Shape Template Research Articles

Dynamic mechanochemical feedback between curved membranes and BAR protein self-organization

In many physiological situations, BAR proteins reshape membranes with pre-existing curvature (templates), contributing to essential cellular processes. However, the mechanism and the biological implications of this reshaping process remain unclear. Here we show, both experimentally and through modelling, that BAR proteins reshape low curvature membrane templates through a mechanochemical phase transition. This phenomenon depends on initial template shape and involves the co-existence and progressive transition between distinct local states in terms of molecular organization (protein arrangement and density) and membrane shape (template size and spherical versus cylindrical curvature). Further, we demonstrate in cells that this phenomenon enables a mechanotransduction mode, in which cellular stretch leads to the mechanical formation of membrane templates, which are then reshaped into tubules by BAR proteins. Our results demonstrate the interplay between membrane mechanics and BAR protein molecular organization, integrating curvature sensing and generation in a comprehensive framework with implications for cell mechanical responses.

An Improved Automatic Shape Feature Extraction Method Based on Template Matching

Image shape extraction is an important step in the image analysis, AI electronic industry and automation, as well as a significant part of content-based image retrieval(CBIR), which cannot be separated from contour extraction. However, traditional approach of the border following algorithm is susceptible to noise interference, thus the shape extracted is always complex in real images and cannot express feature of the target image well. Therefore, an improved shape feature extraction method is proposed, which converts color space into HSV model when preprocessing, filters contour by area size, merges adjacent contours by drawing convex hull and filters with template shapes. Lastly, this method is tested on UAV123 and YCB_Video dataset, which showed that the proportion of valid contour improved from less than 10% to 87.7% based on border following algorithm. In the experiment of OPenCV open source library in Visual Studio environment, we hope to improve the extraction efficiency of shape features.

A feature-based statistical shape model for geometric analysis of the human talus and development of universal talar prostheses.

Statistical data pertaining to anatomic variations of the human talus contain valuable information for advances in biological anthropology, diagnosis of the talar pathologies, and designing talar prostheses. A statistical shape model (SSM) can be a powerful data analysis tool for the anatomic variations of the talus. The main concern in constructing an SSM for the talus is establishing the true geometric correspondence between the talar geometries. The true correspondence complies with biological and/or mathematical homologies on the talar surfaces. In this study, we proposed a semi-automatic approach to establish a dense correspondence between talar surfaces discretized by triangular meshes. Through our approach, homologous salient surface features in the form of crest lines were detected on 49 talar surfaces. Then, the point-wise correspondence information of the crest lines was recruited to create posterior Gaussian process morphable models that non-rigidly registered the talar meshes and consequently established inter-mesh dense correspondence. The resultant correspondence perceptually represented the true correspondence as per our visual assessments. Having established the correspondence, we computed the mean shape using full generalized Procrustes analysis and constructed an SSM by means of principal component analysis. Anatomical variations and the mean shape of the talus were predicted by the SSM. As a clinically related application, we considered the mean shape and investigated the feasibility of designing universal talar prostheses. Our results suggest that the mean shape of (the shapes of) tali can be used as a scalable shape template for designing universal talar prostheses.

Cross ratio arrays: A descriptor invariant to severe projective deformation and robust to occlusion for planar shape recognition

Recognizing planar objects such as characters, symbols and logos is considered a hard problem in computer vision due to the possibility of these shapes suffer from different kinds of disturbances: projective or other nonlinear deformations, occlusions and spurious insertions. Different planar descriptors have been proposed by taking advantage of geometric features that are invariant to certain image transformations, usually linear ones such as scaling, rotation and affinity. In this work, a new descriptor of planar shapes robust to projective deformations is proposed: Cross Ratio Arrays (CRA). The descriptor is based on tracing rays across the images and collecting their intersections with the borders of the shapes to assemble arrays of computed cross ratios, one of the most fundamental projective invariants. Higher level arrays are built out of these sets of arrays from both query and template shapes, which ultimately allows us to identify correspondences in these shapes to estimate how projectively deformed one shape is from the other. Experiments with synthetic shapes as well as real world scene shapes suffering from severe projective deformations were conducted, with CRA outperforming state-of-the-art descriptors. In addition, tests were performed with different levels of occlusion and weak nonlinear deformations to evidence CRA’s robustness to such cases.

