Development and validation of GT3X accelerometer cut-off points in 5- to 9-year-old children based on indirect calorimetry measurements

The ActiGraph accelerometer is commonly used to measure physical activity in children. Count cut-off points are needed when using accelerometer data to determine the time a person spent in moderate or vigorous physical activity. For the GT3X accelerometer no cut-off points for young children have been published yet. The aim of the current study was thus to develop and validate count cut-off points for young children. Thirty-two children aged 5 to 9 years performed four locomotor and four play activities. Activity classification into the light-, moderate- or vigorous-intensity category was based on energy expenditure measurements with indirect calorimetry. Vertical axis as well as vector magnitude cut-off points were determined through receiver operating characteristic curve analyses with the data of two thirds of the study group and validated with the data of the remaining third. The vertical axis cut-off points were 133 counts per 5 sec for moderate to vigorous physical activity (MVPA), 193 counts for vigorous activity (VPA) corresponding to a metabolic threshold of 5 MET and 233 for VPA corresponding to 6 MET. The vector magnitude cut-off points were 246 counts per 5 sec for MVPA, 316 counts for VPA - 5 MET and 381 counts for VPA - 6 MET. When validated, the current cut-off points generally showed high recognition rates for each category, high sensitivity and specificity values and moderate agreement in terms of the Kappa statistic. These results were similar for vertical axis and vector magnitude cut-off points. The current cut-off points adequately reflect MVPA and VPA in young children. Cut-off points based on vector magnitude counts did not appear to reflect the intensity categories better than cut-off points based on vertical axis counts alone.

Sedimentology of ODP Leg 126 deep-water volcaniclastics

Three sites were drilled in the Izu-Bonin forearc basin during Ocean Drilling Program (ODP) Leg 126. High-quality formation microscanner (FMS) data from two of the sites provide images of part of a thick, volcaniclastic, middle to upper Oligocene, basin-plain turbidite succession. The FMS images were used to construct bed-by-bed sedimentary sections for the depth intervals 2232-2441 m below rig floor (mbrf) in Hole 792E, and 4023-4330 mbrf in Hole 793B. Beds vary in thickness from those that are near or below the resolution of the FMS tool (2.5 cm) to those that are 10-15 m thick. The bed thicknesses are distributed according to a power law with an exponent of about 1.0. There are no obvious upward thickening or thinning sequences in the bed-by-bed sections. Spaced packets of thick and very thick beds may be a response to (1) low stands of global sea level, particularly at 30 Ma, (2) periods of increased tectonic uplift, or (3) periods of more intense volcanism. Graded sandstones, most pebbly sandstones, and graded to graded-stratified conglomerates were deposited by turbidity currents. The very thick, mainly structureless beds of sandstone, pebbly sandstone, and pebble conglomerate are interpreted as sandy debris-flow deposits. Many of the sediment gravity flows may have been triggered by earthquakes. Long recurrence intervals of 0.3-1 m.y. for the very thickest beds are consistent with triggering by large-magnitude earthquakes (M = 9) with epicenters approximately 10-50 km away from large, unstable accumulations of volcaniclastic sand and ash on the flanks of arc volcanoes. Paleocurrents were obtained from the grain fabric of six thicker sandstone beds, and ripple migration directions in about 40 thinner beds; orientations were constrained by the FMS images. The data from ripples are very scattered and cannot be used to specify source positions. They do, however, indicate that the paleoenvironment was a basin plain where weaker currents were free to follow a broad range of flow paths. The data from sandstone fabric are more reliable and indicate that turbidity currents flowed toward 150? during the time period from 28.9 to 27.3 Ma. This direction is essentially along the axis of the forearc basin, from north to south, with a small component of flow away from the western margin of the basin.

