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4,693 results on '"Wu, Yin"'

203. Data-driven methods distort optimal cutoffs and accuracy estimates of depression screening tools: a simulation study using individual participant data

Author

Sun, Ying, He, Chen, Rice, Danielle B., Krishnan, Ankur, Wu, Yin, Azar, Marleine, Sanchez, Tatiana A., Chiovitti, Matthew J., Saadat, Nazanin, Riehm, Kira E., Imran, Mahrukh, Negeri, Zelalem, Boruff, Jill T., Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., Ziegelstein, Roy C., Comeau, Liane, Mitchell, Nicholas D., Tonelli, Marcello, Vigod, Simone N., Aceti, Franca, Alvarado, Rubén, Alvarado-Esquivel, Cosme, Bakare, Muideen O., Barnes, Jacqueline, Bavle, Amar D., Beck, Cheryl Tatano, Bindt, Carola, Boyce, Philip M., Bunevicius, Adomas, Castro e Couto, Tiago, Chaudron, Linda H., Correa, Humberto, de Figueiredo, Felipe Pinheiro, Eapen, Valsamma, Favez, Nicolas, Felice, Ethel, Fernandes, Michelle, Figueiredo, Barbara, Fisher, Jane R.W., Garcia-Esteve, Lluïsa, Giardinelli, Lisa, Helle, Nadine, Howard, Louise M., Khalifa, Dina Sami, Kohlhoff, Jane, Kozinszky, Zoltán, Kusminskas, Laima, Lelli, Lorenzo, Leonardou, Angeliki A., Maes, Michael, Meuti, Valentina, Radoš, Sandra Nakić, García, Purificación Navarro, Nishi, Daisuke, Luwa E-Andjafono, Daniel Okitundu, Pawlby, Susan J., Quispel, Chantal, Robertson-Blackmore, Emma, Rochat, Tamsen J., Rowe, Heather J., Sharp, Deborah J., Siu, Bonnie W.M., Skalkidou, Alkistis, Stein, Alan, Stewart, Robert C., Su, Kuan-Pin, Sundström-Poromaa, Inger, Tadinac, Meri, Tandon, S. Darius, Tendais, Iva, Thiagayson, Pavaani, Töreki, Annamária, Torres-Giménez, Anna, Tran, Thach D., Trevillion, Kylee, Turner, Katherine, Vega-Dienstmaier, Johann M., Wynter, Karen, Yonkers, Kimberly A., Bhandari, Parash Mani, Levis, Brooke, Neupane, Dipika, Patten, Scott B., Shrier, Ian, Thombs, Brett D., and Benedetti, Andrea

Published
2021
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204. The Accuracy of the Patient Health Questionnaire-9 Algorithm for Screening to Detect Major Depression : An Individual Participant Data Meta-Analysis

Author

He, Chen, Levis, Brooke, Riehm, Kira E., Saadat, Nazanin, Levis, Alexander W., Azar, Marleine, Rice, Danielle B., Krishnan, Ankur, Wu, Yin, Sun, Ying, Imran, Mahrukh, Boruff, Jill, Cuijpers, Pim, Gilbody, Simon, Ioannidis, John P.A., Kloda, Lorie A., McMillan, Dean, Patten, Scott B., Shrier, Ian, Ziegelstein, Roy C., Akena, Dickens H., Arroll, Bruce, Ayalon, Liat, Baradaran, Hamid R., Baron, Murray, Beraldi, Anna, Bombardier, Charles H., Butterworth, Peter, Carter, Gregory, Chagas, Marcos Hortes Nisihara, Chan, Juliana C.N., Cholera, Rushina, Clover, Kerrie, Conwell, Yeates, de Man-van Ginkel, Janneke M., Fann, Jesse R., Fischer, Felix H., Fung, Daniel, Gelaye, Bizu, Goodyear-Smith, Felicity, Greeno, Catherine G., Hall, Brian J., Harrison, Patricia A., Härter, Martin, Hegerl, Ulrich, Hides, Leanne, Hobfoll, Stevan E., Hudson, Marie, Hyphantis, Thomas N., Inagaki, Masatoshi, Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E., Kiely, Kim M., Kwan, Yunxin, Lamers, Femke, Liu, Shen-Ing, Lotrakul, Manote, Loureiro, Sonia R., Löwe, Bernd, Marsh, Laura, McGuire, Anthony, Mohd-Sidik, Sherina, Munhoz, Tiago N., Muramatsu, Kumiko, Osório, Flávia L., Patel, Vikram, Pence, Brian W., Persoons, Philippe, Picardi, Angelo, Reuter, Katrin, Rooney, Alasdair G., da Silva dos Santos, Iná S., Shaaban, Juwita, Sidebottom, Abbey, Simning, Adam, Stafford, Lesley, Sung, Sharon, Tan, Pei Lin Lynnette, Turner, Alyna, van Weert, Henk C.P.M., White, Jennifer, Whooley, Mary A., Winkley, Kirsty, Yamada, Mitsuhiko, Thombs, Brett D., and Benedetti, Andrea

