Shape Manipulation Research Articles

Shape Memory Polymers: Magnetic Shape Memory Polymers with Integrated Multifunctional Shape Manipulation (Adv. Mater. 4/2020)

In article number 1906657, H. Jerry Qi, Ruike Zhao, and co-workers present a novel magnetic shape memory polymer that uses the embedded magnetic particles to regulate the material stiffness and induce actuation. This enables integrated shape-manipulation functions, including untethered rapid reversible shape change, sequential actuation, shape locking, and reprogrammability. The integrated functions permit applications such as soft grippers with large grabbing force, morphing electronics, and minimally invasive biomedical devices.

Efficient 3D animation shape manipulation with region smoothness preservation

Efficient 3D animation shape manipulation with region smoothness preservation

Shape Manipulation of Diffusion Curves Images

Diffusion curves image (DCI) is a kind of vector graphics with its geometric primitives defined by a set of Bezier curves. As one of the vector graphics, editability is an important property for diffusion curves. However, most of the current DCI shape manipulation methods are typically limited to single curve. It is tedious for users to edit the shape of DCI by deforming each curve individually, especially with the increasing number of curves. In addition, the image contents cannot well preserved because there is no constraints among curves. We present an efficient and flexible DCI manipulation method by combining global and local deformations. The overall shape is easily changed by our global manipulation tool with a few user interactions, while the local manipulation tool is used to modify details. These two tools can be combined to obtain desired effects. In both cases, the constraints during deformation preserve the quality of the editing results. Our experimental results demonstrate that the proposed method provides more convenient control for DCI shape editing than existing techniques based on diffusion curves.

Magnetic Shape Memory Polymers with Integrated Multifunctional Shape Manipulation.

Shape-programmable soft materials that exhibit integrated multifunctional shape manipulations, including reprogrammable, untethered, fast, and reversible shape transformation and locking, are highly desirable for a plethora of applications, including soft robotics, morphing structures, and biomedical devices. Despite recent progress, it remains challenging to achieve multiple shape manipulations in one material system. Here, a novel magnetic shape memory polymer composite is reported to achieve this. The composite consists of two types of magnetic particles in an amorphous shape memory polymer matrix. The matrix softens via magnetic inductive heating of low-coercivity particles, and high-remanence particles with reprogrammable magnetization profiles drive the rapid and reversible shape change under actuation magnetic fields. Once cooled, the actuated shape can be locked. Additionally, varying the particle loadings for heating enables sequential actuation. The integrated multifunctional shape manipulations are further exploited for applications including soft magnetic grippers with large grabbing force, reconfigurable antennas, and sequential logic for computing.

Rice microtubule-associated protein IQ67-DOMAIN14 regulates grain shape by modulating microtubule cytoskeleton dynamics.

SummaryCortical microtubule (MT) arrays play a critical role in plant cell shape determination by defining the direction of cell expansion. As plants continuously adapt to ever‐changing environmental conditions, multiple environmental and developmental inputs need to be translated into changes of the MT cytoskeleton. Here, we identify and functionally characterize an auxin‐inducible and MT‐localized protein OsIQ67‐DOMAIN14 (OsIQD14), which is highly expressed in rice seed hull cells. We show that while deficiency of OsIQD14 results in short and wide seeds and increases overall yield, overexpression leads to narrow and long seeds, caused by changed MT alignment. We further show that OsIQD14‐mediated MT reordering is regulated by specifically affecting MT dynamics, and ectopic expression of OsIQD14 in Arabidopsis could change the cell shape both in pavement cells and in hypocotyl cells. Additionally, OsIQD14 activity is tightly controlled by calmodulin proteins, providing an alternative way to modify the OsIQD14 activity. Our results indicate that OsIQD14 acts as a key factor in regulating MT rearrangements in rice hull cells and hence the grain shape, and allows effective local cell shape manipulation to improve the rice yield trait.

