3,433 research outputs found

    Class Conditional Gaussians for Continual Learning

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    Dealing with representation shift is one of the main problems in online continual learning. Current methods mainly solve this by reducing representation shift, but leave the classifier on top of the representation to slowly adapt, in many update steps, to the remaining representation shift, increasing forgetting. We propose DeepCCG, an empirical Bayesian approach to solve this problem. DeepCCG works by updating the posterior of a class conditional Gaussian classifier such that the classifier adapts instantly to representation shift. The use of a class conditional Gaussian classifier also enables DeepCCG to use a log conditional marginal likelihood loss to update the representation, which can be seen as a new type of replay. To perform the update to the classifier and representation, DeepCCG maintains a fixed number of examples in memory and so a key part of DeepCCG is selecting what examples to store, choosing the subset that minimises the KL divergence between the true posterior and the posterior induced by the subset. We demonstrate the performance of DeepCCG on a range of settings, including those with overlapping tasks which thus far have been under-explored. In the experiments, DeepCCG outperforms all other methods, evidencing its potential.Comment: 9 pages, 6 figures, preprin

    Twentieth century warming of the tropical Atlantic captured by Sr-U paleothermometry

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    Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Paleoceanography 32 (2017): 146–160, doi:10.1002/2016PA002976.Coral skeletons are valuable archives of past ocean conditions. However, interpretation of coral paleotemperature records is confounded by uncertainties associated with single-element ratio thermometers, including Sr/Ca. A new approach, Sr-U, uses U/Ca to constrain the influence of Rayleigh fractionation on Sr/Ca. Here we build on the initial Pacific Porites Sr-U calibration to include multiple Atlantic and Pacific coral genera from multiple coral reef locations spanning a temperature range of 23.15–30.12°C. Accounting for the wintertime growth cessation of one Bermuda coral, we show that Sr-U is strongly correlated with the average water temperature at each location (r2 = 0.91, P < 0.001, n = 19). We applied the multispecies spatial calibration between Sr-U and temperature to reconstruct a 96 year long temperature record at Mona Island, Puerto Rico, using a coral not included in the calibration. Average Sr-U derived temperature for the period 1900–1996 is within 0.12°C of the average instrumental temperature at this site and captures the twentieth century warming trend of 0.06°C per decade. Sr-U also captures the timing of multiyear variability but with higher amplitude than implied by the instrumental data. Mean Sr-U temperatures and patterns of multiyear variability were replicated in a second coral in the same grid box. Conversely, Sr/Ca records from the same two corals were inconsistent with each other and failed to capture absolute sea temperatures, timing of multiyear variability, or the twentieth century warming trend. Our results suggest that coral Sr-U paleothermometry is a promising new tool for reconstruction of past ocean temperatures.NSF Graduate Research Fellowships Grant Numbers: NSF-OCE-1338320, NSF-OCE-1031971, NSF-OCE-0926986; WHOI Access to the Sea Grant Numbers: 27500056, 0734826; NSF HRD; UPR Central Administration to EAHD through the Center for Applied Tropical Ecology and Conservation of UPR2017-08-1

    Human genes differ by their UV sensitivity estimated through analysis of UV-induced silent mutations in melanoma

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    We hypothesized that human genes differ by their sensitivity to ultraviolet (UV) exposure. We used somatic mutations detected by genome-wide screens in melanoma and reported in the Catalog Of Somatic Mutations In Cancer. As a measure of UV sensitivity, we used the number of silent mutations generated by C>T transitions in pyrimidine dimers of a given transcript divided by the number of potential sites for this type of mutations in the transcript. We found that human genes varied by UV sensitivity by two orders of magnitude. We noted that the melanoma-associated tumor suppressor gene CDKN2A was among the top five most UV-sensitive genes in the human genome. Melanoma driver genes have a higher UV-sensitivity compared with other genes in the human genome. The difference was more prominent for tumor suppressors compared with oncogene. The results of this study suggest that differential sensitivity of human transcripts to UV light may explain melanoma specificity of some driver genes. Practical significance of the study relates to the fact that differences in UV sensitivity among human genes need to be taken into consideration whereas predicting melanoma-associated genes by the number of somatic mutations detected in a given gene

    Pennsylvania Folklife Vol. 11, No. 1

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    • A Dunker Weekend Love Feast of 100 Years Ago • The Peacock in Pennsylvania • The Get-Togethers of the Young Amish Folk • Church and Meetinghouse Stables and Sheds • Abraham Harley Cassel - Dunkard Bibliophile • Mennonite Folklore • Springs and Springhouses • Finishing Wooden Surfaces • Early Funeral Notices • Collecting Dialect Folk Songshttps://digitalcommons.ursinus.edu/pafolklifemag/1006/thumbnail.jp

    Genetic signal maximization using environmental regression

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    Joint analyses of correlated phenotypes in genetic epidemiology studies are common. However, these analyses primarily focus on genetic correlation between traits and do not take into account environmental correlation. We describe a method that optimizes the genetic signal by accounting for stochastic environmental noise through joint analysis of a discrete trait and a correlated quantitative marker. We conducted bivariate analyses where heritability and the environmental correlation between the discrete and quantitative traits were calculated using Genetic Analysis Workshop 17 (GAW17) family data. The resulting inverse value of the environmental correlation between these traits was then used to determine a new β coefficient for each quantitative trait and was constrained in a univariate model. We conducted genetic association tests on 7,087 nonsynonymous SNPs in three GAW17 family replicates for Affected status with the β coefficient fixed for three quantitative phenotypes and compared these to an association model where the β coefficient was allowed to vary. Bivariate environmental correlations were 0.64 (± 0.09) for Q1, 0.798 (± 0.076) for Q2, and −0.169 (± 0.18) for Q4. Heritability of Affected status improved in each univariate model where a constrained β coefficient was used to account for stochastic environmental effects. No genome-wide significant associations were identified for either method but we demonstrated that constraining β for covariates slightly improved the genetic signal for Affected status. This environmental regression approach allows for increased heritability when the β coefficient for a highly correlated quantitative covariate is constrained and increases the genetic signal for the discrete trait

    Clonal hematopoiesis and therapy-related myeloid neoplasms following neuroblastoma treatment.

