How Can Skin Check Reminders be Personalised to Patient Conscientiousness?

This paper explores the potential of personalising health reminders to melanoma patients based on their personality (high vs low conscientiousness). We describe a study where we presented participants with a scenario with a fictional patient who has not performed a skin check for recurrent melanoma. The patient was described as either very conscientious, or very unconscientious. We asked participants to rate reminders inspired by Cialdini’s 6 principles of persuasion for their suitability for the patient. Participants then chose their favourite reminder and an alternative reminder to send if that one failed. We found that conscientiousness had an effect on both the ratings of reminder types and the most preferred reminders selected by participants

Total skin self-examination at home for people treated for cutaneous melanoma : development and pilot of a digital intervention

This work was funded by the RCUK Digital Economy award to the dot.rural Digital Economy Hub, University of Aberdeen; award reference: EP/G066051/1. The Experience Laboratory event was supported in part by a separate award from the University of Aberdeen Knowledge Exchange and Transfer Fund; award reference: GP057 UZZ0101.Peer reviewedPublisher PD

In vivo imaging of microenvironmental and anti-PD-L1-mediated dynamics in cancer using S100A8/S100A9 as an imaging biomarker

Purpose: As a promotor of tumor invasion and tumor microenvironment (TME) formation, the protein complex S100A8/S100A9 is associated with poor prognosis. Our aim was to further evaluate its origin and regulatory effects, and to establish an imaging biomarker for TME activity. Methods: S100A9−/−cells (ko) were created from syngeneic murine breast cancer 4T1 (high malignancy) and 67NR (low malignancy) wildtype (wt) cell lines and implanted into either female BALB/c wildtype or S100A9−/− mice (n = 10 each). Anti-S100A9-Cy5.5-targeted fluorescence reflectance imaging was performed at 0 h and 24 h after injection. Potential early changes of S100A9-presence under immune checkpoint inhibition (anti-PD-L1, n = 7 vs. rat IgG2b as isotype control, n = 3) were evaluated. Results: In S100A9−/−mice contrast-to-noise-ratios were significantly reduced for wt and S100A9−/−tumors. No significant differences were detected for 4T1 ko and 67NR ko cells as compared to wildtype cells. Under anti-PD-L1 treatment S100A9 presence significantly decreased compared with the control group. Conclusion: Our results confirm a secretion of S100A8/S100A9 by the TME, while tumor cells do not apparently release the protein. Under immune checkpoint inhibition S100A9-imaging reports an early decrease of TME activity. Therefore, S100A9-specific imaging may serve as an imaging biomarker for TME formation and activity

the State of Utah v. Walter Preston Boggess, Jr. : Brief of Respondent

An Appeal from a Judgment of the District Court of the Fourth Judicial District, The Honorable J, Robert Bullock, District Court Judg

Modeling a mobile group recommender system for tourism with intelligent agents and gamification

To provide recommendations to groups of people is a complex task, especially due to the group’s heterogeneity and conflicting preferences and personalities. This heterogeneity is even deeper in occasional groups formed for predefined tour packages in tourism. Group Recommender Systems (GRS) are being designed for helping in situations like those. However, many limitations can still be found, either on their time-consuming configurations and excessive intrusiveness to build the tourists’ profile, or in their lack of concern for the tourists’ interests during the planning and tours, like feeling a greater liberty, diminish the sense of fear/being lost, increase their sense of companionship, and promote the social interaction among them without losing a personalized experience. In this paper, we propose a conceptual model that intends to enhance GRS for tourism by using gamification techniques, intelligent agents modeled with the tourists’ context and profile, such as psychological and socio-cultural aspects, and dialogue games between the agents for the post-recommendation process. Some important aspects of a GRS for tourism are also discussed, opening the way for the proposed conceptual model, which we believe will help to solve the identified limitations.This work was supported by the GrouPlanner Project (POCI-01-0145-FEDER-29178) and by National Funds through the FCT –Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2019 and UID/EEA/00760/2019

Actual persuasiveness : Impact of personality, age and gender on message type susceptibility

The authors would like to acknowledge and thank all the volunteers who participated in the experiment and provided helpful comments. The first author is funded by an EPSRC doctoral training grant.Postprin

Recommending video content for use in group-based reminiscence therapy

REMPAD is a semi-automated cloud-based system used to facilitate digital reminiscence therapy for patients with mild-to-moderate dementia, enacted in a group setting. REMPAD uses profiles for participants and groups to proactively recommend interactive video content from the Internet to match these profiles. In this chapter, we focus on the design of the system and then the system architecture, the system build, data curation, and usage scenarios. We also report a series of steps carried out as part of our user-centered design approach to system development, and a series of analyses on interaction logs which indicate various levels of effectiveness for different configurations of the recommendation algorithm we use. The results indicate high user satisfaction when using the system, and strong tendency towards repeated use in future

NightSplitter: a scheduling tool to optimize (sub)group activities

International audienceHumans are social animals and usually organize activities in groups. However, they are often willing to split temporarily a bigger group in subgroups to enhance their preferences. In this work we present NightSplitter, an on-line tool that is able to plan movie and dinner activities for a group of users, possibly splitting them in subgroups to optimally satisfy their preferences. We first model and prove that this problem is NP-complete. We then use Constraint Programming (CP) or alternatively Simulated Annealing (SA) to solve it. Empirical results show the feasibility of the approach even for big cities where hundreds of users can select among hundreds of movies and thousand of restaurants