Method for measurement of lattice parameter of cubic GaN layers on GaAs (001)

An extended technique derived from triple-axis diffraction setup was proposed to measure lattice parameters of cubic GaN(c-GaN) films. The fully relaxed lattice parameters of c-GaN are determined to be 4.5036+0.0004 Angstrom, which is closer to the values of a hypothetical perfect crystal. The speculated zero setting correction (Deltatheta) is very slight and within the range of the accuracy of measurement. Additionally, we applied this method to analyze strain of four different kinds of c-GaN samples. It is found that in-plane strain caused by large lattice mismatch and thermal expansion coefficients mismatch directly influence the epilayer growth at high temperatures, indicating that the relaxation of tensile strain after thermal annealing helps to improve the crystalline quality of c-GaN films and optical properties. (C) 2003 Elsevier Science B.V. All rights reserved.

Low-temperature (10 K) infrared measurement of interstitial oxygen in heavily antimony-doped silicon via wafer thinning

A new technique is reported for the rapid determination of interstitial oxygen in heavily Sb-doped silicon. This technique includes wafer thinning and low-temperature 10 K infrared measurement on highly thinned wafers. The fine structure of the interstitial oxygen absorption band around 1136 cm(-1) is obtained. Our results show that this method efficiently reduces free-carrier absorption interference, allowing a high reliability of measurement, and can be used at resistivities down to 1 x 10(-2) Omega cm for heavily Sb-doped silicon.

Improved digital processing method used for image motion measurement based on hybrid opto-digital joint transform correlator

Hybrid opto-digital joint transform correlator (HODJTC) is effective for image motion measurement, but it is different from the traditional joint transform correlator because it only has one optical transform and the joint power spectrum is directly input into a digital processing unit to compute the image shift. The local cross-correlation image can be directly obtained by adopting a local Fourier transform operator. After the pixel-level location of cross-correlation peak is initially obtained, the up-sampling technique is introduced to relocate the peak in even higher accuracy. With signal-to-noise ratio >= 20 dB, up-sampling factor k >= 10 and the maximum image shift <= 60 pixels, the root-mean-square error of motion measurement accuracy can be controlled below 0.05 pixels.

Reducing Drifts in the Inertial Measurements of Wrist and Elbow Positions

In this paper, we present an inertial-sensor-based monitoring system for measuring the movement of human upper limbs. Two wearable inertial sensors are placed near the wrist and elbow joints, respectively. The measurement drift in segment orientation is dramatically reduced after a Kalman filter is applied to estimate inclinations using accelerations and turning rates from gyroscopes. Using premeasured lengths of the upper and lower arms, we compute the position of the wrist and elbow joints via a proposed kinematic model. Experimental results demonstrate that this new motion capture system, in comparison to an optical motion tracker, possesses an RMS position error of less than 0.009 m, with a drift of less than 0.005 ms-1 in five daily activities. In addition, the RMS angle error is less than 3??. This indicates that the proposed approach has performed well in terms of accuracy and reliability.

How long is a piece of Strix? Methods in measuring and measuring the measurers

An experiment to quantify intra- and interobserver error in anatomical measurements found that interobserver measurements can vary by over 14% of mean specimen length; disparity in measurement increases logarithmically with the number of contributors; instructions did not reduce variation or measurement disparity; scale of the specimen influenced the precision of measurement (relative error increasing with specimen size); different methods of taking a measurement yielded different results, although they did not differ in terms of precision, and topographical complexity of the elements being considered may potentially influence error (error increasing with complexity). These results highlight concerns about introduction of noise and potential bias that should be taken into account when compiling composite datasets and meta-analyses.

Optimizing the efficiency of the sub-map technique for large-scale simultaneous localization and mapping

A technique for optimizing the efficiency of the sub-map method for large-scale simultaneous localization and mapping (SLAM) is proposed. It optimizes the benefits of the sub-map technique to improve the accuracy and consistency of an extended Kalman filter (EKF)-based SLAM. Error models were developed and engaged to investigate some of the outstanding issues in employing the sub-map technique in SLAM. Such issues include the size (distance) of an optimal sub-map, the acceptable error effect caused by the process noise covariance on the predictions and estimations made within a sub-map, when to terminate an existing sub-map and start a new one and the magnitude of the process noise covariance that could produce such an effect. Numerical results obtained from the study and an error-correcting process were engaged to optimize the accuracy and convergence of the Invariant Information Local Sub-map Filter previously proposed. Applying this technique to the EKF-based SLAM algorithm (a) reduces the computational burden of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. A Monte Carlo analysis of the system is presented as a means of demonstrating the consistency and efficacy of the proposed technique.

Heritability of refractive error and familial aggregation of myopia in an elderly American population.

PURPOSE: To determine the heritability of refractive error and the familial aggregation of myopia in an older population. METHODS: Seven hundred fifty-nine siblings (mean age, 73.4 years) in 241 families were recruited from the Salisbury Eye Evaluation (SEE) Study in eastern Maryland. Refractive error was determined by noncycloplegic subjective refraction (if presenting distance visual acuity was < or =20/40) or lensometry (if best corrected visual acuity was >20/40 with spectacles). Participants were considered plano (refractive error of zero) if uncorrected visual acuity was >20/40. Preoperative refraction from medical records was used for pseudophakic subjects. Heritability of refractive error was calculated with multivariate linear regression and was estimated as twice the residual between-sibling correlation after adjusting for age, gender, and race. Logistic regression models were used to estimate the odds ratio (OR) of myopia, given a myopic sibling relative to having a nonmyopic sibling. RESULTS: The estimated heritability of refractive error was 61% (95% confidence interval [CI]: 34%-88%) in this population. The age-, race-, and sex-adjusted ORs of myopia were 2.65 (95% CI: 1.67-4.19), 2.25 (95% CI: 1.31-3.87), 3.00 (95% CI: 1.56-5.79), and 2.98 (95% CI: 1.51-5.87) for myopia thresholds of -0.50, -1.00, -1.50, and -2.00 D, respectively. Neither race nor gender was significantly associated with an increased risk of myopia. CONCLUSIONS: Refractive error and myopia are highly heritable in this elderly population.

Prevalence and determinants of spectacle nonwear among rural Chinese secondary schoolchildren: the Xichang Pediatric Refractive Error Study Report 3.

OBJECTIVE: To study spectacle wear among rural Chinese children. METHODS: Visual acuity, refraction, spectacle wear, and visual function were measured. RESULTS: Among 1892 subjects (84.7% of the sample), the mean (SD) age was 14.7 (0.8) years. Among 948 children (50.1%) potentially benefiting from spectacle wear, 368 (38.8%) did not own them. Among 580 children owning spectacles, 17.9% did not wear them at school. Among 476 children wearing spectacles, 25.0% had prescriptions that could not improve their visual acuity to better than 6/12. Therefore, 62.3% (591 of 948) of children needing spectacles did not benefit from appropriate correction. Children not owning and not wearing spectacles had better self-reported visual function but worse visual acuity at initial examination than children wearing spectacles and had a mean (SD) refractive error of -2.06 (1.15) diopter (D) and -2.78 (1.32) D, respectively. Girls (P < .001) and older children (P = .03) were more likely to be wearing their spectacles. A common reason for nonwear (17.0%) was the belief that spectacles weaken the eyes. Among children without spectacles, 79.3% said their families would pay for them (mean, US $15). CONCLUSIONS: Although half of the children could benefit from spectacle wear, 62.3% were not wearing appropriate correction. These children have significant uncorrected refractive errors. There is potential to support programs through spectacle sales.

Measurement Quality in Indicators of Compositions: a Compositional Multitrait-Multimethod Approach

Compositional data, also called multiplicative ipsative data, are common in survey research instruments in areas such as time use, budget expenditure and social networks. Compositional data are usually expressed as proportions of a total, whose sum can only be 1. Owing to their constrained nature, statistical analysis in general, and estimation of measurement quality with a confirmatory factor analysis model for multitrait-multimethod (MTMM) designs in particular are challenging tasks. Compositional data are highly non-normal, as they range within the 0-1 interval. One component can only increase if some other(s) decrease, which results in spurious negative correlations among components which cannot be accounted for by the MTMM model parameters. In this article we show how researchers can use the correlated uniqueness model for MTMM designs in order to evaluate measurement quality of compositional indicators. We suggest using the additive log ratio transformation of the data, discuss several approaches to deal with zero components and explain how the interpretation of MTMM designs di ers from the application to standard unconstrained data. We show an illustration of the method on data of social network composition expressed in percentages of partner, family, friends and other members in which we conclude that the faceto-face collection mode is generally superior to the telephone mode, although primacy e ects are higher in the face-to-face mode. Compositions of strong ties (such as partner) are measured with higher quality than those of weaker ties (such as other network members)

