Effects of intervention with the SAFE strategy on trachoma across Ethiopia.

BACKGROUND/AIMS: The impact of the SAFE strategy (surgery, antibiotics, face washing, environmental hygiene), recommended to eliminate blinding trachoma, is not well explored. We determined the operational effectiveness of the whole SAFE intervention package. METHODS: Analytical cross-sectional trachoma surveys were conducted in four program areas across Ethiopia before and after 3 years of intervention with the SAFE strategy. A total of 8358 children 1-9 years, 4684 people above 14 and 3572 households were assessed in the follow-up evaluations using methodologies recommended by the WHO. Effects were measured by comparing follow-up proportions with baseline estimates of four key indicators. RESULTS: Coverage was 36% for trichiasis surgery, 59% for antibiotic and 57% for health-promotion services. Prevalence of trachoma trichiasis (TT) decreased from 4.6% (95% CI: 3.6% to 5.8%) down to 2.9% (CI: 2.1% to 3.9%). Prevalence of trachoma inflammation-follicular (TF) dropped from 36.7% (33.9% to 39.6%) to 18.4% (CI: 15.4% to 21.8%). The proportion of unclean faces and households not using latrines fell from 72.8% (68.9% to 76.4%) and 74.5% (69.9% to 78.7%) down to 47.0% (CI: 43% to 51%) and 51.7% (47.2% to 56.2%), respectively. All the reductions related with antibiotic (TF), face washing (clean face) and environmental (latrine) components were statistically significant except for Surgery (TT). CONCLUSIONS: Considerable decline in the magnitude of trachoma and its risk factors was observed in areas where the SAFE strategy was implemented. The coverage of services should be maintained or improved in order to eliminate blinding trachoma by the year 2020

Influence of Electrode Material and Process Parameters on Surface Quality and MRR in EDM of AISI H13 using ANN

Electrical Discharge Machining (EDM) is a non conventional machining process where electrically conductive materials are machined by using precisely controlled spark that occurs between an electrode and a work piece in the presence of a dielectric fluid. It has been a demanding research area to model and optimize the EDM process in the present scenario. In the present p aper Artificial Neural Network (ANN) model has been proposed for the prediction of Material Removal Rate (MRR), Surface Roughness (SR) and Tool Wear Rate (TWR) in Electrical Discharge Machining (ED M) of AISI H13 Steel. For this purpose Neural Network Toolbox (nntool) with Matlab 7.1 has been used. The neural network based on process model has been generated to establish relationship between input process conditions ( Gap Voltage, Peak Current, Pulse On Time, Pulse Off Time and Electrode M aterial ) an d process responses (MRR, SR and TWR ). The ANN model has been trained and tested using the d ata generated from a series of experiments on EDM machine. The trained neural network system has been used to predict MRR , SR and TWR for different input conditions. The ANN model has been found efficient to predict EDM process response s for selected process conditions

CO J = 2 - 1 Emission from Evolved Stars in the Galactic Bulge

We observe a sample of 8 evolved stars in the Galactic Bulge in the CO J = 2 - 1 line using the Submillimeter Array (SMA) with angular resolution of 1 - 4 arcseconds. These stars have been detected previously at infrared wavelengths, and several of them have OH maser emission. We detect CO J = 2 - 1 emission from three of the sources in the sample: OH 359.943 +0.260, [SLO2003] A12, and [SLO2003] A51. We do not detect the remaining 5 stars in the sample because of heavy contamination from the galactic foreground CO emission. Combining CO data with observations at infrared wavelengths constraining dust mass loss from these stars, we determine the gas-to-dust ratios of the Galactic Bulge stars for which CO emission is detected. For OH 359.943 +0.260, we determine a gas mass-loss rate of 7.9 (+/- 2.2) x 10^-5 M_Sun/year and a gas-to-dust ratio of 310 (+/- 89). For [SLO2003] A12, we find a gas mass-loss rate of 5.4 (+/- 2.8) x 10^-5 M_Sun/year and a gas-to-dust ratio of 220 (+/- 110). For [SLO2003] A51, we find a gas mass-loss rate of 3.4 (+/- 3.0) x 10^-5 M_Sun/year and a gas-to-dust ratio of 160 (+/- 140), reflecting the low quality of our tentative detection of the CO J = 2 - 1 emission from A51. We find the CO J = 2 - 1 detections of OH/IR stars in the Galactic Bulge require lower average CO J = 2 - 1 backgrounds.Comment: 40 pages, 16 figures, appeared in the 1 March 2013 issue of the Astrophysical Journa