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  • 11
    Publication Date: 2015-01-16
    Description: The influence of blade angle distribution along leading edge on cavitation performance of centrifugal pumps is analysed in the present paper. Three sets of blade angle distribution along leading edge for three blade inlet angles are chosen to design nine centrifugal pump impellers. The RNG k- ##IMG## [http://ej.iop.org/icons/Entities/epsilon.gif] {epsilon} turbulence model and the Zwart-Gerber-Belamri cavitation model are employed to simulate the cavitation flows in centrifugal pumps with different impellers and the same volute. The numerical results are compared with the experimental data, and the comparison proves that the numerical simulation can accurately predict the cavitation performance of centrifugal pumps. On the basis of the numerical simulations, the pump head variations with pump inlet pressure, and the flow details in centrifugal pump are revealed to demonstrate the influence of blade an...
    Print ISSN: 1757-8981
    Electronic ISSN: 1757-899X
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 12
    Publication Date: 2015-01-16
    Description: The influence of prewhirl regulation by inlet guide vanes (IGVs) on cavitation performance and flow characteristic in a centrifugal pump is investigated. At the impeller inlet, the streamlines are regulated by the IGVs, and the axial velocity distribution is also influenced by the IGVs. Due to the total pressure loss on the IGVs, the cavitation performance of the centrifugal pump degrades. The cavitation area in impeller with IGVs is larger than one without IGVs. The specify values of total pressure loss between the suction pipe inlet and impeller inlet for three cavitation conditions show that the IGVs will generate additional pressure loss, which is related to the IGVs angles and cavitation conditions.
    Print ISSN: 1757-8981
    Electronic ISSN: 1757-899X
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 13
    Publication Date: 2018-02-17
    Description: We introduce the Clouds Above the United States and Errors at the Surface (CAUSES) project with its aim of better understanding the physical processes leading to warm screen-temperature biases over the American Midwest in many numerical models. In this first of four companion papers, 11 different models, from 9 institutes, perform a series of 5-day hindcasts, each initialised from reanalyses. After describing the common experimental protocol and detailing each model configuration, a gridded temperature data set is derived from observations and used to show that all the models have a warm bias over parts of the Midwest. Additionally, a strong diurnal cycle in the screen-temperature bias is found in most models. In some models the bias is largest around midday, while in others it is largest during the night. At the Department of Energy Atmospheric Radiation Measurement Southern Great Plains (SGP) site, the model biases are shown to extend several kilometers into the atmosphere. Finally, to provide context for the companion papers, in which observations from the SGP site are used to evaluate the different processes contributing to errors there, it is shown that there are numerous locations across the Midwest where the diurnal cycle of the error is highly correlated with the diurnal cycle of the error at SGP. This suggests that conclusions drawn from detailed evaluation of models using instruments located at SGP will be representative of errors that are prevalent over a larger spatial scale.
    Print ISSN: 0148-0227
    Topics: Geosciences , Physics
    Published by Wiley on behalf of American Geophysical Union (AGU).
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  • 14
    Publication Date: 2018-02-28
    Description: Many weather forecast and climate models simulate warm surface air temperature (T 2m ) biases over mid-latitude continents during the summertime, especially over the Great Plains. We present here one of a series of papers from a multi-model intercomparison project (CAUSES: Cloud Above the United States and Errors at the Surface), which aims to evaluate the role of cloud, radiation, and precipitation biases in contributing to the T 2m bias using a short-term hindcast approach during the spring and summer of 2011. Observations are mainly from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) sites. The present study examines the contributions of surface energy budget errors. All participating models simulate too much net shortwave and longwave fluxes at the surface but with no consistent mean bias sign in turbulent fluxes over the Central U.S. and SGP. Nevertheless, biases in the net shortwave and downward longwave fluxes, as well as surface evaporative fraction (EF) are contributors to T 2m bias. Radiation biases are largely affected by cloud simulations, while EF bias is largely affected by soil moisture modulated by seasonal accumulated precipitation and evaporation. An approximate equation based upon the surface energy budget is derived to further quantify the magnitudes of radiation and EF contributions to T 2m bias. Our analysis ascribes that a large EF underestimate is the dominant source of error in all models with a large positive temperature bias, whereas an EF overestimate compensates for an excess of absorbed shortwave radiation in nearly all the models with the smallest temperature bias.
    Print ISSN: 0148-0227
    Topics: Geosciences , Physics
    Published by Wiley on behalf of American Geophysical Union (AGU).
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  • 15
    Publication Date: 2018-03-06
    Description: Many numerical weather prediction and climate models exhibit too warm lower tropospheres near the mid-latitude continents. The warm bias has been shown to coincide with important surface radiation biases that likely play a critical role in the inception or the growth of the warm bias. This paper presents an attribution study on the net radiation biases in 9 model simulations, performed in the framework of the CAUSES project (Clouds Above the United States and Errors at the Surface). Contributions from deficiencies in the surface properties, clouds, water vapor and aerosols are quantified, using an array of radiation measurement stations near the ARM SGP site. Furthermore, an in-depth analysis is shown to attribute the radiation errors to specific cloud regimes. The net surface shortwave radiation is overestimated in all models throughout most of the simulation period. Cloud errors are shown to contribute most to this overestimation, although non-negligible contributions from the surface albedo exist in most models. Missing deep cloud events and/or simulating deep clouds with too weak cloud-radiative effects dominate in the cloud-related radiation errors. Some models have compensating errors between excessive occurrence of deep cloud, but largely underestimating their radiative effect, while other models miss deep cloud events altogether. Surprisingly, even the latter models tend to produce too much and too frequent afternoon surface precipitation. This suggests that rather than issues with the triggering of deep convection, cloud-radiative deficiencies are related to too weak convective cloud detrainment and too large precipitation efficiencies.