Learning adaptive hierarchical cuboid abstractions of 3D shape collections

Abstracting man-made 3D objects as assemblies of primitives, i.e. , shape abstraction, is an important task in 3D shape understanding and analysis. In this paper, we propose an unsupervised learning method for automatically constructing compact and expressive shape abstractions of 3D objects in a class. The key idea of our approach is an adaptive hierarchical cuboid representation that abstracts a 3D shape with a set of parametric cuboids adaptively selected from a hierarchical and multi-level cuboid representation shared by all objects in the class. The adaptive hierarchical cuboid abstraction offers a compact representation for modeling the variant shape structures and their coherence at different abstraction levels. Based on this representation, we design a convolutional neural network (CNN) for predicting the parameters of each cuboid in the hierarchical cuboid representation and the adaptive selection mask of cuboids for each input 3D shape. For training the CNN from an unlabeled 3D shape collection, we propose a set of novel loss functions to maximize the approximation quality and compactness of the adaptive hierarchical cuboid abstraction and present a progressive training scheme to refine the cuboid parameters and the cuboid selection mask effectively. We evaluate the effectiveness of our approach on various 3D shape collections and demonstrate its advantages over the existing cuboid abstraction approach. We also illustrate applications of the resulting adaptive cuboid representations in various shape analysis and manipulation tasks.

L’utilisation de l’art-thérapie dans le cadre d’une fugue dissociative

IntroductionStudies on post-traumatic stress disorder with dissociative subtype (PTSD+DS) have proved successful and there is now a need to develop treatments that focus on dissociation. We were interested in a post-traumatic symptom: the dissociative fugue. In the acting-out clinic, art therapy offers creative process methods that focus on emotions. ObjectiveWhile following a dissociative runaway the “mental level” of the person remains frozen, art therapy should allow the awareness for its reactivation and gradually the self-management of these runaways. MethodWe have detained two people disturbed by dissociative runaways. One of them has been sexually abused since childhood and we support her on an art therapy blog. The other is a migrant person housed in an emergency centre of the Aurore association where we provide art therapy workshops. ResultsThe major contributions of this care process are at the conceptual, physical and motor levels. Dissociative fugues were recognized by both subjects. The manipulation of shapes and colours has allowed them to undergo a beneficial transformation and recomposition, after crumbling towards a return and maintenance in the present time. ConclusionThe contribution of these workshops allowed the updating of the different identity structures of the participants. The art therapeutic framework containing and well-treating supports the process of formalizing the unspeakable. Working in mirror with the art therapist therefore opens up access to self-management and the reduction of dissociative fugues.

A flexible formula for incorporating distributive concerns into cost-effectiveness analyses: Priority weights.

Cost effectiveness analyses (CEAs) are widely used to evaluate the opportunity cost of health care investments. However, few functions that take equity concerns into account are available for such CEA methods, and these concerns are therefore at risk of being disregarded. Among the functions that have been developed, most focus on the distribution of health gains, as opposed to the distribution of lifetime health. This is despite the fact that there are good reasons to give higher priority to individuals and groups with a low quality adjusted life expectancy from birth (QALE). Also, an even distribution of health gains may imply an uneven distribution of lifetime health. We develop a systematic and explicit approach that allows for the inclusion of lifetime health concerns in CEAs, by creating a new priority weight function, PW = α+(t-γ)·C·e-β·(t-γ), where t is the health measure. PW has several desirable properties. First, it is continuous and smooth, ensuring that people with similar health characteristics are treated alike. For example, those who achieve 50 QALE should be treated similarly to those who achieve 49.9 QALE. Second, it is flexible regarding shape and outcome measure (i.e., caters to other measures than QALE), so that a broad range of values may be modelled. Third, the coefficients have distinct roles. This allows for the easy manipulation of the PW's shape. In order to demonstrate how PW may be applied, we use data from a previous study and estimated the coefficients of PW based on two approaches. Equity concerns are important when conducting CEAs, which means that suitable PWs should be developed. We do not intend to determine which PW is the most appropriate, but to illustrate how a flexible general PW can be estimated based on empirical data.

