The Evolution of a Female Genital Trait Widely Distributed in the Lepidoptera: Comparative Evidence for an Effect of Sexual Coevolution

Sexual coevolution is considered responsible for the evolution of many male genital traits, but its effect on female genital morphology is poorly understood. In many lepidopterans, females become temporarily unreceptive after mating and the length of this refractory period is inversely related to the amount of spermatophore remaining in their genital tracts. Sperm competition can select for males that delay female remating by transferring spermatophores with thick spermatophore envelopes that take more time to be broken. These envelopes could select for signa, sclerotized sharp structures located within the female genital tract, that are used for breaking spermatophores. Thus, this hypothesis predicts that thick spermatophore envelopes and signa evolve in polyandrous species, and that these adaptations are lost when monandry evolves subsequently. Here we test the expected associations between female mating pattern and presence/absence of signa, and review the scant information available on the thickness of spermatophore envelopes.We made a literature review and found information on female mating pattern (monandry/polyandry), presence/absence of signa and phylogenetic position for 37 taxa. We built a phylogenetic supertree for these taxa, mapped both traits on it, and tested for the predicted association by using Pagel's test for correlated evolution. We found that, as predicted by our hypothesis, monandry evolved eight times and in five of them signa were lost; preliminary evidence suggests that at least in two of the three exceptions males imposed monandry on females by means of specially thick spermatophore envelopes. Previously published data on six genera of Papilionidae is in agreement with the predicted associations between mating pattern and the characteristics of spermatophore envelopes and signa.Our results support the hypothesis that signa are a product of sexually antagonistic coevolution with spermatophore envelopes

Vision Language Navigation with Knowledge-driven Environmental Dreamer

Vision-language navigation (VLN) requires an agent to perceive visual observation in a house scene and navigate step-by-step following natural language instruction. Due to the high cost of data annotation and data collection, current VLN datasets provide limited instruction-trajectory data samples. Learning vision-language alignment for VLN from limited data is challenging since visual observation and language instruction are both complex and diverse. Previous works only generate augmented data based on original scenes while failing to generate data samples from unseen scenes, which limits the generalization ability of the navigation agent. In this paper, we introduce the Knowledge-driven Environmental Dreamer (KED), a method that leverages the knowledge of the embodied environment and generates unseen scenes for a navigation agent to learn. Generating an unseen environment with texture consistency and structure consistency is challenging. To address this problem, we incorporate three knowledge-driven regularization objectives into the KED and adopt a reweighting mechanism for self-adaptive optimization. Our KED method is able to generate unseen embodied environments without extra annotations. We use KED to successfully generate 270 houses and 500K instruction-trajectory pairs. The navigation agent with the KED method outperforms the state-of-the-art methods on various VLN benchmarks, such as R2R, R4R, and RxR. Both qualitative and quantitative experiments prove that our proposed KED method is able to high-quality augmentation data with texture consistency and structure consistency