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This study aims to provide supplements to the research on digital human avatar (DHA) and suggestions for brands to use DHA appropriately to build brand fans effect.

On the basis of integrating Avatar theory and Stimulus-organism-response theory, this study obtains data from 733 Chinese respondents aged 18–25 and uses regression analysis and bootstrap analysis to verify the relationships among the variables: DHA characteristics (form realism, behavioral realism and brand alignment) as the independent variables, brand fans effect as the dependent variable, consumer positive emotion as the mediating variable and product type (experience vs search) as the moderating variable.

The results show that DHA characteristics positively influence brand fans effect and consumer positive emotion, consumer positive emotion positively influences brand fans effect and consumer positive emotion plays a mediating role. Meanwhile, for experience products, the impact of DHA’s form realism and behavioral realism on consumer positive emotion is higher than that of brand alignment; for search products, the impact of DHA’s brand alignment on consumer positive emotion is higher than that of form realism and behavioral realism.

This study enriches and expands the empirical research perspectives and conclusions in the DHA field, improves its research framework and provides suggestions for brands to appropriately use DHA to build brand fans effect.

With burgeoning interest in the low-altitude economy, applications of long-endurance unmanned aerial vehicles (LE-UAVs) have increased in remote logistics distribution. Given LE-UAVs’ advantages of wide coverage, strong versatility and low cost, in addition to logistics distribution, they are widely used in military reconnaissance, communication relay, disaster monitoring and other activities. With limited autonomous intelligence, LE-UAVs require regular periodic and non-periodic control from ground control resources (GCRs) during flights and mission execution. However, the lack of GCRs significantly restricts the applications of LE-UAVs in parallel.

We consider the constraints of GCRs, investigating an integrated optimization problem of multi-LE-UAV mission planning and GCR allocation (Multi-U&G IOP). The problem integrates GCR allocation into traditional multi-UAV cooperative mission planning. The coupling decision of mission planning and GCR allocation enlarges the decision space and adds complexities to the problem’s structure. Through characterizing the problem, this study establishes a mixed integer linear programming (MILP) model for the integrated optimization problem. To solve the problem, we develop a three-stage iterative optimization algorithm combining a hybrid genetic algorithm with local search-variable neighborhood decent, heuristic conflict elimination and post-optimization of GCR allocation.

Numerical experimental results show that our developed algorithm can solve the problem efficiently and exceeds the solution performance of the solver CPLEX. For small-scale instances, our algorithm can obtain optimal solutions in less time than CPLEX. For large-scale instances, our algorithm produces better results in one hour than CPLEX does. Implementing our approach allows efficient coordination of multiple UAVs, enabling faster mission completion with a minimal number of GCRs.

Drawing on the interplay between LE-UAVs and GCRs and considering the practical applications of LE-UAVs, we propose the Multi-U&G IOP problem. We formulate this problem as a MILP model aiming to minimize the maximum task completion time (makespan). Furthermore, we present a relaxation model for this problem. To efficiently address the MILP model, we develop a three-stage iterative optimization algorithm. Subsequently, we verify the efficacy of our algorithm through extensive experimentation across various scenarios.

This study aims to investigate the impact of temperature and fiber volume fraction on the mechanical properties of 3D-printed composites of continuous glass fiber reinforced onyx.

Continuous glass fiber reinforced onyx (carbon-filled nylon) 3D-Printed composites have been designed and tested at 40°C, 60°C and 80°C for fiber volume fractions ranging from 13%, 20%, 27%, 33% and 40%.

The results of three-point bending tests have shown that at higher temperatures, i.e. greater than the room temperature the 3D-Printed onyx loses its mechanical properties as obvious for thermoplastic composites. However, the inclusion of high temperature glass fibers has improved the mechanical properties of the onyx polymer and its resistance to deformation at higher temperatures. At all temperatures, the increase in fiber fraction increases the yield strength and decreases the elongation of the composite in the strain region below the yield point. At Vf >0.27 the elongation in samples seems less affected by the fiber content. The comparison of the specimen with different fiber volume fractions (Vf) shows that the elongation of the samples at Vf = 0.4, the samples’ response to the applied load has become independent of the temperature above 40°C.

The experimental and numerically calculated results are well matched, showing the accuracy in the methodology of designing the fiber reinforced onyx composites.