FROM INTERACTION TO INTERACTION: EXPLORING SHARED RESOURCES CONSTRUCTED THROUGH AND MEDIATING CLASSROOM SCIENCE LEARNING

Recent reform documents and science education literature emphasize the importance of scientific argumentation as a discourse and practice of science that should be supported in school science learning. Much of this literature focuses on the structure of argument, whether for assessing the quality of argument or designing instructional scaffolds. This study challenges the narrowness of this research paradigm and argues for the necessity of examining students' argumentative practices as rooted in the complex, evolving system of the classroom. Employing a sociocultural-historical lens of activity theory (Engestrӧm, 1987, 1999), discourse analysis is employed to explore how a high school biology class continuously builds affordances and constraints for argumentation practices through interactions. The ways in which argumentation occurs, including the nature of teacher and student participation, are influenced by learning goals, classroom norms, teacher-student relationships and epistemological stances constructed through a class' interactive history. Based on such findings, science education should consider promoting classroom scientific argumentation as a long-term process, requiring supportive resources that develop through continuous classroom interactions. Moreover, in order to understand affordances that support disciplinary learning in classroom, we need to look beyond just disciplinary interactions. This work has implications for classroom research on argumentation and teacher education, specifically, the preparation of teachers for secondary science teaching

A uniformly accurate (UA) multiscale time integrator pseudospectral method for the Dirac equation in the nonrelativistic limit regime

We propose and rigourously analyze a multiscale time integrator Fourier pseudospectral (MTI-FP) method for the Dirac equation with a dimensionless parameter $\varepsilon\in(0,1]$ which is inversely proportional to the speed of light. In the nonrelativistic limit regime, i.e. $0<\varepsilon\ll 1$, the solution exhibits highly oscillatory propagating waves with wavelength $O(\varepsilon^2)$ and $O(1)$ in time and space, respectively. Due to the rapid temporal oscillation, it is quite challenging in designing and analyzing numerical methods with uniform error bounds in $\varepsilon\in(0,1]$. We present the MTI-FP method based on properly adopting a multiscale decomposition of the solution of the Dirac equation and applying the exponential wave integrator with appropriate numerical quadratures. By a careful study of the error propagation and using the energy method, we establish two independent error estimates via two different mathematical approaches as $h^{m_0}+\frac{\tau^2}{\varepsilon^2}$ and $h^{m_0}+\tau^2+\varepsilon^2$, where $h$ is the mesh size, $\tau$ is the time step and $m_0$ depends on the regularity of the solution. These two error bounds immediately imply that the MTI-FP method converges uniformly and optimally in space with exponential convergence rate if the solution is smooth, and uniformly in time with linear convergence rate at $O(\tau)$ for all $\varepsilon\in(0,1]$ and optimally with quadratic convergence rate at $O(\tau^2)$ in the regimes when either $\varepsilon=O(1)$ or $0<\varepsilon\lesssim \tau$. Numerical results are reported to demonstrate that our error estimates are optimal and sharp. Finally, the MTI-FP method is applied to study numerically the convergence rates of the solution of the Dirac equation to those of its limiting models when $\varepsilon\to0^+$.Comment: 25 pages, 1 figur

Numerical methods and comparison for the Dirac equation in the nonrelativistic limit regime

We analyze rigorously error estimates and compare numerically spatial/temporal resolution of various numerical methods for the discretization of the Dirac equation in the nonrelativistic limit regime, involving a small dimensionless parameter $0<\varepsilon\ll 1$ which is inversely proportional to the speed of light. In this limit regime, the solution is highly oscillatory in time, i.e. there are propagating waves with wavelength $O(\varepsilon^2)$ and $O(1)$ in time and space, respectively. We begin with several frequently used finite difference time domain (FDTD) methods and obtain rigorously their error estimates in the nonrelativistic limit regime by paying particular attention to how error bounds depend explicitly on mesh size $h$ and time step $\tau$ as well as the small parameter $\varepsilon$. Based on the error bounds, in order to obtain `correct' numerical solutions in the nonrelativistic limit regime, i.e. $0<\varepsilon\ll 1$, the FDTD methods share the same $\varepsilon$-scalability on time step: $\tau=O(\varepsilon^3)$. Then we propose and analyze two numerical methods for the discretization of the Dirac equation by using the Fourier spectral discretization for spatial derivatives combined with the exponential wave integrator and time-splitting technique for temporal derivatives, respectively. Rigorous error bounds for the two numerical methods show that their $\varepsilon$-scalability on time step is improved to $\tau=O(\varepsilon^2)$ when $0<\varepsilon\ll 1$. Extensive numerical results are reported to support our error estimates.Comment: 34 pages, 2 figures. arXiv admin note: substantial text overlap with arXiv:1511.0119

What Causes the Target Stock Price Run-Up Prior to M&A Announcements?

We investigate the target stock price run-up prior to M&amp;A announcements between 1981 and 2011. About one third of the total price run-up occurs before announcements, and the pre-announcement run-up does not seem to be caused by market anticipation of M&amp;As, toehold acquisitions or reported insider trading. Instead, the pre-announcement run-up is significantly larger when media attention on insider trading is lower, when institutional ownership is lower, and when probability of informed trading is higher. The findings are consistent with the view that the target stock price run-up prior to M&amp;A announcements is caused by unreported insider trading

OncoDB: An interactive online database for analysis of gene expression and viral infection in cancer

Large-scale multi-omics datasets, most prominently from the TCGA consortium, have been made available to the public for systematic characterization of human cancers. However, to date, there is a lack of corresponding online resources to utilize these valuable data to study gene expression dysregulation and viral infection, two major causes for cancer development and progression. To address these unmet needs, we established OncoDB, an online database resource to explore abnormal patterns in gene expression as well as viral infection that are correlated to clinical features in cancer. Specifically, OncoDB integrated RNA-seq, DNA methylation, and related clinical data from over 10 000 cancer patients in the TCGA study as well as from normal tissues in the GTEx study. Another unique aspect of OncoDB is its focus on oncoviruses. By mining TCGA RNA-seq data, we have identified six major oncoviruses across cancer types and further correlated viral infection to changes in host gene expression and clinical outcomes. All the analysis results are integratively presented in OncoDB with a flexible web interface to search for data related to RNA expression, DNA methylation, viral infection, and clinical features of the cancer patients. OncoDB is freely accessible at http://oncodb.org