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This paper aims to report the influence of hexamethylenetetramine (HMTA) on phosphate coatings formed on AZ31 magnesium alloys.

These phosphate coatings were obtained by immersing magnesium alloys in phosphate baths with HMTA. The morphology and composition of the phosphate coatings were investigated via scanning electron microscopy, energy dispersive spectrometry and X-ray diffraction.

The phosphate coatings were mainly composed of CaHPO₄·2H₂O. The HMTA concentration in the phosphate bath influenced the crystallization and corrosion resistance of the phosphate coating.

The polarization curve shows that the anti-corrosion qualities of the phosphate coating were optimal when the HMTA concentration was 1.0 g/L in the phosphate bath. Electrochemical impedance spectroscopy (EIS) shows that the electrochemical impedances increased gradually when the HMTA concentration varied from 1.0 to 3.0 g/L.

With the rapid development of materials informatics and the Semantic Web, the semantic-driven solution has emerged to improve traditional query technology, which is hard to discover implicit knowledge from materials data. However, it is a nontrivial thing for materials scientists to construct a semantic query, and the query results are usually presented in RDF/XML format which is not convenient for users to understand. This paper aims to propose an approach to construct semantic query and visualize the query results for metallic materials domain.

The authors design a query builder to generate SPARQL query statements automatically based on domain ontology and query conditions inputted by users. Moreover, a semantic visualization model is defined based on the materials science tetrahedron to support the visualization of query results in an intuitive, dynamic and interactive way.

Based on the Semantic Web technology, the authors design an automatic semantic query builder to help domain experts write the normative semantic query statements quickly and simply, as well as a prototype (named MatViz) is developed to visually show query results, which could help experts discover implicit knowledge from materials data. Moreover, the experiments demonstrate that the proposed system in this paper can rapidly and effectively return visualized query results over the metallic materials data set.

This paper mainly discusses an approach to support semantic query and visualization of metallic materials data. The implementation of MatViz will be a meaningful work for the research of metal materials data integration.

Social media have become an increasingly important source for people to learn about politics and public affairs. The purpose of this study is to investigate the role of social media news sharing as a reasoning process of the O-S-R-O-R model and the moderation role of social media news performance on the association between news consumption and attitudinal changes.

A national survey was conducted in the US. The researcher recruited participants in the Qualtrics national panel by following the census adult demographic breakdown.

This study finds that social media news consumption on the US-China trade conflict is likely to lead Americans to change attitudes toward Chinese, and this relationship is mediated by social media news sharing. In addition, the indirect relationship via news sharing is found particularly strong among individuals who perceive social media news fair and balanced.

This study extends the literature by examining social media news engagement on the ongoing trade conflict between the US and China. It reveals that the impact of social media news consumption on people's attitudinal and behavioral changes depends on people's perceived news quality on these platforms. Theoretical contribution to the O-S-R-O-R model and practical implications to social media news are discussed in terms of the role that social media platforms play in attitude change.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2020-0178

The purpose of this paper was to obtain the lubrication characteristics of heavy hydrostatic bearing in heavy equipment manufacturing industry through theoretical analysis and numerical simulation.

This paper discusses the influence of oil film thickness variation on velocity field, outlet-L and outlet-R flow velocity under the hydrostatic bearing running in no-load 0 N, load 400 KN, full load 1,500 KN and rotating speeds of 10 r/min, 20 r/min, 30 r/min, 40 r/min, 50 r/min and 60 r/min, by using dynamic mesh technology and FLUENT software.

When the working table rotates clockwise, in the change process of oil film thickness, the fluid flow pattern of the lubricating oil at the edge of the sealing oil is the rule of laminar flow, and the oil cavity has a vortex. The outlet-R flow velocity becomes higher and higher by increasing the bearing load and working table speed, and the flow velocity increases with the decrease in oil film thickness; the outlet-L flow velocity increases with the decrease in oil film thickness under low rotating speed (less than 10 r/min) condition and decreases with the decrease of oil film thickness under high rotating speed (more than 60 r/min) condition.

The influence of the oil film thickness on the flow state distribution of the oil film was analyzed under different working conditions, and the influence rules of oil film thickness on the flow velocity of hydrostatic bearing oil pad was obtained by using dynamic mesh technology.

Facebook has been identified as a primary source of political information by a majority (63 percent) of its users. The purpose of this paper is to examine the relationship between Facebook use and political participation, and investigate the mediating effects of the characteristics of one’s Facebook network (i.e. network size, proportion of strong ties, and discussion network heterogeneity).

This study relies on a representative survey of American adults (n=1,032) conducted during the 2012 primary election campaigns from May 3 to May 10. The sample was randomly selected from a representative online panel maintained by a professional research organization. Given this study’s focus on the influence of Facebook use and network characteristics, an online panel is suitable for testing the hypotheses.

The results show positive associations between Facebook use and both off- and online political participation. Further, the positive association between Facebook use and political participation is mediated by discussion network heterogeneity and the proportion of strong ties in one’s Facebook network, but not the network size.

This study sheds light on the roles played by network characteristics of Facebook. The composition of a user’s Facebook network is closely related with what kind of information she encounters and how likely she is to participate in politics. Hence, network characteristics (e.g. Facebook discussion network heterogeneity) arise as important for gaining a nuanced understanding of the relationship between general use of the medium and its political outcomes.

