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5. Calibrationless Reconstruction of Uniformly-Undersampled Multi-Channel MR Data with Deep Learning Estimated ESPIRiT Maps

Author

Zhang, Junhao, Yi, Zheyuan, Zhao, Yujiao, Xiao, Linfang, Hu, Jiahao, Man, Christopher, Lau, Vick, Su, Shi, Chen, Fei, Leong, Alex T. L., and Wu, Ed X.

Subjects
Electrical Engineering and Systems Science - Signal Processing
Abstract

Purpose: To develop a truly calibrationless reconstruction method that derives ESPIRiT maps from uniformly-undersampled multi-channel MR data by deep learning. Methods: ESPIRiT, one commonly used parallel imaging reconstruction technique, forms the images from undersampled MR k-space data using ESPIRiT maps that effectively represents coil sensitivity information. Accurate ESPIRiT map estimation requires quality coil sensitivity calibration or autocalibration data. We present a U-Net based deep learning model to estimate the multi-channel ESPIRiT maps directly from uniformly-undersampled multi-channel multi-slice MR data. The model is trained using fully-sampled multi-slice axial brain datasets from the same MR receiving coil system. To utilize subject-coil geometric parameters available for each dataset, the training imposes a hybrid loss on ESPIRiT maps at the original locations as well as their corresponding locations within the standard reference multi-slice axial stack. The performance of the approach was evaluated using publicly available T1-weighed brain and cardiac data. Results: The proposed model robustly predicted multi-channel ESPIRiT maps from uniformly-undersampled k-space data. They were highly comparable to the reference ESPIRiT maps directly computed from 24 consecutive central k-space lines. Further, they led to excellent ESPIRiT reconstruction performance even at high acceleration, exhibiting a similar level of errors and artifacts to that by using reference ESPIRiT maps. Conclusion: A new deep learning approach is developed to estimate ESPIRiT maps directly from uniformly-undersampled MR data. It presents a general strategy for calibrationless parallel imaging reconstruction through learning from coil and protocol specific data.

Published
2022

6. Robust Electromagnetic Interference (EMI) Elimination via Simultaneous Sensing and Deep Learning Prediction for RF Shielding-free MRI

Author

Zhao, Yujiao, Xiao, Linfang, Lau, Vick, Liu, Yilong, Leong, Alex T., and Wu, Ed X.

Subjects
Electrical Engineering and Systems Science - Signal Processing, Physics - Instrumentation and Detectors
Abstract

At present, MRI scans are performed inside a fully-enclosed RF shielding room, posing stringent installation requirement and unnecessary patient discomfort. We aim to develop an electromagnetic interference (EMI) cancellation strategy for MRI with no or incomplete RF shielding. In this study, a simultaneous sensing and deep learning driven EMI cancellation strategy is presented to model, predict and remove EMI signals from acquired MRI signals. Specifically, during each MRI scan, separate EMI sensing coils placed in various spatial locations are utilized to simultaneously sample environmental and internal EMI signals within two windows (for both conventional MRI signal acquisition and EMI characterization acquisition). Then a CNN model is trained using the EMI characterization data to relate EMI signals detected by EMI sensing coils to EMI signals in MRI receive coil. This model is utilized to retrospectively predict and remove EMI signals components detected by MRI receive coil during the MRI signal acquisition window. We implemented and demonstrated this strategy for various EMI sources on a mobile ultra-low-field 0.055 T permanent magnet MRI scanner and a 1.5 T superconducting magnet MRI scanner with no or incomplete RF shielding. Our experimental results demonstrate that the method is highly effective and robust in predicting and removing various EMI sources from both external environments and internal scanner electronics at both 0.055 T (2.3 MHz) and 1.5 T (64 MHz), producing final image signal-to-noise ratios that are comparable to those obtained using a fully enclosed RF shielding. Our proposed strategy enables MRI operation with no or incomplete RF shielding, alleviating MRI installation and operational requirements. It is also potentially applicable to other scenarios of accurate RF signal detection or discrimination in presence of external and internal EMI or RF sources., Comment: Submitted to NMR in Biomedicine

