Discriminating between cool season and warm season grassland cover types in northeastern Kansas

This study assesses the ability of multitemporal Landsat Thematic Mapper (TM) data and the normalized difference vegetation index (NDVI) to spectrally separate grazed cool season and warm season grassland cover types in Douglas County, Kansas. Biophysical data collected during the summer of 1997 suggest that differences in the per cent of total living vegetation cover, per cent of senescent vegetation, and proportion of forb cover between the two grassland cover types could make cool season and warm season grassland cover types spectrally distinct. The results show that the two grassland cover types were spectrally different in several spring (May) and mid-summer (July) bands, but not in any fall (September) bands. Furthermore, the two grassland cover types could be discriminated with a high level of accuracy. Accuracy assessments of the three single dates showed that the mid-summer (July) image and NDVI discriminated between the grassland cover types most accurately (81.8%). The multitemporal TM and NDVI data did not improve the spectral discrimination of the two grassland cover types over the mid-summer image or NDVI and had classification accuracy levels of 63.6% and 68.2%, respectively.     

Estimating above-ground net primary productivity of the tallgrass prairie ecosystem of the Central Great Plains using AVHRR NDVI

Above-ground net primary productivity (ANPP) is indicative of an ecosystem's ability to capture solar energy and convert it to organic carbon (or biomass), which may be used by consumers or decomposers, or stored in the form of living and nonliving organic matter. Annual and interannual variation in ANPP is often linked to climate dynamics and anthropogenic influences, such as fertilization, irrigation, above-ground biomass harvest, and so on. The Central Great Plains grasslands occupy over 1.5 million km² and are a primary resource for livestock production in North America. The tallgrass prairies are the most productive grasslands in this region, and the Flint Hills of North America represent the largest contiguous area of unploughed tallgrass prairie (1.6 million ha). Measurements of ANPP are of critical importance to the proper management and understanding of climatic and anthropogenic influences on tallgrass prairie. Yet, accurate, detailed, and systematic measurements of ANPP over large geographic regions do not exist for this ecosystem. For these reasons, this study was conducted to investigate the use of the normalized difference vegetation index (NDVI) to model ANPP of the tallgrass prairie. Many studies have established a positive relationship between the NDVI and ANPP, but the strength of this relationship is influenced by vegetation types and can vary significantly from year to year depending on land use and climatic conditions. The goal of this study was to develop a robust model using the Advanced Very High Resolution Radiometer (AVHRR) biweekly NDVI values to predict tallgrass ANPP. This study was conducted using ANPP measurements from a watershed within the Konza Prairie Biological Station (KPBS) as the primary study area, with additional measurements from the Rannells Flint Hills Prairie Preserve (RFHPP) and biennial ANPP measurements by Kansas State University (KSU) students from tallgrass areas near Manhattan, Kansas. Data from the primary study site covered the period of 1989–2005. The optimal period for estimating ANPP using AVHRR NDVI composite data sets was found to be late July. The Tallgrass ANPP Model (TAM) explained 54% (coefficient of determination, R ² = 0.54, p < 0.001) of the year-to-year variation in ANPP. The creation of 1.0 km × 1.0 km resolution ANPP maps for a four-county (～7000 ha) area for years 1989–2007 showed considerable variation in annual and interannual ANPP spatial patterns, suggesting complex interactions among factors influencing ANPP spatially and temporally.     

E-auction web assessment model in China

Electronic auction (e-auction), a major e-commerce model, has enjoyed rapid growth in many countries. This study develops a web assessment model (EAWAM) from a consumer perspective that suggests that user intention to continue using an e-auction website is based on users’ satisfaction with the e-auction website, which is determined by perceived e-auction user friendliness, functionality and interactivity. Web trustworthiness serves as an important antecedent to perceived e-auction user friendliness and functionality. To validate this model, a survey was conducted using 191 users of Taobao.com from 15 cities in China. Partial Least Square analysis results provided strong support for this model and also yielded important implications and suggestions for further research.     

Ehancement of Dissolution Rate by Incorporation into a Water Insoluble Polymer, Polycaprolactone

This report concerns the use of water insoluble polymer, polycaprolactone, as a carrier to enhance the dissolution rate of two drugs, chlorpromazine and progesterone. Polycaprolactone microspheres containing these drugs were prepared by an emulsion-solvent evaporation technique and dissolution characteristics were compared to pure drug.

Dissolution studies revealed that both chlorpromazine-poly-caprolactone and progesterone-polycaprolactone microspheres exhibited a faster dissolution rate than the pure drugs. Molecular or colloidal dispersion of drugs in the polycaprolactone microshere matrix and the high permeability of polycaprolactone to the drugs and water are possible reasons for the rapid release perties observed.     

A novel method to dope diamond — Ion Beam Nuclear Transmutation Doping (IBNTD)

Using MeV-range protons to transmute a small fraction of host nuclei into n- or p-type dopants, we have demonstrated a novel method to dope challenging wide bandgap semiconductors. In particular, we have doped isotopically-enriched ¹³C diamond and AlGaN films using this method focusing on the ¹³C + ¹H → ¹⁴N + γ, radiative proton capture resonance at 1.75 MeV and ²⁷Al + ¹H → ²⁸Si + γ proton capture resonance at 0.997 MeV. Both samples sustained primarily end-of-range damage which was annealable in AlGaN. We have performed a variety of measurements to characterize the doped samples including Raman spectroscopy, STM, and X-ray diffraction on the doped samples which suggest the viability of IBNTD as a doping method. Calculations indicate that doping layer thicknesses of the order of 10 nm are achievable. Possible doping concentrations using this technique are also estimated.     

Pipelined Scheduling of Functional HW/SW Modules for Platform‐Based SoC Design

We developed a pipelined scheduling technique of functional hardware and software modules for platform‐based system‐on‐a‐chip (SoC) designs. It is based on a modified list scheduling algorithm. We used the pipelined scheduling technique for a performance analysis of an MPEG4 video encoder application. Then, we applied it for architecture exploration to achieve a better performance. In our experiments, the modified SoC platform with 6 pipelines for the 32‐bit dual layer architecture shows a 118% improvement in performance compared to the given basic SoC platform with 4 pipelines for the 16‐bit single‐layer architecture.     

Simple theory of double-barrier tunneling

The author analyzes resonant electron tunneling in parallel-plane heterostructures that have a central well region enclosed by two generalized barriers, which are reflectors of the Bloch waves. A single Bloch pair is assumed for the central region as well as in the surrounding semi-infinite semiconductors. The transmission probability versus electron energy is obtained for this model in terms of the transmission probabilities of the two barrier elements taken separately and the quasi-classical transit time for the trapped electron to make one circuit of the central well layer. The implications and limitations of these results are briefly discussed     

Empirical Investigation of Construction Contractors' Organizational Learning

Conceptual frameworks dominate organizational learning literature with limited empirical assessments. This raises several questions about the validity and applicability of the various conceptual frameworks for how managers can build organizational learning capabilities. As such, lessons from the conceptual frameworks of organizational learning for addressing performance improvement that might have been used by construction contractors have been limited. This paper presents a quantitative analysis of organizational learning by construction contractors. The principles that underlie organizational learning and the factors that promote double-loop learning as a strategy for improving construction contractors’ business processes are presented. The paper has also established the learning orientations and focus of the surveyed construction contractors to determine their organizational learning dimensions as well as the factors that induced their double-loop learning, as rich lessons for organizations in the construction industry.