Tracking of physical activity in young children

The purpose of this study was to determine whether physical activity behavior tracks during early childhood. Forty-seven children (22 males, 25 females) aged 3-4 yr at the beginning of the study were followed over a 3-yr period. Heart rates were measured at least 2 and up to 4 d . yr(-1) with a Quantum XL Telemetry heart rate monitor. Physical activity was quantified as the percentage of observed minutes between 3:00 and 6:00 p.m. during which heart rate was 50% or more above individual resting heart rate (PAHR-50 Index). Tracking of physical activity was analyzed using Pearson and Spearman correlations. Yearly PAHR-50 index tertiles were created and examined for percent agreement and Cohen's kappa. Repeated measures ANOVA was used to calculate the intraclass correlation coefficient across the 3 yr of the study. Spearman rank order correlations ranged from 0.57 to 0.66 (P < 0.0001). Percent agreement ranged from 49% to 62%. The intraclass R for the 3 yr was 0.81. It was concluded that physical activity behavior tends to track during early childhood.

Tracking of physical activity, physical inactivity, and health-related physical fitness in rural youth

This study examined the tracking of selected measures of physical activity, inactivity, and fitness in a cohort of rural youth. Students (N = 181, 54.7% female, 63.5% African American) completed test batteries during their fifth-(age = 10.7 +/- 0.7 years), sixth-, and seventh-grade years. The Previous Day Physical Activity Recall (PDPAR) was used to assess 30-min blocks of vigorous physical activity (VPA), moderate-to-vigorous physical activity (MVPA), TV watching and other sedentary activities, and estimated energy expenditure (EE). Fitness measures included the PWC 170 cycle ergometer test, strength tests, triceps skinfold thickness, and BMI. Intraclass correlation coefficients (ICCs) for VPA, MVPA, and after-school EE ranged from 0.63 to 0.78. ICCs ranged from 0.49 to 0.71 for measures of inactivity and from 0.78 to 0.82 for the fitness measures. These results indicate that measures of physical activity, inactivity, and physical fitness tend to track during the transition from elementary to middle school.

Field validation of controlled Monte Carlo data generation for statistical damage identification employing Mahalanobis squared distance

This article presents the field applications and validations for the controlled Monte Carlo data generation scheme. This scheme was previously derived to assist the Mahalanobis squared distance–based damage identification method to cope with data-shortage problems which often cause inadequate data multinormality and unreliable identification outcome. To do so, real-vibration datasets from two actual civil engineering structures with such data (and identification) problems are selected as the test objects which are then shown to be in need of enhancement to consolidate their conditions. By utilizing the robust probability measures of the data condition indices in controlled Monte Carlo data generation and statistical sensitivity analysis of the Mahalanobis squared distance computational system, well-conditioned synthetic data generated by an optimal controlled Monte Carlo data generation configurations can be unbiasedly evaluated against those generated by other set-ups and against the original data. The analysis results reconfirm that controlled Monte Carlo data generation is able to overcome the shortage of observations, improve the data multinormality and enhance the reliability of the Mahalanobis squared distance–based damage identification method particularly with respect to false-positive errors. The results also highlight the dynamic structure of controlled Monte Carlo data generation that makes this scheme well adaptive to any type of input data with any (original) distributional condition.

Structural evolution of nanocrystalline silicon thin films synthesized in high-density, low-temperature reactive plasmas

Silicon thin films with a variable content of nanocrystalline phase were deposited on single-crystal silicon and glass substrates by inductively coupled plasma-assisted chemical vapor deposition using a silane precursor without any hydrogen dilution in the low substrate temperature range from 100 to 300 °C. The structural and optical properties of the deposited films are systematically investigated by Raman spectroscopy, x-ray diffraction, Fourier transform infrared absorption spectroscopy, UV/vis spectroscopy, scanning electron microscopy and high-resolution transmission electron microscopy. It is shown that the structure of the silicon thin films evolves from the purely amorphous phase to the nanocrystalline phase when the substrate temperature is increased from 100 to 150 °C. It is found that the variations of the crystalline fraction fc, bonded hydrogen content CH, optical bandgap ETauc, film microstructure and growth rate Rd are closely related to the substrate temperature. In particular, at a substrate temperature of 300 °C, the nanocrystalline Si thin films of our interest feature a high growth rate of 1.63nms-1, a low hydrogen content of 4.0at.%, a high crystalline fraction of 69.1%, a low optical bandgap of 1.55eV and an almost vertically aligned columnar structure with a mean grain size of approximately 10nm. It is also shown that the low-temperature synthesis of nanocrystalline Si thin films without any hydrogen dilution is attributed to the outstanding dissociation ability of the high-density inductively coupled plasmas and effective plasma-surface interactions during the growth process. Our results offer a highly effective yet simple and environmentally friendly technique to synthesize high-quality nanocrystalline Si films, vitally needed for the development of new-generation solar cells and other emerging nanotechnologies.

