The Fluctuating Intergalactic Radiation Field at Redshifts z = 2.3-2.9 from He II and H I Absorption towards HE 2347-4342

We provide an in-depth analysis of the He II and H I absorption in the intergalactic medium (IGM) at redshifts z = 2.3-2.9 toward HE 2347-4342, using spectra from the Far Ultraviolet Spectroscopic Explorer (FUSE) and the Ultraviolet-Visual Echelle Spectrograph (UVES) on the VLT telescope. Following up on our earlier study (Kriss et al. 2001, Science, 293, 1112), we focus here on two major topics: (1) small-scale variability (Delta z = 10^-3) in the ratio eta = N(He II)/N(H I); and (2) an observed correlation of high-eta absorbers (soft radiation fields) with voids in the (H I) Ly-alpha distribution. These effects may reflect fluctuations in the ionizing sources on scales of 1 Mpc, together with radiative transfer through a filamentary IGM whose opacity variations control the penetration of 1-5 ryd radiation over 30-40 Mpc distances. Owing to photon statistics and backgrounds, we can measure optical depths over the ranges 0.1 < tau(HeII) < 2.3 and 0.02 < tau(HI) < 3.9, and reliably determine values of eta = 4 tau(HeII)/tau(HI) over the range 0.1 to 460. Values of eta = 20-200 are consistent with models of photoionization by quasars with observed spectral indices alpha_s = 0-3. Values of eta > 200 may require additional contributions from starburst galaxies, heavily filtered quasar radiation, or density variations. Regions with eta < 30 may indicate the presence of local hard sources. We find that eta is higher in "void" regions, where H I is weak or undetected and 80% of the path length has eta > 100. These voids may be ionized by soft sources (dwarf starbursts) or by QSO radiation softened by escape from the AGN cores or transfer through the "cosmic web". The apparent differences in ionizing spectra may help to explain the 1.45 Gyr lag between the reionization epochs, z(HI) = 6.2 +/-0.2 and z(HeII) = 2.8 +/-0.2.Comment: 27 pages, 7 figures, to appear in Ap

Tests of the ratio rule in categorization

Many theories of learning and memory (e.g. connectionist, associative, rational, exemplar-based) produce psychological magnitude terms as output (i.e. numbers representing the momentary level of some subjective property). Many theories assume that these numbers may be translated into choice probabilities via the Ratio Rule, a.k.a. the Choice Axiom (Luce, 1959) or the Constant-Ratio Rule (Clarke, 1957). We present two categorization experiments employing artificial, visual, prototype-structured stimuli constructed from twelve symbols positioned on a grid. The Ratio Rule is shown to be incorrect for these experiments, given the assumption that the magnitude terms for each category are univariate functions of the number of category-appropriate symbols contained in the presented stimulus. A connectionist winner-take-all model of categorical decision (Wills & McLaren, 1997) is shown to account for our data given the same assumption. The central feature underlying the success of this model is the assumption that categorical decisions are based on a Thurstonian choice process (Thurstone, 1927, Case V) whose noise distribution is not double exponential in form

Quality assessment of microarrays: Visualization of spatial artifacts and quantitation of regional biases

BACKGROUND: Quality-control is an important issue in the analysis of gene expression microarrays. One type of problem is regional bias, in which one region of a chip shows artifactually high or low intensities (or ratios in a two-channel array) relative to the majority of the chip. Current practice in quality assessment for microarrays does not address regional biases. RESULTS: We present methods implemented in R for visualizing regional biases and other spatial artifacts on spotted microarrays and Affymetrix chips. We also propose a statistical index to quantify regional bias and investigate its typical distribution on spotted and Affymetrix arrays. We demonstrate that notable regional biases occur on both Affymetrix and spotted arrays and that they can make a significant difference in the case of spotted microarray results. Although strong biases are also seen at the level of individual probes on Affymetrix chips, the gene expression measures are less affected, especially when the RMA method is used to summarize intensities for the probe sets. A web application program for visualization and quantitation of regional bias is provided at . CONCLUSION: Researchers should visualize and measure the regional biases and should estimate their impact on gene expression measurements obtained. Here, we (i) introduce pictorial visualizations of the spatial biases; (ii) present for Affymetrix chips a useful resolution of the biases into two components, one related to background, the other to intensity scale factor; (iii) introduce a single parameter to reflect the global bias present across an array. We also examine the pattern distribution of such biases and conclude that algorithms based on smoothing are unlikely to compensate adequately for them

RCMAT: a regularized covariance matrix approach to testing gene sets

<p>Abstract</p> <p>Background</p> <p>Gene sets are widely used to interpret genome-scale data. Analysis techniques that make better use of the correlation structure of microarray data while addressing practical "n<p" concerns could provide a real increase in power. However correlation structure is hard to estimate with typical genomics sample sizes. In this paper we present an extension of a classical multivariate procedure that confronts this challenge by the use of a regularized covariance matrix.</p> <p>Results</p> <p>We evaluated our testing procedure using both simulated data and a widely analyzed diabetes data set. We compared our approach to another popular multivariate test for both sets of data. Our results suggest an increase in power for detecting gene set differences can be obtained using our approach relative to the popular multivariate test with no increase in the false positive rate.</p> <p>Conclusion</p> <p>Our regularized covariance matrix multivariate approach to gene set testing showed promise in both real and simulated data comparisons. Our findings are consistent with the recent literature in gene set methodology.</p