Published
2020

209. Safety and immunogenicity of one versus two doses of the COVID-19 vaccine BNT162b2 for patients with cancer: interim analysis of a prospective observational study

Author

Monin, Leticia, Laing, Adam G, Muñoz-Ruiz, Miguel, McKenzie, Duncan R, del Molino del Barrio, Irene, Alaguthurai, Thanussuyah, Domingo-Vila, Clara, Hayday, Thomas S, Graham, Carl, Seow, Jeffrey, Abdul-Jawad, Sultan, Kamdar, Shraddha, Harvey-Jones, Elizabeth, Graham, Rosalind, Cooper, Jack, Khan, Muhammad, Vidler, Jennifer, Kakkassery, Helen, Sinha, Shubhankar, Davis, Richard, Dupont, Liane, Francos Quijorna, Isaac, O'Brien-Gore, Charlotte, Lee, Puay Ling, Eum, Josephine, Conde Poole, Maria, Joseph, Magdalene, Davies, Daniel, Wu, Yin, Swampillai, Angela, North, Bernard V, Montes, Ana, Harries, Mark, Rigg, Anne, Spicer, James, Malim, Michael H, Fields, Paul, Patten, Piers, Di Rosa, Francesca, Papa, Sophie, Tree, Timothy, Doores, Katie J, Hayday, Adrian C, and Irshad, Sheeba

Published
2021
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211. List of contributors

Author

Bales, Clare, primary, Ballesteros, Florencio, additional, Belgiorno, Vincenzo, additional, Borea, Laura, additional, Chen, Mei, additional, Chen, Xi, additional, Chen, Zhibin, additional, Choo, Kwang-Ho, additional, Corpuz, Mary Vermi Aizza, additional, Cusick, Roland, additional, Dai, Ruobin, additional, Gao, Fei, additional, Gao, Miao, additional, Gu, Zhenao, additional, Hasan, Shadi W., additional, Hou, Chia-Hung, additional, Hu, Chengzhi, additional, Hu, Hong-Ying, additional, Huang, Xia, additional, Huo, Zheng-Yang, additional, Jeon, Jemin, additional, Jiang, Chenxiao, additional, Kayiwa, Emmanuel, additional, Kong, Xiangtong, additional, Li, Jiayi, additional, Li, Wen-Wei, additional, Li, Xuesong, additional, Li, Yang, additional, Li, Zhouyan, additional, Liu, Hai, additional, Liu, Han, additional, Liu, Lihu, additional, Liu, Yanbiao, additional, Liu, Yang, additional, Lu, Chenghai, additional, Luo, Shuai, additional, Ma, Jinxing, additional, Mameda, Naresh, additional, Mei, Ying, additional, Naddeo, Vincenzo, additional, Ni, Xin-Ye, additional, Qiao, Yiwen, additional, Ren, Yifan, additional, Román Santiago, Anaira, additional, Su, Xiao, additional, Sun, Jingqiu, additional, Tang, Chuyang Y., additional, Waite, T. David, additional, Wang, Hao-Bin, additional, Wang, Lei, additional, Wang, Tianyu, additional, Wang, Xueye, additional, Wang, Zhiwei, additional, Wu, Yin-Hu, additional, Wu, You, additional, You, Shijie, additional, Yuan, Jia, additional, Zhang, Changyong, additional, Zhang, Yang, additional, Zhang, Zhong, additional, and Zuo, Kuichang, additional

Published
2022
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225. Factors associated with fears due to COVID-19: A Scleroderma Patient-centered Intervention Network (SPIN) COVID-19 cohort study

