials based on material type classification and functional classification. Combined with the requirements for drilling fluid additives in drilling fluid application practice, the application prospects of elastomer materials in drilling fluid plugging, fluid loss reduction, and lubrication are discussed. Oil-absorbing expansion and water-absorbing expansion elastomer materials, such as polyurethane, can be used as lost circulation materials, and enter the downhole to absorb water or absorb oil to expand, forming an overall high-strength elastomer to plug the leakage channel. When graphene/nano-composite material is used as a fluid loss additive, flexibility and elasticity facilitate the elastomer particles to enter the pores of the filter cake under the action of differential pressure, block a part of the larger pores, and thus, reduce the water loss, while it would not greatly change the rheology of drilling fluid. As a lubricating material, elastic graphite can form a protective film on the borehole wall, smooth the borehole wall, behaving like a scaly film, so that the sliding friction between the metal surface of the drill pipe and the casing becomes the sliding friction between the graphite flakes, thereby reducing the friction of the drilling fluid. Self-healing elastomers can be healed after being damaged by external forces, making drilling fluid technology more intelligent. The research and application of elastomer materials in the field of drilling fluid will promote the ability of drilling fluid to cope with complex formation changes, which is of great significance in the engineering development of oil and gas wells.

Learning configurations of wires for real-time shape estimation and manipulation planning

Robotic manipulation of a wire by its ends requires rapid reasoning of its shape in real-time. A recent development of an analytical model has shown that sensing of the force and torque on one end can be used to determine its shape. However, the model relies on assumptions that may not be met in real world wires and do not take into account gravity and non-linearity of the Force/Torque (F/T) sensor. Hence, the model cannot be applied to any wire with accurate shape estimation. In this paper, we explore the learning of a model to estimate the shape of a wire based solely on measurements of F/T states and without any visual perception. Visual perception is only used for off-line data collection. We propose to train a Supervised Autoencoder with convolutional layers that reconstructs the spatial shape of the wire while enforcing the latent space to resemble the space of F/T. Then, the encoder operates as a descriptor of the wire where F/T states can be mapped to its shape. On the other hand, the decoder of the model is the inverse problem where a desired goal shape can be mapped to the required F/T state. With the same collected data, we also learn the mapping from F/T states to grippers poses. Then, a motion planner can plan a path within the F/T space to a goal while avoiding obstacles. We validate the proposed data-based approach on Nitinol and standard electrical wires, and demonstrate the ability to accurately estimate their shapes.

Shadow-Robust Silhouette Reconstruction for Small-Body Applications

Small bodies’ exploration highlighted the need to develop new algorithms for deep space probes navigation. The estimation of the small-body shape is a crucial step for relative navigation, mission planning, and gravity investigation. This paper develops a shape from silhouette algorithm that takes as input a series of images to construct a polyhedral shape for small bodies of the solar system. First, the silhouette associated with the visible part of the body is extracted and modified to account for shadowing effects. Second, the shape is computed by intersecting the viewing cones, i.e., the cone whose apex is the camera center and whose vertices are the silhouette points. The algorithm output is a polyhedral shape whose reconstruction is robust to shadowing. The algorithm is validated by reconstructing the shape of Itokawa and Bennu from synthetic images simulated with Airbus Defence & Space’s rendering engine SurRender™. Moreover, the algorithm is tested on real images from Hayabusa’s approach. Results prove the capability to provide an efficient shape reconstruction for small-body applications.

3D reconstruction for maxillary anterior tooth crown based on shape and pose estimation networks.

The design of a maxillary anterior tooth crown is crucial to post-treatment aesthetic appearance. Currently, the design is performed manually or by semi-automatic methods, both of which are time-consuming. As such, automatic methods could improve efficiency, but existing automatic methods ignore the relationships among crowns and are primarily used for occlusal surface reconstruction. In this study, the authors propose a novel method for automatically reconstructing a three-dimensional model of the maxillary anterior tooth crown. A pose estimation network (PEN) and a shape estimation network (SEN) are developed for jointly estimating the crown point cloud. PEN is a regression network used for estimating the crown pose, and SEN is based on an encoder-decoder architecture and used for estimating the initial crown point cloud. First, SEN adopts a transformer encoder to calculate the shape relationship among crowns to ensure that the shape of the reconstructed point cloud is precise. Second, the initial point cloud is subjected to pose transformation according to the estimated pose. Finally, the iterative method is used to form the crown mesh model based on the point cloud. The proposed method is evaluated on a dataset with 600 cases. Both SEN and PEN are converged within 1000 epochs. The average deviation between the reconstructed point cloud and the ground truth of the point cloud is 0.22mm. The average deviation between the reconstructed crown mesh model and the ground truth of the crown model is 0.13mm. The results show that the proposed method can automatically and accurately reconstruct the three-dimensional model of the missing maxillary anterior tooth crown, which indicates the method has promising application prospects. Furthermore, the reconstruction time takes less than 11s for one case, demonstrating improved work efficiency.

Deep learning estimation of three-dimensional left atrial shape from two-chamber and four-chamber cardiac long axis views.

