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The commercialisation of virtual reality (VR) headsets has made them more affordable and popular in gaming and entertainment. The natural interaction between the VR environment and users can maximise immersion and is crucial to VR gaming. Despite their growing popularity, educational VR games prioritise learning over immersion and require users to learn to interact with and play games using tutorials. Herein, we developed a game named Numverse with an accompanying tutorial. After selecting the tutorial content, we programmed the user interface and proposed a delivery method for the tutorial. We evaluated the user experience based on the effects of the presence or absence of the tutorial and its mode of delivery. The tutorials were of three types: no tutorial, instruction-screen tutorial, and context-sensitive tutorial, with the latter being the most preferred. The evaluation results show that presence, ability to learn controls, intrinsic motivation, and learning effectiveness are higher for the instruction-screen and context-sensitive tutorials than for no tutorial. On average, users experienced more motion sickness in the no-tutorial case, with a significant difference in nausea items. This study asserts the importance of tutorials in VR games, and its findings could improve user experience in future VR games. [ABSTRACT FROM AUTHOR]

This study aims to understand the usability of common button colours and background choices in the existing augmented reality (AR) interface. AR is increasingly used in dynamic situations, such as driving using an AR head-up display. However, studies regarding the usability of AR interfaces, especially about the colours, are scarce. Twenty-four participants performed button selection tasks in an experiment using Microsoft HoloLens. Three measures (task completion time, the number of errors, and button colour visibility were collected for the 12 experimental conditions (3 backgrounds by 4 button colours). Significant differences were found in completion time between backgrounds and blue button visibility. On a moving background, the most effective button colour is orange, and the most minor effective button colour is blue. The results of this study can be used for colour choices in designing AR applications and devices. [ABSTRACT FROM AUTHOR]

This study assessed the intra‐acquirer, intra‐ and inter‐processor reliability, and validity of the in vivo assessment of the medial gastrocnemius (MG), lateral gastrocnemius (LG) and soleus (SOL) muscle volumes using freehand 3D ultrasound (3DUS) in typically developing infants. Reliability assessments of freehand 3DUS were undertaken in infants across three ages groups: three, six and twelve months of age, with validity testing completed against magnetic resonance imaging (MRI) in infants at 3 months of age. Freehand 3DUS scanning was carried out by a single acquirer, with two independent processors manually segmenting images to render volumes. MRI images were segmented independently by a separate processor, with the volumes compared to those obtained via freehand 3DUS. Reliability was assessed using intraclass correlation (ICC), coefficient of variance (CV) and minimal detectable change (MDC) across each assessment time point. Validity was assessed using the limits of agreement. ICCs for intra‐acquirer reliability of the acquisition process for freehand 3DUS ranged from 0.91 to 0.99 across all muscles. ICCs for intra‐processor and inter‐processor reliability for the segmentation process of freehand 3DUS ranged from 0.80 to 0.98 across all muscles. Acceptable levels of agreement between muscle volume obtained by freehand 3DUS and MRI were found for all muscles; however, freehand 3DUS overestimated muscle volume of MG and LG and underestimate the SOL compared with MRI, with average absolute differences of MG = 0.3 ml, LG = 0.3 ml and Sol = 1.2 ml. Freehand 3DUS is a reliable method for measuring in vivo triceps surae muscle volume in typically developing infants. We conclude that freehand 3DUS is a useful tool to assess changes in muscle volume in response to growth and interventions in infants. [ABSTRACT FROM AUTHOR]

The dissemination of rumours and fabricated information via social media has the potential to adversely impact social cohesiveness and contribute to political polarization, which may lead to political divisions by casting doubt on the effectiveness of government and politicians. In light of the global economic crisis caused by the Russian–Ukrainian War, this study aims to identify economic rumours that were circulating in Egyptian society via social media. Machine learning was employed as a means of analysing the sentiment of user comments on various posts, thus providing an effective method for debunking fake news. In order to identify the most salient features of misleading information, the study qualitatively assessed the visual and linguistic elements of the postings. A total of 10,031 comments were analysed after being categorized into main groups. The study's results revealed key features pertaining to the sentiments expressed in the comments as well as identifying common textual traits of rumours and specific visual sentiments depicted in accompanying photos. This research sheds light on the importance of identifying and debunking rumours and fabricated information in order to mitigate their potentially negative effects on social cohesiveness and political polarization. Additionally, it highlights the utility of employing machine learning as a tool for analysing sentiment in user-generated content on social media platforms. [ABSTRACT FROM AUTHOR]

AI has become increasingly relevant to the media sector, especially for news media companies considering the integration of this technology into their production processes. While the application of AI promises productivity gains, the impact on consumers' perceptions of the resulting news and the level of AI integration accepted by the market has not been well studied. Our research focused on the analysis of news consumers' preferred level of AI integration, AI news trust, and AI news usage intentions linked to the application of the technology in the discovery/information-gathering and writing/editing phases. By connecting a comprehensive set of factors influencing the perception of news and AI, we approached this gap through structural equation modeling, presenting an overview of consumers' responses to AI integration into news production processes. Our research showed that while participants generally prefer lower levels of AI integration into both phases of production, news trust and usage intention can even increase as AI enters the production process—as long as humans remain in the lead. These findings provide researchers and news media managers with a first overview of consumers' responses to news production augmentation and its implications for news perception in the market. [ABSTRACT FROM AUTHOR]