6,476 research outputs found
Three-dimensional numerical study of flow characteristic and membrane fouling evolution in an enzymatic membrane reactor
In order to enhance the understanding of membrane fouling mechanism, the
hydrodynamics of granular flow in a stirred enzymatic membrane reactor was
numerically investigated in the present study. A three-dimensional Euler-Euler
model, coupled with k-e mixture turbulence model and drag function for
interphase momentum exchange, was applied to simulate the two-phase
(fluid-solid) turbulent flow. Numerical simulations of single- or two-phase
turbulent flow under various stirring speed were implemented. The numerical
results coincide very well with some published experimental data. Results for
the distributions of velocity, shear stress and turbulent kinetic energy were
provided. Our results show that the increase of stirring speed could not only
enlarge the circulation loops in the reactor, but it can also increase the
shear stress on the membrane surface and accelerate the mixing process of
granular materials. The time evolution of volumetric function of granular
materials on the membrane surface has qualitatively explained the evolution of
membrane fouling.Comment: 10 panges, 8 figure
On Shapley Value in Data Assemblage Under Independent Utility
In many applications, an organization may want to acquire data from many data
owners. Data marketplaces allow data owners to produce data assemblage needed
by data buyers through coalition. To encourage coalitions to produce data, it
is critical to allocate revenue to data owners in a fair manner according to
their contributions. Although in literature Shapley fairness and alternatives
have been well explored to facilitate revenue allocation in data assemblage,
computing exact Shapley value for many data owners and large assembled data
sets through coalition remains challenging due to the combinatoric nature of
Shapley value. In this paper, we explore the decomposability of utility in data
assemblage by formulating the independent utility assumption. We argue that
independent utility enjoys many applications. Moreover, we identify interesting
properties of independent utility and develop fast computation techniques for
exact Shapley value under independent utility. Our experimental results on a
series of benchmark data sets show that our new approach not only guarantees
the exactness of Shapley value, but also achieves faster computation by orders
of magnitudes.Comment: Accepted by VLDB 202
2-ChloroÂmethyl-2,3-dihydroÂthieno[3,4-b][1,4]dioxine
In the molÂecule of the title compound, C7H7ClO2S, the six-membered ring adopts a twisted conformation. In the crystal structure, weak interÂmolecular C—H⋯O hydrogen bonds link the molÂecules. There is also a weak C—H⋯π interÂaction
To aggregate or not to aggregate high-dimensional classifiers
<p>Abstract</p> <p>Background</p> <p>High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually much smaller in the order of ten or hundred. This poses statistical challenges and calls for appropriate solutions for the analysis of this kind of data.</p> <p>Results</p> <p>Principal component discriminant analysis (PCDA), an adaptation of classical linear discriminant analysis (LDA) for high-dimensional data, has been selected as an example of a base learner. The multiple versions of PCDA models from repeated double cross-validation were aggregated, and the final classification was performed by majority voting. The performance of this approach was evaluated by simulation, genomics, proteomics and metabolomics data sets.</p> <p>Conclusions</p> <p>The aggregating PCDA learner can improve the prediction performance, provide more stable result, and help to know the variability of the models. The disadvantage and limitations of aggregating were also discussed.</p
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