For biomedical applications, such as targeted drug delivery and microsurgery, it is essential to develop a system of swimmers that can be propelled wirelessly in fluidic environments with good control. Here, we report the construction and operation of chiral colloidal propellers that can be navigated in water with micrometer-level precision using homogeneous magnetic fields. The propellers are made via nanostructured surfaces and can be produced in large numbers. The nanopropellers can carry chemicals, push loads, and act as local probes in rheological measurements.
We report what we believe to be the first realization of a computer-generated complex-valued hologram recorded in a single film of photoactive polymer. Complex-valued holograms give rise to a diffracted optical field with control over its amplitude and phase. The holograms are generated by a one-step direct laser writing process in which a spatial light modulator (SLM) is imaged onto a polymer film. Temporal modulation of the SLM during exposure controls both the strength of the induced birefringence and the orientation of the fast axis. We demonstrate that complex holograms can be used to impart arbitrary amplitude and phase profiles onto a beam and thereby open new possibilities in the control of optical beams.
While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.
The human visual system is able to recognize objects despite tremendous variation in their appearance on the retina resulting from variation in view, size, lighting, etc. This ability--known as "invariant" object recognition--is central to visual perception, yet its computational underpinnings are poorly understood. Traditionally, nonhuman primates have been the animal model-of-choice for investigating the neuronal substrates of invariant recognition, because their visual systems closely mirror our own. Meanwhile, simpler and more accessible animal models such as rodents have been largely overlooked as possible models of higher-level visual functions, because their brains are often assumed to lack advanced visual processing machinery. As a result, little is known about rodents' ability to process complex visual stimuli in the face of real-world image variation. In the present work, we show that rats possess more advanced visual abilities than previously appreciated. Specifically, we trained pigmented rats to perform a visual task that required them to recognize objects despite substantial variation in their appearance, due to changes in size, view, and lighting. Critically, rats were able to spontaneously generalize to previously unseen transformations of learned objects. These results provide the first systematic evidence for invariant object recognition in rats and argue for an increased focus on rodents as models for studying high-level visual processing.
Primates can easily identify visual objects over large changes in retinal position--a property commonly referred to as position "invariance." This ability is widely assumed to depend on neurons in inferior temporal cortex (IT) that can respond selectively to isolated visual objects over similarly large ranges of retinal position. However, in the real world, objects rarely appear in isolation, and the interplay between position invariance and the representation of multiple objects (i.e., clutter) remains unresolved. At the heart of this issue is the intuition that the representations of nearby objects can interfere with one another and that the large receptive fields needed for position invariance can exacerbate this problem by increasing the range over which interference acts. Indeed, most IT neurons' responses are strongly affected by the presence of clutter. While external mechanisms (such as attention) are often invoked as a way out of the problem, we show (using recorded neuronal data and simulations) that the intrinsic properties of IT population responses, by themselves, can support object recognition in the face of limited clutter. Furthermore, we carried out extensive simulations of hypothetical neuronal populations to identify the essential individual-neuron ingredients of a good population representation. These simulations show that the crucial neuronal property to support recognition in clutter is not preservation of response magnitude, but preservation of each neuron's rank-order object preference under identity-preserving image transformations (e.g., clutter). Because IT neuronal responses often exhibit that response property, while neurons in earlier visual areas (e.g., V1) do not, we suggest that preserving the rank-order object preference regardless of clutter, rather than the response magnitude, more precisely describes the goal of individual neurons at the top of the ventral visual stream.
We report electroluminescence (EL) measurements carried out on three-terminal devices incorporating individual n-type CdSe nanowires. Simultaneous optical and electrical measurements reveal that EL occurs near the contact between the nanowire and a positively biased electrode or drain. The surface potential profile, obtained by using Kelvin probe microscopy, shows an abrupt potential drop near the position of the EL spot, while the band profile obtained from scanning photocurrent microscopy indicates the existence of an n-type Schottky barrier at the interface. These observations indicate that light emission occurs through a hole leakage or an inelastic scattering induced by the rapid potential drop at the nanowire-electrode interface.