Ripple migration directions and grain fabric measurements on ODP Hole 210-1276A sediments

Albian turbidites and intercalated shales were cored from ~1145 to 1700 meters below seafloor at Site 1276 in the Newfoundland Basin. Strata at this level dip ~2.5° seaward (toward an azimuth of ~130°) based on seismic profiles. In contrast, beds dip an average of ~10° in the cores. This higher apparent dip is the sum of the ~2.5° seaward dip and a measured hole deviation of 7.43°, which must be essentially in the same seaward direction. Using the maximum dip direction in the cores as a reference direction, paleocurrents were measured from 11 current-ripple foresets and 11 vector means of grain fabric in planar-laminated sandstones. Five of the planar-laminated sandstone samples have a grain imbrication 8°, permitting specification of a unique flow direction rather than just the line-of-motion of the current. Both ripples and grain fabric point to unconfined flow toward the north-northeast. There is considerable spread in the data so that some paleoflow indicators point toward the northwest, whereas others point southeast. Nevertheless, the overall pattern of paleoflow suggests a source for the turbidity currents on the southeastern Grand Banks, likely from the long-emergent Avalon Uplift in that area. On average, turbidity currents apparently flowed axially in the young Albian rift, toward the north. This is opposite to what might be expected for a northward-propagating rift and a young ocean opening in a zipperlike fashion from south to north.

Microstructure-based inherent anisotropy of asphalt mixtures

Asphalt mixtures have been demonstrated to be anisotropic materials in both laboratory and field tests. The anisotropy of asphalt mixtures consists of inherent anisotropy and stress-induced anisotropy. In previous work, the inherent anisotropy of asphalt mixtures was quantified by using only the inclination angles of the coarse aggregate particles in the asphalt mixtures. However, the inclination of fine aggregates also has a contribution to the inherent anisotropy. Moreover, the contribution to the inherent anisotropy of each aggregate may not be the same as in the previous work but will depend on the size, orientation, and sphericity of the aggregate particle. This paper quantifies the internal microstructure of the aggregates in asphalt mixtures by using an aggregate-related geometric parameter, the vector magnitude. The original formulation of the vector magnitude, which addresses only the orientation of coarse aggregates, is modified to account for not only the coarse aggregate orientation, but also the size, orientation, and sphericity of coarse and fine aggregates. This formulation is applied to cylindrical lab-mixed lab-compacted asphalt mixture specimens varying in asphalt binder type, air void content, and aging period. The vertical modulus and the horizontal modulus are also measured by using nondestructive tests. A relationship between the modified vector magnitude and the modulus ratio of the vertical modulus to the horizontal modulus is developed to quantify the influence of the inherent microstructure of the aggregates on the anisotropy of the mixtures. The modulus ratio is found to depend solely on the aggregate characteristics including the inclination angle, size, and sphericity, and it is independent of the asphalt binder type, air void content, and aging period. The inclination angle, itself, proves to be insufficient to quantify the inherent anisotropy of the asphalt mixtures. © 2011 American Society of Civil Engineers.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Bayesian estimation and selection of nonlinear vector error correction models: The case of the sugar-ethanol-oil nexus in Brazil

Nonlinear adjustment toward long-run price equilibrium relationships in the sugar-ethanol-oil nexus in Brazil is examined. We develop generalized bivariate error correction models that allow for cointegration between sugar, ethanol, and oil prices, where dynamic adjustments are potentially nonlinear functions of the disequilibrium errors. A range of models are estimated using Bayesian Monte Carlo Markov Chain algorithms and compared using Bayesian model selection methods. The results suggest that the long-run drivers of Brazilian sugar prices are oil prices and that there are nonlinearities in the adjustment processes of sugar and ethanol prices to oil price but linear adjustment between ethanol and sugar prices.

Does mixed frequency vector error correction model add relevant information to exchange misalignment calculus? Evidence for United States

Real exchange rate is an important macroeconomic price in the economy and a ects economic activity, interest rates, domestic prices, trade and investiments ows among other variables. Methodologies have been developed in empirical exchange rate misalignment studies to evaluate whether a real e ective exchange is overvalued or undervalued. There is a vast body of literature on the determinants of long-term real exchange rates and on empirical strategies to implement the equilibrium norms obtained from theoretical models. This study seeks to contribute to this literature by showing that it is possible to calculate the misalignment from a mixed ointegrated vector error correction framework. An empirical exercise using United States' real exchange rate data is performed. The results suggest that the model with mixed frequency data is preferred to the models with same frequency variables