Agentic AI holds promise for usability testing, yet its role as an audio moderator in think-aloud protocols is not well understood. This study explores: (1) how to design and develop an agentic audio moderator for think-aloud usability testing, and (2) how participants moderated by an agentic moderator differ from those moderated by a human regarding task performance, verbalization behaviors, user experience, and social perceptions of the moderator. Using a design-based research approach, we interviewed nine UX experts, iteratively developed an AI moderator, and evaluated it in a randomized controlled trial (N = 60) with a note-taking application. Results suggest that significant differences were not observed between AI and human moderators in task performance or verbalization behaviors, though AI moderators received lower social perception ratings. This work contributes the first design-oriented evaluation of AI moderators in usability testing, offering implications for developing more acceptable and effective agentic audio moderators.

Structure reasoning is a fundamental capability of large language models (LLMs), enabling them to reason about structured commonsense and answer multi-hop questions. However, existing benchmarks for structure reasoning mainly focus on horizontal and coordinate structures (e.g. graphs), overlooking the hierarchical relationships within them. Hierarchical structure reasoning is crucial for human cognition, particularly in memory organization and problem-solving. It also plays a key role in various real-world tasks, such as information extraction and decision-making. To address this gap, we propose HiBench, the first framework designed to systematically benchmark the hierarchical reasoning capabilities of LLMs from initial structure generation to final proficiency assessment. It encompasses six representative scenarios, covering both fundamental and practical aspects, and consists of 30 tasks with varying hierarchical complexity, totaling 39,519 queries. To evaluate LLMs comprehensively, we develop five capability dimensions that depict different facets of hierarchical structure understanding. Through extensive evaluation of 20 LLMs from 10 model families, we reveal key insights into their capabilities and limitations: 1) existing LLMs show proficiency in basic hierarchical reasoning tasks; 2) they still struggle with more complex structures and implicit hierarchical representations, especially in structural modification and textual reasoning. Based on these findings, we create a small yet well-designed instruction dataset, which enhances LLMs' performance on HiBench by an average of 88.84% (Llama-3.1-8B) and 31.38% (Qwen2.5-7B) across all tasks. The HiBench dataset and toolkit are available at https://github.com/jzzzzh/HiBench to encourage evaluation.

Locomotion has a marked impact on user experience in VR, but currently, common to-go techniques such as steering and teleportation have their limitations. Particularly, steering is prone to cybersickness, while teleportation trades presence for mitigating cybersickness. Inspired by how we manipulate a picture on a mobile phone, we propose illumotion, an optical-illusion-based method that, we believe, can provide an alternative to these two typical techniques. Instead of zooming in a picture by pinching two fingers, we can move forward by “zooming” toward part of the 3D virtual scene with pinched hands. Not only is the proposed technique easy to use, it also seems to minimize cybersickness to some degree.illumotion relies on the manipulation of optics; as such, it requires solving motion parameters in screen space and a model of how we perceive depth. To evaluate it, a comprehensive user study with 66 users was conducted. Results show that, compared with either teleportation, steering or both, illumotion has better performance, presence, usability, user experience and cybersickness alleviation. We believe the result is a clear indication that our novel optically-driven method is a promising candidate for generalized locomotion.

This study examines the effects of political/cultural beliefs and situational perceptions on public support for government surveillance amidst COVID-19, using a representative survey conducted in Hong Kong. Our results indicate that situational responses (i.e. privacy trust and self-efficacy) balance against each other in mediating the effects of political/cultural beliefs (i.e. political trust, political efficacy, democratic-individualism) and situational perceptions (i.e. perceived cost and benefit of disclosure, perceived threat of COVID-19) on surveillance support. Both perceived benefit of disclosure and political trust positively affects surveillance support indirectly by promoting the contributing mediator privacy trust while suppressing the inhibiting mediator privacy self-efficacy. Perceived cost of disclosure shows no direct effect, but a positive indirect effect on surveillance support by suppressing privacy self-efficacy; perceived threat shows a positive direct effect while a negative indirect effect by suppressing privacy trust. Internal political efficacy shows a strong negative direct effect, but no indirect effect; and external political efficacy shows a negative indirect effect by promoting privacy self-efficacy. Alternative media use, as a proxy for democratic-individualism, mitigates situational perceptions’ effects on surveillance support, regardless of the directions. The findings advance our understanding of the formation process of public opinion on government surveillance.

