200 research outputs found

    Micro-Electro-Mechanical-Systems (MEMS) and Fluid Flows

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    The micromachining technology that emerged in the late 1980s can provide micron-sized sensors and actuators. These micro transducers are able to be integrated with signal conditioning and processing circuitry to form micro-electro-mechanical-systems (MEMS) that can perform real-time distributed control. This capability opens up a new territory for flow control research. On the other hand, surface effects dominate the fluid flowing through these miniature mechanical devices because of the large surface-to-volume ratio in micron-scale configurations. We need to reexamine the surface forces in the momentum equation. Owing to their smallness, gas flows experience large Knudsen numbers, and therefore boundary conditions need to be modified. Besides being an enabling technology, MEMS also provide many challenges for fundamental flow-science research

    Earliest Triassic microbialites in the South China Block and other areas; controls on their growth and distribution

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    Earliest Triassic microbialites (ETMs) and inorganic carbonate crystal fans formed after the end-Permian mass extinction (ca. 251.4 Ma) within the basal Triassic Hindeodus parvus conodont zone. ETMs are distinguished from rarer, and more regional, subsequent Triassic microbialites. Large differences in ETMs between northern and southern areas of the South China block suggest geographic provinces, and ETMs are most abundant throughout the equatorial Tethys Ocean with further geographic variation. ETMs occur in shallow-marine shelves in a superanoxic stratified ocean and form the only widespread Phanerozoic microbialites with structures similar to those of the Cambro-Ordovician, and briefly after the latest Ordovician, Late Silurian and Late Devonian extinctions. ETMs disappeared long before the mid-Triassic biotic recovery, but it is not clear why, if they are interpreted as disaster taxa. In general, ETM occurrence suggests that microbially mediated calcification occurred where upwelled carbonate-rich anoxic waters mixed with warm aerated surface waters, forming regional dysoxia, so that extreme carbonate supersaturation and dysoxic conditions were both required for their growth. Long-term oceanic and atmospheric changes may have contributed to a trigger for ETM formation. In equatorial western Pangea, the earliest microbialites are late Early Triassic, but it is possible that ETMs could exist in western Pangea, if well-preserved earliest Triassic facies are discovered in future work

    Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

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    Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

    Thermalisation of a two-dimensional photonic gas in a 'white-wall' photon box

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    Bose-Einstein condensation, the macroscopic accumulation of bosonic particles in the energetic ground state below a critical temperature, has been demonstrated in several physical systems. The perhaps best known example of a bosonic gas, blackbody radiation, however exhibits no Bose-Einstein condensation at low temperatures. Instead of collectively occupying the lowest energy mode, the photons disappear in the cavity walls when the temperature is lowered - corresponding to a vanishing chemical potential. Here we report on evidence for a thermalised two-dimensional photon gas with freely adjustable chemical potential. Our experiment is based on a dye filled optical microresonator, acting as a 'white-wall' box for photons. Thermalisation is achieved in a photon number-conserving way by photon scattering off the dye-molecules, and the cavity mirrors both provide an effective photon mass and a confining potential - key prerequisites for the Bose-Einstein condensation of photons. As a striking example for the unusual system properties, we demonstrate a yet unobserved light concentration effect into the centre of the confining potential, an effect with prospects for increasing the efficiency of diffuse solar light collection.Comment: 15 pages, 3 figure

    Metabolic profiling of human brain metastases using in vivo proton MR spectroscopy at 3T

