Swarm-intelligent foraging in honeybees: benefits and costs of task-partitioning and environmental fluctuations

For honeybee colonies, it is crucial to collect nectar in an efficient way. Empiric experiments showed that the process of decision making, which allows the colony to select the optimal nectar source, is based on individual decisions. These decisions are made by returning nectar foragers, which alter their dancing behaviours based on the nectar source’s quality and based on the experienced search time for a receiver bee. Nectar receivers, which represent a shared limited resource for foragers, can modulate the foraging decisions performed by the colony. We investigated the interplay between foragers and receivers by using a multi-agent simulation. Therefore, we implemented agents which are capable of a limited set of behaviours and which spend energy according to their behaviour. In simulation experiments, we tested colonies with various receiver-to-forager ratios and measured colony-level results like the emerging foraging patterns and the colony’s net honey gain. We show that the number of receivers prominently regulates the foraging workforce. All tested environmental fluctuations are predicted to cause energetic costs for the colony. Task-partitioning additionally influences the colony’s decision-making concerning the question whether or not the colony sticks to a nectar source after environmental fluctuations.     

Non-targeted analysis of tea by hydrophilic interaction liquid chromatography and high resolution mass spectrometry

Tea is the second most consumed beverage in the world and its consumption has been associated with numerous potential health benefits. Factors such as fermentation methods, geographical origin and season can affect the primary and secondary metabolite composition of tea. In this study, a hydrophilic interaction liquid chromatography (HILIC) method coupled to high resolution mass spectrometry in both positive and negative ionisation modes was developed and optimised. The method when combined with principal component analysis to analyse three different types of tea, successfully distinguished samples into different categories, and provided evidence of the metabolites which differed between them. The accurate mass and high resolution attributes of the mass spectrometric data were utilised and relative quantification data were extracted post-data acquisition on 18 amino acids, showing significant differences in amino acid concentrations between tea types and countries. This study highlights the potential of HILIC chromatography combined with non-targeted mass spectrometric methods to provide a comprehensive understanding of polar metabolites in plant extracts.     

An NMR-based metabolomic assessment of cultured cobia health in response to dietary manipulation

Commercial aquaculture feeds rely heavily on fishmeal and fish oil, which can be expensive and ecologically unsustainable. To evaluate the efficacy of reduced fishmeal diets for outgrowth, a dietary study was conducted on the finfish cobia, Rachycentron canadum. NMR-based metabolomic techniques were used to assess the effect of decreasing dietary fishmeal on the health of the cobia. Filtered serum ¹H NMR spectra analysed by principal components analysis (PCA) showed cobia fed reduced fishmeal diets were metabolically different than cobia on control diets. In particular, tyrosine and betaine increased in cobia fed reduced fishmeal diets while glucose decreased, suggesting that these cobia were not receiving the necessary nutritional components required for energy and growth. The formulated control diet contributed to enriched growth and significantly elevated lactate levels suggesting enhanced gut microflora metabolism in response to dietary components. The results show that NMR-based metabolomic analysis is a useful tool in aquaculture studies.     

Hyperwelcome

Web page annotation and adaptive navigation support are two active, but independent research directions focused on the same goal: expanding the functionality of the Web as a hypertext system. The goal of the AnnotatEd system presented in this paper has been to integrate annotation and adaptive navigation support into a single value-added service where the components can reinforce each other and create new unique attributes. This paper describes the implementation of AnnotatEd from early prototypes to the current version, which has been explored in several contexts. We summarize some lessons we learned during the development process and which defined the current functionality of the system. We also present the results of several classroom studies of the system. These results demonstrate the importance of the browsing-based information access supported by AnnotatEd and the value of both the annotation and navigation support functionalities offered by the system.     

Adaptive controller placement for wireless sensor–actuator networks with erasure channels

Wireless sensor–actuator networks offer flexibility for control design. One novel element which may arise in networks with multiple nodes is that the role of some nodes does not need to be fixed. In particular, there is no need to pre-allocate which nodes assume controller functions and which ones merely relay data. We present a flexible architecture for networked control using multiple nodes connected in series over analog erasure channels without acknowledgments. The control architecture proposed adapts to changes in network conditions, by allowing the role played by individual nodes to depend upon transmission outcomes. We adopt stochastic models for transmission outcomes and characterize the distribution of controller location and the covariance of system states. Simulation results illustrate that the proposed architecture has the potential to give better performance than limiting control calculations to be carried out at a fixed node.     

Terrain classification and identification of tree stems using ground‐based LiDAR

To operate autonomously in forested terrain, unmanned ground vehicles must be able to identify the load‐bearing surface of the terrain (i.e., the ground) and obstacles in the environment. To travel long distances, they must be able to track their position even when the forest canopy obstructs GPS signals, e.g., by tracking progress relative to tree stems. This paper presents a novel, robust approach for modeling the ground plane and tree stems in forests from a single viewpoint using a lightweight LiDAR scanner. Ground plane identification is implemented using a two‐stage approach. The first stage, a local height‐based filter, discards most nonground points. The second stage, based on a support vector machine classifier, identifies which of the remaining points belong to the ground. Main tree stems are modeled as cylinders or cones to estimate the diameter 130 cm above the ground plane. To fit these models, candidate main stem data are selected by finding points approximately 130 cm above the ground. These points are clustered into separate point clouds for each stem. Cylinders and cones are fit to each point cloud, and heuristic filters identify which fits correspond to tree stems. Experimental results from five forested environments demonstrate the effectiveness of this approach. For ground plane estimation, the overall classification accuracy was 86.28% with a mean error for the ground height of approximately 4.7 cm. For stem estimation, up to 50% of the main stems were accurately modeled using cones, with a root mean square diameter error of 13.2 cm.© 2012 Wiley Periodicals, Inc.     

Designing and evaluating business process models: an experimental approach

This paper presents an experimental approach to compare the performance of alternative business process designs. We use an example case of an electronic group buying setting to demonstrate how our approach can be applied in practice. More specifically, we chose a standard business process, the sales process as implemented on a group buying platform, to illustrate how a business process may be redesigned in order to better meet the needs of customers. For that purpose, we introduce a social technology feature to support cooperation among buyers in the sales process and then analyze the performance impact of the proposed business process redesign. We combine principles from design science and experimental economics to aid the business redesign process. To allow for an experimental evaluation in a controlled laboratory setting, we implement a simplified prototype model and an experimental electronic group-buying platform in the laboratory. We then employ the methods of experimental economics to generate process performance data and evaluate the effectiveness of the new process model design in the lab that can provide valuable insights to platform managers for redesigning the real-world system. We posit that combining the principles of design science and experimental economics offers researchers a useful and cost-effective method to systematically evaluate theoretical predictions about process model design.