Automation of DEM Cutting for Hydrologic/Hydraulic Modeling

Hydrologic analysis is a critical part of transportation design because it helps ensure that hydraulic structures are able to accommodate the flow regimes they are likely to see. This analysis is currently conducted using computer simulations of water flow patterns, and continuing developments in elevation survey techniques result in higher and higher resolution surveys. Current survey techniques now resolve many natural and anthropogenic features that were not practical to map and, thus, require new methods for dealing with depressions and flow discontinuities. A method for depressional analysis is proposed that uses the fact that most anthropogenically constructed embankments are roughly more symmetrical with greater slopes than natural depressions. An enforcement method for draining depressions is then analyzed on those depressions that should be drained. This procedure has been evaluated on a small watershed in central Iowa, Walnut Creek of the South Skunk River, HUC12 # 070801050901, and was found to accurately identify 88 of 92 drained depressions and place enforcements within two pixels, although the method often tries to drain prairie pothole depressions that are bisected by anthropogenic features

Residence time distribution and hold-up in a cocurrent upflow packed bed reactor at elevated pressure

The residence time distribution in liquid phase was measured in a cocurrent upflow packed bed reactor for the system methanol-hydrogen at low Reynolds numbers and at elevated pressure. The plug flow with axial dispersion model was used to describe mixing in the system. The imperfect pulse method was used to measure the system response to a tracer pulse input. The parameters were calculated using the weighted moments method. The influence of the weighting factor was investigated. The experimental and theoretical outputs, as calculated by convolution, agreed very well. Different types of correlations were used for the Bodenstein number and liquid hold-up. From these correlations, the optimal one was selected for each parameter. A comparison was made between the ordinary moments and the weighted moments methods which led to the conclusion that the latter method is superior with respect to the accuracy of the estimated parameters and therefore strongly recommended

Can a supported self-management program for COPD upon hospital discharge reduce readmissions? A randomized controlled trial

Introduction: Patients with COPD experience exacerbations that may require hospitalization. Patients do not always feel supported upon discharge and frequently get readmitted. A Self-management Program of Activity, Coping, and Education for COPD (SPACE for COPD), a brief self-management program, may help address this issue. Objective: To investigate if SPACE for COPD employed upon hospital discharge would reduce readmission rates at 3 months, compared with usual care. Methods: This is a prospective, single-blinded, two-center trial (ISRCTN84599369) with participants admitted for an exacerbation, randomized to usual care or SPACE for COPD. Measures, including health-related quality of life and exercise capacity, were taken at baseline (hospital discharge) and at 3 months. The primary outcome measure was respiratory readmission at 3 months. Results: Seventy-eight patients were recruited (n=39 to both groups). No differences were found in readmission rates or mortality at 3 months between the groups. Ten control patients were readmitted within 30 days compared to five patients in the intervention group (P>0.05). Both groups significantly improved their exercise tolerance and Chronic Respiratory Questionnaire (CRQ-SR) results, with between-group differences approaching statistical significance for CRQ-dyspnea and CRQ-emotion, in favor of the intervention. The “Ready for Home” survey revealed that patients receiving the intervention reported feeling better able to arrange their life to cope with COPD, knew when to seek help about feeling unwell, and more often took their medications as prescribed, compared to usual care (P<0.05). Conclusion: SPACE for COPD did not reduce readmission rates at 3 months above that of usual care. However, encouraging results were seen in secondary outcomes for those receiving the intervention. Importantly, SPACE for COPD appears to be safe and may help prevent readmission with 30 days

Testing and modelling autoregressive conditional heteroskedasticity of streamflow processes

Conventional streamflow models operate under the assumption of constant variance or season-dependent variances (e.g. ARMA (AutoRegressive Moving Average) models for deseasonalized streamflow series and PARMA (Periodic AutoRegressive Moving Average) models for seasonal streamflow series). However, with McLeod-Li test and Engle's Lagrange Multiplier test, clear evidences are found for the existence of autoregressive conditional heteroskedasticity (i.e. the ARCH (AutoRegressive Conditional Heteroskedasticity) effect), a nonlinear phenomenon of the variance behaviour, in the residual series from linear models fitted to daily and monthly streamflow processes of the upper Yellow River, China. It is shown that the major cause of the ARCH effect is the seasonal variation in variance of the residual series. However, while the seasonal variation in variance can fully explain the ARCH effect for monthly streamflow, it is only a partial explanation for daily flow. It is also shown that while the periodic autoregressive moving average model is adequate in modelling monthly flows, no model is adequate in modelling daily streamflow processes because none of the conventional time series models takes the seasonal variation in variance, as well as the ARCH effect in the residuals, into account. Therefore, an ARMA-GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) error model is proposed to capture the ARCH effect present in daily streamflow series, as well as to preserve seasonal variation in variance in the residuals. The ARMA-GARCH error model combines an ARMA model for modelling the mean behaviour and a GARCH model for modelling the variance behaviour of the residuals from the ARMA model. Since the GARCH model is not followed widely in statistical hydrology, the work can be a useful addition in terms of statistical modelling of daily streamflow processes for the hydrological community

Early Category-Specific Cortical Activation Revealed by Visual Stimulus Inversion

Visual categorization may already start within the first 100-ms after stimulus onset, in contrast with the long-held view that during this early stage all complex stimuli are processed equally and that category-specific cortical activation occurs only at later stages. The neural basis of this proposed early stage of high-level analysis is however poorly understood. To address this question we used magnetoencephalography and anatomically-constrained distributed source modeling to monitor brain activity with millisecond-resolution while subjects performed an orientation task on the upright and upside-down presented images of three different stimulus categories: faces, houses and bodies. Significant inversion effects were found for all three stimulus categories between 70–100-ms after picture onset with a highly category-specific cortical distribution. Differential responses between upright and inverted faces were found in well-established face-selective areas of the inferior occipital cortex and right fusiform gyrus. In addition, early category-specific inversion effects were found well beyond visual areas. Our results provide the first direct evidence that category-specific processing in high-level category-sensitive cortical areas already takes place within the first 100-ms of visual processing, significantly earlier than previously thought, and suggests the existence of fast category-specific neocortical routes in the human brain