Mass equidistribution of Hilbert modular eigenforms

Let F be a totally real number field, and let f traverse a sequence of non-dihedral holomorphic eigencuspforms on GL(2)/F of weight (k_1,...,k_n), trivial central character and full level. We show that the mass of f equidistributes on the Hilbert modular variety as max(k_1,...,k_n) tends to infinity. Our result answers affirmatively a natural analogue of a conjecture of Rudnick and Sarnak (1994). Our proof generalizes the argument of Holowinsky-Soundararajan (2008) who established the case F = Q. The essential difficulty in doing so is to adapt Holowinsky's bounds for the Weyl periods of the equidistribution problem in terms of manageable shifted convolution sums of Fourier coefficients to the case of a number field with nontrivial unit group.Comment: 40 pages; typos corrected, nearly accepted for

A finite model of two-dimensional ideal hydrodynamics

A finite-dimensional su($N$) Lie algebra equation is discussed that in the infinite $N$ limit (giving the area preserving diffeomorphism group) tends to the two-dimensional, inviscid vorticity equation on the torus. The equation is numerically integrated, for various values of $N$, and the time evolution of an (interpolated) stream function is compared with that obtained from a simple mode truncation of the continuum equation. The time averaged vorticity moments and correlation functions are compared with canonical ensemble averages.Comment: (25 p., 7 figures, not included. MUTP/92/1

Dual mechanism of brain injury and novel treatment strategy in maple syrup urine disease

Maple syrup urine disease (MSUD) is an inherited disorder of branched-chain amino acid metabolism presenting with lifethreatening cerebral oedema and dysmyelination in affected individuals. Treatment requires life-long dietary restriction and monitoring of branched-chain amino acids to avoid brain injury. Despite careful management, children commonly suffer metabolic decompensation in the context of catabolic stress associated with non-specific illness. The mechanisms underlying this decompensation and brain injury are poorly understood. Using recently developed mouse models of classic and intermediate maple syrup urine disease, we assessed biochemical, behavioural and neuropathological changes that occurred during encephalopathy in these mice. Here, we show that rapid brain leucine accumulation displaces other essential amino acids resulting in neurotransmitter depletion and disruption of normal brain growth and development. A novel approach of administering norleucine to heterozygous mothers of classic maple syrup urine disease pups reduced branched-chain amino acid accumulation in milk as well as blood and brain of these pups to enhance survival. Similarly, norleucine substantially delayed encephalopathy in intermediate maple syrup urine disease mice placed on a high protein diet that mimics the catabolic stress shown to cause encephalopathy in human maple syrup urine disease. Current findings suggest two converging mechanisms of brain injury in maple syrup urine disease including: (i) neurotransmitter deficiencies and growth restriction associated with branchedchain amino acid accumulation and (ii) energy deprivation through Krebs cycle disruption associated with branched-chain ketoacid accumulation. Both classic and intermediate models appear to be useful to study the mechanism of brain injury and potential treatment strategies for maple syrup urine disease. Norleucine should be further tested as a potential treatment to prevent encephalopathy in children with maple syrup urine disease during catabolic stress

Debiasing Decisions. Improved Decision Making With A Single Training Intervention

From failures of intelligence analysis to misguided beliefs about vaccinations, biased judgment and decision making contributes to problems in policy, business, medicine, law, and private life. Early attempts to reduce decision biases with training met with little success, leading scientists and policy makers to focus on debiasing by using incentives and changes in the presentation and elicitation of decisions. We report the results of two longitudinal experiments that found medium to large effects of one-shot debiasing training interventions. Participants received a single training intervention, played a computer game or watched an instructional video, which addressed biases critical to intelligence analysis (in Experiment 1: bias blind spot, confirmation bias, and fundamental attribution error; in Experiment 2: anchoring, representativeness, and social projection). Both kinds of interventions produced medium to large debiasing effects immediately (games ≥ -31.94% and videos ≥ -18.60%) that persisted at least 2 months later (games ≥ -23.57% and videos ≥ -19.20%). Games, which provided personalized feedback and practice, produced larger effects than did videos. Debiasing effects were domain-general: bias reduction occurred across problems in different contexts, and problem formats that were taught and not taught in the interventions. The results suggest that a single training intervention can improve decision making. We suggest its use alongside improved incentives, information presentation, and nudges to reduce costly errors associated with biased judgments and decisions

