If at First You Do Not Succeed: Student Behavior When Provided Feedforward With Multiple Trials for Online Summative Assessments

Best practices suggest that timely, actionable feedback is provided with the option to apply the feedback. We used a learning management system to deliver assessments with automatic feedback provided at the conclusion of the assessment, allowing for multiple attempts in order to apply the knowledge gained. Questions were pooled so each attempt was unique, the highest score earned was awarded, with no penalty for failure to use multiple attempts. We found that students who did not earn an A on their first attempt were more likely to try again. Those that did tended to score better on their second attempt. This leads us to conclude that assessment design with multiple attempts that incorporates feedforward influences student behavior. Future work will include additional STEM general education courses in a broader study and a survey of student opinions regarding the utility of the feedback and the option for multiple attempts

Empirical constraints on the nucleosynthesis of nitrogen

We derive empirical constraints on the nucleosynthetic yields of nitrogen by incorporating N enrichment into our previously developed and empirically tuned multizone galactic chemical evolution model. We adopt a metallicity-independent (‘primary’) N yield from massive stars and a metallicity-dependent (‘secondary’) N yield from AGB stars. In our model, galactic radial zones do not evolve along the observed [N/O]–[O/H] relation, but first increase in [O/H] at roughly constant [N/O], then move upward in [N/O] via secondary N production. By t ≈ 5 Gyr, the model approaches an equilibrium [N/O]–[O/H] relation, which traces the radial oxygen gradient. Reproducing the [N/O]–[O/H] trend observed in extragalactic systems constrains the ratio of IMF-averaged N yields to the IMF-averaged O yield of core-collapse supernovae. We find good agreement if we adopt |$y_\text{N}^\text{CC}/y_\text{O}^\text{CC}=0.024$| and |$y_\text{N}^\text{AGB}/y_\text{O}^\text{CC} = 0.062(Z/Z_\odot)$|⁠. For the theoretical AGB yields we consider, simple stellar populations release half their N after only ∼250 Myr. Our model reproduces the [N/O]–[O/H] relation found for Milky Way stars in the APOGEE survey, and it reproduces (though imperfectly) the trends of stellar [N/O] with age and [O/Fe]. The metallicity-dependent yield plays the dominant role in shaping the gas-phase [N/O]–[O/H] relation, but the AGB time-delay is required to match the stellar age and [O/Fe] trends. If we add ∼40 per cent oscillations to the star formation rate, the model reproduces the scatter in the gas phase [N/O]–[O/H] relation observed in external galaxies by MaNGA. We discuss implications of our results for theoretical models of N production by massive stars and AGB stars

Nucleosynthesis signatures of neutrino-driven winds from proto-neutron stars: a perspective from chemical evolution models

We test the hypothesis that the observed first-peak (Sr, Y, Zr) and second-peak (Ba) s-process elemental abundances in low-metallicity Milky Way stars, and the abundances of the elements Mo and Ru, can be explained by a pervasive r-process contribution originating in neutrino-driven winds from highly-magnetic and rapidly rotating proto-neutron stars (proto-NSs). We construct chemical evolution models that incorporate recent calculations of proto-NS yields in addition to contributions from AGB stars, Type Ia supernovae, and two alternative sets of yields for massive star winds and core-collapse supernovae. For non-rotating massive star yields from either set, models without proto-NS winds underpredict the observed s-process peak abundances by $0.3$-$1\,\text{dex}$ at low metallicity, and they severely underpredict Mo and Ru at all metallicities. Models incorporating wind yields from proto-NSs with spin periods $P \sim 2$-$5\,\text{ms}$ fit the observed trends for all these elements well. Alternatively, models omitting proto-NS winds but adopting yields of rapidly rotating massive stars, with $v_{\rm rot}$ between $150$ and $300\,\text{km}\,\text{s}^{-1}$, can explain the observed abundance levels reasonably well for $\text{[Fe/H]}<-2$. These models overpredict [Sr/Fe] and [Mo/Fe] at higher metallicities, but with a tuned dependence of $v_{\rm rot}$ on stellar metallicity they might achieve an acceptable fit at all [Fe/H]. If many proto-NSs are born with strong magnetic fields and short spin periods, then their neutrino-driven winds provide a natural source for Sr, Y, Zr, Mo, Ru, and Ba in low-metallicity stellar populations. Conversely, spherical winds from unmagnetized proto-NSs overproduce the observed Sr, Y, and Zr abundances by a large factor.Comment: Accepted for publication in MNRA

