952 research outputs found

    The Value in Verifying Medical Folklore

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    Citing a related article published within this issue of the Journal of Patient-Centered Research and Reviews, the author opines on why traditional ideas regarding human health can persist over decades, and even centuries, despite a lack of scientifically accumulated evidence. It is important to keep in mind that some commonly accepted truths are supported by little to no factual data, and that occasionally patients may benefit from clarification on what is (or, often, is not) actually known about longstanding “rules of thumb” (eg, certain home remedies, disease-prevention measures or behavioral concerns). On the flip side, traditions that are shown to be not harmful, like drinking chicken soup to relieve cold symptoms, may be safely indulged regardless of effectiveness

    Freshwater Fungal Infections

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    Fungal infections as a result of freshwater exposure or trauma are fortunately rare. Etiologic agents are varied, but commonly include filamentous fungi and Candida. This narrative review describes various sources of potential freshwater fungal exposure and the diseases that may result, including fungal keratitis, acute otitis externa and tinea pedis, as well as rare deep soft tissue or bone infections and pulmonary or central nervous system infections following traumatic freshwater exposure during natural disasters or near-drowning episodes. Fungal etiology should be suspected in appropriate scenarios when bacterial cultures or molecular tests are normal or when the infection worsens or fails to resolve with appropriate antibacterial therapy

    An analysis of metropolitan land-use by machine processing of earth resources technology satellite data

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    A successful application of state-of-the-art remote sensing technology in classifying an urban area into its broad land use classes is reported. This research proves that numerous urban features are amenable to classification using ERTS multispectral data automatically processed by computer. Furthermore, such automatic data processing (ADP) techniques permit areal analysis on an unprecedented scale with a minimum expenditure of time. Also, classification results obtained using ADP procedures are consistent, comparable, and replicable. The results of classification are compared with the proposed U. S. G. S. land use classification system in order to determine the level of classification that is feasible to obtain through ERTS analysis of metropolitan areas

    Determining density of maize canopy. 2: Airborne multispectral scanner data

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    Multispectral scanner data were collected in two flights over a light colored soil background cover plot at an altitude of 305 m. Energy in eleven reflective wavelength band from 0.45 to 2.6 microns was recorded. Four growth stages of maize (Zea mays L.) gave a wide range of canopy densities for each flight date. Leaf area index measurements were taken from the twelve subplots and were used as a measure of canopy density. Ratio techniques were used to relate uncalibrated scanner response to leaf area index. The ratios of scanner data values for the 0.72 to 0.92 micron wavelength band over the 0.61 to 0.70 micron wavelength band were calculated for each plot. The ratios related very well to leaf area index for a given flight date. The results indicated that spectral data from maize canopies could be of value in determining canopy density

    Urban land use monitoring from computer-implemented processing of airborne multispectral data

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    Machine processing techniques were applied to multispectral data obtained from airborne scanners at an elevation of 600 meters over central Indianapolis in August, 1972. Computer analysis of these spectral data indicate that roads (two types), roof tops (three types), dense grass (two types), sparse grass (two types), trees, bare soil, and water (two types) can be accurately identified. Using computers, it is possible to determine land uses from analysis of type, size, shape, and spatial associations of earth surface images identified from multispectral data. Land use data developed through machine processing techniques can be programmed to monitor land use changes, simulate land use conditions, and provide impact statistics that are required to analyze stresses placed on spatial systems

    Comparing soil boundaries delineated by digital analysis of multispectral scanner data from high and low spatial resolution systems

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    The author has identified the following significant results. Computer-aided analysis techniques used with aircraft MSS data showed that the spatial resolution was sufficient to recognize each soil mapping unit of the test site. Some difficulties occurred where different soil series were intricately mixed, and this mixture showed as a separate spectral mapping unit, or where the difference between two soils depended on the depth of silty surface material. Analysis of LANDSAT data with computer-aided techniques showed that it was not possible to find spectrally homogeneous soil features of the seven soil series on the 40 ha test site on the digital display or on a picture print map. Cluster techniques could be used on an extended test area to group spectrally similar data points into cluster classes

    The use of ERTS-1 multispectral imagery for crop identification in a semi-arid climate

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    Crop identification using multispectral satellite imagery and multivariate pattern recognition was used to identify wheat accurately in Greeley County, Kansas. A classification accuracy of 97 percent was found for wheat and the wheat estimate in hectares was within 5 percent of the USDA's Statistical Reporting Service estimate for 1973. The multispectral response of cotton and sorghum in Texas was not unique enough to distinguish between them nor to separate them from other cultivated crops

    Evaluation of surface water resources from machine-processing of ERTS multispectral data

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    The surface water resources of a large metropolitan area, Marion County (Indianapolis), Indiana, are studied in order to assess the potential value of ERTS spectral analysis to water resources problems. The results of the research indicate that all surface water bodies over 0.5 ha were identified accurately from ERTS multispectral analysis. Five distinct classes of water were identified and correlated with parameters which included: degree of water siltiness; depth of water; presence of macro and micro biotic forms in the water; and presence of various chemical concentrations in the water. The machine processing of ERTS spectral data used alone or in conjunction with conventional sources of hydrological information can lead to the monitoring of area of surface water bodies; estimated volume of selected surface water bodies; differences in degree of silt and clay suspended in water and degree of water eutrophication related to chemical concentrations
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