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522 results on '"Li, Tingxuan"'

1. Effects of Four Species of Polygonum on Nitrogen and Phosphorus Removal from Simulated Domestic Sewage

Author

LI Zhe, WANG Qiaohong, ZHENG Zicheng, and LI Tingxuan

Subjects
domestic sewage, polygonum plants, nitrogen and phosphorus removal, accumulation of nitrogen and phosphorus, Environmental sciences, GE1-350, Agriculture
Abstract

[Objective] To investigate the water purification capabilities of Polygonum species and assess their suitability for the remediation of domestic sewage. [Methods] Polygonum hydropiper, Polygonum orientale, Polygonum divaricatum and Polygonum lapathifolium were selected as the research objects. The removal effects of total nitrogen (TN), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3--N), and total phosphorus (TP) in two concentrations of domestic sewage by these four species of Polygonum were discussed through a simulated hydroponic experiment. Additionally, the accumulation ability of Polygonum species to nitrogen and phosphorus in sewage was examined. [Results] (1) All four species of Polygonum exhibited good removal effects on nitrogen and phosphorus in two concentrations of domestic sewage. (2) Under high concentration sewage treatment, the removal rates of TN, NH4+-N and TP by Polygonum orientale, Polygonum divaricatum and Polygonum lapathifolium were 96.04%~97.41%, 94.60%~97.79% and 98.78%~99.68% (28 days), respectively, which were significantly higher than those of Polygonum hydropiper (p

Published
2024
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2. The Use of Cognitive Diagnostic Modeling in the Assessment of Computational Thinking

Author

Li, Tingxuan and Traynor, Anne

Abstract

Computational thinking (CT) is a set of cognitive skills that every child should acquire. K-12 classrooms are expected to provide students opportunities (tasks) to think computationally. We introduce a CT competency assessment for middle school students. The assessment design process started by establishing a cognitive model of CT domain mastery, in which three broad skill types were identified to represent CT competency. After multiple-choice item prototypes were written, pilot tested, and revised, 15 of them were finally selected to be administered to 564 students in two middle schools in the Midwestern United States. Using a cognitive diagnostic scoring model, mastery classifications for each student were determined that can be used diagnostically by teachers as a pretest and, perhaps in the future, to compare the outcomes of CT instructional programs. The results inform an initial understanding of typical learning progressions in CT at the middle school level.

Published
2022
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12. Japanese How-to Tip Machine Reading Comprehension by Multi-task Learning Based on Generative Model

Author

Wang, Xiaotian, Li, Tingxuan, Tamura, Takuya, Nishida, Shunsuke, Zhu, Fuzhu, Utsuro, Takehito, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ekštein, Kamil, editor, Pártl, František, editor, and Konopík, Miloslav, editor

Published
2023
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13. A Bioenergy Competency Assessment Tool: Development and Validation

Author

Li, Tingxuan, Clase, Kari L., Li, Weiling, and Traynor, Anne

Abstract

This research is motivated by the perspective that when empirical studies and assessment frameworks inform each other, assessments can enrich science education and strengthen its connections to modern science. The research proposes a bioenergy competency assessment for science education. It uses an argument-based approach to validation. Multiple types of validity evidence were collected to support the proposed scores use and scores interpretation. Along with reporting a series of psychometric properties of response data, the findings indicated that empirical response data corresponded to the hypothesized data structure. The latent logistic scale established through a generalized partial credit model (GPCM) seemed useful in measuring students' bioenergy competency.

Published
2019

34. Gauging Uncertainty in Test-to-Curriculum Alignment Indices

Author

Traynor, Anne, Li, Tingxuan, and Zhou, Shuqi

Abstract

During the development of large-scale school achievement tests, panels of independent subject-matter experts use systematic judgmental methods to rate the correspondence between a given test's items and performance objective statements. The individual experts' ratings may then be used to compute summary indices to quantify the match between a given test and its target item domain. The magnitude of alignment index variability across experts within a panel, and randomly-sampled panels, is largely unknown, however. Using rater-by-item data from alignment reviews of 14 US states' achievement tests, we examine observed distributions and estimate standard errors for three alignment indices developed by Webb. Our results suggest that alignment decisions based on the recommended criterion for the balance-of-representation index may often be uncertain, and that the criterion for the depth-of-knowledge consistency index should perhaps be reconsidered. We also examine current recommendations about the number of expert panelists required to compute these alignment indices.

Published
2020
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43. The Use of Cognitive Diagnostic Modeling in the Assessment of Computational Thinking

Author

Li, Tingxuan

Abstract

In order to achieve broadening participation in computer science and other careers related to computing, middle school classrooms should provide students opportunities (tasks) to think like a computer scientist. Researchers in computing education promote the idea that programming skill should not be a pre-requisite for students to display computational thinking (CT). Thus, some tasks that aim to deliberately elicit students' CT competency should be stand-alone tasks rather than coding fluency-oriented tasks. Guided by this approach, this assessment design process began by examining national standards in CT. A Q-matrix (i.e., item-attribute alignment table) was then developed and modified using (a) literature in CT, (b) input from subject-matter experts, and (c) cognitive interviews with a small sample of students. After multiple-choice item prototypes were written, pilot-tested, and revised, 15 of them were finally selected to be administered to 564 students in two middle schools in the Mid-western US. Through cognitive diagnostic modeling, the estimation results yielded mastery classifications or subscores that can be used diagnostically by teachers. The results help teachers facilitate students' "mastery orientations," that is, to address the gap between what students know and what students need to know in order to meet desired learning goals. By equipping teachers with a diagnostic classification based assessment, this research has the capacity to inform instruction which, in turn, will enrich students' learning experience in CT. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2019

45. An ATP-responsive metal–organic framework against periodontitis via synergistic ion-interference-mediated pyroptosis.

Author

Yang, Qijing, Sun, Xiaolin, Ding, Qihang, Qi, Manlin, Liu, Chengyu, Li, Tingxuan, Shi, Fangyu, Wang, Lin, Li, Chunyan, and Kim, Jong Seung

Subjects
MAGNESIUM ions, LACTATE dehydrogenase, ZINC ions, STROMAL cells, PYROPTOSIS
Abstract

Periodontitis involves hyperactivated stromal cells that recruit immune cells, exacerbating inflammation. This study presents an ATP-responsive metal–organic framework (Mg/Zn-MOF) designed for periodontitis treatment, utilizing ion interference to modulate immune responses and prevent tissue destruction. Addressing the challenges of synergistic ion effects and targeted delivery faced by traditional immunomodulatory nanomaterials, the Mg/Zn-MOF system is activated by extracellular ATP—a pivotal molecule in periodontitis pathology—ensuring targeted ion release. Magnesium and zinc ions released from the framework synergistically inhibit membrane pore formation by attenuating Gasdermin D (GSDMD) expression and activation. This action curtails pyroptosis, lactate dehydrogenase and IL-1β release, thwarting the onset of inflammatory cascades. Mechanistically, Mg/Zn-MOF intervenes in both the NLRP3/Caspase-1/GSDMD and Caspase-11/GSDMD pathways to mitigate pyroptosis. In vivo assessments confirm its effectiveness in diminishing inflammatory cell infiltration and preserving collagen integrity, thereby safeguarding against periodontal tissue damage and bone loss. This investigation highlights the promise of ion-interference strategies in periodontitis immunotherapy, representing a significant stride in developing targeted therapeutic approaches. [ABSTRACT FROM AUTHOR]

Published
2024
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