Henry E. Eccles, Rear Admiral, U.S. Navy (Ret)

The Naval War College has been in historic Newport on glorious Narragansett Bay for almost a century. Its mission has remained constant, but the faculty and students stay for only short periods-and most of the population of Newport ebb and flow even faster. Yet, the Naval War College has been remarkably stable with all the frequent changes

Irrigated lands assessment for water management: Technique test

A procedure for estimating irrigated land using full frame LANDSAT imagery was demonstrated. Relatively inexpensive interpretation of multidate LANDSAT photographic enlargements was used to produce a map of irrigated land in California. The LANDSAT and ground maps were then linked by regression equations to enable precise estimation of irrigated land area by county, basin, and statewide. Land irrigated at least once in California in 1979 was estimated to be 9.86 million acres, with an expected error of less than 1.75% at the 99% level of confidence. To achieve the same level of error with a ground-only sample would have required 3 to 5 times as many ground sample units statewide. A procedure for relatively inexpensive computer classification of LANDSAT digital data to irrigated land categories was also developed. This procedure is based on ratios of MSS band 7 and 5, and gave good results for several counties in the Central Valley

BMQ

BMQ: Boston Medical Quarterly was published from 1950-1966 by the Boston University School of Medicine and the Massachusetts Memorial Hospitals

Gulf of Mexico Regional Collaborative Final Report

This report presents the results of the Gulf of Mexico Regional Collaborative (GoMRC), a year-long project funded by NASA. The GoMRC project was organized around end user outreach activities, a science applications team, and a team for information technology (IT) development. Key outcomes are summarized below for each of these areas. End User Outreach Successfully engaged federal and state end users in project planning and feedback With end user input, defined needs and system functional requirements Conducted demonstration to End User Advisory Committee on July 9, 2007 and presented at Gulf of Mexico Alliance (GOMA) meeting of Habitat Identification committee Conducted significant engagement of other end user groups, such as the National Estuary Programs (NEP), in the Fall of 2007 Established partnership with SERVIR and Harmful Algal Blooms Observing System (HABSOS) programs and initiated plan to extend HABs monitoring and prediction capabilities to the southern Gulf. Established a science and technology working group with Mexican institutions centered in the State of Veracruz. Key team members include the Federal Commission for the Protection Against Sanitary Risks (COFEPRIS), the Ecological Institute (INECOL) a unit of the National Council for science and technology (CONACYT), the Veracruz Aquarium (NOAA’s first international Coastal Ecology Learning Center) and the State of Veracruz. The Mexican Navy (critical to coastal studies in the Southern Gulf) and other national and regional entities have also been engaged. Training on use of SERVIR portal planned for Fall 2007 in Veracruz, Mexico Science Applications Worked with regional scientists to produce conceptual models of submerged aquatic vegetation (SAV) ecosystems Built a logical framework and tool for ontological modeling of SAV and HABs Created online guidance for SAV restoration planning Created model runs which link potential future land use trends, runoff and SAV viability Analyzed SAV cover change at five other bays in the Gulf of Mexico to demonstrate extensibility of the analytical tools Initiated development of a conceptual model for understanding the causes and effects of HABs in the Gulf of Mexico IT Tool Development Established a website with the GoMRC web-based tools at www.gomrc.org Completed development of an ArcGIS-based decision support tool for SAV restoration prioritization decisions, and demonstrated its use in Mobile Bay Developed a web-based application, called Conceptual Model Explorer (CME), that enables non-GIS users to employ the prioritization model for SAV restoration Created CME tool enabling scientists to view existing, and create new, ecosystem conceptual models which can be used to document cause-effect relationships within coastal ecosystems, and offer guidance on management solutions. Adapted the science-driven advanced web search engine, Noesis, to focus on an initial set of coastal and marine resource issues, including SAV and HABs Incorporated map visualization tools with initial data layers related to coastal wetlands and SAV

Celebrating 20 Years of the ExCEEd Teaching Workshop

In response to the clear need for faculty training, the American Society of Civil Engineers (ASCE) developed and funded Project ExCEEd (Excellence in Civil Engineering Education) which is celebrating its twentieth year of existence. For the past two decades, 38 ExCEEd Teaching Workshops (ETW) have been held at six different universities. The program has 910 graduates from over 267 different U.S. and international colleges and universities. The ExCEEd effort has transformed from one that relied on the grass roots support of its participants to one that is supported and embraced by department heads and deans. This paper summarizes the history of Project ExCEEd, describes the content of the ETW, assesses its effectiveness, highlights changes in the program as a result of the assessment, and outlines the future direction of the program

Brand Suicide? Memory and Liking of Negative Brand Names

Negative brand names are surprisingly common in the marketplace (e.g., Poison perfume; Hell pizza, and Monster energy drink), yet their effects on consumer behavior are currently unknown. Three studies investigated the effects of negative brand name valence on brand name memory and liking of a branded product. Study 1 demonstrates that relative to nonnegative brand names, negative brand names and their associated logos are better recognised. Studies 2 and 3 demonstrate that negative valence of a brand name tends to have a detrimental influence on product evaluation with evaluations worsening as negative valence increases. However, evaluation is also dependent on brand name arousal, with high arousal brand names resulting in more positive evaluations, such that moderately negative brand names are equally as attractive as some non-negative brand names. Study 3 shows evidence for affective habituation, whereby the effects of negative valence reduce with repeated exposures to some classes of negative brand name

A Combined Perceptual, Physico-Chemical, and Imaging Approach to ‘Odour-Distances’ Suggests a Categorizing Function of the Drosophila Antennal Lobe

How do physico-chemical stimulus features, perception, and physiology relate? Given the multi-layered and parallel architecture of brains, the question specifically is where physiological activity patterns correspond to stimulus features and/or perception. Perceived distances between six odour pairs are defined behaviourally from four independent odour recognition tasks. We find that, in register with the physico-chemical distances of these odours, perceived distances for 3-octanol and n-amylacetate are consistently smallest in all four tasks, while the other five odour pairs are about equally distinct. Optical imaging in the antennal lobe, using a calcium sensor transgenically expressed in only first-order sensory or only second-order olfactory projection neurons, reveals that 3-octanol and n-amylacetate are distinctly represented in sensory neurons, but appear merged in projection neurons. These results may suggest that within-antennal lobe processing funnels sensory signals into behaviourally meaningful categories, in register with the physico-chemical relatedness of the odours

Comparing the effects of calibration and climate errors on a statistical crop model and a process-based crop model

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve