Hodge ideals and spectrum of isolated hypersurface singularities

We introduce Hodge ideal spectrum for isolated hypersurface singularities to see the difference between the Hodge ideals and the microlocal $V$-filtration modulo the Jacobian ideal. Via the Tjurina subspectrum, we can compare the Hodge ideal spectrum with the Steenbrink spectrum which can be defined by the microlocal $V$-filtration. As a consequence of a formula of Mustata and Popa, these two spectra coincide in the weighted homogeneous case. We prove sufficient conditions for their coincidence and non-coincidence in some non-weighted-homogeneous cases where the defining function is semi-weighted-homogeneous or with non-degenerate Newton boundary in most cases. We also show that the convenience condition can be avoided in a formula of Zhang for the non-degenerate case, and present an example where the Hodge ideals are not weakly decreasing even modulo the Jacobian ideal.Comment: 29 page

Three Reading-Intervention Teachers’ Identity Positioning and Practices to Motivate and Engage Emergent Bilinguals in an Urban Middle School

This study investigated three urban middle-school teachers’ practices with respect to motivating and engaging emergent bilinguals in reading-intervention classrooms by exploring the teachers’ identity positioning. The three teachers’ sociocultural and sociopolitical positioning of their students (e.g. students as individuals, as monolithic learners, or as problems) was found to be related to their practices for motivating and engaging the students (e.g. hybrid, calibrated, or imposed practices). The teachers’ historical and current resources partially shaped how they positioned their students. The findings support that teachers should not only learn motivational practices but also reflect critically on positioning processes in the classroom

Three reading-intervention teachers’ identity positioning and practices to motivate and engage emergent bilinguals in an urban middle school

This study investigated three urban middle-school teachers’ practices with respect to motivating and engaging emergent bilinguals in reading-intervention classrooms by exploring the teachers’ identity positioning. The three teachers’ sociocultural and sociopolitical positioning of their students (e.g., students as individuals, as monolithic learners, or as problems) was found to be related to their practices for motivating and engaging the students (e.g., hybrid, calibrated, or imposed practices). The teachers’ historical and current resources partially shaped how they positioned their students. The findings support that teachers should not only learn motivational practices but also reflect critically on positioning processes in the classroom

An International Comparison Study Exploring the Influential Variables Affecting Students’ Reading Literacy and Life Satisfaction

The Program for International Student Assessment (PISA) aims to provide comparative data on 15-year-olds’ academic performance and well-being. The purpose of the current study is to explore and compare the variables that predict the reading literacy and life satisfaction of U.S. and South Korean students. The random forest algorithm, which is a machine learning approach, was applied to PISA 2018 data (4,677 U.S. students and 6,650 South Korean students) to explore and select the key variables among 305 variables that predict reading literacy and life satisfaction. In each random forest analysis, one for the U.S. and another for South Korea, 23 variables were derived as key variables in students’ reading literacy. In addition, 23 variables in the U.S. and 26 variables in South Korea were derived as important variables for students’ life satisfaction. The multilevel analysis revealed that various student-, teacher- or school-related key variables derived from the random forest were statistically related to either U.S. and/or South Korean students’ reading literacy and/or life satisfaction. The current study proposes to use a machine learning approach to examine international large-scale data for an international comparison. The implications of the current study and suggestions for future research are discussed

