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.     

一种实用的多数据库量子信息检索协议

针对目前量子私有信息检索不能适用与云存储的多数据库问题,基于现在成熟的量子密钥分发方法,提出了一种适合在多数据库环境下,实用的量子私有信息检索协议。对于不同大小的数据库,协议可通过调节参数θ和k,在保证数据库安全及用户隐私的情况下,完成信息的检索。性能分析结果表明,协议的通信复杂度低,检索成功率高、易于实施。     

调节性B细胞在自身免疫性溶血性贫血患者外周血中的表达及临床意义

目的: 探讨自身免疫性溶血性贫血（AIHA）患者外周血中调节性B细胞（Bregs）的表达及其在该病发病中的意义。方法:选择16例自身免疫性溶血性贫血患者和14例健康志愿者为研究对象，用流式细胞术分析外周血CD19+IL-10+调节性B细胞及CD19+CD24hiCD27+调节性B细胞的表达；ELISA方法检测培养上清液中IL-10的水平。结果:自身免疫性溶血性贫血患者外周血中CD19+IL-10+调节性B细胞、CD19+CD24hiCD27+调节性B细胞的表达分别为（1.27±0.39）％、（9.85±2.18）％，健康志愿者组分别为（2.92±0.71）％、（26.47±4.31）％，两组比较差异有统计学意义（P<0.05）；自身免疫性溶血性贫血患者细胞培养上清中IL-10的水平低于健康志愿者组（P<0.05）。结论:自身免疫性溶血性贫血患者外周血中CD19+IL-10+调节性B细胞及CD19+CD24hiCD27+调节性B细胞比例降低，提示调节性B细胞可能参与自身免疫性溶血性贫血的发病过程。     

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.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.