Catalytic Hydrocracking of a Bitumen‐Derived Asphaltene over NiMo/γ‐Al2O3 at Various Temperatures

Hydrocracking of a bitumen‐derived asphaltene over NiMo/γ‐Al₂O₃ was investigated in a microbatch reactor at varying temperatures. The molar kinetics of asphaltene cracking reaction was examined by fitting the experimental data. Below a defined temperature, the molar reaction showed the first‐order kinetic feature while at higher temperatures secondary reactions such as coke formation became significant, causing deviation of the reaction behavior from the proposed first‐order kinetic model. Selectivity analysis proved that dominant products varied from gases to liquids to gases with increasing temperature, shifting the dominant reaction from C–S bonds cleavage to C–C bonds cleavage.     

Structures and properties of chicken myofibrillar protein gel induced by microwave heating

Structures and properties of myofibrillar protein gel prepared at different power (300–800 W) were evaluated. Amino acid analysis demonstrated that changes in microwave power did not alter primary structure of gel. However, an increase in microwave power could change higher structures of gel. As microwave power increased, α-helix content decreased and β-sheet content increased. Increased microwave power probably facilitated protein to unfold and expose the internal groups, causing surface hydrophobicity and the formation of disulphide bonds were enhanced, which indicated changes in tertiary and quaternary structures of protein. At 500 W, gel had the best ultrastructure where surface morphology, springiness and water holding capacity reached the optimum. Our findings suggested that microwave at an appropriate power (500 W) could change higher structures of myofibrillar protein gel to achieve desired processing and quality protein gel characteristics.     

Preparation of ZrC/SiC porous self-supporting monoliths via sol-gel process using polyethylene glycol as phase separation inducer

We present a straightforward method via sol-gel process using polyethylene glycol (PEG) as phase separation inducer to prepare zirconium carbide/silicon carbide (ZrC/SiC) porous monoliths. Organic/inorganic hybrid gels are prepared using zirconium oxychloride, furfuryl alcohol, and tetraethyl orthosilicate as major starting materials. In the presence of PEG, crack-free hybrid monoliths are obtained by drying the wet gels under ambient pressure, whereas in the absence of PEG, the wet gels break into pieces as expected. PEG plays a key role in maintaining the macroscopic shape of the monoliths. After ceramization at 1300–1500?°C, ZrC/SiC porous monoliths are obtained. SEM and mercury intrusion porosimetry data show that PEG also has strong influence on the microstructures of the monoliths. The compressive strengths of the ceramic monoliths are in the range of 0.3 to 0.7?MPa. And their compressive behavior starts to differ due to the changes in their microstructures, especially the pore structure.     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.