Author

Fortuné, Catherine, Gietzen, Amy, Guillot, Geneviève, Lewis, Nancy, Richard, Michelle, Sauvé, Maureen, Welling, Joep, Fligelstone, Kim, Gottesman, Karen, Leite, Catarina, Pérez, Elisabet, Baron, Murray, Malcarne, Vanessa, Mayes, Maureen D., Nielson, Warren R., Riggs, Robert, Assassi, Shervin, Ells, Carolyn, van den Ende, Cornelia, Frech, Tracy, Harel, Daphna, Hinchcliff, Monique, Hudson, Marie, Johnson, Sindhu R., Larche, Maggie, Nguyen, Christelle, Pope, Janet, Rannou, François, Reyna, Tatiana Sofia Rodriguez, Schouffoer, Anne A., Suarez-Almazor, Maria E., Agard, Christian, Albert, Alexandra, Bernstein, Elana J., Berthier, Sabine, Bissonnette, Lyne, Bruns, Alessandra, Carreira, Patricia, Chaigne, Benjamin, Chung, Lorinda, Correia, Chase, Denton, Christopher, Domsic, Robyn, Dunne, James V., Dunogue, Bertrand, Farge-Bancel, Dominique, Fortin, Paul R., Gordon, Jessica, Granel-Rey, Brigitte, Hatron, Pierre-Yves, Herrick, Ariane L., Hoa, Sabrina, Jones, Niall, Fernandes, Artur Jose de B., Kafaja, Suzanne, Khalidi, Nader, Launay, David, Manning, Joanne, Marie, Isabelle, Martin, Maria, Mekinian, Arsene, Melchor, Sheila, Nikpour, Mandana, Olagne, Louis, Proudman, Susanna, Régent, Alexis, Rivière, Sébastien, Robinson, David, Rodriguez, Esther, Roux, Sophie, Sobanski, Vincent, Steen, Virginia, Sutton, Evelyn, Thorne, Carter, Wilcox, Pearce, Ayala, Mara Cañedo, Carboni-Jiménez, Andrea, Gagarine, Maria, Nordlund, Julia, Østbø, Nora, Rice, Danielle B., Turner, Kimberly A., Culos-Reed, Nicole, Dyas, Laura, El-Baalbaki, Ghassan, Hebblethwaite, Shannon, Bustamante, Laura, Duchek, Delaney, Ellis, Kelsey, Wu, Yin, Kwakkenbos, Linda, Henry, Richard S., Carrier, Marie-Eve, Harb, Sami, Bourgeault, Angelica, Tao, Lydia, Negeri, Zelalem, Patten, Scott, Bartlett, Susan J., Mouthon, Luc, Varga, John, Benedetti, Andrea, and Thombs, Brett D.

Published
2021
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228. Cross-layer Framework for Energy Harvesting-LPWAN Resource Management based on Fuzzy Cognitive Maps and Adaptive Glowworm Swarm Optimization for Smart Forest

Author

Wang, Hancong, Wu, Yin, Ni, Qiang, Liu, Wenbo, Wang, Hancong, Wu, Yin, Ni, Qiang, and Liu, Wenbo

Abstract

Modern forestry research and management increasingly rely on precise environmental data. Presently, Low Power Wide Area Networks (LPWANs) offer potential advantages for such field monitoring tasks. However, their applicability requires enhancements in aspects such as power consumption, transmission range, data rate, and consistent quality of service. This paper introduces a novel control model emphasizing cross-layer collaboration, aiming to bolster the efficiency and reliability of Energy Harvesting (EH) LPWANs within the context of intelligent forest management. By employing the influential factors of EH-LPWAN as conceptual nodes, an innovative fuzzy cognitive map (FCM) can be designed. The interrelations among these concepts become instrumental in developing the cross-layer optimization model, addressing various objectives and tackling overlapping constraints. To further refine the model’s efficacy, an adaptive glowworm swarm optimization (AGSO) driven dynamic FCM method is presented to ascertain the conceptual weights while facilitating real-time updates. Preliminary results manifest a noteworthy enhancement in communication range by 40.2%, a betterment in packet delivery accuracy by 19%, and an extension in the LoRaWAN’s projected lifespan by 33.8% during scenarios with diminished EH rates. It’s evident that the energy self-sustainability of EH nodes coupled with the data handling capacity of the entire network fully aligns with the stringent real-time and consistency criteria mandated for meticulous forest observation.

