Trends in Orange Juice Consumption and Nutrient Adequacy in Children 2003-2016

This study aimed to examine secular trends in 100% orange juice (OJ) consumption and trends in nutrient adequacy in children 2-18 years participating in the 2003-2016 National Health and Nutrition Examination Survey. The National Cancer Institute method was used to estimate the usual intake. Ten deciles of OJ consumption were determined based on intakes with non-consumers in the first decile. Nutrient adequacy was determined using the percentage below the Estimated Average Requirement (EAR) or the Adequate Intake (AI) percentage. Linear regression coefficients for changes in intake over time and across deciles of OJ were generated. Approximately 14% of the total sample consumed OJ with a mean intake of 40.0 g/d (77 KJ [0.9% of total energy intake]). Amounts of all 100% fruit juices consumed decreased by 44%, and whole fruit intake increased by approximately 32% from 2003-2016. Consumption of total energy, total carbohydrates, added sugars, and saturated fatty acids decreased. Intakes of folate, riboflavin, zinc, and vitamin C decreased from 2003-2016. The percentage of children below the EAR increased for vitamin C and zinc and decreased for vitamin A from 2003-2016. Percent of children above the AI increased for fiber. Across the deciles of OJ consumption, the percent of children with an inadequate vitamin D intake, calcium, iron, and phosphorus decreased. OJ and other 100% juices were major food sources of many nutrients consumed at levels below recommendations. One strategy to reduce inadequate intake of calcium, phosphorus, and potassium intake is to maintain or increase the consumption of OJ and other 100% juice

COLOR IMAGE DESATURATION USING SPARSE RECONSTRUCTION

In this paper, we propose an algorithm to estimate the true values of saturated pixels in color images. Pixel saturation occurs when at least one color channel is clipped at some value below the full dynamic range of the scene, resulting in a loss in image fidelity. The proposed algorithm is based on the assumptions that images are nearly sparse in an appropriate transform domain, and that saturated pixels can be inferred from the structure of non-saturated neighboring pixels. Consequently, we use a hierarchical windowing algorithm which selects image regions containing relatively few saturated pixels for processing. Starting with small sized regions, and progressively increasing the size, we solve a sparsity promoting constrained ℓ1 minimization problem for each selected region to recover the saturated pixels. Moreover, we provide simulation results to show the effectiveness of our algorithm. Index Terms — Color image desaturation, sparse signal reconstruction. 1