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SN1991bg-like supernovae are a distinct subclass of thermonuclear Type Ia supernovae (SNe Ia). Their spectral and photometric peculiarities indicate that their progenitors and explosion mechanisms differ from ‘normal’ SNe Ia. One method of determining information about supernova progenitors we cannot directly observe is to observe the stellar population adjacent to the apparent supernova explosion site to infer the distribution of stellar population ages and metallicities. We obtain integral field observations and analyse the spectra extracted from regions of projected radius
about the apparent SN explosion site for 11 91bg-like SNe in both early- and late-type galaxies. We utilise full-spectrum spectral fitting to determine the ages and metallicities of the stellar population within the aperture. We find that the majority of the stellar populations that hosted 91bg-like supernovae have little recent star formation. The ages of the stellar populations suggest that that 91bg-like SN progenitors explode after delay times of >6 Gyr, much longer than the typical delay time of normal SNe Ia, which peaks at
The study compared the contributions of self- and social-oriented personality factors to Chinese adolescents’ career exploration with a longitudinal perspective. The mediation effects of career decision self-efficacy and perceived parental support were also investigated. A total of 488 high school students in Hong Kong took three waves of a questionnaire survey at Grade 10, Grade 11 and Grade 12 respectively. The results indicated that adolescents’ career exploration at Grade 12 could be predicted by both self- and social-oriented personalities at Grade 10. Specifically, both self- and social-oriented personality factors could contribute to adolescents’ environmental exploration, and the effect was mediated by perceived parental support at Grade 11, after controlling for the effect of career exploration at Grade 11; whereas self-oriented personality factor could contribute to self-exploration, and the effect was mediated by career self-efficacy at Grade 11. The implications for career counseling and education for Chinese adolescents are discussed.
Understanding the two-way interactions between finite-size solid particles and a wall-bounded turbulent flow is crucial in a variety of natural and engineering applications. Previous experimental measurements and particle-resolved direct numerical simulations revealed some interesting phenomena related to particle distribution and turbulence modulation, but their in-depth analyses are largely missing. In this study, turbulent channel flows laden with neutrally buoyant finite-size spherical particles are simulated using the lattice Boltzmann method. Two particle sizes are considered, with diameters equal to 14.45 and 28.9 wall units. To understand the roles played by the particle rotation, two additional simulations with the same particle sizes but no particle rotation are also presented for comparison. Particles of both sizes are found to form clusters. Under the Stokes lubrication corrections, small particles are found to have a stronger preference to form clusters, and their clusters orientate more in the streamwise direction. As a result, small particles reduce the mean flow velocity less than large particles. Particles are also found to result in a more homogeneous distribution of turbulent kinetic energy (TKE) in the wall-normal direction, as well as a more isotropic distribution of TKE among different spatial directions. To understand these turbulence modulation phenomena, we analyse in detail the total and component-wise volume-averaged budget equations of TKE with the simulation data. This budget analysis reveals several mechanisms through which the particles modulate local and global TKE in the particle-laden turbulent channel flow.
In preparation for a multisite antibiotic stewardship intervention, we assessed knowledge and attitudes toward management of asymptomatic bacteriuria (ASB) plus teamwork and safety climate among providers, nurses, and clinical nurse assistants (CNAs).
Prospective surveys during January–June 2018.
All acute and long-term care units of 4 Veterans’ Affairs facilities.
The survey instrument included 2 previously tested subcomponents: the Kicking CAUTI survey (ASB knowledge and attitudes) and the Safety Attitudes Questionnaire (SAQ).
A total of 534 surveys were completed, with an overall response rate of 65%. Cognitive biases impacting management of ASB were identified. For example, providers presented with a case scenario of an asymptomatic patient with a positive urine culture were more likely to give antibiotics if the organism was resistant to antibiotics. Additionally, more than 80% of both nurses and CNAs indicated that foul smell is an appropriate indication for a urine culture. We found significant interprofessional differences in teamwork and safety climate (defined as attitudes about issues relevant to patient safety), with CNAs having highest scores and resident physicians having the lowest scores on self-reported perceptions of teamwork and safety climates (P < .001). Among providers, higher safety-climate scores were significantly associated with appropriate risk perceptions related to ASB, whereas social norms concerning ASB management were correlated with higher teamwork climate ratings.
