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1. Microstructure-Dependent Particulate Filtration using Multifunctional Metallic Nanowire Foams

Author

Malloy, James, Marlowe, Erin, Jensen, Christopher J., Liu, Isaac S., Hulse, Thomas, Murray, Anne F., Bryan, Daniel, Denes, Thomas G., Gilbert, Dustin A., Yin, Gen, and Liu, Kai

Subjects
Physics - Applied Physics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

The COVID-19 pandemic has shown the urgent need for the development of efficient, durable, reusable and recyclable filtration media for the deep-submicron size range. Here we demonstrate a multifunctional filtration platform using porous metallic nanowire foams that are efficient, robust, antimicrobial, and reusable, with the potential to further guard against multiple hazards. We have investigated the foam microstructures, detailing how the growth parameters influence the overall surface area and characteristic feature size, as well as the effects of the microstructures on the filtration performance. Nanogranules deposited on the nanowires during electrodeposition are found to greatly increase the surface area, up to 20 m$^{2}$/g. Surprisingly, in the high surface area regime, the overall surface area gained from the nanogranules has little correlation with the improvement in capture efficiency. However, nanowire density and diameter play a significant role in the capture efficiency of PM$_{0.3}$ particles, as do the surface roughness of the nanowire fibers and their characteristic feature sizes. Antimicrobial tests on the Cu foams show a >99.9995% inactivation efficiency after contacting the foams for 30 seconds. These results demonstrate promising directions to achieve a highly efficient multifunctional filtration platform with optimized microstructures., Comment: 25 pages, 5 figures, 1 table; 11 page of supplementary information with 7 figures

Published
2024
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4. Effects of antipsychotic drugs on energy metabolism

Author

Panizzutti, Bruna, Bortolasci, Chiara C., Spolding, Briana, Kidnapillai, Srisaiyini, Connor, Timothy, Martin, Sheree D., Truong, Trang T. T., Liu, Zoe S. J., Gray, Laura, Kowalski, Greg M., McGee, Sean L., Kim, Jee Hyun, Berk, Michael, and Walder, Ken

Published
2024
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6. Understanding the Universal Dust Attenuation Scaling Relation of Star-Forming Galaxies

Author

Qin, J., Zheng, X. Z., Wuyts, S., Lv, Z., Qiao, M., Huang, J. -S., Liu, F. S., Katsianis, A., Gonzalez, V., Bian, F., Xu, H., Pan, Z., Liu, W., Tan, Q. -H., An, F. X., Shi, D. D., Zhang, Y., Wen, R., Liu, S., and Yang, C.

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Star-forming galaxies (SFGs) adhere to a surprisingly tight scaling relation of dust attenuation parameterized by the infrared excess (IRX=$L_{\rm IR}/L_{\rm UV}$), being jointly determined by the star formation rate (SFR), galaxy size ($R_{\rm e}$), metallicity ($Z$/Z$_\odot$) and axial ratio ($b/a$). We examine how these galaxy parameters determine the effective dust attenuation and give rise to the universal IRX relation, utilizing a simple two-component star-dust geometry model in which dust in the dense and diffuse interstellar medium (ISM) follows exponential mass density profiles, connected with but not necessarily identical to the stellar mass profiles. Meanwhile, empirical relations are adopted to link galaxy properties, including the gas--star formation relation, the dust-to-stellar size relation, as well as the dust-to-gas ratio versus metallicity relation. By fitting a large sample of local SFGs with the model, we obtain the best-fitting model parameters as a function of metallicity, showing that the two-component geometry model is able to successfully reproduce the dependence of IRX on SFR, $R_{\rm e}$, $b/a$ at given $Z$/Z$_\odot$, as well as the dependence of power-law indices on metallicity. Moreover, we also retrieve constraints on the model geometry parameters, including the optical depth of birth clouds (BCs), BC-to-total dust mass fraction, BC covering factor of UV-emitting stars, and star-to-total dust disc radius ratio, which all evolve with galaxy metallicity. Finally, a consistent picture of how the star-dust geometry in SFGs evolves with galaxy metallicity is discussed., Comment: 20 pages, 10 figures, published in MNRAS (2024, Volume 528, Issue 1, pp.658-675); A PHTHON package IRX_TAU_TOT is available at https://github.com/LvZF/irx_tau_tot/ to calculate the total dust optical depth of a galaxy with given metallicity and best-fitting geometry parameters

Published
2023
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15. Shallow current of viscous fluid flowing between diverging or converging walls

Author

Liu, M-S. and Huppert, H. E.

