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A cyclic storage (CS) system is defined as physically-integrated and operationally interconnected surface water and groundwater subsystems with full direct interactions between the subsystems. The proposed definition treats surface and subsurface impoundment subsystems as competing and potentially interconnected parallel storage facilities that minimize most of the problems associated with large-scale surface impoundments for water supply purposes. This paper emphasizes on the development and implementation of a hybrid two-stage genetic algorithm (GA)-linear programming (LP) algorithm to optimize the design and operation of a nonlinear, nonconvex, and large-scale semidistributed, CS system in an irrigable area. Performance of the proposed model is tested with a 240-period problem where other approaches failed to locate a feasible solution. For optimal operation of the system, a set of operating rules are developed for the joint utilization of surface and subsurface storage capacities to meet a predefined demand minimizing construction and operation cost over a 20-seasonal planning period. Results show that CS dominates a noncyclic storage system both in cost and operation flexibility. CE Database subject headings: Hybrid methods; Algorithms; Decomposition; Hydraulic design; Reservoirs. Author keywords: Hybrid methods; Decomposition; Genetic algorithms; cyclic storage; Hydraulic design; Operation. DOI: 10.106l/(ASCE)0733-9496(2010)136:1(59)

Objective: The purpose of the study is to examine diabetes screening and monitoring among Latino individuals as compared with non-Latino White individuals and to better understand how we can use neighborhood data to address diabetes care inequities.Research Design and Methods: This is a retrospective observational study linked with neighborhood-level Latino subgroup data obtained from the American Community Survey. We used generalized estimating equation negative binomial and logistic regression models adjusted for patient-level covariates to compare annual rates of glycated hemoglobin (HbA1c) monitoring for those with diabetes and odds of HbA1c screening for those without diabetes by ethnicity and among Latinos living in neighborhoods with low (0.0-22.0%), medium (22.0-55.7%), and high (55.7-98.0%) population percent of Mexican origin.Results: Latino individuals with diabetes had 18% higher rates of HbA1c testing than non-Latino White individuals with diabetes (adjusted rate ratio [aRR] 1.18 [95% CI 1.07-1.29]), and Latinos without diabetes had 25% higher odds of screening (adjusted odds ratio 1.25 [95% CI 1.15-1.36]) than non-Latino White individuals without diabetes. In the analyses in which neighborhood-level percent Mexican population was the main independent variable, all Latinos without diabetes had higher odds of HbA1c screening compared with non-Latino White individuals, yet only those living in low percent Mexican-origin neighborhoods had increased monitoring rates (aRR 1.31 [95% CI 1.15-1.49]).Conclusions: These findings reveal novel variation in health care utilization according to Latino subgroup neighborhood characteristics and could inform the delivery of diabetes care for a growing and increasingly diverse Latino patient population. Clinicians and researchers whose work focuses on diabetes care should take steps to improve equity in diabetes and prevent inequity in treatment. [ABSTRACT FROM AUTHOR]

BACKGROUND: Foreign-born Latino children in the United States (US) have poor asthma outcomes, but the role of routine care utilization in these outcomes is unclear. Our objective was to compare select ambulatory care utilization measures for asthma between foreign-born Latino, US-born Latino, and non-Hispanic white children. METHODS: Using a multistate network of clinics with a linked electronic health record, we compared the International Classification of Disease (ICD)-coded asthma diagnosis among those with respiratory symptoms, electronic health records documentation of diagnosis, prescriptions, and influenza vaccination of foreign-born and US-born Latino children, and non-Hispanic white children over a 10+ year study period. We also examined outcomes by country of birth in children from Mexico, Cuba, and Guatemala. RESULTS: Among our study population (n = 155,902), 134,570 were non-Hispanic white, 19,143 were US-born Latino, and 2189 were foreign-born Latino. Among those with suspicious respiratory symptoms, there was no difference between these groups in the predicted probability of an ICD-coded asthma diagnosis. US-born Latino children with asthma were less likely to have asthma documented on their problem list, more likely to have an albuterol prescription, and less likely to have an inhaled steroid prescribed. All Latino children had higher rates of influenza vaccination than non-Hispanic white children. CONCLUSIONS: In a national network, there were few disparities between Latino (US- and foreign-born) children and non-Hispanic white comparators in many common asthma care services, except some measures in US-born Latino children. Providers should understand that their US-born Latino children may be at elevated risk for not receiving adequate asthma care. [ABSTRACT FROM AUTHOR]

