Shape Template Research Articles

Realizing quality inspection in magnetic pulse crimping manufacturing: Using Steger algorithm and self-attention

Magnetic pulse crimping (MPC) is a high-speed forming using magnetic force to derive metal deformation, which has advantages of controllability and excellent formability. However, due to similar joint appearance and unobservable connection area, evaluating joint quality nondestructively is difficult. This paper presents a quality inspection using the similarity between typical joints (templates) and tests to solve the difficulty. Templates corresponded to joints with deformations ranging from insufficient to excessive (categories 0–4), and the intermediate was qualified. Deformed shapes of the joints on coaxial sections were analytical features to make the most of the correlation between shape and quality. Detailed analysis on quality-related shape avoids unobservable areas and explores subtle differences. Shapes were extracted from the structure light image using the Steger-based algorithm. Self-attention network, a machine learning algorithm, learned the shapes of typical joints to form a comparator. The comparator was used to determine which template shape (types 0–4) the different shapes of the test joint were similar to. The test joint category depended on which type has the maximum ratio in shape prediction. Steger extracts shapes without the discrete spots effect, abnormal and missing values. The comparator accuracy is 0.9701, 0.9841 and 0.9881 for training, validation, and testing. The F1 of the qualified category is 0.98. The untrained joints were used as validation. The maximum ratios are 0.878, 0.842, 0.764, 0.469, and 0.997, whose predicted categories coincide with the real ones. This proves that it is feasible to design inspection based on process characteristics.

A high-precision Mark positioning algorithm based on sub-pixel shape template matching in wafer bonding alignment

Mark's precise positioning is critical for achieving wafer bonding accuracy. A Mark positioning algorithm is proposed to improve the accuracy and stability of Mark positioning. Shape template matching can effectively reduce the impact of image quality on positioning accuracy, but it can only achieve pixel precision Mark location. On the basis of this method, the algorithm uses the facet model method to extract the sub-pixel edge information for the Mark contour, and combines the sub-pixel traversal strategy to achieve accurate sub-pixel precision Mark location. Simultaneously, the composite template method is proposed for the first time to improve the template information's quality, which effectively improves the robustness of the algorithm to image quality. The simulation results indicate that the algorithm is capable of positioning with an accuracy of approximately 0.04 pixels. The experimental results indicate that the algorithm is capable of positioning with an accuracy of approximately 0.052 pixels and is resistant to image noise and blur, which meets the accuracy and stability requirements for Mark positioning in wafer bonding alignment.

An Implicit Parametric Morphable Dental Model

3D Morphable models of the human body capture variations among subjects and are useful in reconstruction and editing applications. Current dental models use an explicit mesh scene representation and model only the teeth, ignoring the gum. In this work, we present the first parametric 3D morphable dental model for both teeth and gum. Our model uses an implicit scene representation and is learned from rigidly aligned scans. It is based on a component-wise representation for each tooth and the gum, together with a learnable latent code for each of such components. It also learns a template shape thus enabling several applications such as segmentation, interpolation and tooth replacement. Our reconstruction quality is on par with the most advanced global implicit representations while enabling novel applications. The code will be available at https://github.com/cong-yi/DMM

DEM modeling of mini-triaxial test on soil-rock mixture considering particle shape effect

Soil-rock mixture (SRM) that is seriously affected by multiple factors such as particle morphology, grading, and composition has been widely used in geotechnical engineering. In this study, a series of discrete element method (DEM) simulations of mini-triaxial tests on SRM were carried out considering the particle shape effect. First, micro-computed tomography, advanced image processing, and spherical harmonics analysis techniques were successively used to obtain the natural particle shapes of grains which were used to build the particle shape template by the clumping algorithm in DEM. Then, a flexible membrane with constant confining pressure loading was made allowing free deformation of the SRM specimens. After that, a set of micro-parameters involved in the DEM model were calibrated by the uniaxial compression tests, and 9 DEM models of mini-triaxial tests were established to investigate the effects of particle shape, size (gradation), and the percentage of irregularly shaped particles on the deformation and failure characteristics of SRM under shearing. Lastly, the mechanical behaviors of SRM, e.g., stress–strain, macroscopic deformation, and cracks generation and evolutions, were comprehensively analyzed. The simulation results provide new insights into the discrete element study of SRM and contribute to the development of soil stabilization materials for geotechnical engineering.

