In this paper we discuss the transformation of a sheet of material into a wide range of desired shapes and patterns by introducing a set of simple cuts in a multilevel hierarchy with different ...motifs. Each choice of hierarchical cut motif and cut level allows the material to expand into a unique structure with a unique set of properties. We can reverse-engineer the desired expanded geometries to find the requisite cut pattern to produce it without changing the physical properties of the initial material. The concept was experimentally realized and applied to create an electrode that expands to >800% the original area with only very minor stretching of the underlying material. The generality of our approach greatly expands the design space for materials so that they can be tuned for diverse applications.
Entanglement is the key quantum resource for improving measurement sensitivity beyond classical limits. However, the production of entanglement in mesoscopic atomic systems has been limited to ...squeezed states, described by Gaussian statistics. Here, we report on the creation and characterization of non-Gaussian many-body entangled states. We develop a general method to extract the Fisher information, which reveals that the quantum dynamics of a classically unstable system creates quantum states that are not spin squeezed but nevertheless entangled. The extracted Fisher information quantifies metrologically useful entanglement, which we confirm by Bayesian phase estimation with sub–shot-noise sensitivity. These methods are scalable to large particle numbers and applicable directly to other quantum systems.
Phylogenetic signal is the tendency for closely related species to display similar trait values due to their common ancestry. Several methods have been developed for quantifying phylogenetic signal ...in univariate traits and for sets of traits treated simultaneously, and the statistical properties of these approaches have been extensively studied. However, methods for assessing phylogenetic signal in high-dimensional multivariate traits like shape are less well developed, and their statistical performance is not well characterized. In this article, I describe a generalization of the statistic of Blomberg et al. that is useful for quantifying and evaluating phylogenetic signal in highly dimensional multivariate data. The method (Kmult) is found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices. Using computer simulations based on Brownian motion, I demonstrate that the expected value of Kmult remains at 1.0 as trait variation among species is increased or decreased, and as the number of trait dimensions is increased. By contrast, estimates of phylogenetic signal found with a squared-change parsimony procedure for multivariate data change with increasing trait variation among species and with increasing numbers of trait dimensions, confounding biological interpretations. I also evaluate the statistical performance of hypothesis testing procedures based on and find that the method displays appropriate Type I error and high statistical power for detecting phylogenetic signal in highdimensional data. Statistical properties of Kmult were consistent for simulations using bifurcating and random phylogenies, for simulations using different numbers of species, for simulations that varied the number of trait dimensions, and for different underlying models of trait covariance structure. Overall these findings demonstrate that provides a useful means of evaluating phylogenetic signal in high-dimensional multivariate traits. Finally, I illustrate the utility of the new approach by evaluating the strength of phylogenetic signal for head shape in a lineage of Plethodon salamanders.
Simulation as an engine of physical scene understanding Battaglia, Peter W.; Hamrick, Jessica B.; Tenenbaum, Joshua B.
Proceedings of the National Academy of Sciences - PNAS,
11/2013, Letnik:
110, Številka:
45
Journal Article
Recenzirano
Odprti dostop
In a glance, we can perceive whether a stack of dishes will topple, a branch will support a child’s weight, a grocery bag is poorly packed and liable to tear or crush its contents, or a tool is ...firmly attached to a table or free to be lifted. Such rapid physical inferences are central to how people interact with the world and with each other, yet their computational underpinnings are poorly understood. We propose a model based on an “intuitive physics engine,” a cognitive mechanism similar to computer engines that simulate rich physics in video games and graphics, but that uses approximate, probabilistic simulations to make robust and fast inferences in complex natural scenes where crucial information is unobserved. This single model fits data from five distinct psychophysical tasks, captures several illusions and biases, and explains core aspects of human mental models and common-sense reasoning that are instrumental to how humans understand their everyday world.
Computational imaging enables retrieval of the spatial information of an object with the use of single-pixel detectors. By projecting a series of known random patterns and measuring the backscattered ...intensity, it is possible to reconstruct a two-dimensional (2D) image. We used several single-pixel detectors in different locations to capture the 3D form of an object. From each detector we derived a 2D image that appeared to be illuminated from a different direction, even though only a single digital projector was used for illumination. From the shading of the images, the surface gradients could be derived and the 3D object reconstructed. We compare our result to that obtained from a stereophotogrammetric system using multiple cameras. Our simplified approach to 3D imaging can readily be extended to nonvisible wavebands.
Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shape and surface properties ...remains, however, challenging. Most current designs are based on the multifingered hand, but this approach introduces hardware and software complexities. These include large numbers of controllable joints, the need for force sensing if objects are to be handled securely without crushing them, and the computational overhead to decide how much stress each finger should apply and where. Here we demonstrate a completely different approach to a universal gripper. Individual fingers are replaced by a single mass of granular material that, when pressed onto a target object, flows around it and conforms to its shape. Upon application of a vacuum the granular material contracts and hardens quickly to pinch and hold the object without requiring sensory feedback. We find that volume changes of less than 0.5% suffice to grip objects reliably and hold them with forces exceeding many times their weight. We show that the operating principle is the ability of granular materials to transition between an unjammed, deformable state and a jammed state with solid-like rigidity. We delineate three separate mechanisms, friction, suction, and interlocking, that contribute to the gripping force. Using a simple model we relate each of them to the mechanical strength of the jammed state. This advance opens up new possibilities for the design of simple, yet highly adaptive systems that excel at fast gripping of complex objects.
In vacuum, air, and other surroundings that support ballistic light propagation according to Maxwell's equations, invisibility cloaks that are macroscopic, three-dimensional, broadband, passive, and ...that work for all directions and polarizations of light are not consistent with the laws of physics. We show that the situation is different for surroundings leading to multiple light scattering, according to Fick's diffusion equation. We have fabricated cylindrical and spherical invisibility cloaks made of thin shells of polydimethylsiloxane doped with melamine-resin microparticles. The shells surround a diffusively reflecting hollow core, in which arbitrary objects can be hidden. We find good cloaking performance in a water-based diffusive surrounding throughout the entire visible spectrum and for all illumination conditions and incident polarizations of light.
Marine debris is recognized as an important global issue that can negatively affect wildlife, habitats, environmental processes, ecosystem services, and human activities including tourism, fishing, ...and navigation. To improve understanding of the sources and impacts of marine debris, we carried out a national litter survey at 175 sites around Australia using a stratified random sampling approach. Litter from land-and sea-based sources is ubiquitous, and sampling effects related to coastline shape, substrate characteristics, gradient, and backshore type were highly significant. Source effects related to land-based sources (eg population density and distance to road) were also highly significant. Of the total debris sampled, approximately 75% was plastic; 2% was related to recreational fishing. Litter density significantly increased with proximity to urban areas, suggesting a domestic origin; statistical patterns suggest that illegal rubbish disposal is a major driver. By quantifying debris at a large scales and distinguishing potential litter sources, we can better develop scale-appropriate solutions to reduce debris inputs to the environment.
We describe a simple and robust method to construct complex three-dimensional (3D) structures by using short synthetic DNA strands that we call "DNA bricks." In one-step annealing reactions, bricks ...with hundreds of distinct sequences self-assemble into prescribed 3D shapes. Each 32-nucleotide brick is a modular component; it binds to four local neighbors and can be removed or added independently. Each 8-base pair interaction between bricks defines a voxel with dimensions of 2.5 by 2.5 by 2.7 nanometers, and a master brick collection defines a "molecular canvas" with dimensions of 10 by 10 by 10 voxels. By selecting subsets of bricks from this canvas, we constructed a panel of 102 distinct shapes exhibiting sophisticated surface features, as well as intricate interior cavities and tunnels.
Quantifying integration and modularity of evolutionary changes in morphometric traits is crucial for understanding how organismal shapes evolve. For this purpose, comparative studies are necessary, ...which need to take into account the phylogenetic structure of interspecific data. This study applies several of the standard tools of geometric morphometrics, which mostly have been used in intraspecific studies, in the new context of analyzing integration and modularity based on comparative data. Morphometric methods such as principal component analysis, multivariate regression, partial least squares, and modularity tests can be applied to phylogenetically independent contrasts of shape data. We illustrate this approach in an analysis of cranial evolution in 160 species from all orders of birds. Mapping the shape information onto the phylogeny indicates that there is a significant phylogenetic signal in skull shape. Multivariate regression of independent contrasts of shape on independent contrasts of size reveals clear evolutionary allometry. Regardless of whether or not a correction for allometry is used, evolutionary integration between the face and braincase is strong, and tests reject the hypothesis that the face and braincase are separate evolutionary modules. These analyses can easily be applied to other taxa and can be combined with other morphometric tools to address a wide range of questions about evolutionary patterns and processes.
PDF