Our survey revealed substantial misunderstanding regarding management of ASB among providers, nurses, and CNAs. Educating and empowering these professionals to discourage unnecessary urine culturing and inappropriate antibiotic use will be key components of antibiotic stewardship efforts.
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.
To compare and validate neurocognitive tests in the Harmonized Cognitive Assessment Protocol (HCAP) for the China Health and Retirement Longitudinal Study (CHARLS), and to identify appropriate tests to be administered in future waves of CHARLS.
We recruited 825 individuals from the CHARLS sample and 766 subjects from hospitals in six provinces and cities in China. All participants were administered the HCAP-neurocognitive tests, and their informants were interviewed regarding the respondents’ functional status. Trained clinicians administered the Clinical Dementia Rating scale (CDR) to assess the respondents’ cognitive status independently.
The testing protocol took an average of 58 minutes to complete. Refusal rates for tests of general cognition, episodic memory, and language were less than 10%. All neurocognitive test scores significantly correlated with the CDR global score (correlation coefficients ranged from 0.139 to 0.641). The Mini-Mental State Examination (MMSE), the Health and Retirement Study (HRS) - telephone interview for cognitive status (TICS), community screening instrument for dementia (CSI-D) for respondent, episodic memory and language tests each accounted for more than 20% of the variance in global CDR score (p < 0.001) in bivariate tests. In the CHARLS subsample, age and education were associated with neuropsychological performance across most cognitive domains, and with functional status.
A brief set of the CHARLS-HCAP neurocognitive tests are feasible and valid to be used in the CHARLS sample and hospital samples. It could be applied in the future waves of the CHARLS study, and it allows estimating the prevalence of dementia in China through the population-based CHARLS.
Personality disorders are now internationally recognised as a mental health priority. Nevertheless, there are no systematic reviews examining the global prevalence of personality disorders.
To calculate the worldwide prevalence of personality disorders and examine whether rates vary between high-income countries and low- and middle-income countries (LMICs).
We systematically searched PsycINFO, MEDLINE, EMBASE and PubMed from January 1980 to May 2018 to identify articles reporting personality disorder prevalence rates in community populations (PROSPERO registration number: CRD42017065094).
A total of 46 studies (from 21 different countries spanning 6 continents) satisfied inclusion criteria. The worldwide pooled prevalence of any personality disorder was 7.8% (95% CI 6.1–9.5). Rates were greater in high-income countries (9.6%, 95% CI 7.9–11.3%) compared with LMICs (4.3%, 95% CI 2.6–6.1%). In univariate meta-regressions, significant heterogeneity was partly attributable to study design (two-stage v. one-stage assessment), county income (high-income countries v. LMICs) and interview administration (clinician v. trained graduate). In multiple meta-regression analysis, study design remained a significant predictor of heterogeneity. Global rates of cluster A, B and C personality disorders were 3.8% (95% CI 3.2, 4.4%), 2.8% (1.6, 3.7%) and 5.0% (4.2, 5.9%).
Personality disorders are prevalent globally. Nevertheless, pooled prevalence rates should be interpreted with caution due to high levels of heterogeneity. More large-scale studies with standardised methodologies are now needed to increase our understanding of population needs and regional variations.
The order Onchoproteocephalidea (Eucestoda) was recently erected to accommodate the hook-bearing tetraphyllideans and the proteocephalideans, which are characterized by internal proglottization and a tetra-acetabulate scolex. The recognized subfamilies in the Proteocephalidae appeared to be non-monophyletic based on 28S recombinant DNA (rDNA) sequence data. Other molecular markers with higher phylogenetic resolution, such as large mitochondrial DNA fragments and multiple genes, are obviously needed. Thus the mitochondrial genome of Gangesia oligonchis, belonging to the putative earliest diverging group of the Proteocephalidae, was sequenced. The circular mitogenome of G. oligonchis was 13,958 bp in size, and contained the standard 36 genes: 22 transfer RNA genes, two rRNA genes and 12 protein-coding genes, as well as two major non-coding regions. A short NCR and a large NCR (lNCR) region were 216 bp and 419 bp in size, respectively. Highly repetitive regions in the lNCR region were detected with that of 11 repeat units. The mitogenome of G. oligonchis shared 71.1% nucleotide identity with Testudotaenia sp. WL-2016. Phylogenetic analyses of the complete mitochondrial genomes with Bayesian inference and maximum likelihood methods indicated that G. oligonchis formed a sister clade with Testudotaenia sp. WL-2016 with maximum support. The ordinal topology is (Caryophyllidea, (Diphyllobothriidea, (Bothriocephalidea, (Onchoproteocephalidea, Cyclophyllidea)))). The mitogenomic gene arrangement of G. oligonchis was identical to that of Testudotaenia sp. WL-2016. Both mitogenomic and nuclear sequence data for many more taxa are required to effectively explore the inter-relationships among the Onchoproteocephalidea.
