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6,411 results on '"Hu Feng"'

101. Concurrent inhibition of oncogenic and wild-type RAS-GTP for cancer therapy

Author

Holderfield, Matthew, Lee, Bianca J., Jiang, Jingjing, Tomlinson, Aidan, Seamon, Kyle J., Mira, Alessia, Patrucco, Enrico, Goodhart, Grace, Dilly, Julien, Gindin, Yevgeniy, Dinglasan, Nuntana, Wang, Yingyun, Lai, Lick Pui, Cai, Shurui, Jiang, Lingyan, Nasholm, Nicole, Shifrin, Nataliya, Blaj, Cristina, Shah, Harshit, Evans, James W., Montazer, Nilufar, Lai, Oliver, Shi, Jade, Ahler, Ethan, Quintana, Elsa, Chang, Stephanie, Salvador, Anthony, Marquez, Abby, Cregg, Jim, Liu, Yang, Milin, Anthony, Chen, Anqi, Ziv, Tamar Bar, Parsons, Dylan, Knox, John E., Klomp, Jennifer E., Roth, Jennifer, Rees, Matthew, Ronan, Melissa, Cuevas-Navarro, Antonio, Hu, Feng, Lito, Piro, Santamaria, David, Aguirre, Andrew J., Waters, Andrew M., Der, Channing J., Ambrogio, Chiara, Wang, Zhengping, Gill, Adrian L., Koltun, Elena S., Smith, Jacqueline A. M., Wildes, David, and Singh, Mallika

Published
2024
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106. Investigating Berezinskii-Kosterlitz-Thouless phase transitions in Kagome spin ice by quantifying Monte Carlo process: Distribution of Hamming distances

Author

Su, Wen-Yu, Hu, Feng, Cheng, Chen, and Ma, Nvsen

Subjects
Condensed Matter - Statistical Mechanics
Abstract

We reinvestigate the phase transitions of the Ising model on the Kagome lattice with antiferromagnetic nearest-neighbor and ferromagnetic next-nearest-neighbor interactions, which has a six-state-clock spin ice ground state and two consecutive Berezinskii-Kosterlitz-Thouless (BKT) phase transitions. Employing the classical Monte Carlo (MC) simulations, the phases are characterized by the magnetic order parameter, and the critical temperatures are obtained by the finite-size scaling of related physical quantities. Moreover, we attempt to gain general information on the phase transitions from the MC process instead of MC results and successfully extract the correct transition points with surprisingly high accuracy. Specifically, we focus on the selected data set of uncorrelated MC configurations and quantify the MC process using the distribution of two-configuration Hamming distances in this small data collection. This distribution is more than a quantity that features different behaviors in different phases but also nicely supports the same BKT scaling form as the order parameter, from which we successfully determine the two BKT transition points with surprisingly high accuracy. We also discuss the connection between the phase transitions and the intrinsic dimension extracted from the Hamming distances, which is widely used in the growing field of machine learning and is reported to be able to detect critical points. Our findings provide a new understanding of the spin ice transitions in the Kagome lattice and can hopefully be used similarly to identify transitions in the quantum system on the same lattice with strong frustrations., Comment: 12 figures

Published
2023
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107. MAE-GEBD:Winning the CVPR'2023 LOVEU-GEBD Challenge

Author

Sun, Yuanxi, He, Rui, Li, Youzeng, Huang, Zuwei, Hu, Feng, Cheng, Xu, and Tang, Jie

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The Generic Event Boundary Detection (GEBD) task aims to build a model for segmenting videos into segments by detecting general event boundaries applicable to various classes. In this paper, based on last year's MAE-GEBD method, we have improved our model performance on the GEBD task by adjusting the data processing strategy and loss function. Based on last year's approach, we extended the application of pseudo-label to a larger dataset and made many experimental attempts. In addition, we applied focal loss to concentrate more on difficult samples and improved our model performance. Finally, we improved the segmentation alignment strategy used last year, and dynamically adjusted the segmentation alignment method according to the boundary density and duration of the video, so that our model can be more flexible and fully applicable in different situations. With our method, we achieve an F1 score of 86.03% on the Kinetics-GEBD test set, which is a 0.09% improvement in the F1 score compared to our 2022 Kinetics-GEBD method., Comment: Winner of CVPR2023 LOVEU GEBD Challenge

Published
2023

108. Determination of Lead, Cadmium, Copper and Iron Contents in Water by Multi-walled Carbon Nanotubes-solid Phase Extraction

Author

SUN Na, CHI Xiao-feng, HU Feng-zu, and YANG Yue-qin

Subjects
water samples, pb, cd, cu, fe, solid phase extraction, multi-walled carbon nanotubes, Geology, QE1-996.5, Ecology, QH540-549.5
Abstract

The traditional solid phase extraction sorbent contains certain deficiencies in the progress of processing heavy metals in environmental samples, such as pH instability and co-extraction difficulty. Therefore, it is particularly important to find more efficient sorbents. A solid-phase extraction method using multi-walled carbon nanotube as absorbent materials for Pb, Cd, Cu and Fe in water has been determined. The effects of solution pH, elution solution, sample volume and matrix effects were investigated. Pb and Cd were determined by Graphite Furnace Atomic Absorption Spectrometry; alternatively, Cu and Fe were determined by inductively coupled plasma atomic emission spectrometry. Experimental results show that the extraction of the metal elements is most efficient when the pH value is 9.0 and flow rate is 2 mL/min with 1 mol/L HNO3 as the elution solution by using the unmodified multi-walled carbon nanotube (outer diameter

Published
2014

111. (Mis)Information and the Value of College Names. EdWorkingPaper No. 20-329

Author

Annenberg Institute for School Reform at Brown University, Eble, Alex, and Hu, Feng

Abstract

Hundreds of colleges have changed their names to signal higher quality. We estimate how this affects college choice and the labor market performance of college graduates. Administrative data show that name-changing colleges enroll higher-aptitude students, with larger effects for attractive-but-misleading name changes and among students with less information. A resume audit study shows that employer callbacks respond to the increased aptitude of recruited students at these colleges. We broaden these results using scraped online text data, survey data, and other administrative data. Our study demonstrates that signals designed to change beliefs can have real, lasting impacts on market outcomes.

Published
2021

129. Masked Autoencoders for Generic Event Boundary Detection CVPR'2022 Kinetics-GEBD Challenge

Author

He, Rui, Sun, Yuanxi, Li, Youzeng, Huang, Zuwei, Hu, Feng, Cheng, Xu, and Tang, Jie

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Generic Event Boundary Detection (GEBD) tasks aim at detecting generic, taxonomy-free event boundaries that segment a whole video into chunks. In this paper, we apply Masked Autoencoders to improve algorithm performance on the GEBD tasks. Our approach mainly adopted the ensemble of Masked Autoencoders fine-tuned on the GEBD task as a self-supervised learner with other base models. Moreover, we also use a semi-supervised pseudo-label method to take full advantage of the abundant unlabeled Kinetics-400 data while training. In addition, we propose a soft-label method to partially balance the positive and negative samples and alleviate the problem of ambiguous labeling in this task. Lastly, a tricky segmentation alignment policy is implemented to refine boundaries predicted by our models to more accurate locations. With our approach, we achieved 85.94% on the F1-score on the Kinetics-GEBD test set, which improved the F1-score by 2.31% compared to the winner of the 2021 Kinetics-GEBD Challenge. Our code is available at https://github.com/ContentAndMaterialPortrait/MAE-GEBD.

Published
2022

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