07. Appropriate Levels of Care

Consumers of long-term care are primarily the elderly, whose numbers are approaching 25 million; they comprise almost eleven percent of this nation\u27s population.1 They experience higher incidents of chronic disease and long term illness, with the most serious health care problems occurring in those over 75.2 These health care problems are usually costly because of the need for hospital and nursing home care, as well as other forms of intervention, and the unavailability of suitable, less costly alternatives, particularly in rural areas. In addition, these problems are compounded by lack of mobility, poor nutrition, lack of primary care and other elements often related to limited financial resources

Sociocultural Learning: A Perspective on GSS-Enabled Global Education

Virtual teams are rapidly developing in organisations of the new economy. As educators, we have a responsibility to ensure that our students are appropriately prepared for work in the virtual workspace, where teams may cross time, geographical, and cultural boundaries. In this article, the culturally sensitive theory of sociocultural learning is combined with GSS (Group Support Systems) in an illustration of how cross-cultural, globally distributed virtual teams of students located in The Netherlands, Greece, and Hong Kong work on vested interest projects. Finally, a set of critical success factors that inform virtual learning contexts is derived from our findings and recommendations are made for operational practice in the virtual work space

Switchgrass Biomass Simulation at Diverse Sites in the Northern Great Plains of the U.S.

The Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) model, originally developed and tested in Texas, needs to be tested for switchgrass (Panicum virgatum L.) simulation in more northerly locations. The Northern Great Plains of the U.S. has regionally adapted native populations of switchgrass and has excellent potential for growing switchgrass as a biofuel crop. The objective of this study was to adjust switchgrass parameters (potential leaf area index (DMLA) and degree days to maturity (PHU)) for northern sites and populations and to validate the model against switchgrass data from diverse sites in this region. Three or 4 years of measured yield data were used from a ten field sites in North Dakota (ND), South Dakota (SD), and Nebraska (NE). ALMANAC realistically simulated mean annual switchgrass yields ranging from means of 4.75 to 9.13 Mg ha−1. Mean simulated yields were within 3%, 15%, and 9% of mean measured yields for NE, SD, and ND, respectively. Sensitivity analysis with temperature and rainfall demonstrated variable responses of potential yields depending on whether season duration, soil water, or soil nitrogen was the limiting factor at a site. ALMANAC shows promise as a useful tool for switchgrass evaluation and management in the northern Great Plains and in similar latitudes with low rainfall such as the East European Plain

Soil Carbon Storage by Switchgrass Grown for Bioenergy

Life-cycle assessments (LCAs) of switchgrass (Panicum virgatum L.) grown for bioenergy production require data on soil organic carbon (SOC) change and harvested C yields to accurately estimate net greenhouse gas (GHG) emissions. To date, nearly all information on SOC change under switchgrass has been based on modeled assumptions or small plot research, both of which do not take into account spatial variability within or across sites for an agro-ecoregion. To address this need, we measured change in SOC and harvested C yield for switchgrass fields on ten farms in the central and northern Great Plains, USA (930 km latitudinal range). Change in SOC was determined by collecting multiple soil samples in transects across the fields prior to planting switchgrass and again 5 years later after switchgrass had been grown and managed as a bioenergy crop. Harvested aboveground C averaged 2.5± 0.7 Mg C ha−1 over the 5 year study. Across sites, SOC increased significantly at 0–30 cm (P=0.03) and 0–120 cm (P=0.07), with accrual rates of 1.1 and 2.9 Mg C ha−1 year−1 (4.0 and 10.6 Mg CO2 ha−1 year−1), respectively. Change in SOC across sites varied considerably, however, ranging from −0.6 to 4.3 Mg C ha−1 year−1 for the 0–30 cm depth. Such variation in SOC change must be taken into consideration in LCAs. Net GHG emissions from bioenergy crops vary in space and time. Such variation, coupled with an increased reliance on agriculture for energy production, underscores the need for long-term environmental monitoring sites in major agro-ecoregions

