In order to maximize the utility of future studies of trilobite ontogeny, we propose a set of standard practices that relate to the collection, nomenclature, description, depiction, and interpretation of ontogenetic series inferred from articulated specimens belonging to individual species. In some cases, these suggestions may also apply to ontogenetic studies of other fossilized taxa.

Errors inherent in self-reported measures of energy intake (EI) are substantial and well documented, but correlates of misreporting remain unclear. Therefore, potential predictors of misreporting were examined. In Study One, fifty-nine individuals (BMI = 26·1 (sd 3·8) kg/m2, age = 42·7 (sd 13·6) years, females = 29) completed a 14-d stay in a residential feeding behaviour suite where eating behaviour was continuously monitored. In Study Two, 182 individuals (BMI = 25·7 (sd 3·9) kg/m2, age = 42·4 (sd 12·2) years, females = 96) completed two consecutive days in a residential feeding suite and five consecutive days at home. Misreporting was directly quantified by comparing covertly measured laboratory weighed intakes (LWI) with self-reported EI (weighed dietary record (WDR), 24-h recall, 7-d diet history, FFQ). Personal (age, sex and %body fat) and psychological traits (personality, social desirability, body image, intelligence quotient and eating behaviour) were used as predictors of misreporting. In Study One, those with lower psychoticism (P = 0·009), openness to experience (P = 0·006) and higher agreeableness (P = 0·038) reduced EI on days participants knew EI was being measured to a greater extent than on covert days. Isolated associations existed between personality traits (psychoticism and openness to experience), eating behaviour (emotional eating) and differences between the LWI and self-reported EI, but these were inconsistent between dietary assessment techniques and typically became non-significant after accounting for multiplicity of comparisons. In Study Two, sex was associated with differences between LWI and the WDR (P = 0·009), 24-h recall (P = 0·002) and diet history (P = 0·050) in the laboratory, but not home environment. Personal and psychological correlates of misreporting identified displayed no clear pattern across studies or dietary assessment techniques and had little utility in predicting misreporting.

Introduction: Emergency department (ED) crowding is a major problem across Canada. We studied the ability of artificial intelligence methods to improve patient flow through the ED by predicting patient disposition using information available at triage and shortly after patients’ arrival in the ED. Methods: This retrospective study included all visits to an urban, academic, adult ED between May 2012 and June 2019. For each visit, 489 variables were extracted including triage data that had been collected for use in the Canadian Triage Assessment Scale (CTAS) and information regarding laboratory tests, radiological tests, consultations and admissions. A training set consisting of all visits from April 2012 up to December 2018 was used to train 5 classes of machine learning models to predict admission to the hospital from the ED. The models were trained to predict admission at the time of the patient's arrival in the ED and every 30 minutes after arrival until 6 hours into their ED stay. The performance of models was compared using the area under the ROC curve (AUC) on a test set consisting of all visits from January 2019 to June 2019. Results: The study included 536,332 visits and the admission rate was 15.0%. Gradient boosting models generally outperformed other machine learning models. A gradient boosting model using all available data at 2 hours after patient arrival in the ED yielded a test set AUC 0.92 [95% CI 0.91-0.93], while a model using only data available at triage yielded an AUC 0.90 [95% CI 0.89-0.91]. The quality of predictions generally improved as predictions were made later in the patient's ED stay leading to an AUC 0.95 [95% CI 0.93-0.96] at 6 hours after arrival. A gradient boosting model with 20 variables available at 2 hours after patient arrival in the ED yielded an AUC 0.91 [95% CI 0.89-0.93]. A gradient boosting model that makes predictions at 2 hours after arrival in ED using only variables that are available at all EDs in the province of Quebec yielded an AUC 0.91 [95% 0.89-0.92]. Conclusion: Machine learning can predict admission to a hospital from the ED using variables that area collected as part of routine ED care. Machine learning tools may potentially be used to help ED physicians to make faster and more appropriate disposition decisions, to decrease unnecessary testing and alleviate ED crowding.

We present a detailed analysis of the radio galaxy PKS $2250{-}351$ , a giant of 1.2 Mpc projected size, its host galaxy, and its environment. We use radio data from the Murchison Widefield Array, the upgraded Giant Metre-wavelength Radio Telescope, the Australian Square Kilometre Array Pathfinder, and the Australia Telescope Compact Array to model the jet power and age. Optical and IR data come from the Galaxy And Mass Assembly (GAMA) survey and provide information on the host galaxy and environment. GAMA spectroscopy confirms that PKS $2250{-}351$ lies at $z=0.2115$ in the irregular, and likely unrelaxed, cluster Abell 3936. We find its host is a massive, ‘red and dead’ elliptical galaxy with negligible star formation but with a highly obscured active galactic nucleus dominating the mid-IR emission. Assuming it lies on the local M– $\sigma$ relation, it has an Eddington accretion rate of $\lambda_{\rm EDD}\sim 0.014$ . We find that the lobe-derived jet power (a time-averaged measure) is an order of magnitude greater than the hotspot-derived jet power (an instantaneous measure). We propose that over the lifetime of the observed radio emission ( ${\sim} 300\,$ Myr), the accretion has switched from an inefficient advection-dominated mode to a thin disc efficient mode, consistent with the decrease in jet power. We also suggest that the asymmetric radio morphology is due to its environment, with the host of PKS $2250{-}351$ lying to the west of the densest concentration of galaxies in Abell 3936.