Noninvasive shape-fitting method quantifies cam morphology in femoroacetabular impingement syndrome: Implications for diagnosis and surgical planning.

There are considerable limitations associated with the standard 2D imaging currently used for the diagnosis and surgical planning of cam-type femoroacetabular impingement syndrome (FAIS). The aim of this study was to determine the accuracy of a new patient-specific shape-fitting method that quantifies cam morphology in 3D based solely on preoperative MRI imaging. Preoperative and postoperative 1.5T MRI scans were performed on n = 15 patients to generate 3D models of the proximal femur, in turn used to create the actual and the virtual cam. The actual cams were reconstructed by subtracting the postoperative from the preoperative 3D model and used as reference, while the virtual cams were generated by subtracting the preoperative 3D model from the virtual shape template produced with the shape-fitting method based solely on preoperative MRI scans. The accuracy of the shape-fitting method was tested on all patients by evaluating the agreement between the metrics of height, surface area, and volume that quantified virtual and actual cams. Accuracy of the shape-fitting method was demonstrated obtaining a 97.8% average level of agreement between these metrics. In conclusion, the shape-fitting technique is a noninvasive and patient-specific tool for the quantification and localization of cam morphology. Future studies will include the implementation of the technique within a clinically based software for diagnosis and surgical planning for cam-type FAIS.

3D Shape Deformation Using Stick Figures

Obtaining new poses of an articulated character is a critical task in computer graphics. We address this issue with a new shape deformation approach consisting of two phases enabling the user to express the new pose as a simple stick figure, also called skeleton consisting of few bones. We interchangeably refer to this problem as shape transfer because the template shape is transferred to the independent stick figure that may be obtained from any source such as motion capture and 3D sketching. In the first phase, the stick figure is embedded into the template shape, resembling the rigging process of character skinning. Then, instead of computing blend weights as in skinning, the shape, discretized as a mesh, is augmented by adding extra edges between a subset of mesh vertices and the embedded stick figure. The second phase deforms the augmented mesh towards the new pose under the guidance of the embedded stick figure by minimizing an As-Rigid-As-Possible (ARAP) energy. The overall deformation is intuitive as skinning, preserves surface details as it is based on ARAP deformation yet has better volume preservation capability owing to the augmented mesh. Our results are validated both in terms of timing and accuracy in a comprehensive test suite that includes state-of-the-art deformation techniques. • Edges between mesh and its skeleton prevent from volume loss in ARAP deformation. • Two skeletons can be matched by minimizing a distance-based penalty function. • Distance-based skeleton matching method can be used as an automatic rigging method. • New poses of a shape can be created by using a stick figure and a template mesh.

Synthesis of Highly Conductive Poly(3-hexylthiophene) by Chemical Oxidative Polymerization Using Surfactant Templates.

Poly(3-hexylthiophene) (P3HT) was systematically synthesized by chemical oxidative polymerization in chloroform with ferric chloride (FeCl3) as the oxidizing agent and various surfactants of the shape templates. The effects of 3HT: FeCl3 mole ratios, polymerization times, and surfactant types and concentrations on the electrical conductivity, particle shape and size were systematically investigated. Furthermore, dodecylbenzenesulfonic acid (DBSA), p-toluenesulfonic acid (PTSA), sodium dodecyl sulfate (SDS), and sodium dioctyl sulfosuccinate (AOT) were utilized as the surfactant templates. The P3HT synthesized with DBSA at 6 CMC, where CMC stands for the Critical Micelle Concentration of surfactant, provided a higher electrical conductivity than those with PTSA, SDS and AOT. The highest electrical conductivity of P3HT using DBSA was 16.21 ± 1.55 S cm−1 in which the P3HT particle shape was spherical with an average size of 1530 ± 227 nm. The thermal analysis indicated that the P3HT synthesized with the surfactants yielded higher stability and char yields than that of P3HT without. The P3HT_DBSA electrical conductivity was further enhanced by de-doping and doping with HClO4. At the 10:1 doping mole ratio, the electrical conductivity of dP3HT_DBSA increased by one order of magnitude relative to P3HT_DBSA prior to the de-doping. The highest electrical conductivity of dP3HT_DBSA obtained was 172 ± 5.21 S cm−1 which is the highest value relative to previously reported.

