scholarly journals The agent-based modelling as a decision support tool for brownfield redevelopment

2020 ◽  
Vol 18 (1) ◽  
pp. 65-75
Author(s):  
Tanja Mitrovic ◽  
Milica Vracaric
Keyword(s):  
Decision Support ◽  
Decision Support Tool ◽  
Sustainable Urban Development ◽  
Brownfield Redevelopment ◽  
Support Tool ◽  
Agent Based ◽  
Agent Based Modelling ◽  
History Of ◽  
Development Plans

In recent history of urban studies there is a focus on sustainable urban development and long-term strategies. Dealing with brownfield redevelopment is of vital importance for the prosperous practice of urban planning. The current decisionmaking methods for brownfield redevelopment are mainly used for evaluating on-site situation, but not for future development plans. The purpose of this paper is to consider potential uses of agent-based modelling (ABM) in brownfield redevelopment decision support practice. In these models, agents are assigned with certain rules of behaviour that define their mutual interactions and allow simulations in a previously defined spatial framework. These collective behaviours influence the spatial patterns through interactions of individuals, which is reflected in the fact that the actions of the agents do not simply sum to the activity of the whole. This tool provides us with opportunity of observing possible scenarios of future brownfield development and making adequate decisions and strategies accordingly.

An online decision support tool to evaluate ecological weed management strategies

Weed Science ◽  
2019 ◽  
Vol 67 (4) ◽  
pp. 463-473
Author(s):  
Douglas Bessette ◽  
Robyn Wilson ◽  
Christian Beaudrie ◽  
Clayton Schroeder
Keyword(s):  
Decision Support ◽  
Soil Quality ◽  
Weed Management ◽  
Decision Support Tool ◽  
The United States ◽  
Support Tool ◽  
Organic Farmers ◽  
Ecological Weed Management ◽  
On Farm

AbstractWeeds remain the most commonly cited concern of organic farmers. Without the benefit of synthetic herbicides, organic farmers must rely on a host of ecological weed management (EWM) practices to control weeds. Despite EWM’s ability to improve soil quality, the perceived rate of integrated EWM strategy adoption remains low. This low adoption is likely a result of the complexity in designing and evaluating EWM strategies, the tendency for outreach to focus on the risks of EWM strategies rather than their benefits, and a lack of quantitative measures linking the performance of EWM strategies to farmers’ on-farm objectives and practices. Here we report on the development and deployment of an easy-to-use online decision support tool (DST) that aids organic farmers in identifying their on-farm objectives, characterizing the performance of their practices, and evaluating EWM strategies recommended by an expert advisory panel. Informed by the principles of structured decision making, the DST uses multiple choice tasks to help farmers evaluate the short- and long-term trade-offs of EWM strategies, while also focusing their attention on their most important objectives. We then invited organic farmers across the United States, in particular those whose email addresses were registered on the USDA’s Organic Research Integrity Database, to engage the DST online. Results show considerable movement in participants’ (n = 45) preferences from practices focused on reducing weeding costs and labor in the short term to EWM strategies focused on improving soil quality in the long term. Indeed, nearly half of those farmers (48%) who initially ranked a strategy composed of their current practices highest ultimately preferred a better-performing EWM strategy focused on eliminating the weed seedbank over 5 yr.

scholarly journals Reduction of the long-term use of proton pump inhibitors by a patient-oriented electronic decision support tool (arriba-PPI): study protocol for a randomized controlled trial

Trials ◽  
2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Anja Rieckert ◽  
Annette Becker ◽  
Norbert Donner-Banzhof ◽  
Annika Viniol ◽  
Bettina Bücker ◽  
...  
Keyword(s):  
Randomized Controlled Trial ◽  
Decision Support ◽  
Controlled Trial ◽  
Decision Support Tool ◽  
Routine Care ◽  
Electronic Decision Support ◽  
Support Tool ◽  
Randomized Controlled ◽  
Cluster Randomized

Abstract Background Proton pump inhibitors (PPIs) are increasingly being prescribed, although long-term use is associated with multiple side effects. Therefore, an electronic decision support tool with the aim of reducing the long-term use of PPIs in a shared decision-making process between general practitioners (GPs) and their patients has been developed. The developed tool is a module that can be added to the so-called arriba decision support tool, which is already used by GPs in Germany in routine care. In this large-scale cluster-randomized controlled trial we evaluate the effectiveness of this arriba-PPI tool. Methods The arriba-PPI tool is an electronic decision support system that supports shared decision-making and evidence-based decisions around the long-term use of PPIs at the point of care. The tool will be evaluated in a cluster-randomized controlled trial involving 210 GP practices and 3150 patients in Germany. GP practices will be asked to recruit 20 patients aged ≥ 18 years regularly taking PPIs for ≥ 6 months. After completion of patient recruitment, each GP practice with enrolled patients will be cluster-randomized. Intervention GP practices will get access to the software arriba-PPI, whereas control GPs will treat their patients as usual. After an observation period of six months, GP practices will be compared regarding the reduction of cumulated defined daily doses of PPI prescriptions per patient. Discussion Our principal hypothesis is that the application of the arriba-PPI tool can reduce PPI prescribing in primary care by at least 15% compared to conventional strategies used by GPs. A positive result implies the implementation of the arriba-PPI tool in routine care. Trial registration German Clinical Trials Register, DRKS00016364. Registered on 31 January 2019.

scholarly journals Model-Based Decision Support Tools at Jugos S.A. Concentrated Fruit Juice Plant

