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Cybernetic Model (cybernetic + model)
Selected AbstractsPersonal Goal Facilitation through Work: Implications for Employee Satisfaction and Well-BeingAPPLIED PSYCHOLOGY, Issue 2 2006Laura ter Doest Que le travail facilite la réalisation des objectifs personnels dépend de la perception de l'impact du travail sur l'atteinte de ces objectifs personnels. En accord avec la littérature sur l'autorégulation et le modèle cybernétique du stress organisationnel proposé par Edwards (1992), la facilitation de l'accès à ses objectifs personnels par le travail fut supposée en relation positive avec les attitudes relatives à l'emploi et le bien-être de l'employé. En outre, on a prédit un rapport plus étroit entre la facilitation de l'accès à ses objectifs personnels par le travail et les performances du salarié quand les buts personnels étaient fortement valorisés. Ces hypothèses ont été mises à l'épreuve à travers un questionnaire rempli par 1036 employés du secteur de la santé. D'après l'analyse de régression, la facilitation de l'accès à ses objectifs personnels par le travail expliquait une part importante de la variance du bien-être et des attitudes relatives à l'emploi, même après avoir contrôlé les caractéristiques des postes en référence au modèle de Karasek concernant les relations agents stressants,tension au travail (1979; Karasek & Theorell, 1990). L'importance des objectifs n'avait qu'une influence des plus limitées. On en conclut que la facilitation de l'accès à ses objectifs personnels par le travail offre une voie prometteuse pour explorer les attitudes liées à l'emploi et le bien-être, en complément des modèles plus traditionnels des caractéristiques de l'emploi. Personal goal facilitation through work refers to perceptions of the extent to which one's job facilitates the attainment of one's personal goals. In line with the self-regulation literature and Edwards' (1992) cybernetic model of organisational stress, personal goal facilitation through work was predicted to show positive associations with job attitudes and employee well-being. Moreover, stronger relationships between personal goal facilitation through work and employee outcomes were predicted for highly valued personal goals. These predictions were investigated in a questionnaire study of 1,036 health care employees. In regression analyses, personal goal facilitation through work accounted for substantial variance in job attitudes and well-being, even after controlling for job characteristics from Karasek's (1979; Karasek & Theorell, 1990) model of occupational stressor,strain relations. There was only very limited evidence of moderating effects of goal importance. It is concluded that personal goal facilitation through work offers a promising source of insight into job attitudes and well-being, complementing more traditional job characteristics models. [source] Prediction of metabolic function from limited data: Lumped hybrid cybernetic modeling (L-HCM)BIOTECHNOLOGY & BIOENGINEERING, Issue 2 2010Hyun-Seob Song Abstract Motivated by the need for a quick quantitative assessment of metabolic function without extensive data, we present an adaptation of the cybernetic framework, denoted as the lumped hybrid cybernetic model (L-HCM), which combines the attributes of the classical lumped cybernetic model (LCM) and the recently developed HCM. The basic tenet of L-HCM and HCM is the same, that is, they both view the uptake flux as being split among diverse pathways in an optimal way as a result of cellular regulation such that some chosen metabolic objective is realized. The L-HCM, however, portrays this flux distribution to occur in a hierarchical way, that is, first among lumped pathways, and next among individual elementary modes (EM) in each lumped pathway. Both splits are described by the cybernetic control laws using operational and structural return-on-investments, respectively. That is, the distribution of uptake flux at the first split is dynamically regulated according to environmental conditions, while the subsequent split is based purely on the stoichiometry of EMs. The resulting model is conveniently represented in terms of lumped pathways which are fully identified with respect to yield coefficients of all products unlike classical LCMs based on instinctive lumping. These characteristics enable the model to account for the complete set of EMs for arbitrarily large metabolic networks despite containing only a small number of parameters which can be identified using minimal data. However, the inherent conflict of questing for quantification of larger networks with smaller number of parameters cannot be resolved without a mechanism for parameter tuning of an empirical nature. In this work, this is accomplished by manipulating the relative importance of EMs by tuning the cybernetic control of mode-averaged enzyme activity with an empirical parameter. In a case study involving aerobic batch growth of Saccharomyces cerevisiae, L-HCM is compared with LCM. The former provides a much more satisfactory prediction than the latter when parameters are identified from a few primary metabolites. On the other hand, the