Search

Your search keyword '"Song, Weidong"' showing total 410 results
Start Over Author "Song, Weidong" Search Limiters Available in Library Collection
410 results on '"Song, Weidong"'

13. Finite Element Analysis of Flexsplines of Cone-beam Oral CT Harmonic Reducers

Author

Wang Zhijie, Song Weidong, Zhang Yue, Guan Haoran, and Zhang Fengshou

Subjects
Cone-beam oral CT, Harmonic reducer, Flexspline, Finite element analysis, Mechanical engineering and machinery, TJ1-1570
Abstract

The cone-beam oral CT requires high transmission accuracy, and harmonic reducers with smooth operation, high precision efficiency and safety factor are mostly used. Its flexspline is prone to failure due to periodic deformation under alternating load when rotating. The tooth profile of the flexspline is designed, modeled by SolidWorks, and imported into the Ansys Workbench for the static analysis, modal analysis, and transient dynamic analysis. The results show that the flexural strain is mainly located at the long and short axes of the wave generator, and the axial strain decreases gradually along the cylinder. The maximum stress is located at the contact between the wave generator and the flexspline, and the maximum stress is located at the connection between the tooth root and the cylinder during the transient dynamic analysis. At the same time, the stress and strain of the flexspline are also affected by tooth width, barrel length and barrel thickness.

Published
2023
Full Text
View/download PDF

18. Circadian rhythm dysfunction and psychopathology in the offspring of parents with bipolar disorder: a high-risk study in the Chinese population

Author

Lei, Binbin, primary, Feng, Hongliang, additional, Yang, Lulu, additional, Wang, Jing, additional, Chen, Jie, additional, Song, Weidong, additional, Jiang, Chao, additional, Zhang, Kun, additional, Wang, Qunfeng, additional, Tsang, Jessie Chi Ching, additional, Chan, Ngan Yin, additional, Liu, Yaping, additional, Chan, Joey W.Y., additional, Pan, Jiyang, additional, Zhang, Bin, additional, Li, Tao, additional, Merikangas, Kathleen Ries, additional, Zhang, Jihui, additional, and Wing, Yun Kwok, additional