Simulating the Formation of the Local Galaxy Population

We simulate the formation and evolution of the local galaxy population starting from initial conditions with a smoothed linear density field which matches that derived from the IRAS 1.2 Jy galaxy survey. Our simulations track the formation and evolution of all dark matter haloes more massive than 10e+11 solar masses out to a distance of 8000 km/s from the Milky Way. We implement prescriptions similar to those of Kauffmann et al. (1999) to follow the assembly and evolution of the galaxies within these haloes. We focus on two variants of the CDM cosmology: an LCDM and a tCDM model. Galaxy formation in each is adjusted to reproduce the I-band Tully-Fisher relation of Giovanelli et al. (1997). We compare the present-day luminosity functions, colours, morphology and spatial distribution of our simulated galaxies with those of the real local population, in particular with the Updated Zwicky Catalog, with the IRAS PSCz redshift survey, and with individual local clusters such as Coma, Virgo and Perseus. We also use the simulations to study the clustering bias between the dark matter and galaxies of differing type. Although some significant discrepancies remain, our simulations recover the observed intrinsic properties and the observed spatial distribution of local galaxies reasonably well. They can thus be used to calibrate methods which use the observed local galaxy population to estimate the cosmic density parameter or to draw conclusions about the mechanisms of galaxy formation. To facilitate such work, we publically release our z=0 galaxy catalogues, together with the underlying mass distribution.Comment: 25 pages, 20 figures, submitted to MNRAS. High resolution copies of figures 1 and 3, halo and galaxy catalogues can be found at http://www.mpa-garching.mpg.de/NumCos/CR/index.htm

Beyond Controlled Environments: 3D Camera Re-Localization in Changing Indoor Scenes

Long-term camera re-localization is an important task with numerous computer vision and robotics applications. Whilst various outdoor benchmarks exist that target lighting, weather and seasonal changes, far less attention has been paid to appearance changes that occur indoors. This has led to a mismatch between popular indoor benchmarks, which focus on static scenes, and indoor environments that are of interest for many real-world applications. In this paper, we adapt 3RScan - a recently introduced indoor RGB-D dataset designed for object instance re-localization - to create RIO10, a new long-term camera re-localization benchmark focused on indoor scenes. We propose new metrics for evaluating camera re-localization and explore how state-of-the-art camera re-localizers perform according to these metrics. We also examine in detail how different types of scene change affect the performance of different methods, based on novel ways of detecting such changes in a given RGB-D frame. Our results clearly show that long-term indoor re-localization is an unsolved problem. Our benchmark and tools are publicly available at waldjohannau.github.io/RIO10Comment: ECCV 2020, project website https://waldjohannau.github.io/RIO1

Adult women and ADHD: on the temporal dimensions of ADHD identities

This paper uses conceptual resources drawn psychosocial process thinking (Stenner, 2017, Brown and Reavey, 2015, Brown and Stenner, 2009) and from G.H. Mead in particular, to contribute to an emerging body of work on the experiences of adult women with ADHD (Singh, 2002, Waite and Ivey, 2009, Quinn and Madhoo, 2014, Horton-Salway and Davies, 2018). It has a particular focus on how ADHD features in the construction of women’s identities and life-stories and it draws upon findings from a qualitative investigation of adult women diagnosed or self-diagnosed with Attention Deficit Hyperactivity Disorder (ADHD). A theoretically informed ‘thematic decomposition’ of 16 depth interviews reveals how complex processes of identity transformation are mediated by the social category of ADHD. Through this process, pasts are reconstructed from the perspective of an ‘emergent’ identity that offers participants the potential for a more enabling and positive future

Power Spectrum Estimation from Peculiar Velocity Catalogues

The peculiar velocities of galaxies are an inherently valuable cosmological probe, providing an unbiased estimate of the distribution of matter on scales much larger than the depth of the survey. Much research interest has been motivated by the high dipole moment of our local peculiar velocity field, which suggests a large scale excess in the matter power spectrum, and can appear to be in some tension with the LCDM model. We use a composite catalogue of 4,537 peculiar velocity measurements with a characteristic depth of 33 h-1 Mpc to estimate the matter power spectrum. We compare the constraints with this method, directly studying the full peculiar velocity catalogue, to results from Macaulay et al. (2011), studying minimum variance moments of the velocity field, as calculated by Watkins, Feldman & Hudson (2009) and Feldman, Watkins & Hudson (2010). We find good agreement with the LCDM model on scales of k > 0.01 h Mpc-1. We find an excess of power on scales of k < 0.01 h Mpc-1, although with a 1 sigma uncertainty which includes the LCDM model. We find that the uncertainty in the excess at these scales is larger than an alternative result studying only moments of the velocity field, which is due to the minimum variance weights used to calculate the moments. At small scales, we are able to clearly discriminate between linear and nonlinear clustering in simulated peculiar velocity catalogues, and find some evidence (although less clear) for linear clustering in the real peculiar velocity data.Comment: 10 pages, 13 figures, updated to match version accepted by MNRA

Antibody Duration after infection From Sars-Cov-2 in the Texas Coronavirus antibody Response Survey

Understanding the duration of antibodies to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that causes COVID-19 is important to controlling the current pandemic. Participants from the Texas Coronavirus Antibody Response Survey (Texas CARES) with at least 1 nucleocapsid protein antibody test were selected for a longitudinal analysis of antibody duration. A linear mixed model was fit to data from participants (n = 4553) with 1 to 3 antibody tests over 11 months (1 October 2020 to 16 September 2021), and models fit showed that expected antibody response after COVID-19 infection robustly increases for 100 days postinfection, and predicts individuals may remain antibody positive from natural infection beyond 500 days depending on age, body mass index, smoking or vaping use, and disease severity (hospitalized or not; symptomatic or not)