2020 ◽  
Vol 50 (4) ◽  
pp. 255-268
Author(s):  
Aníbal M. Blanco ◽  
M. Susana Moreno ◽  
Carolina Taraborelli ◽  
Flavio D’Angelo ◽  
Facundo Iturmendi ◽  
...  
Keyword(s):  
Decision Support ◽  
User Interfaces ◽  
Decision Support Tool ◽  
Raw Material ◽  
Mixed Integer ◽  
Support Tool ◽  
Support Tools ◽  
Optimal Target ◽  
And Storage

We describe the development of a decision-support tool to assist in the operations of a large concentrated apple and pear juice plant. The tool’s objective is to generate detailed schedules of clarified juice batches to be produced in the following weeks considering incoming fruit forecasts, commercial commitments, and infrastructural constraints. The tool is based on two interactive modules, PLANNER and SIMOPT, with different and complementary purposes. Each module is based on mixed-integer models with specific inputs, outputs, and user interfaces. PLANNER consists of three submodules: (i) planning assigns a batch of concentrated juice to be produced on a specific day, taking into account cleaning activities, rest days, raw material availability, and production and storage constraints; (ii) preprocessing organizes juice orders in batches; and (iii) pooling provides a detailed monitoring of semielaborated juice in storage pools in terms of inventories and sugar and acid content. Finally, SIMOPT provides a detailed optimal operative condition of the plant together with a thorough calculation of specific costs. This information is used by PLANNER to evaluate the corresponding economic objective functions. Besides providing optimal target conditions to the plant and feasible production schedules, the developed tools generate production guidelines in the long term and allow performing scenario studies.

A decision-support tool to assist muscle-invasive bladder cancer patients choosing between radical cystectomy and chemoradiotherapy.

2018 ◽  
Vol 36 (6_suppl) ◽  
pp. 505-505
Author(s):  
Brian Christopher Baumann ◽  
Wei-Ting Hwang ◽  
Sharadha Srinivasan ◽  
Xingmei Wang ◽  
Ronac Mamtani ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Decision Support ◽  
Decision Support Tool ◽  
Short Term ◽  
Muscle Invasive Bladder Cancer ◽  
Support Tool ◽  
Trade Offs ◽  
Muscle Invasive ◽  
Break Even Point

505 Background: Patients with high-risk muscle-invasive bladder cancer (MIBC) who are borderline medically operable for radical cystectomy (RC) face a difficult decision between RC which has higher short-term treatment-related morbidity/mortality & chemoradiotherapy (CRT) which is better tolerated in the short-term but may have worse long-term cancer control outcomes. There are no existing decision support tools to assist patients & providers in understanding these trade-offs. Herein, we developed a visualization tool to inform patients & providers how the relative risks & benefits of RC & CRT vary over time with respect to overall survival (OS). Methods: We identified cT2-3 N0 M0 urothelial bladder cancer patients ≥65 y/o treated with RC +/- chemo (n = 5981) or definitive-dose CRT after TURBT (n = 793) in the National Cancer Database, 2003-2011. The database was split into a development & validation cohort. Multivariate Cox regression with time-varying hazard ratio was performed to assess pre-treatment factors associated with OS. The inverse probability of treatment weighting method using the propensity score was employed to reduce selection bias. External validation was performed. Visualization tool showing adjusted survival curves based on pre-op patient features was generated with input from patients & a multidisciplinary expert panel. Tool calculates median OS & the “break-even point,” where the short-term OS disadvantage of RC equals the long-term advantage of RC (i.e. the point where the restricted mean survival for RC & CRT are equal). Results: On MVA, significant predictors of OS were age, Charlson Deyo comorbidity index, & cT stage (p < 0.001 for all). Using these results, we iteratively developed a web application that utilizes clinical inputs to generate patient-specific survival curves that display estimated OS differences over time. Median OS, the break-even point, & percent alive at the break-even point are provided. Conclusions: This is the first decision-support tool developed to assist high-risk borderline operable MIBC patients & their providers in understanding the short-term & long-term trade-offs between RC & CRT. Additional testing is underway.

scholarly journals Role of Knowledge Networks and Boundary Organizations in Coproduction: A Short History of a Decision-Support Tool and Model for Adapting Multiuse Reservoir and Water-Energy Governance to Climate Change in California

2019 ◽  
Vol 11 (4) ◽  
pp. 823-849
Author(s):  
S. Ziaja
Keyword(s):  
Decision Support ◽  
Climate Adaptation ◽  
Decision Support Tool ◽  
Knowledge Networks ◽  
Positive Case ◽  
Theoretical Frameworks ◽  
Support Tool ◽  
Boundary Organizations ◽  
History Of ◽  
Collaborative Engagement

Abstract Climate adaptation relies on theoretical frameworks of coproduced science and knowledge networks to produce acceptable outcomes for politically contentious resources. As adaptation moves from theory to implementation, there is a need for positive case studies to use as benchmarks. Building from literature on actionable science this paper presents one such positive case—the development of a hydropower and reservoir decision-support tool. The focus of this history is on the multiple phases of interaction (and noninteraction) between researchers and a semidefined community of stakeholders. The lessons presented from the Integrated Forecast and Reservoir Management (INFORM) system project stress that collaborations between managers and researchers were crucial to the success of the project by building knowledge networks, which could outlast formal processes, and by incorporating policy preferences of end users into the model. The history also provides examples of how even successful collaborative projects do not always follow the usual expectations for coproduced science and shows that, even when those guidelines are followed, external circumstances can threaten the adoption of research products. Ultimately, this paper argues for the importance of building strong knowledge networks alongside more formal processes—like those in boundary organizations—for effective collaborative engagement.

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