Micro-fabricated mirrors with finesse exceeding one million

The Fabry–Perot resonator is one of the most widely used optical devices, enabling scientific and technological breakthroughs in diverse fields including cavity quantum electrodynamics, optical clocks, precision length metrology, and spectroscopy. Though resonator designs vary widely, all high-end applications benefit from mirrors with the lowest loss and highest finesse possible. Fabrication of the highest-finesse mirrors relies on centuries-old mechanical polishing techniques, which offer losses at the parts-per-million (ppm) level. However, no existing fabrication techniques are able to produce high-finesse resonators with the large range of mirror geometries needed for scalable quantum devices and next-generation compact atomic clocks. In this paper, we introduce a scalable approach to fabricate mirrors with ultrahigh finesse ( ≥ 10 6 ) and user-defined radius of curvature spanning of four orders of magnitude ( 10 − 4 − 10 0 m ). We employ photoresist reflow and reactive ion etching to shape and transfer mirror templates onto a substrate while maintaining sub-Angstrom roughness. This substrate is coated with a dielectric stack and used to create arrays of compact Fabry–Perot resonators with finesse values as high as 1.3 million and measured excess loss < 1 p p m . Optical ringdown measurements of 43 devices across five substrates reveal that the fabricated cavity mirrors—with both small and large radii of curvature—produce an average coating-limited finesse of 1.05 million. This versatile approach opens the door to scalable fabrication of high-finesse miniaturized Fabry–Perot cavities needed for emerging quantum optics and frequency metrology technologies.

Template Synthesis and Characterization of Ni Nanostructures

Nanostructures of a typical ferromagnetic material, nickel are fabricated by electro-deposition (in a DC mode) within the pores of polycarbonate track etched membranes. The cylindrical pores with pore diameter 100 nm have been used for present study. Negative template method via two electrode potentiostatic arrangement in electrochemical cell has been used to synthesize the ordered array of one-dimensional Ni nanostructures. Deposition has been carried out at \(41\pm2\) degree, 1.6 V and so formed one dimensional nanostructure has been obtained at a Copper substrate. The elegant approach of template synthesis has advantage that shape and diameter of one-dimensional nanostructure can be varied as per the requirement, by using the templates of different pore shapes and diameters. Crystalline nature of one-dimensional Ni nanostructures is confirmed by X-ray spectroscopy using Rigaku X-ray diffractometer. I-V characteristics have also been drawn using Keithley source meter, in order to check out the variation in electrical conductivity from bulk to nanoscale.

CBCT Analysis of Maxillary First Molar in Indian Population.

AimThis study aimed to assess the variations in root canal morphology of permanent maxillary first molar with the use of cone-beam computed tomography (CBCT).Materials and methodsOne hundred extracted teeth were cleaned and arranged in U shape template mimicking natural arch in set of five teeth. These arches were scanned in CBCT and were analyzed by expert radiologist for number of roots, number of canals per root, and Vertucci classification.ResultA maximum number of permanent maxillary first molars had three roots, and only 2% had two roots. All the palatal roots and 99% of distobuccal roots had one canal, but one of the distobuccal roots had two canals. Incidence of two canals in MB root is more frequent (60%) than incidence of one canal. The most common type of Vertucci's classification for MB root is a type I, followed by type IV, type II, type VI, type V, type VII.How to cite this articleSharma M, Gupta S, Bhayya DP, et al. CBCT Analysis of Maxillary First Molar in Indian Population. Int J Clin Pediatr Dent 2022;15(3):258-262.

