Prevalence and spatial concordance of visual field deterioration in fellow eyes of glaucoma patients.

PurposeTo examine the prevalence of visual field deterioration in contralateral eyes of patients with worsening open-angle glaucoma and to evaluate the spatial concordance of visual field deterioration between both eyes.MethodsOne hundred sixteen open-angle glaucoma patients who underwent 8 or more visual field examinations over ≥ 6 years of follow-up were included. The rates of the fast and slow components of visual field decay for each of 52 visual field test locations were calculated with point-wise exponential regression analysis. The spatial concordance of visual field deterioration in contralateral eyes was evaluated with a concordance ratio (calculated as the number of overlapping locations divided by the total number of deteriorating locations) and by comparing the rate of decay in corresponding modified glaucoma hemifield test clusters.ResultsThe average visual field mean deviation (± standard deviation [SD]) was -8.5 (± 6.4) dB and the mean (± SD) follow-up time was 9.0 (± 1.6) years. Sixty-three patients had mild damage, 23 had moderate damage, and 30 had severe damage. The mean concordance ratio (± SD) was 0.46 (± 0.32) for the mild group, 0.33 (± 0.27) for the moderate group, and 0.35 (± 0.21) for the severe group. Thirty-one patients (27%) had deterioration in concordant locations (p < 0.05). Visual field deterioration was greater in the superior hemifield than the inferior hemifield (p < 0.05) when evaluated with both the concordance ratio and modified glaucoma hemifield test cluster analysis methods.ConclusionsThere is only fair spatial concordance with regard to visual field deterioration between the both eyes of an individual. We conclude that testing algorithms taking advantage of inter-eye spatial concordance would not be particularly advantageous in the early detection of glaucomatous deterioration

A Performance Evaluation of Low Pressure Carbon Dioxide Discharge Test

For gaseous fire extinguishing systems, the maximum percent of agent in pipe, i.e., pipe volume vs. agent liquid volume should be determined for proper system design and performance by confirming the maximum length of pipe run in which their flow calculation methods can predict the discharge pressures and agent concentration. It is the purpose of this paper to determine the ability and limitations of the NFPA 12 flow calculation methodology to identify the maximum percent of agent in pipe by conducting full scale low-pressure CO2 system discharge tests. A total of twenty low-pressure CO2 system discharge tests were conducted under different conditions. If all the measured pressures at the three node points of pipe runs and the measured CO2 concentrations in the test enclosures did not deviate from the predicted values of computerized flow calculations by more than ¡¾10 percent, the tests were judged to be acceptable. In the test results, the low-pressure CO2 system with a pipe run exceeding 492 ft (150 m) was not likely to achieve the concentration required for fire extinguishment within the determined discharge time although the pipe network was installed in compliance with the calculations based on the pressure drop equation in NFPA 12

Product Market Competition And Analysts’ Forecasting Properties: Evidence From Korea

In this paper, we examine the association between product market competition and financial analysts’ forecasting properties in a sample of 76,621 analyst-firm-year observations in South Korea between 2000 and 2014. Using the Herfindahl–Hirschman Index to proxy for product market competition, we document that financial analysts are likely to issue less accurate and more optimistic forecasts in highly competitive product markets. In addition, we find that analysts’ reports show more optimism in stock recommendations in firms with high market competition

Large scale bias and the peak background split

Dark matter haloes are biased tracers of the underlying dark matter distribution. We use a simple model to provide a relation between the abundance of dark matter haloes and their spatial distribution on large scales. Our model shows that knowledge of the unconditional mass function alone is sufficient to provide an accurate estimate of the large scale bias factor. Then we use the mass function measured in numerical simulations of SCDM, OCDM and LCDM to compute this bias. Comparison with these simulations shows that this simple way of estimating the bias relation and its evolution is accurate for less massive haloes as well as massive ones. In particular, we show that haloes which are less/more massive than typical M* haloes at the time they form are more/less strongly clustered than formulae based on the standard Press-Schechter mass function predict.Comment: 8 pages, 6 figures, submitted to MNRAS corrected y-label for fig.4 (newlabel = 1 + oldlabel