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We used video playback of courting maleSchizocosa ocreatawolf spiders to examine responses of intended receivers (conspecific females) and eavesdroppers (competitor males, predatory spiders, toads) to manipulations of spider color (natural color, monochromatic gray, monochromatic RBG average) displayed against complex leaf litter backgrounds (color, grayscale). Models of chromatic and achromatic contrast between spider stimuli and backgrounds were used to predict receiver responses. The results support the hypothesis that interactions between spider and background coloration affect detection and recognition, although responses varied with receiver type. Detection responses of intended receivers (femaleS. ocreata) did not fit predictions of the chromatic contrast model in some cases, but showed a fair fit to the achromatic model. Detection responses of social eavesdroppers (maleS. ocreata) fit the chromatic and achromatic contrast models slightly better than did female responses (poor fit and very good fit, respectively). Eavesdropping wolf spider predators (Rabidosa) exhibited detection responses that significantly matched predictions of the chromatic (very good fit) and achromatic (excellent fit) models. Whereas jumping spiders (Phidippus) showed a good fit to the chromatic and achromatic contrast models, toad predators had a good fit only to the chromatic model. Recognition responses revealed a different pattern of fit to the chromatic and achromatic models across receiver types, althoughRabidosaagain indicated a significant fit to both models. Taken together, the results of this study identify both chromatic and achromatic features of spider appearance as likely explanations for differences in behavioral responses of intended and unintended receivers. This outcome suggests the possibility that both sexual and natural selection likely target different features of male appearance during courtship.

 

The transfer of DNA among distantly related organisms is relatively common in bacteria but less prevalent in eukaryotes. Among fungi and plants, few of these events have been reported. Two segments of fungal mitochondrial DNA have been recently discovered in the mitogenome of orchids. Here, we build on that work to understand the timing of those transfer events, which orchids retain the fungal DNA and the fate of the foreign DNA during orchid evolution. We update the content of the large DNA fragment and establish that it was transferred to the most recent common ancestor of a highly diverse clade of epidendroid orchids that lived ~28–43 Mya. Also, we present hypotheses of the origin of the small transferred fragment. Our findings deepen the knowledge of these interesting DNA transfers among organelles and we formulate a probable mechanism for these horizontal gene transfer events.

 

ABSTRACT The goal of this article is to offer framing for conversations about the role of measurement in informing public policy about the Internet. We review different stakeholders’ approaches to measurements and associated challenges, including the activities of U.S. government agencies. We show how taxonomies of existing harms can facilitate the search for clarity along the fraught path from identifying to measuring harms. Looking forward, we identify barriers to advancing our empirical grounding of Internet infrastructure to inform policy, societal challenges that create pressure to overcome these barriers, and steps that could facilitate measurement to support policymaking. 

Information leaks in software can unintentionally reveal private data, yet they are hard to detect and fix. Although several methods have been proposed to detect leakage, such as static verification-based approaches, they require specialist knowledge, and are time-consuming. Recently, we introduced HyperGI, a dynamic, hypertest-based approach that can detect and produce potential fixes for hyperproperty violations. In particular, we focused on violations of the noninterference property, as it results in information flow leakage. Our instantiation of HyperGI was able to detect and reduce leakage in three small programs. Its fitness function tried to balance information leakage and program correctness but, as we pointed out, there may be tradeoffs between keeping program semantics and reducing information leakage that require developer decisions. In this work we ask if it is possible to automatically detect and repair information leakage in more realistic programs without requiring specialist knowledge. We instantiate a multi-objective version of HyperGI in a tool, called LeakReducer, which explicitly encodes the tradeoff between program correctness and information leakage. We apply LeakReducer to six leaky programs, including the well-known Heartbleed bug. LeakReducer is able to detect leakage in all, in contrast to state-of-the-art fuzzers, detecting leakage in only two programs. Moreover, LeakReducer is able to reduce leakage in all subjects, with comparable results to previous work, while scaling to much larger software. 

Extreme climatic events (ECEs) such as hurricanes have been hypothesized to be a major driving force of natural selection. Recent studies argue that, following strong hurricane disturbance, Anolis lizards in the Caribbean undergo selection for traits such as longer forelimbs or smaller body sizes that improve their clinging ability to their substrates increasing their chances of surviving hurricane wind gusts. Some authors challenge the generalization of this hypothesis arguing that other mechanisms may explain these phenotypic changes or that they may not necessarily be generalizable across systems. To address this issue, we compared body size and relative forelimb length of Anolis gundlachi , a trunk–ground anole living in closed-canopy forests in Puerto Rico, before, four months after, and 15 months after Hurricanes Irma and Maria in 2017. Overall, our results show no clear evidence of a temporal decrease in body size or increase forelimb length (relative to body size) challenging the generalizability of the clinging ability hypothesis. Understanding how animals adapt to ECE is an emerging field. Still, we are quickly learning that this process is complex and nuanced. 

Crawling insects, when starved, tend to have fewer head wavings and travel in straighter tracks in search of food. We used theDrosophila melanogasterlarva to investigate whether this flexibility in the insect’s navigation strategy arises during early olfactory processing and, if so, how. We demonstrate a critical role for Keystone-LN, an inhibitory local neuron in the antennal lobe, in implementing head-sweep behavior. Keystone-LN responds to odor stimuli, and its inhibitory output is required for a larva to successfully navigate attractive and aversive odor gradients. We show that insulin signaling in Keystone-LN likely mediates the starvation-dependent changes in head-sweep magnitude, shaping the larva’s odor-guided movement. Our findings demonstrate how flexibility in an insect’s navigation strategy can arise from context-dependent modulation of inhibitory neurons in an early sensory processing center. They raise new questions about modulating a circuit’s inhibitory output to implement changes in a goal-directed movement.

 

We investigate a novel approach to the use of jitter to infer network congestion using data collected by probes in access networks. We discovered a set of features in jitter and jitter dispersion —a jitter-derived time series we define in this paper—time series that are characteristic of periods of congestion. We leverage these concepts to create a jitter-based congestion inference framework that we call Jitterbug. We apply Jitterbug’s capabilities to a wide range of traffic scenarios and discover that Jitterbug can correctly identify both recurrent and one-off congestion events. We validate Jitterbug inferences against state-of-the-art autocorrelation-based inferences of recurrent congestion. We find that the two approaches have strong congruity in their inferences, but Jitterbug holds promise for detecting one-off as well as recurrent congestion. We identify several future directions for this research including leveraging ML/AI techniques to optimize performance and accuracy of this approach in operational settings. 

Parasites exploit hosts to replicate and transmit, but overexploitation kills both host and parasite. Predators may shift this cost–benefit balance by consuming infected hosts or changing host behaviour, but the strength of these effects remains unclear. Here we use field and lab data on Trinidadian guppies and their Gyrodactylus spp. parasites to show how differential predation pressure influences parasite virulence and transmission. We use an experimentally demonstrated virulence–transmission trade-off to parametrize a mathematical model in which host shoaling (as a means of anti-predator defence), increases contact rates and selects for higher virulence. Then we validate model predictions by collecting parasites from wild, Trinidadian populations; parasites from high-predation populations were more virulent in common gardens than those from low-predation populations. Broadly, our results indicate that reduced social contact selects against parasite virulence.