We investigated this aspect by assessing the sensitivity of the patchy patterns to the various parameters (diffusion, decay, production, and basal production) of the Gierer Meinhardt model.
It also argued that in the globalization process, as countries become more open to international trade, FDI, and international technological diffusion, domestic production and productivity growth can also depend on R&D activities of other countries (Bodman and Le 2013).
When the pore pressure is high enough, the influence of surface diffusion on production is hard to observe and thus can be ignored.
Nevertheless, the development of this technology depends on the growth and diffusion of production, storage and refuelling infrastructures together with accurate risk analyses to appropriately design the safety and management systems used in these plants.
In order to capture these different processes in different times of the year, i.e., diffusion versus production processes we calculated a new index, normalised seasonal difference in soil respiration (SDSR), which is proposed as a good indicator of the state and functioning of the ecosystem.
As a result we only have relative rather than absolute parameter values, i.e. relative diffusion coefficients, production and decay rates etc.
Gains from trade can be characterised by improved labor supply, expanded production, diffusion of innovation, competitive pressures, economic restructuring, etc., leading to total factor productivity and GDP growth (Lakshmanan, 2011).
Meanwhile, the impact of surface diffusion on the production of fractured horizontal wells becomes bigger and thus cannot be ignored.
Lundvall (1992) defined NSI as the location-bound elements and relationships interacting in the production, diffusion and use of new, and economically useful, knowledge.
Javadpour and Moghanloo (2013) built a methane molecule migration model and further discussed the contribution of molecular diffusion to gas production.