Published
2024
Full Text
View/download PDF

21. The burden of mild asthma: Clinical burden and healthcare resource utilisation in the NOVELTY study

Author

Benhabib, Gabriel, Mandhane, Piushkumar, Ruiz, Xavier Bocca, McIvor, Andrew, Olmo, Ricardo del, Pek, Bonavuth, Lisanti, Raul Eduardo, Petrella, Robert, Marino, Gustavo, Stollery, Daniel, Mattarucco, Walter, Chen, Meihua, Nogueira, Juan, Chen, Yan, Parody, Maria, Gu, Wei, Pascale, Pablo, Hui, Kim Ming Christopher, Rodriguez, Pablo, Li, Manxiang, Silva, Damian, Li, Shiyue, Svetliza, Graciela, Ma, Lijun, Victorio, Carlos F., Qin, Guangyue, Rolon, Roxana Willigs, Song, Weidong, Yañez, Anahi, Tan, Wei, Baines, Stuart, Tang, Yijun, Bowler, Simon, Wang, Chen, Bremner, Peter, Wang, Tan, Bull, Sheetal, Wen, Fuqiang, Carroll, Patrick, Wu, Feng, Chaalan, Mariam, Xiang, PingChao, Farah, Claude, Xiao, Zuke, Hammerschlag, Gary, Xiong, Shengdao, Hancock, Kerry, Yang, Jinghua, Harrington, Zinta, Yang, Jingping, Katsoulotos, Gregory, Zhang, Caiqing, Kim, Joshua, Zhang, Min, Langton, David, Zhang, Ping, Lee, Donald, Zhang, Wei, Peters, Matthew, Zheng, Xiaohe, Prassad, Lakshman, Zhu, Dan, Reddel, Helen, Bolivar Grimaldos, Fabio, Sajkov, Dimitar, Arboleda, Alejandra Cañas, Santiago, Francis, Bueno, Carlos Matiz, Simpson, Frederick Graham, Molina de Salazar, Dora, Tai, Sze, Bendstrup, Elisabeth, Thomas, Paul, Hilberg, Ole, Wark, Peter, Kjellerup, Carsten, Cançado, José Eduardo Delfini, Weinreich, Ulla, Cunha, Thúlio, Bonniaud, Philippe, Lima, Marina, Brun, Olivier, Cardoso, Alexandre Pinto, Burgel, Pierre-Régis, Rabahi, Marcelo, Chouaid, Christos, Anees, Syed, Couturaud, Francis, Bertley, John, de Blic, Jacques, Bell, Alan, Debieuvre, Didier, Cheema, Amarjit, Delsart, Dominique, Chouinard, Guy, Demaegdt, Axelle, Csanadi, Michael, Demoly, Pascal, Dhar, Anil, Deschildre, Antoine, Dhillon, Ripple, Devouassoux, Gilles, FitzGerald, J. Mark, Egron, Carole, Kanawaty, David, Falchero, Lionel, Kelly, Allan, Goupil, François, Killorn, William, Kessler, Romain, Landry, Daniel, Le Roux, Pascal, Luton, Robert, Mabire, Pascal, Mahay, Guillaume, Ide, Yumiko, Martinez, Stéphanie, Inomata, Minehiko, Melloni, Boris, Inoue, Hiromasa, Moreau, Laurent, Inoue, Koji, Raherison, Chantal, Inoue, Sumito, Riviere, Emilie, Kato, Motokazu, Roux-Claudé, Pauline, Kawasaki, Masayuki, Soulier, Michel, Kawayama, Tomotaka, Vignal, Guillaume, Kita, Toshiyuki, Yaici, Azzedine, Kobayashi, Kanako, Aries, Sven Philip, Koto, Hiroshi, Bals, Robert, Nishi, Koichi, Beck, Ekkehard, Saito, Junpei, Deimling, Andreas, Shimizu, Yasuo, Feimer, Jan, Shirai, Toshihiro, Grimm-Sachs, Vera, Sugihara, Naruhiko, Groth, Gesine, Takahashi, Ken-ichi, Herth, Felix, Tashimo, Hiroyuki, Hoheisel, Gerhard, Tomii, Keisuke, Kanniess, Frank, Yamada, Takashi, Lienert, Thomas, Yanai, Masaru, Mronga, Silke, Javier, Ruth Cerino, Reinhardt, Jörg, Domínguez Peregrina, Alfredo, Schlenska, Christian, Corzo, Marco Fernández, Stolpe, Christoph, Montano