Ensembled CTR Prediction via Knowledge Distillation

Recently, deep learning-based models have been widely studied for click-through rate (CTR) prediction and lead to improved prediction accuracy in many industrial applications. However, current research focuses primarily on building complex network architectures to better capture sophisticated feature interactions and dynamic user behaviors. The increased model complexity may slow down online inference and hinder its adoption in real-time applications. Instead, our work targets at a new model training strategy based on knowledge distillation (KD). KD is a teacher-student learning framework to transfer knowledge learned from a teacher model to a student model. The KD strategy not only allows us to simplify the student model as a vanilla DNN model but also achieves significant accuracy improvements over the state-of-the-art teacher models. The benefits thus motivate us to further explore the use of a powerful ensemble of teachers for more accurate student model training. We also propose some novel techniques to facilitate ensembled CTR prediction, including teacher gating and early stopping by distillation loss. We conduct comprehensive experiments against 12 existing models and across three industrial datasets. Both offline and online A/B testing results show the effectiveness of our KD-based training strategy.Comment: Published in CIKM'202

Glycyrrhiza uralensis polysaccharides ameliorates cecal ligation and puncture-induced sepsis by inhibiting the cGAS-STING signaling pathway

Ethnopharmacological relevance:G. uralensis Fisch. (Glycyrrhiza uralensis) is an ancient and widely used traditional Chinese medicine with good efficacy in clearing heat and detoxifying action. Studies suggest that Glycyrrhiza Uralensis Polysaccharides (GUP), one of the major components of G. uralensis, has anti-inflammatory, anti-cancer and hepatoprotective effects., but its exact molecular mechanism has not been explored in depth.Aim of the study: Objectives of our research are about exploring the anti-inflammatory role of GUP and the mechanisms of its action.Materials and methods: ELISA kits, Western blotting, immunofluorescence, quantitative real-time PCR, immunoprecipitation and DMXAA-mediated STING activation mice models were performed to investigate the role of GUP on the cGAS-STING pathway. To determine the anti-inflammatory effects of GUP, cecal ligation and puncture (CLP) sepsis models were employed.Results: GUP could effectively inhibit the activation of the cGAS-STING signaling pathway accompany by a decrease the expression of type I interferon-related genes and inflammatory factors in BMDMs, THP-1, and human PBMCs. Mechanistically, GUP does not affect the oligomerization of STING, but affects the interaction of STING with TBK1 and TBK1 with IRF3. Significantly, GUP had great therapeutic effects on DMXAA-induced agonist experiments in vivo as well as CLP sepsis in mice.Conclusion: Our studies suggest that GUP is an effective inhibitor of the cGAS-STING pathway, which may be a potential medicine for the treatment of inflammatory diseases mediated by the cGAS-STING pathway

Cigarette Smoking in Male Patients with Chronic Schizophrenia in a Chinese Population: Prevalence and Relationship to Clinical Phenotypes

The high prevalence of smoking in schizophrenia of European background may be related to smoking's reducing clinical symptoms and medication side effects. Because smoking prevalence and its associations with clinical phenotypes are less well characterized in Chinese than European patients with schizophrenia, we assessed these smoking behaviors using clinician-administered questionnaires and the Fagerstrom Test for Nicotine Dependence (FTND) in 776 Chinese male schizophrenia and 560 control subjects. Patients also were rated on the Positive and Negative Symptom Scale (PANSS), the Simpson and Angus Extrapyramidal Symptom Rating Scale (SAES), and the Abnormal Involuntary Movement Scale (AIMS). We found that the schizophrenia patients had a higher lifetime incidence of smoking (79% vs 63%), were more likely to be heavy smokers (61% vs 31%), and had lower smoking cessation rates (4% vs 9%) (all p<0.0001) than controls. Among the schizophrenia patients smoking prevalence increased with age, with the largest difference from controls in the age cohort of 55–75 years: 75% vs 46% (p<0.0001). Among the schizophrenia smokers 73% started to smoke before the onset of their illness by an average of 7.6 years. The patients with schizophrenia who were current smokers scored significantly lower on the PANSS negative symptom subscore (p<0.005), and on the SAES symptom scale (p<0.04; Bonferroni corrected p>0.05) than the non-smoking patients. These results suggest that Chinese males with schizophrenia smoke more frequently than the general population. Further, smokers with schizophrenia may display fewer negative symptoms and possibly less parkinsonism than non-smokers with schizophrenia

Fisher ship present communication situation and the countermeasures

This paper in recent years, commercial fishing vessel collision cases, the author analyzes the reasons of commercial fishing vessel collision, puts forward the coastal fishing area present situation and countermeasures of safe navigation

The feature of double typhoon in South China Sea and ship avoiding measures

Discussion in this article is phenomenon existent features about the double of the South China Sea tropical cyclone, including a variety of meteorological elements and the waves. Meanwhile, considering the influence of various factors and allowing for unforeseen circumstances, we forecast the relative position and movement about the ship and the typhoon. Also, we come up with some efficient scheme and measures related to avoiding double typhoons combined with avoiding measures taken in one typhoon

A Clustering Framework to Reveal the Structural Effect Mechanisms of Natural and Social Factors on PM_2.5 Concentrations in China

Understanding the mechanisms of various factors that affect PM2.5 can assist in the development of scientific measures to improve air quality. Nevertheless, existing research has concentrated on exploring local effect mechanisms, while structural effect mechanisms at regional or national scales have scarcely been analysed. Consequently, this study presents an analytical framework for elucidating the structural effect mechanisms of associated factors on PM2.5. Geographically and temporally weighted regression was used to explore the local effect mechanisms. This was followed by spatial clustering analysis to reveal these mechanisms by detecting their aggregation patterns. In the analysis, datasets for annual mean PM2.5 and socio-economic factors in China from 1999 to 2016 were employed. Urban population, gross industrial output, and sulphur dioxide emissions were identified as factors affecting changes in PM2.5 concentrations. These three factors had both negative and positive effects, while the gross industrial output had the largest coefficient variation degree. Three geographically related factors exhibited different impacts on PM2.5 concentrations in most of mainland China. These factors were the urban population roughly west of the Heihe-Tengchong line, gross industrial output primarily in southwestern China, and sulphur dioxide emissions primarily in southern China