Investigation of hindwing folding in ladybird beetles by artificial elytron transplantation and microcomputed tomography
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 3 years ago
Ladybird beetles are high-mobility insects and explore broad areas by switching between walking and flying. Their excellent wing transformation systems enabling this lifestyle are expected to provide large potential for engineering applications. However, the mechanism behind the folding of their hindwings remains unclear. The reason is that ladybird beetles close the elytra ahead of wing folding, preventing the observation of detailed processes occurring under the elytra. In the present study, artificial transparent elytra were transplanted on living ladybird beetles, thereby enabling us to observe the detailed wing-folding processes. The result revealed that in addition to the abdominal movements mentioned in previous studies, the edge and ventral surface of the elytra, as well as characteristic shaped veins, play important roles in wing folding. The structures of the wing frames enabling this folding process and detailed 3D shape of the hindwing were investigated using microcomputed tomography. The results showed that the tape spring-like elastic frame plays an important role in the wing transformation mechanism. Compared with other beetles, hindwings in ladybird beetles are characterized by two seemingly incompatible properties: (i) the wing rigidity with relatively thick veins and (ii) the compactness in stored shapes with complex crease patterns. The detailed wing-folding process revealed in this study is expected to facilitate understanding of the naturally optimized system in this excellent deployable structure.
Reconfigurable devices, whose shape can be drastically altered, are central to expandable shelters, deployable space structures, reversible encapsulation systems and medical tools and robots. All these applications require structures whose shape can be actively controlled, both for deployment and to conform to the surrounding environment. While most current reconfigurable designs are application specific, here we present a mechanical metamaterial with tunable shape, volume and stiffness. Our approach exploits a simple modular origami-like design consisting of rigid faces and hinges, which are connected to form a periodic structure consisting of extruded cubes. We show both analytically and experimentally that the transformable metamaterial has three degrees of freedom, which can be actively deformed into numerous specific shapes through embedded actuation. The proposed metamaterial can be used to realize transformable structures with arbitrary architectures, highlighting a robust strategy for the design of reconfigurable devices over a wide range of length scales.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 2 years ago
How do humans learn to trust unfamiliar others? Decisions in the absence of direct knowledge rely on our ability to generalize from past experiences and are often shaped by the degree of similarity between prior experience and novel situations. Here, we leverage a stimulus generalization framework to examine how perceptual similarity between known individuals and unfamiliar strangers shapes social learning. In a behavioral study, subjects play an iterative trust game with three partners who exhibit highly trustworthy, somewhat trustworthy, or highly untrustworthy behavior. After learning who can be trusted, subjects select new partners for a second game. Unbeknownst to subjects, each potential new partner was parametrically morphed with one of the three original players. Results reveal that subjects prefer to play with strangers who implicitly resemble the original player they previously learned was trustworthy and avoid playing with strangers resembling the untrustworthy player. These decisions to trust or distrust strangers formed a generalization gradient that converged toward baseline as perceptual similarity to the original player diminished. In a second imaging experiment we replicate these behavioral gradients and leverage multivariate pattern similarity analyses to reveal that a tuning profile of activation patterns in the amygdala selectively captures increasing perceptions of untrustworthiness. We additionally observe that within the caudate adaptive choices to trust rely on neural activation patterns similar to those elicited when learning about unrelated, but perceptually familiar, individuals. Together, these findings suggest an associative learning mechanism efficiently deploys moral information encoded from past experiences to guide future choice.
Mechanical metamaterials exhibit unusual properties through the shape and movement of their engineered subunits. This work presents a new investigation of the Poisson’s ratios of a family of cellular metamaterials based on Kirigami design principles. Kirigami is the art of cutting and folding paper to obtain 3D shapes. This technique allows us to create cellular structures with engineered cuts and folds that produce large shape and volume changes, and with extremely directional, tuneable mechanical properties. We demonstrate how to produce these structures from flat sheets of composite materials. By a combination of analytical models and numerical simulations we show how these Kirigami cellular metamaterials can change their deformation characteristics. We also demonstrate the potential of using these classes of mechanical metamaterials for shape change applications like morphing structures.
Understanding the factors that influence the growth and final shape of noble metal nanostructures is important for controlling their properties. However, relative to their single-crystalline counterparts, the growth of nanoparticles that contain twin defects can be difficult to control because multiple competitive growth pathways can yield such structures. We used spherical, cubic, and octahedral single-crystalline gold nanoparticles as dual electron microscopy labels and plasmonic seeds to track the growth of multiply twinned silver nanostructures. As the bimetallic nanostructures grew, they successively developed twin planes to ultimately form multiply twinned nanoparticles from single-crystalline seeds. Collectively, these data demonstrate how a series of nanoparticles of different shapes and internal crystal structures are interrelated and develop from one another.