We present a survey of modeling techniques used to describe and predict architected cellular metamaterials, and to optimize their topology and geometry toward tailoring their mechanical properties such as stiffness, strength, fracture toughness, and energy absorption. Architectures of interest include truss-, plate-, and shell-based networks with and without periodicity, whose effective mechanical behavior is simulated by tools such as classical finite elements, further scale-bridging techniques such as homogenization and concurrent scale-coupling, and effective continuum descriptions of the underlying discrete networks. In addition to summarizing advances in applying the latter techniques to improve the properties of metamaterials and featuring prominent examples of structure–property relations achieved this way, we also present recently introduced techniques to improve the optimization process toward a full exploitation of the available design space, accounting for both linear and nonlinear material behavior.

Basal ice of glaciers and ice sheets frequently contains a well-developed stratification of distinct, semi-continuous, alternating layers of debris-poor and debris-rich ice. Here, the nature and distribution of shear within stratified basal ice are assessed through the anisotropy of magnetic susceptibility (AMS) of samples collected from Matanuska Glacier, Alaska. Generally, the AMS reveals consistent moderate-to-strong fabrics reflecting simple shear in the direction of ice flow; however, AMS is also dependent upon debris content and morphology. While sample anisotropy is statistically similar throughout the sampled section, debris-rich basal ice composed of semi-continuous mm-scale layers (the stratified facies) possesses well-defined triaxial to oblate fabrics reflecting shear in the direction of ice flow, whereas debris-poor ice containing mm-scale star-shaped silt aggregates (the suspended facies) possesses nearly isotropic fabrics. Thus, deformation within the stratified basal ice appears concentrated in debris-rich layers, likely the result of decreased crystal size and greater availability of unfrozen water associated with high debris content. These results suggest that variations in debris-content over small spatial scales influence ice rheology and deformation in the basal zone.

We have observed the G23 field of the Galaxy AndMass Assembly (GAMA) survey using the Australian Square Kilometre Array Pathfinder (ASKAP) in its commissioning phase to validate the performance of the telescope and to characterise the detected galaxy populations. This observation covers ~48 deg2 with synthesised beam of 32.7 arcsec by 17.8 arcsec at 936MHz, and ~39 deg2 with synthesised beam of 15.8 arcsec by 12.0 arcsec at 1320MHz. At both frequencies, the root-mean-square (r.m.s.) noise is ~0.1 mJy/beam. We combine these radio observations with the GAMA galaxy data, which includes spectroscopy of galaxies that are i-band selected with a magnitude limit of 19.2. Wide-field Infrared Survey Explorer (WISE) infrared (IR) photometry is used to determine which galaxies host an active galactic nucleus (AGN). In properties including source counts, mass distributions, and IR versus radio luminosity relation, the ASKAP-detected radio sources behave as expected. Radio galaxies have higher stellar mass and luminosity in IR, optical, and UV than other galaxies. We apply optical and IR AGN diagnostics and find that they disagree for ~30% of the galaxies in our sample. We suggest possible causes for the disagreement. Some cases can be explained by optical extinction of the AGN, but for more than half of the cases we do not find a clear explanation. Radio sources aremore likely (~6%) to have an AGN than radio quiet galaxies (~1%), but the majority of AGN are not detected in radio at this sensitivity.

Perceived discrimination (PD) is reliably and strongly associated with partisan identity (PID) among US immigrant minorities such as Latinos and Asian Americans. Yet whether PD causes PID remains unclear, since it is possible that partisanship influences perceptions of discrimination or that other factors drive the observed association. Here, we assess the causal influence of group-level PD on PID using five experiments with Latino and Asian American adults. These experiments varied in important ways: they took place inside and outside the lab, occurred prior to and during Donald Trump’s presidential campaign, and tested different manifestations of PD and partisan attitudes (total n = 2,528). These efforts point to a simple but unexpected conclusion: our experiments and operationalizations do not support the claim that group-targeted PD directly causes PID. These results have important implications for understanding partisanship among immigrants and their co-ethnics and the political incorporation of Latinos and Asian Americans.

This study examined effects of risk factors in multiple domains measured in preschool and kindergarten on age 6 depression symptoms, and on changes in symptom levels between ages 4 and 6. Two models were examined in a large, diverse (N = 796) community sample of children and parents. Risk variables included SES, stress, conflict, parental depression, parental hostility, support, scaffolding, child negative affect (NA), effortful control (EC), sensory regulation (SR), and attachment security. Model 1 included effects of risk factors at ages 4 and 5 on child depression symptoms at age 6. Model 2 also included depression symptoms at all three ages to examine changes in these symptoms. Model 1 revealed that age 4 and 5 parental depression, NA, EC, and SR predicted age 6 child depression levels, Several age 4 variables had indirect pathways to age 6 depression via age 5 EC. Model 2 revealed that preschool depression was the only age 4 variable, and EC and SR were the only age 5 variables that significantly predicted increases in age 6 depression. These findings highlight the role of self-regulation in child depression and suggest that targeting self-regulation may be an effective prevention and intervention strategy.

