Quantification of interpoint topographic correlations of threshold values in glaucomatous visual fields

Purpose: The authors sought to quantify neighboring and distant interpoint correlations of threshold values within the visual field in patients with glaucoma. Methods: Visual fields of patients with confirmed or suspected glaucoma were analyzed (n = 255). One eye per patient was included. Patients were examined using the 32 program of the Octopus 1-2-3. Linear regression analysis among each of the locations and the rest of the points of the visual field was performed, and the correlation coefficient was calculated. The degree of correlation was categorized as high (r > 0.66), moderate (0.66 = r > 0.33), or low (r = 0.33). The standard error of threshold estimation was calculated. Results: Most locations of the visual field had high and moderate correlations with neighboring points and with distant locations corresponding to the same nerve fiber bundle. Locations of the visual field had low correlations with those of the opposite hemifield, with the exception of locations temporal to the blind spot. The standard error of threshold estimation increased from 0.6 to 0.9 dB with an r reduction of 0.1. Conclusion: Locations of the visual field have highest interpoint correlation with neighboring points and with distant points in areas corresponding to the distribution of the retinal nerve fiber layer. The quantification of interpoint correlations may be useful in the design and interpretation of visual field tests in patients with glaucoma.

Comparison of two fast strategies, SITA fast and TOP, for the assessment of visual fields in glaucoma patients

Purpose: To compare two fast threshold strategies of visual field assessment; SITA Fast (HSF) and Tendency Orientated Perimetry (TOP), in detecting visual field loss in patients with glaucoma. Methods: Seventy-six glaucoma, ocular hypertensive and normal patients had HSF and TOP performed in random order. Quantitative comparisons for the global visual field indices - mean deviation and defect (MD) for HSF and TOP, and pattern standard deviation (PSD) for HSF and loss variance (LV) for TOP - were made using correlation coefficients. Humphrey global parameters were converted to Octopus equivalents, and method comparison analysis was used to determine agreement between the two strategies. Test duration times were compared using t-test. Sensitivity and specificity for these two algorithms were determined according to predetermined criteria. Results: High correlation coefficient values were obtained for MD measurements between HSF and TOP (r=-0.89, P

Generation of scaled protogalactic seed magnetic fields in laser-produced shock waves

The standard model for the origin of galactic magnetic fields is through the amplification of seed fields via dynamo or turbulent processes to the level consistent with present observations. Although other mechanisms may also operate, currents from misaligned pressure and temperature gradients (the Biermann battery process) inevitably accompany the formation of galaxies in the absence of a primordial field. Driven by geometrical asymmetries in shocks associated with the collapse of protogalactic structures, the Biermann battery is believed to generate tiny seed fields to a level of about 10 gauss (refs 7, 8). With the advent of high-power laser systems in the past two decades, a new area of research has opened in which, using simple scaling relations, astrophysical environments can effectively be reproduced in the laboratory. Here we report the results of an experiment that produced seed magnetic fields by the Biermann battery effect. We show that these results can be scaled to the intergalactic medium, where turbulence, acting on timescales of around 700 million years, can amplify the seed fields sufficiently to affect galaxy evolution.

Soil Moisture Deficit as a predictor of the trend in soil water status of grass fields

Nutrient loss from agricultural land following organic fertilizer spreading can lead to eutrophication and poor water quality. The risk of pollution is partly related to the soil water status during and after spreading. In response to these issues, a decision support system (DSS) for nutrient management has been developed to predict when soil and weather conditions are suitable for slurry spreading. At the core of the DSS, the Hybrid Soil Moisture Deficit (HSMD) model estimates soil water status relative to field capacity (FC) for three soil classes (well, moderately and poorly drained) and has potential to predict the occurrence of a transport vector when the soil is wetter than FC. Three years of field observation of volumetric water content was used to validate HSMD model predictions of water status and to ensure correct use and interpretation of the drainage classes. Point HSMD model predictions were validated with respect to the temporal and spatial variations in volumetric water content and soil strength properties. It was found that the HSMD model predictions were well related to topsoil water content through time, but a new class intermediate between poor and moderate, perhaps ‘imperfectly drained’, was needed. With correct allocations of a field into a drainage class, the HSMD model predictions reflect field scale trends in water status and therefore the model is suitable for use at the core of a DSS.