943 resultados para Conformal Field Models in String Theory
Resumo:
Purpose The aim of this study was to test the correlation between Fourier-domain (FD) optical coherence tomography (OCT) macular and retinal nerve fibre layer (RNFL) thickness and visual field (VF) loss on standard automated perimetry (SAP) in chiasmal compression. Methods A total of 35 eyes with permanent temporal VF defects and 35 controls underwent SAP and FD-OCT (3D OCT-1000; Topcon Corp.) examinations. Macular thickness measurements were averaged for the central area and for each quadrant and half of that area, whereas RNFL thickness was determined for six sectors around the optic disc. VF loss was estimated in six sectors of the VF and in the central 16 test points in the VF. The correlation between VF loss and OCT measurements was tested with Spearman`s correlation coefficients and with linear regression analysis. Results Macular and RNFL thickness parameters correlated strongly with SAP VF loss. Correlations were generally stronger between VF loss and quadrantic or hemianopic macular thickness than with sectoral RNFL thickness. For the macular parameters, we observed the strongest correlation between macular thickness in the inferonasal quadrant and VF loss in the superior temporal central quadrant (rho=0.78; P<0.001) whereas for the RNFL parameters the strongest correlation was observed between the superonasal optic disc sector and the central temporal VF defect (rho=0.60; P<0.001).
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Objective: To determine intraocular pressure (IOP)-dependent and IOP-independent variables associated with visual field (VF) progression in treated glaucoma. Design: Retrospective cohort of the Glaucoma Progression Study. Methods: Consecutive, treated glaucoma patients with repeatable VF loss who had 8 or more VF examinations of either eye, using the Swedish Interactive Threshold Algorithm (24-2 SITA-Standard, Humphrey Field Analyzer II; Carl Zeiss Meditec, Inc, Dublin, California), during the period between January 1999 and September 2009 were included. Visual field progression was evaluated using automated pointwise linear regression. Evaluated data included age, sex, race, central corneal thickness, baseline VF mean deviation, mean follow-up IOP, peak IOP, IOP fluctuation, a detected disc hemorrhage, and presence of beta-zone parapapillary atrophy. Results: We selected 587 eyes of 587 patients (mean [SD] age, 64.9 [13.0] years). The mean (SD) number of VFs was 11.1 (3.0), spanning a mean (SD) of 6.4 (1.7) years. In the univariable model, older age (odds ratio [OR], 1.19 per decade; P = .01), baseline diagnosis of exfoliation syndrome (OR, 1.79; P = .01), decreased central corneal thickness (OR, 1.38 per 40 mu m thinner; P < .01), a detected disc hemorrhage (OR, 2.31; P < .01), presence of beta-zone parapapillary atrophy (OR, 2.17; P < .01), and all IOP parameters (mean follow-up, peak, and fluctuation; P < .01) were associated with increased risk of VF progression. In the multivariable model, peak IOP (OR, 1.13; P < .01), thinner central corneal thickness (OR, 1.45 per 40 mu m thinner; P < .01), a detected disc hemorrhage (OR, 2.59; P < .01), and presence of beta-zone parapapillary atrophy (OR, 2.38; P < .01) were associated with VF progression. Conclusions: IOP-dependent and IOP-independent risk factors affect disease progression in treated glaucoma. Peak IOP is a better predictor of progression than is IOP mean or fluctuation.
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This study conducted in 1999/2000 was designed to evaluate the efficacy of praziquantel against Schistosoma japonicum in an area with repeated chemotherapy (Area A) compared with a newly identified endemic focus (Area B) in Hunan Province, China. The population size was 2015 and 2180 in Areas A and B, respectively, of which 1129 and 1298 subjects received stool examination. A total of 230 subjects were identified by the Kato-Katz technique (4 smears per person) as being infected with S. japonicum, 124 in Area A (prevalence 11 %) and 106 in Area B (prevalence 8.2%). They were treated with a single oral dose of praziquantel (40 mg/kg) in the non-transmission season. A follow-up stool examination was made 50 days after treatment. Among the 220 cases followed, 22 were found stool-egg-positive, with an overall cure rate of 90 %, and 99 % reduction of infection intensity (eggs per gram stool). No significant difference was found in cure rates between the 2 areas (89.7% vs 90.3%). The efficacy of the drug in the area with repeated chemotherapy was not significantly different from that in the newly identified endemic focus. This study, therefore, suggests that the efficacy of praziquantel against S. japonicum has not changed in the Dongting Lake region after more than 14 years of mass chemotherapy, and there is no evidence of tolerance or resistance of S. japonicum against praziquantel.
