Design study of a device to simulate the dynamic environment encountered under condi- tions of reduced or zero gravity final report

Design study of reduced or zero gravity environment simulation devic

The longitudinal negative impact of early stressful events on emotional and physical well-being: The buffering role of cardiac vagal development

Early stressful events negatively affect emotional and physical well-being. Cardiac vagal tone (CVT), which is associated with better emotional and physical well-being, usually gradually increase in early childhood. Nonetheless, children's CVT developmental trajectories are greatly variable, such that CVT can increase or decrease across the years. The present study examines the longitudinal effects of early stressful events and the role of 4 years CVT developmental trajectory on children's emotional and physical well-being. Forty-two 4-year-old children were enrolled. Number of stressful events and resting electrocardiogram (ECG) were collected at T1. ECG was registered again after one (T2), two (T3) and three (T4) years. Children's emotional and physical well-being were assessed at T4 through the Child Health and Illness Profile – Child Edition (CHIP–CE). CVT development was calculated as the angular coefficient, reflecting the developmental trajectory of CVT across the four timepoints. Results yielded that higher experienced stressful events predicted poorer emotional and physical well-being after 4 years. The interaction between the number of stressful events and CVT development emerged on physical well-being. Early stressful events negatively affect long-term children's emotional and physical well-being while a positive CVT development seems to mitigate the negative effects of early stressful events on physical well-being

MaineCare Stage A Health Homes Year 1 Report: Implementation Findings and Baseline Analysis

In January 2013, Maine established Health Homes under federal authority pursuant to Section 2703 of the Affordable Care Act to improve care coordination for MaineCare members with chronic conditions. Stage A of the Health Homes initiative focuses on members with complex medical chronic conditions. Stage B, planned for early 2014, will focus on persons with severe and persistent mental health conditions and children with serious emotional disturbances. The Stage A demonstration builds off the State’s existing Maine multi-payer Patient Centered Medical Home (PCMH) Pilot project and Maine’s Medicare Advanced Primary Care Practice (MAPCP) Demonstration by providing add-on payments to primary care practices and strengthening the community care team (CCT) model to provide care management and social support services to high-need MaineCare patients. As part of the initiative, MaineCare commissioned the Muskie School of Public Service to evaluate this new model of care. This report presents evaluation findings after the first year of Stage A implementation and provides preliminary baseline data on quality, use and cost of care for eligible MaineCare members in Health Homes (HH) relative to a comparison group that will form the basis for assessing overall impact at the close of the two years of enhanced federal match under the initiative. The report is divided into two parts. Part I focuses on how the model has been implemented in Year 1 including the number of practices and members that are participating and how practices and Community Care Teams (CCTs) have enhanced service delivery based on program data and qualitative interviews with participating practices, CCTs and stakeholders. Part II presents baseline data from 2011, prior to the beginning of the Stage A, comparing the quality, utilization and cost of services for MaineCare members that are participating in Health Homes with members with similar HH eligible conditions that did not enroll in Health Homes. Preliminary baseline data included in this report will be updated and used in the final report to assess how quality, use and cost of MaineCare services changed over time in each of these groups, to evaluate the impact of the intervention

Monitoring Grassland Seasonal Carbon Dynamics, by Integrating MODIS NDVI, Proximal Optical Sampling, and Eddy Covariance Measurements

This study evaluated the seasonal productivity of a prairie grassland (Mattheis Ranch, in Alberta, Canada) using a combination of remote sensing, eddy covariance, and field sampling collected in 2012–2013. A primary objective was to evaluate different ways of parameterizing the light-use efficiency (LUE) model for assessing net ecosystem fluxes at two sites with contrasting productivity. Three variations on the NDVI (Normalized Difference Vegetation Index), differing by formula and footprint, were derived: (1) a narrow-band NDVI (NDVI680,800, derived from mobile field spectrometer readings); (2) a broad-band proxy NDVI (derived from an automated optical phenology station consisting of broad-band radiometers); and (3) a satellite NDVI (derived from MODIS AQUA and TERRA sensors). Harvested biomass, net CO2 flux, and NDVI values were compared to provide a basis for assessing seasonal ecosystem productivity and gap filling of tower flux data. All three NDVIs provided good estimates of dry green biomass and were able to clearly show seasonal changes in vegetation growth and senescence, confirming their utility as metrics of productivity. When relating fluxes and optical measurements, temporal aggregation periods were considered to determine the impact of aggregation on model accuracy. NDVI values from the different methods were also calibrated against fAPARgreen (the fraction of photosynthetically active radiation absorbed by green vegetation) values to parameterize the APARgreen (absorbed PAR) term of the LUE (light use efficiency) model for comparison with measured fluxes. While efficiency was assumed to be constant in the model, this analysis revealed hysteresis in the seasonal relationships between fluxes and optical measurements, suggesting a slight change in efficiency between the first and second half of the growing season. Consequently, the best results were obtained by splitting the data into two stages, a greening phase and a senescence phase, and applying separate fits to these two periods. By incorporating the dynamic irradiance regime, the model based on APARgreen rather than NDVI best captured the high variability of the fluxes and provided a more realistic depiction of missing fluxes. The strong correlations between these optical measurements and independently measured fluxes demonstrate the utility of integrating optical with flux measurements for gap filling, and provide a foundation for using remote sensing to extrapolate from the flux tower to larger regions (upscaling) for regional analysis of net carbon uptake by grassland ecosystems