What FIREs up star formation: the emergence of the Kennicutt–Schmidt law from feedback

We present an analysis of the global and spatially resolved Kennicutt–Schmidt (KS) star formation relation in the FIRE (Feedback In Realistic Environments) suite of cosmological simulations, including haloes with z = 0 masses ranging from 10^(10) to 10^(13) M_⊙. We show that the KS relation emerges and is robustly maintained due to the effects of feedback on local scales regulating star-forming gas, independent of the particular small-scale star formation prescriptions employed. We demonstrate that the time-averaged KS relation is relatively independent of redshift and spatial averaging scale, and that the star formation rate surface density is weakly dependent on metallicity and inversely dependent on orbital dynamical time. At constant star formation rate surface density, the ‘cold and dense’ gas surface density (gas with T 10 cm^(−3), used as a proxy for the molecular gas surface density) of the simulated galaxies is ∼0.5 dex less than observed at ∼kpc scales. This discrepancy may arise from underestimates of the local column density at the particle-scale for the purposes of shielding in the simulations. Finally, we show that on scales larger than individual giant molecular clouds, the primary condition that determines whether star formation occurs is whether a patch of the galactic disc is thermally Toomre-unstable (not whether it is self-shielding): once a patch can no longer be thermally stabilized against fragmentation, it collapses, becomes self-shielding, cools, and forms stars, regardless of epoch or environment

The many faces of fear:A synthesis of methodological variation in characterizing predation risk from carnivores

Predators affect prey by killing them directly (lethal effects) and by inducing costly antipredator behaviours in living prey (risk effects). Risk effects can strongly influence prey populations and cascade through trophic systems. A prerequisite for assessing risk effects is characterizing the spatiotemporal variation in predation risk. Risk effects research has experienced rapid growth in the last several decades. However, preliminary assessments of the resultant literature suggest that researchers characterize predation risk using a variety of techniques. The implications of this methodological variation for inference and comparability among studies have not been well recognized or formally synthesized. We couple a literature survey with a hierarchical framework, developed from established theory, to quantify the methodological variation in characterizing risk using carnivore-ungulate systems as a case study. Via this process, we documented 244 metrics of risk from 141 studies falling into at least 13 distinct subcategories within three broader categories. Both empirical and theoretical work suggest risk and its effects on prey constitute a complex, multi-dimensional process with expressions varying by spatiotemporal scale. Our survey suggests this multi-scale complexity is reflected in the literature as a whole but often underappreciated in any given study, which complicates comparability among studies and leads to an overemphasis on documenting the presence of risk effects rather than their mechanisms or scale of influence. We suggest risk metrics be placed in a more concrete conceptual framework to clarify inference surrounding risk effects and their cascading effects throughout ecosystems. We recommend studies (i) take a multi-scale approach to characterizing risk; (ii) explicitly consider 'true' predation risk (probability of predation per unit time); and (iii) use risk metrics that facilitate comparison among studies and the evaluation of multiple competing hypotheses. Addressing the pressing questions in risk effects research, including how, to what extent and on what scale they occur, requires leveraging the advantages of the many methods available to characterize risk while minimizing the confusion caused by variability in their application.The NSF Graduate Research Fellowship Program (RJM), the Michigan State University MasterCard Foundation Scholars Program (ABM), CNPq-Brasil (LA), and the University of Montana Boone and Crockett Program (JJM).http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-26562018-07-30cs2017Centre for Wildlife Managemen

Collage 2018

The KSU School of Music is proud to present the 12th Annual Collage Concert. An exciting highlight each season, Collage is the signature production of the School of Music and a major fundraising event for supporting scholarships for music students. This special performance features over 200 student and faculty performers and includes jazz, orchestra, choir, band, percussion, and opera selections for soloists, chamber groups, and ensembles. Special lighting effects and stage design combine with the diverse and exciting program presented as rapid-fire, flowing vignettes to create a truly unique performance.https://digitalcommons.kennesaw.edu/musicprograms/2021/thumbnail.jp

What FIREs up star formation: the emergence of the Kennicutt–Schmidt law from feedback

We present an analysis of the global and spatially resolved Kennicutt–Schmidt (KS) star formation relation in the FIRE (Feedback In Realistic Environments) suite of cosmological simulations, including haloes with z = 0 masses ranging from 10^(10) to 10^(13) M_⊙. We show that the KS relation emerges and is robustly maintained due to the effects of feedback on local scales regulating star-forming gas, independent of the particular small-scale star formation prescriptions employed. We demonstrate that the time-averaged KS relation is relatively independent of redshift and spatial averaging scale, and that the star formation rate surface density is weakly dependent on metallicity and inversely dependent on orbital dynamical time. At constant star formation rate surface density, the ‘cold and dense’ gas surface density (gas with T 10 cm^(−3), used as a proxy for the molecular gas surface density) of the simulated galaxies is ∼0.5 dex less than observed at ∼kpc scales. This discrepancy may arise from underestimates of the local column density at the particle-scale for the purposes of shielding in the simulations. Finally, we show that on scales larger than individual giant molecular clouds, the primary condition that determines whether star formation occurs is whether a patch of the galactic disc is thermally Toomre-unstable (not whether it is self-shielding): once a patch can no longer be thermally stabilized against fragmentation, it collapses, becomes self-shielding, cools, and forms stars, regardless of epoch or environment

