Spontaneous Formation of One-dimensions Ripples in Transit to Highly Ordered Two-dimensional Herringbone Structures Through Sequential and Unequal Biaxial Mechanical Stretching

The authors report the formation of various submicron wrinkle patterns and their transition from one-dimensional (1D) ripples to two-dimensional (2D) herringbone structures on poly(dimethylsiloxane) films. Using mechanical force they can separately control the amount and timing of strain applied to the substrate on both planar directions (either simultaneously or sequentially), which appears to be critical to maneuver the pattern formation in real time. They demonstrate reversible transitions from flat to 1D ripple, to ripple with bifurcation, to ripple/herringbone mixed features, and to well-controlled formation of a highly ordered zigzag-based 2D herringbone structures

EFFICIENT APPROXIMATION FOR LARGE-SCALE KERNEL CLUSTERING ANALYSIS

Kernel k-means is useful for performing clustering on nonlinearly separable data. The kernel k-means is hard to scale to large data due to the quadratic complexity. In this paper, we propose an approach which utilizes the low-dimensional feature approximation of the Gaussian kernel function to capitalize a fast linear k-means solver to perform the nonlinear kernel k-means. This approach takes advantage of the efficiency of the linear solver and the nonlinear partitioning ability of the kernel clustering. The experimental results show that the proposed approach is much more efficient than a normal kernel k- means solver and achieves similar clustering performance

Strain responsive concave and convex microlens arrays

We report the fabrication of single-component, strain responsive microlens arrays with real-time tunability. The concave lens array is fabricated by patterning hard oxide layer on a bidirectionally prestretched soft elastomer, polydimethylsiloxane PDMS followed by confined buckling upon release of the prestrain. The convex microlens array is replica molded from the concave lenses in PDMS. Due to difference in lens formation mechanisms, the two types of lenses show different tunable range of focal length in response to the applied strain: large focal length change is observed from the concave microlens array, whereas that from the convex microlens array is much smaller

The Impact of Story Reading and Retelling on the Oral Development of English Language Learners

Due to the increasing population of English language learners in the United States and the academic gap between their English-speaking counterparts, the purpose of this study was to explore the impact of the structured instruction composed of story reading, retelling, higher-order thinking skills and ESL strategies on the oral language development of English language learners. The data utilized in this study was retrieved from the archived data from a five-year longitudinal research project targeting Spanish-speaking students with limited English language proficiency at elementary level. All the participants in the treatment groups received the structured language instruction from the entry of kindergarten to the end of third grade with multiple instructional components. In order to compare the oral proficiency of students in two different treatment conditions, 64 third grade students were randomly selected from the transitional bilingual education program. Among the 64 participants, 32 received enhanced English instruction and the other 32 received only typical ESL instruction. The enhanced instruction the participants received in the year of third grade included story reading, retelling, content area integration, direct vocabulary instruction, higher-order thinking skills and ESL strategies. All the participants in treatment and control groups received curriculum-based vocabulary measure and standardized assessment. The first research question focused on the oral fluency based on the curriculum-based vocabulary knowledge. The findings suggested significant impact of time and treatment, and also a significant interaction effect between these two variables, indicating that the intervention had a significant effect on the students’ oral proficiency based on the curriculum-based measurement and the effect was more evident in the posttest. The second and third research question focused on students’ vocabulary knowledge and listening comprehension on the measure of standardized assessment after receiving repeated story reading and explicit vocabulary instruction. The results showed the treatment group outperformed the control group in the aspects of vocabulary knowledge and listening comprehension. The findings suggested that the students who received structured instruction of story reading and retelling incorporating higher-order thinking skills and ESL strategies showed better performance in oral fluency, vocabulary knowledge and listening comprehension

Data-driven spatial-temporal analysis of highway traffic volume considering weather and festival impacts

This paper aims to discover the relationships among the weather, holidays, and the traffic volume using multisource data from the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) and to reveal the corresponding regional spatial–temporal traffic and migration patterns. Using accurate hourly weather and traffic volume data, this study examines the traffic volume from the origin to the destination county by considering traffic factors, weather factors, and temporal factors. A Random-effect regression model and a random forest model are established to analyze the above factors and identify the factors that contribute to the annual variation in traffic patterns. An RER + RF fusion prediction model based on ridge regression is proposed to predict the hourly traffic volume from origin to destination county, and is adopted in the spatial–temporal submodels. The results show that the impact of rainfall on traffic volume varies as the rainfall varies, and a rain-induced traffic pattern shift towards highway travel is found, which interacts with the negative effect of rainfall on highway traffic volumes. The Spring Festival holiday witnesses a V-shaped traffic volume curve during the study period. Some traffic pattern differences are also found in different spatial–temporal submodels. The RER + RF fusion model performs better in predicting in parent model and most of the spatial–temporal submodels, which validates the proposed model in predicting the traffic volume. The findings can provide transport agencies, urban planning agencies, and urban agglomeration travelers with valuable information for highway transport activity analysis considering the effects of weather and festival events