Trust is essential in shaping human interactions with one another and with robots. In this article we investigate how human trust in robot capabilities transfers across multiple tasks. We present a human-subject study of two distinct task domains: a Fetch robot performing household tasks and a virtual reality simulation of an autonomous vehicle performing driving and parking maneuvers. The findings expand our understanding of trust and provide new predictive models of trust evolution and transfer via latent task representations: a rational Bayes model, a data-driven neural network model, and a hybrid model that combines the two. Experiments show that the proposed models outperform prevailing models when predicting trust over unseen tasks and users. These results suggest that (i) task-dependent functional trust models capture human trust in robot capabilities more accurately and (ii) trust transfer across tasks can be inferred to a good degree. The latter enables trust-mediated robot decision-making for fluent human–robot interaction in multi-task settings.
In this paper, we present results from a humansubject study designed to explore two facets of human mental models of robots-inferred capability and intention-and their relationship to overall trust and eventual decisions. In particular, we examine delegation situations characterized by uncertainty, and explore how inferred capability and intention are applied across different tasks. We develop an online survey where human participants decide whether to delegate control to a simulated UAV agent. Our study shows that human estimations of robot capability and intent correlate strongly with overall self-reported trust. However, overall trust is not independently sufficient to determine whether a human will decide to trust (delegate) a given task to a robot. Instead, our study reveals that estimations of robot intention, capability, and overall trust are integrated when deciding to delegate. From a broader perspective, these results suggest that calibrating overall trust alone is insufficient; to make correct decisions, humans need (and use) multi-faceted mental models when collaborating with robots across multiple contexts.
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is responsible for the global epidemic of Coronavirus Disease 2019 (COVID-19), with a significant impact on the global economy and human safety. Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard for detecting SARS-CoV-2, but because the virus’s genome is prone to mutations, the effectiveness of vaccines and the sensitivity of detection methods are declining. Variants of concern (VOCs) include Alpha, Beta, Gamma, Delta, and Omicron, which are able to evade recognition by host immune mechanisms leading to increased transmissibility, morbidity, and mortality of COVID-19. A range of research has been reported on detection techniques for VOCs, which is beneficial to prevent the rapid spread of the epidemic, improve the effectiveness of public health and social measures, and reduce the harm to human health and safety. However, a meaningful translation of this that reduces the burden of disease, and delivers a clear and cohesive message to guide daily clinical practice, remains preliminary. Herein, we summarize the capabilities of various nucleic acid and protein-based detection methods developed for VOCs in identifying and differentiating current VOCs and compare the advantages and disadvantages of each method, providing a basis for the rapid detection of VOCs strains and their future variants and the adoption of corresponding preventive and control measures.
Objective Peyronie’s disease (PD) is a fibrotic disorder of the penis, but effective treatments are lacking. Here, we observed the effects of rat-derived bone marrow mesenchymal stem cells (BMSCs) injection in the active phase and chronic phase in a rat model of PD, and the possible mechanism was analysed with fibroblasts derived from rat penile tunica albuginea (TA). Methods Thirty-two male Sprague-Dawley rats were divided into four groups. In sham group, the rats were injected with 50 µL of vehicle. In the PD group, the rats were injected with 50 µg TGF-β1. In the PD + BMSCs early treatment group, the rats were injected with 50 µg TGF-β1 and injected with 1 × 106 BMSCs after 1 day. In the PD + BMSCs late treatment group, the rats were injected with 50 µg TGF-β1 and injected with 1 × 106 BMSCs after 28 days. Twenty-seven days after the last injection, the erectile function of the rats was measured, and then, penile fibrosis was analysed by histology and western blot. In vitro, fibroblasts derived from rat penile TA were used to identify a possible antifibrotic mechanism of BMSCs, and a Smad7 expression vector was used as a positive control. Fibroblasts were pretreated with the Smad7 expression vector or BMSCs for 48 h and then activated with 10 ng/mL TGF-β1 for 24 h. Cells viability was assessed, and Smad7, collagen 3, elastase-2B and osteopontin expression levels were analysed by immunofluorescence and western blot. Furthermore, fibroblasts were transfected with Smad7 siRNA or scramble control to observe whether the effects of BMSCs could be offset. Results Erectile function obviously improved, and fibrosis of penile TA was prevented after BMSCs treatment compared with that in the rats with PD. Furthermore, the effects of BMSCs treatment in the active phase were better than those in the chronic phase. After cocultured with BMSCs, cell viability was not affected, Smad7 expression was upregulated, and collagen 3, elastase-2B and osteopontin levels were decreased in the TGF-β1-treated fibroblasts. After transfection with Smad7 siRNA, the antifibrotic effects of BMSCs were offset. Conclusions The antifibrotic effects of BMSCs treatment in the active phase of the PD rat model were better than those in the chronic phase. A possible mechanism of BMSCs treatment was related to increased Smad7 expression, suggesting a possible effective and safe procedure for the treatment of PD.
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