Cigarette smoking is associated with amplified age-related volume loss in subcortical brain regions

BACKGROUND: Magnetic resonance imaging studies of cigarette smoking-related effects on human brain structure have primarily employed voxel-based morphometry, and the most consistently reported finding was smaller volumes or lower density in anterior frontal regions and the insula. Much less is known about the effects of smoking on subcortical regions. We compared smokers and non-smokers on regional subcortical volumes, and predicted that smokers demonstrate greater age-related volume loss across subcortical regions than non-smokers. METHODS: Non-smokers (n=43) and smokers (n=40), 22-70 years of age, completed a 4T MRI study. Bilateral total subcortical lobar white matter (WM) and subcortical nuclei volumes were quantitated via FreeSurfer. In smokers, associations between smoking severity measures and subcortical volumes were examined. RESULTS: Smokers demonstrated greater age-related volume loss than non-smokers in the bilateral subcortical lobar WM, thalamus, and cerebellar cortex, as well as in the corpus callosum and subdivisions. In smokers, higher pack-years were associated with smaller volumes of the bilateral amygdala, nucleus accumbens, total corpus callosum and subcortical WM. CONCLUSIONS: Results provide novel evidence that chronic smoking in adults is associated with accelerated age-related volume loss in subcortical WM and GM nuclei. Greater cigarette quantity/exposure was related to smaller volumes in regions that also showed greater age-related volume loss in smokers. Findings suggest smoking adversely affected the structural integrity of subcortical brain regions with increasing age and exposure. The greater age-related volume loss in smokers may have implications for cortical-subcortical structural and/or functional connectivity, and response to available smoking cessation interventions

Optimization Of Fuzzy Evapotranspiration Model Through Neural Training With Input–Output Examples

In a previous study, we demonstrated that fuzzy evapotranspiration (ET) models can achieve accurate estimation of daily ET comparable to the FAO Penman–Monteith equation, and showed the advantages of the fuzzy approach over other methods. The estimation accuracy of the fuzzy models, however, depended on the shape of the membership functions and the control rules built by trial–and–error methods. This paper shows how the trial and error drawback is eliminated with the application of a fuzzy–neural system, which combines the advantages of fuzzy logic (FL) and artificial neural networks (ANN). The strategy consisted of fusing the FL and ANN on a conceptual and structural basis. The neural component provided supervised learning capabilities for optimizing the membership functions and extracting fuzzy rules from a set of input–output examples selected to cover the data hyperspace of the sites evaluated. The model input parameters were solar irradiance, relative humidity, wind speed, and air temperature difference. The optimized model was applied to estimate reference ET using independent climatic data from the sites, and the estimates were compared with direct ET measurements from grass–covered lysimeters and estimations with the FAO Penman–Monteith equation. The model–estimated ET vs. lysimeter–measured ET gave a coefficient of determination (r2) value of 0.88 and a standard error of the estimate (Syx) of 0.48 mm d–1. For the same set of independent data, the FAO Penman–Monteith–estimated ET vs. lysimeter–measured ET gave an r2 value of 0.85 and an Syx value of 0.56 mm d–1. These results show that the optimized fuzzy–neural–model is reasonably accurate, and is comparable to the FAO Penman–Monteith equation. This approach can provide an easy and efficient means of tuning fuzzy ET models

Report of the panel on earth structure and dynamics, section 6

The panel identified problems related to the dynamics of the core and mantle that should be addressed by NASA programs. They include investigating the geodynamo based on observations of the Earth's magnetic field, determining the rheology of the mantle from geodetic observations of post-glacial vertical motions and changes in the gravity field, and determining the coupling between plate motions and mantle flow from geodetic observations of plate deformation. Also emphasized is the importance of support for interdisciplinary research to combine various data sets with models which couple rheology, structure and dynamics

Calculation of Turbulent Subsonic Diffuser Flows Using the NPARC Navier-Stokes Code

Axisymmetric subsonic diffuser flows were calculated with the NPARC Navier-Stokes code in order to determine the effects various code features have on the flow solutions. The code features examined in this work were turbulence models and boundary conditions. Four turbulence models available in NPARC were used: the Baldwin-Lomax algebraic model, the Baldwin-Barth one-equation model, and the Chien kappa-epsilon and Wilcox kappa-omega two-equation models. The three boundary conditions examined were the free boundary, the mass flux boundary and the subsonic outflow with variable static pressure. In addition to boundary condition type, the geometry downstream of the diffuser was varied to see if upstream influences were present. The NPARC results are compared with experimental data and recommendations are given for using NPARC to compute similar flows

Ocean Chlorophyll Studies from a U-2 Aircraft Platform

Chlorophyll gradient maps of large ocean areas were generated from U-2 ocean color scanner data obtained over test sites in the Pacific and Atlantic Oceans. The delineation of oceanic features using the upward radiant intensity relies on an analysis method which presupposes that radiation backscattered from the atmosphere and ocean surface can be properly modeled using a measurement made at 778 nm. An estimation of the chlorophyll concentration was performed by properly ratioing radiances measured at 472 nm and 548 nm after removing the atmospheric effects. The correlation between the remotely sensed data and in-situ surface chlorophyll measurements was validated in two sets of data. The results show that the correlation between the in-situ measured chlorophyll and the derived quantity is a negative exponential function and the correlation coefficient was calculated to be -0.965