Statistics of natural movements are reflected in motor errors.

Humans use their arms to engage in a wide variety of motor tasks during everyday life. However, little is known about the statistics of these natural arm movements. Studies of the sensory system have shown that the statistics of sensory inputs are key to determining sensory processing. We hypothesized that the statistics of natural everyday movements may, in a similar way, influence motor performance as measured in laboratory-based tasks. We developed a portable motion-tracking system that could be worn by subjects as they went about their daily routine outside of a laboratory setting. We found that the well-documented symmetry bias is reflected in the relative incidence of movements made during everyday tasks. Specifically, symmetric and antisymmetric movements are predominant at low frequencies, whereas only symmetric movements are predominant at high frequencies. Moreover, the statistics of natural movements, that is, their relative incidence, correlated with subjects' performance on a laboratory-based phase-tracking task. These results provide a link between natural movement statistics and motor performance and confirm that the symmetry bias documented in laboratory studies is a natural feature of human movement.

Biomimicking of natural cellular materials

The role that microstructure plays in the mechanical efficiency of natural cellular materials is examined here. The focus of this study is on elastic behaviour. Two natural materials with microstructures resistant to local bucking: plant stems and animal quills have also been examined.

Robust estimation of local genetic ancestry in admixed populations using a nonparametric Bayesian approach.

We present a new haplotype-based approach for inferring local genetic ancestry of individuals in an admixed population. Most existing approaches for local ancestry estimation ignore the latent genetic relatedness between ancestral populations and treat them as independent. In this article, we exploit such information by building an inheritance model that describes both the ancestral populations and the admixed population jointly in a unified framework. Based on an assumption that the common hypothetical founder haplotypes give rise to both the ancestral and the admixed population haplotypes, we employ an infinite hidden Markov model to characterize each ancestral population and further extend it to generate the admixed population. Through an effective utilization of the population structural information under a principled nonparametric Bayesian framework, the resulting model is significantly less sensitive to the choice and the amount of training data for ancestral populations than state-of-the-art algorithms. We also improve the robustness under deviation from common modeling assumptions by incorporating population-specific scale parameters that allow variable recombination rates in different populations. Our method is applicable to an admixed population from an arbitrary number of ancestral populations and also performs competitively in terms of spurious ancestry proportions under a general multiway admixture assumption. We validate the proposed method by simulation under various admixing scenarios and present empirical analysis results from a worldwide-distributed dataset from the Human Genome Diversity Project.

Self-assembled multilayer graphene oxide membrane and carbon nanotubes synthesized using a rare form of natural graphite

The fabrication of flexible multilayer graphene oxide (GO) membrane and carbon nanotubes (CNTs) using a rare form of high-purity natural graphite, vein graphite, is reported for the first time. Graphite oxide is synthesized using vein graphite following Hummer's method. By facilitating functionalized graphene sheets in graphite oxide to self-assemble, a multilayer GO membrane is fabricated. Electric arc discharge is used to synthesis CNTs from vein graphite. Both multilayer GO membrane and CNTs are investigated using microscopy and spectroscopy experiments, i.e., scanning electron microscopy (SEM), atomic force microscopy (AFM), high-resolution transmission electron microscopy (HRTEM), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis (TGA), core level photoelectron spectroscopy, and C K-edge X-ray absorption spectroscopy (NEXAFS), to characterize their structural and topographical properties. Characterization of vein graphite using different techniques reveals that it has a large number of crystallites, hence the large number of graphene sheets per crystallite, preferentially oriented along the (002) plane. NEXAFS and core level spectra confirm that vein graphite is highly crystalline and pure. Fourier transform infrared (FT-IR) and C 1s core level spectra show that oxygen functionalities (-C-OH, -CO,-C-O-C-) are introduced into the basal plane of graphite following chemical oxidation. Carbon nanotubes are produced from vein graphite through arc discharge without the use of any catalyst. HRTEM confirm that multiwalled carbon nanotube (MWNTs) are produced with the presence of some structure in the central pipe. A small percentage of single-walled nanotubes (SWNTs) are also produced simultaneously with MWNTs. Spectroscopic and microscopic data are further discussed here with a view to using vein graphite as the source material for the synthesis of carbon nanomaterials. © 2013 American Chemical Society.