3,712 research outputs found

    Weka: A machine learning workbench for data mining

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    The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data preprocessing tools. The basic way of interacting with these methods is by invoking them from the command line. However, convenient interactive graphical user interfaces are provided for data exploration, for setting up large-scale experiments on distributed computing platforms, and for designing configurations for streamed data processing. These interfaces constitute an advanced environment for experimental data mining. The system is written in Java and distributed under the terms of the GNU General Public License

    Expression of Liver Phenotypes in Cultured Mouse Hepatoma Cells

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    Mouse hepatoma cells were established in vitro as a permanently growing line designated Hepa. The mass population and a subclone were characterized for their karyotype and their retention of liver-specific properties. An examination of 17 hepatic traits revealed that the cell lines secreted several serum proteins. The activities of a number of liver-specific enzymes, however, appeared to be absent in these cells. The identification of differentiated properties of cultured hepatoma cells permits the use of these lines in a variety of studies such as cell hybridization, biochemical analysis of tissue-specific gene products, and the modulation of expression of genes governing differentiated phenotypes. This report presents the analysis of a broad spectrum of characteristics and thereby describes one of the most fully defined hepatoma cell lines of murine origin in the literatur

    Acute and Sub-Acute Toxicity of the Polycyclic Aromatic Hydrocarbon 1-Methylnaphthalene to the Shallow-Water Coral Porites divaricata: Application of a Novel Exposure Protocol

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    Previous research evaluating hydrocarbon toxicity to corals and coral reefs has generally focused on community-level effects, and results often are not comparable between studies because of variability in hydrocarbon exposure characterization and evaluation of coral health and mortality during exposure. Toxicity of the polycyclic aromatic hydrocarbon 1-methylnaphthalene to the coral Porites divaricata was assessed in a constant exposure toxicity test utilizing a novel toxicity testing protocol uniquely applicable to shallow-water corals, which considered multiple assessment metrics and evaluated the potential for post-exposure mortality and/or recovery. Acute and subacute effects (gross morphological changes, photosynthetic efficiency, mortality, and histologic cellular changes) were evaluated during pre-exposure (4 wk), exposure (48 h), and post-exposure recovery (4 wk) periods. Coral condition scores were used to determine a 48-h median effective concentration of 7442 μg/L. Significant physical and histological changes resulted from exposure to 640 μg/L and 5427 μg/L 1-methylnaphthalene, with a 1-d to 3-d delay in photosynthetic efficiency effects (ΔF/Fm). Pigmented granular amoebocyte area was found to be a potentially useful sublethal endpoint for this species. Coral mortality was used to estimate a 48-h median lethal concentration of 12 123 μg/L

    Evaluating different methods of MR-based motion correction in simultaneous PET/MR using a head phantom moved by a robotic system

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    BACKGROUND: Due to comparatively long measurement times in simultaneous positron emission tomography and magnetic resonance (PET/MR) imaging, patient movement during the measurement can be challenging. This leads to artifacts which have a negative impact on the visual assessment and quantitative validity of the image data and, in the worst case, can lead to misinterpretations. Simultaneous PET/MR systems allow the MR-based registration of movements and enable correction of the PET data. To assess the effectiveness of motion correction methods, it is necessary to carry out measurements on phantoms that are moved in a reproducible way. This study explores the possibility of using such a phantom-based setup to evaluate motion correction strategies in PET/MR of the human head. METHOD: An MR-compatible robotic system was used to generate rigid movements of a head-like phantom. Different tools, either from the manufacturer or open-source software, were used to estimate and correct for motion based on the PET data itself (SIRF with SPM and NiftyReg) and MR data acquired simultaneously (e.g. MCLFIRT, BrainCompass). Different motion estimates were compared using data acquired during robot-induced motion. The effectiveness of motion correction of PET data was evaluated by determining the segmented volume of an activity-filled flask inside the phantom. In addition, the segmented volume was used to determine the centre-of-mass and the change in maximum activity concentration. RESULTS: The results showed a volume increase between 2.7 and 36.3% could be induced by the experimental setup depending on the motion pattern. Both, BrainCompass and MCFLIRT, produced corrected PET images, by reducing the volume increase to 0.7–4.7% (BrainCompass) and to -2.8–0.4% (MCFLIRT). The same was observed for example for the centre-of-mass, where the results show that MCFLIRT (0.2–0.6 mm after motion correction) had a smaller deviation from the reference position than BrainCompass (0.5–1.8 mm) for all displacements. CONCLUSIONS: The experimental setup is suitable for the reproducible generation of movement patterns. Using open-source software for motion correction is a viable alternative to the vendor-provided motion-correction software. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40658-022-00442-6

    The Weiss conjecture and weak norms

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    In this note we show that for analytic semigroups the so-called Weiss condition of uniform boundedness of the operators Re(\lambda)^\einhalb C(\lambda+A)^{-1}, \qquad Re(\lambda)>0 on the complex right half plane and weak Lebesgue L2,L^{2,\infty}--admissibility are equivalent. Moreover, we show that the weak Lebesgue norm is best possible in the sense that it is the endpoint for the 'Weiss conjecture' within the scale of Lorentz spaces Lp,qL^{p,q}

