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1,720 results on '"Zhao, Yingjie"'

1. Liberal-Conservative Hierarchies of Intercoder Reliability Estimators

Author

Zhao, Yingjie Jay, Feng, Guangchao Charles, Li, Dianshi Moses, Ao, Song Harris, Li, Ming Milano, Tuo, Zhan Thor, Huang, Hui, Deng, Ke, and Zhao, Xinshu

Subjects
Physics - Physics and Society
Abstract

While numerous indices of inter-coder reliability exist, Krippendorff's {\alpha} and Cohen's \{kappa} have long dominated in communication studies and other fields, respectively. The near consensus, however, may be near the end. Recent theoretical and mathematical analyses reveal that these indices assume intentional and maximal random coding, leading to paradoxes and inaccuracies. A controlled experiment with one-way golden standard and Monte Carlo simulations supports these findings, showing that \{kappa} and {\alpha} are poor predictors and approximators of true intercoder reliability. As consensus on a perfect index remains elusive, more authors recommend selecting the best available index for specific situations (BAFS). To make informed choices, researchers, reviewers, and educators need to understand the liberal-conservative hierarchy of indices, i.e., which indices produce higher or lower scores. This study extends previous efforts by expanding the math-based hierarchies to include 23 indices and constructing six additional hierarchies using Monte Carlo simulations. These simulations account for factors like the number of categories and distribution skew. The resulting eight hierarchies display a consistent pattern and reveal a previously undetected paradox in the Ir index., Comment: 30 pages

Published
2024

2. Phase engineering of giant second harmonic generation in Bi$_2$O$_2$Se

Author

Lou, Zhefeng, Zhao, Yingjie, Gong, Zhihao, Zhu, Ziye, Wu, Mengqi, Wang, Tao, Wang, Jialu, Qi, Haoyu, Zuo, Huakun, Xu, Zhuokai, Shen, Jichuang, Wang, Zhiwei, Li, Lan, Xu, Shuigang, Kong, Wei, Li, Wenbin, Zheng, Xiaorui, Wang, Hua, and Lin, Xiao

Subjects
Condensed Matter - Materials Science, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Two-dimensional (2D) materials with remarkable second-harmonic generation (SHG) hold promise for future on-chip nonlinear optics. Relevant materials with both giant SHG response and environmental stability are long-sought targets. Here, we demonstrate the enormous SHG from the phase engineering of a high-performance semiconductor, Bi$_2$O$_2$Se (BOS), under uniaxial strain. SHG signals captured in strained 20 nm-BOS films exceed those of NbOI$_2$ and NbOCl$_2$ of similar thickness by a factor of 10, and are four orders of magnitude higher than monolayer-MoS$_2$, resulting in a significant second-order nonlinear susceptibility on the order of 1 nm V$^{-1}$. Intriguingly, the strain enables continuous adjustment of the ferroelectric phase transition across room temperature. Consequently, an exceptionally large tunability of SHG, approximately six orders of magnitude, is achieved through strain or thermal modulation. This colossal SHG, originating from the geometric phase of Bloch wave functions and coupled with sensitive tunability through multiple approaches in this air-stable 2D semiconductor, opens new possibilities for designing chip-scale, switchable nonlinear optical devices.

Published
2024

5. Physics-Transfer Learning for Material Strength Screening

Author

Zhao, Yingjie, Zhang, Zian, and Xu, Zhiping

Subjects
Condensed Matter - Materials Science, Computer Science - Machine Learning, Physics - Computational Physics
Abstract