Published
2024

229. Decomposing Label Space, Format and Discrimination: Rethinking How LLMs Respond and Solve Tasks via In-Context Learning

Author

Long, Quanyu, Wu, Yin, Wang, Wenya, Pan, Sinno Jialin, Long, Quanyu, Wu, Yin, Wang, Wenya, and Pan, Sinno Jialin

Abstract

In-context Learning (ICL) has emerged as a powerful capability alongside the development of scaled-up large language models (LLMs). By instructing LLMs using few-shot demonstrative examples, ICL enables them to perform a wide range of tasks without updating millions of parameters. However, the precise contributions of demonstrations towards improving end-task performance have not been thoroughly investigated in recent analytical studies. In this paper, we empirically decompose the overall performance of ICL into three dimensions, label space, format, and discrimination, and we evaluate four general-purpose LLMs across a diverse range of tasks. Counter-intuitively, we find that the demonstrations have a marginal impact on provoking discriminative knowledge of language models. However, ICL exhibits significant efficacy in regulating the label space and format which helps LLMs to respond in desired label words. We then demonstrate this ability functions similar to detailed instructions for LLMs to follow. We additionally provide an in-depth analysis of the mechanism of retrieval helping with ICL and find that retrieving the most semantically similar examples notably boosts model's discriminative capability., Comment: 36 pages, 8 figures

Published
2024

230. Expansion dynamics in a one-dimensional hard-core boson model with three-body interactions

Author

Ren, Jie, Wu, Yin-Zhong, and Xu, Xue-Fen

Subjects
Quantum Physics, Condensed Matter - Quantum Gases
Abstract

Using the adaptive time-dependent density matrix renormalization group method, we numerically investigate the expansion dynamics of bosons in a one-dimensional hard-core boson model with three-body interactions. It is found that the bosons expand ballistically with weak interaction, which are obtained by local density and the radius $R_n$. It is shown that the expansion velocity $V$, obtained from $R_n=Vt$, is dependent on the number of bosons. As a prominent result, the expansion velocity decreases with the enhancement of three-body interaction. We further study the dynamics of the system, which quenches from the ground state with two-thirds filling, the results indicate the expansion is also ballistic in the gapless phase regime. It could help us detect the phase transition in the system.

Published
2015
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231. College Readiness and Engagement Gaps between Domestic and International Students: Re-Envisioning Educational Diversity and Equity for Global Campus

Author

Lee, Jaekyung, Kim, Namsook, and Wu, Yin

Abstract

This study examines undergraduate students' college readiness and educational engagement gaps in a US public research university. The study reveals the heterogeneity of domestic (American) and international student groups. While typical international students may have disadvantages in college readiness and engagement, English speakers and American high schoolers among international students perform even better than domestic peers. In contrast, English learners and foreign high schoolers among domestic students, such as recent immigrants face the same challenges as typical international peers lacking adequate language and cultural preparation for college success. The study re-envisions educational diversity and equity for global campus where an integrated system of academic and sociocultural support enables transnational students to succeed. [For a related report, see ED583679.]

Published
2019
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232. Comparison of Chiggers (Acari: Trombiculidae, Leeuwenhoekiidae) on Two Sibling Mouse Species, Apodemus draco and A. ilex (Rodentia: Muridae), in Southwest China

Author

Yu Guo, Xian-Guo Guo, Wen-Yu Song, Yan Lv, Peng-Wu Yin, and Dao-Chao Jin

Subjects
chigger mites, ectoparasite, South China field mouse, Lantsang field mouse, rodent, southwest China, Veterinary medicine, SF600-1100, Zoology, QL1-991
Abstract

Chigger mites (Acari) are common ectoparasites on rodents, and they are the exclusive vector of scrub typhus. South China field mouse (Apodemus draco) and Lantsang field mouse (A. ilex) are two sibling rodent species. Based on field investigations in southwest China (2001–2015), this paper compared the infestation of these two mouse species with chiggers. Of 42 chigger species identified from two mouse species, 36 were found on A. draco, 11 on A. ilex and 5 common species on both mice. Jaccard similarity index (J = 0.12, J < 0.25) showed a very different species composition of chiggers on two mouse species, and some parameters of the chigger community were also different. The overall mean intensity of chiggers on A. draco (MI = 4.26) was higher than that on A. ilex (MI = 3.91, p < 0.05). The dominant chigger species on A. draco were Trombiculindus yunnanus, Leptotrombidium scutellare (a major vector species in China) and L. sinicum with a total constituent ratio Cr = 42.9% (106/247). Leptorombidium sinicum and L. scutellare independently occurred on A. draco with an association coefficient V = 0.09 (V ≈ 0). The dominant chigger species on A. ilex were L. rusticum, L. densipunctatum and L. gongshanense, with a total Cr = 58.14% (25/43). Leptorombidium rusticum and L. densipunctatum on A. ilex had a slight positive association (V = 0.49, 0.5 < V < 1). All dominant chigger species were unevenly distributed among different individuals of two mouse species. Chigger infestation showed sex bias on different sexes of two mouse species. The species abundance of the chigger community on A. draco was revealed as a log-normal distribution pattern.