Ridge regression with adaptive additive rectangles and other piecewise functional templates

We propose a penalization algorithm for functional linear regression models, where the coefficient function β is shrunk towards a data-driven shape template γ. To the best of our knowledge, we employ the nonzero centered L2 penalty in a novel manner, as the center of the penalty γ is also optimized while being constrained to belong to a class of piecewise functions Γ, by restricting its basis expansion. This indirect penalization allows the user to control the overall shape of β, by imposing his prior knowledge on γ through the definition of Γ, without limiting the flexibility of the estimated model. In particular, we focus on the case where γ is expressed as a sum of q rectangles that are adaptively positioned with respect to the regression error. As the problem of finding the optimal knot placement of a piecewise function is nonconvex, we also propose a novel parametrization that allows to reduce the number of variables in the global optimization scheme, resulting in a fitting algorithm that alternates between approximating a suitable template and solving a convex ridge-like problem. The predictive power and interpretability of our method is shown on multiple simulations and two real world case studies.

Insulator Hydrophobic Image Edge Detection Algorithm considering Deconvolution and Deblurring Algorithm

In this paper, the Gram matrix is used to calculate the correlation of the filter response sets under different scale kernels learned by each layer of the network in the deconvolution, and the loss between the corresponding feature response correlations in the multilayer network is calculated. Linear summation is used to obtain a stable, multiscale image model representation. This paper extracts the contours of the salient areas of the image and adjusts the parameters of the deconvolution network to learn the salient area patterns of the image. At the same time, for the image to be generated, a shape template is used to limit the range of the area to be generated in order to obtain a shape image with similar patterns. When the spatial relative relationship characteristics of the image constituent objects are obvious, we appropriately add high-level semantic feature activation values for reinforcement. This paper solves the estimation of the unknown blur kernel by using image prior knowledge, filtering and gradient domain algorithms and other different technologies to obtain image jitter or scene movement information and estimate the size, location, and density of the blur kernel. This paper studies a relatively robust deconvolution model, which is insensitive to random noise, has stable effects, and can overcome the water ripple effect caused by the usual convolution process. This paper attempts to study the fuzzy model with variable space. The usual blur is a spatial invariant model; that is, a single kernel is used to describe the motion of all pixels on the image. By selecting different characteristic parameters, this paper conducts experimental research on some existing hydrophobic indicator function methods and calculates the relationship between characteristic parameters and hydrophobicity when different hydrophobic indicator functions are adopted. One characteristic of the hydrophobic image of composite insulators is low contrast. The traditional method of converting color images to grayscale images cannot improve the image contrast. This paper analyzes the hydrophobic image of the composite insulator, and the extracted B channel component image of the hydrophobic image improves the contrast of the image and facilitates the subsequent segmentation of water traces and background. In this paper, the water repellent image's watermark area is counted, and connected-domain wave processing is used to limit the area of water droplets retained, thereby improving the efficiency of filtering water droplets without having a big impact on the image as a whole. The problem of uneven illumination is an unavoidable problem in the field of image processing, and the resulting reflection problem brings difficulties to image processing. This article regards the reflective area of the watermark as a “hole” and uses the idea of “hole filling” to eliminate the reflective point, which weakens the reflection problem to a certain extent.

Tailoring Ordered Wrinkle Arrays for Tunable Surface Performances by Template-Modulated Gradient Films.

Complex wrinkled microstructures are ubiquitous in natural systems and living bodies. Although homogeneous wrinkles in film-substrate bilayers have been extensively investigated in the past 2 decades, tailoring heterogeneous wrinkles by a facile method is still a challenge. Here, we report on the controllable heterogeneous wrinkles in template-modulated thickness-gradient metal films sputter-deposited on polydimethylsiloxane substrates. It is found that the stress of the gradient film is strongly position-dependent and the wrinkles are always restricted in thinner film regions. The morphological characteristic and formation mechanism of the heterogeneous wrinkles are analyzed and discussed in detail based on the stress theory. Ordered wrinkle arrays are achieved by adjusting the deposition time, copper grid period, template shape, and lifting height. The surface performances (e.g., the friction property) are well controlled by the wrinkle arrays. This work could promote better understanding of the spontaneously heterogeneous wrinkles in template-modulated gradient films and controllable fabrication of various wrinkle arrays by independently tuning film deposition conditions and template parameters.