The strength of materials, like many problems in the natural sciences, spans multiple length and time scales, and the solution has to balance accuracy and performance. Peierls stress is one of the central concepts in crystal plasticity that measures the strength through the resistance of a dislocation to plastic flow. The determination of Peierls stress involves a multiscale nature depending on both elastic lattice responses and the energy landscape of crystal slips. Material screening by strength via the Peierls stress from first-principles calculations is computationally intractable for the nonlocal characteristics of dislocations, and not included in the state-of-the-art computational material databases. In this work, we propose a physics-transfer framework to learn the physics of crystal plasticity from empirical atomistic simulations and then predict the Peierls stress from chemically accurate density functional theory-based calculations of material parameters. Notably, the strengths of single-crystalline metals can be predicted from a few single-point calculations for the deformed lattice and on the {\gamma} surface, allowing efficient, high-throughput screening for material discovery. Uncertainty quantification is carried out to assess the accuracy of models and sources of errors, showing reduced physical and system uncertainties in the predictions by elevating the fidelity of training models. This physics-transfer framework can be generalized to other problems facing the accuracy-performance dilemma, by harnessing the hierarchy of physics in the multiscale models of materials science.

Published
2024

13. Predicting Fatigue Crack Growth via Path Slicing and Re-Weighting

Author

Zhao, Yingjie, Liu, Yong, and Xu, Zhiping

Subjects
Computer Science - Machine Learning
Abstract

Predicting potential risks associated with the fatigue of key structural components is crucial in engineering design. However, fatigue often involves entangled complexities of material microstructures and service conditions, making diagnosis and prognosis of fatigue damage challenging. We report a statistical learning framework to predict the growth of fatigue cracks and the life-to-failure of the components under loading conditions with uncertainties. Digital libraries of fatigue crack patterns and the remaining life are constructed by high-fidelity physical simulations. Dimensionality reduction and neural network architectures are then used to learn the history dependence and nonlinearity of fatigue crack growth. Path-slicing and re-weighting techniques are introduced to handle the statistical noises and rare events. The predicted fatigue crack patterns are self-updated and self-corrected by the evolving crack patterns. The end-to-end approach is validated by representative examples with fatigue cracks in plates, which showcase the digital-twin scenario in real-time structural health monitoring and fatigue life prediction for maintenance management decision-making.

Published
2023
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14. A Data-Driven Approach to Morphogenesis under Structural Instability

Author

Zhao, Yingjie and Xu, Zhiping

Subjects
Nonlinear Sciences - Pattern Formation and Solitons, Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Quantitative Methods, Statistics - Machine Learning
Abstract

Morphological development into evolutionary patterns under structural instability is ubiquitous in living systems and often of vital importance for engineering structures. Here we propose a data-driven approach to understand and predict their spatiotemporal complexities. A machine-learning framework is proposed based on the physical modeling of morphogenesis triggered by internal or external forcing. Digital libraries of structural patterns are constructed from the simulation data, which are then used to recognize the abnormalities, predict their development, and assist in risk assessment and prognosis. The capabilities to identify the key bifurcation characteristics and predict the history-dependent development from the global and local features are demonstrated by examples of brain growth and aerospace structural design, which offer guidelines for disease diagnosis/prognosis and instability-tolerant design.

Published
2023
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17. Chromatin regulators in the TBX1 network confer risk for conotruncal heart defects in 22q11.2DS.

Author

Zhao, Yingjie, Wang, Yujue, Shi, Lijie, McDonald-McGinn, Donna, Crowley, T, McGinn, Daniel, Tran, Oanh, Miller, Daniella, Lin, Jhih-Rong, Zackai, Elaine, Johnston, H, Chow, Eva, Vorstman, Jacob, Vingerhoets, Claudia, van Amelsvoort, Therese, Gothelf, Doron, Swillen, Ann, Breckpot, Jeroen, Vermeesch, Joris, Eliez, Stephan, Schneider, Maude, van den Bree, Marianne, Owen, Michael, Kates, Wendy, Repetto, Gabriela, Shashi, Vandana, Schoch, Kelly, Digilio, M, Unolt, Marta, Putotto, Carolina, Marino, Bruno, Pontillo, Maria, Armando, Marco, Vicari, Stefano, Angkustsiri, Kathleen, Campbell, Linda, Busa, Tiffany, Heine-Suñer, Damian, Murphy, Kieran, Murphy, Declan, García-Miñaúr, Sixto, Fernández, Luis, Zhang, Zhengdong, Goldmuntz, Elizabeth, Gur, Raquel, Emanuel, Beverly, Zheng, Deyou, Marshall, Christian, Bassett, Anne, Wang, Tao, Morrow, Bernice, and Bearden, Carrie