Prior studies suggest that emotional empathy is one of the components of intercultural sensitivity - the affective dimension under the concept of intercultural communication competence. Based on existing theories and findings, this paper reports a randomised parallel longitudinal study investigating the use of virtual reality (VR) exposure to enhance intercultural sensitivity. A total of 80 participants (36 females and 44 males) joined the study and were included in the data analysis. The participants were randomly assigned to the VR group, the video group, and the control group. Their intercultural sensitivity was measured three times: one week before the exposure ($T_{1}$), right after the exposure ($T_{2}$), and three weeks after the exposure ($T_{3}$). The results suggested that (1) the intercultural sensitivity of the VR group was significantly enhanced in both within-subject comparisons and between-subject comparisons, (2) there were no significant differences in intercultural sensitivity between the VR group and the video group at $T_{2}$, but the VR group retained the enhancement better at $T_{3}$, and (3) the sense of presence and emotional empathy well predicted the change in intercultural sensitivity of the VR group. The results, together with the participants' feedback and comments, provide new insights into the practice of using VR for intercultural sensitivity training and encourage future research on exploring the contributing factors of the results.

This work addresses cybersickness, a major barrier to successful long-exposure immersive virtual reality (VR) experiences since user discomfort frequently leads to prematurely ending such experiences. Starting from sensory conflict theory, we posit that if a vibrating floor delivers vestibular stimuli that minimally match the vibration characteristics of a scenario, the size of the conflict between the visual and vestibular senses will be reduced and, thus, the incidence and/or severity of cybersickness will also be reduced. We integrated a custom-built, computer-controlled vibrating floor in our VR system. To evaluate the system, we implemented a realistic off-road vehicle driving simulator in which participants rode multiple laps as passengers on an off-road course. We programmed the floor to generate vertical vibrations similar to those experienced in real off-road vehicle travel. The scenario and driving conditions were designed to be cybersickness-inducing for users in both the Vibration and No-vibration conditions. We collected subjective and objective data for variables previously shown to be related to levels of cybersickness or presence. These included presence and simulator sickness questionnaires (SSQ), self-rated discomfort levels, and the physiological signals of heart rate, galvanic skin response (GSR), and pupil size. Comparing data between participants in the Vibration group (N=11) to the No-Vibration group (N=11), we found that Delta-SSQ Oculomotor response and the GSR physiological signal, both known to be positively correlated with cybersickness, were significantly lower (with large effect sizes) for the Vibration group. Other variables differed between groups in the same direction, but with trivial or small effect sizes. The results indicate that the floor vibration significantly reduced some measures of cybersickness.

BACKGROUND: Horizontal Gene Transfer (HGT) refers to the transfer of genetic materials between organisms through mechanisms other than parent-offspring inheritance. HGTs may affect human health through a large number of microorganisms, especially the gut microbiomes which the human body harbors. The transferred segments may lead to complicated local genome structural variations. Details of the local genome structure can elucidate the effects of the HGTs. RESULTS: In this work, we propose a graph-based method to reconstruct the local strains from the gut metagenomics data at the HGT sites. The method is implemented in a package named LEMON. The simulated results indicate that the method can identify transferred segments accurately on reference sequences of the microbiome. Simulation results illustrate that LEMON could recover local strains with complicated structure variation. Furthermore, the gene fusion points detected in real data near HGT breakpoints validate the accuracy of LEMON. Some strains reconstructed by LEMON have a replication time profile with lower standard error, which demonstrates HGT events recovered by LEMON is reliable. CONCLUSIONS: Through LEMON we could reconstruct the sequence structure of bacteria, which harbors HGT events. This helps us to study gene flow among different microbial species.

Microsoft Kinect sensors nowadays are widely used for real-time controller-free virtual reality (VR) interactions. However, there has been limited research on interaction-oriented analysis of motion data captured by Kinect from those who suffer from both intellectual and physical challenges. In this paper, a software framework based on Kinect is proposed to support a psycho-educational program (InSPAL) in a special school setting, which aims to enable students with severe intellectual disabilities (SID) to interact with the educational VR content and through which their pre-learning skills could be enhanced. Also, algorithms embedded in this framework are designed and modified in order to overcome limitations of the sensor and challenges originated from unique features of SID students' body movement.