| 1. |
- Tingö, Lina, 1984-, et al.
(författare)
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The effect of whole-diet interventions on memory and cognitive function in healthy older adults : a systematic review
- 2024
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Ingår i: Advances in nutrition (Bethesda, Md.). - : Oxford University Press. - 2161-8313 .- 2156-5376.
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Forskningsöversikt (refereegranskat)abstract
- BACKGROUND: An increasing number of cross-sectional studies suggests that diet may impact memory and cognition in healthy older adults. However, randomized, controlled trials investigating the effects of whole-diet interventions on memory and cognition in healthy older adults are rather rare and conflicting results are often reported.OBJECTIVE: Therefore, a systematic review was conducted to compile the current evidence regarding the potential effects of whole-diet interventions on 1) memory and, 2) other cognitive outcomes in older adults.METHODS: Studies that reported on randomized, controlled trials with dietary interventions in healthy older adults (60 yrs. and older) were included. Studies utilizing supplements, single food items or trials in specific patient groups (ie neurodegenerative diagnoses) were excluded.RESULTS: For the 23 included articles, the main outcomes examined fell into one or more of the following categories: cognitive task-based outcomes related to memory, other cognitive task-based outcomes, and additional outcomes related to cognitive function or disease risk. Three of the studies that investigated dietary interventions alone and two multi-domain study showed positive effects on memory function, whereas five multi-domain interventions and one intervention that focused on diet alone showed positive effects on other cognitive outcomes.CONCLUSIONS: The effect of randomized, controlled whole-diet interventions on memory and cognitive function in healthy older adults is modest and inconclusive, highlighting the need for more well-designed, sufficiently powered studies. Furthermore, the potential mechanisms by which diet impacts cognition in healthy aging need to be elucidated.REGISTRY AND REGISTRY NUMBER FOR SYSTEMATIC REVIEWS OR META-ANALYSES: This systematic review is registered in PROSPERO under ID CRD42022329759.
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| 2. |
- Andersson, Olov, 1979-, et al.
(författare)
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WARA-PS : a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation
- 2021
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Ingår i: Autonomous Intelligent Systems. - : Springer Nature. - 2730-616X. ; 1:1
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Tidskriftsartikel (refereegranskat)abstract
- A research arena (WARA-PS) for sensing, data fusion, user interaction, planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented. The objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal challenges. The enabler is a computational infrastructure with a core system architecture for industrial and academic collaboration. This includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial vehicles. The motivating application for the demonstration is marine search and rescue operations. A state-of-art delegation framework for the mission planning together with three specific applications is also presented. The first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface vehicles. The second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles, and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine environments. The research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test facility. It would be most difficult to do experiments on this large scale without the WARA-PS research arena. Furthermore, these demonstrator activities have resulted in effective research dissemination with high public visibility, business impact and new research collaborations between academia and industry.
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| 3. |
- Bereza-Jarocinski, Robert, et al.
(författare)
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Distributed Model Predictive Control for Cooperative Landing
- 2020
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Ingår i: Proceedings 21st IFAC World Congress on Automatic Control - Meeting Societal Challenges. - : Elsevier BV. ; , s. 15180-15185
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Konferensbidrag (refereegranskat)abstract
- We design, implement and test two control algorithms for autonomously landing a drone on an autonomous boat. The first algorithm uses distributed model predictive control (DMPC), while the second combines a cascade controller with DMPC. The algorithms are implemented on a real drone, while the boat's motion is simulated, and their performance is compared to a centralized model predictive controller. Field experiments are performed, where all algorithms show an ability to land while avoiding violation of the safety constraints. The two distributed algorithms further show the ability to use longer prediction horizons than the centralized model predictive controller, especially in the cascade case, and also demonstrate improved robustness towards breaks in communication.
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| 4. |
- Braam, Svenja, 1989, et al.
(författare)
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Exploring carbon source related localization and phosphorylation in the Snf1/Mig1 network using population and single cell-based a pproaches
- 2024
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Ingår i: MICROBIAL CELL. - 2311-2638. ; 11:1, s. 143-154
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Tidskriftsartikel (refereegranskat)abstract
- The AMPK/SNF1 pathway governs energy balance in eukaryotic cells, notably influencing glucose de-repression. In S. cerevisiae , Snf1 is phosphorylated and hence activated upon glucose depletion. This activation is required but is not sufficient for mediating glucose de-repression, indicating further glucosedependent regulation mechanisms. Employing fluorescence recovery after photobleaching (FRAP) in conjunction with non -linear mixed effects modelling, we explore the spatial dynamics of Snf1 as well as the relationship between Snf1 phosphorylation and its target Mig1 controlled by hexose sugars. Our results suggest that inactivation of Snf1 modulates Mig1 localization and that the kinetic of Snf1 localization to the nucleus is modulated by the presence of non -fermentable carbon sources. Our data offer insight into the true complexity of regulation of this central signaling pathway in orchestrating cellular responses to fluctuating environmental cues. These insights not only expand our understanding of glucose homeostasis but also pave the way for further studies evaluating the importance of Snf1 localization in relation to its phosphorylation state and regulation of downstream targets.