Subjects
Physics - Fluid Dynamics
Abstract

We investigate the shallow flow of viscous fluid into and out of a channel whose gap width increases as a power-law ($x^n$), where $x$ is the downstream axis. The fluid flows slowly, while injected at a rate in the form of $t^\alpha$, where $t$ is time and $\alpha$ is a constant. The invading fluid has higher viscosity than the ambient fluid, thus avoiding Saffman-Taylor instability. Similarity solutions of the first kind for the outflow problem are found using approximations of lubrication theory. Zheng et al [2014] studied the deep-channel case and found divergent behaviour of the similarity variable as $n\rightarrow1$ and $n\rightarrow3$, when fluid flows into and out of the channel respectively. No divergence is found in the shallow case presented here. The characteristic equilibration time for the numerically simulated constant-volume flow to converge to the similarity solution is calculated assuming inverse dependence on the ratio disagreement between the current front using the method of lines (MOL). The inverse power dependence between equilibration time and ratio disagreement is found for channels of different powers. A similarity solution of the second kind for the inflow problem is found using the phase plane formalism and the bisection method. An exponential decay relationship is found between $n$ and the degree $\delta$ of the similarity variable $xt^{-\delta}$, which does not show any divergent behaviour for large $n$. An asymptotic behaviour is found for $\delta$ that approaches $1/2$ as $n\rightarrow\infty$.

Published
2023
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16. Examining Shifts in Conceptual Knowledge, Procedural Knowledge and Procedural Flexibility in the Context of Two Game-Based Technologies

Author

Chan, Jenny Yun-Chen, Closser, Avery H., Ngo, Vy, Smith, Hannah, Liu, Allison S., and Ottmar, Erin

Abstract

Background: Prior work has shown that middle school students struggle with algebra and that game-based educational technologies, such as DragonBox and From Here to There!, are effective at improving students' algebraic performance. However, it remains unclear which aspects of algebraic knowledge shift as a result of playing these games and what game design features support algebraic learning. Objective: Using the data from a randomized controlled trial conducted in the 2020-2021 academic year, we (a) examined students' relative performance on assessment items measuring conceptual knowledge, procedural knowledge and procedural flexibility in algebraic equation solving, and (b) identified changes in these aspects of algebraic knowledge after playing DragonBox or From Here to There!. Methods: Eight hundred eighty-seven seventh-graders were randomly assigned to playing DragonBox or From Here to There! for nine 30-min sessions throughout the school year. Students also completed a pretest, midtest and posttest measuring their algebraic knowledge. Results and Conclusion: First, prior to the intervention, students scored the highest on procedural knowledge and lowest on conceptual knowledge. Second, students significantly improved and maintained learning gains on conceptual knowledge throughout the intervention. Their performance on procedural knowledge and procedural flexibility items increased at midtest but decreased at posttest. Third, the pattern of results was consistent for students in the DragonBox and From Here to There! conditions, suggesting that both games may support students' conceptual understanding of algebra. The findings have implications for research and practice on supporting algebraic learning through game-based technologies during and beyond educational disruptions. [For the corresponding grantee submission, see ED628258.]

Published
2023
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17. Keep DRAGging ON: Is Solving More Problems in DragonBox 12+ Associated with Higher Mathematical Performance during the COVID-19 Pandemic?

Author

Chan, Jenny Yun-Chen, Byrne, Chloe, Jerusal, Janette, Liu, Allison S., Roberts, Justin, and Ottmar, Erin

Abstract

Prior research has shown that game-based learning tools, such as DragonBox 12+, support algebraic understanding and that students' in-game progress positively predicts their later performance. Using data from 253 seventh-graders (12-13 years old) who played DragonBox as a part of technology intervention, we examined (a) the relations between students' progress within DragonBox and their algebraic knowledge and general mathematics achievement, (b) the moderating effects of students' prior performance on these relations and (c) the potential factors associated with students' in-game progress. Among students with higher prior algebraic knowledge, higher in-game progress was related to higher algebraic knowledge after the intervention. Higher in-game progress was also associated with higher end-of-year mathematics achievement, and this association was stronger among students with lower prior mathematics achievement. Students' demographic characteristics, prior knowledge and prior achievement did not significantly predict in-game progress beyond the number of intervention sessions students completed. These findings advance research on how, for whom and in what contexts game-based interventions, such as DragonBox, support mathematical learning and have implications for practice using game-based technologies to supplement instruction. [For the corresponding grantee submission, see ED626412.]