Published
2022

12. Early cellular and molecular signatures correlate with severity of West Nile virus infection

Author

Lee, Ho-Joon, Zhao, Yujiao, Fleming, Ira, Mehta, Sameet, Wang, Xiaomei, Wyk, Brent Vander, Ronca, Shannon E., Kang, Heather, Chou, Chih-Hung, Fatou, Benoit, Smolen, Kinga K., Levy, Ofer, Clish, Clary B., Xavier, Ramnik J., Steen, Hanno, Hafler, David A., Love, J. Christopher, Shalek, Alex K., Guan, Leying, Murray, Kristy O., Kleinstein, Steven H., and Montgomery, Ruth R.

Published
2023
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13. New energy exploitation in coal-endowed areas under the target of 'double carbon': a new path for transformation and upgrading of coal mines in the future

Author

WANG Shuangming, LIU Lang, ZHAO Yujiao, ZHANG Bo, WANG Jingyu, ZHU Mengbo, WANG Mei, and ZHANG Xiaoyan

Subjects
“double carbon” target, full-life-cycle, new energy development, energy storage in goaf, multi-energy complementation, Mining engineering. Metallurgy, TN1-997
Abstract

Under the “dual carbon” goal, China’s energy structure is accelerating transformation and upgrading, and new energy represented by solar energy, wind energy, geothermal energy is gradually replacing traditional coal, oil, gas and other fossil energy. Promoting the optimal combination of coal and new energy is a new requirement for achieving the “double carbon” goal, and also an important path for the green and low-carbon transformation of coal mines in the future. Based on the analysis of the energy distribution characteristics of coal-endowed areas in China, it is found that the fossil energy distribution areas dominated by coal are often also areas rich in solar energy, wind energy, thermal energy and other new energy, which are suitable for large-scale development of new energy in in coal-endowed areas. The research results are as follows: ① Put forward the concept of full life cycle energy development in coal-endowed areas, divide the energy development process in coal-endowed areas into three stages: coal, coal and new energy optimization combination, and new energy, and build a general framework for new energy development in coal-endowed areas; ② In terms of solar energy development, the theoretical reserves and development potential of solar energy in the mining area are evaluated based on the overlapping relationship between the coal occurrence and the solar energy resource rich area, and a hierarchical comprehensive utilization scheme of solar energy coupled with photochemical utilization, such as distributed/centralized photovoltaic power generation, solar thermal utilization and solar hydrogen production, is proposed to achieve diversified and efficient conversion and utilization of solar energy and collaborative mining with coal resources; ③ In terms of geothermal energy development, the potential of geothermal energy development in coal-endowed areas is evaluated based on the overlapping relationship between the coal bearing area and the geothermal energy resource rich area. In combination with the formation mechanism, distribution law and mining situation of the mine geothermal, a collaborative development system of deep mineral resources and geothermal resources is established to form a comprehensive application scheme for the graded mining of mine geothermal energy and the cascade utilization of thermal users, including the hot water type, rock temperature type and mixed type of the mine, realizing the strategic transfer of “harm” to “benefit” of mine geothermal; ④ In terms of wind energy development, the potential of wind energy development in the mining area is evaluated based on the overlapping relationship between the coal occurrence and the wind energy resource rich area, and the application approaches of wind power generation, wind water lifting, and wind heating technologies in the coal bearing area are proposed, and the wind energy utilization framework for power supply, water cycle power, heating self-sufficiency, and grid connected power generation of underground and underground facilities is constructed; ⑤ Considering that the roof is generally managed by the caving method in the current underground coal mining, and the caving space cannot be effectively used for underground energy storage, a technical path of energy storage in the goaf of the mine is proposed, which is “advanced planning of energy storage reservoir → construction of energy storage reservoir using functional backfilling→ Energy storage and release operation control”; ⑥ In view of the complex and changeable characteristics of multi energy complementary integrated energy system (MCIES) in coal-endowed areas, a heterogeneous energy flow coupling model of energy production and supply units in coal-endowed areas is established, the mathematical expressions of different energy hubs in MCIES are unified, and the energy management and optimization logic method and operation mode of MCIES in coal-endowed areas are proposed. This paper aims to explore the combination path of coal and new energy, demonstrate the feasibility of large-scale development of new energy in coal-endowed areas, endow coal bearing areas with the function of energy supply in the whole life cycle, and form a new mode of energy industry development of coal enterprises integrating “mine-wind-light-heat-storage”.

