Non-balanced Growth Research Articles

OPTIMAL HARVESTING OF LIPIDS-RICH MICROALGAE SUBJECT TO A CIRCADIAN CYCLE UNDER LIMITED NITROGEN SUPPLY

The harvesting of algae rich in triacylglycerol from an open raceway pond with volume-changes synchronized to the circadian cycle and under limited nitrogen supply is researched. A reduced metabolic model of its non-balanced growth is embedded into a macroscopic balance for simulating growth in such a type of bioreactor. Afterwards, the model is used jointly with optimal control to derive cyclic inlet and outlet flow policies as well as optimal nitrogen levels for different time-horizons and initial physiological states in a case study which uses bibliographic data for the Tisochrysis lutea alga.

Land and housing: The twin forces of non-balanced growth

In a three-sector closed economy where housing land is accumulated for the construction of houses, we depict significant effects of housing and land market on sectoral growth. We assume agriculture is the most intensive in the use of land, followed by manufacturing and then services. In the long run, land intensity differences in conjunction with labor growth contribute to sectoral growth gaps. In the short run, due to housing land accumulation, the economy transitions along a non-monotonic convergent path to the steady state. Using the US data, we quantify that land accounts for about one-tenth of long-run and short-run sectoral output growth gaps. We also incorporate sector-specific land-use restrictions to show that, despite these regulations, land and housing have qualitative effects on non-balanced growth.

Data deepening and nonbalanced economic growth

As a newly emerging factor, data can promote economic growth by driving technological progress, and nonbalanced growth between digital industries and nondigital industries has been notable in recent years. This paper provides a novel growth model with two sectors that differ in the degree of data deepening and the factor structure of the production function. In the model, data in one sector is the by-product of economic activities not only in its sector, but also in the other sector. More importantly, data utilization within and across sectors can spur new ideas and promote technological innovation. The model indicates that increases in the stock of data in the two sectors have opposite effects on the allocation of skilled labor between the two sectors. The skill premium (the wage of skilled labor relative to the wage of unskilled labor) decreases with an increase in the fraction of skilled labor employed in the data-extensive sector. With credible parameter values, model calibration shows that faster growth of output occurs in the more data-intensive sector and the high skill premium persists in the long run.

Romer meets Kongsamut–Rebelo–Xie in a nonbalanced growth model

To explain the newly found empirical relationship between human capital accumulation and structural change, the paper introduces Romer (1990)’s endogenous technological change into the multi-sector growth model pioneered by KRX (1997, 2001), and shows that an increase in the level of human capital accelerates the structural transformation of the economy, while the incremental effect of human capital on structural change is smaller at higher levels of human capital. The theoretical results of the combined model matches the empirical findings very well.

DRUM: A New Framework for Metabolic Modeling under Non-Balanced Growth. Application to the Carbon Metabolism of Unicellular Microalgae

Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.

A new framework for metabolic modeling under non-balanced growth. Application to carbon metabolism of unicellular microalgae

Macroscopic and metabolic models are ubiquitous tools for bioprocess modeling and understanding. While these two modeling approaches bring answers to different objectives, a remaining challenging question is how to couple macroscopic and intracellular models to enlarge the prediction capabilities of the model while keeping a model structure with low complexity level? In this paper, we provide conceptual guidelines to address this question. We propose a new modeling framework that manages non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage consists in determining metabolic sub-networks, which are assumed to satisfy balanced growth condition. Then, the remaining metabolites interconnecting the sub-networks can dynamically accumulate or be reused. The basis of our approach is illustrated for the carbon metabolic network of unicellular microalgae.

Capital Deepening and Nonbalanced Economic Growth

We present a model of nonbalanced growth based on differences in factor proportions and capital deepening. Capital deepening increases the relative output of the more capital‐intensive sector but simultaneously induces a reallocation of capital and labor away from that sector. Using a two‐sector general equilibrium model, we show that nonbalanced growth is consistent with an asymptotic equilibrium with a constant interest rate and capital share in national income. For plausible parameter values, the model generates dynamics consistent with U.S. data, in particular, faster growth of employment and slower growth of output in less capital‐intensive sectors, and aggregate behavior consistent with the Kaldor facts.