The compartmental modeling approach has been widely used for simulating contaminant transport in porous media and surface waters. Yet a commonly used compartmental model that has only first-order accuracy may introduce considerable numerical errors under certain circumstances. Following a review of compartmental systems and compartmental modeling methodologies, performance and limitations of such a compartmental model are discussed. In particular, improvement approaches, including multipoint, high-order, linear, and nonlinear methods, are presented in detail. Finally, a number of testing problems are examined and various compartmental models that describe three-phase (dissolved, adsorbed, and vapor phases) contaminant transport in unsaturated porous media are compared with each other and also with standard numerical and analytical counterparts. The comparisons highlight the accuracy, applicability, and limitations of different compartmental models. DOI: 10.1061/(ASCE)0733-9372(2006)132:2(211) CE Database subject headings: Contaminants; Simulation models; Unsaturated soils; Vadose zone; Closed form solutions; Numerical models.

A physically based, one-dimensional, mathematical model is developed to simulate transport of herbicides applied to roadsides into adjacent surface water. Herbicide transport by overland flow, infiltrating water, and subsurface flow is considered. The model accounts for advection, dispersion, equilibrium linear sorption in the soil, and first-order decay of the herbicides. Chemical transport between soil and overland flow is described using a rate-limited mass exchange between the two compartments that is proportional to the difference between the chemical concentration in overland flow and the pore water with a proportionality constant that is a function of overland flow characteristics and rain intensity. For simulating overland and subsurface flow, the kinematic wave equation is solved using a Crank-Nicolson finite difference scheme. Richards' equation is solved using a Galerkin finite element method to model infiltration, and the transport equation is solved using a finite difference method. The model is calibrated and verified using extensive field data on the runoff of five herbicides with a range of physical-chemical properties at two field sites. Good agreement is obtained between predicted and measured event-mean concentrations in runoff and the herbicide concentration remaining in the application-zone soil. CE Database subject headings: Overland flow; Vadose zone; Contamination, Storm runoff; Mathematical models; Numerical models; Herbicides.

Presented herein is an attempt to put into practice the multicriteria decision making technique of compromise programming for a real urban water management case study in the city of Zahidan in Iran. Zahidan, the capital of Sistan and Balouchistan Province, faces serious water problems in terms of both quality and quantity. To satisfy future water demands, a long-distance water transmission project is being implemented. Compromise programming is applied to aiding decision makers in selecting the best possible alternatives for distribution of both available and the transmitted water in the city. The results obtained reveal that the method is capable of being employed by decision-makers for comprehensive urban water management studies. CE Database subject headings: Urban areas; Water management; Water supply; Decision making; Sensitivity analysis; Iran; Case reports.

Energy costs constitute the largest expenditure for nearly all water utilities worldwide and can consume up to 65% of a water utility's annual operating budget. One of the greatest potential areas for energy cost savings is in the scheduling of pump operations. This paper presents a new management model, WAPIRRA Scheduler, for the optimal design and operation of water distribution systems. The model makes use of the latest advances in genetic algorithm (GA) optimization to automatically determine annually the least cost of pumping stations while satisfying target hydraulic performance requirements. Optimal design and operation refers to selecting pump type, capacity, and number of units as well as scheduling the operation of irrigation pumps that results in minimum design and operating cost for a given set of demand curves. The optimization process consists of three main steps: (1) generating randomly an initial set of pump combinations to start the optimization process for a given demand-duration curve; (2) minimizing the total annual cost, which consists of operation and maintenance costs and depreciation cost of the initial investment, by changing the set and discharge of pump sets based on the provided model; and (3) achieving the final criterion to stop the optimization process and reporting the optimized results of the model. Computational analysis is based upon one major objective function and solving it by means of a computer program that is developed following the GA approach to find the optimized solution of generated equations. Application of the model to a real-world project shows considerable savings in cost and energy. DOI: 10.1061/(ASCE)0733-9437(2004)130:5(357) CE Database subject headings: Pumping stations; Design; Irrigation; Algorithms; Operation; Energy consumption.