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    <p>Abstract</p> <p>Background</p> <p>Metastases to the central nervous system from different primary cancers are an oncologic challenge as the overall prognosis for these patients is generally poor. The incidence of brain metastases varies with type of primary cancer and is probably increasing due to improved therapies of extracranial metastases prolonging patient's overall survival and thereby time for brain metastases to develop. In addition, the greater access to improved neuroimaging techniques can provide earlier diagnosis. The aim of this study was to investigate the feasibility of using proton magnetic resonance spectroscopy (MRS) and multivariate analyses to characterize brain metastases originating from different primary cancers, to assess changes in spectra during radiation treatment and to correlate the spectra to clinical outcome after treatment.</p> <p>Methods</p> <p>Patients (n = 26) with brain metastases were examined using single voxel MRS at a 3T clinical MR system. Five patients were excluded due to poor spectral quality. The spectra were obtained before start (n = 21 patients), immediately after (n = 6 patients) and two months after end of treatment (n = 4 patients). Principal component analysis (PCA) and partial least square regression analysis (PLS) were applied in order to identify clustering of spectra due to origin of metastases and to relate clinical outcome (survival) of the patients to spectral data from the first MR examination.</p> <p>Results</p> <p>The PCA results indicated that brain metastases from primary lung and breast cancer were separated into two clusters, while the metastases from malignant melanomas showed no uniformity. The PLS analysis showed a significant correlation between MR spectral data and survival five months after MRS before start of treatment.</p> <p>Conclusion</p> <p>MRS determined metabolic profiles analysed by PCA and PLS might give valuable clinical information when planning and evaluating the treatment of brain metastases, and also when deciding to terminate further therapies.</p

    Evaluation of extra-virgin olive oils shelf life using an electronic tongue-chemometric approach

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    Physicochemical quality parameters, olfactory and gustatoryretronasal positive sensations of extra-virgin olive oils vary during storage leading to a decrease in the overall quality. Olive oil quality decline may prevent the compliance of olive oil quality with labeling and significantly reduce shelf life, resulting in important economic losses and negatively condition the consumer confidence. The feasibility of applying an electronic tongue to assess olive oils usual commercial light storage conditions and storage time was evaluated and compared with the discrimination potential of physicochemical or positive olfactory/gustatory sensorial parameters. Linear discriminant models, based on subsets of 58 electronic tongue sensor signals, selected by the meta-heuristic simulated annealing variable selection algorithm, allowed the correct classification of olive oils according to the light exposition conditions and/or storage time (sensitivities and specificities for leave-one-out cross-validation: 8296Β %). The predictive performance of the E-tongue approach was further evaluated using an external independent dataset selected using the KennardStone algorithm and, in general, better classification rates (sensitivities and specificities for external dataset: 67100Β %) were obtained compared to those achieved using physicochemical or sensorial data. So, the work carried out is a proof-of-principle that the proposed electrochemical device could be a practical and versatile tool for, in a single and fast electrochemical assay, successfully discriminate olive oils with different storage times and/or exposed to different light conditions.The authors acknowledge the financial support from the strategic funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145-FEDER-006984β€”Associate Laboratory LSRELCM funded by FEDER funds through COMPETE2020β€”Programa Operacional Competitividade e Internacionalização (POCI)β€”and by national funds through FCTβ€”Fundação para a CiΓͺncia e a Tecnologia and under the strategic funding of UID/BIO/04469/2013 unit. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).info:eu-repo/semantics/publishedVersio

    Genome-wide characterization of simple sequence repeats in cucumber (Cucumis sativus L.)

