Analyzing the commercial activities of a street network by ranking their nodes: a case study in Murcia, Spain

Urban researchers and planners are often interested in understanding how economic activities are distributed in urban regions, what forces influence their special pattern and how urban structure and functions are mutually dependent. In this paper, we want to show how an algorithm for ranking the nodes in a network can be used to understand and visualize certain commercial activities of a city. The first part of the method consists of collecting real information about different types of commercial activities at each location in the urban network of the city of Murcia, Spain. Four clearly differentiated commercial activities are studied, such as restaurants and bars, shops, banks and supermarkets or department stores, but obviously we can study other. The information collected is then quantified by means of a data matrix, which is used as the basis for the implementation of a PageRank algorithm which produces a ranking of all the nodes in the network, according to their significance within it. Finally, we visualize the resulting classification using a colour scale that helps us to represent the business network.

Construction of Intelligent Virtual Worlds Using a Grammatical Framework

The potential of integrating multiagent systems and virtual environments has not been exploited to its whole extent. This paper proposes a model based on grammars, called Minerva, to construct complex virtual environments that integrate the features of agents. A virtual world is described as a set of dynamic and static elements. The static part is represented by a sequence of primitives and transformations and the dynamic elements by a series of agents. Agent activation and communication is achieved using events, created by the so-called event generators. The grammar defines a descriptive language with a simple syntax and a semantics, defined by functions. The semantics functions allow the scene to be displayed in a graphics device, and the description of the activities of the agents, including artificial intelligence algorithms and reactions to physical phenomena. To illustrate the use of Minerva, a practical example is presented: a simple robot simulator that considers the basic features of a typical robot. The result is a functional simple simulator. Minerva is a reusable, integral, and generic system, which can be easily scaled, adapted, and improved. The description of the virtual scene is independent from its representation and the elements that it interacts with.

Plant regeneration functional groups modulate the response to fire of soil enzyme activities in a Mediterranean shrubland

Soil enzymes are critical to soil nutrient cycling function but knowledge on the factors that control their response to major disturbances such as wildfires remains very limited. We evaluated the effect of fire-related plant functional traits (resprouting and seeding) on the resistance and resilience to fire of two soil enzyme activities involved in phosphorus and carbon cycling (acid phosphatase and β-glucosidase) in a Mediterranean shrublands in SE Spain. Using experimental fires, we compared four types of shrubland microsites: SS (vegetation patches dominated by seeder species), RR (patches dominated by resprouter species), SR (patches co-dominated by seeder and resprouter species), and IP (shrub interpatches). We assessed pre- and post-fire activities of the target soil enzymes, available P, soil organic C, and plant cover dynamics over three years after the fire. Post-fire regeneration functional groups (resprouter, seeder) modulated both pre- and post-fire activity of acid phosphatase and β-glucosidase, with higher activity in RR and SR patches than in SS patches and IP. However, we found no major differences in enzyme resistance and resilience between microsite types, except for a trend towards less resilience in SS patches. Fire similarly reduced the activity of both enzymes. However, acid phosphatase and β-glucosidase showed contrasting post-fire dynamics. While β-glucosidase proved to be rather resilient to fire, fully recovering three years after fire, acid phosphatase showed no signs of recovery in that period. Overall, the results indicate a positive influence of resprouter species on soil enzyme activity that is very resistant to fire. Long-lasting decrease in acid phosphatase activity probably resulted from the combined effect of P availability and post-fire drought. Our results provide insights on how plant functional traits modulate soil biochemical and microbiological response to fire in Mediterranean fire-prone shrublands.