A general morphometric method for describing shape variation in a sample consisting of landmarks and multiple outline shapes is developed in this article. A distance metric is developed for such data and is used to embed the data in a low-dimensional Euclidean space. The Euclidean space is used to generate summary statistics such as mean and principal shape variation which are implicitly represented in the original space using elements of the sample. A new distance metric for outline shapes is proposed based on Procrustes distance that does not require the extraction of discrete points along the curve. The outline distance metric can be naturally combined with distances between landmarks. A method for aligning outlines and multiple outlines is developed that minimizes the distance metric. The method is compared with semilandmarks on synthetic data and 2 real data sets. Outline methods produce useful and valid results when suitably constrained by landmarks and are useful visualization aids, but questions remain about their suitability for answering biological questions until appropriate distance metrics can be biologically validated. [Morphometrics; outline analysis; semilandmark.].
Self-assembly enables nature to build complex forms, from multicellular organisms to complex animal structures such as flocks of birds, through the interaction of vast numbers of limited and unreliable individuals. Creating this ability in engineered systems poses challenges in the design of both algorithms and physical systems that can operate at such scales. We report a system that demonstrates programmable self-assembly of complex two-dimensional shapes with a thousand-robot swarm. This was enabled by creating autonomous robots designed to operate in large groups and to cooperate through local interactions and by developing a collective algorithm for shape formation that is highly robust to the variability and error characteristic of large-scale decentralized systems. This work advances the aim of creating artificial swarms with the capabilities of natural ones.
In this article, we consider how the broad context of Aboriginal people’s lives can shape their experience and understanding of their HIV diagnosis. We conducted interviews across Canada with 72 Aboriginal people living with HIV who also reported feelings of depression. Consistent with what has been found in previous studies, participants responded to their HIV diagnosis with shock, disbelief, and often anger. Prior depression, drug and alcohol use, multiple losses, stigma, and social isolation also shaped how participants experienced their diagnosis. We consider how the history of colonization of Aboriginal communities in Canada relates to the experience of HIV diagnosis, and end with a discussion of the service implications of our findings.
The assembly of artificial nanostructured and microstructured materials which display structures and functionalities that mimic nature’s complexity requires building blocks with specific and directional interactions, analogous to those displayed at the molecular level. Despite remarkable progress in synthesizing “patchy” particles encoding anisotropic interactions, most current methods are restricted to integrating up to two compositional patches on a single “molecule” and to objects with simple shapes. Currently, decoupling functionality and shape to achieve full compositional and geometrical programmability remains an elusive task. We use sequential capillarity-assisted particle assembly which uniquely fulfills the demands described above. This is a new method based on simple, yet essential, adaptations to the well-known capillary assembly of particles over topographical templates. Tuning the depth of the assembly sites (traps) and the surface tension of moving droplets of colloidal suspensions enables controlled stepwise filling of traps to “synthesize” colloidal molecules. After deposition and mechanical linkage, the colloidal molecules can be dispersed in a solvent. The template’s shape solely controls the molecule’s geometry, whereas the filling sequence independently determines its composition. No specific surface chemistry is required, and multifunctional molecules with organic and inorganic moieties can be fabricated. We demonstrate the “synthesis” of a library of structures, ranging from dumbbells and triangles to units resembling bar codes, block copolymers, surfactants, and three-dimensional chiral objects. The full programmability of our approach opens up new directions not only for assembling and studying complex materials with single-particle-level control but also for fabricating new microscale devices for sensing, patterning, and delivery applications.
Ceria nanoparticles (nanoceria) are well known as a superoxide scavenger. However, inherent superoxide-scavenging ability has only been found in the nanoceria with sizes of less than 5 nm and with very limited shape diversity. Reported herein is a strategy to significantly improve the superoxide-scavenging activity of nanoceria sized at greater than 5 nm. The nanoceria with sizes of greater than 5 nm, with different shapes, and with a negligible Ce(3+) /Ce(4+) ratio can acquire remarkable superoxide-scavenging abilities through electron transfer. This method will make it possible to develop nanoceria-based superoxide-scavengers with long-acting activity and tailorable characteristics.