Academic literature on the topic 'Oregon. Executive Department'

James E. Meacham is a Senior Research Associate at the University of Oregon, and Executive Director and co-founder of the InfoGraphics Lab in the University’s Department of Geography. He received his MA in Geography from the UO in 1992, and has served as the president of NACIS. His interests include map and atlas design, and data visualization. He is a co-creator of the Atlas of Yellowstone (2012), Archaeology and Landscape in the Mongolian Altai: An Atlas (2010), and the Atlas of Oregon (2001). He teaches cartography courses at the University of Oregon. His current projects include the development of the Atlas of Wildlife Migration: Wyoming’s Ungulates.

Abstract To examine the impact from land model upgrades and different land initializations on the National Centers for Environmental Prediction (NCEP)’s Climate Forecast System (CFS), extensive T126 CFS experiments are carried out for 25 summers with 10 ensemble members using the old Oregon State University (OSU) land surface model (LSM) and the new Noah LSM. The CFS using the Noah LSM, initialized in turn with land states from the NCEP–Department of Energy Global Reanalysis 2 (GR-2), Global Land Data System (GLDAS), and GLDAS climatology, is compared to the CFS control run using the OSU LSM initialized with the GR-2 land states. Using anomaly correlation as a primary measure, the summer-season prediction skill of the CFS using different land models and different initial land states is assessed for SST, precipitation, and 2-m air temperature over the contiguous United States (CONUS) on an ensemble basis. Results from these CFS experiments indicate that upgrading from the OSU LSM to the Noah LSM improves the overall CONUS June–August (JJA) precipitation prediction, especially during ENSO neutral years. Such an enhancement in CFS performance requires the execution of a GLDAS with the very same Noah LSM as utilized in the land component of the CFS, while improper initializations of the Noah LSM using the GR-2 land states lead to degraded CFS performance. In comparison with precipitation, the land upgrades have a relatively small impact on both of the SST and 2-m air temperature predictions.

Abstract Objectives Nutrients and their metabolites have interactive qualities that may be harnessed for prevention of cognitive decline. Simultaneous modulation of one-carbon, fatty acid and vitamin D metabolism (25-OH-D) may offer neuroprotection. We examined whether n-3 polyunsaturated fatty acids (n-3 PUFA), 25-OH-D, and homocysteine (HCy) formed into a Nutritional Risk Index (NRI) can explain cognitive performance of older non-demented adults. Methods The NBAS enrolled older participants from the NIA-Layton Oregon Alzheimer's Disease Center aging studies with serum samples available yielding 306 cognitively characterized older adults. Plasma fatty acids were quantified by GC-FID and 25-hydroxyvitamin D and homocysteine by LC-MS/MS. Nutritional risk defined as population nutrient biomarker tertiles with NRI calculated as the number of nutrient biomarkers meeting a sub-optimum criterion with scores ranging from 0 to 3. Global and domain specific cognitive z-scores were fit with multivariate linear regression models and NRI as the primary exposure of interest. Results Mean age was 85.8 (7.6) years, MMSE was 27.8 (2.8) and 70% were female. Sixty-five % met criteria for ‘nutritional risk’ (NRI ³ 1: 193/293). Participants with optimum nutritional status exhibited superior global cognitive performance (NRI-0: mean global z-score ± SE = 0.10 ± 0.097) while each addition NRI point score associated with an incremental decrease in cognitive performance (NRI-1: 0.02 ± 0.09; NRI-2: −0.23 ± 0.13; NRI-3: −0.53 ± 0.19, P for trend = 0.002). Significant and similar trends were seen in specific cognitive domains, including attention (NRI-0: mean z-score ± SE = 0.20 ± 0.11; NRI-1: 0.02 ± 0.10; NRI-2: −0.32 ± 0.13; NRI-3: −0.38 ± 0.19, P for trend < 0.001) and executive function (NRI-0: mean z-score ± SE = 0.15 ± 0.10; NRI-1: −0.09 ± 0.10; NRI-2: −0.15 ± 0.13; NRI-3: −0.55 ± 0.20, P for trend = 0.002). Conclusions The Nutritional Risk Index representing plasma n-3 PUFA, 25-OH-D and HCy explains significant variance in the cognitive performance of older adults, particularly attention and executive skills. These results in exceptionally healthy older adults suggest that cognitive performance is superior in those with plasma EPA + DHA wt% ≥ 2.53, 25-OH-D ≥ 25 ng/ml, and HCy < 11.57 umol/L. Funding Sources Nestle Institute of Health Sciences, Hinda and Arthur Marcus Institute for Aging Research, NIA-Layton Aging & Alzheimer Disease Center, Department of Veterans Affairs.