The effects of the thermo-mechanical treatment on the properties and microstructure of the Al–Cu–Mg–Ag alloy were investigated.

A short-duration preprecipitation process is designed prior to predeformation aging. The novel predeformation aging (solution treatment + holding at 185 °C for 15 min+ rolling deformation + aging at 185 °C, also named T8) was performed on a heat-resistant Al–Cu–Mg–Ag alloy.

The purpose of this study indicate that a short-duration heat treatment before predeformation is beneficial to the precipitation of O during the aging process. The precursors of O during this process might pin the dislocation and cause the grains to orient along some specific direction, which might be advantageous to the precipitation of O while disadvantageous to that of θ′. This novel thermal-mechanical process could result in an increase in the quantity and decrease in the size of the precipitation of O, which leads to a remarkable strength effect. The potential increases while the current density decreases with an increase in the deformation amount, which implies a smaller intergranular corrosion rate. The fine deformed structure leads to an opposite behavior in the exfoliation corrosion test compared with that for intergranular corrosion.

The intergranular corrosion resistance of the Al–Cu–Mg–Ag alloy is enhanced, whereas the exfoliation corrosion resistance is reduced by novel predeformation aging.

Fake news in cyberspace has greatly interfered with national governance, economic development and cultural communication, which has greatly increased the demand for fake news detection and intervention. At present, the recognition methods based on news content all lose part of the information to varying degrees. This paper proposes a lightweight content-based detection method to achieve early identification of false information with low computation costs.

The authors' research proposes a lightweight fake news detection framework for English text, including a new textual feature extraction method, specifically mapping English text and symbols to 0–255 using American Standard Code for Information Interchange (ASCII) codes, treating the completed sequence of numbers as the values of picture pixel points and using a computer vision model to detect them. The authors also compare the authors' framework with traditional word2vec, Glove, bidirectional encoder representations from transformers (BERT) and other methods.

The authors conduct experiments on the lightweight neural networks Ghostnet and Shufflenet, and the experimental results show that the authors' proposed framework outperforms the baseline in accuracy on both lightweight networks.

The authors' method does not rely on additional information from text data and can efficiently perform the fake news detection task with less computational resource consumption. In addition, the feature extraction method of this framework is relatively new and enlightening for text content-based classification detection, which can detect fake news in time at the early stage of fake news propagation.

This paper examines Aman Ullah’s contributions to robust inference, finite sample econometrics, nonparametrics and semiparametrics, and panel and spatial models. His early works on robust inference and finite sample theory were mostly motivated by his thesis advisor, Professor Anirudh Lal Nagar. They eventually led to his most original rethinking of many statistics and econometrics models that developed into the monograph Finite Sample Econometrics published in 2004. His desire to relax distributional and functional-form assumptions lead him in the direction of nonparametric estimation and he summarized his views in his most influential textbook Nonparametric Econometrics (with Adrian Pagan) published in 1999 that has influenced a whole generation of econometricians. His innovative contributions in the areas of seemingly unrelated regressions, parametric, semiparametric and nonparametric panel data models, and spatial models have also inspired a larger literature on nonparametric and semiparametric estimation and inference and spurred on research in robust estimation and inference in these and related areas.

To provide human judgment input for computer algorithm development, this study examines the relative importance of source, content, and style cues in predicting the truthfulness ratings of two common types of online health information: news stories and institutional news releases.

This study employed a multi-method approach using (1) a manual content analysis of 400 randomly selected online health news stories and news releases from HealthNewsReview.org and (2) an online experiment comparing truthfulness ratings between news stories and news releases.

Using content analysis, the authors found significant differences in the importance of source, content, and style cues in predicting truthfulness ratings of news stories and news releases: source and style cues predicted truthfulness ratings better than content cues. In the experiment, source credibility was the most important predictor of truthfulness ratings, controlling for individual differences. Experts have higher ratings for news media stories than news releases and lay people have no differences in rating the two news formats.

It is important for health educators to curb consumer trust in misinformation and increase health information literacy. Rather than solely reporting scientific evidence, educators should focus on addressing cues people use to judge the truthfulness of health information.

This is the first study that directly compares human judgments of health news stories and news releases. Using both the breadth of content analysis and experimental causality testing, the authors evaluate the relative importance of source, content, and style cues in predicting truthfulness ratings.

The purpose of this paper is to examine the effect of application of a heat pipe in an aspect of hydrostatic thrust bearings on thermal balance and deformation and the role of this application in increasing the rotating speed of a workbench.

Numerical simulations of oil film temperature field, the temperature field and thermal deformation of the bearing’s workbench and base were performed by finite element analysis (FEA) software for both the traditional hydrostatic thrust bearings and the heat pipe ones.

Oil pad and workbench of the hydrostatic thrust bearings are fabricated with a heat pipe cooling structure, which can take away most of the heat generated by shearing of the oil film, control the temperature rise and thermal deformation of the hydrostatic thrust bearing effectively, avoid the dry friction phenomenon and finally improve the processing quality of equipment.

The heat pipe hydrostatic thrust bearings could control the temperature rise and thermal deformation of the hydrostatic thrust bearing effectively, avoid the dry friction phenomenon and improve the processing quality of equipment.