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A major question in ecology is how often competing species evolve to reduce competitive interactions and facilitate coexistence. One untested route for a reduction in competitive interactions is through ontogenetic changes in the trophic niche of one or more of the interacting species. In such cases, theory predicts that two species can coexist if the weaker competitor changes its resource niche to a greater degree with increased body size than the superior competitor. We tested this prediction using stable isotopes that yield information about the trophic position (δ15 N) and carbon source (δ13 C) of two coexisting fish species: Trinidadian guppies (Poecilia reticulata) and killifish (Rivulus hartii). We examined fish from locations representing three natural community types: 1) where killifish and guppies live with predators; 2) where killifish and guppies live without predators; and 3) where killifish are the only fish species. We also examined killifish from communities in which we had introduced guppies, providing a temporal sequence of the community changes following the transition from a killifish only to a killifish-guppy community. We found that killifish, which are the weaker competitor, had a much larger ontogenetic niche shift in trophic position than guppies in the community where competition is most intense (killifish-guppy only). This result is consistent with theory for size-structured populations, which predicts that these results should lead to stable coexistence of the two species. Comparisons with other communities containing guppies, killifish and predators and ones where killifish live by themselves revealed that these results are caused primarily by a loss of ontogenetic niche changes in guppies, even though they are the stronger competitor. Comparisons of these natural communities with communities in which guppies were translocated into sites containing only killifish showed that the experimental communities were intermediate between the natural killifish-guppy community and the killifish-guppy-predator community, suggesting contemporary evolution in these ontogenetic trophic differences. These results provide comparative evidence for ontogenetic niche shifts in contributing to species coexistence and comparative and experimental evidence for evolutionary or plastic changes in ontogenetic niche shifts following the formation of new communities.

At Sandia National Laboratories, QSCOUT (the Quantum Scientific Computing Open User Testbed) is an ion-trap based quantum computer built for the purpose of allowing users low-level access to quantum hardware. Commands are executed on the hardware using Jaqal (Just Another Quantum Assembly Language), a programming language designed in-house to support the unique capabilities of QSCOUT. In this work, we describe a batching implementation of our custom software that speeds the experimental run-time through the reduction of communication and upload times. Reducing the code upload time during experimental runs improves system performance by mitigating the effects of drift. We demonstrate this implementation through a set of quantum chemistry experiments using a variational quantum eigensolver (VQE). While developed specifically for this testbed, this idea finds application across many similar experimental platforms that seek greater hardware control or reduced overhead., 6 pages, 3 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible

Scalable coherent control hardware for quantum information platforms is rapidly growing in priority as their number of available qubits continues to increase. As these systems scale, more calibration steps are needed, leading to challenges with system instability as calibrated parameters drift. Moreover, the sheer amount of data required to run circuits with large depth tends to balloon, especially when implementing state-of-the-art dynamical-decoupling gates which require advanced modulation techniques. We present a control system that addresses these challenges for trapped-ion systems, through a combination of novel features that eliminate the need for manual bookkeeping, reduction in data transfer bandwidth requirements via gate compression schemes, and other automated error handling techniques. Moreover, we describe an embedded pulse compiler that applies staged optimization, including compressed intermediate representations of parsed output products, performs in-situ mutation of compressed gate data to support high-level algorithmic feedback to account for drift, and can be run entirely on chip., Comment: 11 pages, 8 figures, submitted to IEEE International Conference on Quantum Computing and Engineering (QCE), 2022

The basal ganglia are an intricately connected assembly of subcortical nuclei, forming the core of an adaptive network connecting cortical and thalamic circuits. For nearly three decades, researchers and medical practitioners have conceptualized how the basal ganglia circuit works, and how its pathology underlies motor disorders such as Parkinson’s and Huntington’s diseases, using what is often referred to as the “box-and-arrow model”: a circuit diagram showing the broad strokes of basal ganglia connectivity and the pathological increases and decreases in the weights of specific connections that occur in disease. While this model still has great utility and has led to groundbreaking strategies to treat motor disorders, our evolving knowledge of basal ganglia function has made it clear that this classic model has several shortcomings that severely limit its predictive and descriptive abilities. In this review, we will focus on the striatum, the main input nucleus of the basal ganglia. We describe recent advances in our understanding of the rich microcircuitry and plastic capabilities of the striatum, factors not captured by the original box-and-arrow model, and provide examples of how such advances inform our current understanding of the circuit pathologies underlying motor disorders.

Soluble and insoluble Aβ1–42 (pg/mg protein). (DOC 28 kb)

Soluble and insoluble Aβ1–42 (pg/mg protein). (DOC 28 kb)

Pharmacokinetic and toxicology studies on CAD-31. (DOC 41 kb)

Pharmacokinetic and toxicology studies on CAD-31. (DOC 41 kb)