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| 5. |
- Braam, Svenja, 1989, et al.
(författare)
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Exploring carbon source related localization and phosphorylation in the Snf1/Mig1 network using population and single cell-based approaches
- 2024
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Ingår i: Microbial Cell. - 2311-2638. ; 11:1, s. 143-154
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Tidskriftsartikel (refereegranskat)abstract
- The AMPK/SNF1 pathway governs energy balance in eukaryotic cells, notably influencing glucose de-repression. In S. cerevisiae, Snf1 is phosphorylated and hence activated upon glucose depletion. This activation is required but is not sufficient for mediating glucose de-repression, indicating further glucose-dependent regulation mechanisms. Employing fluorescence recovery after photobleaching (FRAP) in conjunction with non-linear mixed effects modelling, we explore the spatial dynamics of Snf1 as well as the relationship between Snf1 phosphorylation and its target Mig1 controlled by hexose sugars. Our results suggest that inactivation of Snf1 modulates Mig1 localization and that the kinetic of Snf1 localization to the nucleus is modulated by the presence of non-fermentable carbon sources. Our data offer insight into the true complexity of regulation of this central signaling pathway in orchestrating cellular responses to fluctuating environmental cues. These insights not only expand our understanding of glucose homeostasis but also pave the way for further studies evaluating the importance of Snf1 localization in relation to its phosphorylation state and regulation of downstream targets.
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| 6. |
- Lapandic, Dzenan, et al.
(författare)
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Aperiodic Communication for MPC in Autonomous Cooperative Landing
- 2021
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Ingår i: IFAC PAPERSONLINE. - : Elsevier BV. - 2405-8963. ; , s. 113-118
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Konferensbidrag (refereegranskat)abstract
- This paper investigates the rendezvous problem for the autonomous cooperative landing of an unmanned aerial vehicle (UAV) on an unmanned surface vehicle (USV). Such heterogeneous agents, with nonlinear dynamics, are dynamically decoupled but share a common cooperative rendezvous task. The underlying control scheme is based on distributed Model Predictive Control (MPC). The main contribution is a rendezvous algorithm with an online update rule of the rendezvous location. The algorithm only requires the agents to exchange information when they can not guarantee to rendezvous. Hence, the exchange of information occurs aperiodically, which reduces the necessary communication between the agents. Furthermore, we prove that the algorithm guarantees recursive feasibility. The simulation results illustrate the effectiveness of the proposed algorithm applied to the problem of autonomous cooperative landing.
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| 7. |
- Persson, Linnea, 1992-
(författare)
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Autonomous and Cooperative Landings Using Model Predictive Control
- 2019
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Cooperation is increasingly being applied in the control of interconnected multi-agent systems, and it introduces many benefits. In particular, cooperation can improve the efficiency of many types of missions, and adds flexibility and robustness against external disturbances or unknown obstacles. This thesis investigates cooperative maneuvers for aerial vehicles autonomously landing on moving platforms, and how to safely and robustly perform such landings on a real system subject to a variety of disturbances and physical and computational constraints. Two specific examples are considered: the landing of a fixed-wing drone on top of a moving ground carriage; and the landing of a quadcopter on a boat. The maneuvers are executed in a cooperative manner where both vehicles are allowed to take actions to reach their common objective while avoiding safety based spatial constraints. Applications of such systems can be found in, for example, autonomous deliveries, emergency landings, and search and rescue missions. Particular challenges of cooperative landing maneuvers include the heterogeneous and nonlinear dynamics, the coupled control, the sensitivity to disturbances, and the safety criticality of performing a high-velocity landing maneuver.The thesis suggests the design of a cooperative control algorithm for performing autonomous and cooperative landings. The algorithm is based on model predictive control, an optimization-based method where at every sampling instant a finite-horizon optimal control problem is solved. The advantages of applying this control method in this setting arise from its ability to include explicit dynamic equations, constraints, and disturbances directly in the computation of the control inputs. It is shown how the resulting optimization problem of the autonomous landing controller can be decoupled into a horizontal and a vertical sub-problem, a finding which significantly increases the efficiency of the algorithm. The algorithm is derived for two different autonomous landing systems, which are subsequently implemented in realistic simulations and on a drone for real-world flight tests. The results demonstrate both that the controller is practically implementable on real systems with computational limitations, and that the suggested controller can successfully be used to perform the cooperative landing under the influence of external disturbances and under the constraint of various safety requirements.
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| 8. |
- Persson, Linnea, 1992-, et al.
