Beware of the Small-World neuroscientist!

The SW has undeniably been one of the most popular network descriptors in the neuroscience literature. Two main reasons for its lasting popularity are its apparent ease of computation and the intuitions it is thought to provide on how networked systems operate. Over the last few years, some pitfalls of the SW construct and, more generally, of network summary measures, have widely been acknowledged

Effect of stocking density of fish on water quality and growth performance of European Carp and leafy vegetables in a low-tech aquaponic system

Aquaponics (AP) is a semi-closed system of food production that combines aquaculture and hydroponics and represents a new agricultural system integrating producers and consumers. The aim of this study was to test the effect of stocking densities (APL, 2.5 kg m-3; APH, 4.6 kg m-3) on water quality, growth performance of the European Carp (Cyprinus carpio L.), and yield of leafy vegetables (catalogna, lettuce, and Swiss Chard) in a low-technology AP pilot system compared to a hydroponic cultivation. The AP daily consumption of water due to evapotranspiration was not different among treatments with an average value of 8.2 L d-1, equal to 1.37% of the total water content of the system. Dissolved oxygen was significantly (p < 0.05) different among treatments with the lowest median value recorded with the highest stocking density of fish (5.6 mg L-1) and the highest median value in the hydroponic control (8.7 mg L-1). Marketable yield of the vegetables was significantly different among treatments with the highest production in the hydroponic control for catalogna (1.2 kg m-2) and in the APL treatment for Swiss Chard (5.3 kg m-2). The yield of lettuce did not differ significantly between hydroponic control and APL system (4.0 kg m-2 on average). The lowest production of vegetables was obtained in the APH system. The final weight (515 g vs. 413 g for APL and APH, respectively), specific growth rate (0.79% d-1 vs. 0.68% d-1), and feed conversion (1.55 vs. 1.86) of European Carp decreased when stocking density increased, whereas total yield of biomass was higher in the APH system (4.45 kg m-3 vs. 6.88 kg m-3). A low mortality (3% on average) was observed in both AP treatments. Overall, the results showed that a low initial stocking density at 2.5 kg m-3 improved the production of European Carp and of leafy vegetables by maintaining a better water quality in the tested AP system

New perspectives for air transport performance

The average delays of flights and passengers are not the same. The air transport industry is lacking passenger-centric metrics; its reporting is flight-centric. We report on the first European network simulation model with explicit passenger itineraries and full delay cost estimations. Trade-offs in performance are assessed using passenger-centric and flight-centric metrics, under a range of novel flight and passenger prioritisation scenarios. The need for passenger-centric metrics is established. Delay propagation is characterised under the scenarios using, inter alia, Granger causality techniques

Combining complex networks and data mining: why and how

The increasing power of computer technology does not dispense with the need to extract meaningful in- formation out of data sets of ever growing size, and indeed typically exacerbates the complexity of this task. To tackle this general problem, two methods have emerged, at chronologically different times, that are now commonly used in the scientific community: data mining and complex network theory. Not only do complex network analysis and data mining share the same general goal, that of extracting information from complex systems to ultimately create a new compact quantifiable representation, but they also often address similar problems too. In the face of that, a surprisingly low number of researchers turn out to resort to both methodologies. One may then be tempted to conclude that these two fields are either largely redundant or totally antithetic. The starting point of this review is that this state of affairs should be put down to contingent rather than conceptual differences, and that these two fields can in fact advantageously be used in a synergistic manner. An overview of both fields is first provided, some fundamental concepts of which are illustrated. A variety of contexts in which complex network theory and data mining have been used in a synergistic manner are then presented. Contexts in which the appropriate integration of complex network metrics can lead to improved classification rates with respect to classical data mining algorithms and, conversely, contexts in which data mining can be used to tackle important issues in complex network theory applications are illustrated. Finally, ways to achieve a tighter integration between complex networks and data mining, and open lines of research are discussed.Comment: 58 pages, 19 figure