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The drosophilid fauna in Australia offers an important study system for evolutionary studies. Larval hosts are unknown for most species, however, and this imposes serious limits to understanding their ecological context. The present paper reports the first systematic, large-scale field survey of potential larval hosts to be conducted, in order to obtain an overview of the host utilisation patterns of Australian drosophilids. Potential hosts (mostly fruit and fungi) were collected from different vegetation types in northern and eastern Australia. Host data were obtained for 81 drosophilid species from 17 genera (or 28% of the known Fauna). Most genera were restricted to either fruit or fungi, although Scaptodrosophila spp. and Drosophila spp. were recorded from fruit, fungi, flowers and compost, and Drosophila spp. also emerged from the parasitic plant Balanophora fungosa. There was no evidence that use of either fruit or fungi was correlated to host phylogeny. Drosophilids emerged from hosts collected from all sampled vegetation types (rainforest, open forest, heath and domestic environments). Vegetation type influenced drosophilid diversity, both by affecting host availability and because some drosophilid species apparently restricted their search for hosts to particular vegetation types.
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Evaluation of the performance of the APACHE III (Acute Physiology and Chronic Health Evaluation) ICU (intensive care unit) and hospital mortality models at the Princess Alexandra Hospital, Brisbane is reported. Prospective collection of demographic, diagnostic, physiological, laboratory, admission and discharge data of 5681 consecutive eligible admissions (1 January 1995 to 1 January 2000) was conducted at the Princess Alexandra Hospital, a metropolitan Australian tertiary referral medical/surgical adult ICU. ROC (receiver operating characteristic) curve areas for the APACHE III ICU mortality and hospital mortality models demonstrated excellent discrimination. Observed ICU mortality (9.1%) was significantly overestimated by the APACHE III model adjusted for hospital characteristics (10.1%), but did not significantly differ from the prediction of the generic APACHE III model (8.6%). In contrast, observed hospital mortality (14.8%) agreed well with the prediction of the APACHE III model adjusted for hospital characteristics (14.6%), but was significantly underestimated by the unadjusted APACHE III model (13.2%). Calibration curves and goodness-of-fit analysis using Hosmer-Lemeshow statistics, demonstrated that calibration was good with the unadjusted APACHE III ICU mortality model, and the APACHE III hospital mortality model adjusted for hospital characteristics. Post hoc analysis revealed a declining annual SMR (standardized mortality rate) during the study period. This trend was present in each of the non-surgical, emergency and elective surgical diagnostic groups, and the change was temporally related to increased specialist staffing levels. This study demonstrates that the APACHE III model performs well on independent assessment in an Australian hospital. Changes observed in annual SMR using such a validated model support an hypothesis of improved survival outcomes 1995-1999.
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Prior theoretical studies indicate that the negative spatial derivative of the electric field induced by magnetic stimulation may he one of the main factors contributing to depolarization of the nerve fiber. This paper studies this parameter for peripheral nerve stimulation (PNS) induced by time.-varying gradient fields during MRI scans. The numerical calculations are based on an efficient, quasi-static, finite-difference scheme and an anatomically realistic human, full-body model. Whole-body cylindrical and planar gradient sets in MRI systems and various input signals have been explored. The spatial distributions of the induced electric field and their gradients are calculated and attempts are made to correlate these areas with reported experimental stimulation data. The induced electrical field pattern is similar for both the planar coils and cylindrical coils. This study provides some insight into the spatial characteristics of the induced field gradients for PNS in MRI, which may be used to further evaluate the sites where magnetic stimulation is likely to occur and to optimize gradient coil design.
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A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.
Resumo:
A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.