(författare)
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Model predictive control for autonomous ship landing in a search and rescue scenario
- 2019
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Ingår i: Model predictive control for autonomous ship landing in a search and rescue scenario. - San Diego : American Institute of Aeronautics and Astronautics. ; , s. 1169-
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Konferensbidrag (refereegranskat)abstract
- This paper presents a Model Predictive Control approach for autonomous landing of a quadcopter on the deck of a moving boat. The research is motivated by a large-scale demonstrator arena equipped with autonomous boats and drones that should collaborate to perform various tasks related to search and rescue missions. The landing maneuver is executed in a cooperative manner where both the boat and the drone take actions to reach their common objective. The maneuver is designed to be feasible under a range of conditions, including scenarios where the boat is moving across the water or when it is subjected to disturbances such as waves and winds. During the landing, the vehicles must also consider various safety constraints for landing safely and efficiently. The algorithms are implemented both in hardware-in-the-loop simulations, where we demonstrate some of the different scenarios that the algorithm is expected to handle, as well as on a real boat-drone system, on which initial tests have been carried out.
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| 9. |
- Persson, Linnea, 1992-
(författare)
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Model Predictive Control for Cooperative Rendezvous of Autonomous Unmanned Vehicles
- 2021
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- This thesis investigates cooperative maneuvers for aerial vehicles autonomously landing on moving platforms. The objective has been to develop methods for safely performing such landings on real systems subject to a variety of disturbances, as well as physical and computational constraints. Two specific examples are considered: the landing of a fixed-wing drone on top of a moving ground carriage; and the landing of a quadcopter on the deck of a boat. The maneuvers are executed in a cooperative manner where both vehicles are allowed to take actions to reach their common objective, while avoiding safety based spatial constraints. Applications of such systems can be found in, for example, autonomous deliveries, emergency landings, and in search and rescue missions. Particular challenges of cooperative landing maneuvers include the heterogeneous and nonlinear dynamics, the coupled control, the sensitivity to disturbances, and the safety criticality of performing a high-velocity landing maneuver.In this thesis, a cooperative landing algorithm based on Model Predictive Control (MPC) that includes spatial safety constraints for avoiding dangerous regions is developed. MPC offers many advantages for the autonomous landing problem, with its ability to explicitly consider dynamic equations, constraints, and disturbances directly in the computation of the control inputs. It is shown that the cooperative landing MPC can be decoupled into a horizontal and a vertical sub-problem. This result makes the optimization problems significantly less computationally demandingand facilitates the real-time implementation. The autonomous landing maneuver is further improved by the employment of a variable horizon. The variable-horizon MPC framework lets the finite horizon length become a part of the optimization problem, and makes it possible to always extend the horizon to the end of the landing maneuver. An algorithm for variable horizon MPC that can be implemented to real-time systems is derived by the use of efficient update rules, and by taking into account the similarities between the multiple optimization problems that we have to solve in each sampling period. The algorithm is fast enough to be used even in time-critical systems with long horizons. Furthermore, the solution time of the variable-horizon MPC decreases as the target gets closer. This means that the computational demand becomes smaller in the most critical part of the landing maneuver.The algorithms are derived for two different landing systems, and are subsequently implemented in realistic simulations and in real-world outdoors flight tests through the WASP research arena. The results demonstrate both that the controllers are practically implementable on real systems with computational limitations, and that the suggested controller can successfully be used to perform the cooperative landing under the influence of external disturbances and under the constraint of various safety requirements.
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| 10. |
- Persson, Linnea, 1992-, et al.
(författare)
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Variable Prediction Horizon Control for Cooperative Landing on Moving Target
- 2021
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Ingår i: 2021 IEEE Aerospace Conference (AEROCONF 2021). - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- Motivated by applications in autonomous UAV landings on moving platforms, this paper proposes a Variable Horizon Model Predictive Control (VH-MPC) algorithm for cooperative rendezvous problems. Compared to existing VH-MPC, for which the associated computations are extensive which makes implementation on real-time UAV-platform systems most difficult, the look-ahead horizon in our VH-MPC algorithm adapts to the distance and time left to reach the rendezvous state in a computationally tractable manner. Our main contribution is the derivation of these efficient horizon-update rules. More specifically, the computational concerns in standard MPC for rendezvous maneuvers stem from that for the MPC to find a feasible solution, the look-ahead time needs to be long enough to ensure that a complete trajectory to the target set exists (i.e., the position and point in time where the two agents should meet). However, choosing a too long horizon results in expensive computations. A variable horizon can be used to find a horizon that is just long enough to make the control problem feasible, while reducing the computational complexity as the target set gets closer. To validate our proposed VH-MPC scheme, we conduct several experiments both in a realistic simulation environment (FlightGear-JSBSim, which includes nonlinear and complex dynamical effects), and in outdoors experiments with a quadrotor. Our experiments demonstrate i) the prohibitive computational cost of standard MPC, and ii) successful real-time computations of feasible trajectories and control inputs for an autonomous cooperative landing (fixed-wing UAV landing on an unmanned sea-surface vehicle), while satisfying important spatial safety-constraints (e.g., zones around the landing platform to avoid). Our experiments establish the feasibility of important future real-world applications in, e.g., sea rescue missions with fixed-wing drones and autonomous sea vessels.
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