Studies on Preparation, Characterization and Application of Porous Functionalized Glycidyl Methacrylate-Based Microspheres.

A one-step swelling and polymerization technique was used in the synthesis of porous glycidyl methacrylate (GMA) and ethylene glycol dimethacrylate (EGDMA) monodisperse polymeric microspheres. The polystyrene (PS) seed obtained in the dispersion polymerization was used as a shape template. The presence of epoxide rings in the chemical structure of microspheres enables their post-polymerization chemical modifications involving: the Diels-Alder reaction with sodium cyclopentadienide and maleic anhydride, the reaction with 4,4′-(bismaleimido)diphenylmethane, and the thiol-Michael reaction with methacryloyl chloride and 2-mercaptopropionic acid. Changing the reaction mixture composition—the amounts of crosslinking monomer and PS seed as well as the type and concentration of porogen porous microspheres of different porous structures were obtained. Their porous structures were characterized in the dry and swollen states. The copolymers obtained from the equimolar monomers mixture modified in the above way were applied as the column packing materials and tested in the reverse-phase HPLC (High-Performance Liquid Chromatography). A few factors influencing morphology and porous structure of microspheres were studied.

Synthesis of Molecularly Imprinted Polymers by Two-Step Swelling and Polymerization.

Synthesis of a molecularly imprinted polymer (MIP) by two-step swelling and polymerization is described. Monodisperse, spherical MIP particles, whose diameters are ca. 5-9μm, are prepared using a polystyrene particle as a shape template and dibutyl phthalate as an activating solvent. The obtained MIPs are suitable for separation media in liquid chromatography or solid-phase extraction media. Procedures for synthesis of MIPs and restricted access media (RAM)-MIP, packing of MIPs and RAM-MIPs, and application of MIPs and RAM-MIPs for selective separation and extraction of a target compound(s) are described.

Molecular Imprints Frozen by Strong Intermolecular Interactions in Place of Cross-Linking.

A new way to freeze molecular imprints in a polymer material is reported. So far, molecular imprinted polymers (MIP) involve copolymerization of a functional monomer and large amounts of cross-linking agent, which keeps the template shape memory in rigid molecular imprints. MIP materials are prepared herein without cross-linking agent. Stiff chains of polyaniline grafted on a solid support as a brush-like material achieve the necessary rigidity. Differential adsorption to imprinted and non-imprinted materials provides evidence of molecular imprints. A correct adsorption isotherm for mobile adsorbed layers (Volmer isotherm) is introduced instead of the popular but inadequate Langmuir isotherm. Non-selective adsorption is entropic, whereas adsorption to molecular imprints has an enthalpic contribution coming from specific interactions. Fast adsorption kinetics are a definite benefit with regards to applications such as chromatographic separations and chemical sensors.

Making and shaping endochondral and intramembranous bones.

Skeletal elements have a diverse range of shapes and sizes specialized to their various roles including protecting internal organs, locomotion, feeding, hearing, and vocalization. The precise positioning, size, and shape of skeletal elements is therefore critical for their function. During embryonic development, bone forms by endochondral or intramembranous ossification and can arise from the paraxial and lateral plate mesoderm or neural crest. This review describes inductive mechanisms to position and pattern bones within the developing embryo, compares and contrasts the intrinsic vs extrinsic mechanisms of endochondral and intramembranous skeletal development, and details known cellular processes that precisely determine skeletal shape and size. Key cellular mechanisms are employed at distinct stages of ossification, many of which occur in response to mechanical cues (eg, joint formation) or preempting future load‐bearing requirements. Rapid shape changes occur during cellular condensation and template establishment. Specialized cellular behaviors, such as chondrocyte hypertrophy in endochondral bone and secondary cartilage on intramembranous bones, also dramatically change template shape. Once ossification is complete, bone shape undergoes functional adaptation through (re)modeling. We also highlight how alterations in these cellular processes contribute to evolutionary change and how differences in the embryonic origin of bones can influence postnatal bone repair.

