Patterns of orographic uplift in the Sierra Nevada and their relationship to upper-level atmospheric circulation

We examine monthly and seasonal patterns of precipitation across various elevations of the eastern Central Valley of California and the Sierra Nevada. A measure of the strength of the orographic effect called the “precipitation ratio” is calculated, and we separate months into four groups based on being wet or dry and having low or high precipitation ratios. Using monthly maps of mean 700-mb height anomalies, we describe the northern hemisphere mid-tropospheric circulation patterns associated with each of the four groups. Wet months are associated with negative height anomalies over the eastern Pacific, as expected. However, the orientation of the trough is different for years with high and low precipitation ratios. Wet months with high ratios typically have circulation patterns factoring a west-southwest to east-northeast storm track from around the Hawaiian Islands to the Pacific Northwest of the United States. Wet months with low precipitation ratios are associated with a trough centered near the Aleutians and a northwest to southeast storm track. Dry months are marked by anticyclones in the Pacific, but this feature is more localized to the eastern Pacific for months with low precipitation ratios than for those with high ratios. Using precipitation gauge and snow course data from the American River and Truckee-Tahoe basins, we determined that the strength of the orographic effect on a seasonal basis is spatially coherent at low and high elevations and on opposite sides of the Sierra Nevada crestline.

On-line learning of mutually orthogonal subspaces for face recognition by image sets.

We address the problem of face recognition by matching image sets. Each set of face images is represented by a subspace (or linear manifold) and recognition is carried out by subspace-to-subspace matching. In this paper, 1) a new discriminative method that maximises orthogonality between subspaces is proposed. The method improves the discrimination power of the subspace angle based face recognition method by maximizing the angles between different classes. 2) We propose a method for on-line updating the discriminative subspaces as a mechanism for continuously improving recognition accuracy. 3) A further enhancement called locally orthogonal subspace method is presented to maximise the orthogonality between competing classes. Experiments using 700 face image sets have shown that the proposed method outperforms relevant prior art and effectively boosts its accuracy by online learning. It is shown that the method for online learning delivers the same solution as the batch computation at far lower computational cost and the locally orthogonal method exhibits improved accuracy. We also demonstrate the merit of the proposed face recognition method on portal scenarios of multiple biometric grand challenge.

Post-CMOS wafer level growth of carbon nanotubes for low-cost microsensors--a proof of concept.

Here we demonstrate a novel technique to grow carbon nanotubes (CNTs) on addressable localized areas, at wafer level, on a fully processed CMOS substrate. The CNTs were grown using tungsten micro-heaters (local growth technique) at elevated temperature on wafer scale by connecting adjacent micro-heaters through metal tracks in the scribe lane. The electrical and optical characterization show that the CNTs are identical and reproducible. We believe this wafer level integration of CNTs with CMOS circuitry enables the low-cost mass production of CNT sensors, such as chemical sensors.

Prioritizing county-level well-being: Moving toward assessment of Gulf Coast counties impacted by the Deepwater Horizon Industrial Disaster

To develop a portfolio of indicators and measures that could best measure changes in the social, economic, environmental and health dimensions of well-being in coastal counties we convened a group of experts March 8-9, 2011 in Charleston, SC, U.S.A. The region of interest was of the northern Gulf of Mexico, specifically, those coastal counties most impacted during the explosion and subsequent oil spill from the Macondo Prospect wellhead during the summer of 2010. Over the course of the two-day workshop participants moved through presentations and facilitated sessions to identify and prioritize potential indicators and measures deemed most valuable for capturing changes in well-being related to changes in or disruption of ecosystem services. The experts reached consensus on a list of indicators that are now being operationalized by NOAA researchers. The ultimate goal of this research project is to determine whether a meaningful set of social and economic indicators can be developed to document changes in well-being that occur as a result of changes in ecosystem services. The outcomes and outputs from the workshop that is the subject of this report helped us to identify high-quality indicators useful for measuring well-being.

PCR-based assay for detection of four coral pathogens

Several microorganisms have been identified as pathogenic agents responsible for various outbreaks of coral disease. Little has been learned about the exclusivity of a pathogen to given disease signs. Most pathogens have only been implicated within a subset of corals, leaving gaps in our knowledge of the host range and geographic extent of a given pathogen. PCR-based assays provide a rapid and inexpensive route for detection of pathogens. Pathogen-specific 16S rDNA primer sets were designed to target four identified coral pathogens: Aurantimonas coralicida, Serratia marcescens, Vibrio shilonii, and Vibrio coralliilyticus. Assays detected the presence of targets at concentrations of less than one cell per microliter. The assay was applied to 142 coral samples from the Florida Keys, Puerto Rico, and U.S. Virgin Islands as an in situ specificity test. Assays displayed a high-level of specificity, seemingly limited only by the resolution of the 16S rDNA.