Mechanism of Action and Structural Requirements of Constrained Peptide Inhibitors of RGS Proteins

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66199/1/j.1747-0285.2006.00373.x.pd

Optimal Flying Wings: A Numerical Optimization Study

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97067/1/AIAA2012-1758.pd

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

Dimethyl fumarate in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

Dimethyl fumarate (DMF) inhibits inflammasome-mediated inflammation and has been proposed as a treatment for patients hospitalised with COVID-19. This randomised, controlled, open-label platform trial (Randomised Evaluation of COVID-19 Therapy [RECOVERY]), is assessing multiple treatments in patients hospitalised for COVID-19 (NCT04381936, ISRCTN50189673). In this assessment of DMF performed at 27 UK hospitals, adults were randomly allocated (1:1) to either usual standard of care alone or usual standard of care plus DMF. The primary outcome was clinical status on day 5 measured on a seven-point ordinal scale. Secondary outcomes were time to sustained improvement in clinical status, time to discharge, day 5 peripheral blood oxygenation, day 5 C-reactive protein, and improvement in day 10 clinical status. Between 2 March 2021 and 18 November 2021, 713 patients were enroled in the DMF evaluation, of whom 356 were randomly allocated to receive usual care plus DMF, and 357 to usual care alone. 95% of patients received corticosteroids as part of routine care. There was no evidence of a beneficial effect of DMF on clinical status at day 5 (common odds ratio of unfavourable outcome 1.12; 95% CI 0.86-1.47; p = 0.40). There was no significant effect of DMF on any secondary outcome

PRELIMINARY HAZARD SUMMARY REPORT ON THE BOILING EXPERIMENTAL REACTOR (BER)

A preliminary evaluation of the hazards associated with a 20-Mw boiling reactor for the purpose of determining site requirements is presented. The Boiling Experimental Reactor design, safety features, and performance are given and the surroundings of the site at Argonne National Laboratory are described. (T.R.H.