A methodology based on solving a large-scale nonlinear programming problem is presented for the optimal design and operation of pumping stations. Optimum design and operation refers to the selection of pump type, capacity, and number of units as well as scheduling the operation of irrigation pumps that results in minimum design and operating cost for a given set of demand curves. The design criteria for such pumping stations are based fundamentally on some important and critical parameters, such as pump capacity, number of units, types of pumps, and civil works. The optimization process consists of three main steps: (1) determination of minimum yearly consumed energy; (2) minimization of the total cost for all sets of pumping stations; and (3) selection of the least-cost set among the feasible sets of pumping stations, recognizing a combination of the cited criteria. The computational analysis is based upon one major objective function and a computer program, which is developed to solve the generated equations. Application of the model to the Farabi Agricultural and Industrial Project, Iran, shows considerable savings, about 25% in total annual cost of the pumping station. DOI: 10.1061/(ASCE)0733-9437(2003)129:3(149) CE Database subject headings: Pumping station; Optimization; Lagrangian functions; Irrigation.

It is uncertain if disparities in asthma diagnosis between Latino and non-Hispanic white children stem from differences in diagnosis over time among children presenting with similar clinical scenarios suggestive of asthma. We evaluated the odds of International Classification of Disease (ICD)-coded asthma diagnosis in Latino (English and Spanish preferring) and non-Hispanic white children, overall (N = 524,456) and among those presenting with possible asthma indicators (N = 85,516) over a 13-year period, using electronic health record data from a multi-state network of community health centers. Among those with possible asthma indicators, Spanish-preferring Latinos had lower adjusted odds of ICD-coded asthma diagnosis compared to non-Hispanic whites (OR = 0.87, 95%CI = 0.77-0.99); English-preferring Latinos did not differ from non-Hispanic whites. Differences in ICD-coded diagnosis between ethnicity/language groups varied by presenting symptom. Spanish-preferring Latino children may be less-likely to have ICD-coded asthma documented in the EHR when presenting with certain clinical indicators suggestive of asthma. Clinicians should be cognizant of the need for the follow-up of these indicators in Spanish-preferring Latino children. [ABSTRACT FROM AUTHOR]

Introduction: National reports suggest that Hispanic patients may underutilize influenza and pneumococcal vaccination, although studies sometimes conflict on this point. A clearer picture of adult immunization utilization in older Hispanic patients is necessary to ensure equity in adult vaccinations. Methods: Using electronic health records from 648 community health centers (CHCs) across 21 states, we compared English‐preferring Hispanic patients, Spanish‐preferring Hispanic patients, and Non‐Hispanic White (NHW) adults aged ≥50 years across five outcomes between 2012–2017: (1) Odds of ever receiving pneumococcal vaccination after age 65, (2) Odds of ever receiving ≥2 pneumococcal vaccinations for those ≥65, (3) odds of vaccination between the ages of 50 and 64 for those with diabetes or heart disease, (4) odds of influenza vaccine, and (5) annual rate of influenza vaccination. Results: Of our total study sample (N = 143,869), 85,562 were age 50–64 during the entire study period, and 65,977 were ≥65 at some point during the study period. In patients aged 50–64, Spanish‐preferring Hispanic patients were more likely to have ever had an influenza vaccination (covariate‐adjusted odds ratio [aOR] = 1.33, 95% CI = 1.29–1.37), had higher rates of annual influenza vaccination (covariate‐adjusted rate ratio [aRR] = 1.41, 95% CI = 1.38–1.44), and higher odds of pneumococcal vaccination (aOR = 1.87, 95% CI = 1.76–1.98) than NHW patients. These findings were similar in Spanish‐preferring Hispanic patients ≥65. English‐preferring Hispanics ≥65 were less likely than NHW patients to ever have an influenza vaccination (aOR = 0.91, 95% CI = 0.85–0.98) and to have ever received at least one (aOR = 0.92, 95% CI = 0.86–0.99) or two (aOR = 0.86, 95% CI = 0.77–0.95) pneumococcal vaccine doses. Conclusions: In a multistate CHC network, Spanish‐preferring Hispanic patients were more likely to receive influenza and pneumococcal vaccinations than NHW patients; older English‐preferring Hispanic patients were often less likely than NHW patients to receive these vaccinations. In vaccine initiatives, English‐preferring Hispanic patients may be at higher risk of vaccination inequity. [ABSTRACT FROM AUTHOR]