Left atrial volume is commonly estimated using the bi-plane area-length method from two-chamber (2CH) and four-chamber (4CH) long axes views. However, this can be inaccurate due to a violation of geometric assumptions. We aimed to develop a deep learning neural network to infer 3D left atrial shape, volume and surface area from 2CH and 4CH views. A 3D UNet was trained and tested using 2CH and 4CH segmentations generated from 3D coronary computed tomography angiography (CCTA) segmentations (n = 1700, with 1400/100/200 cases for training/validating/testing). An independent test dataset from another institution was also evaluated, using cardiac magnetic resonance (CMR) 2CH and 4CH segmentations as input and 3D CCTA segmentations as the ground truth (n = 20). For the 200 test cases generated from CCTA, the network achieved a mean Dice score value of 93.7%, showing excellent 3D shape reconstruction from two views compared with the 3D segmentation Dice of 97.4%. The network also showed significantly lower mean absolute error values of 3.5 mL/4.9 cm2 for LA volume/surface area respectively compared to the area-length method errors of 13.0 mL/34.1 cm2 respectively (P < 0.05 for both). For the independent CMR test set, the network achieved accurate 3D shape estimation (mean Dice score value of 87.4%), and a mean absolute error values of 6.0 mL/5.7 cm2 for left atrial volume/surface area respectively, significantly less than the area-length method errors of 14.2 mL/19.3 cm2 respectively (P < 0.05 for both). Compared to the bi-plane area-length method, the network showed higher accuracy and robustness for both volume and surface area.

KST-Mixer: kinematic spatio-temporal data mixer for colon shape estimation

ABSTRACT We propose a spatio-temporal mixing kinematic data estimation method to estimate the shape of the colon with deformations caused by colonoscope insertion. Endoscope tracking or a navigation system that navigates physicians to target positions is needed to reduce such complications as organ perforations. Although many previous methods focused to track bronchoscopes and surgical endoscopes, few number of colonoscope tracking methods were proposed because the colon largely deforms during colonoscope insertion. The deformation causes significant tracking errors. Colon deformation should be considered in the tracking process. We propose a colon shape estimation method using a Kinematic Spatio-Temporal data Mixer (KST-Mixer) that can be used during colonoscope insertions to the colon. Kinematic data of a colonoscope and the colon, including positions and directions of their centerlines, are obtained using electromagnetic and depth sensors. The proposed method separates the data into sub-groups along the spatial and temporal axes. The KST-Mixer extracts kinematic features and mix them along the axes multiple times. We evaluated colon shape estimation accuracies in phantom studies. The proposed method achieved 11.92 mm mean Euclidean distance error, the smallest of the previous methods. Statistical analysis indicated that the proposed method significantly reduced the error compared to the previous methods.

Imaging Cloaked Objects: Diffraction Tomography of Realistic Invisibility Devices (Laser Photonics Rev. 17(2)/2023)

Imaging Cloaked Objects Artist's rendering of a tomographic image of a hexagonal invisibility cloak based on transformation optics. While this type of cloak has been shown to do a good job of hiding objects from scattering cross-section measurements, as can be seen, diffraction tomography is able to reveal its presence by providing an image of its approximate shape, as discussed in article number 2200237 by Francisco J. Díaz-Fernández, Javier Martí, and Carlos García-Meca.

Demonstration of beam loading compensation system for discrete beam with comb-like structure in proton linear accelerator

In the Japan Proton Accelerator Research Complex (J-PARC) linear accelerator (LINAC), certain macro pulses of a beam with a frequency of 25 Hz have a discrete comb-like structure (called an intermediate pulse), which is a typical period of 0.815 ns and a width of 0.456 ns. The ability to change of the beam structure has been a useful tool in adjusting beam current and in the various beam studies. However, the digital feedback (DFB) and feedforward (DFF) system controlling the radio frequency (RF) field in the acceleration cavity in LINAC has not been able to accommodate this change. Further, the momentum of the injection beam within the macro pulses varies, which can cause beam loss in the downstream accelerators and beam transport lines. Therefore, in this study, we established a chop pulse gate signal distribution system and its signal that contains information on the pattern of the intermediate pulses is sent to each DFB and DFF system. In contrast to the current system, which compensates the beam loading in an approximate rectangular shape without considering the intermediate pulses (FF_BEAM), we developed the beam loading compensation system by the same structure as the discrete beam by the external chop pulse gate signal; it was labeled FF_BEAM_chop. The experiment was carried out in the 324-MHz stations using a beam current of 25 mA, which is half the current of the usual beam. When the beam pattern was changed via thinnings where it means reduction of the number of the intermediate pulses, the FF_BEAM_chop method significantly suppressed the decrease in the amplitude and phase stabilities compared to the FF_BEAM method. When the widths of the intermediate pulses were changed, the amplitude and phase stabilities generated by the FF_BEAM method deteriorated, but those generated by the FF_BEAM_chop method exhibited almost no deterioration. This demonstrates that FF_BEAM_chop is advantageous for the beam loading compensation of the discrete beam. The adaption of this demonstrated FF_BEAM_chop can be expected to suppress the momentum variation within the macro pulse, to reduce beam loss, and to help the beam commissioning.

How do my earnings compare? Pay referents and just earnings

Abstract Comparisons are crucial in shaping evaluations of one’s own position. Following this notion, we investigated the role of historical, financial, partner, occupational, and regional pay referents in predicting the just gross hourly earnings in a representative sample of German workers. Looking at this broad range of pay referents, we find that higher reference earnings were generally associated with higher just earnings. In particular, controlling for actual gross hourly earnings, higher occupational, regional, and partners’ hourly earnings were associated with higher just gross hourly earnings. One’s own pay history, in form of average hourly earnings over the past 10 years, did not shape just earnings. Financial needs on the household level, however, mapped on to higher just earnings and this association was particularly pronounced among men. Overall, occupational and financial referents showed the strongest association with just earnings followed by partner earnings. These findings underscore that, while referents closely related to one’s job (e.g., occupational referents) are important, referents that extend beyond the sphere of work (e.g., regional, financial, and partner referents) are also relevant in shaping ideas of the just reward.