Gonzalez, Efraín, Teber, Ishak, Ramírez-Venegas, Alejandra, Timmermann, Hartmut, Rendon, Adrian, Ulrich, Thomas, Boersma, Willem, Velling, Peter, Djamin, R.S., Wehgartner-Winkler, Sabina, Eijsvogel, Michiel, Welling, Juergen, Franssen, Frits, Winkelmann, Ernst-Joachim, Goosens, Martijn, Barbetta, Carlo, Graat-Verboom, Lidwien, Braido, Fulvio, Veen, Johannes in 't, Cardaci, Vittorio, Janssen, Rob, Clini, Enrico Maria, Kuppens, Kim, Costantino, Maria Teresa, van den Berge, Maarten, Cuttitta, Giuseppina, van de Ven, Mario, di Gioacchino, Mario, Brunstad, Ole Petter, Fois, Alessandro, Einvik, Gunnar, Foschino-Barbaro, Maria Pia, Høines, Kristian Jong, Gammeri, Enrico, Khusrawi, Alamdar, Inchingolo, Riccardo, Oien, Torbjorn, Lavorini, Federico, Chang, Yoon-Seok, Molino, Antonio, Cho, Young Joo, Nucera, Eleonora, Hwang, Yong Il, Papi, Alberto, Kim, Woo Jin, Patella, Vincenzo, Koh, Young-Il, Pesci, Alberto, Lee, Byung-Jae, Ricciardolo, Fabio, Lee, Kwan-Ho, Rogliani, Paola, Lee, Sang-Pyo, Sarzani, Riccardo, Lee, Yong Chul, Vancheri, Carlo, Lim, Seong Yong, Vincenti, Rigoletta, Min, Kyung Hun, Endo, Takeo, Oh, Yeon-Mok, Fujita, Masaki, Park, Choon-Sik, Hara, Yu, Park, Hae-Sim, Horiguchi, Takahiko, Park, Heung-Woo, Hosoi, Keita, Rhee, Chin Kook, Yoon, Ho Joo, Morice, Alyn, Yoon, Hyoung-Kyu, Pandya, Preeti, García-Navarro, Alvar Agusti, Patel, Manish, Andújar, Rubén, Roy, Kay, Anoro, Laura, Sathyamurthy, Ramamurthy, García, María Buendía, Thiagarajan, Swaminathan, Mozo, Paloma Campo, Turner, Alice, Campos, Sergio, Vestbo, Jorgen, Maldonado, Francisco Casas, Wedzicha, Wisia, Castilla Martínez, Manuel, Wilkinson, Tom, Serrano, Carolina Cisneros, Wilson, Pete, Comeche Casanova, Lorena, Al-Asadi, Lo’Ay, Corbacho, Dolores, Anholm, James, Campo Matías, Felix Del, Averill, Frank, Echave-Sustaeta, Jose, Bansal, Sandeep, Corral, Gloria Francisco, Baptist, Alan, Gamboa Setién, Pedro, Campbell, Colin, García Clemente, Marta, Campos, Michael A., Núñez, Ignacio García, Chipps, Bradley, Robaina, Jose García, Crook, Gretchen, García Salmones, Mercedes, DeLeon, Samuel, Marín Trigo, Jose Maria, Eid, Alain, Fernandez, Marta Nuñez, Epstein, Ellen, Palomo, Sara Nuñez, Fritz, Stephen, Olaguibel Rivera, José, Harris, Hoadley, de Llano, Luis Pérez, Hewitt, Mitzie, Pueyo Bastida, Ana, Holguin, Fernando, Rañó, Ana, Hudes, Golda, Rodríguez González-Moro, José, Jackson, Richard, Reig, Albert Roger, Kaufman, Alan, Velasco Garrido, José, Kaufman, David, Curiac, Dan, Klapholz, Ari, Janson, Christer, Krishna, Harshavardhan, Lif-Tiberg, Cornelia, Lee, Daria, Luts, Anders, Lin, Robert, Råhlen, Lennart, Maselli-Caceres, Diego, Rustscheff, Stefan, Mehta, Vinay, Adams, Frances, Moy, James N., Bradman, Drew, Nwokoro, Ugo, Broughton, Emma, Parikh, Purvi, Cosgrove, John, Parikh, Sudhir, Flood-Page, Patrick, Perrino, Frank, Fuller, Elizabeth, Ruhlmann, James, Harrison, Timothy, Sassoon, Catherine, Hartley, David, Settipane, Russell A., Hattotuwa, Keith, Sousa, Daniel, Jones, Gareth, Sriram, Peruvemba, Lewis, Keir, Wachs, Richard, McGarvey, Lorcan, Golam, Sarowar Muhammad, Beasley, Richard, FitzGerald, J Mark, Harrison, Tim, Hughes, Rod, Müllerová, Hana, Olaguibel, José María, Rapsomaniki, Eleni, Reddel, Helen K., and Sadatsafavi, Mohsen