Untangling the Sources of Abundance Dispersion in Low-metallicity Stars

We measure abundances of 12 elements (Na, Mg, Si, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni) in a sample of 86 metal-poor (−2 ≲ [Fe/H] ≲ −1) subgiant stars in the solar neighborhood. Abundances are derived from high-resolution spectra taken with the Potsdam Echelle Polarimetric and Spectroscopic Instrument on the Large Binocular Telescope, modeled using iSpec and MOOG. By carefully quantifying the impact of photon-noise (&lt;0.05 dex for all elements), we robustly measure the intrinsic scatter of abundance ratios. At fixed [Fe/H], the rms intrinsic scatter in [X/Fe] ranges from 0.04 (Cr) to 0.16 dex (Na), with a median of 0.08 dex. Scatter in [X/Mg] is similar, and accounting for [α/Fe] only reduces the overall scatter moderately. We consider several possible origins of the intrinsic scatter with particular attention to fluctuations in the relative enrichment by core-collapse supernovae (CCSN) and Type Ia supernovae and stochastic sampling of the CCSN progenitor mass distribution. The stochastic sampling scenario provides a good quantitative explanation of our data if the effective number of CCSN contributing to the enrichment of a typical sample star is N ∼ 50. At the median metallicity of our sample, this interpretation implies that the CCSN ejecta are mixed over a gas mass ∼6 × 104 M ⊙ before forming stars. The scatter of elemental abundance ratios is a powerful diagnostic test for simulations of star formation, feedback, and gas mixing in the early phases of the Galaxy

Stellar migration and chemical enrichment in the milky way disc: a hybrid model

We develop a hybrid model of galactic chemical evolution that combines a multiring computation of chemical enrichment with a prescription for stellar migration and the vertical distribution of stellar populations informed by a cosmological hydrodynamic disc galaxy simulation. Our fiducial model adopts empirically motivated forms of the star formation law and star formation history, with a gradient in outflow mass loading tuned to reproduce the observed metallicity gradient. With this approach, the model reproduces many of the striking qualitative features of the Milky Way disc’s abundance structure: (i) the dependence of the [O/Fe]–[Fe/H] distribution on radius Rgal and mid-plane distance |z|; (ii) the changing shapes of the [O/H] and [Fe/H] distributions with Rgal and |z|; (iii) a broad distribution of [O/Fe] at sub-solar metallicity and changes in the [O/Fe] distribution with Rgal, |z|, and [Fe/H]; (iv) a tight correlation between [O/Fe] and stellar age for [O/Fe] > 0.1; (v) a population of young and intermediate-age α-enhanced stars caused by migration-induced variability in the Type Ia supernova rate; (vi) non-monotonic age–[O/H] and age–[Fe/H] relations, with large scatter and a median age of ∼4 Gyr near solar metallicity. Observationally motivated models with an enhanced star formation rate ∼2 Gyr ago improve agreement with the observed age–[Fe/H] and age–[O/H] relations, but worsen agreement with the observed age–[O/Fe] relation. None of our models predict an [O/Fe] distribution with the distinct bimodality seen in the observations, suggesting that more dramatic evolutionary pathways are required. All code and tables used for our models are publicly available through the Versatile Integrator for Chemical Evolution (VICE; https://pypi.org/project/vice)

Berkeley Supernova Ia Program I: Observations, Data Reduction, and Spectroscopic Sample of 582 Low-Redshift Type Ia Supernovae

In this first paper in a series we present 1298 low-redshift (z\leq0.2) optical spectra of 582 Type Ia supernovae (SNe Ia) observed from 1989 through 2008 as part of the Berkeley SN Ia Program (BSNIP). 584 spectra of 199 SNe Ia have well-calibrated light curves with measured distance moduli, and many of the spectra have been corrected for host-galaxy contamination. Most of the data were obtained using the Kast double spectrograph mounted on the Shane 3 m telescope at Lick Observatory and have a typical wavelength range of 3300-10,400 Ang., roughly twice as wide as spectra from most previously published datasets. We present our observing and reduction procedures, and we describe the resulting SN Database (SNDB), which will be an online, public, searchable database containing all of our fully reduced spectra and companion photometry. In addition, we discuss our spectral classification scheme (using the SuperNova IDentification code, SNID; Blondin & Tonry 2007), utilising our newly constructed set of SNID spectral templates. These templates allow us to accurately classify our entire dataset, and by doing so we are able to reclassify a handful of objects as bona fide SNe Ia and a few other objects as members of some of the peculiar SN Ia subtypes. In fact, our dataset includes spectra of nearly 90 spectroscopically peculiar SNe Ia. We also present spectroscopic host-galaxy redshifts of some SNe Ia where these values were previously unknown. [Abridged]Comment: 34 pages, 11 figures, 11 tables, revised version, re-submitted to MNRAS. Spectra will be released in January 2013. The SN Database homepage (http://hercules.berkeley.edu/database/index_public.html) contains the full tables, plots of all spectra, and our new SNID template

Exploring the impact of selection bias in observational studies of COVID-19: a simulation study

