Selection
of solvents and process aids (i.e., ionic liquids (ILs))
is considered to be one of the key steps during solvent extraction
for heavy hydrocarbon recovery from unconventional oil ores. In this
study, the COSMOtherm software was applied to screen highly efficient
solvents and ionic liquid systems based on oil fraction solubility
and surface free energy calculations. It is found that the dispersion
force parameter (δd) of solvents plays the dominant
role in dissolving oil fractions compared with the roles of the polar
force parameter (δp) and hydrogen bonding force parameter
(δh). The simulation results also show that the surface
free energy of oil fractions (SARA fractions) at the organic solvent-IL
interface is significantly lower than that found at the IL-SARA fraction
interface, which is favorable for unconventional oil dissolution in
solvents. In addition, further interactive energy calculation shows
that the interaction between IL and the silica surface is stronger
than that between oil fraction and the silica surface. These results
suggest that the presence of IL between the organic solvent and oil
fraction is beneficial for the transfer of the oil fraction from the
solid surface and bulk oil phase to the bulk organic solvent. Additionally,
unconventional oil recovery has been found to be highly influenced
by the mutual solubility between the solvent and IL, which increased
the entrainments of oil components in the IL phase. Calculation of
surface free energy and mutual solubility suggests that increasing
the chain length of IL molecules is detrimental for bitumen extraction
due to the higher mutual solubility of solvents and entrainments of
bitumen in ILs. The above simulation results are confirmed by the
bottle extraction tests and instrumental detection in which the oil
sands ores are extracted by organic solvents with or without ILs.
These findings suggest that the COSMOtherm simulation is a potential
way for future solvent and IL screening as well as a way to reveal
mechanism during unconventional oil exploitation, which would save
time and cost.
As the explosive growth of web videos on video-shared sites like YouTube, the discovery of video topics has become a hot research area. In order to utilize all kinds of characteristics in web video such as visual features (SIFT, shape or color) and contextual cues (such as title or tags) effectively, this paper proposes an approach to represent the explicit and implicit correlations hidden in web videos by a starstructured K-partite graph model, and then a co-clustering process is conducted to discover video topics. The experimental results demonstrate the feasibility and effectiveness of the proposed approach.
Abstract. Transformation of higher vocational education in China requires a good opinion atmosphere. Being effected by traditional occupation concept and media environment, higher vocational education in China faces many difficulties in terms of opinion atmosphere. The public considers that higher vocational education is the same as college education. Starting from the unique role of opinion atmosphere in higher vocational education, we need to instruct the public to form correct higher vocational education value and to understand and support the development of higher vocational education, help them to exploit ideas, and seek for the vocational education atmosphere and education view. Finally, we can achieve the objective of formulating a good opinion atmosphere and facilitating the development of higher vocational education.
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