Published
2023
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233. Depression prevalence using the HADS-D compared to SCID major depression classification: An individual participant data meta-analysis

Author

Brehaut, Eliana, Neupane, Dipika, Levis, Brooke, Wu, Yin, Sun, Ying, Krishnan, Ankur, He, Chen, Bhandari, Parash Mani, Negeri, Zelalem, Riehm, Kira E., Rice, Danielle B., Azar, Marleine, Yan, Xin Wei, Imran, Mahrukh, Chiovitti, Matthew J., Saadat, Nazanin, Cuijpers, Pim, Ioannidis, John P.A., Markham, Sarah, Patten, Scott B., Ziegelstein, Roy C., Henry, Melissa, Ismail, Zahinoor, Loiselle, Carmen G., Mitchell, Nicholas D., Tonelli, Marcello, Boruff, Jill T., Kloda, Lorie A., Beraldi, Anna, Braeken, Anna P.B.M., Carter, Gregory, Clover, Kerrie, Conroy, Ronán M., Cukor, Daniel, da Rocha e Silva, Carlos E., De Souza, Jennifer, Downing, Marina G., Feinstein, Anthony, Ferentinos, Panagiotis P., Fischer, Felix H., Flint, Alastair J., Fujimori, Maiko, Gallagher, Pamela, Goebel, Simone, Jetté, Nathalie, Julião, Miguel, Keller, Monika, Kjærgaard, Marie, Love, Anthony W., Löwe, Bernd, Martin-Santos, Rocio, Michopoulos, Ioannis, Navines, Ricard, O’Rourke, Suzanne J., Öztürk, Ahmet, Pintor, Luis, Ponsford, Jennie L., Rooney, Alasdair G., Sánchez-González, Roberto, Schwarzbold, Marcelo L., Sharpe, Michael, Simard, Sébastien, Singer, Susanne, Stone, Jon, Tung, Ka-Yee, Turner, Alyna, Walker, Jane, Walterfang, Mark, White, Jennifer, Benedetti, Andrea, and Thombs, Brett D.

Published
2020
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234. Validation of the COVID-19 Fears Questionnaires for Chronic Medical Conditions: A Scleroderma Patient-centered Intervention Network COVID-19 Cohort study

Author

Culos-Reed, Nicole, El-Baalbaki, Ghassan, Hebblethwaite, Shannon, Patten, Scott, Varga, John, Bustamante, Laura, Duchek, Delaney, Ellis, Kelsey, Rice, Danielle, Dyas, Laura, Fortuné, Catherine, Gietzen, Amy, Guillot, Geneviève, Lewis, Nancy, Nielsen, Karen, Richard, Michelle, Sauvé, Maureen, Welling, Joep, Wu, Yin, Kwakkenbos, Linda, Henry, Richard S., Tao, Lydia, Harb, Sami, Bourgeault, Angelica, Carrier, Marie-Eve, Levis, Brooke, Sun, Ying, Bhandari, Parash Mani, Carboni-Jiménez, Andrea, Gagarine, Maria, He, Chen, Krishnan, Ankur, Negeri, Zelalem F., Neupane, Dipika, Mouthon, Luc, Bartlett, Susan J., Benedetti, Andrea, and Thombs, Brett D.

Published
2020
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235. Monitoring the Nitrogen Nutrition Index Using Leaf-Based Hyperspectral Reflectance in Cut Chrysanthemums.