When an area to be irrigated has a high slope gradient in the manifold line direction, an option is to use a tapered pipeline to economize on pipe costs and to keep pressure head variations within desired limits. The objective of this paper is to develop a linear optimization model to design a microirrigation system with tapered, downhill manifold lines, minimizing the equivalent annual cost of the hydraulic network and the annual pumping cost, and maximizing the emission uniformity previously established to the subunit. The input data are irrigation system layout, cost of all hydraulic network components, and electricity price. The output data are equivalent annual cost, pipeline diameter in each line of the system, pressure head in each node, and total operating pressure head. To illustrate its capability, the model is applied in a citrus orchard in Sao Paulo State, Brazil, considering slopes of 3, 6, and 9%. The model proved to be efficient in the design of the irrigation system in terms of the emission uniformity desired. DOI: 10.1061/(ASCE)0733-9437(2002)128:2(116) CE Database keywords: Optimization models; Irrigation; Slopes; Linear programming; Water pipelines; Costs.

This paper develops a forward dynamic programming (FDP) model to solve the problem of reservoir operation and irrigation scheduling. The typical scenario for application of the model is composed of a system of two reservoirs in parallel supplying water to as many as three irrigation districts. Two models are coupled. The interseasonal model defines seasonal deliveries from the reservoir system. The intraseasonal model uses area and water allocations generated from the interseasonal model to produce an irrigation scheduling for the individual farms in one of the irrigation districts in the reservoir system. Crop evapotranspiration, reservoir evaporation, and inflows are forecasted. Upon availability of the current values, the forecast is updated and the model runs to generate a more precise irrigation schedule. This feature permits the application of the model for real-time operation of the irrigation district. At the end of the season, the intraseasonal model is updated. The FDP model is applied to a real watershed with a 2 year planning horizon for the interseasonal and 6 months for the intraseasonal model. DOI: 10.1061/(ASCE)0733-9437(2002)128:2(63) CE Database keywords: Optimization models; Irrigation scheduling; Reservoir operation; Dynamic programming.

In this paper, two different pesticide transport simulation models are presented and compared to carry out preliminary analysis on the applicability of those models in determining ground-water vulnerability to aldicarb contamination. The first model is a physically based analytical model that simulates ID pesticide movement in soils, based on the concept of complete mixing and 2D advective-dispersive transport in the aquifer. The second model is a numerical simulation model that links the existing numerical codes PRZM2, MODFLOW, and MT3D to simulate pesticide transport in the subsurface. The concentrations of aldicarb residues in soil and in the aquifer calculated by the two models are found to be in good agreement. However, the analytical model tends to produce an earlier arrival of the peak concentration in each year due to the assumption of complete mixing. It is also found that the infiltrating water following aldicarb application plays a significant role on the leaching potential of aldicarb, which is also affected by various meteorological and hydrological factors as well as by agricultural practices.