Dimensional control and morphological transformations of supramolecular polymeric nanofibers based on cofacially-stacked planar amphiphilic platinum(II) complexes

Square-planar platinum­(II) complexes often stack cofacially to yield supramolecular fiber-like structures with interesting photophysical properties. However, control over fiber dimensions and the resulting colloidal stability is limited. We report the self-assembly of amphiphilic Pt­(II) complexes with solubilizing ancillary ligands based on polyethylene glycol [PEG_<i>n</i>, where <i>n</i> = 16, 12, 7]. The complex with the longest solubilizing PEG ligand, <b>Pt-PEG</b>_<b>16</b>, self-assembled to form polydisperse one-dimensional (1D) nanofibers (diameters <5 nm). Sonication led to short seeds which, on addition of further molecularly dissolved <b>Pt-PEG</b>_<b>16</b> complex, underwent elongation in a “living supramolecular polymerization” process to yield relatively uniform fibers of length up to <i>ca</i>. 400 nm. The fiber lengths were dependent on the <b>Pt-PEG</b>_<b>16</b> complex to seed mass ratio in a manner analogous to a living covalent polymerization of molecular monomers. Moreover, the fiber lengths were unchanged in solution after 1 week and were therefore “static” with respect to interfiber exchange processes on this time scale. In contrast, similarly formed near-uniform fibers of <b>Pt-PEG</b>_<b>12</b> exhibited dynamic behavior that led to broadening of the length distribution within 48 h. After aging for 4 weeks in solution, <b>Pt-PEG</b>_<b>12</b> fibers partially evolved into 2D platelets. Furthermore, self-assembly of <b>Pt-PEG</b>_<b>7</b> yielded only transient fibers which rapidly evolved into 2D platelets. On addition of further fiber-forming Pt complex (<b>Pt-PEG</b>_<b>16</b>), the platelets formed assemblies <i>via</i> the growth of fibers selectively from their short edges. Our studies demonstrate that when interfiber dynamic exchange is suppressed, dimensional control and hierarchical structure formation are possible for supramolecular polymers through the use of kinetically controlled seeded growth methods

Refining epigenetic prediction of chronological and biological age

Background Epigenetic clocks can track both chronological age (cAge) and biological age (bAge). The latter is typically defined by physiological biomarkers and risk of adverse health outcomes, including all-cause mortality. As cohort sample sizes increase, estimates of cAge and bAge become more precise. Here, we aim to develop accurate epigenetic predictors of cAge and bAge, whilst improving our understanding of their epigenomic architecture. Methods First, we perform large-scale (N = 18,413) epigenome-wide association studies (EWAS) of chronological age and all-cause mortality. Next, to create a cAge predictor, we use methylation data from 24,674 participants from the Generation Scotland study, the Lothian Birth Cohorts (LBC) of 1921 and 1936, and 8 other cohorts with publicly available data. In addition, we train a predictor of time to all-cause mortality as a proxy for bAge using the Generation Scotland cohort (1214 observed deaths). For this purpose, we use epigenetic surrogates (EpiScores) for 109 plasma proteins and the 8 component parts of GrimAge, one of the current best epigenetic predictors of survival. We test this bAge predictor in four external cohorts (LBC1921, LBC1936, the Framingham Heart Study and the Women’s Health Initiative study). Results Through the inclusion of linear and non-linear age-CpG associations from the EWAS, feature pre-selection in advance of elastic net regression, and a leave-one-cohort-out (LOCO) cross-validation framework, we obtain cAge prediction with a median absolute error equal to 2.3 years. Our bAge predictor was found to slightly outperform GrimAge in terms of the strength of its association to survival (HRGrimAge = 1.47 [1.40, 1.54] with p = 1.08 × 10−52, and HRbAge = 1.52 [1.44, 1.59] with p = 2.20 × 10−60). Finally, we introduce MethylBrowsR, an online tool to visualise epigenome-wide CpG-age associations. Conclusions The integration of multiple large datasets, EpiScores, non-linear DNAm effects, and new approaches to feature selection has facilitated improvements to the blood-based epigenetic prediction of biological and chronological age