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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.

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

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.

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.

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.

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.

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.

When the clearance oil film of hydrostatic bearing friction pair is in critical lubrication state, the phenomenon of zero flow of local lubricating oil will aggravate the oil film temperature rise, which needs to be solved.

In this paper, the critical lubrication parameter equation and the oil film temperature rise mathematical model are derived for the new type q1-205 double rectangular cavity hydrostatic bearing. Based on a combination of theoretical analysis, simulation and experimental verification, this paper analyzes the flow characteristics and temperature rise characteristics of the lubricating oil when the hydrostatic bearing is in a critical lubrication state under different operating conditions and finally obtains the critical lubrication state of the oil film.

This study found that the numerical simulations and the derived formulas agree with the results. When the oil film is in critical lubrication, the cross-section side flow of the oil side is almost zero. The heat cannot be taken away in time, resulting in the local temperature rise of the oil film, which causes serious heat accumulation.

It is concluded that the operating condition parameters corresponding to the critical lubrication state provide a theoretical basis for the selection of actual hydrostatic bearing operating conditions, which is of great scientific significance.

To solve the problem of oil film thinning when hydrostatic thrust bearings are overloaded or rotating at high speed, the dynamic pressure formed by tiny oil wedges is used to compensate, and the optimum height of oil wedges is determined by the compensation rate to improve the bearing capacity of hydrostatic thrust bearings.

This research method is aimed at the new type of double rectangular cavity static bearing with microbevel surface of q1-205. The wedge parameters of oil film were defined. The oil film lubrication performance of the bearing with the wedge parameters of 0, 0.02, 0.04, 0.06, 0.08 and 0.10 mm was simulated by the finite volume method, the comprehensive influence law of the wedge-shaped parameters on the vorticity and flow rate of the oil cavity pressure fluid was revealed. Finally, the oil cavity pressure changes of oil films with different wedge parameters under certain load and speed were tested by design experiments, and the theoretical analysis and simulation were verified.

This study found that the oil film wedge shape can well compensate the static pressure loss caused by the high-speed or heavy-duty operation of the bearing, but the dynamic pressure effect of the wedge shape does not always increase with the increase of the wedge height. The oil film exhibits superior lubrication performance in the range of 0.06–0.08 mm.

The original hydrostatic oil pad was designed as a microinclined plane, and the dynamic pressure caused by the microwedge of the oil pad was used to compensate the static pressure loss of the bearing. The lubrication performance of the oil film under the condition of varying viscosity was obtained by using the simulation method.

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.