Published
2023
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14. Multi-omic longitudinal study reveals immune correlates of clinical course among hospitalized COVID-19 patients

Author

Abraham, James, Adkisson, Michael, Albert, Marisa, Altamirano, Luz Torres, Alvarenga, Bonny, Anderson, Matthew L., Anderson, Evan J., Arnett, Azlann, Asashima, Hiromitsu, Atkinson, Mark A., Baden, Lindsey R., Barton, Brenda, Beach, Katherine, Beagle, Elizabeth, Becker, Patrice M., Bell, Matthew R., Bernui, Mariana, Bime, Christian, Boddapati, Arun Kumar, Booth, J. Leland, Borresen, Brittney, Brakenridge, Scott C., Bristow, Laurel, Bryant, Robert, Calfee, Carolyn S., Carreño, Juan Manuel, Carrillo, Sidney, Chak, Suzanna, Chang, Iris, Connors, Jennifer, Conway, Michelle, Corry, David B., Cowan, David, Croen, Brett, Dela Cruz, Charles S., Cusimano, Gina, Eaker, Lily, Edwards, Carolyn, Ehrlich, Lauren I.R., Elashoff, David, Erickson, Heidi, Erle, David J., Farhadian, Shelli, Farrugia, Keith, Fatou, Benoit, Fernandes, Andrea, Fernandez-Sesma, Ana, Fragiadakis, Gabriela K., Furukawa, Sara, Geltman, Janelle N., Ghale, Rajani, Bermúdez González, Maria Carolina, Goonewardene, I. Michael, Guerrero, Estella Sanchez, Guirgis, Faheem W., Hafler, David A., Hamilton, Sydney, Harris, Paul, Hayati, Arash Nemati, Hendrickson, Carolyn M., Agudelo Higuita, Nelson I., Hodder, Thomas, Holland, Steven M., Hough, Catherine L., Huerta, Christopher, Hurley, Kerin C., Hutton, Scott R., Iwasaki, Akiko, Jauregui, Alejandra, Jha, Meenakshi, Johnson, Brandi, Joyner, David, Kangelaris, Kirsten N., Kelly, Geoffrey, Khalil, Zain, Khan, Zenab, Kheradmand, Farrah, Kim, James N., Kimura, Hiroki, Ko, Albert I., Kohr, Bernard, Kraft, Monica, Krummel, Matthew, Kutzler, Michele A., Lasky-Su, Jessica, Lee, Serena, Lee, Deanna, Leipold, Michael, Lentucci, Claudia, Leroux, Carolyn, Lin, Edward, Liu, Shanshan, Love, Christina, Lu, Zhengchun, Maliskova, Lenka, Manning, Brittany Roth, Manohar, Monali, Martens, Mark, McComsey, Grace A., McEnaney, Kerry, McLin, Renee, Melamed, Esther, Melnyk, Nataliya, Mendez, Kevin, Messer, William B., Metcalf, Jordan