2016 Nebraska Water Leaders Academy - Final Report

The effective management of Nebraska’s water resources is evermore challenged by variations in weather, climate, technology, socioeconomic policies, and regulation. Anthropogenic climate change, declining water tables and stream flows, increasing demands on freshwater, aging water infrastructure, fiscal constraints, and impacts on aquatic organisms are particularly imminent challenges in Nebraska and around the world (Pahl-Wostl et al., 2013; Pittock et al., 2008; USACE, 2010). Sustaining freshwater ecosystem services in the face of emerging environmental threats presents an immense societal dilemma worldwide (Pittock et al., 2013; Rockström et al., 2009, Millenium Ecosystem Assessment, 2005). The rapidly changing conditions of water resources in Nebraska demands knowledgeable and skilled leaders (Burbach, et al., 2015; Lincklaen Arriëns & When de Montalvo, 2013; Morton & Brown, 2011). McIntosh and Taylor (2013) assert that in order to meet future water challenges, “leadership is needed to initiate and drive change, enable innovation (both incremental and radical), build shared visions for a more sustainable water future, and deliver these visions through aligning resources and building commitment to collective success” (p. 46). Building leadership capacity is required to drive the necessary change (Brasier et al., 2011; Morton et al., 2011; Pahl-Wostl et al., 2011; Redekop, 2010; Taylor et al., 2012). Recognizing this critical need for future leaders in water resources, the Nebraska State Irrigation Associatio

The Nebraska Water Leaders Academy: Blending Science with Research and Engagement

Nebraska faces increasing challenges to its water resources due to changing climate, mounting demand for freshwater, aging infrastructure, declining aquatic species and declining water tables and stream flows in some areas, with unprecedented floods in others. These challenges require new and innovative leadership approaches for sustainable water management. In response, the Nebraska Water Leaders Academy (NWLA) was created through a partnership between the Nebraska State Irrigation Association and the University of Nebraska-Lincoln, to prepare Nebraska’s future leaders in the water arena to meet these challenges. The NWLA was designed to offer an educational and developmental experience to mid-level professionals. Information is presented by experts from various technical disciplines in six sessions, which are held throughout the state of Nebraska over the course of one year. Topics include, but are not limited to, basic hydrology, economics, social issues and competing uses of water in Nebraska. The Academy also includes a strong leadership development component

A dynamic model for delta rhythm fit to high-frequency cortical activity data shows discrete functional connectivity in mouse cortex

Spontaneous activity as recorded by fMRI has often been used to infer active connections (\u27functional connectivity\u27) in the human brain through correlations of activity measures. Some serious questions have been raised about the interpretation of these correlations, which are often apparent only on time scales of tens of seconds. Confirmation of correlations in measures of activity on shorter time-scales closer to those of neural activity would be very desirable. Numerous mechanisms have been proposed for various rhythms but in the past half-century little consensus has been reached on the mechanism of any major rhythm. The recent development of high-throughput imaging methods enable us for the first time to rigorously and quantitatively test ideas about the dynamics of brain rhythms. We have generated high-resolution data on neural activity over most of one hemisphere of mouse cortex by voltage-sensitive dyes, in both anesthetized and awake animals. In previous work [1] we have analyzed relations between activity measures at different locations in terms of correlations. Here we fit these data to a predictive model, in which we attempt to predict the next change in activity at every point on cortex from the current pattern of activity over cortex. We fit both linear and non-linear models, whose parameters represent the intrinsic dynamics of local cortical regions and the inputs from distal regions. We find that all regions of mouse cortex appear to have virtually identical patterns of intrinsic dynamics (Figure 1A). We find that even a simple linear fit gives surprisingly sparse patterns of inferred connectivity. Where we have clear anatomical information, these fitted patterns appear to match known anatomy. Furthermore this fit can be used to identify the most prominent functional inputs into anatomically diffusely-connected areas such as the parietal association area (Figure 1B). Poster presentation from the Twenty Third Annual Computational Neuroscience Meeting: CNS*201

The LeFE Algorithm: Embracing the Complexity of Gene Expression in the Interpretation of Microarray Data

The LeFE algorithm has been developed to address the complex, non-linear regulation of gene expression. Interpretation of microarray data remains a challenge, and most methods fail to consider the complex, nonlinear regulation of gene expression. To address that limitation, we introduce Learner of Functional Enrichment (LeFE), a statistical/machine learning algorithm based on Random Forest, and demonstrate it on several diverse datasets: smoker/never smoker, breast cancer classification, and cancer drug sensitivity. We also compare it with previously published algorithms, including Gene Set Enrichment Analysis. LeFE regularly identifies statistically significant functional themes consistent with known biology.National Cancer Institute's Center for Cancer Researc

The evolutions of joint attention to objects between infants and their mothers: Diversity and convergence

The authors share a perception of human development as an opportunistic process, not arising from universal necessary causes, but drawing idiosyncratically on a variety of resources. In this paper they trace the evolution of idiosyncratic patterns of joint activity with objects, how the infant’s activity is mantained and directed, in two mother-child dyads until two years old. The authors also show that, althought the processes used by the two dyads are different, the same functions are achieved, like attracting attention, introducing a new topic, or assisting with difficulties.RESUMO: OS autores partilham a percepcção de que o desenvolvimento é oportunista, em vez de surgir de causas universais necessárias, é delineado idiossincraticamente por uma variedade de recursos. Neste artigo OS autores descrevem a evolução de padrões idiossincráticos de actividade conjunta com objectos em duas díades até aos 2 anos de idade, como a actividade da crianca é mantida e direccionada. Por outro lado, OS autores também mostram que apesar das duas díades usarem processos diferentes, alcançam as mesmas funções, como atraír a atenção, introduzir um tópico novo, ou ajudar nas dificuldades que o bebé tem