Применение метода аналитических сетей для оптимизации процесса выбора стратегии развития пассажирского автотранспортного предприятия

В статье обозначена проблема снижения рентабельности пассажирских автотранспортных предприятий и связанные с этим сложности по реализации процедуры стратегического прогнозирования и управления предприятием. Обосновано использование метода аналитических сетей в модели поддержки принятия решений при управлении стратегией автотранспортного предприятия, представленной в работе [1], в качестве инструмента, позволяющего формализовать экспертные знания на основных этапах оценки и выбора проектов стратегического развития. Описаны основные шаги и приведены результаты расчета алгоритма метода аналитических сетей в рамках данной модели.The article outlines the problem of reducing the profitability of passenger motor transport enterprises and the associated difficulties in implementing the procedure of strategic forecasting and enterprise management. The use of the method of analytical networks in the model of decision support in managing the strategy of a trucking enterprise presented in [1] is substantiated as a tool that allows to formalize expert knowledge at the main stages of evaluation and selection of projects for strategic development. The main steps and calculations of the algorithm algorithm for analytical networks within the framework of this model are described

Aortic valve stenotic area calculation from phase contrast cardiovascular magnetic resonance: the importance of short echo time

<p>Abstract</p> <p>Background</p> <p>Cardiovascular magnetic resonance (CMR) can potentially quantify aortic valve area (AVA) in aortic stenosis (AS) using a single-slice phase contrast (PC) acquisition at valve level: AVA = aortic flow/aortic velocity-time integral (VTI). However, CMR has been shown to underestimate aortic flow in turbulent high velocity jets, due to intra-voxel dephasing. This study investigated the effect of decreasing intra-voxel dephasing by reducing the echo time (TE) on AVA estimates in patients with AS.</p> <p>Method</p> <p>15 patients with moderate or severe AS, were studied with three different TEs (2.8 ms/2.0 ms/1.5 ms), in the main pulmonary artery (MPA), left ventricular outflow tract (LVOT) and 0 cm/1 cm/2.5 cm above the aortic valve (AoV). PC estimates of stroke volume (SV) were compared with CMR left ventricular SV measurements and PC peak velocity, VTI and AVA were compared with Doppler echocardiography. CMR estimates of AVA obtained by direct planimetry from cine acquisitions were also compared with the echoAVA.</p> <p>Results</p> <p>With a TE of 2.8 ms, the mean PC SV was similar to the ventricular SV at the MPA, LVOT and AoV_{0 cm}(by Bland-Altman analysis bias ± 1.96 SD, 1.3 ± 20.2 mL/-6.8 ± 21.9 mL/6.5 ± 50.7 mL respectively), but was significantly lower at AoV₁and AoV_2.5(-29.3 ± 31.2 mL/-21.1 ± 35.7 mL). PC peak velocity and VTI underestimated Doppler echo estimates by approximately 10% with only moderate agreement. Shortening the TE from 2.8 to 1.5 msec improved the agreement between ventricular SV and PC SV at AoV_{0 cm}(6.5 ± 50.7 mL vs 1.5 ± 37.9 mL respectively) but did not satisfactorily improve the PC SV estimate at AoV_{1 cm}and AoV_{2.5 cm}. Agreement of CMR AVA with echoAVA was improved at TE 1.5 ms (0.00 ± 0.39 cm²) versus TE 2.8 (0.11 ± 0.81 cm²). The CMR method which agreed best with echoAVA was direct planimetry (-0.03 cm²± 0.24 cm²).</p> <p>Conclusion</p> <p>Agreement of CMR AVA at the aortic valve level with echo AVA improves with a reduced TE of 1.5 ms. However, flow measurements in the aorta (AoV 1 and 2.5) are underestimated and 95% limits of agreement remain large. Further improvements or novel, more robust techniques are needed in the CMR PC technique in the assessment of AS severity in patients with moderate to severe aortic stenosis.</p

Educational level, prevalence of hysterectomy, and age at amenorrhoea: a cross-sectional analysis of 9536 women from six population-based cohort studies in Germany

BACKGROUND: Hysterectomy prevalence has been shown to vary by education level. Hysterectomy influences age at amenorrhoea. The aim of this study was to examine these associations in Germany within population-based data sets. METHODS: Baseline assessments in six population-based cohorts took place from 1997 through 2006 and included 9,548 women aged 20–84 years. All studies assessed hysterectomy history, school and professional degrees. Degrees were categorized into three levels each. Adjusted prevalence ratios and 95% confidence intervals (95% CI) were estimated. RESULTS: Prevalences were higher in West Germany than East Germany, increased by age, and leveled off starting at 55–64 years. The age- and study-adjusted prevalence ratio (lowest versus highest school level) was 2.61 (95% CI: 1.28-5.30), 1.48 (95% CI: 1.21-1.81), and 1.01 (95% CI: 0.80-1.28) for women aged 20–45, 45–64, and 65 and more years respectively. The estimated adjusted prevalence ratios per one unit decrement of the educational qualification score (range 1 = lowest, 8 = highest) were 1.29 (95% CI: 1.02-1.64), 1.08 (95% CI: 1.04-1.12), and 0.98 (95% CI: 0.93-1.03) for women aged 20–44, 45–64, and 65–84 years respectively. Age at amenorrhoea was on average 6.2 years lower (43.5 years versus 49.7 years) among women with a history of hysterectomy than those without. CONCLUSIONS: Lower educational level was associated with a higher hysterectomy prevalence among women aged 20–64 years. Several mediators associated with educational level and hysterectomy including women’s disease risk, women’s treatment preference, and women’s access to uterus-preserving treatment may explain this association. At population level, hysterectomy decreases the age of amenorrhoea on average by 6.2 years