Literatura polska w Chinach i wymiana kulturalna między Polską a Chinami. Zapiski tłumacza

The article is an introduction into the presence of Polish literature in China from the perspective of one of its most active researchers and translators. The author describes his fascination with Bolesław Prus’s work that resulted in the Chinese translation of Lalka (The Doll) and his work on two-volume Historia literatury polskiej (The history of Polish literature) aimed at Chinese readers.The article is an introduction into the presence of Polish literature in China from the perspective of one of its most active researchers and translators. The author describes his fascination with Bolesław Prus’s work that resulted in the Chinese translation of Lalka (The Doll) and his work on two-volume Historia literatury polskiej (The history of Polish literature) aimed at Chinese readers

Mixture of Virtual-Kernel Experts for Multi-Objective User Profile Modeling

In many industrial applications like online advertising and recommendation systems, diverse and accurate user profiles can greatly help improve personalization. For building user profiles, deep learning is widely used to mine expressive tags to describe users' preferences from their historical actions. For example, tags mined from users' click-action history can represent the categories of ads that users are interested in, and they are likely to continue being clicked in the future. Traditional solutions usually introduce multiple independent Two-Tower models to mine tags from different actions, e.g., click, conversion. However, the models cannot learn complementarily and support effective training for data-sparse actions. Besides, limited by the lack of information fusion between the two towers, the model learning is insufficient to represent users' preferences on various topics well. This paper introduces a novel multi-task model called Mixture of Virtual-Kernel Experts (MVKE) to learn multiple topic-related user preferences based on different actions unitedly. In MVKE, we propose a concept of Virtual-Kernel Expert, which focuses on modeling one particular facet of the user's preference, and all of them learn coordinately. Besides, the gate-based structure used in MVKE builds an information fusion bridge between two towers, improving the model's capability much and maintaining high efficiency. We apply the model in Tencent Advertising System, where both online and offline evaluations show that our method has a significant improvement compared with the existing ones and brings about an obvious lift to actual advertising revenue.Comment: 10 pages, under revie

CoLight: Learning Network-level Cooperation for Traffic Signal Control

Cooperation among the traffic signals enables vehicles to move through intersections more quickly. Conventional transportation approaches implement cooperation by pre-calculating the offsets between two intersections. Such pre-calculated offsets are not suitable for dynamic traffic environments. To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication. Specifically, for a target intersection in a network, CoLight can not only incorporate the temporal and spatial influences of neighboring intersections to the target intersection, but also build up index-free modeling of neighboring intersections. To the best of our knowledge, we are the first to use graph attentional networks in the setting of reinforcement learning for traffic signal control and to conduct experiments on the large-scale road network with hundreds of traffic signals. In experiments, we demonstrate that by learning the communication, the proposed model can achieve superior performance against the state-of-the-art methods.Comment: 10 pages. Proceedings of the 28th ACM International on Conference on Information and Knowledge Management. ACM, 201

Effect of a combination of infrared irradiation and magnesium sulfate wet compress on infection and healing of episiotomy incision in puerperae

Purpose: To investigate the effect of a combination of infrared irradiation and magnesium sulfate wet compress on infection and healing of episiotomy incision in puerperae during spontaneous delivery. Methods: A total of 120 puerperae who underwent lateral episiotomy in Jinan Maternity and Child Hospital Affiliated to Shandong First Medical University from January 2019 to January 2020 were used as study subjects. They were randomly assigned to group A (n = 60) and group B (n = 60). Group B received external application of anerdian, while group A was treated with infrared irradiation and magnesium sulfate wet compress, in addition to receiving the treatment given to group B. The two groups were compared with respect to perineal edema, levels of inflammatory factors, wound pain grading, degree of incision healing, incision healing time, and incidence of infection. Results: Group A patients had significantly lighter perineal edema and more pronounced pain relief than group B patients (p < 0.05). The number of puerperae with grade A healing and grade C healing in group A was significantly higher than that in group B (p < 0.05). Incision healing time and incidence of infection were lower in group A than in group B (p < 0.05). Conclusion: The combination of infrared irradiation and magnesium sulfate wet compress effectively mitigates perineal edema in puerperae, reduces pain, enhances the healing of incision, and lowers maternal infection. Thus, this combination strategy may have some merit in clinical practice