Showing 1 - 20 results of 470 for search 'Houston Texans~', query time: 5.07s Refine Results
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    Nourishing change in Houston, Texas: exploring grocery shopping behaviours and fruit and vegetable consumption among low-income families in the Brighter Bites program by Victoria Kwentua, Allison Marshall, Ru-Jye Chuang, Jessica Chen, Christine Markham, Mallika Mathur, Mike Pomeroy, Megan Hall, Shreela Sharma

    Published 2025-01-01
    “… Abstract Objective: We qualitatively examine the grocery shopping behaviours and fruit and vegetable consumption of low-income families participating in the Brighter Bites program in Houston, Texas. Design: We used a single-group observational study design. …”
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    Plasmodium vivax Infection in Multiple Family Members in Texas, USA by Roukaya Al Hammoud, James R. Murphy, Michael L. Chang

    Published 2019-01-01
    “…We report a cluster of 6 pediatric residents of Houston, Texas, USA, who presented with Plasmodium vivax infection within an eight-week period. …”
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    Maximum ozone concentrations in the southwestern US and Texas: implications of the growing predominance of the background contribution by D. D. Parrish, I. C. Faloona, I. C. Faloona, R. G. Derwent

    Published 2025-01-01
    “…US anthropogenic emissions from urban and industrial sectors now produce only relatively modest enhancements to ODVs (less than <span class="inline-formula">∼</span> 6 ppb in 2020) outside of the three largest urban areas considered (Dallas, Houston and Los Angeles), where the 2020 enhancements were in the 17–30 ppb range. …”
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    Prediction of High-ozone Events Using GAM, SMOTE, and Tail Dependence Approaches in Texas (2005–2019) by Benjamin Brown-Steiner, Xiong Zhou, Matthew J. Alvarado, Brook T. Russell

    Published 2021-07-01
    “…Abstract We test three methods for ozone prediction in the El Paso (ELP) and Houston-Galveston-Brazoria (HGB) regions of Texas from 2005–2019: (1) a Generalized Additive Model (GAMs) approach; (2) a GAM approach with the addition of the Synthetic Minority Over-sampling TEchnique (SMOTE) and (3) a tail dependence modeling approach based in extreme value theory (EVT). …”
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    How do crime and neighborhood environment affect transit ridership? Evidence from five metropolitan cities in the Texas Triangle by Qian He, Jianling Li

    Published 2025-01-01
    “…Using stop-level transit ridership and service characteristics data from transit agencies in five metropolitan areas in the Texas Triangle (Austin, Dallas, Fort Worth, Houston, and San Antonio) in 2018, we find that although the crime rate is negatively associated with ridership, better transit service characteristics such as higher service frequency and shorter average headway are associated with higher ridership, based on results of the negative binomial regression model. …”
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