Fabrication of Hollow LDH nanocages using ZIF-67 template as superb adsorbent for anionic organic pollutant

Zeolitic imidazolate framework-67 (ZIF-67) was occupied as self-sacrifice template to fabricate hollow LDH nanocages, and the template was consumed during the formation of LDH nanocages. The nanocages composed of NiCo-LDH nanosheets maintained the dodecahedron shape of the ZIF-67 template. The resultant LDH nanocages were of large surface area and hollow porous structure and performed excellent in the adsorptive removal of Congo Red (CR). Influence of factors on the removal of CR was investigated and kinetic study and thermodynamic study were carried out to verify that the removal of CR was a chemisorption process. LDH nanocages after adsorption can be separated and regenerated through solvothermal method using ethanol, and the regenerated LDH nanocages can be recycling used and 89.3% removal of CR can still be reached in the fifth cycling.

3D Personalized Human Modeling and Deformation Technology for Garment CAD

According to the design requirements of garment CAD system, this paper summarizes and analyzes the flow, characteristics and existing problems of existing human modeling algorithms, and proposes a 3D human modeling method based on section ring calculation, and realizes the dynamic modeling of human body driven by joint points. Firstly, the human body shape is classified to create a 3D human body shape template library. On the basis of extracting feature points and feature lines of the human model, the relationship between the size change and the feature points is calculated by using simple linear scaling ratio. Through the mathematical modeling of chest curve, waist hip curve and longitudinal datum line, the fitting curve results which reflect the curve characteristics and are convenient for subsequent clothing deformation are obtained. The algorithm is simple and efficient. It can not only accurately reproduce the surface static characteristics of the original scanned human body, but also change the dynamic characteristics of the human body interactively, which can meet the basic requirements of the human body model in the process of fashion design.

A synergistic catalyst based on a multivalence monodisperse-porous microspheres with oxygen vacancies for benzyl alcohol oxidation

A heterogeneous catalyst for selective oxidation of benzyl alcohol (BzOH) was synthesized by immobilization of Pd nanoparticles (Pd NPs, 3 nm) on monodisperse-porous manganese oxide (MnOx, 4 μm) microspheres obtained by “staged shape templating protocol”. MnOx microspheres containing Mn5O8 (97 %) and MnO2 (78 %) phases were evaluated as supports. The catalysts carrying immobilized Pd NPs were also synthesized, using monodisperse-porous SiO2 and TiO2 microspheres with similar size and porous properties (i.e. Pd@SiO2 and Pd@TiO2). Pd NP decorated-Mn5O8 (Pd@Mn5O8) microspheres provided the highest catalytic activity with BzOH conversion of 92.2 % and benzaldehyde (BzCHO) selectivity of 96.3 %. Higher catalytic activity of Pd@Mn5O8 was explained by mixed valence nature of Mn5O8 microspheres assisting the formation of abundant oxygen vacancies. Mn (II), Mn(III) and Mn(IV) oxidation states were shown by deconvoluted x-ray photoelectron spectra. A synergistic catalytic activity was reported for the first time, by combination of Pd NPs with Mn5O8 microspheres. Pd@Mn5O8 microspheres could be reused up to 5 times without remarkable loss in the activity and selectivity towards BzCHO. A methodology for comparison of catalytic activity and synergistic interaction between active site and support was also exemplified by choosing a nanoparticle type and a monodisperse-porous microsphere type.

Efficient Body Registration Using Single-View Range Imaging and Generic Shape Templates

Abstract Computer-aided medical systems, e.g. in the fields of medical robotics or image-based assistance, are continuously investigated to overcome human limitations concerning perception, memory or dexterity. A common requirement of such systems is the availability of a digital model describing the patient’s position and morphology during a procedure. Operational complexity and technical limitations of established 3D imaging methods leave clinical settings in need of a method for the fast acquisition of a three-dimensional body surface representation. For this purpose, we propose an unsupervised and efficient body registration pipeline based on the markerless elastic registration and completion of single-view stereo range images of the body surface with statistical parametric body shape templates. Initial results show a promising representative quality of the models generated through the registration process with submillimetric fitting accuracy and realistic surface morphology, indicating the general feasibility of our approach as an instant body registration method for automated medical and biometric applications.