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    Therapy-related myeloid neoplasms (TMN) constitute one of the most challengingcomplications of cancer treatment.1 Whilst understanding of TMN pathogenesis remains fragmentary, genomic studies in adults have thus far refuted the notion that TMN simply result from cytotoxin-induced DNA damage.2–4 Analysis of the preclinical evolution of a limited number of adult TMN have retraced the majority of cases to clonal haematopoiesis (CH) that predates cytotoxic treatment and lacks the mutational footprint of genotoxic therapies.2–6 Balanced translocations, generally attributed to treatment with topoisomerase II inhibitors, are implicated in a minority of TMN.1 TMN is a leading cause of premature death in childhood cancer survivors, and affects 7-11% of children treated for high-risk neuroblastoma and sarcoma.7,8 However, the origin of pediatric TMN remains unclear. Targeted sequencing of known cancer genes detects CH in ~4% of children following cytotoxic treatment,6,9 whereas CH is vanishingly rare in young individuals in the general population.10,11 Moreover, to our knowledge, no cases of childhood TMN have been retraced to pretreatment CH. In light of these observations, we asked whether a broader driver landscape had eluded targeted CH screens in pediatric cancer patients and/or whether therapy-induced mutagenesis may be an under-recognised catalyst of CH and TMN in this patient group

    Steric constraints in model proteins

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    A simple lattice model for proteins that allows for distinct sizes of the amino acids is presented. The model is found to lead to a significant number of conformations that are the unique ground state of one or more sequences or encodable. Furthermore, several of the encodable structures are highly designable and are the non-degenerate ground state of several sequences. Even though the native state conformations are typically compact, not all compact conformations are encodable. The incorporation of the hydrophobic and polar nature of amino acids further enhances the attractive features of the model.Comment: RevTex, 5 pages, 3 postscript figure

    Detecting the direction of a signal on high-dimensional spheres: Non-null and Le Cam optimality results

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    We consider one of the most important problems in directional statistics, namely the problem of testing the null hypothesis that the spike direction θ\theta of a Fisher-von Mises-Langevin distribution on the pp-dimensional unit hypersphere is equal to a given direction θ0\theta_0. After a reduction through invariance arguments, we derive local asymptotic normality (LAN) results in a general high-dimensional framework where the dimension pnp_n goes to infinity at an arbitrary rate with the sample size nn, and where the concentration κn\kappa_n behaves in a completely free way with nn, which offers a spectrum of problems ranging from arbitrarily easy to arbitrarily challenging ones. We identify various asymptotic regimes, depending on the convergence/divergence properties of (κn)(\kappa_n), that yield different contiguity rates and different limiting experiments. In each regime, we derive Le Cam optimal tests under specified κn\kappa_n and we compute, from the Le Cam third lemma, asymptotic powers of the classical Watson test under contiguous alternatives. We further establish LAN results with respect to both spike direction and concentration, which allows us to discuss optimality also under unspecified κn\kappa_n. To investigate the non-null behavior of the Watson test outside the parametric framework above, we derive its local asymptotic powers through martingale CLTs in the broader, semiparametric, model of rotationally symmetric distributions. A Monte Carlo study shows that the finite-sample behaviors of the various tests remarkably agree with our asymptotic results.Comment: 47 pages, 4 figure

    Women's gambling behaviour, product preferences, and perceptions of product harm: Differences by age and gambling risk status

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    Background: Women's participation in, and harm from gambling, is steadily increasing. There has been very limited research to investigate how gambling behaviour, product preferences, and perceptions of gambling harm may vary across subgroups of women. Methods: This study surveyed a convenience sample of 509 women from Victoria and New South Wales, Australia. Women were asked a range of questions about their socio-demographic characteristics and gambling behaviour. Focusing on four gambling products in Australia-casino gambling, electronic gambling machines (EGMs), horse betting, and sports betting-women were asked about their frequency of participation, their product preferences, and perceptions of product harms. The sample was segmented a priori according to age and gambling risk status, and differences between groups were identified using Chi-square tests and ANOVAs. Thematic analysis was used to interpret qualitative data. Results: Almost two thirds (n=324, 63.7%) of women had engaged with one of the four products in the previous 12 months. Compared to other age groups, younger women aged 16-34 years exhibited a higher proportion of problem gambling, gambled more frequently, and across more products. While EGMs were the product gambled on most frequently by women overall, younger women were significantly more likely to bet on sports and gamble at casinos relative to older women. Qualitative data indicated that younger women engaged with gambling products as part of a 'night out', 'with friends', due to their 'ease of access' and perceived 'chance of winning big'. There were significant differences in the perceptions of the harms associated with horse and sports betting according to age and gambling risk status, with younger women and gamblers perceiving these products as less harmful. Conclusions: This study highlights that there are clear differences in the gambling behaviour, product preferences, and perceptions of product harms between subgroups of women. A gendered approach will enable public health researchers and policymakers to ensure that the unique factors associated with women's gambling are taken into consideration in a comprehensive public health approach to reducing and preventing gambling harm
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