classical model is more accurate than L-HCM when sufficient datasets are involved in parameter identification. In applying the two models to a chemostat scenario, L-HCM shows a reasonable prediction on metabolic shift from respiration to fermentation due to the Crabtree effect, which LCM predicts unsatisfactorily. While L-HCM appears amenable to expeditious estimates of metabolic function with minimal data, the more detailed dynamic models [such as HCM or those of Young et al. (Young et al., Biotechnol Bioeng, 2008; 100: 542,559)] are best suited for accurate treatment of metabolism when the potential of modern omic technology is fully realized. However, in view of the monumental effort surrounding the development of detailed models from extensive omic measurements, the preliminary insight into the behavior of a genotype and metabolic engineering directives that can come from L-HCM is indeed valuable. Biotechnol. Bioeng. 2010;106: 271,284. © 2010 Wiley Periodicals, Inc. [source] Modeling and Parameter Identification of the Simultaneous Saccharification-Fermentation Process for Ethanol ProductionBIOTECHNOLOGY PROGRESS, Issue 6 2007Silvia Ochoa Despite many environmental advantages of using alcohol as a fuel, there are still serious questions about its economical feasibility when compared with oil-based fuels. The bioethanol industry needs to be more competitive, and therefore, all stages of its production process must be simple, inexpensive, efficient, and "easy" to control. In recent years, there have been significant improvements in process design, such as in the purification technologies for ethanol dehydration (molecular sieves, pressure swing adsorption, pervaporation, etc.) and in genetic modifications of microbial strains. However, a lot of research effort is still required in optimization and control, where the first step is the development of suitable models of the process, which can be used as a simulated plant, as a soft sensor or as part of the control algorithm. Thus, toward developing good, reliable, and simple but highly predictive models that can be used in the future for optimization and process control applications, in this paper an unstructured and a cybernetic model are proposed and compared for the simultaneous saccharification-fermentation process (SSF) for the production of ethanol from starch by a recombinant Saccharomyces cerevisiae strain. The cybernetic model proposed is a new one that considers the degradation of starch not only into glucose but also into dextrins (reducing sugars) and takes into account the intracellular reactions occurring inside the cells, giving a more detailed description of the process. Furthermore, an identification procedure based on the Metropolis Monte Carlo optimization method coupled with a sensitivity analysis is proposed for the identification of the modelapos;s parameters, employing experimental data reported in the literature. [source] Cybernetic Model Predictive Control of a Continuous Bioreactor with Cell RecycleBIOTECHNOLOGY PROGRESS, Issue 5 2003Kapil G. Gadkar The control of poly-,-hydroxybutyrate (PHB) productivity in a continuous bioreactor with cell recycle is studied by simulation. A cybernetic model of PHB synthesis in Alcaligenes eutrophus is developed. Model parameters are identified using experimental data, and simulation results are presented. The model is interfaced to a multirate model predictive control (MPC) algorithm. PHB productivity and concentration are controlled by manipulating dilution rate and recycle ratio. Unmeasured time varying disturbances are imposed to study regulatory control performance, including unreachable setpoints. With proper controller tuning, the nonlinear MPC algorithm can track productivity and concentration setpoints despite a change in the sign of PHB productivity gain with respect to dilution rate. It is shown that the nonlinear MPC algorithm is able to track the maximum achievable productivity for unreachable setpoints under significant process/model mismatch. The impact of model uncertainty upon controller performance is explored. The multirate MPC algorithm is tested using three controllers employing models that vary in complexity of regulation. It is shown that controller performance deteriorates as a function of decreasing biological complexity. [source] Cybernetic Modeling and Regulation of Metabolic Pathways in Multiple Steady States of Hybridoma CellsBIOTECHNOLOGY PROGRESS, Issue 5 2000Maria Jesus Guardia Hybridoma cells utilize a pair of complementary and partially substitutable substrates, glucose and glutamine, for growth. It has been shown that cellular metabolism shifts under different culture conditions. When those cultures at different metabolic states are switched to a continuous mode, they reach different steady states under the same operating conditions. A cybernetic model was constructed to describe the complementary and partial substitutable nature of substrate utilization. The model successfully predicted the metabolic shift and multiple steady-state behavior. The results are consistent with the experimental observation that the history of the culture affects the resulting steady state. [source] | ||||||||||