Template Electrochemical Synthesis of Hydroxyapatite on a Titania–Silver Composite Surface for Potential Use in Implantology

Modern materials science, both in terms of functional and structural materials, is actively developing towards the creation of structures with a given ordering. A wide range of methods involves ordering the structure according to a template shape. Template synthesis is one of the mots wide-spread approaches. Most often, the template synthesis method is implemented under conditions of limiting the growth of the phase due to the geometry of the template. In the present work, a template electrochemical method is considered for calcium hydroxyapatite (HAp) coating synthesis, based on the replication of the planar template texture during deposition. In this case, the template is an array of silver microparticles immobilized on an electrically conductive substrate, separated by an insulator layer. The developed approach is similar to the mask metallization widely used in planar technology. In this work, the possibility of the template pulsed electrodeposition of ceramics rather than metal is shown using HAp as an example. This approach is interesting for materials science, in particular, for obtaining micro-ordered hydroxyapatite structures—a crystallochemical analogue of the inorganic bone tissue component—on the surface of bone implants, which can be implemented to improve their biomedical characteristics. As a result of our study, we experimentally determined the conditions for obtaining the composite coating TiO2/Ag/Ca10(PO4)6(OH)2 with controlled phase structure, topology and localization of components on the surface, which was confirmed by Scanning Electron Microscopy, Energy Dispersive Spectroscopy, and X-ray Diffraction (SEM, EDS and XRD). The absence of cytotoxicity for the osteoblast-like cells of the developed coating was revealed by cytological tests.

Polarised W+j production at the LHC: a study at NNLO QCD accuracy

We study polarisation of W-bosons produced in association with one jet at the LHC. In particular, we provide all necessary theoretical ingredients for the precise extraction of polarisation fractions. To that end, we present new polarised predictions up to NNLO QCD accuracy employing the narrow-width approximation, in two phase spaces: inclusive and fiducial. We compare results in the fiducial phase space to a full off-shell computation as well as experimental data. Finally, we fit the polarisation fractions using shape templates and show that NNLO corrections significantly improve their determination.

EViS: An Enhanced Virtual Screening Approach Based on Pocket-Ligand Similarity.

Virtual screening (VS) is a popular technology in drug discovery to identify a new scaffold of actives for a specific drug target, which can be classified into ligand-based and structure-based approaches. As the number of protein-ligand complex structures available in public databases increases, it would be possible to develop a template searching-based VS approach that utilizes such information. In this work, we proposed an enhanced VS approach, which is termed EViS, to integrate ligand docking, protein pocket template searching, and ligand template shape similarity calculation. A novel and simple PL-score to characterize local pocket-ligand template similarity was used to evaluate the screening compounds. Benchmark tests were performed on three datasets including DUDE, LIT-PCBA, and DEKOIS. EViS achieved the average enrichment factors (EFs) of 27.8 and 23.4 at a 1% cutoff for experimental and predicted structures on the widely used DUDE dataset, respectively. Detailed data analysis shows that EViS benefits from obtaining favorable ligand poses from docking and using such ligand geometric information to perform three-dimensional (3D) ligand similarity calculations, and the PL-score is efficient to screen compounds based on template searching in the protein-ligand structure database.

AAO Template-Assisted Fabrication of Ordered Ag Nanoparticles-Decorated Au Nanotubes Array for Surface-Enhanced Raman Scattering Detection

Highly sensitive and reproducible surface-enhanced Raman scattering (SERS) substrates are the main challenge for practical applications. In this work, an ordered and hierarchical Ag nanoparticles (Ag-NPs)-decorated Au nanotubes (Au-NTs) array was achieved based on a funnel-shaped pore anodic aluminum oxide (AAO) template-assisted strategy. First, funnel-pore-AAO templates were fabricated by further oxidation of conical-pore-AAO templates achieved by multistep anodization and etching. Then physical sputtering was used to assemble the Au-NTs and Ag-NPs using the as-prepared funnel-pore-AAO as sacrificial templates. SEM revealed abundant sub-10 nm neighboring gaps and sub-10 nm nanocavities at the bottom of the nanotubes because of the special shape of the AAO template, which resulted in abundant strong “hot spots” contributing to the sensitive SERS detection. The resultant hierarchical substrates manifested a SERS enhancement factor of 1.8 × 107 and reproducible response to 10−11 M rhodamine 6G and 10−8 M methyl parathion, showing potential in SERS-based rapid detection of trace pollutants in the environment.

