#281 GRACeFUL: A complex system to support group decision making processes in Climate Resilient Urban Design
Authors: Linda Nijland and Etiënne Rouwette
Interest in climate resilience is growing worldwide among policy makers, urban planners, citizens and scientists. Climate Resilient Urban Design (CRUD) relates to the (re-)design of urban areas in such a way that cities and citizens become less vulnerable to climate change. Weather phenomena like heat stress, droughts and floods impact the lives of city dwellers, villagers, and rural residents all over the globe. The making of policies dealing with climate resilience in urban environments is a process that inevitably involves stakeholders from various disciplines, each with their own interests, constraints and goals. Group Model Building (GMB) (Vennix, 1999) is known to facilitate the decision making processes by modelling important variables and their causal relations. This participatory group modelling process creates a shared understanding of the problem, incorporating the views of all stakeholders, and it improves the support for the final decisions taken.
The GRACeFUL (Global systems Rapid Assessment tools through Constraint Functional Languages) project aims at supporting decision making in complex problems by connecting participatory processes to scientific evidence through novel tools. Rapid Assessment Tools typify causal factors and linkages with concrete data from other system layers and produce a set of viable and acceptable alternative solutions to be used in decision making. Simulation tools will simulate the alternative scenarios over time and visualization tools will show the results of the different CRUD solutions on maps. The case study area is a neighbourhood in the city of Dordrecht, the Netherlands. Here heavy rainfall caused flooded streets and cellars last summer. The municipality is planning to redevelop the public space in this neighbourhood taking into account climate resilience and involving different stakeholders, including citizens.
#285 A Reaction-Diffusion Model for a Chemo-Hydrodynamical Effect in a Belousov Zhabotinsky Oscillator
Authors: Mihnea R Hristea, Jakob Klien and Florian Wodlei
The coupling between the nonlinear kinetics and the transport phenomena leads to a complex evolution of a closed unstirred Ferroin-catalyzed Belousov Zhabotinsky reaction. An initially periodic phase evolves into a chaotic one, which itself evolves back into another periodic phase that last until the reaction reaches thermodynamic equilibrium. We have discovered that a limited stirring phase can result in the disappearance of the chaotic transient, leading to a purely periodic evolution of the system. We describe this effect here in detail and show our first results in modeling this complex behavior.
After successfully implementing a modified FKN [1] reaction model developed by Marchettini et al. [2] that assumes reactants consumption we are following the original ideas of Turing [3] to take also diffusion into account. With this simplified reaction-diffusion model we are able to reproduce the periodic behavior of the system. Modifying this reaction-diffusion equation by adding an advective term to model the limited stirring of the system is the task of our ongoing research.
[1] Field, Richard J.; Noyes, Richard M. J. Chem. Phys. 60: 1877–1884 (1974)
[2] Rossi, F.; Budroni, M. A.; Marchettini, N.; Cutietta, L.; Rustici, M. & Liveri, M. L. T. Chemical Physics Letters, 480, 322-326 (2009)
[3] Turing, A. M. Philosophical Transactions of the Royal Society B 237 (641): 37–72 (1952)
#289 Identifying risk profiles in the London’s public transport system
Authors: Roberto Murcio, Ed Manley and Chen Zhong
Public transport networks are vital in ensuring efficient urban function.
In many cities, mass disruption to the public transport network has the potential to cause significant damage to the urban economy and well-being.
Information about where in the network a disruption would cause the more damage is therefore critical for contingency planning. Several studies associate risk to crowdedness, and hence they only consider the most crowded areas as the most susceptible ones to disruption. Nevertheless, some areas, not affected by crowdedness, can be identified as important hubs or brokers of people travelling through the network. These areas have the potential to create unexpected disruptions in the system, due to their spatial-temporal position. The temporal component would strongly depends on the individual behaviours on route choices since these shape relevant emergent properties of the network. These aspects are essential to understand causation so that well-informed risk management decisions can be taken.
