Survey of Research on Personalized News Recommendation Approaches

Personalized news recommendation is an important technology to help users obtain the news information they are interested in and alleviate information overload. In recent years, with the development of information technology and society, personalized news recommendation has been increasingly widely studied, and has achieved remarkable success in improving the news reading experience of users. This paper aims to systematically summarize personalized news recommendation methods based on deep learning. Firstly, it introduces personalized news recommendation methods and analyzes their characteristics and influencing factors. Then, the overall framework of personalized news recommendation is given, and the personalized news recommendation methods based on deep learning are analyzed and summarized. On this basis, it focuses on personalized news recommendation methods based on graph structure learning, including user-news interaction graph, knowledge graph and social relationship graph. Finally, it analyzes the challenges of the current personalized news recommendation, discusses how to solve the problems of data sparsity, model interpretability, diversity of recommendation results and news privacy protection in personalized news recommendation system, and puts forward more specific and operable research ideas in the future research direction

Fuzzy Spatiotemporal Data Modeling and Operations in RDF

With the emergence of a large number of fuzzy spatiotemporal data on the Web, how to represent and operate fuzzy spatiotemporal data has become an important research issue. Meanwhile, the Resource Description Framework (RDF) is a standard data and knowledge description language of the Semantic Web and has been applied in many application areas, such as geographic information systems and meteorological systems. In this paper, a model for representing fuzzy spatiotemporal data is proposed and a set of algebraic operations for the model are investigated. First, a representation method of fuzzy spatiotemporal RDF data and a fuzzy spatiotemporal RDF graph model are proposed. In addition, a formal fuzzy spatiotemporal RDF algebra is proposed and a set of algebraic operations for manipulating fuzzy spatiotemporal RDF data are developed. The algebraic operations include: set operation, selection operation, projection operation, join operation, and construction operation. Finally, the existing SPARQL query language is extended and an example that shows how to apply the proposed algebraic operations to capture the queries expressed by the extended SPARQL query language is given

Fuzzy Spatiotemporal Data Modeling and Operations in RDF

With the emergence of a large number of fuzzy spatiotemporal data on the Web, how to represent and operate fuzzy spatiotemporal data has become an important research issue. Meanwhile, the Resource Description Framework (RDF) is a standard data and knowledge description language of the Semantic Web and has been applied in many application areas, such as geographic information systems and meteorological systems. In this paper, a model for representing fuzzy spatiotemporal data is proposed and a set of algebraic operations for the model are investigated. First, a representation method of fuzzy spatiotemporal RDF data and a fuzzy spatiotemporal RDF graph model are proposed. In addition, a formal fuzzy spatiotemporal RDF algebra is proposed and a set of algebraic operations for manipulating fuzzy spatiotemporal RDF data are developed. The algebraic operations include: set operation, selection operation, projection operation, join operation, and construction operation. Finally, the existing SPARQL query language is extended and an example that shows how to apply the proposed algebraic operations to capture the queries expressed by the extended SPARQL query language is given

Spatiotemporal RDF Data Query Based on Subgraph Matching

Resource Description Framework (RDF), as a standard metadata description framework proposed by the World Wide Web Consortium (W3C), is suitable for modeling and querying Web data. With the growing importance of RDF data in Web data management, there is an increasing need for modeling and querying RDF data. Previous approaches mainly focus on querying RDF. However, a large amount of RDF data have spatial and temporal features. Therefore, it is important to study spatiotemporal RDF data query approaches. In this paper, firstly, we formally define spatiotemporal RDF data, and construct a spatiotemporal RDF model st-RDF that is used to represent and manipulate spatiotemporal RDF data. Secondly, we present a spatiotemporal RDF query algorithm stQuery based on subgraph matching. This algorithm can quickly determine whether the query result is empty for queries whose temporal or spatial range exceeds a specific range by adopting a preliminary query filtering mechanism in the query process. Thirdly, we propose a sorting strategy that calculates the matching order of query nodes to speed up the subgraph matching. Finally, we conduct experiments in terms of effect and query efficiency. The experimental results show the performance advantages of our approach

