986 resultados para ddc: 658.812
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LOW-ENERGY electron diffraction (LEED) has become the most successful technique in surface crystallography1, but because of the complexity of the surface-electron scattering interactions, analyses of LEED data are still conducted on a trial-and-error basis: a direct-inversion method for treating LEED intensity data remains an attractive goal2. Building on recent theoretical and experimental developments in electron holography from surface structures3-16, we show here that three-dimensional images with atomic resolution can be obtained by a direct transform of conventional LEED intensity spectra.
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We present a novel method for the light-curve characterization of Pan-STARRS1 Medium Deep Survey (PS1 MDS) extragalactic sources into stochastic variables (SVs) and burst-like (BL) transients, using multi-band image-differencing time-series data. We select detections in difference images associated with galaxy hosts using a star/galaxy catalog extracted from the deep PS1 MDS stacked images, and adopt a maximum a posteriori formulation to model their difference-flux time-series in four Pan-STARRS1 photometric bands gP1, rP1, iP1, and zP1. We use three deterministic light-curve models to fit BL transients; a Gaussian, a Gamma distribution, and an analytic supernova (SN) model, and one stochastic light-curve model, the Ornstein-Uhlenbeck process, in order to fit variability that is characteristic of active galactic nuclei (AGNs). We assess the quality of fit of the models band-wise and source-wise, using their estimated leave-out-one cross-validation likelihoods and corrected Akaike information criteria. We then apply a K-means clustering algorithm on these statistics, to determine the source classification in each band. The final source classification is derived as a combination of the individual filter classifications, resulting in two measures of classification quality, from the averages across the photometric filters of (1) the classifications determined from the closest K-means cluster centers, and (2) the square distances from the clustering centers in the K-means clustering spaces. For a verification set of AGNs and SNe, we show that SV and BL occupy distinct regions in the plane constituted by these measures. We use our clustering method to characterize 4361 extragalactic image difference detected sources, in the first 2.5 yr of the PS1 MDS, into 1529 BL, and 2262 SV, with a purity of 95.00% for AGNs, and 90.97% for SN based on our verification sets. We combine our light-curve classifications with their nuclear or off-nuclear host galaxy offsets, to define a robust photometric sample of 1233 AGNs and 812 SNe. With these two samples, we characterize their variability and host galaxy properties, and identify simple photometric priors that would enable their real-time identification in future wide-field synoptic surveys.
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Aim: Impacts of invasive species may vary across invasion gradients, owing to trait-based sorting of individuals through dispersal: those aggregating at invasion fronts may be more aggressive and voracious. We examine, in the field and laboratory, variation in the predatory impacts of an invasive Ponto-Caspian crustacean Hemimysis anomala G.O. Sars, 1907 at two sites along a spatio-temporal gradient of invasion.
Location: Republic of Ireland.
Methods: We used reciprocal transplant field-deployed mesocosms to compare predation rates of invasion front and well-established H. anomala on natural zooplankton assemblages. In the laboratory, we measured the functional response (relationship between predation rate and prey supply) of H. anomala from both sites, for a per capita mechanistic comparison of predation efficiency. We also assessed prey selectivity of H. anomala in the mesocosm experiments to further compare feeding behaviour. Finally, we used a correlative approach to assess the community impact of H. anomala across sites, including a nearby uninvaded site, by comparing zooplankton diversities and densities.
Results: Invasion front H. anomala had higher predation rates than well-established H. anomala at high in situ zooplankton densities. Invasion front H. anomala also had higher functional responses - in particular showing higher 'attack rates' - indicating a heightened ability to locate and capture prey. Prey selectivity was consistent across the spatio-temporal contrast, with positive selection for cladocerans. Zooplankton diversity and density declined with time since H. anomala invasion, both being maximal at the uninvaded site.
Main conclusions: Our study, for the first time, (1) reveals differences in predatory per capita effects and associated behavioural traits between two sites along a spatio-temporal invasion gradient and (2) shows a negative community-level impact of the invasive H. anomala in natural water bodies. Further spatio-temporal comparisons of predatory per capita effects of invaders are needed to assess the generality of these results.
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Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis.
Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain.
Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 X 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 X 10(-11)), cholesterol transport (P = 2.96 X 10(-9)), and proteasome-ubiquitin activity (P = 1.34 X 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05).
Conclusions: The immime response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics. (C) 2015 Published by Elsevier Inc. on behalf of The Alzheimer's Association.
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Tumor cells require angiogenesis to deliver nutrients and oxygen to support their fast growth and metabolism. The vascular endothelial growth factor (VEGF) pathway plays an important role in promoting angiogenesis, including tumor-induced angiogenesis. Recent clinical trials have demonstrated the benefit of targeting VEGF in the treatment of glioblastoma. However, the prognostic significance of the expression of VEGFA and its receptors VEGFR1 (FLT1) and VEGFR2 (KDR) are still largely elusive. In the present study, we aimed to investigate the prognostic significance of these three factors, alone or in combination, in glioma patients. Gene mRNA expression was extracted from three independent brain tumor cohorts totaling 242 patients and the association between gene expression and survival was tested. We found that when VEGFA, FLT1 and KDR expressions were considered alone, only VEGFA demonstrated a significant association with patient survival. Patients with high expression of both VEGFA and either receptor had significantly worse survival than patients expressing both factors at a low level. Importantly, we found that those patients whose tumors overexpressed all three genes had a significantly shorter survival compared to those patients with a low level expression of these genes. Our results suggest that a high level expression of VEGFA and its receptors, both FLT1 and KDR, may be required for brain tumor progression, and that these three factors should be considered together as a prognostic indicator for brain tumor patients.