A unified approach for automated segmentation of pupil and iris in on-axis images

We propose a unified approach for the automatic and accurate segmentation of the pupil and iris from on-axis grayscale eye images. The segmentation of pupil and iris is achieved with Basis-spline-based active contour and circular active contour, respectively. The circular active contour shape template has three free parameters, i.e., a pair of center coordinates and the radius. Basis-spline has M knots in the shape template and five free parameters i.e., a pair of center coordinates, scaling in the horizontal and vertical directions, and the rotation angle. The segmentation of the region of interest is done by minimization of the local energy function. Optimization of the local energy function of circular and Basis-spline-based active contour is carried out using gradient descent technique and Green’s theorem. To achieve the segmentation of iris boundary, the circular active contour method is combined with our novel occlusion removal algorithm. This helps in removing eyelid and eyelash occlusions for accurate iris segmentation. Automatic localization of the pupil is achieved by the sum of absolute difference method. The proposed algorithm is validated on three publicly available databases: IIT Delhi Iris, CASIA Iris Interval V3, and CASIA Iris Interval V4 databases consisting of 7518 grayscale iris images in total. For the segmentation of pupil from the aforementioned databases, we attained a Dice index of 0.971, 0.950, and 0.960, respectively, and for the segmentation of iris, we attained a Dice index of 0.905, 0.898, and 0.900, respectively. An exploratory data analysis was then done to visualize the distribution of the performance parameters throughout the databases. The segmentation performance of the proposed algorithm is on par with that of the reported state-of-the-art algorithms.

Bayesian logistic shape model inference: Application to cochlear image segmentation.

Incorporating shape information is essential for the delineation of many organs and anatomical structures in medical images. While previous work has mainly focused on parametric spatial transformations applied to reference template shapes, in this paper, we address the Bayesian inference of parametric shape models for segmenting medical images with the objective of providing interpretable results. The proposed framework defines a likelihood appearance probability and a prior label probability based on a generic shape function through a logistic function. A reference length parameter defined in the sigmoid controls the trade-off between shape and appearance information. The inference of shape parameters is performed within an Expectation-Maximisation approach in which a Gauss-Newton optimization stage provides an approximation of the posterior probability of the shape parameters. This framework is applied to the segmentation of cochlear structures from clinical CT images constrained by a 10-parameter shape model. It is evaluated on three different datasets, one of which includes more than 200 patient images. The results show performances comparable to supervised methods and better than previously proposed unsupervised ones. It also enables an analysis of parameter distributions and the quantification of segmentation uncertainty, including the effect of the shape model.

New Palladium - ZrO2 Nano-Architectures from Thermal Transformation of UiO-66-NH2 for Carbonylative Suzuki and Hydrogenation Reactions.

The new nanocomposites, Pd/C/ZrO2 , PdO/ZrO2, and Pd/PdO/ZrO2 , were prepared by thermal conversion of Pd@UiO-66-Zr-NH2 (MOF) in nitrogen or air atmosphere. The presence of Pd nanoparticles, uniformly distributed on the ZrO2 or C/ZrO2 matrix, was evidenced by transmission electron microscopy, scanning electron microscopy (SEM), Raman and X-ray Photoelectron Spectroscopy (XPS) methods. All pyrolysed composites retained the shape of the MOF template. They catalyze carbonylative Suzuki coupling under 1 atm CO with an efficiency significantly higher than the original Pd@UiO-66-Zr-NH2 . The most active PdO/ZrO2 composite, formed benzophenone with TOF up to 1600 h-1 , while by using Pd@UiO-66-Zr-NH2 , much lower TOF values, 51-95 h-1 , were achieved. After the reaction, PdO/ZrO2 was recovered with the same composition and catalytic activity. Very good results were also obtained in the transfer hydrogenation of benzophenones to alcohols with Pd/C/ZrO2 and PdO/ZrO2 catalysts under microwave irradiation.