The aims of this study were to explore the hydrodynamic mechanism of Xenopus laevis swimming and to describe how hind limb kinematics shift to control swimming performance. Kinematics of the joints, feet and body were obtained from high speed video of X. laevis frogs (N=4) during swimming over a range of speeds. A blade element approach was used to estimate thrust produced by both translational and rotational components of foot velocity. Peak thrust from the feet ranged from 0.09 to 0.69 N across speeds ranging from 0.28 to 1.2 m s(-1). Among 23 swimming strokes, net thrust impulse from rotational foot motion was significantly higher than net translational thrust impulse, ranging from 6.1 to 29.3 N ms, compared with a range of -7.0 to 4.1 N ms from foot translation. Additionally, X. laevis kinematics were used as a basis for a forward dynamic anuran swimming model. Input joint kinematics were modulated to independently vary the magnitudes of foot translational and rotational velocity. Simulations predicted that maximum swimming velocity (among all of the kinematics patterns tested) requires that maximal translational and maximal rotational foot velocity act in phase. However, consistent with experimental kinematics, translational and rotational motion contributed unequally to total thrust. The simulation powered purely by foot translation reached a lower peak stroke velocity than the pure rotational case (0.38 vs 0.54 m s(-1)). In all simulations, thrust from the foot was positive for the first half of the power stroke, but negative for the second half. Pure translational foot motion caused greater negative thrust (70% of peak positive thrust) compared with pure rotational simulation (35% peak positive thrust) suggesting that translational motion is propulsive only in the early stages of joint extension. Later in the power stroke, thrust produced by foot rotation overcomes negative thrust (due to translation). Hydrodynamic analysis from X. laevis as well as forward dynamics give insight into the differential roles of translational and rotational foot motion in the aquatic propulsion of anurans, providing a mechanistic link between joint kinematics and swimming performance.
High spatial resolution imaging of material properties is an important task for the continued development of nanomaterials and studies of biological systems. Time-varying interaction forces between the vibrating tip and the sample in a tapping-mode atomic force microscope contain detailed information about the elastic, adhesive, and dissipative response of the sample. We report real-time measurement and analysis of the time-varying tip-sample interaction forces with recently introduced torsional harmonic cantilevers. With these measurements, high-resolution maps of elastic modulus, adhesion force, energy dissipation, and topography are generated simultaneously in a single scan. With peak tapping forces as low as 0.6 nN, we demonstrate measurements on blended polymers and self-assembled molecular architectures with feature sizes at 1, 10, and 500 nm. We also observed an elastic modulus measurement range of four orders of magnitude (1 MPa to 10 GPa) for a single cantilever under identical feedback conditions, which can be particularly useful for analyzing heterogeneous samples with largely different material components.
Pectin methyl esterases (PMEs) and their endogenous inhibitors are involved in the regulation of many processes in plant physiology, ranging from tissue growth and fruit ripening to parasitic plant haustorial formation and host invasion. Thus, control of PME activity is critical for enhancing our understanding of plant physiological processes and regulation. Here, we report on the identification of epigallocatechin gallate (EGCG), a green tea component, as a natural inhibitor for pectin methyl esterases. In a gel assay for PME activity, EGCG blocked esterase activity of pure PME as well as PME extracts from citrus and from parasitic plants. Fluorometric tests were used to determine the IC50 for a synthetic substrate. Molecular docking analysis of PME and EGCG suggests close interaction of EGCG with the catalytic cleft of PME. Inhibition of PME by the green tea compound, EGCG, provides the means to study the diverse roles of PMEs in cell wall metabolism and plant development. In addition, this study introduces the use of EGCG as natural product to be used in the food industry and agriculture.
Cells actively produce contractile forces for a variety of processes including cytokinesis and motility. Contractility is known to rely on myosin II motors which convert chemical energy from ATP hydrolysis into forces on actin filaments. However, the basic physical principles of cell contractility remain poorly understood. We reconstitute contractility in a simplified model system of purified F-actin, muscle myosin II motors, and alpha-actinin cross-linkers. We show that contractility occurs above a threshold motor concentration and within a window of cross-linker concentrations. We also quantify the pore size of the bundled networks and find contractility to occur at a critical distance between the bundles. We propose a simple mechanism of contraction based on myosin filaments pulling neighboring bundles together into an aggregated structure. Observations of this reconstituted system in both bulk and low-dimensional geometries show that the contracting gels pull on and deform their surface with a contractile force of approximately 1 microN, or approximately 100 pN per F-actin bundle. Cytoplasmic extracts contracting in identical environments show a similar behavior and dependence on myosin as the reconstituted system. Our results suggest that cellular contractility can be sensitively regulated by tuning the (local) activity of molecular motors and the cross-linker density and binding affinity.
Optical label-free detectors, such as the venerable surface plasmon resonance (SPR) sensor, are generally favored for their ability to obtain quantitative data on intermolecular binding. However, before the recent introduction of resonant microcavities that use whispering gallery mode (WGM) recirculation, sensitivity to single binding events had not materialized. Here we describe the enhancement mechanisms responsible for the extreme sensitivity of the WGM biosensor, review its current implementations and applications, and discuss its future possibilities.