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- Reinke, Beth A, et al.
(författare)
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Diverse aging rates in ectothermic tetrapods provide insights for the evolution of aging and longevity
- 2022
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Ingår i: Science. - : American Association for the Advancement of Science. - 0036-8075 .- 1095-9203. ; 376:6600, s. 1459-1466
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Tidskriftsartikel (refereegranskat)abstract
- Comparative studies of mortality in the wild are necessary to understand the evolution of aging; yet, ectothermic tetrapods are underrepresented in this comparative landscape, despite their suitability for testing evolutionary hypotheses. We present a study of aging rates and longevity across wild tetrapod ectotherms, using data from 107 populations (77 species) of nonavian reptiles and amphibians. We test hypotheses of how thermoregulatory mode, environmental temperature, protective phenotypes, and pace of life history contribute to demographic aging. Controlling for phylogeny and body size, ectotherms display a higher diversity of aging rates compared with endotherms and include phylogenetically widespread evidence of negligible aging. Protective phenotypes and life-history strategies further explain macroevolutionary patterns of aging. Analyzing ectothermic tetrapods in a comparative context enhances our understanding of the evolution of aging.
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- Wang, Yuan, et al.
(författare)
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Resilient Consensus for Multi-Agent Systems Under Adversarial Spreading Processes
- 2022
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Ingår i: IEEE Transactions on Network Science and Engineering. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4697. ; 9:5, s. 3316-3331
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Tidskriftsartikel (refereegranskat)abstract
- This paper addresses novel consensus problems for multi-agent systems operating in an unreliable environment where adversaries are spreading. The dynamics of the adversarial spreading processes follows the susceptible-infected-recovered (SIR) model, where the infection induces faulty behaviors in the agents and affects their state values. Such a problem setting serves as a model of opinion dynamics in social networks where consensus is to be formed at the time of pandemic and infected individuals may deviate from their true opinions. To ensure resilient consensus among the noninfectious agents, the difficulty is that the number of infectious agents changes over time. We assume that a local policy maker announces the local level of infection in real-time, which can be adopted by the agent for its preventative measures. It is demonstrated that this problem can be formulated as resilient consensus in the presence of the socalled mobile malicious models, where the mean subsequence reduced (MSR) algorithms are known to be effective. We characterize sufficient conditions on the network structures for different policies regarding the announced infection levels and the strength of the epidemic. Numerical simulations are carried out for random graphs to verify the effectiveness of our approach.
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- Wang, Yuan, et al.
(författare)
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Resilient Real-Valued Consensus in Spite of Mobile Malicious Agents on Directed Graphs
- 2022
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Ingår i: IEEE Transactions on Parallel and Distributed Systems. - : Institute of Electrical and Electronics Engineers (IEEE). - 1045-9219 .- 1558-2183. ; 33:3, s. 586-603
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Tidskriftsartikel (refereegranskat)abstract
- This article addresses novel real-valued consensus problems in the presence of malicious adversaries that can move within the network and induce faulty behaviors in the attacked agents. By adopting several mobile adversary models from the computer science literature, we develop protocols which can mitigate the influence of such malicious agents. The algorithms follow the class of mean subsequence reduced (MSR) algorithms, under which agents ignore the suspicious values received from neighbors during their state updates. Different from the static adversary models, even after the adversaries move away, the infected agents may remain faulty in their values, whose effects must be taken into account. We develop conditions on the network structures for both the complete and non-complete directed graph cases, under which the proposed algorithms are guaranteed to attain resilient consensus. The tolerance bound for network conditions becomes more strict as the adversaries are allowed to have more power. Extensive simulations are carried out over random graphs to verify the effectiveness of our approach when the information of the adversarial agents in terms of their models and numbers is unknown to the agents.
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