North Carolina State University

About: North Carolina State University is a education organization based out in Raleigh, North Carolina, United States. It is known for research contribution in the topics: Population & Thin film. The organization has 44161 authors who have published 101744 publications receiving 3456774 citations. The organization is also known as: NCSU & North Carolina State University at Raleigh.

DNA barcoding of oomycetes with cytochrome c oxidase subunit I and internal transcribed spacer.

Abstract: Oomycete species occupy many different environments and many ecological niches. The genera Phytophthora and Pythium for example, contain many plant pathogens which cause enormous damage to a wide range of plant species. Proper identification to the species level is a critical first step in any investigation of oomycetes, whether it is research driven or compelled by the need for rapid and accurate diagnostics during a pathogen outbreak. The use of DNA for oomycete species identification is well established, but DNA barcoding with cytochrome c oxidase subunit I (COI) is a relatively new approach that has yet to be assessed over a significant sample of oomycete genera. In this study we have sequenced COI, from 1205 isolates representing 23 genera. A comparison to internal transcribed spacer (ITS) sequences from the same isolates showed that COI identification is a practical option; complementary because it uses the mitochondrial genome instead of nuclear DNA. In some cases COI was more discriminative than ITS at the species level. This is in contrast to the large ribosomal subunit, which showed poor species resolution when sequenced from a subset of the isolates used in this study. The results described in this paper indicate that COI sequencing and the dataset generated are a valuable addition to the currently available oomycete taxonomy resources, and that both COI, the default DNA barcode supported by GenBank, and ITS, the de facto barcode accepted by the oomycete and mycology community, are acceptable and complementary DNA barcodes to be used for identification of oomycetes.

Characterization of bias-enhanced nucleation of diamond on silicon by invacuo surface analysis and transmission electron microscopy.

Abstract: An in-depth study has been performed of the nucleation of diamond on silicon by bias-enhanced microwave plasma chemical vapor deposition. Substrates were pretreated by negative biasing in a 2% methane-hydrogen plasma. The bias pretreatment enhanced the nucleation density on unscratched silicon wafers up to ${10}^{11}$ ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}2}$ as compared with ${10}^{7}$ ${\mathrm{cm}}^{\mathrm{\ensuremath{-}}2}$ on scratched wafers. In vacuo surface analysis including x-ray photoelecton spectroscopy (XPS), Auger electron spectroscopy, and combined XPS and electron-energy-loss spectroscopy were used to study systematically both the initial-nucleation and growth processes. High-resolution cross-sectional transmission electron microscopy (TEM) was used to study the physical and structural characteristics of the diamond-silicon interface as well as to complement and enhance the in vacuo surface-analytical results. Raman spectroscopy confirmed that diamond was actually nucleating during the bias pretreatment. Scanning electron microscopy has shown that once the bias is turned off, and conventional growth is conducted, diamond grows on the existing nuclei and no continued nucleation occurs. If the bias is left on throughout the entire deposition, the resulting film will be of much poorer quality than if the bias had been turned off and conventional growth allowed to begin. Intermittent surface analysis showed that a complete silicon carbide layer developed before diamond could be detected. High-resolution cross-sectional TEM confirmed that the interfacial layer was amorphous and varied in thickness from 10 to 100 \AA{}. A small amount of amorphous carbon is detected on the surface of the silicon carbide and it is believed to play a major role in the nucleation sequence. A model is proposed to help explain bias-enhanced nucleation on silicon, in hopes that this will improve the understanding of diamond nucleation, in general, and eventually result in the nucleation and growth of better-quality diamond films.

Impacts of Waste from Concentrated Animal Feeding Operations on Water Quality.

Abstract: Waste from agricultural livestock operations has been a long-standing concern with respect to contamination of water resources, particularly in terms of nutrient pollution. However, the recent growth of concentrated animal feeding operations (CAFOs) presents a greater risk to water quality because of both the increased volume of waste and to contaminants that may be present (e.g., antibiotics and other veterinary drugs) that may have both environmental and public health importance. Based on available data, generally accepted livestock waste management practices do not adequately or effectively protect water resources from contamination with excessive nutrients, microbial pathogens, and pharmaceuticals present in the waste. Impacts on surface water sources and wildlife have been documented in many agricultural areas in the United States. Potential impacts on human and environmental health from long-term inadvertent exposure to water contaminated with pharmaceuticals and other compounds are a growing public concern. This work-group, which is part of the Conference on Environmental Health Impacts of Concentrated Animal Feeding Operations: Anticipating Hazards—Searching for Solutions, identified needs for rigorous ecosystem monitoring in the vicinity of CAFOs and for improved characterization of major toxicants affecting the environment and human health. Last, there is a need to promote and enforce best practices to minimize inputs of nutrients and toxicants from CAFOs into freshwater and marine ecosystems.

Gait recognition using wifi signals

Abstract: In this paper, we propose WifiU, which uses commercial WiFi devices to capture fine-grained gait patterns to recognize humans. The intuition is that due to the differences in gaits of different people, the WiFi signal reflected by a walking human generates unique variations in the Channel State Information (CSI) on the WiFi receiver. To profile human movement using CSI, we use signal processing techniques to generate spectrograms from CSI measurements so that the resulting spectrograms are similar to those generated by specifically designed Doppler radars. To extract features from spectrograms that best characterize the walking pattern, we perform autocorrelation on the torso reflection to remove imperfection in spectrograms. We evaluated WifiU on a dataset with 2,800 gait instances collected from 50 human subjects walking in a room with an area of 50 square meters. Experimental results show that WifiU achieves top-1, top-2, and top-3 recognition accuracies of 79.28%, 89.52%, and 93.05%, respectively.

Nonlinear control synthesis by sum of squares optimization: a Lyapunov-based approach

Abstract: This paper addresses the state feedback control synthesis problems for nonlinear systems, either without or with guaranteed cost or H/sub /spl infin// performance objectives. By representing the open-loop nonlinear systems in a state dependent linear-like form and considering a special class of Lyapunov functions, sufficient conditions for the solutions to the above problems can be formulated in terms of state dependent linear matrix inequalities. Semidefinite programming relaxations based on the sum of squares decomposition are then used to efficiently solve such inequalities.