Evolution of Langmuir waves in a plasma contaminated by variable-charge impurities

The propagation of Langmuir waves in nonisothermal plasmas contaminated by fine dust particles with variable charge is investigated for a self-consistent closed system. Dust charge relaxation, ionization, recombination, and collisional dissipation are taken into account. It is shown that the otherwise unstable coupling of the Langmuir and dust-charge relaxation modes becomes stable and the Langmuir waves are frequency down-shifted.

Senataxin plays an essential role with DNA damage response proteins in meiotic recombination and gene silencing

Senataxin, mutated in the human genetic disorder ataxia with oculomotor apraxia type 2 (AOA2), plays an important role in maintaining genome integrity by coordination of transcription, DNA replication, and the DNA damage response. We demonstrate that senataxin is essential for spermatogenesis and that it functions at two stages in meiosis during crossing-over in homologous recombination and in meiotic sex chromosome inactivation (MSCI). Disruption of the Setx gene caused persistence of DNA double-strand breaks, a defect in disassembly of Rad51 filaments, accumulation of DNA:RNA hybrids (R-loops), and ultimately a failure of crossing-over. Senataxin localised to the XY body in a Brca1-dependent manner, and in its absence there was incomplete localisation of DNA damage response proteins to the XY chromosomes and ATR was retained on the axial elements of these chromosomes, failing to diffuse out into chromatin. Furthermore persistence of RNA polymerase II activity, altered ubH2A distribution, and abnormal XY-linked gene expression in Setx⁻/⁻ revealed an essential role for senataxin in MSCI. These data support key roles for senataxin in coordinating meiotic crossing-over with transcription and in gene silencing to protect the integrity of the genome.

Hybrid polymer/metal nanoparticles with surface enhanced raman tracking for potential use in nanomedicine

This project was a preliminary step towards the development of novel methods for early stage cancer diagnosis and treatment. Diagnostic imaging agents with high Raman signal enhancement were developed based on tailored assemblies of gold nanoparticles, which demonstrated potential for non-invasive detection from deep under the skin surface. Specifically designed polymers were employed to assemble gold nanoparticles into controlled morphologies including dimers, nanochains, nanoplates, globular and core-satellite nanostructures. Our findings suggest that the Raman enhancement is strongly dependent on assembly morphology and can be tuned to adapt to the requirements of the diagnostic agent.

A Study of feature extraction algorithms for optical flow tracking

Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.

Data fusion and tracking with multiple UAVs

This chapter describes decentralized data fusion algorithms for a team of multiple autonomous platforms. Decentralized data fusion (DDF) provides a useful basis with which to build upon for cooperative information gathering tasks for robotic teams operating in outdoor environments. Through the DDF algorithms, each platform can maintain a consistent global solution from which decisions may then be made. Comparisons will be made between the implementation of DDF using two probabilistic representations. The first, Gaussian estimates and the second Gaussian mixtures are compared using a common data set. The overall system design is detailed, providing insight into the overall complexity of implementing a robust DDF system for use in information gathering tasks in outdoor UAV applications.

Molecular phylogeny, biogeography, and habitat preference evolution of marsupials

Marsupials exhibit great diversity in ecology and morphology. However, compared to their sister group, the placental mammals, our understanding of many aspects of marsupial evolution remains limited. We use 101 mitochondrial genomes and data from 26 nuclear loci to reconstruct a dated phylogeny including 97% of extant genera and 58% of modern marsupial species. This tree allows us to analyze the evolution of habitat preference and geographic distributions of marsupial species through time. We found a pattern of mesic-adapted lineages evolving to use more arid and open habitats, which is broadly consistent with regional climate and environmental change. However, contrary to the general trend, several lineages subsequently appear to have reverted from drier to more mesic habitats. Biogeographic reconstructions suggest that current views on the connectivity between Australia and New Guinea/Wallacea during the Miocene and Pliocene need to be revised. The antiquity of several endemic New Guinean clades strongly suggests a substantially older period of connection stretching back to the Middle Miocene, and implies that New Guinea was colonized by multiple clades almost immediately after its principal formation.