Assessment of physical and hydrological properties of biological soil crusts using x-ray microtomography and modelling

Biological soil crusts (BSCs) are formed by aggregates of soil particles and communities of microbial organisms and are common in all drylands. The role of BSCs on infiltration remains uncertain due to the lack of data on their role in affecting soil physical properties such as porosity and structure. Quantitative assessment of these properties is primarily hindered by the fragile nature of the crusts. Here we show how the use of a combination of non-destructive imaging X-ray microtomography (XMT) and Lattice Boltzmann method (LBM) enables quantification of key soil physical parameters and the modeling of water flow through BSCs samples from Kalahari Sands, Botswana. We quantify porosity and flow changes as a result of mechanical disturbance of such a fragile cyanobacteria-dominated crust. Results show significant variations in porosity between different types of crusts and how they affect the flow and that disturbance of a cyanobacteria-dominated crust results in the breakdown of larger pore spaces and reduces flow rates through the surface layer. We conclude that the XMT–LBM approach is well suited for study of fragile surface crust samples where physical and hydraulic properties cannot be easily quantified using conventional methods.

Drawing association rules between purchases and in-store behavior:an extension of the market basket analysis

Shopping behavior is often exclusively studied through consumer purchases, since they are an easily measurable ouput. Still, the observation of in-store physical behavior (paths, moves and actions) is crucial, as is the quantification of its impact on purchases. Using an innovative PDA tool to precisely record and time stamp consumer’s moves and gestures, we extend the classical Market Basket Analysis (MBA) by integrating this new kind of information. We draw associations not only from purchases but also from in-store consumer moves and actions. We compare results of our new method with classical MBA results and show a significant improvement.

Drawing association rules between purchases and in-store behaviour:an extension of the market basket analysis

Shopping behavior is often exclusively studied through consumer purchases, since they are an easily measurable ouput. Still, the observation of in-store physical behavior (path, moves and actions) is crucial, as is the quantification of its impact on purchases. Using an innovative PDA tool to precisely record and time stamp consumers' moves and actions, we extend the classical Market Basket Analysis (MBA) by integrating this new information: associations between product categories are measured not only from purchases but also from consumer physical behavior. We compare results of our new method with classical MBA results and show a significant improvement.

Exploring the link between In-store physical shopping behavior and purchases

Only little research investigates the relationship between consumer purchases and in-store physical shopping behavior, largely because of the difficulty involved with reconciling a precise observation of in-store behavior with a robust statistical analyses of the data. Using an innovative data collection method, this article determines that physical shopping behavior manifests itself along two main dimensions: shopping width (behavioral scope throughout the store) and shopping depth (specific store elements). Both dimensions have strong impacts on purchases: the former tends to influence the number of items bought, and the latter affects the price of purchased items, depending on the product category.