Modern temporal network theory: A colloquium

The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.Comment: Final accepted versio

Elastic spaces may snap under perfect maps

The perfect image of an elastic space need not be elastic. Other relevant examples are presented

Elastic spaces may snap under perfect maps

The perfect image of an elastic space need not be elastic. Other relevant examples are presented

Modelling nutrient uptake: A possible indicator of phosphorus deficiency

An understanding of the processes controlling soil nutrient supply and plant uptake has led to process-based models that can predict nutrient uptake and the concentration gradient that develops at the root surface. By using this information, it may be possible to develop an indicator of soil phosphorus status based on the predicted uptake and/or concentration of phosphorus (P) at the root surface. To identify the potential for such a test, the relationships between model output and observed plant growth were examined using data from a published experiment. The experiment was initially designed to investigate the relationship between common indices of soil-available P and the growth of maize (Zea mays) in 26 surface soils from Queensland. There was a high correlation between observed and predicted P uptake, and between relative dry matter yield and predicted P uptake. The predicted concentration of P at the root surface was also highly correlated with P uptake and dry weight increase. It is hypothesised that the short growth period (25 days) was responsible for the high correlation between P uptake and measured soil solution P. The hypothesis that a predicted concentration of P at the root surface or predicted P uptake may be valuable indicators of P deficiency in the longer term still remains to be tested