Photosynthesis ( P n ), transpiration ( E ) and water use efficiency ( WUE ) of more than 66 arid sand species from different environmental habitats, shifting sand dune, fixed sand dune, lowland and wetland in ...Photosynthesis ( P n ), transpiration ( E ) and water use efficiency ( WUE ) of more than 66 arid sand species from different environmental habitats, shifting sand dune, fixed sand dune, lowland and wetland in the Maowusu Sand Area were analyzed and the relation among these characteristics and the resource utilization efficiency, taxonomic categories and growth forms of the species were assessed. The results showed that species from Chenopodiaceae, Gramineae, Leguminosae which possessed the C 4 photosynthesis pathway, or C 3 pathway and also with nitrogen_fixation capacities had higher or the highest P n values, i.e., 20～30 μmol CO 2·m -2 ·s -1 , while that of evergreen shrub of Pinaceae had the lowest P n values, i.e., 0～5 μmol CO 2·m -2 ·s -1 . Those species from Compositae, Scrophulariaceae, and Gramineae with C 3 pathway but no N_fixation capacity had the highest E rates, i.e., 20～30 mmol H 2O·m -2 ·s -1 and again the evergreen shrub together with some species from Salicaceae and Compositae had the lowest E rates, i.e., 0～5 mmol H 2O·m -2 ·s -1 . Species from Leguminosae, Gramineae and Chenopodiaceae with C 4 pathway or C 3 pathway with N_fixation capacity, both shrubs and grasses, generally had higher WUE . However, even the physiological traits of the same species were habitat_ and season_specific. The values of both P n and E in late summer were much higher than those in early summer, with average increases of 26%, 40% respectively in the four habitats. WUE in late summer was, however, 12% lower. Generally, when the environments became drier as a result of habitats changed, i.e., in the order of wetland, lowland, fixed sand dune and shifting sand dune, P n and E decreased but WUE increased.展开更多
Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope wit...Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things （IoT）- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems （CPSs）, cloud computing, big data analytics （BDA）, and information and communications technology （ICT） that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.展开更多
文摘Photosynthesis ( P n ), transpiration ( E ) and water use efficiency ( WUE ) of more than 66 arid sand species from different environmental habitats, shifting sand dune, fixed sand dune, lowland and wetland in the Maowusu Sand Area were analyzed and the relation among these characteristics and the resource utilization efficiency, taxonomic categories and growth forms of the species were assessed. The results showed that species from Chenopodiaceae, Gramineae, Leguminosae which possessed the C 4 photosynthesis pathway, or C 3 pathway and also with nitrogen_fixation capacities had higher or the highest P n values, i.e., 20～30 μmol CO 2·m -2 ·s -1 , while that of evergreen shrub of Pinaceae had the lowest P n values, i.e., 0～5 μmol CO 2·m -2 ·s -1 . Those species from Compositae, Scrophulariaceae, and Gramineae with C 3 pathway but no N_fixation capacity had the highest E rates, i.e., 20～30 mmol H 2O·m -2 ·s -1 and again the evergreen shrub together with some species from Salicaceae and Compositae had the lowest E rates, i.e., 0～5 mmol H 2O·m -2 ·s -1 . Species from Leguminosae, Gramineae and Chenopodiaceae with C 4 pathway or C 3 pathway with N_fixation capacity, both shrubs and grasses, generally had higher WUE . However, even the physiological traits of the same species were habitat_ and season_specific. The values of both P n and E in late summer were much higher than those in early summer, with average increases of 26%, 40% respectively in the four habitats. WUE in late summer was, however, 12% lower. Generally, when the environments became drier as a result of habitats changed, i.e., in the order of wetland, lowland, fixed sand dune and shifting sand dune, P n and E decreased but WUE increased.
文摘Our next generation of industry-lndustry 4.0-holds the promise of increased flexibility in manufacturing, along with mass customization, better quality, and improved productivity. It thus enables companies to cope with the challenges of producing increasingly individualized products with a short lead-time to market and higher quality. Intelligent manufacturing plays an important role in Industry 4.0. Typical resources are converted into intelligent objects so that they are able to sense, act, and behave within a smart environment. In order to fully understand intelligent manufacturing in the context of Industry 4.0, this paper provides a comprehensive review of associated topics such as intelligent manufacturing, Internet of Things （IoT）- enabled manufacturing, and cloud manufacturing. Similarities and differences in these topics are highlighted based on our analysis. We also review key technologies such as the loT, cyber-physical systems （CPSs）, cloud computing, big data analytics （BDA）, and information and communications technology （ICT） that are used to enable intelligent manufacturing. Next, we describe worldwide movements in intelligent manufacturing, including governmental strategic plans from different countries and strategic plans from major international companies in the European Union, United States, Japan, and China. Finally, we present current challenges and future research directions. The concepts discussed in this paper will spark new ideas in the effort to realize the much-anticipated Fourth Industrial Revolution.