    Mapping the EQ-5D index by UPDRS and PDQ-8 in patients with Parkinson’s disease

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    Background: Clinical studies employ the Unified Parkinson’s Disease Rating Scale (UPDRS) to measure the severity of Parkinson’s disease. Evaluations often fail to consider the health-related quality of life (HrQoL) or apply disease-specific instruments. Health-economic studies normally use estimates of utilities to calculate quality-adjusted life years. We aimed to develop an estimation algorithm for EuroQol- 5 dimensions (EQ-5D)-based utilities from the clinical UPDRS or disease-specific HrQoL data in the absence of original utilities estimates. Methods: Linear and fractional polynomial regression analyses were performed with data from a study of Parkinson’s disease patients (n=138) to predict the EQ-5D index values from UPDRS and Parkinson’s disease questionnaire eight dimensions (PDQ-8) data. German and European weights were used to calculate the EQ-5D index. The models were compared by R2, the root mean square error (RMS), the Bayesian information criterion, and Pregibon’s link test. Three independent data sets validated the models. Results: The regression analyses resulted in a single best prediction model (R2: 0.713 and 0.684, RMS: 0.139 and 13.78 for indices with German and European weights, respectively) consisting of UPDRS subscores II, III, IVa-c as predictors. When the PDQ-8 items were utilised as independent variables, the model resulted in an R2 of 0.60 and 0.67. The independent data confirmed the prediction models. Conclusion: The best results were obtained from a model consisting of UPDRS subscores II, III, IVa-c. Although a good model fit was observed, primary EQ-5D data are always preferable. Further validation of the prediction algorithm within large, independent studies is necessary prior to its generalised use

    Comparison of NTF Experimental Data with CFD Predictions from the Third AIAA CFD Drag Prediction Workshop

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    Recently acquired experimental data for the DLR-F6 wing-body transonic transport con figuration from the National Transonic Facility (NTF) are compared with the database of computational fluid dynamics (CFD) predictions generated for the Third AIAA CFD Drag Prediction Workshop (DPW-III). The NTF data were collected after the DPW-III, which was conducted with blind test cases. These data include both absolute drag levels and increments associated with this wing-body geometry. The baseline DLR-F6 wing-body geometry is also augmented with a side-of-body fairing which eliminates the flow separation in this juncture region. A comparison between computed and experimentally observed sizes of the side-of-body flow-separation bubble is included. The CFD results for the drag polars and separation bubble sizes are computed on grids which represent current engineering best practices for drag predictions. In addition to these data, a more rigorous attempt to predict absolute drag at the design point is provided. Here, a series of three grid densities are utilized to establish an asymptotic trend of computed drag with respect to grid convergence. This trend is then extrapolated to estimate a grid-converged absolute drag level

    Summary of the Third AIAA CFD Drag Prediction Workshop

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    The workshop focused on the prediction of both absolute and differential drag levels for wing-body and wing-al;one configurations of that are representative of transonic transport aircraft. The baseline DLR-F6 wing-body geometry, previously utilized in DPW-II, is also augmented with a side-body fairing to help reduce the complexity of the flow physics in the wing-body juncture region. In addition, two new wing-alone geometries have been developed for the DPW-II. Numerical calculations are performed using industry-relevant test cases that include lift-specific and fixed-alpha flight conditions, as well as full drag polars. Drag, lift, and pitching moment predictions from previous Reynolds-Averaged Navier-Stokes computational fluid Dynamics Methods are presented, focused on fully-turbulent flows. Solutions are performed on structured, unstructured, and hybrid grid systems. The structured grid sets include point-matched multi-block meshes and over-set grid systems. The unstructured and hybrid grid sets are comprised of tetrahedral, pyramid, and prismatic elements. Effort was made to provide a high-quality and parametrically consistent family of grids for each grid type about each configuration under study. The wing-body families are comprised of a coarse, medium, and fine grid, while the wing-alone families also include an extra-fine mesh. These mesh sequences are utilized to help determine how the provided flow solutions fair with respect to asymptotic grid convergence, and are used to estimate an absolute drag of each configuration

    Socio-economic vision graph generation and handover in distributed smart camera networks

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    In this article we present an approach to object tracking handover in a network of smart cameras, based on self-interested autonomous agents, which exchange responsibility for tracking objects in a market mechanism, in order to maximise their own utility. A novel ant-colony inspired mechanism is used to learn the vision graph, that is, the camera neighbourhood relations, during runtime, which may then be used to optimise communication between cameras. The key benefits of our completely decentralised approach are on the one hand generating the vision graph online, enabling efficient deployment in unknown scenarios and camera network topologies, and on the other hand relying only on local information, increasing the robustness of the system. Since our market-based approach does not rely on a priori topology information, the need for any multicamera calibration can be avoided. We have evaluated our approach both in a simulation study and in network of real distributed smart cameras

    Interleukin 7 from Maternal Milk Crosses the Intestinal Barrier and Modulates T- Cell Development in Offspring

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    Background Breastfeeding protects against illnesses and death in hazardous environments, an effect partly mediated by improved immune function. One hypothesis suggests that factors within milk supplement the inadequate immune response of the offspring, but this has not been able to account for a series of observations showing that factors within maternally derived milk may supplement the development of the immune system through a direct effect on the primary lymphoid organs. In a previous human study we reported evidence suggesting a link between IL-7 in breast milk and the thymic output of infants. Here we report evidence in mice of direct action of maternally-derived IL-7 on T cell development in the offspring. Methods and Findings  We have used recombinant IL-7 labelled with a fluorescent dye to trace the movement in live mice of IL-7 from the stomach across the gut and into the lymphoid tissues. To validate the functional ability of maternally derived IL- 7 we cross fostered IL-7 knock-out mice onto normal wild type mothers. Subsets of thymocytes and populations of peripheral T cells were significantly higher than those found in knock-out mice receiving milk from IL-7 knock-out mothers. Conclusions/Significance Our study provides direct evidence that interleukin 7, a factor which is critical in the development of T lymphocytes, when maternally derived can transfer across the intestine of the offspring, increase T cell production in the thymus and support the survival of T cells in the peripheral secondary lymphoid tissue
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