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"Seeing" Data Like an Expert: An Eye-Tracking Study Using Graphical Data Representations
No full textGiven the centrality of data visualizations in communicating scientific information, increased emphasis has been placed on the development of students’ graph literacy—the ability to generate and interpret data representations—to foster understanding of domain-specific knowledge and the successful navigation of everyday life. Despite prior literature that identifies student difficulties and methods to improve graphing competencies, there is little understanding as to how learners develop these skills. To gain a better resolution of the cognitive basis by which individuals “see” graphs, this study uses eye tracking (ET) to compare the strategies of non–science undergraduates (n = 9), early (n = 7) and advanced (n = 8) biology undergraduates, graduate students (n = 6), and science faculty (n = 6) in making sense of data displays. Results highlight variation in how individuals direct their attention (i.e., fixations and visual search patterns) when completing graph-based tasks as a function of science expertise. As research on the transition from novice to expert is crucially important in understanding how we might design curricula that help novices move toward more expert-like performance, this study has implications for the advancement of new strategies to aid the teaching and learning of data analysis skills
Template Independent Component Analysis: Targeted and Reliable Estimation of Subject-level Brain Networks using Big Data Population Priors
No full textLarge brain imaging databases contain a wealth of information on brain organization in the populations they target, and on individual variability. While such databases have been used to study group-level features of populations directly, they are currently underutilized as a resource to inform single-subject analysis. Here, we propose leveraging the information contained in large functional magnetic resonance imaging (fMRI) databases by establishing population priors to employ in an empirical Bayesian framework. We focus on estimation of brain networks as source signals in independent component analysis (ICA). We formulate a hierarchical “template” ICA model where source signals—including known population brain networks and subject-specific signals—are represented as latent variables. For estimation, we derive an expectation–maximization (EM) algorithm having an explicit solution. However, as this solution is computationally intractable, we also consider an approximate subspace algorithm and a faster two-stage approach. Through extensive simulation studies, we assess performance of both methods and compare with dual regression, a popular but ad-hoc method. The two proposed algorithms have similar performance, and both dramatically outperform dual regression. We also conduct a reliability study utilizing the Human Connectome Project and find that template ICA achieves substantially better performance than dual regression, achieving 75–250% higher intra-subject reliability. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement
Context-enriched identification of particles with a convolutional network for neutrino events
No full textParticle detectors record the interactions of subatomic particles and their passage through matter. The identification of these particles is necessary for in-depth physics analysis. While particles can be identified by their individual behavior as they travel through matter, the full context of the interaction in which they are produced can aid the classification task substantially. We have developed the first convolutional neural network for particle identification which uses context information. This is also the first implementation of a four-tower siamese-type architecture both for separation of independent inputs and inclusion of context information. The network classifies clusters of energy deposits from the NOv A neutrino detectors as electrons, muons, photons, pions, and protons with an overall efficiency and purity of 83.3% and 83.5%, respectively. We show that providing the network with context information improves performance by comparing our results with a network trained without context information
Predicting Voluntary Exercise Training among Korean Firefighters: Using Elicitation Study and the Theory of Planned Behavior
No full textBackground: Firefighters are required to have high levels of aerobic and anaerobic power because they often perform physically demanding work in dangerous environments. Therefore, it is important to find out salient factors influencing voluntary exercise training among Korean firefighters based on well-validated theory. Methods: The present study conducted an elicitation study to elicit salient behavioral, normative, and control beliefs about exercise training among Korean firefighters and identified salient beliefs that have a significant indirect effect on behavior through intention using structural equation modeling. Results: Although ten modal salient beliefs obtained from our elicitation study are similar to those elicited from previous TPB belief-based research with a focus on exercise behavior, only three of these (i.e., “improves my physical ability” (coef. = 0.078, p = 0.006), “takes too much time” (coef. = 0.064, p = 0.023), and “colleagues” (coef. = 0.069, p = 0.016) indirectly influenced exercise training behavior through intention among Korean firefighters. Conclusions: Our results may contribute to the literature by providing important information suggesting that three modal salient beliefs are major cognitive determinants of exercise training behavior among Korean firefighters and they may play an essential role in developing effective programs or policies for promoting Korean firefighters’ exercise training
Complete Measurement of the Electromagnetic Form Factors
No full textThe exclusive process , with and , has been studied at = 2.396 GeV for measurement of the Λ electric and magnetic form factors, and . A data sample, corresponding to an integrated luminosity of 66.9pb, was collected with the BESIII detector for this purpose. A multi-dimensional analysis with a complete decomposition of the spin structure of the reaction enables a determination of the modulus of the ratio and, for the first time for any baryon, the relative phase . The resulting values are obtained using the recent and most precise measured value of the asymmetry parameter = to be = and , respectively. In addition, the cross section is measured with unprecedented precision to be pb, which corresponds to an effective form factor of . The contribution from two-photon exchange is found to be negligible. Our result enables the first complete determination of baryon time-like electromagnetic form factors
Cross section measurements of and at center-of-mass energies from 2.10 to 3.08 GeV
No full textWe measure the Born cross sections of the process at center-of-mass (c.m.) energies, , between 2.100 and 3.080 GeV. The data were collected using the BESIII detector at the BEPCII collider. An enhancement at = 2.232 GeV is observed, very close to the production threshold. A similar enhancement at the same c.m. energy is observed in the cross section. The energy dependence of the and cross sections differs significantly from that of
Observation of the decay
No full textUsing a total of 9.0 fb of collision data with center-of-mass energies between 4.15 and 4.30 GeV collected by the BESIII detector, we search for the processes with for . We report the first observation of , a new decay mode of the , with a statistical significance of more than 5. Normalizing to the previously established process with , we find , where the first error is statistical and the second is systematic. We set 90% confidence level upper limits on the corresponding ratios for the decays to and of 19 and 1.1, respectively
Guidelines for DNA recombination and repair studies: Mechanistic assays of DNA repair processes
No full textUnderstanding the plasticity of genomes has been greatly aided by assays for recombination, repair and mutagenesis. These assays have been developed in microbial systems that provide the advantages of genetic and molecular reporters that can readily be manipulated. Cellular assays comprise genetic, molecular, and cytological reporters. The assays are powerful tools but each comes with its particular advantages and limitations. Here the most commonly used assays are reviewed, discussed, and presented as the guidelines for future studies
Rad52 Restrains Resection at DNA Double-Strand Break Ends in Yeast
No full textRad52 is a key factor for homologous recombination (HR) in yeast. Rad52 helps assemble Rad51-ssDNA nucleoprotein filaments that catalyze DNA strand exchange, and it mediates single-strand DNA annealing. We find that Rad52 has an even earlier function in HR in restricting DNA double-stranded break ends resection that generates 3′ single-stranded DNA (ssDNA) tails. In fission yeast, Exo1 is the primary resection nuclease, with the helicase Rqh1 playing a minor role. We demonstrate that the choice of two extensive resection pathways is regulated by Rad52. In rad52 cells, the resection rate increases from ∼3–5 kb/h up to ∼10–20 kb/h in an Rqh1-dependent manner, while Exo1 becomes dispensable. Budding yeast Rad52 similarly inhibits Sgs1-dependent resection. Single-molecule analysis with purified budding yeast proteins shows that Rad52 competes with Sgs1 for DNA end binding and inhibits Sgs1 translocation along DNA. These results identify a role for Rad52 in limiting ssDNA generated by end resection