Author

Wu, Yin, Lu, Jingshan, Liu, Huahao, Gou, Tingyu, Chen, Fadi, Fang, Weimin, Chen, Sumei, Zhao, Shuang, Jiang, Jiafu, and Guan, Zhiyong

Subjects
*PARTIAL least squares regression, *REMOTE sensing, *LEAST squares, *CHRYSANTHEMUMS, *REFLECTANCE, *BIOMASS
Abstract

Precise nitrogen supply is crucial for ensuring the quality of cut chrysanthemums (Chrysanthemum morifolium Ramat.). The nitrogen nutrition index (NNI) serves as an important indicator for diagnosing crop nitrogen (N) nutrition. Hyperspectral remote sensing (HRS) technology has been widely used in monitoring crop N status due to its rapid, accurate, and non-destructive capabilities. However, its application in estimating the NNI of cut chrysanthemums has received limited attention. Therefore, this study aimed to use HRS to accurately determine the cut chrysanthemum NNI, thereby providing valuable guidance for managing N fertilization. During several key growth stages, a hyperspectral spectroradiometer was used to capture hyperspectral reflectance data (350–2500 nm) from three leaf layers. Subsequently, cut chrysanthemum canopies were sampled for aboveground biomass (AGB) and plant nitrogen concentration (PNC). The collected AGB and PNC data were then utilized to fit the critical N (Nc) dilution curve of cut chrysanthemums using a Bayesian hierarchical model, enabling the calculation of the NNI. Finally, spectral indices and partial least squares regression (PLSR) were used to establish the NNI estimation model for cut chrysanthemums. The results showed that the Nc dilution curve of the cut chrysanthemums was Nc = 5.401 × AGB−0.468. The first leaf layer (L1) proved to be optimal for estimating cut chrysanthemum NNI. Additionally, a newly proposed two-band spectral index, DVI-L1 (R1105, R700), demonstrated moderate predictive capabilities for the NNI of cut chrysanthemums (R2 = 0.5309, RMSE = 0.3210). Compared with the spectral index-based NNI estimation model, PLSR-L1 showed the best performance in estimating the cut chrysanthemum NNI (R2 = 0.8177, RMSE = 0.2000). Our results highlight the rapid NNI prediction potential of HRS and its significance in facilitating precise N management in cut chrysanthemums. [ABSTRACT FROM AUTHOR]

Published
2024
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237. Research on a Method for Classifying Bolt Corrosion Based on an Acoustic Emission Sensor System.

Author

Di, Shuyi, Wu, Yin, and Liu, Yanyi

Subjects
*ACOUSTIC emission, *MACHINE learning, *FEATURE selection, *SENSOR networks, *ACCIDENT prevention
Abstract

High-strength bolts play a crucial role in ultra-high-pressure equipment such as bridges and railway tracks. Effective monitoring of bolt conditions is of paramount importance for common fault repair and accident prevention. This paper aims to detect and classify bolt corrosion levels accurately. We design and implement a bolt corrosion classification system based on a Wireless Acoustic Emission Sensor Network (WASN). Initially, WASN nodes collect high-speed acoustic emission (AE) signals from bolts. Then, the ReliefF feature selection algorithm is applied to identify the optimal feature combination. Subsequently, the Extreme Learning Machine (ELM) model is utilized for bolt corrosion classification. Additionally, to achieve high prediction accuracy, an improved goose algorithm (GOOSE) is employed to ensure the most suitable parameter combination for the ELM model. Experimental measurements were conducted on five classes of bolt corrosion levels: 0%, 25%, 50%, 75%, and 100%. The classification accuracy obtained using the proposed method was at least 98.04%. Compared to state-of-the-art classification diagnostic models, our approach exhibits superior AE signal recognition performance and stronger generalization ability to adapt to variations in working conditions. [ABSTRACT FROM AUTHOR]

Published
2024
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238. B1 inhomogeneity corrected CEST MRI based on direct saturation removed omega plot model at 5T.

Author

Wu, Qiting, Gong, Pengcheng, Liu, Shengping, Li, Ye, Liang, Dong, Zheng, Hairong, and Wu, Yin

Subjects
INTERPOLATION algorithms, MAGNETIC resonance imaging, WHITE matter (Nerve tissue), INTERPOLATION, MAGNETIZATION transfer
Abstract