Published
2023
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23. Keep DRAGging ON: Is Solving More Problems in DragonBox 12+ Associated with Higher Mathematical Performance during the COVID-19 Pandemic?

Author

Chan, Jenny Yun-Chen, Byrne, Chloe, Jerusal, Janette, Liu, Allison S., Roberts, Justin, and Ottmar, Erin

Abstract

Prior research has shown that game-based learning tools, such as DragonBox 12+, support algebraic understanding and that students' in-game progress positively predicts their later performance. Using data from 253 seventh-graders (12-13 years old) who played DragonBox as a part of technology intervention, we examined (a) the relations between students' progress within DragonBox and their algebraic knowledge and general mathematics achievement, (b) the moderating effects of students' prior performance on these relations and (c) the potential factors associated with students' in-game progress. Among students with higher prior algebraic knowledge, higher in-game progress was related to higher algebraic knowledge after the intervention. Higher in-game progress was also associated with higher end-of-year mathematics achievement, and this association was stronger among students with lower prior mathematics achievement. Students' demographic characteristics, prior knowledge and prior achievement did not significantly predict in-game progress beyond the number of intervention sessions students completed. These findings advance research on "how," "for whom" and "in what contexts" game-based interventions, such as DragonBox, support mathematical learning and have implications for practice using game-based technologies to supplement instruction. [This is the online version of an article published in "British Journal of Educational Technology."]

Published
2023
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24. Examining Shifts in Conceptual Knowledge, Procedural Knowledge and Procedural Flexibility in the Context of Two Game-Based Technologies

Author

Chan, Jenny Yun-Chen, Closser, Avery H., Ngo, Vy, Smith, Hannah, Liu, Allison S., and Ottmar, Erin

Abstract

Background: Prior work has shown that middle school students struggle with algebra and that game-based educational technologies, such as DragonBox and From Here to There!, are effective at improving students' algebraic performance. However, it remains unclear which aspects of algebraic knowledge shift as a result of playing these games and what game design features support algebraic learning. Objective: Using the data from a randomized controlled trial conducted in the 2020-2021 academic year, we: (1) examined students' relative performance on assessment items measuring conceptual knowledge, procedural knowledge and procedural flexibility in algebraic equation solving; and (2) identified changes in these aspects of algebraic knowledge after playing DragonBox or From Here to There!. Methods: Eight hundred eighty-seven seventh-graders were randomly assigned to playing DragonBox or From Here to There! for nine 30-min sessions throughout the school year. Students also completed a pretest, midtest and posttest measuring their algebraic knowledge. Results and Conclusion: First, prior to the intervention, students scored the highest on procedural knowledge and lowest on conceptual knowledge. Second, students significantly improved and maintained learning gains on conceptual knowledge throughout the intervention. Their performance on procedural knowledge and procedural flexibility items increased at midtest but decreased at posttest. Third, the pattern of results was consistent for students in the DragonBox and From Here to There! conditions, suggesting that both games may support students' conceptual understanding of algebra. The findings have implications for research and practice on supporting algebraic learning through game-based technologies during and beyond educational disruptions. [This is the online version of an article published in "Journal of Computer Assisted Learning."]

Published
2023
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30. Numeracy, Cognitive, and Motivational Predictors of Elementary Mathematics Achievement

Author

Liu, Allison S., Rutherford, Teomara, and Karamarkovich, Sarah M.

Abstract

Cognitive, numeracy, and motivational factors have been implicated in math achievement. However, few studies have investigated these factors simultaneously and in middle childhood, limiting our understanding of the relative contributions of these factors during an important developmental period. The current study investigated how one numeracy, four cognitive, and three motivational factors predicted math performance in 525 third, 771 fourth, and 465 fifth grade students, and whether these relations changed by grade and the type of math measured. Participants completed the California Standards Test (CST; Educational Testing Service, 2014) in Spring 2012 and Spring 2013 to assess math performance, and a battery of numeracy, cognitive, and motivational measures in Spring 2013. Separate multilevel regressions predicting 2013 CST performance were conducted for each grade, and z scores were used to compare the coefficients between grades. Results showed that updating and math expectancy were related to broad-level math performance for all grades. Further, numeracy and shifting were most predictive of math performance for younger grades, whereas math expectancy was most predictive for older grades across a range of math content. The results suggest that numeracy, cognitive, and motivational factors all relate to math performance when these three types of factors are considered, with numeracy, updating, shifting, and math expectancy showing the most reliable relations depending on grade. The relations between factors and math types may also have implications for interventions aiming to improve specific types of math.

