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- Glasbey, JC, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Tabiri, S, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Bravo, L, et al.
(författare)
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- 2021
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swepub:Mat__t
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- Evangelou, Evangelos, et al.
(författare)
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Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits.
- 2018
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 50:10, s. 1412-1425
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Tidskriftsartikel (refereegranskat)abstract
- High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.
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- Vasile, C. -I, et al.
(författare)
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Minimum-violation scLTL motion planning for mobility-on-demand
- 2017
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Ingår i: 2017 IEEE International Conference on Robotics and Automation (ICRA). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781509046331 ; , s. 1481-1488
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Konferensbidrag (refereegranskat)abstract
- This work focuses on integrated routing and motion planning for an autonomous vehicle in a road network. We consider a problem in which customer demands need to be met within desired deadlines, and the rules of the road need to be satisfied. The vehicle might not, however, be able to satisfy these two goals at the same time. We propose a systematic way to compromise between delaying the satisfaction of the given demand and violating the road rules. We utilize scLTL formulas to specify desired behavior and develop a receding horizon approach including a periodically interacting routing algorithm and a RRT<-based motion planner. The proposed solution yields a provably minimum-violation trajectory. An illustrative case study is included.
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