Purpose: CEST can image macromolecules/compounds via detecting chemical exchange between labile protons and bulk water. B1 field inhomogeneity impairs CEST quantification. Conventional B1 inhomogeneity correction methods depend on interpolation algorithms, B1 choices, acquisition number or calibration curves, making reliable correction challenging. This study proposed a novel B1 inhomogeneity correction method based on a direct saturation (DS) removed omega plot model. Methods: Four healthy volunteers underwent B1 field mapping and CEST imaging under four nominal B1 levels of 0.75, 1.0, 1.5, and 2.0 μT at 5T. DS was resolved using a multi‐pool Lorentzian model and removed from respective Z spectrum. Residual spectral signals were used to construct the omega plot as a linear function of 1/B12$$ {B}_1^2 $$, from which corrected signals at nominal B1 levels were calculated. Routine asymmetry analysis was conducted to quantify amide proton transfer (APT) effect. Its distribution across white matter was compared before and after B1 inhomogeneity correction and also with the conventional interpolation approach. Results: B1 inhomogeneity yielded conspicuous artifact on APT images. Such artifact was mitigated by the proposed method. Homogeneous APT maps were shown with SD consistently smaller than that before B1 inhomogeneity correction and the interpolation method. Moreover, B1 inhomogeneity correction from two and four CEST acquisitions yielded similar results, superior over the interpolation method that derived inconsistent APT contrasts among different B1 choices. Conclusion: The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI. [ABSTRACT FROM AUTHOR]

Published
2024
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240. Determination of Xylazine and Its Metabolite in Milk by a Molecularly Imprinted Microsphere Based Pseudo Immunoassay.

Author

Liu, Ge Lin, Hou, Hao Zhe, Su, Yan, Peng, Yao Jia, Wu, Yin Liang, and Wang, Jian Ping

Subjects
IMPRINTED polymers, FOOD of animal origin, LIQUID chromatography-mass spectrometry, XYLAZINE, ENZYME-linked immunosorbent assay
Abstract

The residues of xylazine and its metabolite in foods of animal origin are dangerous to consumers, but there has been no enzyme-linked immunosorbent assay (ELISA) or ELISA-like method reported to determine them so far. In this study, molecularly imprinted microspheres with xylazine as the template were synthesized, and 2,6-dimethylaniline (the metabolite of xylazine) was used as a hapten to prepare a streptavidinated horseradish peroxidase-labeled conjugate. A direct competitive pseudo-ELISA was developed on a microplate for xylazine and 2,6-dimethylaniline in milk. Because biotinylated horseradish peroxidase was employed to enhance the signal, the limits of detection for xylazine (0.003 ng/mL) and 2,6-dimethylaniline (0.005 ng/mL) were increased by 16.7- and 14-fold, respectively, compared to a horseradish peroxidase-labeled conjugate. Moreover, this material may be reused three times. The analysis of milk samples was consistent with values obtained by liquid chromatography tandem mass spectrometry. This is the first paper reporting a molecularly imprinted polymer-based method for the determination of xylazine and its metabolites in food. [ABSTRACT FROM AUTHOR]

Published
2024
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242. An Adaptive Kalman Filter Based Ocean Wave Prediction Model Using Motion Reference Unit Data

Author

Tang, Yan, Guo, Zequan, Wu, Yin, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Li, Guoliang, editor, Yang, Jun, editor, Gama, Joao, editor, Natwichai, Juggapong, editor, and Tong, Yongxin, editor

Published
2019
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249. Protocol for a partially nested randomised controlled trial to evaluate the effectiveness of the scleroderma patient-centered intervention network COVID-19 home-isolation activities together (SPIN-CHAT) program to reduce anxiety among at-risk scleroderma patients