In this work, the high-risk areas are associated with underground stations and the transfer of information between them, understanding information as the amount of people travelling throughout the network. A novel methodology to the field of Big Data through the use of mathematical models from information theory data is introduced. These tools reveal those high risk areas in contrast with previous assumptions focussed on crowdedness.
After the analysis the main outputs produced are:
1) A comprehensive temporal profile of the volume of people that are in each one of the stations. This corresponds not only to the individuals getting in/out of the transport network, but also its transient population.
2) A complete spatio-temporal risk profile that highlights the so-called
hubs in the system. In addition, they lead to important insights about specific activity patterns, other than work related, that could eventually be used to assess particular social mobility risks
#291 Cultural regulators in social-ecological systems: A hierarchy theory perspective
Authors: J. Mario Siqueiros-García, Abril Cid, Luis Bojórquez and David Manuel-Navarrete
A theoretical perspective that can make explicit the role of cultural aspects in the dynamics of social-ecological systems (SES) is needed. In this work we advance the idea that human societies, being part of a SES, create “cultural objects” through which they interact with the biophysical subsystem of a SES. We call these cultural objects “transducers” because they translate signals between subsystems. Transducers regulate the interactions between the socio-cultural subsystem and the biophysical one as they constrain the flows of energy, matter and/ or information that run through them.Transducers as “cultural objects” are not necessarily things, they are mostly processes instantiated as social institutions. Because transducers are created in and as part of a society, they are locally meaningful and play an important role in regulating social interactions around exchanges with the biophysical subsystem. A central tenet of our approach is the notion of culture. Based on the ideas of Howard Pattee on the emergence of symbols from material systems and semantic closure, culture is the symbolic description that emerges from social interactions that exerts control over social dynamics. Culture is different from the symbolic representations of other social organisms in that humans collectively feed that symbolic realm, and contextually apply it as functional constraints to the social interactions and to their interactions with the biophysical subsystems. In this sense, transducers are dynamic symbolic entities that act as context-dependent, functional constraints. We exemplify our ideas in two cases: 1) the role of rituals and shrines in the rice fields of Bali, and 2) the legal framework of sport fishing in Los Cabos, Mexico. We conclude that culture can effectively intervene and define new routes to the flow of energy, matter and information between SES components, and ignoring this is missing an important part of the complexity of SES.
#293 Rhesus monkeys show attentional biases to higher fractal dimension
Authors: Kelly R. Finn, James P. Crutchfield and Eliza Bliss-Moreau
Animals are exposed to many complex patterns in natural environments: branching plant life, rough textures of terrain, a diversity of sounds and smells, unpredictable interactions with other organisms and weather. Captivity often puts animals in drastically different environments that include less complex visual stimuli, and though many advocate for using more naturalistic enclosures, little work has been done to determine precisely which qualities about a ‘naturalistic’ environment are discernibly different to specific animals and important for their welfare. The present study investigates visual attentional biases of captive rhesus monkeys (Macaca mulatta) with respect to image complexity determined by fractal dimension. We used noninvasive infrared eye-tracking technology to measure attention of seven adult male rhesus monkeys as they passively viewed paired black-white images of simulated self-similar contours with varying fractal dimension (d varying from 1.1 to 1.9). All monkeys completed a total of 243 trials over 3-6 testing sessions. Multilevel generalized linear regression models revealed that monkeys did discriminate between different fractal dimensions. They showed attentional biases towards greater complexity (p < 0.001) as indicated by increased fixation count on images of higher fractal dimension and fewer fixation counts when paired alongside images of higher complexity (p<0.001). On average, monkeys held twice as many unique fixations on images of the highest dimensionality (d1.9 = 20.91 fixations) as compared to the lowest (d1.1 = 10.86 fixations). Future projects will investigate the actual scanning paths of macaque vision across these images, whether or not macaques will choose to spend more time in environments with more complex visual stimuli, and attentional biases to images that vary in other complexity metrics. These findings help us understand what features of patterns monkeys attend to, what information they may process from their visual environments, and will allow us to eventually design more stimulating environmental enrichment.
