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      Intelligent Virtual Agents : Third International Workshop, IVA 2001 Madrid, Spain, September 10–11, 2001 Proceedings 

      Reducing the Gap Between the Conceptual Models of Students and Experts Using Graph-Based Adaptive Instructional Systems

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          Network motifs: simple building blocks of complex networks.

          Complex networks are studied across many fields of science. To uncover their structural design principles, we defined "network motifs," patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This approach may uncover the basic building blocks of most networks.
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            A Community Based Systems Diagram of Obesity Causes

            Introduction Application of system thinking to the development, implementation and evaluation of childhood obesity prevention efforts represents the cutting edge of community-based prevention. We report on an approach to developing a system oriented community perspective on the causes of obesity. Methods Group model building sessions were conducted in a rural Australian community to address increasing childhood obesity. Stakeholders (n = 12) built a community model that progressed from connection circles to causal loop diagrams using scripts from the system dynamics literature. Participants began this work in identifying change over time in causes and effects of childhood obesity within their community. The initial causal loop diagram was then reviewed and elaborated by 50 community leaders over a full day session. Results The process created a causal loop diagram representing community perceptions of determinants and causes of obesity. The causal loop diagram can be broken down into four separate domains; social influences; fast food and junk food; participation in sport; and general physical activity. Discussion This causal loop diagram can provide the basis for community led planning of a prevention response that engages with multiple levels of existing settings and systems.
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              Finding All the Elementary Circuits of a Directed Graph

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                Book Chapter
                2020
                October 04 2020
                : 538-556
                10.1007/978-3-030-60128-7_40
                c8f72e31-6f53-444f-85b7-c4ce41786c44
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