Linking chlorophyll-nutrient dynamics to the RedÞeld N:C ratio with a model of optimal phytoplankton growth

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 287:33-43 (2005) - doi:10.3354/meps287033 Linking chlorophyll-nutrient dynamics to the Redfield N:C ratio with a model of optimal phytoplankton growth Markus Pahlow* Dalhousie University, 1355 Oxford Street, Halifax, B3H 4J1 Nova Scotia, CanadaBedford Institute of Oceanography, PO Box, 1006 Dartmouth, B2Y 4A2 Nova Scotia, Canada *-Address for correspondence: Dartmouth Email: pahlowm@mar.dfo-mpo.gc.ca ABSTRACT: The Redfield N:C ratio is a fundamental quantity in marine biogeochemistry because it is a key determinant of the efficiency of the biological carbon pump, yet no convincing explanations have been put forward for its remarkable constancy over much of the world ocean. Phytoplankton growth models have so far been unable to account for the different relationships between growth rate and N:C ratio under nutrient and light limitation, and have not been able to predict the Redfield N:C ratio. A relatively simple model of coupled chlorophyll and nutrient dynamics is developed from the premise that phytoplankton maximize growth by optimally allocating nutrient and energy resources among competing metabolic requirements for nutrient uptake, light-harvesting, and growth. The model reconciles nutrient and light limitation and appears valid under both balanced and non-balanced growth conditions. The Redfield N:C ratio and its constancy are explained as a result of evolutionary pressure towards maximizing light-limited growth rates in relatively carbon-rich oceanic waters. KEY WORDS: Light limitation · Nutrient limitation · Phytoplankton growth model · Redfield N:C Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 287. Online publication date: February 18, 2005 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2005 Inter-Research.

National Accounting with Natural and Other Types of Capital

We do double-entry national accounting and incorporate zero profit arbitrageconditions (Euler equations) for different types of capital, includingnatural capital. In non-balanced growth, capital gains terms for capitalgoods appear in the income side of the accounts. Depreciation terms appearon the product or expenditure side. We consider renewable natural capital aswell as non-renewable of both durable and non-durable types.

Transition Probability Cell Cycle Model. Part II—Nonbalanced Growth

A cell cycle model based on the transition probability model of Smith & Martin has been extended to non-balanced growth conditions in batch cultures. The model considers transition to a quiescent cell fraction, variable maturity-velocity, exogenous maintenance, and cell death. This extended model is capable of describing a large range of cell culture behavior which may not conform to Monod kinetics. The use of a constant quiescent transition allows the population to enter a stationary phase, but with a very large A-state to B-phase cell ratio. A substrate dependent quiescent transition helps to reduce this ratio while maintaining the general features of the population growth curves. A model with substrate dependent variable maturity-velocity qualitatively is similar to the Monod equation, while providing additional information on population distribution. The combination of quiescent transition and a substrate dependent maturity-velocity is also examined, and the resulting model is shown to capture the essence of both features.

Non-Balanced Growth and Kondratieff Waves in the World Economy, 1850–1913

During 1850–1913 the growth of the world economy was not steady. The observed variations are described with the phrase “G-waves.” In contrast to Kondratieff long waves, G-waves lack a regular periodicity and amplitude.

Durable capital and economic growth

InCapital and Time Hicks explores Neo-Austrian capital theory. It is shown here that this approach is a special case of the more general method of treating fixed capital as introduced by Von Neumann. In the Neo-Austrian model the path of balanced growth is analysed with reduced form equations. The second part of this article discusses paths of non-balanced growth. If the steady state is disturbed by the introduction of a superior technique Hicks needs a three-stage dynamic model for a full description of subsequent developments. Special attention is given to the Full Employment path.