Authors: Linda Nijland and Etiënne Rouwette
Interest in climate resilience is growing worldwide among policy makers, urban planners, citizens and scientists. Climate Resilient Urban Design (CRUD) relates to the (re-)design of urban areas in such a way that cities and citizens become less vulnerable to climate change. Weather phenomena like heat stress, droughts and floods impact the lives of city dwellers, villagers, and rural residents all over the globe. The making of policies dealing with climate resilience in urban environments is a process that inevitably involves stakeholders from various disciplines, each with their own interests, constraints and goals. Group Model Building (GMB) (Vennix, 1999) is known to facilitate the decision making processes by modelling important variables and their causal relations. This participatory group modelling process creates a shared understanding of the problem, incorporating the views of all stakeholders, and it improves the support for the final decisions taken.
The GRACeFUL (Global systems Rapid Assessment tools through Constraint Functional Languages) project aims at supporting decision making in complex problems by connecting participatory processes to scientific evidence through novel tools. Rapid Assessment Tools typify causal factors and linkages with concrete data from other system layers and produce a set of viable and acceptable alternative solutions to be used in decision making. Simulation tools will simulate the alternative scenarios over time and visualization tools will show the results of the different CRUD solutions on maps. The case study area is a neighbourhood in the city of Dordrecht, the Netherlands. Here heavy rainfall caused flooded streets and cellars last summer. The municipality is planning to redevelop the public space in this neighbourhood taking into account climate resilience and involving different stakeholders, including citizens.
#285 A Reaction-Diffusion Model for a Chemo-Hydrodynamical Effect in a Belousov Zhabotinsky Oscillator
Authors: Mihnea R Hristea, Jakob Klien and Florian Wodlei
The coupling between the nonlinear kinetics and the transport phenomena leads to a complex evolution of a closed unstirred Ferroin-catalyzed Belousov Zhabotinsky reaction. An initially periodic phase evolves into a chaotic one, which itself evolves back into another periodic phase that last until the reaction reaches thermodynamic equilibrium. We have discovered that a limited stirring phase can result in the disappearance of the chaotic transient, leading to a purely periodic evolution of the system. We describe this effect here in detail and show our first results in modeling this complex behavior.
After successfully implementing a modified FKN [1] reaction model developed by Marchettini et al. [2] that assumes reactants consumption we are following the original ideas of Turing [3] to take also diffusion into account. With this simplified reaction-diffusion model we are able to reproduce the periodic behavior of the system. Modifying this reaction-diffusion equation by adding an advective term to model the limited stirring of the system is the task of our ongoing research.
[1] Field, Richard J.; Noyes, Richard M. J. Chem. Phys. 60: 1877–1884 (1974)
[2] Rossi, F.; Budroni, M. A.; Marchettini, N.; Cutietta, L.; Rustici, M. & Liveri, M. L. T. Chemical Physics Letters, 480, 322-326 (2009)
[3] Turing, A. M. Philosophical Transactions of the Royal Society B 237 (641): 37–72 (1952)
#289 Identifying risk profiles in the London’s public transport system
Authors: Roberto Murcio, Ed Manley and Chen Zhong
Public transport networks are vital in ensuring efficient urban function.
In many cities, mass disruption to the public transport network has the potential to cause significant damage to the urban economy and well-being.
Information about where in the network a disruption would cause the more damage is therefore critical for contingency planning. Several studies associate risk to crowdedness, and hence they only consider the most crowded areas as the most susceptible ones to disruption. Nevertheless, some areas, not affected by crowdedness, can be identified as important hubs or brokers of people travelling through the network. These areas have the potential to create unexpected disruptions in the system, due to their spatial-temporal position. The temporal component would strongly depends on the individual behaviours on route choices since these shape relevant emergent properties of the network. These aspects are essential to understand causation so that well-informed risk management decisions can be taken.
