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The majority of existing linear temporal logic (LTL) planning methods rely on the construction of a discrete product automaton, which combines a discrete abstraction of robot mobility and a Büchi automaton that captures the LTL specification. Representing this product automaton as a graph and using graph search techniques, optimal plans that satisfy the LTL task can be synthesized. However, constructing expressive discrete abstractions makes the synthesis problem computationally intractable. In this article, we propose a new sampling-based LTL planning algorithm that does not require any discrete abstraction of robot mobility. Instead, it incrementally builds trees that explore the product state-space, until a maximum number of iterations is reached or a feasible plan is found. The use of trees makes data storage and graph search tractable, which significantly increases the scalability of our algorithm. To accelerate the construction of feasible plans, we introduce bias in the sampling process, which is guided by transitions in the Büchi automaton that belong to the shortest path to the accepting states. We show that our planning algorithm, with and without bias, is probabilistically complete and asymptotically optimal. Finally, we present numerical experiments showing that our method outperforms relevant temporal logic planning methods. [ABSTRACT FROM AUTHOR]

Cell behaviors are dictated by epigenetic and transcriptional programs. Little is known about how extracellular stimuli modulate these programs to reshape gene expression and control cell behavioral responses. Here, we interrogated the epigenetic and transcriptional response of endothelial cells to VEGFA treatment and found rapid chromatin changes that mediate broad transcriptomic alterations. VEGFA-responsive genes were associated with active promoters, but changes in promoter histone marks were not tightly linked to gene expression changes. VEGFA altered transcription factor occupancy and the distal epigenetic landscape, which profoundly contributed to VEGFA-dependent changes in gene expression. Integration of gene expression, dynamic enhancer, and transcription factor occupancy changes induced by VEGFA yielded a VEGFA-regulated transcriptional regulatory network, which revealed that the small MAF transcription factors are master regulators of the VEGFA transcriptional program and angiogenesis. Collectively these results revealed that extracellular stimuli rapidly reconfigure the chromatin landscape to coordinately regulate biological responses., (© 2019 Wang et al.; Published by Cold Spring Harbor Laboratory Press.)