LANDSAT data for state planning

The results of an effort to generate and apply automated classification of LANDSAT digital data to state of Georgia problems are presented. This phase centers on an analysis of the usefulness of LANDSAT digital data to provide land-use data for transportation planning. Hall County, Georgia was chosen as a test site because it is part of a seventeen county area for which the Georgia Department of Transportation is currently designing a Transportation Planning Land-Use Simulation Model. The land-cover information derived from this study was compared to several other existing sources of land-use data for Hall County and input into this simulation. The results indicate that there is difficulty comparing LANDSAT derived land-cover information with previous land-use information since the LANDSAT data are acquired on an acre by acre grid basis while all previous land-use surveys for Hall County used land-use data on a parcel basis

Study of USGS/NASA land use classification system

It is known from several previous investigations that many categories of land-use can be mapped via computer processing of Earth Resources Technology Satellite data. The results are presented of one such experiment using the USGS/NASA land-use classification system. Douglas County, Georgia, was chosen as the test site for this project. It was chosen primarily because of its recent rapid growth and future growth potential. Results of the investigation indicate an overall land-use mapping accuracy of 67% with higher accuracies in rural areas and lower accuracies in urban areas. It is estimated, however, that 95% of the State of Georgia could be mapped by these techniques with an accuracy of 80% to 90%

LANDSAT information for state planning

The transfer of remote sensing technology for the digital processing of LANDSAT data to state and local agencies in Georgia and other southeastern states is discussed. The project consists of a series of workshops, seminars, and demonstration efforts, and transfer of NASA-developed hardware concepts and computer software to state agencies. Throughout the multi-year effort, digital processing techniques have been emphasized classification algorithms. Software for LANDSAT data rectification and processing have been developed and/or transferred. A hardware system is available at EES (engineering experiment station) to allow user interactive processing of LANDSAT data. Seminars and workshops emphasize the digital approach to LANDSAT data utilization and the system improvements scheduled for LANDSATs C and D. Results of the project indicate a substantially increased awareness of the utility of digital LANDSAT processing techniques among the agencies contracted throughout the southeast. In Georgia, several agencies have jointly funded a program to map the entire state using digitally processed LANDSAT data

Design of a low cost earth resources system

The author has identified the following significant results. Survey results indicated that users of remote sensing data in the Southeastern U.S. were increasingly turning to digital processing techniques. All the states surveyed have had some involvement in projects using digitally processed data. Even those states which do not yet have in-house capabilities for digital processing were extremely interested in and were planning to develop such capabilities

Computer processing of peach tree decline data

There are no author-identified significant results in this report

Processing and Transmission of Information

Contains research objectives and reports on three research projects.National Science Foundation (Grant GP-2495)National Institutes of Health (Grant MH-04737-04)National Aeronautics and Space Administration (Grant NsG-334)National Aeronautics and Space Administration (Grant NsG-496

Pay What You Want as a Marketing Strategy in Monopolistic and Competitive Markets

Pay What You Want (PWYW) can be an attractive marketing strategy to price discriminate between fair-minded and selfish customers, to fully penetrate a market without giving away the product for free, and to undercut competitors that use posted prices. We report on laboratory experiments that identify causal factors determining the willingness of buyers to pay voluntarily under PWYW. Furthermore, to see how competition affects the viability of PWYW, we implement markets in which a PWYW seller competes with a traditional seller. Finally, we endogenize the market structure and let sellers choose their pricing strategy. The experimental results show that outcome-based social preferences and strategic considerations to keep the seller in the market can explain why and how much buyers pay voluntarily to a PWYW seller. We find that PWYW can be viable in isolation, but it is less successful as a competitive strategy because it does not drive traditional posted-price sellers out of the market. Instead, the existence of a posted-price competitor reduces buyers’ payments and prevents the PWYW seller from fully penetrating the market. If given the choice, the majority of sellers opt for setting a posted price rather than a PWYW pricing. We discuss the implications of these results for the use of PWYW as a marketing strategy

Genetics, recombination and clinical features of human rhinovirus species C (HRV-C) infections; interactions of HRV-C with other respiratory viruses

To estimate the frequency, molecular epidemiological and clinical associations of infection with the newly described species C variants of human rhinoviruses (HRV), 3243 diagnostic respiratory samples referred for diagnostic testing in Edinburgh were screened using a VP4-encoding region-based selective polymerase chain reaction (PCR) for HRV-C along with parallel PCR testing for 13 other respiratory viruses. HRV-C was the third most frequently detected behind respiratory syncytial virus (RSV) and adenovirus, with 141 infection episodes detected among 1885 subjects over 13 months (7.5%). Infections predominantly targeted the very young (median age 6–12 months; 80% of infections in those <2 years), occurred throughout the year but with peak incidence in early winter months. HRV-C was detected significantly more frequently among subjects with lower (LRT) and upper respiratory tract (URT) disease than controls without respiratory symptoms; HRV-C mono-infections were the second most frequently detected virus (behind RSV) in both disease presentations (6.9% and 7.8% of all cases respectively). HRV variants were classified by VP4/VP2 sequencing into 39 genotypically defined types, increasing the current total worldwide to 60. Through sequence comparisons of the 5′untranslated region (5′UTR), the majority grouped with species A (n = 96; 68%, described as HRV-Ca), the remainder forming a phylogenetically distinct 5′UTR group (HRV-Cc). Multiple and bidirectional recombination events between HRV-Ca and HRV-Cc variants and with HRV species A represents the most parsimonious explanation for their interspersed phylogeny relationships in the VP4/VP2-encoding region. No difference in age distribution, seasonality or disease associations was identified between HRV-Ca and HRV-Cc variants. HRV-C-infected subjects showed markedly reduced detection frequencies of RSV and other respiratory viruses, providing evidence for a major interfering effect of HRV-C on susceptibility to other respiratory virus infections. HRV-C's disease associations, its prevalence and evidence for interfering effects on other respiratory viruses mandates incorporation of rhinoviruses into future diagnostic virology screening

The Privacy, Security and Discoverability of Data on Wearable Health Devices: Fitness or Folly?

Introduction Wearable Health Devices and Their Data Advantages Privacy Security Discoverability Research Plan Research Goals Reference

Pulmonary epithelial barrier and immunological functions at birth and in early life - key determinants of the development of asthma? A description of the protocol for the Breathing Together study

Acknowledgements The authors are indebted to the participants and parents who have already been recruited. We also acknowledge the enthusiasm and endeavour of the research nurse team which includes: Stephen Main, Margaret Connon, Catherine Beveridge, Julie Baggott, Kay Riding, Ellie McCamie, Maria Larsson, Lynda Melvin, Mumtaz Idris, Tara Murray, Nicky Tongue, Nicolene Plaatjies, Sheila Mortimer, Sally Spedding, Susy Grevatt, Victoria Welch, Morag Zelisko, Jillian Doherty, Jane Martin, Emma Macleod and Cilla Snape. We are also delighted to be working alongside the following colleagues in laboratories: Marie Craigon, Marie McWilliam, Maria Zarconi, Judit Barabas, Lindsay Broadbent, Ceyda Oksel and Sheerien Manzoor. Grant information The study is supported by the Wellcome Trust [108818]; and the PHA HSC R&D Division, Northern Ireland.Peer reviewedPublisher PD