38 research outputs found

    Body mass index is a better indicator of body composition than weight-for-length at age 1 month

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    Objective: To assess whether body mass index (BMI) provides a better assessment of measured adiposity at age 1 month compared with weight-for-length (WFL). Study design: Participants were healthy term-born infants in the Infant Growth and Microbiome (n = 146) and the Baby Peas (n = 147) studies. Length, weight, and body composition by air displacement plethysmography were measured at 1 month. World Health Organization-based WFL and BMI z-scores were calculated. Within-cohort z-scores of percent fat-Z, fat mass-Z, fat mass/length 2 -Z, fat mass/length 3 -Z, fat-free mass-Z, and fat-free mass/length 2 -Z were calculated. Correlation and multiple linear regression (adjusted for birth weight) analyses tested the associations between body composition outcomes and BMI-Z vs WFL-Z. Quantile regression was used to test the stability of these associations across the distribution of body compositions. Results: The sample was 52% female and 56% African American. Accounting for birth weight, both BMI-Z and WFL-Z were strongly associated with fat mass-Z (coefficients 0.56 and 0.35, respectively), FM/L 2 -Z (0.73 and 0.51), and FM/L 3 -Z (0.79 and 0.58), with stronger associations for BMI-Z compared with WFL-Z (P <.05). Even after accounting statistically for birth weight, BMI-Z was persistently more strongly associated than WFL-Z with body composition outcomes across the distribution of body composition outcomes. Conclusions: We demonstrate in 2 distinct cohorts that BMI is a better indicator of adiposity in early infancy compared with WFL. Our findings support the preferred use of BMI for growth and nutritional status assessment in infancy. © 2018 Elsevier Inc

    State Variables for Engineers

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    Reduction of missile navigation errors by roll programming

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    Development of a Matlab/Simulink Tool to Facilitate System Analysis and Simulation via the Adjoint and Covariance Methods

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    The COVariance and ADjoint Analysis Tool (COVAD) is a specially designed software tool, written for the Matlab/Simulink environment, which allows the user the capability to carry out system analysis and simulation using the adjoint, covariance or Monte Carlo methods. This paper describes phase one of the COVAD evolution, which includes a user-friendly and flexible Graphical User Interface (GUI), a missile homing loop template, an adjoint construction module, a Monte Carlo simulation module and various analysis and plotting options. As an illustration, the application of the software to the preliminary analysis of a generic guided missile homing loop problem is included. The covariance analysis module is still under construction and will not be covered here. It is scheduled to appear in phase two of the COVAD development

    Optimal State Space Descriptions

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    Modern guidance law for high-order autopilot

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