36 resultados para Median voter


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Blocks of 3Y-TZP were indented with conical diamond indenters. indentation caused tetragonal to monoclinic phase transformation in a subsurface. Of the cracks generated in the subsurface, radial and lateral cracks can be accounted for by a continuum model of the indented subsurface, built using a combination of the Boussinesq and blister stress fields. Additional ring, median and cone cracks were also observed. It is hypothesized that the latter are motivated by the reduction in blister strength or residual energy brought about by the material damage caused by the phase transformation. This damage reduces the load bearing capacity of the material progressively with increasing normal load.

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Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio HR] = 2.4; 95% CI = 1.4-3.8; p < 0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1-2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4-2.8; p < 0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04-1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.

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Seizure electroencephalography (EEG) was recorded from two channels-right (Rt) and left (Lt)-during bilateral electroconvulsive therapy (ECT) (n = 12) and unilateral ECT (n = 12). The EEG was also acquired into a microcomputer and was analyzed without knowledge of the clinical details. EEG recordings of both ECT procedures yielded seizures of comparable duration. The Strength Symmetry Index (SSI) was computed from the early- and midseizure phases using the fractal dimension of the EEG. The seizures of unilateral ECT were characterized by significantly smaller SSI in both phases. More unilateral than bilateral ECT seizures had a smaller than median SSI in both phases. The seizures also differed on other measures as reported in the literature. The findings indicate that SSI may be a potential measure of seizure adequacy that remains to be validated in future research.

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We present two online algorithms for maintaining a topological order of a directed acyclic graph as arcs are added, and detecting a cycle when one is created. Our first algorithm takes O(m 1/2) amortized time per arc and our second algorithm takes O(n 2.5/m) amortized time per arc, where n is the number of vertices and m is the total number of arcs. For sparse graphs, our O(m 1/2) bound improves the best previous bound by a factor of logn and is tight to within a constant factor for a natural class of algorithms that includes all the existing ones. Our main insight is that the two-way search method of previous algorithms does not require an ordered search, but can be more general, allowing us to avoid the use of heaps (priority queues). Instead, the deterministic version of our algorithm uses (approximate) median-finding; the randomized version of our algorithm uses uniform random sampling. For dense graphs, our O(n 2.5/m) bound improves the best previously published bound by a factor of n 1/4 and a recent bound obtained independently of our work by a factor of logn. Our main insight is that graph search is wasteful when the graph is dense and can be avoided by searching the topological order space instead. Our algorithms extend to the maintenance of strong components, in the same asymptotic time bounds.

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Ionic polymer-metal composites are soft artificial muscle-like bending actuators, which can work efficiently in wet environments such as water. Therefore, there is significant motivation for research on the development and design analysis of ionic polymer-metal composite based biomimetic underwater propulsion systems. Among aquatic animals, fishes are efficient swimmers with advantages such as high maneuverability, high cruising speed, noiseless propulsion, and efficient stabilization. Fish swimming mechanisms provide biomimetic inspiration for underwater propulsor design. Fish locomotion can be broadly classified into body and/or caudal fin propulsion and median and/or paired pectoral fin propulsion. In this article, the paired pectoral fin-based oscillatory propulsion using ionic polymer-metal composite for aquatic propulsor applications is studied. Beam theory and the concept of hydrodynamic function are used to describe the interaction between the beam and water. Furthermore, a quasi-steady blade element model that accounts for unsteady phenomena such as added mass effects, dynamic stall, and the cumulative Wagner effect is used to obtain hydrodynamic performance of the ionic polymer-metal composite propulsor. Dynamic characteristics of ionic polymer-metal composite fin are analyzed using numerical simulations. It is shown that the use of optimization methods can lead to significant improvement in performance of the ionic polymer-metal composite fin.

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We reconsider standard uniaxial fatigue test data obtained from handbooks. Many S-N curve fits to such data represent the median life and exclude load-dependent variance in life. Presently available approaches for incorporating probabilistic aspects explicitly within the S-N curves have some shortcomings, which we discuss. We propose a new linear S-N fit with a prespecified failure probability, load-dependent variance, and reasonable behavior at extreme loads. We fit our parameters using maximum likelihood, show the reasonableness of the fit using Q-Q plots, and obtain standard error estimates via Monte Carlo simulations. The proposed fitting method may be used for obtaining S-N curves from the same data as already available, with the same mathematical form, but in cases in which the failure probability is smaller, say, 10 % instead of 50 %, and in which the fitted line is not parallel to the 50 % (median) line.