Abstract

Congenital heart disease (CHD) affecting the conotruncal region of the heart, occurs in 40-50% of patients with 22q11.2 deletion syndrome (22q11.2DS). This syndrome is a rare disorder with relative genetic homogeneity that can facilitate identification of genetic modifiers. Haploinsufficiency of TBX1, encoding a T-box transcription factor, is one of the main genes responsible for the etiology of the syndrome. We suggest that genetic modifiers of conotruncal defects in patients with 22q11.2DS may be in the TBX1 gene network. To identify genetic modifiers, we analyzed rare, predicted damaging variants in whole genome sequence of 456 cases with conotruncal defects and 537 controls, with 22q11.2DS. We then performed gene set approaches and identified chromatin regulatory genes as modifiers. Chromatin genes with recurrent damaging variants include EP400, KAT6A, KMT2C, KMT2D, NSD1, CHD7 and PHF21A. In total, we identified 37 chromatin regulatory genes, that may increase risk for conotruncal heart defects in 8.5% of 22q11.2DS cases. Many of these genes were identified as risk factors for sporadic CHD in the general population. These genes are co-expressed in cardiac progenitor cells with TBX1, suggesting that they may be in the same genetic network. The genes KAT6A, KMT2C, CHD7 and EZH2, have been previously shown to genetically interact with TBX1 in mouse models. Our findings indicate that disturbance of chromatin regulatory genes impact the TBX1 gene network serving as genetic modifiers of 22q11.2DS and sporadic CHD, suggesting that there are some shared mechanisms involving the TBX1 gene network in the etiology of CHD.

Published
2023

19. Research on hydraulic control system for shield type temporary support robot driving under pressure

Author

MA Hongwei, LI Lang, XUE Xusheng, WANG Chuanwei, WANG Saisai, ZHAO Yingjie, ZHOU Wenjian, and ZHANG Heng

Subjects
shield type temporary support robot, hydraulic control system, driving under pressure, support force control, driving displacement control, fuzzy pid control, Mining engineering. Metallurgy, TN1-997
Abstract

The shield type temporary support robot is an important component of the intelligent excavation robot system for large section roadways that adapts to the coexistence of dirt and debris. Its main function is to provide a safe and reliable workspace for achieving 'parallel excavation and support' operations. In order to enhance the safe and stable support of the shield type temporary support robot for surrounding rock during its pushing and driving process, based on the structure, working environment, and operational requirements of the shield type temporary support robot, a mathematical model of its pushing amount and support force during pressurized driving, as well as a dynamic model of pressurized driving, are established. A hydraulic control system for the shield type temporary support robot driving under pressure is designed. The system mainly consists of a support hydraulic system and a driving hydraulic system. During static support, the support hydraulic system needs to constantly output a support force greater than the weight of the upper shield body itself, and the driving hydraulic system is in standby mode. When driving under pressure, the support hydraulic system and the driving hydraulic system work simultaneously, ensuring that the temporary support robot 'reducing stress without leaving the roof' while steadily moving forward with the roof under pressure at all times. A precise control method for shield type temporary support robot driving under pressure based on fuzzy PID is proposed. The pressure and displacement signals of the temporary support robot are collected in real time by displacement sensors integrated on the displacement cylinder and pressure sensors in the hydraulic circuit. The signals are used to reflect the changes in support force and driving displacement during the temporary support robot's driving under pressure. Based on the error and error rate of the support force and displacement, the fuzzy PID algorithm is used to modify the control parameters of the support force and displacement, achieving reliable control of driving under pressure based on the fuzzy PID algorithm. Both simulation and experimental results show that the effect of fuzzy PID control is superior to traditional PID control. Under fuzzy PID control, the relative error of support force during the pushing and driving process of the shield type temporary support robot is less than 1%, and the driving displacement error is less than 2 mm. Moreover, the response speed of support force and pushing amount control is fast, ensuring the safe and stable support of the surrounding rock during the pushing and driving process.

Published
2024
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