Mesh Convolution: A Novel Feature Extraction Method for 3D Nonrigid Object Classification

Applying convolution methods to domains that lack regular underlying structures is a challenging task for 3D vision. Existing methods require the manual design of feature representations suitable for the task or full-voxel-level analysis, which is memory intensive. In this paper, we propose a novel feature extraction method to facilitate 3D nonrigid shape analysis. Our approach, called 3D-MConv, extends convolution operations from regular grids to irregular mesh sets by parametrizing a series of convolutional templates and adopts a novel local perspective to ensure that the algorithm is more invariant against global isometric deformation and articulation. We carefully design the convolutional template as a polynomial function that flexibly represents the local shape. An unsupervised learning method is adopted to learn the convolutional template function. By using the convolution operation and the movement of the template on the model surface, we can obtain the distribution of the typical template shapes. We combine this distribution feature with the spatial co-occurrence information of typical template shapes modelled by Markov chains to form a high-level descriptor of a 3D model. The support vector machine method is used to classify the nonrigid 3D objects. Experiments on SHREC10 and SHREC15 demonstrate that 3D-MConv achieves state-of-the-art accuracy on standard benchmarks.

Discrete element modeling of switchgrass particles under compression and rotational shear

Switchgrass is a perennial herbaceous plant regarded as a biomass energy crop in the United States for its high adaptability and yield potential. Processing and handling of switchgrass particles are challenging due to the erratic mechanical and flow behavior originating from their intrinsic particulate properties. In this work, we present a bonded-sphere discrete element model designed specifically for switchgrass particles. The model simultaneously captures three key particulate features, i.e., fibrous particle shapes, a wide range of particle sizes, and particle deformability. Realistic yet computationally efficient particle shape templates are created based on the image analysis data of switchgrass specimens. A fitting procedure is proposed to ensure both the particle width and length distributions are captured, a unique requirement for fibrous particles. Two full-scale numerical models, i.e., a uniaxial compression model and a Schulze ring shear model, are developed using information from physical experiments. The model is calibrated using experimental data of chopped-small switchgrass specimens, and then, is validated using data of chopped-large specimens in both compression and ring-shear tests. Numerical results show that the numerical models capture bulk densities accurately (with an error of 3%) while slightly underestimate the bulk friction angle. Furthermore, an extensive sensitivity analysis reveals that (1) switchgrass particles with rougher edges (due to different processing techniques) exhibit a higher shear strength and a lower flowability; (2) stiffer particles yield a lower bulk density (up to 21% lower) compared to more deformable particles, indicating particle deformability should be incorporated when modeling biomass flow in a preprocessing system.

3D porous graphene/NiCo2O4 hybrid film as an advanced electrode for supercapacitors

Graphene, as a family of 2D materials, can be used as film electrodes in energy storage devices because of its high surface area, electrical conductivity, and environmental stability. However, the pure graphene electrode attains aggregating nature, which significantly limits its practical application. To solve the overstacking problems, we construct a 3D porous reduced graphene (rGN) film by a novel and green Cu2O template-assisted route based on “coordinating etching and precipitating” process. Noticeably, a brand new material-NiCo2O4 is generated when the template is removed by optimizing the coordinating etchant and the reaction conditions. It is observed that NiCo2O4 perfectly imitates the shape of Cu2O template and has a hollow hydrangea-like structure. Furthermore, these emerging hollow NiCo2O4 hydrangeas not only prevent the re-accumulation of sheet layers, but also afford 3D porous structure for film, and greatly enhance the energy storage properties on account of the pseudocapacitance of NiCo2O4. The 3D graphene/NiCo2O4 film (3D rGN/NiCo2O4) exhibits high specific capacity of 708.36 F g−1 at 1 A g−1, remarkable rate performance of 582.11 F g−1 even at 16 A g−1, and superior circulation ability with 94.3% capacitance retention after 6000 cycles at 10 A g−1, indicating the potential applications in energy storage.

Fabrication of three-dimensional calcium alginate hydrogels using sacrificial templates of sugar

Hydrogels are receiving increasing attention in bioapplications. Among hydrogels, calcium alginate (Ca-alginate) hydrogels are widely used for their biocompatibility, low toxicity, low cost, and rapid fabrication by simple mixing of Ca2+ and sodium alginate (Na-alginate). For bioapplications using hydrogels, it is necessary to construct designed hydrogel structures. Although several methods have been proposed for fabricating designed hydrogels, a simple and low-cost method is desirable. Therefore, we developed a new method using sacrificial templates of sugar structures to fabricate three-dimensional (3D) designed Ca-alginate hydrogels. In this method, Na-alginate solution is mixed with molten sugar, and the resulting highly viscous material used to mold 3D sugar structures as sacrificial templates. Since sugar constructs are easily handled compared to hydrogels, sugar templates are useful for preparing 3D constructs. Finally, the sugar and Na-alginate structure is immersed in a CaCl2 solution to simultaneously dissolve the template and form the Ca-alginate hydrogel. The resulting hydrogel takes the shape of the sugar template. By stacking and fusing various sugar structures, such as fibers and blocks, 3D designed Ca-alginate hydrogels can be successfully fabricated. This simple and low-cost method shows excellent potential for application to a variety of bioapplications.

