570,895 research outputs found

    Evaluation of geophysical parameters measured by the Nimbus-7 microwave radiometer for the TOGA Heat Exchange Project

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    The data distributed by the National Space Science Data Center on the Geophysical parameters of precipitable water, sea surface temperature, and surface-level wind speed, measured by the Scanning Multichannel Microwave Radiometer (SMMR) on Nimbus-7, are evaluated with in situ measurements between Jan. 1980 and Oct. 1983 over the tropical oceans. In tracking annual cycles and the 1982-83 E1 Nino/Southern Oscillation episode, the radiometer measurements are coherent with sea surface temperatures and surface-level wind speeds measured at equatorial buoys and with precipitable water derived from radiosonde soundings at tropical island stations. However, there are differences between SMMR and in situ measurements. Corrections based on radiosonde and ship data were derived supplementing correction formulae suggested in the databook. This study is the initial evaluation of the data for quantitative description of the 1982-83 E1 Nino/Southern Oscillation episode. It paves the way for determination of the ocean-atmosphere moisture and latent heat exchanges, a priority of the Tropical Ocean and Global Atmosphere (TOGA) Heat Exchange Program

    Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

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    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications

    Planning, implementation, and first results of the Tropical Composition, Cloud and Climate Coupling Experiment (TC4)

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    The Tropical Composition, Cloud and Climate Coupling Experiment (TC4), was based in Costa Rica and Panama during July and August 2007. The NASA ER-2, DC-8, and WB-57F aircraft flew 26 science flights during TC4. The ER-2 employed 11 instruments as a remote sampling platform and satellite surrogate. The WB-57F used 25 instruments for in situ chemical and microphysical sampling in the tropical tropopause layer (TTL). The DC-8 used 25 instruments to sample boundary layer properties, as well as the radiation, chemistry, and microphysics of the TTL. TC4 also had numerous sonde launches, two ground-based radars, and a ground-based chemical and microphysical sampling site. The major goal of TC4 was to better understand the role that the TTL plays in the Earth's climate and atmospheric chemistry by combining in situ and remotely sensed data from the ground, balloons, and aircraft with data from NASA satellites. Significant progress was made in understanding the microphysical and radiative properties of anvils and thin cirrus. Numerous measurements were made of the humidity and chemistry of the tropical atmosphere from the boundary layer to the lower stratosphere. Insight was also gained into convective transport between the ground and the TTL, and into transport mechanisms across the TTL. New methods were refined and extended to all the NASA aircraft for real-time location relative to meteorological features. The ability to change flight patterns in response to aircraft observations relayed to the ground allowed the three aircraft to target phenomena of interest in an efficient, well-coordinated manner

    Tropical Support Vector Machine and its Applications to Phylogenomics

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    Most data in genome-wide phylogenetic analysis (phylogenomics) is essentially multidimensional, posing a major challenge to human comprehension and computational analysis. Also, we can not directly apply statistical learning models in data science to a set of phylogenetic trees since the space of phylogenetic trees is not Euclidean. In fact, the space of phylogenetic trees is a tropical Grassmannian in terms of max-plus algebra. Therefore, to classify multi-locus data sets for phylogenetic analysis, we propose tropical support vector machines (SVMs). Like classical SVMs, a tropical SVM is a discriminative classifier defined by the tropical hyperplane which maximizes the minimum tropical distance from data points to itself in order to separate these data points into sectors (half-spaces) in the tropical projective torus. Both hard margin tropical SVMs and soft margin tropical SVMs can be formulated as linear programming problems. We focus on classifying two categories of data, and we study a simpler case by assuming the data points from the same category ideally stay in the same sector of a tropical separating hyperplane. For hard margin tropical SVMs, we prove the necessary and sufficient conditions for two categories of data points to be separated, and we show an explicit formula for the optimal value of the feasible linear programming problem. For soft margin tropical SVMs, we develop novel methods to compute an optimal tropical separating hyperplane. Computational experiments show our methods work well. We end this paper with open problems.Comment: 27 pages, 6 figures, 2 table

    Social sciences research in neglected tropical diseases 3: Investment in social science research in neglected diseases of poverty: a case study of Bill and Melinda Gates Foundation

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    This article has been made available through the Brunel Open Access Publishing Fund.BACKGROUND: The level of funding provides a good proxy for the level of commitment or prioritisation given to a particular issue. While the need for research relevant to social, economic, cultural and behavioural aspects of neglected tropical diseases (NTD) control has been acknowledged, there is limited data on the level of funding that supports NTD social science research. METHOD: A case study was carried out in which the spending of a major independent funder, the Bill and Melinda Gates Foundation (BMGF) - was analysed. A total of 67 projects funded between October 1998 and November 2008 were identified from the BMGF database. With the help of keywords within the titles of 67 grantees, they were categorised as social science or non-social science research based on available definition of social science. A descriptive analysis was conducted. RESULTS: Of 67 projects analysed, 26 projects (39%) were social science related while 41 projects (61%) were basic science or other translational research including drug development. A total of US697millionwasspenttofundtheprojects,ofwhich35 697 million was spent to fund the projects, of which 35% ((US 241 million) went to social science research. Although the level of funding for social science research has generally been lower than that for non-social science research over 10 year period, social science research attracted more funding in 2004 and 2008. CONCLUSION: The evidence presented in this case study indicates that funding on NTD social science research compared to basic and translational research is not as low as it is perceived to be. However, as there is the acute need for improved delivery and utilisation of current NTD drugs/technologies, informed by research from social science approaches, funding priorities need to reflect the need to invest significantly more in NTD social science research

    Fungi of Madre De Dios

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    Elevated temperatures and high moisture in tropical ecosystems lead to rapid nutrient cycling and turnover. Therefore, decomposers serve vital roles in biodiversity protection within tropical climates. This quick turnover makes identification of fungi extremely difficult since existing fungi identification lists are not exhaustive and new species are likely appearing annually, causing a lack of fungi knowledge. Citizen science plays a critical role in combating this deficit by increasing the sightings and photographs of fungi in tropical ecosystems. With more amateur data, scientists will have more resources and incentives to genotypically sequence tropical fungi to determine rates of speciation and evolution

    Are Special Processes at Work in the Rapid Intensification of Tropical Cyclones?

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    Probably not. Frequency distributions of intensification and dissipation developed from synthetic open-ocean tropical cyclone data show no evidence of significant departures from exponential distributions, though there is some evidence for a fat tail of dissipation rates. This suggests that no special factors govern high intensification rates and that tropical cyclone intensification and dissipation are controlled by statistically random environmental and internal variability.National Science Foundation (U.S.) (Grant AGS1032244
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