Students’ Self-Report of Motivational Orientation and Teacher Evaluation on Coping and Motivational Orientation Related to Elementary Students’ Mathematical Problem Solving and Reading Comprehension

The present study examined the correlations between motivational orientation and students’ academic performance in mathematical problem solving and reading comprehension. The main purpose is to see if students’ intrinsic motivation is related to their actual performance in different subject areas, math and reading. In addition, two different informants, students and teachers, were adopted to check whether the correlation is different by different informants. Pearson’s correlational analysis was a major method, coupled with regression analysis. The result confirmed the significant positive correlation between students’ academic performance and students’ self-report and teacher evaluation on their motivational orientation respectively. Teacher evaluation turned out with more predictive value for the academic achievement in math and reading. Between the subjects, mathematical problem solving showed higher correlation with most of the motivational subscales than reading comprehension did. The highest correlation was found between teacher evaluation on task orientation and students’ mathematical problem solving. The positive relationship between intrinsic motivation and academic achievement was proved. The disparity between students ’ self-report and teacher evaluation on motivational orientation was also addressed with the need of further examination.Siirretty Doriast

Satellite-based auroral tomography and time-varying volume reconstruction

Tomography, originally developed to observe the internal structure of a human body in medical applications, can also be applied to research in Space Science applications. An upcoming satellite mission incorporates two imagers for auroral observation in the upper atmosphere. For this mission, development of auroral volume reconstruction using tomographic imaging is useful for understanding the internal structure of auroras. We have shown that beam-pixel clipping in image reconstruction improves the quality of reconstructed images, compared to previous techniques. The goal is to develop a suitable algorithm for auroral volume reconstruction using auroral images measured from satellite-borne optical instruments. We have demonstrated that weighting factor approximation in algebraic methods plays a crucial role in the quality of volume reconstruction. We also have evaluated the effectiveness of this algorithm with measured images of known volumes using perspective projections. In addition, a time-varying volume reconstruction scheme is discussed where auroras move over time

Deep reinforcement learning for large-eddy simulation modeling in wall-bounded turbulence

The development of a reliable subgrid-scale (SGS) model for large-eddy simulation (LES) is of great importance for many scientific and engineering applications. Recently, deep learning approaches have been tested for this purpose using high-fidelity data such as direct numerical simulation (DNS) in a supervised learning process. However, such data are generally not available in practice. Deep reinforcement learning (DRL) using only limited target statistics can be an alternative algorithm in which the training and testing of the model are conducted in the same LES environment. The DRL of turbulence modeling remains challenging owing to its chaotic nature, high dimensionality of the action space, and large computational cost. In the present study, we propose a physics-constrained DRL framework that can develop a deep neural network (DNN)-based SGS model for the LES of turbulent channel flow. The DRL models that produce the SGS stress were trained based on the local gradient of the filtered velocities. The developed SGS model automatically satisfies the reflectional invariance and wall boundary conditions without an extra training process so that DRL can quickly find the optimal policy. Furthermore, direct accumulation of reward, spatially and temporally correlated exploration, and the pre-training process are applied for the efficient and effective learning. In various environments, our DRL could discover SGS models that produce the viscous and Reynolds stress statistics perfectly consistent with the filtered DNS. By comparing various statistics obtained by the trained models and conventional SGS models, we present a possible interpretation of better performance of the DRL model

Huffing and puffing about /f/-ing everything: language ideologies and phonological borrowing in South Korea

Scholars have noted that English usage in Korean society is laden with indexical value. On the one hand English is linked with modernity (Lee 2005), chicness (Park H.J. 2004), and global cosmopolitanism (Park J.K. 2009). On the other hand, for a long time it has also been linked with negative values, such as immodesty, pretentiousness, and being a traitor to the nation (Park J. 2009). While the traditional linguistic ideologies are still very much alive and in circulation, I argue that recently a new language ideology has been forming, which I call phonological accuracy. This shift occurs along with the changes in social climate and as Koreans are no longer viewed as citizens of what used to be the “hermit kingdom”, but see themselves as global citizens. As a result, phonemes from foreign languages which used to be markers of immodesty are now finding their way into everyday spoken Korean. By using a foreign phoneme, a speaker of Korean can position themselves as either a trendy global cosmopolitan, an elite snob whose loyalty to the nation is suspect, or a poser. In this paper, I focus on the phonological borrowing of /f/ and what it means to the modern day Korean, who is no longer limited to speaking "pure" Korean

Methods and mechanisms to improve endothelial colony forming cell (ECFC) survival and promote ECFC vasculogenesis in three dimensional (3D) collagen matrices in vitro and in vivo

Indiana University-Purdue University Indianapolis (IUPUI)Human cord blood (CB) derived circulating endothelial colony forming cells (ECFCs) display a hierarchy of clonogenic proliferative potential and possess de novo vessel forming ability upon implantation in immunodeficient mice. Since survival of ECFC post-implantation is a critical variable that limits in vivo vasculogenesis, we tested the hypothesis that activation of Notch signaling or co-implantation of ECFC with human platelet lysate (HPL) would enhance cultured ECFC vasculogenic abilities in vitro and in vivo. Co-implantation of ECFCs with Notch ligand Delta-like 1 (DL1) expressing OP9 stromal cells (OP9-DL1) decreased apoptosis of ECFC in vitro and increased vasculogenesis of ECFC in vivo. The co-culture of ECFC with HPL diminished apoptosis of ECFC by altering the expression of pro-survival molecules (pAkt, pBad and Bcl-xL) in vitro and increased vasculogenesis of human EC-derived vessels both in vitro and in vivo. Thus, activation of the Notch pathway by OP9-DL1 stromal cells or co-implantation of ECFC with HPL enhances vasculogenesis and augments blood vessel formation by diminishing apoptosis of the implanted ECFC. The results from this study will provide critical information for the development of a cell therapy for limb and organ re-vascularization that can be applied to recovery of ischemic tissues in human subjects

Yoshinaga Fumis Ōoku: Historical Imagination and the Potential of Japanese Womens Manga

This article analyzes three aspects of Yoshinaga Fumis Ōoku: The Inner Chambers: its rereading of Japanese history from a female perspective, its reconstruction of gender relations as entertainment, and its incorporation of the legacy of girls (shōjo) and Boys Love manga. Heavily influenced by Yoshiya Nobukos novel, Wives of the Tokugawa Family, Ōoku depicts a number of female shoguns and their male companions across generations in order to highlight the problems of the existing, oppressive social structure and portray relationships between the genders as initiated by women. A comprehensive description of the rise and fall of a female shogunate allows Yoshinaga to illustrate the transformation and reconstruction of gender as a social construct. This manner of storytelling is rooted in the tradition of girls manga, which explores the use of androgynous heroines. Ōoku also shares much in common with Yaoi manga, which successfully explores the theme of gender difference in depicting male homosexuality. By blurring the conventional boundaries between girls, Yaoi, and amateur fanwork manga (dōjinshi) and creatively incorporating the legacies of each genre, Yoshinagas Ōoku demonstrates the potential of Japanese womens manga, a feat deserving of high critical praise. In this work, Yoshinaga succeeds in adroitly challenging readers notions of gender while remaining firmly within the bounds of popular entertainment

Preclinical Development of Genetic Normalization Strategies to Treat Pitt-Hopkins Syndrome

Neurodevelopmental disorders (NDDs) are defined as a group of conditions with onset in the developmental period, including intellectual or language impairments, attention-deficit disorders, and autism spectrum disorder. The United States’ National Health Interview Survey has shown that 1 in 6 children have a developmental disability. The current guidelines for NDDs recommend undergoing an evaluation for genetic etiology and receiving general developmental interventions. Despite no approved treatments for NDDs, development of precision treatment strategies for NDDs has been on the rise. Pitt-Hopkins syndrome (PTHS) is a rare neurodevelopmental disorder caused by monoallelic mutations or deletions of Transcription Factor 4 (TCF4). A decade of basic research has led to an increased understanding of TCF4, including genetic variants and functional roles in brain development. The development of PTHS mouse models has expanded knowledge in molecular and pathophysiological mechanisms underlying PTHS, underpinning the potential therapeutic opportunities to treat the disorder. However, effective therapeutic approaches for PTHS have not been developed yet. The absence of a validated preclinical pipeline has ultimately impeded successful therapeutic development. Here I propose a genetic normalization strategy to treat PTHS and experimentally demonstrate the feasibility of treating PTHS by normalizing TCF4 expression. Furthermore, I address the challenges faced in developing a rational preclinical pipeline by characterizing the cell type-specific distribution of TCF4 and identifying a feasible intervention window. The studies comprising this dissertation provide an important framework for future rational design of genetic normalization clinical treatments for PTHS.Doctor of Philosoph

Lose The Views: Limited Angle CT Reconstruction via Implicit Sinogram Completion

Computed Tomography (CT) reconstruction is a fundamental component to a wide variety of applications ranging from security, to healthcare. The classical techniques require measuring projections, called sinograms, from a full 180$^\circ$ view of the object. This is impractical in a limited angle scenario, when the viewing angle is less than 180$^\circ$, which can occur due to different factors including restrictions on scanning time, limited flexibility of scanner rotation, etc. The sinograms obtained as a result, cause existing techniques to produce highly artifact-laden reconstructions. In this paper, we propose to address this problem through implicit sinogram completion, on a challenging real world dataset containing scans of common checked-in luggage. We propose a system, consisting of 1D and 2D convolutional neural networks, that operates on a limited angle sinogram to directly produce the best estimate of a reconstruction. Next, we use the x-ray transform on this reconstruction to obtain a "completed" sinogram, as if it came from a full 180$^\circ$ measurement. We feed this to standard analytical and iterative reconstruction techniques to obtain the final reconstruction. We show with extensive experimentation that this combined strategy outperforms many competitive baselines. We also propose a measure of confidence for the reconstruction that enables a practitioner to gauge the reliability of a prediction made by our network. We show that this measure is a strong indicator of quality as measured by the PSNR, while not requiring ground truth at test time. Finally, using a segmentation experiment, we show that our reconstruction preserves the 3D structure of objects effectively.Comment: Spotlight presentation at CVPR 201