P., Michelotti, Gregory, Mick, Eran, Mohanty, Subhasis, Mosier, Jarrod, Mulder, Lubbertus C.F., Murphy, Maimouna, Nadeau, Kari R.C., Nelson, Ebony, Nelson, Allison, Nguyen, Viet, Oberhaus, Jordan, Panganiban, Bernadine, Pellegrini, Kathryn L., Pickering, Harry C., Powell, Debra L., Presnell, Scott, Pulendran, Bali, Rahman, Adeeb H., Rashid, Ahmad Sadeed, Raskin, Ariel, Reed, Elaine F., Ribeiro, Susan Pereira, Rivera, Adreanne M., Rogers, Jacob E., Rogers, Angela, Rogowski, Brandon, Rooks, Rebecca, Rosenberg-Hasson, Yael, Rothman, Jessica, Rousseau, Justin F., Salehi-Rad, Ramin, Saluvan, Mehmet, Samaha, Hady, Schaenman, Joanna, Schunk, Ron, Semenza, Nicholas C., Sen, Subha, Sevransky, Jonathan, Seyfert-Margolis, Vicki, Shaheen, Tanzia, Shaw, Albert C., Sieg, Scott, Siegel, Sarah A.R., Sigal, Natalia, Siles, Nadia, Simmons, Brent, Simon, Viviana, Singh, Gagandeep, Sinko, Lauren, Smith, Cecilia M., Smolen, Kinga K., Song, Li-Zhen, Srivastava, Komal, Sullivan, Peter, Syphurs, Caitlin, Tcheou, Johnstone, Tegos, George P., Tharp, Greg K., Tong, Alexandra, Tsitsiklis, Alexandra, Ungaro, Ricardo F., Vaysman, Tatyana, Viode, Arthur, Vita, Randi, Wang, Xiaomei, Ward, Alyssa, Ward, Dawn C., Willmore, Andrew, Woloszczuk, Kyra, Wong, Kari, Woodruff, Prescott G., Xu, Leqi, van Haren, Simon, van de Guchte, Adriana, Zhao, Yujiao, Diray-Arce, Joann, Fourati, Slim, Doni Jayavelu, Naresh, Patel, Ravi, Maguire, Cole, Chang, Ana C., Dandekar, Ravi, Qi, Jingjing, Lee, Brian H., van Zalm, Patrick, Schroeder, Andrew, Chen, Ernie, Konstorum, Anna, Brito, Anderson, Gygi, Jeremy P., Kho, Alvin, Chen, Jing, Pawar, Shrikant, Gonzalez-Reiche, Ana Silvia, Hoch, Annmarie, Milliren, Carly E., Overton, James A., Westendorf, Kerstin, Cairns, Charles B., Rouphael, Nadine, Bosinger, Steven E., Kim-Schulze, Seunghee, Krammer, Florian, Rosen, Lindsey, Grubaugh, Nathan D., van Bakel, Harm, Wilson, Michael, Rajan, Jayant, Steen, Hanno, Eckalbar, Walter, Cotsapas, Chris, Langelier, Charles R., Levy, Ofer, Altman, Matthew C., Maecker, Holden, Montgomery, Ruth R., Haddad, Elias K., Sekaly, Rafick P., Esserman, Denise, Ozonoff, Al, Augustine, Alison D., Guan, Leying, Peters, Bjoern, and Kleinstein, Steven H.