Published
2022
Full Text
View/download PDF

22. Frequent productive cough: Symptom burden and future exacerbation risk among patients with asthma and/or COPD in the NOVELTY study

Author

Benhabib, Gabriel, Ruiz, Xavier Bocca, Olmo, Ricardo del, Lisanti, Raul Eduardo, Marino, Gustavo, Mattarucco, Walter, Nogueira, Juan, Parody, Maria, Pascale, Pablo, Rodriguez, Pablo, Silva, Damian, Svetliza, Graciela, Victorio, Carlos F., Rolon, Roxana Willigs, Yañez, Anahi, Baines, Stuart, Bowler, Simon, Bremner, Peter, Bull, Sheetal, Carroll, Patrick, Chaalan, Mariam, Farah, Claude, Hammerschlag, Gary, Hancock, Kerry, Harrington, Zinta, Katsoulotos, Gregory, Kim, Joshua, Langton, David, Lee, Donald, Peters, Matthew, Prassad, Lakshman, Reddel, Helen, Sajkov, Dimitar, Santiago, Francis, Simpson, Frederick Graham, Tai, Sze, Thomas, Paul, Wark, Peter, Delfini Cançado, José Eduardo, Cunha, Thúlio, Lima, Marina, Cardoso, Alexandre Pinto, Rabahi, Marcelo, Anees, Syed, Bertley, John, Bell, Alan, Cheema, Amarjit, Chouinard, Guy, Csanadi, Michael, Dhar, Anil, Dhillon, Ripple, FitzGerald, J. Mark, Kanawaty, David, Kelly, Allan, Killorn, William, Landry, Daniel, Luton, Robert, Mandhane, Piushkumar, McIvor, Andrew, Pek, Bonavuth, Petrella, Robert, Stollery, Daniel, Chen, Meihua, Chen, Yan, Gu, Wei, Christopher Hui, Kim Ming, Li, Manxiang, Li, Shiyue, Lijun, Ma, Qin, Guangyue, Song, Weidong, Tan, Wei, Tang, Yijun, Wang, Chen, Wang, Tan, Wen, Fuqiang, Wu, Feng, Xiang, PingChao, Xiao, Zuke, Xiong, Shengdao, Yang, Jinghua, Yang, Jingping, Zhang, Caiqing, Zhang, Min, Zhang, Ping, Zhang, Wei, Zheng, Xiaohe, Zhu, Dan, Grimaldos, Fabio Bolivar, Arboleda, Alejandra Cañas, Bueno, Carlos Matiz, Molina de Salazar, Dora, Bendstrup, Elisabeth, Hilberg, Ole, Kjellerup, Carsten, Weinreich, Ulla, Bonniaud, Philippe, Brun, Olivier, Burgel, Pierre-Régis, Chouaid, Christos, Couturaud, Francis, de Blic, Jacques, Debieuvre, Didier, Delsart, Dominique, Demaegdt, Axelle, Demoly, Pascal, Deschildre, Antoine, Devouassoux, Gilles, Egron, Carole, Falchero, Lionel, Goupil, François, Kessler, Romain, Le Roux, Pascal, Mabire, Pascal, Mahay, Guillaume, Martinez, Stéphanie, Melloni, Boris, Moreau, Laurent, Raherison, Chantal, Riviere, Emilie, Roux-Claudé, Pauline, Soulier, Michel, Vignal, Guillaume, Yaici, Azzedine, Aries, Sven Philip, Bals, Robert, Beck, Ekkehard, Deimling, Andreas, Feimer, Jan, Grimm-Sachs, Vera, Groth, Gesine, Herth, Felix, Hoheisel, Gerhard, Kanniess, Frank, Lienert, Thomas, Mronga, Silke, Reinhardt, Jörg, Schlenska, Christian, Stolpe, Christoph, Teber, Ishak, Timmermann, Hartmut, Ulrich, Thomas, Velling, Peter, Wehgartner-Winkler, Sabina, Welling, Juergen, Winkelmann, Ernst-Joachim, Barbetta, Carlo, Braido, Fulvio, Cardaci, Vittorio, Clini, Enrico Maria, Costantino, Maria Teresa, Cuttitta, Giuseppina, di Gioacchino, Mario, Fois, Alessandro, Foschino-Barbaro, Maria