176 research outputs found

    Implicit Stochastic Optimization for deriving reservoir operating rules in semiarid Brazil

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    Este artigo investiga a aplicação de Otimização Estocástica Implícita (OEI) para determinar regras de operações mensais em um sistema de reservatórios localizado no nordeste semi-árido brasileiro. OEI emprega um modelo de otimização determinística para encontrar alocações ótimas do reservatório sob vários cenários possíveis de afluências e posteriormente constrói as regras a partir da análise deste conjunto de liberações ótimas. As políticas operacionais fornecem a alocação mensal do reservatório condicionada ao armazenamento no início do mês e a afluência prevista para o mês. Além da clássica análise de regressão, este estudo estabelece as regras por meio de uma estratégia de interpolação bidimensional. Após a sua identificação, as regras são aplicadas para operar o sistema sob novas realizações de afluências e mostram habilidade para produzir políticas semelhantes às obtidas a partir de otimização determinística tendo estas mesmas afluências como previsão perfeita.._________________________________________________________________________________________ ABSTRACT: This paper deals with the application of Implicit Stochastic Optimization (ISO) to determine monthly operating rules for a reservoir system located in the semiarid Northeast of Brazil. ISO employs a deterministic optimization model to find optimal reservoir allocations under several possible inflow scenarios and later constructs the rules by analyzing the ensemble of these optimal releases. The operating policies provide the monthly reservoir release conditioned on the storage at the beginning of the month and the inflow predicted for the month. In addition to the classical regression analysis, this study establishes the rules by a two-dimensional interpolation strategy. After the rules are identified, they are applied to operate the system under new inflow realizations and show ability to produce policies similar to those obtained by deterministic optimization taking the same inflows as perfect forecasts

    Alteration of Proteins and Pigments Influence the Function of Photosystem I under Iron Deficiency from Chlamydomonas reinhardtii

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    BACKGROUND: Iron is an essential micronutrient for all organisms because it is a component of enzyme cofactors that catalyze redox reactions in fundamental metabolic processes. Even though iron is abundant on earth, it is often present in the insoluble ferric [Fe (III)] state, leaving many surface environments Fe-limited. The haploid green alga Chlamydomonas reinhardtii is used as a model organism for studying eukaryotic photosynthesis. This study explores structural and functional changes in PSI-LHCI supercomplexes under Fe deficiency as the eukaryotic photosynthetic apparatus adapts to Fe deficiency. RESULTS: 77K emission spectra and sucrose density gradient data show that PSI and LHCI subunits are affected under iron deficiency conditions. The visible circular dichroism (CD) spectra associated with strongly-coupled chlorophyll dimers increases in intensity. The change in CD signals of pigments originates from the modification of interactions between pigment molecules. Evidence from sucrose gradients and non-denaturing (green) gels indicates that PSI-LHCI levels were reduced after cells were grown for 72 h in Fe-deficient medium. Ultrafast fluorescence spectroscopy suggests that red-shifted pigments in the PSI-LHCI antenna were lost during Fe stress. Further, denaturing gel electrophoresis and immunoblot analysis reveals that levels of the PSI subunits PsaC and PsaD decreased, while PsaE was completely absent after Fe stress. The light harvesting complexes were also susceptible to iron deficiency, with Lhca1 and Lhca9 showing the most dramatic decreases. These changes in the number and composition of PSI-LHCI supercomplexes may be caused by reactive oxygen species, which increase under Fe deficiency conditions. CONCLUSIONS: Fe deficiency induces rapid reduction of the levels of photosynthetic pigments due to a decrease in chlorophyll synthesis. Chlorophyll is important not only as a light-harvesting pigment, but also has a structural role, particularly in the pigment-rich LHCI subunits. The reduced level of chlorophyll molecules inhibits the formation of large PSI-LHCI supercomplexes, further decreasing the photosynthetic efficiency

    The Natural Statistics of Audiovisual Speech

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    Humans, like other animals, are exposed to a continuous stream of signals, which are dynamic, multimodal, extended, and time varying in nature. This complex input space must be transduced and sampled by our sensory systems and transmitted to the brain where it can guide the selection of appropriate actions. To simplify this process, it's been suggested that the brain exploits statistical regularities in the stimulus space. Tests of this idea have largely been confined to unimodal signals and natural scenes. One important class of multisensory signals for which a quantitative input space characterization is unavailable is human speech. We do not understand what signals our brain has to actively piece together from an audiovisual speech stream to arrive at a percept versus what is already embedded in the signal structure of the stream itself. In essence, we do not have a clear understanding of the natural statistics of audiovisual speech. In the present study, we identified the following major statistical features of audiovisual speech. First, we observed robust correlations and close temporal correspondence between the area of the mouth opening and the acoustic envelope. Second, we found the strongest correlation between the area of the mouth opening and vocal tract resonances. Third, we observed that both area of the mouth opening and the voice envelope are temporally modulated in the 2–7 Hz frequency range. Finally, we show that the timing of mouth movements relative to the onset of the voice is consistently between 100 and 300 ms. We interpret these data in the context of recent neural theories of speech which suggest that speech communication is a reciprocally coupled, multisensory event, whereby the outputs of the signaler are matched to the neural processes of the receiver

    In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae

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    BACKGROUND: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). RESULTS: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. CONCLUSION: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models

    Joining S100 proteins and migration:for better or for worse, in sickness and in health

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    The vast diversity of S100 proteins has demonstrated a multitude of biological correlations with cell growth, cell differentiation and cell survival in numerous physiological and pathological conditions in all cells of the body. This review summarises some of the reported regulatory functions of S100 proteins (namely S100A1, S100A2, S100A4, S100A6, S100A7, S100A8/S100A9, S100A10, S100A11, S100A12, S100B and S100P) on cellular migration and invasion, established in both culture and animal model systems and the possible mechanisms that have been proposed to be responsible. These mechanisms involve intracellular events and components of the cytoskeletal organisation (actin/myosin filaments, intermediate filaments and microtubules) as well as extracellular signalling at different cell surface receptors (RAGE and integrins). Finally, we shall attempt to demonstrate how aberrant expression of the S100 proteins may lead to pathological events and human disorders and furthermore provide a rationale to possibly explain why the expression of some of the S100 proteins (mainly S100A4 and S100P) has led to conflicting results on motility, depending on the cells used. © 2013 Springer Basel

    Saturation Vapor Pressures and Transition Enthalpies of Low-Volatility Organic Molecules of Atmospheric Relevance: From Dicarboxylic Acids to Complex Mixtures

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    Robust estimation of bacterial cell count from optical density

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    Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data
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