958 research outputs found

    Clustering approach applied on an artificial neural network model to predict PM10 in mega cities of México

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    A cluster-based artificial neural network model called CLASO (Classification-Assemblage-Association) has been proposed to predict the maximum of the 24-h moving average of PM10 concentration on the next day in the three largest metropolitan areas of Mexico. The model is a self-organised, real-time learning neural network, which builds its topology via a process of pattern classification by using an historical database. This process is based on a supervised clustering technique, assigning a class to each centroid of the hidden layer, employing the Euclidean distance as a hierarchical criterion. A set of ARIMA models was compared with CLASO model in the forecast performance of the 24-h average PM10 concentration on the next day. In general, CLASO model produced more accurate predictions of the maximum of the 24-h moving average of PM10 concentration than the ARIMA models, although the latter showed a minor tendency to underpredict the results. The CLASO model solely requires to be built a historical database of the air quality parameter, an initial radius of classification and the learning factor. CLASO has demonstrated acceptable predictions of 24-h average PM10 concentration by using exclusively regressive PM10 concentrations. The forecasting capabilities of the model were found to be satisfactory compared to the classical models, demonstrating its potential application to the other major pollutants used in the Mexican air quality index

    Engineering principles for rationally design therapeutic strategies against hepatocellular carcinoma

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    The search for new therapeutic strategies against cancer has favored the emergence of rationally designed treatments. These treatments have focused on attacking cell plasticity mechanisms to block the transformation of epithelial cells into cancerous cells. The aim of these approaches was to control particularly lethal cancers such as hepatocellular carcinoma. However, they have not been able to control the progression of cancer for unknown reasons. Facing this scenario, emerging areas such as systems biology propose using engineering principles to design and optimize cancer treatments. Beyond the possibilities that this approach might offer, it is necessary to know whether its implementation at a clinical level is viable or not. Therefore, in this paper, we will review the engineering principles that could be applied to rationally design strategies against hepatocellular carcinoma, and discuss whether the necessary elements exist to implement them. In particular, we will emphasize whether these engineering principles could be applied to fight hepatocellular carcinoma

    Detection and quantification of pore, solid and gravel spaces in CT images of a 3D soil sample

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    © 2020 Elsevier Inc. In this study, we scanned the core of a cylindrical soil sample (60mm diameter and 100mm height) by X-ray Computed Tomography (CT) producing 300 consecutive 2D digital images with 16-bit gray level depth and a resolution of 32 microns (image size 676 × 676 pixels). The aim of this work was to determine the geometry and spatial distribution of the elements in a sample, related in this case to pore, solid and gravel, inside each 2D image for the latter reconstruction of the corresponding 3D approximation of the elements using the total set of 300 soil images. Therefore, it was possible to determine the relative percentage of each element present in each 2D image and, correspondingly, the structure and total percentage in the 3D reconstruction. The identification of elements in the 2D image slices was very well accomplished using three standard segmentation algorithms: k-Means, Fuzzy c-Means and Otsu multilevel. In order to compare and evaluate the quality of results, a non-uniformity (NU) measure was applied such that low values were indicative of homogeneous regions. Due to the depth of the greyscale of the images, the results were very similar with comparable statistics and homogeneity (NU values) among the detected materials of the three algorithms. That suggests that the pore, solid and gravel spaces were very well identified, and this is reflected through their connectivity in the 3D reconstruction. Additionally, the gray level depth was reduced to 8 bits and the same study was undertaken. In this case, the quality of results was comparable to the previous ones, as the number of elements and NU values were very close. However, this also depends largely on the high resolution of the images. Thereby, the soil sample of this work was very well characterized using the simplest and most common algorithms for image segmentation thanks to the high contrast and resolution, and regardless the depth of the grey-level

    The molecular basis and biologic significance of the β-dystroglycan-emerin interaction

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    β-dystroglycan (β-DG) assembles with lamins A/C and B1 and emerin at the nuclear envelope (NE) to maintain proper nuclear architecture and function. To provide insight into the nuclear function of β-DG, we characterized the interaction between β-DG and emerin at the molecular level. Emerin is a major NE protein that regulates multiple nuclear processes and whose deficiency results in Emery–Dreifuss muscular dystrophy (EDMD). Using truncated variants of β-DG and emerin, via a series of in vitro and in vivo binding experiments and a tailored computational analysis, we determined that the β-DG–emerin interaction is mediated at least in part by their respective transmembrane domains (TM). Using surface plasmon resonance assays we showed that emerin binds to β-DG with high affinity (KD in the nanomolar range). Remarkably, the analysis of cells in which DG was knocked out demonstrated that loss of β-DG resulted in a decreased emerin stability and impairment of emerin-mediated processes. β-DG and emerin are reciprocally required for their optimal targeting within the NE, as shown by immunofluorescence, western blotting and immunoprecipitation assays using emerin variants with mutations in the TM domain and B-lymphocytes of a patient with EDMD. In summary, we demonstrated that β-DG plays a role as an emerin interacting partner modulating its stability and function

