基于综合用电煤耗的电力高质量发展评价指标研究及应用

煤电平均供电煤耗作为评价能源系统效率的指标已在行业内广泛应用。但该项指标无法很好地反映一个国家、地区的用电结构与用电能耗水平。为此，参照行业内普遍采用的火电厂发电煤耗和供电煤耗指标，定义“综合用电煤耗”，即用户每用1 kW?h电“消耗”的标准煤量（单位:g/(kW?h)）。在此基础上，提出“综合发电煤耗”与“综合供电煤耗”的概念，形成完整的指标评价体系。对近年典型省份指标值的研究表明，该指标体系能够很好地反映供给侧国家、省区或企业的发电结构与电能生产能耗水平。这一指标体系能够为正确理解和计算用电、输电与电能替代项目的化石能源消耗量及其排放量提供依据。     

Supramolecular Glyco‐nanoparticles Toward Immunological Applications

Glyco‐mimicking nanoparticles (glyco‐NPs) with Förster resonance energy transfer (FRET) donor and acceptor groups formed via dynamic covalent bond of benzoboroxole and sugar from two complementary polymers are prepared. The glyco‐NPs are proved to be quite stable under physiological conditions but sensitive to pH. So the glyco‐NPs can be internalized by dendritic cells with integrity and nontoxicity and then dissociate within the acidic organelles. This particle dissociation is directly observed and visualized in vitro, for the first time via the FRET measurements and fluorescent microscopy. This feature makes controlled release of drug or protein by glyco‐NPs possible, i.e., when model antigen Ovalbumin is loaded in the glyco‐NPs, the released Ovalbumin in dendritic cells stimulates T cells more efficiently than the free Ovalbumin itself as a result of the enhanced antigen processing and presentation. Thus, the results enlighten a bright future of the glyco‐NPs in immunotherapy.     

Effect of an abrupt change in pulling rate on microstructures of directionally solidified Al2O3-Er3Al5O12 eutectic and off-eutectic composite ceramics

Directionally solidified microstructures of Al₂O₃-Er₃Al₅O₁₂ eutectic and off-eutectic in situ composite ceramics were explored under abrupt-change pulling rate conditions. Corresponding temperature distributions and interface locations were studied. In eutectic composition, fluctuation of eutectic spacing occurred when the pulling rate increased abruptly. A gradually increase or abrupt increase in eutectic spacing was observed when the pulling rate decreased abruptly. In hypoeutectic and hypereutectic compositions, formation of the primary phases were suppressed when the pulling rate increased abruptly from 10?µm/s to 100?µm/s, while primary phases precipitated when the pulling rate decreased abruptly from 100?µm/s to 10?µm/s. The interface altitude decreased after the pulling rate increased abruptly, but increased after the pulling rate decreased abruptly. The liquid composition restriction (around the eutectic composition) at the eutectic interface plays an important role in the suppression of the primary dendrite and coupled eutectic oxides can be obtained in off-eutectic compositions even under higher solidification rate conditions.     

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.     

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.