Author

Fortuné, Catherine, Gietzen, Amy, Guillot, Geneviève, Lewis, Nancy, Nielsen, Karen, Richard, Michelle, Sauvé, Maureen, Welling, Joep, Baron, Murray, Furst, Daniel E., Gottesman, Karen, Malcarne, Vanessa, Mayes, Maureen D., Mouthon, Luc, Nielson, Warren R., Riggs, Robert, Wigley, Fredrick, Assassi, Shervin, Boutron, Isabelle, Ells, Carolyn, van den Ende, Cornelia, Fligelstone, Kim, Frech, Tracy, Godard, Dominique, Harel, Daphna, Hinchcliff, Monique, Hudson, Marie, Johnson, Sindhu R., Larche, Maggie, Leite, Catarina, Nguyen, Christelle, Pope, Janet, Portales, Alexandra, Rannou, François, Reyna, Tatiana Sofia Rodriguez, Schouffoer, Anne A., Suarez-Almazor, Maria E., Agard, Christian, Albert, Alexandra, André, Marc, Arsenault, Guylaine, Benzidia, Ilham, Bernstein, Elana J., Berthier, Sabine, Bissonnette, Lyne, Boire, Gilles, Bruns, Alessandra, Carreira, Patricia, Casadevall, Marion, Chaigne, Benjamin, Chung, Lorinda, Cohen, Pascal, Correia, Chase, Dagenais, Pierre, Denton, Christopher, Domsic, Robyn, Dubois, Sandrine, Dunne, James V., Dunogue, Bertrand, Fare, Regina, Farge-Bancel, Dominique, Fortin, Paul R., Gill, Anna, Gordon, Jessica, Granel-Rey, Brigitte, Gyger, Genevieve, Hachulla, Eric, Hatron, Pierre-Yves, Herrick, Ariane L., Hij, Adrian, Hoa, Sabrina, Ikic, Alena, Jones, Niall, de B. Fernandes, Artur Jose, Kafaja, Suzanne, Khalidi, Nader, Lambert, Marc, Launay, David, Liang, Patrick, Maillard, Hélène, Maltez, Nancy, Manning, Joanne, Marie, Isabelle, Martin, Maria, Martin, Thierry, Masetto, Ariel, Maurier, François, Mekinian, Arsene, Melchor, Sheila, Nikpour, Mandana, Olagne, Louis, Poindron, Vincent, Proudman, Susanna, Régent, Alexis, Rivière, Sébastien, Robinson, David, Rodriguez, Esther, Roux, Sophie, Smets, Perrine, Smith, Doug, Sobanski, Vincent, Spiera, Robert, Steen, Virginia, Stevens, Wendy, Sutton, Evelyn, Terrier, Benjamin, Thorne, Carter, Varga, John, Wilcox, Pearce, Ayala, Mara Cañedo, Ostbo, Nora, Thombs, Brett D., Kwakkenbos, Linda, Carrier, Marie-Eve, Bourgeault, Angelica, Tao, Lydia, Harb, Sami, Gagarine, Maria, Rice, Danielle, Bustamante, Laura, Ellis, Kelsey, Duchek, Delaney, Wu, Yin, Bhandari, Parash Mani, Neupane, Dipika, Carboni-Jiménez, Andrea, Henry, Richard S., Krishnan, Ankur, Sun, Ying, Levis, Brooke, He, Chen, Turner, Kimberly A., Benedetti, Andrea, Culos-Reed, Nicole, El-Baalbaki, Ghassan, Hebblethwaite, Shannon, Bartlett, Susan J., Dyas, Laura, and Patten, Scott

Published
2020
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250. Patient Health Questionnaire-9 scores do not accurately estimate depression prevalence: individual participant data meta-analysis

Author

Levis, Brooke, Benedetti, Andrea, Ioannidis, John P.A., Sun, Ying, Negeri, Zelalem, He, Chen, Wu, Yin, Krishnan, Ankur, Bhandari, Parash Mani, Neupane, Dipika, Imran, Mahrukh, Rice, Danielle B., Riehm, Kira E., Saadat, Nazanin, Azar, Marleine, Boruff, Jill, Cuijpers, Pim, Gilbody, Simon, Kloda, Lorie A., McMillan, Dean, Patten, Scott B., Shrier, Ian, Ziegelstein, Roy C., Alamri, Sultan H., Amtmann, Dagmar, Ayalon, Liat, Baradaran, Hamid R., Beraldi, Anna, Bernstein, Charles N., Bhana, Arvin, Bombardier, Charles H., Carter, Gregory, Chagas, Marcos H., Chibanda, Dixon, Clover, Kerrie, Conwell, Yeates, Diez-Quevedo, Crisanto, Fann, Jesse R., Fischer, Felix H., Gholizadeh, Leila, Gibson, Lorna J., Green, Eric P., Greeno, Catherine G., Hall, Brian J., Haroz, Emily E., Ismail, Khalida, Jetté, Nathalie, Khamseh, Mohammad E., Kwan, Yunxin, Lara, Maria Asunción, Liu, Shen-Ing, Loureiro, Sonia R., Löwe, Bernd, Marrie, Ruth Ann, Marsh, Laura, McGuire, Anthony, Muramatsu, Kumiko, Navarrete, Laura, Osório, Flávia L., Petersen, Inge, Picardi, Angelo, Pugh, Stephanie L., Quinn, Terence J., Rooney, Alasdair G., Shinn, Eileen H., Sidebottom, Abbey, Spangenberg, Lena, Tan, Pei Lin Lynnette, Taylor-Rowan, Martin, Turner, Alyna, van Weert, Henk C., Vöhringer, Paul A., Wagner, Lynne I., White, Jennifer, Winkley, Kirsty, and Thombs, Brett D.

Published
2020
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