Conductive Polymer Porous Film with Tunable Wettability and Adhesion

A conductive polymer porous film with tunable wettability and adhesion was fabricated by the chloroform solution of poly(3-hexylthiophene) (P3HT) and [6,6]-phenyl-C61-butyricacid-methyl-ester (PCBM) via the freeze drying method. The porous film could be obtained from the solution of 0.8 wt%, whose pore diameters ranged from 50 nm to 500 nm. The hydrophobic porous surface with a water contact angle (CA) of 144.7° could be transferred into a hydrophilic surface with CA of 25° by applying a voltage. The water adhesive force on the porous film increased with the increase of the external voltage. The electro-controllable wettability and adhesion of the porous film have potential application in manipulating liquid collection and transportation

Bioinspired Design of Honeycomb Structure Interfaces with Controllable Water Adhesion

Inspired by biological attachment systems, we fabricated the honeycomb structural films with different diameters by breath figure (BF) method, which were similar to the patterned octopus suckers. The experimental results showed, besides different van der Waals forces between the polystyrene (PS) surfaces and water, another important factor; that is, different negative pressures produced by different volumes of sealed air could be a crucial factor for the different adhesions. So the water adhesive forces of the as-prepared films can be effectively controlled from relative high to relative low adhesion by varying the pore diameters, which effectively adjusted the negative pressures produced by the pores. This unique adhesive phenomenon of honeycomb structure will be very useful for manipulating water droplet behaviors, as well as controlling liquid collection and transportation. These findings are interesting and helpful for us to further understand the biological attachment systems and to optimize the design of artificial analogues

High Performance Soluble Polyimides from Ladder-Type Fluorinated Dianhydride with Polymorphism

A novel rigid semi-alicyclic dianhydride 9,10-difluoro-9,10-bis(trifluoromethyl)-9,10-dihydroanthracene-2,3,6,7-tetracarboxylic acid dianhydride (8FDA) was reported, and its single crystal X-ray diffraction result revealed the existence of the polymorphic structure in this compound. The detail geometric configuration transition during the synthesized process was investigated, exhibiting a transition of from trans- to cis- when the hydroxyl groups were substituted by fluoride with diethylaminosulfur trifluoride (DAST). Compared with the dianhydride 4,4′-(Hexaflouroisopropylidene) diphthalic anhydride (6FDA) and 1S,2R,4S,5R-cyclohexanetetracarboxylic dianhydride (HPMDA), the resulting polyimide (PI) films based on 8FDA exhibited an obviously higher glass transition temperature (Tg, 401 °C) and a much lower coefficient of thermal expansion (CTE, 14 ppm K−1). This indicates that 8FDA is an ideal building block in high-performance soluble PIs with low CTE

ZXDC enhances cervical cancer metastasis through IGF2BP3-mediated activation of RhoA/ROCK signaling

Summary: Metastasis in cervical cancer (CC) has a significant negative impact on patient survival, highlighting the urgent need for investigation in this area. In this study, we identified significant overexpression of zinc finger, X-linked, duplicated family member C (ZXDC) in CC tissue with metastasis, which correlates with poor outcomes for CC patients. We observed that overexpression of ZXDC promotes, while silencing of ZXDC inhibits the metastasis of CC cells both in vitro and in vivo. Additionally, our research demonstrated that ZXDC activated RhoA/ROCK signaling pathway, leading to enhanced cytoskeleton remodeling in CC cells. Besides, we found that IGF2BP3 plays an essential role in the activation of ZXDC on the RhoA/ROCK signaling pathway by stabilizing RhoA mRNA. These findings reveal a mechanism whereby ZXDC promotes the cervical cancer metastasis by targeting IGF2BP3/RhoA/ROCK pathway