Self-standing zeolite foam monoliths with hierarchical micro-meso-macroporous structures.

The zeolite monoliths were synthesized by a facile polymer scaffold template assisted hydrothermal method. The selected foam-shaped template of a polyurethane (PU) foam monolith, was used to prepare the self-standing zeolite foam (ZF) monolithic materials. The obtained ZF products can preserve the same size, shape and macroporous network structure of the original PU foam scaffold template, although the zeolite nano-crystallites had been fully substituted for the PU template to form the new skeleton struts and walls. The as-synthesized ZF products demonstrated abundant hierarchical porosity (involving triple micro-, meso- and macropores). Meanwhile, compared with the conventional zeolite powders, the self-standing ZF monolithic materials exhibited greater total pore volume and nearly three times higher mesopore volume, suggesting wider applications as catalysts, catalyst supports and adsorbents in industry.

IRONSperm: Sperm-templated soft magnetic microrobots.

We develop biohybrid magnetic microrobots by electrostatic self-assembly of nonmotile sperm cells and magnetic nanoparticles. Incorporating a biological entity into microrobots entails many functional advantages beyond shape templating, such as the facile uptake of chemotherapeutic agents to achieve targeted drug delivery. We present a single-step electrostatic self-assembly technique to fabricate IRONSperms, soft magnetic microswimmers that emulate the motion of motile sperm cells. Our experiments and theoretical predictions show that the swimming speed of IRONSperms exceeds 0.2 body length/s (6.8 ± 4.1 µm/s) at an actuation frequency of 8 Hz and precision angle of 45°. We demonstrate that the nanoparticle coating increases the acoustic impedance of the sperm cells and enables localization of clusters of IRONSperm using ultrasound feedback. We also confirm the biocompatibility and drug loading ability of these microrobots, and their promise as biocompatible, controllable, and detectable biohybrid tools for in vivo targeted therapy.

Locating victims in hot environments using combined thermal and optical imaging

This work presents an autonomous system based on an Unmanned Aerial Vehicle (UAV) for victim detection using shape template matching. The system blends an optical image into a thermograph to overcome limitations inherent in the visible and infrared spectra. The system also implements image enhancements to counter thermal image degradation in warm climates. All processing is performed in real-time on-board the UAV to maximize autonomy. The outcome is a set of coordinates allowing direct access to the detected victims by rescue crews. An evaluation vehicle was constructed using a readily available drone with standard off-the-shelf components. The prototype accurately detected all victims in the test area, with rare false positives. The proposed image analysis combination was effective even under elevated ambient temperatures. The prototype was able to capture and analyze an image every three seconds allowing travel at a speed close to 2 m/sec. An area of 10,000 m2 can be scanned from an altitude of 10 m without the need for recharging.

Temporal Upsampling of Point Cloud Sequences by Optimal Transport for Plant Growth Visualization

AbstractPlant growth visualization from a series of 3D scanner measurements is a challenging task. Time intervals between successive measurements are typically too large to allow a smooth animation of the growth process. Therefore, obtaining a smooth animation of the plant growth process requires a temporal upsampling of the point cloud sequence in order to obtain approximations of the intermediate states between successive measurements. Additionally, there are suddenly arising structural changes due to the occurrence of new plant parts such as new branches or leaves. We present a novel method that addresses these challenges via semantic segmentation and the generation of a segment hierarchy per scan, the matching of the hierarchical representations of successive scans and the segment‐wise computation of optimal transport. The transport problems' solutions yield the information required for a realistic temporal upsampling, which is generated in real time. Thereby, our method does not require shape templates, good correspondences or huge databases of examples. Newly grown and decayed parts of the plant are detected as unmatched segments and are handled by identifying corresponding bifurcation points and introducing virtual segments in the previous, respectively successive time step. Our method allows the generation of realistic upsampled growth animations with moderate computational effort.