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

Nitrogen fertilization modifies organic transformations and coatings on soil biogeochemical interfaces through microbial polysaccharides synthesis

The soil-water interfaces (SWI) in soil pores are hotspots for organic matter (OM) transformation. However, due to the heterogeneous and opaque nature of soil microenvironment, direct and continuous tracing of interfacial reactions, such as OM transformations and formation of organo-mineral associations, are rare. To investigate these processes, a new soil microarray technology (SoilChips) was developed and used. Homogeneous 800-μm-diameter SoilChips were constructed by depositing a dispersed Oxisol A horizon suspension on a patterned glass. Dissolved organic matter from the original soil was added on the SoilChips to mimic SWI processes. The effects of ammonium fertilization (90 mg N kg−1 soil) on chemical composition of SWIs were evaluated via X-ray photoelectron spectroscopy. Over 21 days, ammonium addition increased OM coatings at SWIs and modified the OM chemical structure with more alcoholic- and carboxylic-C compared to the unfertilized control. Molecular modeling of OM composition at SWIs showed that N fertilization mainly facilitated the microbial production of glucans. We demonstrated that N availability modifies the specific OM molecular processing and its immobilization on SWIs, thereby providing a direct insight into biogeochemical transformation of OM at micro-scale. © 2019, The Author(s)

Significant delay and decreased chance of treatment for acute ischemic stroke patients on remote outer islets of China compared with the main island: the PUTUO Study

Introduction: Data from acute ischemic stroke patients throughout 2021 from one district of an archipelago city of China were collected and analyzed retrospectively to determine the management difference due to time lags from onset of symptoms to the arrival at the stroke center (FMCT) of two regions: main island (MI) and outer islets (OIs). Methods: All patients information from 1 January to 31 December 2021 was retrieved through the electronic medical records system of the only stroke center in MI. After screening and exclusion, each patient's medical record was reviewed by two neurologists separately. Before OI patients were allocated to a group, their residential addresses at onset of the stroke were confirmed by telephone. Comparisons were analyzed between the two regions for gender, age, pre-stroke risk factors and peri-admission management parameters. Results: A total of 326 patients met the inclusion criteria: 300 from the MI group and 26 for the OI group. Intergroup comparisons for gender, age and most of the risk factors showed no significant difference. FMCT were shown to be significantly distinct (p<0.001). Hospitalization expenses also showed significant difference. The odds ratio of the definite treatment IV thrombolysis was 0.131 (OI group to MI group range: 0.017-0.987, p=0.021). Conclusion: The diagnosis and treatment of acute ischemic stroke patients from OIs was significantly postponed compared to those from MI. Therefore, new effective and efficient solutions are urgently needed

Gene Therapy Restores Auditory and Vestibular Function in a Mouse Model of Usher Syndrome Type 1c

Because there are currently no biological treatments for deafness, we sought to advance gene therapy approaches to treat genetic deafness. We reasoned that gene delivery systems that target auditory and vestibular sensory cells with high efficiency would be required to restore complex auditory and balance function. We focused on Usher Syndrome, a devastating genetic disorder that causes blindness, balance disorders and profound deafness, and used a knock-in mouse model, Ush1c c.216G>A, which carries a cryptic splice site mutation found in French-Acadian patients with Usher Syndrome type IC (USH1C). Following delivery of wild-type Ush1c into the inner ears of neonatal Ush1c c.216G>A mice, we find recovery of gene and protein expression, restoration of sensory cell function, rescue of complex auditory function and recovery of hearing and balance behavior to near wild-type levels. The data represent unprecedented recovery of inner ear function and suggest that biological therapies to treat deafness may be suitable for translation to humans with genetic inner ear disorders

Reliability modeling for competing failure systems with instant-shift hard failure threshold

There are many researches about the modeling for system under multiple dependent competing failure processes (MDCFP) in recent years. Typically speaking, those failure processes are composed by degradation process (soft failure) and random shock process (hard failure). The threshold of hard failure is a fixed value in previous papers which is not compliance with the engineering practices. Threshold means the ability to resist external random shocks which is also shifting with time due to the usage of system. Thus, this paper establishes a model for MDCFP with instant-shift hard threshold. The hard failure threshold changes with time instantaneously and it is also influenced by external shocks. Afterwards, system reliability model is built. The effectiveness of presented model is demonstrated by the reliability analysis of the micro-engine of Sandia National Laboratories. In addition, sensitive analysis is performed for specific parameters.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Exponential Synchronization of a Class of N-Coupled Complex Partial Differential Systems with Time-Varying Delay

This paper is concerned with the exponential synchronization for a class of N-coupled complex partial differential systems (PDSs) with time-varying delay. The synchronization error dynamic of the PDSs is defined in the q-dimensional spatial domain. To achieve synchronization, we added a linear feedback controller. A sufficient condition is derived to ensure the exponential synchronization of the proposed networks using the Lyapunov–Krasovskii stability approach and matrix inequality technology. The proposed system has broad applications. Two example applications are presented in the final section of this paper to verify the proposed theoretical result

International Conference on Artificial Intelligence and Cloud Computing (ICAICC) 2020 18-20 December 2020, Suzhou, China

This paper intent to improve consumer communication by text mining analysis with users’ reviews. The news aggregator we focus on is: Toutiao, known as “today's headlines” in Chinese. It is the top news aggregator application run by Bytedance company in China. It utilizes AI algorithms to provide numerous news feed for its users. As new technologies are shaping the business strategy studies as well as online communication analysis, it requires innovative and effective analyses of unconventional data, such as the 12,290 online reviews on Toutiao we collected from Apple’s App Store. Through the LDA topic modelling and sentiment analysis, our research has identified three major negative complains the consumers have regarding Toutiao application, namely: too many unsolicited advertisements, contents (vulgar content, time consuming video, privacy and copyrights infringement issue) and incompatibility with the latest Apple digital devices</p