| 1. |
- Breitfeld, Jana, et al.
(författare)
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Genetic dissection of serum vaspin highlights its causal role in lipid metabolism
- 2023
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Ingår i: Obesity. - 1930-7381. ; 31:11, s. 2862-2874
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Vaspin (visceral adipose tissue derived serine protease inhibitor, SERPINA12) is associated with obesity-related metabolic traits, but its causative role is still elusive. The role of genetics in serum vaspin variability to establish its causal relationship with metabolically relevant traits was investigated. Methods: A meta-analysis of genome-wide association studies for serum vaspin from six independent cohorts (N = 7446) was conducted. Potential functional variants of vaspin were included in Mendelian randomization (MR) analyses to assess possible causal pathways between vaspin and homeostasis model assessment and lipid traits. To further validate the MR analyses, data from Genotype-Tissue Expression (GTEx) were analyzed, db/db mice were treated with vaspin, and serum lipids were measured. Results: A total of 468 genetic variants represented by five independent variants (rs7141073, rs1956709, rs4905216, rs61978267, rs73338689) within the vaspin locus were associated with serum vaspin (all p < 5×10−8, explained variance 16.8%). MR analyses revealed causal relationships between serum vaspin and triglycerides, low-density lipoprotein, and total cholesterol. Gene expression correlation analyses suggested that genes, highly correlated with vaspin expression in adipose tissue, are enriched in lipid metabolic processes. Finally, in vivo vaspin treatment reduced serum triglycerides in obese db/db mice. Conclusions: The data show that serum vaspin is strongly determined by genetic variants within vaspin, which further highlight vaspin's causal role in lipid metabolism.
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| 2. |
- Maasri, Alain, et al.
(författare)
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A global agenda for advancing freshwater biodiversity research
- 2022
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Ingår i: Ecology Letters. - : Wiley. - 1461-023X .- 1461-0248. ; 25:2, s. 255-263
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Tidskriftsartikel (refereegranskat)abstract
- Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation.
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| 3. |
- Pek, Christian, et al.
(författare)
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SpaTiaL : monitoring and planning of robotic tasks using spatio-temporal logic specifications
- 2023
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Ingår i: Autonomous Robots. - : Springer Nature. - 0929-5593 .- 1573-7527. ; 47:8, s. 1439-1462
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Tidskriftsartikel (refereegranskat)abstract
- Many tasks require robots to manipulate objects while satisfying a complex interplay of spatial and temporal constraints. For instance, a table setting robot first needs to place a mug and then fill it with coffee, while satisfying spatial relations such as forks need to placed left of plates. We propose the spatio-temporal framework SpaTiaL that unifies the specification, monitoring, and planning of object-oriented robotic tasks in a robot-agnostic fashion. SpaTiaL is able to specify diverse spatial relations between objects and temporal task patterns. Our experiments with recorded data, simulations, and real robots demonstrate how SpaTiaL provides real-time monitoring and facilitates online planning. SpaTiaL is open source and easily expandable to new object relations and robotic applications.
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| 4. |
- Schuppe, Georg Friedrich, 1993-
(författare)
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Assumptions in Synthesis : An Approach to Multi-Agent Planning from Spatio-Temporal Specifications
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- As the deployment of autonomous robots in real-world environments becomes increasingly prevalent, the need for these robots to operate safely and efficiently alongside human actors and other robots grows. Ensuring that robots adhere to their intended tasks and safety constraints as specified is of utmost importance, particularly when considering interactions between different robots and humans. To address this challenge, formal methods-based strategy synthesis techniques have emerged as a promising approach, offering rigorous specification languages and algorithms that generate correct-by-design strategies.This doctoral thesis focuses on the design and development of decentralized strategy synthesis algorithms to handle multi-agent systems consisting of multiple robots, or robots and humans. By considering task planning in a shared environment, the research seeks to achieve guarantees regarding specification satisfaction while considering interactions between computational agents and human actors.Several key considerations are addressed in this work. Scalability is a major concern in strategy synthesis methods, given their high computational costs. We avoid constructing a global, centralized model of the system to mitigate the state explosion problem. Instead, we focus on decentralized methods that ensure global integrity through communication of necessary, but minimal assumptions as least-limiting advisers.Another challenge lies in effectively modeling human agents in the system. Human behavior is influenced by context and preferences, making it difficult to provide explicit models. We avoid explicitly modelling the human and instead propose an assume-guarantee approach, where the robot conveys only necessary advice to the human.This advice, if followed by the human, enables us to provide conditional guarantees on the satisfaction of the task specification.Lastly, while temporal logics are a rich and expressive specification language, it can be difficult to correctly capture desired tasks and constraints. We present a specification language for object-oriented tasks that leverages spatial relations to intuitively specify desired spatial and temporal relations between objects. We show that this language can be used for monitoring and planning in various scenarios.We also demonstrate how it can be used to enable a robot to request help from a human assistant through structured language.Overall, this doctoral thesis aims to bring the benefits of formal methods-based strategy synthesis to multi-agent systems with human actors, providing a unified methodology to compute and convey least-limiting advice in interactions between robots and between robots and humans.
