| 1. |
- Cornelissen, Johannes H C, et al.
(författare)
-
Global negative vegetation feedback to climate warming responses of leaf litter decomposition rates in cold biomes
- 2007
-
Ingår i: Ecology Letters. - : Wiley. - 1461-023X .- 1461-0248. ; 10:7, s. 619-627
-
Tidskriftsartikel (refereegranskat)abstract
- Whether climate change will turn cold biomes from large long-term carbon sinks into sources is hotly debated because of the great potential for ecosystem-mediated feedbacks to global climate. Critical are the direction, magnitude and generality of climate responses of plant litter decomposition. Here, we present the first quantitative analysis of the major climate-change-related drivers of litter decomposition rates in cold northern biomes worldwide.Leaf litters collected from the predominant species in 33 global change manipulation experiments in circum-arctic-alpine ecosystems were incubated simultaneously in two contrasting arctic life zones. We demonstrate that longer-term, large-scale changes to leaf litter decomposition will be driven primarily by both direct warming effects and concomitant shifts in plant growth form composition, with a much smaller role for changes in litter quality within species. Specifically, the ongoing warming-induced expansion of shrubs with recalcitrant leaf litter across cold biomes would constitute a negative feedback to global warming. Depending on the strength of other (previously reported) positive feedbacks of shrub expansion on soil carbon turnover, this may partly counteract direct warming enhancement of litter decomposition.
|
|
| 2. |
- Hu, J., et al.
(författare)
-
Detection of clenbuterol hydrochloride residuals in pork liver using a customized surface plasmon resonance bioanalyzer
- 2015
-
Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 10:3
-
Tidskriftsartikel (refereegranskat)abstract
- A surface plasmon resonance (SPR) immunoassay with an immobilization of self-assembled molecular identification membrane for the detection of residual Clenbuterol Hydrochloride (CLB) in pork liver was systematically investigated and experimentally validated for its high performance. SPR immunoassay with a regular competitive inhibition assay cannot be directly verified to detect CLB residuals. In this study, the binding of Au film with mercaptopropionic acid was investigated using the known form of the strong S-Au covalent bonds formed by the chemical radical of the mercaptopropionic acid and the Au film. After that, the immunoglobulin IgG of swine (SwIgG-CLB) was bonded with the mercaptopropionic acid by covalent -CO-NH- amide bonding. The modified comprehensive analysis of how the membrane structure works was introduced together with the customized SPR bioanalyzer. In order to evaluate the performance of this biomembrane structure, the concentrations of CLBcontained solutions of 0 ng•mL-1, 10 ng•mL-1, 20 ng•mL-1, 33.3 ng•mL-1, and 40 ng•mL-1 were prepared by adding CLB reagents into the solutions of CLB antibody (Clenbuterol Hydrochloride Antibody, CLB-Ab), successively and then the response unit (RU) was measured individually. Using the data collected from the linear CCD array, the fitting curve was established with the R-Square value of 0.9929. Correspondingly, the recovery rate ranged from 88.48% to 103.21% was experimented and the limit of detection of CLB in 1.26 ng•mL-1 was obtained efficiently. It was concluded that the detection method associated with biomembrane properties is expected to contribute much to the determination of residual CLB in pork liver quantitatively by using the customized SPR bioanalyzer. © 2015 Hu et al.
|
|
| 3. |
- Hu, W., et al.
(författare)
-
Requires analysis based on software maintainability
- 2014
-
Ingår i: ICRMS 2014 - Proceedings of 2014 10th International Conference on Reliability, Maintainability and Safety. - 9781479919925 ; , s. 354-357
-
Konferensbidrag (refereegranskat)abstract
- Requirements analysis is the most important phase of the software life cycle process. Some studies have shown the most faults of software are from the requirements phase. Therefore, the quality of Software Requirements Specification has become the key to project success, which correctness, consistency, no ambiguity of software requirements specification is more important. This paper presents a classification method based on natural language processing techniques and grey similar correlation. The first step of this method is that keywords refined from various functional requirements through segmentation of natural language processing, thus made up of heavy weight vector based on the weight of functional requirements, such a functional requirement corresponds to a weight vector. The second step is that the related technology of grey system is used to compute grey correlation coefficient between two weight vectors, in order to construct a correlation matrix. Finally, the appropriate statistical tools are used to classify functional requirements statements. The clustering results based on this method can provide work guidance for requirement analysts, software developers, software testers, software maintenance.
|
|