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In this paper we propose a postprocessing technique for a spectrogram diffusion based harmonic/percussion decom- position algorithm. The proposed technique removes har- monic instrument leakages in the percussion enhanced out- puts of the baseline algorithm. The technique uses median filtering and an adaptive detection of percussive segments in subbands followed by piecewise signal reconstruction using envelope properties to ensure that percussion is enhanced while harmonic leakages are suppressed. A new binary mask is created for the percussion signal which upon applying on the original signal improves harmonic versus percussion separation. We compare our algorithm with two recent techniques and show that on a database of polyphonic Indian music, the postprocessing algorithm improves the harmonic versus percussion decomposition significantly.

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Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

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Glioblastoma is one of the common types of primary brain tumors with a median survival of 12-15 months. The receptor tyrosine kinase (RTK) pathway is known to be deregulated in 88% of the patients with glioblastoma. 45% of GBM patients show amplifications and activating mutations in EGFR gene leading to the upregulation of the pathway. In the present study, we demonstrate that a brain specific miRNA, miR-219-5p, repressed EGFR by directly binding to its 3'-UTR. The expression of miR-219-5p was downregulated in glioblastoma and the overexpression of miR-219-5p in glioma cell lines inhibited the proliferation, anchorage independent growth and migration. In addition, miR-219-5p inhibited MAPK and PI3K pathways in glioma cell lines in concordance with its ability to target EGFR. The inhibitory effect of miR-219-5p on MAPK and PI3K pathways and glioma cell migration could be rescued by the overexpression of wild type EGFR and vIII mutant of EGFR (both lacking 3'-UTR and thus being insensitive to miR-219-5p) suggesting that the inhibitory effects of miR-219-5p were indeed because of its ability to target EGFR. We also found significant negative correlation between miR-219-5p levels and total as well as phosphorylated forms of EGFR in glioblastoma patient samples. This indicated that the downregulation of miR-219-5p in glioblastoma patients contribute to the increased activity of the RTK pathway by the upregulation of EGFR. Thus, we have identified and characterized miR-219-5p as the RTK regulating novel tumor suppressor miRNA in glioblastoma.

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Dendrimeric nanoparticles are potential drug delivery devices which can enhance the solubility of hydrophobic drugs, thus increasing their bioavailability and sustained release action. A quantitative understanding of the dendrimer-drug interactions can give valuable insight into the solubility and release profile of hydrophobic drug molecules in various solvent conditions. Fully atomistic molecular dynamics (MD) simulations have been performed to study the interactions of G5 PPIEDA (G5 ethylenediamine cored poly(propylene imine)) dendrimer and two well known drugs (Famotidine and Indomethacin) at different pH conditions. The study suggested that at low pH the dendrimer-drug complexes are thermodynamically unstable as compared to neutral and high pH conditions. Calculated Potential of Mean Force (PMF) by umbrella sampling showed that the release of drugs from the dendrimer at low pH is spontaneous, median release at neutral pH and slow release at high pH. In addition, Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA) binding free energy calculations were also performed at each umbrella sampling window to identify the various energy contributions. To understand the effect of dendrimer chemistry and topology on the solubility and release profile of drugs, this study is extended to explore the solubility and release profile of phenylbutazone drug complexed with G3 poly(amidoamine) and G4 diaminobutane cored PPI dendrimers. The results indicate that the pH-induced conformational changes in dendrimer, ionization states, dendrimer type and pK(a) of the guest molecules influence the free energy barrier and stability of complexation, and thus regulate drug loading, solubility and release.

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Insulin like growth factor binding protein 4 (IGFBP4) regulates growth and development of tissues and organs by negatively regulating IGF signaling. Among most cancers, IGFBP4 has growth inhibitory role and reported as a down-regulated gene, except for renal cell carcinoma, wherein IGFBP4 promotes tumor progression. IGFBP4 expression has been shown to be higher in increasing grades of astrocytoma. However, the functional role of IGFBP4 in gliomas has not been explored. Surgical biopsies of 20 normal brain and 198 astrocytoma samples were analyzed for IGFBP4 expression by qRT-PCR. Highest expression of IGFBP4 mRNA was seen in GBM tumors compared to control brain tissues (median log2 of 2.035, p < 0.0001). Immunohistochemical analysis of 53 tissue samples revealed predominant nuclear staining of IGFBP4, seen maximally in GBMs when compared to DA and AA tumors (median LI = 29.12 +/- A 16.943, p < 0.001). Over expression of IGFBP4 in U343 glioma cells resulted in up-regulation of molecules involved in tumor growth, EMT and invasion such as pAkt, pErk, Vimentin, and N-cadherin and down-regulation of E-cadherin. Functionally, IGFBP4 over expression in these cells resulted in increased proliferation, migration and invasion as assessed by MTT, transwell migration, and Matrigel invasion assays. These findings were confirmed upon IGFBP4 knockdown in U251 glioma cells. Our data suggest a pro-tumorigenic role for IGFBP4 in glioma.

