56 research outputs found

    Een knagend geweten?

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    <p>This is the only case in which a limited exhaustive search is possible. Interestingly, the exhaustive search locates the same nodes as the best+1 strategy for fixing up to eight nodes. The efficiency-ranked strategy performs poorly compared to the Monte Carlo strategy because the search space is small and a large portion of the available space is sampled by the Monte Carlo search.</p

    Influencia de la calidad de las calizas para la producción de cal viva en la calera La Conga del caserío de Sogorón Alto Distrito de la Encañada, Cajamarca 2017

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    RESUMEN: En el presente proyecto de investigación titulado “INFLUENCIA DE LA CALIDAD DE LAS CALIZAS PARA LA PRODUDUCCIÓN DE CAL VIVA EN LA CALERA LA CONGA DEL CASERÍO DE SOGORÓN ALTO DISTRITO DE LA ENCAÑADA, CAJAMARCA 2017”, se realizaron estudios para evaluar la calidad de las calizas dentro del área de estudio CALERA LA CONGA, con fines de producir cal viva; mediante el mapeo geológico, muestreo de calizas dentro del área de interés, análisis gravimétrico de calizas. Las calizas de la CALERA LA CONGA requieren un estudio geoquímico para determinar su calidad. Esta área de estudio está ubicada en el caserío de Sogorón Alto, distrito de La Encañada, provincia de Cajamarca y departamento de Cajamarca; esta ubicación presenta numerosas ventajas desde el punto de vista económico, como es la proximidad a las distintas unidades mineras. Para esta evaluación se realizó una investigación experimental con diseño transversal, descriptivo y aplicativo; a las 02 muestras de roca caliza; llegando a concluir que; de acuerdo a los resultados de laboratorios la presencia de CaCO en la roca caliza está entre el 92.2 a 95.64%; y que las impurezas presentes en el la roca caliza entre 4.36 a 7.8%, lo cual hace de esto una buena materia prima para la obtención de cal viva. 3ABSTRACT: In the present research project entitled “INFLUENCE OF QUALITY OF LIMES FOR THE PRODUCTION OF LIVE LIMES IN LA CALERA LA CONGA DEL CASERÍO DE SOGORÓN ALTO DISTRITO DE LA ENCAÑADA, CAJAMARCA 2017” studies were carried out to evaluate the quality of the limestone within the study area CALERA LA CONGA, in order to produce quicklime; through geological mapping, sampling of limestone within the area of interest, gravimetric analysis of limestones. The limestones of the LA CALERA LA CONGA require a geochemical study to determine their quality. This study area is located in the village Sogorón Alto, La Encañada district, province of Cajamarca and Cajamarca department; this location presents numerous advantages from the economic point of view, as is the proximity to the different mining units. For this evaluation will be realized the experimental research with transversal design, descriptive and application; at 02 samples of limestone; arriving to conclude that, according to the results of laboratories the presence of CaCO in the limestone rock is between the 92.2 to 95.64%; and that the impurities present in the limestone rock between 4.36 to 7.8%, which makes this a good raw material for the production of quicklime.

    Reference table for symbols.

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    <p>This table lists all important symbols introduced in the article with a brief explanation of its purpose.</p><p>Reference table for symbols.</p

    General properties of the full networks.

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    <p>The network used for the analysis of lung cancer is a generic one obtained combining the data sets in Refs. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105842#pone.0105842-Yang1" target="_blank">[32]</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105842#pone.0105842-Matys1" target="_blank">[33]</a>. The B cell network is a curated version of the B cell interactome obtained in Ref. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105842#pone.0105842-Lefebvre1" target="_blank">[34]</a> using a network reconstruction method and gene expression data from B cells.</p><p>General properties of the full networks.</p

    A directed acyclic network.

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    <p>Controlling all three source nodes (nodes 1, 2 and 3) guarantees full control of the network, but are ineffective when targeted individually. The best single node to control in this network is node 6 because it directly controls all downstream nodes.</p

    Properties of the largest weakly connected differential subnetworks for all cell types.

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    <p>I =  IMR-90 (normal), A =  A549 (cancer), H =  NCI-H358 (cancer), N =  Naïve (normal), M =  Memory (normal), D =  DLBCL (cancer), F =  Follicular lymphoma (cancer), L =  EBV-immortalized lymphoblastoma (cancer).</p><p>Properties of the largest weakly connected differential subnetworks for all cell types.</p

    Largest weakly connected differential subnetwork for IMR-90/A549 and <i>p</i> = 2.

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    <p>Out of the 506 pictured nodes, 450 are sinks and therefore have an impact equal to one. The top five bottlenecks are labeled with their gene names and colored orange.</p

    A network in which nodes 4, 5, 6 and 7 compose a single cycle cluster.

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    <p>The high connectivity of node 4 prevents any changes made to the spin of nodes 1–3 from propagating downstream. The only way to indirectly control nodes 8–10 is to target nodes inside of the cycle cluster. Targeting node 4, 6 or 7 will cause the entire cycle cluster to flip away from its initial state, guaranteeing control of nodes 4–10 (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0105842#pone-0105842-g004" target="_blank">Fig. 4</a>).</p

    Evolutionary properties of communities and DAVID groups in HumanNet.

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    <p>See <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005009#pcbi.1005009.t001" target="_blank">Table 1</a> for explanation of column headers.</p

    Cell cycle time series gene expression data encoded as cyclic attractors in Hopfield systems

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    <div><p>Modern time series gene expression and other omics data sets have enabled unprecedented resolution of the dynamics of cellular processes such as cell cycle and response to pharmaceutical compounds. In anticipation of the proliferation of time series data sets in the near future, we use the Hopfield model, a recurrent neural network based on spin glasses, to model the dynamics of cell cycle in HeLa (human cervical cancer) and <i>S. cerevisiae</i> cells. We study some of the rich dynamical properties of these cyclic Hopfield systems, including the ability of populations of simulated cells to recreate experimental expression data and the effects of noise on the dynamics. Next, we use a genetic algorithm to identify sets of genes which, when selectively inhibited by local external fields representing gene silencing compounds such as kinase inhibitors, disrupt the encoded cell cycle. We find, for example, that inhibiting the set of four kinases <i>AURKB</i>, <i>NEK1</i>, <i>TTK</i>, and <i>WEE1</i> causes simulated HeLa cells to accumulate in the M phase. Finally, we suggest possible improvements and extensions to our model.</p></div
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