Dynamics of manganese, cadmium, and lead in experimental power plant ponds

This study was designed to determine the effect of heated power plant cooling water on the compartmentalization of manganese, lead and cadmium in experimental ponds. Caged channel catfish and green sunfish were kept in an experimental pond and a control pond. Periodically, whole fishes, gill, heart, kidney, liver and musculature were analyzed for the three metals. Concentrations of the three metals in fishes were not affected by the temperature differential maintained during the study. There was no correlation in concentrations of cadmium and lead with age (weight and length) of fishes but manganese concentrations declined slightly with age. The water component of the system contained the lowest concentration of the metals with sediments acting as a characteristic sink. Concentrations of the three metals in water and sediments of the ponds were unaffected by heat inasmuch as concentration differences between ponds were not significant at the .05 level. Aquatic organisms such as snails, fingernail clams, leeches, tubificid annelids and dragonfly nymphs exhibited concentrations of cadmium higher than sediments while snails and duckweed more closely reflected concentrations of manganese in sediments. Tubificid worms and leeches more closely reflected lead concentrations in sediments while fingernail clams and snails exhibited higher concentrations.U.S. Department of the InteriorU.S. Geological SurveyOpe

The Dark Energy Survey Data Management System

The Dark Energy Survey collaboration will study cosmic acceleration with a 5000 deg2 griZY survey in the southern sky over 525 nights from 2011-2016. The DES data management (DESDM) system will be used to process and archive these data and the resulting science ready data products. The DESDM system consists of an integrated archive, a processing framework, an ensemble of astronomy codes and a data access framework. We are developing the DESDM system for operation in the high performance computing (HPC) environments at NCSA and Fermilab. Operating the DESDM system in an HPC environment offers both speed and flexibility. We will employ it for our regular nightly processing needs, and for more compute-intensive tasks such as large scale image coaddition campaigns, extraction of weak lensing shear from the full survey dataset, and massive seasonal reprocessing of the DES data. Data products will be available to the Collaboration and later to the public through a virtual-observatory compatible web portal. Our approach leverages investments in publicly available HPC systems, greatly reducing hardware and maintenance costs to the project, which must deploy and maintain only the storage, database platforms and orchestration and web portal nodes that are specific to DESDM. In Fall 2007, we tested the current DESDM system on both simulated and real survey data. We used Teragrid to process 10 simulated DES nights (3TB of raw data), ingesting and calibrating approximately 250 million objects into the DES Archive database. We also used DESDM to process and calibrate over 50 nights of survey data acquired with the Mosaic2 camera. Comparison to truth tables in the case of the simulated data and internal crosschecks in the case of the real data indicate that astrometric and photometric data quality is excellent.Comment: To be published in the proceedings of the SPIE conference on Astronomical Instrumentation (held in Marseille in June 2008). This preprint is made available with the permission of SPIE. Further information together with preprint containing full quality images is available at http://desweb.cosmology.uiuc.edu/wik

Intra- and inter-individual genetic differences in gene expression

Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.

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Efficient description of shape perturbations

Airbus wish to have efficient ways of describing perturbations of a manu- factured aerofoil from its design shape. The typical kind of perturbations expected are waves, steps, and bumps, and automatic classification into the classes is desired. Various possible methods of analysis were pro- posed and studied in some detail, including projection onto suitable basis functions, wavelets, and radial basis functions. Other methods were studied in less detail, but with the aim of giving a digital signature of defects that could be used to classify them

The New Generation Atlas of Quasar Spectral Energy Distributions from Radio to X-rays

We have produced the next generation of quasar spectral energy distributions (SEDs), essentially updating the work of Elvis et al. (1994) by using high-quality data obtained with several space and ground-based telescopes, including NASA's Great Observatories. We present an atlas of SEDs of 85 optically bright, non-blazar quasars over the electromagnetic spectrum from radio to X-rays. The heterogeneous sample includes 27 radio-quiet and 58 radio-loud quasars. Most objects have quasi-simultaneous ultraviolet-optical spectroscopic data, supplemented with some far-ultraviolet spectra, and more than half also have Spitzer mid-infrared IRS spectra. The X-ray spectral parameters are collected from the literature where available. The radio, far-infrared, and near-infrared photometric data are also obtained from either the literature or new observations. We construct composite spectral energy distributions for radio-loud and radio-quiet objects and compare these to those of Elvis et al., finding that ours have similar overall shapes, but our improved spectral resolution reveals more detailed features, especially in the mid and near-infrared.Comment: 46 pages, 10 figures, 10 tables, Accepted by ApJS. Composite SED data files for radio-loud and radio-quiet quasars (rlmsedMR.txt, rqmsedMR.txt) are included in the source (Other formats -> Source). Supplemental figures are not include

Educational innovation for infection control in Tanzania: Bridging the policy to practice gap

The incidence of hospital acquired infection in developing countries is between two to 20 times higher than in developed countries and is attributable to multiple causes. Evidence-based international policies and guidelines developed to improve infection prevention and control are often not used in practice in these countries. To combat this challenge, this article presents an innovative educational framework used to bridge the gap between policy written by global health agencies and the realities of practice in Tanzania

MoMo: Momentum Models for Adaptive Learning Rates

Training a modern machine learning architecture on a new task requires extensive learning-rate tuning, which comes at a high computational cost. Here we develop new adaptive learning rates that can be used with any momentum method, and require less tuning to perform well. We first develop MoMo, a Momentum Model based adaptive learning rate for SGD-M (Stochastic gradient descent with momentum). MoMo uses momentum estimates of the batch losses and gradients sampled at each iteration to build a model of the loss function. Our model also makes use of any known lower bound of the loss function by using truncation, e.g. most losses are lower-bounded by zero. We then approximately minimize this model at each iteration to compute the next step. We show how MoMo can be used in combination with any momentum-based method, and showcase this by developing MoMo-Adam - which is Adam with our new model-based adaptive learning rate. Additionally, for losses with unknown lower bounds, we develop on-the-fly estimates of a lower bound, that are incorporated in our model. Through extensive numerical experiments, we demonstrate that MoMo and MoMo-Adam improve over SGD-M and Adam in terms of accuracy and robustness to hyperparameter tuning for training image classifiers on MNIST, CIFAR10, CIFAR100, Imagenet, recommender systems on the Criteo dataset, and a transformer model on the translation task IWSLT14.Comment: 25 pages, 11 figure