Steady-state global optimization of metabolic non-linear dynamic models through recasting into power-law canonical models

Background: Design of newly engineered microbial strains for biotechnological purposes would greatly benefit from the development of realistic mathematical models for the processes to be optimized. Such models can then be analyzed and, with the development and application of appropriate optimization techniques, one could identify the modifications that need to be made to the organism in order to achieve the desired biotechnological goal. As appropriate models to perform such an analysis are necessarily non-linear and typically non-convex, finding their global optimum is a challenging task. Canonical modeling techniques, such as Generalized Mass Action (GMA) models based on the power-law formalism, offer a possible solution to this problem because they have a mathematical structure that enables the development of specific algorithms for global optimization. Results: Based on the GMA canonical representation, we have developed in previous works a highly efficient optimization algorithm and a set of related strategies for understanding the evolution of adaptive responses in cellular metabolism. Here, we explore the possibility of recasting kinetic non-linear models into an equivalent GMA model, so that global optimization on the recast GMA model can be performed. With this technique, optimization is greatly facilitated and the results are transposable to the original non-linear problem. This procedure is straightforward for a particular class of non-linear models known as Saturable and Cooperative (SC) models that extend the power-law formalism to deal with saturation and cooperativity. Conclusions: Our results show that recasting non-linear kinetic models into GMA models is indeed an appropriate strategy that helps overcoming some of the numerical difficulties that arise during the global optimization task.

The global uranium rush and its Africa frontier. Lessons from Namibia

Uranium mines are the - often forgotten - source of nuclear power. The promotion of nuclear energy as a clean alternative and the projected increase of electricity demand in countries such as China and India, have led to a global “uranium rush”, unseen since the peak of the Cold War. This article studies the formation of the expanding nuclear frontier looking at the interaction between the global uranium metabolism, industrial dynamics and local ecologies of resistance using Namibia as a case-study. Namibia, the world´s fourth largest producer of uranium, stands at the frontier of this rush with sixty-six recently granted prospecting licenses that could turn into mines, compared to only three currently operating mines. We focus on three generic attributes that help to explain the emergence and intensity of resistance by local communities to uranium mining: the ecology and geography of the resource; the degree and type of political and economic marginalization of the community; and crucially, the connection and integration of local concerns with broader social movements and political demands. We show with the use of empirical material how these factors play out differently in five Namibian communities that have been, or stand to be, affected by uranium mining, and explain how local ecologies of resistance shape the global uranium rush.

International regimes as knowledge syndicates? Energy and trends of global governance

El poder de l'Estat i la sobirania tradicional s'està deteriorant de manera constant, sobretot en termes de la provisió de certs béns públics fonamentals. Els Estats, en particular, són incapaços de manejar el coneixement i la informació que és essencial per mantenir la competitivitat i la sostenibilitat en una economia interdependent. Estructures fiables de la governança mundial i la cooperació internacional estan lluny de ser establertes. Energia com a problema a les agendes p dels governs, les empreses privades i la societat civil és un exemple manifest d'aquesta dinàmica.. L'actual sistema de governança mundial d'energia implica accions polítiques disperses per actors divers. L'Agència Internacional de l'Energia té un paper destacat, però està debilitat per la seva composició limitada i basada en el coneixement- epistèmic en lloc del material o executiu. Aquest treball sosté que ni la mida ni nombre de membres disponibles estan dificultant la governabilitat mundial d'energia. Més aviat, l'energia és una sèrie de béns públics que es troben als llimbs, on els estats no poden pagar la seva disposició, així com els diversos interessos impedir l'establiment d'una autoritat internacional. Després de la introducció de la teoria del règim internacional i el concepte de coneixement basats en les comunitats epistèmiques, l'article revisa l'estat actual de la governabilitat de l'energia mundia. A continuació es presenta una comparació d'aquesta estructura amb els règims de govern nacional i regional, d'una banda, i amb règims globals ambientals i de salut, de l'altra

Power supply noise and logic error probability

Voltage fluctuations caused by parasitic impedances in the power supply rails of modern ICs are a major concern in nowadays ICs. The voltage fluctuations are spread out to the diverse nodes of the internal sections causing two effects: a degradation of performances mainly impacting gate delays anda noisy contamination of the quiescent levels of the logic that drives the node. Both effects are presented together, in thispaper, showing than both are a cause of errors in modern and future digital circuits. The paper groups both error mechanismsand shows how the global error rate is related with the voltage deviation and the period of the clock of the digital system.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.