    Print ISSN: 0148-0227
    Topics: Geosciences , Physics
    Published by Wiley on behalf of American Geophysical Union (AGU).
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  • 16
    Publication Date: 2015-04-03
    Description: Motivation: Ovarian cancer is the fifth leading cause of cancer deaths in women in the western world for 2013. In ovarian cancer, benign tumors turn malignant, but the point of transition is difficult to predict and diagnose. The 5-year survival rate of all types of ovarian cancer is 44%, but this can be improved to 92% if the cancer is found and treated before it spreads beyond the ovary. However, only 15% of all ovarian cancers are found at this early stage. Therefore, the ability to automatically identify and diagnose ovarian cancer precisely and efficiently as the tissue changes from benign to invasive is important for clinical treatment and for increasing the cure rate. This study proposes a new ovarian carcinoma classification model using two algorithms: a novel discretization of food sources for an artificial bee colony (DfABC), and a support vector machine (SVM). For the first time in the literature, oncogene detection using this method is also investigated. Results: A novel bio-inspired computing model and hybrid algorithms combining DfABC and SVM was applied to ovarian carcinoma and oncogene classification. This study used the human ovarian cDNA expression database to collect 41 patient samples and 9600 genes in each pathological stage. Feature selection methods were used to detect and extract 15 notable oncogenes. We then used the DfABC-SVM model to examine these 15 oncogenes, dividing them into eight different classifications according to their gene expressions of various pathological stages. The average accuracyof the eight classification experiments was 94.76%. This research also found some oncogenes that had not been discovered or indicated in previous scientific studies. The main contribution of this research is the proof that these newly discovered oncogenes are highly related to ovarian or other cancers. Availability and implementation: http://mht.mis.nchu.edu.tw/moodle/course/view.php?id=7 Contact: mychen@nutc.edu.tw
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
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  • 17
    Publication Date: 2017-05-19
    Description: With the rapid rise in pollution-associated nitrogen inputs to the western Pacific, it has been suggested that even the open ocean has been affected. In a coral core from Dongsha Atoll, a remote coral reef ecosystem, we observe a decline in the 15 N/ 14 N of coral skeleton–bound organic matter, which signals increased deposition of anthropogenic atmospheric N on the open ocean and its incorporation into plankton and, in turn, the atoll corals. The first clear change occurred just before 2000 CE, decades later than predicted by other work. The amplitude of change suggests that, by 2010, anthropogenic atmospheric N deposition represented 20 ± 5% of the annual N input to the surface ocean in this region, which appears to be at the lower end of other estimates.
    Keywords: Geochemistry, Geophysics
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Geosciences , Computer Science , Medicine , Natural Sciences in General , Physics
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  • 18
    Publication Date: 2017-04-13
    Description: Locating sources of diffusion and spreading from minimum data is a significant problem in network science with great applied values to the society. However, a general theoretical framework dealing with optimal source localization is lacking. Combining the controllability theory for complex networks and compressive sensing, we develop a framework with high efficiency and robustness for optimal source localization in arbitrary weighted networks with arbitrary distribution of sources. We offer a minimum output analysis to quantify the source locatability through a minimal number of messenger nodes that produce sufficient measurement for fully locating the sources. When the minimum messenger nodes are discerned, the problem of optimal source localization becomes one of sparse signal reconstruction, which can be solved using compressive sensing. Application of our framework to model and empirical networks demonstrates that sources in homogeneous and denser networks are more readily to be located. A surprising finding is that, for a connected undirected network with random link weights and weak noise, a single messenger node is sufficient for locating any number of sources. The framework deepens our understanding of the network source localization problem and offers efficient tools with broad applications.
    Keywords: complexity, graph theory
    Electronic ISSN: 2054-5703
    Topics: Natural Sciences in General
    Published by Royal Society
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  • 19
    Publication Date: 2013-09-06
    Description: The X-ray emission from Swift J1644+57 is not steadily decreasing; instead, it shows multiple pulses with declining amplitudes. We model the pulses as reverse shocks from collisions between the late ejected shells and the externally shocked material, which is decelerated while sweeping the ambient medium. The peak of each pulse is taken as the maximum emission of each reverse shock. With a proper set of parameters, the envelope of peaks in the light curve as well as the spectrum can be modelled well.
    Print ISSN: 0035-8711
    Electronic ISSN: 1365-2966
    Topics: Physics
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  • 20
    Publication Date: 2013-06-07
    Description: Protogenin prevents premature apoptosis of rostral cephalic neural crest cells by activating the α5β1-integrin Cell Death and Disease 4, e651 (June 2013). doi:10.1038/cddis.2013.177 Authors: Y-C Wang, H-C Juan, Y-H Wong, W-C Kuo, Y-L Lu, S-F Lin, C-J Lu & M-J Fann
    Keywords: Radilbranchial archesbone formationintegrin
    Electronic ISSN: 2041-4889
    Topics: Biology , Medicine
    Published by Springer Nature
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