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Recent high-resolution observations of sunspot oscillations using simultaneously operated ground- and space-based telescopes reveal the intrinsic connection between different layers of the solar atmosphere. However, it is not clear whether these oscillations are externally driven or generated in situ. We address this question by using observations of propagating slow magnetoacoustic waves along a coronal fan loop system. In addition to the generally observed decreases in oscillation amplitudes with distance, the observed wave amplitudes are also found to be modulated with time, with similar variations observed throughout the propagation path of the wave train. Employing multi-wavelength and multi-instrument data, we study the amplitude variations with time as the waves propagate through different layers of the solar atmosphere. By comparing the amplitude modulation period in different layers, we find that slow magnetoacoustic waves observed in sunspots are externally driven by photospheric p-modes, which propagate upward into the corona before becoming dissipated.
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Background: RAS is mutated (RASMT) in ~55% of mCRC, and phase III studies have shown that patients harbouring RAS mutations do not benefit from anti-EGFR MoAbs. In addition, ~50% of RAS Wild Type (RASWT) will not benefit from the addition of an EGFR MoAb to standard chemotherapy. Hence, novel treatment strategies are urgently needed for RASMT and > 50% of RASWT mCRC patients. c-MET is overexpressed in ~50-60%, amplified in ~2-3% and mutated in ~3-5% of mCRC. Recent preclinical studies have shown that c-MET is an important mediator of resistance to MEK inhibitors (i) in RASMT mCRC, and that combined MEKi/METi resulted in synergistic reduction in tumour growth in RASMT xenograft models (1). A number of recent studies have highlighted the role of c-MET in mediating primary/secondary resistance to anti-EGFR MoAbs in mCRC, suggesting that patient with RASWT tumours with aberrant c-MET (RASWT/c-MET+) may benefit from anti-c-MET targeted therapies (2). These preclinical data supported the further clinical evaluation of combined MEKi/METi treatment in RASMT and RASWT CRC patients with aberrant c-MET signalling (overexpression, amplification or mutation; RASWT/c-MET+). Methods: MErCuRIC1 is a phase I combination study of METi crizotinib with MEKi PD-0325901. The dose escalation phase, utilizing a rolling six design, recruits 12-24 patients with advanced solid tumours and aims to assess safety/toxicity of combination, recommended phase II (RPII) dose, pharmacokinetics (PK) and pharmacodynamics (PD) (pERK1/2 in PBMC and tumour; soluble c-MET). In the dose expansion phase an additional 30-42 RASMT and RASWT/c-MET mCRC patients with biopsiable disease will be treated at the RPII dose to further evaluate safety, PK, PD and treatment response. In the dose expansion phase additional biopsy and blood samples will be obtained to define mechanisms of response/resistance to crizotinib/PD-0325901 therapy. Enrolment into the dose escalation phase began in December 2014 with cohort 1 still ongoing. EudraCT registry number: 2014-000463-40. (1) Van Schaeybroeck S et al. Cell Reports 2014;7(6):1940-55; (2) Bardelli A et al. Cancer Discov 2013;3(6):658-73. Clinical trial information: 2014-000463-40.
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The main objective of the study presented in this paper was to investigate the feasibility using support vector machines (SVM) for the prediction of the fresh properties of self-compacting concrete. The radial basis function (RBF) and polynomial kernels were used to predict these properties as a function of the content of mix components. The fresh properties were assessed with the slump flow, T50, T60, V-funnel time, Orimet time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 min after adding the first water. The water dosage varied from 188 to 208 L/m3, the dosage of superplasticiser (SP) from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3. In total, twenty mixes were used to measure the fresh state properties with different mixture compositions. RBF kernel was more accurate compared to polynomial kernel based support vector machines with a root mean square error (RMSE) of 26.9 (correlation coefficient of R2 = 0.974) for slump flow prediction, a RMSE of 0.55 (R2 = 0.910) for T50 (s) prediction, a RMSE of 1.71 (R2 = 0.812) for T60 (s) prediction, a RMSE of 0.1517 (R2 = 0.990) for V-funnel time prediction, a RMSE of 3.99 (R2 = 0.976) for Orimet time prediction, and a RMSE of 0.042 (R2 = 0.988) for L-box ratio prediction, respectively. A sensitivity analysis was performed to evaluate the effects of the dosage of cement and limestone powder, the water content, the volumes of coarse aggregate and sand, the dosage of SP and the testing time on the predicted test responses. The analysis indicates that the proposed SVM RBF model can gain a high precision, which provides an alternative method for predicting the fresh properties of SCC.
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Dissertação de mest., Marketing, Faculdade de Economia, Universidade do Algarve, 2009
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Dissertação de Mestrado , Ciências Económicas e Empresariais, Faculdade de Economia, Universidade do Algarve, 2008
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Dissertação mest., Gestão Empresarial, Universidade do Algarve, 2009
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Dissertação de mest., Finanças Empresariais, Faculdade de Economia, Universidade do Algarve, 2009
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Dissertação mest., Gestão Empresarial, Universidade do Algarve, 2008
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Dissertação de Mestrado, Biologia Marinha, especialização em Pescas e Aquacultura, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2009