A cross-calibration of chlorine isotopic measurements and suitability of seawater as the international reference material

A collection of 24 seawaters from various worldwide locations and differing depth was culled to measure their chlorine isotopic composition (delta(37)Cl). These samples cover all the oceans and large seas: Atlantic, Pacific, Indian and Antarctic oceans, Mediterranean and Red seas. This collection includes nine seawaters from three depth profiles down to 4560 mbsl. The standard deviation (2sigma) of the delta(37)Cl of this collection is +/-0.08 parts per thousand, which is in fact as large as our precision of measurement ( +/- 0.10 parts per thousand). Thus, within error, oceanic waters seem to be an homogeneous reservoir. According to our results, any seawater could be representative of Standard Mean Ocean Chloride (SMOC) and could be used as a reference standard. An extended international cross-calibration over a large range of delta(37)Cl has been completed. For this purpose, geological fluid samples of various chemical compositions and a manufactured CH3Cl gas sample, with delta(37)Cl from about -6 parts per thousand to +6 parts per thousand have been compared. Data were collected by gas source isotope ratio mass spectrometry (IRMS) at the Paris, Reading and Utrecht laboratories and by thermal ionization mass spectrometry (TIMS) at the Leeds laboratory. Comparison of IRMS values over the range -5.3 parts per thousand to +1.4 parts per thousand plots on the Y=X line, showing a very good agreement between the three laboratories. On 11 samples, the trend line between Paris and Reading Universities is: delta(37)Cl(Reading)= (1.007 +/- 0.009)delta(37)Cl(Paris) - (0.040 +/- 0.025), with a correlation coefficient: R-2 = 0.999. TIMS values from Leeds University have been compared to IRMS values from Paris University over the range -3.0 parts per thousand to +6.0 parts per thousand. On six samples, the agreement between these two laboratories, using different techniques is good: delta(37)Cl(Leeds)=(1.052 +/- 0.038)delta(37)Cl(Paris) + (0.058 +/- 0.099), with a correlation coefficient: R-2 = 0.995. The present study completes a previous cross-calibration between the Leeds and Reading laboratories to compare TIMS and IRMS results (Anal. Chem. 72 (2000) 2261). Both studies allow a comparison of IRMS and TIMS techniques between delta(37)Cl values from -4.4 parts per thousand to +6.0 parts per thousand and show a good agreement: delta(37)Cl(TIMS)=(1.039 +/- 0.023)delta(37)Cl(IRMS)+(0.059 +/- 0.056), with a correlation coefficient: R-2 = 0.996. Our study shows that, for fluid samples, if chlorine isotopic compositions are near 0 parts per thousand, their measurements either by IRMS or TIMS will give comparable results within less than +/- 0.10 parts per thousand, while for delta(37)Cl values as far as 10 parts per thousand (either positive or negative) from SMOC, both techniques will agree within less than +/- 0.30 parts per thousand. (C) 2004 Elsevier B.V. All rights reserved.

Spatial analysis of the error in a model of soil nitrogen

Models of the dynamics of nitrogen in soil (soil-N) can be used to aid the fertilizer management of a crop. The predictions of soil-N models can be validated by comparison with observed data. Validation generally involves calculating non-spatial statistics of the observations and predictions, such as their means, their mean squared-difference, and their correlation. However, when the model predictions are spatially distributed across a landscape the model requires validation with spatial statistics. There are three reasons for this: (i) the model may be more or less successful at reproducing the variance of the observations at different spatial scales; (ii) the correlation of the predictions with the observations may be different at different spatial scales; (iii) the spatial pattern of model error may be informative. In this study we used a model, parameterized with spatially variable input information about the soil, to predict the mineral-N content of soil in an arable field, and compared the results with observed data. We validated the performance of the N model spatially with a linear mixed model of the observations and model predictions, estimated by residual maximum likelihood. This novel approach allowed us to describe the joint variation of the observations and predictions as: (i) independent random variation that occurred at a fine spatial scale; (ii) correlated random variation that occurred at a coarse spatial scale; (iii) systematic variation associated with a spatial trend. The linear mixed model revealed that, in general, the performance of the N model changed depending on the spatial scale of interest. At the scales associated with random variation, the N model underestimated the variance of the observations, and the predictions were correlated poorly with the observations. At the scale of the trend, the predictions and observations shared a common surface. The spatial pattern of the error of the N model suggested that the observations were affected by the local soil condition, but this was not accounted for by the N model. In summary, the N model would be well-suited to field-scale management of soil nitrogen, but suited poorly to management at finer spatial scales. This information was not apparent with a non-spatial validation. (c),2007 Elsevier B.V. All rights reserved.

