707 research outputs found

    Case Studies of Canadian Environmental Decision Support Systems

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    Redesign of Lawrence Expressway and Pruneridge Avenue

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    In 2012, the segment of Pruneridge Avenue from Lawrence Expressway to Pomeroy Avenue saw a project called a Road Diet. A Road Diet refers to the replacement of vehicle lanes with bicycle lanes and a center turning lane, in order to create safe zones for cyclists and drivers on the same street. While the Road Diet sufficiently addressed the safety issues of the corridor, it severely worsened its traffic capacity, creating long queues along Pruneridge and on Lawrence Expressway during peak traffic hours as residents around the area commute to and from work. The queues are so long that many drivers decide to run red lights to avoid waiting additional cycles, introducing a new set of safety concerns. Pedestrians also had to deal with cars speeding through righthand turns between Pruneridge and Lawrence, because the visibility on the curb is very low at night. Finally, the center turn lane that was implemented on Pruneridge is very underutilized during peak hours, and that space could be used for something more efficient or useful than a suicide lane. This project aims to address the problems that the Road Diet introduced and some preexisting issues while maintaining the bike lanes to provide safety and encourage cycling in the area

    In Vitro Culture of 'Dog Ridge' Grapevine

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    Vitis champini ‘Dog Ridge’ grapevine is a potentially desirable rootstock for Texas grapevines because of its disease resistance. This selection is reported to be difficult to root through hardwood cuttage as is often practiced for grapevine. A study was undertaken to establish a protocol to propagate ‘Dog Ridge’ grapevine in vitro by comparing combinations of explant type, basal salts, and benzyladenine (BA) concentration to proliferate shoots followed by in vitro and ex vitro rooting. Shoot tip and axillary bud explants were harvested from actively growing stock plants, disinfested with 10% v/v Clorox, rinsed in sterile distilled water and cultured on either Murashige and Skoog (MS) or Woody Plant Medium (WPM) containing 0, 4.4 and 8.8 μM BA for 12 weeks. Axillary bud explants cultured on MS medium proliferated better than shoot tips. Axillary bud explants cultured on media containing 4.4 or 8.8 μM BA proliferated better than shoot tip explants regardless of the BA concentration in the medium. Tissue cultured shoots rooted in either WPM medium without BA in vitro or in Redi-earth® potting mix ex vitro. Shoots developed roots in vitro better than under ex vitro conditions

    A Loosely-Coupled Collaborative Integrated Environmental Modelling Framework

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    Integration of environmental models requires full support of the modelling community. When a large number of models are integrated, it requires consistency within scale, datasets, and model to model interactions to minimize the uncertainty among the models. The integrated environmental modelling (IEM) framework is a necessary approach to integrate multiple environmental models for a particular study. When modellers cannot afford considerable amount of time to get involved with full and tightly-integrated IEM or an IEM has very short time frame to complete, then a loosely-coupled collaborative IEM environment can provide the benefits of the integrated approach while minimizing the effort of each individual modeller. However, such a framework will require setting rules that all participants must adhere to. These rules address the issues of model inputs and model to model interaction. The framework should also provide value-added functionality to make the IEM framework more transparent and applicable

    Neural Networks and Dynamic Complex Systems

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    We describe the use of neural networks for optimization and inference associated with a variety of complex systems. We show how a string formalism can be used for parallel computer decomposition, message routing and sequential optimizing compilers. We extend these ideas to a general treatment of spatial assessment and distributed artificial intelligence

    Helping Students to Build Multicultural and Multidisciplinary Competences: A Pilot of Challenge-Based Collaborative Learning on a Digital Gamified Platform

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    Global issues such as poverty, hunger, and environmental problems are inextricable and cannot be solved comprehensively by homogeneous groups. With the advance of technology, collaborations with peoples at different geographical locations can be achieved effectively. Higher education in the 21st Century must therefore facilitate students to learn how to eclectically connect their creativity and problem-solving skills with technology, and most importantly to work with heterogeneous groups to solve complex global issues.This paper will elaborate on a pilot study of a project in Hong Kong, titled the CCGame Project, which aims to heighten students’ multicultural and multidisciplinary competences by deploying gamified learning and challenge-based learning. Team-based, self-guided learning is the core of the challenge-based learning approach. To preserve students’ interest in learning and accomplishing the tasks for the team, cloud-based learning platforms have been deployed. In the pilot, the online learning platform collected data for analysis of individual and team behaviour. The pilot demonstrated that students could work in a diverse team to complete a challenge. Evidence-based results supported with data analytics will be presented and the project’s plan of work will also be elucidated in this paper

    Application of Knowledge-based Tools in Environmental Decision Support Systems

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    Decision support system often requires the combined knowledge of multiple domains. A knowledge-based approach is proposed to include not only the process modelling knowledge but also the descriptive knowledge in the integration. Descriptive knowledge such as survey statistics and expert opinions forms the core of a study on the uncertainty of the combined knowledge. It was found that the use of expert systems, neural network and belief causal network assist greatly in the implementation of these concepts. Examples are drawn from the combination of scientific and economic knowledge to solve some acid rain problems.decision support system; knowledge-based system; expert system; causal network

    Male reproductive adjustments to an introduced nest predator

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    Nest predation has a large impact on reproductive success in many taxa. Defending offspring from would-be predators can also be energetically and physiologically costly for parents. Thus, to maximize their reproductive payoffs, individuals should adjust their reproductive behaviors in relation to the presence of nest predators. However, effects of nest predator presence on parental behaviors across multiple reproductive contexts remain poorly understood, particularly in non-avian taxa. We ran a series of experiments to test how the presence of an egg predator, the invasive rockpool shrimp, Palaemon elegans, influences male reproductive decisions and egg survival in a species of fish with exclusive paternal care, the three-spined stickleback, Gasterosteus aculeatus. We found that, in the presence of shrimp, male sticklebacks were less likely to build a nest, invested less in territory defense against an intruder, and tended to fan eggs in their nest less and in shorter bouts, but did not alter their investment in courtship behavior. The predator's presence also did not affect egg survival rates, suggesting that males effectively defended their brood from the shrimp. These results show that reproducing individuals can be highly responsive to the presence of nest predators and adjust their behavioral decisions accordingly across a suite of reproductive contexts.Peer reviewe
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