Published
2023
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15. Phenotypes of disease severity in a cohort of hospitalized COVID-19 patients: Results from the IMPACC study

Author

Ozonoff, Al, Schaenman, Joanna, Jayavelu, Naresh Doni, Milliren, Carly E., Calfee, Carolyn S., Cairns, Charles B., Kraft, Monica, Baden, Lindsey R., Shaw, Albert C., Krammer, Florian, van Bakel, Harm, Esserman, Denise A., Liu, Shanshan, Sesma, Ana Fernandez, Simon, Viviana, Hafler, David A., Montgomery, Ruth R., Kleinstein, Steven H., Levy, Ofer, Bime, Chris, Haddad, Elias K., Erle, David J., Pulendran, Bali, Nadeau, Kari C., Davis, Mark M, Hough, Catherine L., Messer, William B., Higuita, Nelson I. Agudelo, Metcalf, Jordan P., Atkinson, Mark A., Brakenridge, Scott C., Corry, David, Kheradmand, Farrah, Ehrlich, Lauren I.R., Melamed, Esther, McComsey, Grace A., Sekaly, Rafick, Diray-Arce, Joann, Peters, Bjoern, Augustine, Alison D., Reed, Elaine F., McEnaney, Kerry, Barton, Brenda, Lentucci, Claudia, Saluvan, Mehmet, Chang, Ana C., Hoch, Annmarie, Albert, Marisa, Shaheen, Tanzia, Kho, Alvin T., Thomas, Sanya, Chen, Jing, Murphy, Maimouna D., Cooney, Mitchell, Presnell, Scott, Fragiadakis, Gabriela K., Patel, Ravi, Guan, Leying, Gygi, Jeremy, Pawar, Shrikant, Brito, Anderson, Khalil, Zain, Maguire, Cole, Fourati, Slim, Overton, James A., Vita, Randi, Westendorf, Kerstin, Salehi-Rad, Ramin, Leligdowicz, Aleksandra, Matthay, Michael A., Singer, Jonathan P., Kangelaris, Kirsten N., Hendrickson, Carolyn M., Krummel, Matthew F., Langelier, Charles R., Woodruff, Prescott G., Powell, Debra L., Kim, James N., Simmons, Brent, Goonewardene, I. Michael, Smith, Cecilia M., Martens, Mark, Mosier, Jarrod, Kimura, Hiroki, Sherman, Amy C., Walsh, Stephen R., Issa, Nicolas C., Dela Cruz, Charles, Farhadian, Shelli, Iwasaki, Akiko, Ko, Albert I., Chinthrajah, Sharon, Ahuja, Neera, Rogers, Angela J., Artandi, Maja, Siegel, Sarah A.R., Lu, Zhengchun, Drevets, Douglas A., Brown, Brent R., Anderson, Matthew L., Guirgis, Faheem W., Thyagarajan, Rama V., Rousseau, Justin F., Wylie, Dennis, Busch, Johanna, Gandhi, Saurin, Triplett, Todd A., Yendewa, George, Giddings, Olivia, Anderson, Evan J., Mehta, Aneesh K., Sevransky, Jonathan E., Khor, Bernard, Rahman, Adeeb, Stadlbauer, Daniel, Dutta, Jayeeta, Xie, Hui, Kim-Schulze, Seunghee, Gonzalez-Reiche, Ana Silvia, van de Guchte, Adriana, Farrugia, Keith, Khan, Zenab, Maecker, Holden T., Elashoff, David, Brook, Jenny, Ramires-Sanchez, Estefania, Llamas, Megan, Rivera, Adreanne, Perdomo, Claudia, Ward, Dawn C., Magyar, Clara E., Fulcher, Jennifer A., Abe-Jones, Yumiko, Asthana, Saurabh, Beagle, Alexander, Bhide, Sharvari, Carrillo, Sidney