Stochastic Optimization for Network-Constrained Power System Scheduling Problem

The stochastic nature of demand and wind generation has a considerable effect on solving the scheduling problem of a modern power system. Network constraints such as power flow equations and transmission capacities also need to be considered for a comprehensive approach to model renewable energy integration and analyze generation system flexibility. Firstly, this paper accounts for the stochastic inputs in such a way that the uncertainties are modeled as normally distributed forecast errors. The forecast errors are then superimposed on the outputs of load and wind forecasting tools. Secondly, it efficiently models the network constraints and tests an iterative algorithm and a piecewise linear approximation for representing transmission losses in mixed integer linear programming (MILP). It also integrates load shedding according to priority factors set by the system operator. Moreover, the different interactions among stochastic programming, network constraints, and prioritized load shedding are thoroughly investigated in the paper. The stochastic model is tested on a power system adopted from Jeju Island, South Korea. Results demonstrate the impact of wind speed variability and network constraints on the flexibility of the generation system. Further analysis shows the effect of loss modeling approaches on total cost, accuracy, computational time, and memory requirement

Retrospective review of antiretroviral therapy program data in accredited private hospitals in Addis Ababa City Administration, Ethiopia

Background: Ethiopia is committed to improving access to human immunodeficiency virus (HIV) care and antiretroviral therapy (ART) service. In May 2005, some private hospitals in Addis Ababa City Administration received accreditation to provide ART services to eligible patients.Objective: To examine and describe the achievements of the ART Program in accredited private hospitals.Methods: Descriptive retrospective analyses of reported ART Program Data from accredited private hospitals, between May 2005 and 31st December 2009. The aggregate data was obtained from Addis Ababa Regional Health Bureau and consisted of information about patients enrolled for care, those who started ART, and those presently are on ART.Results: During the study period, 10,849 patients were enrolled for care, 9,442 who had just started ART and 5,608 already on it across the study private facilities. In general close to 75% of the total patients enrolled for  care at five facilities. Although the majority (87%) had started treatment in the past, only 59.4% were currently on treatment. Overall, the program retained 66.4% of the patients (n=6,270) and attrition was 32% (n=3,021).Conclusions: Differences in patient enrollment for care, ART initiation and retention were observed across facilities. A significant number of patients discontinued treatment and their outcome status was unclear. A better monitoring and reporting of ART Program Data will improve program quality. An effective strategy is needed to enhance patient retention and tracing in the accredited private hospitals in Addis Ababa City Administration. [Ethiop J Health Dev. 2011;25(2):110-115

EC11-101 Spring Seed Guide

Welcome to the 2011 Spring Seed Guide. Corn, soybean, sorghum, and alfalfa are included in this seed guide. This circular is a progress report of variety trials conducted by personnel of the Agronomy Department, West Central, and Northeast Extension Centers, and their associated agricultural laboratories and the associates of the University of Wyoming at SAREC

Evapotranspiration Rates of Three Sweet Corn Cultivars under Different Irrigation Levels

Understanding plants’ response to different irrigation levels is essential for developing effective irrigation scheduling practices that conserve water without affecting plant growth and yield. The objective of this study was to evaluate the responses of three sweet corn (Zea mays var. saccharata) cultivars 1170, 8021, and Battalion under three irrigation levels (50%, 75%, and 100%). Irrigation treatments were based on soil moisture management allowable depletion. Replicated trials were conducted, in an open field using 1-gal containers, at the Tropical Research and Education Center, Homestead, FL. A drip system with microsprinklers was used for irrigation. Daily crop evapotranspiration (ETc) rates were measured using a digital scale based on differences in weights of soil containers and plants. Reference evapotranspiration (ETo) was calculated using the FAO-Penman-Monteith equation. Crop-coefficient (Kc) values for the three cultivars were calculated from measured ETc and calculated ETo. In addition, leaf area, stomatal conductance, and fresh biomass were measured. Total irrigation amounts corresponding to the 50%, 75%, and 100% treatments were 116, 162, and 216 mm, and total ETc values were 128, 157, and 170 mm, respectively. The two deficit irrigation treatments (50% and 75%) resulted in a reduction of ETc for the three cultivars compared with the 100% irrigation treatments. Results also showed that under 75% and 100% treatments, Kc values were usually greater than 1 for the three cultivars and reached as high as 1.5. Additionally, leaf area and fresh biomass weight in the 50% treatment were mostly lower than in the 75% or 100% treatments

Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine

Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine

Partitioning the impacts of land use/land cover change and climate variability on water supply over the source region of the Blue Nile Basin

Water plays a vital role in sustaining the natural functioning of the entire ecosystem that supports life on Earth. It plays key roles in the well‐being of society in numerous ways. However, climate variability and land use land cover (LULC) change have caused spatiotemporal water supply variation. Disentangling the effects of climate variability from LULC change on water supply is crucial for sustainable water resource management. The main purpose of this study is, therefore, to disentangle the relative contribution of LULC change and climate variability to the overall average annual water supply variation. Residual trends analysis combined with Integrated Valuation of Environmental Services and Tradeoffs (InVEST) annual water yield model was adopted to perform simulations and disentangle the relative impacts of climate variability and LULC change. Ground and satellite data were used in this study. The study area has experienced a significant increasing wetness trend and significant LULC dynamics between 2003 and 2017. As a result, an increasing water supply was observed due to the joint effects of climate variability and LULC change in the watershed (203 mm). The contribution of climate variability was 94%, whereas LULC contributes only 6% from 2003 to 2017. Climate variability negatively led to water supply variation while LULC change contributed positively from 2010 to 2017. Although the ongoing soil and water conservation (SWC) practices improved vegetation cover and water retention of the watershed, climate variability is the main driver of water supply variation. Therefore, SWC practices should incorporate ecosystem‐based climate change adaptation strategies and scale up to community‐based integrated watershed management to sustain water supply