In this work, the high-risk areas are associated with underground stations and the transfer of information between them, understanding information as the amount of people travelling throughout the network. A novel methodology to the field of Big Data through the use of mathematical models from information theory data is introduced. These tools reveal those high risk areas in contrast with previous assumptions focussed on crowdedness.
After the analysis the main outputs produced are:
1) A comprehensive temporal profile of the volume of people that are in each one of the stations. This corresponds not only to the individuals getting in/out of the transport network, but also its transient population.
2) A complete spatio-temporal risk profile that highlights the so-called
hubs in the system. In addition, they lead to important insights about specific activity patterns, other than work related, that could eventually be used to assess particular social mobility risks
#291 Cultural regulators in social-ecological systems: A hierarchy theory perspective
Authors: J. Mario Siqueiros-García, Abril Cid, Luis Bojórquez and David Manuel-Navarrete
A theoretical perspective that can make explicit the role of cultural aspects in the dynamics of social-ecological systems (SES) is needed. In this work we advance the idea that human societies, being part of a SES, create “cultural objects” through which they interact with the biophysical subsystem of a SES. We call these cultural objects “transducers” because they translate signals between subsystems. Transducers regulate the interactions between the socio-cultural subsystem and the biophysical one as they constrain the flows of energy, matter and/ or information that run through them.Transducers as “cultural objects” are not necessarily things, they are mostly processes instantiated as social institutions. Because transducers are created in and as part of a society, they are locally meaningful and play an important role in regulating social interactions around exchanges with the biophysical subsystem. A central tenet of our approach is the notion of culture. Based on the ideas of Howard Pattee on the emergence of symbols from material systems and semantic closure, culture is the symbolic description that emerges from social interactions that exerts control over social dynamics. Culture is different from the symbolic representations of other social organisms in that humans collectively feed that symbolic realm, and contextually apply it as functional constraints to the social interactions and to their interactions with the biophysical subsystems. In this sense, transducers are dynamic symbolic entities that act as context-dependent, functional constraints. We exemplify our ideas in two cases: 1) the role of rituals and shrines in the rice fields of Bali, and 2) the legal framework of sport fishing in Los Cabos, Mexico. We conclude that culture can effectively intervene and define new routes to the flow of energy, matter and information between SES components, and ignoring this is missing an important part of the complexity of SES.
#293 Rhesus monkeys show attentional biases to higher fractal dimension
Authors: Kelly R. Finn, James P. Crutchfield and Eliza Bliss-Moreau
Animals are exposed to many complex patterns in natural environments: branching plant life, rough textures of terrain, a diversity of sounds and smells, unpredictable interactions with other organisms and weather. Captivity often puts animals in drastically different environments that include less complex visual stimuli, and though many advocate for using more naturalistic enclosures, little work has been done to determine precisely which qualities about a ‘naturalistic’ environment are discernibly different to specific animals and important for their welfare. The present study investigates visual attentional biases of captive rhesus monkeys (Macaca mulatta) with respect to image complexity determined by fractal dimension. We used noninvasive infrared eye-tracking technology to measure attention of seven adult male rhesus monkeys as they passively viewed paired black-white images of simulated self-similar contours with varying fractal dimension (d varying from 1.1 to 1.9). All monkeys completed a total of 243 trials over 3-6 testing sessions. Multilevel generalized linear regression models revealed that monkeys did discriminate between different fractal dimensions. They showed attentional biases towards greater complexity (p < 0.001) as indicated by increased fixation count on images of higher fractal dimension and fewer fixation counts when paired alongside images of higher complexity (p<0.001). On average, monkeys held twice as many unique fixations on images of the highest dimensionality (d1.9 = 20.91 fixations) as compared to the lowest (d1.1 = 10.86 fixations). Future projects will investigate the actual scanning paths of macaque vision across these images, whether or not macaques will choose to spend more time in environments with more complex visual stimuli, and attentional biases to images that vary in other complexity metrics. These findings help us understand what features of patterns monkeys attend to, what information they may process from their visual environments, and will allow us to eventually design more stimulating environmental enrichment.
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