A., Chak, Suzanna, Ghale, Rajani, Gonzalez, Ana, Jauregui, Alejandra, Jones, Norman, Lea, Tasha, Lee, Deanna, Lota, Raphael, Milush, Jeff, Nguyen, Viet, Pierce, Logan, Prasad, Priya A., Rao, Arjun, Samad, Bushra, Shaw, Cole, Sigman, Austin, Sinha, Pratik, Ward, Alyssa, Willmore, Andrew, Zhan, Jenny, Rashid, Sadeed, Rodriguez, Nicklaus, Tang, Kevin, Altamirano, Luz Torres, Betancourt, Legna, Curiel, Cindy, Sutter, Nicole, Paz, Maria Tercero, Tietje-Ulrich, Gayelan, Leroux, Carolyn, Connors, Jennifer, Bernui, Mariana, Kutzler, Michel A., Edwards, Carolyn, Lee, Edward, Lin, Edward, Croen, Brett, Semenza, Nicholas C., Rogowski, Brandon, Melnyk, Nataliya, Woloszczuk, Kyra, Cusimano, Gina, Bell, Mathew R., Furukawa, Sara, McLin, Renee, Marrero, Pamela, Sheidy, Julie, Tegos, George P., Nagle, Crystal, Mege, Nathan, Ulring, Kristen, Seyfert-Margolis, Vicki, Conway, Michelle, Francisco, Dave, Molzahn, Allyson, Erickson, Heidi, Wilson, Connie Cathleen, Schunk, Ron, Sierra, Bianca, Hughes, Trina, Smolen, Kinga, Desjardins, Michael, van Haren, Simon, Mitre, Xhoi, Cauley, Jessica, Li, Xiaofang, Tong, Alexandra, Evans, Bethany, Montesano, Christina, Licona, Jose Humberto, Krauss, Jonathan, Chang, Jun Bai Park, Izaguirre, Natalie, Chaudhary, Omkar, Coppi, Andreas, Fournier, John, Mohanty, Subhasis, Muenker, M. Catherine, Nelson, Allison, Raddassi, Khadir, Rainone, Michael, Ruff, William E., Salahuddin, Syim, Schulz, Wade L., Vijayakumar, Pavithra, Wang, Haowei, Wunder Jr., Elsio, Young, H. Patrick, Zhao, Yujiao, Saksena, Miti, Altman, Deena, Kojic, Erna, Srivastava, Komal, Eaker, Lily Q., Bermúdez-González, Maria C., Beach, Katherine F., Sominsky, Levy A., Azad, Arman R., Carreño, Juan Manuel, Singh, Gagandeep, Raskin, Ariel, Tcheou, Johnstone, Bielak, Dominika, Kawabata, Hisaaki, Mulder, Lubbertus CF, Kleiner, Giulio, Lee, Alexandra S., Do, Evan Do, Fernandes, Andrea, Manohar, Monali, Hagan, Thomas, Blish, Catherine A., Din, Hena Naz, Roque, Jonasel, Yang, Samuel, Brunton, Amanda, Sullivan, Peter E., Strnad, Matthew, Lyski, Zoe L., Coulter, Felicity J., Booth, J. Leland, Sinko, Lauren A., Moldawer, Lyle L., Borresen, Brittany, Roth-Manning, Brittney, Song, Li-Zhen, Nelson, Ebony, Lewis-Smith, Megan, Smith, Jacob, Tipan, Pablo Guaman, Siles, Nadia, Bazzi, Sam, Geltman, Janelle, Hurley, Kerin, Gabriele, Gio, Sieg, Scott, Vaysman, Tatyana, Bristow, Laurel, Hussaini, Laila, Hellmeister, Kieffer, Samaha, Hady, Cheng, Andrew, Spainhour, Christine, Scherer, Erin M., Johnson, Brandi, Bechnak, Amer, Ciric, Caroline R., Hewitt, Lauren, Carter, Erin, Mcnair, Nina, Panganiban, Bernadine, Huerta, Christopher, Usher, Jacob, Ribeiro, Susan Pereira, Altman, Matthew C., Becker, Patrice M., Rouphael, Nadine, Bime, Christian, and Davis, Mark M.

