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.     

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.     

Enhancing the efficiency of alternating current driven organic light-emitting devices by optimizing the operation frequency

We report efficient and bright organic light-emitting devices operated by capacitive energy coupling. In this approach, the organic layers are enclosed between sputter-deposited hafnium dioxide layers to prevent charge carrier injection. When a sinusoidal voltage signal is applied to the electrodes, the devices emit bright green light whereas no detectable emission is generated upon application of a constant voltage. The efficiency of the process depends heavily on the frequency of the applied voltage signal. By optimizing the driving scheme, a record luminous efficacy for AC driven OLEDs of 2.7 lm/W at 500 cd/m² is achieved.     

An algorithm for computing compatibly Frobenius split subvarieties

This paper describes an algorithm which produces all ideals compatible with a given surjective Frobenius near-splitting.     

Coking behavior of nickel and a rhodium based catalyst used in steam reforming for power-to-gas applications

This paper proposes partial steam reforming of natural gas as a chemical storage option for excess electricity. Thermodynamic simulations with Aspen Plus^® show that highest process efficiencies are reached at low steam-to-carbon (S/C) ratios in the feed. However, coke deposition due to unwanted side or follow-up reactions and thus catalyst deactivation is likely in this operation range. In an experimental evaluation three catalysts were selected to test their resistance towards coking: two nickel based and one rhodium based noble metal catalyst. They were tested regarding their long-term stability at S/C ratios as low as 0 to 0.1 and reaction temperatures between 450 and 500 °C. A different reaction and deactivation behavior was observed for nickel and the noble metal catalysts. The measured life times of the noble metal catalyst were by a factor of at least 100 higher than for the two selected nickel catalysts at the applied reforming conditions. Furthermore, after each reforming experiment, a temperature-programmed oxidation (TPO) analysis was performed for the spent catalysts. Based on literature data, the measured CO₂ peaks at corresponding temperatures were related to the different forms of solid carbon depositions. Main carbonaceous species found on the nickel catalysts were of filamentous nature, whereas one or two more reactive C species with monoatomic or polymeric structure at much lower amount were detected on the noble metal catalyst. Further SEM analysis confirmed these findings.