Population Growth

Capital accumulation or capital formation is the process of adding a net capital stock in an economy in an effort to increase total output. Whereas population growth is a change in population at any time, and can be calculated as a change in the number of individuals in a population using "per unit time" for measurement. The purpose of this research is to find out what is capital accumulation and population growth and to know what its effects on economic growth are, and to show the development of technological progress in the Solow Model. The data in this study uses a quantitative method model. The results of data analysis show that capital accumulation and population growth are very influential on economic growth. The Sollow model also assumes an unchanging relationship between capital and labor input and the output of goods and services.

This study reports on action research efforts that were aimed at developing institutional arrangements beneficial for soil fertility improvement. Three stages of action research are described and analyzed. We initially began by bringing stakeholders together in a platform to engage in a collaborative design of new arrangements. However, this effort was stymied mainly because conditions conducive for learning and negotiation were lacking. We then proceeded to support experimentation with alternative arrangements initiated by individual landowners and migrant farmers. The implementation of these arrangements too ran into difficulties due to intra-family dynamics and ambiguities regarding land tenure. Further investigations to find out how ambiguities could be tackled revealed that the local actors themselves had taken initiatives towards developing institutional innovations to reduce ambiguities. However, there is still considerable scope for further development of these self-organized innovations. The article ends with a reflection on inter-disciplinary action research, where it is argued that making ''mistakes'' is an inherent and necessary characteristic in action research that aims to address complex social issues.

The generic, quantitative, spatially explicit, individual-based model BacSim was developed to simulate growth and behaviour of bacteria. The potential of this approach is in relating the properties of microscopic entities -cells -to the properties of macroscopic, complex systems such as biofilms. Here, the growth of a single Escherichia coli cell into a colony was studied. The object-oriented program BacSim is an extension of Gecko, an ecosystem dynamics model which uses the Swarm toolkit for multi-agent simulations. The model describes bacterial properties including substrate uptake, metabolism, maintenance, cell division and death at the individual cell level. With the aim of making the model easily applicable to various bacteria under different conditions, the model uses as few as eight readily obtainable parameters which can be randomly varied. For substrate diffusion, a two-dimensional diffusion lattice is used. For growth-rate-dependent cell size variation, a conceptual model of cell division proposed by Donachie was examined. A mechanistic version of the Donachie model led to unbalanced growth at higher growth rates, whereas including a minimum period between subsequent replication initiations ensured balanced growth only if this period was unphysiologically long. Only a descriptive version of the Donachie model predicted cell sizes correctly. For maintenance, the Herbert model (constant specific rate of biomass consumption) and for substrate uptake, the Michaelis-Menten or the Best equations were implemented. The simulator output faithfully reproduced all input parameters. Growth characteristics when maintenance and uptake rates were proportional to either cell mass or surface area are compared. The authors propose a new generic measure of growth synchrony to quantify the loss of synchrony due to random variation of cell parameters or spatial heterogeneity. Variation of the maximal uptake rate completely desynchronizes the simulated culture but variation of the volume-at-division does not. A new measure for spatial heterogeneity is introduced : the standard deviation of substrate concentrations as experienced by the cells. Spatial heterogeneity desynchronizes population growth by subdividing the population into parts synchronously growing at different rates. At a high enough spatial heterogeneity, the population appears to grow completely asynchronously.