Pia, Gammeri, Enrico, Inchingolo, Riccardo, Lavorini, Federico, Molino, Antonio, Nucera, Eleonora, Papi, Alberto, Patella, Vincenzo, Pesci, Alberto, Ricciardolo, Fabio, Rogliani, Paola, Sarzani, Riccardo, Vancheri, Carlo, Vincenti, Rigoletta, Endo, Takeo, Fujita, Masaki, Hara, Yu, Horiguchi, Takahiko, Hosoi, Keita, Ide, Yumiko, Inomata, Minehiko, Inoue, Hiromasa, Inoue, Koji, Inoue, Sumito, Kato, Motokazu, Kawasaki, Masayuki, Kawayama, Tomotaka, Kita, Toshiyuki, Kobayashi, Kanako, Koto, Hiroshi, Nishi, Koichi, Saito, Junpei, Shimizu, Yasuo, Shirai, Toshihiro, Sugihara, Naruhiko, Takahashi, Ken-ichi, Tashimo, Hiroyuki, Tomii, Keisuke, Yamada, Takashi, Yanai, Masaru, Javier, Ruth Cerino, Peregrina, Alfredo Domínguez, Corzo, Marco Fernández, Gonzalez, Efraín Montano, Ramírez-Venegas, Alejandra, Rendon, Adrian, Boersma, Willem, Djamin, R.S., Eijsvogel, Michiel, Franssen, Frits, Goosens, Martijn, Graat-Verboom, Lidwien, Veen, Johannes in 't, Janssen, Rob, Kuppens, Kim, van den Berge, Maarten, van de Ven, Mario, Brunstad, Ole Petter, Einvik, Gunnar, Høines, Kristian Jong, Khusrawi, Alamdar, Oien, Torbjorn, Chang, Yoon-Seok, Cho, Young Joo, Hwang, Yong Il, Kim, Woo Jin, Koh, Young-Il, Lee, Byung-Jae, Lee, Kwan-Ho, Lee, Sang-Pyo, Lee, Yong Chul, Lim, Seong Yong, Min, Kyung Hun, Oh, Yeon-Mok, Park, Choon-Sik, Park, Hae-Sim, Park, Heung-Woo, Rhee, Chin Kook, Yoon, Ho Joo, Yoon, Hyoung-Kyu, García-Navarro, Alvar Agusti, Andújar, Rubén, Anoro, Laura, García, María Buendía, Mozo, Paloma Campo, Campos, Sergio, Maldonado, Francisco Casas, Martínez, Manuel Castilla, Serrano, Carolina Cisneros, Casanova, Lorena Comeche, Corbacho, Dolores, Del Campo Matías, Felix, Echave-Sustaeta, Jose, Corral, Gloria Francisco, Setién, Pedro Gamboa, Clemente, Marta García, Núñez, Ignacio García, Robaina, Jose García, Salmones, Mercedes García, Marín Trigo, Jose Maria, Fernandez, Marta Nuñez, Palomo, Sara Nuñez, Rivera, José Olaguibel, Pérez de Llano, Luis, Bastida, Ana Pueyo, Rañó, Ana, González-Moro, José Rodríguez, Reig, Albert Roger, Garrido, José Velasco, Curiac, Dan, Janson, Christer, Lif-Tiberg, Cornelia, Luts, Anders, Råhlen, Lennart, Rustscheff, Stefan, Adams, Frances, Bradman, Drew, Broughton, Emma, Cosgrove, John, Flood-Page, Patrick, Fuller, Elizabeth, Harrison, Timothy, Hartley, David, Hattotuwa, Keith, Jones, Gareth, Lewis, Keir, McGarvey, Lorcan, Morice, Alyn, Pandya, Preeti, Patel, Manish, Roy, Kay, Sathyamurthy, Ramamurthy, Thiagarajan, Swaminathan, Turner, Alice, Vestbo, Jorgen, Wedzicha, Wisia, Wilkinson, Tom, Wilson, Pete, Al-Asadi, Lo’Ay, Anholm, James, Averill, Frank, Bansal, Sandeep, Baptist, Alan, Campbell, Colin, Campos, Michael A., Chipps, Bradley, Crook, Gretchen, DeLeon, Samuel, Eid, Alain, Epstein, Ellen, Fritz, Stephen, Harris, Hoadley, Hewitt, Mitzie, Holguin, Fernando, Hudes, Golda, Jackson, Richard, Kaufman, Alan, Kaufman, David, Klapholz, Ari, Krishna, Harshavardhan, Lee, Daria, Lin, Robert, Maselli-Caceres, Diego, Mehta, Vinay, Moy, James N., Nwokoro, Ugo, Parikh, Purvi, Parikh, Sudhir, Perrino, Frank, Ruhlmann, James, Sassoon, Catherine, Settipane, Russell A., Sousa, Daniel, Sriram, Peruvemba, Wachs, Richard, Hughes, Rod, Rapsomaniki, Eleni, Keen, Christina, Make, Barry J., Tomaszewski, Erin L., Müllerová, Hana, and Reddel, Helen K.