BACKGROUND: Non-random selection of analytic subsamples could introduce selection bias in observational studies. We explored the potential presence and impact of selection in studies of SARS-CoV-2 infection and COVID-19 prognosis. METHODS: We tested the association of a broad range of characteristics with selection into COVID-19 analytic subsamples in the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank (UKB). We then conducted empirical analyses and simulations to explore the potential presence, direction and magnitude of bias due to this selection (relative to our defined UK-based adult target populations) when estimating the association of body mass index (BMI) with SARS-CoV-2 infection and death-with-COVID-19. RESULTS: In both cohorts, a broad range of characteristics was related to selection, sometimes in opposite directions (e.g. more-educated people were more likely to have data on SARS-CoV-2 infection in ALSPAC, but less likely in UKB). Higher BMI was associated with higher odds of SARS-CoV-2 infection and death-with-COVID-19. We found non-negligible bias in many simulated scenarios. CONCLUSIONS: Analyses using COVID-19 self-reported or national registry data may be biased due to selection. The magnitude and direction of this bias depend on the outcome definition, the true effect of the risk factor and the assumed selection mechanism; these are likely to differ between studies with different target populations. Bias due to sample selection is a key concern in COVID-19 research based on national registry data, especially as countries end free mass testing. The framework we have used can be applied by other researchers assessing the extent to which their results may be biased for their research question of interest

IL4Rα signaling abrogates hypoxic neutrophil survival and limits acute lung injury responses <i>in vivo</i>

Rationale: Acute respiratory distress syndrome is defined by the presence of systemic hypoxia and consequent on disordered neutrophilic inflammation. Local mechanisms limiting the duration and magnitude of this neutrophilic response remain poorly understood.  Objectives: To test the hypothesis that during acute lung inflammation tissue production of proresolution type 2 cytokines (IL-4 and IL-13) dampens the proinflammatory effects of hypoxia through suppression of HIF-1a (hypoxia-inducible factor-1a)mediated neutrophil adaptation, resulting in resolution of lung injury.  Methods: Neutrophil activation of IL4Ra (IL-4 receptor a) signaling pathways was explored ex vivo in human acute respiratory distress syndrome patient samples, in vitro after the culture of human peripheral blood neutrophils with recombinant IL-4 under conditions of hypoxia, and in vivo through the study of IL4Ra-deficient neutrophils in competitive chimera models and wild-type mice treated with IL-4.  Measurements and Main Results: IL-4 was elevated in human BAL from patients with acute respiratory distress syndrome, and its receptor was identified on patient blood neutrophils. Treatment of human neutrophils with IL-4 suppressed HIF-1a-dependent hypoxic survival and limited proinflammatory transcriptional responses. Increased neutrophil apoptosis in hypoxia, also observed with IL-13, required active STAT signaling, and was dependent on expression of the oxygen-sensing prolyl hydroxylase PHD2. In vivo, IL-4Ra-deficient neutrophils had a survival advantage within a hypoxic inflamed niche; in contrast, inflamed lung treatment with IL-4 accelerated resolution through increased neutrophil apoptosis.  Conclusions: We describe an important interaction whereby IL4Ra-dependent type 2 cytokine signaling can directly inhibit hypoxic neutrophil survival in tissues and promote resolution of neutrophil-mediated acute lung injury

Deficiency in origin licensing proteins impairs cilia formation: implications for the aetiology of meier-gorlin syndrome

Mutations in ORC1, ORC4, ORC6, CDT1, and CDC6, which encode proteins required for DNA replication origin licensing, cause Meier-Gorlin syndrome (MGS), a disorder conferring microcephaly, primordial dwarfism, underdeveloped ears, and skeletal abnormalities. Mutations in ATR, which also functions during replication, can cause Seckel syndrome, a clinically related disorder. These findings suggest that impaired DNA replication could underlie the developmental defects characteristic of these disorders. Here, we show that although origin licensing capacity is impaired in all patient cells with mutations in origin licensing component proteins, this does not correlate with the rate of progression through S phase. Thus, the replicative capacity in MGS patient cells does not correlate with clinical manifestation. However, ORC1-deficient cells from MGS patients and siRNA-mediated depletion of origin licensing proteins also have impaired centrosome and centriole copy number. As a novel and unexpected finding, we show that they also display a striking defect in the rate of formation of primary cilia. We demonstrate that this impacts sonic hedgehog signalling in ORC1-deficient primary fibroblasts. Additionally, reduced growth factor-dependent signaling via primary cilia affects the kinetics of cell cycle progression following cell cycle exit and re-entry, highlighting an unexpected mechanism whereby origin licensing components can influence cell cycle progression. Finally, using a cell-based model, we show that defects in cilia function impair chondroinduction. Our findings raise the possibility that a reduced efficiency in forming cilia could contribute to the clinical features of MGS, particularly the bone development abnormalities, and could provide a new dimension for considering developmental impacts of licensing deficiency