Effect of medial surface shape on voice production in a MRI-based three-dimensional phonation model

Our previous studies using simplified vocal fold geometry have shown that medial surface shape, particularly the vertical thickness, has an important effect on the closure pattern of vocal fold vibration. The goal of this study is to investigate if similar effect can be observed for medial surface shape that occurs in realistic human phonation, using a parametric MRI-based three-dimensional vocal fold model. Manipulation of medial surface shape is achieved through a two-level control of the superior and inferior portion of the medial surface, based on experimental observations. Simulations show that, in general, both superior-medial bulging and inferior-medial bulging of the medial surface, which leads to an increased vertical thickness and a more rectangular glottal configuration, increase the closed quotient of the vocal fold vibration. Changes in medial surface shape also have significant effect on the phonation threshold pressure. This effect of the medial surface shape varies significantly across larynges, indicating the important effect of subject-specific laryngeal geometry. The results point to the importance of taking into consideration of the medial surface shape in clinical management of voice disorders. [Work supported by NIH.]

Site-Selective Atomic Layer Precision Thinning of MoS2 via Laser-Assisted Anisotropic Chemical Etching.

Various exotic optoelectronic properties of two-dimensional (2D) transition metal dichalcogenides (TMDCs) strongly depend on their number of layers, and typically manifest in ultrathin few-layer or monolayer formats. Thus, precise manipulation of thickness and shape is essential to fully access their potential in optoelectronic applications. Here, we demonstrate site-selective atomic layer precision thinning of exfoliated MoS2 flake by laser. The oxidation mediated anisotropic chemical etching initiated from edge defects and progressed by controlled scanning of the laser beam. Thereby, the topmost layer can be preferentially removed in designed patterns without damaging the bottom flake. In addition, we could monitor the deceleration of the thinning by in situ reflectance measurement. The apparent slow down of the thinning rate is attributed to the sharp reduction in the temperature of the flake due to thickness dependent optical properties. Fabrication of monolayer stripes by laser thinning suggests potential applications in nonlinear optical gratings. The proposed thinning method would offer a unique and rather straightforward way to obtain arbitrary shape and thickness of a TMDCs flake for various optoelectronic applications.

Human body reshaping and its application using multiple RGB-D sensors

Automatic reshaping of human bodies is a computer vision and graphics technique with many applications. It manipulates various shape attributes of the visual appearance of a person without any manual editing. Keeping coherent reshaping results across many video frames is more challenging. In this paper, we present a novel pipeline to reshape the human body using noisy depth data from multiple RGB-D sensors. Compared with a single view, the data from multiple RGB-D sensors provide more constraints and lead to more consistent results. However, there exist a number of challenges in estimating the pose and shape of human in RGB-D data due to self-occlusion and motion complexity. To cope with the time-varying articulated human shape, we propose a new approach that combines a Gaussian Mixture Model (GMM) based fitting approach with a morphable model learned from range scans. Without any user input, this approach can automatically account for the variations in pose and shape, and enable different types of reshaping by changing body attributes such as height, weight or other physical features. Experimental results are provided to demonstrate the effectiveness of our system in manipulation of human body shapes.

Orientational Disorder in Epitaxially Connected Quantum Dot Solids.

Periodic arrays of strongly coupled colloidal quantum dots (QDs) may enable unprecedented control of electronic band structure through manipulation of QD size, shape, composition, spacing, and assembly geometry. This includes the possibilities of precisely engineered bandgaps and charge carrier mobilities, as well as remarkable behaviors such as metal-insulator transitions, massless carriers, and topological states. However, experimental realization of these theoretically predicted electronic structures is presently limited by structural disorder. Here, we use aberration-corrected scanning transmission electron microscopy to precisely quantify the orientational disorder of epitaxially connected QD films. In spite of coherent atomic connectivity between nearest neighbor QDs, we find misalignment persists with a standard deviation of 1.9°, resulting in significant bending strain localized to the adjoining necks. We observe and quantify a range of out-of-plane particle orientations over thousands of QDs and correlate the in-plane and out-of-plane misalignments, finding QDs misoriented out-of-plane display a statistically greater misalignment with respect to their in-plane neighbors as well. Using the bond orientational order metric ψ4, we characterize the 4-fold symmetry and introduce a quantification of the local superlattice (SL) orientation. This enables direct comparison between local orientational order in the SL and atomic lattice (AL). We find significantly larger variations in the SL orientation and a statistically robust but locally highly variable correlation between the orientations of the two differently scaled lattices. Distinct AL and SL behaviors are observed about a grain boundary, with a sharp boundary in the AL orientations, but a more smooth transition in the SL, facilitated by lattice deformation between the neighboring grains. Coupling between the AL and SL is a fundamental driver of film growth, and these results suggest nontrivial underlying mechanics, implying that simplified models of epitaxial attachment may be insufficient to understand QD growth and disorder when oriented attachment and superlattice growth occur in concert.