Published
2022
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16. Ensuring reliability in electronic examinations through UPPAAL-based trustworthy design.

Author

Zhou, Wenbo, Zhao, Yujiao, Zhang, Ye, Mu, Liwen, Wang, Yiyuan, and Yin, Minghao

Subjects
TRUST, SYSTEMS design, EDUCATIONAL outcomes, COMPUTERS, ENCODING
Abstract

Electronic examination serves as an efficient method for assessing learning outcomes, yet the integration of computers into exam processes introduces potential for unreliability. In this article, we propose a formal model for electronic examinations using timed automata, providing a structured approach to understanding and managing the complexities. The electronic examination process is modeled by defining four UPPAAL templates, i.e., candidate, administrator, invigilator, and examiner. Crucial properties specific to electronic examination are encoded as specifications in UPPAAL. Verification against these properties demonstrates the validity and reliability of this model. The modelable and verifiable electronic examination designed with UPPAAL suggests great potential for deeper exploration in trustworthy digital education. [ABSTRACT FROM AUTHOR]

Published
2024
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20. Effect of a novel dwarfing mutant site on chromosome 4B on agronomic traits in common wheat

Author

Hao, Jiamin, primary, Zhao, Zhangchen, additional, Fu, Xiaoge, additional, Zhao, Yujiao, additional, Ateeq, Muhammad, additional, Mou, Liming, additional, Han, Yong, additional, Liu, Yangbin, additional, Yin, Yongan, additional, Zotova, Lyudmila, additional, Serikbay, Dauren, additional, Fan, Chunyan, additional, Hu, Yin-Gang, additional, and Chen, Liang, additional

Published
2024
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26. Improving Local Search for Pseudo Boolean Optimization by Fragile Scoring Function and Deep Optimization

Author

Wenbo Zhou and Yujiao Zhao and Yiyuan Wang and Shaowei Cai and Shimao Wang and Xinyu Wang and Minghao Yin, Zhou, Wenbo, Zhao, Yujiao, Wang, Yiyuan, Cai, Shaowei, Wang, Shimao, Wang, Xinyu, Yin, Minghao, Wenbo Zhou and Yujiao Zhao and Yiyuan Wang and Shaowei Cai and Shimao Wang and Xinyu Wang and Minghao Yin, Zhou, Wenbo, Zhao, Yujiao, Wang, Yiyuan, Cai, Shaowei, Wang, Shimao, Wang, Xinyu, and Yin, Minghao

Abstract

Pseudo-Boolean optimization (PBO) is usually used to model combinatorial optimization problems, especially for some real-world applications. Despite its significant importance in both theory and applications, there are few works on using local search to solve PBO. This paper develops a novel local search framework for PBO, which has three main ideas. First, we design a two-level selection strategy to evaluate all candidate variables. Second, we propose a novel deep optimization strategy to disturb some search spaces. Third, a sampling flipping method is applied to help the algorithm jump out of local optimum. Experimental results show that the proposed algorithms outperform three state-of-the-art PBO algorithms on most instances.

Published
2023
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27. Numerical Investigation on the Performance of Horizontal Helical-Coil-Type Backfill Heat Exchangers with Different Configurations in Mine Stopes.

Author

Zhang, Bo, Shi, Long, Zhang, Wenxuan, Huan, Chao, Zhao, Yujiao, and Wang, Jingyu

Subjects
HEAT exchangers, HEAT storage, HEAT transfer, THERMAL conductivity, HEAT capacity
Abstract

The application of ground heat exchanger technology in backfill mines can actualize subterranean heat storage, which is one of the most effective solutions for addressing solar energy faults such as intermittence and fluctuation. This paper provides a 3D unsteady heat transfer numerical model for full-size horizontal backfill heat exchangers (BFHEs) with five configurations in a mining layer of a metal mine by using a COMSOL environment. In order to ensure the fairness of the comparative analysis, the pipes of BFHEs studied have the same heat exchange surface area. By comparing and evaluating the heat storage/release characteristics of BFHEs in continuous operation for three years, it was discovered that the helical pipe with serpentine layout may effectively enhance the performance of BFHEs. Compared with the traditional SS BFHEs, the heat storage capacity of the S-FH type is significantly increased by 21.7%, followed by the SA-FH type, which is increased by 11.1%, while the performances of U-DH and SH type are considerably lowered. Also, the impact of the critical structural factors (pitch length and pitch diameter) was further studied using the normalized parameters C1 and C2 based on the inner diameter of the pipe. It is discovered that BFHEs should be distributed in a pipe with a lower C1, and increasing C2 encourages BFHEs to increase the storaged/released heat of BFHEs. By comparatively analysing the effect of thermal conductivity, it is found that the positive effects of thermal conductivity on the performance of SH, U-DH, SA-FH, and S-FH type BFHEs are found to decrease successively. This work proposes a strategy for improving the heat storage and release potential of BFHEs in terms of optimal pipe arrangement. [ABSTRACT FROM AUTHOR]

