ASU Scholarship Showcase

In situ multianvil press (MAP) studies have reported that the depth and the Clapeyron slope of the postspinel boundary are significantly less than those of the 660 km discontinuity inferred from seismic studies. These results have raised questions about whether the postspinel transition is associated with the discontinuity. We determined the postspinel transition in pyrolitic compositions in the laser-heated diamond anvil cell (LHDAC) combined with in situ synchrotron X-ray diffraction. The Clapeyron slope was determined to be −2.5 ± 0.4MPa/K and did not vary significantly with compositions and used pressure scales. Using Pt scales, our data indicate that the postspinel transition occurs in pyrolitic compositions at 23.6–24.5GPa (1850K). The transition pressure and slope are consistent with the depth and topography of the 660 km discontinuity. Our data reveal that inaccuracy in pressure scales alone cannot explain the discrepancy and technical differences between MAP and LHDAC contribute significantly to the discrepancy.

Consider tuples (K₁,…,K_r) of separable algebras over a common local or global number field F F, with the K_i related to each other by specified resolvent constructions. Under the assumption that all ramification is tame, simple group-theoretic calculations give best possible divisibility relations among the discriminants of K_i∕F. We show that for many resolvent constructions, these divisibility relations continue to hold even in the presence of wild ramification.

Nonuniform Fourier data are routinely collected in applications such as magnetic resonance imaging, synthetic aperture radar, and synthetic imaging in radio astronomy. To acquire a fast reconstruction that does not require an online inverse process, the nonuniform fast Fourier transform (NFFT), also called convolutional gridding, is frequently employed. While various investigations have led to improvements in accuracy, efficiency, and robustness of the NFFT, not much attention has been paid to the fundamental analysis of the scheme, and in particular its convergence properties. This paper analyzes the convergence of the NFFT by casting it as a Fourier frame approximation. In so doing, we are able to design parameters for the method that satisfy conditions for numerical convergence. Our so-called frame theoretic convolutional gridding algorithm can also be applied to detect features (such as edges) from nonuniform Fourier samples of piecewise smooth functions.

A globally integrated carbon observation and analysis system is needed to improve the fundamental understanding of the global carbon cycle, to improve our ability to project future changes, and to verify the effectiveness of policies aiming to reduce greenhouse gas emissions and increase carbon sequestration. Building an integrated carbon observation system requires transformational advances from the existing sparse, exploratory framework towards a dense, robust, and sustained system in all components: anthropogenic emissions, the atmosphere, the ocean, and the terrestrial biosphere. The paper is addressed to scientists, policymakers, and funding agencies who need to have a global picture of the current state of the (diverse) carbon observations.

We identify the current state of carbon observations, and the needs and notional requirements for a global integrated carbon observation system that can be built in the next decade. A key conclusion is the substantial expansion of the ground-based observation networks required to reach the high spatial resolution for CO₂ and CH₄ fluxes, and for carbon stocks for addressing policy-relevant objectives, and attributing flux changes to underlying processes in each region. In order to establish flux and stock diagnostics over areas such as the southern oceans, tropical forests, and the Arctic, in situ observations will have to be complemented with remote-sensing measurements. Remote sensing offers the advantage of dense spatial coverage and frequent revisit. A key challenge is to bring remote-sensing measurements to a level of long-term consistency and accuracy so that they can be efficiently combined in models to reduce uncertainties, in synergy with ground-based data.

Bringing tight observational constraints on fossil fuel and land use change emissions will be the biggest challenge for deployment of a policy-relevant integrated carbon observation system. This will require in situ and remotely sensed data at much higher resolution and density than currently achieved for natural fluxes, although over a small land area (cities, industrial sites, power plants), as well as the inclusion of fossil fuel CO₂ proxy measurements such as radiocarbon in CO₂ and carbon-fuel combustion tracers. Additionally, a policy-relevant carbon monitoring system should also provide mechanisms for reconciling regional top-down (atmosphere-based) and bottom-up (surface-based) flux estimates across the range of spatial and temporal scales relevant to mitigation policies. In addition, uncertainties for each observation data-stream should be assessed. The success of the system will rely on long-term commitments to monitoring, on improved international collaboration to fill gaps in the current observations, on sustained efforts to improve access to the different data streams and make databases interoperable, and on the calibration of each component of the system to agreed-upon international scales.

Altered thermal regimes under climate change may influence host-parasite interactions and invasive species, both potentially impacting valuable ecosystem services. There is considerable interest in how parasite life cycle rates, growth, and impacts on hosts will change under altered environmental temperatures. Likewise, transformed thermal regimes may reduce natural resistance and barriers preventing establishment of invasive species or alter the range and impacts of established exotic species. The Laurentian Great Lakes are some of the most invaded ecosystems and have been profoundly shaped by exotic species. Invasion by the parasitic sea lamprey (Petromyzon marinus) contributed to major declines in many Great Lakes fish populations. In Lake Superior, substantial progress has been made towards controlling invasive sea lamprey and rehabilitating native fish populations. Surface water temperatures in Lake Superior have been increasing rapidly since 1980 presenting a new challenge for management.

Here we test how thermal changes in Lake Superior have impacted the feeding and growth of the parasitic sea lamprey. Sea lamprey have increased in size corresponding with longer durations of thermal habitat (i.e., longer growing seasons) for their preferred hosts. To compare regional differences in sea lamprey feeding and growth rates, we used a bioenergetics model with temperature estimates from a lake-wide hydrodynamic model hindcast from 1979–2006. Spatial differences in patterns of warming across the lake result in regionally different predictions for increases in sea lamprey feeding rates and size. These predictions were matched by data from adult sea lamprey spawning in streams draining into these different thermal regions. Larger sea lampreys will be more fecund and have increased feeding rates, thus increasing mortality among host fishes. Resource management should consider these climate driven regional impacts when allocating resources to sea lamprey control efforts. Under new and evolving thermal regimes, successful management systems may need to be restructured for changing phenology, growth, and shifts in host-parasite systems towards greater impacts on host populations.

Cyber-taxonomy of name usage has focused primarily on producing authoritative lists of names or cross-linking names and data across disparate databases. A feature missing from much of this work is the recording and analysis of the context in which a name was used—context which can be critical for understanding not only what name an author used, but to which currently recognized species they actually refer. An experiment on recording contextual information associated with name usage was conducted for the fiddler crabs (genus Uca). Data from approximately one quarter of all publications that mention fiddler crabs, including 95% of those published prior to 1924 and 67% of those published prior to 1976, have currently been recorded in a database. Approaches and difficulties in recording and analyzing the context of name use are discussed. These results are not meant to be a full solution, rather to highlight problems which have not been previously investigated and may act as a springboard for broader approaches and discussion. Some data on the accessibility of the literature, including in particular electronic forms of publication, are also presented. The resulting data has been integrated for general browsing into the website http://www.fiddlercrab.info; the raw data and code used to construct the website is available at https://github.com/msrosenberg/fiddlercrab.info.

Background: Comorbidity among childhood mental health symptoms is common in clinical and community samples and should be accounted for when investigating etiology. We therefore aimed to uncover latent classes of mental health symptoms in middle childhood in a community sample, and to determine the latent genetic and environmental influences on those classes.

Methods: The sample comprised representative cohorts of twins. A questionnaire-based assessment of mental health symptoms was used in latent class analyses. Data on 3223 twins (1578 boys and 1645 girls) with a mean age of 7.5 years were analyzed. The sample was predominantly non-Hispanic Caucasian (92.1%).

Results: Latent class models delineated groups of children according to symptom profiles–not necessarily clinical groups but groups representing the general population, most with scores in the normative range. The best-fitting models suggested 9 classes for both girls and boys. Eight of the classes were very similar across sexes; these classes ranged from a ‘‘Low Symptom’’ class to a ‘‘Moderately Internalizing & Severely Externalizing’’ class. In addition, a ‘‘Moderately Anxious’’ class was identified for girls but not boys, and a ‘‘Severely Impulsive & Inattentive’’ class was identified for boys but not girls. Sex-combined analyses implicated moderate genetic influences for all classes. Shared environmental influences were moderate for the ‘‘Low Symptom’’ and ‘‘Moderately Internalizing & Severely Externalizing’’ classes, and small to zero for other classes.

Conclusions: We conclude that symptom classes are largely similar across sexes in middle childhood. Heritability was moderate for all classes, but shared environment played a greater role for classes in which no one type of symptom predominated.

The best-response dynamics is an example of an evolutionary game where players update their strategy in order to maximize their payoff. The main objective of this paper is to study a stochastic spatial version of this game based on the framework of interacting particle systems in which players are located on an infinite square lattice. In the presence of two strategies, and calling a strategy selfish or altruistic depending on a certain ordering of the coefficients of the underlying payoff matrix, a simple analysis of the nonspatial mean-field approximation of the spatial model shows that a strategy is evolutionary stable if and only if it is selfish, making the system bistable when both strategies are selfish. The spatial and nonspatial models agree when at least one strategy is altruistic. In contrast, we prove that in the presence of two selfish strategies and in any spatial dimension, only the most selfish strategy remains evolutionary stable. The main ingredients of the proof are monotonicity results and a coupling between the best-response dynamics properly rescaled in space with bootstrap percolation to compare the infinite time limits of both systems.

Vision and Change in Undergraduate Biology Education outlined five core concepts intended to guide undergraduate biology education: 1) evolution; 2) structure and function; 3) information flow, exchange, and storage; 4) pathways and transformations of energy and matter; and 5) systems. We have taken these general recommendations and created a Vision and Change BioCore Guide—a set of general principles and specific statements that expand upon the core concepts, creating a framework that biology departments can use to align with the goals of Vision and Change. We used a grassroots approach to generate the BioCore Guide, beginning with faculty ideas as the basis for an iterative process that incorporated feedback from more than 240 biologists and biology educators at a diverse range of academic institutions throughout the United States. The final validation step in this process demonstrated strong national consensus, with more than 90% of respondents agreeing with the importance and scientific accuracy of the statements. It is our hope that the BioCore Guide will serve as an agent of change for biology departments as we move toward transforming undergraduate biology education.

A fundamental problem in computational biophysics is to deduce the function of a protein from the structure. Many biological macromolecules such as enzymes, molecular motors or membrane transport proteins perform their function by cycling between multiple conformational states. Understanding such conformational transitions, which typically occur on the millisecond to second time scale, is central to understanding protein function. Molecular dynamics (MD) computer simulations have become an important tool to connect molecular structure to function, but equilibrium MD simulations are rarely able to sample on time scales longer than a few microseconds – orders of magnitudes shorter than the time scales of interest. A range of different simulation methods have been proposed to overcome this time-scale limitation. These include calculations of the free energy landscape and path sampling methods to directly sample transitions between known conformations. All these methods solve the problem to sample infrequently occupied but important regions of configuration space. Many path-sampling algorithms have been applied to the closed – open transition of the enzyme adenylate kinase (AdK), which undergoes a large, clamshell-like conformational transition between an open and a closed state. Here we review approaches to sample macromolecular transitions through the lens of AdK. We focus our main discussion on the current state of knowledge – both from simulations and experiments – about the transition pathways of ligand-free AdK, its energy landscape, transition rates and interactions with substrates. We conclude with a comparison of the discussed approaches with a view towards quantitative evaluation of path-sampling methods.