    Search for bottom squarks in pbarp collisions at sqrt(s)=1.8 TeV

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    We report on a search for bottom squarks produced in pbarp collisions at sqrt(s) = 1.8 TeV using the D0 detector at Fermilab. Bottom squarks are assumed to be produced in pairs and to decay to the lightest supersymmetric particle (LSP) and a b quark with branching fraction of 100%. The LSP is assumed to be the lightest neutralino and stable. We set limits on the production cross section as a function of bottom squark mass and LSP mass.Comment: 5 pages, Latex. submitted 3-12-1999 to PRD - Rapid Communicatio

    Differential Production Cross Section of Z Bosons as a Function of Transverse Momentum at sqrt{s}=1.8 TeV

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    We present a measurement of the transverse momentum distribution of Z bosons produced in ppbar collisions at sqrt{s}=1.8 TeV using data collected by the D0 experiment at the Fermilab Tevatron Collider during 1994--1996. We find good agreement between our data and a current resummation calculation. We also use our data to extract values of the non-perturbative parameters for a particular version of the resummation formalism, obtaining significantly more precise values than previous determinations.Comment: 10 pages, 2 figures, submitted to Phys. Rev. Letters v2 has margin error correcte

    Search for Squarks and Gluinos in Events Containing Jets and a Large Imbalance in Transverse Energy

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    Using data corresponding to an integrated luminosity of 79 pb-1, D0 has searched for events containing multiple jets and large missing transverse energy in pbar-p collisions at sqrt(s)=1.8 TeV at the Fermilab Tevatron collider. Observing no significant excess beyond what is expected from the standard model, we set limits on the masses of squarks and gluinos and on the model parameters m_0 and m_1/2, in the framework of the minimal low-energy supergravity models of supersymmetry. For tan(beta) = 2 and A_0 = 0, with mu < 0, we exclude all models with m_squark < 250 GeV/c^2. For models with equal squark and gluino masses, we exclude m < 260 GeV/c^2.Comment: 10 pages, 3 figures, Submitted to PRL, Fixed typo on page bottom of p. 6 (QCD multijet background is 35.4 events

    Search for Charged Higgs Bosons in Decays of Top Quark Pairs

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    We present a search for charged Higgs bosons in decays of pair-produced top quarks using 109.2 +- 5.8 pb^-1 of data recorded from ppbar collisions at sqrt{s} = 1.8 TeV by the D0 detector during 1992-96 at the Fermilab Tevatron. No evidence is found for charged Higgs production, and most parts of the [m(H+),tan(beta)] parameter space where the decay t -> bH+ has a branching fraction close to or larger than that for t -> bW+ are excluded at 95% confidence level. Assuming m(t) = 175 GeV and sigma(ppbar -> ttbar) = 5.5 pb, for m(H+) = 60 GeV, we exclude tan(beta) 40.9.Comment: 11 pages, 3 figures, submitted to PR

    Measurement of the Top Quark Mass Using Dilepton Events

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    The D0 collaboration has performed a measurement of the top quark mass based on six candidate events for the process t tbar -> b W+ bbar W-, where the W bosons decay to e nu or mu nu. This sample was collected during an exposure of the D0 detector to an integrated luminosity of 125 pb^-1 of sqrt(s)=1.8 TeV p-pbar collisions. We obtain mt = 168.4 +- 12.3 (stat) +- 3.7 (sys) GeV/c^2, consistent with the measurement obtained using single-lepton events. Combination of the single-lepton and dilepton results yields mt = 172.0 +- 7.5 GeV/c^2.Comment: 12 pages, 3 figure

    Measurement of the WW Boson Mass

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    A measurement of the mass of the WW boson is presented based on a sample of 5982 WeνW \rightarrow e \nu decays observed in ppp\overline{p} collisions at s\sqrt{s} = 1.8~TeV with the D\O\ detector during the 1992--1993 run. From a fit to the transverse mass spectrum, combined with measurements of the ZZ boson mass, the WW boson mass is measured to be MW=80.350±0.140(stat.)±0.165(syst.)±0.160(scale)GeV/c2M_W = 80.350 \pm 0.140 (stat.) \pm 0.165 (syst.) \pm 0.160 (scale) GeV/c^2.Comment: 12 pages, LaTex, style Revtex, including 3 postscript figures (submitted to PRL
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