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.     

Integrative Analysis of Metabolomic,Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs

The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein “phosphoglycerate mutase 2” and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes.     

A simple frequency‐domain method for stress analysis of stall‐regulated wind turbines

A simple method, based in the frequency domain, was developed for calculating the dynamic response of a stall‐regulated wind turbine. Emphasis is placed on two aspects of the method, which are necessary in order to obtain a reasonable linearization of behavior when the blades are stalled. First, the tangential (in‐plane) component of turbulence is included, in addition to the axial component. Second, the linearized relationship between lift coefficient and angle‐of‐attack is adjusted to account for the effects of dynamic stall: separate linearizations are used for excitation and damping of vibration. A thorough comparison is made between linear and non‐linear dynamic‐stall methods, with the conclusion that the accuracy of the linear method depends upon the frequency and amplitude of oscillation. The linear dynamic‐stall method is accurate at blade vibrational frequencies, but it can be inaccurate at frequencies in the vicinity of 1P or below, when the angle‐of‐attack oscillates with an amplitude of 3° or more. Load spectra of a Nordtank 500 turbine, calculated using the frequency‐domain method, are compared with measurements. The frequency‐domain method provides estimates of load spectra and aerodynamic damping (stability) that are useful for preliminary design and optimization, but the method lacks sufficient accuracy and generality to be used for certification. Copyright © 2011 John Wiley & Sons, Ltd.     

Methanol Conversion to Hydrocarbons (MTH) Over H-ITQ-13 (ITH) Zeolite

Product flexibility is key to meeting fluctuating chemicals demands in the future. In this contribution, the methanol to hydrocarbons (MTH) reaction was investigated over two Ge-containing H-ITQ-13 samples, one with needle-like (H-ITQ-13(N), with (Si+Ge)/Al) = 42) and another with plate-like (H-ITQ-13(P), with (Si+Ge)/Al > 100) morphology. The samples were characterised using XRD, BET, SEM/EDS and FTIR spectroscopy, and their MTH performance was compared with the performance of H-ZSM-5 and H-ZSM-22. Similar specific surface areas (413 and 455 m² g^?1 for H-ITQ-13(N) and (P), respectively) and similar acid strength (Δν ~ ?327(?310) cm^?1) was observed for the two H-ITQ-13 samples. Testing of H-ITQ-13(N) at weight hourly space velocity (WHSV) = 2–8 h^?1 at 350–450 °C revealed that C₅₊ alkenes were the main products (35–45 % selectivity at 400 °C), followed by propene and butene. A low but significant selectivity for aromatic products was observed (6–8 % selectivity at 400 °C). Product selectivity was found to be independent of deactivation. The methanol conversion capacity of H-ITQ-13(N) was 120–150 g methanol g^?1 catalyst at 400 °C. Testing H-ITQ-13 at high (30 atm) and ambient pressure, respectively, at 350 °C showed that a high pressure led to enhanced C₅₊ selectivity, but close to a tenfold decrease in methanol conversion capacity. H-ITQ-13(P) was tested at 400 °C and 2 h^?1. It gave lower conversion than H-ITQ-13(N). Furthermore, when compared at the same conversion level, H-ITQ-13(P) gave higher C₅₊ alkene selectivity, lower aromatics selectivity, and a higher propene to ethene ratio than H-ITQ-13(N). The H-ITQ-13 samples yielded a product spectrum intermediate of H-ZSM-22 and H-ZSM-5. The effluent product cut-off of H-ITQ-13 was similar to that of H-ZSM-5 with tetramethylbenzene as the largest significant product, while H-ZSM-22 produced mainly linear and branched alkenes. The lifetime of H-ITQ-13(N) was clearly enhanced compared to H-ZSM-22, but inferior to H-ZSM-5.     

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.