Contributions to the Analyses of Recurrent Events and Competing Risk

There is a growing interest in the analysis of recurrent events data. Recurrent events are frequently considered as an outcome when a subject could possibly experience more than one event over follow-up period. Thus, It is important to consider previous events history to explore the relationship between the effects of covariates and the correlated failure times. We extend the Cox-type model with time-varying effect depending on the number and the gap time between previous events to enhance both model fit and prediction. Parameter estimation and statistical inference can be achieved via the partial likelihood. A statistical test procedure is provided to assess the existence of the triggering effects. We demonstrate our approach via comprehensive simulation studies and chronic pseudomonas infections in young cystic fibrosis patients’ data. Significantly, our model provides better predictions than the existing models. When some patients do not adhere to their assigned treatments in a randomized trial, the standard intention-to-treat analysis may not properly estimate the effect of treatment on the outcome. Also, considering only received treatment without accounting for unmeasured confounders could be biased. Therefore, it is challenging to obtain the true treatment effect, which can be observed when all subjects comply their assigned regime. Instrumental variable methods help us to consistently estimate the average causal effect of an exposure on some outcome of interest even in the presence of latent confounding. We apply Abadie's weighting scheme to estimate corresponding local average response functions in survival analysis. The method is demonstrated by simulation studies and the colorectal cancer screening data, designed and sponsored by the National Cancer Institute. Competing risks also occur when subjects can experience one or more events which compete with the outcome of interest. In these cases, the competing risk inhibits to observe the event of interest or modifies the chance that this event occurs. We extend existing parametric approaches to estimate the cumulative incidence function for considering both left truncation and interval in competing risks settings. This parametric method is applied to data from the study of osteoporotic fractures to bone mineral density testing interval with age as time scale.Doctor of Philosoph

Structural shift and increasing variety in Korea, 19602010 : empirical evidence of the economic development model by the creation of new sectors

In this paper, we examine the experiences of the Korean economy alongside theoretical knowledge of economic development and structural change. To demonstrate the generalized hypotheses on structural change, inputoutput tables of Korea, from 1960 to 2010, were analyzed. Our interest in taking time series of inputoutput tables originates from the following two issues. Firstly, we raise the question of whether Korean industrial structure changes have followed a certain pattern of structural shifts as well as increasing variety. Secondly, if so, it is questioned how the meso-level conditions for economic development could be explained from such a pattern. To search for answers, we adopt a model of the economic development by the creation of new sectors, named TEVECON, as our theoretical framework. Using this growth model, we derive hypotheses about how the structural change could affect economic development, and then we determine how the empirical analysis of the Korean economy verifies and deepens our understanding of structural change and economic development. This paper contributes to the empirical validation of the theoretical knowledge of economic development by the emergence of key sectors and the creation of new industries

Hide-and-Tell: Learning to Bridge Photo Streams for Visual Storytelling

Visual storytelling is a task of creating a short story based on photo streams. Unlike existing visual captioning, storytelling aims to contain not only factual descriptions, but also human-like narration and semantics. However, the VIST dataset consists only of a small, fixed number of photos per story. Therefore, the main challenge of visual storytelling is to fill in the visual gap between photos with narrative and imaginative story. In this paper, we propose to explicitly learn to imagine a storyline that bridges the visual gap. During training, one or more photos is randomly omitted from the input stack, and we train the network to produce a full plausible story even with missing photo(s). Furthermore, we propose for visual storytelling a hide-and-tell model, which is designed to learn non-local relations across the photo streams and to refine and improve conventional RNN-based models. In experiments, we show that our scheme of hide-and-tell, and the network design are indeed effective at storytelling, and that our model outperforms previous state-of-the-art methods in automatic metrics. Finally, we qualitatively show the learned ability to interpolate storyline over visual gaps.Comment: AAAI 2020 pape

Thiol-linked peroxidase activity of human ceruloplasmin

AbstractHuman ceruloplasmin exhibited different antioxidant effects according to the electron donors in a metal-catalyzed oxidation system. Purified ceruloplasmin did not play a significant role in the protection of DNA strand breaks in the ascorbate/Fe3+/O2 system. However, when ascorbates were replaced with a thiol-reducing equivalent such as dithiothreitol, DNA strand breaks were significantly prevented by the same amount of ceruloplasmin. Ceruloplasmin did not catalyze the decomposition of H2O2 in the absence of reduced glutathione. On the contrary, ceruloplasmin showed a potent peroxidase ability to destroy H2O2 in the presence of reduced glutathione. In conclusion, the removal of H2O2 by human ceruloplasmin is not simply stoichiometric but thiol-dependent