Published
2023
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29. Featured Cover

Author

Konstorum, Anna, primary, Mohanty, Subhasis, additional, Zhao, Yujiao, additional, Melillo, Anthony, additional, Vander Wyk, Brent, additional, Nelson, Allison, additional, Tsang, Sui, additional, Blevins, Tamara P., additional, Belshe, Robert B., additional, Chawla, Daniel G., additional, Rondina, Matthew T., additional, Gill, Thomas M., additional, Montgomery, Ruth R., additional, Allore, Heather G., additional, Kleinstein, Steven H., additional, and Shaw, Albert C., additional

Published
2023
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30. Platelet response to influenza vaccination reflects effects of aging

Author

Konstorum, Anna, primary, Mohanty, Subhasis, additional, Zhao, Yujiao, additional, Melillo, Anthony, additional, Vander Wyk, Brent, additional, Nelson, Allison, additional, Tsang, Sui, additional, Blevins, Tamara P., additional, Belshe, Robert B., additional, Chawla, Daniel G., additional, Rondina, Matthew T., additional, Gill, Thomas M., additional, Montgomery, Ruth R., additional, Allore, Heather G., additional, Kleinstein, Steven H., additional, and Shaw, Albert C., additional

Published
2023
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44. The Safety, Immunogenicity, and Immunopersistence of Hepatitis A Vaccine in HBs-Ag-Positive Participants: A Retrospective Study

Author

Wang, Xiaodan, primary, Luo, Jia, additional, Ma, Fubao, additional, Kang, Guodong, additional, Ding, Zhengrong, additional, Pan, Yue, additional, Zhao, Yujiao, additional, Chen, Junying, additional, Feng, Kai, additional, Yan, Lingmei, additional, Zhang, Juan, additional, Li, Linhao, additional, Lan, Qiangping, additional, Li, Daiying, additional, Yang, Xiaolei, additional, Li, Guoliang, additional, Yang, Jingsi, additional, and Sun, Qiangming, additional

Published
2021
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46. Nlrp9b inflammasome restricts rotavirus infection in intestinal epithelial cells

Author

Zhu, Shu, Ding, Siyuan, Wang, Penghua, Wei, Zheng, Pan, Wen, Palm, Noah W., Yang, Yi, Yu, Hua, Li, Hua-Bing, Wang, Geng, Lei, Xuqiu, de Zoete, Marcel R., Zhao, Jun, Zheng, Yunjiang, Chen, Haiwei, Zhao, Yujiao, Jurado, Kellie A., Feng, Ningguo, Shan, Liang, Kluger, Yuval, Lu, Jun, Abraham, Clara, Fikrig, Erol, Greenberg, Harry B., and Flavell, Richard A.

Subjects
Rotaviruses -- Health aspects, Epithelial cells -- Health aspects, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Shu Zhu [1]; Siyuan Ding [2, 3]; Penghua Wang [4]; Zheng Wei [1]; Wen Pan [5]; Noah W. Palm [1]; Yi Yang [1]; Hua Yu [1]; Hua-Bing Li [1]; [...]

Published
2017
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49. Single cell immune profiling of dengue virus patients reveals intact immune responses to Zika virus with enrichment of innate immune signatures

Author

Zhao, Yujiao, primary, Amodio, Matthew, additional, Vander Wyk, Brent, additional, Gerritsen, Bram, additional, Kumar, Mahesh M., additional, van Dijk, David, additional, Moon, Kevin, additional, Wang, Xiaomei, additional, Malawista, Anna, additional, Richards, Monique M., additional, Cahill, Megan E., additional, Desai, Anita, additional, Sivadasan, Jayasree, additional, Venkataswamy, Manjunatha M., additional, Ravi, Vasanthapuram, additional, Fikrig, Erol, additional, Kumar, Priti, additional, Kleinstein, Steven H., additional, Krishnaswamy, Smita, additional, and Montgomery, Ruth R., additional

Published
2020
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