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| 5. |
- Schuppe, Georg Friedrich, 1993-, et al.
(författare)
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Decentralized Multi-Agent Strategy Synthesis under LTLf Specifications via Exchange of Least-Limiting Advisers
- 2021
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Ingår i: 2021 International Symposium on Multi-Robot and Multi-Agent Systems (MRS). - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- We propose a decentralized solution to a high-level task-planning problem for a multi-agent system under a set of possibly dependent LTL f specifications. We propose an approach where the problem is turned into a number of individual two and a half player stochastic games with reachability objectives. If almost-surely winning strategies cannot be found for them, we deploy so-called least-limiting advisers to restrict agents' behaviours. A key step is treating safety and liveness separately, by synthesizing necessary safety and fairness assumptions and iteratively exchanging them in the form of advisers between the agents. We avoid the state-space explosion problem by computing advisers locally in each game, independently of the model and specification of other agents. The solution is sound, but conservative. We demonstrate its scalability in a series of simulated scenarios involving cleaning of an office-like environment.
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| 6. |
- Schuppe, Georg Friedrich, 1993-, et al.
(författare)
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Multi-Agent Strategy Synthesis for LTL Specifications through Assumption Composition
- 2020
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Ingår i: 2020 IEEE 16th International Conference on Automation Science and Engineering (CASE). - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- We propose a compositional solution to the strategy synthesis problem for LTL specifications in the cooperative (heterogeneous) multi-agent scenario. A main challenge of the general strategy synthesis approach is the state-space explosion occurring during construction of a global model for agents with different, mutually dependent goals. Given a set of agents and their individual goal specifications represented through a local model and an LTL formula, we compute a compliant set of strategies that fulfill each agents’ goal specification. We avoid the state-space explosion by computing individual solutions for each agent separately and then composing these solutions. During the initial strategy computation, assumptions over the states of other agents not represented in the local model are generated only where needed. These assumptions are resolved during composition of the individual solutions to assure compliance of the computed strategies. The effectiveness of this approach is demonstrated in several simulation case studies and compared to the classical, monolithic approach.
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| 7. |
- Wang, Wei, et al.
(författare)
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Decentralized Multi-agent Coordination under MITL Specifications and Communication Constraints
- 2023
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Ingår i: 2023 31st Mediterranean Conference on Control and Automation, MED 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 842-849
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Konferensbidrag (refereegranskat)abstract
- We propose a decentralized solution for high-level multi-agent task planning problems in environments considering communication network failure. In particular, we consider that robots can only sense each other and communicate within a limited radius, yet, they may need to collaborate to accomplish their tasks. These tasks are given in Metric Interval Temporal Logic (MITL), which is capable to capture complex task specifications involving explicit time constraints. To substitute for the lacking communication networks, we deploy an agile robot (e.g., drones) to transfer information between the heavy-duty robots while executing tasks. We propose an algorithm to decompose each MITL formula that is assigned to the corresponding heavy-duty robot into an independent task of that robot and an independent request for others. The agile robot systematically pursues heavy-duty robots to exchange requests. The heavy-duty robots use formal methods-based algorithms to compute path plans satisfying the independent promises and the received requests. While the robots' plan computation is fully decentralized, the satisfaction of all tasks is guaranteed (if such plans are found). The proposed solution can be applied to practical applications where the communication network fails or is restricted, such as post-catastrophe search and rescue and wildlife surveillance.
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| 8. |
- Wang, Wei, et al.
(författare)
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Decentralized Multi-agent Coordination under MITL Tasks and Communication Constraints
- 2022
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Ingår i: Proceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 320-321
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Konferensbidrag (refereegranskat)abstract
- We propose a decentralized framework to solve a coordination problem for multi-agent systems consisting of heterogeneous agents, each of which uses only local information based on limited sensing and communication capabilities. In the proposed method, slower heavy-duty robots are each assigned a task specification specified in metric interval temporal logic. These specifications express complex, time-bounded tasks that are potentially dependent on other agents' actions. Heavy-duty robots update their task plans upon receiving a cooperative request from other heavy-duty robots in order to complete cooperative tasks. These requests are transmitted by the more agile light-duty robots responsible for information exchange, which systematically pursue heavy-duty robots. Our work in progress aims to present the framework together with a set of assumptions under which the solution is complete. We also aim to evaluate the framework on a series of use cases motivated by search and rescue.
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