The optimal design of groundwater remediation systems are often subject to uncertain hydrogeological parameters and multiple uncertain objectives, involving minimization of remediation cost, and minimization of contaminant mass remaining in the aquifer. To design a robust and reliable groundwater remediation system, the stochastic simulations (Monte Carlo simulation) with multiple realizations of uncertain parameters, which are generated by Sequential Gaussian Simulation (SGSIM), are applied to tackle the uncertainty analysis of an synthetic remediation site. In the present study, we propose a probabilistic multi-objective evolutionary algorithm, named probabilistic improved niched Pareto genetic algorithm (PINPGA). PINPGA was improved by using stochastic simulation for objection function evaluations and incorporating probabilistic Pareto ranking and niche technique into INPGA for multi-objective selection operator. The proposed algorithm is then applied to the synthetic groundwater remediation test case. The performances of the methodology generating the reliability of the Pareto-optimal solution are assessed and compared using Monte Carlo analysis. The optimization results indicate that using such an uncertainty-based multi-objective optimization scheme can give reliable solution to groundwater remediation design, giving decision makers a practical and robust optimization tool.
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The inherent statistical heterogeneities associated with chain length, composition, and architecture of synthetic block copolymers compromise the quantitative interpretation of their self-assembly process. This study scrutinizes the contribution of molecular architecture on phase behaviors using discrete ABA triblock copolymers with precise chemical structure and uniform chain length. A group of discrete triblock copolymers with varying composition and symmetry were modularly synthesized through a combination of iterative growth methods and efficient coupling reactions. The symmetric ABA triblock copolymers self-assemble into long-range ordered structures with expanded domain spacings and enhanced phase stability, compared with the diblock counterparts snipped at the middle point. By tuning the relative chain length of two end blocks, the molecular asymmetry reduces the packing frustration, and thus increases the order-to-disorder transition temperature and enlarges the domain sizes. This study would serve as a quantitative model system to correlate the experimental observations with the theoretical assessments and to provide quantitative understandings for the relationship between molecular architecture and self-assembly.
Background: Clinical coding is important for reimbursement, resource planning, administration and medical research. Objective: This study aimed to evaluate clinical coding accuracy and its influencing factors, especially the benefits of physician–clinical coder collaboration. Method: Twenty-four physicians and one senior clinical coder participated in the quality audit. The audit checklist, assessment criteria, training program and physician–clinical coder collaboration mechanism were clearly defined. The homepage filling standards, homepage filling guidelines and the guidelines of the International Classification of Diseases were used as the assessment criteria for evaluating accuracy. Results: A total of 323,320 medical records were reviewed. The average accuracy of homepage completion was 60.4% and poor-quality homepages accounted for 89.9% of coding errors. The average coding accuracy and correction percentage were 83.4% and 62.3%, respectively. After physician–clinical coder collaboration, the coding accuracy increased from 78.9% to 87.1% (χ² = 799.904, p < 0.001) and correction percentage increased from 52.0% to 73.0% (χ² = 1628.015, p < 0.001). Multivariate logistic regression revealed that complexity of medical records (odds ratio (OR) = 0.625), quality of homepages (OR = 20.445), month of physician–clinical coder collaboration (OR = 1.133–2.297), coder’s major (OR = 1.616), coding experience (OR = 1.953), work engagement (OR = 1.290) and day of the week (OR = 1.054) were factors influencing coding accuracy. Conclusion: Physician–clinical coder collaboration effectively improved clinical coding accuracy and clinical coders benefited greatly. However, homepage quality was not improved. Furthermore, homepage quality and psychological factors influenced coding accuracy. Implications: Managers should implement regular standardised training for homepage completion, alongside ongoing improvements in coding practices and training.
Abstract The parallel distribution is a non-centralized mechanism for distributing indivisible items to agents, which can take into account computing efficiency, economic benefits and social equality. However, as most decentralized allocation mechanism, the parallel protocol is not strategy-proof. In this paper, supposed the manipulator has additive preferences with possible indifferences between single objects, we study the most basic manipulation problem under the parallel allocation mechanism. For any given set of items, we proved that the agent1 can determine whether all objects in the set can be guaranteed in polynomial time. In addition, we given an algorithm for finding pessimism and proved the correctness, completeness and time complexity of polynomial.
Welcome to the WIT Press eLibrary - the home of the Transactions of the Wessex Institute collection, providing on-line access to papers presented at the Institute's prestigious international conferences and from its State-of-the-Art in Science & Engineering publications.
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