Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atomcounting diagnosed by combining a thorough statistical method and detailed image simulations.

Abstract: The increasing availability of real-time in situ measurements and remote sensing observations have the potential to contribute to the optimization of water resources management. Global challenges such as climate change, intensive agriculture and urbanization put a high pressure on our water resources. Due to recent innovations in measuring both water quantity and quality, river systems can now be monitored in real time at an unprecedented spatial and temporal scale. To interpret the sensor measurements and remote sensing observations additional data for example on: the location of the measurement, upstream and downstream catchment characteristics, horizontal ellipsis are required. In this paper, we present a data management system to support flow-path related functionality for decision making and prediction modelling. Adding meta data sets and facilitating (near) real-time processing of sensor data questions are key concepts for the systems. The potential of the database framework for hydrological applications is demonstrated using different applications for the river system of Flanders. In one, the database framework is used to simulate the daily discharge for each segment within a catchment using a simple data-driven approach. The presented system is useful for numerous applications including pollution tracking, alerting and inter-sensor validation in river systems, or related networks.

Abstract: Gian Giacomo Inchiocchio (1604-1656), better known as Barbelli, was one of the main exponents of Lombard painting of the seventeenth century. A large body of work is attributed to him, encompassing a wide range of drawings, murals, and oil paintings. However, despite his broad production, there are still many open questions regarding his painting techniques and materials. In this paper, a multi-analytical study of the cycle Stories of the life of Saint George that originally decorated the presbytery of the parish church of Casaletto Vaprio (Cremona, Italy) was performed, combining non-invasive techniques with the characterisation of selected micro samples. Results show that Barbelli used a very limited number of inorganic pigments, often mixing them together to create different colours and shades. Remains of caseinate and degradation products (i.e. weddellite and whewellite) related to the strappo intervention were also highlighted. The study helped to decipher the materials and technique of this painting, providing data that can be used as a reference to study his extensive production.

Abstract: Canola production is an important alternative for agricultural policy-makers in Iran to reduce dependency on the imported vegetable oils. Nevertheless, the canola planted area is only increasing at a slow pace, indicating a low willingness-to-accept of farmers. The general aim of this study was to determine the factors influencing the canola adoption in the Kermanshah Province in Western Iran. Employing stratified random sampling method, 106 farmers from each adopter and non-adopter group were selected. Helping to reach a suitable extensional program, two main categories of variables were defined; i.e. farmers personal characteristics and extension parameters. The analysis of farmers personal characteristics variables revealed that the adopters had larger farms and were younger. The results also show that 80% of the adopters were highly to very highly willing to cultivate canola. Furthermore, a logistic regression model estimated the influence of extensional parameters variables on the canola adoption. According to the regression model, the most effective factors are contact with extension agents and participating in extension classes. As a conclusion, it is suggested that the focus of extension services should be to reduce the distance to agricultural service centers in combination with more contact with extension agents and classes.