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    <p>Abstract</p> <p>Background</p> <p>Cucumber, <it>Cucumis sativus </it>L. is an important vegetable crop worldwide. Until very recently, cucumber genetic and genomic resources, especially molecular markers, have been very limited, impeding progress of cucumber breeding efforts. Microsatellites are short tandemly repeated DNA sequences, which are frequently favored as genetic markers due to their high level of polymorphism and codominant inheritance. Data from previously characterized genomes has shown that these repeats vary in frequency, motif sequence, and genomic location across taxa. During the last year, the genomes of two cucumber genotypes were sequenced including the Chinese fresh market type inbred line '9930' and the North American pickling type inbred line 'Gy14'. These sequences provide a powerful tool for developing markers in a large scale. In this study, we surveyed and characterized the distribution and frequency of perfect microsatellites in 203 Mbp assembled Gy14 DNA sequences, representing 55% of its nuclear genome, and in cucumber EST sequences. Similar analyses were performed in genomic and EST data from seven other plant species, and the results were compared with those of cucumber.</p> <p>Results</p> <p>A total of 112,073 perfect repeats were detected in the Gy14 cucumber genome sequence, accounting for 0.9% of the assembled Gy14 genome, with an overall density of 551.9 SSRs/Mbp. While tetranucleotides were the most frequent microsatellites in genomic DNA sequence, dinucleotide repeats, which had more repeat units than any other SSR type, had the highest cumulative sequence length. Coding regions (ESTs) of the cucumber genome had fewer microsatellites compared to its genomic sequence, with trinucleotides predominating in EST sequences. AAG was the most frequent repeat in cucumber ESTs. Overall, AT-rich motifs prevailed in both genomic and EST data. Compared to the other species examined, cucumber genomic sequence had the highest density of SSRs (although comparable to the density of poplar, grapevine and rice), and was richest in AT dinucleotides. Using an electronic PCR strategy, we investigated the polymorphism between 9930 and Gy14 at 1,006 SSR loci, and found unexpectedly high degree of polymorphism (48.3%) between the two genotypes. The level of polymorphism seems to be positively associated with the number of repeat units in the microsatellite. The <it>in silico </it>PCR results were validated empirically in 660 of the 1,006 SSR loci. In addition, primer sequences for more than 83,000 newly-discovered cucumber microsatellites, and their exact positions in the Gy14 genome assembly were made publicly available.</p> <p>Conclusions</p> <p>The cucumber genome is rich in microsatellites; AT and AAG are the most abundant repeat motifs in genomic and EST sequences of cucumber, respectively. Considering all the species investigated, some commonalities were noted, especially within the monocot and dicot groups, although the distribution of motifs and the frequency of certain repeats were characteristic of the species examined. The large number of SSR markers developed from this study should be a significant contribution to the cucurbit research community.</p

    A retrospective comparison of venetoclax alone or in combination with an anti-CD20 monoclonal antibody in R/R CLL

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    Venetoclax (VEN) is approved for relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL) as monotherapy (VENmono) or in combination with rituximab. Whether VEN plus anti-CD20 (VENcombo) is superior to VENmono is unknown. We conducted a multicenter, retrospective cohort analysis comparing 321 CLL patients treated with VENmono vs VENcombo across the United States and the United Kingdom. We examined demographics, baseline characteristics, dosing, adverse events, response rates, and outcomes. The primary endpoints were progression-free survival (PFS) and overall survival (OS), estimated by Kaplan-Meier method, in patients treated with VENmono vs VENcombo. Univariate and bivariate analyses were performed with COX regression. Three hundred twenty-one CLL patients were included (3 median prior treatments, 78% prior ibrutinib). The overall response rates (ORRs) were similar (VENmono, 81% ORR, 34% complete remission [CR] vs VENcombo, 84% ORR, 32% CR). With a median follow-up of 13.4 months, no differences in PFS and OS were observed between the groups. In unadjusted analyses, the hazard ratios (HRs) for PFS and OS for VENmono vs VENcombo were HR 1.0 (95% confidence interval [CI], 0.6-1.8; P = .7) and HR 1.2 (95% CI, 0.6-2.3; P = .5), respectively. When adjusting for differences between the cohorts, the addition of an anti-CD20 antibody in combination with VEN did not impact PFS (HR, 1.0; 95% CI, 0.5-2.0; P = .9) or OS (HR, 1.1; 95% CI, 0.4-2.6; P = .8). We demonstrate comparable efficacy between VENmono and VENcombo in a heavily pretreated, high-risk, retrospective cohort, in terms of both response data and survival outcomes. Prospective studies are needed to validate these findings

    Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

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    A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1Ξ², and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-ΞΊB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals
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