Published
2022
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34. Continuous symmetry breaking in a two-dimensional Rydberg array

Author

Chen, Cheng, Bornet, Guillaume, Bintz, Marcus, Emperauger, Gabriel, Leclerc, Lucas, Liu, Vincent S., Scholl, Pascal, Barredo, Daniel, Hauschild, Johannes, Chatterjee, Shubhayu, Schuler, Michael, Läuchli, Andreas M., Zaletel, Michael P., Lahaye, Thierry, Yao, Norman Y., and Browaeys, Antoine

Published
2023
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37. Targeted degradation via direct 26S proteasome recruitment

Author

Bashore, Charlene, Prakash, Sumit, Johnson, Matthew C., Conrad, Ryan J., Kekessie, Ivy A., Scales, Suzie J., Ishisoko, Noriko, Kleinheinz, Tracy, Liu, Peter S., Popovych, Nataliya, Wecksler, Aaron T., Zhou, Lijuan, Tam, Christine, Zilberleyb, Inna, Srinivasan, Rajini, Blake, Robert A., Song, Aimin, Staben, Steven T., Zhang, Yingnan, Arnott, David, Fairbrother, Wayne J., Foster, Scott A., Wertz, Ingrid E., Ciferri, Claudio, and Dueber, Erin C.

Published
2023
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39. How Reward- and Error-Based Feedback Systems Create Microfailures to Support Learning Strategies

Author

Liu, Allison S., Vanacore, Kirk, and Ottmar, Erin

Abstract

Feedback in educational technologies can teach and engage students in math, but questions remain on how to present failure feedback that supports positive learning behaviors. We explore how error- and reward-based feedback influenced students' choices to replay completed problems in "From Here to There!," a math game-based educational technology. We conducted a multilevel logistic regression in 1,031 seventh-grade students predicting whether a problem was replayed, using whether an error was made during the first problem attempt and how many clovers were earned after solving the problem (with more clovers earned for more efficient solutions). Preliminary results show that making an error or earning two clovers increased the likelihood of replays, whereas earning one or three clovers decreased the likelihood. Our findings suggest that clovers and errors may be "micro-failures" that encourage replays by supporting feelings of competency and/or autonomy, which has implications for game design elements for learning and engagement. [This paper was published in: ICLS2022 Proceedings, International Society of the Learning Sciences (ISLS), 2022, pp. 1633-1636.]

Published
2022

40. Aging is associated with a systemic length-associated transcriptome imbalance

Author

Stoeger, Thomas, Grant, Rogan A., McQuattie-Pimentel, Alexandra C., Anekalla, Kishore R., Liu, Sophia S., Tejedor-Navarro, Heliodoro, Singer, Benjamin D., Abdala-Valencia, Hiam, Schwake, Michael, Tetreault, Marie-Pier, Perlman, Harris, Balch, William E., Chandel, Navdeep S., Ridge, Karen M., Sznajder, Jacob I., Morimoto, Richard I., Misharin, Alexander V., Budinger, G. R. Scott, and Nunes Amaral, Luis A.

Published
2022
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41. Reconstruction of Cherenkov image by multiple telescopes of LHAASO-WFCTA