DIFFERENCES BETWEEN DYSLEXIC AND NON-DYSLEXIC STUDENTS IN THE PERFORMANCE OF SPATIAL AND GEOGRAPHICAL THINKING

Dyslexia is a specific form of learning disability which comes along with diverse difficulties, both in learning and in social and emotional fields. It obstructs the development of the individual at all levels of education. This research investigates students’ spatial and geographical thinking and whether there is differentiation of these abilities between dyslexic and non-dyslexic ones. For this purpose, 50 questionnaires were distributed to 25 dyslexic and 25 non-dyslexic students aged 14. To implement this research, opportunity sampling from different areas (rural, urban) was used. The questionnaire included spatial thinking exercises like mental rotation, plan views, shapes folding - unfolding and mental manipulation of shapes and exercises by which geographical thinking are examined, according to the Greek geography curriculum. By using SPSSv.23.00 we codified children's answers. The results indicated that the non-dyslexic students had a better score than the dyslexic ones. The most significant difference was in the section of plan views and mental rotation, whereas in the folding and unfolding and shapes mental manipulation, it was found that both children’s groups faced difficulties. Although the research sample is limited, which does not allow for generalization of the conclusions, it was observed that through the students' answers we were led to conclusions that fully match the theoretical framework .

The Process and Operations of Shape Generation and Manipulation during the Architectural Designing Activity

AbstractThis piece of work is concerned with how shapes are generated, explored and transformed during the architectural designing process. It postulates that the relations and connections between sketches, produced during the design activity, can be defined in terms of shape transformations and described according to a closed list of shape operators. These latters provide a formal description of the shape exploration process and allow a deep understanding of its logic. To achieve its goal, this study creates a model to describe the different shape transformations, performed by designers, during the sketching activity.

Assumption-Free Assessment of Corpus Callosum Shape: Benchmarking and Application

Shape analysis provides a unique insight into biological processes. This paper evaluates the properties, performance, and utility of elliptical Fourier (eFourier) analysis to operationalise global shape, focussing on the human corpus callosum. 8000 simulated corpus callosum contours were generated, systematically varying in terms of global shape (midbody arch, splenium size), local complexity (surface smoothness), and nonshape characteristics (e.g., rotation). 2088 real corpus callosum contours were manually traced from the PATH study. Performance of eFourier was benchmarked in terms of its capacity to capture and then reconstruct shape and systematically operationalise that shape via principal components analysis. We also compared the predictive performance of corpus callosum volume, position in Procrustes-aligned Landmark tangent space, and position in eFourier n-dimensional shape space in relation to the Symbol Digit Modalities Test. Jaccard index for original vs. reconstructed from eFourier shapes was excellent (M=0.98). The combination of eFourier and PCA performed particularly well in reconstructing known n-dimensional shape space but was disrupted by the inclusion of local shape manipulations. For the case study, volume, eFourier, and landmark measures were all correlated. Mixed effect model results indicated all methods detected similar features, but eFourier estimates were most predictive, and of the two shape operationalization techniques had the least error and better model fit. Elliptical Fourier analysis, particularly in combination with principal component analysis, is a powerful, assumption-free and intuitive method of quantifying global shape of the corpus callosum and shows great promise for shape analysis in neuroimaging more broadly.

Assessment of Soft Ligand Removal Strategies: Alkylation as a Promising Alternative to High-Temperature Treatments for Colloidal Nanoparticle Surfaces

Advances in nanocrystal syntheses over the past decades now enable routine manipulation of particle shape, size, and chemistry with unprecedented precision. Building on decades of knowledge in coll...