Flux comparison of Eulerian and Lagrangian estimates of Agulhas leakage: A case study using a numerical model

Estimating the magnitude of Agulhas leakage, the volume flux of water from the Indian to the Atlantic Ocean, is difficult because of the presence of other circulation systems in the Agulhas region. Indian Ocean water in the Atlantic Ocean is vigorously mixed and diluted in the Cape Basin. Eulerian integration methods, where the velocity field perpendicular to a section is integrated to yield a flux, have to be calibrated so that only the flux by Agulhas leakage is sampled. Two Eulerian methods for estimating the magnitude of Agulhas leakage are tested within a high-resolution two-way nested model with the goal to devise a mooring-based measurement strategy. At the GoodHope line, a section halfway through the Cape Basin, the integrated velocity perpendicular to that line is compared to the magnitude of Agulhas leakage as determined from the transport carried by numerical Lagrangian floats. In the first method, integration is limited to the flux of water warmer and more saline than specific threshold values. These threshold values are determined by maximizing the correlation with the float-determined time series. By using the threshold values, approximately half of the leakage can directly be measured. The total amount of Agulhas leakage can be estimated using a linear regression, within a 90% confidence band of 12 Sv. In the second method, a subregion of the GoodHope line is sought so that integration over that subregion yields an Eulerian flux as close to the float-determined leakage as possible. It appears that when integration is limited within the model to the upper 300 m of the water column within 900 km of the African coast the time series have the smallest root-mean-square difference. This method yields a root-mean-square error of only 5.2 Sv but the 90% confidence band of the estimate is 20 Sv. It is concluded that the optimum thermohaline threshold method leads to more accurate estimates even though the directly measured transport is a factor of two lower than the actual magnitude of Agulhas leakage in this model.

The evaluation of CloudSat and CALIPSO ice microphysical products using ground-based cloud radar and lidar observations

In this paper, the statistical properties of tropical ice clouds (ice water content, visible extinction, effective radius, and total number concentration) derived from 3 yr of ground-based radar–lidar retrievals from the U.S. Department of Energy Atmospheric Radiation Measurement Climate Research Facility in Darwin, Australia, are compared with the same properties derived using the official CloudSat microphysical retrieval methods and from a simpler statistical method using radar reflectivity and air temperature. It is shown that the two official CloudSat microphysical products (2B-CWC-RO and 2B-CWC-RVOD) are statistically virtually identical. The comparison with the ground-based radar–lidar retrievals shows that all satellite methods produce ice water contents and extinctions in a much narrower range than the ground-based method and overestimate the mean vertical profiles of microphysical parameters below 10-km height by over a factor of 2. Better agreements are obtained above 10-km height. Ways to improve these estimates are suggested in this study. Effective radii retrievals from the standard CloudSat algorithms are characterized by a large positive bias of 8–12 μm. A sensitivity test shows that in response to such a bias the cloud longwave forcing is increased from 44.6 to 46.9 W m−2 (implying an error of about 5%), whereas the negative cloud shortwave forcing is increased from −81.6 to −82.8 W m−2. Further analysis reveals that these modest effects (although not insignificant) can be much larger for optically thick clouds. The statistical method using CloudSat reflectivities and air temperature was found to produce inaccurate mean vertical profiles and probability distribution functions of effective radius. This study also shows that the retrieval of the total number concentration needs to be improved in the official CloudSat microphysical methods prior to a quantitative use for the characterization of tropical ice clouds. Finally, the statistical relationship used to produce ice water content from extinction and air temperature obtained by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is evaluated for tropical ice clouds. It is suggested that the CALIPSO ice water content retrieval is robust for tropical ice clouds, but that the temperature dependence of the statistical relationship used should be slightly refined to better reproduce the radar–lidar retrievals.