Quantum Tunneling in Nuclear Fusion

Recent theoretical advances in the study of heavy ion fusion reactions below the Coulomb barrier are reviewed. Particular emphasis is given to new ways of analyzing data, such as studying barrier distributions; new approaches to channel coupling, such as the path integral and Green function formalisms; and alternative methods to describe nuclear structure effects, such as those using the Interacting Boson Model. The roles of nucleon transfer, asymmetry effects, higher-order couplings, and shape-phase transitions are elucidated. The current status of the fusion of unstable nuclei and very massive systems are briefly discussed.Comment: To appear in the January 1998 issue of Reviews of Modern Physics. 13 Figures (postscript file for Figure 6 is not available; a hard copy can be requested from the authors). Full text and figures are also available at http://nucth.physics.wisc.edu/preprints

Children, parents and pets exercising together (CPET) : exploratory randomised controlled trial

Levels of physical activity (PA) in UK children are much lower than recommended and novel approaches to its promotion are needed. The Children, Parents and Pets Exercising Together (CPET) study is the first exploratory randomised controlled trial (RCT) to develop and evaluate an intervention aimed at dog-based PA promotion in families. CPET aimed to assess the feasibility, acceptability and potential efficacy of a theory-driven, family-based, dog walking intervention for 9-11 year olds

An exploratory analysis of planning characteristics in Australian visitor attractions

This paper provides an exploratory analysis of the planning practices of 408 Australian attraction operators. The results indicate that attraction managers can be divided into four categories: those that do not engage in any formal planning, those that adopt a short-term planning approach, those that develop long-term plans, and those that use both short-term and long-term planning approaches. An evaluation of the sophistication of attraction planning showed a bipolar distribution. Attraction managers favored a planning horizon of three or five years, and were inclined to involve their employees in the planning process. Managers relied strongly on their own research and tourism industry intelligence when formulating business plans. The content of plans tended to focus on operational activities, financial planning and marketing. The study provides a benchmark for the comparison of attraction planning efforts in various contexts. © 2006 Asia Pacific Tourism Association

Radio and X-ray observations of the luminous fast blue optical transient AT 2020xnd

We present deep X-ray and radio observations of the fast blue optical transient (FBOT) AT 2020xnd/ZTF 20acigmel at z = 0.2433 from 13 days to 269 days after explosion. AT 2020xnd belongs to the category of optically luminous FBOTs with similarities to the archetypal event AT 2018cow. AT 2020xnd shows luminous radio emission reaching L ν ≈ 8 × 1029 erg s−1 Hz−1 at 20 GHz and 75 days post-explosion, accompanied by luminous and rapidly fading soft X-ray emission peaking at L X ≈ 6 × 1042 erg s−1. Interpreting the radio emission in the context of synchrotron radiation from the explosion’s shock interaction with the environment, we find that AT 2020xnd launched a high-velocity outflow (v ∼ 0.1c–0.2c) propagating into a dense circumstellar medium (effective Ṁ≈10−3M⊙ yr−1 for an assumed wind velocity of v w = 1000 km s−1). Similar to AT 2018cow, the detected X-ray emission is in excess compared to the extrapolated synchrotron spectrum and constitutes a different emission component, possibly powered by accretion onto a newly formed black hole or neutron star. These properties make AT 2020xnd a high-redshift analog to AT 2018cow, and establish AT 2020xnd as the fourth member of the class of optically luminous FBOTs with luminous multiwavelength counterparts

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

Genetic risk factors for BMI and obesity in an ethnically diverse population: Results from the population architecture using genomics and epidemiology (PAGE) study

Several genome-wide association studies (GWAS) have demonstrated that common genetic variants contribute to obesity. However, studies of this complex trait have focused on ancestrally European populations, despite the high prevalence of obesity in some minority groups. As part of the ‘Population Architecture using Genomics and Epidemiology (PAGE)’ Consortium, we investigated the association between thirteen GWAS-identified SNPs and BMI and obesity in 69,775 subjects, including 6,149 American Indians, 15,415 African-Americans, 2,438 East Asians, 7,346 Hispanics, 604 Pacific Islanders, and 37,823 European Americans. For the BMI-increasing allele of each SNP, we calculated beta coefficients using linear regression (for BMI) and risk estimates using logistic regression (for obesity defined as BMI ≥ 30) followed by fixed-effects meta-analysis to combine results across PAGE sites. Analyses stratified by racial/ethnic group assumed an additive genetic model and adjusted for age, sex, and current smoking. We defined “replicating SNPs” (in European Americans) and “generalizing SNPs” (in other racial/ethnic groups) as those associated with an allele frequency-specific increase in BMI. By this definition, we replicated 9/13 SNP associations (5 out of 8 loci) in European Americans. We also generalized 8/13 SNP associations (5/8 loci) in East Asians, 7/13 (5/8 loci) in African Americans, 6/13 (4/8 loci) in Hispanics, 5/8 in Pacific Islanders (5/8 loci), and 5/9 (4/8 loci) in American Indians. Linkage disequilibrium patterns suggest that tagSNPs selected for European Americans may not adequately tag causal variants in other ancestry groups. Accordingly, fine-mapping in large samples is needed to comprehensively explore these loci in diverse populations

Understanding the genetic complexity of puberty timing across the allele frequency spectrum

Pubertal timing varies considerably and is associated with later health outcomes. We performed multi-ancestry genetic analyses on ~800,000 women, identifying 1,080 signals for age at menarche. Collectively, these explained 11% of trait variance in an independent sample. Women at the top and bottom 1% of polygenic risk exhibited ~11 and ~14-fold higher risks of delayed and precocious puberty, respectively. We identified several genes harboring rare loss-of-function variants in ~200,000 women, including variants in ZNF483, which abolished the impact of polygenic risk. Variant-to-gene mapping approaches and mouse gonadotropin-releasing hormone neuron RNA sequencing implicated 665 genes, including an uncharacterized G-protein-coupled receptor, GPR83, which amplified the signaling of MC3R, a key nutritional sensor. Shared signals with menopause timing at genes involved in DNA damage response suggest that the ovarian reserve might signal centrally to trigger puberty. We also highlight body size-dependent and independent mechanisms that potentially link reproductive timing to later life disease

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to similar to 370,000 women, we identify 389 independent signals (P <5 x 10(-8)) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain similar to 7.4% of the population variance in age at menarche, corresponding to similar to 25% of the estimated heritability. We implicate similar to 250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility