This study looked to improve reproducibility in the procedure to determine the yield stress of water-in-oil (W/O) emulsions prepared with waxy crude oil. The influence of various experimental variables was studied: measurement geometry, emulsion cooling rate, shear stress during the cooling step, gap reduction (parallel plates), final gap (parallel plates), and conditioning steps. The measured yield stress varied significantly depending upon the measuring geometry used (from 100 to 500 Pa). The geometries cross-hatched parallel plate (D = 60 mm) and grooved coaxial cylinder measured the highest yield stress, and it was observed that the shear stress during cooling was the most important measurement variable in the emulsion yield stress.

No abstract

Despite their importance, hierarchical clustering has been little explored for semi-supervised algorithms. In this paper, we address the problem of semi-supervised hierarchical clustering by using an active learning solution with cluster-level constraints. This active learning approach is based on a new concept of merge confidence in agglomerative clustering. When there is low confidence in a cluster merge the user is queried and provides a cluster-level constraint. The proposed method is compared with an unsupervised algorithm (average-link) and two state-of-the-art semi-supervised algorithms (pairwise constraints and Constrained Complete-Link). Results show that our algorithm tends to be better than the two semi-supervised algorithms and can achieve a significant improvement when compared to the unsupervised algorithm. Our approach is particularly useful when the number of clusters is high which is the case in many real problems.

Biodiesel may be produced by vegetable oil transesterification, followed by purification steps of product sedimentation and water washing. The occurrence of stable emulsions during the purification steps in the biodiesel production process from castor oil is a severe problem that precludes its use as an industrial raw material. The stability behavior of emulsions formed by castor oil biodiesel−water with 10, 20, and 30% (w/w) water content was studied using laser light profiling. Emulsion stability showed a decrease for emulsions with 10−20% water, but emulsions with 30% water showed a very high stability. Demulsification of water in biodiesel emulsions using microwave irradiation was also investigated as a function of the water content, separation temperature, and stirring speed. Analysis of the separation efficiency results showed that all of the variables were statistically significant but that water content was the most important factor. A comparison of microwave irradiation to gravitational sedimentation showed that a higher separation efficiency is obtained for emulsions submitted to the microwave irradiation.