Author

Aharonian, F., An, Q., Axikegu, Bai, L. X., Bai, Y. X., Bao, Y. W., Bastieri, D., Bi, X. J., Bi, Y. J., Cai, J. T., Cao, Zhe, Cao, Zhen, Chang, J., Chang, J. F., Chen, E. S., Chen, Liang, Chen, Liang, Chen, Long, Chen, M. J., Chen, M. L., Chen, Q. H., Chen, S. H., Chen, S. Z., Chen, T. L., Chen, Y., Cheng, H. L., Cheng, N., Cheng, Y. D., Cui, S. W., Cui, X. H., Cui, Y. D., D’Ettorre Piazzoli, B., Dai, B. Z., Dai, H. L., Dai, Z. G., Danzengluobu, della Volpe, D., Duan, K. K., Fan, J. H., Fan, Y. Z., Fan, Z. X., Fang, J., Fang, K., Feng, C. F., Feng, L., Feng, S. H., Feng, X. T., Feng, Y. L., Gao, B., Gao, C. D., Gao, L. Q., Gao, Q., Gao, W., Gao, W. K., Ge, M. M., Geng, L. S., Gong, G. H., Gou, Q. B., Gu, M. H., Guo, F. L., Guo, J. G., Guo, X. L., Guo, Y. Q., Guo, Y. Y., Han, Y. A., He, H. H., He, H. N., He, S. L., He, X. B., He, Y., Heller, M., Hor, Y. K., Hou, C., Hou, X., Hu, H. B., Hu, Q., Hu, S., Hu, S. C., Hu, X. J., Huang, D. H., Huang, W. H., Huang, X. T., Huang, X. Y., Huang, Y., Huang, Z. C., Ji, X. L., Jia, H. Y., Jia, K., Jiang, K., Jiang, Z. J., Jin, M., Kang, M. M., Ke, T., Kuleshov, D., Levochkin, K., Li, B. B., Li, Cheng, Li, Cong, Li, F., Li, H. B., Li, H. C., Li, H. Y., Li, J., Li, Jian, Li, Jie, Li, K., Li, W. L., Li, X. R., Li, Xin, Li, Xin, Li, Y. Z., Li, Zhe, Li, Zhuo, Liang, E. W., Liang, Y. F., Lin, S. J., Liu, B., Liu, C., Liu, D., Liu, H., Liu, H. D., Liu, J., Liu, J. L., Liu, J. S., Liu, J. Y., Liu, M. Y., Liu, R. Y., Liu, S. M., Liu, W., Liu, Y., Liu, Y. N., Long, W. J., Lu, R., Luo, Q., Lv, H. K., Ma, B. Q., Ma, L. L., Ma, X. H., Mao, J. R., Masood, A., Min, Z., Mitthumsiri, W., Nan, Y. C., Ou, Z. W., Pang, B. Y., Pattarakijwanich, P., Pei, Z. Y., Qi, M. Y., Qi, Y. Q., Qiao, B. Q., Qin, J. J., Ruffolo, D., Sáiz, A., Shao, C. Y., Shao, L., Shchegolev, O., Sheng, X. D., Shi, J. Y., Song, H. C., Stenkin, Yu. V., Stepanov, V., Su, Y., Sun, Q. N., Sun, X. N., Sun, Z. B., Tam, P. H. T., Tang, Z. B., Tian, W. W., Wang, B. D., Wang, C., Wang, H., Wang, H. G., Wang, J. C., Wang, J. S., Wang, L. P., Wang, L. Y., Wang, R., Wang, R. N., Wang, W., Wang, X. G., Wang, X. Y., Wang, Y., Wang, Y. D., Wang, Y. J., Wang, Y. P., Wang, Z. H., Wang, Z. X., Wang, Zhen, Wang, Zheng, Wei, D. M., Wei, J. J., Wei, Y. J., Wen, T., Wu, C. Y., Wu, H. R., Wu, S., Wu, X. F., Wu, Y. S., Xi, S. Q., Xia, J., Xia, J. J., Xiang, G. M., Xiao, D. X., Xiao, G., Xin, G. G., Xin, Y. L., Xing, Y., Xiong, Z., Xu, D. L., Xu, R. X., Xue, L., Yan, D. H., Yan, J. Z., Yang, C. W., Yang, F. F., Yang, H. W., Yang, J. Y., Yang, L. L., Yang, M. J., Yang, R. Z., Yang, S. B., Yao, Y. H., Yao, Z. G., Ye, Y. M., Yin, L. Q., Yin, N., You, X. H., You, Z. Y., Yu, Y. H., Yuan, Q., Yue, H., Zeng, H. D., Zeng, T. X., Zeng, W., Zeng, Z. K., Zha, M., Zhai, X. X., Zhang, B. B., Zhang, F., Zhang, H. M., Zhang, H. Y., Zhang, J. L., Zhang, L. X., Zhang, Li, Zhang, Lu, Zhang, P. F., Zhang, P. P., Zhang, R., Zhang, S. B., Zhang, S. R., Zhang, S. S., Zhang, X., Zhang, X. P., Zhang, Y. F., Zhang, Y. L., Zhang, Yi, Zhang, Yong, Zhao, B., Zhao, J., Zhao, L., Zhao, L. Z., Zhao, S. P., Zheng, F., Zheng, Y., Zhou, B., Zhou, H., Zhou, J. N., Zhou, P., Zhou, R., Zhou, X. X., Zhu, C. G., Zhu, F. R., Zhu, H., Zhu, K. J., and Zuo, X.

Published
2022
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