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Species interactions have long been predicted to increase in intensity toward the tropics and low elevations because of gradients in climate, productivity, or biodiversity. Despite their importance for understanding global ecological and evolutionary processes, plant-animal interaction gradients are particularly difficult to test systematically across large geographic gradients, and evidence from smaller, disparate studies is inconclusive. By systematically measuring postdispersal seed predation using 6995 standardized seed depots along 18 mountains in the Pacific cordillera, we found that seed predation increases by 17% from the Arctic to the Equator and by 17% from 4000 meters above sea level to sea level. Clines in total predation, likely driven by invertebrates, were consistent across treeline ecotones and within continuous forest and were better explained by climate seasonality than by productivity, biodiversity, or latitude. These results suggest that species interactions play predictably greater ecological and evolutionary roles in tropical, lowland, and other less seasonal ecosystems.
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Periodicities in the Daily Proton Fluxes from 2011 to 2019 Measured by the Alpha Magnetic Spectrometer on the International Space Station from 1 to 100 GV
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A<sc>bstract</sc> In AdS/CFT, observables on the boundary are invariant under renormalization group (RG) flow in the bulk. In this paper, we study holographic entanglement entropy under bulk RG flow and find that it is indeed invariant. We focus on tree-level RG flow, where massive fields in a UV theory are integrated out to give the IR theory. We explicitly show that in several simple examples, holographic entanglement entropy calculated in the UV theory agrees with that calculated in the IR theory. Moreover, we give an argument for this agreement to hold for general tree-level RG flow. Along the way, we generalize the replica method of calculating holographic entanglement entropy to bulk theories that include matter fields with nonzero spin.more » « less
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Hardware faults are a known source of security vulnerabilities. Fault injection in secure embedded systems leads to information leakage and privilege escalation, and countless fault attacks have been demonstrated both in simulation and in practice. However, there is a significant gap between simulated fault attacks and physical fault attacks. Simulations use idealized fault models such as single-bit flips with uniform distribution. These ideal fault models may not hold in practice. On the other hand, practical experiments lack the white-box visibility necessary to determine the true nature of the fault, leading to probabilistic vulnerability assessments and unexplained results. In embedded software, this problem is further exacerbated by the layered abstractions between the hardware (where the fault originates) and the application software (where the fault effect is observed). We present FaultDetective, a method to investigate the root-cause of fault injection from fault detection in software. Our main insight is that fault detection in software is only the end-point of a chain of events that starts with a fault manifestation in hardware and propagates through the micro-architecture and architecture before reaching the software level. To understand the fault effects at the hardware level, we use a scan chain, a low-level hardware test structure. We then use white-box simulation to propagate and observe hardware faults in the embedded software. We efficiently visualize the fault propagation across abstraction levels using a hash-tree representation of the scan chain. We implement this concept in a multi-core MSP430 micro-controller that redundantly executes an application in lock-step. With this setup, we observe the fault effects for several different stressors, including clock glitching and thermal laser stimulation, and explain the root-cause in each case.more » « less
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Students often struggle with visualizing protein structures when working with two-dimensional textbook and lecture materials, so introducing them to 3D visualization software developed by and for structural biologists offers them a unique opportunity to work with authentic data while furthering their spatial reasoning skills and understanding of molecular structure and function. This article presents an active learning virtual laboratory in which students use authentic structural biology data to investigate the effects of both hypothetical and real-world SARS-CoV-2 mutations on the virus’s ability to bind to human ACE2 receptors and infect a host, causing COVID-19. Through this activity, introductory-level college students or advanced high school students gain a better understanding of applied biology, such as how vaccines and treatments are designed, as well as strengthening their understanding of core disciplinary concepts, such as the relationship between protein structure and function and the central dogma of molecular biology. While there were challenges during the pilot phase of activity development due to COVID-19 restrictions, students in the pilot groups came away from the activity with deeper understanding of the relationship between proteins and amino acid sequences and a new appreciation for the ways researchers design treatments for and study viruses.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1103/PhysRevLett.127.271102
