The Value in Verifying Medical Folklore

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

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

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

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

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

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

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

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

Aerosol particles in the mexican east pacific part I: processing and vertical redistribution by clouds

International audienceAirborne measurements of aerosol particle size distributions were made in the Mexican Intertropical Convergence Zone. The shape of the spectra at cloud base was compared with those at higher altitudes and near cloud boundaries to identify signatures of cloud processed particles. Of 78 cases analyzed, 71% showed enhancement in volume of super-micron particles, 49% had enhanced volume of sub-micron particles, 28% were homogeneous mixtures with boundary layer air, and 24% had super-micron particles removed by precipitation. Almost 100% of the cases with enhanced volume in sub-micron particles also occurred with enhanced super-micron volume. The enhanced volume in super-micron particles is approximately 10 times larger than the sub-micron enhancement. Cloud processed particles in marine air masses had twice as much enhancement of super-micron mass than found in particles processed by clouds formed from continental sources, likely a result of a more efficient coalescence process in clean, maritime clouds. These results are in qualitative agreement with previous observational and theoretical studies that relate enhancements in particle mass to the uptake by cloud droplets of SO2 and subsequent growth by coalescence

Cutline: 1981-82 scholarship winner - Ronan

Background: Self-management support has been shown to improve clinical outcomes. Health coaching, one form of self-management support, empowers patients within the health care system by providing information and through collaboratively developed care plans. Purpose: Assess the impact of The Lifestyle Initiative, a coaching-based health program utilized by Aurora Health Care caregivers or family members. Methods: The Lifestyle Initiative is a coaching-based approach for Aurora caregivers or family members enrolled in Aurora’s health insurance network. Individuals were recruited from the care management database, and all participants had an Aurora primary care provider. Participation was limited to those ≥ 18 years of age who had a diagnosis of type 2 diabetes or hypertension (or both), had glycated hemoglobin (A1c) ≤ 8.0, and were not on insulin. The Lifestyle Initiative was rolled out in three phases. Phase I: health coaching sessions through a standard web- and app-based platform (Noom Health), and access to a stress-management program (HeartMath). Phase II: health coaching sessions through a standard web- and app-based platform co-created by Aurora’s Department of Integrative Medicine and Noom Health, and access to HeartMath; Phase III: health coaching sessions through a standard web- and app-based platform (Noom Health), and a customized web- and app-based platform. Those enrolled in each phase acted as their own controls. Paired t-tests were used to compare pre- and postintervention results of each phase. Results: The majority of Phase I participants (n = 23; mean age 54.4 years) were female (91.3%) and white (52.2%). Preintervention A1c and blood pressure were not statistically different postintervention. However, pre- vs postintervention weights were statistically different (228.2 vs 218.5 lb; P \u3c 0.01), as well as pre- vs postintervention body mass index (37.3 vs 35.7 kg/m2; P \u3c 0.01). The majority of Phase II participants (n = 63; mean age 54.8 years) also were female (81.0%) and white (88.9%). Pre- and postintervention blood pressures were not statistically different. However, pre- vs postintervention A1c (7.2 vs 6.6; P \u3c 0.02), weights (229.6 vs 225.7 lb; P \u3c 0.05), and body mass index (37.1 vs 36.5 kg/m2; P \u3c 0.05) were statistically improved. Phase III data collection is underway. Conclusion: The Lifestyle Initiative health coaching program significantly improves certain health metrics when applied to health system employees and family members with diabetes or hypertension. Further study is needed to explore sustainability and the effects of more robust programs