Highly efficient facial blendshape animation with analytical dynamic deformations

Adding physics to facial blendshape animation is an active research topic. Existing physics-based approaches of facial blendshape animation are numerical, so they require special knowledge and skills, additional preprocess, large computer capacity, and expensive calculations leading to low animation frame rates, and are not easy to learn, implement and use. To tackle these problems, we propose an analytical approach and develop a blending force-based framework for physics-based facial animation. The proposed approach introduces the equation of motion to consider inertial effects, damping effects and the resistance against deformations, combines them with source and target facial shapes to formulate the mathematical model of dynamic deformations, and develops a simple and efficient closed-form solution. The blending force-based framework incorporates the new proposed slider force-based, exponentiation force-based and random force-based methods built on the obtained closed form solution to achieve highly efficient facial animation. Compared with facial blendshape animation using geometric linear interpolation, the proposed approach is physics-based. It not only creates all the blended shapes generated by linear interpolation, but also a much larger superset of blended shapes. Unlike linear interpolation which can only generate blended shapes with a same deformation rate, the proposed approach can generate blended shapes with different deformation rates, resulting in special effects of acceleration and deceleration. Compared to existing physics-based approaches of facial blendshape animation which are numerical, the proposed approach is the first time to develop an analytical approach of physics-based facial blendshapes. It does not require any special knowledge and skills and is easy to learn, implement and use. More importantly, it can avoid the additional preprocess of numerical methods and create various physics-based facial blendshape animations highly efficiently. Moreover, it can be used to estimate physical parameters from real shapes and developed into an interactive and real-time physics-based shape manipulation tool.

Spectroscopy of Quantum Dot Orbitals with In-Plane Magnetic Fields

We show that in-plane magnetic-field-assisted spectroscopy allows extraction of the in-plane orientation and full 3D size parameters of the quantum mechanical orbitals of a single electron GaAs lateral quantum dot with subnanometer precision. The method is based on measuring the orbital energies in a magnetic field with various strengths and orientations in the plane of the 2D electron gas. From such data, we deduce the microscopic confinement potential landscape and quantify the degree by which it differs from a harmonic oscillator potential. The spectroscopy is used to validate shape manipulation with gate voltages, agreeing with expectations from the gate layout. Our measurements demonstrate a versatile tool for quantum dots with one dominant axis of strong confinement.

String‐Based Synthesis of Structured Shapes

AbstractWe propose a novel method to synthesize geometric models from a given class of context‐aware structured shapes such as buildings and other man‐made objects. The central idea is to leverage powerful machine learning methods from the area of natural language processing for this task. To this end, we propose a technique that maps shapes to strings and vice versa, through an intermediate shape graph representation. We then convert procedurally generated shape repositories into text databases that, in turn, can be used to train a variational autoencoder. The autoencoder enables higher level shape manipulation and synthesis like, for example, interpolation and sampling via its continuous latent space. We provide project code and pre‐trained models.

Model-based analysis and quality-by-design framework for high aspect ratio crystals in crystallizer-wet mill systems using GPU acceleration enabled optimization

The simultaneous control of crystal size and shape is particularly important in pharmaceutical crystallization processes. These two quantities not only influence the dissolution rate and bioavailability of final drug products, but also contribute to the manufacturability and efficiency of downstream operations. The manipulation of crystal shape, however, is difficult since it requires decoupled growth rate control of individual crystal faces. The aim of this work is to analyze and evaluate the effectiveness of wet milling for control of bivariate size distribution of high-aspect ratio crystals during solution crystallization. Three configurations are compared: the pure batch crystallizer, the crystallizer with internal wet mill (immersion mill) and crystallizer with external wet mill. Population balance models (PBMs) are employed to describe bivariate size density function dynamics, with stirring rate dependent breakage to enable the direct optimization of wet mill operation. The generated system of hyperbolic partial differential and ordinary differential equations is solved by a fully discretized high-resolution finite volume method (HR-FVM), involving graphical processing unit (GPU) acceleration, which brings up to two orders of magnitude speed-up by compared to the serial C implementation. The simulation studies revealed that wet milling significantly extends the achievable crystal size and shape domain, but it also broadens the product size distribution. The analysis of the optimized operating profiles, which include temperature, wet mill rotation (RPM) and recirculation rate, enabled the generalization of optimal operation, which can efficiently guide a QbD approach by considerably reducing the design space without compromising the process performance.