Synthesis and tunable luminescent properties of Eu-doped Ca2NaSiO4F – Coexistence of the Eu2+ and Eu3+ centers

AbstractNovel phosphors Ca2NaSiO4F:Eu were synthesized successfully by the conventional solid-state method in CO atmosphere, and their spectroscopic properties in UV−vis region were investigated. The photoluminescence properties show that Eu3+ ions were partially reduced to Eu2+ in Ca2NaSiO4F. As a result of radiation and re-absorption energy transfer from Eu2+ to Eu3+, both Eu2+ bluish-green emission at around 520nm and Eu3+ red emission are observed in the emission spectra under the n-UV light excitation. Furthermore, the ratio between Eu2+ and Eu3+ emissions varies with increasing content of overall Eu. Because relative intensity of the red component from Eu3+ became systematically stronger, white light emission can be realized by combining the emission of Eu2+ and Eu3+ in a single host lattice under n-UV light excitation. These results indicate that the Ca2NaSiO4F:Eu phosphors have potential applications as a n-UV convertible phosphor for light-emitting diodes

DEFINE: friendship detection based on node enhancement

Network representation learning (NRL) is a matter of importance to a variety of tasks such as link prediction. Learning low-dimensional vector representations for node enhancement based on nodes attributes and network structures can improve link prediction performance. Node attributes are important factors in forming networks, like psychological factors and appearance features affecting friendship networks. However, little to no work has detected friendship using the NRL technique, which combines students’ psychological features and perceived traits based on facial appearance. In this paper, we propose a framework named DEFINE (No enhancement based r e dship D tection) to detect students’ friend relationships, which combines with students’ psychological factors and facial perception information. To detect friend relationships accurately, DEFINE uses the NRL technique, which considers network structure and the additional attributes information for nodes. DEFINE transforms them into low-dimensional vector spaces while preserving the inherent properties of the friendship network. Experimental results on real-world friendship network datasets illustrate that DEFINE outperforms other state-of-art methods. © 2020, Springer Nature Switzerland AG.E

Judging a Book by Its Cover: The Effect of Facial Perception on Centrality in Social Networks

Facial appearance matters in social networks. Individuals frequently make trait judgments from facial clues. Although these face-based impressions lack the evidence to determine validity, they are of vital importance, because they may relate to human network-based social behavior, such as seeking certain individuals for help, advice, dating, and cooperation, and thus they may relate to centrality in social networks. However, little to no work has investigated the apparent facial traits that influence network centrality, despite the large amount of research on attributions of the central position including personality and behavior. In this paper, we examine whether perceived traits based on facial appearance affect network centrality by exploring the initial stage of social network formation in a first-year college residential area. We took face photos of participants who are freshmen living in the same residential area, and we asked them to nominate community members linking to different networks. We then collected facial perception data by requiring other participants to rate facial images for three main attributions: dominance, trustworthiness, and attractiveness. Meanwhile, we proposed a framework to discover how facial appearance affects social networks. Our results revealed that perceived facial traits were correlated with the network centrality and that they were indicative to predict the centrality of people in different networks. Our findings provide psychological evidence regarding the interaction between faces and network centrality. Our findings also offer insights in to a combination of psychological and social network techniques, and they highlight the function of facial bias in cuing and signaling social traits. To the best of our knowledge, we are the first to explore the influence of facial perception on centrality in social networks.Comment: 11 pages, 8 figure

Xanthanolides in Xanthium L.: Structures, Synthesis and Bioactivity

Xanthanolides were particularly characteristic of the genus Xanthium, which exhibited broad biological effects and have drawn much attention in pharmacological application. The review surveyed the structures and bioactivities of the xanthanolides in the genus Xanthium, and summarized the synthesis tactics of xanthanolides. The results indicated that over 30 naturally occurring xanthanolides have been isolated from the genus Xanthium in monomeric, dimeric and trimeric forms. The bioassay-guided fractionation studies suggested that the effective fractions on antitumor activities were mostly from weak polar solvents, and xanthatin (1) was the most effective and well-studied xanthanolide. The varieties of structures and structure-activity relationships of the xanthanolides had provided the promising skeleton for the further study. The review aimed at providing guidance for the efficient preparation and the potential prospects of the xanthanolides in the medicinal industry

Promising Fungicides from Allelochemicals: Synthesis of Umbelliferone Derivatives and Their Structure–Activity Relationships

Umbelliferone was discovered to be an important allelochemical in our previous study, but the contribution of its activity and structure has not yet been revealed. In this study, a series of analogues were synthesized to determine the skeleton of umbelliferone and examine its fungicidal activity. Furthermore, targeted modifications were conducted with three plant parasitic fungi to examine the lead compounds. Among those tested, compounds 2f and 10 were found to show excellent antifungal activity with an inhibitory rate over 80% at 100 ug/mL. The study proves that umbelliferone can be a promising skeleton for fungicides discovery. In addition, the primary structure⁻activity relationship provides a good guidance for the discovery of novel fungicides based on natural products in the future