Field-Scale Soil Property Changes under Switchgrass Managed for Bioenergy

The capacity of perennial grasses to affect change in soil properties is well documented but information on switchgrass (Panicum virgatum L.) managed for bioenergy is limited. An on-farm study (10 fields) in North Dakota, South Dakota, and Nebraska was sampled before switchgrass establishment and after 5 years to determine changes in soil bulk density (SBD), pH, soil phosphorus (P), and equivalent mass soil organic carbon (SOC). Changes in SBD were largely constrained to near-surface depths (0–0.05 m). SBD increased (0–0.05 m) at the Nebraska locations (mean=0.16 Mgm-3), while most South Dakota and North Dakota locations showed declines in SBD (mean=-0.18 Mgm-3; range=-0.42–0.07 Mgm-3). Soil pH change was significant at five of the 10 locations at near surface depths (0–0.05 m), but absolute changes were modest (range=-0.67–0.44 pH units). Available P declined at all sites where it was measured (North Dakota and South Dakota locations). When summed across the surface 0.3 m depth, annual decreases in available P averaged 1.5 kg P ha-1 yr-1 (range=0.5–2.8 kg P ha-1 yr-1). Averaged across locations, equivalent mass SOC increased by 0.5 and 2.4 Mg Cha-1 yr-1 for the 2500 and 10 000 Mg ha-1 soil masses, respectively. Results from this study underscore the contribution of switchgrass to affect soil property changes, though considerable variation in soil properties exists within and across locations

The Conservation Reserve Program: Economic Implications for Rural America

This report estimates the impact that high levels of enrollment in the Conservation Reserve Program (CRP) have had on economic trends in rural counties since the program's inception in 1985 until today. The results of a growth model and quasi-experimental control group analysis indicate no discernible impact by the CRP on aggregate county population trends. Aggregate employment growth may have slowed in some high-CRP counties, but only temporarily. High levels of CRP enrollment appear to have affected farm-related businesses over the long run, but growth in the number of other nonfarm businesses moderated CRP's impact on total employment. If CRP contracts had ended in 2001, simulation models suggest that roughly 51 percent of CRP land would have returned to crop production, and that spending on outdoor recreation would decrease by as much as $300 million per year in rural areas. The resulting impacts on employment and income vary widely among regions having similar CRP enrollments, depending upon local economic conditions.Community/Rural/Urban Development, Land Economics/Use,

Switchgrass Leaf Area Index and Light Extinction Coefficients

Much of recent interest in biofuel species modeling has been for switchgrass (Panicum virgatum L.). Such modeling requires accurate simulation of light interception. We investigated the stability of the light extinction coefficient (k) in Beer’s Law with data from Temple, TX; Lincoln, NE; and Elsberry, MO. Variability in k values was not related to fraction of light intercepted, time of day, or incident solar radiation. Only the magnitude of leaf area index (LAI) showed a significant impact on the k value. Th e mean k value (−0.37) for the ‘Alamo’ switchgrass data at Temple was similar to the previously published k value (−0.33) and similar to Alamo k values in Nebraska (−0.38) and Missouri (−0.31). Compared to Alamo, other switchgrass cultivars had similar k values in Nebraska but were higher in Missouri. This study gave guidance as to which factors are important for quantifying k with Beer’s Law for light interception of switchgrass

Nanoparticle ζ-potential measurements using tunable resistive pulse sensing with variable pressure

Modern resistive pulse sensing techniques can be used to measure nanoparticle electrophoretic mobility, and hence ζ-potential. In contrast to conventional light scattering methods, resistive pulse sensing produces particle-by-particle data. We have used tunable resistive pulse sensing (TRPS) to compare methods for measuring the ζ-potential of carboxylated polystyrene nanoparticles. The five particle sets studied had nominal surface charge density (σ) between 0 and -0.67Cm, and diameters in the range 160-230nm. Data were collected with pressure in the range ±500Pa applied across a tunable pore. In each experiment, pressure was varied either continuously or in discrete steps. Calculations of the ζ-potential were obtained by analysing both the rate and the full-width half maximum duration of resistive pulses. Data obtained from duration analyses were more reproducible than rate methods, yielding typical variations smaller than ±5mV. When σ was greater (less negative) than -0.32Cm, all of the analysis methods studied yielded a monotonic relationship between ζ-potential and σ. Complicated pulse data were observed near the pressure at which the net particle flux is zero, and these observations have been explored by examining competition between electrokinetic and pressure-driven transport. The typical difference between ζ-potentials obtained using TRPS and phase analysis light scattering was 15%