Rubber seed oil (RO) that is rich in polyunsaturated fatty acids (FA) can improve milk production and milk FA profiles of dairy cows; however, the responses of digestion and ruminal fermentation to RO supplementation in vivo are still unknown. This experiment was conducted to investigate the effect of RO and flaxseed oil (FO) supplementation on nutrients digestibility, rumen fermentation parameters and rumen FA profile of dairy cows. Forty-eight mid-lactation Holstein dairy cows were randomly assigned to one of four treatments for 8 weeks, including basal diet (CON) or the basal dietary supplemented with 4% RO, 4% FO or 2% RO plus 2% FO on a DM basis. Compared with CON, dietary oil supplementation improved the total tract apparent digestibility of DM, neutral detergent fibre and ether extracts ( P < 0.05). Oil treatment groups had no effects on ruminal digesta pH value, ammonia N and microbial crude protein ( P > 0.05), whereas oil groups significantly changed the volatile fatty acid (VFA) profile by increasing the proportion of propionate whilst decreasing total VFA concentration, the proportion of acetate and the ratio of acetate to propionate ( P < 0.05). However, there were no differences in VFA proportions between the three oil groups (P > 0.05). In addition, dietary oil supplementation increased the total unsaturated FA proportion in the rumen by enhancing the proportion of trans-11 C18:1 vaccenic acid (VA), cis-9, trans-11 conjugated linoleic acid (CLA) and α-linolenic acid (ALA) ( P < 0.05). These results indicate that dietary supplementation with RO and FO could improve nutrients digestibility, ruminal fermentation and ruminal FA profile by enhancing the VA, cis-9, trans-11 CLA and ALA composition of lactating dairy cows. These findings provide a theoretical basis for the application of RO in livestock production.
Introduction: Children diagnosed with medulloblastoma (MB) who are refractory to upfront therapy or experience recurrence have very poor prognoses. Although phase I and phase II trials exist, these treatments bear significant treatment-related morbidity and mortality. Methods: A retrospective review of children diagnosed with a recurrence of MB from 2002 to 2015 at McMaster University was undertaken. Results: Recurrent disease in 10 patients involved leptomeningeal dissemination, with 3 experiencing local recurrence. In three recurrent patients the disease significantly progressed, and the children were palliated. The remaining 10 children underwent some form of salvage therapy, including surgical re-resection, radiation, and chemotherapy, either in isolation or in varying combinations. Of the 13 children experiencing treatment-refractory or recurrent disease, 4 are currently alive with a median follow-up of 38.5 months (75.5 months). Of the eight patients with molecular subgrouping data, none of the Wnt MB experienced recurrence. Conclusion: Recurrent MB carried a poor prognosis with a 5-year overall survival (OS) of 18.2% despite the administration of salvage therapy. The upfront therapy received, available treatment, and tolerability of the proposed salvage therapy resulted in significant heterogeneity in the treatment of our recurrent cohort.
The authors showcase the potential of symbolic regression as an analytic method for use in materials research. First, the authors briefly describe the current state-of-the-art method, genetic programming-based symbolic regression (GPSR), and recent advances in symbolic regression techniques. Next, the authors discuss industrial applications of symbolic regression and its potential applications in materials science. The authors then present two GPSR use-cases: formulating a transformation kinetics law and showing the learning scheme discovers the well-known Johnson–Mehl–Avrami–Kolmogorov form, and learning the Landau free energy functional form for the displacive tilt transition in perovskite LaNiO3. Finally, the authors propose that symbolic regression techniques should be considered by materials scientists as an alternative to other machine learning-based regression models for learning from data.