Chinese Named Entity Recognition Based on Knowledge Based Question Answering System

The KBQA (Knowledge-Based Question Answering) system is an essential part of the smart customer service system. KBQA is a type of QA (Question Answering) system based on KB (Knowledge Base). It aims to automatically answer natural language questions by retrieving structured data stored in the knowledge base. Generally, when a KBQA system receives the user’s query, it first needs to recognize topic entities of the query, such as name, location, organization, etc. This process is the NER (Named Entity Recognition). In this paper, we use the Bidirectional Long Short-Term Memory-Conditional Random Field (Bi-LSTM-CRF) model and introduce the SoftLexicon method for a Chinese NER task. At the same time, according to the analysis of the characteristics of application scenario, we propose a fuzzy matching module based on the combination of multiple methods. This module can efficiently modify the error recognition results, which can further improve the performance of entity recognition. We combine the NER model and the fuzzy matching module into an NER system. To explore the availability of the system in some specific fields, such as a power grid field, we utilize the power grid-related original data collected by the Hebei Electric Power Company to improve our system according to the characteristics of data in the power grid field. We innovatively make the dataset and high-frequency word lexicon in the power grid field, which makes our proposed NER system perform better in recognizing entities in the field of power grid. We used the cross-validation method for validation. The experimental results show that the F1-score of the improved NER model on the power grid dataset reaches 92.43%. After processing the recognition results by using the fuzzy matching module, about 99% of the entities in the test set can be correctly recognized. It proves that the proposed NER system can achieve excellent performance in the application scenario of a power grid. The results of this work will also fill the gap in the research of intelligent customer-service-related technologies in the power grid field in China

Chinese Named Entity Recognition Based on Knowledge Based Question Answering System

The KBQA (Knowledge-Based Question Answering) system is an essential part of the smart customer service system. KBQA is a type of QA (Question Answering) system based on KB (Knowledge Base). It aims to automatically answer natural language questions by retrieving structured data stored in the knowledge base. Generally, when a KBQA system receives the user’s query, it first needs to recognize topic entities of the query, such as name, location, organization, etc. This process is the NER (Named Entity Recognition). In this paper, we use the Bidirectional Long Short-Term Memory-Conditional Random Field (Bi-LSTM-CRF) model and introduce the SoftLexicon method for a Chinese NER task. At the same time, according to the analysis of the characteristics of application scenario, we propose a fuzzy matching module based on the combination of multiple methods. This module can efficiently modify the error recognition results, which can further improve the performance of entity recognition. We combine the NER model and the fuzzy matching module into an NER system. To explore the availability of the system in some specific fields, such as a power grid field, we utilize the power grid-related original data collected by the Hebei Electric Power Company to improve our system according to the characteristics of data in the power grid field. We innovatively make the dataset and high-frequency word lexicon in the power grid field, which makes our proposed NER system perform better in recognizing entities in the field of power grid. We used the cross-validation method for validation. The experimental results show that the F1-score of the improved NER model on the power grid dataset reaches 92.43%. After processing the recognition results by using the fuzzy matching module, about 99% of the entities in the test set can be correctly recognized. It proves that the proposed NER system can achieve excellent performance in the application scenario of a power grid. The results of this work will also fill the gap in the research of intelligent customer-service-related technologies in the power grid field in China

Laboratory evaluation on water-based and flexible epoxy/SiO2 nanocomposites to enhance anti-sliding effectiveness of pavement

The anti-slip (AS) layer of the cement concrete pavement (CCP) can probability decrease traffic accidents and extend the service life of the road. Epoxy resin has excellent adhesion and mechanical strength, making it possible in this field. Herein, a flexible waterborne epoxy resin (WER) without a small molecule emulsifier was synthesized by bisphenol A epoxy resin, poly (propylene glycol) diglycidyl ether (PDE), diethylenetriamine (DETA). The mechanism of the group reaction was characterized by fourier transform infrared (FTIR), and dynamic scanning calorimetry (DSC) determined the heat of curing of WER. Then, the physical properties of WER were enhanced by the silane coupling agent modified nano-silica (SCA-NS) and the composite’s water absorption rate and mechanical propriety were evaluated. Finally, the pavement performance of the AS layer was prepared and tested as well as compared with the commercial waterborne epoxy resin (CWER) and emulsified asphalt (EA). The result shows EA has low durability and adhesion strength than epoxy resin. The small molecule emulsifier and low-flexible resistance of CWER decrease water stability and anti-sliding durability of the AS layer. Due to applied nanomaterial reinforced and without small molecule emulsifiers, the WER base AS layer shows extremely high adhesion strength, water stability, and skid-resistance durability at addition 3 wt% of SCA-NS, which have a great potential for CCP