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Recently, several reports showed that about 80 % of mid-log phase Mycobacterium smegmatis, Mycobacterium marinum, and Mycobacterium bovis BCG cells divide symmetrically with 5-10 % deviation in the septum position from the median. However, the mode of cell division of the pathogenic mycobacterial species, Mycobacterium tuberculosis, remained unclear. Therefore, in the present study, using electron microscopy, fluorescence microscopy of septum- and nucleoid-stained live and fixed cells, and live cell time-lapse imaging, we show the occurrence of asymmetric cell division with unusually deviated septum/constriction in 20 % of the 15 % septating M. tuberculosis cells in the mid-log phase population. The remaining 80 % of the 15 % septating cells divided symmetrically but with 2-5 % deviation in the septum/constriction position, as reported for M. smegmatis, M. marinum, and M. bovis BCG cells. Both the long and the short portions of the asymmetrically dividing M. tuberculosis cells with unusually deviated septum contained nucleoids, thereby generating viable short and long cells from each asymmetric division. M. tuberculosis short cells were acid fast positive and, like the long cells, further readily underwent growth and division to generate micro-colony, thereby showing that they were neither mini cells, spores nor dormant forms of mycobacteria. The freshly diagnosed pulmonary tuberculosis patients' sputum samples, which are known for the prevalence of oxidative stress conditions, also contained short cells at the same proportion as that in the mid-log phase population. The probable physiological significance of the generation of the short cells through unusually deviated asymmetric cell division is discussed.

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The capacity of species to track shifting climates into the future will strongly influence outcomes for biodiversity under a rapidly changing climate. However, we know remarkably little about the dispersal abilities of most species and how these may be influenced by climate change. Here we show that climate change is projected to substantially reduce the seed dispersal services provided by frugivorous vertebrates in rainforests across the Australian Wet Tropics. Our model projections show reductions in both median and long-distance seed dispersal, which may markedly reduce the capacity of many rainforest plant species to track shifts in suitable habitat under climate change. However, our analyses suggest that active management to maintain the abundances of a small set of important frugivores under climate change could markedly reduce the projected loss of seed dispersal services and facilitate shifting distributions of rainforest plant species.

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Cancer is a complex disease which arises due to a series of genetic changes related to cell division and growth control. Cancer remains the second leading cause of death in humans next to heart diseases. As a testimony to our progress in understanding the biology of cancer and developments in cancer diagnosis and treatment methods, the overall median survival time of all cancers has increased six fold one year to six years during the last four decades. However, while the median survival time has increased dramatically for some cancers like breast and colon, there has been only little change for other cancers like pancreas and brain. Further, not all patients having a single type of tumour respond to the standard treatment. The differential response is due to genetic heterogeneity which exists not only between tumours, which is called intertumour heterogeneity, but also within individual tumours, which is called intratumoural heterogeneity. Thus it becomes essential to personalize the cancer treatment based on a specific genetic change in a given tumour. It is also possible to stratify cancer patients into low- and high-risk groups based on expression changes or alterations in a group of genes gene signatures and choose a more suitable mode of therapy. It is now possible that each tumour can be analysed using various high-throughput methods like gene expression profiling and next-generation sequencing to identify its unique fingerprint based on which a personalized or tailor-made therapy can be developed. Here, we review the important progress made in the recent years towards personalizing cancer treatment with the use of gene signatures.

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Following rising demands in positioning with GPS, low-cost receivers are becoming widely available; but their energy demands are still too high. For energy efficient GPS sensing in delay-tolerant applications, the possibility of offloading a few milliseconds of raw signal samples and leveraging the greater processing power of the cloud for obtaining a position fix is being actively investigated. In an attempt to reduce the energy cost of this data offloading operation, we propose Sparse-GPS(1): a new computing framework for GPS acquisition via sparse approximation. Within the framework, GPS signals can be efficiently compressed by random ensembles. The sparse acquisition information, pertaining to the visible satellites that are embedded within these limited measurements, can subsequently be recovered by our proposed representation dictionary. By extensive empirical evaluations, we demonstrate the acquisition quality and energy gains of Sparse-GPS. We show that it is twice as energy efficient than offloading uncompressed data, and has 5-10 times lower energy costs than standalone GPS; with a median positioning accuracy of 40 m.