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This paper aims to examine the effect of domain knowledge on eye-tracking measures and predict readers’ domain knowledge from these measures in a navigational table of contents (N-TOC) system.

A controlled experiment of three reading tasks was conducted in an N-TOC system for 24 postgraduates of Wuhan University. Data including fixation duration, fixation count and inter-scanning transitions were collected and calculated. Participants’ domain knowledge was measured by pre-experiment questionnaires. Logistic regression analysis was leveraged to build the prediction model and the model’s performance was evaluated based on baseline model.

The results showed that novices spent significantly more time in fixating on text area than experts, because of the difficulty of understanding the information of text area. Total fixation duration on text area (TFD_T) was a significantly negative predictor of domain knowledge. The prediction performance of logistic regression model using eye-tracking measures was better than baseline model, with the accuracy, precision and F(β = 1) scores to be 0.71, 0.86, 0.79.

Little research has been reported in literature on investigation of domain knowledge effect on eye-tracking measures during reading and prediction of domain knowledge based on eye-tracking measures. Most studies focus on multimedia learning. With respect to the prediction of domain knowledge, only some studies are found in the field of information search. This paper makes a good contribution to the literature on the effect of domain knowledge on eye-tracking measures during N-TOC reading and predicting domain knowledge.

The purpose of this paper is to examine the difference between experts and novices when reading with navigational table of contents (N-TOC). Experts refer to readers with high level of domain knowledge; novices refer to readers with low level of domain knowledge.

The authors performed a controlled experiment of three reading tasks (including fact finding task, partial understanding task, and full-text understanding task) on an N-TOC system for 35 post-graduates of Wuhan University who have rich experience in reading with N-TOC. Participants’ domain knowledge was measured by pre-experiment questionnaires; reading performance data including score, time, navigation use, and evaluation of N-TOC were collected.

The results showed that there was significant difference in neither navigation use nor participants’ evaluation, but domain experts performed significantly better in both score and time of all tasks than domain novices, which revealed an “illusion of control” phenomenon that rich experience in reading with N-TOC enabled domain novices to achieve the same performance as domain experts. In addition, this research found that N-TOC was not suitable for domain novices to solve full-text understanding task because of “cognitive overload” phenomenon.

This study makes a good contribution to the literature on the effect of domain knowledge on reading performance during N-TOC reading and how to provide better digital reading service in the field of library science and information science.

This paper aims to study the encounter issues of the Tethered-Space Net Robot System (TSNRS) with non-target objects on orbit during the maneuver, including the collision issues with small space debris and the obstacle avoidance from large obstacles.

For the collision of TSNRS with small debris, the available collision model of the tethered net and its limitation is discussed, and the collision detection method is improved. Then the dynamic response of TSNRS is studied and a closed-loop controller is designed. For the obstacle avoidance, the variable enveloping circle of the TSNRS has coupled with the artificial potential field (APF) method. In addition, the APF is improved with a local trajectory correction method to avoid the overbending segment of the trajectory.

The collision model coupled with the improved collision detection method solves the detection failure and speeds up calculation efficiency by 12 times. Collisions of TSNRS with small debris make the local thread stretch and deforms finally making the net a mess. The boundary of the disturbance is obtained by a series of collision tests, and the designed controller not only achieved the tracking control of the TSNRS but also suppressed the disturbance of the net.

This paper fills the gap in the research on the collision of the tethered net with small debris and makes the collision model more general and efficient by improving the collision detection method. And the coupled obstacle avoidance method makes the process of obstacle avoidance safer and smoother.

The work in this paper provides a reference for the on-orbit application of TSNRS in the active space debris removal mission.

Retailers have recently leveraged store-loyal customers’ store attachment to maintain customer relationships and motivate patronage intentions. However, the COVID-19 outbreak has driven customer migration from offline to mobile channels. Mobile retail applications (APPs) have been used by numerous retailers to reach their customers. Nonetheless, it has yet to be determined (1) whether store attachment can facilitate (or impede) the adoption of mobile retail APPs and (2) whether store-loyal customers will continue visiting offline stores in the post-pandemic era. To address these questions, we propose a theoretical account using integrated theories on trust transfer and store attachment.

We conducted multi-stage, longitudinal field surveys in two cities of mainland China: Beijing and Guangzhou. From two rounds of data collection, 237 and 103 responses were obtained in March 2022. Hypotheses were tested by partial least squares – structural equation modelling (PLS–SEM).

Results showed that customer trust in an offline retailer can be transferred to the retailer’s mobile APP at the pre-adoption stage, facilitating APP adoption. Notably, store-loyal customers who exhibited a strong attachment to the physical store of a retailer were more inclined to transfer their trust to the mobile APP of the retailer. This occurrence leads to an increased adoption rate, enhanced post-adoption satisfaction and increased inclination to continue (rather than discontinue) usage.

This study is the first to investigate the changes in store-loyal customers' shopping behaviour in the mobile retail era and in the post-COVID-19 pandemic recovery. Our findings elucidate the role of physical store attachment in the trust-transfer mechanism. Furthermore, store attachment may not prevent customers’ channel migration behaviour. Retailers may have to re-consider how to manage channel cannibalisation issues in the post-pandemic recovery.