Published
2022
Full Text
View/download PDF

30. PAN: Improved PointNet++ for Pavement Crack Information Extraction.

Author

Fan, Jiakai, Song, Weidong, Zhang, Jinhe, Sun, Shangyu, Jia, Guohui, and Jin, Guang

Subjects
CRACKING of pavements, POINT cloud, DATA mining, DEEP learning, FEATURE extraction
Abstract

Maintenance and repair of expressways are becoming increasingly important due to the growing frequency of their use. Accurate pavement crack information extraction helps with routine maintenance and reduces the risk of traffic accidents. The traditional 2D crack image detection method has limitations and cannot effectively obtain depth information. Three-dimensional crack extraction from 3D point cloud has become a new solution that can capture pavement crack information more comprehensively and accurately. However, the existing algorithms are not effective in the feature extraction of cracks due to the different and irregular shapes and sizes of pavement cracks and interference from the external environment. To solve this, a new method for detecting pavement cracks in point clouds, namely point attention net (PAN), is herein proposed. It uses a two-branch attention fusion module to focus on space and feature information in the cloud and capture features of crack points at different scales. It also uses the Poly Loss function to solve the imbalance of foreground and background points in pavement point cloud data. Experiments on the LNTU-RDD-LiDAR dataset were carried out to verify the effectiveness of the proposed method. Compared with the traditional method and the latest point cloud segmentation technology, the performance indexes of mIoU, Acc, F1, and Rec achieved significant improvement, reaching 75.4%, 91.5%, 75.4%, and 67.1%, respectively. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

36. Study on a Moisture Ratio Curve Model for Refractance Window Drying Based on a D‐Optimal Mixture Design.

Author

He, Jingyu, Song, Weidong, Li, Jianqiang, Ding, Tianhang, Guan, Jian, Wu, Jinji, Wang, Jiaoling, and Demiray, Engin

Subjects
DRYING apparatus, AIR speed, WIND speed, MODEL validation, DIFFUSION coefficients
Abstract

Refractance window (RW) drying is a new thin‐layer drying technology that can control well the heating temperature to effectively reduce the loss of heat‐sensitive substances. Here, an experiment on tomato pulp drying was carried out to study the drying characteristics of RW drying based on a D‐optimal mixture design. The fitting of the classical model of thin‐layer drying was studied, and SAS and 1stOpt calculation software were used to analyze the test data. The result showed that the RW drying equipment could dry 8 mm of tomato pulp in 120 min, and the maximum drying speed could reach 0.40 g/(g·min). Based on an effective diffusion coefficient under different conditions, the activation energy was 27.35 kJ/mol at an air speed of 3 m/s. When comparing the fitting of the moisture ratio curve in four classic thin‐layer drying models, it was found that the R‐square value of the modified Page model was 0.9960, which had better fitting properties. Then, the polynomial fitting model of thin‐layer drying reflects the regression relationship between the coefficient of the classic model and drying conditions including temperature, wind speed, and time. After comparison with the classic model and validation experiment, the results showed that there is no significant difference between the polynomial fitting model and the validations under a confidence level of 0.95, which could well predict the change in the water content ratio over time under different conditions. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

37. Automated Multi-Type Pavement Distress Segmentation and Quantification Using Transformer Networks for Pavement Condition Index Prediction.

Author

Zhang, Zaiyan, Song, Weidong, Zhuang, Yangyang, Zhang, Bing, and Wu, Jiachen

Subjects
TRANSFORMER models, PAVEMENTS, MODEL validation, PREDICTION models
Abstract

Pavement distress detection is a crucial task when assessing pavement performance conditions. Here, a novel deep-learning method based on a transformer network, referred to as ISTD-DisNet, is proposed for multi-type pavement distress semantic segmentation. In this methodology, a mix transformer (MiT) based on a hierarchical transformer structure is chosen as the backbone to obtain multi-scale feature information on pavement distress, and a mixed attention module (MAM) is introduced at the decoding stage to capture the pavement distress features across different channels and spatial locations. A learnable transposed convolution upsampling module (TCUM) enhances the model's ability to restore multi-scale distress details. Subsequently, a novel parameter—the distress pixel density ratio (PDR)—is introduced based on the segmentation results. Analyzing the intrinsic correlation between the PDR and the pavement condition index (PCI), a new pavement damage index prediction model is proposed. Finally, the experimental results reveal that the F1 and mIOU of the proposed method are 95.51% and 91.67%, respectively, and the segmentation performance is better than that of the other seven mainstream segmentation models. Further PCI prediction model validation experimental results also indicate that utilizing the PDR enables the quantitative evaluation of the pavement damage conditions for each assessment unit, holding promising engineering application potential. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results