Evidence regarding the seasonality of urinary tract infection (UTI) consultations in primary care is conflicting and methodologically poor. To our knowledge, this is the first study to determine whether this seasonality exists in the UK, identify the peak months and describe seasonality by age. The monthly number of UTI consultations (N = 992 803) and nitrofurantoin and trimethoprim prescriptions (N = 1 719 416) during 2008–2015 was extracted from The Health Improvement Network (THIN), a large nationally representative UK dataset of electronic patient records. Negative binomial regression models were fitted to these data to investigate seasonal fluctuations by age group (14–17, 18–24, 25–45, 46–69, 70–84, 85+) and by sex, accounting for a change in the rate of UTI over the study period. A September to November peak in UTI consultation incidence was observed for ages 14–69. This seasonality progressively faded in older age groups and no seasonality was found in individuals aged 85+, in whom UTIs were most common. UTIs were rare in males but followed a similar seasonal pattern than in females. We show strong evidence of an autumnal seasonality for UTIs in individuals under 70 years of age and a lack of seasonality in the very old. These findings should provide helpful information when interpreting surveillance reports and the results of interventions against UTI.

The Taipan galaxy survey (hereafter simply ‘Taipan’) is a multi-object spectroscopic survey starting in 2017 that will cover 2π steradians over the southern sky (δ ≲ 10°, |b| ≳ 10°), and obtain optical spectra for about two million galaxies out to z < 0.4. Taipan will use the newly refurbished 1.2-m UK Schmidt Telescope at Siding Spring Observatory with the new TAIPAN instrument, which includes an innovative ‘Starbugs’ positioning system capable of rapidly and simultaneously deploying up to 150 spectroscopic fibres (and up to 300 with a proposed upgrade) over the 6° diameter focal plane, and a purpose-built spectrograph operating in the range from 370 to 870 nm with resolving power R ≳ 2000. The main scientific goals of Taipan are (i) to measure the distance scale of the Universe (primarily governed by the local expansion rate, H 0) to 1% precision, and the growth rate of structure to 5%; (ii) to make the most extensive map yet constructed of the total mass distribution and motions in the local Universe, using peculiar velocities based on improved Fundamental Plane distances, which will enable sensitive tests of gravitational physics; and (iii) to deliver a legacy sample of low-redshift galaxies as a unique laboratory for studying galaxy evolution as a function of dark matter halo and stellar mass and environment. The final survey, which will be completed within 5 yrs, will consist of a complete magnitude-limited sample (i ⩽ 17) of about 1.2 × 106 galaxies supplemented by an extension to higher redshifts and fainter magnitudes (i ⩽ 18.1) of a luminous red galaxy sample of about 0.8 × 106 galaxies. Observations and data processing will be carried out remotely and in a fully automated way, using a purpose-built automated ‘virtual observer’ software and an automated data reduction pipeline. The Taipan survey is deliberately designed to maximise its legacy value by complementing and enhancing current and planned surveys of the southern sky at wavelengths from the optical to the radio; it will become the primary redshift and optical spectroscopic reference catalogue for the local extragalactic Universe in the southern sky for the coming decade.

The yields of spring barley during a medium-term (7 years) compost and slurry addition experiment and the soil carbon (C) and nitrogen (N) contents, bacterial community structure, soil microbial biomass and soil respiration rates have been determined to assess the effects of repeated, and in some cases very large, organic amendments on soil and crop parameters. For compost, total additions were equivalent to up to 119 t C/ha and 1·7 t N/ha and for slurry they were 25 t C/ha and 0·35 t N/ha over 7 years, which represented very large additions compared to control soil C and N contents (69 t C/ha and 0·3 t N/ha in the 0–30 cm soil depth). There was an initial positive response to compost and slurry addition on barley yield, but over the experiment the yield differential between the amounts of compost addition declined, indicating that repeated addition of compost at a lower rate over several years had the same cumulative effect as a large single compost application. By the end of the experiment it was clear that the addition of compost and slurry increased soil C and N contents, especially towards the top of the soil profile, as well as soil respiration rates. However, the increases in soil C and N contents were not proportional to the amount of C and N added, suggesting either that: (i) a portion of the added C and N was more vulnerable to loss; (ii) that its addition rendered another C or N pool in the soil more susceptible to loss; or (iii) that the C inputs from additional crop productivity did not increase in line with the organic amendments. Soil microbial biomass was depressed at the highest rate of organic amendment, and whilst this may have been due to genuine toxic or inhibitory effects of large amounts of compost, it could also be due to the inaccuracy of the substrate-induced respiration approach used for determining soil biomass when there is a large supply of organic matter. At the highest compost addition, the bacterial community structure was significantly altered, suggesting that the amendments significantly altered soil community dynamics.